diff --git a/data/covid/preprints-summary.csv b/data/covid/preprints-summary.csv index b2619a0f..9b745da6 100644 --- a/data/covid/preprints-summary.csv +++ b/data/covid/preprints-summary.csv @@ -1,45 +1,46 @@ -primary care research,occupational and environmental health,epidemiology,public and global health,immunology,allergy and immunology,dentistry and oral medicine,ophthalmology,psychiatry and clinical psychology,pediatrics,pathology,radiology and imaging,surgery,health economics,orthopedics,biochemistry,neurology,biophysics,systems biology,respiratory medicine,infectious diseases,obstetrics and gynecology,health systems and quality improvement,pharmacology and therapeutics,emergency medicine,oncology,molecular biology,cardiovascular medicine,geriatric medicine,intensive care and critical care medicine,health policy,genomics,microbiology,genetic and genomic medicine,bioinformatics,health informatics,Total,scientific communication and education,dermatology,month -,,,,,,,,,,,,,,,,,,,1,1,,,,,,,,,,,,,,,1,3,,,Oct-23 -1,1,4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,6,,,Aug-23 -,,3,1,,,,,,,,,,,,,,,,,,,2,,,,,,,,,,,1,,,7,,,Jul-23 -,1,1,,,,,,,,,,,,1,,,,,,2,,,,,,,,,,,,,,,1,7,1,,Jun-23 -,,2,1,1,,,,,,,,,,,,,,,1,1,,,,,,,,,,,,,,,,6,,,May-23 -,,,2,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,,,3,,,Apr-23 -,1,2,2,,,,,1,,,,,,,,,,,,3,,,,,,,,,,,,,,,,9,,,Mar-23 -,,4,2,,,,,,,,,,,,,1,,,1,,,,,,,,,,,,,,,,,8,,,Feb-23 -,,4,,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,,,5,,,Jan-23 -,,3,1,,,,,,,1,,,,,,,,,2,4,,,,,,,,,,1,,,,,,12,,,Dec-22 -,,,,,,,,,,,,,,,,,,,,4,,,,,,,,,,,,,,,,4,,,Nov-22 -,,1,2,,,,,,,,,,,,,,,,,2,,,,,,,1,,,,,,,,,6,,,Oct-22 -,2,1,1,,,,,,1,,,,,,,,,,1,2,,,,,,,,,,,,1,,,,9,,,Sep-22 -,,4,3,,,,,,,,,,,,,,,,,3,,,,,,,,,,,,,,,,10,,,Aug-22 -,,2,,1,,,,,1,,,,,,,,,,,3,,,,,,,,,,,,,,,1,8,,,Jul-22 -,,6,1,,,,,5,,,,,,,,,,,,4,,,,,,,,,,,,,1,,1,18,,,Jun-22 -1,,2,1,,,,,2,,,,,1,,,,,,,5,,,,,,,,,,,,1,,,,13,,,May-22 -,1,5,1,,,,,,,,,,1,,,,,,1,3,,2,,,,,1,,,,,,,,,15,,,Apr-22 -1,,9,,,,,,1,,,,,,,,,,,1,3,,,,,,,,,,,,,,,,15,,,Mar-22 -,,6,1,,,,,,,,,,,,,1,,,,4,,,,,,,,,,,,,,,,12,,,Feb-22 -,1,5,,1,,,,,,,,,,,,,,,,3,,,,,,,1,,,,,,,,2,13,,,Jan-22 -1,,10,1,,,,,,1,,,,,,,1,,,,8,,,,,,,1,,,,,1,,,,24,,,Dec-21 -1,,9,3,,,,,1,,,,,,,,1,1,,,5,,1,,,,,,,1,,,,,,,23,,,Nov-21 -,,4,,,,,,2,1,,,,,,,,,,,3,,,,,,,,1,,,,,,,,11,,,Oct-21 -,,4,2,,,,,,,,,,,,,,,,,5,,,1,,,,1,,1,,,,,,1,15,,,Sep-21 -,1,2,3,,,,,,,,,,,,,,,,1,3,,,,,,,1,,1,,,,,,1,13,,,Aug-21 -,,3,4,,,,,,1,,,,,,,,,,2,11,,,,1,1,,,,1,,,,1,,,25,,,Jul-21 -1,1,7,4,1,,,,1,1,,,,,,,1,,,,7,,1,,,,,,,1,,,,,,1,27,,,Jun-21 -,,11,1,,,,,1,,,,,,,,,,,,8,,,,,,,,,,,,,1,,1,24,,1,May-21 -1,2,4,1,,1,,,1,,,,,,,,,,,,7,,1,,,,,,,,,,1,,,1,20,,,Apr-21 -,,6,5,,,,,1,1,,1,1,,,1,1,,,,16,,,,,,,,2,,,,,1,,2,38,,,Mar-21 -,,9,1,,,,,,,,,1,1,,,,,,,9,,1,,,,,1,,,,,,,,1,24,,,Feb-21 -1,,4,3,1,,1,,1,,,,,,,,,,,,8,,1,,,,,,1,1,1,,,,,,23,,,Jan-21 -1,,4,3,,,,,2,,,,,,,,,,,,4,,1,,,,,2,,,,2,1,,,3,23,,,Dec-20 -,,6,5,1,,,,,,,,,,,,,,,,13,,,,,,,,,,1,,,,1,1,28,,,Nov-20 -1,,5,,1,,,,2,,,,,,,,,,1,,12,,,,,1,,,1,1,1,,,,1,1,28,,,Oct-20 -1,,6,3,,,,,2,,,,,,,,,,,,8,,,,2,,,,,1,,,1,,,1,25,,,Sep-20 -,1,6,2,,,,,,,,,,,,,,,,,11,1,1,,2,,1,,,,,,,1,,,26,,,Aug-20 -,,10,4,1,,,,1,,,,,,,,,,,1,8,,,,,,,1,,1,,1,,,,,28,,,Jul-20 -,,7,3,1,,,1,4,,,,,,,,,,,1,9,,1,,,1,,1,1,3,1,,,,1,1,36,,,Jun-20 -,1,8,9,,,,,,,,,,1,,,,,,1,10,,,,,1,,2,1,,,,,,1,1,36,,,May-20 -,,7,1,,,,,,,,,,,,,,,,,7,,1,,,,,,,,,1,,2,,,19,,,Apr-20 -,,4,3,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,,,8,,,Mar-20 -,,3,2,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,,,6,,,Feb-20 +respiratory medicine,infectious diseases,pediatrics,biophysics,immunology,Total,month,orthopedics,allergy and immunology,primary care research,psychiatry and clinical psychology,intensive care and critical care medicine,systems biology,occupational and environmental health,geriatric medicine,health policy,molecular biology,pathology,dermatology,evolutionary biology,bioinformatics,biochemistry,public and global health,ophthalmology,obstetrics and gynecology,genetic and genomic medicine,neurology,epidemiology,health economics,health systems and quality improvement,oncology,genomics,microbiology,hiv aids,radiology and imaging,cardiovascular medicine,dentistry and oral medicine,pharmacology and therapeutics,scientific communication and education,emergency medicine,surgery,health informatics +1,1,,,,3,Oct-23,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1 +,1,,,,1,Sep-23,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +,,,,,7,Aug-23,,,1,,,,1,,,,,,,,,1,,,,,4,,,,,,,,,,,,,, +,,,,,7,Jul-23,,,,,,,,,,,,,,,,1,,,1,,3,,2,,,,,,,,,,,, +,2,,,,7,Jun-23,1,,,,,,1,,,,,,,,,,,,,,1,,,,,,,,,,,1,,,1 +,1,,,1,5,May-23,,,,,,,,,,,,,,,,1,,,,,2,,,,,,,,,,,,,, +,1,,,,3,Apr-23,,,,,,,,,,,,,,,,2,,,,,,,,,,,,,,,,,,, +,3,,,,9,Mar-23,,,,1,,,1,,,,,,,,,2,,,,,2,,,,,,,,,,,,,, +1,,,,,7,Feb-23,,,,,,,,,,,,,,,,2,,,,,4,,,,,,,,,,,,,, +,1,,,,6,Jan-23,,,,,,,,,,,,,,,,,,,,,5,,,,,,,,,,,,,, +1,4,,,,10,Dec-22,,,,,,,,,,,1,,,,,1,,,,,3,,,,,,,,,,,,,, +,3,,,,3,Nov-22,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +,2,,,,6,Oct-22,,,,,,,,,,,,,,,,2,,,,,1,,,,,,,,1,,,,,, +1,2,1,,,9,Sep-22,,,,,,,2,,,,,,,,,1,,,,,1,,,,,1,,,,,,,,, +,3,,,,10,Aug-22,,,,,,,,,,,,,,,,3,,,,,4,,,,,,,,,,,,,, +,3,1,,1,8,Jul-22,,,,,,,,,,,,,,,,,,,,,2,,,,,,,,,,,,,,1 +,4,,,,17,Jun-22,,,,4,,,,,,,,,,,,1,,,1,,6,,,,,,,,,,,,,,1 +,5,,,,14,May-22,,,1,2,,,,,,,,,,,,1,,,,,2,1,1,,,1,,,,,,,,, +1,3,,,,15,Apr-22,,,,,,,,,,,,,,,,1,,,,,5,1,2,,,1,,,1,,,,,, +1,5,,,,18,Mar-22,,,1,1,,,,,,,,,1,,,,,,,,9,,,,,,,,,,,,,, +,4,,,,12,Feb-22,,,,,,,,,,,,,,,,1,,,,1,6,,,,,,,,,,,,,, +,3,,,1,14,Jan-22,,,,,,,1,,,,,,,,,1,,,,,5,,,,,,,,1,,,,,,2 +,7,1,,,22,Dec-21,,,1,,,,,,,,,,,,,1,,,,1,9,,,,,1,,,1,,,,,, +,5,,1,,25,Nov-21,,,1,1,1,,,,,,,,,,,3,,,,1,9,,2,,1,,,,,,,,,, +,3,1,,,11,Oct-21,,,,2,,,,1,,,,,,,,,,,,,4,,,,,,,,,,,,,, +,4,,,,15,Sep-21,,,,,1,,,,,,,,,,,2,,,,,5,,,,,,,,1,,1,,,,1 +1,1,,,,11,Aug-21,,,,,1,,1,,,,,,,,,3,,,,,2,,,,,,,,1,,,,,,1 +2,12,1,,,26,Jul-21,,,,,1,,,,,,,,,,,4,,,1,,3,,,1,,,,,,,,,1,, +,6,1,,1,27,Jun-21,,1,1,1,1,,1,,,,,,,,,4,,,,1,7,,1,,,,,,,,,,,,1 +,8,,,,24,May-21,,,,1,,,,,,,,1,,,,1,,,1,,11,,,,,,,,,,,,,,1 +,6,,,,19,Apr-21,,1,1,1,,,2,,,,,,,,,1,,,,,4,,1,,,1,,,,,,,,,1 +,17,1,,,39,Mar-21,,,,1,,,,2,,,,,,,1,5,,,1,1,6,,,,,,,1,,,,,,1,2 +,9,,,,24,Feb-21,,,,,,,,,,,,,,,,1,,,,,9,1,1,,,,,,1,,,,,1,1 +,8,,,1,23,Jan-21,,,1,1,1,,,1,1,,,,,,,3,,,,,4,,1,,,,,,,1,,,,, +,4,,,,23,Dec-20,,,1,2,,,,,,,,,,,,3,,,,,4,,1,,2,1,,,2,,,,,,3 +,12,,,1,26,Nov-20,,,,,,,,,1,,,,,1,,5,,,,,6,,,,,,,,,,,,,, +,11,,,1,28,Oct-20,,,1,3,1,1,,1,1,,,,,1,,,,,,,5,,,1,,,,,,,,,,,1 +,8,,,,26,Sep-20,,,1,2,1,,,,,,,,,,,3,,,,,5,,,,,1,1,,,,,,3,,1 +,12,,,,27,Aug-20,,,,,,,1,,,1,,,,,,2,,1,1,,6,,1,,,,,,,,,,2,, +1,7,,,1,26,Jul-20,,,,1,1,,,,,,,,,,,4,,,,,10,,,,,,,,1,,,,,, +1,9,,,1,34,Jun-20,,,,4,3,,,1,1,,,,,1,,3,1,,,,6,,,1,,,,,1,,,,,,1 +1,10,,,,36,May-20,,,,,1,,1,1,,,,,,1,,8,,,,,8,1,,1,,,,,2,,,,,,1 +,7,,,,19,Apr-20,,,,,,,,,,,,,,,,1,,,2,,7,,1,,1,,,,,,,,,, +,1,,,,7,Mar-20,,,,,,,,,,,,,,,,3,,,,,3,,,,,,,,,,,,,, +,1,,,,7,Feb-20,,,,,,,,,,,,,,,,2,,,,,4,,,,,,,,,,,,,, diff --git a/data/covid/preprints.csv b/data/covid/preprints.csv index 253945fa..360c5db5 100644 --- a/data/covid/preprints.csv +++ b/data/covid/preprints.csv @@ -24,6 +24,13 @@ InterpretationSymptom profiles varied little by aetiology, making distinguishing FundingUK Health Security Agency, Department of Health and Social Care, National Institute for Health Research.",respiratory medicine,fuzzy,100,100 medRxiv,10.1101/2023.10.06.23296657,2023-10-06,https://medrxiv.org/cgi/content/short/2023.10.06.23296657,The macroeconomic and epidemiological impacts of Covid-19 in Pakistan.,Henning Tarp Jensen; Marcus R. Keogh-Brown; Rosalind M Eggo; Carl A. B. Pearson; Sergio Torres-Rueda; Maryam Huda; Muhammad Khalid; Wahaj Sulfiqar; - CMMID COVID-19 Working Group; Richard D. Smith; Mark Jit; Anna Vassall,"London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; Aga Khan University; Ministry of National Health Services, Regulations & Coordination, Islamabad, Pakistan; Ministry of National Health Services, Regulations & Coordination, Islamabad, Pakistan; -; University of Exeter; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine","""Coronavirus Disease 2019"" (C19) is a respiratory illness caused by ""new Coronavirus"" SARS-CoV-2. The C19 pandemic, which engulfed the world in 2021, also caused a national C19 epidemic in Pakistan, who responded with initial forced lockdowns (15-30 March 2020) and a subsequent switch to a smart lockdown strategy, and, by 31 December 2020, Pakistan had managed to limit confirmed cases and case fatalities to 482,506 (456 per 100,000) and 10,176 (4.8 per 100,000). The early switch to a smart lockdown strategy, and successful follow-up move to central coordination and effective communication and enforcement of Standard Operating Procedures, was motivated by a concern over how broad-based forced lockdowns would affect poor households and day-labour. The current study aims to investigate how the national Pakistan C19 epidemic would have unfolded under an uncontrolled baseline scenario and an alternative set of controlled non-pharmaceutical intervention (NPI) policy lockdown scenarios, including health and macroeconomic outcomes. We employ a dynamically-recursive version of the IFPRI Standard Computable General Equilibrium model framework (Lofgren, Lee Harris and Robinson 2002), and a, by now, well-established epidemiological transmission-dynamic model framework (Davies, Klepac et al 2020) using Pakistan-specific 5-year age-group contact matrices on four types of contact rates, including at home, at work, at school, and at other locations (Prem, Cook & Jit 2017), to characterize an uncontrolled spread of disease. Our simulation results indicate that an uncontrolled C19 epidemic, by itself, would have led to a 0.12% reduction in Pakistani GDP (-721mn USD), and a total of 0.65mn critically ill and 1.52mn severely ill C19 patients during 2020-21, while 405,000 Pakistani citizens would have lost their lives. Since the majority of case fatalities and symptomatic cases, respectively 345,000 and 35.9mn, would have occurred in 2020, the case fatality and confirmed case numbers, observed by 31. December 2020 represents an outcome which is far better than the alternative. Case fatalities by 31. December 2020 could possibly have been somewhat improved either via a more prolonged one-off 10 week forced lockdown (66% reduction) or a 1-month forced lockdown/2-months opening intermittent lockdown strategy (33% reduction), but both sets of strategies would have carried significant GDP costs in the order of 2.2%-6.2% of real GDP.",infectious diseases,fuzzy,100,100 +medRxiv,10.1101/2023.08.30.23294821,2023-09-01,https://medrxiv.org/cgi/content/short/2023.08.30.23294821,Symptom experience before vs. after confirmed SARS-CoV-2 infection: a population and case control study using prospectively recorded symptom data.,Carole Helene Sudre; Michela Antonelli; Nathan J Cheetham; Erika Molteni; Liane S Canas; Vicky Bowyer; Benjamin Murray; Khaled Rjoob; Marc Modat; Joan Capdevia Pujol; Christina Hu; Jonathan Wolf; Timothy D Spector; Alexander Hammers; Claire J Steves; Sebastien Ourselin; Emma L Duncan,University College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; University College London; King's College London; Zoe Ltd; Zoe Ltd; Zoe Ltd; King's College London; King's College London; King's College London; King's College London; King's College London,"BackgroundSome individuals experience prolonged illness after acute COVID-19. We assessed whether pre-infection symptoms affected post-COVID illness duration. + +MethodsSurvival analysis was performed in adults (n=23,452) with community-managed SARC-CoV-2 infection prospectively self-logging data through the ZOE COVID Symptom Study app, at least weekly, from 8 weeks before to 12 weeks after COVID-19 onset, conditioned on presence vs. absence of baseline symptoms (4-8 weeks before COVID-19). A case-control study was performed in 1350 individuals with long illness ([≥]8 weeks, 906 [67.1%] with illness [≥]12 weeks), matched 1:1 (for age, sex, body mass index, testing week, prior infection, vaccination, smoking, index of multiple deprivation) with 1350 individuals with short illness (<4 weeks). Baseline symptoms were compared between the two groups; and against post-COVID symptoms. + +FindingsIndividuals reporting baseline symptoms had longer post-COVID symptom duration (from 10 to 15 days) with baseline fatigue nearly doubling duration. Two-thirds (910 of 1350 [67.4%]) of individuals with long illness were asymptomatic beforehand. However, 440 (32.6%) had baseline symptoms, vs. 255 (18.9%) of 1350 individuals with short illness (p<0.0001). Baseline symptoms increased the odds ratio for long illness (2.14 [CI: 1.78; 2.57]). Prior comorbidities were more common in individuals with long vs. short illness. In individuals with long illness, baseline symptomatic (vs. asymptomatic) individuals were more likely to be female, younger, and have prior comorbidities; and baseline and post-acute symptoms and symptom burden correlated strongly. + +InterpretationIndividuals experiencing symptoms before COVID-19 have longer illness duration and increased odds of long illness. However, many individuals with long illness are well before SARS-CoV-2 infection.",infectious diseases,fuzzy,94,100 medRxiv,10.1101/2023.08.25.23294609,2023-08-25,https://medrxiv.org/cgi/content/short/2023.08.25.23294609,Risk factors for SARS-Cov-2 infection at a United Kingdom electricity-generating company: a test-negative design case-control study,Charlotte E Rutter; Martie J Van Tongeren; Tony Fletcher; Sarah E Rhodes; Yiqun Chen; Ian Hall; Nicholas Warren; Neil Pearce,London School of Hygiene and Tropical Medicine; University of Manchester; London School of Hygiene and Tropical Medicine; University of Manchester; Health and Safety Executive; University of Manchester; Health and Safety Executive; London School of Hygiene and Tropical Medicine,"ObjectivesIdentify workplace risk factors for SARS-Cov-2 infection, using data collected by a United Kingdom electricity-generating company. MethodsUsing a test-negative design case-control study we estimated the odds ratios (OR) of infection by job category, site, test reason, sex, vaccination status, vulnerability, site outage, and site COVID-19 weekly risk rating, adjusting for age, test date and test type. @@ -38,6 +45,7 @@ Key messagesO_LIThe effects of different job types on risk of COVID-19 infection C_LIO_LIBoth date and reason of test are important confounders to be included when estimating odds ratios for COVID-19 infection C_LIO_LIThere was little difference in COVID-19 infection risk by job category after adjusting for test reason; however women were less likely to test positive than men C_LI",occupational and environmental health,fuzzy,100,100 +medRxiv,10.1101/2023.08.11.23293977,2023-08-15,https://medrxiv.org/cgi/content/short/2023.08.11.23293977,"Digital Mental Health Service engagement changes during Covid-19 in children and young people across the UK: presenting concerns, service activity, and access by gender, ethnicity, and deprivation",Duleeka Knipe; Santiago de Ossorno Garcia; Louisa Salhi; Lily Mainstone-Cotton; Aaron Sefi; Ann John,University of Bristol School of Social and Community Medicine: University of Bristol Population Health Sciences; Kooth Digital Health; Kooth Digital Health; Kooth Digital Health; Kooth Digital Health; Swansea University,"The adoption of digital health technologies accelerated during Covid-19, with concerns over the equity of access due to digital exclusion. Using data from a text-based online mental health service for children and young people we explore the impact of the pandemic on service access and presenting concerns and whether differences were observed by sociodemographic characteristics in terms of access (gender, ethnicity and deprivation). We used interrupted time-series models to assess whether there was a change in the level and rate of service use during the Covid-19 pandemic (April 2020-April 2021) compared to pre-pandemic trends (June 2019-March 2020). Routinely collected data from 61221 service users were extracted for observation, those represented half of the service population as only those with consent to share their data were used. The majority of users identified as female (74%) and White (80%), with an age range between 13 and 20 years of age. There was evidence of a sudden increase (13%) in service access at the start of the pandemic (RR 1.13 95% CI 1.02, 1.25), followed by a reduced rate (from 25% to 21%) of engagement during the pandemic compared to pre-pandemic trends (RR 0.97 95% CI 0.95,0.98). There was a sudden increase in almost all presenting issues apart from physical complaints. There was evidence of a step increase in the number of contacts for Black/African/Caribbean/Black British (38% increase; 95% CI: 1%-90%) and White ethnic groups (14% increase; 95% CI: 2%-27%)), sudden increase in service use at the start of the pandemic for the most (58% increase; 95% CI: 1%-247%) and least (47% increase; 95% CI: 6%-204%) deprived areas. During the pandemic, contact rates decreased, and referral sources change at the start. Findings on access and service activity align with other studies observing reduced service utilization. The lack of differences in deprivation levels and ethnicity at lockdown suggests exploring equity of access to the anonymous service. The study provides unique insights into changes in digital mental health use during Covid-19 in the UK.",public and global health,fuzzy,100,100 medRxiv,10.1101/2023.08.07.23293778,2023-08-09,https://medrxiv.org/cgi/content/short/2023.08.07.23293778,"Diabetes following SARS-CoV-2 infection: Incidence, persistence, and implications of COVID-19 vaccination. A cohort study of fifteen million people.",Kurt Taylor; Sophie Eastwood; Venexia Walker; Genevieve Cezard; Rochelle Knight; Marwa Al Arab; Yinghui Wei; Elsie M F Horne; Lucy Teece; Harriet Forbes; Alex Walker; Louis Fisher; Jon Massey; Lisa E M Hopcroft; Tom Palmer; Jose Cuitun Coronado; Samantha Ip; Simon Davy; Iain Dillingham; Caroline Morton; Felix Greaves; John MacLeod; Ben Goldacre; Angela Wood; Nishi Chaturvedi; Jonathan A C Sterne; Rachel Denholm; - CONVALESCENCE Long-COVID study; - Longitudinal Health and Wellbeing and Data and Connectivity UK COVID-19 National Core Studies; - OpenSAFELY collaborative,University of Bristol; University College London; University of Bristol; University of Cambridge; University of Bristol; University of Bristol; University of Plymouth; University of Bristol; University of Leicester; London School of Hygiene & Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Bristol; University of Bristol; University of Cambridge; University of Oxford; University of Oxford; University of Oxford; National Institute for Health and Care Excellence; University of Bristol; University of Oxford; University of Cambridge; University College London; University of Bristol; University of Bristol; -; -; -,"BackgroundType 2 diabetes (T2DM) incidence is increased after diagnosis of COVID-19. The impact of vaccination on this increase, for how long it persists, and the effect of COVID-19 on other types of diabetes remain unclear. MethodsWith NHS England approval, we studied diabetes incidence following COVID-19 diagnosis in pre-vaccination (N=15,211,471, January 2020-December 2021), vaccinated (N =11,822,640), and unvaccinated (N=2,851,183) cohorts (June-December 2021), using linked electronic health records. We estimated adjusted hazard ratios (aHRs) comparing diabetes incidence post-COVID-19 diagnosis with incidence before or without diagnosis up to 102 weeks post-diagnosis. Results were stratified by COVID-19 severity (hospitalised/non-hospitalised) and diabetes type. @@ -219,14 +227,6 @@ ResultsOf over 45 million patients, 69,220 (0.15%) had a Post-COVID syndrome dia DiscussionThis study demonstrates variation in diagnosis and referral coding rates for Post-COVID syndrome across different patient groups. The results, with limited crossover of referral and diagnostic codes, suggest only one type of code is usually recorded. Recording one code limits the use of routine data for monitoring Post-COVID syndrome diagnosis and management, but suggests several areas for improvement in coding. Post-COVID syndrome coding, particularly diagnosis coding, needs to improve before administrators and researchers can use it to evaluate care pathways.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2023.05.17.23290105,2023-05-24,https://medrxiv.org/cgi/content/short/2023.05.17.23290105,Within-host SARS-CoV-2 viral kinetics informed by complex life course exposures reveals different intrinsic properties of Omicron and Delta variants,Timothy W Russell; Hermaleigh Townsley; Sam Abbott; Joel Hellewell; Edward J Carr; Lloyd Chapman; Rachael Pung; Billy J Quilty; David Hodgson; Ashley Fowler; Lorin Adams; Christopher Bailey; Harriet V Mears; Ruth Harvey; Bobbi Clayton; Nicola O'Reilly; Yenting Ngai; Jerome Nicod; Steve Gamblin; Bryan Williams; Sonia Gandhi; Charles Swanton; Rupert Beale; David LV Bauer; Emma C Wall; Adam Kucharski,London School of Hygiene and Tropical Medicine; The Francis Crick Institute; London School of Hygiene and Tropical Medicine; European Molecular Biology Laboratory; The Francis Crick Institute; Lancaster University; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; National Institute for Health Research (NIHR) University College London Hospitals (UCLH); The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; London School of Hygiene and Tropical Medicine,"The emergence of successive SARS-CoV-2 variants of concern (VOC) during 2020-22, each exhibiting increased epidemic growth relative to earlier circulating variants, has created a need to understand the drivers of such growth. However, both pathogen biology and changing host characteristics - such as varying levels of immunity - can combine to influence replication and transmission of SARS-CoV-2 within and between hosts. Disentangling the role of variant and host in individual-level viral shedding of VOCs is essential to inform COVID-19 planning and response, and interpret past epidemic trends. Using data from a prospective observational cohort study of healthy adult volunteers undergoing weekly occupational health PCR screening, we developed a Bayesian hierarchical model to reconstruct individual-level viral kinetics and estimate how different factors shaped viral dynamics, measured by PCR cycle threshold (Ct) values over time. Jointly accounting for both inter-individual variation in Ct values and complex host characteristics - such as vaccination status, exposure history and age - we found that age and number of prior exposures had a strong influence on peak viral replication. Older individuals and those who had at least five prior antigen exposures to vaccination and/or infection typically had much lower levels of shedding. Moreover, we found evidence of a correlation between the speed of early shedding and duration of incubation period when comparing different VOCs and age groups. Our findings illustrate the value of linking information on participant characteristics, symptom profile and infecting variant with prospective PCR sampling, and the importance of accounting for increasingly complex population exposure landscapes when analysing the viral kinetics of VOCs.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2023.05.08.23289442,2023-05-11,https://medrxiv.org/cgi/content/short/2023.05.08.23289442,Cohort Profile: Post-hospitalisation COVID-19 study (PHOSP-COVID),Omer Elneima; Hamish J C McAuley; Olivia C Leavy; James D Chalmers; Alex Horsley; Ling-Pei Ho; Michael Marks; Krisnah Poinasamy; Betty Raman; Aarti Shikotra; Amisha Singapuri; Marco Sereno; Victoria C Harris; Linzy Houchen-Wolloff; Ruth M Saunders; Neil J Greening; Matthew Richardson; Jennifer K Quint; Andrew Briggs; Annemarie B Docherty; Steven Kerr; Ewen M Harrison; Nazir I Lone; Mathew Thorpe; Liam G Heaney; Keir E Lewis; Raminder Aul; Paul Beirne; Charlotte E Bolton; Jeremy S Brown; Gourab Choudhury; Nawar Diar Bakerly; Nicholas Easom; Carlos Echevarria; Jonathan Fuld; Nick Hart; John R Hurst; Mark G Jones; Dhruv Parekh; Paul E Pfeffer; Najib M Rahman; Sarah L Rowland-Jones; AA Roger Thompson; Caroline Jolley; Ajay M Shah; Dan G Wootton; Trudie Chalder; Melanie J Davies; Anthony De Soyza; John R Geddes; William Greenhalf; Simon Heller; Luke S Howard; Joseph Jacob; R Gisli Jenkins; Janet M Lord; William D-C Man; Gerry P McCann; Stefan Neubauer; Peter JM Openshaw; Joanna C Porter; Matthew J Rowland; Janet T Scott; Malcolm G Semple; Sally J Singh; David C Thomas; Mark Toshner; Aziz Sheikh; Chris E Brightling; Louise v Wain; Rachael A Evans; - on behalf of the PHOSP-COVID Collaborative Group,"The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Population Health Sciences, University of Leicester, Leicester, UK; University of Dundee, Ninewells Hospital and Medical School, Dundee, UK; Division of Infection, Immunity & Respiratory Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK; MRC Human Immunology Unit, University of Oxford, Oxford, UK; Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK; Asthma and Lung UK, London, UK; Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre- Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; National Heart and Lung Institute, Imperial College London, London, UK; London School of Hygiene & Tropical Medicine, London, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; The Roslin Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Wellcome-Wolfson Institute for Experimental Medicine, Queens University Belfast, Belfast, UK; Hywel Dda University Health Board, Wales, UK; St George's University Hospitals NHS Foundation Trust, London, UK; Leeds Teaching Hospitals NHS Trust, Leeds, UK; NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK; UCL Respiratory, Department of Medicine, University College London, London, UK; Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK; Salford Royal NHS Foundation Trust, Manchester, UK; Infection Research Group, Hull University Teaching Hospitals, Hull, UK; Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, UK; Department of Respiratory Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK; Lane Fox Respiratory Unit, Guy's and St Thomas' NHS Foundation Trust, London, UK; Royal Free London NHS Foundation Trust, London, UK; Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK; Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK; Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK; NIHR Oxford Biomedical Research Centre, Oxford, UK; University of Sheffield, Sheffield, UK; University of Sheffield, Sheffield, UK; Centre for Human & Applied Physiological Sciences, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK; King's College London British Heart Foundation Centre, London, UK; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool, UK; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK; NIHR Oxford Health Biomedical Research Centre, University of Oxford, Oxford, UK; The CRUK Liverpool Experimental Cancer Medicine Centre, Liverpool, UK; Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK; Imperial College Healthcare NHS Trust, London, UK; Centre for Medical Image Computing, University College London, London, UK; National Heart and Lung Institute, Imperial College London, London, UK; MRC-Versus Arthritis Centre for Musculoskeletal Ageing Research, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK; Royal Brompton & Harefield Hospitals, Guy's and St. Thomas' NHS Foundation Trust, London, UK; Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester; NIHR Oxford Biomedical Research Centre, Oxford, UK; National Heart and Lung Institute, Imperial College London, London, UK; UCL Respiratory, Department of Medicine, University College London, London, UK; Kadoorie Centre for Critical Care Research, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; MRC-University of Glasgow Center for Virus research; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool, UK; Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Immunology and Inflammation, Imperial College London, London, UK; NIHR Cambridge Biomedical Research Centre, Cambridge, United Kingdom; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Population Health Sciences, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; ","O_LIPHOSP-COVID is a national UK multi-centre cohort study of patients who were hospitalised for COVID-19 and subsequently discharged. -C_LIO_LIPHOSP-COVID was established to investigate the medium- and long-term sequelae of severe COVID-19 requiring hospitalisation, understand the underlying mechanisms of these sequelae, evaluate the medium- and long-term effects of COVID-19 treatments, and to serve as a platform to enable future studies, including clinical trials. -C_LIO_LIData collected covered a wide range of physical measures, biological samples, and Patient Reported Outcome Measures (PROMs). -C_LIO_LIParticipants could join the cohort either in Tier 1 only with remote data collection using hospital records, a PROMs app and postal saliva sample for DNA, or in Tier 2 where they were invited to attend two specific research visits for further data collection and biological research sampling. These research visits occurred at five (range 2-7) months and 12 (range 10-14) months post-discharge. Participants could also participate in specific nested studies (Tier 3) at selected sites. -C_LIO_LIAll participants were asked to consent to further follow-up for 25 years via linkage to their electronic healthcare records and to be re-contacted for further research. -C_LIO_LIIn total, 7935 participants were recruited from 83 UK sites: 5238 to Tier 1 and 2697 to Tier 2, between August 2020 and March 2022. -C_LIO_LICohort data are held in a Trusted Research Environment and samples stored in a central biobank. Data and samples can be accessed upon request and subject to approvals. -C_LI",respiratory medicine,fuzzy,100,100 medRxiv,10.1101/2023.05.08.23289637,2023-05-08,https://medrxiv.org/cgi/content/short/2023.05.08.23289637,SARS-CoV-2 Infection Biomarkers Reveal an Extended RSAD2 Dependant Metabolic Pathway,Samuele Sala; Philipp Nitschke; Reika Masuda; Nicola Gray; Nathan Lawler; James M. Wood; Joshua N Butler; Georgy Berezhnoy; Alejandro Bolanos; Berin A. Boughton; Caterina Lonati; Titus Roessler; Yogesh Singh; Ian D. Wilson; Samantha Lodge; Aude-Claire Morillon; Ruey Leng Loo; Drew Hall; Luke Whiley; Gary B. Evans; Tyler L. Grove; Steven C. Almo; Lawrence D. Harris; Elaine Holmes; Uta Merle; Christoph Trautwein; Jeremy K. Nicholson; Julien Wist,"The Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Aust; The Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Aust; The Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Aust; The Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Aust; The Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Aust; Ferrier Research Institute, Victoria University of Wellington, Wellington 6012, New Zealand ;The Maurice Wilkins Centre for Molecular Biodiscovery, The Universi; Ferrier Research Institute, Victoria University of Wellington, Wellington 6012, New Zealand; Department of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, University Hospital Tuebingen, Tuebingen, Germany; Chemistry Department, Universidad del Valle, Cali 76001, Colombia; The Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Aust; Center for Preclinical Research, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy; Department of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, University Hospital Tuebingen, Tuebingen, Germany; Institute of Medical Genetics and Applied Genomics, University Hospital Tuebingen, Germany; Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College, Burlington Danes Building, Du Cane Road, London W12 0NN, U; The Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Aust; The Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Aust; The Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Aust; The Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Aust; The Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Aust; Ferrier Research Institute, Victoria University of Wellington, Wellington 6012, New Zealand ;The Maurice Wilkins Centre for Molecular Biodiscovery, The Universi; Department of Biochemistry, Albert Einstein College of Medicine, Bronx, New York 10461, United States; Department of Biochemistry, Albert Einstein College of Medicine, Bronx, New York 10461, United States; Ferrier Research Institute, Victoria University of Wellington, Wellington 6012, New Zealand ;The Maurice Wilkins Centre for Molecular Biodiscovery, The Universi; The Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Aust; Department of Internal Medicine IV, University Hospital Heidelberg, Heidelberg, Germany; Department of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, University Hospital Tuebingen, Tuebingen, Germany; The Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Aust; The Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Aust","We present compelling evidence for the existence of an extended innate viperin dependent pathway which provides crucial evidence for an adaptive response to viral agents like SARS-CoV-2. We show the in vivo biosynthesis of a family of endogenous cytosine metabolites with potential antiviral activity. Two dimensional Nuclear magnetic resonance (NMR) spectroscopy revealed a characteristic spin-system motif indicating the presence of an extended panel of urinary metabolites during the acute viral replication phase. Mass spectrometry additionally allowed the characterization and quantification of the most abundant serum metabolites showing potential diagnostic value of the compounds for viral infections. In total, we unveiled ten nucleoside (cytosine and uracil based) analogue structures, eight of which were previously unknown in humans. The molecular structures of the nucleoside analogues and their correlation with an array of serum cytokines, including IFN-2, IFN-{gamma} and IL-10, suggest an association with the viperin enzyme contributing to an endogenous innate immune defence mechanism against viral infection.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2023.04.24.23289043,2023-04-24,https://medrxiv.org/cgi/content/short/2023.04.24.23289043,LONG-TERM PHYSICAL AND MENTAL HEALTH IMPACT OF COVID-19 ON ADULTS IN ENGLAND: FOLLOW UP OF A LARGE RANDOM COMMUNITY SAMPLE,Christina J Atchison; Bethan Davies; Emily Cooper; Adam Lound; Matthew Whitaker; Adam Hampshire; Adriana Azor; Christl A Donnelly; Marc Chadeau-Hyam; Graham Cooke; Helen Ward; Paul Elliott,Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College; Imperial College London; Imperial College London School of Public Health,"BackgroundThe COVID-19 pandemic is having a lasting impact on health and well-being. We compare current self-reported health, quality of life and symptom profiles for people with ongoing symptoms following COVID-19 to those who have never had COVID-19 or have recovered. @@ -357,21 +357,6 @@ Methods and ResultsSurface sampling was undertaken at 12 workplaces that experie ConclusionsFew workplace surface samples were positive for SARS-CoV-2 RNA and positive samples typically contained low levels of nucleic acid. Although these data may infer a low probability of fomite transmission or other forms of transmission within the workplace, Ct values may have been lower at the time of contamination. Workplace environmental sampling identified lapses in COVID-control measures within individual sites and showed trends through the pandemic. Significance and Impact of the StudyPrior to this study, few published reports investigated SARS-CoV-2 RNA contamination within workplaces experiencing cases of COVID-19. This report provides extensive data on environmental sampling identifying trends across workplaces and through the pandemic.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2023.02.18.23286127,2023-02-19,https://medrxiv.org/cgi/content/short/2023.02.18.23286127,Antipsychotic prescribing and mortality in people with dementia before and during the COVID-19 pandemic: retrospective cohort study,Christian Schnier; Aoife McCarthy; Daniel R Morales; Ashley Akbari; Reecha Sofat; Caroline Dale; Rohan Takhar; Mamas Mamas; Kamlesh Khunti; Francesco Zaccardi; Cathie LM Sudlow; Tim Wilkinson,University of Edinburgh; University of Edinburgh; University of Dundee; Swansea University; University of Liverpool; University of Liverpool; University College London; Keele University; University of Leicester; University of Leicester; University of Edinburgh; University of Edinburgh,"BackgroundAntipsychotic drugs have been associated with increased mortality, stroke and myocardial infarction in people with dementia. Concerns have been raised that antipsychotic prescribing may have increased during the COVID-19 pandemic due to social restrictions imposed to limit the spread of the virus. We used multisource, routinely-collected healthcare data from Wales, UK, to investigate prescribing and mortality trends in people with dementia before and during the COVID-19 pandemic. - -MethodsWe used individual-level, anonymised, population-scale linked health data to identify adults aged [≥]60 years with a diagnosis of dementia in Wales, UK. We explored antipsychotic prescribing trends over 67 months between 1st January 2016 and 1st August 2021, overall and stratified by age and dementia subtype. We used time series analyses to examine all-cause, myocardial infarction (MI) and stroke mortality over the study period and identified the leading causes of death in people with dementia. - -FindingsOf 57,396 people with dementia, 11,929 (21%) were prescribed an antipsychotic at any point during follow-up. Accounting for seasonality, antipsychotic prescribing increased during the second half of 2019 and throughout 2020. However, the absolute difference in prescribing rates was small, ranging from 1253 to 1305 per 10,000 person-months. Prescribing in the 60-64 age group and those with Alzheimers disease increased throughout the 5-year period. All-cause and stroke mortality increased in the second half of 2019 and throughout 2020 but MI mortality declined. From January 2020, COVID-19 was the second commonest underlying cause of death in people with dementia. - -InterpretationDuring the COVID-19 pandemic there was a small increase in antipsychotic prescribing in people with dementia. The long-term increase in antipsychotic prescribing in younger people and in those with Alzheimers disease warrants further investigation. - -FundingBritish Heart Foundation (BHF) (SP/19/3/34678) via the BHF Data Science Centre led by HDR UK, and the Scottish Neurological Research Fund. - -Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched Ovid MEDLINE for studies describing antipsychotic prescribing trends in people with dementia during the COVID-19 pandemic, published between 1st January 2020 and 22nd March 2022. The following search terms were used: (exp Antipsychotic Agents/ OR antipsychotic.mp OR neuroleptic.mp OR risperidone.mp OR exp Risperidone/ OR quetiapine.mp OR exp Quetiapine Fumarate/ OR olanzapine.mp OR exp Olanzapine/ OR exp Psychotropic Drugs/ or psychotropic.mp) AND (exp Dementia/ OR exp Alzheimer Disease/ or alzheimer.mp) AND (prescri*.mp OR exp Prescriptions/ OR exp Electronic Prescribing/ OR trend*.mp OR time series.mp). The search identified 128 published studies, of which three were eligible for inclusion. Two studies, based on data from England and the USA, compared antipsychotic prescribing in people with dementia before and during the COVID-19 pandemic. Both reported an increase in the proportion of patients prescribed an antipsychotic after the onset of the pandemic. A third study, based in the Netherlands, reported antipsychotic prescription trends in nursing home residents with dementia during the first four months of the pandemic, comparing prescribing rates to the timings of lifting of social restrictions, showing that antipsychotic prescribing rates remained constant throughout this period. - -Added value of this studyWe conducted age-standardised time series analyses using comprehensive, linked, anonymised, individual-level routinely-collected, population-scale health data for the population of Wales, UK. By accounting for seasonal variations in prescribing and mortality, we demonstrated that the absolute increase in antipsychotic prescribing in people with dementia of any cause during the COVID-19 pandemic was small. In contrast, antipsychotic prescribing in the youngest age group (60-64 years) and in people with a subtype diagnosis of Alzheimers disease increased throughout the five-year study period. Accounting for seasonal variation, all-cause mortality rates in people with dementia began to increase in late 2019 and increased sharply during the first few months of the pandemic. COVID-19 became the leading non-dementia cause of death in people with dementia from 2020 to 2021. Stroke mortality increased during the pandemic, following a similar pattern to that of all-cause mortality, whereas myocardial infarction rates decreased. - -Implications of all the available evidenceDuring COVID-19 we observed a large increase in all-cause and stroke mortality in people with dementia. When seasonal variations are accounted for, antipsychotic prescribing rates in all-cause dementia increased by a small amount before and during the pandemic in the UK. The increased prescribing rates in younger age groups and in people with Alzheimers disease warrants further investigation.",neurology,fuzzy,100,100 medRxiv,10.1101/2023.02.16.23286017,2023-02-18,https://medrxiv.org/cgi/content/short/2023.02.16.23286017,Long-term outdoor air pollution and COVID-19 mortality in London: an individual-level analysis,Loes Charlton; Chris Gale; Jasper Morgan; Myer Glickman; Sean Beevers; Anna L Hansell; Vahé Nafilyan,Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Imperial College London; University of Leicester; Office for National Statistics,"BackgroundThe risk of COVID-19 severity and mortality differs markedly by age, socio-demographic characteristics and pre-existing health status. Various studies have suggested that higher air pollution exposures also increase the likelihood of dying from COVID-19. Objectives: To assess the association between long-term outdoor air pollution (NO2, NOx, PM10 and PM2.5) concentrations and the risk of death involving COVID-19, using a large individual-level dataset. @@ -455,6 +440,7 @@ MethodsWe analysed secondary care data linked to Virus Watch study data for adul ResultsOf 30,276 adults in the analyses, 26,492 (87.5%) were UK-born and 3,784 (12.5%) were migrants. COVID-19-related hospitalisation incidence rates for UK-born and migrant individuals across waves 1-3 were 2.7 [95% CI 2.2-3.2], and 4.6 [3.1-6.7] per 1,000 person-years, respectively. Pooled incidence rate ratios across waves suggested increased rate of COVID-19-related hospitalisation in migrants compared to UK-born individuals in unadjusted 1.68 [1.08-2.60] and adjusted analyses 1.35 [0.71-2.60]. ConclusionOur findings suggest migration populations in the UK have excess risk of COVID-19-related hospitalisations and underscore the need for more equitable interventions particularly aimed at COVID-19 vaccination uptake among migrants.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2023.01.04.22283762,2023-01-05,https://medrxiv.org/cgi/content/short/2023.01.04.22283762,Challenges in estimating waning effectiveness of two doses of BNT162b2 and ChAdOx1 COVID-19 vaccines beyond six months: an OpenSAFELY cohort study using linked electronic health records,Elsie MF Horne; William J Hulme; Ruth H Keogh; Tom M Palmer; Elizabeth Williamson; Edward PK Parker; Venexia M Walker; Rochelle Knight; Yinghui Wei; Kurt Taylor; Louis Fisher; Jessica Morley; Amir Mehrkar; Iain Dillingham; Sebastian CJ Bacon; Ben Goldacre; Jonathan AC Sterne; - The OpenSAFELY Collaborative,University of Bristol; University of Oxford; London School of Hygiene and Tropical Medicine; University of Bristol; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Bristol; University of Bristol; University of Plymouth; University of Bristol; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Bristol; -,"Quantifying the waning effectiveness of second COVID-19 vaccination beyond six months and against the omicron variant is important for scheduling subsequent doses. With the approval of NHS England, we estimated effectiveness up to one year after second dose, but found that bias in such estimates may be substantial.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2023.01.04.23284174,2023-01-05,https://medrxiv.org/cgi/content/short/2023.01.04.23284174,Ethnic differences in the indirect impacts of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: An observational cohort study using OpenSAFELY,Ruth E Costello; John Tazare; Dominik Piehlmaier; Emily Herrett; Edward PK Parker; Bang Zheng; Kathryn E Mansfield; Alasdair D Henderson; Helena Carreira; Patrick Bidulka; Angel YS Wong; Charlotte Warren-Gash; Joseph F Hayes; Jennifer K Quint; Brian MacKenna; Rosalind M Eggo; Srinivasa Vittal Katikireddi; Laurie Tomlinson; Sinead M Langan; Rohini Mathur; - The longitudinal health and wellbeing; - The OpenSAFELYcollaborative,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Sussex; London School of Hygiene and Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; UCL; Imperial College London; University of Oxford; London School of Hygiene & Tropical Medicine; University of Glasgow; LSHTM; London School of Hygiene and Tropical Medicine; Queen Mary University of London; ; ,"BackgroundThe COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England. MethodsWe conducted a cohort study using OpenSAFELY (2018-2022). We grouped ethnicity (exposure), into five categories: White, South Asian, Black, Other, Mixed. We used interrupted time-series regression to estimate ethnic differences in clinical monitoring frequency (e.g., blood pressure measurements) before and after 23rd March 2020. We used multivariable Cox regression to quantify ethnic differences in hospitalisations related to: diabetes, cardiovascular disease, respiratory disease, and mental health before and after 23rd March 2020. @@ -517,29 +503,7 @@ MethodsWith the approval of NHS England we utilised individual-level electronic FindingsThere were large declines in avoidable hospitalisations during the first national lockdown, which then reversed post-lockdown albeit never reaching pre-pandemic levels. While trends were consistent by each measure of inequality, absolute levels of inequalities narrowed throughout 2020 (especially during the first national lockdown) and remained lower than pre-pandemic trends. While the scale of inequalities remained similar into 2021 for deprivation and ethnicity, we found evidence of widening absolute and relative inequalities by geographic region in 2021 and 2022. InterpretationThe anticipation that healthcare disruption from the COVID-19 pandemic and lockdowns would result in more (avoidable) hospitalisations and widening social inequalities was wrong. However, the recent growing gap between geographic regions suggests that the effects of the pandemic has reinforced spatial inequalities.",public and global health,fuzzy,100,100 -medRxiv,10.1101/2022.12.13.22283391,2022-12-14,https://medrxiv.org/cgi/content/short/2022.12.13.22283391,The effects of sleep disturbance on dyspnoea and impaired lung function following COVID-19 hospitalisation: a prospective multi-centre cohort study,Callum Jackson; Iain Stewart; Tatiana Plekhanova; Peter Cunningham; Andrew L. Hazel; Bashar Al-Sheklly; Raminder Aul; Charlotte E. Bolton; Trudie Chalder; James D. Chalmers; Nazia Chaudhuri; Annemaire B. Docherty; Gavin Donaldson; Charlotte L. Edwardson; Omer Elneima; Neil J Greening; Neil A. Hanley; Victoria C. Harris; Ewen M. Harrison; Ling-Pei Ho; Linzy Houchen-Wolloff; Luke S. Howard; Caroline J. Jolley; Mark G. Jones; Olivia C. Leavy; Keir E. Lewis; Nazir I. Lone; Michael Marks; Hamish J. C. McAuley; Melitta A. McNarry; Brijesh Patel; Karen Piper-Hanley; Krisnah Poinasamy; Betty Raman; Matthew Richardson; Pilar Rivera-Ortega; Sarah L. Rowland-Jones; Alex V. Rowlands; Ruth M. Saunders; Janet T Scott; Marco Sereno; Ajay M. Shah; Aarti Shikotra; Amisha Singapuri; Stefan C. Stanel; Mathew Thorpe; Daniel G. Wootton; Thomas Yates; R Gisli Jenkins; Sally Singh; William D-C. Man; Chris E. Brightling; Louise V. Wain; Joanna C. Porter; A. A. Roger Thompson; Alexander Horsley; Phil L. Molyneaux; Rachael E. Evans; Samuel E. Jones; Martin K. Rutter; John F. Blaikley,"Department of Mathematics, The University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom; National Heart & Lung Institute, Imperial College London, London, UK; Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK; Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester M13 9PL United Kingdom; Department of Mathematics, The University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom; Manchester University NHS Foundation Trust & University of Manchester; St Georges Univeristy Hospitals NHS Foundation Trust, London, UK; NIHR Nottingham BRC respiratory theme, Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; University of Dundee, Ninewells Hospital and Medical School, Dundee, UK; University Hospital of South Manchester NHS Foundation Trust; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; National Heart & Lung Institute, Imperial College London, London, UK; Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Manchester University NHS Foundation Trust; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Oxford University Hospitals NHS Foundation Trust & University of Oxford; Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; National Heart & Lung Institute, Imperial College London, London, UK; King's College London; Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK; Department of Health Sciences, Univeristy of Leicester, Leicester, UK; Swansea University, Swansea Welsh Network, Hywel Dda University Health Board; Usher Institute, University of Edinburgh, Edinburgh, UK; Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Swansea University, Swansea Welsh Network, Hywel Dda University Health Board; Royal Brompton and Harefield Clinical Group, Guys and St Thomas NHS Foundation trust; Manchester University NHS Foundation Trust & University of Manchester; Asthma UK and British Lung Foundation, London, UK; Oxford University Hospitals NHS Foundation Trust & University of Oxford; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Manchester University NHS Foundation Trust; University of Sheffield, Sheffield, UK; Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; MRC - University of Glasgow Centre for Virus Research, Glasgow, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; King's College Hospital NHS Foundation Trust & Kings College London; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Interstitial Lung Disease Unit, North West Lung Centre, Wythenshawe Hospital, Southmoor Rd, Wythenshawe, Manchester M23 9LT, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Liverpool University Hospitals NHS Foundation Trust & University of Liverpool; Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK; National Heart & Lung Institute, Imperial College London, London, UK; University Hospitals of Leicester NHS Trust & University of Leicester; National Heart & Lung Institute, Imperial College London, London, UK; University Hospitals of Leicester NHS Trust & University of Leicester; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Department of Respiratory Medicine, University College London WC1E 2JF; Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield UK; Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester M13 9PL United Kingdom; National Heart & Lung Institute, Imperial College London, London, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland; Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester M13 9PL United Kingdom; The University of Manchester","BackgroundSleep disturbance is common following hospitalisation both for COVID-19 and other causes. The clinical associations are poorly understood, despite it altering pathophysiology in other scenarios. We, therefore, investigated whether sleep disturbance is associated with dyspnoea along with relevant mediation pathways. - -MethodsSleep parameters were assessed in a prospective cohort of patients (n=2,468) hospitalised for COVID-19 in the United Kingdom in 39 centres using both subjective and device-based measures. Results were compared to a matched UK biobank cohort and associations were evaluated using multivariable linear regression. - -Findings64% (456/714) of participants reported poor sleep quality; 56% felt their sleep quality had deteriorated for at least 1-year following hospitalisation. Compared to the matched cohort, both sleep regularity (44.5 vs 59.2, p<0.001) and sleep efficiency (85.4% vs 88.5%, p<0.001) were lower whilst sleep period duration was longer (8.25h vs 7.32h, p<0.001). Overall sleep quality (effect estimate 4.2 (3.0-5.5)), deterioration in sleep quality following hospitalisation (effect estimate 3.2 (2.0-4.5)), and sleep regularity (effect estimate 5.9 (3.7-8.1)) were associated with both dyspnoea and impaired lung function (FEV1 and FVC). Depending on the sleep metric, anxiety mediated 13-42% of the effect of sleep disturbance on dyspnoea and muscle weakness mediated 29-43% of this effect. - -InterpretationSleep disturbance is associated with dyspnoea, anxiety and muscle weakness following COVID-19 hospitalisation. It could have similar effects for other causes of hospitalisation where sleep disturbance is prevalent. - -FundingUK Research and Innovation, National Institute for Health Research, and Engineering and Physical Sciences Research Council.",respiratory medicine,fuzzy,100,100 medRxiv,10.1101/2022.12.09.22283280,2022-12-13,https://medrxiv.org/cgi/content/short/2022.12.09.22283280,Identification of a protein expression signature distinguishing early from organising diffuse alveolar damage in COVID-19 patients.,Helen Ashwin; Luke Milross; Julie Wilson; Joaquim Majo; Jimmy T. H. Lee; Grant Calder; Bethany Hunter; Sally James; Dimitris Lagos; Nathalie Signoret; Andrew Filby; Omer Ali Bayraktar; Andrew J Fisher; Paul M Kaye,University of York; Newcastle University; University of York; Newcastle upon Tyne Hospitals NHS Foundation Trust; Sanger Institute; University of York; Newcastle University; University of York; University of York; University of York; Newcastle University; Sanger Institute; Newcastle University; University of York,"Diffuse alveolar damage (DAD) is a histopathological finding associated with severe viral infections, including SARS-CoV-2. However, the mechanisms mediating progression of DAD are poorly understood. Applying protein digital spatial profiling to lung tissue obtained from a cohort of 27 COVID-19 autopsy cases from the UK, we identified a protein signature (ARG1, CD127, GZMB, IDO1, Ki67, phospho-PRAS40 (T246), and VISTA that distinguishes early / exudative DAD from late / organising DAD with good predictive accuracy. These proteins warrant further investigation as potential immunotherapeutic targets to modulate DAD progression and improve patient outcome.",pathology,fuzzy,92,100 -medRxiv,10.1101/2022.11.29.22282883,2022-12-12,https://medrxiv.org/cgi/content/short/2022.11.29.22282883,"The protection gap under a social health protection initiative in the COVID-19 pandemic: A case study from Khyber Pakhtunkhwa, Pakistan.",Sheraz Ahmad Khan; Kathrin Cresswell; Aziz Sheikh,The University of Edinburgh; The University of Edinburgh College of Medicine and Veterinary Medicine; The University of Edinburgh College of Medicine and Veterinary Medicine,"BackgroundSehat Sahulat Programme (SSP) is a Social Health Protection (SHP) initiative by the Government of Khyber Pakhtunkhwa (GoKP), covering inpatient services for 100% of the provinces population. In this paper, we describe SSPs role in GoKPs COVID-19 response and draw inferences for similar programmes in Pakistan. - -Methodology and methodsWe conceptualised SSP as an instrumental case study and collected three complementary data sources. First, we studied GoKPs official documents to understand SSPs benefits package. Then we undertook in-depth interviews and collected non-participant observations at the SSP policy and implementation levels. We recruited participants through direct (verbal and email) and indirect (invitation posters) methods. - -Use of maximum variation sampling enabled us to understand contrasting views from various stakeholders on SSPs policy dimensions (i.e., coverage and financing), tensions between the policy directions (i.e., whether or not to cover COVID-19) and how policy decisions were made and implemented. We collected data from March 2021 to December 2021. Thematic analysis was conducted with the help of Nvivo12. - -FindingsThroughout 2020, SSP did not cover COVID-19 treatment. The insurer and GoKP officials considered the pandemic a standard exclusion to insurance coverage. One SSP official said: ""COVID-19 is not covered and not relevant to us"". GoKP had stopped non-emergency services at all hospitals. When routine services restarted, the insurer did not cover COVID-19 screening tests, which were mandatory prior to hospital admission. - -In 2021, GoKP engaged 10 private SSP hospitals for COVID-19 treatment. The SSP Reserve Fund, rather than insurance pooled money, was used. The Reserve Fund was originally meant to cover high-cost organ transplants. In 2021, SSP had 1,002 COVID-19-related admissions, which represented 0.2% of all hospital admissions (N=544,841). - -An advocacy group representative called the COVID-19 care under SSP ""too little too late"". In contrast, SSP officials suggested their insurance database and funds flow mechanism could help GoKP in future health emergencies. - -ConclusionThe commercially focused interpretation of SHP arrangements led to a protection gap in the context of COVID-19. SSP and similar programmes in other provinces of Pakistan should emphasise the notion of protection and not let commercial interests lead to protection gaps.",health policy,fuzzy,100,100 medRxiv,10.1101/2022.12.03.22282974,2022-12-07,https://medrxiv.org/cgi/content/short/2022.12.03.22282974,Non-generalizability of biomarkers for mortality in SARS-CoV-2: a meta-analyses series,ME Rahman Shuvo; Max Schweining; Felipe Soares; Oliver Feng; Susana Abreu; Niki Veale; William Thomas; AA Roger Thompson; Richard Samworth; Nicholas W Morrell; Stefan Marciniak; Elaine Soon,Cambridge University Hospitals NHS Foundation Trust; University of Cambridge; University of Sheffield; University of Cambridge; University of Cambridge; University of Cambridge; Cambridge University Hospitals NHS Foundation Trust; University of Sheffield; University of Cambridge; University of Cambridge; University of Cambridge; University Of Cambridge,"ObjectivesSophisticated scores have been proposed for prognostication of mortality due to SARS-CoV-2 but perform inconsistently. We conducted these meta-analyses to uncover why and to pragmatically seek a single dependable biomarker for mortality. DesignWe searched the PubMed database for the keywords SARS-CoV-2 with biomarker name and mortality. All studies published from 01st December 2019 to 30th June 2021 were surveyed. To aggregate the data, the meta library in R was used to report overall mean values and 95% confidence intervals. We fitted a random effects model to obtain pooled AUCs and associated 95% confidence intervals for the European/North American, Asian, and overall datasets. @@ -574,21 +538,6 @@ ResultsAmong the 2367 renal patients treated with sotrovimab (n=1852) or molnupi ConclusionsIn routine care of non-hospitalised patients with COVID-19 on kidney replacement therapy, those who received sotrovimab had substantially lower risk of severe COVID-19 outcomes than those receiving molnupiravir.",epidemiology,fuzzy,92,100 medRxiv,10.1101/2022.11.29.22282916,2022-11-30,https://medrxiv.org/cgi/content/short/2022.11.29.22282916,Correlates of protection against SARS-CoV-2 Omicron variant and anti-spike antibody responses after a third/booster vaccination or breakthrough infection in the UK general population,Jia Wei; Philippa C Matthews; Nicole Stoesser; John Newton; Ian Diamond; Ruth Studley; Nick Taylor; John Bell; Jeremy Farrar; Brian Marsden; Jaison Kolenchery; Sarah Hoosdally; Yvonne Jones; David Stuart; Derrick Crook; Tim E Peto; Ann Sarah Walker; Koen Pouwels; David W Eyre,University of Oxford; University of Oxford; University of Oxford; Public Health England; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Wellcome Trust; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford,"Following primary SARS-CoV-2 vaccination, understanding the relative extent of protection against SARS-CoV-2 infection from boosters or from breakthrough infections (i.e. infection in the context of previous vaccination) has important implications for vaccine policy. In this study, we investigated correlates of protection against Omicron BA.4/5 infections and anti-spike IgG antibody trajectories after a third/booster vaccination or breakthrough infection following second vaccination in 154,149 adults [≥]18y from the United Kingdom general population. We found that higher anti-spike IgG antibody levels were associated with increased protection against Omicron BA.4/5 infection and that breakthrough infections were associated with higher levels of protection at any given antibody level than booster vaccinations. Breakthrough infections generated similar antibody levels to third/booster vaccinations, and the subsequent declines in antibody levels were similar to or slightly slower than those after third/booster vaccinations. Taken together our findings show that breakthrough infection provides longer lasting protection against further infections than booster vaccinations. For example, considering antibody levels associated with 67% protection against infection, a third/booster vaccination did not provide long-lasting protection, while a Delta/Omicron BA.1 breakthrough infection could provide 5-10 months of protection against Omicron BA.4/5 reinfection. 50-60% of the vaccinated UK population with a breakthrough infection would still be protected by the end of 2022, compared to <15% of the triple-vaccinated UK population without previous infection. Although there are societal impacts and risks to some individuals associated with ongoing transmission, breakthrough infection could be an efficient immune-boosting mechanism for subgroups of the population, including younger healthy adults, who have low risks of adverse consequences from infection.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2022.11.29.22282899,2022-11-29,https://medrxiv.org/cgi/content/short/2022.11.29.22282899,"Performance of antigen lateral flow devices in the United Kingdom during the Alpha, Delta, and Omicron waves of the SARS-CoV-2 pandemic",David W Eyre; Matthias Futschik; Sarah Tunkel; Jia Wei; Joanna Cole-Hamilton; Rida Saquib; Nick Germanacos; Andrew Dodgson; Paul E Klapper; Malur Sudhanva; Chris Kenny; Peter Marks; Edward Blandford; Susan Hopkins; Tim Peto; Tom Fowler,University of Oxford; UK Health Security Agency; UK Health Security Agency; University of Oxford; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; University of Manchester; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; University of Oxford; UK Health Security Agency,"BackgroundAntigen lateral flow devices (LFDs) have been widely used to control SARS-CoV-2. Changes in LFD sensitivity and detection of infectious individuals during the pandemic with successive variants, vaccination, and changes in LFD use are incompletely understood. - -MethodsPaired LFD and PCR tests were collected from asymptomatic and symptomatic participants, across multiple settings in the UK between 04-November-2020 and 21-March-2022. Multivariable logistic regression was used to analyse LFD sensitivity and specificity, adjusting for viral load, LFD manufacturer, setting, age, sex, assistance, symptoms, vaccination, and variant. National contact tracing data were used to estimate the proportion of transmitting index cases (with [≥]1 PCR/LFD-positive contact) potentially detectable by LFDs over time, accounting for viral load, variant, and symptom status. - -Findings4131/75,382 (5.5%) participants were PCR-positive. Sensitivity vs. PCR was 63.2% (95%CI 61.7-64.6%) and specificity 99.71% (99.66-99.74%). Increased viral load was independently associated with being LFD-positive. There was no evidence LFD sensitivity differed between Delta vs. Alpha/pre-Alpha infections, but Omicron infections were more likely to be LFD positive. Sensitivity was higher in symptomatic participants, 68.7% (66.9-70.4%) than in asymptomatic participants, 52.8% (50.1-55.4%). 79.4% (68.6-81.3%) of index cases resulting in probable onward transmission with were estimated to have been detectable using LFDs, this proportion was relatively stable over time/variants, but lower in asymptomatic vs. symptomatic cases. - -InterpretationLFDs remained able to detect most SARS-CoV-2 infections throughout vaccine roll-out and different variants. LFDs can potentially detect most infections that transmit to others and reduce risks. However, performance is lower in asymptomatic compared to symptomatic individuals. - -FundingUK Government. - -Research in contextO_ST_ABSEvidence before this studyC_ST_ABSLateral flow devices (LFDs; i.e. rapid antigen detection devices) have been widely used for SARS-CoV-2 testing. However, due to their imperfect sensitivity when compared to PCR and a lack of a widely available gold standard proxy for infectiousness, the performance and use of LFDs has been a source of debate. We conducted a literature review in PubMed and bioRxiv/medRxiv for all studies examining the performance of lateral flow devices between 01 January 2020 and 31 October 2022. We used the search terms SARS-CoV-2/COVID-19 and antigen/lateral flow test/lateral flow device. Multiple studies have examined the sensitivity and specificity of LFDs, including several systematic reviews. However, the majority of the studies are based on pre-Alpha infections. Large studies examining the test accuracy for different variants, including Delta and Omicron, and following vaccination are limited. - -Added value of this studyIn this large national LFD evaluation programme, we compared the performance of three different LFDs relative to PCR in various settings. Compared to PCR testing, sensitivity was 63.2% (95%CI 61.7-64.6%) overall, and 71.6% (95%CI 69.8-73.4%) in unselected communitybased testing. Specificity was 99.71% (99.66-99.74%). LFDs were more likely to be positive as viral loads increased. LFD sensitivity was similar during Alpha/pre-Alpha and Delta periods but increased during the Omicron period. There was no association between sensitivity and vaccination status. Sensitivity was higher in symptomatic participants, 68.7% (66.9-70.4%) than in asymptomatic participants, 52.8% (50.1-55.4%). Using national contact tracing data, we estimated that 79.4% (68.6-81.3%) of index cases resulting in probable onward transmission (i.e. with [≥]1 PCR/LFD-positive contact) were detectable using LFDs. Symptomatic index cases were more likely to be detected than asymptomatic index cases due to higher viral loads and better LFD performance at a given viral load. The proportion of index cases detected remained relatively stable over time and with successive variants, with a slight increase in the proportion of asymptomatic index cases detected during Omicron. - -Implications of all the available evidenceOur data show that LFDs detect most SARS-CoV-2 infections, with findings broadly similar to those summarised in previous meta-analyses. We show that LFD performance has been relatively consistent throughout different variant-dominant phases of the pandemic and following the roll-out of vaccination. LFDs can detect most infections that transmit to others and can therefore be used as part of a risk reduction strategy. However, performance is lower in asymptomatic compared to symptomatic individuals and this needs to be considered when designing testing programmes.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2022.11.16.22282396,2022-11-18,https://medrxiv.org/cgi/content/short/2022.11.16.22282396,Comparative effectiveness of two- and three-dose schedules involving AZD1222 and BNT162b2 in people with kidney disease: a linked OpenSAFELY and UK Renal Registry cohort study,- The OpenSAFELY Collaborative; Edward PK Parker; Elsie MF Horne; William J Hulme; John Tazare; Bang Zheng; Edward J Carr; Fiona Loud; Susan Lyon; Viyaasan Mahalingasivam; Brian MacKenna; Amir Mehrkar; Miranda Scanlon; Shalini Santhakumaran; Retha Steenkamp; Ben Goldacre; Jonathan AC Sterne; Dorothea Nitsch; Laurie A Tomlinson; - The LH&W NCS (or CONVALESCENCE) Collaborative,"; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; The Francis Crick Institute, London, NW1 1AT, UK; Kidney Care UK, Alton, UK; Patient Council, UK Kidney Association, Bristol, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK; Kidney Research UK, Peterborough, UK; UK Renal Registry, Bristol, UK; UK Renal Registry, Bristol, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK; Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; ","BackgroundKidney disease is a key risk factor for COVID-19-related mortality and suboptimal vaccine response. Optimising vaccination strategies is essential to reduce the disease burden in this vulnerable population. MethodsWith the approval of NHS England, we performed a retrospective cohort study to estimate the comparative effectiveness of schedules involving AZD1222 (AZ; ChAdOx1-S) and BNT162b2 (BNT) among people with kidney disease. Using linked primary care and UK Renal Registry records in the OpenSAFELY-TPP platform, we identified adults with stage 3- 5 chronic kidney disease, dialysis recipients, and kidney transplant recipients. We used Cox proportional hazards models to compare COVID-19-related outcomes and non-COVID-19 death after two-dose (AZ-AZ vs BNT-BNT) and three-dose (AZ-AZ-BNT vs BNT-BNT- BNT) schedules. @@ -947,20 +896,6 @@ Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC=""FIGDIR/small/22276437v1_ufig1.gif"" ALT=""Figure 1""> View larger version (38K): org.highwire.dtl.DTLVardef@12b0afborg.highwire.dtl.DTLVardef@ddf3b2org.highwire.dtl.DTLVardef@1aa670forg.highwire.dtl.DTLVardef@5415ec_HPS_FORMAT_FIGEXP M_FIG C_FIG",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2022.06.17.22276433,2022-06-17,https://medrxiv.org/cgi/content/short/2022.06.17.22276433,It hurts your heart: frontline healthcare worker experiences of moral injury during the COVID-19 pandemic,Siobhan Hegarty; Danielle Lamb; Sharon Stevelink; Rupa Bhundia; Rosalind Raine; Mary Jane Docherty; Hannah Rachel Scott; Anne Marie Rafferty; Victoria Williamson; Sarah Dorrington; Matthew hotopf; Reza Razavi; Neil Greenberg; Simon Wessely,King's College London; UCL; King's College London; King's College London; University College London; South London and Maudsley NHS Foundation Trust; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London,"BackgroundMoral injury is defined as the strong emotional and cognitive reactions following events which clash with someones moral code, values or expectations. During the COVID-19 pandemic, increased exposure to potentially morally injurious events (PMIEs) has placed healthcare workers (HCWs) at risk of moral injury. Yet little is known about the lived experience of cumulative PMIE exposure and how NHS staff respond to this. - -ObjectiveWe sought to rectify this knowledge gap by qualitatively exploring the lived experiences and perspectives of clinical frontline NHS staff who responded to COVID-19. - -MethodsWe recruited a diverse sample of 30 clinical frontline HCWs from the NHS CHECK study cohort, for single time point qualitative interviews. All participants endorsed at least one item on the 9-item Moral Injury Events Scale (MIES) (Nash et al., 2013) at six month follow up. Interviews followed a semi-structured guide and were analysed using reflexive thematic analysis. - -ResultsHCWs described being routinely exposed to ethical conflicts, created by exacerbations of pre-existing systemic issues including inadequate staffing and resourcing. We found that HCWs experienced a range of mental health symptoms primarily related to perceptions of institutional betrayal as well as feeling unable to fulfil their duty of care towards patients. - -ConclusionThese results suggest that a multi-facetted organisational strategy is warranted to prepare for PMIE exposure, promote opportunities for resolution of symptoms associated with moral injury and prevent organisational disengagement. - -HighlightsO_LIClinical frontline healthcare workers (HCWs) have been exposed to an accumulation of potentially morally injurious events (PMIEs) throughout the COVID-19 pandemic, including feeling betrayed by both government and NHS leaders as well as feeling unable to provide duty of care to patients -C_LIO_LIHCWs described the significant adverse impact of this exposure on their mental health, including increased anxiety and depression symptoms and sleep disturbance -C_LIO_LIMost HCWs interviewed believed that organisational change within the NHS was necessary to prevent excess PMIE exposure and promote resolution of moral distress -C_LI",psychiatry and clinical psychology,fuzzy,100,100 medRxiv,10.1101/2022.06.16.22276479,2022-06-16,https://medrxiv.org/cgi/content/short/2022.06.16.22276479,Mental health of healthcare workers in England during the COVID-19 pandemic: a longitudinal cohort study,Danielle Lamb; Rafael Gafoor; Hannah Scott; Ewan Carr; Sharon Stevelink; Rosalind Raine; Matthew Hotopf; Neil Greenberg; Siobhan Hegarty; Ira Madan; Paul Moran; Richard Morriss; Dominic Murphy; Anne Marie Rafferty; Scott Weich; Sarah Dorrington; Simon Wessely,UCL; University College London; King's College London; King's College London; King's College London; University College London; King's College London; King's College London; King's College London; Guy's and St Thomas' NHS Foundation Trust; University of Bristol; University of Nottingham; Combat Stress; King's College London; University of Sheffield; King's College London; King's College London,"ObjectiveTo examine variations in impact of the COVID-19 pandemic on the mental health of all types of healthcare workers (HCWs) in England over the first 17 months of the pandemic. MethodWe undertook a prospective cohort study of 22,501 HCWs from 18 English acute and mental health NHS Trusts, collecting online survey data on common mental disorders (CMDs), depression, anxiety, alcohol use, and PTSD, from April 2020 to August 2021. We analysed these data cross-sectionally by time period (corresponding to periods the NHS was under most pressure), and longitudinally. Data were weighted to better represent Trust population demographics. @@ -1119,6 +1054,13 @@ FindingsVaccination programmes with early start dates incur the most health bene InterpretationAfrican countries with large proportions of their populations unvaccinated by late 2021 may find vaccination programmes less cost-effective than they could have been earlier in 2021. Lower vaccine purchasing costs and/or the emergence of new variants may improve cost-effectiveness. FundingBill and Melinda Gates Foundation, World Health Organization, National Institute of Health Research (UK), Health Data Research (UK)",health economics,fuzzy,100,100 +medRxiv,10.1101/2022.05.06.22274658,2022-05-07,https://medrxiv.org/cgi/content/short/2022.05.06.22274658,"STIMULATE-ICP-CAREINEQUAL - Defining usual care and examining inequalities in Long Covid support: protocol for a mixed-methods study (part of STIMULATE-ICP: Symptoms, Trajectory, Inequalities and Management: Understanding Long-COVID to Address and Transform Existing Integrated Care Pathways).",Mel Ramasawmy; Yi Mu; Donna Clutterbuck; Marija Pantelic; Gregory Y.H. Lip; Christina Van der Feltz-Cornelis; Dan Wootton; Nefyn H Williams; Hugh Montgomery; Rita Mallinson Cookson; Emily Attree; Mark Gabbay; Melissa J Heightman; Nisreen A Alwan; Amitava Banerjee; Paula Lorgelly; - STIMULATE-ICP consortium,"Institute of Health Informatics, University College London; Institute of Health Informatics, University College London; School of Primary Care, Population Sciences and Medical Education, University of Southampton; Brighton and Sussex Medical School, University of Sussex; Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool, United Kingdom; and Department of Clinical; Department of Health Sciences, HYMS, University of York, and Institute of Health Informatics, University College London; Institute of Infection Veterinary and Ecological Sciences, University of Liverpool; Department of Primary Care and Mental Health, University of Liverpool; Centre for Human Health and Performance, Department of Medicine, University College London; PPIE Representative; PPIE Representative; Department of Primary Care and Mental Health, University of Liverpool; University College London Hospitals NHS Trust; School of Primary Care, Population Sciences and Medical Education, University of Southampton; NIHR Southampton Biomedical Research Centre, University of Southam; Institute of Health Informatics, University College London; School of Population Health and Department of Economics, University of Auckland; ","IntroductionIndividuals with Long Covid represent a new and growing patient population. In England, fewer than 90 Long Covid clinics deliver assessment and treatment informed by NICE guidelines. However, a paucity of clinical trials or longitudinal cohort studies means that the epidemiology, clinical trajectory, healthcare utilisation and effectiveness of current Long Covid care are poorly documented, and that neither evidence-based treatments nor rehabilitation strategies exist. In addition, and in part due to pre-pandemic health inequalities, access to referral and care varies, and patient experience of the Long Covid care pathways can be poor. + +In a mixed methods study, we therefore aim to: (1) describe the usual healthcare, outcomes and resource utilisation of individuals with Long Covid; (2) assess the extent of inequalities in access to Long Covid care, and specifically to understand Long Covid patients experiences of stigma and discrimination. + +Methods and analysisA mixed methods study will address our aims. Qualitative data collection from patients and health professionals will be achieved through surveys, interviews and focus group discussions, to understand their experience and document the function of clinics. A patient cohort study will provide an understanding of outcomes and costs of care. Accessible data will be further analysed to understand the nature of Long Covid, and the care received. + +Ethics and disseminationEthical approval was obtained from South Central - Berkshire Research Ethics Committee (reference 303958). The dissemination plan will be decided by the patient and public involvement and engagement (PPIE) group members and study Co-Is, but will target 1) policy makers, and those responsible for commissioning and delivering Long Covid services, 2) patients and the public, and 3) academics.",health systems and quality improvement,fuzzy,100,100 medRxiv,10.1101/2022.05.05.22273234,2022-05-07,https://medrxiv.org/cgi/content/short/2022.05.05.22273234,Changes in English medication safety indicators throughout the COVID-19 pandemic: a federated analysis of 57 million patients' primary care records in situ using OpenSAFELY,Louis Fisher; Lisa E M Hopcroft; Sarah Rodgers; James Barrett; Kerry Oliver; Anthony J Avery; Dai Evans; Helen Curtis; Richard Croker; Orla Macdonald; Jessica Morley; Amir Mehrkar; Seb Bacon; Simon Davy; Iain Dillingham; David Evans; George Hickman; Peter Inglesby; Caroline E Morton; Becky Smith; Tom Ward; William Hulme; Amelia Green; Jon Massey; Alex J Walker; Chris Bates; Jonathan Cockburn; John Parry; Frank Hester; Sam Harper; Shaun O'Hanlon; Alex Eavis; Richard Jarvis; Dima Avramov; Paul Griffiths; Aaron Fowles; Nasreen Parkes; Ben Goldacre; Brian MacKenna,"Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; PRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; PRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; PRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; Centre for Academic Primary Care, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; PRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG","ObjectiveTo describe the impact of the COVID-19 pandemic on safe prescribing, using the PINCER prescribing indicators; to implement complex prescribing indicators at national scale using GP data. DesignPopulation based cohort study, with the approval of NHS England using the OpenSAFELY platform. @@ -1152,19 +1094,6 @@ Conflicts of InterestsNothing to declare. Funding statementThis work was supported by the Medical Research Council MR/V015737/1. TPP provided technical expertise and infrastructure within their data centre pro bono in the context of a national emergency. Rosalind Eggo is funded by HDR UK (grant: MR/S003975/1), MRC (grant: MC_PC 19065), NIHR (grant: NIHR200908).",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2022.04.29.22274267,2022-05-01,https://medrxiv.org/cgi/content/short/2022.04.29.22274267,Multi-omics identify LRRC15 as a COVID-19 severity predictor and persistent pro-thrombotic signals in convalescence,Jack S Gisby; Norzawani B Buang; Artemis Papadaki; Candice L Clarke; Talat H Malik; Nicholas Medjeral-Thomas; Damiola Pinheiro; Paige M Mortimer; Shanice Lewis; Eleanor Sandhu; Stephen P McAdoo; Maria F Prendecki; Michelle Willicombe; Matthew C Pickering; Marina Botto; David C Thomas; James E Peters,Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London,"Patients with end-stage kidney disease (ESKD) are at high risk of severe COVID-19. Here, we performed longitudinal blood sampling of ESKD haemodialysis patients with COVID-19, collecting samples pre-infection, serially during infection, and after clinical recovery. Using plasma proteomics, and RNA-sequencing and flow cytometry of immune cells, we identified transcriptomic and proteomic signatures of COVID-19 severity, and found distinct temporal molecular profiles in patients with severe disease. Supervised learning revealed that the plasma proteome was a superior indicator of clinical severity than the PBMC transcriptome. We showed that both the levels and trajectory of plasma LRRC15, a proposed co-receptor for SARS-CoV-2, are the strongest predictors of clinical outcome. Strikingly, we observed that two months after the acute infection, patients still display dysregulated gene expression related to vascular, platelet and coagulation pathways, including PF4 (platelet factor 4), which may explain the prolonged thrombotic risk following COVID-19.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2022.04.28.22273177,2022-04-29,https://medrxiv.org/cgi/content/short/2022.04.28.22273177,Occupational differences in SARS-CoV-2 infection: Analysis of the UK ONS Coronavirus (COVID-19) Infection Survey,Sarah Rhodes; Jack Wilkinson; Neil Pearce; Will Mueller; Mark Cherrie; Katie Stocking; Matthew Gittins; Srinivasa Vittal Katikireddi; Martie van Tongeren,University of Manchester; University of Manchester; London School of Hygiene and Tropical Medicine; Institute of Occupational Medicine; Institute of Occupational Medicine; University of Manchester; University of Manchester; University of Glasgow; University of Manchester,"BackgroundConsiderable concern remains about how occupational SARS-CoV-2 risk has evolved during the COVID-19 pandemic. We aimed to ascertain which occupations had the greatest risk of SARS-CoV-2 infection and explore how relative differences varied over the pandemic. - -MethodsAnalysis of cohort data from the UK Office of National Statistics Coronavirus (COVID-19) Infection Survey from April 2020 to November 2021. This survey is designed to be representative of the UK population and uses regular PCR testing. Cox and multilevel logistic regression to compare SARS-CoV-2 infection between occupational/sector groups, overall and by four time periods with interactions, adjusted for age, sex, ethnicity, deprivation, region, household size, urban/rural neighbourhood and current health conditions. - -ResultsBased on 3,910,311 observations from 312,304 working age adults, elevated risks of infection can be seen overall for social care (HR 1.14; 95% CI 1.04 to 1.24), education (HR 1.31; 95% CI 1.23 to 1.39), bus and coach drivers (1.43; 95% CI 1.03 to 1.97) and police and protective services (HR 1.45; 95% CI 1.29 to 1.62) when compared to non-essential workers. By time period, relative differences were more pronounced early in the pandemic. For healthcare elevated odds in the early waves switched to a reduction in the later stages. Education saw raises after the initial lockdown and this has persisted. Adjustment for covariates made very little difference to effect estimates. - -ConclusionsElevated risks among healthcare workers have diminished over time but education workers have had persistently higher risks. Long-term mitigation measures in certain workplaces may be warranted. - -What is already known on this topicSome occupational groups have observed increased rates of disease and mortality relating to COVID-19. - -What this study addsRelative differences between occupational groups have varied during different stages of the COVID-19 pandemic with risks for healthcare workers diminishing over time and workers in the education sector seeing persistent elevated risks. - -How this study might affect research, practice or policyIncreased long term mitigation such as ventilation should be considered in sectors with a persistent elevated risk. It is important for workplace policy to be responsive to evolving pandemic risks.",occupational and environmental health,fuzzy,100,100 medRxiv,10.1101/2022.04.26.22274332,2022-04-27,https://medrxiv.org/cgi/content/short/2022.04.26.22274332,"Community factors and excess mortality in the COVID-19 pandemic in England, Italy and Sweden",Brandon Parkes; Massimo Stafoggia; Daniela Fecht; Bethan Davies; Carl Bonander; Francesca de'Donato; Paola Michelozzi; Frédéric B. Piel; Ulf Strömberg; Marta Blangiardo,Imperial College London; Lazio Regional Health Service; Imperial College London; Imperial College London; University of Gothenburg; Lazio Regional Health Service; Lazio Regional Health Service; Imperial College London; University of Gothenburg; Imperial College London,"BackgroundAnalyses of COVID-19 suggest specific risk factors make communities more or less vulnerable to pandemic related deaths within countries. What is unclear is whether the characteristics affecting vulnerability of small communities within countries produce similar patterns of excess mortality across countries with different demographics and public health responses to the pandemic. Our aim is to quantify community-level variations in excess mortality within England, Italy and Sweden and identify how such spatial variability was driven by community-level characteristics. MethodsWe applied a two-stage Bayesian model to quantify inequalities in excess mortality in people aged 40 years and older at the community level in England, Italy and Sweden during the first year of the pandemic (March 2020-February 2021). We used community characteristics measuring deprivation, air pollution, living conditions, population density and movement of people as covariates to quantify their associations with excess mortality. @@ -1204,6 +1133,7 @@ C_LI",health economics,fuzzy,100,100 medRxiv,10.1101/2022.04.22.22274176,2022-04-22,https://medrxiv.org/cgi/content/short/2022.04.22.22274176,Association between household composition and severe COVID-19 outcomes in older people by ethnicity: an observational cohort study using the OpenSAFELY platform,Kevin Wing; Daniel J Grint; Rohini Mathur; Hamish Gibbs; George Hickman; Emily Nightingale; Anna Schultze; Harriet Forbes; Vahe Nafilyan; Krishnan Bhaskaran; Elizabeth Williamson; Thomas House; Lorenzo Pellis; Emily Herrett; Nileesa Gautam; Helen J Curtis; Christopher T. Rentsch; Angel Wong; Brian MacKenna; Amir Mehrkar; Seb Bacon; Ian J Douglas; Stephen Evans; Laurie Tomlinson; Ben Goldacre; Rosalind M Eggo,"London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University College London; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Trop. Med.; University of Bristol; Office for National Statistics; London School of Hygiene and Tropical Medicine; London School of Hygiene & Tropical Medicine; University of Manchester; The University of Manchester; London School of Hygiene & Tropical Medicine; Aetion Inc; University of Oxford; US Department of Veterans Affairs, London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; University of Oxford; London School of Hygiene & Tropical Medicine","Ethnic differences in the risk of severe COVID-19 may be linked to household composition. We quantified the association between household composition and risk of severe COVID-19 by ethnicity for older individuals. With the approval of NHS England, we analysed ethnic differences in the association between household composition and severe COVID-19 in people aged 67 or over in England. We defined households by number of generations living together, and used multivariable Cox regression stratified by location and wave of the pandemic and accounted for age, sex, comorbidities, smoking, obesity, housing density and deprivation. We included 2 692 223 people over 67 years in wave 1 (01/02/2020-31/08/2020) and 2 731 427 in wave 2 (01/09/2020-31/01/2021). Multigenerational living was associated with increased risk of severe COVID-19 for White and South Asian older people in both waves (e.g. wave 2, 67+ living with 3 other generations vs 67+ year olds only: White HR 1{middle dot}61 95% CI 1{middle dot}38-1{middle dot}87, South Asian HR 1{middle dot}76 95% CI 1{middle dot}48-2{middle dot}10), with a trend for increased risks of severe COVID-19 with increasing generations in wave 2. Multigenerational living was associated with severe COVID-19 in older adults. Older South Asian people are over-represented within multigenerational households in England, especially in the most deprived settings. The number of generations in a household, number of occupants, ethnicity and deprivation status are important considerations in the continued roll-out of COVID-19 vaccination and targeting of interventions for future pandemics. FundingThis research was funded in part, by the Wellcome Trust. For the purpose of open access, the author has applied a CC-BY public copyright licence to any Author Accepted Manuscript version arising from this submission.",epidemiology,fuzzy,100,100 +bioRxiv,10.1101/2022.04.20.488895,2022-04-20,https://biorxiv.org/cgi/content/short/2022.04.20.488895,Emergence of new subgenomic mRNAs in SARS-CoV-2,Harriet V Mears; George R Young; Theo Sanderson; Ruth Harvey; Margaret Crawford; Daniel M Snell; Ashley S Fowler; Saira Hussain; Jerome Nicod; Edward Emmott; Katja Finsterbusch; Jakub Luptak; Emma Wall; Bryan Williams; Sonia Gandhi; Charles Swanton; David LV Bauer,"RNA Virus Replication Laboratory, The Francis Crick Institute, London, UK; RNA Virus Replication Laboratory & Bioinformatics and Biostatistics STP, The Francis Crick Institute, London, UK; Malaria Biochemistry Laboratory, The Francis Crick Institute, London, UK; Worldwide Influenza Centre, The Francis Crick Institute, London, UK; Advanced Sequencing Facility, The Francis Crick Institute, London, UK; Advanced Sequencing Facility, The Francis Crick Institute, London, UK; Advanced Sequencing Facility, The Francis Crick Institute, London, UK; RNA Virus Replication Laboratory, The Francis Crick Institute, London, UK; Advanced Sequencing Facility, The Francis Crick Institute, London, UK; Centre for Proteome Research, Department of Biochemistry & Systems Biology, Institute of Systems Molecular & Integrative Biology, University of Liverpool, Liver; Immunoregulation Laboratory, The Francis Crick Institute, London, UK; MRC Laboratory of Molecular Biology, Cambridge, UK; Crick/UCLH Legacy Study, The Francis Crick Institute, London, UK; and National Institute for Health Research (NIHR) University College London Hospitals (UCLH) B; University College London; and National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK; Neurodegeneration Biology Laboratory, The Francis Crick Institute, London, UK; Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK; RNA Virus Replication Laboratory, The Francis Crick Institute, London, UK","Two mutations occurred in SARS-CoV-2 early during the COVID-19 pandemic that have come to define circulating virus lineages1: first a change in the spike protein (D614G) that defines the B.1 lineage and second, a double substitution in the nucleocapsid protein (R203K, G204R) that defines the B.1.1 lineage, which has subsequently given rise to three Variants of Concern: Alpha, Gamma and Omicron. While the latter mutations appear unremarkable at the protein level, there are dramatic implications at the nucleotide level: the GGG[->]AAC substitution generates a new Transcription Regulatory Sequence (TRS) motif, driving SARS-CoV-2 to express a novel subgenomic mRNA (sgmRNA) encoding a truncated C-terminal portion of nucleocapsid (N.iORF3), which is an inhibitor of type I interferon production. We find that N.iORF3 also emerged independently within the Iota variant, and further show that additional TRS motifs have convergently evolved to express novel sgmRNAs; notably upstream of Spike within the nsp16 coding region of ORF1b, which is expressed during human infection. Our findings demonstrate that SARS-CoV-2 is undergoing evolutionary changes at the functional RNA level in addition to the amino acid level, reminiscent of eukaryotic evolution. Greater attention to this aspect in the assessment of emerging strains of SARS-CoV-2 is warranted.",microbiology,fuzzy,100,100 medRxiv,10.1101/2022.04.14.22273903,2022-04-20,https://medrxiv.org/cgi/content/short/2022.04.14.22273903,Effects of COVID-19 in Care Homes - A Mixed Methods Review,C Heneghan; M Dietrich; J Brassey; T Jefferson,The University of Oxford; Collateral Global; Trip Database Ltd; The University of Oxford,"IntroductionThe report provides an up-to-date review of the global effects of the COVID-19 pandemic in care homes. We used a mixed methods approach to assess care home mortality by country, how the deaths compared with previous periods, and how excess deaths may be explained. We retrieved national datasets for 25 countries on mortality, 17 cohort studies assessing deaths compared to a previous period, and 16 cohort studies reporting interventions or factors associated with excess mortality. The COVID-19 pandemic disproportionately impacted those living in care homes at the highest risk for severe outcomes. However, the pandemic only highlighted and exacerbated a long-running problem: underfunding, poor structural layout, undertraining, under-skilling, under-equipping, and finally, lack of humanity in dealing with the most vulnerable members of society. @@ -1324,6 +1254,30 @@ MethodsThis cohort study, using the OpenSAFELY-TPP database and approved by NHS FindingsThe BNT162b2, ChAdOx1 and unvaccinated groups comprised 1,773,970, 2,961,011 and 2,433,988 individuals, respectively. Waning of vaccine effectiveness was similar across outcomes and vaccine brands: e.g. in the 65+ years subgroup ratios of aHRs versus unvaccinated for COVID-19 hospitalisation, COVID-19 death and positive SARS-CoV-2 test ranged from 1.23 (95% CI 1.15-1.32) to 1.27 (1.20-1.34) for BNT162b2 and 1.16 (0.98-1.37) to 1.20 (1.14-1.27) for ChAdOx1. Despite waning, rates of COVID-19 hospitalisation and COVID-19 death were substantially lower among vaccinated individuals compared to unvaccinated individuals up to 26 weeks after second dose, with estimated aHRs <0.20 (>80% vaccine effectiveness) for BNT162b2, and <0.26 (>74%) for ChAdOx1. By weeks 23-26, rates of SARS-CoV-2 infection in fully vaccinated individuals were similar to or higher than those in unvaccinated individuals: aHRs ranged from 0.85 (0.78-0.92) to 1.53 (1.07-2.18) for BNT162b2, and 1.21 (1.13-1.30) to 1.99 (1.94-2.05) for ChAdOx1. InterpretationThe rate at which estimated vaccine effectiveness waned was strikingly consistent for COVID-19 hospitalisation, COVID-19 death and positive SARS-CoV-2 test, and similar across subgroups defined by age and clinical vulnerability. If sustained to outcomes of infection with the Omicron variant and to booster vaccination, these findings will facilitate scheduling of booster vaccination doses.",infectious diseases,fuzzy,100,100 +medRxiv,10.1101/2022.03.18.22272607,2022-03-21,https://medrxiv.org/cgi/content/short/2022.03.18.22272607,"Multi-organ impairment and Long COVID: a 1-year prospective, longitudinal cohort study",Andrea Dennis; Daniel J Cuthbertson; Dan Wootton; Michael Crooks; Mark Gabbay; Nicole Eichert; Sofia Mouchti; Michele Pansini; Adriana Roca-Fernandez; Helena Thomaides-Brears; Matt Kelly; Matthew Robson; Lyth Hishmeh; Emily Attree; Melissa J Heightman; Rajarshi Banerjee; Amitava Banerjee,Perspectum Ltd; University of Liverpool; University of Liverpool; University of Hull; University of Liverpool; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Diagnostics; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Long COVID SoS; UKDoctors#Longcovid; UCLH; Perspectum Ltd; University College London,"ImportanceMulti-organ impairment associated with Long COVID is a significant burden to individuals, populations and health systems, presenting challenges for diagnosis and care provision. Standardised assessment across multiple organs over time is lacking, particularly in non-hospitalised individuals. + +ObjectiveTo determine the prevalence of organ impairment in Long COVID patients at 6 and at 12 months after initial symptoms and to explore links to clinical presentation. + +DesignThis was a prospective, longitudinal study in individuals following recovery from acute COVID-19. We assessed symptoms, health status, and multi-organ tissue characterisation and function, using consensus definitions for single and multi-organ impairment. Physiological and biochemical investigations were performed at baseline on all individuals and those with organ impairment were reassessed, including multi-organ MRI, 6 months later. + +SettingTwo non-acute settings (Oxford and London). + +Participants536 individuals (mean 45 years, 73% female, 89% white, 32% healthcare workers, 13% acute COVID-19 hospitalisation) completed baseline assessment (median: 6 months post-COVID-19). 331 (62%) with organ impairment or incidental findings had follow up, with reduced symptom burden from baseline (median number of symptoms: 10 and 3, at 6 and 12 months). + +ExposureSARS-CoV-2 infection 6 months prior to first assessment. + +Main outcomePrevalence of single and multi-organ impairment at 6 and 12 months post-COVID-19. + +ResultsExtreme breathlessness (36% and 30%), cognitive dysfunction (50% and 38%) and poor health-related quality of life (EQ-5D-5L<0.7; 55% and 45%) were common at 6 and 12 months, and associated with female gender, younger age and single organ impairment. At baseline, there was fibro-inflammation in the heart (9%), pancreas (9%), kidney (15%) and liver (11%); increased volume in liver (7%), spleen (8%) and kidney (9%); decreased capacity in lungs (2%); and excessive fat deposition in the liver (25%) and pancreas (15%). Single and multi-organ impairment were present in 59% and 23% at baseline, persisting in 59% and 27% at follow-up. + +Conclusion and RelevanceOrgan impairment was present in 59% of individuals at 6 months post-COVID-19, persisting in 59% of those followed up at 1 year, with implications for symptoms, quality of life and longer-term health, signalling need for prevention and integrated care of Long COVID. + +Trial RegistrationClinicalTrials.gov Identifier: NCT04369807 + +Key pointsO_LIQuestion: What is the prevalence of organ impairment in Long COVID at 6- and 12-months post-COVID-19? +C_LIO_LIFindings: In a prospective study of 536 mainly non-hospitalised individuals, symptom burden decreased, but single organ impairment persisted in 59% at 12 months post-COVID-19. +C_LIO_LIMeaning: Organ impairment in Long COVID has implications for symptoms, quality of life and longer-term health, signalling need for prevention and integrated care of Long COVID. +C_LI",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2022.03.17.22272414,2022-03-18,https://medrxiv.org/cgi/content/short/2022.03.17.22272414,Modelling the impact of non-pharmaceutical interventions on workplace transmission of SARS-CoV-2 in the home-delivery sector,Carl A Whitfield; Martie Van Tongeren; Yang Han; Hua Wei; Sarah A Daniels; Martyn Regan; David W Denning; Arpana Verma; Lorenzo Pellis; - University of Manchester COVID-19 Modelling Group; Ian Hall,University of Manchester; University of Manchester; University of Manchester; University of Manchester; University of Manchester; University of Manchester; University of Manchaster; University of Manchester; University of Manchester; ; University of Manchester,"ObjectiveWe aimed to use mathematical models of SARS-COV-2 to assess the potential efficacy of non-pharmaceutical interventions on transmission in the parcel delivery and logistics sector. MethodsWe developed a network-based model of workplace contacts based on data and consultations from companies in the parcel delivery and logistics sectors. We used these in stochastic simulations of disease transmission to predict the probability of workplace outbreaks in this settings. Individuals in the model have different viral load trajectories based on SARS-CoV-2 in-host dynamics, which couple to their infectiousness and test positive probability over time, in order to determine the impact of testing and isolation measures. @@ -1429,6 +1383,7 @@ Added value of this studyWe report findings from a prospective cohort study that This is the first study to examine and describe waning of immunity over a one-year period, as well as vaccine effectiveness of a booster dose, in a large cohort of LTCF staff and residents. Implications of all the available evidenceTaken together, our findings indicate high short-term immunity against SARS-CoV2 infection and very high immunity against severe clinical outcomes of COVID-19 for LTCF residents and staff following vaccination. However substantial waning in vaccine-derived immunity is seen beyond 3 months, irrespective of vaccine type, suggesting the need for regular boosting to maintain protection in this vulnerable cohort. Although this analysis took place in the pre-Omicron period, these trends of waning immunity over time are likely to be generalisable across variants, carrying important implications for long-term vaccination policy in LTCFs. Ongoing surveillance in this vulnerable cohort remains crucial, in order to describe further changes in vaccine-induced immunity, particularly in the context of new variants.",infectious diseases,fuzzy,100,100 +bioRxiv,10.1101/2022.03.08.481609,2022-03-08,https://biorxiv.org/cgi/content/short/2022.03.08.481609,The origins and molecular evolution of SARS-CoV-2 lineage B.1.1.7 in the UK,Verity Hill; Louis du Plessis; Thomas P Alexander Peacock; Dinesh Aggarwal; Alessandro Carabelli; Rachel Colquhoun; Nicholas Ellaby; Eileen Gallagher; Natalie Groves; Ben Jackson; JT McCrone; Anna Price; Theo Sanderson; Emily Scher; Joel Alexander Southgate; Erik Volz; - The COVID-19 genomics UK (COG-UK) consortium; Wendy S Barclay; Jeffrey Barrett; Meera Chand; Thomas R Connor; Ian G. Goodfellow; Ravindra K Gupta; Ewan Harrison; Nicholas Loman; Richard Myers; David L Robertson; Oliver Pybus; Andrew Rambaut,The University of Edinburgh; University of Oxford; University College London (UCL); University of Cambridge; University of Cambridge; University of Edinburgh; UK Health Security Agency; Uk Health Security Agency; UK Health Security Agency; University of Edinburgh; University of Edinburgh; Cardiff University; Sanger Institute; University of Edinburgh; Cardiff University; Imperial College London; -; Imperial College London; Sanger Institute; UK Health Security Agency; Cardiff University; University of Cambridge; University of Cambridge; Sanger Institute; University of Birmingham; UK Health Security Agency; University of Glasgow; University of Oxford; University of Edinburgh,"The first SARS-CoV-2 variant of concern (VOC) to be designated was lineage B.1.1.7, later labelled by the World Health Organisation (WHO) as Alpha. Originating in early Autumn but discovered in December 2020, it spread rapidly and caused large waves of infections worldwide. The Alpha variant is notable for being defined by a long ancestral phylogenetic branch with an increased evolutionary rate, along which only two sequences have been sampled. Alpha genomes comprise a well-supported monophyletic clade within which the evolutionary rate is more typical of SARS-CoV-2. The Alpha epidemic continued to grow despite the continued restrictions on social mixing across the UK, and the imposition of new restrictions, in particular the English national lockdown in November 2020. While these interventions succeeded in reducing the absolute number of cases, the impact of these non-pharmaceutical interventions was predominantly to drive the decline of the SARS-CoV-2 lineages which preceded Alpha. We investigate the only two sampled sequences that fall on the branch ancestral to Alpha. We find that one is likely to be a true intermediate sequence, providing information about the order of mutational events that led to Alpha. We explore alternate hypotheses that can explain how Alpha acquired a large number of mutations yet remained largely unobserved in a region of high genomic surveillance: an under-sampled geographical location, a non-human animal population, or a chronically-infected individual. We conclude that the last hypothesis provides the best explanation of the observed behaviour and dynamics of the variant, although we find that the individual need not be immunocompromised, as persistently-infected immunocompetent hosts also display a higher within-host rate of evolution. Finally, we compare the ancestral branches and mutation profiles of other VOCs to each other, and identify that Delta appears to be an outlier both in terms of the genomic locations of its defining mutations, and its lack of rapid evolutionary rate on the ancestral branch. As new variants, such as Omicron, continue to evolve (potentially through similar mechanisms) it remains important to investigate the origins of other variants to identify ways to potentially disrupt their evolution and emergence.",evolutionary biology,fuzzy,100,100 medRxiv,10.1101/2022.03.06.21267462,2022-03-08,https://medrxiv.org/cgi/content/short/2022.03.06.21267462,Risk of myocarditis and pericarditis following COVID-19 vaccination in England and Wales,Samanatha Ip; Fatemeh Torabi; Spiros Denaxas; Ashley Akbari; Hoda Abbasizanjani; Rochelle Knight; Jennifer Anne Cooper; Rachel Denholm; Spencer Keene; Thomas Bolton; Sam Hollings; Efosa Omigi; Teri-Louise North; Arun Karthikeyan Suseeladevi; Emanuele Di Angelantonio; Kamlesh Khunti; Jonathan A C Sterne; Cathie Sudlow; William Whiteley; Angela Wood; Venexia Walker; - British Heart Foundation Data Science Centre (HDR UK) CVD-COVID-UK/COVID-IMPACT Consortium; - UK Covid-19 Longitudinal Health and Wellbeing National Core Study; - UK Covid-19 Data and Connectivity National Core Study,University of Cambridge; Swansea University; University College London; Swansea University; Swansea University; University of Bristol; University of Bristol; University of Bristol; University of Cambridge; Health Data Research UK; NHS Digital; NHS Digital; University of Bristol; University of Bristol; University of Cambridge; University of Leicester; University of Bristol; Health Data Research UK; University of Edinburgh; University of Cambridge; University of Bristol; ; ; ,"We describe our analyses of data from over 49.7 million people in England, representing near-complete coverage of the relevant population, to assess the risk of myocarditis and pericarditis following BNT162b2 and ChAdOx1 COVID-19 vaccination. A self-controlled case series (SCCS) design has previously reported increased risk of myocarditis after first ChAdOx1, BNT162b2, and mRNA-1273 dose and after second doses of mRNA COVID-19 vaccines in England. Here, we use a cohort design to estimate hazard ratios for hospitalised or fatal myocarditis/pericarditis after first and second doses of BNT162b2 and ChAdOx1 vaccinations. SCCS and cohort designs are subject to different assumptions and biases and therefore provide the opportunity for triangulation of evidence. In contrast to the findings from the SCCS approach previously reported for England, we found evidence for lower incidence of hospitalised or fatal myocarditis/pericarditis after first ChAdOx1 and BNT162b2 vaccination, as well as little evidence to suggest higher incidence of these events after second dose of either vaccination.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2022.03.02.22271762,2022-03-04,https://medrxiv.org/cgi/content/short/2022.03.02.22271762,"Disparities in SARS-CoV-2 case rates by ethnicity, religion, measures of socio-economic position, English proficiency, and self-reported disability: cohort study of 39 million people in England during the Alpha and Delta waves",Tim Larsen; Matthew L Bosworth; Daniel Ayoubkhani; Ryan Schofield; Raghib Ali; Kamlesh Khunti; Ann Sarah Walker; Myer Glickman; Vahe Nafilyan,Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Cambridge; University of Leicester; University of Oxford; Office for National Statistics; Office for National Statistics,"ObjectiveTo examine socio-demographic disparities in SARS-CoV-2 case rates during the second (Alpha) and third (Delta) waves of the COVID-19 pandemic. @@ -1451,6 +1406,15 @@ What this study addsUsing linked data on 39 million people in England, we found Adjusting for geographical factors, socio-demographic characteristics, and pre-pandemic health status explained some, but not all, of the excess risk When stratifying the dataset by broad age groups, the odds of receiving a positive test remained higher among the Bangladeshi and Pakistani ethnic groups aged 65 years and over during the third wave, which may partly explain the continued elevated mortality rates in these groups",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2022.03.02.22271623,2022-03-03,https://medrxiv.org/cgi/content/short/2022.03.02.22271623,"Baricitinib in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial and updated meta-analysis",Peter W Horby; Jonathan R Emberson; Marion Mafham; Mark Campbell; Leon Peto; Guilherme Pessoa-Amorim; Enti Spata; Natalie Staplin; Catherine Lowe; David R Chadwick; Christopher Brightling; Richard Stewart; Paul Collini; Abdul Ashish; Christopher A Green; Benjamin Prudon; Tim Felton; Anthony Kerry; J Kenneth Baillie; Maya H Buch; Jeremy N Day; Saul N Faust; Thomas Jaki; Katie Jeffery; Edmund Juszczak; Marian Knight; Wei Shen Lim; Alan Montgomery; Andrew Mumford; Kathryn Rowan; Guy Thwaites; Richard Haynes; Martin J Landray,"Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Liverpool University Hospitals NHS Foundation Trust; Centre for Clinical Infection, James Cook University Hospital, Middlesbrough, United Kingdom; Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; Milton Keynes University Hospital, Milton Keynes, United Kingdom; Sheffield Teaching Hospitals NHS Foundation Trust and University of Sheffield, Sheffield, United Kingdom; Wrightington, Wigan and Leigh Teaching Hospitals NHS Foundation Trust, Wigan, United Kingdom; University Hospitals Birmingham NHS Foundation Trust; North Tees and Hartlepool NHS Foundation Trust, Hartlepool, United Kingdom; Manchester University NHS Foundation Trust; Great Western Hospitals Foundation Trust, Swindon, United Kingdom; Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom; Centre for Musculoskeletal Research, University of Manchester, Manchester, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom; NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, ; Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom; Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Respiratory Medicine Department, Nottingham University Hospitals NHS Foundation Trust, Nottingham, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom; Intensive Care National Audit and Research Centre, London, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom","BackgroundWe evaluated the use of baricitinib, a Janus kinase (JAK) 1/2 inhibitor, for the treatment of patients admitted to hospital because of COVID-19. + +MethodsThis randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple possible treatments in patients hospitalised for COVID-19. Eligible and consenting patients were randomly allocated (1:1) to either usual standard of care alone (usual care group) or usual care plus baricitinib 4 mg once daily by mouth for 10 days or until discharge if sooner (baricitinib group). The primary outcome was 28-day mortality assessed in the intention-to-treat population. A meta-analysis was conducted that included the results from the RECOVERY trial and all previous randomised controlled trials of baricitinib or other JAK inhibitor in patients hospitalised with COVID-19. The RECOVERY trial is registered with ISRCTN (50189673) and clinicaltrials.gov (NCT04381936). + +FindingsBetween 2 February 2021 and 29 December 2021, 8156 patients were randomly allocated to receive usual care plus baricitinib versus usual care alone. At randomisation, 95% of patients were receiving corticosteroids and 23% receiving tocilizumab (with planned use within the next 24 hours recorded for a further 9%). Overall, 513 (12%) of 4148 patients allocated to baricitinib versus 546 (14%) of 4008 patients allocated to usual care died within 28 days (age-adjusted rate ratio 0{middle dot}87; 95% CI 0{middle dot}77-0{middle dot}98; p=0{middle dot}026). This 13% proportional reduction in mortality was somewhat smaller than that seen in a meta-analysis of 8 previous trials of a JAK inhibitor (involving 3732 patients and 425 deaths) in which allocation to a JAK inhibitor was associated with a 43% proportional reduction in mortality (rate ratio 0.57; 95% CI 0.45-0.72). Including the results from RECOVERY into an updated meta-analysis of all 9 completed trials (involving 11,888 randomised patients and 1484 deaths) allocation to baricitinib or other JAK inhibitor was associated with a 20% proportional reduction in mortality (rate ratio 0.80; 95% CI 0.71-0.89; p<0.001). In RECOVERY, there was no significant excess in death or infection due to non-COVID-19 causes and no excess of thrombosis, or other safety outcomes. + +InterpretationIn patients hospitalised for COVID-19, baricitinib significantly reduced the risk of death but the size of benefit was somewhat smaller than that suggested by previous trials. The total randomised evidence to date suggests that JAK inhibitors (chiefly baricitinib) reduce mortality in patients hospitalised for COVID-19 by about one-fifth. + +FundingUK Research and Innovation (Medical Research Council) and National Institute of Health Research (Grant ref: MC_PC_19056).",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2022.02.24.22271466,2022-02-25,https://medrxiv.org/cgi/content/short/2022.02.24.22271466,Risk of COVID-19 related deaths for SARS-CoV-2 Omicron (B.1.1.529) compared with Delta (B.1.617.2),Isobel L. Ward; Charlotte Bermingham; Daniel Ayoubkhani; Owen J. Gethings; Koen Pouwels; Thomas Yates; Kamlesh Khunti; Julia Hippisley-Cox; Amitava Banerjee; Ann Sarah Walker; Vahe Nafilyan,"Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford; Diabetes Research Centre, University of Leicester; Diabetes Research Centre, University of Leicester; University of Oxford; University College London; University of Oxford; Office for National Statistics","ObjectiveTo assess the risk of death involving COVID-19 following infection from Omicron (B.1.1.539/BA.1) relative to Delta (B.1.617.2). DesignRetrospective cohort study. @@ -1599,6 +1563,26 @@ ResultsRisk of hospital admission was markedly lower in 1241 residents infected ConclusionsRisk of severe outcomes in LTCF residents with the SARS-CoV-2 Omicron variant was substantially lower than that seen for previous variants. This suggests the current wave of Omicron infections is unlikely to lead to a major surge in severe disease in LTCF populations with high levels of vaccine coverage and/or natural immunity. Trial Registration NumberISRCTN 14447421",infectious diseases,fuzzy,100,100 +medRxiv,10.1101/2022.01.21.22269651,2022-01-22,https://medrxiv.org/cgi/content/short/2022.01.21.22269651,"Prior health-related behaviours in children (2014-2020) and association with a positive SARS-CoV-2 test during adolescence (2020-2021): a retrospective cohort study using survey data linked with routine health data in Wales, UK",Emily Marchant; Emily Lowthian; Tom Crick; Lucy Griffiths; Richard Fry; Kevin Dadaczynski; Orkan Okan; Michaela James; Laura Cowley; Fatemeh Torabi; Jonathan Kennedy; Ashley Akbari; Ronan Lyons; Sinead Brophy,Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Fulda University of Applied Sciences; Technical University Munich; Swansea University; Public Health Wales; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University,"ObjectivesExamine if pre-COVID-19 pandemic (prior March 2020) health-related behaviours during primary school are associated with i) being tested for SARS-CoV-2 and ii) testing positive between 1 March 2020 to 31 August 2021. + +DesignRetrospective cohort study using an online cohort survey (January 2018 to February 2020) linked to routine PCR SARS-CoV-2 test results. + +SettingChildren attending primary schools in Wales (2018-2020), UK who were part of the HAPPEN school network. + +ParticipantsComplete linked records of eligible participants were obtained for n=7,062 individuals. 39.1% (n=2,764) were tested (age 10.6{+/-}0.9, 48.9% girls) and 8.1% (n=569) tested positive for SARS-CoV-2 (age 10.6{+/-}1.0, 54.5% girls). + +Main outcome measuresLogistic regression of health-related behaviours and demographics were used to determine Odds Ratios (OR) of factors associated with i) being tested for SARS-CoV-2 and ii) testing positive for SARS-CoV-2. + +ResultsConsuming sugary snacks (1-2 days/week OR=1.24, 95% CI 1.04 - 1.49; 5-6 days/week 1.31, 1.07 - 1.61; reference 0 days) can swim 25m (1.21, 1.06 - 1.39) and age (1.25, 1.16 - 1.35) were associated with an increased likelihood of being tested for SARS-CoV-2. Eating breakfast (1.52, 1.01 - 2.27), weekly physical activity [≥] 60 mins (1-2 days 1.69, 1.04 - 2.74; 3-4 days 1.76, 1.10 - 2.82, reference 0 days), out of school club participation (1.06, 1.02 - 1.10), can ride a bike (1.39, 1.00 - 1.93), age (1.16, 1.05 - 1.28) and girls (1.21, 1.00 - 1.46) were associated with an increased likelihood of testing positive for SARS-CoV-2. Living in least deprived quintiles 4 (0.64, 0.46 - 0.90) and 5 (0.64, 0.46 - 0.89) compared to the most deprived quintile was associated with a decreased likelihood. + +ConclusionsAssociations may be related to parental health literacy and monitoring behaviours. Physically active behaviours may include co-participation with others, and exposure to SARS-CoV-2. A risk versus benefit approach must be considered given the importance of health-related behaviours for development. + +STRENGTHS AND LIMITATIONSO_LIInvestigation of the association of pre-pandemic child health-related behaviour measures with subsequent SARS-CoV-2 testing and infection. +C_LIO_LIReporting of multiple child health behaviours linked at an individual-level to routine records of SARS-CoV-2 testing data through the SAIL Databank. +C_LIO_LIChild-reported health behaviours were measured before the COVID-19 pandemic (1 January 2018 to 28 February 2020) which may not reflect behaviours during COVID-19. +C_LIO_LIHealth behaviours captured through the national-scale HAPPEN survey represent children attending schools that engaged with the HAPPEN Wales primary school network and may not be representative of the whole population of Wales. +C_LIO_LIThe period of study for PCR-testing for and testing positive for SARS-CoV-2 includes a time frame with varying prevalence rates, approaches to testing children (targeted and mass testing) and restrictions which were not measured in this study. +C_LI",public and global health,fuzzy,100,100 bioRxiv,10.1101/2022.01.14.475727,2022-01-18,https://biorxiv.org/cgi/content/short/2022.01.14.475727,Obesity associated with attenuated tissue immune cell responses in COVID-19,Shuang Andrew Guo; Georgina S Bowyer; John Robert Ferdinand; Mailis Maes; Zewen K Tuong; Eleanor Gilman; Rik G. H. Lindeboom; Masahiro Yoshida; Kaylee Worlock; Hudaa Gopee; Emily Stephenson; Paul A Lyons; Kenneth G. C. Smith; Muzlifah Haniffa; Kerstin B Meyer; Marko Z Nikolic; Richard G Wunderink; Alexander V Misharin; Gordon Dougan; Vilas Navapurkar; Sarah A Teichmann; Andrew Conway Morris; Menna R Clatworthy,University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; Wellcome Sanger Institute; University College London; University College London; Newcastle University; Newcastle University; University of Cambridge; University of Cambridge; Newcastle University; Wellcome Sanger Institute; University College London; Northwestern University; Northwestern University; University of Cambridge; Cambridge University Hospitals NHS Foundation Trust; Wellcome Sanger Institute; University of Cambridge; University of Cambridge,"Obesity is common and associated with more severe COVID-19, proposed to be in part related to an adipokine-driven pro-inflammatory state. Here we analysed single cell transcriptomes from bronchiolar lavage in three adult cohorts, comparing obese (Ob, body mass index (BMI) >30m2) and non-obese (N-Ob, BMI <30m2). Surprisingly, we found that Ob subjects had attenuated lung immune/inflammatory responses in SARS-CoV-2 infection, with decreased expression of interferon (IFN), IFN{gamma} and tumour necrosis factor (TNF) alpha response gene signatures in almost all lung epithelial and immune cell subsets, and lower expression of IFNG and TNF in specific lung immune cells. Analysis of peripheral blood immune cells in an independent adult cohort showed a similar, but less marked, reduction in type I IFN and IFN{gamma} response genes, as well as decreased serum IFN, in Ob patients with SARS-CoV-2. Nasal immune cells from Ob children with COVID-19 also showed reduced enrichment of IFN and IFN{gamma} response genes. Altogether, these findings show blunted tissue immune responses in Ob COVID-19 patients, with clinical implications.",immunology,fuzzy,100,100 medRxiv,10.1101/2022.01.18.22269082,2022-01-18,https://medrxiv.org/cgi/content/short/2022.01.18.22269082,OMICRON-ASSOCIATED CHANGES IN SARS-COV-2 SYMPTOMS IN THE UNITED KINGDOM,Karina-Doris Vihta; Koen B. Pouwels; Tim EA Peto; Emma Pritchard; Thomas House; Ruth Studley; Emma Rourke; Duncan Cook; Ian Diamond; Derrick Crook; David A Clifton; Philippa C. Matthews; Nicole Stoesser; David W. Eyre; Ann Sarah Walker; - COVID-19 Infection Survey team,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Manchester; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistcs; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; ,"BackgroundThe SARS-CoV-2 Delta variant has been replaced by the highly transmissible Omicron BA.1 variant, and subsequently by Omicron BA.2. It is important to understand how these changes in dominant variants affect reported symptoms, while also accounting for symptoms arising from other co-circulating respiratory viruses. @@ -1631,21 +1615,6 @@ ResultsYear-on-year change in dispensed CVD medicines by month were observed, wi ConclusionsManagement of key CVD risk factors as proxied by incident use of CVD medicines has not returned to pre-pandemic levels in the UK. Novel methods to identify and treat individuals who have missed treatment are urgently required to avoid large numbers of additional future CVD events, further adding indirect cost of the COVID-19 pandemic.",cardiovascular medicine,fuzzy,100,100 medRxiv,10.1101/2021.12.30.21268307,2021-12-30,https://medrxiv.org/cgi/content/short/2021.12.30.21268307,Short-term Projections based on Early Omicron Variant Dynamics in England.,Matt J Keeling; Ellen Brooks-Pollock; Robert J Challen; Leon Danon; Louise Dyson; Julia Rose Gog; Laura Guzman-Rincon; Edward M Hill; Lorenzo M Pellis; Jonathan M Read; Michael Tildesley,"University of Warwick; University of Bristol; University of Exeter / Taunton NHS Trust; Department of Engineering Mathematics, University of Bristol, UK.; University of Warwick; University of Cambridge; University of Warwick; University of Warwick; The University of Manchester; Lancaster University; University of Warwick","Throughout the ongoing COVID-19 pandemic, the worldwide transmission and replication of SARS-COV-2, the causative agent of COVID-19 disease, has resulted in the opportunity for multiple mutations to occur that may alter the virus transmission characteristics, the effectiveness of vaccines and the severity of disease upon infection. The Omicron variant (B.1.1.529) was first reported to the WHO by South Africa on 24 November 2021 and was declared a variant of concern by the WHO on 26 November 2021. The variant was first detected in the UK on 27 November 2021 and has since been reported in a number of countries globally where it is frequently associated with rapid increase in cases. Here we present analyses of UK data showing the earliest signatures of the Omicron variant and mathematical modelling that uses the UK data to simulate the potential impact of this variant in the UK. In order to account for the uncertainty in transmission advantage, vaccine escape and severity at the time of writing, we carry out a sensitivity analysis to assess the impact of these variant characteristics on future risk.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2021.12.21.21268058,2021-12-27,https://medrxiv.org/cgi/content/short/2021.12.21.21268058,"Effectiveness of CoronaVac, ChAdOx1, BNT162b2 and Ad26.COV2.S among individuals with prior SARS-CoV-2 infection in Brazil",Thiago Cerqueira-Silva; Jason R Andrews; Viviane S Boaventura; Otavio T Ranzani; Vinicius de Araujo Oliveira; Enny S Paixao; Juracy Bertoldo Jr.; Tales Mota Machado; Matt D T Hitchings; Murilo Dorion; Margaret L Lind; Gerson O. Penna; Derek A.T. Cummings; Natalie E Dean; Guilherme Loureiro Werneck; Neil Pearce; Mauricio L Barreto; Albert I Ko; Julio Croda; Manoel Barral-Netto,"Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA,USA; Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Universidade Federal da Bahia, Salvador, BA, Brazil; Barcelona Institute for Global Health, ISGlobal, Spain / Pulmonary Division, University of Sao Paulo; Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Healt; London School of Hygiene and Tropical Medicine, London, United Kingdom; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Health - Fiocruz, Salvador, BA, Brazil; Universidade Federal de Ouro Preto, Ouro Preto, MG, Brazil; Department of Biostatistics, College of Public Health & Health Professions, University of Florida, Gainesville, FL, USA; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Heaven, CT, USA; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Heaven, CT, USA; Nucleo de Medicina Tropical, Universidade de Brasilia, Brasilia, DF, Brazil; Escola Fiocruz de Governo, Fiocruz Brasilia. Brasilia, DF, Brazil; Department of Biology, University of Florida, Gainesville, FL, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA; Department of Biostatistics & Bioinformatics, Rollins School of Public Health, Emory University; Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil; London School of Hygiene and Tropical Medicine; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Health - Fiocruz, Salvador, BA, Brazil; Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Heaven, CT, USA; Universidade Federal de Mato Grosso do Sul, Campo Grande, MS, Brazil; Fiocruz Mato Grosso do Sul, Fundacao Oswaldo Cruz, Campo Grande, MS, Brazil; Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Healt","BackgroundCOVID-19 vaccines have proven highly effective among SARS-CoV-2 naive individuals, but their effectiveness in preventing symptomatic infection and severe outcomes among individuals with prior infection is less clear. - -MethodsUtilizing national COVID-19 notification, hospitalization, and vaccination datasets from Brazil, we performed a case-control study using a test-negative design to assess the effectiveness of four vaccines (CoronaVac, ChAdOx1, Ad26.COV2.S and BNT162b2) among individuals with laboratory-confirmed prior SARS-CoV-2 infection. We matched RT-PCR positive, symptomatic COVID-19 cases with RT-PCR-negative controls presenting with symptomatic illnesses, restricting both groups to tests performed at least 90 days after an initial infection. We used multivariable conditional logistic regression to compare the odds of test positivity, and the odds of hospitalization or death due to COVID-19, according to vaccination status and time since first or second dose of vaccines. - -FindingsAmong individuals with prior SARS-CoV-2 infection, vaccine effectiveness against symptomatic infection [≥] 14 days from vaccine series completion was 39.4% (95% CI 36.1-42.6) for CoronaVac, 56.0% (95% CI 51.4-60.2) for ChAdOx1, 44.0% (95% CI 31.5-54.2) for Ad26.COV2.S, and 64.8% (95% CI 54.9-72.4) for BNT162b2. For the two-dose vaccine series (CoronaVac, ChAdOx1, and BNT162b2), effectiveness against symptomatic infection was significantly greater after the second dose compared with the first dose. Effectiveness against hospitalization or death [≥] 14 days from vaccine series completion was 81.3% (95% CI 75.3-85.8) for CoronaVac, 89.9% (95% CI 83.5-93.8) for ChAdOx1, 57.7% (95% CI -2.6-82.5) for Ad26.COV2.S, and 89.7% (95% CI 54.3-97.7) for BNT162b2. - -InterpretationAll four vaccines conferred additional protection against symptomatic infections and severe outcomes among individuals with previous SARS-CoV-2 infection. Provision of a full vaccine series to individuals following recovery from COVID-19 may reduce morbidity and mortality. - -FundingBrazilian National Research Council, Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro, Oswaldo Cruz Foundation, JBS S.A., Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, Generalitat de Catalunya. - -RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed, medRxiv, and SSRN for articles published from January 1, 2020 until December 15, 2021, with no language restrictions, using the search terms ""vaccine effectiveness"" AND ""previous*"" AND (""SARS-CoV-2"" OR ""COVID-19""). We found several studies evaluating ChAdOx1 and BNT162b2, and one additionally reporting on mRNA-1273 and Ad26.COV2.S, which found that previously infected individuals who were vaccinated had lower risk of symptomatic SARS-CoV-2 infection. One study found that risk of hospitalization was lower for previously infected individuals after a full series of BNT162b2 or mRNA-1273. Limited evidence is available comparing effectiveness of one versus two doses among individuals with prior infection. No studies reported effectiveness of inactivated vaccines among previously infected individuals. - -Added value of this studyWe used national databases of COVID-19 case surveillance, laboratory testing, and vaccination from Brazil to investigate effectiveness of CoronaVac, ChAdOx1, Ad26.COV2.S and BNT162b2 among individuals with a prior, laboratory-confirmed SARS-CoV-2 infection. We matched >22,000 RT-PCR-confirmed re-infections with >145,000 RT-PCR-negative controls using a test-negative design. All four vaccines were effective against symptomatic SARS-CoV-2 infections, with effectiveness from 14 days after series completion ranging from 39-65%. For vaccines with two-dose regimens, the second dose provided significantly increased effectiveness compared with one dose. Effectiveness against COVID-19-associated hospitalization or death from 14 days after series completion was >80% for CoronaVac, ChAdOx1and BNT162b2. - -Implications of all the available evidenceWe find evidence that four vaccines, using three different platforms, all provide protection to previously infected individuals against symptomatic SARS-CoV-2 infection and severe outcomes, with a second dose conferring significant additional benefits. These results support the provision of a full vaccine series among individuals with prior SARS-CoV-2 infection.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.12.23.21268276,2021-12-25,https://medrxiv.org/cgi/content/short/2021.12.23.21268276,Risk of myocarditis following sequential COVID-19 vaccinations by age and sex,Martina Patone; Winnie Xue Mei; Lahiru Handunnetthi; Sharon Dixon; Francesco Zaccardi; Manu Shankar-Hari; Peter Watkinson; Kamlesh Khunti; Anthony Harnden; Carol AC Coupland; Keith M. Channon; Nicholas L Mills; Aziz Sheikh; Julia Hippisley-Cox,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Leicester; University of Edinburgh; University of Oxford; University of Leicester; University of Oxford; University of Oxford; University of Oxford; University of Edinburgh; University of Edinburgh; University of Oxford,"In an updated self-controlled case series analysis of 42,200,614 people aged 13 years or more, we evaluate the association between COVID-19 vaccination and myocarditis, stratified by age and sex, including 10,978,507 people receiving a third vaccine dose. Myocarditis risk was increased during 1-28 days following a third dose of BNT162b2 (IRR 2.02, 95%CI 1.40, 2.91). Associations were strongest in males younger than 40 years for all vaccine types with an additional 3 (95%CI 1, 5) and 12 (95% CI 1,17) events per million estimated in the 1-28 days following a first dose of BNT162b2 and mRNA-1273, respectively; 14 (95%CI 8, 17), 12 (95%CI 1, 7) and 101 (95%CI 95, 104) additional events following a second dose of ChAdOx1, BNT162b2 and mRNA-1273, respectively; and 13 (95%CI 7, 15) additional events following a third dose of BNT162b2, compared with 7 (95%CI 2, 11) additional events following COVID-19 infection. An association between COVID-19 infection and myocarditis was observed in all ages for both sexes but was substantially higher in those older than 40 years. These findings have important implications for public health and vaccination policy. FundingHealth Data Research UK.",epidemiology,fuzzy,100,100 @@ -1739,13 +1708,6 @@ MethodsWe estimated prevalence of SARS-CoV2 infection and used multiple logistic ResultsDuring mid-October to early-November 2021, weighted prevalence was 1.57% (1.48%, 1.66%) compared to 0.83% (0.76%, 0.89%) in September 2021 (round 14). Weighted prevalence increased between rounds 14 and 15 across most age groups (including older ages, 65 years and over) and regions, with average reproduction number across rounds of R=1.09 (1.08, 1.11). During round 15, there was a fall in prevalence from a maximum around 20-21 October, with an R of 0.76 (0.70, 0.83), reflecting falls in prevalence at ages 17 years and below and 18 to 54 years. School-aged children had the highest weighted prevalence of infection: 4.95% (4.39%, 5.58%) in those aged 5 to 12 years and 5.21% (4.61%, 5.87%) in those aged 13 to 17 years. In multiple logistic regression, age, sex, key worker status and presence of one or more children in the home were associated with swab positivity. There was evidence of heterogeneity between rounds in swab positivity rates among vaccinated individuals at ages 18 to 64 years, and differences in key demographic and other variables between vaccinated and unvaccinated adults at these ages. Vaccine effectiveness against infection in children was estimated to be 56.2% (41.3%, 67.4%) in rounds 13, 14 and 15 combined, adjusted for demographic factors, with a similar estimate obtained for round 15 only. Among adults we found that those who received a third dose of vaccine were less likely to test positive compared to those who received only two vaccine doses, with adjusted odds ratio (OR) =0.38 (0.26, 0.55). DiscussionSwab-positivity was very high at the start of round 15, reaching a maximum around 20 to 21 October 2021, and then falling through late October with an uncertain trend in the last few days of data collection. The observational nature of survey data and the relatively small proportion of unvaccinated adults call into question the comparability of vaccinated and unvaccinated groups at this relatively late stage in the vaccination programme. However, third vaccine doses for eligible adults and the vaccination of children aged 12 years and over are associated with lower infection risk and, thus, remain a high priority (with possible extension to children aged 5-12 years). These should help reduce SARS-CoV-2 transmission during the winter period when healthcare demands typically rise.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2021.12.16.21267906,2021-12-16,https://medrxiv.org/cgi/content/short/2021.12.16.21267906,Workplace Contact Patterns in England during the COVID-19 Pandemic: Analysis of the Virus Watch prospective cohort study,Sarah Beale; Susan J Hoskins; Thomas Edward Byrne; Erica Wing Lam Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Annalan MD Navaratnam; Vincent Nguyen; Parth Patel; Alexei Yavlinsky; Anne M Johnson; Robert W Aldridge; Andrew Hayward,University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London,"BackgroundWorkplaces are an important potential source of SARS-CoV-2 exposure; however, investigation into workplace contact patterns is lacking. This study aimed to investigate how workplace attendance and features of contact varied between occupations and over time during the COVID-19 pandemic in England. - -MethodsData were obtained from electronic contact diaries submitted between November 2020 and November 2021 by employed/self-employed prospective cohort study participants (n=4,616). We used mixed models to investigate the main effects and potential interactions between occupation and time for: workplace attendance, number of people in shared workspace, time spent sharing workspace, number of close contacts, and usage of face coverings. - -FindingsWorkplace attendance and contact patterns varied across occupations and time. The predicted probability of intense space sharing during the day was highest for healthcare (78% [95% CI: 75-81%]) and education workers (64% [59%-69%]), who also had the highest probabilities for larger numbers of close contacts (36% [32%-40%] and 38% [33%-43%] respectively). Education workers also demonstrated relatively low predicted probability (51% [44%-57%]) of wearing a face covering during close contact. Across all occupational groups, levels of workspace sharing and close contact were higher and usage of face coverings at work lower in later phases of the pandemic compared to earlier phases. - -InterpretationMajor variations in patterns of workplace contact and mask use are likely to contribute to differential COVID-19 risk. Across occupations, increasing workplace contact and reduced usage of face coverings presents an area of concern given ongoing high levels of community transmission and emergence of variants.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.12.13.21267471,2021-12-15,https://medrxiv.org/cgi/content/short/2021.12.13.21267471,Clinical characteristics with inflammation profiling of Long-COVID and association with one-year recovery following hospitalisation in the UK: a prospective observational study,Rachael Andrea Evans; Olivia C Leavy; Matthew Richardson; Omer Elneima; Hamish J C McAuley; Aarti Shikotra; Amisha Singapuri; Marco Sereno; Ruth M Saunders; Victoria C Harris; Raminder Aul; Paul Beirne; Charlotte E Bolton; Jeremy S Brown; Gourab Choudhury; Nawar Diar Bakerly; Nicholas Easom; Carlos Echevarria; Jonathan Fuld; Nick Hart; John R Hurst; Mark Jones; Dhruv Parekh; Paul Pfeffer; Najib M Rahman; Sarah Rowland-Jones; Ajay M Shah; Dan G Wootton; Trudie Chalder; Melanie J Davies; Anthony De Soyza; John R Geddes; William Greenhalf; Neil J Greening; Liam G Heaney; Simon Heller; Luke Howard; Joseph Jacob; R Gisli Jenkins; Janet M Lord; Will D-C Man; Gerry P McCann; Stefan Neubauer; Peter JM Openshaw; Joanna Porter; Jennifer Quint; Matthew J Rowland; Janet Scott; Malcolm G Semple; Sally J Singh; David Thomas; Mark Toshner; Keir Lewis; Andrew Briggs; Annemarie B Docherty; Steven Kerr; Nazir I Lone; Aziz Sheikh; Mathew Thorpe; Bang Zheng; Ryan S Thwaites; James D Chalmers; Ling-Pei Ho; Alex Horsley; Michael Marks; Krisnah Poinasamy; Betty Raman; Ewen M Harrison; Louise V Wain; Christopher E Brightling; - PHOSP-COVID Collaborative Group,"University of Leicester; Department of Health Sciences, University of Leicester, Leicester, United Kingdom; The Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; University Hospitals of Leicester,; St George's Univeristy Hospitals NHS Foundation Trust, London, United Kingdom; The Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom; University of Nottingham, Nottingham, United Kingdom; Nottingham Univeristy Hospitals NHS Trust, Nottingham, United Kingdom; NIHR Nottingham Biomedical Research; UCL Respiratory, Department of Medicine, University College London, Rayne Institute, London, United Kingdom; University of Edinburgh, Edinburgh, Scotland, United Kingdom; NHS Lothian, Scotland, United Kingdom; Manchester Metropolitan University, Manchester, United Kingdom; Salford Royal NHS Foundation Trust, Manchester, United Kingdom; Infection Research Group, Hull University Teaching Hospitals, Hull, United Kingdom; University of Hull, Hull, United Kingdom; The Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle, United Kingdom; Translational and Clinical Research Institute, Newcastle University, Newcastl; Department of Respiratory Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom; University of Cambridge, Cambridge, United K; Lane Fox Respiratory Service, Guys and St Thomas NHS Foundation Trust, London, United Kingdom; University College London, London, United Kingdom; Royal Free London NHS Foundation Trust, London, United Kingdom; University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom; University of Southampton, Southampton, United Kingdom; University of Birmingham, Birmingham, United Kingdom; University Hospital Birmingham NHS Foundation Trust, Birmingham, United Kingdom; Barts Health NHS Trust, London, United Kingdom; Queen Mary University of London, London, United Kingdom; Oxford University Hospitals NHS Trust, Oxford, United Kingdom; University of Oxford, Oxford, United Kingdom; Oxford NIHR Biomedical Research Centre, Oxford, Uni; University of Sheffield, Sheffield, United Kingdom; Sheffield Teaching NHS Foundation Trust, Sheffield, United Kingdom; King's College London, London, United Kingdom; King's College London NHS Foundation Trust, London, United Kingdom; Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, United Kingdom; Liverpool University Hospitals NHS Foundation Tr; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; South London and Maud; Diabetes Research Centre, University of Leicester, Leicester, United Kingdom; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, Uni; Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, United Kingdom; Newcastle upon Tyne Teaching Hospitals Trust, Newcastle upon Ty; University of Oxford; University of Liverpool, Liverpool, United Kingdom; The CRUK Liverpool Experimental Cancer Medicine Centre, Liverpool, United Kingdom; Liverpool University Hosp; The Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; Wellcome-Wolfson Institute for Experimental Medicine, Queens University Belfast, United Kingdom; Belfast Health & Social Care Trust, Belfast, United Kingdom; Department of Oncology and Metabolism, University of Sheffield, Sheffield, United Kingdom; Imperial College Healthcare NHS Trust, London, United Kingdom; Imperial College London, London, United Kingdom; Centre for Medical Image Computing, University College London, London, United Kingdom; Lungs for Living Research Centre, University College London, London, Unit; National Heart and Lung Institute, Imperial College London, London, United Kingdom; MRC-Versus Arthritis Centre for Musculoskeletal Ageing Research, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, United Kingdom; NIH; Royal Brompton and Harefield Clinical Group, Guys and St Thomas NHS Foundation Trust, London, United Kingdom; National Heart and Lung Institute, Imperial Colleg; Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom; NIHR Leicester Biomedical Research Centre, University of Leicester, L; Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom; NIHR Biomedical Research Centre, John Radcl; National Heart and Lung Institute, Imperial College London, London, United Kingdom; UCL Respiratory, Department of Medicine, University College London, Rayne Institute, London, United Kingdom; ILD Service, University College London Hospital, Lo; National Heart and Lung Institute, Imperial College London, London, United Kingdom; Kadoorie Centre for Critical Care Research, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom; MRC-University of Glasgow Centre for Virus Research, Glasgow, Scotland, United Kingdom; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, U; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; Imperial College London, London, UK; NIHR Cambridge Biomedical Research Centre, Cambridge, United Kingdom; NIHR Cambridge Clinical Research Facility, Cambridge, United Kingdom; Hywel Dda University Health Board, Wales, United Kingdom; University of Swansea, Wales, United Kingdom; Respiratory Innovation Wales, Wales, United Kingdom; London School of Hygiene & Tropical Medicine, London, United Kingdom; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, United Kingdom; Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, U; Usher Institute, University of Edinburgh, Edinburgh, United Kingdom; Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, United Kingdom; Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, United Kingdom; University of Edinburgh, Edinburgh, Scotland, United Kingdom; National Heart and Lung Institute, Imperial College London, London, UK; University of Dundee, Ninewells Hospital and Medical School, Dundee, United Kingdom; MRC Human Immunology Unit, University of Oxford, Oxford, United Kingdom; Division of Infection, Immunity & Respiratory Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom; anchester; Department of Clinical Research, London School of Hygiene & Tropical Medicine Keppel Street, London, United Kingdom; Hospital for Tropical Diseases, University ; Asthma UK and British Lung Foundation, London, United Kingdom; Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom; Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, United Kingdom; Department of Health Sciences, University of Leicester, Leicester, United Kingdom; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, Uni; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; University Hospitals of Leicester,; -","BackgroundThere are currently no effective pharmacological or non-pharmacological interventions for Long-COVID. To identify potential therapeutic targets, we focussed on previously described four recovery clusters five months after hospital discharge, their underlying inflammatory profiles and relationship with clinical outcomes at one year. MethodsPHOSP-COVID is a prospective longitudinal cohort study, recruiting adults hospitalised with COVID-19 across the UK. Recovery was assessed using patient reported outcomes measures (PROMs), physical performance, and organ function at five-months and one-year after hospital discharge. Hierarchical logistic regression modelling was performed for patient-perceived recovery at one-year. Cluster analysis was performed using clustering large applications (CLARA) k-medoids approach using clinical outcomes at five-months. Inflammatory protein profiling from plasma at the five-month visit was performed. @@ -1832,6 +1794,21 @@ MethodsIn this retrospective cohort study, we included all adults ([≥]18 year Results2,311,282 people were included in the study, of whom 164,046 (7.1%) were admitted and 53,156 (2.3%) died within 28 days. There was significant variation in the case hospitalisation and mortality risk over time, peaking in December 2020-February 2021, which remained after adjustment for individual risk factors. Older age groups, males, those resident in more deprived areas, and those with obesity had higher odds of admission and mortality. Of risk factors examined, severe mental illness and learning disability had the highest odds of admission and mortality. ConclusionsIn one of the largest studies of nationally representative Covid-19 risk factors, case hospitalisation and mortality risk varied significantly over time in England during the second pandemic wave, independent of the underlying risk in those infected.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2021.11.29.21266847,2021-11-30,https://medrxiv.org/cgi/content/short/2021.11.29.21266847,Population level impact of a pulse oximetry remote monitoring programme on mortality and healthcare utilisation in the people with covid-19 in England: a national analysis using a stepped wedge design,Thomas Beaney; Jonathan Clarke; Ahmed Alboksmaty; Kelsey Flott; Aidan Fowler; Jonathan R Benger; Paul Aylin; Sarah Elkin; Ana Luisa Neves; Ara Darzi,Imperial College London; Imperial College London; Imperial College London; Imperial College London; NHS England and Improvement; NHS Digital; Imperial College London; Imperial College London; Imperial College London; Imperial College London,"ObjectivesTo identify the population level impact of a national pulse oximetry remote monitoring programme for covid-19 (COVID Oximetry @home; CO@h) in England on mortality and health service use. + +DesignRetrospective cohort study using a stepped wedge pre- and post-implementation design. + +SettingAll Clinical Commissioning Groups (CCGs) in England implementing a local CO@h programme. + +Participants217,650 people with a positive covid-19 polymerase chain reaction test result and symptomatic, from 1st October 2020 to 3rd May 2021, aged [≥]65 years or identified as clinically extremely vulnerable. Care home residents were excluded. + +InterventionsA pre-intervention period before implementation of the CO@h programme in each CCG was compared to a post-intervention period after implementation. + +Main outcome measuresFive outcome measures within 28 days of a positive covid-19 test: i) death from any cause; ii) any A&E attendance; iii) any emergency hospital admission; iv) critical care admission; and v) total length of hospital stay. + +ResultsImplementation of the programme was not associated with mortality or length of hospital stay. Implementation was associated with increased health service utilisation with a 12% increase in the odds of A&E attendance (95% CI: 6%-18%) and emergency hospital admission (95% CI: 5%-20%) and a 24% increase in the odds of critical care admission in those admitted (95% CI: 5%-47%). In a secondary analysis of CO@h sites with at least 10% or 20% of eligible people enrolled, there was no significant association with any outcome measure. However, uptake of the programme was low, with enrolment data received for only 5,527 (2.5%) of the eligible population. + +ConclusionsAt a population level, there was no association with mortality following implementation of the CO@h programme, and small increases in health service utilisation were observed. Low enrolment of eligible people may have diluted the effects of the programme at a population level.",health systems and quality improvement,fuzzy,100,100 medRxiv,10.1101/2021.11.29.21266996,2021-11-29,https://medrxiv.org/cgi/content/short/2021.11.29.21266996,Deficits in planned hospital care for vulnerable adolescents in England during the COVID-19 pandemic: analysis of linked administrative data,Louise Mc Grath-Lone; David Etoori; Ruth Gilbert; Katie Harron; Jenny Woodman; Ruth Blackburn,University College London; University College London; University College London; University College London; University College London; University College London,"Planned hospital care (outpatient attendances and planned hospital admissions) was disrupted during the pandemic, but we lack evidence on which groups of young people were most impacted. We aimed to describe differences in planned care for vulnerable adolescents receiving childrens social care (CSC) services or special educational needs (SEN) support during the pandemic, relative to their peers. Using the ECHILD Database (linked de-identified administrative health, education and social care records for all children in England), we examined changes in planned hospital care from 23 March to 31 December 2020 for secondary school pupils in Years 7 to 11 (N=3,030,235). There were large deficits in planned care for adolescents overall, which disproportionately affected the 21% receiving SEN support or CSC services who bore 25% of the outpatient attendance deficit and 37% of the planned admissions deficit. These findings indicate a need for targeted catch-up funding and resources, particularly for vulnerable groups.",public and global health,fuzzy,100,100 medRxiv,10.1101/2021.11.25.21266848,2021-11-29,https://medrxiv.org/cgi/content/short/2021.11.25.21266848,Evaluating the impact of a pulse oximetry remote monitoring programme on mortality and healthcare utilisation in patients with covid-19 assessed in Accident and Emergency departments in England: a retrospective matched cohort study,Thomas Beaney; Jonathan Clarke; Ahmed Alboksmaty; Kelsey Flott; Aidan Fowler; Jonathan R Benger; Paul Aylin; Sarah Elkin; Ara Darzi; Ana Luisa Neves,Imperial College London; Imperial College London; Imperial College London; Imperial College London; NHS England and Improvement; NHS Digital; Imperial College London; Imperial College London; Imperial College London; Imperial College London,"ObjectivesTo identify the impact of a national pulse oximetry remote monitoring programme for covid-19 (COVID Oximetry @home; CO@h) on health service use and mortality in patients attending Accident and Emergency (A&E) departments. @@ -1848,6 +1825,7 @@ Main outcome measuresFive outcome measures were examined within 28 days of first Results15,621 participants were included in the primary analysis, of whom 639 were enrolled onto CO@h and 14,982 were controls. Odds of death were 52% lower in those enrolled (95% CI: 7%-75% lower) compared to those not enrolled on CO@h. Odds of any A&E attendance or admission were 37% (95% CI: 16-63%) and 59% (95% CI: 16-63%) higher, respectively, in those enrolled. Of those admitted, those enrolled had 53% (95% CI: 7%-76%) lower odds of critical care admission. There was no significant impact on length of stay. ConclusionsThese findings indicate that for patients assessed in A&E, pulse oximetry remote monitoring may be a clinically effective and safe model for early detection of hypoxia and escalation, leading to increased subsequent A&E attendance and admissions, and reduced critical care requirement and mortality.",health systems and quality improvement,fuzzy,100,100 +bioRxiv,10.1101/2021.11.24.469860,2021-11-26,https://biorxiv.org/cgi/content/short/2021.11.24.469860,Nanopore ReCappable Sequencing maps SARS-CoV-2 5' capping sites and provides new insights into the structure of sgRNAs,Camilla Ugolini; Logan Mulroney; Adrien Leger; Matteo Castelli; Elena Criscuolo; Maia Kavanagh Williamson; Andrew D Davidson; Abdulaziz Almuqrin; Roberto Giambruno; Miten Jain; Gianmaria Frigè; Hugh Olsen; George Tzertzinis; Ira Schildkraut; Madalee F Wulf; Ivan R. Corrêa Jr.; Laurence Ettwiller; Nicola Clementi; Massimo Clementi; Nicasio Mancini; Ewan Birney; Mark Akeson; Francesco Nicassio; David A Matthews; Tommaso Leonardi,Italian Institute of Technology; Italian Institute of Technology; Oxford Nanopore Technologies; Vita-Salute San Raffaele University; Vita-Salute San Raffaele University; University of Bristol; University of Bristol; University of Bristol; Istituto Italiano di Tecnologia; University of California Santa Cruz; Istituto Europeo di Oncologia; University of California Santa Cruz; New England Biolabs; New England Biolabs; New England Biolabs; New England Biolabs; New England Biolabs Inc; Vita-Salute San Raffaele University; Vita-Salute San Raffaele University; Università Vita-Salute San Raffaele; European Bioinformatics Institute; University of California Santa Cruz; Istituto Italiano di Tecnologia; University of Bristol; Italian Institute of Technology,"The SARS-CoV-2 virus has a complex transcriptome characterised by multiple, nested sub genomic RNAs used to express structural and accessory proteins. Long-read sequencing technologies such as nanopore direct RNA sequencing can recover full-length transcripts, greatly simplifying the assembly of structurally complex RNAs. However, these techniques do not detect the 5' cap, thus preventing reliable identification and quantification of full-length, coding transcript models. Here we used Nanopore ReCappable Sequencing (NRCeq), a new technique that can identify capped full-length RNAs, to assemble a complete annotation of SARS-CoV-2 sgRNAs and annotate the location of capping sites across the viral genome. We obtained robust estimates of sgRNA expression across cell lines and viral isolates and identified novel canonical and non-canonical sgRNAs, including one that uses a previously un-annotated leader-to-body junction site. The data generated in this work constitute a useful resource for the scientific community and provide important insights into the mechanisms that regulate the transcription of SARS-CoV-2 sgRNAs.",genomics,fuzzy,100,100 medRxiv,10.1101/2021.11.24.21266748,2021-11-26,https://medrxiv.org/cgi/content/short/2021.11.24.21266748,COVID-19 due to the B.1.617.2 (Delta) variant compared to B.1.1.7 (Alpha) variant of SARS-CoV-2: two prospective observational cohort studies,Kerstin Klaser; Erika Molteni; Mark S Graham; Liane S Canas; Marc F Osterdahl; Michela Antonelli; Liyuan Chen; Jie Deng; Benjamin Murray; Eric Kerfoot; Jonathan Wolf; Anna May; Ben Fox; Joan Capdevila Pujol; - The COVID-19 Genomics UK (COG-UK) consortium; Marc Modat; Alexander Hammers; Timothy Spector; Claire Steves; Carole Sudre; Sebastien Ourselin; Emma Duncan,King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; ZOE Limited; ZOE Limited; ZOE Limited; ZOE Limited; ; King's College London; King's College London; King's College London; King's College London; University College London; King's College London; King's College London,"BackgroundThe Delta (B.1.617.2) variant became the predominant UK circulating SARS-CoV-2 strain in May 2021. How Delta infection compares with previous variants is unknown. MethodsThis prospective observational cohort study assessed symptomatic adults participating in the app-based COVID Symptom Study who tested positive for SARS-CoV-2 from May 26 to July 1, 2021 (Delta overwhelmingly predominant circulating UK variant), compared (1:1, age- and sex-matched) with individuals presenting from December 28, 2020 to May 6, 2021 (Alpha (B.1.1.7) predominant variant). We assessed illness (symptoms, duration, presentation to hospital) during Alpha- and Delta-predominant timeframes; and transmission, reinfection, and vaccine effectiveness during the Delta-predominant period. @@ -2144,21 +2122,6 @@ FindingsBased on the training data (London data spanning surges 1 and 2), the fr InterpretationOur results suggest that dynamic patient contact networks can be a robust predictor of respiratory viral infections spreading in hospitals. Their integration in clinical care has the potential to enhance individualised infection prevention and early diagnosis. FundingMedical Research Foundation, World Health Organisation, Engineering and Physical Sciences Research Council, National Institute for Health Research, Swiss National Science Foundation, German Research Foundation.",health informatics,fuzzy,100,100 -medRxiv,10.1101/2021.09.27.21264166,2021-09-29,https://medrxiv.org/cgi/content/short/2021.09.27.21264166,Prevalence and duration of detectable SARS-CoV-2 nucleocapsid antibody in staff and residents of long-term care facilities over the first year of the pandemic (VIVALDI study): prospective cohort study,Maria Krutikov; Tom Palmer; Gokhan Tut; Christopher Fuller; Borscha Azmi; Rebecca Giddings; Madhumita Shrotri; Nayandeep Kaur; Panagiota Sylla; Tara Lancaster; Aidan Irwin-Singer; Andrew Hayward; Paul Moss; Andrew Copas; Laura Shallcross,"University College London; University College London; University of Birmingham, Medical School; University College London; University College London; University College London; University College London; University of Birmingham; University of Birmingham; University of Birmingham; Department of Health & Social Care; UCL; University of Birmingham; University College London; UCL","BackgroundLong Term Care Facilities (LTCF) have reported high SARS-CoV-2 infection rates and related mortality, but the proportion infected amongst survivors and duration of the antibody response to natural infection is unknown. We determined the prevalence and stability of nucleocapsid antibodies - the standard assay for detection of prior infection - in staff and residents from 201 LTCFs. - -MethodsProspective cohort study of residents aged >65 years and staff of LTCFs in England (11 June 2020-7 May 2021). Serial blood samples were tested for IgG antibodies against SARS-CoV-2 nucleocapsid protein. Prevalence and cumulative incidence of antibody-positivity were weighted to the LTCF population. Cumulative incidence of sero-reversion was estimated from Kaplan-Meier curves. - -Results9488 samples were included, 8636 (91%) of which could be individually-linked to 1434 residents or 3288 staff members. The cumulative incidence of nucleocapsid seropositivity was 35% (95% CI: 30-40%) in residents and 26% (95% CI: 23-30%) in staff over 11 months. The incidence rate of loss of antibodies (sero-reversion) was 2{middle dot}1 per 1000 person-days at risk, and median time to reversion was around 8 months. - -InterpretationAt least one-quarter of staff and one-third of surviving residents were infected during the first two pandemic waves. Nucleocapsid-specific antibodies often become undetectable within the first year following infection which is likely to lead to marked underestimation of the true proportion of those with prior infection. Since natural infection may act to boost vaccine responses, better assays to identify natural infection should be developed. - -FundingUK Government Department of Health and Social Care. - -Research in contextO_ST_ABSEvidence before this studyC_ST_ABSA search was conducted of Ovid MEDLINE and MedRxiv on 21 July 2021 to identify studies conducted in long term care facilities (LTCF) that described seroprevalence using the terms ""COVID-19"" or ""SARS-CoV-2"" and ""nursing home"" or ""care home"" or ""residential"" or ""long term care facility"" and ""antibody"" or ""serology"" without date or language restrictions. One meta-analysis was identified, published before the introduction of vaccination, that included 2 studies with a sample size of 291 which estimated seroprevalence as 59% in LTCF residents. There were 28 seroprevalence surveys of naturally-acquired SARS-CoV-2 antibodies in LTCFs; 16 were conducted in response to outbreaks and 12 conducted in care homes without known outbreaks. 16 studies included more than 1 LTCF and all were conducted in Autumn 2020 after the first wave of infection but prior to subsequent peaks. Seroprevalence studies conducted following a LTCF outbreak were biased towards positivity as the included population was known to have been previously infected. In the 12 studies that were conducted outside of known outbreaks, seroprevalence varied significantly according to local prevalence of infection. The largest of these was a cross-sectional study conducted in 9,000 residents and 10,000 staff from 362 LTCFs in Madrid, which estimated seroprevalence in staff as 31{middle dot}5% and 55{middle dot}4% in residents. However, as this study was performed in one city, it may not be generalisable to the whole of Spain and sequential sampling was not performed. Of the 28 studies, 9 undertook longitudinal sampling for a maximum of four months although three of these reported from the same cohort of LTCFs in London. None of the studies reported on antibody waning amongst the whole resident population. - -Added value of this studyWe estimated the proportion of care home staff and residents with evidence of SARS-CoV-2 natural infection using data from over 3,000 staff and 1,500 residents in 201 geographically dispersed LTCFs in England. Population selection was independent of outbreak history and the sample is therefore more reflective of the population who reside and work in LTCFs. Our estimates of the proportion of residents with prior natural infection are substantially higher than estimates based on population-wide PCR testing, due to limited testing coverage at the start of the pandemic. 1361 individuals had at least one positive antibody test and participants were followed for up to 11 months, which allowed modelling of the time to loss of antibody in over 600 individuals in whom the date of primary infection could be reliably estimated. This is the longest reported serological follow up in a population of LTCF residents, a group who are known to be most at risk of severe outcomes following infection with SARS-CoV-2 and provides important evidence on the duration that nucleocapsid antibodies remained detectable over the first and second waves of the pandemic. - -Implications of all available researchA substantial proportion of the LTCF population will have some level of natural immunity to infection as a result of past infection. Immunological studies have highlighted greater antibody responses to vaccination in seropositive individuals, so vaccine efficacy in this population may be affected by this large pool of individuals who have survived past infection. In addition, although the presence of nucleocapsid-specific antibodies is generally considered as the standard marker for prior infection, we find that antibody waning is such that up to 50% of people will lose detectable antibody responses within eight months. Individual prior natural infection history is critical to assess the impact of factors such as vaccine response or protection against re-infection. These findings may have implications for duration of immunity following natural infection and indicate that alternative assays for prior infection should be developed.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.09.20.21263828,2021-09-23,https://medrxiv.org/cgi/content/short/2021.09.20.21263828,"Colchicine for COVID-19 in adults in the community (PRINCIPLE): a randomised, controlled, adaptive platform trial",- The PRINCIPLE Trial Collaborative Group; Jienchi Dorward; Ly-Mee Yu; Gail Hayward; Benjamin R Saville; Oghenekome Gbinigie; Oliver van Hecke; Emma Ogburn; Philip H Evans; Nicholas PB Thomas; Mahendra G Patel; Duncan Richards; Nicholas Berry; Michelle A Detry; Christina Saunders; Mark Fitzgerald; Victoria Harris; Milensu Shanyinde; Simon de Lusignan; Monique I Andersson; Christopher C Butler; FD Richard Hobbs,"; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom and Centre for the AIDS Programme of Research in South Africa ; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; Berry Consultants, Texas, USA and Department of Biostatistics, Vanderbilt University School of Medicine, Tennessee, USA; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; College of Medicine and Health, University of Exeter and National Institute for Health Research, Clinical Research Network; Royal College of General Practitioners, London, UK, and National Institute for Health Research, Clinical Research Network; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom and School of Pharmacy and Medical Sciences, University of Bra; Oxford Clinical Trials Research Unit, Botnar Research Centre, University of Oxford, Oxford, UK; Berry Consultants, Texas, USA; Berry Consultants, Texas, USA; Berry Consultants, Texas, USA; Berry Consultants, Texas, USA; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; Nuffield Department of Clinical Medicine, University of Oxford, United Kingdom,; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom","ObjectivesColchicine has been proposed as a COVID-19 treatment, but its effect on time to recovery is unknown. We aimed to determine whether colchicine is effective at reducing time to recovery and COVID-19 related hospitalisations/deaths among people in the community. DesignProspective, multicentre, open-label, multi-arm, adaptive Platform Randomised Trial of Treatments in the Community for Epidemic and Pandemic Illnesses (PRINCIPLE). @@ -2176,15 +2139,6 @@ ResultsThe trial opened on April 2, 2020, with randomisation to colchicine start ConclusionsColchicine did not improve time to recovery in people at higher risk of complications with COVID-19 in the community. Trial registrationISRCTN86534580.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2021.09.16.21263684,2021-09-22,https://medrxiv.org/cgi/content/short/2021.09.16.21263684,The removal of airborne SARS-CoV-2 and other microbial bioaerosols by air filtration on COVID-19 surge units,Andrew Conway Morris; Katherine Sharrocks; Rachel Bousfield; Leanne Kermack; Mailis Maes; Ellen Higginson; Sally Forrest; Joannna Pereira-Dias; Claire Cormie; Timothy Old; Sophie Brooks; Islam Hamed; Alicia Koenig; Andrew Turner; Paul White; R. Andres Floto; Gordon Dougan; Effrossyni Gkrania-Klotsas; Theodore Gouliouris; Stephen Baker; Vilas Navapurkar,University of Cambridge; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; University of Cambridge; University of Cambridge; Cambridge University Hospitals NHS Foundation trust; Cambridge University Hospitals NHS Foundation Trust; University of Cambridge; Cambridge University Hospitals,"BackgroundThe COVID-19 pandemic has overwhelmed the respiratory isolation capacity in hospitals; many wards lacking high-frequency air changes have been repurposed for managing patients infected with SARS-CoV-2 requiring either standard or intensive care. Hospital-acquired COVID-19 is a recognised problem amongst both patients and staff, with growing evidence for the relevance of airborne transmission. This study examined the effect of air filtration and ultra-violet (UV) light sterilisation on detectable airborne SARS-CoV-2 and other microbial bioaerosols. - -MethodsWe conducted a crossover study of portable air filtration and sterilisation devices in a repurposed surge COVID ward and surge ICU. National Institute for Occupational Safety and Health (NIOSH) cyclonic aerosol samplers and PCR assays were used to detect the presence of airborne SARS-CoV-2 and other microbial bioaerosol with and without air/UV filtration. - -ResultsAirborne SARS-CoV-2 was detected in the ward on all five days before activation of air/UV filtration, but on none of the five days when the air/UV filter was operational; SARS-CoV-2 was again detected on four out of five days when the filter was off. Airborne SARS-CoV-2 was infrequently detected in the ICU. Filtration significantly reduced the burden of other microbial bioaerosols in both the ward (48 pathogens detected before filtration, two after, p=0.05) and the ICU (45 pathogens detected before filtration, five after p=0.05). - -ConclusionsThese data demonstrate the feasibility of removing SARS-CoV-2 from the air of repurposed surge wards and suggest that air filtration devices may help reduce the risk of hospital-acquired SARS-CoV-2. - -FundingWellcome Trust, MRC, NIHR",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.09.17.21262724,2021-09-21,https://medrxiv.org/cgi/content/short/2021.09.17.21262724,Deleterious drugs in COVID-19: a rapid systematic review and meta-analysis,Michael W Holder; Catherine Heeney; Stephen Malden; Uditha Perera; Aziz Sheikh,"The Usher Institute, University of Edinburgh; The Usher Institute, University of Edinburgh; The Usher Institute, University of Edinburgh; The Usher Institute, University of Edinburgh; The Usher Institute, University of Edinburgh","BackgroundConcerns have been expressed about a number of drugs that potentially worsen outcomes in patients with COVID-19. We sought to identify all potentially deleterious drug groups in COVID-19 and critically assess the underpinning strength of evidence pertaining to the harmful effects of these drugs. Methods and findingsWe performed a rapid systematic review, searching Medline, Embase and two COVID-19 portfolios (WHO COVID-19 database and NIH iSearch COVID-19 portfolio) for papers and preprints related to primary studies investigating drugs identified as potentially deleterious. Primary outcomes were direct measures of susceptibility to infection, disease severity and mortality. Study quality was assessed using the National Heart, Lung, and Blood Institute quality assessment tools. Random-effects meta-analyses were used for data synthesis with further subgroup analyses where possible for specific outcome, study design, statistical adjustment and drug groups when two were combined. Sensitivity analyses were performed by removing any studies at high risk of bias and by publication status. @@ -2224,6 +2178,15 @@ Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSeveral reports hav Added value of this studyThis study shows that efficacy of both AstraZeneca and mRNA vaccines against severe COVID-19 (fatal or requiring critical care) remains high (around 90%) in the most recent time window, but that efficacy of the AstraZeneca vaccine wanes to about 70% by 20 weeks from second dose. In contrast efficacy of the mRNA vaccines wanes rapidly at first but stabilises at about 90% by 20 weeks from second dose. Implications of all the available evidenceThese results suggest that booster doses of vaccine are not needed for those who have received two doses of mRNA vaccine, except for vulnerable individuals who may require a third primary dose.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2021.09.09.21263026,2021-09-13,https://medrxiv.org/cgi/content/short/2021.09.09.21263026,The clinically extremely vulnerable to COVID: Identification and changes in health care while self-isolating (shielding) during the coronavirus pandemic,Jessica Erin Butler; Mintu Nath; Dimitra Blana; William P Ball; Nicola Beech; Corri Black; Graham Osler; Sebastien Peytrignet; Katie Wilde; Artur Wozniak; Simon Sawhney,University of Aberdeen; University of Aberdeen; University of Aberdeen; University of Aberdeen; NHS Grampian; NHS Grampian and University of Aberdeen; NHS Grampian; Health Foundation; University of Aberdeen; University of Aberdeen; NHS Grampian and University of Aberdeen,"BackgroundIn March 2020, the government of Scotland identified people deemed clinically extremely vulnerable to COVID due to their pre-existing health conditions. These people were advised to strictly self-isolate (shield) at the start of the pandemic, except for necessary healthcare. We examined who was identified as clinically extremely vulnerable, how their healthcare changed during isolation, and whether this process exacerbated healthcare inequalities. + +MethodsWe linked those on the shielding register in NHS Grampian, a health authority in Scotland, to healthcare records from 2015-2020. We described the source of identification, demographics, and clinical history of the cohort. We measured changes in out-patient, in-patient, and emergency healthcare during isolation in the shielding population and compared to the general non-shielding population. + +ResultsThe register included 16,092 people (3% of the population), clinically vulnerable primarily due to a respiratory disease, immunosuppression, or cancer. Among them, 42% were not identified by national healthcare record screening but added ad hoc, with these additions including more children and fewer economically-deprived. + +During isolation, all forms of healthcare use decreased (25%-46%), with larger decreases in scheduled care than in emergency care. However, people shielding had better maintained scheduled care compared to the non-shielding general population: out-patient visits decreased 35% vs 49%; in-patient visits decreased 46% vs 81%. Notably, there was substantial variation in whose scheduled care was maintained during isolation: younger people and those with cancer had significantly higher visit rates, but there was no difference between sexes or socioeconomic levels. + +ConclusionsHealthcare changed dramatically for the clinically extremely vulnerable population during the pandemic. The increased reliance on emergency care while isolating indicates that continuity of care for existing conditions was not optimal. However, compared to the general population, there was success in maintaining scheduled care, particularly in young people and those with cancer. We suggest that integrating demographic and primary care data would improve identification of the clinically vulnerable and could aid prioritising their care.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.09.03.21262888,2021-09-10,https://medrxiv.org/cgi/content/short/2021.09.03.21262888,Risk of severe COVID-19 outcomes associated with immune-mediated inflammatory diseases and immune modifying therapies: a nationwide cohort study in the OpenSAFELY platform,Brian MacKenna; Nicholas A. Kennedy; Amir Mehkar; Anna Rowan; James Galloway; Kathryn E Mansfield; Katie Bechman; Julian Matthewman; Mark Yates; Jeremy Brown; Anna Schultze; Sam Norton; Alex J Walker; Caroline E Morton; David Harrison; Krishnan Bhaskaran; Christopher T Rentsch; Elizabeth Williamson; Richard Croker; Seb Bacon; George Hickman; Tom Ward; Simon Davy; Amelia Green; Louis Fisher; William Hulme; Chris Bates; Helen J Curtis; John Tazare; Rosalind M Eggo; David Evans; Peter Inglesby; Jonathan Cockburn; Helen I McDonald; Laurie A Tomlinson; Rohini Mathur; Angel YS Wong; Harriet Forbes; John Parry; Frank Hester; Sam Harper; Ian J Douglas; Liam Smeeth; Charlie W Lees; Stephen JW Evans; Ben Goldacre; Catherine Smith; Sinead M Langan,"The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Department of Gastroenterology, Royal Devon & Exeter NHS Foundation Trust, Exeter, UK. IBD Research Group, University of Exeter, Exeter, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Centre of Rheumatic Diseases, Kings College London, Denmark Hill, London, SE5 9RS; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; Centre of Rheumatic Diseases, Kings College London, Denmark Hill, London SE5 9RS; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; Centre of Rheumatic Diseases, Kings College London, Denmark Hill, London SE5 9RS; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; Centre of Rheumatic Diseases, Kings College London, Denmark Hill, London SE5 9RS; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Intensive Care National Audit & Research Centre (ICNARC), High Holborn, London WC1V 6AZ; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; he DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; Centre for Genomics and Experimental Medicine, University of Edinburgh Western General Hospital, Edinburgh, UK; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; St John's Institute of Dermatology, Guys and St Thomas' NHS Foundation Trust and Kings College London SE1 9RT; London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT. St John's Institute of Dermatology, Guys and St Thomas NHS Foundation Trust and Ki","BackgroundIt is unclear if people with immune-mediated inflammatory diseases (IMIDs) (joint, bowel and skin) and on immune modifying therapy have increased risk of serious COVID-19 outcomes. MethodsWith the approval of NHS England we conducted a cohort study, using OpenSAFELY, analysingroutinely-collected primary care data linked to hospital admission, death and previously unavailable hospital prescription data. We used Cox regression (adjusting for confounders) to estimate hazard ratios (HR) comparing risk of COVID-19-death, death/critical care admission, and hospitalisation (March to September 2020) in: 1) people with IMIDs compared to the general population; and 2) people with IMIDs on targeted immune modifying drugs (e.g., biologics) compared to standard systemic treatment (e.g., methotrexate). @@ -2259,6 +2222,13 @@ C_LI How might this impact on clinical practice?O_LIThese findings can help shape global AT medication policy and provide population-scale, observational analysis results alongside gold-standard randomised control trials to help assess whether a potential beneficial effect of pre-existing AT use on COVID-19 death alters risk to benefit assessments in AT prescribing decisions. C_LI",cardiovascular medicine,fuzzy,100,100 +medRxiv,10.1101/2021.09.02.21262979,2021-09-10,https://medrxiv.org/cgi/content/short/2021.09.02.21262979,"Exponential growth, high prevalence of SARS-CoV-2 and vaccine effectiveness associated with Delta variant in England during May to July 2021",Paul Elliott; David J Haw; Haowei Wang; Oliver Eales; Caroline E Walters; Kylie E. C. Ainslie; Christina J Atchison; Claudio Fronterre; Peter Diggle; Andrew J Page; Alex Trotter; Sophie J Prosolek; - The COVID-19 Genomics UK (COG-UK) consortium; Deborah Ashby; Christl Donnelly; Wendy Barclay; Graham P Taylor; Graham Cooke; Helen Ward; Ara Darzi; Steven Riley,"Imperial College London School of Public Health; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Lancaster University; Lancaster University; Quadram Institute; Quadram Institute Bioscience; Quadram Institute; The COVID-19 Genomics UK (COG-UK) consortium; Imperial College London; University of Oxford; Imperial College London; Imperial College London; Imperial College; Imperial College London; Imperial College London; Dept Inf Dis Epi, Imperial College","BackgroundThe prevalence of SARS-CoV-2 infection continues to drive rates of illness and hospitalisations despite high levels of vaccination, with the proportion of cases caused by the Delta lineage increasing in many populations. As vaccination programs roll out globally and social distancing is relaxed, future SARS-CoV-2 trends are uncertain. + +MethodsWe analysed prevalence trends and their drivers using reverse transcription-polymerase chain reaction (RT-PCR) swab-positivity data from round 12 (between 20 May and 7 June 2021) and round 13 (between 24 June and 12 July 2021) of the REal-time Assessment of Community Transmission-1 (REACT-1) study, with swabs sent to non-overlapping random samples of the population ages 5 years and over in England. + +ResultsWe observed sustained exponential growth with an average doubling time in round 13 of 25 days (lower Credible Interval of 15 days) and an increase in average prevalence from 0.15% (0.12%, 0.18%) in round 12 to 0.63% (0.57%, 0.18%) in round 13. The rapid growth across and within rounds appears to have been driven by complete replacement of Alpha variant by Delta, and by the high prevalence in younger less-vaccinated age groups, with a nine-fold increase between rounds 12 and 13 among those aged 13 to 17 years. Prevalence among those who reported being unvaccinated was three-fold higher than those who reported being fully vaccinated. However, in round 13, 44% of infections occurred in fully vaccinated individuals, reflecting imperfect vaccine effectiveness against infection despite high overall levels of vaccination. Using self-reported vaccination status, we estimated adjusted vaccine effectiveness against infection in round 13 of 49% (22%, 67%) among participants aged 18 to 64 years, which rose to 58% (33%, 73%) when considering only strong positives (Cycle threshold [Ct] values < 27); also, we estimated adjusted vaccine effectiveness against symptomatic infection of 59% (23%, 78%), with any one of three common COVID-19 symptoms reported in the month prior to swabbing. Sex (round 13 only), ethnicity, household size and local levels of deprivation jointly contributed to the risk of higher prevalence of swab-positivity. + +DiscussionFrom end May to beginning July 2021 in England, where there has been a highly successful vaccination campaign with high vaccine uptake, infections were increasing exponentially driven by the Delta variant and high infection prevalence among younger, unvaccinated individuals despite double vaccination continuing to effectively reduce transmission. Although slower growth or declining prevalence may be observed during the summer in the northern hemisphere, increased mixing during the autumn in the presence of the Delta variant may lead to renewed growth, even at high levels of vaccination.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.09.03.21263083,2021-09-07,https://medrxiv.org/cgi/content/short/2021.09.03.21263083,Suicide and self-harm in low- and middle- income countries during the COVID-19 pandemic: A systematic review,Duleeka Kniipe; Ann John; Prianka Padmanathan; Emily Eyles; Dana Dekel; Julian Higgins; Jason Bantjes; Rakhi Dandona; Catherine Macleod-Hall; Luke A McGuinness; Lena Schmidt; Roger Webb; David Gunnell,"Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; South Asian Clinical Toxicology Research Collaboration, Faculty of Medic; Population Data Science, Swansea University Medical School, Swansea, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.; Population Data Science, Swansea University Medical School, Swansea, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.; National Institute of Health Research Biomedical Research Centre, Unive; Institute for Life Course Health Research, Department of Global Health, Faculty of medicine and Health Sciences, Stellenbosch University, South Africa.; Public Health Foundation of India, Gurugram, India; Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.; Sciome LLC, Research Triangle Park, NC, United States.; Division of Psychology & Mental Health, University of Manchester, Manchester, UK; National Institute of Health Research Greater Manchester Patient Safety Transl; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.; National Institute of Health Research Biomedical Research Centre, Unive","There is widespread concern over the potential impact of the COVID-19 pandemic on suicide and self-harm globally, particularly in low- and middle-income countries (LMIC) where the burden of these behaviours is greatest. We synthesised the evidence from the published literature on the impact of the pandemic on suicide and self-harm in LMIC. This review is nested within a living systematic review that continuously identifies published evidence (all languages) through a comprehensive automated search of multiple databases (PubMed; Scopus; medRxiv, PsyArXiv; SocArXiv; bioRxiv; the WHO COVID-19 database; and the COVID-19 Open Research Dataset by Semantic Scholar (up to 11/2020), including data from Microsoft Academic, Elsevier, arXiv and PubMed Central.) All articles identified by the 4th August 2021 were screened. Papers reporting on data from a LMIC and presenting evidence on the impact of the pandemic on suicide or self-harm were included. @@ -2312,15 +2282,6 @@ ConclusionsThese findings support a causal association between CVT and the Astra What is already known on this topicThe risk of cerebral venous thrombosis (CVT) within 28 days of receiving the AstraZeneca ChAdOx1 vaccine has been estimated as 18 to 25 per million doses in Germany and Scandinavia, but only 5 per million doses in the UK based on the Yellow Card reporting scheme. Risk estimates based on adverse event reporting systems are subject to under-ascertainment and other biases. What this study addsAll diagnosed cases of CVT in Scotland were ascertained by searching neuroimaging studies from December 2020 to May 2021 and linked to national vaccination records. The risk of CVT within 28 days of vaccination with ChAdOx1 was estimated as 3.5 per million doses with an upper bound of 6 per million doses, against a background incidence of about 12 per million adults per year. This indicates that the Yellow Card system has not seriously underestimated the risk in the UK; the explanation for higher risk in other European countries is not clear.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2021.08.19.21262231,2021-08-24,https://medrxiv.org/cgi/content/short/2021.08.19.21262231,Symptoms and SARS-CoV-2 positivity in the general population in the UK,Karina-Doris Vihta; Koen B. Pouwels; Tim Peto; Emma Pritchard; David W. Eyre; Thomas House; Owen Gethings; Ruth Studley; Emma Rourke; Duncan Cook; Ian Diamond; Derrick Crook; Philippa C. Matthews; Nicole Stoesser; Ann Sarah Walker; - COVID-19 Infection Survey team,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Manchester; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; University of Oxford; University of Oxford; University of Oxford; ,"BackgroundSeveral community-based studies have assessed the ability of different symptoms to identify COVID-19 infections, but few have compared symptoms over time (reflecting SARS-CoV-2 variants) and by vaccination status. - -MethodsUsing data and samples collected by the COVID-19 Infection Survey at regular visits to representative households across the UK, we compared symptoms in new PCR-positives and comparator test-negative controls. - -ResultsFrom 26/4/2020-7/8/2021, 27,869 SARS-CoV-2 PCR-positive episodes occurred in 27,692 participants (median 42 years (IQR 22-58)); 13,427 (48%) self-reported symptoms (""symptomatic positive episodes""). The comparator group comprised 3,806,692 test-negative visits (457,215 participants); 130,612 (3%) self-reported symptoms (""symptomatic negative visit""). Reporting of any symptoms in positive episodes varied over calendar time, reflecting changes in prevalence of variants, incidental changes (e.g. seasonal pathogens, schools re-opening) and vaccination roll-out. There was a small increase in sore throat reporting in symptomatic positive episodes and negative visits from April-2021. After May-2021 when Delta emerged there were substantial increases in headache and fever in positives, but not in negatives. Although specific symptom reporting in symptomatic positive episodes vs. negative visits varied by age, sex, and ethnicity, only small improvements in symptom-based infection detection were obtained; e.g. adding fatigue/weakness or all eight symptoms to the classic four symptoms (cough, fever, loss of taste/smell) increased sensitivity from 74% to 81% to 90% but tests per positive from 4.6 to 5.3 to 8.7. - -ConclusionsWhilst SARS-CoV-2-associated symptoms vary by variant, vaccination status and demographics, differences are modest and do not warrant large-scale changes to targeted testing approaches given resource implications. - -SummaryWithin the COVID-19 Infection Survey, recruiting representative households across the UK general population, SARS-CoV-2-associated symptoms varied by viral variant, vaccination status and demographics. However, differences are modest and do not currently warrant large-scale changes to targeted testing approaches.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.08.18.21262222,2021-08-23,https://medrxiv.org/cgi/content/short/2021.08.18.21262222,"Association of COVID-19 vaccines ChAdOx1 and BNT162b2 with major venous, arterial, and thrombocytopenic events: whole population cohort study in 46 million adults in England",William Whiteley; Samantha Ip; Jennifer Anne Cooper; Thomas Bolton; Spencer Keene; Venexia Walker; Rachel Denholm; Ashley Akbari; Efosa Omigie; Sam Hollings; Emanuele Di Angelantonio; Spiros Denaxas; Angela Wood; Jonathan Sterne; Cathie Sudlow; - CVD-COVID-UK consortium,University of Edinburgh; University of Cambridge; University of Bristol; University of Cambridge; University of Cambridge; University of Bristol; University of Bristol; University of Swansea; NHS Digital; NHS Digital; University of Cambridge; University College London; University of Cambridge; University of Bristol; Health Data Research UK; ,"BackgroundThromboses in unusual locations after the COVID-19 vaccine ChAdOx1-S have been reported. Better understanding of population-level thrombotic risks after COVID-19 vaccination is needed. MethodsWe analysed linked electronic health records from adults living in England, from 8th December 2020 to 18th March 2021. We estimated incidence rates and hazard ratios (HRs) for major arterial, venous and thrombocytopenic outcomes 1-28 and >28 days after first vaccination dose for ChAdOx1-S and BNT162b2 vaccines. Analyses were performed separately for ages <70 and [≥]70 years, and adjusted for age, sex, comorbidities, and social and demographic factors. @@ -2346,9 +2307,6 @@ https://clinicaltrials.gov/ct2/show/NCT04394117 Clinical Trial Registry of India: CTRI/2020/07/026831 Version and revisionsVersion 1.0. No revisions.",respiratory medicine,fuzzy,100,100 -medRxiv,10.1101/2021.08.13.21261889,2021-08-18,https://medrxiv.org/cgi/content/short/2021.08.13.21261889,Robust SARS-CoV-2-specific and heterologous immune responses after natural infection in elderly residents of Long-Term Care Facilities,Gokhan Tut; Tara Lancaster; Megan S Butler; Panagiota Sylla; Eliska Spalkova; David Bone; Nayandeep Kaur; Christopher Bentley; Umayr Amin; Azar T Jadir; Samuel Hulme; Morenike Ayodele; Alexander C Dowell; Hayden Pearce; Sandra Margielewska-Davies; Kriti Verma; Samantha Nicol; Jusnara Begum; Elizabeth Jinks; Elif Tut; Rachel Bruton; Maria Krutikov; Madhumita Shrotri; Rebecca Giddings; Borscha Azmi; Chris Fuller; Aidan Irwin-Singer; Andrew Hayward; Andrew Copas; Laura Shallcross; Paul Moss,"Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; Department of Health and Social Care, London, UK; Health Data Research UK; UCL Institute for Global Health, London, UK; UCL Institute of Health Informatics, London, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK","Long term care facilities (LTCF) provide residential and/or nursing care support for frail and elderly people and many have suffered from a high prevalence of SARS-CoV-2 infection. Although mortality rates have been high in LTCF residents there is little information regarding the features of SARS-CoV-2-specific immunity after infection in this setting or how this may influence immunity to other infections. We studied humoral and cellular immunity against SARS-CoV-2 in 152 LTCF staff and 124 residents over a prospective 4-month period shortly after the first wave of infection and related viral serostatus to heterologous immunity to other respiratory viruses and systemic inflammatory markers. LTCF residents developed high levels of antibodies against spike protein and RBD domain which were stable over 4 months of follow up. Nucleocapsid-specific responses were also elevated in elderly donors but showed waning across all populations. Antibodies showed stable and equivalent levels of functional inhibition against spike-ACE2 binding in all age groups with comparable activity against viral variants of concern. SARS-CoV-2 seropositive donors showed high levels of antibodies to other beta-coronaviruses but serostatus did not impact humoral immunity to influenza or RSV. SARS-CoV-2-specific cellular responses were equivalent across the life course but virus-specific populations showed elevated levels of activation in older donors. LTCF residents who are survivors of SARS-CoV-2 infection thus show robust and stable immunity which does not impact responses to other seasonal viruses. These findings augur well for relative protection of LTCF residents to re-infection. Furthermore, they underlie the potent influence of previous infection on the immune response to Covid-19 vaccine which may prove to be an important determinant of future vaccine strategy. - -One sentence summeryCare home residents show waning of nucleocapsid specific antibodies and enhanced expression of activation markers on SARS-CoV-2 specific cells",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.08.13.21261959,2021-08-13,https://medrxiv.org/cgi/content/short/2021.08.13.21261959,Factors influencing wellbeing in young people during COVID-19.,Michaela James; Hope Jones; Amana Baig; Emily Marchant; Tegan Waites; Charlotte Todd; Karen Hughes; Sinead Brophy,Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Public Health Wales; Bangor University; Swansea University,"COVID-19 infection and the resultant restrictions has impacted all aspects of life across the world. This study explores factors that promote or support wellbeing for young people during the pandemic, how they differ by age, using a self-reported online survey with those aged 8 - 25 in Wales between September 2020 and February 2021. Open-ended responses were analysed via thematic analysis to provide further context. A total of 6,291 responses were obtained from 81 education settings across Wales (including primary and secondary schools as well as sixth form, colleges and universities). Wellbeing was highest in primary school children and boys and lowest in those who were at secondary school children, who were girls and, those who preferred not to give a gender. Among primary school children, higher wellbeing was seen for those who played with others (rather than alone), were of Asian ethnicity (OR 2.3, 95% CI: 1.26 to 4.3), lived in a safe area (OR: 2.0, 95% CI: 1.67 to 2.5) and had more sleep. To support their wellbeing young people reported they would like to be able to play with their friends more. Among secondary school children those who were of mixed ethnicity reported lower wellbeing (OR: 5.10, 95% CI: 1.70 to 15.80). To support their wellbeing they reported they would like more support with mental health (due to anxiety and pressure to achieve when learning online). This study found self-reported wellbeing differed by gender, ethnicity and deprivation and found younger children report the need for play and to see friends to support wellbeing but older children/young people wanted more support with anxiety and educational pressures.",public and global health,fuzzy,100,100 medRxiv,10.1101/2021.08.12.21261987,2021-08-13,https://medrxiv.org/cgi/content/short/2021.08.12.21261987,Characterising the persistence of RT-PCR positivity and incidence in a community survey of SARS-CoV-2,Oliver Eales; Caroline E. Walters; Haowei Wang; David Haw; Kylie E. C. Ainslie; Christina Atchinson; Andrew Page; Sophie Prosolek; Alexander J. Trotter; Thanh Le Viet; Nabil-Fareed Alikhan; Leigh M Jackson; Catherine Ludden; - The COVID-19 Genomics UK (COG-UK) Consortium; Deborah Ashby; Christl A Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott; Steven Riley,"School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Medical School, University of Exeter, UK; Department of Medicine, University of Cambridge, UK; ; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc","BackgroundCommunity surveys of SARS-CoV-2 RT-PCR swab-positivity provide prevalence estimates largely unaffected by biases from who presents for routine case testing. The REal-time Assessment of Community Transmission-1 (REACT-1) has estimated swab-positivity approximately monthly since May 2020 in England from RT-PCR testing of self-administered throat and nose swabs in random non-overlapping cross-sectional community samples. Estimating infection incidence from swab-positivity requires an understanding of the persistence of RT-PCR swab positivity in the community. @@ -2593,6 +2551,7 @@ MethodsWe report interim results from round 13 of the REal-time Assessment of Co ResultsIn round 13 interim, we found 237 positives from 47,729 swabs giving a weighted prevalence of 0.59% (0.51%, 0.68%) which was approximately four-fold higher compared with round 12 at 0.15% (0.12%, 0.18%). This resulted from continued exponential growth in prevalence with an average doubling time of 15 (13, 17) days between round 12 and round 13. However, during the recent period of round 13 interim only, we observed a shorter doubling time of 6.1 (4.0, 12) days with a corresponding R number of 1.87 (1.40, 2.45). There were substantial increases in all age groups under the age of 75 years, and especially at younger ages, with the highest prevalence in 13 to 17 year olds at 1.33% (0.97%, 1.82%) and in 18 to 24 years olds at 1.40% (0.89%, 2.18%). Infections have increased in all regions with the largest increase in London where prevalence increased more than eight-fold from 0.13% (0.08%, 0.20%) in round 12 to 1.08% (0.79%, 1.47%) in round 13 interim. Overall, prevalence was over 3 times higher in the unvaccinated compared with those reporting two doses of vaccine in both round 12 and round 13 interim, although there was a similar proportional increase in prevalence in vaccinated and unvaccinated individuals between the two rounds. DiscussionWe are entering a critical period with a number of important competing processes: continued vaccination rollout to the whole adult population in England, increased natural immunity through infection, reduced social mixing of children during school holidays, increased proportion of mixing occurring outdoors during summer, the intended full opening of hospitality and entertainment and cessation of mandated social distancing and mask wearing. Surveillance programmes are essential during this next phase of the epidemic to provide clear evidence to the government and the public on the levels and trends in prevalence of infections and their relationship to vaccine coverage, hospitalisations, deaths and Long COVID.",infectious diseases,fuzzy,100,100 +medRxiv,10.1101/2021.07.02.21259897,2021-07-05,https://medrxiv.org/cgi/content/short/2021.07.02.21259897,Anti-spike antibody response to natural SARS-CoV-2 infection in the general population,Jia Wei; Philippa C Matthews; Nicole Stoesser; Thomas Maddox; Luke Lorenzi; Ruth Studley; John I Bell; John N Newton; Jeremy Farrar; Ian Diamond; Emma Rourke; Alison Howarth; Brian D Marsden; Sarah Hoosdally; E Yvonne Jones; David I Stuart; Derrick W Crook; Tim E.A. Peto; Koen B. Pouwels; A. Sarah Walker; David W Eyre,University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; Office for National Statistics; Office for National Statistics; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; NIHR Oxford Biomedical Research Centre; University of Oxford; University of Oxford; University of Oxford; University of Oxford,"We estimated the duration and determinants of antibody response after SARS-CoV-2 infection in the general population using representative data from 7,256 United Kingdom COVID-19 infection survey participants who had positive swab SARS-CoV-2 PCR tests from 26-April-2020 to 14-June-2021. A latent class model classified 24% of participants as non-responders not developing anti-spike antibodies. These seronegative non-responders were older, had higher SARS-CoV-2 cycle threshold values during infection (i.e. lower viral burden), and less frequently reported any symptoms. Among those who seroconverted, using Bayesian linear mixed models, the estimated anti-spike IgG peak level was 7.3-fold higher than the level previously associated with 50% protection against reinfection, with higher peak levels in older participants and those of non-white ethnicity. The estimated anti-spike IgG half-life was 184 days, being longer in females and those of white ethnicity. We estimated antibody levels associated with protection against reinfection likely last 1.5-2 years on average, with levels associated with protection from severe infection present for several years. These estimates could inform planning for vaccination booster strategies.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.06.28.21259452,2021-07-03,https://medrxiv.org/cgi/content/short/2021.06.28.21259452,"Persistent symptoms following SARS-CoV-2 infection in a random community sample of 508,707 people",Matthew Whitaker; Joshua Elliott; Marc Chadeau-Hyam; Steven Riley; Ara Darzi; Graham Cooke; Helen Ward; Paul Elliott,"Imperial College London; Imperial College London; Imperial College London; Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London School of Public Health","BackgroundLong COVID, describing the long-term sequelae after SARS-CoV-2 infection, remains a poorly defined syndrome. There is uncertainty about its predisposing factors and the extent of the resultant public health burden, with estimates of prevalence and duration varying widely. MethodsWithin rounds 3-5 of the REACT-2 study, 508,707 people in the community in England were asked about a prior history of COVID-19 and the presence and duration of 29 different symptoms. We used uni-and multivariable models to identify predictors of persistence of symptoms (12 weeks or more). We estimated the prevalence of symptom persistence at 12 weeks, and used unsupervised learning to cluster individuals by symptoms experienced. @@ -2644,9 +2603,6 @@ MethodsWe collected viral sequences and clinical data of patients admitted with ResultsSequences were obtained from 2341 inpatients (HOCI cases = 786) and analysis of clinical outcomes was carried out in 2147 inpatients with all data available. The hazard ratio (HR) for mortality of B.1.1.7 compared to other lineages was 1.01 (95% CI 0.79-1.28, P=0.94) and for ITU admission was 1.01 (95% CI 0.75-1.37, P=0.96). Analysis of sex-specific effects of B.1.1.7 identified increased risk of mortality (HR 1.30, 95% CI 0.95-1.78) and ITU admission (HR 1.82, 95% CI 1.15-2.90) in females infected with the variant but not males (mortality HR 0.82, 95% CI 0.61-1.10; ITU HR 0.74, 95% CI 0.52-1.04). ConclusionsIn common with smaller studies of patients hospitalised with SARS-CoV-2 we did not find an overall increase in mortality or ITU admission associated with B.1.1.7 compared to other lineages. However, women with B.1.1.7 may be at an increased risk of admission to intensive care and at modestly increased risk of mortality.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2021.06.24.21259374,2021-06-26,https://medrxiv.org/cgi/content/short/2021.06.24.21259374,A proteomic survival predictor for COVID-19 patients in intensive care,Vadim Demichev; Pinkus Tober-Lau; Tatiana Nazarenko; Simran Kaur Aulakh; Harry Whitwell; Oliver Lemke; Annika Roehl; Anja Freiwald; Mirja Mittermaier; Lukasz Szyrwiel; Daniela Ludwig; Clara Correia-Melo; Lena Lippert; Elisa T. Helbig; Paula Stubbemann; Nadine Olk; Charlotte Thibeault; Nana-Maria Gruening; Oleg Blyuss; Spyros Vernardis; Matthew White; Christoph B. Messner; Michael Joannidis; Thomas Sonnweber; Sebastian J. Klein; Alex Pizzini; Yvonne Wohlfarter; Sabina Sahanic; Richard Hilbe; Benedikt Schaefer; Sonja Wagner; Felix Machleidt; Carmen Garcia; Christoph Ruwwe-Gloesenkamp; Tilman Lingscheid; Laure Bosquillon de Jarcy; Miriam Stegemann; Moritz Pfeiffer; Linda Juergens; Sophy Denker; Daniel Zickler; Claudia Spies; Andreas Edel; Nils B. Mueller; Philipp Enghard; Aleksej Zelezniak; Rosa Bellmann-Weiler; Guenter Weiss; Archie Campbell; Caroline Hayward; David J. Porteous; Riccardo E. Marioni; Alexander Uhrig; Heinz Zoller; Judith Loeffler-Ragg; Markus A. Keller; Ivan Tancevski; John F. Timms; Alexey Zaikin; Stefan Hippenstiel; Michael Ramharter; Holger Mueller-Redetzky; Martin Witzenrath; Norbert Suttorp; Kathryn Lilley; Michael Muelleder; Leif Erik Sander; - PA-COVID- Study group; Florian Kurth; Markus Ralser,"The Francis Crick Institute; Charité - Universitätsmedizin Berlin; University College London; The Francis Crick Institute; Imperial College London; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; The Francis Crick Institute; Charité - Universitätsmedizin Berlin; The Francis Crick Institute; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Lobachevsky University,; The Francis Crick Institute; The Francis Crick Institute; Charité - Universitätsmedizin Berlin; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; The Francis Crick Institute; Medical University of Innsbruck; Medical University of Innsbruck; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; Charité - Universitätsmedizin Berlin; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; University College London; University College London; Charité - Universitätsmedizin Berlin; Bernhard Nocht Institute for Tropical Medicine; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; The University of Cambridge; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin","Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Comprehensively capturing the host physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index and APACHE II score were poor predictors of survival. Plasma proteomics instead identified 14 proteins that showed concentration trajectories different between survivors and non-survivors. A proteomic predictor trained on single samples obtained at the first time point at maximum treatment level (i.e. WHO grade 7) and weeks before the outcome, achieved accurate classification of survivors in an exploratory (AUROC 0.81) as well as in the independent validation cohort (AUROC of 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that predictors derived from plasma protein levels have the potential to substantially outperform current prognostic markers in intensive care. - -Trial registrationGerman Clinical Trials Register DRKS00021688",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.06.21.21259254,2021-06-25,https://medrxiv.org/cgi/content/short/2021.06.21.21259254,"Acceptability, usability and performance of lateral flow immunoassay tests for SARS-CoV-2 antibodies: REACT-2 study of self-testing in non-healthcare key workers",Bethan Davies; Marzieh Araghi; Maya Moshe; He Gao; Kimberly Bennet; Jordan Jenkins; Christina Atchison; Ara Darzi; Deborah Ashby; Steven Riley; Wendy Barclay; Paul Elliott; Helen Ward; Graham Cooke,Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London,"BackgroundSeroprevalence studies in key worker populations are essential to understand the epidemiology of SARS-CoV-2. Various technologies, including laboratory assays and point-of-care self-tests, are available for antibody testing. The interpretation of seroprevalence studies requires comparative data on the performance of antibody tests. MethodsIn June 2020, current and former members of the UK Police forces and Fire service performed a self-test lateral flow immunoassay (LFIA) and provided a saliva sample, nasopharyngeal swab, venous blood samples for Abbott ELISA and had a nurse performed LFIA. We present the prevalence of PCR positivity and antibodies to SARS-CoV-2 in this cohort following the first wave of infection in England; the acceptability and usability of self-test LFIAs (defined as use of the LFIA kit and provision of a valid result, respectively); and determine the sensitivity and specificity of LFIAs compared to laboratory ELISAs. @@ -2720,6 +2676,21 @@ C_LIO_LIStudy population were not self-selected C_LIO_LIJob exposure matrix allowed adjustment for occupational exposure C_LIO_LIData did not extend to the start of the second wave in September 2020 C_LI",occupational and environmental health,fuzzy,97,100 +medRxiv,10.1101/2021.06.09.21258556,2021-06-13,https://medrxiv.org/cgi/content/short/2021.06.09.21258556,"Safety, Immunogenicity, and Efficacy of a COVID-19 Vaccine (NVX-CoV2373) Co-administered With Seasonal Influenza Vaccines",Paul Heath; Seth Toback; Eva Galiza; Catherine Cosgrove; James Galloway; Anna L. Goodman; Pauline A. Swift; Sankarasubramanian Rajaram; Alison Graves-Jones; Jonathan Edelman; Fiona Burns; Angela M. Minassian; Iksung Cho; Lakshmi Kumar; Joyce S. Plested; E. Joy Rivers; Andreana Robertson; Filip Dubovsky; Greg Glenn,"St Georges, University of London; Novavax; St. George's, University of London; St Georges University of London; Kings College London; Guy's and St Thomas' NHS Foundation Trust; Epsom and St. Helier University Hospitals NHS Trust; Seqirus; Seqirus; Seqirus; University College London, and Royal Free London NHS Foundation Trust; University of Oxford, and Oxford Health NHS Foundation Trust; Novavax; Novavax; Novavax; Novavax; Novavax; Novavax; Novavax","BackgroundThe safety and immunogenicity profile of COVID-19 vaccines when administered concomitantly with seasonal influenza vaccines has not yet been reported. + +MethodsA sub-study on influenza vaccine co-administration was conducted as part of the phase 3 randomized trial of the safety and efficacy of NVX-CoV2373. The first [~]400 participants meeting main study entry criteria and with no contraindications to influenza vaccination were invited to join the sub-study. After randomization in a 1:1 ratio to receive NVX-CoV2373 (n=217) or placebo (n=214), sub-study participants received an age-appropriate, licensed, open-label influenza vaccine with dose 1 of NVX-CoV2373. Reactogenicity was evaluated via electronic diary for 7 days post-vaccination in addition to monitoring for unsolicited adverse events (AEs), medically-attended AEs (MAAEs), and serious AEs (SAEs). Influenza haemagglutination inhibition and SARS-CoV-2 anti-spike IgG assays were performed. Vaccine efficacy against PCR-confirmed, symptomatic COVID-19 was assessed. Comparisons were made between sub-study and main study participants. + +FindingsSub-study participants were younger, more racially diverse, and had fewer comorbid conditions than main study participants. Reactogenicity events more common in the co-administration group included tenderness (70.1% vs 57.6%) or pain (39.7% vs 29.3%) at injection site, fatigue (27.7% vs 19.4%), and muscle pain (28.3% vs 21.4%). Rates of unsolicited AEs, MAAEs, and SAEs were low and balanced between the two groups. Co-administration resulted in no change to influenza vaccine immune response, while a reduction in antibody responses to the NVX-CoV2373 vaccine was noted. Vaccine efficacy in the sub-study was 87.5% (95% CI: -0.2, 98.4) while efficacy in the main study was 89.8% (95% CI: 79.7, 95.5). + +InterpretationThis is the first study to demonstrate the safety, immunogenicity, and efficacy profile of a COVID-19 vaccine when co-administered with seasonal influenza vaccines. The results suggest concomitant vaccination may be a viable immunisation strategy. + +FundingThis study was funded by Novavax, Inc. + +Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for research articles published from December 2019 until 1 April 2021 with no language restrictions for the terms ""SARS-CoV-2"", ""COVID-19"", ""vaccine"", ""co-administration"", and ""immunogenicity"". There were no peer-reviewed publications describing the simultaneous use of any SARS-CoV-2 vaccine and another vaccine. Several vaccine manufacturers had recent publications on phase 3 trials results (Pfizer/BioNTech, Moderna, AstraZeneca, Janssen, and the Gamaleya Research Institute of Epidemiology and Microbiology). Neither these publications nor their clinical trials protocols (when publicly available) described co-administration and they often had trial criteria specifically excluding those with recent or planned vaccination with any licenced vaccine near or at the time of any study injection. + +Added value of this studyImmune interference and safety are always a concern when two vaccines are administered at the same time. This is the first study to demonstrate the safety and immunogenicity profile and clinical vaccine efficacy of a COVID-19 vaccine when co-administered with a seasonal influenza vaccine. + +Implications of all the available evidenceThis study provides much needed information to help guide national immunisation policy decision making on the critical issue of concomitant use of COVID-19 vaccines with influenza vaccines.",allergy and immunology,fuzzy,95,100 medRxiv,10.1101/2021.06.08.21258533,2021-06-12,https://medrxiv.org/cgi/content/short/2021.06.08.21258533,The impact of co-circulating pathogens on SARS-CoV-2/COVID-19 surveillance. How concurrent epidemics may decrease true SARS-CoV-2 percent positivity.,Aleksandra Kovacevic; Rosalind M Eggo; Marc Baguelin; Matthieu Domenech de Cellès; Lulla Opatowski,Institut Pasteur; London School of Hygiene & Tropical Medicine; Imperial College London; Max Planck Institute for Infection Biology; Univ Versailles Saint Quentin / Institut Pasteur / Inserm,"BackgroundCirculation of non-SARS-CoV-2 respiratory viruses during the COVID-19 pandemic may alter quality of COVID-19 surveillance, with possible consequences for real-time analysis and delay in implementation of control measures. Here, we assess the impact of an increased circulation of other respiratory viruses on the monitoring of positivity rates of SARS-CoV-2 and interpretation of surveillance data. MethodsUsing a multi-pathogen Susceptible-Exposed-Infectious-Recovered (SEIR) transmission model formalizing co-circulation of SARS-CoV-2 and another respiratory we assess how an outbreak of secondary virus may inflate the number of SARS-CoV-2 tests and affect the interpretation of COVID-19 surveillance data. Using simulation, we assess to what extent the use of multiplex PCR tests on a subsample of symptomatic individuals can support correction of the observed SARS-CoV-2 percent positive during other virus outbreaks and improve surveillance quality. @@ -3085,13 +3056,6 @@ ConclusionVaccination with a single dose of Oxford-AstraZeneca or Pfizer-BioNTec RegistrationThe study is registered with the ISRCTN Registry, ISRCTN21086382.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.04.12.21255275,2021-04-19,https://medrxiv.org/cgi/content/short/2021.04.12.21255275,Children develop strong and sustained cross-reactive immune responses against spike protein following SARS-CoV-2 infection,Alexander C Dowell; Megan S. Butler; Elizabeth Jinks; Gokhan Tut; Tara Lancaster; Panagiota Sylla; Jusnara Begum; Rachel Bruton; Hayden Pearce; Kriti Verma; Nicola Logan; Grace Tyson; Eliska Spalkova; Sandra Margielewska-Davies; Graham S. Taylor; Eleni Syrimi; Frances Baawuah; Joanne Beckmann; Ifeanyichukwu Okike; Shazaad Ahmad; Joanna Garstang; Andrew Brent; Bernadette Brent; Georgina Ireland; Felicity Aiano; Zahin Amin-Chowdhury; Samuel Jones; Ray Borrow; Ezra Linley; Rafaq Azad; John Wright; Dagmar Waiblinger; Chris Davis; Emma C Thomson; Massimo Palmarini; Brian James Willett; Wendy S Barclay; John Poh; Vanessa Saliba; Gayatri Amirthalingam; Kevin Brown; Mary Ramsay; Jianmin Zuo; Paul Moss; Shamez Ladhani,"Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; University of Birmingham; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; University of Birmingham; MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow G61-1QH, UK; MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow G61-1QH, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; East London NHS Foundation Trust, 9 Allie Street, London E1 8DE, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK 4. University Hospitals of Derby and Burton NHS Foundation Trust, Uttoxeter New Road, Derby; Manchester University NHS Foundation Trust, Oxford Road, Manchester M13 9WL, UK; Birmingham Community Healthcare NHS Trust, Holt Street, Aston B7 4BN, UK; Oxford University Hospitals NHS Foundation Trust, Old Road, Oxford OX3 7HE University of Oxford, Wellington Square, Oxford OX1 2JD, UK; Oxford University Hospitals NHS Foundation Trust, Old Road, Oxford OX3 7HE; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Public Health England, Manchester Royal Infirmary, Manchester, United Kingdom; Public Health England, Manchester Royal Infirmary, Manchester, United Kingdom; Bradford Teaching Hospitals NHS Foundation Trust; Bradford Teaching Hospitals NHS Foundation Trust; Bradford Teaching Hospitals NHS Foundation Trust; University of Glasgow; University of Glasgow; University of Glasgow; University of Glasgow; Imperial College, London; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK","SARS-CoV-2 infection is generally mild or asymptomatic in children but the biological basis for this is unclear. We studied the profile of antibody and cellular immunity in children aged 3-11 years in comparison with adults. Antibody responses against spike and receptor binding domain (RBD) were high in children and seroconversion boosted antibody responses against seasonal Beta-coronaviruses through cross-recognition of the S2 domain. Seroneutralisation assays against alpha, beta and delta SARS-CoV-2 variants demonstrated comparable neutralising activity between children and adults. T cell responses against spike were >2-fold higher in children compared to adults and displayed a TH1 cytokine profile. SARS-CoV-2 spike-specific T cells were also detected in many seronegative children, revealing pre-existing responses that were cross-reactive with seasonal Alpha and Beta-coronaviruses. Importantly, all children retained high antibody titres and cellular responses at 6 months after infection whilst relative antibody waning was seen in adults. Spike-specific responses in children also remained broadly stable beyond 12 months. Children thus distinctly generate robust, cross-reactive and sustained immune responses after SARS-CoV-2 infection with focussed specificity against spike protein. These observations demonstrate novel features of SARS-CoV-2-specific immune responses in children and may provide insight into their relative clinical protection. Furthermore, this information will help to guide the introduction of vaccination regimens in the paediatric population.",allergy and immunology,fuzzy,100,100 -medRxiv,10.1101/2021.04.08.21255100,2021-04-15,https://medrxiv.org/cgi/content/short/2021.04.08.21255100,REACT-1 round 10 report: Level prevalence of SARS-CoV-2 swab-positivity in England during third national lockdown in March 2021,Steven Riley; Oliver Eales; David Haw; Caroline E. Walters; Haowei Wang; Kylie E. C. Ainslie; Christina Atchinson; Claudio Fronterre; Peter J. Diggle; Deborah Ashby; Christl A Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott,"School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear","BackgroundIn England, hospitalisations and deaths due to SARS-CoV-2 have been falling consistently since January 2021 during the third national lockdown of the COVID-19 pandemic. The first significant relaxation of that lockdown occurred on 8 March when schools reopened. - -MethodsThe REal-time Assessment of Community Transmission-1 (REACT-1) study augments routine surveillance data for England by measuring swab-positivity for SARS-CoV-2 in the community. The current round, round 10, collected swabs from 11 to 30 March 2021 and is compared here to round 9, in which swabs were collected from 4 to 23 February 2021. - -ResultsDuring round 10, we estimated an R number of 1.00 (95% confidence interval 0.81, 1.21). Between rounds 9 and 10 we estimated national prevalence has dropped by [~]60% from 0.49% (0.44%, 0.55%) in February to 0.20% (0.17%, 0.23%) in March. There were substantial falls in weighted regional prevalence: in South East from 0.36% (0.29%, 0.44%) in round 9 to 0.07% (0.04%, 0.12%) in round 10; London from 0.60% (0.48%, 0.76%) to 0.16% (0.10%, 0.26%); East of England from 0.47% (0.36%, 0.60%) to 0.15% (0.10%, 0.24%); East Midlands from 0.59% (0.45%, 0.77%) to 0.19% (0.13%, 0.28%); and North West from 0.69% (0.54%, 0.88%) to 0.31% (0.21%, 0.45%). Areas of apparent higher prevalence remain in parts of the North West, and Yorkshire and The Humber. The highest prevalence in March was found among school-aged children 5 to 12 years at 0.41% (0.27%, 0.62%), compared with the lowest in those aged 65 to 74 and 75 and over at 0.09% (0.05%, 0.16%). The close approximation between prevalence of infections and deaths (suitably lagged) is diverging, suggesting that infections may have resulted in fewer hospitalisations and deaths since the start of widespread vaccination. - -ConclusionWe report a sharp decline in prevalence of infections between February and March 2021. We did not observe an increase in the prevalence of SARS-CoV-2 following the reopening of schools in England, although the decline of prevalence appears to have stopped. Future rounds of REACT-1 will be able to measure the rate of growth or decline from this current plateau and hence help assess the effectiveness of the vaccination roll-out on transmission of the virus as well as the potential size of any third wave during the ensuing months.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.04.08.21255099,2021-04-14,https://medrxiv.org/cgi/content/short/2021.04.08.21255099,Occupational risks of COVID-19 in NHS workers in England,Diana van der Plaat; Ira Madan; David Coggon; Martie van Tongeren; Rhiannon Edge; Rupert Muiry; Vaughan Parsons; Paul Cullinan,Imperial College London; Guy's and St Thomas' NHS Foundation Trust; Southampton General Hospital; University of Manchester; Lancaster University; Guy's and St Thomas NHS Foundation Trust; Guy's and St Thomas NHS Foundation Trust; Imperial College London,"ObjectiveTo quantify occupational risks of Covid-19 among healthcare staff during the first wave of the pandemic in England MethodsUsing pseudonymised data on 902,813 individuals continuously employed by 191 National Health Service trusts during 1.1.19 to 31.7.20, we explored demographic and occupational risk factors for sickness absence ascribed to Covid-19 during 9.3.20 to 31.7.20 (n = 92,880). We estimated odds ratios (ORs) by multivariable logistic regression. @@ -3358,6 +3322,33 @@ Implications of all the available evidenceDespite the UK having a simple set of bioRxiv,10.1101/2021.03.14.435295,2021-03-16,https://biorxiv.org/cgi/content/short/2021.03.14.435295,3D genomic capture of regulatory immuno-genetic profiles in COVID-19 patients for prognosis of severe COVID disease outcome,Ewan Hunter; Christina Koutsothanasi; Adam Wilson; Francisco Coroado Santos; Matthew Salter; Ryan Powell; Ann Dring; Paulina Brajer; Benedict Egan; Jurjen Westra; Aroul Ramadass; William Messner; Amanda Brunton; Zoe Lyski; Rama Vancheeswaran; Andrew Barlow; Dmitri Pchejetski; Alexandre Akoulitchev,"Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oregon Health & Science University, Portland, OR; Oregon Health & Science University, Portland, OR; Oregon Health & Science University, Portland, OR; West Hertfordshire NHS Trust, Watford, UK; West Hertfordshire NHS Trust, Watford, UK; Norwich Medical School, University of East Anglia; Oxford BioDynamics Plc, Oxford UK","Human infection with the SARS-CoV-2 virus leads to coronavirus disease (COVID-19). A striking characteristic of COVID-19 infection in humans is the highly variable host response and the diverse clinical outcomes, ranging from clinically asymptomatic to severe immune reactions leading to hospitalization and death. Here we used a 3D genomic approach to analyse blood samples at the time of COVID diagnosis, from a global cohort of 80 COVID-19 patients, with different degrees of clinical disease outcomes. Using 3D whole genome EpiSwitch(R) arrays to generate over 1 million data points per patient, we identified a distinct and measurable set of differences in genomic organization at immune-related loci that demonstrated prognostic power at baseline to stratify patients with mild forms of illness and those with severe forms that required hospitalization and intensive care unit (ICU) support. Further analysis revealed both well established and new COVID-related dysregulated pathways and loci, including innate and adaptive immunity; ACE2; olfactory, G{beta}{psi}, Ca2+ and nitric oxide (NO) signalling; prostaglandin E2 (PGE2), the acute inflammatory cytokine CCL3, and the T-cell derived chemotactic cytokine CCL5. We identified potential therapeutic agents for mitigation of severe disease outcome, with several already being tested independently, including mTOR inhibitors (rapamycin and tacrolimus) and general immunosuppressants (dexamethasone and hydrocortisone). Machine learning algorithms based on established EpiSwitch(R) methodology further identified a subset of 3D genomic changes that could be used as prognostic molecular biomarker leads for the development of a COVID-19 disease severity test.",biochemistry,fuzzy,92,100 medRxiv,10.1101/2021.03.09.21253012,2021-03-15,https://medrxiv.org/cgi/content/short/2021.03.09.21253012,The local and systemic response to SARS-CoV-2 infection in children and adults,Masahiro Yoshida; Kaylee B Worlock; Ni Huang; Rik GH Lindeboom; Colin R Butler; Natsuhiko Kumasaka; Cecilia Dominguez Conde; Lira Mamanova; Liam Bolt; Laura Richardson; Krzysztof Polanski; Elo Madissoon; Josephine L Barnes; Jessica Allen-Hyttinen; Eliz Kilich; Brendan C Jones; Angus de Wilton; Anna Wilbrey-Clark; Waradon Sungnak; Jan Patrick Prett; Elena Prigmore; Henry Yung; Puja Mehta; Aarash Saleh; Anita Saigal; Vivian Chu; Jonathan M Cohen; Clare Cane; Aikaterini Iordanidou; Soichi Shibuya; Ann-Kathrin Reuschl; A. Christine Argento; Richard G Wunderink; Sean B Smith; Taylor A Poor; Catherine A Gao; Jane E Dematte; - NU SCRIPT Study Investigators; Gary Reynolds; Muzlifah Haniffa; Georgina S Bowyer; Matthew Coates; Menna R Clatworthy; Fernando J Calero-Nieto; Berthold Gottgens; Neil J Sebire; Clare Jolly; Paolo de Coppi; Claire M Smith; Alexander V Misharin; Sam M Janes; Sarah A Teichmann; Marko Z Nikolic; Kerstin B Meyer,"UCL Respiratory, Division of Medicine, University College London, London, UK; UCL Respiratory, Division of Medicine, University College London, London, UK; Wellcome Sanger Institute, Cambridge, UK; Wellcome Sanger Institute, Cambridge, UK; UCL Great Ormond Street Institute of Child Health, London, UK; Wellcome Trust Sanger Institute; Wellcome Sanger Institute, Cambridge, UK; Wellcome Sanger Institute, Cambridge, UK; Wellcome Sanger Institute, Cambridge, UK; Wellcome Sanger Institute, Cambridge, UK; Wellcome Sanger Institute, Cambridge, UK; Wellcome Sanger Institute, Cambridge, UK; UCL Respiratory, Division of Medicine, University College London, London, UK; UCL Respiratory, Division of Medicine, University College London, London, UK; University College London Hospitals NHS Foundation Trust, London, UK; UCL Great Ormond Street Institute of Child Health, London, UK; University College London Hospital Trust; Wellcome Sanger Institute, Cambridge, UK; Wellcome Sanger Institute; Wellcome Sanger Institute, Cambridge, UK; Wellcome Sanger Institute, Cambridge, UK; UCL Respiratory, Division of Medicine, University College London, London, UK; UCL Respiratory, Division of Medicine, University College London, London, UK; Royal Free Hospital, London, UK; Royal Free Hospital, London, UK; Royal Free Hospital, London, UK; University College London Hospitals NHS Foundation Trust, London, UK; Royal Free Hospital, London, UK; Royal Free Hospital, London, UK; UCL Great Ormond Street Institute of Child Health, London, UK; Division of Infection and Immunity, University College London, London, UK; Division of Pulmonary and Critical Care Medicine, Northwestern University, Feinberg School of Medicine, Chicago, USA; Northwestern University Feinberg School of Medicine; Division of Pulmonary and Critical Care Medicine, Northwestern University, Feinberg School of Medicine, Chicago, USA; Division of Pulmonary and Critical Care Medicine, Northwestern University, Feinberg School of Medicine, Chicago, USA; Division of Pulmonary and Critical Care Medicine, Northwestern University, Feinberg School of Medicine, Chicago, USA; Division of Pulmonary and Critical Care Medicine, Northwestern University, Feinberg School of Medicine, Chicago, USA; ; Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK; Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK; Department of Medicine, University of Cambridge, Cambridge CB2 0QQ, UK; University of Cambridge, Department of Medicine; University of Cambride, Department of Medicine; Wellcome Trust & MRC Cambridge Stem Cell Institute and Department of Haematology, University of Cambridge, Cambridge UK; Wellcome Trust & MRC Cambridge Stem Cell Institute and Department of Haematology, University of Cambridge, Cambridge UK; NIHR Great Ormond Street BRC and Institute of Child Health, London, UK; Division of Infection and Immunity, University College London, UK; UCL Great Ormond Street Institute of Child Health, London, UK; UCL Great Ormond Street Institute of Child Health, London, UK; Northwestern University; UCL Respiratory, Division of Medicine, University College London, London, UK; Wellcome Sanger Institute, Cambridge, UK; UCL Respiratory, Division of Medicine, University College London, London, UK; Wellcome Sanger Institute, Cambridge, UK","While a substantial proportion of adults infected with SARS-CoV-2 progress to develop severe disease, children rarely manifest respiratory complications. Therefore, understanding differences in the local and systemic response to SARS-CoV-2 infection between children and adults may provide important clues about the pathogenesis of SARS-CoV-2 infection. To address this, we first generated a healthy reference multi-omics single cell data set from children (n=30) in whom we have profiled triple matched samples: nasal and tracheal brushings and PBMCs, where we track the developmental changes for 42 airway and 31 blood cell populations from infancy, through childhood to adolescence. This has revealed the presence of naive B and T lymphocytes in neonates and infants with a unique gene expression signature bearing hallmarks of innate immunity. We then contrast the healthy reference with equivalent data from severe paediatric and adult COVID-19 patients (total n=27), from the same three types of samples: upper and lower airways and blood. We found striking differences: children with COVID-19 as opposed to adults had a higher proportion of innate lymphoid and non-clonally expanded naive T cells in peripheral blood, and a limited interferon-response signature. In the airway epithelium, we found the highest viral load in goblet and ciliated cells and describe a novel inflammatory epithelial cell population. These cells represent a transitional regenerative state between secretory and ciliated cells; they were found in healthy children and were enriched in paediatric and adult COVID-19 patients. Epithelial cells display an antiviral and neutrophil-recruiting gene signature that is weaker in severe paediatric versus adult COVID-19. Our matched blood and airway samples allowed us to study the spatial dynamics of infection. Lastly, we provide a user-friendly interface for this data1 as a highly granular reference for the study of immune responses in airways and blood in children.",pediatrics,fuzzy,100,100 medRxiv,10.1101/2021.03.12.21253484,2021-03-13,https://medrxiv.org/cgi/content/short/2021.03.12.21253484,Limits of lockdown: characterising essential contacts during strict physical distancing,Amy C Thomas; Leon Danon; Hannah Christensen; Kate Northstone; Daniel Smith; Emily J Nixon; Adam Trickey; Gibran Hemani; Sarah Sauchelli; Adam Finn; Nicholas J Timpson; Ellen Brooks-Pollock,"University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; NIHR Bristol Biomedical Research Centre, University of Bristol; University of Bristol; University of Bristol; University of Bristol","COVID-19 has exposed health inequalities within countries and globally. The fundamental determining factor behind an individuals risk of infection is the number of social contacts they make. In many countries, physical distancing measures have been implemented to control transmission of SARS-CoV-2, reducing social contacts to a minimum. Characterising unavoidable social contacts is key for understanding the inequalities behind differential risks and planning vaccination programmes. We utilised an existing English longitudinal birth cohort, which is broadly representative of the wider population (n=6807), to explore social contact patterns and behaviours when strict physical distancing measures were in place during the UKs first lockdown in March-May 2020. Essential workers, specifically those in healthcare, had 4.5 times as many contacts as non-essential workers [incident rate ratio = 4.42 (CI95%: 3.88-5.04)], whilst essential workers in other sectors, mainly teaching and the police force had three times as many contacts [IRR = 2.84 (2.58-3.13)]. The number of individuals in a household, which is conflated by number of children, increases essential social contacts by 40%. Self-isolation effectively reduces numbers of contacts outside of the home, but not entirely. Together, these findings will aid the interpretation of epidemiological data and impact the design of effective SARS-CoV-2 control strategies, such as vaccination, testing and contact tracing.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2021.03.10.21253173,2021-03-12,https://medrxiv.org/cgi/content/short/2021.03.10.21253173,"High household transmission of SARS-CoV-2 in the United States: living density, viral load, and disproportionate impact on communities of color",Carla Cerami; Tyler Rapp; Feng-Chang Lin; Kathleen Tompkins; Christopher Basham; Meredith Smith Muller; Maureen Whittelsey; Haoming Zhang; Srijana Bhattarai Chhetri; Judy Smith; Christy Litel; Kelly Lin; Mehal Churiwal; Salman Khan; Faith Claman; Rebecca Rubinstein; Katie Mollan; David Wohl; Lakshmanane Premkumar; Jonathan J. Juliano; Jessica T Lin,"MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; University of North Carolina School of Medicine; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA","BackgroundFew prospective studies of SARS-CoV-2 transmission within households have been reported from the United States, where COVID-19 cases are the highest in the world and the pandemic has had disproportionate impact on communities of color. + +Methods and FindingsThis is a prospective observational study. Between April-October 2020, the UNC CO-HOST study enrolled 102 COVID-positive persons and 213 of their household members across the Piedmont region of North Carolina, including 45% who identified as Hispanic/Latinx or non-white. Households were enrolled a median of 6 days from onset of symptoms in the index case. Secondary cases within the household were detected either by PCR of a nasopharyngeal (NP) swab on study day 1 and weekly nasal swabs (days 7, 14, 21) thereafter, or based on seroconversion by day 28. After excluding household contacts exposed at the same time as the index case, the secondary attack rate (SAR) among susceptible household contacts was 60% (106/176, 95% CI 53%-67%). The majority of secondary cases were already infected at study enrollment (73/106), while 33 were observed during study follow-up. Despite the potential for continuous exposure and sequential transmission over time, 93% (84/90, 95% CI 86%-97%) of PCR-positive secondary cases were detected within 14 days of symptom onset in the index case, while 83% were detected within 10 days. Index cases with high NP viral load (>10^6 viral copies/ul) at enrollment were more likely to transmit virus to household contacts during the study (OR 4.9, 95% CI 1.3-18 p=0.02). Furthermore, NP viral load was correlated within families (ICC=0.44, 95% CI 0.26-0.60), meaning persons in the same household were more likely to have similar viral loads, suggesting an inoculum effect. High household living density was associated with a higher risk of secondary household transmission (OR 5.8, 95% CI 1.3-55) for households with >3 persons occupying <6 rooms (SAR=91%, 95% CI 71-98%). Index cases who self-identified as Hispanic/Latinx or non-white were more likely to experience a high living density and transmit virus to a household member, translating into an SAR in minority households of 70%, versus 52% in white households (p=0.05). + +ConclusionsSARS-CoV-2 transmits early and often among household members. Risk for spread and subsequent disease is elevated in high-inoculum households with limited living space. Very high infection rates due to household crowding likely contribute to the increased incidence of SARS-CoV-2 infection and morbidity observed among racial and ethnic minorities in the US. Quarantine for 14 days from symptom onset of the first case in the household is appropriate to prevent onward transmission from the household. Ultimately, primary prevention through equitable distribution of effective vaccines is of paramount importance. + +AUTHORS SUMMARYO_ST_ABSWhy was this study done?C_ST_ABSO_LIUnderstanding the secondary attack rate and the timing of transmission of SARS-CoV-2 within households is important to determine the role of household transmission in the larger pandemic and to guide public health policies about quarantine. +C_LIO_LIProspective studies looking at the determinants of household transmission are sparse, particularly studies including substantial racial and ethnic minorities in the United States and studies with adequate follow-up to detect sequential transmission events. +C_LIO_LIIdentifying individuals at high risk of transmitting and acquiring SARS-CoV-2 will inform strategies for reducing transmission in the household, or reducing disease in those exposed. +C_LI + +What did the researchers do and find?O_LIBetween April-November 2020, the UNC CO-HOST study enrolled 102 households across the Piedmont region of North Carolina, including 45% with an index case who identified as racial or ethnic minorities. +C_LIO_LIOverall secondary attack rate was 60% with two-thirds of cases already infected at study enrollment. +C_LIO_LIDespite the potential for sequential transmission in the household, the majority of secondary cases were detected within 10 days of symptom onset of the index case. +C_LIO_LIViral loads were correlated within families, suggesting an inoculum effect. +C_LIO_LIHigh viral load in the index case was associated with a greater likelihood of household transmission. +C_LIO_LISpouses/partners of the COVID-positive index case and household members with obesity were at higher risk of becoming infected. +C_LIO_LIHigh household living density contributed to an increased risk of household transmission. +C_LIO_LIRacial/ethnic minorities had an increased risk of acquiring SARS-CoV-2 in their households in comparison to members of the majority (white) racial group. +C_LI + +What do these findings mean?O_LIHousehold transmission often occurs quickly after a household member is infected. +C_LIO_LIHigh viral load increases the risk of transmission. +C_LIO_LIHigh viral load cases cluster within households - suggesting high viral inoculum in the index case may put the whole household at risk for more severe disease. +C_LIO_LIIncreased household density may promote transmission within racial and ethnic minority households. +C_LIO_LIEarly at-home point-of-care testing, and ultimately vaccination, is necessary to effectively decrease household transmission. +C_LI",infectious diseases,fuzzy,92,100 medRxiv,10.1101/2021.03.11.21253189,2021-03-12,https://medrxiv.org/cgi/content/short/2021.03.11.21253189,"Risk, clinical course and outcome of ischemic stroke in patients hospitalized with COVID-19: a multicenter cohort study",Wouter M Sluis; Marijke Linschoten; J Matthijs Biesbroek; Heleen M den Hertog; Tessa Ribbers; Dennis Nieuwkamp; Reinier C van Houwelingen; Andreas Dias; Ingeborg WM van Uden; Joost P Kerklaan; H. Paul Bienfait; Sarah E Vermeer; Sonja W de Jong; Mariam Ali; Marieke JH Wermer; Marieke T de Graaf; Paul JAM Brouwers; Folkert W Asselbergs; L Jaap Kappelle; H Bart van der Worp; Annemijn M Algra; - CAPACITY-COVID collaborative consortium,"University Medical Center Utrecht; University Medical Center Utrecht; Diakonessenhuis Utrecht; Isala Hospital Zwolle; Jeroen Bosch Hospital 's Hertogenbosch; Jeroen Bosch Hospital 's Hertogenbosch; Treant Hospital Emmen; Ikazia Hospital Rotterdam; Catharina Hospital Eindhoven; St. Antonius Hospital Nieuwegein; Gelre Hospital Apeldoorn; Rijnstate Hospital Arnhem; St. Jansdal Hospital Harderwijk; Amsterdam UMC, Amsterdam; Leiden University Medical Center, Leiden; Zaans Medical Center, Zaandam; Medisch Spectrum Twente, Enschede; University Medical Center Utrecht; University Medical Center Utrecht; University Medical Center Utrecht; University Medical Center Utrecht; ","Background and purposeThe frequency of ischemic stroke in patients with COVID-19 varies in the current literature, and risk factors are unknown. We assessed the incidence, risk factors, and outcomes of acute ischemic stroke in hospitalized patients with COVID-19. MethodsWe included patients with a laboratory confirmed SARS-CoV-2 infection admitted in 16 hospitals participating in the international CAPACITY-COVID registry between March 1st and August 1st, 2020. Patients were screened for the occurrence of acute ischemic stroke. We calculated the cumulative incidence of ischemic stroke and compared risk factors, cardiovascular complications, and in-hospital mortality in patients with and without ischemic stroke. @@ -4203,19 +4194,6 @@ ResultsIn an analysis including 327,720 UK participants, the use of probiotics, ConclusionWe observed a modest but significant association between use of probiotics, omega-3 fatty acid, multivitamin or vitamin D supplements and lower risk of testing positive for SARS-CoV-2 in women. No clear benefits for men were observed nor any effect of vitamin C, garlic or zinc for men or women. Randomised controlled trials of selected supplements would be required to confirm these observational findings before any therapeutic recommendations can be made.",public and global health,fuzzy,100,100 medRxiv,10.1101/2020.11.25.20238600,2020-11-29,https://medrxiv.org/cgi/content/short/2020.11.25.20238600,Spatially resolved simulations of the spread of COVID-19 in European countries,Andrea Parisi; Samuel P C Brand; Joe Hilton; Rabia Aziza; Matt J Keeling; D. James Nokes,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; Kemri-Wellcome Trust,"We explore the spatial and temporal spread of the novel SARS-CoV-2 virus under containment measures in three European countries based on fits to data of the early outbreak. Using data from Spain and Italy, we estimate an age dependent infection fatality ratio for SARS-CoV-2, as well as risks of hospitalization and intensive care admission. We use them in a model that simulates the dynamics of the virus using an age structured, spatially detailed agent based approach, that explicitly incorporates governamental interventions, changes in mobility and contact patterns occurred during the COVID-19 outbreak in each country. Our simulations reproduce several of the features of its spatio-temporal spread in the three countries studied. They show that containment measures combined with high density are responsible for the containment of cases within densely populated areas, and that spread to less densely populated areas occurred during the late stages of the first wave. The capability to reproduce observed features of the spatio-temporal dynamics of SARS-CoV-2 makes this model a potential candidate for forecasting the dynamics of SARS-CoV-2 in other settings, and we recommend its application in low and lower-middle countries which remain understudied.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2020.11.23.20237313,2020-11-24,https://medrxiv.org/cgi/content/short/2020.11.23.20237313,"Identifying optimal combinations of symptoms to trigger diagnostic work-up of suspected COVID-19 cases in vaccine trials: analysis from a community-based, prospective, observational cohort",Michela Antonelli; Joan Capdevila; Amol Chaudhari; Julia Granerod; Liane S Canas; Mark S Graham; Kerstin Klaser; Marc Modat; Erika Molteni; Ben Murray; Carole H Sudre; Richard Davies; Anna May; Long H Nguyen; David A Drew; Amit Joshi; Andrew T Chan; Jakob Cramer; Tim Spector; Jonathan Wolf; Sebastien Ourselin; Claire J Steves; Alfred E Loeliger,King's College London; Zoe Global; Coalition for Epidemic Preparedness Innovations; Coalition for Epidemic Preparedness Innovations; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; University College London; Zoe Global; Zoe Global; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Coalition for Epidemic Preparedness Innovations; King's College London; Zoe Global; King's College London; King's College London; Coalition for Epidemic Preparedness Innovations,"ObjectivesDiagnostic work-up following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify optimal symptom combinations to capture most cases using fewer tests with implications for COVID-19 vaccine developers across different resource settings and public health. - -MethodsUK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms and an RT-PCR test within seven days of symptom onset were included. Sensitivity, specificity, and number of RT-PCR tests needed to identify one case (test per case [TPC]) were calculated for different symptom combinations. A multi-objective evolutionary algorithm was applied to generate combinations with optimal trade-offs between sensitivity and specificity. - -FindingsUK and US cohorts included 122,305 (1,202 positives) and 3,162 (79 positive) individuals. Within three days of symptom onset, the COVID-19 specific symptom combination (cough, dyspnoea, fever, anosmia/ageusia) identified 69% of cases requiring 47 TPC. The combination with highest sensitivity (fatigue, anosmia/ageusia, cough, diarrhoea, headache, sore throat) identified 96% cases requiring 96 TPC. - -InterpretationWe confirmed the significance of COVID-19 specific symptoms for triggering RT-PCR and identified additional symptom combinations with optimal trade-offs between sensitivity and specificity that maximize case capture given different resource settings. - -HighlightsO_LIWidely recommended symptoms identified only [~]70% COVID-19 cases -C_LIO_LIAdditional symptoms increased case finding to > 90% but tests needed doubled -C_LIO_LIOptimal symptom combinations maximise case capture considering available resources -C_LIO_LIImplications for COVID-19 vaccine efficacy trials and wider public health -C_LI",health informatics,fuzzy,100,100 medRxiv,10.1101/2020.11.19.20234120,2020-11-23,https://medrxiv.org/cgi/content/short/2020.11.19.20234120,Actionable druggable genome-wide Mendelian randomization identifies repurposingopportunities for COVID-19,Liam Gaziano; Claudia Giambartolomei; Alexandre C Pereira; Anna Gaulton; Daniel C Posner; Sonja A Swanson; Yuk Lam Ho; Sudha K Iyengar; Nicole M Kosik; Marijana Vujkovic; David R Gagnon; A Patricia Bento; Pedro Beltrao; Inigo Barrio Hernandez; Lars Ronnblom; Niklas Hagberg; Christian Lundtoft; Claudia Langenberg; Maik Pietzner; Dennis Valentine; Elias Allara; Praveen Surendran; Stephen Burgess; Jing Hua Zhao; James E Peters; Bram P Prins; John Danesh; Poornima Devineni; Yunling Shi; Kristine E Lynch; Scott L DuVall; Helene Garcon; Lauren Thomann; Jin J Zhou; Bryan R Gorman; Jennifer E Huffman; Christopher J O'Donnell; Philip S Tsao; Jean C Beckham; Saiju Pyarajan; Sumitra Muralidhar; Grant D Huang; Rachel Ramoni; Adriana M Hung; Kyong-Mi Chang; Yan V Sun; Jacob Joseph; Andrew R Leach; Todd L Edwards; Kelly Cho; J Michael Gaziano; Adam S Butterworth; Juan P Casas,"VA Boston Healthcare System, University of Cambridge; Instituto Italiano di Tecnologia, University of California Los Angeles; University of Sao Paulo, Harvard University; European Molecular Biology Laboratory, European Bioinformatics Institute; VA Boston Healthcare System; Erasmus Medical Center; VA Boston Healthcare System; Case Western Reserve University and Louis Stoke Cleveland VAMC; VA Boston Healthcare System; The Corporal Michael J. Crescenz VA Medical Center, the University of Pennsylvania Perelman School of Medicine; Boston University, VA Boston Healthcare System; European Molecular Biology Laboratory, European Bioinformatics Institute; European Molecular Biology Laboratory, European Bioinformatics Institute; European Molecular Biology Laboratory, European Bioinformatics Institute; Uppsala University; Uppsala University; Uppsala University; Charite University Medicine Berlin, Universityof Cambridge; Universityof Cambridge; University College London; University of Cambridge; Wellcome Genome Campus and University of Cambridge; University of Cambridge; University of Cambridge; Imperial College London; Wellcome Genome Campus and University of Cambridge; University of Cambridge; VA Boston Healthcare System; VA Boston Healthcare System; VA Salt Lake City Health Care System, University of Utah; VA Salt Lake City Health Care System, University of Utah; VA Boston Healthcare System; VA Boston Healthcare System; University of Arizona, Phoenix VA Health Care System; VA Boston Healthcare System; VA Boston Healthcare System; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School; VA Palo Alto Health Care System, Stanford University School of Medicine; Durham VA Medical Center, Duke University School of Medicine; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School; Department of Veterans Affairs; Department of Veterans Affairs; Department of Veterans Affairs; Department of Veterans Affairs, Vanderbilt University; The Corporal Michael J. Crescenz VA Medical Center, University of Pennsylvania; Atlanta VA Health Care System, Emory University Rollins School of Public Health; VA Boston Healthcare System and Brigham & Women's Hospital; European Molecular Biology Laboratory, European Bioinformatics Institute; Department of Veterans Affairs Tennessee Valley Healthcare System, Vanderbilt Genetics Institute Vanderbilt University Medical Center; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School; University of Cambridge, Wellcome Genome Campus and University of Cambridge; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School","Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization (MR) analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2: P=1.6x10-6, IFNAR2: P=9.8x10-11, and IL-10RB: P=1.9x10-14) using cis-eQTL genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared eQTL signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.11.19.20234849,2020-11-22,https://medrxiv.org/cgi/content/short/2020.11.19.20234849,Community factors and excess mortality in first wave of the COVID-19 pandemic.,Bethan Davies; Brandon L Parkes; James Bennett; Daniela Fecht; Marta Blangiardo; Majid Ezzati; Paul Elliott,Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London,"Risk factors for increased risk of death from Coronavirus Disease 19 (COVID-19) have been identified1,2 but less is known on characteristics that make communities resilient or vulnerable to the mortality impacts of the pandemic. We applied a two-stage Bayesian spatial model to quantify inequalities in excess mortality at the community level during the first wave of the pandemic in England. We used geocoded data on all deaths in people aged 40 years and older during March-May 2020 compared with 2015-2019 in 6,791 local communities. Here we show that communities with an increased risk of excess mortality had a high density of care homes, and/or high proportion of residents on income support, living in overcrowded homes and/or high percent of people with a non-White ethnicity (including Black, Asian and other minority ethnic groups). Conversely, after accounting for other community characteristics, we found no association between population density or air pollution and excess mortality. Overall, the social and environmental variables accounted for around 15% of the variation in mortality at community level. Effective and timely public health and healthcare measures that target the communities at greatest risk are urgently needed if England and other industrialised countries are to avoid further widening of inequalities in mortality patterns during the second wave.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.11.18.20233932,2020-11-20,https://medrxiv.org/cgi/content/short/2020.11.18.20233932,REACT-1 round 6 updated report: high prevalence of SARS-CoV-2 swab positivity with reduced rate of growth in England at the start of November 2020,Steven Riley; Kylie E. C. Ainslie; Oliver Eales; Caroline E. Walters; Haowei Wang; Christina Atchinson; Claudio Fronterre; Peter J. Diggle; Deborah Ashby; Christl A Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott,"School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear","BackgroundEngland is now in the midst of its second wave of the COVID-19 pandemic. Multiple regions of the country are at high infection prevalence and all areas experienced rapid recent growth of the epidemic during October 2020. @@ -4323,15 +4301,6 @@ Evidence before this studySpecific risk factors for SARS-CoV-2 infection in heal Added value of this studyOur prospective cohort study of almost 6,000 HCWs at a large UK teaching hospital strengthens previous findings from UK-based cohorts in identifying an increased risk of SARS-CoV-2 exposure amongst HCWs. Specifically, factors associated with SARS-CoV-2 exposure include caring for confirmed COVID-19 cases and identifying as being within specific ethnic groups (BAME staff). We further delineated the risk amongst BAME staff and demonstrate that occupational factors alone do not account for all of the increased risk amongst this group. We demonstrate for the first time that healthcare assistants represent a key at-risk occupational group, and challenge previous findings of significantly higher risk amongst nursing staff. Seroprevalence in staff not working in areas with confirmed COVID-19 patients was only marginally higher than that of the general population within the same geographical region. This observation could suggest the increased risk amongst HCWs arises through occupational exposure to confirmed cases and could account for the overall higher seroprevalence in HCWs, rather than purely the presence of staff in healthcare facilities. Over 30% of seropositive staff had not reported symptoms consistent with COVID-19, and in those who did report symptoms, differentiating COVID-19 from other causes based on symptom data alone was unreliable. Implications of all the available evidenceInternational efforts to reduce the risk of SARS-CoV-2 infection amongst HCWs need to be prioritised. The risk of SARS-CoV-2 infection amongst HCWs is heterogenous but also follows demonstrable patterns. Potential mechanisms to reduce the risk for staff working in areas with confirmed COVID-19 patients include improved training in hand hygiene and personal protective equipment (PPE), better access to high quality PPE, and frequent asymptomatic testing. Wider asymptomatic testing in healthcare facilities has the potential to reduce spread of SARS-CoV-2 within hospitals, thereby reducing patient and staff risk and limiting spread between hospitals and into the wider community. The increased risk of COVID-19 amongst BAME staff cannot be explained by purely occupational factors; however, the increased risk amongst minority ethnic groups identified here was stark and necessitates further evaluation.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2020.11.02.20224824,2020-11-04,https://medrxiv.org/cgi/content/short/2020.11.02.20224824,"The duration, dynamics and determinants of SARS-CoV-2 antibody responses in individual healthcare workers",Sheila F Lumley; Jia Wei; Nicole Stoesser; Philippa Matthews; Alison Howarth; Stephanie Hatch; Brian Marsden; Stuart Cox; Tim James; Liam Peck; Thomas Ritter; Zoe de Toledo; Richard Cornall; E Yvonne Jones; David I Stuart; Gavin Screaton; Daniel Ebner; Sarah Hoosdally; Derrick Crook; - Oxford University Hospitals Staff Testing Group; Christopher P Conlon; Koen Pouwels; Ann Sarah Walker; Tim EA Peto; Timothy M Walker; Katie Jeffery; David W Eyre,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; Oxford University Hospitals; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; ; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; University of Oxford,"BackgroundSARS-CoV-2 IgG antibody measurements can be used to estimate the proportion of a population exposed or infected and may be informative about the risk of future infection. Previous estimates of the duration of antibody responses vary. - -MethodsWe present 6 months of data from a longitudinal seroprevalence study of 3217 UK healthcare workers (HCWs). Serial measurements of IgG antibodies to SARS-CoV-2 nucleocapsid were obtained. Bayesian mixed linear models were used to investigate antibody waning and associations with age, gender, ethnicity, previous symptoms and PCR results. - -ResultsIn this cohort of working age HCWs, antibody levels rose to a peak at 24 (95% credibility interval, CrI 19-31) days post-first positive PCR test, before beginning to fall. Considering 452 IgG seropositive HCWs over a median of 121 days (maximum 171 days) from their maximum positive IgG titre, the mean estimated antibody half-life was 85 (95%CrI, 81-90) days. The estimated mean time to loss of a positive antibody result was 137 (95%CrI 127-148) days. We observed variation between individuals; higher maximum observed IgG titres were associated with longer estimated antibody half-lives. Increasing age, Asian ethnicity and prior self-reported symptoms were independently associated with higher maximum antibody levels, and increasing age and a positive PCR test undertaken for symptoms with longer antibody half-lives. - -ConclusionIgG antibody levels to SARS-CoV-2 nucleocapsid wane within months, and faster in younger adults and those without symptoms. Ongoing longitudinal studies are required to track the long-term duration of antibody levels and their association with immunity to SARS-CoV-2 reinfection. - -SummarySerially measured SARS-CoV-2 anti-nucleocapsid IgG titres from 452 seropositive healthcare workers demonstrate levels fall by half in 85 days. From a peak result, detectable antibodies last a mean 137 days. Levels fall faster in younger adults and following asymptomatic infection.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.10.28.20221804,2020-11-03,https://medrxiv.org/cgi/content/short/2020.10.28.20221804,"Genetic association analysis of SARS-CoV-2 infection in 455,838 UK Biobank participants",Jack A Kosmicki; Julie E Horowitz; Nilanjana Banerjee; Rouel Lanche; Anthony Marcketta; Evan Maxwell; Xiaodong Bai; Dylan Sun; Joshua D Backman; Deepika Sharma; Hyun M Kang; Colm O'Dushlaine; Ashish Yadav; Adam J Mansfield; Alexander H Li; Kyoko Watanabe; Lauren Gurski; Shane E McCarthy; Adam E Locke; Shareef Khalid; Sean O'Keeffe; Joelle Mbatchou; Olympe Chazara; Yunfeng Huang; Erika Kvikstad; Amanda O'Neill; Paul Nioi; Margaret M Parker; Slave Petrovski; Heiko Runz; Joseph Szustakowski; Quanli Wang; Emily Wong; Aldo Cordova-Palomera; Erin Smith; Sandor Szalma; Xiuwen Zheng; Sahar Esmaeli; Justin W Davis; Yi-Pin Lai; Xing Chen; Anne E Justice; Joseph B Leader; Tooraj Mirshahi; David J Carey; Anurag Verma; Marylyn D Ritchie; Giorgio Sirugo; Daniel J. Rader; Gundula Povysil; David B Goldstein; Krzysztof Kiryluk; Erola Pairo-Castineira; Konrad Rawlik; Dorota Pasko; Susan Walker; Alison Meynert; Athanasios Kousathanas; Loukas Moutsianas; Albert Tenesa; Mark Caulfield; Richard Scott; James F Wilson; J Kenneth Baillie; Guillaume Butler-Laporte; Tomoko Nakanishi; Mark Lathrop; J Brent Richards; Marcus Jones; Suganthi Balasubramanian; William Salerno; Alan Shuldiner; Jonathan Marchini; John Overton; Lukas Habegger; Michael Cantor; Jeffrey Reid; Aris Baras; Goncalo R Abecasis; Manuel A Ferreira,"Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; AstraZeneca; Biogen; Bristol Myers Squibb; AstraZeneca; Alnylam Pharmaceuticals; Alnylam Pharmaceuticals; AstraZeneca; Biogen; Bristol Myers Squibb; AstraZeneca; Takeda; Takeda; Takeda; Takeda; Abbvie; Abbvie; Abbvie; Pfizer; Pfizer; Geisinger Health; Geisinger Health System; Geisinger Health System; Geisinger Health System; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; Columbia University; Columbia University; Columbia University; University of Edinburgh; University of Edinburgh; Genomics England; Genomics England; University of Edinburgh; Genomics England; Genomics England; University of Edinburgh; Genomics England; Genomics England; University of Edinburgh; Roslin Institute, University of Edinburgh; McGill University; McGill University; McGill University; McGill University; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals; Regeneron Pharmaceuticals","Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease-19 (COVID-19), a respiratory illness that can result in hospitalization or death. We investigated associations between rare genetic variants and seven COVID-19 outcomes in 543,213 individuals, including 8,248 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome-wide or when specifically focusing on (i) 14 interferon pathway genes in which rare deleterious variants have been reported in severe COVID-19 patients; (ii) 167 genes located in COVID-19 GWAS risk loci; or (iii) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, with results publicly browsable at https://rgc-covid19.regeneron.com.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.10.29.20222414,2020-11-03,https://medrxiv.org/cgi/content/short/2020.10.29.20222414,How well does societal mobility restriction help control the COVID-19 pandemic? Evidence from real-time evaluation,Juhwan Oh; Hwa-Young Lee; Khuong Quynh Long; Jeffery F Marcuns; Chris Bullen; Osvaldo Enrique Artaza Barrios; Seung-sik Hwang; Young Sahng Suh; Judith McCool; S. Patrick Kaucher; Chang-Chung Chan; Soonman Kwon; Naoki Kondo; Hoang Van Minh; J. Robin Moon; Mikael Rostila; Ole F. Norheim; Myoungsoon You; Mellissa Withers; Mu Li; Eun-Jeung Lee; Caroline Benski; Soo Kyung Park; Eun-Woo Nam; Katie Gottschalk; Matthew M. Kavanagh; Tran Thi Giang Huong; Jong-Koo Lee; S.V. Subramanian; Lawrence O. Gostin; Martin McKee,"1. Harvard University T.H.Chan School of Public Health 2. Seoul National University College of Medicine; 1. Harvard University T H Chan School of Public Health 2. Institute of Convergence Science, Convergence Science Academy, Yonsei University,; Hanoi University of Public Health; Boston University School of Medicine; The University of Auckland School of Population Health; The University of the Americas; Seoul National University Graduate School of Public Health; Harvard University T.H.Chan School of Public Health; The University of Auckland School of Population Health; Mailman School of Public Health, Columbia University; National Taiwan University College of Public Health; Seoul National University Graduate School of Public Health; Kyoto University School of Public Health; Hanoi University of Public Health; City University of New York Graduate School of Public Health & Health Policy; Stockholm University; 1.University of Bergen 2. Harvard University T.H.Chan School of Public Health; Seoul National University Graduate School of Public Health; University of Southern California; The University of Sydney; Berlin Free University; University Hospital of Geneva; National Health Insurance Research Institute; Yonsei University, Wonju-campus; Georgetown University; Georgetown University; Hanoi Medical University; Seoul National University College of Medicine; Harvard University T.H.Chan School of Public Health; Georgetown University; London School of Hygiene and Tropical Medicine","ObjectivesTo determine the impact of restrictions on mobility on reducing transmission of COVID-19. @@ -4436,21 +4405,6 @@ C_LI ResultsFollowing the onset of the pandemic, the frequency of in-person contacts was significantly reduced compared to that in the previous year ({beta} coefficient: -5829.6 contacts, 95% CI -6919.5 to -4739.6, p<0.001), while the frequency of remote contacts significantly increased ({beta} coefficient: 3338.5 contacts, 95% CI 3074.4 to 3602.7, p<0.001). Rates of remote consultation were lower in older adults than in working age adults, children and adolescents. Despite this change in the type of patient contact, antipsychotic and mood stabiliser prescribing remained at similar levels. ConclusionsThe COVID-19 pandemic has been associated with a marked increase in remote consultation, particularly among younger patients. However, there was no evidence that this has led to changes in psychiatric prescribing. Nevertheless, further work is needed to ensure that older patients are able to access mental healthcare remotely.",psychiatry and clinical psychology,fuzzy,100,100 -medRxiv,10.1101/2020.10.26.20219550,2020-10-27,https://medrxiv.org/cgi/content/short/2020.10.26.20219550,Human movement can inform the spatial scale of interventions against COVID-19 transmission,Hamish Gibbs; Emily Nightingale; Yang Liu; James Cheshire; Leon Danon; Liam Smeeth; Carl AB Pearson; Chris Grundy; - LSHTM CMMID COVID-19 Working Group; Adam J Kucharski; Rosalind M Eggo,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University College London; University of Exeter; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; ; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine,"BackgroundIn 2020, the UK enacted an intensive, nationwide lockdown on March 23 to mitigate transmission of COVID-19. As restrictions began to ease, resurgences in transmission were targeted by geographically-limited interventions of various stringencies. Understanding the spatial scale of networks of human interaction, and how these networks change over time, is critical to inform interventions targeted at the most at-risk areas without unnecessarily restricting areas at low risk of resurgence. - -MethodsWe use detailed human mobility data aggregated from Facebook users to determine how the spatially-explicit network of movements changed before and during the lockdown period, in response to the easing of restrictions, and to the introduction of locally-targeted interventions. We also apply community detection techniques to the weighted, directed network of movements to identify geographically-explicit movement communities and measure the evolution of these community structures through time. - -FindingsWe found that the mobility network became more sparse and the number of mobility communities decreased under the national lockdown, a change that disproportionately affected long distance journeys central to the mobility network. We also found that the community structure of areas in which locally-targeted interventions were implemented following epidemic resurgence did not show reorganization of community structure but did show small decreases in indicators of travel outside of local areas. - -InterpretationWe propose that communities detected using Facebook or other mobility data be used to assess the impact of spatially-targeted restrictions and may inform policymakers about the spatial extent of human movement patterns in the UK. These data are available in near real-time, allowing quantification of changes in the distribution of the population across the UK, as well as changes in travel patterns to inform our understanding of the impact of geographically-targeted interventions. - -Putting Research Into ContextO_ST_ABSEvidence before this studyC_ST_ABSLarge-scale intensive interventions in response to the COVID-19 pandemic have been implemented globally, significantly affecting human movement patterns. Mobility data show spatially-explicit network structure, but it is not clear how that structure changed in response to national or locally-targeted interventions. - -Added value of this studyWe used daily mobility data aggregated from Facebook users to quantify changes in the travel network in the UK during the national lockdown, and in response to local interventions. We identified changes in human behaviour in response to interventions and identified the community structure inherent in these networks. This approach to understanding changes in the travel network can help quantify the extent of strongly connected communities of interaction and their relationship to the extent of spatially-explicit interventions. - -Implications of all the available evidenceWe show that spatial mobility data available in near real-time can give information on connectivity that can be used to understand the impact of geographically-targeted interventions and in the future, to inform spatially-targeted intervention strategies. - -Data SharingData used in this study are available from the Facebook Data for Good Partner Program by application. Code and supplementary information for this paper are available online (https://github.com/hamishgibbs/facebook_mobility_uk), alongside publication.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.10.26.20219642,2020-10-27,https://medrxiv.org/cgi/content/short/2020.10.26.20219642,A2B-COVID: A method for evaluating potential SARS-CoV-2 transmission events,Christopher J R Illingworth; William L Hamilton; Christopher H Jackson; Ashley Popay; Luke Meredith; Charlotte J Houldcroft; Myra Hosmillo; Aminu Jahun; Matthew Routledge; Ben Warne; Laura Caller; Sarah Caddy; Anna Yakovleva; Grant Hall; Fahad A Khokhar; Theresa Feltwell; Malte Pinckert; Iliana Georgana; Yasmin Chaudhry; Martin Curran; Surendra Parmar; Dominic Sparkes; Lucy Rivett; Nick K Jones; Sushmita Sridhar; Sally Forest; Tom Dymond; Kayleigh Grainger; Chris Workman; Effrossyni Gkrania-Klotsas; Nicholas M Brown; Michael Weekes; Stephen Baker; Sharon J Peacock; Theodore Gouliouris; Ian G. Goodfellow; Daniela de Angelis; M. Estee Torok,"MRC Biostatistics Unit, University of Cambridge; Department of Medicine, University of Cambridge; MRC Biostatistics Unit, University of Cambridge; Public Health England Field Epidemiology Unit, Cambridge; Department of Pathology, University of Cambridge; Department of Medicine, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Cambridge University Hospitals NHS Foundation Trust, Cambridge; Department of Medicine, University of Cambridge; Francis Crick Institute; Cambridge Institute for Therapeutic Immunology and Infectious Disease; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Medicine, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Public Health England Clinical Microbiology and Public Health Laboratory, Cambridge; Public Health England Clinical Microbiology and Public Health Laboratory, Cambridge; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Department of Medicine, University of Cambridge; Cambridge Institute for Therapeutic Immunology and Infectious Disease, Cambridge; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University; Cambridge University; Department of Medicine, University of Cambridge; Cambridge University Hospitals NHS Foundation Trust; University of Cambridge; MRC Biostatistics Unit, University of Cambridge; University of Cambridge","Identifying linked cases of infection is a key part of the public health response to viral infectious disease. Viral genome sequence data is of great value in this task, but requires careful analysis, and may need to be complemented by additional types of data. The Covid-19 pandemic has highlighted the urgent need for analytical methods which bring together sources of data to inform epidemiological investigations. We here describe A2B-COVID, an approach for the rapid identification of linked cases of coronavirus infection. Our method combines knowledge about infection dynamics, data describing the movements of individuals, and novel approaches to genome sequence data to assess whether or not cases of infection are consistent or inconsistent with linkage via transmission. We apply our method to analyse and compare data collected from two wards at Cambridge University Hospitals, showing qualitatively different patterns of linkage between cases on designated Covid-19 and non-Covid-19 wards. Our method is suitable for the rapid analysis of data from clinical or other potential outbreak settings.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.10.26.20219725,2020-10-27,https://medrxiv.org/cgi/content/short/2020.10.26.20219725,"Declining prevalence of antibody positivity to SARS-CoV-2: a community study of 365,000 adults",Helen Ward; Graham Cooke; Christina J Atchison; Matthew Whitaker; Joshua Elliott; Maya Moshe; Jonathan C Brown; Barney Flower; Anna Daunt; Kylie E. C. Ainslie; Deborah Ashby; Christl A. Donnelly; Steven Riley; Ara Darzi; Wendy Barclay; Paul Elliott,"Imperial College London; Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London","BackgroundThe prevalence and persistence of antibodies following a peak SARS-CoV-2 infection provides insights into its spread in the community, the likelihood of reinfection and potential for some level of population immunity. @@ -4507,13 +4461,6 @@ MethodsA graph network was constructed from the publicly available CORD-19 datab ResultsThe network shows connections between disease, medication and procedures identified from title and abstracts of 195,958 COVID-19 related publications (CORD-19 Dataset). Connections between terms with few publications, those unconnected to the main network and those irrelevant were not displayed. Nodes were coloured by knowledgebase and node size related to the number of publications containing the term. The dataset and visualisations made publicly accessible via a webtool. ConclusionKnowledge management approaches (text mining and graph networks) can effectively allow rapid navigation and exploration of entity interrelationships to improve understanding of diseases such as COVID-19.",health informatics,fuzzy,100,100 -medRxiv,10.1101/2020.10.12.20211227,2020-10-14,https://medrxiv.org/cgi/content/short/2020.10.12.20211227,High and increasing prevalence of SARS-CoV-2 swab positivity in England during end September beginning October 2020: REACT-1 round 5 updated report,Steven Riley; Kylie E. C. Ainslie; Oliver Eales; Caroline E Walters; Haowei Wang; Christina J Atchison; Claudio Fronterre; Peter J Diggle; Deborah Ashby; Christl A. Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott,"Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Lancaster University; Lancaster University; Imperial College London; Imperial College London; Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London School of Public Health","BackgroundREACT-1 is quantifying prevalence of SARS-CoV-2 infection among random samples of the population in England based on PCR testing of self-administered nose and throat swabs. Here we report results from the fifth round of observations for swabs collected from the 18th September to 5th October 2020. This report updates and should be read alongside our round 5 interim report. - -MethodsRepresentative samples of the population aged 5 years and over in England with sample size ranging from 120,000 to 175,000 people at each round. Prevalence of PCR-confirmed SARS-CoV-2 infection, estimation of reproduction number (R) and time trends between and within rounds using exponential growth or decay models. - -Results175,000 volunteers tested across England between 18th September and 5th October. Findings show a national prevalence of 0.60% (95% confidence interval 0.55%, 0.71%) and doubling of the virus every 29 (17, 84) days in England corresponding to an estimated national R of 1.16 (1.05, 1.27). These results correspond to 1 in 170 people currently swab-positive for the virus and approximately 45,000 new infections each day. At regional level, the highest prevalence is in the North West, Yorkshire and The Humber and the North East with strongest regional growth in North West, Yorkshire and The Humber and West Midlands. - -ConclusionRapid growth has led to high prevalence of SARS-CoV-2 virus in England, with highest rates in the North of England. Prevalence has increased in all age groups, including those at highest risk. Improved compliance with existing policy and, as necessary, additional interventions are required to control the spread of SARS-CoV-2 in the community and limit the numbers of hospital admissions and deaths from COVID-19.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.10.11.20210658,2020-10-14,https://medrxiv.org/cgi/content/short/2020.10.11.20210658,What is the evidence for transmission of COVID-19 by children in schools? A living systematic review,Wei Xu; Xue Li; Marshall Dozier; Yazhou He; Amir Kirolos; Zhongyu Lang; Catherine Mathews; Nandi Siegfried; Evropi Theodoratou,University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; South African Medical Research Council; South African Medical Research Council; University of Edinburgh,"BackgroundIt is of paramount importance to understand the transmission of SARS-CoV-2 in schools, which could support the decision-making about educational facilities closure or re-opening with effective prevention and control measures in place. MethodsWe conducted a systematic review and meta-analysis to investigate the extent of SARS-CoV-2 transmission in schools. We performed risk of bias evaluation of all included studies using the Newcastle-Ottawa Scale (NOS). @@ -4521,6 +4468,10 @@ MethodsWe conducted a systematic review and meta-analysis to investigate the ext Results2,178 articles were retrieved and 11 studies were included. Five cohort studies reported a combined 22 student and 21 staff index cases that exposed 3,345 contacts with 18 transmissions [overall infection attack rate (IAR): 0.08% (95% CI: 0.00%-0.86%)]. IARs for students and school staff were 0.15% (95% CI: 0.00%-0.93%) and 0.70% (95% CI: 0.00%-3.56%) respectively. Six cross-sectional studies reported 639 SARS-CoV-2 positive cases in 6,682 study participants tested [overall SARS-CoV-2 positivity rate: 8.00% (95% CI: 2.17%-16.95%)]. SARS-CoV-2 positivity rate was estimated to be 8.74% (95% CI: 2.34%-18.53%) among students, compared to 13.68% (95% CI: 1.68%-33.89%) among school staff. Gender differences were not found for secondary infection (OR: 1.44, 95% CI: 0.50-4.14, P= 0.49) and SARS-CoV-2 positivity (OR: 0.90, 95% CI: 0.72-1.13, P= 0.36) in schools. Fever, cough, dyspnea, ageusia, anosmia, rhinitis, sore throat, headache, myalgia, asthenia, and diarrhoea were all associated with the detection of SARS-CoV-2 antibodies (based on two studies). Overall, study quality was judged to be poor with risk of performance and attrition bias, limiting the confidence in the results. ConclusionsThere is limited high-quality evidence available to quantify the extent of SARS-CoV-2 transmission in schools or to compare it to community transmission. Emerging evidence suggests lower IAR and SARS-CoV-2 positivity rate in students compared to school staff. Future prospective and adequately controlled cohort studies are necessary to confirm this finding.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2020.10.13.20211813,2020-10-14,https://medrxiv.org/cgi/content/short/2020.10.13.20211813,"Precautionary breaks: planned, limited duration circuit breaks to control the prevalence of COVID-19",Matt J Keeling; Glen Guyver-Fletcher; Alexander Holmes; Louise J Dyson; Michael Tildesley; Edward M Hill; Graham F Medley,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; London School of Hygiene and Tropical Medicine,"The COVID-19 pandemic in the UK has been characterised by periods of exponential growth and decline, as different non-pharmaceutical interventions (NPIs) are brought into play. During the early uncontrolled phase of the outbreak (early March 2020) there was a period of prolonged exponential growth with epidemiological observations such as hospitalisation doubling every 3-4 days (growth rate r {approx} 0.2). The enforcement of strict lockdown measures led to a noticeable decline in all epidemic quantities (r {approx} -0.06) that slowed during the summer as control measures were relaxed (r {approx} -0.02). Since August, infections, hospitalisations and deaths have been rising (precise estimation of the current growth rate is difficult due to extreme regional heterogeneity and temporal lags between the different epidemiological observations) and various NPIs have been applied locally throughout the UK in response. + +Controlling any rise in infection is a compromise between public health and societal costs, with more stringent NPIs reducing cases but damaging the economy and restricting freedoms. Currently, NPI imposition is made in response to the epidemiological state, are of indefinite length and are often imposed at short notice, greatly increasing the negative impact. An alternative approach is to consider planned, limited duration periods of strict NPIs aiming to purposefully reduce prevalence before such emergency NPIs are required. These ""precautionary breaks"" may offer a means of keeping control of the epidemic, while their fixed duration and the forewarning may limit their society impact. Here, using simple analysis and age-structured models matched to the unfolding UK epidemic, we investigate the action of precautionary breaks. In particular we consider their impact on the prevalence of infection, as well as the total number of predicted hospitalisations and deaths. We find that precautionary breaks provide the biggest gains when the growth rate is low, but offer a much needed brake on increasing infection when the growth rate is higher, potentially allowing other measures (such as contact tracing) to regain control.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2020.10.11.20210625,2020-10-13,https://medrxiv.org/cgi/content/short/2020.10.11.20210625,Mental health service activity during COVID-19 lockdown among individuals with learning disabilities: South London and Maudsley data on services and mortality from January to July 2020,Evangelia Martin; Eleanor Nuzum; Matthew Broadbent; Robert Stewart,King's College London; King's College London; South London and Maudsley NHS Foundation Trust; King's College London,"The lockdown and social distancing policy imposed due to the COVID-19 pandemic is likely to have had a widespread impact on mental healthcare service provision and use. Previous reports from the South London and Maudsley NHS Trust (SLaM; a large mental health service provider for 1.2m residents in South London) highlighted a shift to virtual contacts among those accessing community mental health and home treatment teams and an increase in deaths over the pandemics first wave. However, there is a need to quantify this for individuals with particular vulnerabilities, including those with learning disabilities and other neurodevelopmental disorders. Taking advantage of the Clinical Record Interactive Search (CRIS) data resource with 24-hourly updates of electronic mental health records data, this paper describes daily caseloads and contact numbers (face-to-face and virtual) for individuals with potential neurodevelopmental disorders across community, specialist, crisis and inpatient services. The report focussed on the period 1st January to 31st July 2020. We also report on daily accepted and discharged trust referrals, total trust caseloads and daily inpatient admissions and discharges for individuals with potential neurodevelopmental disorders. In addition, daily deaths are described for all current and previous SLaM service users with potential neurodevelopmental disorders over this period. In summary, comparing periods before and after 16th March 2020 there was a shift from face-to-face contacts to virtual contacts across all teams. The largest declines in caseloads and total contacts were seen in Home Treatment Team, Liaison/A&E and Older Adult teams. Reduced accepted referrals and inpatient admissions were observed and there was an 103% increase in average daily deaths in the period after 16th March, compared to the period 1st January to 15th March (or a 282% increase if the 2-month period from 16th March to 15th May was considered alone).",psychiatry and clinical psychology,fuzzy,100,100 medRxiv,10.1101/2020.10.08.20209411,2020-10-13,https://medrxiv.org/cgi/content/short/2020.10.08.20209411,"Elevated antiviral, myeloid and endothelial inflammatory markers in severe COVID-19",Ryan Thwaites; Ashley Sanchez Sevilla Uruchurtu; Matthew Siggins; Felicity Liew; Clark D Russell; Shona Moore; Edwin Carter; Simon Abrams; Charlotte-Eve Short; Thilipan Thaventhiran; Emma Bergstrom; Zoe Gardener; Stephanie Ascough; Christopher Chiu; Annemarie B Docherty; David Hunt; Yanick Crow; Tom Solomon; Graham Taylor; Lance Turtle; Ewen M Harrison; Malcolm Gracie Semple; J Kenneth Baillie; Peter JM Openshaw,"Imperial College London; Imperial College London; Imperial College London; Imperial College London; University of Edinburgh; University of Liverpool; University of Edinburgh; University of Liverpool; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Liverpool; Imperial College London; University ofLiverpool; University of Edinburgh; University of Liverpool; Roslin Institute, University of Edinburgh; Imperial College London","Introductory paragraphThe mechanisms that underpin COVID-19 disease severity, and determine the outcome of infection, are only beginning to be unraveled. The host inflammatory response contributes to lung injury, but circulating mediators levels fall below those in classical cytokine storms. We analyzed serial plasma samples from 619 patients hospitalized with COVID-19 recruited through the prospective multicenter ISARIC clinical characterization protocol U.K. study and 39 milder community cases not requiring hospitalization. Elevated levels of numerous mediators including angiopoietin-2, CXCL10, and GM-CSF were seen at recruitment in patients who later died. Markers of endothelial injury (angiopoietin-2 and von-Willebrand factor A2) were detected early in some patients, while inflammatory cytokines and markers of lung injury persisted for several weeks in fatal COVID-19 despite decreasing antiviral cytokine levels. Overall, markers of myeloid or endothelial cell activation were associated with severe, progressive, and fatal disease indicating a central role for innate immune activation and vascular inflammation in COVID-19.",infectious diseases,fuzzy,91,100 medRxiv,10.1101/2020.10.09.20209957,2020-10-13,https://medrxiv.org/cgi/content/short/2020.10.09.20209957,Development and validation of the 4C Deterioration model for adults hospitalised with COVID-19,Rishi K Gupta; Ewen M Harrison; Antonia Ho; Annemarie B Docherty; Stephen R Knight; Maarten van Smeden; Ibrahim Abubakar; Marc Lipman; Matteo Quartagno; Riinu B Pius; Iain Buchan; Gail Carson; Thomas M Drake; Jake Dunning; Cameron J Fairfield; Carrol Gamble; Christopher A Green; Sophie Halpin; Hayley Hardwick; Karl Holden; Peter Horby; Clare Jackson; Kenneth McLean; Laura Merson; Jonathan S Nguyen-Van-Tam; Lisa Norman; Piero L Olliaro; Mark G Pritchard; Clark D Russell; James Scott-Brown; Catherine A Shaw; Aziz Sheikh; Tom Solomon; Cathie LM Sudlow; Olivia V Swann; Lance Turtle; Peter JM Openshaw; J Kenneth Baillie; Malcolm Gracie Semple; Mahdad Noursadeghi,"University College London; Centre for Medical Informatics, Usher Institute, University of Edinburgh, UK; Medical Research Council University of Glasgow Centre for Virus Research, Glasgow, UK; University of Edinburgh; Centre for Medical Informatics, The Usher Institute, University of Edinburgh; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands; Institute for Global Health, University College London, Gower Street, London, WC1E 6BT; UCL Respiratory, Division of Medicine, University College London, London, UK; MRC Clinical Trials Unit, Institute of Clinical Trials and Methodology, University College London, London, UK; University of Edinburgh; Institute of Population Health Sciences, University of Liverpool; University of Oxford; Centre for Medical Informatics, Usher Institute, University of Edinburgh, UK; National Infection Service Public Health England; Centre for Medical Informatics, Usher Institute, University of Edinburgh, UK; University of Liverpool; Institute of Microbiology & Infection, University of Birmingham; Liverpool Clinical Trials Centre, University of Liverpool, Liverpool, UK; University of Liverpool; University of Liverpool; ISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK; University of Liverpool; Centre for Medical Informatics, The Usher Institute, University of Edinburgh; University of Oxford; Division of Epidemiology and Public Health, University of Nottingham School of Medicine, Nottingham, UK; University of Edinburgh; University of Oxford; University of Oxford; Queens Medical Research Institute, University of Edinburgh, Edinburgh, UK; School of Informatics, University of Edinburgh, Edinburgh, UK; Department of Clinical Surgery, University of Edinburgh; Centre for Medical Informatics, The Usher Institute, University of Edinburgh; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life; University of Edinburgh; Department of Child Life and Health, University of Edinburgh, UK; Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK; Imperial College London; Roslin Institute, University of Edinburgh; University of Liverpool; Division of Infection and Immunity, University College London, Gower Street, London, WC1E 6BT","Prognostic models to predict the risk of clinical deterioration in acute COVID-19 are required to inform clinical management decisions. Among 75,016 consecutive adults across England, Scotland and Wales prospectively recruited to the ISARIC Coronavirus Clinical Characterisation Consortium (ISARIC4C) study, we developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) using 11 routinely measured variables. We used internal-external cross-validation to show consistent measures of discrimination, calibration and clinical utility across eight geographical regions. We further validated the final model in held-out data from 8,252 individuals in London, with similarly consistent performance (C-statistic 0.77 (95% CI 0.75 to 0.78); calibration-in-the-large 0.01 (-0.04 to 0.06); calibration slope 0.96 (0.90 to 1.02)). Importantly, this model demonstrated higher net benefit than using other candidate scores to inform decision-making. Our 4C Deterioration model thus demonstrates unprecedented clinical utility and generalisability to predict clinical deterioration among adults hospitalised with COVID-19.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.10.08.20209304,2020-10-12,https://medrxiv.org/cgi/content/short/2020.10.08.20209304,Prevalence of COVID-19-related risk factors and risk of severe influenza outcomes in cancer survivors: a matched cohort study using linked English electronic health records data,Helena Carreira; Helen Strongman; Maria Peppa; Helen I McDonald; Isabel dos-Santos-Silva; Susannah Stanway; Liam Smeeth; Krishnan Bhaskaran,"London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; NIHR Health Protection Research Unit in Immunisation; London School of Medicine and Tropical Medicine, NIHR Health Protection Research Unit in Immunisation; London School of Hygiene and Tropical Medicine; The Royal Marsden NHS Foundation Trust; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine","BackgroundPeople with active cancer are recognised as at risk of COVID-19 complications, but it is unclear whether the much larger population of cancer survivors is at elevated risk. We aimed to address this by comparing cancer survivors and cancer-free controls for (i) prevalence of comorbidities considered risk factors for COVID-19; and (ii) risk of severe influenza, as a marker of susceptibility to severe outcomes from epidemic respiratory viruses. @@ -4619,7 +4570,17 @@ We identify and replicate three novel genome-wide significant associations, at c We identify potential targets for repurposing of licensed medications. Using Mendelian randomisation we found evidence in support of a causal link from low expression of IFNAR2, and high expression of TYK2, to life-threatening disease. Transcriptome-wide association in lung tissue revealed that high expression of the monocyte/macrophage chemotactic receptor CCR2 is associated with severe Covid-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms, and mediators of inflammatory organ damage in Covid-19. Both mechanisms may be amenable to targeted treatment with existing drugs. Large-scale randomised clinical trials will be essential before any change to clinical practice.",intensive care and critical care medicine,fuzzy,100,100 -medRxiv,10.1101/2020.09.22.20194183,2020-09-24,https://medrxiv.org/cgi/content/short/2020.09.22.20194183,Modelling optimal vaccination strategy for SARS-CoV-2.,Sam Moore; Edward M Hill; Louise Dyson; Michael Tildesley; Matt J Keeling,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick,"The COVID-19 outbreak has highlighted our vulnerability to novel infections. Faced with this threat and no effective treatment, in line with many other countries, the UK adopted enforced social distancing (lockdown) to reduce transmission- successfully reducing the reproductive number, R, below one. However, given the large pool of susceptible individuals that remain, complete relaxation of controls is likely to generate a substantial second wave. Vaccination remains the only foreseeable means of both containing the infection and returning to normal interactions and behaviour. Here, we consider the optimal targeting of vaccination within the UK, with the aim of minimising future deaths or quality adjusted life year (QALY) losses. We show that, for a range of assumptions on the action and efficacy of the vaccine, targeting older age groups first is optimal and can avoid a second wave if the vaccine prevents transmission as well as disease.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2020.09.22.20199661,2020-09-23,https://medrxiv.org/cgi/content/short/2020.09.22.20199661,Risk of adverse COVID-19 outcomes for people living with HIV: a rapid review and meta-analysis,Maya Mellor; Anne Bast; Nicholas Jones; Nia Roberts; Jose Ordonez-Mena; Alastair Reith; Christopher C Butler; Philippa C Matthews; Jienchi Dorward,"Medical Sciences Division, University of Oxford, Oxford, UK; Medical Sciences Division, University of Oxford, Oxford, UK; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK; Outreach Librarian Knowledge Centre, Bodleian Health Care Libraries, Oxford, UK; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK and NIHR Biomedical Research Centre, Oxford University Hospitals NHS Found; Medical Sciences Division, University of Oxford, Oxford, UK; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.; Nuffield Department of Medicine, University of Oxford, Oxford, UK and Department of Infectious Diseases and Microbiology, Oxford University Hospitals NHS Founda; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK and Centre for the AIDS Programme of Research in South Africa, University ","ObjectiveTo assess whether people living with HIV (PLWH) are at increased risk of COVID-19 mortality or adverse outcomes, and whether antiretroviral therapy (ART) influences this risk. + +DesignRapid review with meta-analysis and narrative synthesis. + +MethodsWe searched databases including Embase, Medline, medRxiv, and Google Scholar up to 26th August 2020 for studies describing COVID-19 outcomes in PLWH and conducted a meta-analysis of higher quality studies. + +ResultsWe identified 1,908 studies and included 19 in the review. In a meta-analysis of five studies, PLWH had a higher risk of COVID-19 mortality (hazard ratio (HR) 1.93, 95% Confidence Interval (CI): 1.59-2.34) compared to people without HIV. Risk of death remained elevated for PLWH in a subgroup analysis of hospitalised cohorts (HR 1.54, 95% CI: 1.05-2.24) and studies of PLWH across all settings (HR 2.08, 95%CI: 1.69-2.56). Eight other studies assessed the association between HIV and COVID-19 outcomes, but provided inconclusive, lower-quality evidence due to potential confounding and selection bias. + +There were insufficient data on the effect of CD4+ T cell count and HIV viral load on COVID-19 outcomes. Eleven studies reported COVID-19 outcomes by ART-regimen. In the two largest studies, tenofovir-disoproxil-fumarate (TDF)-based regimens were associated with a lower risk of adverse COVID-19 outcomes, although these analyses are susceptible to confounding by comorbidities. + +ConclusionEvidence is emerging that suggests a moderately increased risk of COVID-19 mortality amongst PLWH. Further investigation into the relationship between COVID-19 outcomes and CD4+ T cell count, HIV viral load, ART and the use of TDF is warranted.",hiv aids,fuzzy,91,100 medRxiv,10.1101/2020.09.22.20198754,2020-09-23,https://medrxiv.org/cgi/content/short/2020.09.22.20198754,"Ethnic differences in COVID-19 infection, hospitalisation, and mortality: an OpenSAFELY analysis of 17 million adults in England",Rohini Mathur; Christopher T. Rentsch; Caroline Morton; William J Hulme; Anna Schultze; Brian MacKenna; Rosalind M Eggo; Krishnan Bhaskaran; Angel YS Wong; Elizabeth J Williamson; Harriet Forbes; Kevin Wing; Helen I McDonald; Chris Bates; Seb Bacon; Alex J Walker; David Evans; Peter Inglesby; Amir Mehrkar; Helen J Curtis; Nicholas J DeVito; Richard Croker; Henry Drysdale; Jonathan Cockburn; John Parry; Frank Hester; Sam Harper; Ian J Douglas; Laurie Tomlinson; Stephen Evans; Richard Grieve; David Harrison; Kathy Rowan; Kamlesh Khunti; Nish Chaturvedi; Liam Smeeth; Ben Goldacre,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Medicine and Tropical Medicine; The Phoenix Partnership; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; The Phoenix Partnership; The Phoenix Partnership; The Phoenix Partnership; The Phoenix Partnership; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Intensive Care National Audit and Research Centre; Intensive Care National Audit and Research Centre; University of Leicester; University College London; London School of Hygiene and Tropical Medicine; University of Oxford,"Background: COVID-19 has had a disproportionate impact on ethnic minority populations, both in the UK and internationally. To date, much of the evidence has been derived from studies within single healthcare settings, mainly those hospitalised with COVID-19. Working on behalf of NHS England, the aim of this study was to identify ethnic differences in the risk of COVID-19 infection, hospitalisation and mortality using a large general population cohort in England. Methods: We conducted an observational cohort study using linked primary care records of 17.5 million adults between 1 February 2020 and 3 August 2020. Exposure was self-reported ethnicity collapsed into the 5 and 16 ethnicity categories of the English Census. Multivariable Cox proportional hazards regression was used to identify ethnic differences in the risk of being tested and testing positive for SARS-CoV-2 infection, COVID-19 related intensive care unit (ICU) admission, and COVID-19 mortality, adjusted for socio-demographic factors, clinical co-morbidities, geographic region, care home residency, and household size. Results: A total of 17,510,002 adults were included in the study; 63% white (n=11,030,673), 6% south Asian (n=1,034,337), 2% black (n=344,889), 2% other (n=324,730), 1% mixed (n=172,551), and 26% unknown (n=4,602,822). After adjusting for measured explanatory factors, south Asian, black, and mixed groups were marginally more likely to be tested (south Asian HR 1.08, 95%CI 1.07-1.09; black HR 1.08; 95%CI 1.06-1.09, mixed HR 1.03, 95%CI 1.01-1.05), and substantially more likely to test positive for SARS-CoV-2 compared with white adults (south Asian HR 2.02. 95% CI 1.97-2.07; black HR 1.68, 95%CI 1.61-1.76; mixed HR 1.46, 95%CI 1.36-1.56). The risk of being admitted to ICU for COVID-19 was substantially increased in all ethnic minority groups compared with white adults (south Asian HR 2.22, 95%CI 1.96-2.52; black HR 3.07, 95%CI 2.61-3.61; mixed HR 2.86, 95%CI 2.19-3.75, other HR 2.86, 95%CI 2.31-3.63). Risk of COVID-19 mortality was increased by 25-56% in ethnic minority groups compared with white adults (south Asian HR 1.27, 95%CI 1.17-1.38; black HR 1.55, 95%CI 1.38-1.75; mixed HR 1.40, 95%CI 1.12-1.76; other HR 1.25, 95%CI 1.05-1.49). We observed heterogeneity of associations after disaggregation into detailed ethnic groupings; Indian and African groups were at higher risk of all outcomes; Pakistani, Bangladeshi and Caribbean groups were less or equally likely to be tested for SARS-CoV-2, but at higher risk of all other outcomes, Chinese groups were less likely to be tested for and test positive for SARS-CoV-2, more likely to be admitted to ICU, and equally likely to die from COVID-19. Conclusions: We found evidence of substantial ethnic inequalities in the risk of testing positive for SARS-CoV-2, ICU admission, and mortality, which persisted after accounting for explanatory factors, including household size. It is likely that some of this excess risk is related to factors not captured in clinical records such as occupation, experiences of structural discrimination, or inequitable access to health and social services. Prioritizing linkage between health, social care, and employment data and engaging with ethnic minority communities to better understand their lived experiences is essential for generating evidence to prevent further widening of inequalities in a timely and actionable manner.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.09.21.20194019,2020-09-23,https://medrxiv.org/cgi/content/short/2020.09.21.20194019,Putting (Big) Data in Action: Saving Lives with Countrywide Population Movement Monitoring Using Mobile Devices during the COVID-19 Crisis,Miklos Karoly Szocska; Peter Pollner; Istvan Schiszler; Tamas Joo; Tamas Palicz; Martin McKee; - Magyar Telekom Nyrt.; - Telenor Magyarorszag Zrt.; Adam Sohonyai; Jozsef Szoke; Adam Toth; Peter Gaal,"Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; University of London, London School of Hygiene and Tropical Medicine, Department of Health Services Research and Policy; ; ; Vodafone Hungary; Vodafone Hungary; Vodafone Hungary; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team","Many countries have implemented strict social distancing measures in the hope of reducing transmission of SARS-CoV-2 but the effectiveness of these measures is determined by the willingness of populations to comply with restrictions. Consequently, a system of monitoring population movement using existing data sources can inform those making decisions about policy responses to the COVID-19 pandemic. We describe a collaboration with all 3 major domestic telecommunication companies in Hungary to use aggregated anonymous mobile phone usage data to calculate two indices for assessing the effect of movement restrictions: a ""mobility-index"" and a ""stay-at-home (or resting) index"". The strengths and weaknesses of this approach are compared with the smartphone-based, COVID-19 Community Mobility Reports from Google. Data generated by mobile phones have long been identified as a potential means to analyse mass population movement, but its operationalisation raises several technical questions, such as making sense of Call Detail Records, collation of data from different mobile network providers, and personal data protection concerns. The method described here addresses these issues and offers an effective and inexpensive tool to monitor the impact of social distancing measures, achieving high levels of accuracy and resolution. Especially in populations where uptake of smartphones is modest, this method has certain advantages over app-based solutions, with greater population coverage, but it is not an alternative to smartphone-based solutions used for contact tracing and quarantine monitoring. We believe that this method can easily be adapted by other countries.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.09.21.20196428,2020-09-22,https://medrxiv.org/cgi/content/short/2020.09.21.20196428,"Sharing a household with children and risk of COVID-19: a study of over 300,000 adults living in healthcare worker households in Scotland",Rachael Wood; Emma C Thomson; Robert Galbraith; Ciara Gribben; David Caldwell; Jennifer Bishop; Martin Reid; Anoop Shah; Kate Templeton; David Goldberg; Chris Robertson; Sharon Hutchinson; Helen M Colhoun; Paul M McKeigue; David McAllister,"University of Edinburgh, Public Heath Scotland; University of Glasgow; Retired; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; London School of Hygiene and Tropical Medicine; University of Edinburgh; Public Health Scotland; Public Health Scotland; Public Health Scotland; University of Edinburgh; University of Edinburgh; University of Glasgow","ObjectiveChildren are relatively protected from COVID-19, possibly due to cross-protective immunity. We investigated if contact with children also affords adults a degree of protection from COVID-19. @@ -4689,6 +4650,17 @@ KEY POINTSO_ST_ABSQuestionC_ST_ABSIs ethnicity associated with vulnerability to, FindingsIn this systematic review and meta-analysis, rates of infection and outcomes from COVID-19 were compared between ethnic groups. Individuals from Black, Asian and Hispanic ethnicity were significantly more vulnerable to SARS-CoV-2 infection than those of White ethnicity. Black individuals were more likely to need intensive care unit (ICU) admission for COVID-19 than White individuals. Risk of mortality was similar across ethnicities among hospitalised patients, but increased among Asian and Mixed ethnic groups in the general population. MeaningThere is strong evidence for an increased risk of SARS-CoV-2 infection amongst ethnic minorities, and targeted public health policies are required to reduce this risk.",infectious diseases,fuzzy,100,100 +medRxiv,10.1101/2020.09.02.20185892,2020-09-07,https://medrxiv.org/cgi/content/short/2020.09.02.20185892,Prognostic accuracy of emergency department triage tools for adults with suspected COVID-19: The PRIEST observational cohort study,Ben Thomas; Steve Goodacre; Ellen Lee; Laura Sutton; Amanda Loban; Simon Waterhouse; Richard Simmonds; Katie Biggs; Carl Marincowitz; Jose Schutter; Sarah Connelly; Elena Sheldon; Jamie Hall; Emma Young; Andrew Bentley; Kirsty Challen; Chris Fitzsimmons; Tim Harris; Fiona Lecky; Andrew Lee; Ian Maconochie; Darren Walter,University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; Manchester University NHS Foundation Trust; Lancashire Teaching Hospitals NHS Foundation Trust; Sheffield Children's NHS Foundation Trust; Barts Health NHS Trust; University of Sheffield; University of Sheffield; Imperial College Healthcare NHS Trust; Manchester University NHS Foundation Trust,"ObjectivesThe World Health Organisation (WHO) and National Institute for Health and Care Excellence (NICE) recommend various triage tools to assist decision-making for patients with suspected COVID-19. We aimed to estimate the accuracy of triage tools for predicting severe illness in adults presenting to the emergency department (ED) with suspected COVID-19 infection. + +MethodsWe undertook a mixed prospective and retrospective observational cohort study in 70 EDs across the United Kingdom (UK). We collected data from people attending with suspected COVID-19 between 26 March 2020 and 28 May 2020, and used presenting data to determine the results of assessment with the following triage tools: the WHO algorithm, NEWS2, CURB-65, CRB-65, PMEWS and the swine flu adult hospital pathway (SFAHP). We used 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome. + +ResultsWe analysed data from 20892 adults, of whom 4672 (22.4%) died or received organ support (primary outcome), with 2058 (9.9%) receiving organ support and 2614 (12.5%) dying without organ support (secondary outcomes). C-statistics for the primary outcome were: CURB-65 0.75; CRB-65 0.70; PMEWS 0.77; NEWS2 (score) 0.77; NEWS2 (rule) 0.69; SFAHP (6-point) 0.70; SFAHP (7-point) 0.68; WHO algorithm 0.61. All triage tools showed worse prediction for receipt of organ support and better prediction for death without organ support. + +At the recommended threshold, PMEWS and the WHO criteria showed good sensitivity (0.96 and 0.95 respectively), at the expense of specificity (0.31 and 0.27 respectively). NEWS2 showed similar sensitivity (0.96) and specificity (0.28) when a lower threshold than recommended was used. + +ConclusionCURB-65, PMEWS and NEWS2 provide good but not excellent prediction for adverse outcome in suspected COVID-19, and predicted death without organ support better than receipt of organ support. PMEWS, the WHO criteria and NEWS2 (using a lower threshold than usually recommended) provide good sensitivity at the expense of specificity. + +RegistrationISRCTN registry, ISRCTN28342533, http://www.isrctn.com/ISRCTN28342533",emergency medicine,fuzzy,100,100 medRxiv,10.1101/2020.09.03.20187377,2020-09-05,https://medrxiv.org/cgi/content/short/2020.09.03.20187377,Impact of baseline cases of cough and fever on UK COVID-19 diagnostic testing rates: estimates from the Bug Watch community cohort study,Max T Eyre; Rachel Burns; Victoria Kirkby; Catherine Smith; Spiros Denaxas; Vincent Nguyen; Andrew Hayward; Laura Shallcross; Ellen Fragaszy; Robert W Aldridge,"Centre of Health Informatics, Computing and Statistics, Lancaster Medical School, Lancaster University, Lancaster, LA1 4YW, UK; Liverpool School of Tropical Med; Centre of Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK; Centre of Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK; Institute of Health Informatics, University College London, London, NW1 2DA, UK; Institute of Health Informatics, University College London, London, NW1 2DA, UK; Health Data Research UK, London, NW1 2DA, UK; The Alan Turing Institute, London; Centre of Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK; Institute of Epidemiology and Health Care; Institute of Epidemiology and Health Care, University College London, London, WC1E 7HB, UK; Institute of Health Informatics, University College London, London, NW1 2DA, UK; Institute of Health Informatics, University College London, London, NW1 2DA, UK; Faculty of Epidemiology and Population Health, London School of Hygiene and Tro; Centre of Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK","BackgroundDiagnostic testing forms a major part of the UKs response to the current COVID-19 pandemic with tests offered to people with a continuous cough, high temperature or anosmia. Testing capacity must be sufficient during the winter respiratory season when levels of cough and fever are high due to non-COVID-19 causes. This study aims to make predictions about the contribution of baseline cough or fever to future testing demand in the UK. MethodsIn this analysis of the Bug Watch prospective community cohort study, we estimated the incidence of cough or fever in England in 2018-2019. We then estimated the COVID-19 diagnostic testing rates required in the UK for baseline cough or fever cases for the period July 2020-June 2021. This was explored for different rates of the population requesting tests and four second wave scenarios and then compared to current national capacity. @@ -4815,6 +4787,13 @@ ConclusionsThe CovidNudge platform offers a sensitive, specific and rapid point Added value of this studyWe describe the development and clinical validation of COVID nudge, a novel point-of-care RT-PCR diagnostic, evaluated during the first wave of the SARS-CoV-2 epidemic. The platform is able to achieve high analytic sensitivity and specificity from dry swabs within a self-contained cartridge. The lack of downstream sample handling makes it suitable for use in a range of clinical settings, without need for a laboratory or specialized operator. Multiplexed assays within the cartridge allow inclusion of a positive human control, which reduces the false negative testing rate due to insufficient sampling. Implication of the available evidencePoint-of-care testing can relieve pressure on centralized laboratories and increase overall testing capacity, complementing existing approaches. These findings support a role for COVID Nudge as part of strategies to improve access to rapid diagnostics to SARS-CoV-2. Since May 2020, the system has been implemented in UK hospitals and is being rolled out nationwide.",infectious diseases,fuzzy,92,100 +medRxiv,10.1101/2020.08.12.20173690,2020-08-14,https://medrxiv.org/cgi/content/short/2020.08.12.20173690,"Antibody prevalence for SARS-CoV-2 in England following first peak of the pandemic: REACT2 study in 100,000 adults",Helen Ward; Christina J Atchison; Matthew Whitaker; Kylie E. C. Ainslie; Joshua Elliott; Lucy C Okell; Rozlyn Redd; Deborah Ashby; Christl A. Donnelly; Wendy Barclay; Ara Darzi; Graham Cooke; Steven Riley; Paul Elliott,"Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Dept Inf Dis Epi, Imperial College; Imperial College London","BackgroundEngland, UK has experienced a large outbreak of SARS-CoV-2 infection. As in USA and elsewhere, disadvantaged communities have been disproportionately affected. + +MethodsNational REal-time Assessment of Community Transmission-2 (REACT-2) prevalence study using a self-administered lateral flow immunoassay (LFIA) test for IgG among a random population sample of 100,000 adults over 18 years in England, 20 June to 13 July 2020. + +ResultsData were available for 109,076 participants, yielding 5,544 IgG positive results; adjusted (for test performance) and re-weighted (for sampling) prevalence was 6.0% (95% Cl: 5.8, 6.1). Highest prevalence was in London (13.0% [12.3, 13.6]), among people of Black or Asian (mainly South Asian) ethnicity (17.3% [15.8, 19.1] and 11.9% [11.0, 12.8] respectively) and those aged 18-24 years (7.9% [7.3, 8.5]). Adjusted odds ratio for care home workers with client-facing roles was 3.1 (2.5, 3.8) compared with non-essential workers. One third (32.2%, [31.0-33.4]) of antibody positive individuals reported no symptoms. Among symptomatic cases, most (78.8%) reported symptoms during the peak of the epidemic in England in March (31.3%) and April (47.5%) 2020. We estimate that 3.36 million (3.21, 3.51) people have been infected with SARS-CoV-2 in England to end June 2020, with an overall infection fatality ratio (IFR) of 0.90% (0.86, 0.94); age-specific IFR was similar among people of different ethnicities. + +ConclusionThe SARS-CoV-2 pandemic in England disproportionately affected ethnic minority groups and health and care home workers. The higher risk of infection in minority ethnic groups may explain their increased risk of hospitalisation and mortality from COVID-19.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.08.13.20174227,2020-08-14,https://medrxiv.org/cgi/content/short/2020.08.13.20174227,Long-Term Exposure to Outdoor Air Pollution and COVID-19 Mortality: an ecological analysis in England,Zhiqiang Feng; Mark Cherrie; Chris DIBBEN,University of Edinburgh; University of Edinburgh; University of Edinburgh,"There is an urgent need to examine what individual and environmental risk factors are associated with COVID-19 mortality. This objective of this study is to investigate the association between long term exposure to air pollution and COVID-19 mortality. We conducted a nationwide, ecological study using zero-inflated negative binomial models to estimate the association between long term (2014-2018) small area level exposure to NOx, PM2.5, PM10 and SO2 and COVID-19 mortality rates in England adjusting for socioeconomic factors and infection exposure. We found that all four pollutant concentrations were positively associated with COVID-19 mortality. The increase in mortality risk ratio per inter quarter range increase was for PM2.5:11%, 95%CIs 6%-17%), PM10 (5%; 95%CIs 1%-11%), NOx (11%, 95%CIs 6%-15%) and SO2 (7%, 95%CIs 3%-11%) were respectively in adjusted models. Public health intervention may need to protect people who are in highly polluted areas from COVID-19 infections.",occupational and environmental health,fuzzy,100,100 medRxiv,10.1101/2020.08.12.20171405,2020-08-14,https://medrxiv.org/cgi/content/short/2020.08.12.20171405,OpenSAFELY: Do adults prescribed Non-steroidal anti-inflammatory drugs have an increased risk of death from COVID-19?,Angel YS Wong; Brian MacKenna; Caroline Morton; Anna Schultze; Alex J Walker; Krishnan Bhaskaran; Jeremy Brown; Christopher T. Rentsch; Elizabeth Williamson; Henry Drysdale; Richard Croker; Seb Bacon; William Hulme; Chris Bates; Helen J Curtis; Amir Mehrkar; David Evans; Peter Inglesby; Jonathan Cockburn; Helen McDonald; Laurie Tomlinson; Rohini Mathur; Kevin Wing; Harriet Forbes; John Parry; Frank Hester; Sam Harper; Stephen Evans; Liam Smeeth; Ian Douglas; Ben Goldacre,"London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; US Department of Veterans Affairs, London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; TPP; TPP; TPP; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford","ImportanceThere has been speculation that non-steroidal anti-inflammatory drugs (NSAIDs) may negatively affect coronavirus disease 2019 (COVID-19) outcomes, yet clinical evidence is limited. @@ -5060,17 +5039,6 @@ Results2,075/9,339 residents developed COVID-19 symptoms (22.2% [95% confidence 217/607 residents with confirmed infection died (case-fatality rate: 35.7% [31.9%; 39.7%]). Mortality in residents with no direct evidence of infection was two-fold higher in care homes with outbreaks versus those without (adjusted HR 2.2 [1.8; 2.6]). ConclusionsFindings suggest many deaths occurred in people who were infected with COVID-19, but not tested. Higher occupancy and lower staffing levels were independently associated with risks of infection. Protecting staff and residents from infection requires regular testing for COVID-19 and fundamental changes to staffing and care home occupancy.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2020.07.15.20151852,2020-07-15,https://medrxiv.org/cgi/content/short/2020.07.15.20151852,"Effect of Hydroxychloroquine in Hospitalized Patients with COVID-19: Preliminary results from a multi-centre, randomized, controlled trial.",Peter Horby; Marion Mafham; Louise Linsell; Jennifer L Bell; Natalie Staplin; Jonathan R Emberson; Martin Wiselka; Andrew Ustianowski; Einas Elmahi; Benjamin Prudon; Anthony Whitehouse; Timothy Felton; John Williams; Jakki Faccenda; Jonathan Underwood; J Kenneth Baillie; Lucy Chappell; Saul N Faust; Thomas Jaki; Katie Jeffery; Wei Shen Lim; Alan Montgomery; Kathryn Rowan; Joel Tarning; James A Watson; Nicholas J White; Edmund Juszczak; Richard Haynes; Martin J Landray,"Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; University Hospitals fo Leicester NHS Trust and University of Leicester; Regional Infectious Diseases Unit, North Manchester General Hospital & University of Manchester, Manchester, UK; Research and Development Department, Northampton General Hospital, Northampton, United Kingdom; Department of Respiratory Medicine, North Tees & Hartlepool NHS Foundation Trust, Stockton-on-Tees, United Kingdom; University Hospitals Birmingham NHS Foundation Trust and Institute of Microbiology & Infection, University of Birmingham, United Kingdom; Univeristy of Manchester and Manchester University NHS Foundation Trust, Manchester, United Kingdom; James Cook University Hospital, Middlesbrough, United Kingdom; North West Anglia NHS Foundation Trust, Peterborough, United Kingdom; Department of Infectious Diseases, Cardiff and Vale University Health Board; Division of Infection and Immunity, Cardiff University, Cardiff, United Kingdom; Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom; School of Life Sciences, King's College London, London, United Kingdom; NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, ; Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom; MRC Biostatistics Unit, University of Cambridge, Cambridge, United Ki; Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; Respiratory Medicine Department, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; Intensive Care National Audit & Research Centre, London, United Kingdom; Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Centre for Tropical Medicine and Global Hea; Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Centre for Tropical Medicine and Global Hea; Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Centre for Tropical Medicine and Global Hea; Nuffield Department of Population Health, University of Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom","BackgroundHydroxychloroquine and chloroquine have been proposed as treatments for coronavirus disease 2019 (COVID-19) on the basis of in vitro activity, uncontrolled data, and small randomized studies. - -MethodsThe Randomised Evaluation of COVID-19 therapy (RECOVERY) trial is a randomized, controlled, open-label, platform trial comparing a range of possible treatments with usual care in patients hospitalized with COVID-19. We report the preliminary results for the comparison of hydroxychloroquine vs. usual care alone. The primary outcome was 28-day mortality. - -Results1561 patients randomly allocated to receive hydroxychloroquine were compared with 3155 patients concurrently allocated to usual care. Overall, 418 (26.8%) patients allocated hydroxychloroquine and 788 (25.0%) patients allocated usual care died within 28 days (rate ratio 1.09; 95% confidence interval [CI] 0.96 to 1.23; P=0.18). Consistent results were seen in all pre-specified subgroups of patients. Patients allocated to hydroxychloroquine were less likely to be discharged from hospital alive within 28 days (60.3% vs. 62.8%; rate ratio 0.92; 95% CI 0.85-0.99) and those not on invasive mechanical ventilation at baseline were more likely to reach the composite endpoint of invasive mechanical ventilation or death (29.8% vs. 26.5%; risk ratio 1.12; 95% CI 1.01-1.25). There was no excess of new major cardiac arrhythmia. - -ConclusionsIn patients hospitalized with COVID-19, hydroxychloroquine was not associated with reductions in 28-day mortality but was associated with an increased length of hospital stay and increased risk of progressing to invasive mechanical ventilation or death. - -FundingMedical Research Council and NIHR (Grant ref: MC_PC_19056). - -Trial registrationsThe trial is registered with ISRCTN (50189673) and clinicaltrials.gov (NCT04381936).",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.07.13.20152793,2020-07-14,https://medrxiv.org/cgi/content/short/2020.07.13.20152793,At what times during infection is SARS-CoV-2 detectable and no longer detectable using RT-PCR based tests?: A systematic review of individual participant data,Sue Mallett; Joy Allen; Sara Graziadio; Stuart A Taylor; Naomi S Sakai; Kile Green; Jana Suklan; Chris Hyde; Bethany Shinkins; Zhivko Zhelev; Jaime Peters; Philip Turner; Nia W Roberts; Lavinia Ferrante di Ruffano; Robert Wolff; Penny Whiting; Amanda Winter; Gauraang Bhatnagar; Brian D Nicholson; Steve Halligan,"University College London, UK; Newcastle University, UK; Newcastle upon Tyne Hospitals NHS Foundation Trust, UK; University College London, UK; University College London, UK; Newcastle University, UK; Newcastle University, UK; University of Exeter, UK; University of Leeds, UK; University of Exeter, UK; University of Exeter, UK; University of Oxford, UK; University of Oxford, UK; University of Birmingham, UK; Kleijnen Systematic Reviews Ltd, UK; University of Bristol, UK; Newcastle University, UK; Frimley Health NHS Foundation Trust, UK; University of Oxford, UK; University College London, UK","STRUCTURED SUMMARYO_ST_ABSBackgroundC_ST_ABSTests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral ribonucleic acid (RNA), using reverse transcription polymerase chain reaction (RT-PCR) are pivotal to detecting current coronavirus disease (COVID-19) and duration of detectable virus indicating potential for infectivity. MethodsWe conducted an individual participant data (IPD) systematic review of longitudinal studies of RT-PCR test results in symptomatic SARS-CoV-2. We searched PubMed, LitCOVID, medRxiv and COVID-19 Living Evidence databases. We assessed risk of bias using a QUADAS- 2 adaptation. Outcomes were the percentage of positive test results by time and the duration of detectable virus, by anatomical sampling sites. @@ -5180,7 +5148,6 @@ MethodsWe calculated survival curves and adjusted Cox proportional hazards model ResultsSurvival curves show an increased proportion of deaths between 23rd March and 14th June 2020 in care homes for older people, with an adjusted HR of 1{middle dot}72 (1{middle dot}55, 1{middle dot}90) compared to 2016. Compared to the general population in 2016-2019, adjusted care home mortality HRs for older adults rose from 2{middle dot}15 (2{middle dot}11,2{middle dot}20) in 2016-2019 to 2{middle dot}94 (2{middle dot}81,3{middle dot}08) in 2020. ConclusionsThe survival curves and increased HRs show a significantly increased risk of death in the 2020 study periods.",public and global health,fuzzy,100,100 -bioRxiv,10.1101/2020.07.01.182709,2020-07-01,https://biorxiv.org/cgi/content/short/2020.07.01.182709,Genetic architecture of host proteins interacting with SARS-CoV-2,Maik Pietzner; Eleanor Wheeler; Julia Carrasco-Zanini; Johannes Raffler; Nicola D. Kerrison; Erin Oerton; Victoria P.W. Auyeung; Chris Finan; Juan P. Casas; Rachel Ostroff; Steve A. Williams; Gabi Kastenmüller; Markus Ralser; Eric G. Gamazon; Nicholas J. Wareham; Aroon Dinesh Hingorani; Claudia Langenberg,University of Cambridge; University of Cambridge; University of Cambridge; Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH); University of Cambridge; University of Cambridge; University of Cambridge; University College London; Harvard Medical School; SomaLogic Inc.; SomaLogic Inc.; Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH); The Francis Crick Institute; Vanderbilt University Medical Center; University of Cambridge; University College London; University of Cambridge,"Strategies to develop therapeutics for SARS-CoV-2 infection may be informed by experimental identification of viral-host protein interactions in cellular assays and measurement of host response proteins in COVID-19 patients. Identification of genetic variants that influence the level or activity of these proteins in the host could enable rapid in silico assessment in human genetic studies of their causal relevance as molecular targets for new or repurposed drugs to treat COVID-19. We integrated large-scale genomic and aptamer-based plasma proteomic data from 10,708 individuals to characterize the genetic architecture of 179 host proteins reported to interact with SARS-CoV-2 proteins or to participate in the host response to COVID-19. We identified 220 host DNA sequence variants acting in cis (MAF 0.01-49.9%) and explaining 0.3-70.9% of the variance of 97 of these proteins, including 45 with no previously known protein quantitative trait loci (pQTL) and 38 encoding current drug targets. Systematic characterization of pQTLs across the phenome identified protein-drug-disease links, evidence that putative viral interaction partners such as MARK3 affect immune response, and establish the first link between a recently reported variant for respiratory failure of COVID-19 patients at the ABO locus and hypercoagulation, i.e. maladaptive host response. Our results accelerate the evaluation and prioritization of new drug development programmes and repurposing of trials to prevent, treat or reduce adverse outcomes. Rapid sharing and dynamic and detailed interrogation of results is facilitated through an interactive webserver (https://omicscience.org/apps/covidpgwas/).",genomics,fuzzy,100,100 medRxiv,10.1101/2020.06.29.20142448,2020-06-30,https://medrxiv.org/cgi/content/short/2020.06.29.20142448,Using past and current data to estimate potential crisis service use in mental healthcare after the COVID-19 lockdown: South London and Maudsley data,Robert Stewart; Matthew Broadbent,King's College London; South London and Maudsley NHS Foundation Trust,"The lockdown policy response to the COVID-19 pandemic in the UK has a potentially important impact on provision of mental healthcare with uncertain consequences over the 12 months ahead. Past activity may provide a means to predict future demand. Taking advantage of the Clinical Record Interactive Search (CRIS) data resource at the South London and Maudsley NHS Trust (SLaM; a large mental health service provider for 1.2m residents in south London), we carried out a range of descriptive analyses to inform the Trust on patient groups who might be most likely to require inpatient and home treatment team (HTT) crisis care. We considered the 12 months following UK COVID-19 lockdown policy on 16th March, drawing on comparable findings from previous years, and quantified levels of change in service delivery to those most likely to receive crisis care. For 12-month crisis days from 16th March in 2015-19, we found that most (over 80%) were accounted for by inpatient care (rather than HTT), most (around 75%) were used by patients who were current or recent Trust patients at the commencement of follow-up, and highest numbers were used by patients with a previously recorded schizophreniform disorder diagnosis. For current/recent patients on 16th March there had been substantial reductions in use of inpatient care in the following 31 days in 2020, more than previous years; changes in total non-inpatient contact numbers did not differ in 2020 compared to previous years, although there had been a marked switch from face-to-face to virtual contacts.",psychiatry and clinical psychology,fuzzy,100,100 medRxiv,10.1101/2020.06.28.20141986,2020-06-29,https://medrxiv.org/cgi/content/short/2020.06.28.20141986,Protocol for the development and evaluation of a tool for predicting risk of short-term adverse outcomes due to COVID-19 in the general UK population,Julia Hippisley-Cox; Ashley Kieran Clift; Carol AC Coupland; Ruth Keogh; Karla Diaz-Ordaz; Elizabeth Williamson; Ewen Harrison; Andrew Hayward; Harry Hemingway; Peter Horby; Nisha Mehta; Jonathan Kieran Benger; Kamlesh Khunti; David Spiegelhalter; Aziz Sheikh; Jonathan Valabhji; Ronan A Lyons; John Robson; Malcolm Gracie Semple; Frank Kee; Peter Johnson; Susan Jebb; Tony Williams; David Coggon,"University of Oxford; University of Oxford; University of Nottingham; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Edinburgh; University College London; University College London; University of Oxford; Department of Health and Social Care; NHS Digital; University of Leicester; University of Cambridge; University of Edinburgh; Imperial College London; Swansea University; Queen Mary University London; University of Liverpool; Queen's University Belfast; University of Southampton; University of Oxford; Working Fit, Ltd.; University of Southampton","IntroductionNovel coronavirus 2019 (COVID-19) has propagated a global pandemic with significant health, economic and social costs. Emerging emergence has suggested that several factors may be associated with increased risk from severe outcomes or death from COVID-19. Clinical risk prediction tools have significant potential to generate individualised assessment of risk and may be useful for population stratification and other use cases. @@ -5192,13 +5159,6 @@ Strengths and limitations of the studyO_LIThe individual-level linkage of genera C_LIO_LIThe models will be trained and evaluated in population-representative datasets of millions of individuals C_LIO_LIShielding for clinically extremely vulnerable was advised and in place during the study period, therefore risk predictions influenced by the presence of some shielding conditions may require careful consideration C_LI",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2020.06.26.20140921,2020-06-28,https://medrxiv.org/cgi/content/short/2020.06.26.20140921,Short Communication: Vitamin D and COVID-19 infection and mortality in UK Biobank,Claire E Hastie; Jill P Pell; Naveed Sattar,University of Glasgow; University of Glasgow; University of Glasgow,"PurposeVitamin D has been proposed as a potential causal factor in COVID-19 risk. We aimed to establish whether blood 25-hydroxyvitamin D (25(OH)D) concentration was associated with COVID-19 mortality, and inpatient confirmed COVID-19 infection, in UK Biobank participants. - -MethodsUK Biobank recruited 502,624 participants aged 37-73 years between 2006 and 2010. Baseline exposure data, including 25(OH)D concentration, were linked to COVID-19 mortality. Univariable and multivariable Cox proportional hazards regression analyses were performed for the association between 25(OH)D and COVID-19 death, and poisson regression analyses for the association between 25(OH)D and severe COVID-19 infection. - -ResultsComplete data were available for 341,484 UK Biobank participants, of which 656 had inpatient confirmed COVID-19 infection and 203 died of COVID-19 infection. Vitamin D was associated with severe COVID-19 infection and mortality univariably (mortality HR=0.99; 95% CI 0.98-0.998; p=0.016), but not after adjustment for confounders (mortality HR=0.998; 95% CI=0.99-1.01; p=0.696). - -ConclusionsOur findings do not support a potential link between vitamin D concentrations and risk of severe COVID-19 infection and mortality. Recommendations for vitamin D supplementation to lessen COVID-19 risks may provide false reassurance.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.06.26.20139873,2020-06-28,https://medrxiv.org/cgi/content/short/2020.06.26.20139873,Secondary pneumonia in critically ill ventilated patients with COVID-19,Mailis Maes; Ellen Higginson; Joana Pereira Dias; Martin D Curran; Surendra Parmar; Fahad Khokhar; Delphine Cuchet-Lourenço; Janine Lux; Sapna Sharma-Hajela; Benjamin Ravenhill; Razeen Mahroof; Amelia Solderholm; Sally Forrest; Sushmita Sridhar; Nicholas M Brown; Stephen Baker; Vilas Navapurkar; Gordon Dougan; Josefin Bartholdson Scott; Andrew Conway Morris,"Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Department of Medicine, University of Cambridge, Cambridge, United Kingdom; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Department of Medicine, University of Cambridge, Cambridge, United Kingdom; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Department of Medicine, University of Cambridge, Cambridge, United Kingdom; Public Health England, Clinical Microbiology and Public Health Laboratory, Addenbrookes Hospital, Cambridge, United Kingdom; Public Health England, Clinical Microbiology and Public Health Laboratory, Addenbrookes Hospital, Cambridge, United Kingdom; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Department of Medicine, University of Cambridge, Cambridge, United Kingdom; Department of Medicine, University of Cambridge, Cambridge, United Kingdom; Department of Medicine, University of Cambridge, Cambridge, United Kingdom; John Farman ICU, Addenbrookes Hospital, Cambridge, United Kingdom; John Farman ICU, Addenbrookes Hospital, Cambridge, United Kingdom; John Farman ICU, Addenbrookes Hospital, Cambridge, United Kingdom; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Department of Medicine, University of Cambridge, Cambridge, United Kingdom; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Department of Medicine, University of Cambridge, Cambridge, United Kingdom; Wellcome Sanger Insitute, Hinxton, United Kingdom; Public Health England, Clinical Microbiology and Public Health Laboratory, Addenbrookes Hospital, Cambridge, United Kingdom; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Department of Medicine, University of Cambridge, Cambridge, United Kingdom; John Farman ICU, Addenbrookes Hospital, Cambridge, United Kingdom; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Department of Medicine, University of Cambridge, Cambridge, United Kingdom; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Department of Medicine, University of Cambridge, Cambridge, United Kingdom; University of Cambridge","BackgroundPandemic COVID-19 caused by the coronavirus SARS-CoV-2 has a high incidence of patients with severe acute respiratory syndrome (SARS). Many of these patients require admission to an intensive care unit (ICU) for invasive artificial ventilation and are at significant risk of developing a secondary, ventilator-associated pneumonia (VAP). ObjectivesTo study the incidence of VAP, as well as differences in secondary infections, and bacterial lung microbiome composition of ventilated COVID-19 and non-COVID-19 patients. @@ -5208,21 +5168,6 @@ MethodsIn this prospective observational study, we compared the incidence of VAP ResultsWe observed a higher percentage of confirmed VAP in COVID-19 patients. However, there was no statistical difference in the detected organisms or pulmonary microbiome when compared to non-COVID-19 patients. ConclusionCOVID-19 makes people more susceptible to developing VAP, partly but not entirely due to the increased duration of ventilation. The pulmonary dysbiosis caused by COVID-19, and the array of secondary infections observed are similar to that seen in critically ill patients ventilated for other reasons.",intensive care and critical care medicine,fuzzy,100,100 -medRxiv,10.1101/2020.06.24.20139048,2020-06-25,https://medrxiv.org/cgi/content/short/2020.06.24.20139048,A geotemporal survey of hospital bed saturation across England during the first wave of the COVID-19 Pandemic,Bilal A Mateen; Harrison Wilde; John m Dennis; Andrew Duncan; Nicholas John Meyrick Thomas; Andrew P McGovern; Spiros Denaxas; Matt J Keeling; Sebastian J Vollmer,"The Alan Turing Institute; University of Warwick; Kings College Hospital NHS Foundation Trust; University of Warwick, Department of Statistics; University of Exeter Medical School; The Alan Turing Institute; Imperial College London, Faculty of Natural Sciences; University of Exeter Medical School; Royal Devon and Exeter NHS Foundation Trust, Diabetes and Endocrinology; University of Exeter Medical School; University College London; University of Warwick; The Alan Turing Institute; University of Warwick, Department of Statistics","BackgroundNon-pharmacological interventions were introduced based on modelling studies which suggested that the English National Health Service (NHS) would be overwhelmed by the COVID-19 pandemic. In this study, we describe the pattern of bed occupancy across England during the first wave of the pandemic, January 31st to June 5th 2020. - -MethodsBed availability and occupancy data was extracted from daily reports submitted by all English secondary care providers, between 27-Mar and 5-June. Two thresholds for safe occupancy were utilized (85% as per Royal College of Emergency Medicine and 92% as per NHS Improvement). - -FindingsAt peak availability, there were 2711 additional beds compatible with mechanical ventilation across England, reflecting a 53% increase in capacity, and occupancy never exceeded 62%. A consequence of the repurposing of beds meant that at the trough, there were 8{middle dot}7% (8,508) fewer general and acute (G&A) beds across England, but occupancy never exceeded 72%. The closest to (surge) capacity that any trust in England reached was 99{middle dot}8% for general and acute beds. For beds compatible with mechanical ventilation there were 326 trust-days (3{middle dot}7%) spent above 85% of surge capacity, and 154 trust-days (1{middle dot}8%) spent above 92%. 23 trusts spent a cumulative 81 days at 100% saturation of their surge ventilator bed capacity (median number of days per trust = 1 [range: 1 to 17]). However, only 3 STPs (aggregates of geographically co-located trusts) reached 100% saturation of their mechanical ventilation beds. - -InterpretationThroughout the first wave of the pandemic, an adequate supply of all bed-types existed at a national level. Due to an unequal distribution of bed utilization, many trusts spent a significant period operating above safe-occupancy thresholds, despite substantial capacity in geographically co-located trusts; a key operational issue to address in preparing for a potential second wave. - -FundingThis study received no funding. - -Research In ContextO_ST_ABSEvidence Before This StudyC_ST_ABSWe identified information sources describing COVID-19 related bed and mechanical ventilator demand modelling, as well as bed occupancy during the first wave of the pandemic by performing regular searches of MedRxiv, PubMed and Google, using the terms COVID-19, mechanical ventilators, bed occupancy, England, UK, demand, and non-pharmacological interventions (NPIs), until June 20th, 2020. Two UK-specific studies were found that modelled the demand for mechanical ventilators, one of which incorporated sensitivity analysis based on the introduction of NPIs and found that their effects might prevent the healthcare system being overwhelmed. Separately, several news reports were found pertaining to a single hospital that reached ventilator capacity in England during the first wave of the pandemic, however, no single authoritative source was identified detailing impact across all hospital sites in England. - -Added Value of This StudyThis national study of hospital-level bed occupancy in England provides unique and timely insight into bed-specific resource utilization during the first wave of the COVID-19 pandemic, nationally, and by specific (geographically defined) health footprints. We found evidence of an unequal distribution of resource utilization across England. Although occupancy of beds compatible with mechanical ventilation never exceeded 62% at the national level, 52 (30%) hospitals across England reached 100% saturation at some point during the first wave of the pandemic. Close examination of the geospatial data revealed that in the vast majority of circumstances there was relief capacity in geographically co-located hospitals. Over the first wave it was theoretically possible to markedly reduce (by 95.1%) the number of hospitals at 100% saturation of their mechanical ventilator bed capacity by redistributing patients to nearby hospitals. - -Implications Of All The Available EvidenceNow-casting using routinely collected administrative data presents a robust approach to rapidly evaluate the effectiveness of national policies introduced to prevent a healthcare system being overwhelmed in the context of a pandemic illness. Early investment in operational field hospital and an independent sector network may yield more overtly positive results in the winter, when G&A occupancy-levels regularly exceed 92% in England, however, during the first wave of the pandemic they were under-utilized. Moreover, in the context of the non-pharmacological interventions utilized during the first wave of COVID-19, demand for beds and mechanical ventilators was much lower than initially predicted, but despite this many trust spent a significant period of time operating above safe-occupancy thresholds. This finding demonstrates that it is vital that future demand (prediction) models reflect the nuances of local variation within a healthcare system. Failure to incorporate such geographical variation can misrepresent the likelihood of surpassing availability thresholds by averaging out over regions with relatively lower demand, and presents a key operational issue for policymakers to address in preparing for a potential second wave.",health systems and quality improvement,fuzzy,100,100 medRxiv,10.1101/2020.06.21.20136853,2020-06-23,https://medrxiv.org/cgi/content/short/2020.06.21.20136853,Modelling the impact of lockdown easing measures on cumulative COVID-19 cases and deaths in England,Hisham Ziauddeen; Naresh Subramaniam; Deepti Gurdasani,"Dept. of Psychiatry, University of Cambridge, Cambridge, UK; Dept. of Psychiatry, University of Cambridge, Cambridge UK; Queen Mary University of London","BackgroundAs countries begin to ease the lockdown measures instituted to control the COVID-19 pandemic, there is a risk of a resurgence of the pandemic, and early reports of this are already emerging from some countries. Unlike many other countries, the UK started easing lockdown in England when levels of community transmission were still high, and this could have a major impact on case numbers and deaths. However thus far, the likely impacts of easing restrictions at this point in the pandemic have not been quantified. Using a Bayesian model, we assessed the potential impacts of successive lockdown easing measures in England, focussing on scenarios where the reproductive number (R) remains [≤]1 in line with the UK governments stated aim. MethodsWe developed a Bayesian model to infer incident cases and R in England, from incident death data from the Office of National Statistics. We then used this to forecast excess cases and deaths in multiple plausible scenarios in which R increases at one or more time points, compared to a baseline scenario where R remains unchanged by the easing of lockdown. @@ -5245,6 +5190,7 @@ Added value of this studyWe estimated excess COVID-19-related mortality in sever Implications of all the available evidenceThese analyses support COVID-19 and non-COVID-19 impact assessment in policy planning during the pandemic. The implications of distancing and isolation measures on incidence and mortality from chronic diseases, particularly relating to obesity, needs to be considered in clinical practice, public health and research. C_TEXTBOX",health policy,fuzzy,100,100 +medRxiv,10.1101/2020.06.22.20137216,2020-06-23,https://medrxiv.org/cgi/content/short/2020.06.22.20137216,"Proteomic blood profiling in mild, severe and critical COVID-19 patients",Hamel Patel; Nicholas J Ashton; Richard J Dobson; Lars-magnus Anderson; Aylin Yilmaz; Kaj Blennow; Magnus Gisslen; Henrik Zetterberg,King's College London; University of Gothenburg; Kings College London; Sahlgrenska university hospital; University of Gothenburg; University of Gothenburg; University of Gothenburg; University of Gothenburg,"The recent SARS-CoV-2 pandemic manifests itself as a mild respiratory tract infection in the majority of individuals leading to COVID-19 disease. However, in some infected individuals, this can progress to severe pneumonia and acute respiratory distress syndrome (ARDS), leading to multi-organ failure and death. The purpose of this study is to explore the proteomic differences between mild, severe and critical COVID-19 positive patients. Blood protein profiling was performed on 59 COVID-19 mild (n=26), severe (n=9) or critical (n=24) cases and 28 controls using the OLINK inflammation, autoimmune, cardiovascular and neurology panels. Differential expression analysis was performed within and between disease groups to generate nine different analyses. From the 368 proteins measured per individual, more than 75% were observed to be significantly perturbed in COVID-19 cases. Six proteins (IL6, CKAP4, Gal-9, IL-1ra, LILRB4 and PD-L1) were identified to be associated with disease severity. The results have been made readily available through an interactive web-based application for instant data exploration and visualization, and can be accessed at https://phidatalab-shiny.rosalind.kcl.ac.uk/COVID19/. Our results demonstrate that dynamic changes in blood proteins that associate with disease severity can potentially be used as early biomarkers to monitor disease severity in COVID-19 and serve as potential therapeutic targets.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.06.22.20137273,2020-06-22,https://medrxiv.org/cgi/content/short/2020.06.22.20137273,Effect of Dexamethasone in Hospitalized Patients with COVID-19: Preliminary Report,Peter Horby; Wei Shen Lim; Jonathan Emberson; Marion Mafham; Jennifer Bell; Louise Linsell; Natalie Staplin; Christopher Brightling; Andrew Ustianowski; Einas Elmahi; Benjamin Prudon; Christopher Green; Timothy Felton; David Chadwick; Kanchan Rege; Christopher Fegan; Lucy C Chappell; Saul N Faust; Thomas Jaki; Katie Jeffery; Alan Montgomery; Kathryn Rowan; Edmund Juszczak; J Kenneth Baillie; Richard Haynes; Martin J Landray; - RECOVERY Collaborative Group,"Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.; Respiratory Medicine Department, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; Regional Infectious Diseases Unit, North Manchester General Hospital & University of Manchester, Manchester, United Kingdom; Research and Development Department, Northampton General Hospital, Northampton, United Kingdom; Department of Respiratory Medicine, North Tees & Hartlepool NHS Foundation Trust, Stockton-on-Tees, United Kingdom; University Hospitals Birmingham NHS Foundation Trust and Institute of Microbiology & Infection, University of Birmingham, Birmingham, United Kingdom; University of Manchester and Manchester University NHS Foundation Trust, Manchester, United Kingdom; Centre for Clinical Infection, James Cook University Hospital, Middlesbrough, United Kingdom; North West Anglia NHS Foundation Trust, Peterborough, United Kingdom; Department of Research and Development, Cardiff and Vale University Health Board, Cardiff, United Kingdom; School of Life Course Sciences, Kings College London, London, United Kingdom; NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, ; Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom and MRC Biostatistics Unit, University of Cambridge, Cambridge, United; Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; Intensive Care National Audit & Research Centre, London, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; ","BackgroundCoronavirus disease 2019 (COVID-19) is associated with diffuse lung damage. Corticosteroids may modulate immune-mediated lung injury and reducing progression to respiratory failure and death. MethodsThe Randomised Evaluation of COVID-19 therapy (RECOVERY) trial is a randomized, controlled, open-label, adaptive, platform trial comparing a range of possible treatments with usual care in patients hospitalized with COVID-19. We report the preliminary results for the comparison of dexamethasone 6 mg given once daily for up to ten days vs. usual care alone. The primary outcome was 28-day mortality. @@ -5417,7 +5363,6 @@ MethodsElectronic databases (Embase and MEDLINE) were searched for applicable ar Results106 abstracts were identified from the databases search, of which 16 were included. 5 studies were included in the meta-analysis. In total, 9988 patients were included across all studies. The overall cases of COVID-19 requiring IMV ranged from 2-77%. Increased age and pre-existing comorbidities increased the likelihood of IMV requirement. The reported mortality rate in patients receiving IMV ranged between 50-100%. On average, IMV was required and initiated between 10-10.5 days from symptoms onset. When invasively ventilated, COVID-19 patients required IMV for a median of 10-17 days across studies. Little information was provided on ventilatory protocols or management strategies and were inconclusive. ConclusionIn these initial reporting studies for the first month of the pandemic, patients receiving IMV were older and had more pre-existing co-morbidities than those who did not require IMV. The mortality rate was high in COVID-19 patients who received IMV. Studies are needed to evaluate protocols and modalities of IMV to improve outcomes and identify the populations most likely to benefit from IMV.",intensive care and critical care medicine,fuzzy,100,100 -medRxiv,10.1101/2020.06.01.20116608,2020-06-03,https://medrxiv.org/cgi/content/short/2020.06.01.20116608,Is death from Covid-19 a multistep process?,Neil Pearce; Giovenale Moirano; Milena Maule; Manolis Kogevinas; Xavier Rodo; Deborah Lawlor; Jan Vandenbroucke; Christina Vandenbroucke-Grauls; Fernando P Polack; Adnan Custovic,"London School of Hygiene and Tropical Medicine; University of Turin, Italy; University of Turin, Italy; ISGlobal; ISGlobal; University of Bristol; Leiden University Medical Center; Amsterdam UMC; Vanderbilt Unversity; Imperial College London","Covid-19 death has a different relationship with age than is the case for other severe respiratory pathogens. The Covid-19 death rate increases exponentially with age, and the main risk factors are age itself, as well as having underlying conditions such as hypertension, diabetes, cardiovascular disease, severe chronic respiratory disease and cancer. Furthermore, the almost complete lack of deaths in children suggests that infection alone is not sufficient to cause death; rather, one must have gone through a number of changes, either as a result of undefined aspects of aging, or as a result of chronic disease. These characteristics of Covid-19 death are consistent with the multistep model of disease, a model which has primarily been used for cancer, and more recently for amyotrophic lateral sclerosis (ALS). We applied the multi-step model to data on Covid-19 case fatality rates (CFRs) from China, South Korea, Italy, Spain and Japan. In all countries we found that a plot of ln (CFR) against ln (age) was approximately linear with a slope of about 5. As a comparison, we also conducted similar analyses for selected other respiratory diseases. SARS showed a similar log-log age-pattern to that of Covid-19, albeit with a lower slope, whereas seasonal and pandemic influenza showed quite different age-patterns. Thus, death from Covid-19 and SARS appears to follow a distinct age-pattern, consistent with a multistep model of disease that in the case of Covid-19 is probably defined by comorbidities and age producing immune-related susceptibility. Identification of these steps would be potentially important for prevention and therapy for SARS-COV-2 infection.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.06.01.20118943,2020-06-02,https://medrxiv.org/cgi/content/short/2020.06.01.20118943,"Greater risk of severe COVID-19 in non-White ethnicities is not explained by cardiometabolic, socioeconomic, or behavioural factors, or by 25(OH)-vitamin D status: study of 1,326 cases from the UK Biobank",Zahra Raisi-Estabragh; Celeste McCracken; Mae S Bethell; Jackie Cooper; Cyrus Cooper; Mark J Caulfield; Patricia B Munroe; Nicholas C Harvey; Steffen E Petersen,"William Harvey Research Institute; William Harvey Research Institute; North West Anglia NHS Foundation Trust; William Harvey Research Institute; MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK; William Harvey Research Institute; William Harvey Research Institute; MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK; William Harvey Research Institute","BackgroundWe examined whether the greater severity of coronavirus disease 2019 (COVID-19) amongst men and non-White ethnicities is explained by cardiometabolic, socio-economic, or behavioural factors. MethodsWe studied 4,510 UK Biobank participants tested for COVID-19 (positive, n = 1,326). Multivariate logistic regression models including age, sex, and ethnicity were used to test whether addition of: 1)cardiometabolic factors (diabetes, hypertension, high cholesterol, prior myocardial infarction, smoking, BMI); 2)25(OH)-vitamin D; 3)poor diet; 4)Townsend deprivation score; 5)housing (home type, overcrowding); or 6)behavioural factors (sociability, risk taking) attenuated sex/ethnicity associations with COVID-19 status. @@ -5782,6 +5727,9 @@ MethodsCohort study analysed by Cox-regression to generate hazard ratios: age an ResultsThere were 5683 deaths attributed to COVID-19. In summary after full adjustment, death from COVID-19 was strongly associated with: being male (hazard ratio 1.99, 95%CI 1.88-2.10); older age and deprivation (both with a strong gradient); uncontrolled diabetes (HR 2.36 95% CI 2.18-2.56); severe asthma (HR 1.25 CI 1.08-1.44); and various other prior medical conditions. Compared to people with ethnicity recorded as white, black people were at higher risk of death, with only partial attenuation in hazard ratios from the fully adjusted model (age-sex adjusted HR 2.17 95% CI 1.84-2.57; fully adjusted HR 1.71 95% CI 1.44-2.02); with similar findings for Asian people (age-sex adjusted HR 1.95 95% CI 1.73-2.18; fully adjusted HR 1.62 95% CI 1.431.82). ConclusionsWe have quantified a range of clinical risk factors for death from COVID-19, some of which were not previously well characterised, in the largest cohort study conducted by any country to date. People from Asian and black groups are at markedly increased risk of in-hospital death from COVID-19, and contrary to some prior speculation this is only partially attributable to pre-existing clinical risk factors or deprivation; further research into the drivers of this association is therefore urgently required. Deprivation is also a major risk factor with, again, little of the excess risk explained by co-morbidity or other risk factors. The findings for clinical risk factors are concordant with policies in the UK for protecting those at highest risk. Our OpenSAFELY platform is rapidly adding further NHS patients records; we will update and extend these results regularly.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2020.05.02.20078642,2020-05-06,https://medrxiv.org/cgi/content/short/2020.05.02.20078642,Impact of ethnicity on outcome of severe COVID-19 infection. Data from an ethnically diverse UK tertiary centre,James T Teo; Daniel Bean; Rebecca Bendayan; Richard Dobson; Ajay Shah,Kings College Hospital NHS Foundation Trust; King's College London; King's College London; Kings College London; King's College London,"During the current COVID-19 pandemic, it has been suggested that BAME background patients may be disproportionately affected compared to White but few detailed data are available. We took advantage of near real-time hospital data access and analysis pipelines to look at the impact of ethnicity in 1200 consecutive patients admitted between 1st March 2020 and 12th May 2020 to Kings College Hospital NHS Trust in London (UK). + +Our key findings are firstly that BAME patients are significantly younger and have different co-morbidity profiles than White individuals. Secondly, there is no significant independent effect of ethnicity on severe outcomes (death or ITU admission) within 14-days of symptom onset, after adjustment for age, sex and comorbidities.",intensive care and critical care medicine,fuzzy,100,100 medRxiv,10.1101/2020.05.02.20086231,2020-05-06,https://medrxiv.org/cgi/content/short/2020.05.02.20086231,Trends in excess cancer and cardiovascular deaths in Scotland during the COVID-19 pandemic 30 December 2019 to 20 April 2020,Jonine Figueroa; Paul Brennan; Evropi Theodoratou; Michael Poon; Karin Purshouse; Farhat Din; Kai Jin; Ines Mesa-Eguiagaray; Malcolm G Dunlop; Peter S Hall; David Cameron; Sarah Wild; Cathie LM Sudlow,University of Edinburgh; University of Edinburgh - Brain Tumour Centre of Excellence; University of Edinburgh - Centre for Clinical Brain Sciences; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; Institute of Genetics and Molecular Medicine; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh,"Understanding the trends in causes of death for different diseases during the current COVID-19 pandemic is important to determine whether there are excess deaths beyond what is normally expected. Using the most recent report from National Records Scotland (NRS) on 29 April 2020, we examined the percentage difference in crude numbers of deaths in 2020 compared to the average for 2015-2019 by week of death within calendar year. To determine if trends were similar, suggesting underreporting/underdiagnosed COVID-19 related deaths, we also looked at the trends in % differences for cardiovascular disease deaths. From the first 17 weeks of data, we found a peak in excess deaths at week 14 of 2020, about four weeks after the first case in Scotland was detected on 1 March 2020-- but by week 17 these excesses had returned to normal levels, 4 weeks after lockdown in the UK began. Similar observations were seen for cardiovascular disease-related deaths. These observations suggest that the short-term increase in excess cancer and cardiovascular deaths might be associated with undetected/unconfirmed deaths related to COVID-19. Both of these conditions make patients more susceptible to infection and lack of widespread access to testing for COVID-19 are likely to have resulted in under-estimation of COVID-19 mortality. These data further suggest that the cumulative toll of COVID-19 on mortality is likely undercounted. More detailed analysis is needed to determine if these excesses were directly or indirectly related to COVID-19. Disease specific mortality will need constant monitoring for the foreseeable future as changes occur in increasing capacity and access to testing, reporting criteria, changes to health services and different measures are implemented to control the spread of the COVID-19. Multidisciplinary, multi-institutional, national and international collaborations for complementary and population specific data analysis is required to respond and mitigate adverse effects of the COVID-19 pandemic and to inform planning for future pandemics.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.04.28.20083170,2020-05-05,https://medrxiv.org/cgi/content/short/2020.04.28.20083170,Quantifying and mitigating the impact of the COVID-19 pandemic on outcomes in colorectal cancer,Amit Sud; Michael Jones; John Broggio; Stephen Scott; Chey Loveday; Bethany Torr; Alice Garrett; David L. Nicol; Shaman Jhanji; Stephen A. Boyce; Matthew Williams; Georgios Lyratzopoulos; Claire Barry; Elio Riboli; Emma Kipps; Ethna McFerran; Mark Lawler; David C. Muller; Muti Abulafi; Richard Houlston; Clare Ann Turnbull,"Institute of Cancer Research; Institute of Cancer Research; Public Health England; RM Partners, West London Cancer Alliance; Institute of Cancer Research; Institute of Cancer Research; Institute of Cancer Research; Royal Marsden NHS Foundation Trust; Royal Marsden NHS Foundation Trust; Oxford University Hospitals NHS Foundation Trust; Imperial College; University College London; RM Partners, West London Cancer Alliance; Imperial College London; Royal Marsden NHS Foundation Trust; Queen's University Belfast; Queen's University Belfast; Imperial College London; Croydon Health Services NHS Trust, on behalf of RMP NICE FIT Steering Group; Institute of Cancer Research; Institute of Cancer Research","BackgroundThe COVID-19 pandemic has caused disruption across cancer pathways for diagnosis and treatment. In England, 32% of colorectal cancer (CRC) is diagnosed via urgent symptomatic referral from primary care, the ""2-week-wait"" (2WW) pathway. Access to routine endoscopy is likely to be a critical bottleneck causing delays in CRC management due to chronic limitation in capacity, acute competition for physician time, and safety concerns. @@ -5807,21 +5755,6 @@ RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSThe prolonged cours Added value of this studyIn a prospective study of 2,135,190 individuals, frontline HCWs may have up to a 12-fold increased risk of reporting a positive COVID-19 test. Compared with those who reported adequate availability of PPE, frontline HCWs with inadequate PPE had a 31% increase in risk. However, adequate availability of PPE did not completely reduce risk among HCWs caring for COVID-19 patients. Implications of all the available evidenceBeyond ensuring adequate availability of PPE, additional efforts to protect HCWs from COVID-19 are needed, particularly as lockdown is lifted in many regions of the world.",epidemiology,fuzzy,94,100 -medRxiv,10.1101/2020.04.28.20082222,2020-05-03,https://medrxiv.org/cgi/content/short/2020.04.28.20082222,"Risk prediction for poor outcome and death in hospital in-patients with COVID-19: derivation in Wuhan, China and external validation in London, UK",Huayu Zhang; Ting Shi; Xiaodong Wu; Xin Zhang; Kun Wang; Daniel Bean; Richard Dobson; James T Teo; Jiaxing Sun; Pei Zhao; Chenghong Li; Kevin Dhaliwal; Honghan Wu; Qiang Li; Bruce Guthrie,"Centre for Medical Informatics, Usher Institute, University of Edinburgh, Scotland, United Kingdom; Centre for Global Health, Usher Institute, University of Edinburgh, Scotland, United Kingdom; Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China; Department of Pulmonary and Critical Care Medicine, Peoples Liberation Army Joint Logistic Support Force 920th Hospital, Yunnan, China; Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, England, United Kingdom; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, England, United Kingdom; Department of Stroke and Neurology, Kings College Hospital NHS Foundation Trust, London, England, United Kingdom; Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China; Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China; Department of Pulmonary and Critical Care Medicine, Wuhan Sixth Hospital, Jianghan University, Wuhan, China; Centre for Inflammation Research, Queens Medical Research Institute, University of Edinburgh, Scotland, United Kingdom; Centre for Medical Informatics, Usher Institute, University of Edinburgh, Scotland, United Kingdom; Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China; Centre for Population Health Sciences, Usher Institute, University of Edinburgh, Scotland, United Kingdom","BackgroundAccurate risk prediction of clinical outcome would usefully inform clinical decisions and intervention targeting in COVID-19. The aim of this study was to derive and validate risk prediction models for poor outcome and death in adult inpatients with COVID-19. - -MethodsModel derivation using data from Wuhan, China used logistic regression with death and poor outcome (death or severe disease) as outcomes. Predictors were demographic, comorbidity, symptom and laboratory test variables. The best performing models were externally validated in data from London, UK. - -Findings4.3% of the derivation cohort (n=775) died and 9.7% had a poor outcome, compared to 34.1% and 42.9% of the validation cohort (n=226). In derivation, prediction models based on age, sex, neutrophil count, lymphocyte count, platelet count, C-reactive protein and creatinine had excellent discrimination (death c-index=0.91, poor outcome c-index=0.88), with good-to-excellent calibration. Using two cut-offs to define low, high and very-high risk groups, derivation patients were stratified in groups with observed death rates of 0.34%, 15.0% and 28.3% and poor outcome rates 0.63%, 8.9% and 58.5%. External validation discrimination was good (c-index death=0.74, poor outcome=0.72) as was calibration. However, observed rates of death were 16.5%, 42.9% and 58.4% and poor outcome 26.3%, 28.4% and 64.8% in predicted low, high and very-high risk groups. - -InterpretationOur prediction model using demography and routinely-available laboratory tests performed very well in internal validation in the lower-risk derivation population, but less well in the much higher-risk external validation population. Further external validation is needed. Collaboration to create larger derivation datasets, and to rapidly externally validate all proposed prediction models in a range of populations is needed, before routine implementation of any risk prediction tool in clinical care. - -FundingMRC, Wellcome Trust, HDR-UK, LifeArc, participating hospitals, NNSFC, National Key R&D Program, Pudong Health and Family Planning Commission - -Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSeveral prognostic models for predicting mortality risk, progression to severe disease, or length of hospital stay in COVID-19 have been published.1 Commonly reported predictors of severe prognosis in patients with COVID-19 include age, sex, computed tomography scan features, C-reactive protein (CRP), lactic dehydrogenase, and lymphocyte count. Symptoms (notably dyspnoea) and comorbidities (e.g. chronic lung disease, cardiovascular disease and hypertension) are also reported to have associations with poor prognosis.2 However, most studies have not described the study population or intended use of prediction models, and external validation is rare and to date done using datasets originating from different Wuhan hospitals.3 Given different patterns of testing and organisation of healthcare pathways, external validation in datasets from other countries is required. - -Added value of this studyThis study used data from Wuhan, China to derive and internally validate multivariable models to predict poor outcome and death in COVID-19 patients after hospital admission, with external validation using data from Kings College Hospital, London, UK. Mortality and poor outcome occurred in 4.3% and 9.7% of patients in Wuhan, compared to 34.1% and 42.9% of patients in London. Models based on age, sex and simple routinely available laboratory tests (lymphocyte count, neutrophil count, platelet count, CRP and creatinine) had good discrimination and calibration in internal validation, but performed only moderately well in external validation. Models based on age, sex, symptoms and comorbidity were adequate in internal validation for poor outcome (ICU admission or death) but had poor performance for death alone. - -Implications of all the available evidenceThis study and others find that relatively simple risk prediction models using demographic, clinical and laboratory data perform well in internal validation but at best moderately in external validation, either because derivation and external validation populations are small (Xie et al3) and/or because they vary greatly in casemix and severity (our study). There are three decision points where risk prediction may be most useful: (1) deciding who to test; (2) deciding which patients in the community are at high-risk of poor outcomes; and (3) identifying patients at high-risk at the point of hospital admission. Larger studies focusing on particular decision points, with rapid external validation in multiple datasets are needed. A key gap is risk prediction tools for use in community triage (decisions to admit, or to keep at home with varying intensities of follow-up including telemonitoring) or in low income settings where laboratory tests may not be routinely available at the point of decision-making. This requires systematic data collection in community and low-income settings to derive and evaluate appropriate models.",public and global health,fuzzy,100,100 medRxiv,10.1101/2020.04.27.20081810,2020-05-03,https://medrxiv.org/cgi/content/short/2020.04.27.20081810,Clinical classifiers of COVID-19 infection from novel ultra-high-throughput proteomics,Christoph B. Messner; Vadim Demichev; Daniel Wendisch; Laura Michalick; Matthew White; Anja Freiwald; Kathrin Textoris-Taube; Spyros I. Vernardis; Anna-Sophia Egger; Marco Kreidl; Daniela Ludwig; Christiane Kilian; Federica Agostini; Aleksej Zelezniak; Charlotte Thibeault; Moritz Pfeiffer; Stefan Hippenstiel; Andreas Hocke; Christof von Kalle; Archie Campbell; Caroline Hayward; David J. Porteous; Riccardo E. Marioni; Claudia Langenberg; Kathryn S. Lilley; Wolfgang M. Kuebler; Michael Muelleder; Christian Drosten; Martin Witzenrath; Florian Kurth; Leif Erik Sander; Markus Ralser,"The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW11AT, United Kingdom; The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW11AT, United Kingdom; Charite Universitaetsmedizin, Berlin, Dept. of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany; Charite Universitaetsmedizin, Institute of Physiology, 10117 Berlin, Germany; The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW11AT, United Kingdom; Charite Universitaetsmedizin, Core Facility - High Throughput Mass Spectrometry, 10117 Berlin, German; Charite Universitaetsmedizin, Core Facility - High Throughput Mass Spectrometry, 10117 Berlin, Germany; The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW11AT, United Kingdom; The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW11AT, United Kingdom; The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW11AT, United Kingdom; Charite Universitaetsmedizin, Department of Biochemistry, 10117 Berlin, Germany; Charite Universitaetsmedizin, Department of Biochemistry, 10117 Berlin, Germany; Charite Universitaetsmedizin, Department of Biochemistry, 10117 Berlin, Germany; Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg SE-412 96, Sweden; Charite Universitaetsmedizin, Berlin, Dept. of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany; Charite Universitaetsmedizin, Berlin, Dept. of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany; Charite Universitaetsmedizin, Berlin, Dept. of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany; Charite Universitaetsmedizin, Berlin, Dept. of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany; Berlin Institute of Health (BIH), and Charite Universitaetsmedizin, Clinical Study Center (CSC), 10117 Berlin, Germany; Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh United Kingdom and Usher Institute, Universi; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, United Kingdom; Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh EH4 2XU, United Kingdom; Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh EH4 2XU, United Kingdom; MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0QQ, United Kingdom; Department of Biochemistry, The University of Cambridge, Cambridge, CB21GA, United Kingdom; Charite Universitaetsmedizin, Berlin, Institute of Physiology, 10117 Berlin, Germany; Charite Universitaetsmedizin, Core Facility - High Throughput Mass Spectrometry, 10117 Berlin, Germany; Charite Universitaetsmedizin, Berlin, Department of Virology, 10117 Berlin, Germany; Charite Universitaetsmedizin, Berlin, Dept. of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany; Charite Universitaetsmedizin, Berlin, Dept. of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany and Department of Tropical Medicine, Bernhard; Charite Universitaetsmedizin, Berlin, Dept. of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany; Charite Universitaetsmedizin, Berlin, Department of Biochemistry, 10117 Berlin, and The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, Lon","The COVID-19 pandemic is an unprecedented global challenge. Highly variable in its presentation, spread and clinical outcome, novel point-of-care diagnostic classifiers are urgently required. Here, we describe a set of COVID-19 clinical classifiers discovered using a newly designed low-cost high-throughput mass spectrometry-based platform. Introducing a new sample preparation pipeline coupled with short-gradient high-flow liquid chromatography and mass spectrometry, our methodology facilitates clinical implementation and increases sample throughput and quantification precision. Providing a rapid assessment of serum or plasma samples at scale, we report 27 biomarkers that distinguish mild and severe forms of COVID-19, of which some may have potential as therapeutic targets. These proteins highlight the role of complement factors, the coagulation system, inflammation modulators as well as pro-inflammatory signalling upstream and downstream of Interleukin 6. Application of novel methodologies hence transforms proteomics from a research tool into a rapid-response, clinically actionable technology adaptable to infectious outbreaks. Highlights- A completely redesigned clinical proteomics platform increases throughput and precision while reducing costs. @@ -6026,7 +5959,6 @@ DATA EXTRACTION AND ANALYSISSix authors independently assessed risk of bias usin RESULTSWe included 15 randomised trials investigating the effect of masks (14 trials) in healthcare workers and the general population and of quarantine (1 trial). We found no trials testing eye protection. Compared to no masks there was no reduction of influenza-like illness (ILI) cases (Risk Ratio 0.93, 95%CI 0.83 to 1.05) or influenza (Risk Ratio 0.84, 95%CI 0.61-1.17) for masks in the general population, nor in healthcare workers (Risk Ratio 0.37, 95%CI 0.05 to 2.50). There was no difference between surgical masks and N95 respirators: for ILI (Risk Ratio 0.83, 95%CI 0.63 to 1.08), for influenza (Risk Ratio 1.02, 95%CI 0.73 to 1.43). Harms were poorly reported and limited to discomfort with lower compliance. The only trial testing quarantining workers with household ILI contacts found a reduction in ILI cases, but increased risk of quarantined workers contracting influenza. All trials were conducted during seasonal ILI activity. CONCLUSIONSMost included trials had poor design, reporting and sparse events. There was insufficient evidence to provide a recommendation on the use of facial barriers without other measures. We found insufficient evidence for a difference between surgical masks and N95 respirators and limited evidence to support effectiveness of quarantine. Based on observational evidence from the previous SARS epidemic included in the previous version of our Cochrane review we recommend the use of masks combined with other measures.",public and global health,fuzzy,100,100 -medRxiv,10.1101/2020.03.24.20043018,2020-03-27,https://medrxiv.org/cgi/content/short/2020.03.24.20043018,Age-dependent effects in the transmission and control of COVID-19 epidemics,Nicholas G Davies; Petra Klepac; Yang Liu; Kiesha Prem; Mark Jit; CMMID COVID-19 working group; Rosalind M Eggo,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; ; London School of Hygiene and Tropical Medicine,"The COVID-19 pandemic has shown a markedly low proportion of cases among children. Age disparities in observed cases could be explained by children having lower susceptibility to infection, lower propensity to show clinical symptoms, or both. We evaluate these possibilities by fitting an age-structured mathematical model to epidemic data from six countries. We estimate that clinical symptoms occur in 25% (95% CrI: 19-32%) of infections in 10-19-year-olds, rising to 76% (68-82%) in over-70s, and that susceptibility to infection in under-20s is approximately half that of older adults. Accordingly, we find that interventions aimed at children may have a relatively small impact on total cases, particularly if the transmissibility of subclinical infections is low. The age-specific clinical fraction and susceptibility we have estimated has implications for the expected global burden of COVID-19 because of demographic differences across settings: in younger populations, the expected clinical attack rate would be lower, although it is likely that comorbidities in low-income countries will affect disease severity. Without effective control measures, regions with older populations may see disproportionally more clinical cases, particularly in the later stages of the pandemic.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.03.22.20040287,2020-03-24,https://medrxiv.org/cgi/content/short/2020.03.22.20040287,Estimating excess 1- year mortality from COVID-19 according to underlying conditions and age in England: a rapid analysis using NHS health records in 3.8 million adults,Amitava Banerjee; Laura Pasea; Steve Harris; Arturo Gonzalez-Izquierdo; Ana Torralbo; Laura Shallcross; Mahdad Noursadeghi; Deenan Pillay; Christina Pagel; Wai Keong Wong; Claudia Langenberg; Bryan Williams; Spiros Denaxas; Harry Hemingway,University College London; University College London; University College London Hospitals NHS Trust; University College London; University College London; UCL; University College London; University College London; University College London; University College London Hospitals NHS Trust; University of Cambridge; University College London; University College London; University College London,"BackgroundThe medical, health service, societal and economic impact of the COVID-19 emergency has unknown effects on overall population mortality. Previous models of population mortality are based on death over days among infected people, nearly all of whom (to date at least) have underlying conditions. Models have not incorporated information on high risk conditions or their longer term background (pre-COVID-19) mortality. We estimated the excess number of deaths over 1 year under different COVID-19 incidence rates and differing mortality impacts. MethodsUsing population based linked primary and secondary care electronic health records in England (HDR UK - CALIBER), we report the prevalence of underlying conditions defined by UK Public Health England COVID-19 guidelines (16 March 2020) in 3,862,012 individuals aged [≥]30 years from 1997-2017. We used previously validated phenotypes, openly available (https://caliberresearch.org/portal), for each condition using ICD-10 diagnosis, Read, procedure and medication codes. We estimated the 1-year mortality in each condition, and developed simple models of excess COVID-19-related deaths assuming relative risk (RR) of the impact of the emergency (compared to background mortality) of 1.2, 1.5 and 2.0. @@ -6085,6 +6017,7 @@ Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSContact tracing and Added value of this studyThis study uses a mathematical model to assess the feasibility of contact tracing and case isolation to control outbreaks of 2019-nCov, a newly emerged pathogen. We used disease transmission characteristics specific to the pathogen and therefore give the best available evidence if contact tracing and isolation can achieve control of outbreaks. Implications of all the available evidenceContact tracing and isolation may not contain outbreaks of 2019-nCoV unless very high levels of contact tracing are achieved. Even in this case, if there is asymptomatic transmission, or a high fraction of transmission before onset of symptoms, this strategy may not achieve control within three months.",public and global health,fuzzy,100,100 +medRxiv,10.1101/2020.01.31.20019265,2020-02-02,https://medrxiv.org/cgi/content/short/2020.01.31.20019265,Effectiveness of airport screening at detecting travellers infected with 2019-nCoV,Billy Quilty; Sam Clifford; Stefan Flasche; Rosalind M Eggo,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine,"As the number of novel coronavirus cases grows both inside and outside of China, public health authorities require evidence on the effectiveness of control measures such as thermal screening of arrivals at airports. We evaluated the effectiveness of exit and entry screening for 2019-nCoV infection. In our baseline scenario, we estimated that 46.5% (95%CI: 35.9 to 57.7) of infected travellers would not be detected, depending on the incubation period, sensitivity of exit and entry screening, and the proportion of cases which are asymptomatic. Airport screening is unlikely to detect a sufficient proportion of 2019-nCoV infected travellers to avoid entry of infected travellers. We developed an online tool so that results can be updated as new information becomes available.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.01.31.20019901,2020-02-02,https://medrxiv.org/cgi/content/short/2020.01.31.20019901,Early dynamics of transmission and control of 2019-nCoV: a mathematical modelling study,Adam J Kucharski; Timothy W Russell; Charlie Diamond; Yang Liu; CMMID nCoV working group; John Edmunds; Sebastian Funk; Rosalind M Eggo,London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine,"BackgroundAn outbreak of the novel coronavirus SARS-CoV-2 has led to 46,997 confirmed cases as of 13th February 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. MethodsWe combined a stochastic transmission model with data on cases of novel coronavirus disease (COVID-19) in Wuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January and February 2020. Based on these estimates, we then calculated the probability that newly introduced cases might generate outbreaks in other areas. diff --git a/data/covid/preprints.exact.csv b/data/covid/preprints.exact.csv index 5aa5387e..b698c68c 100644 --- a/data/covid/preprints.exact.csv +++ b/data/covid/preprints.exact.csv @@ -22,6 +22,7 @@ Key messagesO_LIThe effects of different job types on risk of COVID-19 infection C_LIO_LIBoth date and reason of test are important confounders to be included when estimating odds ratios for COVID-19 infection C_LIO_LIThere was little difference in COVID-19 infection risk by job category after adjusting for test reason; however women were less likely to test positive than men C_LI",occupational and environmental health,exact,100,100 +medRxiv,10.1101/2023.08.11.23293977,2023-08-15,https://medrxiv.org/cgi/content/short/2023.08.11.23293977,"Digital Mental Health Service engagement changes during Covid-19 in children and young people across the UK: presenting concerns, service activity, and access by gender, ethnicity, and deprivation",Duleeka Knipe; Santiago de Ossorno Garcia; Louisa Salhi; Lily Mainstone-Cotton; Aaron Sefi; Ann John,University of Bristol School of Social and Community Medicine: University of Bristol Population Health Sciences; Kooth Digital Health; Kooth Digital Health; Kooth Digital Health; Kooth Digital Health; Swansea University,"The adoption of digital health technologies accelerated during Covid-19, with concerns over the equity of access due to digital exclusion. Using data from a text-based online mental health service for children and young people we explore the impact of the pandemic on service access and presenting concerns and whether differences were observed by sociodemographic characteristics in terms of access (gender, ethnicity and deprivation). We used interrupted time-series models to assess whether there was a change in the level and rate of service use during the Covid-19 pandemic (April 2020-April 2021) compared to pre-pandemic trends (June 2019-March 2020). Routinely collected data from 61221 service users were extracted for observation, those represented half of the service population as only those with consent to share their data were used. The majority of users identified as female (74%) and White (80%), with an age range between 13 and 20 years of age. There was evidence of a sudden increase (13%) in service access at the start of the pandemic (RR 1.13 95% CI 1.02, 1.25), followed by a reduced rate (from 25% to 21%) of engagement during the pandemic compared to pre-pandemic trends (RR 0.97 95% CI 0.95,0.98). There was a sudden increase in almost all presenting issues apart from physical complaints. There was evidence of a step increase in the number of contacts for Black/African/Caribbean/Black British (38% increase; 95% CI: 1%-90%) and White ethnic groups (14% increase; 95% CI: 2%-27%)), sudden increase in service use at the start of the pandemic for the most (58% increase; 95% CI: 1%-247%) and least (47% increase; 95% CI: 6%-204%) deprived areas. During the pandemic, contact rates decreased, and referral sources change at the start. Findings on access and service activity align with other studies observing reduced service utilization. The lack of differences in deprivation levels and ethnicity at lockdown suggests exploring equity of access to the anonymous service. The study provides unique insights into changes in digital mental health use during Covid-19 in the UK.",public and global health,exact,100,100 medRxiv,10.1101/2023.08.07.23293778,2023-08-09,https://medrxiv.org/cgi/content/short/2023.08.07.23293778,"Diabetes following SARS-CoV-2 infection: Incidence, persistence, and implications of COVID-19 vaccination. A cohort study of fifteen million people.",Kurt Taylor; Sophie Eastwood; Venexia Walker; Genevieve Cezard; Rochelle Knight; Marwa Al Arab; Yinghui Wei; Elsie M F Horne; Lucy Teece; Harriet Forbes; Alex Walker; Louis Fisher; Jon Massey; Lisa E M Hopcroft; Tom Palmer; Jose Cuitun Coronado; Samantha Ip; Simon Davy; Iain Dillingham; Caroline Morton; Felix Greaves; John MacLeod; Ben Goldacre; Angela Wood; Nishi Chaturvedi; Jonathan A C Sterne; Rachel Denholm; - CONVALESCENCE Long-COVID study; - Longitudinal Health and Wellbeing and Data and Connectivity UK COVID-19 National Core Studies; - OpenSAFELY collaborative,University of Bristol; University College London; University of Bristol; University of Cambridge; University of Bristol; University of Bristol; University of Plymouth; University of Bristol; University of Leicester; London School of Hygiene & Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Bristol; University of Bristol; University of Cambridge; University of Oxford; University of Oxford; University of Oxford; National Institute for Health and Care Excellence; University of Bristol; University of Oxford; University of Cambridge; University College London; University of Bristol; University of Bristol; -; -; -,"BackgroundType 2 diabetes (T2DM) incidence is increased after diagnosis of COVID-19. The impact of vaccination on this increase, for how long it persists, and the effect of COVID-19 on other types of diabetes remain unclear. MethodsWith NHS England approval, we studied diabetes incidence following COVID-19 diagnosis in pre-vaccination (N=15,211,471, January 2020-December 2021), vaccinated (N =11,822,640), and unvaccinated (N=2,851,183) cohorts (June-December 2021), using linked electronic health records. We estimated adjusted hazard ratios (aHRs) comparing diabetes incidence post-COVID-19 diagnosis with incidence before or without diagnosis up to 102 weeks post-diagnosis. Results were stratified by COVID-19 severity (hospitalised/non-hospitalised) and diabetes type. @@ -85,14 +86,6 @@ ResultsOf over 45 million patients, 69,220 (0.15%) had a Post-COVID syndrome dia DiscussionThis study demonstrates variation in diagnosis and referral coding rates for Post-COVID syndrome across different patient groups. The results, with limited crossover of referral and diagnostic codes, suggest only one type of code is usually recorded. Recording one code limits the use of routine data for monitoring Post-COVID syndrome diagnosis and management, but suggests several areas for improvement in coding. Post-COVID syndrome coding, particularly diagnosis coding, needs to improve before administrators and researchers can use it to evaluate care pathways.",epidemiology,exact,100,100 medRxiv,10.1101/2023.05.17.23290105,2023-05-24,https://medrxiv.org/cgi/content/short/2023.05.17.23290105,Within-host SARS-CoV-2 viral kinetics informed by complex life course exposures reveals different intrinsic properties of Omicron and Delta variants,Timothy W Russell; Hermaleigh Townsley; Sam Abbott; Joel Hellewell; Edward J Carr; Lloyd Chapman; Rachael Pung; Billy J Quilty; David Hodgson; Ashley Fowler; Lorin Adams; Christopher Bailey; Harriet V Mears; Ruth Harvey; Bobbi Clayton; Nicola O'Reilly; Yenting Ngai; Jerome Nicod; Steve Gamblin; Bryan Williams; Sonia Gandhi; Charles Swanton; Rupert Beale; David LV Bauer; Emma C Wall; Adam Kucharski,London School of Hygiene and Tropical Medicine; The Francis Crick Institute; London School of Hygiene and Tropical Medicine; European Molecular Biology Laboratory; The Francis Crick Institute; Lancaster University; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; National Institute for Health Research (NIHR) University College London Hospitals (UCLH); The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; London School of Hygiene and Tropical Medicine,"The emergence of successive SARS-CoV-2 variants of concern (VOC) during 2020-22, each exhibiting increased epidemic growth relative to earlier circulating variants, has created a need to understand the drivers of such growth. However, both pathogen biology and changing host characteristics - such as varying levels of immunity - can combine to influence replication and transmission of SARS-CoV-2 within and between hosts. Disentangling the role of variant and host in individual-level viral shedding of VOCs is essential to inform COVID-19 planning and response, and interpret past epidemic trends. Using data from a prospective observational cohort study of healthy adult volunteers undergoing weekly occupational health PCR screening, we developed a Bayesian hierarchical model to reconstruct individual-level viral kinetics and estimate how different factors shaped viral dynamics, measured by PCR cycle threshold (Ct) values over time. Jointly accounting for both inter-individual variation in Ct values and complex host characteristics - such as vaccination status, exposure history and age - we found that age and number of prior exposures had a strong influence on peak viral replication. Older individuals and those who had at least five prior antigen exposures to vaccination and/or infection typically had much lower levels of shedding. Moreover, we found evidence of a correlation between the speed of early shedding and duration of incubation period when comparing different VOCs and age groups. Our findings illustrate the value of linking information on participant characteristics, symptom profile and infecting variant with prospective PCR sampling, and the importance of accounting for increasingly complex population exposure landscapes when analysing the viral kinetics of VOCs.",epidemiology,exact,100,100 -medRxiv,10.1101/2023.05.08.23289442,2023-05-11,https://medrxiv.org/cgi/content/short/2023.05.08.23289442,Cohort Profile: Post-hospitalisation COVID-19 study (PHOSP-COVID),Omer Elneima; Hamish J C McAuley; Olivia C Leavy; James D Chalmers; Alex Horsley; Ling-Pei Ho; Michael Marks; Krisnah Poinasamy; Betty Raman; Aarti Shikotra; Amisha Singapuri; Marco Sereno; Victoria C Harris; Linzy Houchen-Wolloff; Ruth M Saunders; Neil J Greening; Matthew Richardson; Jennifer K Quint; Andrew Briggs; Annemarie B Docherty; Steven Kerr; Ewen M Harrison; Nazir I Lone; Mathew Thorpe; Liam G Heaney; Keir E Lewis; Raminder Aul; Paul Beirne; Charlotte E Bolton; Jeremy S Brown; Gourab Choudhury; Nawar Diar Bakerly; Nicholas Easom; Carlos Echevarria; Jonathan Fuld; Nick Hart; John R Hurst; Mark G Jones; Dhruv Parekh; Paul E Pfeffer; Najib M Rahman; Sarah L Rowland-Jones; AA Roger Thompson; Caroline Jolley; Ajay M Shah; Dan G Wootton; Trudie Chalder; Melanie J Davies; Anthony De Soyza; John R Geddes; William Greenhalf; Simon Heller; Luke S Howard; Joseph Jacob; R Gisli Jenkins; Janet M Lord; William D-C Man; Gerry P McCann; Stefan Neubauer; Peter JM Openshaw; Joanna C Porter; Matthew J Rowland; Janet T Scott; Malcolm G Semple; Sally J Singh; David C Thomas; Mark Toshner; Aziz Sheikh; Chris E Brightling; Louise v Wain; Rachael A Evans; - on behalf of the PHOSP-COVID Collaborative Group,"The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Population Health Sciences, University of Leicester, Leicester, UK; University of Dundee, Ninewells Hospital and Medical School, Dundee, UK; Division of Infection, Immunity & Respiratory Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK; MRC Human Immunology Unit, University of Oxford, Oxford, UK; Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK; Asthma and Lung UK, London, UK; Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre- Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; National Heart and Lung Institute, Imperial College London, London, UK; London School of Hygiene & Tropical Medicine, London, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; The Roslin Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Wellcome-Wolfson Institute for Experimental Medicine, Queens University Belfast, Belfast, UK; Hywel Dda University Health Board, Wales, UK; St George's University Hospitals NHS Foundation Trust, London, UK; Leeds Teaching Hospitals NHS Trust, Leeds, UK; NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK; UCL Respiratory, Department of Medicine, University College London, London, UK; Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK; Salford Royal NHS Foundation Trust, Manchester, UK; Infection Research Group, Hull University Teaching Hospitals, Hull, UK; Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, UK; Department of Respiratory Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK; Lane Fox Respiratory Unit, Guy's and St Thomas' NHS Foundation Trust, London, UK; Royal Free London NHS Foundation Trust, London, UK; Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK; Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK; Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK; NIHR Oxford Biomedical Research Centre, Oxford, UK; University of Sheffield, Sheffield, UK; University of Sheffield, Sheffield, UK; Centre for Human & Applied Physiological Sciences, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK; King's College London British Heart Foundation Centre, London, UK; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool, UK; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK; NIHR Oxford Health Biomedical Research Centre, University of Oxford, Oxford, UK; The CRUK Liverpool Experimental Cancer Medicine Centre, Liverpool, UK; Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK; Imperial College Healthcare NHS Trust, London, UK; Centre for Medical Image Computing, University College London, London, UK; National Heart and Lung Institute, Imperial College London, London, UK; MRC-Versus Arthritis Centre for Musculoskeletal Ageing Research, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK; Royal Brompton & Harefield Hospitals, Guy's and St. Thomas' NHS Foundation Trust, London, UK; Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester; NIHR Oxford Biomedical Research Centre, Oxford, UK; National Heart and Lung Institute, Imperial College London, London, UK; UCL Respiratory, Department of Medicine, University College London, London, UK; Kadoorie Centre for Critical Care Research, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; MRC-University of Glasgow Center for Virus research; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool, UK; Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Immunology and Inflammation, Imperial College London, London, UK; NIHR Cambridge Biomedical Research Centre, Cambridge, United Kingdom; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Population Health Sciences, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; ","O_LIPHOSP-COVID is a national UK multi-centre cohort study of patients who were hospitalised for COVID-19 and subsequently discharged. -C_LIO_LIPHOSP-COVID was established to investigate the medium- and long-term sequelae of severe COVID-19 requiring hospitalisation, understand the underlying mechanisms of these sequelae, evaluate the medium- and long-term effects of COVID-19 treatments, and to serve as a platform to enable future studies, including clinical trials. -C_LIO_LIData collected covered a wide range of physical measures, biological samples, and Patient Reported Outcome Measures (PROMs). -C_LIO_LIParticipants could join the cohort either in Tier 1 only with remote data collection using hospital records, a PROMs app and postal saliva sample for DNA, or in Tier 2 where they were invited to attend two specific research visits for further data collection and biological research sampling. These research visits occurred at five (range 2-7) months and 12 (range 10-14) months post-discharge. Participants could also participate in specific nested studies (Tier 3) at selected sites. -C_LIO_LIAll participants were asked to consent to further follow-up for 25 years via linkage to their electronic healthcare records and to be re-contacted for further research. -C_LIO_LIIn total, 7935 participants were recruited from 83 UK sites: 5238 to Tier 1 and 2697 to Tier 2, between August 2020 and March 2022. -C_LIO_LICohort data are held in a Trusted Research Environment and samples stored in a central biobank. Data and samples can be accessed upon request and subject to approvals. -C_LI",respiratory medicine,exact,100,100 medRxiv,10.1101/2023.04.24.23289043,2023-04-24,https://medrxiv.org/cgi/content/short/2023.04.24.23289043,LONG-TERM PHYSICAL AND MENTAL HEALTH IMPACT OF COVID-19 ON ADULTS IN ENGLAND: FOLLOW UP OF A LARGE RANDOM COMMUNITY SAMPLE,Christina J Atchison; Bethan Davies; Emily Cooper; Adam Lound; Matthew Whitaker; Adam Hampshire; Adriana Azor; Christl A Donnelly; Marc Chadeau-Hyam; Graham Cooke; Helen Ward; Paul Elliott,Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College; Imperial College London; Imperial College London School of Public Health,"BackgroundThe COVID-19 pandemic is having a lasting impact on health and well-being. We compare current self-reported health, quality of life and symptom profiles for people with ongoing symptoms following COVID-19 to those who have never had COVID-19 or have recovered. MethodsA cohort study was established with participants from the REACT programme. A sample (N=800,000) of adults were contacted between August and December 2022 to complete a questionnaire about their current health and COVID-19 history. We used logistic regression to identify predictors of persistent symptoms lasting [≥]12 weeks following COVID-19. We fitted Accelerated Failure Time models to assess factors associated with rate of recovery from persistent symptoms. @@ -188,21 +181,6 @@ Methods and ResultsSurface sampling was undertaken at 12 workplaces that experie ConclusionsFew workplace surface samples were positive for SARS-CoV-2 RNA and positive samples typically contained low levels of nucleic acid. Although these data may infer a low probability of fomite transmission or other forms of transmission within the workplace, Ct values may have been lower at the time of contamination. Workplace environmental sampling identified lapses in COVID-control measures within individual sites and showed trends through the pandemic. Significance and Impact of the StudyPrior to this study, few published reports investigated SARS-CoV-2 RNA contamination within workplaces experiencing cases of COVID-19. This report provides extensive data on environmental sampling identifying trends across workplaces and through the pandemic.",epidemiology,exact,100,100 -medRxiv,10.1101/2023.02.18.23286127,2023-02-19,https://medrxiv.org/cgi/content/short/2023.02.18.23286127,Antipsychotic prescribing and mortality in people with dementia before and during the COVID-19 pandemic: retrospective cohort study,Christian Schnier; Aoife McCarthy; Daniel R Morales; Ashley Akbari; Reecha Sofat; Caroline Dale; Rohan Takhar; Mamas Mamas; Kamlesh Khunti; Francesco Zaccardi; Cathie LM Sudlow; Tim Wilkinson,University of Edinburgh; University of Edinburgh; University of Dundee; Swansea University; University of Liverpool; University of Liverpool; University College London; Keele University; University of Leicester; University of Leicester; University of Edinburgh; University of Edinburgh,"BackgroundAntipsychotic drugs have been associated with increased mortality, stroke and myocardial infarction in people with dementia. Concerns have been raised that antipsychotic prescribing may have increased during the COVID-19 pandemic due to social restrictions imposed to limit the spread of the virus. We used multisource, routinely-collected healthcare data from Wales, UK, to investigate prescribing and mortality trends in people with dementia before and during the COVID-19 pandemic. - -MethodsWe used individual-level, anonymised, population-scale linked health data to identify adults aged [≥]60 years with a diagnosis of dementia in Wales, UK. We explored antipsychotic prescribing trends over 67 months between 1st January 2016 and 1st August 2021, overall and stratified by age and dementia subtype. We used time series analyses to examine all-cause, myocardial infarction (MI) and stroke mortality over the study period and identified the leading causes of death in people with dementia. - -FindingsOf 57,396 people with dementia, 11,929 (21%) were prescribed an antipsychotic at any point during follow-up. Accounting for seasonality, antipsychotic prescribing increased during the second half of 2019 and throughout 2020. However, the absolute difference in prescribing rates was small, ranging from 1253 to 1305 per 10,000 person-months. Prescribing in the 60-64 age group and those with Alzheimers disease increased throughout the 5-year period. All-cause and stroke mortality increased in the second half of 2019 and throughout 2020 but MI mortality declined. From January 2020, COVID-19 was the second commonest underlying cause of death in people with dementia. - -InterpretationDuring the COVID-19 pandemic there was a small increase in antipsychotic prescribing in people with dementia. The long-term increase in antipsychotic prescribing in younger people and in those with Alzheimers disease warrants further investigation. - -FundingBritish Heart Foundation (BHF) (SP/19/3/34678) via the BHF Data Science Centre led by HDR UK, and the Scottish Neurological Research Fund. - -Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched Ovid MEDLINE for studies describing antipsychotic prescribing trends in people with dementia during the COVID-19 pandemic, published between 1st January 2020 and 22nd March 2022. The following search terms were used: (exp Antipsychotic Agents/ OR antipsychotic.mp OR neuroleptic.mp OR risperidone.mp OR exp Risperidone/ OR quetiapine.mp OR exp Quetiapine Fumarate/ OR olanzapine.mp OR exp Olanzapine/ OR exp Psychotropic Drugs/ or psychotropic.mp) AND (exp Dementia/ OR exp Alzheimer Disease/ or alzheimer.mp) AND (prescri*.mp OR exp Prescriptions/ OR exp Electronic Prescribing/ OR trend*.mp OR time series.mp). The search identified 128 published studies, of which three were eligible for inclusion. Two studies, based on data from England and the USA, compared antipsychotic prescribing in people with dementia before and during the COVID-19 pandemic. Both reported an increase in the proportion of patients prescribed an antipsychotic after the onset of the pandemic. A third study, based in the Netherlands, reported antipsychotic prescription trends in nursing home residents with dementia during the first four months of the pandemic, comparing prescribing rates to the timings of lifting of social restrictions, showing that antipsychotic prescribing rates remained constant throughout this period. - -Added value of this studyWe conducted age-standardised time series analyses using comprehensive, linked, anonymised, individual-level routinely-collected, population-scale health data for the population of Wales, UK. By accounting for seasonal variations in prescribing and mortality, we demonstrated that the absolute increase in antipsychotic prescribing in people with dementia of any cause during the COVID-19 pandemic was small. In contrast, antipsychotic prescribing in the youngest age group (60-64 years) and in people with a subtype diagnosis of Alzheimers disease increased throughout the five-year study period. Accounting for seasonal variation, all-cause mortality rates in people with dementia began to increase in late 2019 and increased sharply during the first few months of the pandemic. COVID-19 became the leading non-dementia cause of death in people with dementia from 2020 to 2021. Stroke mortality increased during the pandemic, following a similar pattern to that of all-cause mortality, whereas myocardial infarction rates decreased. - -Implications of all the available evidenceDuring COVID-19 we observed a large increase in all-cause and stroke mortality in people with dementia. When seasonal variations are accounted for, antipsychotic prescribing rates in all-cause dementia increased by a small amount before and during the pandemic in the UK. The increased prescribing rates in younger age groups and in people with Alzheimers disease warrants further investigation.",neurology,exact,100,100 medRxiv,10.1101/2023.02.16.23286017,2023-02-18,https://medrxiv.org/cgi/content/short/2023.02.16.23286017,Long-term outdoor air pollution and COVID-19 mortality in London: an individual-level analysis,Loes Charlton; Chris Gale; Jasper Morgan; Myer Glickman; Sean Beevers; Anna L Hansell; Vahé Nafilyan,Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Imperial College London; University of Leicester; Office for National Statistics,"BackgroundThe risk of COVID-19 severity and mortality differs markedly by age, socio-demographic characteristics and pre-existing health status. Various studies have suggested that higher air pollution exposures also increase the likelihood of dying from COVID-19. Objectives: To assess the association between long-term outdoor air pollution (NO2, NOx, PM10 and PM2.5) concentrations and the risk of death involving COVID-19, using a large individual-level dataset. @@ -271,6 +249,7 @@ ResultsBetween 16th December 2021 and 22nd April 2022, 7,103 higher-risk patient Within 28 days of a positive test, 628 (9.0%) patients were admitted to hospital or died (84 treated and 544 untreated). The primary analysis indicated a lower risk of hospitalisation or death at any point within 28 days in treated participants compared to those not receiving treatment. The adjusted hazard rate was 35% (95% CI: 18-49%) lower in treated than untreated participants. There was no indication of the superiority of one treatment over another and no evidence of a reduction in risk of hospitalisation or death within 28 days for patients with no or only one comorbidity. In patients treated with sotrovimab, the event rates before and on or after 20th February 2022 were similar (5.0% vs 4.9%) with no significant difference in the hazard ratios for sotrovimab between the time periods. ConclusionsIn higher-risk adult patients in the community with COVID-19, those who received treatment with molnupiravir, nirmatrelvir-ritonavir, or sotrovimab were at lower risk of hospitalisation or death than those not receiving treatment.",infectious diseases,exact,100,100 +medRxiv,10.1101/2023.01.04.22283762,2023-01-05,https://medrxiv.org/cgi/content/short/2023.01.04.22283762,Challenges in estimating waning effectiveness of two doses of BNT162b2 and ChAdOx1 COVID-19 vaccines beyond six months: an OpenSAFELY cohort study using linked electronic health records,Elsie MF Horne; William J Hulme; Ruth H Keogh; Tom M Palmer; Elizabeth Williamson; Edward PK Parker; Venexia M Walker; Rochelle Knight; Yinghui Wei; Kurt Taylor; Louis Fisher; Jessica Morley; Amir Mehrkar; Iain Dillingham; Sebastian CJ Bacon; Ben Goldacre; Jonathan AC Sterne; - The OpenSAFELY Collaborative,University of Bristol; University of Oxford; London School of Hygiene and Tropical Medicine; University of Bristol; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Bristol; University of Bristol; University of Plymouth; University of Bristol; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Bristol; -,"Quantifying the waning effectiveness of second COVID-19 vaccination beyond six months and against the omicron variant is important for scheduling subsequent doses. With the approval of NHS England, we estimated effectiveness up to one year after second dose, but found that bias in such estimates may be substantial.",epidemiology,exact,100,100 medRxiv,10.1101/2022.12.21.22283794,2022-12-22,https://medrxiv.org/cgi/content/short/2022.12.21.22283794,SARS-CoV-2 infections in migrants and the role of household overcrowding: A causal mediation analysis of Virus Watch data,Yamina Boukari; Sarah Beale; Vincent Nguyen; Wing Lam Erica Fong; Rachel Burns; Alexei Yavlinsky; Susan J Hoskins; Kate Marie Lewis; Cyril Geismar; Annalan Mathew Dwight Navaratnam; Isobel Braithwaite; Thomas Edward Byrne; Youssof Oskrochi; Sam Tweed; Jana Kovar; Parth Patel; Andrew Hayward; Robert W Aldridge,University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London,"BackgroundMigrants are over-represented in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infections globally; however, evidence is limited for migrants in England and Wales. Household overcrowding is a risk factor for SARS-CoV-2 infection, with migrants more likely to live in overcrowded households than UK-born individuals. We aimed to estimate the total effect of migration status on SARS-CoV-2 infection and to what extent household overcrowding mediated this effect. MethodsWe included a sub-cohort of individuals from the Virus Watch prospective cohort study during the second SARS-CoV-2 wave (1st September 2020-30th April 2021) who were aged [≥]18 years, self-reported the number of rooms in their household and had no evidence of SARS-CoV-2 infection pre-September 2020. We estimated total, indirect and direct effects using Buis logistic decomposition regression controlling for age, sex, ethnicity, clinical vulnerability, occupation, income and whether they lived with children. @@ -295,19 +274,6 @@ MethodsWith the approval of NHS England we utilised individual-level electronic FindingsThere were large declines in avoidable hospitalisations during the first national lockdown, which then reversed post-lockdown albeit never reaching pre-pandemic levels. While trends were consistent by each measure of inequality, absolute levels of inequalities narrowed throughout 2020 (especially during the first national lockdown) and remained lower than pre-pandemic trends. While the scale of inequalities remained similar into 2021 for deprivation and ethnicity, we found evidence of widening absolute and relative inequalities by geographic region in 2021 and 2022. InterpretationThe anticipation that healthcare disruption from the COVID-19 pandemic and lockdowns would result in more (avoidable) hospitalisations and widening social inequalities was wrong. However, the recent growing gap between geographic regions suggests that the effects of the pandemic has reinforced spatial inequalities.",public and global health,exact,100,100 -medRxiv,10.1101/2022.11.29.22282883,2022-12-12,https://medrxiv.org/cgi/content/short/2022.11.29.22282883,"The protection gap under a social health protection initiative in the COVID-19 pandemic: A case study from Khyber Pakhtunkhwa, Pakistan.",Sheraz Ahmad Khan; Kathrin Cresswell; Aziz Sheikh,The University of Edinburgh; The University of Edinburgh College of Medicine and Veterinary Medicine; The University of Edinburgh College of Medicine and Veterinary Medicine,"BackgroundSehat Sahulat Programme (SSP) is a Social Health Protection (SHP) initiative by the Government of Khyber Pakhtunkhwa (GoKP), covering inpatient services for 100% of the provinces population. In this paper, we describe SSPs role in GoKPs COVID-19 response and draw inferences for similar programmes in Pakistan. - -Methodology and methodsWe conceptualised SSP as an instrumental case study and collected three complementary data sources. First, we studied GoKPs official documents to understand SSPs benefits package. Then we undertook in-depth interviews and collected non-participant observations at the SSP policy and implementation levels. We recruited participants through direct (verbal and email) and indirect (invitation posters) methods. - -Use of maximum variation sampling enabled us to understand contrasting views from various stakeholders on SSPs policy dimensions (i.e., coverage and financing), tensions between the policy directions (i.e., whether or not to cover COVID-19) and how policy decisions were made and implemented. We collected data from March 2021 to December 2021. Thematic analysis was conducted with the help of Nvivo12. - -FindingsThroughout 2020, SSP did not cover COVID-19 treatment. The insurer and GoKP officials considered the pandemic a standard exclusion to insurance coverage. One SSP official said: ""COVID-19 is not covered and not relevant to us"". GoKP had stopped non-emergency services at all hospitals. When routine services restarted, the insurer did not cover COVID-19 screening tests, which were mandatory prior to hospital admission. - -In 2021, GoKP engaged 10 private SSP hospitals for COVID-19 treatment. The SSP Reserve Fund, rather than insurance pooled money, was used. The Reserve Fund was originally meant to cover high-cost organ transplants. In 2021, SSP had 1,002 COVID-19-related admissions, which represented 0.2% of all hospital admissions (N=544,841). - -An advocacy group representative called the COVID-19 care under SSP ""too little too late"". In contrast, SSP officials suggested their insurance database and funds flow mechanism could help GoKP in future health emergencies. - -ConclusionThe commercially focused interpretation of SHP arrangements led to a protection gap in the context of COVID-19. SSP and similar programmes in other provinces of Pakistan should emphasise the notion of protection and not let commercial interests lead to protection gaps.",health policy,exact,100,100 medRxiv,10.1101/2022.12.03.22282974,2022-12-07,https://medrxiv.org/cgi/content/short/2022.12.03.22282974,Non-generalizability of biomarkers for mortality in SARS-CoV-2: a meta-analyses series,ME Rahman Shuvo; Max Schweining; Felipe Soares; Oliver Feng; Susana Abreu; Niki Veale; William Thomas; AA Roger Thompson; Richard Samworth; Nicholas W Morrell; Stefan Marciniak; Elaine Soon,Cambridge University Hospitals NHS Foundation Trust; University of Cambridge; University of Sheffield; University of Cambridge; University of Cambridge; University of Cambridge; Cambridge University Hospitals NHS Foundation Trust; University of Sheffield; University of Cambridge; University of Cambridge; University of Cambridge; University Of Cambridge,"ObjectivesSophisticated scores have been proposed for prognostication of mortality due to SARS-CoV-2 but perform inconsistently. We conducted these meta-analyses to uncover why and to pragmatically seek a single dependable biomarker for mortality. DesignWe searched the PubMed database for the keywords SARS-CoV-2 with biomarker name and mortality. All studies published from 01st December 2019 to 30th June 2021 were surveyed. To aggregate the data, the meta library in R was used to report overall mean values and 95% confidence intervals. We fitted a random effects model to obtain pooled AUCs and associated 95% confidence intervals for the European/North American, Asian, and overall datasets. @@ -324,21 +290,6 @@ Summary boxO_ST_ABSSection 1: What is already known on this topicC_ST_ABSBiomark Section 2: What this study addsCommonly used biomarkers for SARS-CoV-2 have different efficacy in different parts of the world. For example, admission CRP and interleukin-6 levels are good prognostic markers for mortality in Asian countries but only average in Europe and North America. Prognostic markers and scores cannot be transplanted from one region to another. This has implications not just for SARS-CoV-2 but also for scores in other conditions.",respiratory medicine,exact,100,100 medRxiv,10.1101/2022.11.29.22282916,2022-11-30,https://medrxiv.org/cgi/content/short/2022.11.29.22282916,Correlates of protection against SARS-CoV-2 Omicron variant and anti-spike antibody responses after a third/booster vaccination or breakthrough infection in the UK general population,Jia Wei; Philippa C Matthews; Nicole Stoesser; John Newton; Ian Diamond; Ruth Studley; Nick Taylor; John Bell; Jeremy Farrar; Brian Marsden; Jaison Kolenchery; Sarah Hoosdally; Yvonne Jones; David Stuart; Derrick Crook; Tim E Peto; Ann Sarah Walker; Koen Pouwels; David W Eyre,University of Oxford; University of Oxford; University of Oxford; Public Health England; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Wellcome Trust; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford,"Following primary SARS-CoV-2 vaccination, understanding the relative extent of protection against SARS-CoV-2 infection from boosters or from breakthrough infections (i.e. infection in the context of previous vaccination) has important implications for vaccine policy. In this study, we investigated correlates of protection against Omicron BA.4/5 infections and anti-spike IgG antibody trajectories after a third/booster vaccination or breakthrough infection following second vaccination in 154,149 adults [≥]18y from the United Kingdom general population. We found that higher anti-spike IgG antibody levels were associated with increased protection against Omicron BA.4/5 infection and that breakthrough infections were associated with higher levels of protection at any given antibody level than booster vaccinations. Breakthrough infections generated similar antibody levels to third/booster vaccinations, and the subsequent declines in antibody levels were similar to or slightly slower than those after third/booster vaccinations. Taken together our findings show that breakthrough infection provides longer lasting protection against further infections than booster vaccinations. For example, considering antibody levels associated with 67% protection against infection, a third/booster vaccination did not provide long-lasting protection, while a Delta/Omicron BA.1 breakthrough infection could provide 5-10 months of protection against Omicron BA.4/5 reinfection. 50-60% of the vaccinated UK population with a breakthrough infection would still be protected by the end of 2022, compared to <15% of the triple-vaccinated UK population without previous infection. Although there are societal impacts and risks to some individuals associated with ongoing transmission, breakthrough infection could be an efficient immune-boosting mechanism for subgroups of the population, including younger healthy adults, who have low risks of adverse consequences from infection.",infectious diseases,exact,100,100 -medRxiv,10.1101/2022.11.29.22282899,2022-11-29,https://medrxiv.org/cgi/content/short/2022.11.29.22282899,"Performance of antigen lateral flow devices in the United Kingdom during the Alpha, Delta, and Omicron waves of the SARS-CoV-2 pandemic",David W Eyre; Matthias Futschik; Sarah Tunkel; Jia Wei; Joanna Cole-Hamilton; Rida Saquib; Nick Germanacos; Andrew Dodgson; Paul E Klapper; Malur Sudhanva; Chris Kenny; Peter Marks; Edward Blandford; Susan Hopkins; Tim Peto; Tom Fowler,University of Oxford; UK Health Security Agency; UK Health Security Agency; University of Oxford; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; University of Manchester; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; University of Oxford; UK Health Security Agency,"BackgroundAntigen lateral flow devices (LFDs) have been widely used to control SARS-CoV-2. Changes in LFD sensitivity and detection of infectious individuals during the pandemic with successive variants, vaccination, and changes in LFD use are incompletely understood. - -MethodsPaired LFD and PCR tests were collected from asymptomatic and symptomatic participants, across multiple settings in the UK between 04-November-2020 and 21-March-2022. Multivariable logistic regression was used to analyse LFD sensitivity and specificity, adjusting for viral load, LFD manufacturer, setting, age, sex, assistance, symptoms, vaccination, and variant. National contact tracing data were used to estimate the proportion of transmitting index cases (with [≥]1 PCR/LFD-positive contact) potentially detectable by LFDs over time, accounting for viral load, variant, and symptom status. - -Findings4131/75,382 (5.5%) participants were PCR-positive. Sensitivity vs. PCR was 63.2% (95%CI 61.7-64.6%) and specificity 99.71% (99.66-99.74%). Increased viral load was independently associated with being LFD-positive. There was no evidence LFD sensitivity differed between Delta vs. Alpha/pre-Alpha infections, but Omicron infections were more likely to be LFD positive. Sensitivity was higher in symptomatic participants, 68.7% (66.9-70.4%) than in asymptomatic participants, 52.8% (50.1-55.4%). 79.4% (68.6-81.3%) of index cases resulting in probable onward transmission with were estimated to have been detectable using LFDs, this proportion was relatively stable over time/variants, but lower in asymptomatic vs. symptomatic cases. - -InterpretationLFDs remained able to detect most SARS-CoV-2 infections throughout vaccine roll-out and different variants. LFDs can potentially detect most infections that transmit to others and reduce risks. However, performance is lower in asymptomatic compared to symptomatic individuals. - -FundingUK Government. - -Research in contextO_ST_ABSEvidence before this studyC_ST_ABSLateral flow devices (LFDs; i.e. rapid antigen detection devices) have been widely used for SARS-CoV-2 testing. However, due to their imperfect sensitivity when compared to PCR and a lack of a widely available gold standard proxy for infectiousness, the performance and use of LFDs has been a source of debate. We conducted a literature review in PubMed and bioRxiv/medRxiv for all studies examining the performance of lateral flow devices between 01 January 2020 and 31 October 2022. We used the search terms SARS-CoV-2/COVID-19 and antigen/lateral flow test/lateral flow device. Multiple studies have examined the sensitivity and specificity of LFDs, including several systematic reviews. However, the majority of the studies are based on pre-Alpha infections. Large studies examining the test accuracy for different variants, including Delta and Omicron, and following vaccination are limited. - -Added value of this studyIn this large national LFD evaluation programme, we compared the performance of three different LFDs relative to PCR in various settings. Compared to PCR testing, sensitivity was 63.2% (95%CI 61.7-64.6%) overall, and 71.6% (95%CI 69.8-73.4%) in unselected communitybased testing. Specificity was 99.71% (99.66-99.74%). LFDs were more likely to be positive as viral loads increased. LFD sensitivity was similar during Alpha/pre-Alpha and Delta periods but increased during the Omicron period. There was no association between sensitivity and vaccination status. Sensitivity was higher in symptomatic participants, 68.7% (66.9-70.4%) than in asymptomatic participants, 52.8% (50.1-55.4%). Using national contact tracing data, we estimated that 79.4% (68.6-81.3%) of index cases resulting in probable onward transmission (i.e. with [≥]1 PCR/LFD-positive contact) were detectable using LFDs. Symptomatic index cases were more likely to be detected than asymptomatic index cases due to higher viral loads and better LFD performance at a given viral load. The proportion of index cases detected remained relatively stable over time and with successive variants, with a slight increase in the proportion of asymptomatic index cases detected during Omicron. - -Implications of all the available evidenceOur data show that LFDs detect most SARS-CoV-2 infections, with findings broadly similar to those summarised in previous meta-analyses. We show that LFD performance has been relatively consistent throughout different variant-dominant phases of the pandemic and following the roll-out of vaccination. LFDs can detect most infections that transmit to others and can therefore be used as part of a risk reduction strategy. However, performance is lower in asymptomatic compared to symptomatic individuals and this needs to be considered when designing testing programmes.",infectious diseases,exact,100,100 medRxiv,10.1101/2022.10.14.22281081,2022-10-19,https://medrxiv.org/cgi/content/short/2022.10.14.22281081,A spatio-temporal framework for modelling wastewater concentration during the COVID-19 pandemic,Guangquan Li; Hubert Denise; Peter Diggle; Jasmine Grimsley; Chris Holmes; Daniel James; Radka Jersakova; Callum Mole; George Nicholson; Camila Rangel Smith; Sylvia Richardson; William Rowe; Barry Rowlingson; Fatemeh Torabi; Matthew J Wade; Marta Blangiardo,Northumbria University; UKHSA; Lancaster University; UKHSA; Oxford University; UKHSA; Alan Turing Institute; Alan Turing Institute; Oxford University; Alan Turing Institute; MRC Biostatistics Unit; UKHSA; Lancaster University; Swansea University; UKHSA; Imperial College,"The potential utility of wastewater-based epidemiology as an early warning tool has been explored widely across the globe during the current COVID-19 pandemic. Methods to detect the presence of SARS-CoV-2 RNA in wastewater were developed early in the pandemic, and extensive work has been conducted to evaluate the relationship between viral concentration and COVID-19 case numbers at the catchment areas of sewage treatment works (STWs) over time. However, no attempt has been made to develop a model that predicts wastewater concentration at fine spatio-temporal resolutions covering an entire country, a necessary step towards using wastewater monitoring for the early detection of local outbreaks. We consider weekly averages of flow-normalised viral concentration, reported as the number of SARS-CoV-2 N1 gene copies per litre (gc/L) of wastewater available at 303 STWs over the period between 1 June 2021 and 30 March 2022. We specify a spatially continuous statistical model that quantifies the relationship between weekly viral concentration and a collection of covariates covering socio-demographics, land cover and virus-associated genomic characteristics at STW catchment areas while accounting for spatial and temporal correlation. @@ -565,20 +516,6 @@ Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC=""FIGDIR/small/22276437v1_ufig1.gif"" ALT=""Figure 1""> View larger version (38K): org.highwire.dtl.DTLVardef@12b0afborg.highwire.dtl.DTLVardef@ddf3b2org.highwire.dtl.DTLVardef@1aa670forg.highwire.dtl.DTLVardef@5415ec_HPS_FORMAT_FIGEXP M_FIG C_FIG",infectious diseases,exact,100,100 -medRxiv,10.1101/2022.06.17.22276433,2022-06-17,https://medrxiv.org/cgi/content/short/2022.06.17.22276433,It hurts your heart: frontline healthcare worker experiences of moral injury during the COVID-19 pandemic,Siobhan Hegarty; Danielle Lamb; Sharon Stevelink; Rupa Bhundia; Rosalind Raine; Mary Jane Docherty; Hannah Rachel Scott; Anne Marie Rafferty; Victoria Williamson; Sarah Dorrington; Matthew hotopf; Reza Razavi; Neil Greenberg; Simon Wessely,King's College London; UCL; King's College London; King's College London; University College London; South London and Maudsley NHS Foundation Trust; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London,"BackgroundMoral injury is defined as the strong emotional and cognitive reactions following events which clash with someones moral code, values or expectations. During the COVID-19 pandemic, increased exposure to potentially morally injurious events (PMIEs) has placed healthcare workers (HCWs) at risk of moral injury. Yet little is known about the lived experience of cumulative PMIE exposure and how NHS staff respond to this. - -ObjectiveWe sought to rectify this knowledge gap by qualitatively exploring the lived experiences and perspectives of clinical frontline NHS staff who responded to COVID-19. - -MethodsWe recruited a diverse sample of 30 clinical frontline HCWs from the NHS CHECK study cohort, for single time point qualitative interviews. All participants endorsed at least one item on the 9-item Moral Injury Events Scale (MIES) (Nash et al., 2013) at six month follow up. Interviews followed a semi-structured guide and were analysed using reflexive thematic analysis. - -ResultsHCWs described being routinely exposed to ethical conflicts, created by exacerbations of pre-existing systemic issues including inadequate staffing and resourcing. We found that HCWs experienced a range of mental health symptoms primarily related to perceptions of institutional betrayal as well as feeling unable to fulfil their duty of care towards patients. - -ConclusionThese results suggest that a multi-facetted organisational strategy is warranted to prepare for PMIE exposure, promote opportunities for resolution of symptoms associated with moral injury and prevent organisational disengagement. - -HighlightsO_LIClinical frontline healthcare workers (HCWs) have been exposed to an accumulation of potentially morally injurious events (PMIEs) throughout the COVID-19 pandemic, including feeling betrayed by both government and NHS leaders as well as feeling unable to provide duty of care to patients -C_LIO_LIHCWs described the significant adverse impact of this exposure on their mental health, including increased anxiety and depression symptoms and sleep disturbance -C_LIO_LIMost HCWs interviewed believed that organisational change within the NHS was necessary to prevent excess PMIE exposure and promote resolution of moral distress -C_LI",psychiatry and clinical psychology,exact,100,100 medRxiv,10.1101/2022.06.16.22276479,2022-06-16,https://medrxiv.org/cgi/content/short/2022.06.16.22276479,Mental health of healthcare workers in England during the COVID-19 pandemic: a longitudinal cohort study,Danielle Lamb; Rafael Gafoor; Hannah Scott; Ewan Carr; Sharon Stevelink; Rosalind Raine; Matthew Hotopf; Neil Greenberg; Siobhan Hegarty; Ira Madan; Paul Moran; Richard Morriss; Dominic Murphy; Anne Marie Rafferty; Scott Weich; Sarah Dorrington; Simon Wessely,UCL; University College London; King's College London; King's College London; King's College London; University College London; King's College London; King's College London; King's College London; Guy's and St Thomas' NHS Foundation Trust; University of Bristol; University of Nottingham; Combat Stress; King's College London; University of Sheffield; King's College London; King's College London,"ObjectiveTo examine variations in impact of the COVID-19 pandemic on the mental health of all types of healthcare workers (HCWs) in England over the first 17 months of the pandemic. MethodWe undertook a prospective cohort study of 22,501 HCWs from 18 English acute and mental health NHS Trusts, collecting online survey data on common mental disorders (CMDs), depression, anxiety, alcohol use, and PTSD, from April 2020 to August 2021. We analysed these data cross-sectionally by time period (corresponding to periods the NHS was under most pressure), and longitudinally. Data were weighted to better represent Trust population demographics. @@ -646,19 +583,13 @@ MethodsData were collected as a part of the RADAR-CNS (Remote Assessment of Dise ResultsParticipants with MDD (N=255) and MS (N=214) were included in the analyses. Overall, depressive symptoms remained stable across the three periods in both groups. Lower mean HR and HR variation were observed between pre and during lockdown during the day for MDD and during the night for MS. HR variation during rest periods also decreased between pre-and post-lockdown in both clinical conditions. We observed a reduction of physical activity for MDD and MS upon the introduction of lockdowns. The group with MDD exhibited a net increase in social interaction via social network apps over the three periods. ConclusionsBehavioral response to the lockdown measured by social activity, physical activity and HR may reflect changes in stress in people with MDD and MS.",psychiatry and clinical psychology,exact,100,100 -medRxiv,10.1101/2022.04.28.22273177,2022-04-29,https://medrxiv.org/cgi/content/short/2022.04.28.22273177,Occupational differences in SARS-CoV-2 infection: Analysis of the UK ONS Coronavirus (COVID-19) Infection Survey,Sarah Rhodes; Jack Wilkinson; Neil Pearce; Will Mueller; Mark Cherrie; Katie Stocking; Matthew Gittins; Srinivasa Vittal Katikireddi; Martie van Tongeren,University of Manchester; University of Manchester; London School of Hygiene and Tropical Medicine; Institute of Occupational Medicine; Institute of Occupational Medicine; University of Manchester; University of Manchester; University of Glasgow; University of Manchester,"BackgroundConsiderable concern remains about how occupational SARS-CoV-2 risk has evolved during the COVID-19 pandemic. We aimed to ascertain which occupations had the greatest risk of SARS-CoV-2 infection and explore how relative differences varied over the pandemic. - -MethodsAnalysis of cohort data from the UK Office of National Statistics Coronavirus (COVID-19) Infection Survey from April 2020 to November 2021. This survey is designed to be representative of the UK population and uses regular PCR testing. Cox and multilevel logistic regression to compare SARS-CoV-2 infection between occupational/sector groups, overall and by four time periods with interactions, adjusted for age, sex, ethnicity, deprivation, region, household size, urban/rural neighbourhood and current health conditions. +medRxiv,10.1101/2022.05.06.22274658,2022-05-07,https://medrxiv.org/cgi/content/short/2022.05.06.22274658,"STIMULATE-ICP-CAREINEQUAL - Defining usual care and examining inequalities in Long Covid support: protocol for a mixed-methods study (part of STIMULATE-ICP: Symptoms, Trajectory, Inequalities and Management: Understanding Long-COVID to Address and Transform Existing Integrated Care Pathways).",Mel Ramasawmy; Yi Mu; Donna Clutterbuck; Marija Pantelic; Gregory Y.H. Lip; Christina Van der Feltz-Cornelis; Dan Wootton; Nefyn H Williams; Hugh Montgomery; Rita Mallinson Cookson; Emily Attree; Mark Gabbay; Melissa J Heightman; Nisreen A Alwan; Amitava Banerjee; Paula Lorgelly; - STIMULATE-ICP consortium,"Institute of Health Informatics, University College London; Institute of Health Informatics, University College London; School of Primary Care, Population Sciences and Medical Education, University of Southampton; Brighton and Sussex Medical School, University of Sussex; Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool, United Kingdom; and Department of Clinical; Department of Health Sciences, HYMS, University of York, and Institute of Health Informatics, University College London; Institute of Infection Veterinary and Ecological Sciences, University of Liverpool; Department of Primary Care and Mental Health, University of Liverpool; Centre for Human Health and Performance, Department of Medicine, University College London; PPIE Representative; PPIE Representative; Department of Primary Care and Mental Health, University of Liverpool; University College London Hospitals NHS Trust; School of Primary Care, Population Sciences and Medical Education, University of Southampton; NIHR Southampton Biomedical Research Centre, University of Southam; Institute of Health Informatics, University College London; School of Population Health and Department of Economics, University of Auckland; ","IntroductionIndividuals with Long Covid represent a new and growing patient population. In England, fewer than 90 Long Covid clinics deliver assessment and treatment informed by NICE guidelines. However, a paucity of clinical trials or longitudinal cohort studies means that the epidemiology, clinical trajectory, healthcare utilisation and effectiveness of current Long Covid care are poorly documented, and that neither evidence-based treatments nor rehabilitation strategies exist. In addition, and in part due to pre-pandemic health inequalities, access to referral and care varies, and patient experience of the Long Covid care pathways can be poor. -ResultsBased on 3,910,311 observations from 312,304 working age adults, elevated risks of infection can be seen overall for social care (HR 1.14; 95% CI 1.04 to 1.24), education (HR 1.31; 95% CI 1.23 to 1.39), bus and coach drivers (1.43; 95% CI 1.03 to 1.97) and police and protective services (HR 1.45; 95% CI 1.29 to 1.62) when compared to non-essential workers. By time period, relative differences were more pronounced early in the pandemic. For healthcare elevated odds in the early waves switched to a reduction in the later stages. Education saw raises after the initial lockdown and this has persisted. Adjustment for covariates made very little difference to effect estimates. +In a mixed methods study, we therefore aim to: (1) describe the usual healthcare, outcomes and resource utilisation of individuals with Long Covid; (2) assess the extent of inequalities in access to Long Covid care, and specifically to understand Long Covid patients experiences of stigma and discrimination. -ConclusionsElevated risks among healthcare workers have diminished over time but education workers have had persistently higher risks. Long-term mitigation measures in certain workplaces may be warranted. +Methods and analysisA mixed methods study will address our aims. Qualitative data collection from patients and health professionals will be achieved through surveys, interviews and focus group discussions, to understand their experience and document the function of clinics. A patient cohort study will provide an understanding of outcomes and costs of care. Accessible data will be further analysed to understand the nature of Long Covid, and the care received. -What is already known on this topicSome occupational groups have observed increased rates of disease and mortality relating to COVID-19. - -What this study addsRelative differences between occupational groups have varied during different stages of the COVID-19 pandemic with risks for healthcare workers diminishing over time and workers in the education sector seeing persistent elevated risks. - -How this study might affect research, practice or policyIncreased long term mitigation such as ventilation should be considered in sectors with a persistent elevated risk. It is important for workplace policy to be responsive to evolving pandemic risks.",occupational and environmental health,exact,100,100 +Ethics and disseminationEthical approval was obtained from South Central - Berkshire Research Ethics Committee (reference 303958). The dissemination plan will be decided by the patient and public involvement and engagement (PPIE) group members and study Co-Is, but will target 1) policy makers, and those responsible for commissioning and delivering Long Covid services, 2) patients and the public, and 3) academics.",health systems and quality improvement,exact,100,100 medRxiv,10.1101/2022.04.26.22274332,2022-04-27,https://medrxiv.org/cgi/content/short/2022.04.26.22274332,"Community factors and excess mortality in the COVID-19 pandemic in England, Italy and Sweden",Brandon Parkes; Massimo Stafoggia; Daniela Fecht; Bethan Davies; Carl Bonander; Francesca de'Donato; Paola Michelozzi; Frédéric B. Piel; Ulf Strömberg; Marta Blangiardo,Imperial College London; Lazio Regional Health Service; Imperial College London; Imperial College London; University of Gothenburg; Lazio Regional Health Service; Lazio Regional Health Service; Imperial College London; University of Gothenburg; Imperial College London,"BackgroundAnalyses of COVID-19 suggest specific risk factors make communities more or less vulnerable to pandemic related deaths within countries. What is unclear is whether the characteristics affecting vulnerability of small communities within countries produce similar patterns of excess mortality across countries with different demographics and public health responses to the pandemic. Our aim is to quantify community-level variations in excess mortality within England, Italy and Sweden and identify how such spatial variability was driven by community-level characteristics. MethodsWe applied a two-stage Bayesian model to quantify inequalities in excess mortality in people aged 40 years and older at the community level in England, Italy and Sweden during the first year of the pandemic (March 2020-February 2021). We used community characteristics measuring deprivation, air pollution, living conditions, population density and movement of people as covariates to quantify their associations with excess mortality. @@ -731,6 +662,30 @@ ConclusionThere is no evidence of an association between COVID-19 vaccination an What is already known on this topicSeveral studies have highlighted the association between COVID-19 vaccination and the risk of myocarditis, myopericarditis, and other cardiac problems, especially in young people, but associated risk of mortality is unclear. Since younger people have lower risk of COVID-19 hospitalisation and mortality, the mortality risk associated with vaccination is potentially more important to them in balancing the risk and benefit of vaccination. What this study addsAlthough there is a risk of myocarditis or myopericarditis with COVID-19, there is no evidence of increased risk of cardiac or all-cause mortality following COVID-19 vaccination in young people aged 12 to 29. Given the increased risk of mortality following SARS-CoV-2 infection in this group, the risk-benefit analysis favours COVID-19 vaccination for this age group.",epidemiology,exact,100,100 +medRxiv,10.1101/2022.03.18.22272607,2022-03-21,https://medrxiv.org/cgi/content/short/2022.03.18.22272607,"Multi-organ impairment and Long COVID: a 1-year prospective, longitudinal cohort study",Andrea Dennis; Daniel J Cuthbertson; Dan Wootton; Michael Crooks; Mark Gabbay; Nicole Eichert; Sofia Mouchti; Michele Pansini; Adriana Roca-Fernandez; Helena Thomaides-Brears; Matt Kelly; Matthew Robson; Lyth Hishmeh; Emily Attree; Melissa J Heightman; Rajarshi Banerjee; Amitava Banerjee,Perspectum Ltd; University of Liverpool; University of Liverpool; University of Hull; University of Liverpool; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Diagnostics; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Long COVID SoS; UKDoctors#Longcovid; UCLH; Perspectum Ltd; University College London,"ImportanceMulti-organ impairment associated with Long COVID is a significant burden to individuals, populations and health systems, presenting challenges for diagnosis and care provision. Standardised assessment across multiple organs over time is lacking, particularly in non-hospitalised individuals. + +ObjectiveTo determine the prevalence of organ impairment in Long COVID patients at 6 and at 12 months after initial symptoms and to explore links to clinical presentation. + +DesignThis was a prospective, longitudinal study in individuals following recovery from acute COVID-19. We assessed symptoms, health status, and multi-organ tissue characterisation and function, using consensus definitions for single and multi-organ impairment. Physiological and biochemical investigations were performed at baseline on all individuals and those with organ impairment were reassessed, including multi-organ MRI, 6 months later. + +SettingTwo non-acute settings (Oxford and London). + +Participants536 individuals (mean 45 years, 73% female, 89% white, 32% healthcare workers, 13% acute COVID-19 hospitalisation) completed baseline assessment (median: 6 months post-COVID-19). 331 (62%) with organ impairment or incidental findings had follow up, with reduced symptom burden from baseline (median number of symptoms: 10 and 3, at 6 and 12 months). + +ExposureSARS-CoV-2 infection 6 months prior to first assessment. + +Main outcomePrevalence of single and multi-organ impairment at 6 and 12 months post-COVID-19. + +ResultsExtreme breathlessness (36% and 30%), cognitive dysfunction (50% and 38%) and poor health-related quality of life (EQ-5D-5L<0.7; 55% and 45%) were common at 6 and 12 months, and associated with female gender, younger age and single organ impairment. At baseline, there was fibro-inflammation in the heart (9%), pancreas (9%), kidney (15%) and liver (11%); increased volume in liver (7%), spleen (8%) and kidney (9%); decreased capacity in lungs (2%); and excessive fat deposition in the liver (25%) and pancreas (15%). Single and multi-organ impairment were present in 59% and 23% at baseline, persisting in 59% and 27% at follow-up. + +Conclusion and RelevanceOrgan impairment was present in 59% of individuals at 6 months post-COVID-19, persisting in 59% of those followed up at 1 year, with implications for symptoms, quality of life and longer-term health, signalling need for prevention and integrated care of Long COVID. + +Trial RegistrationClinicalTrials.gov Identifier: NCT04369807 + +Key pointsO_LIQuestion: What is the prevalence of organ impairment in Long COVID at 6- and 12-months post-COVID-19? +C_LIO_LIFindings: In a prospective study of 536 mainly non-hospitalised individuals, symptom burden decreased, but single organ impairment persisted in 59% at 12 months post-COVID-19. +C_LIO_LIMeaning: Organ impairment in Long COVID has implications for symptoms, quality of life and longer-term health, signalling need for prevention and integrated care of Long COVID. +C_LI",infectious diseases,exact,100,100 medRxiv,10.1101/2022.03.17.22272414,2022-03-18,https://medrxiv.org/cgi/content/short/2022.03.17.22272414,Modelling the impact of non-pharmaceutical interventions on workplace transmission of SARS-CoV-2 in the home-delivery sector,Carl A Whitfield; Martie Van Tongeren; Yang Han; Hua Wei; Sarah A Daniels; Martyn Regan; David W Denning; Arpana Verma; Lorenzo Pellis; - University of Manchester COVID-19 Modelling Group; Ian Hall,University of Manchester; University of Manchester; University of Manchester; University of Manchester; University of Manchester; University of Manchester; University of Manchaster; University of Manchester; University of Manchester; ; University of Manchester,"ObjectiveWe aimed to use mathematical models of SARS-COV-2 to assess the potential efficacy of non-pharmaceutical interventions on transmission in the parcel delivery and logistics sector. MethodsWe developed a network-based model of workplace contacts based on data and consultations from companies in the parcel delivery and logistics sectors. We used these in stochastic simulations of disease transmission to predict the probability of workplace outbreaks in this settings. Individuals in the model have different viral load trajectories based on SARS-CoV-2 in-host dynamics, which couple to their infectiousness and test positive probability over time, in order to determine the impact of testing and isolation measures. @@ -763,6 +718,7 @@ Added value of this studyWe report findings from a prospective cohort study that This is the first study to examine and describe waning of immunity over a one-year period, as well as vaccine effectiveness of a booster dose, in a large cohort of LTCF staff and residents. Implications of all the available evidenceTaken together, our findings indicate high short-term immunity against SARS-CoV2 infection and very high immunity against severe clinical outcomes of COVID-19 for LTCF residents and staff following vaccination. However substantial waning in vaccine-derived immunity is seen beyond 3 months, irrespective of vaccine type, suggesting the need for regular boosting to maintain protection in this vulnerable cohort. Although this analysis took place in the pre-Omicron period, these trends of waning immunity over time are likely to be generalisable across variants, carrying important implications for long-term vaccination policy in LTCFs. Ongoing surveillance in this vulnerable cohort remains crucial, in order to describe further changes in vaccine-induced immunity, particularly in the context of new variants.",infectious diseases,exact,100,100 +bioRxiv,10.1101/2022.03.08.481609,2022-03-08,https://biorxiv.org/cgi/content/short/2022.03.08.481609,The origins and molecular evolution of SARS-CoV-2 lineage B.1.1.7 in the UK,Verity Hill; Louis du Plessis; Thomas P Alexander Peacock; Dinesh Aggarwal; Alessandro Carabelli; Rachel Colquhoun; Nicholas Ellaby; Eileen Gallagher; Natalie Groves; Ben Jackson; JT McCrone; Anna Price; Theo Sanderson; Emily Scher; Joel Alexander Southgate; Erik Volz; - The COVID-19 genomics UK (COG-UK) consortium; Wendy S Barclay; Jeffrey Barrett; Meera Chand; Thomas R Connor; Ian G. Goodfellow; Ravindra K Gupta; Ewan Harrison; Nicholas Loman; Richard Myers; David L Robertson; Oliver Pybus; Andrew Rambaut,The University of Edinburgh; University of Oxford; University College London (UCL); University of Cambridge; University of Cambridge; University of Edinburgh; UK Health Security Agency; Uk Health Security Agency; UK Health Security Agency; University of Edinburgh; University of Edinburgh; Cardiff University; Sanger Institute; University of Edinburgh; Cardiff University; Imperial College London; -; Imperial College London; Sanger Institute; UK Health Security Agency; Cardiff University; University of Cambridge; University of Cambridge; Sanger Institute; University of Birmingham; UK Health Security Agency; University of Glasgow; University of Oxford; University of Edinburgh,"The first SARS-CoV-2 variant of concern (VOC) to be designated was lineage B.1.1.7, later labelled by the World Health Organisation (WHO) as Alpha. Originating in early Autumn but discovered in December 2020, it spread rapidly and caused large waves of infections worldwide. The Alpha variant is notable for being defined by a long ancestral phylogenetic branch with an increased evolutionary rate, along which only two sequences have been sampled. Alpha genomes comprise a well-supported monophyletic clade within which the evolutionary rate is more typical of SARS-CoV-2. The Alpha epidemic continued to grow despite the continued restrictions on social mixing across the UK, and the imposition of new restrictions, in particular the English national lockdown in November 2020. While these interventions succeeded in reducing the absolute number of cases, the impact of these non-pharmaceutical interventions was predominantly to drive the decline of the SARS-CoV-2 lineages which preceded Alpha. We investigate the only two sampled sequences that fall on the branch ancestral to Alpha. We find that one is likely to be a true intermediate sequence, providing information about the order of mutational events that led to Alpha. We explore alternate hypotheses that can explain how Alpha acquired a large number of mutations yet remained largely unobserved in a region of high genomic surveillance: an under-sampled geographical location, a non-human animal population, or a chronically-infected individual. We conclude that the last hypothesis provides the best explanation of the observed behaviour and dynamics of the variant, although we find that the individual need not be immunocompromised, as persistently-infected immunocompetent hosts also display a higher within-host rate of evolution. Finally, we compare the ancestral branches and mutation profiles of other VOCs to each other, and identify that Delta appears to be an outlier both in terms of the genomic locations of its defining mutations, and its lack of rapid evolutionary rate on the ancestral branch. As new variants, such as Omicron, continue to evolve (potentially through similar mechanisms) it remains important to investigate the origins of other variants to identify ways to potentially disrupt their evolution and emergence.",evolutionary biology,exact,100,100 medRxiv,10.1101/2022.03.06.21267462,2022-03-08,https://medrxiv.org/cgi/content/short/2022.03.06.21267462,Risk of myocarditis and pericarditis following COVID-19 vaccination in England and Wales,Samanatha Ip; Fatemeh Torabi; Spiros Denaxas; Ashley Akbari; Hoda Abbasizanjani; Rochelle Knight; Jennifer Anne Cooper; Rachel Denholm; Spencer Keene; Thomas Bolton; Sam Hollings; Efosa Omigi; Teri-Louise North; Arun Karthikeyan Suseeladevi; Emanuele Di Angelantonio; Kamlesh Khunti; Jonathan A C Sterne; Cathie Sudlow; William Whiteley; Angela Wood; Venexia Walker; - British Heart Foundation Data Science Centre (HDR UK) CVD-COVID-UK/COVID-IMPACT Consortium; - UK Covid-19 Longitudinal Health and Wellbeing National Core Study; - UK Covid-19 Data and Connectivity National Core Study,University of Cambridge; Swansea University; University College London; Swansea University; Swansea University; University of Bristol; University of Bristol; University of Bristol; University of Cambridge; Health Data Research UK; NHS Digital; NHS Digital; University of Bristol; University of Bristol; University of Cambridge; University of Leicester; University of Bristol; Health Data Research UK; University of Edinburgh; University of Cambridge; University of Bristol; ; ; ,"We describe our analyses of data from over 49.7 million people in England, representing near-complete coverage of the relevant population, to assess the risk of myocarditis and pericarditis following BNT162b2 and ChAdOx1 COVID-19 vaccination. A self-controlled case series (SCCS) design has previously reported increased risk of myocarditis after first ChAdOx1, BNT162b2, and mRNA-1273 dose and after second doses of mRNA COVID-19 vaccines in England. Here, we use a cohort design to estimate hazard ratios for hospitalised or fatal myocarditis/pericarditis after first and second doses of BNT162b2 and ChAdOx1 vaccinations. SCCS and cohort designs are subject to different assumptions and biases and therefore provide the opportunity for triangulation of evidence. In contrast to the findings from the SCCS approach previously reported for England, we found evidence for lower incidence of hospitalised or fatal myocarditis/pericarditis after first ChAdOx1 and BNT162b2 vaccination, as well as little evidence to suggest higher incidence of these events after second dose of either vaccination.",epidemiology,exact,100,100 medRxiv,10.1101/2022.02.24.22271466,2022-02-25,https://medrxiv.org/cgi/content/short/2022.02.24.22271466,Risk of COVID-19 related deaths for SARS-CoV-2 Omicron (B.1.1.529) compared with Delta (B.1.617.2),Isobel L. Ward; Charlotte Bermingham; Daniel Ayoubkhani; Owen J. Gethings; Koen Pouwels; Thomas Yates; Kamlesh Khunti; Julia Hippisley-Cox; Amitava Banerjee; Ann Sarah Walker; Vahe Nafilyan,"Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford; Diabetes Research Centre, University of Leicester; Diabetes Research Centre, University of Leicester; University of Oxford; University College London; University of Oxford; Office for National Statistics","ObjectiveTo assess the risk of death involving COVID-19 following infection from Omicron (B.1.1.539/BA.1) relative to Delta (B.1.617.2). @@ -846,6 +802,26 @@ ResultsRisk of hospital admission was markedly lower in 1241 residents infected ConclusionsRisk of severe outcomes in LTCF residents with the SARS-CoV-2 Omicron variant was substantially lower than that seen for previous variants. This suggests the current wave of Omicron infections is unlikely to lead to a major surge in severe disease in LTCF populations with high levels of vaccine coverage and/or natural immunity. Trial Registration NumberISRCTN 14447421",infectious diseases,exact,100,100 +medRxiv,10.1101/2022.01.21.22269651,2022-01-22,https://medrxiv.org/cgi/content/short/2022.01.21.22269651,"Prior health-related behaviours in children (2014-2020) and association with a positive SARS-CoV-2 test during adolescence (2020-2021): a retrospective cohort study using survey data linked with routine health data in Wales, UK",Emily Marchant; Emily Lowthian; Tom Crick; Lucy Griffiths; Richard Fry; Kevin Dadaczynski; Orkan Okan; Michaela James; Laura Cowley; Fatemeh Torabi; Jonathan Kennedy; Ashley Akbari; Ronan Lyons; Sinead Brophy,Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Fulda University of Applied Sciences; Technical University Munich; Swansea University; Public Health Wales; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University,"ObjectivesExamine if pre-COVID-19 pandemic (prior March 2020) health-related behaviours during primary school are associated with i) being tested for SARS-CoV-2 and ii) testing positive between 1 March 2020 to 31 August 2021. + +DesignRetrospective cohort study using an online cohort survey (January 2018 to February 2020) linked to routine PCR SARS-CoV-2 test results. + +SettingChildren attending primary schools in Wales (2018-2020), UK who were part of the HAPPEN school network. + +ParticipantsComplete linked records of eligible participants were obtained for n=7,062 individuals. 39.1% (n=2,764) were tested (age 10.6{+/-}0.9, 48.9% girls) and 8.1% (n=569) tested positive for SARS-CoV-2 (age 10.6{+/-}1.0, 54.5% girls). + +Main outcome measuresLogistic regression of health-related behaviours and demographics were used to determine Odds Ratios (OR) of factors associated with i) being tested for SARS-CoV-2 and ii) testing positive for SARS-CoV-2. + +ResultsConsuming sugary snacks (1-2 days/week OR=1.24, 95% CI 1.04 - 1.49; 5-6 days/week 1.31, 1.07 - 1.61; reference 0 days) can swim 25m (1.21, 1.06 - 1.39) and age (1.25, 1.16 - 1.35) were associated with an increased likelihood of being tested for SARS-CoV-2. Eating breakfast (1.52, 1.01 - 2.27), weekly physical activity [≥] 60 mins (1-2 days 1.69, 1.04 - 2.74; 3-4 days 1.76, 1.10 - 2.82, reference 0 days), out of school club participation (1.06, 1.02 - 1.10), can ride a bike (1.39, 1.00 - 1.93), age (1.16, 1.05 - 1.28) and girls (1.21, 1.00 - 1.46) were associated with an increased likelihood of testing positive for SARS-CoV-2. Living in least deprived quintiles 4 (0.64, 0.46 - 0.90) and 5 (0.64, 0.46 - 0.89) compared to the most deprived quintile was associated with a decreased likelihood. + +ConclusionsAssociations may be related to parental health literacy and monitoring behaviours. Physically active behaviours may include co-participation with others, and exposure to SARS-CoV-2. A risk versus benefit approach must be considered given the importance of health-related behaviours for development. + +STRENGTHS AND LIMITATIONSO_LIInvestigation of the association of pre-pandemic child health-related behaviour measures with subsequent SARS-CoV-2 testing and infection. +C_LIO_LIReporting of multiple child health behaviours linked at an individual-level to routine records of SARS-CoV-2 testing data through the SAIL Databank. +C_LIO_LIChild-reported health behaviours were measured before the COVID-19 pandemic (1 January 2018 to 28 February 2020) which may not reflect behaviours during COVID-19. +C_LIO_LIHealth behaviours captured through the national-scale HAPPEN survey represent children attending schools that engaged with the HAPPEN Wales primary school network and may not be representative of the whole population of Wales. +C_LIO_LIThe period of study for PCR-testing for and testing positive for SARS-CoV-2 includes a time frame with varying prevalence rates, approaches to testing children (targeted and mass testing) and restrictions which were not measured in this study. +C_LI",public and global health,exact,100,100 medRxiv,10.1101/2022.01.18.22269082,2022-01-18,https://medrxiv.org/cgi/content/short/2022.01.18.22269082,OMICRON-ASSOCIATED CHANGES IN SARS-COV-2 SYMPTOMS IN THE UNITED KINGDOM,Karina-Doris Vihta; Koen B. Pouwels; Tim EA Peto; Emma Pritchard; Thomas House; Ruth Studley; Emma Rourke; Duncan Cook; Ian Diamond; Derrick Crook; David A Clifton; Philippa C. Matthews; Nicole Stoesser; David W. Eyre; Ann Sarah Walker; - COVID-19 Infection Survey team,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Manchester; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistcs; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; ,"BackgroundThe SARS-CoV-2 Delta variant has been replaced by the highly transmissible Omicron BA.1 variant, and subsequently by Omicron BA.2. It is important to understand how these changes in dominant variants affect reported symptoms, while also accounting for symptoms arising from other co-circulating respiratory viruses. MethodsIn a nationally representative UK community study, the COVID-19 Infection Survey, we investigated symptoms in PCR-positive infection episodes vs. PCR-negative study visits over calendar time, by age and vaccination status, comparing periods when the Delta, Omicron BA.1 and BA.2 variants were dominant. @@ -869,21 +845,6 @@ Main outcome measuresMonthly counts, percent annual change (1st April 2018 to 31 ResultsYear-on-year change in dispensed CVD medicines by month were observed, with notable uplifts ahead of the first (11.8% higher in March 2020) but not subsequent national lockdowns. Using hypertension as one example of the indirect impact of the pandemic, we observed 491,203 fewer individuals initiated antihypertensive treatment across England, Scotland and Wales during the period March 2020 to end May 2021 than would have been expected compared to 2019. We estimated that this missed antihypertension treatment could result in 13,659 additional CVD events should individuals remain untreated, including 2,281 additional myocardial infarctions (MIs) and 3,474 additional strokes. Incident use of lipid-lowering medicines decreased by an average 14,793 per month in early 2021 compared with the equivalent months prior to the pandemic in 2019. In contrast, the use of incident medicines to treat type-2 diabetes (T2DM) increased by approximately 1,642 patients per month. ConclusionsManagement of key CVD risk factors as proxied by incident use of CVD medicines has not returned to pre-pandemic levels in the UK. Novel methods to identify and treat individuals who have missed treatment are urgently required to avoid large numbers of additional future CVD events, further adding indirect cost of the COVID-19 pandemic.",cardiovascular medicine,exact,100,100 -medRxiv,10.1101/2021.12.21.21268058,2021-12-27,https://medrxiv.org/cgi/content/short/2021.12.21.21268058,"Effectiveness of CoronaVac, ChAdOx1, BNT162b2 and Ad26.COV2.S among individuals with prior SARS-CoV-2 infection in Brazil",Thiago Cerqueira-Silva; Jason R Andrews; Viviane S Boaventura; Otavio T Ranzani; Vinicius de Araujo Oliveira; Enny S Paixao; Juracy Bertoldo Jr.; Tales Mota Machado; Matt D T Hitchings; Murilo Dorion; Margaret L Lind; Gerson O. Penna; Derek A.T. Cummings; Natalie E Dean; Guilherme Loureiro Werneck; Neil Pearce; Mauricio L Barreto; Albert I Ko; Julio Croda; Manoel Barral-Netto,"Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA,USA; Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Universidade Federal da Bahia, Salvador, BA, Brazil; Barcelona Institute for Global Health, ISGlobal, Spain / Pulmonary Division, University of Sao Paulo; Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Healt; London School of Hygiene and Tropical Medicine, London, United Kingdom; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Health - Fiocruz, Salvador, BA, Brazil; Universidade Federal de Ouro Preto, Ouro Preto, MG, Brazil; Department of Biostatistics, College of Public Health & Health Professions, University of Florida, Gainesville, FL, USA; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Heaven, CT, USA; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Heaven, CT, USA; Nucleo de Medicina Tropical, Universidade de Brasilia, Brasilia, DF, Brazil; Escola Fiocruz de Governo, Fiocruz Brasilia. Brasilia, DF, Brazil; Department of Biology, University of Florida, Gainesville, FL, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA; Department of Biostatistics & Bioinformatics, Rollins School of Public Health, Emory University; Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil; London School of Hygiene and Tropical Medicine; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Health - Fiocruz, Salvador, BA, Brazil; Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Heaven, CT, USA; Universidade Federal de Mato Grosso do Sul, Campo Grande, MS, Brazil; Fiocruz Mato Grosso do Sul, Fundacao Oswaldo Cruz, Campo Grande, MS, Brazil; Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Healt","BackgroundCOVID-19 vaccines have proven highly effective among SARS-CoV-2 naive individuals, but their effectiveness in preventing symptomatic infection and severe outcomes among individuals with prior infection is less clear. - -MethodsUtilizing national COVID-19 notification, hospitalization, and vaccination datasets from Brazil, we performed a case-control study using a test-negative design to assess the effectiveness of four vaccines (CoronaVac, ChAdOx1, Ad26.COV2.S and BNT162b2) among individuals with laboratory-confirmed prior SARS-CoV-2 infection. We matched RT-PCR positive, symptomatic COVID-19 cases with RT-PCR-negative controls presenting with symptomatic illnesses, restricting both groups to tests performed at least 90 days after an initial infection. We used multivariable conditional logistic regression to compare the odds of test positivity, and the odds of hospitalization or death due to COVID-19, according to vaccination status and time since first or second dose of vaccines. - -FindingsAmong individuals with prior SARS-CoV-2 infection, vaccine effectiveness against symptomatic infection [≥] 14 days from vaccine series completion was 39.4% (95% CI 36.1-42.6) for CoronaVac, 56.0% (95% CI 51.4-60.2) for ChAdOx1, 44.0% (95% CI 31.5-54.2) for Ad26.COV2.S, and 64.8% (95% CI 54.9-72.4) for BNT162b2. For the two-dose vaccine series (CoronaVac, ChAdOx1, and BNT162b2), effectiveness against symptomatic infection was significantly greater after the second dose compared with the first dose. Effectiveness against hospitalization or death [≥] 14 days from vaccine series completion was 81.3% (95% CI 75.3-85.8) for CoronaVac, 89.9% (95% CI 83.5-93.8) for ChAdOx1, 57.7% (95% CI -2.6-82.5) for Ad26.COV2.S, and 89.7% (95% CI 54.3-97.7) for BNT162b2. - -InterpretationAll four vaccines conferred additional protection against symptomatic infections and severe outcomes among individuals with previous SARS-CoV-2 infection. Provision of a full vaccine series to individuals following recovery from COVID-19 may reduce morbidity and mortality. - -FundingBrazilian National Research Council, Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro, Oswaldo Cruz Foundation, JBS S.A., Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, Generalitat de Catalunya. - -RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed, medRxiv, and SSRN for articles published from January 1, 2020 until December 15, 2021, with no language restrictions, using the search terms ""vaccine effectiveness"" AND ""previous*"" AND (""SARS-CoV-2"" OR ""COVID-19""). We found several studies evaluating ChAdOx1 and BNT162b2, and one additionally reporting on mRNA-1273 and Ad26.COV2.S, which found that previously infected individuals who were vaccinated had lower risk of symptomatic SARS-CoV-2 infection. One study found that risk of hospitalization was lower for previously infected individuals after a full series of BNT162b2 or mRNA-1273. Limited evidence is available comparing effectiveness of one versus two doses among individuals with prior infection. No studies reported effectiveness of inactivated vaccines among previously infected individuals. - -Added value of this studyWe used national databases of COVID-19 case surveillance, laboratory testing, and vaccination from Brazil to investigate effectiveness of CoronaVac, ChAdOx1, Ad26.COV2.S and BNT162b2 among individuals with a prior, laboratory-confirmed SARS-CoV-2 infection. We matched >22,000 RT-PCR-confirmed re-infections with >145,000 RT-PCR-negative controls using a test-negative design. All four vaccines were effective against symptomatic SARS-CoV-2 infections, with effectiveness from 14 days after series completion ranging from 39-65%. For vaccines with two-dose regimens, the second dose provided significantly increased effectiveness compared with one dose. Effectiveness against COVID-19-associated hospitalization or death from 14 days after series completion was >80% for CoronaVac, ChAdOx1and BNT162b2. - -Implications of all the available evidenceWe find evidence that four vaccines, using three different platforms, all provide protection to previously infected individuals against symptomatic SARS-CoV-2 infection and severe outcomes, with a second dose conferring significant additional benefits. These results support the provision of a full vaccine series among individuals with prior SARS-CoV-2 infection.",infectious diseases,exact,100,100 medRxiv,10.1101/2021.12.23.21268276,2021-12-25,https://medrxiv.org/cgi/content/short/2021.12.23.21268276,Risk of myocarditis following sequential COVID-19 vaccinations by age and sex,Martina Patone; Winnie Xue Mei; Lahiru Handunnetthi; Sharon Dixon; Francesco Zaccardi; Manu Shankar-Hari; Peter Watkinson; Kamlesh Khunti; Anthony Harnden; Carol AC Coupland; Keith M. Channon; Nicholas L Mills; Aziz Sheikh; Julia Hippisley-Cox,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Leicester; University of Edinburgh; University of Oxford; University of Leicester; University of Oxford; University of Oxford; University of Oxford; University of Edinburgh; University of Edinburgh; University of Oxford,"In an updated self-controlled case series analysis of 42,200,614 people aged 13 years or more, we evaluate the association between COVID-19 vaccination and myocarditis, stratified by age and sex, including 10,978,507 people receiving a third vaccine dose. Myocarditis risk was increased during 1-28 days following a third dose of BNT162b2 (IRR 2.02, 95%CI 1.40, 2.91). Associations were strongest in males younger than 40 years for all vaccine types with an additional 3 (95%CI 1, 5) and 12 (95% CI 1,17) events per million estimated in the 1-28 days following a first dose of BNT162b2 and mRNA-1273, respectively; 14 (95%CI 8, 17), 12 (95%CI 1, 7) and 101 (95%CI 95, 104) additional events following a second dose of ChAdOx1, BNT162b2 and mRNA-1273, respectively; and 13 (95%CI 7, 15) additional events following a third dose of BNT162b2, compared with 7 (95%CI 2, 11) additional events following COVID-19 infection. An association between COVID-19 infection and myocarditis was observed in all ages for both sexes but was substantially higher in those older than 40 years. These findings have important implications for public health and vaccination policy. FundingHealth Data Research UK.",epidemiology,exact,100,100 @@ -947,13 +908,6 @@ ResultsAmong the 1226855 CYP in the cohort, there were 378402 tests, 19005 PCR c ConclusionsInfants, and CYP with chronic conditions are at highest risk of admission with COVID-19, however the majority of admitted CYP have no chronic conditions. These results provide evidence to support risk/benefit analyses for paediatric COVID-19 vaccination programmes. Studies examining whether maternal vaccine during pregnancy prevents COVID-19 admissions in infants are urgently needed. FundingUK Research and Innovation-Medical Research Council",epidemiology,exact,100,100 -medRxiv,10.1101/2021.12.16.21267906,2021-12-16,https://medrxiv.org/cgi/content/short/2021.12.16.21267906,Workplace Contact Patterns in England during the COVID-19 Pandemic: Analysis of the Virus Watch prospective cohort study,Sarah Beale; Susan J Hoskins; Thomas Edward Byrne; Erica Wing Lam Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Annalan MD Navaratnam; Vincent Nguyen; Parth Patel; Alexei Yavlinsky; Anne M Johnson; Robert W Aldridge; Andrew Hayward,University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London,"BackgroundWorkplaces are an important potential source of SARS-CoV-2 exposure; however, investigation into workplace contact patterns is lacking. This study aimed to investigate how workplace attendance and features of contact varied between occupations and over time during the COVID-19 pandemic in England. - -MethodsData were obtained from electronic contact diaries submitted between November 2020 and November 2021 by employed/self-employed prospective cohort study participants (n=4,616). We used mixed models to investigate the main effects and potential interactions between occupation and time for: workplace attendance, number of people in shared workspace, time spent sharing workspace, number of close contacts, and usage of face coverings. - -FindingsWorkplace attendance and contact patterns varied across occupations and time. The predicted probability of intense space sharing during the day was highest for healthcare (78% [95% CI: 75-81%]) and education workers (64% [59%-69%]), who also had the highest probabilities for larger numbers of close contacts (36% [32%-40%] and 38% [33%-43%] respectively). Education workers also demonstrated relatively low predicted probability (51% [44%-57%]) of wearing a face covering during close contact. Across all occupational groups, levels of workspace sharing and close contact were higher and usage of face coverings at work lower in later phases of the pandemic compared to earlier phases. - -InterpretationMajor variations in patterns of workplace contact and mask use are likely to contribute to differential COVID-19 risk. Across occupations, increasing workplace contact and reduced usage of face coverings presents an area of concern given ongoing high levels of community transmission and emergence of variants.",epidemiology,exact,100,100 medRxiv,10.1101/2021.12.13.21267471,2021-12-15,https://medrxiv.org/cgi/content/short/2021.12.13.21267471,Clinical characteristics with inflammation profiling of Long-COVID and association with one-year recovery following hospitalisation in the UK: a prospective observational study,Rachael Andrea Evans; Olivia C Leavy; Matthew Richardson; Omer Elneima; Hamish J C McAuley; Aarti Shikotra; Amisha Singapuri; Marco Sereno; Ruth M Saunders; Victoria C Harris; Raminder Aul; Paul Beirne; Charlotte E Bolton; Jeremy S Brown; Gourab Choudhury; Nawar Diar Bakerly; Nicholas Easom; Carlos Echevarria; Jonathan Fuld; Nick Hart; John R Hurst; Mark Jones; Dhruv Parekh; Paul Pfeffer; Najib M Rahman; Sarah Rowland-Jones; Ajay M Shah; Dan G Wootton; Trudie Chalder; Melanie J Davies; Anthony De Soyza; John R Geddes; William Greenhalf; Neil J Greening; Liam G Heaney; Simon Heller; Luke Howard; Joseph Jacob; R Gisli Jenkins; Janet M Lord; Will D-C Man; Gerry P McCann; Stefan Neubauer; Peter JM Openshaw; Joanna Porter; Jennifer Quint; Matthew J Rowland; Janet Scott; Malcolm G Semple; Sally J Singh; David Thomas; Mark Toshner; Keir Lewis; Andrew Briggs; Annemarie B Docherty; Steven Kerr; Nazir I Lone; Aziz Sheikh; Mathew Thorpe; Bang Zheng; Ryan S Thwaites; James D Chalmers; Ling-Pei Ho; Alex Horsley; Michael Marks; Krisnah Poinasamy; Betty Raman; Ewen M Harrison; Louise V Wain; Christopher E Brightling; - PHOSP-COVID Collaborative Group,"University of Leicester; Department of Health Sciences, University of Leicester, Leicester, United Kingdom; The Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; University Hospitals of Leicester,; St George's Univeristy Hospitals NHS Foundation Trust, London, United Kingdom; The Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom; University of Nottingham, Nottingham, United Kingdom; Nottingham Univeristy Hospitals NHS Trust, Nottingham, United Kingdom; NIHR Nottingham Biomedical Research; UCL Respiratory, Department of Medicine, University College London, Rayne Institute, London, United Kingdom; University of Edinburgh, Edinburgh, Scotland, United Kingdom; NHS Lothian, Scotland, United Kingdom; Manchester Metropolitan University, Manchester, United Kingdom; Salford Royal NHS Foundation Trust, Manchester, United Kingdom; Infection Research Group, Hull University Teaching Hospitals, Hull, United Kingdom; University of Hull, Hull, United Kingdom; The Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle, United Kingdom; Translational and Clinical Research Institute, Newcastle University, Newcastl; Department of Respiratory Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom; University of Cambridge, Cambridge, United K; Lane Fox Respiratory Service, Guys and St Thomas NHS Foundation Trust, London, United Kingdom; University College London, London, United Kingdom; Royal Free London NHS Foundation Trust, London, United Kingdom; University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom; University of Southampton, Southampton, United Kingdom; University of Birmingham, Birmingham, United Kingdom; University Hospital Birmingham NHS Foundation Trust, Birmingham, United Kingdom; Barts Health NHS Trust, London, United Kingdom; Queen Mary University of London, London, United Kingdom; Oxford University Hospitals NHS Trust, Oxford, United Kingdom; University of Oxford, Oxford, United Kingdom; Oxford NIHR Biomedical Research Centre, Oxford, Uni; University of Sheffield, Sheffield, United Kingdom; Sheffield Teaching NHS Foundation Trust, Sheffield, United Kingdom; King's College London, London, United Kingdom; King's College London NHS Foundation Trust, London, United Kingdom; Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, United Kingdom; Liverpool University Hospitals NHS Foundation Tr; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; South London and Maud; Diabetes Research Centre, University of Leicester, Leicester, United Kingdom; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, Uni; Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, United Kingdom; Newcastle upon Tyne Teaching Hospitals Trust, Newcastle upon Ty; University of Oxford; University of Liverpool, Liverpool, United Kingdom; The CRUK Liverpool Experimental Cancer Medicine Centre, Liverpool, United Kingdom; Liverpool University Hosp; The Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; Wellcome-Wolfson Institute for Experimental Medicine, Queens University Belfast, United Kingdom; Belfast Health & Social Care Trust, Belfast, United Kingdom; Department of Oncology and Metabolism, University of Sheffield, Sheffield, United Kingdom; Imperial College Healthcare NHS Trust, London, United Kingdom; Imperial College London, London, United Kingdom; Centre for Medical Image Computing, University College London, London, United Kingdom; Lungs for Living Research Centre, University College London, London, Unit; National Heart and Lung Institute, Imperial College London, London, United Kingdom; MRC-Versus Arthritis Centre for Musculoskeletal Ageing Research, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, United Kingdom; NIH; Royal Brompton and Harefield Clinical Group, Guys and St Thomas NHS Foundation Trust, London, United Kingdom; National Heart and Lung Institute, Imperial Colleg; Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom; NIHR Leicester Biomedical Research Centre, University of Leicester, L; Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom; NIHR Biomedical Research Centre, John Radcl; National Heart and Lung Institute, Imperial College London, London, United Kingdom; UCL Respiratory, Department of Medicine, University College London, Rayne Institute, London, United Kingdom; ILD Service, University College London Hospital, Lo; National Heart and Lung Institute, Imperial College London, London, United Kingdom; Kadoorie Centre for Critical Care Research, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom; MRC-University of Glasgow Centre for Virus Research, Glasgow, Scotland, United Kingdom; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, U; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; Imperial College London, London, UK; NIHR Cambridge Biomedical Research Centre, Cambridge, United Kingdom; NIHR Cambridge Clinical Research Facility, Cambridge, United Kingdom; Hywel Dda University Health Board, Wales, United Kingdom; University of Swansea, Wales, United Kingdom; Respiratory Innovation Wales, Wales, United Kingdom; London School of Hygiene & Tropical Medicine, London, United Kingdom; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, United Kingdom; Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, U; Usher Institute, University of Edinburgh, Edinburgh, United Kingdom; Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, United Kingdom; Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, United Kingdom; University of Edinburgh, Edinburgh, Scotland, United Kingdom; National Heart and Lung Institute, Imperial College London, London, UK; University of Dundee, Ninewells Hospital and Medical School, Dundee, United Kingdom; MRC Human Immunology Unit, University of Oxford, Oxford, United Kingdom; Division of Infection, Immunity & Respiratory Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom; anchester; Department of Clinical Research, London School of Hygiene & Tropical Medicine Keppel Street, London, United Kingdom; Hospital for Tropical Diseases, University ; Asthma UK and British Lung Foundation, London, United Kingdom; Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom; Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, United Kingdom; Department of Health Sciences, University of Leicester, Leicester, United Kingdom; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, Uni; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; University Hospitals of Leicester,; -","BackgroundThere are currently no effective pharmacological or non-pharmacological interventions for Long-COVID. To identify potential therapeutic targets, we focussed on previously described four recovery clusters five months after hospital discharge, their underlying inflammatory profiles and relationship with clinical outcomes at one year. MethodsPHOSP-COVID is a prospective longitudinal cohort study, recruiting adults hospitalised with COVID-19 across the UK. Recovery was assessed using patient reported outcomes measures (PROMs), physical performance, and organ function at five-months and one-year after hospital discharge. Hierarchical logistic regression modelling was performed for patient-perceived recovery at one-year. Cluster analysis was performed using clustering large applications (CLARA) k-medoids approach using clinical outcomes at five-months. Inflammatory protein profiling from plasma at the five-month visit was performed. @@ -986,6 +940,21 @@ MethodsIn this retrospective cohort study, we included all adults ([≥]18 year Results2,311,282 people were included in the study, of whom 164,046 (7.1%) were admitted and 53,156 (2.3%) died within 28 days. There was significant variation in the case hospitalisation and mortality risk over time, peaking in December 2020-February 2021, which remained after adjustment for individual risk factors. Older age groups, males, those resident in more deprived areas, and those with obesity had higher odds of admission and mortality. Of risk factors examined, severe mental illness and learning disability had the highest odds of admission and mortality. ConclusionsIn one of the largest studies of nationally representative Covid-19 risk factors, case hospitalisation and mortality risk varied significantly over time in England during the second pandemic wave, independent of the underlying risk in those infected.",epidemiology,exact,100,100 +medRxiv,10.1101/2021.11.29.21266847,2021-11-30,https://medrxiv.org/cgi/content/short/2021.11.29.21266847,Population level impact of a pulse oximetry remote monitoring programme on mortality and healthcare utilisation in the people with covid-19 in England: a national analysis using a stepped wedge design,Thomas Beaney; Jonathan Clarke; Ahmed Alboksmaty; Kelsey Flott; Aidan Fowler; Jonathan R Benger; Paul Aylin; Sarah Elkin; Ana Luisa Neves; Ara Darzi,Imperial College London; Imperial College London; Imperial College London; Imperial College London; NHS England and Improvement; NHS Digital; Imperial College London; Imperial College London; Imperial College London; Imperial College London,"ObjectivesTo identify the population level impact of a national pulse oximetry remote monitoring programme for covid-19 (COVID Oximetry @home; CO@h) in England on mortality and health service use. + +DesignRetrospective cohort study using a stepped wedge pre- and post-implementation design. + +SettingAll Clinical Commissioning Groups (CCGs) in England implementing a local CO@h programme. + +Participants217,650 people with a positive covid-19 polymerase chain reaction test result and symptomatic, from 1st October 2020 to 3rd May 2021, aged [≥]65 years or identified as clinically extremely vulnerable. Care home residents were excluded. + +InterventionsA pre-intervention period before implementation of the CO@h programme in each CCG was compared to a post-intervention period after implementation. + +Main outcome measuresFive outcome measures within 28 days of a positive covid-19 test: i) death from any cause; ii) any A&E attendance; iii) any emergency hospital admission; iv) critical care admission; and v) total length of hospital stay. + +ResultsImplementation of the programme was not associated with mortality or length of hospital stay. Implementation was associated with increased health service utilisation with a 12% increase in the odds of A&E attendance (95% CI: 6%-18%) and emergency hospital admission (95% CI: 5%-20%) and a 24% increase in the odds of critical care admission in those admitted (95% CI: 5%-47%). In a secondary analysis of CO@h sites with at least 10% or 20% of eligible people enrolled, there was no significant association with any outcome measure. However, uptake of the programme was low, with enrolment data received for only 5,527 (2.5%) of the eligible population. + +ConclusionsAt a population level, there was no association with mortality following implementation of the CO@h programme, and small increases in health service utilisation were observed. Low enrolment of eligible people may have diluted the effects of the programme at a population level.",health systems and quality improvement,exact,100,100 medRxiv,10.1101/2021.11.29.21266996,2021-11-29,https://medrxiv.org/cgi/content/short/2021.11.29.21266996,Deficits in planned hospital care for vulnerable adolescents in England during the COVID-19 pandemic: analysis of linked administrative data,Louise Mc Grath-Lone; David Etoori; Ruth Gilbert; Katie Harron; Jenny Woodman; Ruth Blackburn,University College London; University College London; University College London; University College London; University College London; University College London,"Planned hospital care (outpatient attendances and planned hospital admissions) was disrupted during the pandemic, but we lack evidence on which groups of young people were most impacted. We aimed to describe differences in planned care for vulnerable adolescents receiving childrens social care (CSC) services or special educational needs (SEN) support during the pandemic, relative to their peers. Using the ECHILD Database (linked de-identified administrative health, education and social care records for all children in England), we examined changes in planned hospital care from 23 March to 31 December 2020 for secondary school pupils in Years 7 to 11 (N=3,030,235). There were large deficits in planned care for adolescents overall, which disproportionately affected the 21% receiving SEN support or CSC services who bore 25% of the outpatient attendance deficit and 37% of the planned admissions deficit. These findings indicate a need for targeted catch-up funding and resources, particularly for vulnerable groups.",public and global health,exact,100,100 medRxiv,10.1101/2021.11.25.21266848,2021-11-29,https://medrxiv.org/cgi/content/short/2021.11.25.21266848,Evaluating the impact of a pulse oximetry remote monitoring programme on mortality and healthcare utilisation in patients with covid-19 assessed in Accident and Emergency departments in England: a retrospective matched cohort study,Thomas Beaney; Jonathan Clarke; Ahmed Alboksmaty; Kelsey Flott; Aidan Fowler; Jonathan R Benger; Paul Aylin; Sarah Elkin; Ara Darzi; Ana Luisa Neves,Imperial College London; Imperial College London; Imperial College London; Imperial College London; NHS England and Improvement; NHS Digital; Imperial College London; Imperial College London; Imperial College London; Imperial College London,"ObjectivesTo identify the impact of a national pulse oximetry remote monitoring programme for covid-19 (COVID Oximetry @home; CO@h) on health service use and mortality in patients attending Accident and Emergency (A&E) departments. @@ -1002,6 +971,7 @@ Main outcome measuresFive outcome measures were examined within 28 days of first Results15,621 participants were included in the primary analysis, of whom 639 were enrolled onto CO@h and 14,982 were controls. Odds of death were 52% lower in those enrolled (95% CI: 7%-75% lower) compared to those not enrolled on CO@h. Odds of any A&E attendance or admission were 37% (95% CI: 16-63%) and 59% (95% CI: 16-63%) higher, respectively, in those enrolled. Of those admitted, those enrolled had 53% (95% CI: 7%-76%) lower odds of critical care admission. There was no significant impact on length of stay. ConclusionsThese findings indicate that for patients assessed in A&E, pulse oximetry remote monitoring may be a clinically effective and safe model for early detection of hypoxia and escalation, leading to increased subsequent A&E attendance and admissions, and reduced critical care requirement and mortality.",health systems and quality improvement,exact,100,100 +bioRxiv,10.1101/2021.11.24.469860,2021-11-26,https://biorxiv.org/cgi/content/short/2021.11.24.469860,Nanopore ReCappable Sequencing maps SARS-CoV-2 5' capping sites and provides new insights into the structure of sgRNAs,Camilla Ugolini; Logan Mulroney; Adrien Leger; Matteo Castelli; Elena Criscuolo; Maia Kavanagh Williamson; Andrew D Davidson; Abdulaziz Almuqrin; Roberto Giambruno; Miten Jain; Gianmaria Frigè; Hugh Olsen; George Tzertzinis; Ira Schildkraut; Madalee F Wulf; Ivan R. Corrêa Jr.; Laurence Ettwiller; Nicola Clementi; Massimo Clementi; Nicasio Mancini; Ewan Birney; Mark Akeson; Francesco Nicassio; David A Matthews; Tommaso Leonardi,Italian Institute of Technology; Italian Institute of Technology; Oxford Nanopore Technologies; Vita-Salute San Raffaele University; Vita-Salute San Raffaele University; University of Bristol; University of Bristol; University of Bristol; Istituto Italiano di Tecnologia; University of California Santa Cruz; Istituto Europeo di Oncologia; University of California Santa Cruz; New England Biolabs; New England Biolabs; New England Biolabs; New England Biolabs; New England Biolabs Inc; Vita-Salute San Raffaele University; Vita-Salute San Raffaele University; Università Vita-Salute San Raffaele; European Bioinformatics Institute; University of California Santa Cruz; Istituto Italiano di Tecnologia; University of Bristol; Italian Institute of Technology,"The SARS-CoV-2 virus has a complex transcriptome characterised by multiple, nested sub genomic RNAs used to express structural and accessory proteins. Long-read sequencing technologies such as nanopore direct RNA sequencing can recover full-length transcripts, greatly simplifying the assembly of structurally complex RNAs. However, these techniques do not detect the 5' cap, thus preventing reliable identification and quantification of full-length, coding transcript models. Here we used Nanopore ReCappable Sequencing (NRCeq), a new technique that can identify capped full-length RNAs, to assemble a complete annotation of SARS-CoV-2 sgRNAs and annotate the location of capping sites across the viral genome. We obtained robust estimates of sgRNA expression across cell lines and viral isolates and identified novel canonical and non-canonical sgRNAs, including one that uses a previously un-annotated leader-to-body junction site. The data generated in this work constitute a useful resource for the scientific community and provide important insights into the mechanisms that regulate the transcription of SARS-CoV-2 sgRNAs.",genomics,exact,100,100 medRxiv,10.1101/2021.11.22.21266512,2021-11-24,https://medrxiv.org/cgi/content/short/2021.11.22.21266512,Association of COVID-19 with arterial and venous vascular diseases: a population-wide cohort study of 48 million adults in England and Wales,Rochelle Knight; Venexia Walker; Samantha Ip; Jennifer A Cooper; Thomas Bolton; Spencer Keene; Rachel Denholm; Ashley Akbari; Hoda Abbasizanjani; Fatemeh Torabi; Efosa Omigie; Sam Hollings; Teri-Louise North; Renin Toms; Emanuele Di Angelantonio; Spiros Denaxas; Johan H Thygesen; Christopher Tomlinson; Ben Bray; Craig J Smith; Mark Barber; George Davey Smith; Nishi Chaturvedi; Cathie Sudlow; William N Whiteley; Angela Wood; Jonathan A C Sterne; - CVD-COVID-UK/COVID-IMPACT consortium; - Longitudinal Health and Wellbeing COVID-19 National Core Study,University of Bristol; University of Bristol; University of Cambridge; University of Bristol; University of Cambridge; University of Cambridge; University of Bristol; Swansea University; Swansea University; Swansea University; NHS Digital; NHS Digital; University of Bristol; University of Bristol; University of Cambridge; University College London; University College London; University College London; Kings College London; University of Manchester; Glasgow Caledonian University; University of Bristol; University College London; Health Data Research UK; University of Edinburgh; University of Cambridge; University of Bristol; ; ,"ImportanceThe long-term effects of COVID-19 on the incidence of vascular diseases are unclear. ObjectiveTo quantify the association between time since diagnosis of COVID-19 and vascular disease, overall and by age, sex, ethnicity, and pre-existing disease. @@ -1137,21 +1107,6 @@ MethodsWe performed a retrospective observational cohort study of adult contacts Results54,667/146,243(37.4%) PCR-tested contacts of 108,498 index cases were PCR-positive. Two doses of BNT162b2 or ChAdOx1 vaccines in Alpha index cases were independently associated with reduced PCR-positivity in contacts (aRR, adjusted rate ratio vs. unvaccinated=0.32[95%CI 0.21-0.48] and 0.48[0.30-0.78] respectively). The Delta variant attenuated vaccine-associated reductions in transmission: two BNT162b2 doses reduced Delta transmission (aRR=0.50[0.39-0.65]), more than ChAdOx1 (aRR=0.76[0.70-0.82]). Variation in Ct values (indicative of viral load) explained 7-23% of vaccine-associated transmission reductions. Transmission reductions declined over time post-second vaccination, for Delta reaching similar levels to unvaccinated individuals by 12 weeks for ChAdOx1 and attenuating substantially for BNT162b2. Protection in contacts also declined in the 3 months post-second vaccination. ConclusionsVaccination reduces transmission of Delta, but by less than the Alpha variant. The impact of vaccination decreased over time. Factors other than PCR Ct values at diagnosis are important in understanding vaccine-associated transmission reductions. Booster vaccinations may help control transmission together with preventing infections.",infectious diseases,exact,100,100 -medRxiv,10.1101/2021.09.27.21264166,2021-09-29,https://medrxiv.org/cgi/content/short/2021.09.27.21264166,Prevalence and duration of detectable SARS-CoV-2 nucleocapsid antibody in staff and residents of long-term care facilities over the first year of the pandemic (VIVALDI study): prospective cohort study,Maria Krutikov; Tom Palmer; Gokhan Tut; Christopher Fuller; Borscha Azmi; Rebecca Giddings; Madhumita Shrotri; Nayandeep Kaur; Panagiota Sylla; Tara Lancaster; Aidan Irwin-Singer; Andrew Hayward; Paul Moss; Andrew Copas; Laura Shallcross,"University College London; University College London; University of Birmingham, Medical School; University College London; University College London; University College London; University College London; University of Birmingham; University of Birmingham; University of Birmingham; Department of Health & Social Care; UCL; University of Birmingham; University College London; UCL","BackgroundLong Term Care Facilities (LTCF) have reported high SARS-CoV-2 infection rates and related mortality, but the proportion infected amongst survivors and duration of the antibody response to natural infection is unknown. We determined the prevalence and stability of nucleocapsid antibodies - the standard assay for detection of prior infection - in staff and residents from 201 LTCFs. - -MethodsProspective cohort study of residents aged >65 years and staff of LTCFs in England (11 June 2020-7 May 2021). Serial blood samples were tested for IgG antibodies against SARS-CoV-2 nucleocapsid protein. Prevalence and cumulative incidence of antibody-positivity were weighted to the LTCF population. Cumulative incidence of sero-reversion was estimated from Kaplan-Meier curves. - -Results9488 samples were included, 8636 (91%) of which could be individually-linked to 1434 residents or 3288 staff members. The cumulative incidence of nucleocapsid seropositivity was 35% (95% CI: 30-40%) in residents and 26% (95% CI: 23-30%) in staff over 11 months. The incidence rate of loss of antibodies (sero-reversion) was 2{middle dot}1 per 1000 person-days at risk, and median time to reversion was around 8 months. - -InterpretationAt least one-quarter of staff and one-third of surviving residents were infected during the first two pandemic waves. Nucleocapsid-specific antibodies often become undetectable within the first year following infection which is likely to lead to marked underestimation of the true proportion of those with prior infection. Since natural infection may act to boost vaccine responses, better assays to identify natural infection should be developed. - -FundingUK Government Department of Health and Social Care. - -Research in contextO_ST_ABSEvidence before this studyC_ST_ABSA search was conducted of Ovid MEDLINE and MedRxiv on 21 July 2021 to identify studies conducted in long term care facilities (LTCF) that described seroprevalence using the terms ""COVID-19"" or ""SARS-CoV-2"" and ""nursing home"" or ""care home"" or ""residential"" or ""long term care facility"" and ""antibody"" or ""serology"" without date or language restrictions. One meta-analysis was identified, published before the introduction of vaccination, that included 2 studies with a sample size of 291 which estimated seroprevalence as 59% in LTCF residents. There were 28 seroprevalence surveys of naturally-acquired SARS-CoV-2 antibodies in LTCFs; 16 were conducted in response to outbreaks and 12 conducted in care homes without known outbreaks. 16 studies included more than 1 LTCF and all were conducted in Autumn 2020 after the first wave of infection but prior to subsequent peaks. Seroprevalence studies conducted following a LTCF outbreak were biased towards positivity as the included population was known to have been previously infected. In the 12 studies that were conducted outside of known outbreaks, seroprevalence varied significantly according to local prevalence of infection. The largest of these was a cross-sectional study conducted in 9,000 residents and 10,000 staff from 362 LTCFs in Madrid, which estimated seroprevalence in staff as 31{middle dot}5% and 55{middle dot}4% in residents. However, as this study was performed in one city, it may not be generalisable to the whole of Spain and sequential sampling was not performed. Of the 28 studies, 9 undertook longitudinal sampling for a maximum of four months although three of these reported from the same cohort of LTCFs in London. None of the studies reported on antibody waning amongst the whole resident population. - -Added value of this studyWe estimated the proportion of care home staff and residents with evidence of SARS-CoV-2 natural infection using data from over 3,000 staff and 1,500 residents in 201 geographically dispersed LTCFs in England. Population selection was independent of outbreak history and the sample is therefore more reflective of the population who reside and work in LTCFs. Our estimates of the proportion of residents with prior natural infection are substantially higher than estimates based on population-wide PCR testing, due to limited testing coverage at the start of the pandemic. 1361 individuals had at least one positive antibody test and participants were followed for up to 11 months, which allowed modelling of the time to loss of antibody in over 600 individuals in whom the date of primary infection could be reliably estimated. This is the longest reported serological follow up in a population of LTCF residents, a group who are known to be most at risk of severe outcomes following infection with SARS-CoV-2 and provides important evidence on the duration that nucleocapsid antibodies remained detectable over the first and second waves of the pandemic. - -Implications of all available researchA substantial proportion of the LTCF population will have some level of natural immunity to infection as a result of past infection. Immunological studies have highlighted greater antibody responses to vaccination in seropositive individuals, so vaccine efficacy in this population may be affected by this large pool of individuals who have survived past infection. In addition, although the presence of nucleocapsid-specific antibodies is generally considered as the standard marker for prior infection, we find that antibody waning is such that up to 50% of people will lose detectable antibody responses within eight months. Individual prior natural infection history is critical to assess the impact of factors such as vaccine response or protection against re-infection. These findings may have implications for duration of immunity following natural infection and indicate that alternative assays for prior infection should be developed.",epidemiology,exact,100,100 medRxiv,10.1101/2021.09.20.21263828,2021-09-23,https://medrxiv.org/cgi/content/short/2021.09.20.21263828,"Colchicine for COVID-19 in adults in the community (PRINCIPLE): a randomised, controlled, adaptive platform trial",- The PRINCIPLE Trial Collaborative Group; Jienchi Dorward; Ly-Mee Yu; Gail Hayward; Benjamin R Saville; Oghenekome Gbinigie; Oliver van Hecke; Emma Ogburn; Philip H Evans; Nicholas PB Thomas; Mahendra G Patel; Duncan Richards; Nicholas Berry; Michelle A Detry; Christina Saunders; Mark Fitzgerald; Victoria Harris; Milensu Shanyinde; Simon de Lusignan; Monique I Andersson; Christopher C Butler; FD Richard Hobbs,"; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom and Centre for the AIDS Programme of Research in South Africa ; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; Berry Consultants, Texas, USA and Department of Biostatistics, Vanderbilt University School of Medicine, Tennessee, USA; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; College of Medicine and Health, University of Exeter and National Institute for Health Research, Clinical Research Network; Royal College of General Practitioners, London, UK, and National Institute for Health Research, Clinical Research Network; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom and School of Pharmacy and Medical Sciences, University of Bra; Oxford Clinical Trials Research Unit, Botnar Research Centre, University of Oxford, Oxford, UK; Berry Consultants, Texas, USA; Berry Consultants, Texas, USA; Berry Consultants, Texas, USA; Berry Consultants, Texas, USA; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; Nuffield Department of Clinical Medicine, University of Oxford, United Kingdom,; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom","ObjectivesColchicine has been proposed as a COVID-19 treatment, but its effect on time to recovery is unknown. We aimed to determine whether colchicine is effective at reducing time to recovery and COVID-19 related hospitalisations/deaths among people in the community. DesignProspective, multicentre, open-label, multi-arm, adaptive Platform Randomised Trial of Treatments in the Community for Epidemic and Pandemic Illnesses (PRINCIPLE). @@ -1170,6 +1125,22 @@ ConclusionsColchicine did not improve time to recovery in people at higher risk Trial registrationISRCTN86534580.",infectious diseases,exact,100,100 medRxiv,10.1101/2021.09.13.21263487,2021-09-16,https://medrxiv.org/cgi/content/short/2021.09.13.21263487,SARS-CoV-2 anti-spike IgG antibody responses after second dose of ChAdOx1 or BNT162b2 in the UK general population,Jia Wei; Koen B. Pouwels; Nicole Stoesser; Philippa C. Matthews; Ian Diamond; Ruth Studley; Emma Rourke; Duncan Cook; John I Bell; John N Newton; Jeremy Farrar; Alison Howarth; Brian D. Marsden; Sarah Hoosdally; E Yvonne Jones; David I Stuart; Derrick W. Crook; Tim E.A. Peto; A.Sarah Walker; David W. Eyre,University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford,"We investigated anti-spike IgG antibody responses and correlates of protection following second doses of ChAdOx1 or BNT162b2 SARS-CoV-2 vaccines in the UK general population. In 222,493 individuals, we found significant boosting of anti-spike IgG by second doses of both vaccines in all ages and using different dosing intervals, including the 3-week interval for BNT162b2. After second vaccination, BNT162b2 generated higher peak levels than ChAdOX1. Older individuals and males had lower peak levels with BNT162b2 but not ChAdOx1, while declines were similar across ages and sexes with ChAdOX1 or BNT162b2. Prior infection significantly increased antibody peak level and half-life with both vaccines. Anti-spike IgG levels were associated with protection from infection after vaccination and, to an even greater degree, after prior infection. At least 67% protection against infection was estimated to last for 2-3 months after two ChAdOx1 doses and 5-8 months after two BNT162b2 doses in those without prior infection, and 1-2 years for those unvaccinated after natural infection. A third booster dose may be needed, prioritised to ChAdOx1 recipients and those more clinically vulnerable.",infectious diseases,exact,100,100 +medRxiv,10.1101/2021.09.09.21263026,2021-09-13,https://medrxiv.org/cgi/content/short/2021.09.09.21263026,The clinically extremely vulnerable to COVID: Identification and changes in health care while self-isolating (shielding) during the coronavirus pandemic,Jessica Erin Butler; Mintu Nath; Dimitra Blana; William P Ball; Nicola Beech; Corri Black; Graham Osler; Sebastien Peytrignet; Katie Wilde; Artur Wozniak; Simon Sawhney,University of Aberdeen; University of Aberdeen; University of Aberdeen; University of Aberdeen; NHS Grampian; NHS Grampian and University of Aberdeen; NHS Grampian; Health Foundation; University of Aberdeen; University of Aberdeen; NHS Grampian and University of Aberdeen,"BackgroundIn March 2020, the government of Scotland identified people deemed clinically extremely vulnerable to COVID due to their pre-existing health conditions. These people were advised to strictly self-isolate (shield) at the start of the pandemic, except for necessary healthcare. We examined who was identified as clinically extremely vulnerable, how their healthcare changed during isolation, and whether this process exacerbated healthcare inequalities. + +MethodsWe linked those on the shielding register in NHS Grampian, a health authority in Scotland, to healthcare records from 2015-2020. We described the source of identification, demographics, and clinical history of the cohort. We measured changes in out-patient, in-patient, and emergency healthcare during isolation in the shielding population and compared to the general non-shielding population. + +ResultsThe register included 16,092 people (3% of the population), clinically vulnerable primarily due to a respiratory disease, immunosuppression, or cancer. Among them, 42% were not identified by national healthcare record screening but added ad hoc, with these additions including more children and fewer economically-deprived. + +During isolation, all forms of healthcare use decreased (25%-46%), with larger decreases in scheduled care than in emergency care. However, people shielding had better maintained scheduled care compared to the non-shielding general population: out-patient visits decreased 35% vs 49%; in-patient visits decreased 46% vs 81%. Notably, there was substantial variation in whose scheduled care was maintained during isolation: younger people and those with cancer had significantly higher visit rates, but there was no difference between sexes or socioeconomic levels. + +ConclusionsHealthcare changed dramatically for the clinically extremely vulnerable population during the pandemic. The increased reliance on emergency care while isolating indicates that continuity of care for existing conditions was not optimal. However, compared to the general population, there was success in maintaining scheduled care, particularly in young people and those with cancer. We suggest that integrating demographic and primary care data would improve identification of the clinically vulnerable and could aid prioritising their care.",epidemiology,exact,100,100 +medRxiv,10.1101/2021.09.02.21262979,2021-09-10,https://medrxiv.org/cgi/content/short/2021.09.02.21262979,"Exponential growth, high prevalence of SARS-CoV-2 and vaccine effectiveness associated with Delta variant in England during May to July 2021",Paul Elliott; David J Haw; Haowei Wang; Oliver Eales; Caroline E Walters; Kylie E. C. Ainslie; Christina J Atchison; Claudio Fronterre; Peter Diggle; Andrew J Page; Alex Trotter; Sophie J Prosolek; - The COVID-19 Genomics UK (COG-UK) consortium; Deborah Ashby; Christl Donnelly; Wendy Barclay; Graham P Taylor; Graham Cooke; Helen Ward; Ara Darzi; Steven Riley,"Imperial College London School of Public Health; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Lancaster University; Lancaster University; Quadram Institute; Quadram Institute Bioscience; Quadram Institute; The COVID-19 Genomics UK (COG-UK) consortium; Imperial College London; University of Oxford; Imperial College London; Imperial College London; Imperial College; Imperial College London; Imperial College London; Dept Inf Dis Epi, Imperial College","BackgroundThe prevalence of SARS-CoV-2 infection continues to drive rates of illness and hospitalisations despite high levels of vaccination, with the proportion of cases caused by the Delta lineage increasing in many populations. As vaccination programs roll out globally and social distancing is relaxed, future SARS-CoV-2 trends are uncertain. + +MethodsWe analysed prevalence trends and their drivers using reverse transcription-polymerase chain reaction (RT-PCR) swab-positivity data from round 12 (between 20 May and 7 June 2021) and round 13 (between 24 June and 12 July 2021) of the REal-time Assessment of Community Transmission-1 (REACT-1) study, with swabs sent to non-overlapping random samples of the population ages 5 years and over in England. + +ResultsWe observed sustained exponential growth with an average doubling time in round 13 of 25 days (lower Credible Interval of 15 days) and an increase in average prevalence from 0.15% (0.12%, 0.18%) in round 12 to 0.63% (0.57%, 0.18%) in round 13. The rapid growth across and within rounds appears to have been driven by complete replacement of Alpha variant by Delta, and by the high prevalence in younger less-vaccinated age groups, with a nine-fold increase between rounds 12 and 13 among those aged 13 to 17 years. Prevalence among those who reported being unvaccinated was three-fold higher than those who reported being fully vaccinated. However, in round 13, 44% of infections occurred in fully vaccinated individuals, reflecting imperfect vaccine effectiveness against infection despite high overall levels of vaccination. Using self-reported vaccination status, we estimated adjusted vaccine effectiveness against infection in round 13 of 49% (22%, 67%) among participants aged 18 to 64 years, which rose to 58% (33%, 73%) when considering only strong positives (Cycle threshold [Ct] values < 27); also, we estimated adjusted vaccine effectiveness against symptomatic infection of 59% (23%, 78%), with any one of three common COVID-19 symptoms reported in the month prior to swabbing. Sex (round 13 only), ethnicity, household size and local levels of deprivation jointly contributed to the risk of higher prevalence of swab-positivity. + +DiscussionFrom end May to beginning July 2021 in England, where there has been a highly successful vaccination campaign with high vaccine uptake, infections were increasing exponentially driven by the Delta variant and high infection prevalence among younger, unvaccinated individuals despite double vaccination continuing to effectively reduce transmission. Although slower growth or declining prevalence may be observed during the summer in the northern hemisphere, increased mixing during the autumn in the presence of the Delta variant may lead to renewed growth, even at high levels of vaccination.",epidemiology,exact,100,100 medRxiv,10.1101/2021.09.02.21263017,2021-09-05,https://medrxiv.org/cgi/content/short/2021.09.02.21263017,Monitoring populations at increased risk for SARS-CoV-2 infection in the community,Emma Pritchard; Joel Jones; Karina Vihta; Nicole Stoesser; Philippa C Matthews; David W Eyre; Thomas House; John I Bell; John N Newton; Jeremy Farrar; Derrick Crook; Susan Hopkins; Duncan Cook; Emma Rourke; Ruth Studley; Ian Diamond; Tim Peto; Koen B Pouwels; A Sarah Walker,University of Oxford; Office for National Statistics; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Manchester; University of Oxford; Public Health England; Wellcome Trust; University of Oxford; Public Health England; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; University of Oxford; University of Oxford,"BackgroundThe COVID-19 pandemic is rapidly evolving, with emerging variants and fluctuating control policies. Real-time population screening and identification of groups in whom positivity is highest could help monitor spread and inform public health messaging and strategy. MethodsTo develop a real-time screening process, we included results from nose and throat swabs and questionnaires taken 19 July 2020-17 July 2021 in the UKs national COVID-19 Infection Survey. Fortnightly, associations between SARS-CoV-2 positivity and 60 demographic and behavioural characteristics were estimated using logistic regression models adjusted for potential confounders, considering multiple testing, collinearity, and reverse causality. @@ -1180,15 +1151,6 @@ InterpretationPopulation-level demographic and behavioural surveillance can be a FundingDepartment of Health and Social Care (UK), Welsh Government, Department of Health (on behalf of the Northern Ireland Government), Scottish Government, National Institute for Health Research.",epidemiology,exact,100,100 medRxiv,10.1101/2021.08.18.21262237,2021-08-24,https://medrxiv.org/cgi/content/short/2021.08.18.21262237,Impact of Delta on viral burden and vaccine effectiveness against new SARS-CoV-2 infections in the UK,Koen B Pouwels; Emma Pritchard; Philippa Matthews; Nicole B Stoesser; David W Eyre; Karina-Doris Vihta; Thomas House; Jodie Hay; John Bell; John Newton; Jeremy Farrar; Derrick W Crook; Duncan Cook; Emma Rourke; Ruth Studley; Tim E Peto; Ian Diamond; Sarah Walker; - COVID-19 Infection Survey Team,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Manchester; Glasgow Lighthouse Laboratory; University of Oxford; Public Health England; Wellcome Trust; NIHR Oxford Biomedical Research Centre; Office for National Statistics; Office for National Statistics; Office for National Statistics; Oxford University; Office for National Statistics; University of Oxford; -,"The effectiveness of BNT162b2, ChAdOx1, and mRNA-1273 vaccines against new SARS-CoV-2 infections requires continuous re-evaluation, given the increasingly dominant Delta variant. We investigated the effectiveness of the vaccines in a large community-based survey of randomly selected households across the UK. We found that the effectiveness of BNT162b2 and ChAd0x1 against any infections (new PCR positives) and infections with symptoms or high viral burden is reduced with the Delta variant. A single dose of the mRNA-1273 vaccine had similar or greater effectiveness compared to a single dose of BNT162b2 or ChAdOx1. Effectiveness of two doses remains at least as great as protection afforded by prior natural infection. The dynamics of immunity following second doses differed significantly between BNT162b2 and ChAdOx1, with greater initial effectiveness against new PCR-positives but faster declines in protection against high viral burden and symptomatic infection with BNT162b2. There was no evidence that effectiveness varied by dosing interval, but protection was higher among those vaccinated following a prior infection and younger adults. With Delta, infections occurring following two vaccinations had similar peak viral burden to those in unvaccinated individuals. SARS-CoV-2 vaccination still reduces new infections, but effectiveness and attenuation of peak viral burden are reduced with Delta.",epidemiology,exact,100,100 -medRxiv,10.1101/2021.08.19.21262231,2021-08-24,https://medrxiv.org/cgi/content/short/2021.08.19.21262231,Symptoms and SARS-CoV-2 positivity in the general population in the UK,Karina-Doris Vihta; Koen B. Pouwels; Tim Peto; Emma Pritchard; David W. Eyre; Thomas House; Owen Gethings; Ruth Studley; Emma Rourke; Duncan Cook; Ian Diamond; Derrick Crook; Philippa C. Matthews; Nicole Stoesser; Ann Sarah Walker; - COVID-19 Infection Survey team,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Manchester; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; University of Oxford; University of Oxford; University of Oxford; ,"BackgroundSeveral community-based studies have assessed the ability of different symptoms to identify COVID-19 infections, but few have compared symptoms over time (reflecting SARS-CoV-2 variants) and by vaccination status. - -MethodsUsing data and samples collected by the COVID-19 Infection Survey at regular visits to representative households across the UK, we compared symptoms in new PCR-positives and comparator test-negative controls. - -ResultsFrom 26/4/2020-7/8/2021, 27,869 SARS-CoV-2 PCR-positive episodes occurred in 27,692 participants (median 42 years (IQR 22-58)); 13,427 (48%) self-reported symptoms (""symptomatic positive episodes""). The comparator group comprised 3,806,692 test-negative visits (457,215 participants); 130,612 (3%) self-reported symptoms (""symptomatic negative visit""). Reporting of any symptoms in positive episodes varied over calendar time, reflecting changes in prevalence of variants, incidental changes (e.g. seasonal pathogens, schools re-opening) and vaccination roll-out. There was a small increase in sore throat reporting in symptomatic positive episodes and negative visits from April-2021. After May-2021 when Delta emerged there were substantial increases in headache and fever in positives, but not in negatives. Although specific symptom reporting in symptomatic positive episodes vs. negative visits varied by age, sex, and ethnicity, only small improvements in symptom-based infection detection were obtained; e.g. adding fatigue/weakness or all eight symptoms to the classic four symptoms (cough, fever, loss of taste/smell) increased sensitivity from 74% to 81% to 90% but tests per positive from 4.6 to 5.3 to 8.7. - -ConclusionsWhilst SARS-CoV-2-associated symptoms vary by variant, vaccination status and demographics, differences are modest and do not warrant large-scale changes to targeted testing approaches given resource implications. - -SummaryWithin the COVID-19 Infection Survey, recruiting representative households across the UK general population, SARS-CoV-2-associated symptoms varied by viral variant, vaccination status and demographics. However, differences are modest and do not currently warrant large-scale changes to targeted testing approaches.",infectious diseases,exact,100,100 medRxiv,10.1101/2021.08.18.21262222,2021-08-23,https://medrxiv.org/cgi/content/short/2021.08.18.21262222,"Association of COVID-19 vaccines ChAdOx1 and BNT162b2 with major venous, arterial, and thrombocytopenic events: whole population cohort study in 46 million adults in England",William Whiteley; Samantha Ip; Jennifer Anne Cooper; Thomas Bolton; Spencer Keene; Venexia Walker; Rachel Denholm; Ashley Akbari; Efosa Omigie; Sam Hollings; Emanuele Di Angelantonio; Spiros Denaxas; Angela Wood; Jonathan Sterne; Cathie Sudlow; - CVD-COVID-UK consortium,University of Edinburgh; University of Cambridge; University of Bristol; University of Cambridge; University of Cambridge; University of Bristol; University of Bristol; University of Swansea; NHS Digital; NHS Digital; University of Cambridge; University College London; University of Cambridge; University of Bristol; Health Data Research UK; ,"BackgroundThromboses in unusual locations after the COVID-19 vaccine ChAdOx1-S have been reported. Better understanding of population-level thrombotic risks after COVID-19 vaccination is needed. MethodsWe analysed linked electronic health records from adults living in England, from 8th December 2020 to 18th March 2021. We estimated incidence rates and hazard ratios (HRs) for major arterial, venous and thrombocytopenic outcomes 1-28 and >28 days after first vaccination dose for ChAdOx1-S and BNT162b2 vaccines. Analyses were performed separately for ages <70 and [≥]70 years, and adjusted for age, sex, comorbidities, and social and demographic factors. @@ -1214,9 +1176,6 @@ https://clinicaltrials.gov/ct2/show/NCT04394117 Clinical Trial Registry of India: CTRI/2020/07/026831 Version and revisionsVersion 1.0. No revisions.",respiratory medicine,exact,100,100 -medRxiv,10.1101/2021.08.13.21261889,2021-08-18,https://medrxiv.org/cgi/content/short/2021.08.13.21261889,Robust SARS-CoV-2-specific and heterologous immune responses after natural infection in elderly residents of Long-Term Care Facilities,Gokhan Tut; Tara Lancaster; Megan S Butler; Panagiota Sylla; Eliska Spalkova; David Bone; Nayandeep Kaur; Christopher Bentley; Umayr Amin; Azar T Jadir; Samuel Hulme; Morenike Ayodele; Alexander C Dowell; Hayden Pearce; Sandra Margielewska-Davies; Kriti Verma; Samantha Nicol; Jusnara Begum; Elizabeth Jinks; Elif Tut; Rachel Bruton; Maria Krutikov; Madhumita Shrotri; Rebecca Giddings; Borscha Azmi; Chris Fuller; Aidan Irwin-Singer; Andrew Hayward; Andrew Copas; Laura Shallcross; Paul Moss,"Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; Department of Health and Social Care, London, UK; Health Data Research UK; UCL Institute for Global Health, London, UK; UCL Institute of Health Informatics, London, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK","Long term care facilities (LTCF) provide residential and/or nursing care support for frail and elderly people and many have suffered from a high prevalence of SARS-CoV-2 infection. Although mortality rates have been high in LTCF residents there is little information regarding the features of SARS-CoV-2-specific immunity after infection in this setting or how this may influence immunity to other infections. We studied humoral and cellular immunity against SARS-CoV-2 in 152 LTCF staff and 124 residents over a prospective 4-month period shortly after the first wave of infection and related viral serostatus to heterologous immunity to other respiratory viruses and systemic inflammatory markers. LTCF residents developed high levels of antibodies against spike protein and RBD domain which were stable over 4 months of follow up. Nucleocapsid-specific responses were also elevated in elderly donors but showed waning across all populations. Antibodies showed stable and equivalent levels of functional inhibition against spike-ACE2 binding in all age groups with comparable activity against viral variants of concern. SARS-CoV-2 seropositive donors showed high levels of antibodies to other beta-coronaviruses but serostatus did not impact humoral immunity to influenza or RSV. SARS-CoV-2-specific cellular responses were equivalent across the life course but virus-specific populations showed elevated levels of activation in older donors. LTCF residents who are survivors of SARS-CoV-2 infection thus show robust and stable immunity which does not impact responses to other seasonal viruses. These findings augur well for relative protection of LTCF residents to re-infection. Furthermore, they underlie the potent influence of previous infection on the immune response to Covid-19 vaccine which may prove to be an important determinant of future vaccine strategy. - -One sentence summeryCare home residents show waning of nucleocapsid specific antibodies and enhanced expression of activation markers on SARS-CoV-2 specific cells",infectious diseases,exact,100,100 medRxiv,10.1101/2021.08.13.21261959,2021-08-13,https://medrxiv.org/cgi/content/short/2021.08.13.21261959,Factors influencing wellbeing in young people during COVID-19.,Michaela James; Hope Jones; Amana Baig; Emily Marchant; Tegan Waites; Charlotte Todd; Karen Hughes; Sinead Brophy,Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Public Health Wales; Bangor University; Swansea University,"COVID-19 infection and the resultant restrictions has impacted all aspects of life across the world. This study explores factors that promote or support wellbeing for young people during the pandemic, how they differ by age, using a self-reported online survey with those aged 8 - 25 in Wales between September 2020 and February 2021. Open-ended responses were analysed via thematic analysis to provide further context. A total of 6,291 responses were obtained from 81 education settings across Wales (including primary and secondary schools as well as sixth form, colleges and universities). Wellbeing was highest in primary school children and boys and lowest in those who were at secondary school children, who were girls and, those who preferred not to give a gender. Among primary school children, higher wellbeing was seen for those who played with others (rather than alone), were of Asian ethnicity (OR 2.3, 95% CI: 1.26 to 4.3), lived in a safe area (OR: 2.0, 95% CI: 1.67 to 2.5) and had more sleep. To support their wellbeing young people reported they would like to be able to play with their friends more. Among secondary school children those who were of mixed ethnicity reported lower wellbeing (OR: 5.10, 95% CI: 1.70 to 15.80). To support their wellbeing they reported they would like more support with mental health (due to anxiety and pressure to achieve when learning online). This study found self-reported wellbeing differed by gender, ethnicity and deprivation and found younger children report the need for play and to see friends to support wellbeing but older children/young people wanted more support with anxiety and educational pressures.",public and global health,exact,100,100 medRxiv,10.1101/2021.08.12.21261987,2021-08-13,https://medrxiv.org/cgi/content/short/2021.08.12.21261987,Characterising the persistence of RT-PCR positivity and incidence in a community survey of SARS-CoV-2,Oliver Eales; Caroline E. Walters; Haowei Wang; David Haw; Kylie E. C. Ainslie; Christina Atchinson; Andrew Page; Sophie Prosolek; Alexander J. Trotter; Thanh Le Viet; Nabil-Fareed Alikhan; Leigh M Jackson; Catherine Ludden; - The COVID-19 Genomics UK (COG-UK) Consortium; Deborah Ashby; Christl A Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott; Steven Riley,"School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Medical School, University of Exeter, UK; Department of Medicine, University of Cambridge, UK; ; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc","BackgroundCommunity surveys of SARS-CoV-2 RT-PCR swab-positivity provide prevalence estimates largely unaffected by biases from who presents for routine case testing. The REal-time Assessment of Community Transmission-1 (REACT-1) has estimated swab-positivity approximately monthly since May 2020 in England from RT-PCR testing of self-administered throat and nose swabs in random non-overlapping cross-sectional community samples. Estimating infection incidence from swab-positivity requires an understanding of the persistence of RT-PCR swab positivity in the community. @@ -1334,6 +1293,7 @@ MethodsWe report interim results from round 13 of the REal-time Assessment of Co ResultsIn round 13 interim, we found 237 positives from 47,729 swabs giving a weighted prevalence of 0.59% (0.51%, 0.68%) which was approximately four-fold higher compared with round 12 at 0.15% (0.12%, 0.18%). This resulted from continued exponential growth in prevalence with an average doubling time of 15 (13, 17) days between round 12 and round 13. However, during the recent period of round 13 interim only, we observed a shorter doubling time of 6.1 (4.0, 12) days with a corresponding R number of 1.87 (1.40, 2.45). There were substantial increases in all age groups under the age of 75 years, and especially at younger ages, with the highest prevalence in 13 to 17 year olds at 1.33% (0.97%, 1.82%) and in 18 to 24 years olds at 1.40% (0.89%, 2.18%). Infections have increased in all regions with the largest increase in London where prevalence increased more than eight-fold from 0.13% (0.08%, 0.20%) in round 12 to 1.08% (0.79%, 1.47%) in round 13 interim. Overall, prevalence was over 3 times higher in the unvaccinated compared with those reporting two doses of vaccine in both round 12 and round 13 interim, although there was a similar proportional increase in prevalence in vaccinated and unvaccinated individuals between the two rounds. DiscussionWe are entering a critical period with a number of important competing processes: continued vaccination rollout to the whole adult population in England, increased natural immunity through infection, reduced social mixing of children during school holidays, increased proportion of mixing occurring outdoors during summer, the intended full opening of hospitality and entertainment and cessation of mandated social distancing and mask wearing. Surveillance programmes are essential during this next phase of the epidemic to provide clear evidence to the government and the public on the levels and trends in prevalence of infections and their relationship to vaccine coverage, hospitalisations, deaths and Long COVID.",infectious diseases,exact,100,100 +medRxiv,10.1101/2021.07.02.21259897,2021-07-05,https://medrxiv.org/cgi/content/short/2021.07.02.21259897,Anti-spike antibody response to natural SARS-CoV-2 infection in the general population,Jia Wei; Philippa C Matthews; Nicole Stoesser; Thomas Maddox; Luke Lorenzi; Ruth Studley; John I Bell; John N Newton; Jeremy Farrar; Ian Diamond; Emma Rourke; Alison Howarth; Brian D Marsden; Sarah Hoosdally; E Yvonne Jones; David I Stuart; Derrick W Crook; Tim E.A. Peto; Koen B. Pouwels; A. Sarah Walker; David W Eyre,University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; Office for National Statistics; Office for National Statistics; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; NIHR Oxford Biomedical Research Centre; University of Oxford; University of Oxford; University of Oxford; University of Oxford,"We estimated the duration and determinants of antibody response after SARS-CoV-2 infection in the general population using representative data from 7,256 United Kingdom COVID-19 infection survey participants who had positive swab SARS-CoV-2 PCR tests from 26-April-2020 to 14-June-2021. A latent class model classified 24% of participants as non-responders not developing anti-spike antibodies. These seronegative non-responders were older, had higher SARS-CoV-2 cycle threshold values during infection (i.e. lower viral burden), and less frequently reported any symptoms. Among those who seroconverted, using Bayesian linear mixed models, the estimated anti-spike IgG peak level was 7.3-fold higher than the level previously associated with 50% protection against reinfection, with higher peak levels in older participants and those of non-white ethnicity. The estimated anti-spike IgG half-life was 184 days, being longer in females and those of white ethnicity. We estimated antibody levels associated with protection against reinfection likely last 1.5-2 years on average, with levels associated with protection from severe infection present for several years. These estimates could inform planning for vaccination booster strategies.",infectious diseases,exact,100,100 medRxiv,10.1101/2021.06.28.21259529,2021-07-01,https://medrxiv.org/cgi/content/short/2021.06.28.21259529,Global patterns of genetic variation and association with clinical phenotypes at genes involved in SARS-CoV-2 infection,Chao Zhang; Anurag Verma; Yuanqing Feng; Marcelo C. R. Melo; Michael McQuillan; Matthew Hansen; Anastasia Lucas; Joseph Park; Alessia Ranciaro; Simon Thompson; Meghan A. Rubel; Michael C. Campbell; William Beggs; JIBRIL HIRBO; Sununguko Wata Mpoloka; Gaonyadiwe George Mokone; - Regeneron Genetic Center; Thomas Nyambo; Dawit Wolde Meskel; Gurja Belay; Charles Fokunang; Alfred K. Njamnshi; Sabah A. Omar; Scott Williams; Daniel Rader; Marylyn D Ritchie; Cesar de la Fuente Nunez; Giorgio Sirugo; Sarah Tishkoff,"University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; Perelman School of Medicine at the University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Howard; University of Pennsylvania; Vanderbilt University Medical Center; University of Botswana, Biological Sciences, Gaborone, Botswana; University of Botswana, Faculty of Medicine, Gaborone, Botswana; ; Department of Biochemistry, Kampala International University in Tanzania, Dar es Salaam, Tanzania; Addis Ababa University Department of Microbial Cellular and Molecular Biology, Addis Ababa, Ethiopia; Addis Ababa University Department of Microbial Cellular and Molecular Biology, Addis Ababa, Ethiopia; Department of Pharmacotoxicology and Pharmacokinetics, Faculty of Medicine and Biomedical Sciences, The University of Yaounde I, Yaounde, Cameroon; Department of Neurology, Central Hospital Yaounde; Brain Research Africa Initiative (BRAIN), Neuroscience Lab, Faculty of Medicine and Biomedical Sciences, The ; Center for Biotechnology Research and Development, Kenya Medical Research Institute, Nairobi, Kenya; Case Western Reserve University; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania","We investigated global patterns of genetic variation and signatures of natural selection at host genes relevant to SARS-CoV-2 infection (ACE2, TMPRSS2, DPP4, and LY6E). We analyzed novel data from 2,012 ethnically diverse Africans and 15,997 individuals of European and African ancestry with electronic health records, and integrated with global data from the 1000GP. At ACE2, we identified 41 non-synonymous variants that were rare in most populations, several of which impact protein function. However, three non-synonymous variants were common among Central African hunter-gatherers from Cameroon and are on haplotypes that exhibit signatures of positive selection. We identify strong signatures of selection impacting variation at regulatory regions influencing ACE2 expression in multiple African populations. At TMPRSS2, we identified 13 amino acid changes that are adaptive and specific to the human lineage. Genetic variants that are targets of natural selection are associated with clinical phenotypes common in patients with COVID-19.",genetic and genomic medicine,exact,100,100 medRxiv,10.1101/2021.06.21.21259237,2021-06-28,https://medrxiv.org/cgi/content/short/2021.06.21.21259237,Changes in mobility pre and post first SARS-CoV-2 vaccination: findings from a prospective community cohort study including GPS movement tracking in England and Wales (Virus Watch),Vincent Nguyen; Yunzhe Liu; Richard Mumford; Ben Flanagan; Parth Patel; Isobel Braithwaite; Madhumita Shrotri; Thomas Edward Byrne; Sarah Beale; Anna Aryee; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Annalan M D Navaratnam; Pia Hardelid; Jana Kovar; Addy Pope; Tao Cheng; Andrew Hayward; Robert W Aldridge; - The Virus watch Collaborative,"Centre for Public Health Data Science, Institute of Health Informatics, University College London, UK; SpaceTimeLab, Department of Civil, Environmental and Geomatic Engineering, University College London, London, UK; Esri UK; Esri UK; Centre for Public Health Data Science, Institute of Health Informatics, University College London, UK; Centre for Public Health Data Science, Institute of Health Informatics, University College London, UK; Centre for Public Health Data Science, Institute of Health Informatics, University College London, UK; Centre for Public Health Data Science, Institute of Health Informatics, University College London, UK; Centre for Public Health Data Science, Institute of Health Informatics, University College London, UK; Centre for Public Health Data Science, Institute of Health Informatics, University College London, UK; Centre for Public Health Data Science, Institute of Health Informatics, University College London, UK; Centre for Public Health Data Science, Institute of Health Informatics, University College London, UK; Centre for Public Health Data Science, Institute of Health Informatics, University College London, UK; Centre for Public Health Data Science, Institute of Health Informatics, University College London, UK; Centre for Public Health Data Science, Institute of Health Informatics, University College London, UK; Institute of Epidemiology and Health Care, University College London, London, UK; Esri UK; SpaceTimeLab, Department of Civil, Environmental and Geomatic Engineering, University College London, London, UK; Institute of Epidemiology and Health Care, University College London, London, UK; Centre for Public Health Data Science, Institute of Health Informatics, University College London, UK; ","BackgroundSome evidence suggests that individuals may change adherence to public health policies aimed at reducing contact, transmission and spread of the SARS-CoV-2 virus after they receive their first SARS-CoV-2 vaccination. In this study, we aim to estimate the rate of change in average daily travel distance from a participants registered address before and after SARS-CoV-2 vaccination. @@ -1964,19 +1924,6 @@ ResultsLiving in a multi-generational household was associated with an increased ConclusionOlder adults living with younger people are at increased risk of COVID-19 mortality, and this is a notable contributing factor to the excess risk experienced by older South Asian females compared to White females. Relevant public health interventions should be directed at communities where such multi-generational households are highly prevalent. FundingThis research was funded by the Office for National Statistics.",epidemiology,exact,100,100 -medRxiv,10.1101/2020.11.23.20237313,2020-11-24,https://medrxiv.org/cgi/content/short/2020.11.23.20237313,"Identifying optimal combinations of symptoms to trigger diagnostic work-up of suspected COVID-19 cases in vaccine trials: analysis from a community-based, prospective, observational cohort",Michela Antonelli; Joan Capdevila; Amol Chaudhari; Julia Granerod; Liane S Canas; Mark S Graham; Kerstin Klaser; Marc Modat; Erika Molteni; Ben Murray; Carole H Sudre; Richard Davies; Anna May; Long H Nguyen; David A Drew; Amit Joshi; Andrew T Chan; Jakob Cramer; Tim Spector; Jonathan Wolf; Sebastien Ourselin; Claire J Steves; Alfred E Loeliger,King's College London; Zoe Global; Coalition for Epidemic Preparedness Innovations; Coalition for Epidemic Preparedness Innovations; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; University College London; Zoe Global; Zoe Global; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Coalition for Epidemic Preparedness Innovations; King's College London; Zoe Global; King's College London; King's College London; Coalition for Epidemic Preparedness Innovations,"ObjectivesDiagnostic work-up following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify optimal symptom combinations to capture most cases using fewer tests with implications for COVID-19 vaccine developers across different resource settings and public health. - -MethodsUK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms and an RT-PCR test within seven days of symptom onset were included. Sensitivity, specificity, and number of RT-PCR tests needed to identify one case (test per case [TPC]) were calculated for different symptom combinations. A multi-objective evolutionary algorithm was applied to generate combinations with optimal trade-offs between sensitivity and specificity. - -FindingsUK and US cohorts included 122,305 (1,202 positives) and 3,162 (79 positive) individuals. Within three days of symptom onset, the COVID-19 specific symptom combination (cough, dyspnoea, fever, anosmia/ageusia) identified 69% of cases requiring 47 TPC. The combination with highest sensitivity (fatigue, anosmia/ageusia, cough, diarrhoea, headache, sore throat) identified 96% cases requiring 96 TPC. - -InterpretationWe confirmed the significance of COVID-19 specific symptoms for triggering RT-PCR and identified additional symptom combinations with optimal trade-offs between sensitivity and specificity that maximize case capture given different resource settings. - -HighlightsO_LIWidely recommended symptoms identified only [~]70% COVID-19 cases -C_LIO_LIAdditional symptoms increased case finding to > 90% but tests needed doubled -C_LIO_LIOptimal symptom combinations maximise case capture considering available resources -C_LIO_LIImplications for COVID-19 vaccine efficacy trials and wider public health -C_LI",health informatics,exact,100,100 medRxiv,10.1101/2020.11.19.20234120,2020-11-23,https://medrxiv.org/cgi/content/short/2020.11.19.20234120,Actionable druggable genome-wide Mendelian randomization identifies repurposingopportunities for COVID-19,Liam Gaziano; Claudia Giambartolomei; Alexandre C Pereira; Anna Gaulton; Daniel C Posner; Sonja A Swanson; Yuk Lam Ho; Sudha K Iyengar; Nicole M Kosik; Marijana Vujkovic; David R Gagnon; A Patricia Bento; Pedro Beltrao; Inigo Barrio Hernandez; Lars Ronnblom; Niklas Hagberg; Christian Lundtoft; Claudia Langenberg; Maik Pietzner; Dennis Valentine; Elias Allara; Praveen Surendran; Stephen Burgess; Jing Hua Zhao; James E Peters; Bram P Prins; John Danesh; Poornima Devineni; Yunling Shi; Kristine E Lynch; Scott L DuVall; Helene Garcon; Lauren Thomann; Jin J Zhou; Bryan R Gorman; Jennifer E Huffman; Christopher J O'Donnell; Philip S Tsao; Jean C Beckham; Saiju Pyarajan; Sumitra Muralidhar; Grant D Huang; Rachel Ramoni; Adriana M Hung; Kyong-Mi Chang; Yan V Sun; Jacob Joseph; Andrew R Leach; Todd L Edwards; Kelly Cho; J Michael Gaziano; Adam S Butterworth; Juan P Casas,"VA Boston Healthcare System, University of Cambridge; Instituto Italiano di Tecnologia, University of California Los Angeles; University of Sao Paulo, Harvard University; European Molecular Biology Laboratory, European Bioinformatics Institute; VA Boston Healthcare System; Erasmus Medical Center; VA Boston Healthcare System; Case Western Reserve University and Louis Stoke Cleveland VAMC; VA Boston Healthcare System; The Corporal Michael J. Crescenz VA Medical Center, the University of Pennsylvania Perelman School of Medicine; Boston University, VA Boston Healthcare System; European Molecular Biology Laboratory, European Bioinformatics Institute; European Molecular Biology Laboratory, European Bioinformatics Institute; European Molecular Biology Laboratory, European Bioinformatics Institute; Uppsala University; Uppsala University; Uppsala University; Charite University Medicine Berlin, Universityof Cambridge; Universityof Cambridge; University College London; University of Cambridge; Wellcome Genome Campus and University of Cambridge; University of Cambridge; University of Cambridge; Imperial College London; Wellcome Genome Campus and University of Cambridge; University of Cambridge; VA Boston Healthcare System; VA Boston Healthcare System; VA Salt Lake City Health Care System, University of Utah; VA Salt Lake City Health Care System, University of Utah; VA Boston Healthcare System; VA Boston Healthcare System; University of Arizona, Phoenix VA Health Care System; VA Boston Healthcare System; VA Boston Healthcare System; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School; VA Palo Alto Health Care System, Stanford University School of Medicine; Durham VA Medical Center, Duke University School of Medicine; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School; Department of Veterans Affairs; Department of Veterans Affairs; Department of Veterans Affairs; Department of Veterans Affairs, Vanderbilt University; The Corporal Michael J. Crescenz VA Medical Center, University of Pennsylvania; Atlanta VA Health Care System, Emory University Rollins School of Public Health; VA Boston Healthcare System and Brigham & Women's Hospital; European Molecular Biology Laboratory, European Bioinformatics Institute; Department of Veterans Affairs Tennessee Valley Healthcare System, Vanderbilt Genetics Institute Vanderbilt University Medical Center; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School; University of Cambridge, Wellcome Genome Campus and University of Cambridge; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School","Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization (MR) analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2: P=1.6x10-6, IFNAR2: P=9.8x10-11, and IL-10RB: P=1.9x10-14) using cis-eQTL genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared eQTL signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.",epidemiology,exact,100,100 medRxiv,10.1101/2020.11.19.20234849,2020-11-22,https://medrxiv.org/cgi/content/short/2020.11.19.20234849,Community factors and excess mortality in first wave of the COVID-19 pandemic.,Bethan Davies; Brandon L Parkes; James Bennett; Daniela Fecht; Marta Blangiardo; Majid Ezzati; Paul Elliott,Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London,"Risk factors for increased risk of death from Coronavirus Disease 19 (COVID-19) have been identified1,2 but less is known on characteristics that make communities resilient or vulnerable to the mortality impacts of the pandemic. We applied a two-stage Bayesian spatial model to quantify inequalities in excess mortality at the community level during the first wave of the pandemic in England. We used geocoded data on all deaths in people aged 40 years and older during March-May 2020 compared with 2015-2019 in 6,791 local communities. Here we show that communities with an increased risk of excess mortality had a high density of care homes, and/or high proportion of residents on income support, living in overcrowded homes and/or high percent of people with a non-White ethnicity (including Black, Asian and other minority ethnic groups). Conversely, after accounting for other community characteristics, we found no association between population density or air pollution and excess mortality. Overall, the social and environmental variables accounted for around 15% of the variation in mortality at community level. Effective and timely public health and healthcare measures that target the communities at greatest risk are urgently needed if England and other industrialised countries are to avoid further widening of inequalities in mortality patterns during the second wave.",epidemiology,exact,100,100 medRxiv,10.1101/2020.11.06.20227108,2020-11-07,https://medrxiv.org/cgi/content/short/2020.11.06.20227108,Primary school staff reflections on school closures due to COVID-19 and recommendations for the future: a national qualitative survey,Emily Marchant; Charlotte Todd; Michaela James; Tom Crick; Russell Dwyer; Sinead Brophy,Swansea University; Swansea University; Swansea University; Swansea University; St Thomas Community Primary School; Swansea University,"School closures due to the COVID-19 global pandemic are likely to have a range of negative consequences spanning the domains of child development, education and health, in addition to the widening of inequalities and inequities. Research is required to improve understanding of the impact of school closures on the education, health and wellbeing of pupils and school staff, the challenges posed during reopening and importantly to identify how countries can return to in-school education and to inform policy. This qualitative study aimed to reflect on the perspectives and experiences of primary school staff (pupils aged 3-11) in Wales regarding school closures and the initial reopening of schools and to identify recommendations for the future. A total of 208 school staff completed a national online survey through the HAPPEN primary school network, consisting of questions about school closures (March to June 2020), the phased reopening of schools (June to July 2020) and a return to full-time education. Thematic analysis of survey responses highlighted that primary school staff perceive that gaps in learning, health and wellbeing have increased and inequalities have widened during school closures. Findings from this study identified five recommendations; (i) prioritise the health and wellbeing of pupils and staff; (ii) focus on enabling parental engagement and support; (iii) improve digital competence amongst pupils, teachers and parents; (iv) consider opportunities for smaller class sizes and additional staffing; and (v) improve the mechanism of communication between schools and families, and between government and schools.",public and global health,exact,100,100 @@ -1997,15 +1944,6 @@ Evidence before this studySpecific risk factors for SARS-CoV-2 infection in heal Added value of this studyOur prospective cohort study of almost 6,000 HCWs at a large UK teaching hospital strengthens previous findings from UK-based cohorts in identifying an increased risk of SARS-CoV-2 exposure amongst HCWs. Specifically, factors associated with SARS-CoV-2 exposure include caring for confirmed COVID-19 cases and identifying as being within specific ethnic groups (BAME staff). We further delineated the risk amongst BAME staff and demonstrate that occupational factors alone do not account for all of the increased risk amongst this group. We demonstrate for the first time that healthcare assistants represent a key at-risk occupational group, and challenge previous findings of significantly higher risk amongst nursing staff. Seroprevalence in staff not working in areas with confirmed COVID-19 patients was only marginally higher than that of the general population within the same geographical region. This observation could suggest the increased risk amongst HCWs arises through occupational exposure to confirmed cases and could account for the overall higher seroprevalence in HCWs, rather than purely the presence of staff in healthcare facilities. Over 30% of seropositive staff had not reported symptoms consistent with COVID-19, and in those who did report symptoms, differentiating COVID-19 from other causes based on symptom data alone was unreliable. Implications of all the available evidenceInternational efforts to reduce the risk of SARS-CoV-2 infection amongst HCWs need to be prioritised. The risk of SARS-CoV-2 infection amongst HCWs is heterogenous but also follows demonstrable patterns. Potential mechanisms to reduce the risk for staff working in areas with confirmed COVID-19 patients include improved training in hand hygiene and personal protective equipment (PPE), better access to high quality PPE, and frequent asymptomatic testing. Wider asymptomatic testing in healthcare facilities has the potential to reduce spread of SARS-CoV-2 within hospitals, thereby reducing patient and staff risk and limiting spread between hospitals and into the wider community. The increased risk of COVID-19 amongst BAME staff cannot be explained by purely occupational factors; however, the increased risk amongst minority ethnic groups identified here was stark and necessitates further evaluation.",infectious diseases,exact,100,100 -medRxiv,10.1101/2020.11.02.20224824,2020-11-04,https://medrxiv.org/cgi/content/short/2020.11.02.20224824,"The duration, dynamics and determinants of SARS-CoV-2 antibody responses in individual healthcare workers",Sheila F Lumley; Jia Wei; Nicole Stoesser; Philippa Matthews; Alison Howarth; Stephanie Hatch; Brian Marsden; Stuart Cox; Tim James; Liam Peck; Thomas Ritter; Zoe de Toledo; Richard Cornall; E Yvonne Jones; David I Stuart; Gavin Screaton; Daniel Ebner; Sarah Hoosdally; Derrick Crook; - Oxford University Hospitals Staff Testing Group; Christopher P Conlon; Koen Pouwels; Ann Sarah Walker; Tim EA Peto; Timothy M Walker; Katie Jeffery; David W Eyre,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; Oxford University Hospitals; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; ; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; University of Oxford,"BackgroundSARS-CoV-2 IgG antibody measurements can be used to estimate the proportion of a population exposed or infected and may be informative about the risk of future infection. Previous estimates of the duration of antibody responses vary. - -MethodsWe present 6 months of data from a longitudinal seroprevalence study of 3217 UK healthcare workers (HCWs). Serial measurements of IgG antibodies to SARS-CoV-2 nucleocapsid were obtained. Bayesian mixed linear models were used to investigate antibody waning and associations with age, gender, ethnicity, previous symptoms and PCR results. - -ResultsIn this cohort of working age HCWs, antibody levels rose to a peak at 24 (95% credibility interval, CrI 19-31) days post-first positive PCR test, before beginning to fall. Considering 452 IgG seropositive HCWs over a median of 121 days (maximum 171 days) from their maximum positive IgG titre, the mean estimated antibody half-life was 85 (95%CrI, 81-90) days. The estimated mean time to loss of a positive antibody result was 137 (95%CrI 127-148) days. We observed variation between individuals; higher maximum observed IgG titres were associated with longer estimated antibody half-lives. Increasing age, Asian ethnicity and prior self-reported symptoms were independently associated with higher maximum antibody levels, and increasing age and a positive PCR test undertaken for symptoms with longer antibody half-lives. - -ConclusionIgG antibody levels to SARS-CoV-2 nucleocapsid wane within months, and faster in younger adults and those without symptoms. Ongoing longitudinal studies are required to track the long-term duration of antibody levels and their association with immunity to SARS-CoV-2 reinfection. - -SummarySerially measured SARS-CoV-2 anti-nucleocapsid IgG titres from 452 seropositive healthcare workers demonstrate levels fall by half in 85 days. From a peak result, detectable antibodies last a mean 137 days. Levels fall faster in younger adults and following asymptomatic infection.",infectious diseases,exact,100,100 medRxiv,10.1101/2020.10.29.20222414,2020-11-03,https://medrxiv.org/cgi/content/short/2020.10.29.20222414,How well does societal mobility restriction help control the COVID-19 pandemic? Evidence from real-time evaluation,Juhwan Oh; Hwa-Young Lee; Khuong Quynh Long; Jeffery F Marcuns; Chris Bullen; Osvaldo Enrique Artaza Barrios; Seung-sik Hwang; Young Sahng Suh; Judith McCool; S. Patrick Kaucher; Chang-Chung Chan; Soonman Kwon; Naoki Kondo; Hoang Van Minh; J. Robin Moon; Mikael Rostila; Ole F. Norheim; Myoungsoon You; Mellissa Withers; Mu Li; Eun-Jeung Lee; Caroline Benski; Soo Kyung Park; Eun-Woo Nam; Katie Gottschalk; Matthew M. Kavanagh; Tran Thi Giang Huong; Jong-Koo Lee; S.V. Subramanian; Lawrence O. Gostin; Martin McKee,"1. Harvard University T.H.Chan School of Public Health 2. Seoul National University College of Medicine; 1. Harvard University T H Chan School of Public Health 2. Institute of Convergence Science, Convergence Science Academy, Yonsei University,; Hanoi University of Public Health; Boston University School of Medicine; The University of Auckland School of Population Health; The University of the Americas; Seoul National University Graduate School of Public Health; Harvard University T.H.Chan School of Public Health; The University of Auckland School of Population Health; Mailman School of Public Health, Columbia University; National Taiwan University College of Public Health; Seoul National University Graduate School of Public Health; Kyoto University School of Public Health; Hanoi University of Public Health; City University of New York Graduate School of Public Health & Health Policy; Stockholm University; 1.University of Bergen 2. Harvard University T.H.Chan School of Public Health; Seoul National University Graduate School of Public Health; University of Southern California; The University of Sydney; Berlin Free University; University Hospital of Geneva; National Health Insurance Research Institute; Yonsei University, Wonju-campus; Georgetown University; Georgetown University; Hanoi Medical University; Seoul National University College of Medicine; Harvard University T.H.Chan School of Public Health; Georgetown University; London School of Hygiene and Tropical Medicine","ObjectivesTo determine the impact of restrictions on mobility on reducing transmission of COVID-19. DesignDaily incidence rates lagged by 14 days were regressed on mobility changes using LOESS regression and logit regression between the day of the 100th case in each country to August 31, 2020. @@ -2079,21 +2017,6 @@ Research in contextO_ST_ABSEvidence before this studyC_ST_ABSUnprecedented contr Added value of this studyThis is the first longitudinal community survey of SARS-CoV-2 infection at national and regional levels in the UK. With more than 500,000 swabs from more than 120,000 individuals this study provides robust evidence that the percentage of individuals from the general community in England testing positive for SARS-CoV-2 clearly declined between end of April and June 2020,, followed by consistently low levels during the summer, before marked increases end of August and September 2020. Risk factors for testing positive varied substantially between the initial and second periods of higher positivity rates, with having a patient-facing role and working outside your home being important risk factors in the first period but not (yet) in the second period, and age (young adults) being an important driver of the second period of increased positivity rates. Positive tests commonly occurred without symptoms being reported. Implications of all the available evidenceThe observed decline in the percentage of individuals testing positive adds to the increasing body of empirical evidence and theoretical models that suggest that the lockdown imposed on 23 March 2020 in England was associated, at least temporarily, with a decrease in infections. Important risk factors for testing positive varied substantially between the initial and second periods of higher positivity rates, and a substantial proportion of infections were in individuals not reporting symptoms, indicating that continued monitoring for SARS-CoV-2 in the community will be important for managing the epidemic moving forwards.",infectious diseases,exact,100,100 -medRxiv,10.1101/2020.10.26.20219550,2020-10-27,https://medrxiv.org/cgi/content/short/2020.10.26.20219550,Human movement can inform the spatial scale of interventions against COVID-19 transmission,Hamish Gibbs; Emily Nightingale; Yang Liu; James Cheshire; Leon Danon; Liam Smeeth; Carl AB Pearson; Chris Grundy; - LSHTM CMMID COVID-19 Working Group; Adam J Kucharski; Rosalind M Eggo,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University College London; University of Exeter; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; ; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine,"BackgroundIn 2020, the UK enacted an intensive, nationwide lockdown on March 23 to mitigate transmission of COVID-19. As restrictions began to ease, resurgences in transmission were targeted by geographically-limited interventions of various stringencies. Understanding the spatial scale of networks of human interaction, and how these networks change over time, is critical to inform interventions targeted at the most at-risk areas without unnecessarily restricting areas at low risk of resurgence. - -MethodsWe use detailed human mobility data aggregated from Facebook users to determine how the spatially-explicit network of movements changed before and during the lockdown period, in response to the easing of restrictions, and to the introduction of locally-targeted interventions. We also apply community detection techniques to the weighted, directed network of movements to identify geographically-explicit movement communities and measure the evolution of these community structures through time. - -FindingsWe found that the mobility network became more sparse and the number of mobility communities decreased under the national lockdown, a change that disproportionately affected long distance journeys central to the mobility network. We also found that the community structure of areas in which locally-targeted interventions were implemented following epidemic resurgence did not show reorganization of community structure but did show small decreases in indicators of travel outside of local areas. - -InterpretationWe propose that communities detected using Facebook or other mobility data be used to assess the impact of spatially-targeted restrictions and may inform policymakers about the spatial extent of human movement patterns in the UK. These data are available in near real-time, allowing quantification of changes in the distribution of the population across the UK, as well as changes in travel patterns to inform our understanding of the impact of geographically-targeted interventions. - -Putting Research Into ContextO_ST_ABSEvidence before this studyC_ST_ABSLarge-scale intensive interventions in response to the COVID-19 pandemic have been implemented globally, significantly affecting human movement patterns. Mobility data show spatially-explicit network structure, but it is not clear how that structure changed in response to national or locally-targeted interventions. - -Added value of this studyWe used daily mobility data aggregated from Facebook users to quantify changes in the travel network in the UK during the national lockdown, and in response to local interventions. We identified changes in human behaviour in response to interventions and identified the community structure inherent in these networks. This approach to understanding changes in the travel network can help quantify the extent of strongly connected communities of interaction and their relationship to the extent of spatially-explicit interventions. - -Implications of all the available evidenceWe show that spatial mobility data available in near real-time can give information on connectivity that can be used to understand the impact of geographically-targeted interventions and in the future, to inform spatially-targeted intervention strategies. - -Data SharingData used in this study are available from the Facebook Data for Good Partner Program by application. Code and supplementary information for this paper are available online (https://github.com/hamishgibbs/facebook_mobility_uk), alongside publication.",epidemiology,exact,100,100 medRxiv,10.1101/2020.10.26.20219725,2020-10-27,https://medrxiv.org/cgi/content/short/2020.10.26.20219725,"Declining prevalence of antibody positivity to SARS-CoV-2: a community study of 365,000 adults",Helen Ward; Graham Cooke; Christina J Atchison; Matthew Whitaker; Joshua Elliott; Maya Moshe; Jonathan C Brown; Barney Flower; Anna Daunt; Kylie E. C. Ainslie; Deborah Ashby; Christl A. Donnelly; Steven Riley; Ara Darzi; Wendy Barclay; Paul Elliott,"Imperial College London; Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London","BackgroundThe prevalence and persistence of antibodies following a peak SARS-CoV-2 infection provides insights into its spread in the community, the likelihood of reinfection and potential for some level of population immunity. MethodsPrevalence of antibody positivity in England, UK (REACT2) with three cross-sectional surveys between late June and September 2020. 365104 adults used a self-administered lateral flow immunoassay (LFIA) test for IgG. A laboratory comparison of LFIA results to neutralization activity in panel of sera was performed. @@ -2114,13 +2037,7 @@ There was evidence of mild organ impairment in heart (32%), lungs (33%), kidneys InterpretationIn a young, low-risk population with ongoing symptoms, almost 70% of individuals have impairment in one or more organs four months after initial symptoms of SARS-CoV-2 infection. There are implications not only for burden of long COVID but also public health approaches which have assumed low risk in young people with no comorbidities. FundingThis work was supported by the UKs National Consortium of Intelligent Medical Imaging through the Industry Strategy Challenge Fund, Innovate UK Grant 104688, and also through the European Unions Horizon 2020 research and innovation programme under grant agreement No 719445.",health policy,exact,100,100 -medRxiv,10.1101/2020.10.12.20211227,2020-10-14,https://medrxiv.org/cgi/content/short/2020.10.12.20211227,High and increasing prevalence of SARS-CoV-2 swab positivity in England during end September beginning October 2020: REACT-1 round 5 updated report,Steven Riley; Kylie E. C. Ainslie; Oliver Eales; Caroline E Walters; Haowei Wang; Christina J Atchison; Claudio Fronterre; Peter J Diggle; Deborah Ashby; Christl A. Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott,"Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Lancaster University; Lancaster University; Imperial College London; Imperial College London; Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London School of Public Health","BackgroundREACT-1 is quantifying prevalence of SARS-CoV-2 infection among random samples of the population in England based on PCR testing of self-administered nose and throat swabs. Here we report results from the fifth round of observations for swabs collected from the 18th September to 5th October 2020. This report updates and should be read alongside our round 5 interim report. - -MethodsRepresentative samples of the population aged 5 years and over in England with sample size ranging from 120,000 to 175,000 people at each round. Prevalence of PCR-confirmed SARS-CoV-2 infection, estimation of reproduction number (R) and time trends between and within rounds using exponential growth or decay models. - -Results175,000 volunteers tested across England between 18th September and 5th October. Findings show a national prevalence of 0.60% (95% confidence interval 0.55%, 0.71%) and doubling of the virus every 29 (17, 84) days in England corresponding to an estimated national R of 1.16 (1.05, 1.27). These results correspond to 1 in 170 people currently swab-positive for the virus and approximately 45,000 new infections each day. At regional level, the highest prevalence is in the North West, Yorkshire and The Humber and the North East with strongest regional growth in North West, Yorkshire and The Humber and West Midlands. - -ConclusionRapid growth has led to high prevalence of SARS-CoV-2 virus in England, with highest rates in the North of England. Prevalence has increased in all age groups, including those at highest risk. Improved compliance with existing policy and, as necessary, additional interventions are required to control the spread of SARS-CoV-2 in the community and limit the numbers of hospital admissions and deaths from COVID-19.",infectious diseases,exact,100,100 +medRxiv,10.1101/2020.10.11.20210625,2020-10-13,https://medrxiv.org/cgi/content/short/2020.10.11.20210625,Mental health service activity during COVID-19 lockdown among individuals with learning disabilities: South London and Maudsley data on services and mortality from January to July 2020,Evangelia Martin; Eleanor Nuzum; Matthew Broadbent; Robert Stewart,King's College London; King's College London; South London and Maudsley NHS Foundation Trust; King's College London,"The lockdown and social distancing policy imposed due to the COVID-19 pandemic is likely to have had a widespread impact on mental healthcare service provision and use. Previous reports from the South London and Maudsley NHS Trust (SLaM; a large mental health service provider for 1.2m residents in South London) highlighted a shift to virtual contacts among those accessing community mental health and home treatment teams and an increase in deaths over the pandemics first wave. However, there is a need to quantify this for individuals with particular vulnerabilities, including those with learning disabilities and other neurodevelopmental disorders. Taking advantage of the Clinical Record Interactive Search (CRIS) data resource with 24-hourly updates of electronic mental health records data, this paper describes daily caseloads and contact numbers (face-to-face and virtual) for individuals with potential neurodevelopmental disorders across community, specialist, crisis and inpatient services. The report focussed on the period 1st January to 31st July 2020. We also report on daily accepted and discharged trust referrals, total trust caseloads and daily inpatient admissions and discharges for individuals with potential neurodevelopmental disorders. In addition, daily deaths are described for all current and previous SLaM service users with potential neurodevelopmental disorders over this period. In summary, comparing periods before and after 16th March 2020 there was a shift from face-to-face contacts to virtual contacts across all teams. The largest declines in caseloads and total contacts were seen in Home Treatment Team, Liaison/A&E and Older Adult teams. Reduced accepted referrals and inpatient admissions were observed and there was an 103% increase in average daily deaths in the period after 16th March, compared to the period 1st January to 15th March (or a 282% increase if the 2-month period from 16th March to 15th May was considered alone).",psychiatry and clinical psychology,exact,100,100 medRxiv,10.1101/2020.10.09.20209957,2020-10-13,https://medrxiv.org/cgi/content/short/2020.10.09.20209957,Development and validation of the 4C Deterioration model for adults hospitalised with COVID-19,Rishi K Gupta; Ewen M Harrison; Antonia Ho; Annemarie B Docherty; Stephen R Knight; Maarten van Smeden; Ibrahim Abubakar; Marc Lipman; Matteo Quartagno; Riinu B Pius; Iain Buchan; Gail Carson; Thomas M Drake; Jake Dunning; Cameron J Fairfield; Carrol Gamble; Christopher A Green; Sophie Halpin; Hayley Hardwick; Karl Holden; Peter Horby; Clare Jackson; Kenneth McLean; Laura Merson; Jonathan S Nguyen-Van-Tam; Lisa Norman; Piero L Olliaro; Mark G Pritchard; Clark D Russell; James Scott-Brown; Catherine A Shaw; Aziz Sheikh; Tom Solomon; Cathie LM Sudlow; Olivia V Swann; Lance Turtle; Peter JM Openshaw; J Kenneth Baillie; Malcolm Gracie Semple; Mahdad Noursadeghi,"University College London; Centre for Medical Informatics, Usher Institute, University of Edinburgh, UK; Medical Research Council University of Glasgow Centre for Virus Research, Glasgow, UK; University of Edinburgh; Centre for Medical Informatics, The Usher Institute, University of Edinburgh; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands; Institute for Global Health, University College London, Gower Street, London, WC1E 6BT; UCL Respiratory, Division of Medicine, University College London, London, UK; MRC Clinical Trials Unit, Institute of Clinical Trials and Methodology, University College London, London, UK; University of Edinburgh; Institute of Population Health Sciences, University of Liverpool; University of Oxford; Centre for Medical Informatics, Usher Institute, University of Edinburgh, UK; National Infection Service Public Health England; Centre for Medical Informatics, Usher Institute, University of Edinburgh, UK; University of Liverpool; Institute of Microbiology & Infection, University of Birmingham; Liverpool Clinical Trials Centre, University of Liverpool, Liverpool, UK; University of Liverpool; University of Liverpool; ISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK; University of Liverpool; Centre for Medical Informatics, The Usher Institute, University of Edinburgh; University of Oxford; Division of Epidemiology and Public Health, University of Nottingham School of Medicine, Nottingham, UK; University of Edinburgh; University of Oxford; University of Oxford; Queens Medical Research Institute, University of Edinburgh, Edinburgh, UK; School of Informatics, University of Edinburgh, Edinburgh, UK; Department of Clinical Surgery, University of Edinburgh; Centre for Medical Informatics, The Usher Institute, University of Edinburgh; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life; University of Edinburgh; Department of Child Life and Health, University of Edinburgh, UK; Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK; Imperial College London; Roslin Institute, University of Edinburgh; University of Liverpool; Division of Infection and Immunity, University College London, Gower Street, London, WC1E 6BT","Prognostic models to predict the risk of clinical deterioration in acute COVID-19 are required to inform clinical management decisions. Among 75,016 consecutive adults across England, Scotland and Wales prospectively recruited to the ISARIC Coronavirus Clinical Characterisation Consortium (ISARIC4C) study, we developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) using 11 routinely measured variables. We used internal-external cross-validation to show consistent measures of discrimination, calibration and clinical utility across eight geographical regions. We further validated the final model in held-out data from 8,252 individuals in London, with similarly consistent performance (C-statistic 0.77 (95% CI 0.75 to 0.78); calibration-in-the-large 0.01 (-0.04 to 0.06); calibration slope 0.96 (0.90 to 1.02)). Importantly, this model demonstrated higher net benefit than using other candidate scores to inform decision-making. Our 4C Deterioration model thus demonstrates unprecedented clinical utility and generalisability to predict clinical deterioration among adults hospitalised with COVID-19.",infectious diseases,exact,100,100 medRxiv,10.1101/2020.10.08.20209304,2020-10-12,https://medrxiv.org/cgi/content/short/2020.10.08.20209304,Prevalence of COVID-19-related risk factors and risk of severe influenza outcomes in cancer survivors: a matched cohort study using linked English electronic health records data,Helena Carreira; Helen Strongman; Maria Peppa; Helen I McDonald; Isabel dos-Santos-Silva; Susannah Stanway; Liam Smeeth; Krishnan Bhaskaran,"London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; NIHR Health Protection Research Unit in Immunisation; London School of Medicine and Tropical Medicine, NIHR Health Protection Research Unit in Immunisation; London School of Hygiene and Tropical Medicine; The Royal Marsden NHS Foundation Trust; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine","BackgroundPeople with active cancer are recognised as at risk of COVID-19 complications, but it is unclear whether the much larger population of cancer survivors is at elevated risk. We aimed to address this by comparing cancer survivors and cancer-free controls for (i) prevalence of comorbidities considered risk factors for COVID-19; and (ii) risk of severe influenza, as a marker of susceptibility to severe outcomes from epidemic respiratory viruses. @@ -2220,6 +2137,17 @@ Research in contextO_ST_ABSEvidence before this studyC_ST_ABSPublished trials an Added value of this studyIn this cohort study representing 40% of the population of England, we investigated whether routine use of hydroxychloroquine prior to the COVID-19 outbreak prevented COVID-19 mortality. Using robust pharmacoepidemiological methods, we found no evidence to support a substantial benefit of hydroxychloroquine in preventing COVID-19 mortality. At the same time, we have shown no significant harm, and this generates the equipoise to justify continuing randomised trials. We have demonstrated in this study that it is feasible to address specific hypotheses about medicines in a rapid and transparent manner to inform interim clinical decision making and support the need for large-scale, randomised trial data. Implications of all the available evidenceThis is the first study to investigate the ongoing routine use of hydroxychloroquine and risk of COVID-19 mortality in a general population. While we found no evidence of any protective benefit, due to the observational nature of the study, residual confounding remains a possibility. Completion of trials for prevention of severe outcomes is warranted, but prior to the completion of these, we found no evidence to support the use of hydroxychloroquine for prevention of COVID-19 mortality.",infectious diseases,exact,100,100 +medRxiv,10.1101/2020.09.02.20185892,2020-09-07,https://medrxiv.org/cgi/content/short/2020.09.02.20185892,Prognostic accuracy of emergency department triage tools for adults with suspected COVID-19: The PRIEST observational cohort study,Ben Thomas; Steve Goodacre; Ellen Lee; Laura Sutton; Amanda Loban; Simon Waterhouse; Richard Simmonds; Katie Biggs; Carl Marincowitz; Jose Schutter; Sarah Connelly; Elena Sheldon; Jamie Hall; Emma Young; Andrew Bentley; Kirsty Challen; Chris Fitzsimmons; Tim Harris; Fiona Lecky; Andrew Lee; Ian Maconochie; Darren Walter,University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; Manchester University NHS Foundation Trust; Lancashire Teaching Hospitals NHS Foundation Trust; Sheffield Children's NHS Foundation Trust; Barts Health NHS Trust; University of Sheffield; University of Sheffield; Imperial College Healthcare NHS Trust; Manchester University NHS Foundation Trust,"ObjectivesThe World Health Organisation (WHO) and National Institute for Health and Care Excellence (NICE) recommend various triage tools to assist decision-making for patients with suspected COVID-19. We aimed to estimate the accuracy of triage tools for predicting severe illness in adults presenting to the emergency department (ED) with suspected COVID-19 infection. + +MethodsWe undertook a mixed prospective and retrospective observational cohort study in 70 EDs across the United Kingdom (UK). We collected data from people attending with suspected COVID-19 between 26 March 2020 and 28 May 2020, and used presenting data to determine the results of assessment with the following triage tools: the WHO algorithm, NEWS2, CURB-65, CRB-65, PMEWS and the swine flu adult hospital pathway (SFAHP). We used 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome. + +ResultsWe analysed data from 20892 adults, of whom 4672 (22.4%) died or received organ support (primary outcome), with 2058 (9.9%) receiving organ support and 2614 (12.5%) dying without organ support (secondary outcomes). C-statistics for the primary outcome were: CURB-65 0.75; CRB-65 0.70; PMEWS 0.77; NEWS2 (score) 0.77; NEWS2 (rule) 0.69; SFAHP (6-point) 0.70; SFAHP (7-point) 0.68; WHO algorithm 0.61. All triage tools showed worse prediction for receipt of organ support and better prediction for death without organ support. + +At the recommended threshold, PMEWS and the WHO criteria showed good sensitivity (0.96 and 0.95 respectively), at the expense of specificity (0.31 and 0.27 respectively). NEWS2 showed similar sensitivity (0.96) and specificity (0.28) when a lower threshold than recommended was used. + +ConclusionCURB-65, PMEWS and NEWS2 provide good but not excellent prediction for adverse outcome in suspected COVID-19, and predicted death without organ support better than receipt of organ support. PMEWS, the WHO criteria and NEWS2 (using a lower threshold than usually recommended) provide good sensitivity at the expense of specificity. + +RegistrationISRCTN registry, ISRCTN28342533, http://www.isrctn.com/ISRCTN28342533",emergency medicine,exact,100,100 medRxiv,10.1101/2020.09.01.20185793,2020-09-03,https://medrxiv.org/cgi/content/short/2020.09.01.20185793,Prognostic accuracy of emergency department triage tools for children with suspected COVID-19: The PRIEST observational cohort study,Katie Biggs; Ben Thomas; Steve Goodacre; Ellen Lee; Laura Sutton; Matthew Bursnall; Amanda Loban; Simon Waterhouse; Richard Simmonds; Carl Marincowitz; Jose Schutter; Sarah Connelly; Elena Sheldon; Jamie Hall; Emma Young; Andrew Bentley; Kirsty Challen; Chris Fitzsimmons; Tim Harris; Fiona Lecky; Andrew Lee; Ian Maconochie; Darren Walter,University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; Manchester University NHS Foundation Trust; Lancashire Teaching Hospitals NHS Foundation Trust; Sheffield Children's NHS Foundation Trust; Barts Health NHS Trust; University of Sheffield; University of Sheffield; Imperial College Healthcare NHS Trust; Manchester University NHS Foundation Trust,"ObjectivesEmergency department clinicians can use triage tools to predict adverse outcome and support management decisions for children presenting with suspected COVID-19. We aimed to estimate the accuracy of triage tools for predicting severe illness in children presenting to the emergency department (ED) with suspected COVID-19 infection. MethodsWe undertook a mixed prospective and retrospective observational cohort study in 44 EDs across the United Kingdom (UK). We collected data from children attending with suspected COVID-19 between 26 March 2020 and 28 May 2020, and used presenting data to determine the results of assessment using the WHO algorithm, swine flu hospital pathway for children (SFHPC), Paediatric Observation Priority Score (POPS) and Childrens Observation and Severity Tool (COAST). We recorded 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome. @@ -2274,6 +2202,13 @@ ResultsWith sensitivity of 80%, infection prevalence of 1 in 2,000, and specific ConclusionTo avoid multiple unnecessary restrictions on whole populations, and in particular individuals, from widespread population testing for SARS-CoV-2, the crucial roles of extremely high test specificity and of confirmatory testing must be fully appreciated and incorporated into policy decisions.",epidemiology,exact,100,100 medRxiv,10.1101/2020.08.17.20175117,2020-08-21,https://medrxiv.org/cgi/content/short/2020.08.17.20175117,Real-time spatial health surveillance: mapping the UK COVID-19 epidemic,Richard Fry; Joe Hollinghurst; Helen R Stagg; Daniel A Thompson; Claudio Fronterre; Chris Orton; Ronan A Lyons; David V Ford; Aziz Sheikh; Peter J Diggle,Swansea University; Swansea University; Edinburgh University; Swansea University; Lancaster University; Swansea University; Swansea University; Swansea University; Edinburgh University; Lancaster University,"The COVID-19 pandemic has highlighted the need for robust data linkage systems and methods for identifying outbreaks of disease in near real-time. Using self-reported app data and the Secure Anonymised Information Linkage (SAIL) Databank, we demonstrate the use of sophisticated spatial modelling for near-real-time prediction of COVID-19 prevalence at small-area resolution to inform strategic government policy areas. A pre-requisite to an effective control strategy is that predictions need to be accompanied by estimates of their precision, to guard against over-reaction to potentially spurious features of best guess predictions. In the UK, important emerging risk-factors such as social deprivation or ethnicity vary over small distances, hence risk needs to be modelled at fine spatial resolution to avoid aggregation bias. We demonstrate that existing geospatial statistical methods originally developed for global health applications are well-suited to this task and can be used in an anonymised databank environment, thus preserving the privacy of the individuals who contribute their data.",public and global health,exact,100,100 +medRxiv,10.1101/2020.08.12.20173690,2020-08-14,https://medrxiv.org/cgi/content/short/2020.08.12.20173690,"Antibody prevalence for SARS-CoV-2 in England following first peak of the pandemic: REACT2 study in 100,000 adults",Helen Ward; Christina J Atchison; Matthew Whitaker; Kylie E. C. Ainslie; Joshua Elliott; Lucy C Okell; Rozlyn Redd; Deborah Ashby; Christl A. Donnelly; Wendy Barclay; Ara Darzi; Graham Cooke; Steven Riley; Paul Elliott,"Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Dept Inf Dis Epi, Imperial College; Imperial College London","BackgroundEngland, UK has experienced a large outbreak of SARS-CoV-2 infection. As in USA and elsewhere, disadvantaged communities have been disproportionately affected. + +MethodsNational REal-time Assessment of Community Transmission-2 (REACT-2) prevalence study using a self-administered lateral flow immunoassay (LFIA) test for IgG among a random population sample of 100,000 adults over 18 years in England, 20 June to 13 July 2020. + +ResultsData were available for 109,076 participants, yielding 5,544 IgG positive results; adjusted (for test performance) and re-weighted (for sampling) prevalence was 6.0% (95% Cl: 5.8, 6.1). Highest prevalence was in London (13.0% [12.3, 13.6]), among people of Black or Asian (mainly South Asian) ethnicity (17.3% [15.8, 19.1] and 11.9% [11.0, 12.8] respectively) and those aged 18-24 years (7.9% [7.3, 8.5]). Adjusted odds ratio for care home workers with client-facing roles was 3.1 (2.5, 3.8) compared with non-essential workers. One third (32.2%, [31.0-33.4]) of antibody positive individuals reported no symptoms. Among symptomatic cases, most (78.8%) reported symptoms during the peak of the epidemic in England in March (31.3%) and April (47.5%) 2020. We estimate that 3.36 million (3.21, 3.51) people have been infected with SARS-CoV-2 in England to end June 2020, with an overall infection fatality ratio (IFR) of 0.90% (0.86, 0.94); age-specific IFR was similar among people of different ethnicities. + +ConclusionThe SARS-CoV-2 pandemic in England disproportionately affected ethnic minority groups and health and care home workers. The higher risk of infection in minority ethnic groups may explain their increased risk of hospitalisation and mortality from COVID-19.",infectious diseases,exact,100,100 medRxiv,10.1101/2020.08.12.20171405,2020-08-14,https://medrxiv.org/cgi/content/short/2020.08.12.20171405,OpenSAFELY: Do adults prescribed Non-steroidal anti-inflammatory drugs have an increased risk of death from COVID-19?,Angel YS Wong; Brian MacKenna; Caroline Morton; Anna Schultze; Alex J Walker; Krishnan Bhaskaran; Jeremy Brown; Christopher T. Rentsch; Elizabeth Williamson; Henry Drysdale; Richard Croker; Seb Bacon; William Hulme; Chris Bates; Helen J Curtis; Amir Mehrkar; David Evans; Peter Inglesby; Jonathan Cockburn; Helen McDonald; Laurie Tomlinson; Rohini Mathur; Kevin Wing; Harriet Forbes; John Parry; Frank Hester; Sam Harper; Stephen Evans; Liam Smeeth; Ian Douglas; Ben Goldacre,"London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; US Department of Veterans Affairs, London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; TPP; TPP; TPP; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford","ImportanceThere has been speculation that non-steroidal anti-inflammatory drugs (NSAIDs) may negatively affect coronavirus disease 2019 (COVID-19) outcomes, yet clinical evidence is limited. ObjectiveTo assess the association between NSAID use and deaths from COVID-19 using OpenSAFELY, a secure analytical platform. @@ -2504,7 +2439,6 @@ MethodsWe calculated survival curves and adjusted Cox proportional hazards model ResultsSurvival curves show an increased proportion of deaths between 23rd March and 14th June 2020 in care homes for older people, with an adjusted HR of 1{middle dot}72 (1{middle dot}55, 1{middle dot}90) compared to 2016. Compared to the general population in 2016-2019, adjusted care home mortality HRs for older adults rose from 2{middle dot}15 (2{middle dot}11,2{middle dot}20) in 2016-2019 to 2{middle dot}94 (2{middle dot}81,3{middle dot}08) in 2020. ConclusionsThe survival curves and increased HRs show a significantly increased risk of death in the 2020 study periods.",public and global health,exact,100,100 -bioRxiv,10.1101/2020.07.01.182709,2020-07-01,https://biorxiv.org/cgi/content/short/2020.07.01.182709,Genetic architecture of host proteins interacting with SARS-CoV-2,Maik Pietzner; Eleanor Wheeler; Julia Carrasco-Zanini; Johannes Raffler; Nicola D. Kerrison; Erin Oerton; Victoria P.W. Auyeung; Chris Finan; Juan P. Casas; Rachel Ostroff; Steve A. Williams; Gabi Kastenmüller; Markus Ralser; Eric G. Gamazon; Nicholas J. Wareham; Aroon Dinesh Hingorani; Claudia Langenberg,University of Cambridge; University of Cambridge; University of Cambridge; Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH); University of Cambridge; University of Cambridge; University of Cambridge; University College London; Harvard Medical School; SomaLogic Inc.; SomaLogic Inc.; Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH); The Francis Crick Institute; Vanderbilt University Medical Center; University of Cambridge; University College London; University of Cambridge,"Strategies to develop therapeutics for SARS-CoV-2 infection may be informed by experimental identification of viral-host protein interactions in cellular assays and measurement of host response proteins in COVID-19 patients. Identification of genetic variants that influence the level or activity of these proteins in the host could enable rapid in silico assessment in human genetic studies of their causal relevance as molecular targets for new or repurposed drugs to treat COVID-19. We integrated large-scale genomic and aptamer-based plasma proteomic data from 10,708 individuals to characterize the genetic architecture of 179 host proteins reported to interact with SARS-CoV-2 proteins or to participate in the host response to COVID-19. We identified 220 host DNA sequence variants acting in cis (MAF 0.01-49.9%) and explaining 0.3-70.9% of the variance of 97 of these proteins, including 45 with no previously known protein quantitative trait loci (pQTL) and 38 encoding current drug targets. Systematic characterization of pQTLs across the phenome identified protein-drug-disease links, evidence that putative viral interaction partners such as MARK3 affect immune response, and establish the first link between a recently reported variant for respiratory failure of COVID-19 patients at the ABO locus and hypercoagulation, i.e. maladaptive host response. Our results accelerate the evaluation and prioritization of new drug development programmes and repurposing of trials to prevent, treat or reduce adverse outcomes. Rapid sharing and dynamic and detailed interrogation of results is facilitated through an interactive webserver (https://omicscience.org/apps/covidpgwas/).",genomics,exact,100,100 medRxiv,10.1101/2020.06.29.20142448,2020-06-30,https://medrxiv.org/cgi/content/short/2020.06.29.20142448,Using past and current data to estimate potential crisis service use in mental healthcare after the COVID-19 lockdown: South London and Maudsley data,Robert Stewart; Matthew Broadbent,King's College London; South London and Maudsley NHS Foundation Trust,"The lockdown policy response to the COVID-19 pandemic in the UK has a potentially important impact on provision of mental healthcare with uncertain consequences over the 12 months ahead. Past activity may provide a means to predict future demand. Taking advantage of the Clinical Record Interactive Search (CRIS) data resource at the South London and Maudsley NHS Trust (SLaM; a large mental health service provider for 1.2m residents in south London), we carried out a range of descriptive analyses to inform the Trust on patient groups who might be most likely to require inpatient and home treatment team (HTT) crisis care. We considered the 12 months following UK COVID-19 lockdown policy on 16th March, drawing on comparable findings from previous years, and quantified levels of change in service delivery to those most likely to receive crisis care. For 12-month crisis days from 16th March in 2015-19, we found that most (over 80%) were accounted for by inpatient care (rather than HTT), most (around 75%) were used by patients who were current or recent Trust patients at the commencement of follow-up, and highest numbers were used by patients with a previously recorded schizophreniform disorder diagnosis. For current/recent patients on 16th March there had been substantial reductions in use of inpatient care in the following 31 days in 2020, more than previous years; changes in total non-inpatient contact numbers did not differ in 2020 compared to previous years, although there had been a marked switch from face-to-face to virtual contacts.",psychiatry and clinical psychology,exact,100,100 medRxiv,10.1101/2020.06.28.20141986,2020-06-29,https://medrxiv.org/cgi/content/short/2020.06.28.20141986,Protocol for the development and evaluation of a tool for predicting risk of short-term adverse outcomes due to COVID-19 in the general UK population,Julia Hippisley-Cox; Ashley Kieran Clift; Carol AC Coupland; Ruth Keogh; Karla Diaz-Ordaz; Elizabeth Williamson; Ewen Harrison; Andrew Hayward; Harry Hemingway; Peter Horby; Nisha Mehta; Jonathan Kieran Benger; Kamlesh Khunti; David Spiegelhalter; Aziz Sheikh; Jonathan Valabhji; Ronan A Lyons; John Robson; Malcolm Gracie Semple; Frank Kee; Peter Johnson; Susan Jebb; Tony Williams; David Coggon,"University of Oxford; University of Oxford; University of Nottingham; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Edinburgh; University College London; University College London; University of Oxford; Department of Health and Social Care; NHS Digital; University of Leicester; University of Cambridge; University of Edinburgh; Imperial College London; Swansea University; Queen Mary University London; University of Liverpool; Queen's University Belfast; University of Southampton; University of Oxford; Working Fit, Ltd.; University of Southampton","IntroductionNovel coronavirus 2019 (COVID-19) has propagated a global pandemic with significant health, economic and social costs. Emerging emergence has suggested that several factors may be associated with increased risk from severe outcomes or death from COVID-19. Clinical risk prediction tools have significant potential to generate individualised assessment of risk and may be useful for population stratification and other use cases. @@ -2516,21 +2450,6 @@ Strengths and limitations of the studyO_LIThe individual-level linkage of genera C_LIO_LIThe models will be trained and evaluated in population-representative datasets of millions of individuals C_LIO_LIShielding for clinically extremely vulnerable was advised and in place during the study period, therefore risk predictions influenced by the presence of some shielding conditions may require careful consideration C_LI",epidemiology,exact,100,100 -medRxiv,10.1101/2020.06.24.20139048,2020-06-25,https://medrxiv.org/cgi/content/short/2020.06.24.20139048,A geotemporal survey of hospital bed saturation across England during the first wave of the COVID-19 Pandemic,Bilal A Mateen; Harrison Wilde; John m Dennis; Andrew Duncan; Nicholas John Meyrick Thomas; Andrew P McGovern; Spiros Denaxas; Matt J Keeling; Sebastian J Vollmer,"The Alan Turing Institute; University of Warwick; Kings College Hospital NHS Foundation Trust; University of Warwick, Department of Statistics; University of Exeter Medical School; The Alan Turing Institute; Imperial College London, Faculty of Natural Sciences; University of Exeter Medical School; Royal Devon and Exeter NHS Foundation Trust, Diabetes and Endocrinology; University of Exeter Medical School; University College London; University of Warwick; The Alan Turing Institute; University of Warwick, Department of Statistics","BackgroundNon-pharmacological interventions were introduced based on modelling studies which suggested that the English National Health Service (NHS) would be overwhelmed by the COVID-19 pandemic. In this study, we describe the pattern of bed occupancy across England during the first wave of the pandemic, January 31st to June 5th 2020. - -MethodsBed availability and occupancy data was extracted from daily reports submitted by all English secondary care providers, between 27-Mar and 5-June. Two thresholds for safe occupancy were utilized (85% as per Royal College of Emergency Medicine and 92% as per NHS Improvement). - -FindingsAt peak availability, there were 2711 additional beds compatible with mechanical ventilation across England, reflecting a 53% increase in capacity, and occupancy never exceeded 62%. A consequence of the repurposing of beds meant that at the trough, there were 8{middle dot}7% (8,508) fewer general and acute (G&A) beds across England, but occupancy never exceeded 72%. The closest to (surge) capacity that any trust in England reached was 99{middle dot}8% for general and acute beds. For beds compatible with mechanical ventilation there were 326 trust-days (3{middle dot}7%) spent above 85% of surge capacity, and 154 trust-days (1{middle dot}8%) spent above 92%. 23 trusts spent a cumulative 81 days at 100% saturation of their surge ventilator bed capacity (median number of days per trust = 1 [range: 1 to 17]). However, only 3 STPs (aggregates of geographically co-located trusts) reached 100% saturation of their mechanical ventilation beds. - -InterpretationThroughout the first wave of the pandemic, an adequate supply of all bed-types existed at a national level. Due to an unequal distribution of bed utilization, many trusts spent a significant period operating above safe-occupancy thresholds, despite substantial capacity in geographically co-located trusts; a key operational issue to address in preparing for a potential second wave. - -FundingThis study received no funding. - -Research In ContextO_ST_ABSEvidence Before This StudyC_ST_ABSWe identified information sources describing COVID-19 related bed and mechanical ventilator demand modelling, as well as bed occupancy during the first wave of the pandemic by performing regular searches of MedRxiv, PubMed and Google, using the terms COVID-19, mechanical ventilators, bed occupancy, England, UK, demand, and non-pharmacological interventions (NPIs), until June 20th, 2020. Two UK-specific studies were found that modelled the demand for mechanical ventilators, one of which incorporated sensitivity analysis based on the introduction of NPIs and found that their effects might prevent the healthcare system being overwhelmed. Separately, several news reports were found pertaining to a single hospital that reached ventilator capacity in England during the first wave of the pandemic, however, no single authoritative source was identified detailing impact across all hospital sites in England. - -Added Value of This StudyThis national study of hospital-level bed occupancy in England provides unique and timely insight into bed-specific resource utilization during the first wave of the COVID-19 pandemic, nationally, and by specific (geographically defined) health footprints. We found evidence of an unequal distribution of resource utilization across England. Although occupancy of beds compatible with mechanical ventilation never exceeded 62% at the national level, 52 (30%) hospitals across England reached 100% saturation at some point during the first wave of the pandemic. Close examination of the geospatial data revealed that in the vast majority of circumstances there was relief capacity in geographically co-located hospitals. Over the first wave it was theoretically possible to markedly reduce (by 95.1%) the number of hospitals at 100% saturation of their mechanical ventilator bed capacity by redistributing patients to nearby hospitals. - -Implications Of All The Available EvidenceNow-casting using routinely collected administrative data presents a robust approach to rapidly evaluate the effectiveness of national policies introduced to prevent a healthcare system being overwhelmed in the context of a pandemic illness. Early investment in operational field hospital and an independent sector network may yield more overtly positive results in the winter, when G&A occupancy-levels regularly exceed 92% in England, however, during the first wave of the pandemic they were under-utilized. Moreover, in the context of the non-pharmacological interventions utilized during the first wave of COVID-19, demand for beds and mechanical ventilators was much lower than initially predicted, but despite this many trust spent a significant period of time operating above safe-occupancy thresholds. This finding demonstrates that it is vital that future demand (prediction) models reflect the nuances of local variation within a healthcare system. Failure to incorporate such geographical variation can misrepresent the likelihood of surpassing availability thresholds by averaging out over regions with relatively lower demand, and presents a key operational issue for policymakers to address in preparing for a potential second wave.",health systems and quality improvement,exact,100,100 medRxiv,10.1101/2020.06.21.20136853,2020-06-23,https://medrxiv.org/cgi/content/short/2020.06.21.20136853,Modelling the impact of lockdown easing measures on cumulative COVID-19 cases and deaths in England,Hisham Ziauddeen; Naresh Subramaniam; Deepti Gurdasani,"Dept. of Psychiatry, University of Cambridge, Cambridge, UK; Dept. of Psychiatry, University of Cambridge, Cambridge UK; Queen Mary University of London","BackgroundAs countries begin to ease the lockdown measures instituted to control the COVID-19 pandemic, there is a risk of a resurgence of the pandemic, and early reports of this are already emerging from some countries. Unlike many other countries, the UK started easing lockdown in England when levels of community transmission were still high, and this could have a major impact on case numbers and deaths. However thus far, the likely impacts of easing restrictions at this point in the pandemic have not been quantified. Using a Bayesian model, we assessed the potential impacts of successive lockdown easing measures in England, focussing on scenarios where the reproductive number (R) remains [≤]1 in line with the UK governments stated aim. MethodsWe developed a Bayesian model to infer incident cases and R in England, from incident death data from the Office of National Statistics. We then used this to forecast excess cases and deaths in multiple plausible scenarios in which R increases at one or more time points, compared to a baseline scenario where R remains unchanged by the easing of lockdown. @@ -2613,7 +2532,6 @@ Main outcome measuresSimulated mean visual acuity and proportions of eyes with v ResultsThe number of nAMD referrals at four major eye treatment hospital groups based in England dropped on average by 72% (range 65 to 87%) in April 2020 compared to April 2019. Simulated one-year visual outcomes for 1000 nAMD eyes with a 3-month treatment delay suggested an increase in the proportion of eyes with vision [≤]6/60 from 15.5% (13.2 to 17.9) to 23.3% (20.7 to25.9), and a decrease in the proportion of eyes with vision [≥]6/12 (driving vision) from 35.1% (32.1 to 38.1) to 26.4% (23.8 to29.2). Outcomes worsened incrementally with longer modelled delays. Assuming nAMD referrals are reduced to this level at the national level for only one month, these simulated results suggest an additional 186-365 eyes with vision [≤]6/60 at one-year with even a short treatment delay. ConclusionsWe report a large decrease in nAMD referrals during the first month of COVID-19 lockdown and provide an important public health message regarding the risk of delayed treatment. As a conservative estimate, a treatment delay of 3 months could lead to a >50% relative increase in the number of eyes with vision [≤]6/60 and 25% relative decrease in the number of eyes with driving vision at one year.",ophthalmology,exact,100,100 -medRxiv,10.1101/2020.06.01.20116608,2020-06-03,https://medrxiv.org/cgi/content/short/2020.06.01.20116608,Is death from Covid-19 a multistep process?,Neil Pearce; Giovenale Moirano; Milena Maule; Manolis Kogevinas; Xavier Rodo; Deborah Lawlor; Jan Vandenbroucke; Christina Vandenbroucke-Grauls; Fernando P Polack; Adnan Custovic,"London School of Hygiene and Tropical Medicine; University of Turin, Italy; University of Turin, Italy; ISGlobal; ISGlobal; University of Bristol; Leiden University Medical Center; Amsterdam UMC; Vanderbilt Unversity; Imperial College London","Covid-19 death has a different relationship with age than is the case for other severe respiratory pathogens. The Covid-19 death rate increases exponentially with age, and the main risk factors are age itself, as well as having underlying conditions such as hypertension, diabetes, cardiovascular disease, severe chronic respiratory disease and cancer. Furthermore, the almost complete lack of deaths in children suggests that infection alone is not sufficient to cause death; rather, one must have gone through a number of changes, either as a result of undefined aspects of aging, or as a result of chronic disease. These characteristics of Covid-19 death are consistent with the multistep model of disease, a model which has primarily been used for cancer, and more recently for amyotrophic lateral sclerosis (ALS). We applied the multi-step model to data on Covid-19 case fatality rates (CFRs) from China, South Korea, Italy, Spain and Japan. In all countries we found that a plot of ln (CFR) against ln (age) was approximately linear with a slope of about 5. As a comparison, we also conducted similar analyses for selected other respiratory diseases. SARS showed a similar log-log age-pattern to that of Covid-19, albeit with a lower slope, whereas seasonal and pandemic influenza showed quite different age-patterns. Thus, death from Covid-19 and SARS appears to follow a distinct age-pattern, consistent with a multistep model of disease that in the case of Covid-19 is probably defined by comorbidities and age producing immune-related susceptibility. Identification of these steps would be potentially important for prevention and therapy for SARS-COV-2 infection.",infectious diseases,exact,100,100 medRxiv,10.1101/2020.05.27.20083287,2020-06-01,https://medrxiv.org/cgi/content/short/2020.05.27.20083287,Estimating excess mortality in people with cancer and multimorbidity in the COVID-19 emergency,Alvina G Lai; Laura Pasea; Amitava Banerjee; Spiros Denaxas; Michail Katsoulis; Wai Hoong Chang; Bryan Williams; Deenan Pillay; Mahdad Noursadeghi; David Linch; Derralynn Hughes; Martin D Forster; Clare Turnbull; Natalie K Fitzpatrick; Kathryn Boyd; Graham R Foster; Matt Cooper; Monica Jones; Kathy Pritchard-Jones; Richard Sullivan; Geoff Hall; Charlie Davie; Mark Lawler; Harry Hemingway,"University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; Royal Free NHS Foundation Trust; University College London; Institute of Cancer Research; University College London; Northern Ireland Cancer Network; Queen Mary University of London; DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners; DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners; DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners; Kings College London; DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners; DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners; DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners; University College London","BackgroundCancer and multiple non-cancer conditions are considered by the Centers for Disease Control and Prevention (CDC) as high risk conditions in the COVID-19 emergency. Professional societies have recommended changes in cancer service provision to minimize COVID-19 risks to cancer patients and health care workers. However, we do not know the extent to which cancer patients, in whom multi-morbidity is common, may be at higher overall risk of mortality as a net result of multiple factors including COVID-19 infection, changes in health services, and socioeconomic factors. MethodsWe report multi-center, weekly cancer diagnostic referrals and chemotherapy treatments until April 2020 in England and Northern Ireland. We analyzed population-based health records from 3,862,012 adults in England to estimate 1-year mortality in 24 cancer sites and 15 non-cancer comorbidity clusters (40 conditions) recognized by CDC as high-risk. We estimated overall (direct and indirect) effects of COVID-19 emergency on mortality under different Relative Impact of the Emergency (RIE) and different Proportions of the population Affected by the Emergency (PAE). We applied the same model to the US, using Surveillance, Epidemiology, and End Results (SEER) program data. @@ -2729,6 +2647,9 @@ MethodsCohort study analysed by Cox-regression to generate hazard ratios: age an ResultsThere were 5683 deaths attributed to COVID-19. In summary after full adjustment, death from COVID-19 was strongly associated with: being male (hazard ratio 1.99, 95%CI 1.88-2.10); older age and deprivation (both with a strong gradient); uncontrolled diabetes (HR 2.36 95% CI 2.18-2.56); severe asthma (HR 1.25 CI 1.08-1.44); and various other prior medical conditions. Compared to people with ethnicity recorded as white, black people were at higher risk of death, with only partial attenuation in hazard ratios from the fully adjusted model (age-sex adjusted HR 2.17 95% CI 1.84-2.57; fully adjusted HR 1.71 95% CI 1.44-2.02); with similar findings for Asian people (age-sex adjusted HR 1.95 95% CI 1.73-2.18; fully adjusted HR 1.62 95% CI 1.431.82). ConclusionsWe have quantified a range of clinical risk factors for death from COVID-19, some of which were not previously well characterised, in the largest cohort study conducted by any country to date. People from Asian and black groups are at markedly increased risk of in-hospital death from COVID-19, and contrary to some prior speculation this is only partially attributable to pre-existing clinical risk factors or deprivation; further research into the drivers of this association is therefore urgently required. Deprivation is also a major risk factor with, again, little of the excess risk explained by co-morbidity or other risk factors. The findings for clinical risk factors are concordant with policies in the UK for protecting those at highest risk. Our OpenSAFELY platform is rapidly adding further NHS patients records; we will update and extend these results regularly.",epidemiology,exact,100,100 +medRxiv,10.1101/2020.05.02.20078642,2020-05-06,https://medrxiv.org/cgi/content/short/2020.05.02.20078642,Impact of ethnicity on outcome of severe COVID-19 infection. Data from an ethnically diverse UK tertiary centre,James T Teo; Daniel Bean; Rebecca Bendayan; Richard Dobson; Ajay Shah,Kings College Hospital NHS Foundation Trust; King's College London; King's College London; Kings College London; King's College London,"During the current COVID-19 pandemic, it has been suggested that BAME background patients may be disproportionately affected compared to White but few detailed data are available. We took advantage of near real-time hospital data access and analysis pipelines to look at the impact of ethnicity in 1200 consecutive patients admitted between 1st March 2020 and 12th May 2020 to Kings College Hospital NHS Trust in London (UK). + +Our key findings are firstly that BAME patients are significantly younger and have different co-morbidity profiles than White individuals. Secondly, there is no significant independent effect of ethnicity on severe outcomes (death or ITU admission) within 14-days of symptom onset, after adjustment for age, sex and comorbidities.",intensive care and critical care medicine,exact,100,100 medRxiv,10.1101/2020.04.28.20083170,2020-05-05,https://medrxiv.org/cgi/content/short/2020.04.28.20083170,Quantifying and mitigating the impact of the COVID-19 pandemic on outcomes in colorectal cancer,Amit Sud; Michael Jones; John Broggio; Stephen Scott; Chey Loveday; Bethany Torr; Alice Garrett; David L. Nicol; Shaman Jhanji; Stephen A. Boyce; Matthew Williams; Georgios Lyratzopoulos; Claire Barry; Elio Riboli; Emma Kipps; Ethna McFerran; Mark Lawler; David C. Muller; Muti Abulafi; Richard Houlston; Clare Ann Turnbull,"Institute of Cancer Research; Institute of Cancer Research; Public Health England; RM Partners, West London Cancer Alliance; Institute of Cancer Research; Institute of Cancer Research; Institute of Cancer Research; Royal Marsden NHS Foundation Trust; Royal Marsden NHS Foundation Trust; Oxford University Hospitals NHS Foundation Trust; Imperial College; University College London; RM Partners, West London Cancer Alliance; Imperial College London; Royal Marsden NHS Foundation Trust; Queen's University Belfast; Queen's University Belfast; Imperial College London; Croydon Health Services NHS Trust, on behalf of RMP NICE FIT Steering Group; Institute of Cancer Research; Institute of Cancer Research","BackgroundThe COVID-19 pandemic has caused disruption across cancer pathways for diagnosis and treatment. In England, 32% of colorectal cancer (CRC) is diagnosed via urgent symptomatic referral from primary care, the ""2-week-wait"" (2WW) pathway. Access to routine endoscopy is likely to be a critical bottleneck causing delays in CRC management due to chronic limitation in capacity, acute competition for physician time, and safety concerns. MethodsWe used age-specific, stage-specific 10 year CRC survival for England 2007-2017 and 2WW CRC cases volumes. We used per-day hazard ratios of CRC survival generated from observational studies of CRC diagnosis-to-treatment interval to model the effect of different durations of per-patient delay. We utilised data from a large London observational study of faecal immunochemical testing (FIT) in symptomatic patients to model FIT-triage to mitigate delay to colonoscopy. diff --git a/data/covid/preprints.exact.json b/data/covid/preprints.exact.json index beca1001..80d7434f 100644 --- a/data/covid/preprints.exact.json +++ b/data/covid/preprints.exact.json @@ -27,6 +27,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2023.08.11.23293977", + "date": "2023-08-15", + "link": "https://medrxiv.org/cgi/content/short/2023.08.11.23293977", + "title": "Digital Mental Health Service engagement changes during Covid-19 in children and young people across the UK: presenting concerns, service activity, and access by gender, ethnicity, and deprivation", + "authors": "Duleeka Knipe; Santiago de Ossorno Garcia; Louisa Salhi; Lily Mainstone-Cotton; Aaron Sefi; Ann John", + "affiliations": "University of Bristol School of Social and Community Medicine: University of Bristol Population Health Sciences; Kooth Digital Health; Kooth Digital Health; Kooth Digital Health; Kooth Digital Health; Swansea University", + "abstract": "The adoption of digital health technologies accelerated during Covid-19, with concerns over the equity of access due to digital exclusion. Using data from a text-based online mental health service for children and young people we explore the impact of the pandemic on service access and presenting concerns and whether differences were observed by sociodemographic characteristics in terms of access (gender, ethnicity and deprivation). We used interrupted time-series models to assess whether there was a change in the level and rate of service use during the Covid-19 pandemic (April 2020-April 2021) compared to pre-pandemic trends (June 2019-March 2020). Routinely collected data from 61221 service users were extracted for observation, those represented half of the service population as only those with consent to share their data were used. The majority of users identified as female (74%) and White (80%), with an age range between 13 and 20 years of age. There was evidence of a sudden increase (13%) in service access at the start of the pandemic (RR 1.13 95% CI 1.02, 1.25), followed by a reduced rate (from 25% to 21%) of engagement during the pandemic compared to pre-pandemic trends (RR 0.97 95% CI 0.95,0.98). There was a sudden increase in almost all presenting issues apart from physical complaints. There was evidence of a step increase in the number of contacts for Black/African/Caribbean/Black British (38% increase; 95% CI: 1%-90%) and White ethnic groups (14% increase; 95% CI: 2%-27%)), sudden increase in service use at the start of the pandemic for the most (58% increase; 95% CI: 1%-247%) and least (47% increase; 95% CI: 6%-204%) deprived areas. During the pandemic, contact rates decreased, and referral sources change at the start. Findings on access and service activity align with other studies observing reduced service utilization. The lack of differences in deprivation levels and ethnicity at lockdown suggests exploring equity of access to the anonymous service. The study provides unique insights into changes in digital mental health use during Covid-19 in the UK.", + "category": "public and global health", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2023.08.07.23293778", @@ -181,20 +195,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2023.05.08.23289442", - "date": "2023-05-11", - "link": "https://medrxiv.org/cgi/content/short/2023.05.08.23289442", - "title": "Cohort Profile: Post-hospitalisation COVID-19 study (PHOSP-COVID)", - "authors": "Omer Elneima; Hamish J C McAuley; Olivia C Leavy; James D Chalmers; Alex Horsley; Ling-Pei Ho; Michael Marks; Krisnah Poinasamy; Betty Raman; Aarti Shikotra; Amisha Singapuri; Marco Sereno; Victoria C Harris; Linzy Houchen-Wolloff; Ruth M Saunders; Neil J Greening; Matthew Richardson; Jennifer K Quint; Andrew Briggs; Annemarie B Docherty; Steven Kerr; Ewen M Harrison; Nazir I Lone; Mathew Thorpe; Liam G Heaney; Keir E Lewis; Raminder Aul; Paul Beirne; Charlotte E Bolton; Jeremy S Brown; Gourab Choudhury; Nawar Diar Bakerly; Nicholas Easom; Carlos Echevarria; Jonathan Fuld; Nick Hart; John R Hurst; Mark G Jones; Dhruv Parekh; Paul E Pfeffer; Najib M Rahman; Sarah L Rowland-Jones; AA Roger Thompson; Caroline Jolley; Ajay M Shah; Dan G Wootton; Trudie Chalder; Melanie J Davies; Anthony De Soyza; John R Geddes; William Greenhalf; Simon Heller; Luke S Howard; Joseph Jacob; R Gisli Jenkins; Janet M Lord; William D-C Man; Gerry P McCann; Stefan Neubauer; Peter JM Openshaw; Joanna C Porter; Matthew J Rowland; Janet T Scott; Malcolm G Semple; Sally J Singh; David C Thomas; Mark Toshner; Aziz Sheikh; Chris E Brightling; Louise v Wain; Rachael A Evans; - on behalf of the PHOSP-COVID Collaborative Group", - "affiliations": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Population Health Sciences, University of Leicester, Leicester, UK; University of Dundee, Ninewells Hospital and Medical School, Dundee, UK; Division of Infection, Immunity & Respiratory Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK; MRC Human Immunology Unit, University of Oxford, Oxford, UK; Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK; Asthma and Lung UK, London, UK; Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre- Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; National Heart and Lung Institute, Imperial College London, London, UK; London School of Hygiene & Tropical Medicine, London, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; The Roslin Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Wellcome-Wolfson Institute for Experimental Medicine, Queens University Belfast, Belfast, UK; Hywel Dda University Health Board, Wales, UK; St George's University Hospitals NHS Foundation Trust, London, UK; Leeds Teaching Hospitals NHS Trust, Leeds, UK; NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK; UCL Respiratory, Department of Medicine, University College London, London, UK; Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK; Salford Royal NHS Foundation Trust, Manchester, UK; Infection Research Group, Hull University Teaching Hospitals, Hull, UK; Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, UK; Department of Respiratory Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK; Lane Fox Respiratory Unit, Guy's and St Thomas' NHS Foundation Trust, London, UK; Royal Free London NHS Foundation Trust, London, UK; Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK; Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK; Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK; NIHR Oxford Biomedical Research Centre, Oxford, UK; University of Sheffield, Sheffield, UK; University of Sheffield, Sheffield, UK; Centre for Human & Applied Physiological Sciences, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK; King's College London British Heart Foundation Centre, London, UK; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool, UK; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK; NIHR Oxford Health Biomedical Research Centre, University of Oxford, Oxford, UK; The CRUK Liverpool Experimental Cancer Medicine Centre, Liverpool, UK; Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK; Imperial College Healthcare NHS Trust, London, UK; Centre for Medical Image Computing, University College London, London, UK; National Heart and Lung Institute, Imperial College London, London, UK; MRC-Versus Arthritis Centre for Musculoskeletal Ageing Research, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK; Royal Brompton & Harefield Hospitals, Guy's and St. Thomas' NHS Foundation Trust, London, UK; Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester; NIHR Oxford Biomedical Research Centre, Oxford, UK; National Heart and Lung Institute, Imperial College London, London, UK; UCL Respiratory, Department of Medicine, University College London, London, UK; Kadoorie Centre for Critical Care Research, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; MRC-University of Glasgow Center for Virus research; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool, UK; Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Immunology and Inflammation, Imperial College London, London, UK; NIHR Cambridge Biomedical Research Centre, Cambridge, United Kingdom; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Population Health Sciences, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; ", - "abstract": "O_LIPHOSP-COVID is a national UK multi-centre cohort study of patients who were hospitalised for COVID-19 and subsequently discharged.\nC_LIO_LIPHOSP-COVID was established to investigate the medium- and long-term sequelae of severe COVID-19 requiring hospitalisation, understand the underlying mechanisms of these sequelae, evaluate the medium- and long-term effects of COVID-19 treatments, and to serve as a platform to enable future studies, including clinical trials.\nC_LIO_LIData collected covered a wide range of physical measures, biological samples, and Patient Reported Outcome Measures (PROMs).\nC_LIO_LIParticipants could join the cohort either in Tier 1 only with remote data collection using hospital records, a PROMs app and postal saliva sample for DNA, or in Tier 2 where they were invited to attend two specific research visits for further data collection and biological research sampling. These research visits occurred at five (range 2-7) months and 12 (range 10-14) months post-discharge. Participants could also participate in specific nested studies (Tier 3) at selected sites.\nC_LIO_LIAll participants were asked to consent to further follow-up for 25 years via linkage to their electronic healthcare records and to be re-contacted for further research.\nC_LIO_LIIn total, 7935 participants were recruited from 83 UK sites: 5238 to Tier 1 and 2697 to Tier 2, between August 2020 and March 2022.\nC_LIO_LICohort data are held in a Trusted Research Environment and samples stored in a central biobank. Data and samples can be accessed upon request and subject to approvals.\nC_LI", - "category": "respiratory medicine", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2023.04.24.23289043", @@ -321,20 +321,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2023.02.18.23286127", - "date": "2023-02-19", - "link": "https://medrxiv.org/cgi/content/short/2023.02.18.23286127", - "title": "Antipsychotic prescribing and mortality in people with dementia before and during the COVID-19 pandemic: retrospective cohort study", - "authors": "Christian Schnier; Aoife McCarthy; Daniel R Morales; Ashley Akbari; Reecha Sofat; Caroline Dale; Rohan Takhar; Mamas Mamas; Kamlesh Khunti; Francesco Zaccardi; Cathie LM Sudlow; Tim Wilkinson", - "affiliations": "University of Edinburgh; University of Edinburgh; University of Dundee; Swansea University; University of Liverpool; University of Liverpool; University College London; Keele University; University of Leicester; University of Leicester; University of Edinburgh; University of Edinburgh", - "abstract": "BackgroundAntipsychotic drugs have been associated with increased mortality, stroke and myocardial infarction in people with dementia. Concerns have been raised that antipsychotic prescribing may have increased during the COVID-19 pandemic due to social restrictions imposed to limit the spread of the virus. We used multisource, routinely-collected healthcare data from Wales, UK, to investigate prescribing and mortality trends in people with dementia before and during the COVID-19 pandemic.\n\nMethodsWe used individual-level, anonymised, population-scale linked health data to identify adults aged [≥]60 years with a diagnosis of dementia in Wales, UK. We explored antipsychotic prescribing trends over 67 months between 1st January 2016 and 1st August 2021, overall and stratified by age and dementia subtype. We used time series analyses to examine all-cause, myocardial infarction (MI) and stroke mortality over the study period and identified the leading causes of death in people with dementia.\n\nFindingsOf 57,396 people with dementia, 11,929 (21%) were prescribed an antipsychotic at any point during follow-up. Accounting for seasonality, antipsychotic prescribing increased during the second half of 2019 and throughout 2020. However, the absolute difference in prescribing rates was small, ranging from 1253 to 1305 per 10,000 person-months. Prescribing in the 60-64 age group and those with Alzheimers disease increased throughout the 5-year period. All-cause and stroke mortality increased in the second half of 2019 and throughout 2020 but MI mortality declined. From January 2020, COVID-19 was the second commonest underlying cause of death in people with dementia.\n\nInterpretationDuring the COVID-19 pandemic there was a small increase in antipsychotic prescribing in people with dementia. The long-term increase in antipsychotic prescribing in younger people and in those with Alzheimers disease warrants further investigation.\n\nFundingBritish Heart Foundation (BHF) (SP/19/3/34678) via the BHF Data Science Centre led by HDR UK, and the Scottish Neurological Research Fund.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched Ovid MEDLINE for studies describing antipsychotic prescribing trends in people with dementia during the COVID-19 pandemic, published between 1st January 2020 and 22nd March 2022. The following search terms were used: (exp Antipsychotic Agents/ OR antipsychotic.mp OR neuroleptic.mp OR risperidone.mp OR exp Risperidone/ OR quetiapine.mp OR exp Quetiapine Fumarate/ OR olanzapine.mp OR exp Olanzapine/ OR exp Psychotropic Drugs/ or psychotropic.mp) AND (exp Dementia/ OR exp Alzheimer Disease/ or alzheimer.mp) AND (prescri*.mp OR exp Prescriptions/ OR exp Electronic Prescribing/ OR trend*.mp OR time series.mp). The search identified 128 published studies, of which three were eligible for inclusion. Two studies, based on data from England and the USA, compared antipsychotic prescribing in people with dementia before and during the COVID-19 pandemic. Both reported an increase in the proportion of patients prescribed an antipsychotic after the onset of the pandemic. A third study, based in the Netherlands, reported antipsychotic prescription trends in nursing home residents with dementia during the first four months of the pandemic, comparing prescribing rates to the timings of lifting of social restrictions, showing that antipsychotic prescribing rates remained constant throughout this period.\n\nAdded value of this studyWe conducted age-standardised time series analyses using comprehensive, linked, anonymised, individual-level routinely-collected, population-scale health data for the population of Wales, UK. By accounting for seasonal variations in prescribing and mortality, we demonstrated that the absolute increase in antipsychotic prescribing in people with dementia of any cause during the COVID-19 pandemic was small. In contrast, antipsychotic prescribing in the youngest age group (60-64 years) and in people with a subtype diagnosis of Alzheimers disease increased throughout the five-year study period. Accounting for seasonal variation, all-cause mortality rates in people with dementia began to increase in late 2019 and increased sharply during the first few months of the pandemic. COVID-19 became the leading non-dementia cause of death in people with dementia from 2020 to 2021. Stroke mortality increased during the pandemic, following a similar pattern to that of all-cause mortality, whereas myocardial infarction rates decreased.\n\nImplications of all the available evidenceDuring COVID-19 we observed a large increase in all-cause and stroke mortality in people with dementia. When seasonal variations are accounted for, antipsychotic prescribing rates in all-cause dementia increased by a small amount before and during the pandemic in the UK. The increased prescribing rates in younger age groups and in people with Alzheimers disease warrants further investigation.", - "category": "neurology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2023.02.16.23286017", @@ -433,6 +419,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2023.01.04.22283762", + "date": "2023-01-05", + "link": "https://medrxiv.org/cgi/content/short/2023.01.04.22283762", + "title": "Challenges in estimating waning effectiveness of two doses of BNT162b2 and ChAdOx1 COVID-19 vaccines beyond six months: an OpenSAFELY cohort study using linked electronic health records", + "authors": "Elsie MF Horne; William J Hulme; Ruth H Keogh; Tom M Palmer; Elizabeth Williamson; Edward PK Parker; Venexia M Walker; Rochelle Knight; Yinghui Wei; Kurt Taylor; Louis Fisher; Jessica Morley; Amir Mehrkar; Iain Dillingham; Sebastian CJ Bacon; Ben Goldacre; Jonathan AC Sterne; - The OpenSAFELY Collaborative", + "affiliations": "University of Bristol; University of Oxford; London School of Hygiene and Tropical Medicine; University of Bristol; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Bristol; University of Bristol; University of Plymouth; University of Bristol; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Bristol; -", + "abstract": "Quantifying the waning effectiveness of second COVID-19 vaccination beyond six months and against the omicron variant is important for scheduling subsequent doses. With the approval of NHS England, we estimated effectiveness up to one year after second dose, but found that bias in such estimates may be substantial.", + "category": "epidemiology", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.12.21.22283794", @@ -475,20 +475,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.11.29.22282883", - "date": "2022-12-12", - "link": "https://medrxiv.org/cgi/content/short/2022.11.29.22282883", - "title": "The protection gap under a social health protection initiative in the COVID-19 pandemic: A case study from Khyber Pakhtunkhwa, Pakistan.", - "authors": "Sheraz Ahmad Khan; Kathrin Cresswell; Aziz Sheikh", - "affiliations": "The University of Edinburgh; The University of Edinburgh College of Medicine and Veterinary Medicine; The University of Edinburgh College of Medicine and Veterinary Medicine", - "abstract": "BackgroundSehat Sahulat Programme (SSP) is a Social Health Protection (SHP) initiative by the Government of Khyber Pakhtunkhwa (GoKP), covering inpatient services for 100% of the provinces population. In this paper, we describe SSPs role in GoKPs COVID-19 response and draw inferences for similar programmes in Pakistan.\n\nMethodology and methodsWe conceptualised SSP as an instrumental case study and collected three complementary data sources. First, we studied GoKPs official documents to understand SSPs benefits package. Then we undertook in-depth interviews and collected non-participant observations at the SSP policy and implementation levels. We recruited participants through direct (verbal and email) and indirect (invitation posters) methods.\n\nUse of maximum variation sampling enabled us to understand contrasting views from various stakeholders on SSPs policy dimensions (i.e., coverage and financing), tensions between the policy directions (i.e., whether or not to cover COVID-19) and how policy decisions were made and implemented. We collected data from March 2021 to December 2021. Thematic analysis was conducted with the help of Nvivo12.\n\nFindingsThroughout 2020, SSP did not cover COVID-19 treatment. The insurer and GoKP officials considered the pandemic a standard exclusion to insurance coverage. One SSP official said: \"COVID-19 is not covered and not relevant to us\". GoKP had stopped non-emergency services at all hospitals. When routine services restarted, the insurer did not cover COVID-19 screening tests, which were mandatory prior to hospital admission.\n\nIn 2021, GoKP engaged 10 private SSP hospitals for COVID-19 treatment. The SSP Reserve Fund, rather than insurance pooled money, was used. The Reserve Fund was originally meant to cover high-cost organ transplants. In 2021, SSP had 1,002 COVID-19-related admissions, which represented 0.2% of all hospital admissions (N=544,841).\n\nAn advocacy group representative called the COVID-19 care under SSP \"too little too late\". In contrast, SSP officials suggested their insurance database and funds flow mechanism could help GoKP in future health emergencies.\n\nConclusionThe commercially focused interpretation of SHP arrangements led to a protection gap in the context of COVID-19. SSP and similar programmes in other provinces of Pakistan should emphasise the notion of protection and not let commercial interests lead to protection gaps.", - "category": "health policy", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.12.03.22282974", @@ -517,20 +503,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.11.29.22282899", - "date": "2022-11-29", - "link": "https://medrxiv.org/cgi/content/short/2022.11.29.22282899", - "title": "Performance of antigen lateral flow devices in the United Kingdom during the Alpha, Delta, and Omicron waves of the SARS-CoV-2 pandemic", - "authors": "David W Eyre; Matthias Futschik; Sarah Tunkel; Jia Wei; Joanna Cole-Hamilton; Rida Saquib; Nick Germanacos; Andrew Dodgson; Paul E Klapper; Malur Sudhanva; Chris Kenny; Peter Marks; Edward Blandford; Susan Hopkins; Tim Peto; Tom Fowler", - "affiliations": "University of Oxford; UK Health Security Agency; UK Health Security Agency; University of Oxford; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; University of Manchester; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; University of Oxford; UK Health Security Agency", - "abstract": "BackgroundAntigen lateral flow devices (LFDs) have been widely used to control SARS-CoV-2. Changes in LFD sensitivity and detection of infectious individuals during the pandemic with successive variants, vaccination, and changes in LFD use are incompletely understood.\n\nMethodsPaired LFD and PCR tests were collected from asymptomatic and symptomatic participants, across multiple settings in the UK between 04-November-2020 and 21-March-2022. Multivariable logistic regression was used to analyse LFD sensitivity and specificity, adjusting for viral load, LFD manufacturer, setting, age, sex, assistance, symptoms, vaccination, and variant. National contact tracing data were used to estimate the proportion of transmitting index cases (with [≥]1 PCR/LFD-positive contact) potentially detectable by LFDs over time, accounting for viral load, variant, and symptom status.\n\nFindings4131/75,382 (5.5%) participants were PCR-positive. Sensitivity vs. PCR was 63.2% (95%CI 61.7-64.6%) and specificity 99.71% (99.66-99.74%). Increased viral load was independently associated with being LFD-positive. There was no evidence LFD sensitivity differed between Delta vs. Alpha/pre-Alpha infections, but Omicron infections were more likely to be LFD positive. Sensitivity was higher in symptomatic participants, 68.7% (66.9-70.4%) than in asymptomatic participants, 52.8% (50.1-55.4%). 79.4% (68.6-81.3%) of index cases resulting in probable onward transmission with were estimated to have been detectable using LFDs, this proportion was relatively stable over time/variants, but lower in asymptomatic vs. symptomatic cases.\n\nInterpretationLFDs remained able to detect most SARS-CoV-2 infections throughout vaccine roll-out and different variants. LFDs can potentially detect most infections that transmit to others and reduce risks. However, performance is lower in asymptomatic compared to symptomatic individuals.\n\nFundingUK Government.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSLateral flow devices (LFDs; i.e. rapid antigen detection devices) have been widely used for SARS-CoV-2 testing. However, due to their imperfect sensitivity when compared to PCR and a lack of a widely available gold standard proxy for infectiousness, the performance and use of LFDs has been a source of debate. We conducted a literature review in PubMed and bioRxiv/medRxiv for all studies examining the performance of lateral flow devices between 01 January 2020 and 31 October 2022. We used the search terms SARS-CoV-2/COVID-19 and antigen/lateral flow test/lateral flow device. Multiple studies have examined the sensitivity and specificity of LFDs, including several systematic reviews. However, the majority of the studies are based on pre-Alpha infections. Large studies examining the test accuracy for different variants, including Delta and Omicron, and following vaccination are limited.\n\nAdded value of this studyIn this large national LFD evaluation programme, we compared the performance of three different LFDs relative to PCR in various settings. Compared to PCR testing, sensitivity was 63.2% (95%CI 61.7-64.6%) overall, and 71.6% (95%CI 69.8-73.4%) in unselected communitybased testing. Specificity was 99.71% (99.66-99.74%). LFDs were more likely to be positive as viral loads increased. LFD sensitivity was similar during Alpha/pre-Alpha and Delta periods but increased during the Omicron period. There was no association between sensitivity and vaccination status. Sensitivity was higher in symptomatic participants, 68.7% (66.9-70.4%) than in asymptomatic participants, 52.8% (50.1-55.4%). Using national contact tracing data, we estimated that 79.4% (68.6-81.3%) of index cases resulting in probable onward transmission (i.e. with [≥]1 PCR/LFD-positive contact) were detectable using LFDs. Symptomatic index cases were more likely to be detected than asymptomatic index cases due to higher viral loads and better LFD performance at a given viral load. The proportion of index cases detected remained relatively stable over time and with successive variants, with a slight increase in the proportion of asymptomatic index cases detected during Omicron.\n\nImplications of all the available evidenceOur data show that LFDs detect most SARS-CoV-2 infections, with findings broadly similar to those summarised in previous meta-analyses. We show that LFD performance has been relatively consistent throughout different variant-dominant phases of the pandemic and following the roll-out of vaccination. LFDs can detect most infections that transmit to others and can therefore be used as part of a risk reduction strategy. However, performance is lower in asymptomatic compared to symptomatic individuals and this needs to be considered when designing testing programmes.", - "category": "infectious diseases", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.10.14.22281081", @@ -825,20 +797,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.06.17.22276433", - "date": "2022-06-17", - "link": "https://medrxiv.org/cgi/content/short/2022.06.17.22276433", - "title": "It hurts your heart: frontline healthcare worker experiences of moral injury during the COVID-19 pandemic", - "authors": "Siobhan Hegarty; Danielle Lamb; Sharon Stevelink; Rupa Bhundia; Rosalind Raine; Mary Jane Docherty; Hannah Rachel Scott; Anne Marie Rafferty; Victoria Williamson; Sarah Dorrington; Matthew hotopf; Reza Razavi; Neil Greenberg; Simon Wessely", - "affiliations": "King's College London; UCL; King's College London; King's College London; University College London; South London and Maudsley NHS Foundation Trust; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London", - "abstract": "BackgroundMoral injury is defined as the strong emotional and cognitive reactions following events which clash with someones moral code, values or expectations. During the COVID-19 pandemic, increased exposure to potentially morally injurious events (PMIEs) has placed healthcare workers (HCWs) at risk of moral injury. Yet little is known about the lived experience of cumulative PMIE exposure and how NHS staff respond to this.\n\nObjectiveWe sought to rectify this knowledge gap by qualitatively exploring the lived experiences and perspectives of clinical frontline NHS staff who responded to COVID-19.\n\nMethodsWe recruited a diverse sample of 30 clinical frontline HCWs from the NHS CHECK study cohort, for single time point qualitative interviews. All participants endorsed at least one item on the 9-item Moral Injury Events Scale (MIES) (Nash et al., 2013) at six month follow up. Interviews followed a semi-structured guide and were analysed using reflexive thematic analysis.\n\nResultsHCWs described being routinely exposed to ethical conflicts, created by exacerbations of pre-existing systemic issues including inadequate staffing and resourcing. We found that HCWs experienced a range of mental health symptoms primarily related to perceptions of institutional betrayal as well as feeling unable to fulfil their duty of care towards patients.\n\nConclusionThese results suggest that a multi-facetted organisational strategy is warranted to prepare for PMIE exposure, promote opportunities for resolution of symptoms associated with moral injury and prevent organisational disengagement.\n\nHighlightsO_LIClinical frontline healthcare workers (HCWs) have been exposed to an accumulation of potentially morally injurious events (PMIEs) throughout the COVID-19 pandemic, including feeling betrayed by both government and NHS leaders as well as feeling unable to provide duty of care to patients\nC_LIO_LIHCWs described the significant adverse impact of this exposure on their mental health, including increased anxiety and depression symptoms and sleep disturbance\nC_LIO_LIMost HCWs interviewed believed that organisational change within the NHS was necessary to prevent excess PMIE exposure and promote resolution of moral distress\nC_LI", - "category": "psychiatry and clinical psychology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.06.16.22276479", @@ -967,14 +925,14 @@ }, { "site": "medRxiv", - "doi": "10.1101/2022.04.28.22273177", - "date": "2022-04-29", - "link": "https://medrxiv.org/cgi/content/short/2022.04.28.22273177", - "title": "Occupational differences in SARS-CoV-2 infection: Analysis of the UK ONS Coronavirus (COVID-19) Infection Survey", - "authors": "Sarah Rhodes; Jack Wilkinson; Neil Pearce; Will Mueller; Mark Cherrie; Katie Stocking; Matthew Gittins; Srinivasa Vittal Katikireddi; Martie van Tongeren", - "affiliations": "University of Manchester; University of Manchester; London School of Hygiene and Tropical Medicine; Institute of Occupational Medicine; Institute of Occupational Medicine; University of Manchester; University of Manchester; University of Glasgow; University of Manchester", - "abstract": "BackgroundConsiderable concern remains about how occupational SARS-CoV-2 risk has evolved during the COVID-19 pandemic. We aimed to ascertain which occupations had the greatest risk of SARS-CoV-2 infection and explore how relative differences varied over the pandemic.\n\nMethodsAnalysis of cohort data from the UK Office of National Statistics Coronavirus (COVID-19) Infection Survey from April 2020 to November 2021. This survey is designed to be representative of the UK population and uses regular PCR testing. Cox and multilevel logistic regression to compare SARS-CoV-2 infection between occupational/sector groups, overall and by four time periods with interactions, adjusted for age, sex, ethnicity, deprivation, region, household size, urban/rural neighbourhood and current health conditions.\n\nResultsBased on 3,910,311 observations from 312,304 working age adults, elevated risks of infection can be seen overall for social care (HR 1.14; 95% CI 1.04 to 1.24), education (HR 1.31; 95% CI 1.23 to 1.39), bus and coach drivers (1.43; 95% CI 1.03 to 1.97) and police and protective services (HR 1.45; 95% CI 1.29 to 1.62) when compared to non-essential workers. By time period, relative differences were more pronounced early in the pandemic. For healthcare elevated odds in the early waves switched to a reduction in the later stages. Education saw raises after the initial lockdown and this has persisted. Adjustment for covariates made very little difference to effect estimates.\n\nConclusionsElevated risks among healthcare workers have diminished over time but education workers have had persistently higher risks. Long-term mitigation measures in certain workplaces may be warranted.\n\nWhat is already known on this topicSome occupational groups have observed increased rates of disease and mortality relating to COVID-19.\n\nWhat this study addsRelative differences between occupational groups have varied during different stages of the COVID-19 pandemic with risks for healthcare workers diminishing over time and workers in the education sector seeing persistent elevated risks.\n\nHow this study might affect research, practice or policyIncreased long term mitigation such as ventilation should be considered in sectors with a persistent elevated risk. It is important for workplace policy to be responsive to evolving pandemic risks.", - "category": "occupational and environmental health", + "doi": "10.1101/2022.05.06.22274658", + "date": "2022-05-07", + "link": "https://medrxiv.org/cgi/content/short/2022.05.06.22274658", + "title": "STIMULATE-ICP-CAREINEQUAL - Defining usual care and examining inequalities in Long Covid support: protocol for a mixed-methods study (part of STIMULATE-ICP: Symptoms, Trajectory, Inequalities and Management: Understanding Long-COVID to Address and Transform Existing Integrated Care Pathways).", + "authors": "Mel Ramasawmy; Yi Mu; Donna Clutterbuck; Marija Pantelic; Gregory Y.H. Lip; Christina Van der Feltz-Cornelis; Dan Wootton; Nefyn H Williams; Hugh Montgomery; Rita Mallinson Cookson; Emily Attree; Mark Gabbay; Melissa J Heightman; Nisreen A Alwan; Amitava Banerjee; Paula Lorgelly; - STIMULATE-ICP consortium", + "affiliations": "Institute of Health Informatics, University College London; Institute of Health Informatics, University College London; School of Primary Care, Population Sciences and Medical Education, University of Southampton; Brighton and Sussex Medical School, University of Sussex; Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool, United Kingdom; and Department of Clinical; Department of Health Sciences, HYMS, University of York, and Institute of Health Informatics, University College London; Institute of Infection Veterinary and Ecological Sciences, University of Liverpool; Department of Primary Care and Mental Health, University of Liverpool; Centre for Human Health and Performance, Department of Medicine, University College London; PPIE Representative; PPIE Representative; Department of Primary Care and Mental Health, University of Liverpool; University College London Hospitals NHS Trust; School of Primary Care, Population Sciences and Medical Education, University of Southampton; NIHR Southampton Biomedical Research Centre, University of Southam; Institute of Health Informatics, University College London; School of Population Health and Department of Economics, University of Auckland; ", + "abstract": "IntroductionIndividuals with Long Covid represent a new and growing patient population. In England, fewer than 90 Long Covid clinics deliver assessment and treatment informed by NICE guidelines. However, a paucity of clinical trials or longitudinal cohort studies means that the epidemiology, clinical trajectory, healthcare utilisation and effectiveness of current Long Covid care are poorly documented, and that neither evidence-based treatments nor rehabilitation strategies exist. In addition, and in part due to pre-pandemic health inequalities, access to referral and care varies, and patient experience of the Long Covid care pathways can be poor.\n\nIn a mixed methods study, we therefore aim to: (1) describe the usual healthcare, outcomes and resource utilisation of individuals with Long Covid; (2) assess the extent of inequalities in access to Long Covid care, and specifically to understand Long Covid patients experiences of stigma and discrimination.\n\nMethods and analysisA mixed methods study will address our aims. Qualitative data collection from patients and health professionals will be achieved through surveys, interviews and focus group discussions, to understand their experience and document the function of clinics. A patient cohort study will provide an understanding of outcomes and costs of care. Accessible data will be further analysed to understand the nature of Long Covid, and the care received.\n\nEthics and disseminationEthical approval was obtained from South Central - Berkshire Research Ethics Committee (reference 303958). The dissemination plan will be decided by the patient and public involvement and engagement (PPIE) group members and study Co-Is, but will target 1) policy makers, and those responsible for commissioning and delivering Long Covid services, 2) patients and the public, and 3) academics.", + "category": "health systems and quality improvement", "match_type": "exact", "author_similarity": 100, "affiliation_similarity": 100 @@ -1091,6 +1049,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2022.03.18.22272607", + "date": "2022-03-21", + "link": "https://medrxiv.org/cgi/content/short/2022.03.18.22272607", + "title": "Multi-organ impairment and Long COVID: a 1-year prospective, longitudinal cohort study", + "authors": "Andrea Dennis; Daniel J Cuthbertson; Dan Wootton; Michael Crooks; Mark Gabbay; Nicole Eichert; Sofia Mouchti; Michele Pansini; Adriana Roca-Fernandez; Helena Thomaides-Brears; Matt Kelly; Matthew Robson; Lyth Hishmeh; Emily Attree; Melissa J Heightman; Rajarshi Banerjee; Amitava Banerjee", + "affiliations": "Perspectum Ltd; University of Liverpool; University of Liverpool; University of Hull; University of Liverpool; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Diagnostics; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Long COVID SoS; UKDoctors#Longcovid; UCLH; Perspectum Ltd; University College London", + "abstract": "ImportanceMulti-organ impairment associated with Long COVID is a significant burden to individuals, populations and health systems, presenting challenges for diagnosis and care provision. Standardised assessment across multiple organs over time is lacking, particularly in non-hospitalised individuals.\n\nObjectiveTo determine the prevalence of organ impairment in Long COVID patients at 6 and at 12 months after initial symptoms and to explore links to clinical presentation.\n\nDesignThis was a prospective, longitudinal study in individuals following recovery from acute COVID-19. We assessed symptoms, health status, and multi-organ tissue characterisation and function, using consensus definitions for single and multi-organ impairment. Physiological and biochemical investigations were performed at baseline on all individuals and those with organ impairment were reassessed, including multi-organ MRI, 6 months later.\n\nSettingTwo non-acute settings (Oxford and London).\n\nParticipants536 individuals (mean 45 years, 73% female, 89% white, 32% healthcare workers, 13% acute COVID-19 hospitalisation) completed baseline assessment (median: 6 months post-COVID-19). 331 (62%) with organ impairment or incidental findings had follow up, with reduced symptom burden from baseline (median number of symptoms: 10 and 3, at 6 and 12 months).\n\nExposureSARS-CoV-2 infection 6 months prior to first assessment.\n\nMain outcomePrevalence of single and multi-organ impairment at 6 and 12 months post-COVID-19.\n\nResultsExtreme breathlessness (36% and 30%), cognitive dysfunction (50% and 38%) and poor health-related quality of life (EQ-5D-5L<0.7; 55% and 45%) were common at 6 and 12 months, and associated with female gender, younger age and single organ impairment. At baseline, there was fibro-inflammation in the heart (9%), pancreas (9%), kidney (15%) and liver (11%); increased volume in liver (7%), spleen (8%) and kidney (9%); decreased capacity in lungs (2%); and excessive fat deposition in the liver (25%) and pancreas (15%). Single and multi-organ impairment were present in 59% and 23% at baseline, persisting in 59% and 27% at follow-up.\n\nConclusion and RelevanceOrgan impairment was present in 59% of individuals at 6 months post-COVID-19, persisting in 59% of those followed up at 1 year, with implications for symptoms, quality of life and longer-term health, signalling need for prevention and integrated care of Long COVID.\n\nTrial RegistrationClinicalTrials.gov Identifier: NCT04369807\n\nKey pointsO_LIQuestion: What is the prevalence of organ impairment in Long COVID at 6- and 12-months post-COVID-19?\nC_LIO_LIFindings: In a prospective study of 536 mainly non-hospitalised individuals, symptom burden decreased, but single organ impairment persisted in 59% at 12 months post-COVID-19.\nC_LIO_LIMeaning: Organ impairment in Long COVID has implications for symptoms, quality of life and longer-term health, signalling need for prevention and integrated care of Long COVID.\nC_LI", + "category": "infectious diseases", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.03.17.22272414", @@ -1119,6 +1091,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "bioRxiv", + "doi": "10.1101/2022.03.08.481609", + "date": "2022-03-08", + "link": "https://biorxiv.org/cgi/content/short/2022.03.08.481609", + "title": "The origins and molecular evolution of SARS-CoV-2 lineage B.1.1.7 in the UK", + "authors": "Verity Hill; Louis du Plessis; Thomas P Alexander Peacock; Dinesh Aggarwal; Alessandro Carabelli; Rachel Colquhoun; Nicholas Ellaby; Eileen Gallagher; Natalie Groves; Ben Jackson; JT McCrone; Anna Price; Theo Sanderson; Emily Scher; Joel Alexander Southgate; Erik Volz; - The COVID-19 genomics UK (COG-UK) consortium; Wendy S Barclay; Jeffrey Barrett; Meera Chand; Thomas R Connor; Ian G. Goodfellow; Ravindra K Gupta; Ewan Harrison; Nicholas Loman; Richard Myers; David L Robertson; Oliver Pybus; Andrew Rambaut", + "affiliations": "The University of Edinburgh; University of Oxford; University College London (UCL); University of Cambridge; University of Cambridge; University of Edinburgh; UK Health Security Agency; Uk Health Security Agency; UK Health Security Agency; University of Edinburgh; University of Edinburgh; Cardiff University; Sanger Institute; University of Edinburgh; Cardiff University; Imperial College London; -; Imperial College London; Sanger Institute; UK Health Security Agency; Cardiff University; University of Cambridge; University of Cambridge; Sanger Institute; University of Birmingham; UK Health Security Agency; University of Glasgow; University of Oxford; University of Edinburgh", + "abstract": "The first SARS-CoV-2 variant of concern (VOC) to be designated was lineage B.1.1.7, later labelled by the World Health Organisation (WHO) as Alpha. Originating in early Autumn but discovered in December 2020, it spread rapidly and caused large waves of infections worldwide. The Alpha variant is notable for being defined by a long ancestral phylogenetic branch with an increased evolutionary rate, along which only two sequences have been sampled. Alpha genomes comprise a well-supported monophyletic clade within which the evolutionary rate is more typical of SARS-CoV-2. The Alpha epidemic continued to grow despite the continued restrictions on social mixing across the UK, and the imposition of new restrictions, in particular the English national lockdown in November 2020. While these interventions succeeded in reducing the absolute number of cases, the impact of these non-pharmaceutical interventions was predominantly to drive the decline of the SARS-CoV-2 lineages which preceded Alpha. We investigate the only two sampled sequences that fall on the branch ancestral to Alpha. We find that one is likely to be a true intermediate sequence, providing information about the order of mutational events that led to Alpha. We explore alternate hypotheses that can explain how Alpha acquired a large number of mutations yet remained largely unobserved in a region of high genomic surveillance: an under-sampled geographical location, a non-human animal population, or a chronically-infected individual. We conclude that the last hypothesis provides the best explanation of the observed behaviour and dynamics of the variant, although we find that the individual need not be immunocompromised, as persistently-infected immunocompetent hosts also display a higher within-host rate of evolution. Finally, we compare the ancestral branches and mutation profiles of other VOCs to each other, and identify that Delta appears to be an outlier both in terms of the genomic locations of its defining mutations, and its lack of rapid evolutionary rate on the ancestral branch. As new variants, such as Omicron, continue to evolve (potentially through similar mechanisms) it remains important to investigate the origins of other variants to identify ways to potentially disrupt their evolution and emergence.", + "category": "evolutionary biology", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.03.06.21267462", @@ -1245,6 +1231,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2022.01.21.22269651", + "date": "2022-01-22", + "link": "https://medrxiv.org/cgi/content/short/2022.01.21.22269651", + "title": "Prior health-related behaviours in children (2014-2020) and association with a positive SARS-CoV-2 test during adolescence (2020-2021): a retrospective cohort study using survey data linked with routine health data in Wales, UK", + "authors": "Emily Marchant; Emily Lowthian; Tom Crick; Lucy Griffiths; Richard Fry; Kevin Dadaczynski; Orkan Okan; Michaela James; Laura Cowley; Fatemeh Torabi; Jonathan Kennedy; Ashley Akbari; Ronan Lyons; Sinead Brophy", + "affiliations": "Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Fulda University of Applied Sciences; Technical University Munich; Swansea University; Public Health Wales; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University", + "abstract": "ObjectivesExamine if pre-COVID-19 pandemic (prior March 2020) health-related behaviours during primary school are associated with i) being tested for SARS-CoV-2 and ii) testing positive between 1 March 2020 to 31 August 2021.\n\nDesignRetrospective cohort study using an online cohort survey (January 2018 to February 2020) linked to routine PCR SARS-CoV-2 test results.\n\nSettingChildren attending primary schools in Wales (2018-2020), UK who were part of the HAPPEN school network.\n\nParticipantsComplete linked records of eligible participants were obtained for n=7,062 individuals. 39.1% (n=2,764) were tested (age 10.6{+/-}0.9, 48.9% girls) and 8.1% (n=569) tested positive for SARS-CoV-2 (age 10.6{+/-}1.0, 54.5% girls).\n\nMain outcome measuresLogistic regression of health-related behaviours and demographics were used to determine Odds Ratios (OR) of factors associated with i) being tested for SARS-CoV-2 and ii) testing positive for SARS-CoV-2.\n\nResultsConsuming sugary snacks (1-2 days/week OR=1.24, 95% CI 1.04 - 1.49; 5-6 days/week 1.31, 1.07 - 1.61; reference 0 days) can swim 25m (1.21, 1.06 - 1.39) and age (1.25, 1.16 - 1.35) were associated with an increased likelihood of being tested for SARS-CoV-2. Eating breakfast (1.52, 1.01 - 2.27), weekly physical activity [≥] 60 mins (1-2 days 1.69, 1.04 - 2.74; 3-4 days 1.76, 1.10 - 2.82, reference 0 days), out of school club participation (1.06, 1.02 - 1.10), can ride a bike (1.39, 1.00 - 1.93), age (1.16, 1.05 - 1.28) and girls (1.21, 1.00 - 1.46) were associated with an increased likelihood of testing positive for SARS-CoV-2. Living in least deprived quintiles 4 (0.64, 0.46 - 0.90) and 5 (0.64, 0.46 - 0.89) compared to the most deprived quintile was associated with a decreased likelihood.\n\nConclusionsAssociations may be related to parental health literacy and monitoring behaviours. Physically active behaviours may include co-participation with others, and exposure to SARS-CoV-2. A risk versus benefit approach must be considered given the importance of health-related behaviours for development.\n\nSTRENGTHS AND LIMITATIONSO_LIInvestigation of the association of pre-pandemic child health-related behaviour measures with subsequent SARS-CoV-2 testing and infection.\nC_LIO_LIReporting of multiple child health behaviours linked at an individual-level to routine records of SARS-CoV-2 testing data through the SAIL Databank.\nC_LIO_LIChild-reported health behaviours were measured before the COVID-19 pandemic (1 January 2018 to 28 February 2020) which may not reflect behaviours during COVID-19.\nC_LIO_LIHealth behaviours captured through the national-scale HAPPEN survey represent children attending schools that engaged with the HAPPEN Wales primary school network and may not be representative of the whole population of Wales.\nC_LIO_LIThe period of study for PCR-testing for and testing positive for SARS-CoV-2 includes a time frame with varying prevalence rates, approaches to testing children (targeted and mass testing) and restrictions which were not measured in this study.\nC_LI", + "category": "public and global health", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.01.18.22269082", @@ -1287,20 +1287,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.12.21.21268058", - "date": "2021-12-27", - "link": "https://medrxiv.org/cgi/content/short/2021.12.21.21268058", - "title": "Effectiveness of CoronaVac, ChAdOx1, BNT162b2 and Ad26.COV2.S among individuals with prior SARS-CoV-2 infection in Brazil", - "authors": "Thiago Cerqueira-Silva; Jason R Andrews; Viviane S Boaventura; Otavio T Ranzani; Vinicius de Araujo Oliveira; Enny S Paixao; Juracy Bertoldo Jr.; Tales Mota Machado; Matt D T Hitchings; Murilo Dorion; Margaret L Lind; Gerson O. Penna; Derek A.T. Cummings; Natalie E Dean; Guilherme Loureiro Werneck; Neil Pearce; Mauricio L Barreto; Albert I Ko; Julio Croda; Manoel Barral-Netto", - "affiliations": "Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA,USA; Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Universidade Federal da Bahia, Salvador, BA, Brazil; Barcelona Institute for Global Health, ISGlobal, Spain / Pulmonary Division, University of Sao Paulo; Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Healt; London School of Hygiene and Tropical Medicine, London, United Kingdom; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Health - Fiocruz, Salvador, BA, Brazil; Universidade Federal de Ouro Preto, Ouro Preto, MG, Brazil; Department of Biostatistics, College of Public Health & Health Professions, University of Florida, Gainesville, FL, USA; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Heaven, CT, USA; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Heaven, CT, USA; Nucleo de Medicina Tropical, Universidade de Brasilia, Brasilia, DF, Brazil; Escola Fiocruz de Governo, Fiocruz Brasilia. Brasilia, DF, Brazil; Department of Biology, University of Florida, Gainesville, FL, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA; Department of Biostatistics & Bioinformatics, Rollins School of Public Health, Emory University; Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil; London School of Hygiene and Tropical Medicine; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Health - Fiocruz, Salvador, BA, Brazil; Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Heaven, CT, USA; Universidade Federal de Mato Grosso do Sul, Campo Grande, MS, Brazil; Fiocruz Mato Grosso do Sul, Fundacao Oswaldo Cruz, Campo Grande, MS, Brazil; Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Healt", - "abstract": "BackgroundCOVID-19 vaccines have proven highly effective among SARS-CoV-2 naive individuals, but their effectiveness in preventing symptomatic infection and severe outcomes among individuals with prior infection is less clear.\n\nMethodsUtilizing national COVID-19 notification, hospitalization, and vaccination datasets from Brazil, we performed a case-control study using a test-negative design to assess the effectiveness of four vaccines (CoronaVac, ChAdOx1, Ad26.COV2.S and BNT162b2) among individuals with laboratory-confirmed prior SARS-CoV-2 infection. We matched RT-PCR positive, symptomatic COVID-19 cases with RT-PCR-negative controls presenting with symptomatic illnesses, restricting both groups to tests performed at least 90 days after an initial infection. We used multivariable conditional logistic regression to compare the odds of test positivity, and the odds of hospitalization or death due to COVID-19, according to vaccination status and time since first or second dose of vaccines.\n\nFindingsAmong individuals with prior SARS-CoV-2 infection, vaccine effectiveness against symptomatic infection [≥] 14 days from vaccine series completion was 39.4% (95% CI 36.1-42.6) for CoronaVac, 56.0% (95% CI 51.4-60.2) for ChAdOx1, 44.0% (95% CI 31.5-54.2) for Ad26.COV2.S, and 64.8% (95% CI 54.9-72.4) for BNT162b2. For the two-dose vaccine series (CoronaVac, ChAdOx1, and BNT162b2), effectiveness against symptomatic infection was significantly greater after the second dose compared with the first dose. Effectiveness against hospitalization or death [≥] 14 days from vaccine series completion was 81.3% (95% CI 75.3-85.8) for CoronaVac, 89.9% (95% CI 83.5-93.8) for ChAdOx1, 57.7% (95% CI -2.6-82.5) for Ad26.COV2.S, and 89.7% (95% CI 54.3-97.7) for BNT162b2.\n\nInterpretationAll four vaccines conferred additional protection against symptomatic infections and severe outcomes among individuals with previous SARS-CoV-2 infection. Provision of a full vaccine series to individuals following recovery from COVID-19 may reduce morbidity and mortality.\n\nFundingBrazilian National Research Council, Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro, Oswaldo Cruz Foundation, JBS S.A., Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, Generalitat de Catalunya.\n\nRESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed, medRxiv, and SSRN for articles published from January 1, 2020 until December 15, 2021, with no language restrictions, using the search terms \"vaccine effectiveness\" AND \"previous*\" AND (\"SARS-CoV-2\" OR \"COVID-19\"). We found several studies evaluating ChAdOx1 and BNT162b2, and one additionally reporting on mRNA-1273 and Ad26.COV2.S, which found that previously infected individuals who were vaccinated had lower risk of symptomatic SARS-CoV-2 infection. One study found that risk of hospitalization was lower for previously infected individuals after a full series of BNT162b2 or mRNA-1273. Limited evidence is available comparing effectiveness of one versus two doses among individuals with prior infection. No studies reported effectiveness of inactivated vaccines among previously infected individuals.\n\nAdded value of this studyWe used national databases of COVID-19 case surveillance, laboratory testing, and vaccination from Brazil to investigate effectiveness of CoronaVac, ChAdOx1, Ad26.COV2.S and BNT162b2 among individuals with a prior, laboratory-confirmed SARS-CoV-2 infection. We matched >22,000 RT-PCR-confirmed re-infections with >145,000 RT-PCR-negative controls using a test-negative design. All four vaccines were effective against symptomatic SARS-CoV-2 infections, with effectiveness from 14 days after series completion ranging from 39-65%. For vaccines with two-dose regimens, the second dose provided significantly increased effectiveness compared with one dose. Effectiveness against COVID-19-associated hospitalization or death from 14 days after series completion was >80% for CoronaVac, ChAdOx1and BNT162b2.\n\nImplications of all the available evidenceWe find evidence that four vaccines, using three different platforms, all provide protection to previously infected individuals against symptomatic SARS-CoV-2 infection and severe outcomes, with a second dose conferring significant additional benefits. These results support the provision of a full vaccine series among individuals with prior SARS-CoV-2 infection.", - "category": "infectious diseases", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.12.23.21268276", @@ -1413,20 +1399,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.12.16.21267906", - "date": "2021-12-16", - "link": "https://medrxiv.org/cgi/content/short/2021.12.16.21267906", - "title": "Workplace Contact Patterns in England during the COVID-19 Pandemic: Analysis of the Virus Watch prospective cohort study", - "authors": "Sarah Beale; Susan J Hoskins; Thomas Edward Byrne; Erica Wing Lam Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Annalan MD Navaratnam; Vincent Nguyen; Parth Patel; Alexei Yavlinsky; Anne M Johnson; Robert W Aldridge; Andrew Hayward", - "affiliations": "University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London", - "abstract": "BackgroundWorkplaces are an important potential source of SARS-CoV-2 exposure; however, investigation into workplace contact patterns is lacking. This study aimed to investigate how workplace attendance and features of contact varied between occupations and over time during the COVID-19 pandemic in England.\n\nMethodsData were obtained from electronic contact diaries submitted between November 2020 and November 2021 by employed/self-employed prospective cohort study participants (n=4,616). We used mixed models to investigate the main effects and potential interactions between occupation and time for: workplace attendance, number of people in shared workspace, time spent sharing workspace, number of close contacts, and usage of face coverings.\n\nFindingsWorkplace attendance and contact patterns varied across occupations and time. The predicted probability of intense space sharing during the day was highest for healthcare (78% [95% CI: 75-81%]) and education workers (64% [59%-69%]), who also had the highest probabilities for larger numbers of close contacts (36% [32%-40%] and 38% [33%-43%] respectively). Education workers also demonstrated relatively low predicted probability (51% [44%-57%]) of wearing a face covering during close contact. Across all occupational groups, levels of workspace sharing and close contact were higher and usage of face coverings at work lower in later phases of the pandemic compared to earlier phases.\n\nInterpretationMajor variations in patterns of workplace contact and mask use are likely to contribute to differential COVID-19 risk. Across occupations, increasing workplace contact and reduced usage of face coverings presents an area of concern given ongoing high levels of community transmission and emergence of variants.", - "category": "epidemiology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.12.13.21267471", @@ -1483,6 +1455,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.11.29.21266847", + "date": "2021-11-30", + "link": "https://medrxiv.org/cgi/content/short/2021.11.29.21266847", + "title": "Population level impact of a pulse oximetry remote monitoring programme on mortality and healthcare utilisation in the people with covid-19 in England: a national analysis using a stepped wedge design", + "authors": "Thomas Beaney; Jonathan Clarke; Ahmed Alboksmaty; Kelsey Flott; Aidan Fowler; Jonathan R Benger; Paul Aylin; Sarah Elkin; Ana Luisa Neves; Ara Darzi", + "affiliations": "Imperial College London; Imperial College London; Imperial College London; Imperial College London; NHS England and Improvement; NHS Digital; Imperial College London; Imperial College London; Imperial College London; Imperial College London", + "abstract": "ObjectivesTo identify the population level impact of a national pulse oximetry remote monitoring programme for covid-19 (COVID Oximetry @home; CO@h) in England on mortality and health service use.\n\nDesignRetrospective cohort study using a stepped wedge pre- and post-implementation design.\n\nSettingAll Clinical Commissioning Groups (CCGs) in England implementing a local CO@h programme.\n\nParticipants217,650 people with a positive covid-19 polymerase chain reaction test result and symptomatic, from 1st October 2020 to 3rd May 2021, aged [≥]65 years or identified as clinically extremely vulnerable. Care home residents were excluded.\n\nInterventionsA pre-intervention period before implementation of the CO@h programme in each CCG was compared to a post-intervention period after implementation.\n\nMain outcome measuresFive outcome measures within 28 days of a positive covid-19 test: i) death from any cause; ii) any A&E attendance; iii) any emergency hospital admission; iv) critical care admission; and v) total length of hospital stay.\n\nResultsImplementation of the programme was not associated with mortality or length of hospital stay. Implementation was associated with increased health service utilisation with a 12% increase in the odds of A&E attendance (95% CI: 6%-18%) and emergency hospital admission (95% CI: 5%-20%) and a 24% increase in the odds of critical care admission in those admitted (95% CI: 5%-47%). In a secondary analysis of CO@h sites with at least 10% or 20% of eligible people enrolled, there was no significant association with any outcome measure. However, uptake of the programme was low, with enrolment data received for only 5,527 (2.5%) of the eligible population.\n\nConclusionsAt a population level, there was no association with mortality following implementation of the CO@h programme, and small increases in health service utilisation were observed. Low enrolment of eligible people may have diluted the effects of the programme at a population level.", + "category": "health systems and quality improvement", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.11.29.21266996", @@ -1511,6 +1497,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "bioRxiv", + "doi": "10.1101/2021.11.24.469860", + "date": "2021-11-26", + "link": "https://biorxiv.org/cgi/content/short/2021.11.24.469860", + "title": "Nanopore ReCappable Sequencing maps SARS-CoV-2 5' capping sites and provides new insights into the structure of sgRNAs", + "authors": "Camilla Ugolini; Logan Mulroney; Adrien Leger; Matteo Castelli; Elena Criscuolo; Maia Kavanagh Williamson; Andrew D Davidson; Abdulaziz Almuqrin; Roberto Giambruno; Miten Jain; Gianmaria Frig\u00e8; Hugh Olsen; George Tzertzinis; Ira Schildkraut; Madalee F Wulf; Ivan R. Corr\u00eaa Jr.; Laurence Ettwiller; Nicola Clementi; Massimo Clementi; Nicasio Mancini; Ewan Birney; Mark Akeson; Francesco Nicassio; David A Matthews; Tommaso Leonardi", + "affiliations": "Italian Institute of Technology; Italian Institute of Technology; Oxford Nanopore Technologies; Vita-Salute San Raffaele University; Vita-Salute San Raffaele University; University of Bristol; University of Bristol; University of Bristol; Istituto Italiano di Tecnologia; University of California Santa Cruz; Istituto Europeo di Oncologia; University of California Santa Cruz; New England Biolabs; New England Biolabs; New England Biolabs; New England Biolabs; New England Biolabs Inc; Vita-Salute San Raffaele University; Vita-Salute San Raffaele University; Universit\u00e0 Vita-Salute San Raffaele; European Bioinformatics Institute; University of California Santa Cruz; Istituto Italiano di Tecnologia; University of Bristol; Italian Institute of Technology", + "abstract": "The SARS-CoV-2 virus has a complex transcriptome characterised by multiple, nested sub genomic RNAs used to express structural and accessory proteins. Long-read sequencing technologies such as nanopore direct RNA sequencing can recover full-length transcripts, greatly simplifying the assembly of structurally complex RNAs. However, these techniques do not detect the 5' cap, thus preventing reliable identification and quantification of full-length, coding transcript models. Here we used Nanopore ReCappable Sequencing (NRCeq), a new technique that can identify capped full-length RNAs, to assemble a complete annotation of SARS-CoV-2 sgRNAs and annotate the location of capping sites across the viral genome. We obtained robust estimates of sgRNA expression across cell lines and viral isolates and identified novel canonical and non-canonical sgRNAs, including one that uses a previously un-annotated leader-to-body junction site. The data generated in this work constitute a useful resource for the scientific community and provide important insights into the mechanisms that regulate the transcription of SARS-CoV-2 sgRNAs.", + "category": "genomics", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.11.22.21266512", @@ -1721,20 +1721,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.09.27.21264166", - "date": "2021-09-29", - "link": "https://medrxiv.org/cgi/content/short/2021.09.27.21264166", - "title": "Prevalence and duration of detectable SARS-CoV-2 nucleocapsid antibody in staff and residents of long-term care facilities over the first year of the pandemic (VIVALDI study): prospective cohort study", - "authors": "Maria Krutikov; Tom Palmer; Gokhan Tut; Christopher Fuller; Borscha Azmi; Rebecca Giddings; Madhumita Shrotri; Nayandeep Kaur; Panagiota Sylla; Tara Lancaster; Aidan Irwin-Singer; Andrew Hayward; Paul Moss; Andrew Copas; Laura Shallcross", - "affiliations": "University College London; University College London; University of Birmingham, Medical School; University College London; University College London; University College London; University College London; University of Birmingham; University of Birmingham; University of Birmingham; Department of Health & Social Care; UCL; University of Birmingham; University College London; UCL", - "abstract": "BackgroundLong Term Care Facilities (LTCF) have reported high SARS-CoV-2 infection rates and related mortality, but the proportion infected amongst survivors and duration of the antibody response to natural infection is unknown. We determined the prevalence and stability of nucleocapsid antibodies - the standard assay for detection of prior infection - in staff and residents from 201 LTCFs.\n\nMethodsProspective cohort study of residents aged >65 years and staff of LTCFs in England (11 June 2020-7 May 2021). Serial blood samples were tested for IgG antibodies against SARS-CoV-2 nucleocapsid protein. Prevalence and cumulative incidence of antibody-positivity were weighted to the LTCF population. Cumulative incidence of sero-reversion was estimated from Kaplan-Meier curves.\n\nResults9488 samples were included, 8636 (91%) of which could be individually-linked to 1434 residents or 3288 staff members. The cumulative incidence of nucleocapsid seropositivity was 35% (95% CI: 30-40%) in residents and 26% (95% CI: 23-30%) in staff over 11 months. The incidence rate of loss of antibodies (sero-reversion) was 2{middle dot}1 per 1000 person-days at risk, and median time to reversion was around 8 months.\n\nInterpretationAt least one-quarter of staff and one-third of surviving residents were infected during the first two pandemic waves. Nucleocapsid-specific antibodies often become undetectable within the first year following infection which is likely to lead to marked underestimation of the true proportion of those with prior infection. Since natural infection may act to boost vaccine responses, better assays to identify natural infection should be developed.\n\nFundingUK Government Department of Health and Social Care.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSA search was conducted of Ovid MEDLINE and MedRxiv on 21 July 2021 to identify studies conducted in long term care facilities (LTCF) that described seroprevalence using the terms \"COVID-19\" or \"SARS-CoV-2\" and \"nursing home\" or \"care home\" or \"residential\" or \"long term care facility\" and \"antibody\" or \"serology\" without date or language restrictions. One meta-analysis was identified, published before the introduction of vaccination, that included 2 studies with a sample size of 291 which estimated seroprevalence as 59% in LTCF residents. There were 28 seroprevalence surveys of naturally-acquired SARS-CoV-2 antibodies in LTCFs; 16 were conducted in response to outbreaks and 12 conducted in care homes without known outbreaks. 16 studies included more than 1 LTCF and all were conducted in Autumn 2020 after the first wave of infection but prior to subsequent peaks. Seroprevalence studies conducted following a LTCF outbreak were biased towards positivity as the included population was known to have been previously infected. In the 12 studies that were conducted outside of known outbreaks, seroprevalence varied significantly according to local prevalence of infection. The largest of these was a cross-sectional study conducted in 9,000 residents and 10,000 staff from 362 LTCFs in Madrid, which estimated seroprevalence in staff as 31{middle dot}5% and 55{middle dot}4% in residents. However, as this study was performed in one city, it may not be generalisable to the whole of Spain and sequential sampling was not performed. Of the 28 studies, 9 undertook longitudinal sampling for a maximum of four months although three of these reported from the same cohort of LTCFs in London. None of the studies reported on antibody waning amongst the whole resident population.\n\nAdded value of this studyWe estimated the proportion of care home staff and residents with evidence of SARS-CoV-2 natural infection using data from over 3,000 staff and 1,500 residents in 201 geographically dispersed LTCFs in England. Population selection was independent of outbreak history and the sample is therefore more reflective of the population who reside and work in LTCFs. Our estimates of the proportion of residents with prior natural infection are substantially higher than estimates based on population-wide PCR testing, due to limited testing coverage at the start of the pandemic. 1361 individuals had at least one positive antibody test and participants were followed for up to 11 months, which allowed modelling of the time to loss of antibody in over 600 individuals in whom the date of primary infection could be reliably estimated. This is the longest reported serological follow up in a population of LTCF residents, a group who are known to be most at risk of severe outcomes following infection with SARS-CoV-2 and provides important evidence on the duration that nucleocapsid antibodies remained detectable over the first and second waves of the pandemic.\n\nImplications of all available researchA substantial proportion of the LTCF population will have some level of natural immunity to infection as a result of past infection. Immunological studies have highlighted greater antibody responses to vaccination in seropositive individuals, so vaccine efficacy in this population may be affected by this large pool of individuals who have survived past infection. In addition, although the presence of nucleocapsid-specific antibodies is generally considered as the standard marker for prior infection, we find that antibody waning is such that up to 50% of people will lose detectable antibody responses within eight months. Individual prior natural infection history is critical to assess the impact of factors such as vaccine response or protection against re-infection. These findings may have implications for duration of immunity following natural infection and indicate that alternative assays for prior infection should be developed.", - "category": "epidemiology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.09.20.21263828", @@ -1763,6 +1749,34 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.09.09.21263026", + "date": "2021-09-13", + "link": "https://medrxiv.org/cgi/content/short/2021.09.09.21263026", + "title": "The clinically extremely vulnerable to COVID: Identification and changes in health care while self-isolating (shielding) during the coronavirus pandemic", + "authors": "Jessica Erin Butler; Mintu Nath; Dimitra Blana; William P Ball; Nicola Beech; Corri Black; Graham Osler; Sebastien Peytrignet; Katie Wilde; Artur Wozniak; Simon Sawhney", + "affiliations": "University of Aberdeen; University of Aberdeen; University of Aberdeen; University of Aberdeen; NHS Grampian; NHS Grampian and University of Aberdeen; NHS Grampian; Health Foundation; University of Aberdeen; University of Aberdeen; NHS Grampian and University of Aberdeen", + "abstract": "BackgroundIn March 2020, the government of Scotland identified people deemed clinically extremely vulnerable to COVID due to their pre-existing health conditions. These people were advised to strictly self-isolate (shield) at the start of the pandemic, except for necessary healthcare. We examined who was identified as clinically extremely vulnerable, how their healthcare changed during isolation, and whether this process exacerbated healthcare inequalities.\n\nMethodsWe linked those on the shielding register in NHS Grampian, a health authority in Scotland, to healthcare records from 2015-2020. We described the source of identification, demographics, and clinical history of the cohort. We measured changes in out-patient, in-patient, and emergency healthcare during isolation in the shielding population and compared to the general non-shielding population.\n\nResultsThe register included 16,092 people (3% of the population), clinically vulnerable primarily due to a respiratory disease, immunosuppression, or cancer. Among them, 42% were not identified by national healthcare record screening but added ad hoc, with these additions including more children and fewer economically-deprived.\n\nDuring isolation, all forms of healthcare use decreased (25%-46%), with larger decreases in scheduled care than in emergency care. However, people shielding had better maintained scheduled care compared to the non-shielding general population: out-patient visits decreased 35% vs 49%; in-patient visits decreased 46% vs 81%. Notably, there was substantial variation in whose scheduled care was maintained during isolation: younger people and those with cancer had significantly higher visit rates, but there was no difference between sexes or socioeconomic levels.\n\nConclusionsHealthcare changed dramatically for the clinically extremely vulnerable population during the pandemic. The increased reliance on emergency care while isolating indicates that continuity of care for existing conditions was not optimal. However, compared to the general population, there was success in maintaining scheduled care, particularly in young people and those with cancer. We suggest that integrating demographic and primary care data would improve identification of the clinically vulnerable and could aid prioritising their care.", + "category": "epidemiology", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, + { + "site": "medRxiv", + "doi": "10.1101/2021.09.02.21262979", + "date": "2021-09-10", + "link": "https://medrxiv.org/cgi/content/short/2021.09.02.21262979", + "title": "Exponential growth, high prevalence of SARS-CoV-2 and vaccine effectiveness associated with Delta variant in England during May to July 2021", + "authors": "Paul Elliott; David J Haw; Haowei Wang; Oliver Eales; Caroline E Walters; Kylie E. C. Ainslie; Christina J Atchison; Claudio Fronterre; Peter Diggle; Andrew J Page; Alex Trotter; Sophie J Prosolek; - The COVID-19 Genomics UK (COG-UK) consortium; Deborah Ashby; Christl Donnelly; Wendy Barclay; Graham P Taylor; Graham Cooke; Helen Ward; Ara Darzi; Steven Riley", + "affiliations": "Imperial College London School of Public Health; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Lancaster University; Lancaster University; Quadram Institute; Quadram Institute Bioscience; Quadram Institute; The COVID-19 Genomics UK (COG-UK) consortium; Imperial College London; University of Oxford; Imperial College London; Imperial College London; Imperial College; Imperial College London; Imperial College London; Dept Inf Dis Epi, Imperial College", + "abstract": "BackgroundThe prevalence of SARS-CoV-2 infection continues to drive rates of illness and hospitalisations despite high levels of vaccination, with the proportion of cases caused by the Delta lineage increasing in many populations. As vaccination programs roll out globally and social distancing is relaxed, future SARS-CoV-2 trends are uncertain.\n\nMethodsWe analysed prevalence trends and their drivers using reverse transcription-polymerase chain reaction (RT-PCR) swab-positivity data from round 12 (between 20 May and 7 June 2021) and round 13 (between 24 June and 12 July 2021) of the REal-time Assessment of Community Transmission-1 (REACT-1) study, with swabs sent to non-overlapping random samples of the population ages 5 years and over in England.\n\nResultsWe observed sustained exponential growth with an average doubling time in round 13 of 25 days (lower Credible Interval of 15 days) and an increase in average prevalence from 0.15% (0.12%, 0.18%) in round 12 to 0.63% (0.57%, 0.18%) in round 13. The rapid growth across and within rounds appears to have been driven by complete replacement of Alpha variant by Delta, and by the high prevalence in younger less-vaccinated age groups, with a nine-fold increase between rounds 12 and 13 among those aged 13 to 17 years. Prevalence among those who reported being unvaccinated was three-fold higher than those who reported being fully vaccinated. However, in round 13, 44% of infections occurred in fully vaccinated individuals, reflecting imperfect vaccine effectiveness against infection despite high overall levels of vaccination. Using self-reported vaccination status, we estimated adjusted vaccine effectiveness against infection in round 13 of 49% (22%, 67%) among participants aged 18 to 64 years, which rose to 58% (33%, 73%) when considering only strong positives (Cycle threshold [Ct] values < 27); also, we estimated adjusted vaccine effectiveness against symptomatic infection of 59% (23%, 78%), with any one of three common COVID-19 symptoms reported in the month prior to swabbing. Sex (round 13 only), ethnicity, household size and local levels of deprivation jointly contributed to the risk of higher prevalence of swab-positivity.\n\nDiscussionFrom end May to beginning July 2021 in England, where there has been a highly successful vaccination campaign with high vaccine uptake, infections were increasing exponentially driven by the Delta variant and high infection prevalence among younger, unvaccinated individuals despite double vaccination continuing to effectively reduce transmission. Although slower growth or declining prevalence may be observed during the summer in the northern hemisphere, increased mixing during the autumn in the presence of the Delta variant may lead to renewed growth, even at high levels of vaccination.", + "category": "epidemiology", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.09.02.21263017", @@ -1791,20 +1805,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.08.19.21262231", - "date": "2021-08-24", - "link": "https://medrxiv.org/cgi/content/short/2021.08.19.21262231", - "title": "Symptoms and SARS-CoV-2 positivity in the general population in the UK", - "authors": "Karina-Doris Vihta; Koen B. Pouwels; Tim Peto; Emma Pritchard; David W. Eyre; Thomas House; Owen Gethings; Ruth Studley; Emma Rourke; Duncan Cook; Ian Diamond; Derrick Crook; Philippa C. Matthews; Nicole Stoesser; Ann Sarah Walker; - COVID-19 Infection Survey team", - "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Manchester; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; University of Oxford; University of Oxford; University of Oxford; ", - "abstract": "BackgroundSeveral community-based studies have assessed the ability of different symptoms to identify COVID-19 infections, but few have compared symptoms over time (reflecting SARS-CoV-2 variants) and by vaccination status.\n\nMethodsUsing data and samples collected by the COVID-19 Infection Survey at regular visits to representative households across the UK, we compared symptoms in new PCR-positives and comparator test-negative controls.\n\nResultsFrom 26/4/2020-7/8/2021, 27,869 SARS-CoV-2 PCR-positive episodes occurred in 27,692 participants (median 42 years (IQR 22-58)); 13,427 (48%) self-reported symptoms (\"symptomatic positive episodes\"). The comparator group comprised 3,806,692 test-negative visits (457,215 participants); 130,612 (3%) self-reported symptoms (\"symptomatic negative visit\"). Reporting of any symptoms in positive episodes varied over calendar time, reflecting changes in prevalence of variants, incidental changes (e.g. seasonal pathogens, schools re-opening) and vaccination roll-out. There was a small increase in sore throat reporting in symptomatic positive episodes and negative visits from April-2021. After May-2021 when Delta emerged there were substantial increases in headache and fever in positives, but not in negatives. Although specific symptom reporting in symptomatic positive episodes vs. negative visits varied by age, sex, and ethnicity, only small improvements in symptom-based infection detection were obtained; e.g. adding fatigue/weakness or all eight symptoms to the classic four symptoms (cough, fever, loss of taste/smell) increased sensitivity from 74% to 81% to 90% but tests per positive from 4.6 to 5.3 to 8.7.\n\nConclusionsWhilst SARS-CoV-2-associated symptoms vary by variant, vaccination status and demographics, differences are modest and do not warrant large-scale changes to targeted testing approaches given resource implications.\n\nSummaryWithin the COVID-19 Infection Survey, recruiting representative households across the UK general population, SARS-CoV-2-associated symptoms varied by viral variant, vaccination status and demographics. However, differences are modest and do not currently warrant large-scale changes to targeted testing approaches.", - "category": "infectious diseases", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.08.18.21262222", @@ -1847,20 +1847,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.08.13.21261889", - "date": "2021-08-18", - "link": "https://medrxiv.org/cgi/content/short/2021.08.13.21261889", - "title": "Robust SARS-CoV-2-specific and heterologous immune responses after natural infection in elderly residents of Long-Term Care Facilities", - "authors": "Gokhan Tut; Tara Lancaster; Megan S Butler; Panagiota Sylla; Eliska Spalkova; David Bone; Nayandeep Kaur; Christopher Bentley; Umayr Amin; Azar T Jadir; Samuel Hulme; Morenike Ayodele; Alexander C Dowell; Hayden Pearce; Sandra Margielewska-Davies; Kriti Verma; Samantha Nicol; Jusnara Begum; Elizabeth Jinks; Elif Tut; Rachel Bruton; Maria Krutikov; Madhumita Shrotri; Rebecca Giddings; Borscha Azmi; Chris Fuller; Aidan Irwin-Singer; Andrew Hayward; Andrew Copas; Laura Shallcross; Paul Moss", - "affiliations": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; Department of Health and Social Care, London, UK; Health Data Research UK; UCL Institute for Global Health, London, UK; UCL Institute of Health Informatics, London, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK", - "abstract": "Long term care facilities (LTCF) provide residential and/or nursing care support for frail and elderly people and many have suffered from a high prevalence of SARS-CoV-2 infection. Although mortality rates have been high in LTCF residents there is little information regarding the features of SARS-CoV-2-specific immunity after infection in this setting or how this may influence immunity to other infections. We studied humoral and cellular immunity against SARS-CoV-2 in 152 LTCF staff and 124 residents over a prospective 4-month period shortly after the first wave of infection and related viral serostatus to heterologous immunity to other respiratory viruses and systemic inflammatory markers. LTCF residents developed high levels of antibodies against spike protein and RBD domain which were stable over 4 months of follow up. Nucleocapsid-specific responses were also elevated in elderly donors but showed waning across all populations. Antibodies showed stable and equivalent levels of functional inhibition against spike-ACE2 binding in all age groups with comparable activity against viral variants of concern. SARS-CoV-2 seropositive donors showed high levels of antibodies to other beta-coronaviruses but serostatus did not impact humoral immunity to influenza or RSV. SARS-CoV-2-specific cellular responses were equivalent across the life course but virus-specific populations showed elevated levels of activation in older donors. LTCF residents who are survivors of SARS-CoV-2 infection thus show robust and stable immunity which does not impact responses to other seasonal viruses. These findings augur well for relative protection of LTCF residents to re-infection. Furthermore, they underlie the potent influence of previous infection on the immune response to Covid-19 vaccine which may prove to be an important determinant of future vaccine strategy.\n\nOne sentence summeryCare home residents show waning of nucleocapsid specific antibodies and enhanced expression of activation markers on SARS-CoV-2 specific cells", - "category": "infectious diseases", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.08.13.21261959", @@ -2043,6 +2029,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.07.02.21259897", + "date": "2021-07-05", + "link": "https://medrxiv.org/cgi/content/short/2021.07.02.21259897", + "title": "Anti-spike antibody response to natural SARS-CoV-2 infection in the general population", + "authors": "Jia Wei; Philippa C Matthews; Nicole Stoesser; Thomas Maddox; Luke Lorenzi; Ruth Studley; John I Bell; John N Newton; Jeremy Farrar; Ian Diamond; Emma Rourke; Alison Howarth; Brian D Marsden; Sarah Hoosdally; E Yvonne Jones; David I Stuart; Derrick W Crook; Tim E.A. Peto; Koen B. Pouwels; A. Sarah Walker; David W Eyre", + "affiliations": "University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; Office for National Statistics; Office for National Statistics; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; NIHR Oxford Biomedical Research Centre; University of Oxford; University of Oxford; University of Oxford; University of Oxford", + "abstract": "We estimated the duration and determinants of antibody response after SARS-CoV-2 infection in the general population using representative data from 7,256 United Kingdom COVID-19 infection survey participants who had positive swab SARS-CoV-2 PCR tests from 26-April-2020 to 14-June-2021. A latent class model classified 24% of participants as non-responders not developing anti-spike antibodies. These seronegative non-responders were older, had higher SARS-CoV-2 cycle threshold values during infection (i.e. lower viral burden), and less frequently reported any symptoms. Among those who seroconverted, using Bayesian linear mixed models, the estimated anti-spike IgG peak level was 7.3-fold higher than the level previously associated with 50% protection against reinfection, with higher peak levels in older participants and those of non-white ethnicity. The estimated anti-spike IgG half-life was 184 days, being longer in females and those of white ethnicity. We estimated antibody levels associated with protection against reinfection likely last 1.5-2 years on average, with levels associated with protection from severe infection present for several years. These estimates could inform planning for vaccination booster strategies.", + "category": "infectious diseases", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.06.28.21259529", @@ -3037,20 +3037,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.11.23.20237313", - "date": "2020-11-24", - "link": "https://medrxiv.org/cgi/content/short/2020.11.23.20237313", - "title": "Identifying optimal combinations of symptoms to trigger diagnostic work-up of suspected COVID-19 cases in vaccine trials: analysis from a community-based, prospective, observational cohort", - "authors": "Michela Antonelli; Joan Capdevila; Amol Chaudhari; Julia Granerod; Liane S Canas; Mark S Graham; Kerstin Klaser; Marc Modat; Erika Molteni; Ben Murray; Carole H Sudre; Richard Davies; Anna May; Long H Nguyen; David A Drew; Amit Joshi; Andrew T Chan; Jakob Cramer; Tim Spector; Jonathan Wolf; Sebastien Ourselin; Claire J Steves; Alfred E Loeliger", - "affiliations": "King's College London; Zoe Global; Coalition for Epidemic Preparedness Innovations; Coalition for Epidemic Preparedness Innovations; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; University College London; Zoe Global; Zoe Global; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Coalition for Epidemic Preparedness Innovations; King's College London; Zoe Global; King's College London; King's College London; Coalition for Epidemic Preparedness Innovations", - "abstract": "ObjectivesDiagnostic work-up following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify optimal symptom combinations to capture most cases using fewer tests with implications for COVID-19 vaccine developers across different resource settings and public health.\n\nMethodsUK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms and an RT-PCR test within seven days of symptom onset were included. Sensitivity, specificity, and number of RT-PCR tests needed to identify one case (test per case [TPC]) were calculated for different symptom combinations. A multi-objective evolutionary algorithm was applied to generate combinations with optimal trade-offs between sensitivity and specificity.\n\nFindingsUK and US cohorts included 122,305 (1,202 positives) and 3,162 (79 positive) individuals. Within three days of symptom onset, the COVID-19 specific symptom combination (cough, dyspnoea, fever, anosmia/ageusia) identified 69% of cases requiring 47 TPC. The combination with highest sensitivity (fatigue, anosmia/ageusia, cough, diarrhoea, headache, sore throat) identified 96% cases requiring 96 TPC.\n\nInterpretationWe confirmed the significance of COVID-19 specific symptoms for triggering RT-PCR and identified additional symptom combinations with optimal trade-offs between sensitivity and specificity that maximize case capture given different resource settings.\n\nHighlightsO_LIWidely recommended symptoms identified only [~]70% COVID-19 cases\nC_LIO_LIAdditional symptoms increased case finding to > 90% but tests needed doubled\nC_LIO_LIOptimal symptom combinations maximise case capture considering available resources\nC_LIO_LIImplications for COVID-19 vaccine efficacy trials and wider public health\nC_LI", - "category": "health informatics", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.11.19.20234120", @@ -3107,20 +3093,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.11.02.20224824", - "date": "2020-11-04", - "link": "https://medrxiv.org/cgi/content/short/2020.11.02.20224824", - "title": "The duration, dynamics and determinants of SARS-CoV-2 antibody responses in individual healthcare workers", - "authors": "Sheila F Lumley; Jia Wei; Nicole Stoesser; Philippa Matthews; Alison Howarth; Stephanie Hatch; Brian Marsden; Stuart Cox; Tim James; Liam Peck; Thomas Ritter; Zoe de Toledo; Richard Cornall; E Yvonne Jones; David I Stuart; Gavin Screaton; Daniel Ebner; Sarah Hoosdally; Derrick Crook; - Oxford University Hospitals Staff Testing Group; Christopher P Conlon; Koen Pouwels; Ann Sarah Walker; Tim EA Peto; Timothy M Walker; Katie Jeffery; David W Eyre", - "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; Oxford University Hospitals; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; ; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; University of Oxford", - "abstract": "BackgroundSARS-CoV-2 IgG antibody measurements can be used to estimate the proportion of a population exposed or infected and may be informative about the risk of future infection. Previous estimates of the duration of antibody responses vary.\n\nMethodsWe present 6 months of data from a longitudinal seroprevalence study of 3217 UK healthcare workers (HCWs). Serial measurements of IgG antibodies to SARS-CoV-2 nucleocapsid were obtained. Bayesian mixed linear models were used to investigate antibody waning and associations with age, gender, ethnicity, previous symptoms and PCR results.\n\nResultsIn this cohort of working age HCWs, antibody levels rose to a peak at 24 (95% credibility interval, CrI 19-31) days post-first positive PCR test, before beginning to fall. Considering 452 IgG seropositive HCWs over a median of 121 days (maximum 171 days) from their maximum positive IgG titre, the mean estimated antibody half-life was 85 (95%CrI, 81-90) days. The estimated mean time to loss of a positive antibody result was 137 (95%CrI 127-148) days. We observed variation between individuals; higher maximum observed IgG titres were associated with longer estimated antibody half-lives. Increasing age, Asian ethnicity and prior self-reported symptoms were independently associated with higher maximum antibody levels, and increasing age and a positive PCR test undertaken for symptoms with longer antibody half-lives.\n\nConclusionIgG antibody levels to SARS-CoV-2 nucleocapsid wane within months, and faster in younger adults and those without symptoms. Ongoing longitudinal studies are required to track the long-term duration of antibody levels and their association with immunity to SARS-CoV-2 reinfection.\n\nSummarySerially measured SARS-CoV-2 anti-nucleocapsid IgG titres from 452 seropositive healthcare workers demonstrate levels fall by half in 85 days. From a peak result, detectable antibodies last a mean 137 days. Levels fall faster in younger adults and following asymptomatic infection.", - "category": "infectious diseases", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.10.29.20222414", @@ -3219,20 +3191,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.10.26.20219550", - "date": "2020-10-27", - "link": "https://medrxiv.org/cgi/content/short/2020.10.26.20219550", - "title": "Human movement can inform the spatial scale of interventions against COVID-19 transmission", - "authors": "Hamish Gibbs; Emily Nightingale; Yang Liu; James Cheshire; Leon Danon; Liam Smeeth; Carl AB Pearson; Chris Grundy; - LSHTM CMMID COVID-19 Working Group; Adam J Kucharski; Rosalind M Eggo", - "affiliations": "London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University College London; University of Exeter; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; ; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine", - "abstract": "BackgroundIn 2020, the UK enacted an intensive, nationwide lockdown on March 23 to mitigate transmission of COVID-19. As restrictions began to ease, resurgences in transmission were targeted by geographically-limited interventions of various stringencies. Understanding the spatial scale of networks of human interaction, and how these networks change over time, is critical to inform interventions targeted at the most at-risk areas without unnecessarily restricting areas at low risk of resurgence.\n\nMethodsWe use detailed human mobility data aggregated from Facebook users to determine how the spatially-explicit network of movements changed before and during the lockdown period, in response to the easing of restrictions, and to the introduction of locally-targeted interventions. We also apply community detection techniques to the weighted, directed network of movements to identify geographically-explicit movement communities and measure the evolution of these community structures through time.\n\nFindingsWe found that the mobility network became more sparse and the number of mobility communities decreased under the national lockdown, a change that disproportionately affected long distance journeys central to the mobility network. We also found that the community structure of areas in which locally-targeted interventions were implemented following epidemic resurgence did not show reorganization of community structure but did show small decreases in indicators of travel outside of local areas.\n\nInterpretationWe propose that communities detected using Facebook or other mobility data be used to assess the impact of spatially-targeted restrictions and may inform policymakers about the spatial extent of human movement patterns in the UK. These data are available in near real-time, allowing quantification of changes in the distribution of the population across the UK, as well as changes in travel patterns to inform our understanding of the impact of geographically-targeted interventions.\n\nPutting Research Into ContextO_ST_ABSEvidence before this studyC_ST_ABSLarge-scale intensive interventions in response to the COVID-19 pandemic have been implemented globally, significantly affecting human movement patterns. Mobility data show spatially-explicit network structure, but it is not clear how that structure changed in response to national or locally-targeted interventions.\n\nAdded value of this studyWe used daily mobility data aggregated from Facebook users to quantify changes in the travel network in the UK during the national lockdown, and in response to local interventions. We identified changes in human behaviour in response to interventions and identified the community structure inherent in these networks. This approach to understanding changes in the travel network can help quantify the extent of strongly connected communities of interaction and their relationship to the extent of spatially-explicit interventions.\n\nImplications of all the available evidenceWe show that spatial mobility data available in near real-time can give information on connectivity that can be used to understand the impact of geographically-targeted interventions and in the future, to inform spatially-targeted intervention strategies.\n\nData SharingData used in this study are available from the Facebook Data for Good Partner Program by application. Code and supplementary information for this paper are available online (https://github.com/hamishgibbs/facebook_mobility_uk), alongside publication.", - "category": "epidemiology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.10.26.20219725", @@ -3263,14 +3221,14 @@ }, { "site": "medRxiv", - "doi": "10.1101/2020.10.12.20211227", - "date": "2020-10-14", - "link": "https://medrxiv.org/cgi/content/short/2020.10.12.20211227", - "title": "High and increasing prevalence of SARS-CoV-2 swab positivity in England during end September beginning October 2020: REACT-1 round 5 updated report", - "authors": "Steven Riley; Kylie E. C. Ainslie; Oliver Eales; Caroline E Walters; Haowei Wang; Christina J Atchison; Claudio Fronterre; Peter J Diggle; Deborah Ashby; Christl A. Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott", - "affiliations": "Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Lancaster University; Lancaster University; Imperial College London; Imperial College London; Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London School of Public Health", - "abstract": "BackgroundREACT-1 is quantifying prevalence of SARS-CoV-2 infection among random samples of the population in England based on PCR testing of self-administered nose and throat swabs. Here we report results from the fifth round of observations for swabs collected from the 18th September to 5th October 2020. This report updates and should be read alongside our round 5 interim report.\n\nMethodsRepresentative samples of the population aged 5 years and over in England with sample size ranging from 120,000 to 175,000 people at each round. Prevalence of PCR-confirmed SARS-CoV-2 infection, estimation of reproduction number (R) and time trends between and within rounds using exponential growth or decay models.\n\nResults175,000 volunteers tested across England between 18th September and 5th October. Findings show a national prevalence of 0.60% (95% confidence interval 0.55%, 0.71%) and doubling of the virus every 29 (17, 84) days in England corresponding to an estimated national R of 1.16 (1.05, 1.27). These results correspond to 1 in 170 people currently swab-positive for the virus and approximately 45,000 new infections each day. At regional level, the highest prevalence is in the North West, Yorkshire and The Humber and the North East with strongest regional growth in North West, Yorkshire and The Humber and West Midlands.\n\nConclusionRapid growth has led to high prevalence of SARS-CoV-2 virus in England, with highest rates in the North of England. Prevalence has increased in all age groups, including those at highest risk. Improved compliance with existing policy and, as necessary, additional interventions are required to control the spread of SARS-CoV-2 in the community and limit the numbers of hospital admissions and deaths from COVID-19.", - "category": "infectious diseases", + "doi": "10.1101/2020.10.11.20210625", + "date": "2020-10-13", + "link": "https://medrxiv.org/cgi/content/short/2020.10.11.20210625", + "title": "Mental health service activity during COVID-19 lockdown among individuals with learning disabilities: South London and Maudsley data on services and mortality from January to July 2020", + "authors": "Evangelia Martin; Eleanor Nuzum; Matthew Broadbent; Robert Stewart", + "affiliations": "King's College London; King's College London; South London and Maudsley NHS Foundation Trust; King's College London", + "abstract": "The lockdown and social distancing policy imposed due to the COVID-19 pandemic is likely to have had a widespread impact on mental healthcare service provision and use. Previous reports from the South London and Maudsley NHS Trust (SLaM; a large mental health service provider for 1.2m residents in South London) highlighted a shift to virtual contacts among those accessing community mental health and home treatment teams and an increase in deaths over the pandemics first wave. However, there is a need to quantify this for individuals with particular vulnerabilities, including those with learning disabilities and other neurodevelopmental disorders. Taking advantage of the Clinical Record Interactive Search (CRIS) data resource with 24-hourly updates of electronic mental health records data, this paper describes daily caseloads and contact numbers (face-to-face and virtual) for individuals with potential neurodevelopmental disorders across community, specialist, crisis and inpatient services. The report focussed on the period 1st January to 31st July 2020. We also report on daily accepted and discharged trust referrals, total trust caseloads and daily inpatient admissions and discharges for individuals with potential neurodevelopmental disorders. In addition, daily deaths are described for all current and previous SLaM service users with potential neurodevelopmental disorders over this period. In summary, comparing periods before and after 16th March 2020 there was a shift from face-to-face contacts to virtual contacts across all teams. The largest declines in caseloads and total contacts were seen in Home Treatment Team, Liaison/A&E and Older Adult teams. Reduced accepted referrals and inpatient admissions were observed and there was an 103% increase in average daily deaths in the period after 16th March, compared to the period 1st January to 15th March (or a 282% increase if the 2-month period from 16th March to 15th May was considered alone).", + "category": "psychiatry and clinical psychology", "match_type": "exact", "author_similarity": 100, "affiliation_similarity": 100 @@ -3513,6 +3471,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.09.02.20185892", + "date": "2020-09-07", + "link": "https://medrxiv.org/cgi/content/short/2020.09.02.20185892", + "title": "Prognostic accuracy of emergency department triage tools for adults with suspected COVID-19: The PRIEST observational cohort study", + "authors": "Ben Thomas; Steve Goodacre; Ellen Lee; Laura Sutton; Amanda Loban; Simon Waterhouse; Richard Simmonds; Katie Biggs; Carl Marincowitz; Jose Schutter; Sarah Connelly; Elena Sheldon; Jamie Hall; Emma Young; Andrew Bentley; Kirsty Challen; Chris Fitzsimmons; Tim Harris; Fiona Lecky; Andrew Lee; Ian Maconochie; Darren Walter", + "affiliations": "University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; Manchester University NHS Foundation Trust; Lancashire Teaching Hospitals NHS Foundation Trust; Sheffield Children's NHS Foundation Trust; Barts Health NHS Trust; University of Sheffield; University of Sheffield; Imperial College Healthcare NHS Trust; Manchester University NHS Foundation Trust", + "abstract": "ObjectivesThe World Health Organisation (WHO) and National Institute for Health and Care Excellence (NICE) recommend various triage tools to assist decision-making for patients with suspected COVID-19. We aimed to estimate the accuracy of triage tools for predicting severe illness in adults presenting to the emergency department (ED) with suspected COVID-19 infection.\n\nMethodsWe undertook a mixed prospective and retrospective observational cohort study in 70 EDs across the United Kingdom (UK). We collected data from people attending with suspected COVID-19 between 26 March 2020 and 28 May 2020, and used presenting data to determine the results of assessment with the following triage tools: the WHO algorithm, NEWS2, CURB-65, CRB-65, PMEWS and the swine flu adult hospital pathway (SFAHP). We used 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome.\n\nResultsWe analysed data from 20892 adults, of whom 4672 (22.4%) died or received organ support (primary outcome), with 2058 (9.9%) receiving organ support and 2614 (12.5%) dying without organ support (secondary outcomes). C-statistics for the primary outcome were: CURB-65 0.75; CRB-65 0.70; PMEWS 0.77; NEWS2 (score) 0.77; NEWS2 (rule) 0.69; SFAHP (6-point) 0.70; SFAHP (7-point) 0.68; WHO algorithm 0.61. All triage tools showed worse prediction for receipt of organ support and better prediction for death without organ support.\n\nAt the recommended threshold, PMEWS and the WHO criteria showed good sensitivity (0.96 and 0.95 respectively), at the expense of specificity (0.31 and 0.27 respectively). NEWS2 showed similar sensitivity (0.96) and specificity (0.28) when a lower threshold than recommended was used.\n\nConclusionCURB-65, PMEWS and NEWS2 provide good but not excellent prediction for adverse outcome in suspected COVID-19, and predicted death without organ support better than receipt of organ support. PMEWS, the WHO criteria and NEWS2 (using a lower threshold than usually recommended) provide good sensitivity at the expense of specificity.\n\nRegistrationISRCTN registry, ISRCTN28342533, http://www.isrctn.com/ISRCTN28342533", + "category": "emergency medicine", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.09.01.20185793", @@ -3611,6 +3583,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.08.12.20173690", + "date": "2020-08-14", + "link": "https://medrxiv.org/cgi/content/short/2020.08.12.20173690", + "title": "Antibody prevalence for SARS-CoV-2 in England following first peak of the pandemic: REACT2 study in 100,000 adults", + "authors": "Helen Ward; Christina J Atchison; Matthew Whitaker; Kylie E. C. Ainslie; Joshua Elliott; Lucy C Okell; Rozlyn Redd; Deborah Ashby; Christl A. Donnelly; Wendy Barclay; Ara Darzi; Graham Cooke; Steven Riley; Paul Elliott", + "affiliations": "Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Dept Inf Dis Epi, Imperial College; Imperial College London", + "abstract": "BackgroundEngland, UK has experienced a large outbreak of SARS-CoV-2 infection. As in USA and elsewhere, disadvantaged communities have been disproportionately affected.\n\nMethodsNational REal-time Assessment of Community Transmission-2 (REACT-2) prevalence study using a self-administered lateral flow immunoassay (LFIA) test for IgG among a random population sample of 100,000 adults over 18 years in England, 20 June to 13 July 2020.\n\nResultsData were available for 109,076 participants, yielding 5,544 IgG positive results; adjusted (for test performance) and re-weighted (for sampling) prevalence was 6.0% (95% Cl: 5.8, 6.1). Highest prevalence was in London (13.0% [12.3, 13.6]), among people of Black or Asian (mainly South Asian) ethnicity (17.3% [15.8, 19.1] and 11.9% [11.0, 12.8] respectively) and those aged 18-24 years (7.9% [7.3, 8.5]). Adjusted odds ratio for care home workers with client-facing roles was 3.1 (2.5, 3.8) compared with non-essential workers. One third (32.2%, [31.0-33.4]) of antibody positive individuals reported no symptoms. Among symptomatic cases, most (78.8%) reported symptoms during the peak of the epidemic in England in March (31.3%) and April (47.5%) 2020. We estimate that 3.36 million (3.21, 3.51) people have been infected with SARS-CoV-2 in England to end June 2020, with an overall infection fatality ratio (IFR) of 0.90% (0.86, 0.94); age-specific IFR was similar among people of different ethnicities.\n\nConclusionThe SARS-CoV-2 pandemic in England disproportionately affected ethnic minority groups and health and care home workers. The higher risk of infection in minority ethnic groups may explain their increased risk of hospitalisation and mortality from COVID-19.", + "category": "infectious diseases", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.08.12.20171405", @@ -3947,20 +3933,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "bioRxiv", - "doi": "10.1101/2020.07.01.182709", - "date": "2020-07-01", - "link": "https://biorxiv.org/cgi/content/short/2020.07.01.182709", - "title": "Genetic architecture of host proteins interacting with SARS-CoV-2", - "authors": "Maik Pietzner; Eleanor Wheeler; Julia Carrasco-Zanini; Johannes Raffler; Nicola D. Kerrison; Erin Oerton; Victoria P.W. Auyeung; Chris Finan; Juan P. Casas; Rachel Ostroff; Steve A. Williams; Gabi Kastenm\u00fcller; Markus Ralser; Eric G. Gamazon; Nicholas J. Wareham; Aroon Dinesh Hingorani; Claudia Langenberg", - "affiliations": "University of Cambridge; University of Cambridge; University of Cambridge; Helmholtz Zentrum M\u00fcnchen - German Research Center for Environmental Health (GmbH); University of Cambridge; University of Cambridge; University of Cambridge; University College London; Harvard Medical School; SomaLogic Inc.; SomaLogic Inc.; Helmholtz Zentrum M\u00fcnchen - German Research Center for Environmental Health (GmbH); The Francis Crick Institute; Vanderbilt University Medical Center; University of Cambridge; University College London; University of Cambridge", - "abstract": "Strategies to develop therapeutics for SARS-CoV-2 infection may be informed by experimental identification of viral-host protein interactions in cellular assays and measurement of host response proteins in COVID-19 patients. Identification of genetic variants that influence the level or activity of these proteins in the host could enable rapid in silico assessment in human genetic studies of their causal relevance as molecular targets for new or repurposed drugs to treat COVID-19. We integrated large-scale genomic and aptamer-based plasma proteomic data from 10,708 individuals to characterize the genetic architecture of 179 host proteins reported to interact with SARS-CoV-2 proteins or to participate in the host response to COVID-19. We identified 220 host DNA sequence variants acting in cis (MAF 0.01-49.9%) and explaining 0.3-70.9% of the variance of 97 of these proteins, including 45 with no previously known protein quantitative trait loci (pQTL) and 38 encoding current drug targets. Systematic characterization of pQTLs across the phenome identified protein-drug-disease links, evidence that putative viral interaction partners such as MARK3 affect immune response, and establish the first link between a recently reported variant for respiratory failure of COVID-19 patients at the ABO locus and hypercoagulation, i.e. maladaptive host response. Our results accelerate the evaluation and prioritization of new drug development programmes and repurposing of trials to prevent, treat or reduce adverse outcomes. Rapid sharing and dynamic and detailed interrogation of results is facilitated through an interactive webserver (https://omicscience.org/apps/covidpgwas/).", - "category": "genomics", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.06.29.20142448", @@ -3989,20 +3961,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.06.24.20139048", - "date": "2020-06-25", - "link": "https://medrxiv.org/cgi/content/short/2020.06.24.20139048", - "title": "A geotemporal survey of hospital bed saturation across England during the first wave of the COVID-19 Pandemic", - "authors": "Bilal A Mateen; Harrison Wilde; John m Dennis; Andrew Duncan; Nicholas John Meyrick Thomas; Andrew P McGovern; Spiros Denaxas; Matt J Keeling; Sebastian J Vollmer", - "affiliations": "The Alan Turing Institute; University of Warwick; Kings College Hospital NHS Foundation Trust; University of Warwick, Department of Statistics; University of Exeter Medical School; The Alan Turing Institute; Imperial College London, Faculty of Natural Sciences; University of Exeter Medical School; Royal Devon and Exeter NHS Foundation Trust, Diabetes and Endocrinology; University of Exeter Medical School; University College London; University of Warwick; The Alan Turing Institute; University of Warwick, Department of Statistics", - "abstract": "BackgroundNon-pharmacological interventions were introduced based on modelling studies which suggested that the English National Health Service (NHS) would be overwhelmed by the COVID-19 pandemic. In this study, we describe the pattern of bed occupancy across England during the first wave of the pandemic, January 31st to June 5th 2020.\n\nMethodsBed availability and occupancy data was extracted from daily reports submitted by all English secondary care providers, between 27-Mar and 5-June. Two thresholds for safe occupancy were utilized (85% as per Royal College of Emergency Medicine and 92% as per NHS Improvement).\n\nFindingsAt peak availability, there were 2711 additional beds compatible with mechanical ventilation across England, reflecting a 53% increase in capacity, and occupancy never exceeded 62%. A consequence of the repurposing of beds meant that at the trough, there were 8{middle dot}7% (8,508) fewer general and acute (G&A) beds across England, but occupancy never exceeded 72%. The closest to (surge) capacity that any trust in England reached was 99{middle dot}8% for general and acute beds. For beds compatible with mechanical ventilation there were 326 trust-days (3{middle dot}7%) spent above 85% of surge capacity, and 154 trust-days (1{middle dot}8%) spent above 92%. 23 trusts spent a cumulative 81 days at 100% saturation of their surge ventilator bed capacity (median number of days per trust = 1 [range: 1 to 17]). However, only 3 STPs (aggregates of geographically co-located trusts) reached 100% saturation of their mechanical ventilation beds.\n\nInterpretationThroughout the first wave of the pandemic, an adequate supply of all bed-types existed at a national level. Due to an unequal distribution of bed utilization, many trusts spent a significant period operating above safe-occupancy thresholds, despite substantial capacity in geographically co-located trusts; a key operational issue to address in preparing for a potential second wave.\n\nFundingThis study received no funding.\n\nResearch In ContextO_ST_ABSEvidence Before This StudyC_ST_ABSWe identified information sources describing COVID-19 related bed and mechanical ventilator demand modelling, as well as bed occupancy during the first wave of the pandemic by performing regular searches of MedRxiv, PubMed and Google, using the terms COVID-19, mechanical ventilators, bed occupancy, England, UK, demand, and non-pharmacological interventions (NPIs), until June 20th, 2020. Two UK-specific studies were found that modelled the demand for mechanical ventilators, one of which incorporated sensitivity analysis based on the introduction of NPIs and found that their effects might prevent the healthcare system being overwhelmed. Separately, several news reports were found pertaining to a single hospital that reached ventilator capacity in England during the first wave of the pandemic, however, no single authoritative source was identified detailing impact across all hospital sites in England.\n\nAdded Value of This StudyThis national study of hospital-level bed occupancy in England provides unique and timely insight into bed-specific resource utilization during the first wave of the COVID-19 pandemic, nationally, and by specific (geographically defined) health footprints. We found evidence of an unequal distribution of resource utilization across England. Although occupancy of beds compatible with mechanical ventilation never exceeded 62% at the national level, 52 (30%) hospitals across England reached 100% saturation at some point during the first wave of the pandemic. Close examination of the geospatial data revealed that in the vast majority of circumstances there was relief capacity in geographically co-located hospitals. Over the first wave it was theoretically possible to markedly reduce (by 95.1%) the number of hospitals at 100% saturation of their mechanical ventilator bed capacity by redistributing patients to nearby hospitals.\n\nImplications Of All The Available EvidenceNow-casting using routinely collected administrative data presents a robust approach to rapidly evaluate the effectiveness of national policies introduced to prevent a healthcare system being overwhelmed in the context of a pandemic illness. Early investment in operational field hospital and an independent sector network may yield more overtly positive results in the winter, when G&A occupancy-levels regularly exceed 92% in England, however, during the first wave of the pandemic they were under-utilized. Moreover, in the context of the non-pharmacological interventions utilized during the first wave of COVID-19, demand for beds and mechanical ventilators was much lower than initially predicted, but despite this many trust spent a significant period of time operating above safe-occupancy thresholds. This finding demonstrates that it is vital that future demand (prediction) models reflect the nuances of local variation within a healthcare system. Failure to incorporate such geographical variation can misrepresent the likelihood of surpassing availability thresholds by averaging out over regions with relatively lower demand, and presents a key operational issue for policymakers to address in preparing for a potential second wave.", - "category": "health systems and quality improvement", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.06.21.20136853", @@ -4143,20 +4101,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.06.01.20116608", - "date": "2020-06-03", - "link": "https://medrxiv.org/cgi/content/short/2020.06.01.20116608", - "title": "Is death from Covid-19 a multistep process?", - "authors": "Neil Pearce; Giovenale Moirano; Milena Maule; Manolis Kogevinas; Xavier Rodo; Deborah Lawlor; Jan Vandenbroucke; Christina Vandenbroucke-Grauls; Fernando P Polack; Adnan Custovic", - "affiliations": "London School of Hygiene and Tropical Medicine; University of Turin, Italy; University of Turin, Italy; ISGlobal; ISGlobal; University of Bristol; Leiden University Medical Center; Amsterdam UMC; Vanderbilt Unversity; Imperial College London", - "abstract": "Covid-19 death has a different relationship with age than is the case for other severe respiratory pathogens. The Covid-19 death rate increases exponentially with age, and the main risk factors are age itself, as well as having underlying conditions such as hypertension, diabetes, cardiovascular disease, severe chronic respiratory disease and cancer. Furthermore, the almost complete lack of deaths in children suggests that infection alone is not sufficient to cause death; rather, one must have gone through a number of changes, either as a result of undefined aspects of aging, or as a result of chronic disease. These characteristics of Covid-19 death are consistent with the multistep model of disease, a model which has primarily been used for cancer, and more recently for amyotrophic lateral sclerosis (ALS). We applied the multi-step model to data on Covid-19 case fatality rates (CFRs) from China, South Korea, Italy, Spain and Japan. In all countries we found that a plot of ln (CFR) against ln (age) was approximately linear with a slope of about 5. As a comparison, we also conducted similar analyses for selected other respiratory diseases. SARS showed a similar log-log age-pattern to that of Covid-19, albeit with a lower slope, whereas seasonal and pandemic influenza showed quite different age-patterns. Thus, death from Covid-19 and SARS appears to follow a distinct age-pattern, consistent with a multistep model of disease that in the case of Covid-19 is probably defined by comorbidities and age producing immune-related susceptibility. Identification of these steps would be potentially important for prevention and therapy for SARS-COV-2 infection.", - "category": "infectious diseases", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.05.27.20083287", @@ -4311,6 +4255,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.05.02.20078642", + "date": "2020-05-06", + "link": "https://medrxiv.org/cgi/content/short/2020.05.02.20078642", + "title": "Impact of ethnicity on outcome of severe COVID-19 infection. Data from an ethnically diverse UK tertiary centre", + "authors": "James T Teo; Daniel Bean; Rebecca Bendayan; Richard Dobson; Ajay Shah", + "affiliations": "Kings College Hospital NHS Foundation Trust; King's College London; King's College London; Kings College London; King's College London", + "abstract": "During the current COVID-19 pandemic, it has been suggested that BAME background patients may be disproportionately affected compared to White but few detailed data are available. We took advantage of near real-time hospital data access and analysis pipelines to look at the impact of ethnicity in 1200 consecutive patients admitted between 1st March 2020 and 12th May 2020 to Kings College Hospital NHS Trust in London (UK).\n\nOur key findings are firstly that BAME patients are significantly younger and have different co-morbidity profiles than White individuals. Secondly, there is no significant independent effect of ethnicity on severe outcomes (death or ITU admission) within 14-days of symptom onset, after adjustment for age, sex and comorbidities.", + "category": "intensive care and critical care medicine", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.04.28.20083170", diff --git a/data/covid/preprints.json b/data/covid/preprints.json index c17dfa0f..67baf42a 100644 --- a/data/covid/preprints.json +++ b/data/covid/preprints.json @@ -41,6 +41,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2023.08.30.23294821", + "date": "2023-09-01", + "link": "https://medrxiv.org/cgi/content/short/2023.08.30.23294821", + "title": "Symptom experience before vs. after confirmed SARS-CoV-2 infection: a population and case control study using prospectively recorded symptom data.", + "authors": "Carole Helene Sudre; Michela Antonelli; Nathan J Cheetham; Erika Molteni; Liane S Canas; Vicky Bowyer; Benjamin Murray; Khaled Rjoob; Marc Modat; Joan Capdevia Pujol; Christina Hu; Jonathan Wolf; Timothy D Spector; Alexander Hammers; Claire J Steves; Sebastien Ourselin; Emma L Duncan", + "affiliations": "University College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; University College London; King's College London; Zoe Ltd; Zoe Ltd; Zoe Ltd; King's College London; King's College London; King's College London; King's College London; King's College London", + "abstract": "BackgroundSome individuals experience prolonged illness after acute COVID-19. We assessed whether pre-infection symptoms affected post-COVID illness duration.\n\nMethodsSurvival analysis was performed in adults (n=23,452) with community-managed SARC-CoV-2 infection prospectively self-logging data through the ZOE COVID Symptom Study app, at least weekly, from 8 weeks before to 12 weeks after COVID-19 onset, conditioned on presence vs. absence of baseline symptoms (4-8 weeks before COVID-19). A case-control study was performed in 1350 individuals with long illness ([≥]8 weeks, 906 [67.1%] with illness [≥]12 weeks), matched 1:1 (for age, sex, body mass index, testing week, prior infection, vaccination, smoking, index of multiple deprivation) with 1350 individuals with short illness (<4 weeks). Baseline symptoms were compared between the two groups; and against post-COVID symptoms.\n\nFindingsIndividuals reporting baseline symptoms had longer post-COVID symptom duration (from 10 to 15 days) with baseline fatigue nearly doubling duration. Two-thirds (910 of 1350 [67.4%]) of individuals with long illness were asymptomatic beforehand. However, 440 (32.6%) had baseline symptoms, vs. 255 (18.9%) of 1350 individuals with short illness (p<0.0001). Baseline symptoms increased the odds ratio for long illness (2.14 [CI: 1.78; 2.57]). Prior comorbidities were more common in individuals with long vs. short illness. In individuals with long illness, baseline symptomatic (vs. asymptomatic) individuals were more likely to be female, younger, and have prior comorbidities; and baseline and post-acute symptoms and symptom burden correlated strongly.\n\nInterpretationIndividuals experiencing symptoms before COVID-19 have longer illness duration and increased odds of long illness. However, many individuals with long illness are well before SARS-CoV-2 infection.", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 94, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2023.08.25.23294609", @@ -55,6 +69,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2023.08.11.23293977", + "date": "2023-08-15", + "link": "https://medrxiv.org/cgi/content/short/2023.08.11.23293977", + "title": "Digital Mental Health Service engagement changes during Covid-19 in children and young people across the UK: presenting concerns, service activity, and access by gender, ethnicity, and deprivation", + "authors": "Duleeka Knipe; Santiago de Ossorno Garcia; Louisa Salhi; Lily Mainstone-Cotton; Aaron Sefi; Ann John", + "affiliations": "University of Bristol School of Social and Community Medicine: University of Bristol Population Health Sciences; Kooth Digital Health; Kooth Digital Health; Kooth Digital Health; Kooth Digital Health; Swansea University", + "abstract": "The adoption of digital health technologies accelerated during Covid-19, with concerns over the equity of access due to digital exclusion. Using data from a text-based online mental health service for children and young people we explore the impact of the pandemic on service access and presenting concerns and whether differences were observed by sociodemographic characteristics in terms of access (gender, ethnicity and deprivation). We used interrupted time-series models to assess whether there was a change in the level and rate of service use during the Covid-19 pandemic (April 2020-April 2021) compared to pre-pandemic trends (June 2019-March 2020). Routinely collected data from 61221 service users were extracted for observation, those represented half of the service population as only those with consent to share their data were used. The majority of users identified as female (74%) and White (80%), with an age range between 13 and 20 years of age. There was evidence of a sudden increase (13%) in service access at the start of the pandemic (RR 1.13 95% CI 1.02, 1.25), followed by a reduced rate (from 25% to 21%) of engagement during the pandemic compared to pre-pandemic trends (RR 0.97 95% CI 0.95,0.98). There was a sudden increase in almost all presenting issues apart from physical complaints. There was evidence of a step increase in the number of contacts for Black/African/Caribbean/Black British (38% increase; 95% CI: 1%-90%) and White ethnic groups (14% increase; 95% CI: 2%-27%)), sudden increase in service use at the start of the pandemic for the most (58% increase; 95% CI: 1%-247%) and least (47% increase; 95% CI: 6%-204%) deprived areas. During the pandemic, contact rates decreased, and referral sources change at the start. Findings on access and service activity align with other studies observing reduced service utilization. The lack of differences in deprivation levels and ethnicity at lockdown suggests exploring equity of access to the anonymous service. The study provides unique insights into changes in digital mental health use during Covid-19 in the UK.", + "category": "public and global health", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2023.08.07.23293778", @@ -377,20 +405,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2023.05.08.23289442", - "date": "2023-05-11", - "link": "https://medrxiv.org/cgi/content/short/2023.05.08.23289442", - "title": "Cohort Profile: Post-hospitalisation COVID-19 study (PHOSP-COVID)", - "authors": "Omer Elneima; Hamish J C McAuley; Olivia C Leavy; James D Chalmers; Alex Horsley; Ling-Pei Ho; Michael Marks; Krisnah Poinasamy; Betty Raman; Aarti Shikotra; Amisha Singapuri; Marco Sereno; Victoria C Harris; Linzy Houchen-Wolloff; Ruth M Saunders; Neil J Greening; Matthew Richardson; Jennifer K Quint; Andrew Briggs; Annemarie B Docherty; Steven Kerr; Ewen M Harrison; Nazir I Lone; Mathew Thorpe; Liam G Heaney; Keir E Lewis; Raminder Aul; Paul Beirne; Charlotte E Bolton; Jeremy S Brown; Gourab Choudhury; Nawar Diar Bakerly; Nicholas Easom; Carlos Echevarria; Jonathan Fuld; Nick Hart; John R Hurst; Mark G Jones; Dhruv Parekh; Paul E Pfeffer; Najib M Rahman; Sarah L Rowland-Jones; AA Roger Thompson; Caroline Jolley; Ajay M Shah; Dan G Wootton; Trudie Chalder; Melanie J Davies; Anthony De Soyza; John R Geddes; William Greenhalf; Simon Heller; Luke S Howard; Joseph Jacob; R Gisli Jenkins; Janet M Lord; William D-C Man; Gerry P McCann; Stefan Neubauer; Peter JM Openshaw; Joanna C Porter; Matthew J Rowland; Janet T Scott; Malcolm G Semple; Sally J Singh; David C Thomas; Mark Toshner; Aziz Sheikh; Chris E Brightling; Louise v Wain; Rachael A Evans; - on behalf of the PHOSP-COVID Collaborative Group", - "affiliations": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Population Health Sciences, University of Leicester, Leicester, UK; University of Dundee, Ninewells Hospital and Medical School, Dundee, UK; Division of Infection, Immunity & Respiratory Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK; MRC Human Immunology Unit, University of Oxford, Oxford, UK; Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK; Asthma and Lung UK, London, UK; Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre- Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; National Heart and Lung Institute, Imperial College London, London, UK; London School of Hygiene & Tropical Medicine, London, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; The Roslin Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Wellcome-Wolfson Institute for Experimental Medicine, Queens University Belfast, Belfast, UK; Hywel Dda University Health Board, Wales, UK; St George's University Hospitals NHS Foundation Trust, London, UK; Leeds Teaching Hospitals NHS Trust, Leeds, UK; NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK; UCL Respiratory, Department of Medicine, University College London, London, UK; Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK; Salford Royal NHS Foundation Trust, Manchester, UK; Infection Research Group, Hull University Teaching Hospitals, Hull, UK; Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, UK; Department of Respiratory Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK; Lane Fox Respiratory Unit, Guy's and St Thomas' NHS Foundation Trust, London, UK; Royal Free London NHS Foundation Trust, London, UK; Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK; Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK; Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK; NIHR Oxford Biomedical Research Centre, Oxford, UK; University of Sheffield, Sheffield, UK; University of Sheffield, Sheffield, UK; Centre for Human & Applied Physiological Sciences, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK; King's College London British Heart Foundation Centre, London, UK; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool, UK; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK; NIHR Oxford Health Biomedical Research Centre, University of Oxford, Oxford, UK; The CRUK Liverpool Experimental Cancer Medicine Centre, Liverpool, UK; Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK; Imperial College Healthcare NHS Trust, London, UK; Centre for Medical Image Computing, University College London, London, UK; National Heart and Lung Institute, Imperial College London, London, UK; MRC-Versus Arthritis Centre for Musculoskeletal Ageing Research, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK; Royal Brompton & Harefield Hospitals, Guy's and St. Thomas' NHS Foundation Trust, London, UK; Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester; NIHR Oxford Biomedical Research Centre, Oxford, UK; National Heart and Lung Institute, Imperial College London, London, UK; UCL Respiratory, Department of Medicine, University College London, London, UK; Kadoorie Centre for Critical Care Research, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; MRC-University of Glasgow Center for Virus research; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool, UK; Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Immunology and Inflammation, Imperial College London, London, UK; NIHR Cambridge Biomedical Research Centre, Cambridge, United Kingdom; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Population Health Sciences, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; ", - "abstract": "O_LIPHOSP-COVID is a national UK multi-centre cohort study of patients who were hospitalised for COVID-19 and subsequently discharged.\nC_LIO_LIPHOSP-COVID was established to investigate the medium- and long-term sequelae of severe COVID-19 requiring hospitalisation, understand the underlying mechanisms of these sequelae, evaluate the medium- and long-term effects of COVID-19 treatments, and to serve as a platform to enable future studies, including clinical trials.\nC_LIO_LIData collected covered a wide range of physical measures, biological samples, and Patient Reported Outcome Measures (PROMs).\nC_LIO_LIParticipants could join the cohort either in Tier 1 only with remote data collection using hospital records, a PROMs app and postal saliva sample for DNA, or in Tier 2 where they were invited to attend two specific research visits for further data collection and biological research sampling. These research visits occurred at five (range 2-7) months and 12 (range 10-14) months post-discharge. Participants could also participate in specific nested studies (Tier 3) at selected sites.\nC_LIO_LIAll participants were asked to consent to further follow-up for 25 years via linkage to their electronic healthcare records and to be re-contacted for further research.\nC_LIO_LIIn total, 7935 participants were recruited from 83 UK sites: 5238 to Tier 1 and 2697 to Tier 2, between August 2020 and March 2022.\nC_LIO_LICohort data are held in a Trusted Research Environment and samples stored in a central biobank. Data and samples can be accessed upon request and subject to approvals.\nC_LI", - "category": "respiratory medicine", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2023.05.08.23289637", @@ -587,20 +601,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2023.02.18.23286127", - "date": "2023-02-19", - "link": "https://medrxiv.org/cgi/content/short/2023.02.18.23286127", - "title": "Antipsychotic prescribing and mortality in people with dementia before and during the COVID-19 pandemic: retrospective cohort study", - "authors": "Christian Schnier; Aoife McCarthy; Daniel R Morales; Ashley Akbari; Reecha Sofat; Caroline Dale; Rohan Takhar; Mamas Mamas; Kamlesh Khunti; Francesco Zaccardi; Cathie LM Sudlow; Tim Wilkinson", - "affiliations": "University of Edinburgh; University of Edinburgh; University of Dundee; Swansea University; University of Liverpool; University of Liverpool; University College London; Keele University; University of Leicester; University of Leicester; University of Edinburgh; University of Edinburgh", - "abstract": "BackgroundAntipsychotic drugs have been associated with increased mortality, stroke and myocardial infarction in people with dementia. Concerns have been raised that antipsychotic prescribing may have increased during the COVID-19 pandemic due to social restrictions imposed to limit the spread of the virus. We used multisource, routinely-collected healthcare data from Wales, UK, to investigate prescribing and mortality trends in people with dementia before and during the COVID-19 pandemic.\n\nMethodsWe used individual-level, anonymised, population-scale linked health data to identify adults aged [≥]60 years with a diagnosis of dementia in Wales, UK. We explored antipsychotic prescribing trends over 67 months between 1st January 2016 and 1st August 2021, overall and stratified by age and dementia subtype. We used time series analyses to examine all-cause, myocardial infarction (MI) and stroke mortality over the study period and identified the leading causes of death in people with dementia.\n\nFindingsOf 57,396 people with dementia, 11,929 (21%) were prescribed an antipsychotic at any point during follow-up. Accounting for seasonality, antipsychotic prescribing increased during the second half of 2019 and throughout 2020. However, the absolute difference in prescribing rates was small, ranging from 1253 to 1305 per 10,000 person-months. Prescribing in the 60-64 age group and those with Alzheimers disease increased throughout the 5-year period. All-cause and stroke mortality increased in the second half of 2019 and throughout 2020 but MI mortality declined. From January 2020, COVID-19 was the second commonest underlying cause of death in people with dementia.\n\nInterpretationDuring the COVID-19 pandemic there was a small increase in antipsychotic prescribing in people with dementia. The long-term increase in antipsychotic prescribing in younger people and in those with Alzheimers disease warrants further investigation.\n\nFundingBritish Heart Foundation (BHF) (SP/19/3/34678) via the BHF Data Science Centre led by HDR UK, and the Scottish Neurological Research Fund.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched Ovid MEDLINE for studies describing antipsychotic prescribing trends in people with dementia during the COVID-19 pandemic, published between 1st January 2020 and 22nd March 2022. The following search terms were used: (exp Antipsychotic Agents/ OR antipsychotic.mp OR neuroleptic.mp OR risperidone.mp OR exp Risperidone/ OR quetiapine.mp OR exp Quetiapine Fumarate/ OR olanzapine.mp OR exp Olanzapine/ OR exp Psychotropic Drugs/ or psychotropic.mp) AND (exp Dementia/ OR exp Alzheimer Disease/ or alzheimer.mp) AND (prescri*.mp OR exp Prescriptions/ OR exp Electronic Prescribing/ OR trend*.mp OR time series.mp). The search identified 128 published studies, of which three were eligible for inclusion. Two studies, based on data from England and the USA, compared antipsychotic prescribing in people with dementia before and during the COVID-19 pandemic. Both reported an increase in the proportion of patients prescribed an antipsychotic after the onset of the pandemic. A third study, based in the Netherlands, reported antipsychotic prescription trends in nursing home residents with dementia during the first four months of the pandemic, comparing prescribing rates to the timings of lifting of social restrictions, showing that antipsychotic prescribing rates remained constant throughout this period.\n\nAdded value of this studyWe conducted age-standardised time series analyses using comprehensive, linked, anonymised, individual-level routinely-collected, population-scale health data for the population of Wales, UK. By accounting for seasonal variations in prescribing and mortality, we demonstrated that the absolute increase in antipsychotic prescribing in people with dementia of any cause during the COVID-19 pandemic was small. In contrast, antipsychotic prescribing in the youngest age group (60-64 years) and in people with a subtype diagnosis of Alzheimers disease increased throughout the five-year study period. Accounting for seasonal variation, all-cause mortality rates in people with dementia began to increase in late 2019 and increased sharply during the first few months of the pandemic. COVID-19 became the leading non-dementia cause of death in people with dementia from 2020 to 2021. Stroke mortality increased during the pandemic, following a similar pattern to that of all-cause mortality, whereas myocardial infarction rates decreased.\n\nImplications of all the available evidenceDuring COVID-19 we observed a large increase in all-cause and stroke mortality in people with dementia. When seasonal variations are accounted for, antipsychotic prescribing rates in all-cause dementia increased by a small amount before and during the pandemic in the UK. The increased prescribing rates in younger age groups and in people with Alzheimers disease warrants further investigation.", - "category": "neurology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2023.02.16.23286017", @@ -741,6 +741,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2023.01.04.22283762", + "date": "2023-01-05", + "link": "https://medrxiv.org/cgi/content/short/2023.01.04.22283762", + "title": "Challenges in estimating waning effectiveness of two doses of BNT162b2 and ChAdOx1 COVID-19 vaccines beyond six months: an OpenSAFELY cohort study using linked electronic health records", + "authors": "Elsie MF Horne; William J Hulme; Ruth H Keogh; Tom M Palmer; Elizabeth Williamson; Edward PK Parker; Venexia M Walker; Rochelle Knight; Yinghui Wei; Kurt Taylor; Louis Fisher; Jessica Morley; Amir Mehrkar; Iain Dillingham; Sebastian CJ Bacon; Ben Goldacre; Jonathan AC Sterne; - The OpenSAFELY Collaborative", + "affiliations": "University of Bristol; University of Oxford; London School of Hygiene and Tropical Medicine; University of Bristol; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Bristol; University of Bristol; University of Plymouth; University of Bristol; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Bristol; -", + "abstract": "Quantifying the waning effectiveness of second COVID-19 vaccination beyond six months and against the omicron variant is important for scheduling subsequent doses. With the approval of NHS England, we estimated effectiveness up to one year after second dose, but found that bias in such estimates may be substantial.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2023.01.04.23284174", @@ -839,20 +853,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.12.13.22283391", - "date": "2022-12-14", - "link": "https://medrxiv.org/cgi/content/short/2022.12.13.22283391", - "title": "The effects of sleep disturbance on dyspnoea and impaired lung function following COVID-19 hospitalisation: a prospective multi-centre cohort study", - "authors": "Callum Jackson; Iain Stewart; Tatiana Plekhanova; Peter Cunningham; Andrew L. Hazel; Bashar Al-Sheklly; Raminder Aul; Charlotte E. Bolton; Trudie Chalder; James D. Chalmers; Nazia Chaudhuri; Annemaire B. Docherty; Gavin Donaldson; Charlotte L. Edwardson; Omer Elneima; Neil J Greening; Neil A. Hanley; Victoria C. Harris; Ewen M. Harrison; Ling-Pei Ho; Linzy Houchen-Wolloff; Luke S. Howard; Caroline J. Jolley; Mark G. Jones; Olivia C. Leavy; Keir E. Lewis; Nazir I. Lone; Michael Marks; Hamish J. C. McAuley; Melitta A. McNarry; Brijesh Patel; Karen Piper-Hanley; Krisnah Poinasamy; Betty Raman; Matthew Richardson; Pilar Rivera-Ortega; Sarah L. Rowland-Jones; Alex V. Rowlands; Ruth M. Saunders; Janet T Scott; Marco Sereno; Ajay M. Shah; Aarti Shikotra; Amisha Singapuri; Stefan C. Stanel; Mathew Thorpe; Daniel G. Wootton; Thomas Yates; R Gisli Jenkins; Sally Singh; William D-C. Man; Chris E. Brightling; Louise V. Wain; Joanna C. Porter; A. A. Roger Thompson; Alexander Horsley; Phil L. Molyneaux; Rachael E. Evans; Samuel E. Jones; Martin K. Rutter; John F. Blaikley", - "affiliations": "Department of Mathematics, The University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom; National Heart & Lung Institute, Imperial College London, London, UK; Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK; Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester M13 9PL United Kingdom; Department of Mathematics, The University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom; Manchester University NHS Foundation Trust & University of Manchester; St Georges Univeristy Hospitals NHS Foundation Trust, London, UK; NIHR Nottingham BRC respiratory theme, Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; University of Dundee, Ninewells Hospital and Medical School, Dundee, UK; University Hospital of South Manchester NHS Foundation Trust; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; National Heart & Lung Institute, Imperial College London, London, UK; Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Manchester University NHS Foundation Trust; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Oxford University Hospitals NHS Foundation Trust & University of Oxford; Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; National Heart & Lung Institute, Imperial College London, London, UK; King's College London; Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK; Department of Health Sciences, Univeristy of Leicester, Leicester, UK; Swansea University, Swansea Welsh Network, Hywel Dda University Health Board; Usher Institute, University of Edinburgh, Edinburgh, UK; Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Swansea University, Swansea Welsh Network, Hywel Dda University Health Board; Royal Brompton and Harefield Clinical Group, Guys and St Thomas NHS Foundation trust; Manchester University NHS Foundation Trust & University of Manchester; Asthma UK and British Lung Foundation, London, UK; Oxford University Hospitals NHS Foundation Trust & University of Oxford; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Manchester University NHS Foundation Trust; University of Sheffield, Sheffield, UK; Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; MRC - University of Glasgow Centre for Virus Research, Glasgow, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; King's College Hospital NHS Foundation Trust & Kings College London; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Interstitial Lung Disease Unit, North West Lung Centre, Wythenshawe Hospital, Southmoor Rd, Wythenshawe, Manchester M23 9LT, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Liverpool University Hospitals NHS Foundation Trust & University of Liverpool; Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK; National Heart & Lung Institute, Imperial College London, London, UK; University Hospitals of Leicester NHS Trust & University of Leicester; National Heart & Lung Institute, Imperial College London, London, UK; University Hospitals of Leicester NHS Trust & University of Leicester; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Department of Respiratory Medicine, University College London WC1E 2JF; Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield UK; Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester M13 9PL United Kingdom; National Heart & Lung Institute, Imperial College London, London, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland; Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester M13 9PL United Kingdom; The University of Manchester", - "abstract": "BackgroundSleep disturbance is common following hospitalisation both for COVID-19 and other causes. The clinical associations are poorly understood, despite it altering pathophysiology in other scenarios. We, therefore, investigated whether sleep disturbance is associated with dyspnoea along with relevant mediation pathways.\n\nMethodsSleep parameters were assessed in a prospective cohort of patients (n=2,468) hospitalised for COVID-19 in the United Kingdom in 39 centres using both subjective and device-based measures. Results were compared to a matched UK biobank cohort and associations were evaluated using multivariable linear regression.\n\nFindings64% (456/714) of participants reported poor sleep quality; 56% felt their sleep quality had deteriorated for at least 1-year following hospitalisation. Compared to the matched cohort, both sleep regularity (44.5 vs 59.2, p<0.001) and sleep efficiency (85.4% vs 88.5%, p<0.001) were lower whilst sleep period duration was longer (8.25h vs 7.32h, p<0.001). Overall sleep quality (effect estimate 4.2 (3.0-5.5)), deterioration in sleep quality following hospitalisation (effect estimate 3.2 (2.0-4.5)), and sleep regularity (effect estimate 5.9 (3.7-8.1)) were associated with both dyspnoea and impaired lung function (FEV1 and FVC). Depending on the sleep metric, anxiety mediated 13-42% of the effect of sleep disturbance on dyspnoea and muscle weakness mediated 29-43% of this effect.\n\nInterpretationSleep disturbance is associated with dyspnoea, anxiety and muscle weakness following COVID-19 hospitalisation. It could have similar effects for other causes of hospitalisation where sleep disturbance is prevalent.\n\nFundingUK Research and Innovation, National Institute for Health Research, and Engineering and Physical Sciences Research Council.", - "category": "respiratory medicine", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.12.09.22283280", @@ -867,20 +867,6 @@ "author_similarity": 92, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.11.29.22282883", - "date": "2022-12-12", - "link": "https://medrxiv.org/cgi/content/short/2022.11.29.22282883", - "title": "The protection gap under a social health protection initiative in the COVID-19 pandemic: A case study from Khyber Pakhtunkhwa, Pakistan.", - "authors": "Sheraz Ahmad Khan; Kathrin Cresswell; Aziz Sheikh", - "affiliations": "The University of Edinburgh; The University of Edinburgh College of Medicine and Veterinary Medicine; The University of Edinburgh College of Medicine and Veterinary Medicine", - "abstract": "BackgroundSehat Sahulat Programme (SSP) is a Social Health Protection (SHP) initiative by the Government of Khyber Pakhtunkhwa (GoKP), covering inpatient services for 100% of the provinces population. In this paper, we describe SSPs role in GoKPs COVID-19 response and draw inferences for similar programmes in Pakistan.\n\nMethodology and methodsWe conceptualised SSP as an instrumental case study and collected three complementary data sources. First, we studied GoKPs official documents to understand SSPs benefits package. Then we undertook in-depth interviews and collected non-participant observations at the SSP policy and implementation levels. We recruited participants through direct (verbal and email) and indirect (invitation posters) methods.\n\nUse of maximum variation sampling enabled us to understand contrasting views from various stakeholders on SSPs policy dimensions (i.e., coverage and financing), tensions between the policy directions (i.e., whether or not to cover COVID-19) and how policy decisions were made and implemented. We collected data from March 2021 to December 2021. Thematic analysis was conducted with the help of Nvivo12.\n\nFindingsThroughout 2020, SSP did not cover COVID-19 treatment. The insurer and GoKP officials considered the pandemic a standard exclusion to insurance coverage. One SSP official said: \"COVID-19 is not covered and not relevant to us\". GoKP had stopped non-emergency services at all hospitals. When routine services restarted, the insurer did not cover COVID-19 screening tests, which were mandatory prior to hospital admission.\n\nIn 2021, GoKP engaged 10 private SSP hospitals for COVID-19 treatment. The SSP Reserve Fund, rather than insurance pooled money, was used. The Reserve Fund was originally meant to cover high-cost organ transplants. In 2021, SSP had 1,002 COVID-19-related admissions, which represented 0.2% of all hospital admissions (N=544,841).\n\nAn advocacy group representative called the COVID-19 care under SSP \"too little too late\". In contrast, SSP officials suggested their insurance database and funds flow mechanism could help GoKP in future health emergencies.\n\nConclusionThe commercially focused interpretation of SHP arrangements led to a protection gap in the context of COVID-19. SSP and similar programmes in other provinces of Pakistan should emphasise the notion of protection and not let commercial interests lead to protection gaps.", - "category": "health policy", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.12.03.22282974", @@ -937,20 +923,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.11.29.22282899", - "date": "2022-11-29", - "link": "https://medrxiv.org/cgi/content/short/2022.11.29.22282899", - "title": "Performance of antigen lateral flow devices in the United Kingdom during the Alpha, Delta, and Omicron waves of the SARS-CoV-2 pandemic", - "authors": "David W Eyre; Matthias Futschik; Sarah Tunkel; Jia Wei; Joanna Cole-Hamilton; Rida Saquib; Nick Germanacos; Andrew Dodgson; Paul E Klapper; Malur Sudhanva; Chris Kenny; Peter Marks; Edward Blandford; Susan Hopkins; Tim Peto; Tom Fowler", - "affiliations": "University of Oxford; UK Health Security Agency; UK Health Security Agency; University of Oxford; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; University of Manchester; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; University of Oxford; UK Health Security Agency", - "abstract": "BackgroundAntigen lateral flow devices (LFDs) have been widely used to control SARS-CoV-2. Changes in LFD sensitivity and detection of infectious individuals during the pandemic with successive variants, vaccination, and changes in LFD use are incompletely understood.\n\nMethodsPaired LFD and PCR tests were collected from asymptomatic and symptomatic participants, across multiple settings in the UK between 04-November-2020 and 21-March-2022. Multivariable logistic regression was used to analyse LFD sensitivity and specificity, adjusting for viral load, LFD manufacturer, setting, age, sex, assistance, symptoms, vaccination, and variant. National contact tracing data were used to estimate the proportion of transmitting index cases (with [≥]1 PCR/LFD-positive contact) potentially detectable by LFDs over time, accounting for viral load, variant, and symptom status.\n\nFindings4131/75,382 (5.5%) participants were PCR-positive. Sensitivity vs. PCR was 63.2% (95%CI 61.7-64.6%) and specificity 99.71% (99.66-99.74%). Increased viral load was independently associated with being LFD-positive. There was no evidence LFD sensitivity differed between Delta vs. Alpha/pre-Alpha infections, but Omicron infections were more likely to be LFD positive. Sensitivity was higher in symptomatic participants, 68.7% (66.9-70.4%) than in asymptomatic participants, 52.8% (50.1-55.4%). 79.4% (68.6-81.3%) of index cases resulting in probable onward transmission with were estimated to have been detectable using LFDs, this proportion was relatively stable over time/variants, but lower in asymptomatic vs. symptomatic cases.\n\nInterpretationLFDs remained able to detect most SARS-CoV-2 infections throughout vaccine roll-out and different variants. LFDs can potentially detect most infections that transmit to others and reduce risks. However, performance is lower in asymptomatic compared to symptomatic individuals.\n\nFundingUK Government.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSLateral flow devices (LFDs; i.e. rapid antigen detection devices) have been widely used for SARS-CoV-2 testing. However, due to their imperfect sensitivity when compared to PCR and a lack of a widely available gold standard proxy for infectiousness, the performance and use of LFDs has been a source of debate. We conducted a literature review in PubMed and bioRxiv/medRxiv for all studies examining the performance of lateral flow devices between 01 January 2020 and 31 October 2022. We used the search terms SARS-CoV-2/COVID-19 and antigen/lateral flow test/lateral flow device. Multiple studies have examined the sensitivity and specificity of LFDs, including several systematic reviews. However, the majority of the studies are based on pre-Alpha infections. Large studies examining the test accuracy for different variants, including Delta and Omicron, and following vaccination are limited.\n\nAdded value of this studyIn this large national LFD evaluation programme, we compared the performance of three different LFDs relative to PCR in various settings. Compared to PCR testing, sensitivity was 63.2% (95%CI 61.7-64.6%) overall, and 71.6% (95%CI 69.8-73.4%) in unselected communitybased testing. Specificity was 99.71% (99.66-99.74%). LFDs were more likely to be positive as viral loads increased. LFD sensitivity was similar during Alpha/pre-Alpha and Delta periods but increased during the Omicron period. There was no association between sensitivity and vaccination status. Sensitivity was higher in symptomatic participants, 68.7% (66.9-70.4%) than in asymptomatic participants, 52.8% (50.1-55.4%). Using national contact tracing data, we estimated that 79.4% (68.6-81.3%) of index cases resulting in probable onward transmission (i.e. with [≥]1 PCR/LFD-positive contact) were detectable using LFDs. Symptomatic index cases were more likely to be detected than asymptomatic index cases due to higher viral loads and better LFD performance at a given viral load. The proportion of index cases detected remained relatively stable over time and with successive variants, with a slight increase in the proportion of asymptomatic index cases detected during Omicron.\n\nImplications of all the available evidenceOur data show that LFDs detect most SARS-CoV-2 infections, with findings broadly similar to those summarised in previous meta-analyses. We show that LFD performance has been relatively consistent throughout different variant-dominant phases of the pandemic and following the roll-out of vaccination. LFDs can detect most infections that transmit to others and can therefore be used as part of a risk reduction strategy. However, performance is lower in asymptomatic compared to symptomatic individuals and this needs to be considered when designing testing programmes.", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.11.16.22282396", @@ -1497,20 +1469,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.06.17.22276433", - "date": "2022-06-17", - "link": "https://medrxiv.org/cgi/content/short/2022.06.17.22276433", - "title": "It hurts your heart: frontline healthcare worker experiences of moral injury during the COVID-19 pandemic", - "authors": "Siobhan Hegarty; Danielle Lamb; Sharon Stevelink; Rupa Bhundia; Rosalind Raine; Mary Jane Docherty; Hannah Rachel Scott; Anne Marie Rafferty; Victoria Williamson; Sarah Dorrington; Matthew hotopf; Reza Razavi; Neil Greenberg; Simon Wessely", - "affiliations": "King's College London; UCL; King's College London; King's College London; University College London; South London and Maudsley NHS Foundation Trust; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London", - "abstract": "BackgroundMoral injury is defined as the strong emotional and cognitive reactions following events which clash with someones moral code, values or expectations. During the COVID-19 pandemic, increased exposure to potentially morally injurious events (PMIEs) has placed healthcare workers (HCWs) at risk of moral injury. Yet little is known about the lived experience of cumulative PMIE exposure and how NHS staff respond to this.\n\nObjectiveWe sought to rectify this knowledge gap by qualitatively exploring the lived experiences and perspectives of clinical frontline NHS staff who responded to COVID-19.\n\nMethodsWe recruited a diverse sample of 30 clinical frontline HCWs from the NHS CHECK study cohort, for single time point qualitative interviews. All participants endorsed at least one item on the 9-item Moral Injury Events Scale (MIES) (Nash et al., 2013) at six month follow up. Interviews followed a semi-structured guide and were analysed using reflexive thematic analysis.\n\nResultsHCWs described being routinely exposed to ethical conflicts, created by exacerbations of pre-existing systemic issues including inadequate staffing and resourcing. We found that HCWs experienced a range of mental health symptoms primarily related to perceptions of institutional betrayal as well as feeling unable to fulfil their duty of care towards patients.\n\nConclusionThese results suggest that a multi-facetted organisational strategy is warranted to prepare for PMIE exposure, promote opportunities for resolution of symptoms associated with moral injury and prevent organisational disengagement.\n\nHighlightsO_LIClinical frontline healthcare workers (HCWs) have been exposed to an accumulation of potentially morally injurious events (PMIEs) throughout the COVID-19 pandemic, including feeling betrayed by both government and NHS leaders as well as feeling unable to provide duty of care to patients\nC_LIO_LIHCWs described the significant adverse impact of this exposure on their mental health, including increased anxiety and depression symptoms and sleep disturbance\nC_LIO_LIMost HCWs interviewed believed that organisational change within the NHS was necessary to prevent excess PMIE exposure and promote resolution of moral distress\nC_LI", - "category": "psychiatry and clinical psychology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.06.16.22276479", @@ -1819,6 +1777,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2022.05.06.22274658", + "date": "2022-05-07", + "link": "https://medrxiv.org/cgi/content/short/2022.05.06.22274658", + "title": "STIMULATE-ICP-CAREINEQUAL - Defining usual care and examining inequalities in Long Covid support: protocol for a mixed-methods study (part of STIMULATE-ICP: Symptoms, Trajectory, Inequalities and Management: Understanding Long-COVID to Address and Transform Existing Integrated Care Pathways).", + "authors": "Mel Ramasawmy; Yi Mu; Donna Clutterbuck; Marija Pantelic; Gregory Y.H. Lip; Christina Van der Feltz-Cornelis; Dan Wootton; Nefyn H Williams; Hugh Montgomery; Rita Mallinson Cookson; Emily Attree; Mark Gabbay; Melissa J Heightman; Nisreen A Alwan; Amitava Banerjee; Paula Lorgelly; - STIMULATE-ICP consortium", + "affiliations": "Institute of Health Informatics, University College London; Institute of Health Informatics, University College London; School of Primary Care, Population Sciences and Medical Education, University of Southampton; Brighton and Sussex Medical School, University of Sussex; Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool, United Kingdom; and Department of Clinical; Department of Health Sciences, HYMS, University of York, and Institute of Health Informatics, University College London; Institute of Infection Veterinary and Ecological Sciences, University of Liverpool; Department of Primary Care and Mental Health, University of Liverpool; Centre for Human Health and Performance, Department of Medicine, University College London; PPIE Representative; PPIE Representative; Department of Primary Care and Mental Health, University of Liverpool; University College London Hospitals NHS Trust; School of Primary Care, Population Sciences and Medical Education, University of Southampton; NIHR Southampton Biomedical Research Centre, University of Southam; Institute of Health Informatics, University College London; School of Population Health and Department of Economics, University of Auckland; ", + "abstract": "IntroductionIndividuals with Long Covid represent a new and growing patient population. In England, fewer than 90 Long Covid clinics deliver assessment and treatment informed by NICE guidelines. However, a paucity of clinical trials or longitudinal cohort studies means that the epidemiology, clinical trajectory, healthcare utilisation and effectiveness of current Long Covid care are poorly documented, and that neither evidence-based treatments nor rehabilitation strategies exist. In addition, and in part due to pre-pandemic health inequalities, access to referral and care varies, and patient experience of the Long Covid care pathways can be poor.\n\nIn a mixed methods study, we therefore aim to: (1) describe the usual healthcare, outcomes and resource utilisation of individuals with Long Covid; (2) assess the extent of inequalities in access to Long Covid care, and specifically to understand Long Covid patients experiences of stigma and discrimination.\n\nMethods and analysisA mixed methods study will address our aims. Qualitative data collection from patients and health professionals will be achieved through surveys, interviews and focus group discussions, to understand their experience and document the function of clinics. A patient cohort study will provide an understanding of outcomes and costs of care. Accessible data will be further analysed to understand the nature of Long Covid, and the care received.\n\nEthics and disseminationEthical approval was obtained from South Central - Berkshire Research Ethics Committee (reference 303958). The dissemination plan will be decided by the patient and public involvement and engagement (PPIE) group members and study Co-Is, but will target 1) policy makers, and those responsible for commissioning and delivering Long Covid services, 2) patients and the public, and 3) academics.", + "category": "health systems and quality improvement", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.05.05.22273234", @@ -1875,20 +1847,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.04.28.22273177", - "date": "2022-04-29", - "link": "https://medrxiv.org/cgi/content/short/2022.04.28.22273177", - "title": "Occupational differences in SARS-CoV-2 infection: Analysis of the UK ONS Coronavirus (COVID-19) Infection Survey", - "authors": "Sarah Rhodes; Jack Wilkinson; Neil Pearce; Will Mueller; Mark Cherrie; Katie Stocking; Matthew Gittins; Srinivasa Vittal Katikireddi; Martie van Tongeren", - "affiliations": "University of Manchester; University of Manchester; London School of Hygiene and Tropical Medicine; Institute of Occupational Medicine; Institute of Occupational Medicine; University of Manchester; University of Manchester; University of Glasgow; University of Manchester", - "abstract": "BackgroundConsiderable concern remains about how occupational SARS-CoV-2 risk has evolved during the COVID-19 pandemic. We aimed to ascertain which occupations had the greatest risk of SARS-CoV-2 infection and explore how relative differences varied over the pandemic.\n\nMethodsAnalysis of cohort data from the UK Office of National Statistics Coronavirus (COVID-19) Infection Survey from April 2020 to November 2021. This survey is designed to be representative of the UK population and uses regular PCR testing. Cox and multilevel logistic regression to compare SARS-CoV-2 infection between occupational/sector groups, overall and by four time periods with interactions, adjusted for age, sex, ethnicity, deprivation, region, household size, urban/rural neighbourhood and current health conditions.\n\nResultsBased on 3,910,311 observations from 312,304 working age adults, elevated risks of infection can be seen overall for social care (HR 1.14; 95% CI 1.04 to 1.24), education (HR 1.31; 95% CI 1.23 to 1.39), bus and coach drivers (1.43; 95% CI 1.03 to 1.97) and police and protective services (HR 1.45; 95% CI 1.29 to 1.62) when compared to non-essential workers. By time period, relative differences were more pronounced early in the pandemic. For healthcare elevated odds in the early waves switched to a reduction in the later stages. Education saw raises after the initial lockdown and this has persisted. Adjustment for covariates made very little difference to effect estimates.\n\nConclusionsElevated risks among healthcare workers have diminished over time but education workers have had persistently higher risks. Long-term mitigation measures in certain workplaces may be warranted.\n\nWhat is already known on this topicSome occupational groups have observed increased rates of disease and mortality relating to COVID-19.\n\nWhat this study addsRelative differences between occupational groups have varied during different stages of the COVID-19 pandemic with risks for healthcare workers diminishing over time and workers in the education sector seeing persistent elevated risks.\n\nHow this study might affect research, practice or policyIncreased long term mitigation such as ventilation should be considered in sectors with a persistent elevated risk. It is important for workplace policy to be responsive to evolving pandemic risks.", - "category": "occupational and environmental health", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.04.26.22274332", @@ -1945,6 +1903,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "bioRxiv", + "doi": "10.1101/2022.04.20.488895", + "date": "2022-04-20", + "link": "https://biorxiv.org/cgi/content/short/2022.04.20.488895", + "title": "Emergence of new subgenomic mRNAs in SARS-CoV-2", + "authors": "Harriet V Mears; George R Young; Theo Sanderson; Ruth Harvey; Margaret Crawford; Daniel M Snell; Ashley S Fowler; Saira Hussain; Jerome Nicod; Edward Emmott; Katja Finsterbusch; Jakub Luptak; Emma Wall; Bryan Williams; Sonia Gandhi; Charles Swanton; David LV Bauer", + "affiliations": "RNA Virus Replication Laboratory, The Francis Crick Institute, London, UK; RNA Virus Replication Laboratory & Bioinformatics and Biostatistics STP, The Francis Crick Institute, London, UK; Malaria Biochemistry Laboratory, The Francis Crick Institute, London, UK; Worldwide Influenza Centre, The Francis Crick Institute, London, UK; Advanced Sequencing Facility, The Francis Crick Institute, London, UK; Advanced Sequencing Facility, The Francis Crick Institute, London, UK; Advanced Sequencing Facility, The Francis Crick Institute, London, UK; RNA Virus Replication Laboratory, The Francis Crick Institute, London, UK; Advanced Sequencing Facility, The Francis Crick Institute, London, UK; Centre for Proteome Research, Department of Biochemistry & Systems Biology, Institute of Systems Molecular & Integrative Biology, University of Liverpool, Liver; Immunoregulation Laboratory, The Francis Crick Institute, London, UK; MRC Laboratory of Molecular Biology, Cambridge, UK; Crick/UCLH Legacy Study, The Francis Crick Institute, London, UK; and National Institute for Health Research (NIHR) University College London Hospitals (UCLH) B; University College London; and National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK; Neurodegeneration Biology Laboratory, The Francis Crick Institute, London, UK; Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK; RNA Virus Replication Laboratory, The Francis Crick Institute, London, UK", + "abstract": "Two mutations occurred in SARS-CoV-2 early during the COVID-19 pandemic that have come to define circulating virus lineages1: first a change in the spike protein (D614G) that defines the B.1 lineage and second, a double substitution in the nucleocapsid protein (R203K, G204R) that defines the B.1.1 lineage, which has subsequently given rise to three Variants of Concern: Alpha, Gamma and Omicron. While the latter mutations appear unremarkable at the protein level, there are dramatic implications at the nucleotide level: the GGG[->]AAC substitution generates a new Transcription Regulatory Sequence (TRS) motif, driving SARS-CoV-2 to express a novel subgenomic mRNA (sgmRNA) encoding a truncated C-terminal portion of nucleocapsid (N.iORF3), which is an inhibitor of type I interferon production. We find that N.iORF3 also emerged independently within the Iota variant, and further show that additional TRS motifs have convergently evolved to express novel sgmRNAs; notably upstream of Spike within the nsp16 coding region of ORF1b, which is expressed during human infection. Our findings demonstrate that SARS-CoV-2 is undergoing evolutionary changes at the functional RNA level in addition to the amino acid level, reminiscent of eukaryotic evolution. Greater attention to this aspect in the assessment of emerging strains of SARS-CoV-2 is warranted.", + "category": "microbiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.04.14.22273903", @@ -2141,6 +2113,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2022.03.18.22272607", + "date": "2022-03-21", + "link": "https://medrxiv.org/cgi/content/short/2022.03.18.22272607", + "title": "Multi-organ impairment and Long COVID: a 1-year prospective, longitudinal cohort study", + "authors": "Andrea Dennis; Daniel J Cuthbertson; Dan Wootton; Michael Crooks; Mark Gabbay; Nicole Eichert; Sofia Mouchti; Michele Pansini; Adriana Roca-Fernandez; Helena Thomaides-Brears; Matt Kelly; Matthew Robson; Lyth Hishmeh; Emily Attree; Melissa J Heightman; Rajarshi Banerjee; Amitava Banerjee", + "affiliations": "Perspectum Ltd; University of Liverpool; University of Liverpool; University of Hull; University of Liverpool; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Diagnostics; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Long COVID SoS; UKDoctors#Longcovid; UCLH; Perspectum Ltd; University College London", + "abstract": "ImportanceMulti-organ impairment associated with Long COVID is a significant burden to individuals, populations and health systems, presenting challenges for diagnosis and care provision. Standardised assessment across multiple organs over time is lacking, particularly in non-hospitalised individuals.\n\nObjectiveTo determine the prevalence of organ impairment in Long COVID patients at 6 and at 12 months after initial symptoms and to explore links to clinical presentation.\n\nDesignThis was a prospective, longitudinal study in individuals following recovery from acute COVID-19. We assessed symptoms, health status, and multi-organ tissue characterisation and function, using consensus definitions for single and multi-organ impairment. Physiological and biochemical investigations were performed at baseline on all individuals and those with organ impairment were reassessed, including multi-organ MRI, 6 months later.\n\nSettingTwo non-acute settings (Oxford and London).\n\nParticipants536 individuals (mean 45 years, 73% female, 89% white, 32% healthcare workers, 13% acute COVID-19 hospitalisation) completed baseline assessment (median: 6 months post-COVID-19). 331 (62%) with organ impairment or incidental findings had follow up, with reduced symptom burden from baseline (median number of symptoms: 10 and 3, at 6 and 12 months).\n\nExposureSARS-CoV-2 infection 6 months prior to first assessment.\n\nMain outcomePrevalence of single and multi-organ impairment at 6 and 12 months post-COVID-19.\n\nResultsExtreme breathlessness (36% and 30%), cognitive dysfunction (50% and 38%) and poor health-related quality of life (EQ-5D-5L<0.7; 55% and 45%) were common at 6 and 12 months, and associated with female gender, younger age and single organ impairment. At baseline, there was fibro-inflammation in the heart (9%), pancreas (9%), kidney (15%) and liver (11%); increased volume in liver (7%), spleen (8%) and kidney (9%); decreased capacity in lungs (2%); and excessive fat deposition in the liver (25%) and pancreas (15%). Single and multi-organ impairment were present in 59% and 23% at baseline, persisting in 59% and 27% at follow-up.\n\nConclusion and RelevanceOrgan impairment was present in 59% of individuals at 6 months post-COVID-19, persisting in 59% of those followed up at 1 year, with implications for symptoms, quality of life and longer-term health, signalling need for prevention and integrated care of Long COVID.\n\nTrial RegistrationClinicalTrials.gov Identifier: NCT04369807\n\nKey pointsO_LIQuestion: What is the prevalence of organ impairment in Long COVID at 6- and 12-months post-COVID-19?\nC_LIO_LIFindings: In a prospective study of 536 mainly non-hospitalised individuals, symptom burden decreased, but single organ impairment persisted in 59% at 12 months post-COVID-19.\nC_LIO_LIMeaning: Organ impairment in Long COVID has implications for symptoms, quality of life and longer-term health, signalling need for prevention and integrated care of Long COVID.\nC_LI", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.03.17.22272414", @@ -2267,6 +2253,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "bioRxiv", + "doi": "10.1101/2022.03.08.481609", + "date": "2022-03-08", + "link": "https://biorxiv.org/cgi/content/short/2022.03.08.481609", + "title": "The origins and molecular evolution of SARS-CoV-2 lineage B.1.1.7 in the UK", + "authors": "Verity Hill; Louis du Plessis; Thomas P Alexander Peacock; Dinesh Aggarwal; Alessandro Carabelli; Rachel Colquhoun; Nicholas Ellaby; Eileen Gallagher; Natalie Groves; Ben Jackson; JT McCrone; Anna Price; Theo Sanderson; Emily Scher; Joel Alexander Southgate; Erik Volz; - The COVID-19 genomics UK (COG-UK) consortium; Wendy S Barclay; Jeffrey Barrett; Meera Chand; Thomas R Connor; Ian G. Goodfellow; Ravindra K Gupta; Ewan Harrison; Nicholas Loman; Richard Myers; David L Robertson; Oliver Pybus; Andrew Rambaut", + "affiliations": "The University of Edinburgh; University of Oxford; University College London (UCL); University of Cambridge; University of Cambridge; University of Edinburgh; UK Health Security Agency; Uk Health Security Agency; UK Health Security Agency; University of Edinburgh; University of Edinburgh; Cardiff University; Sanger Institute; University of Edinburgh; Cardiff University; Imperial College London; -; Imperial College London; Sanger Institute; UK Health Security Agency; Cardiff University; University of Cambridge; University of Cambridge; Sanger Institute; University of Birmingham; UK Health Security Agency; University of Glasgow; University of Oxford; University of Edinburgh", + "abstract": "The first SARS-CoV-2 variant of concern (VOC) to be designated was lineage B.1.1.7, later labelled by the World Health Organisation (WHO) as Alpha. Originating in early Autumn but discovered in December 2020, it spread rapidly and caused large waves of infections worldwide. The Alpha variant is notable for being defined by a long ancestral phylogenetic branch with an increased evolutionary rate, along which only two sequences have been sampled. Alpha genomes comprise a well-supported monophyletic clade within which the evolutionary rate is more typical of SARS-CoV-2. The Alpha epidemic continued to grow despite the continued restrictions on social mixing across the UK, and the imposition of new restrictions, in particular the English national lockdown in November 2020. While these interventions succeeded in reducing the absolute number of cases, the impact of these non-pharmaceutical interventions was predominantly to drive the decline of the SARS-CoV-2 lineages which preceded Alpha. We investigate the only two sampled sequences that fall on the branch ancestral to Alpha. We find that one is likely to be a true intermediate sequence, providing information about the order of mutational events that led to Alpha. We explore alternate hypotheses that can explain how Alpha acquired a large number of mutations yet remained largely unobserved in a region of high genomic surveillance: an under-sampled geographical location, a non-human animal population, or a chronically-infected individual. We conclude that the last hypothesis provides the best explanation of the observed behaviour and dynamics of the variant, although we find that the individual need not be immunocompromised, as persistently-infected immunocompetent hosts also display a higher within-host rate of evolution. Finally, we compare the ancestral branches and mutation profiles of other VOCs to each other, and identify that Delta appears to be an outlier both in terms of the genomic locations of its defining mutations, and its lack of rapid evolutionary rate on the ancestral branch. As new variants, such as Omicron, continue to evolve (potentially through similar mechanisms) it remains important to investigate the origins of other variants to identify ways to potentially disrupt their evolution and emergence.", + "category": "evolutionary biology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.03.06.21267462", @@ -2295,6 +2295,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2022.03.02.22271623", + "date": "2022-03-03", + "link": "https://medrxiv.org/cgi/content/short/2022.03.02.22271623", + "title": "Baricitinib in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial and updated meta-analysis", + "authors": "Peter W Horby; Jonathan R Emberson; Marion Mafham; Mark Campbell; Leon Peto; Guilherme Pessoa-Amorim; Enti Spata; Natalie Staplin; Catherine Lowe; David R Chadwick; Christopher Brightling; Richard Stewart; Paul Collini; Abdul Ashish; Christopher A Green; Benjamin Prudon; Tim Felton; Anthony Kerry; J Kenneth Baillie; Maya H Buch; Jeremy N Day; Saul N Faust; Thomas Jaki; Katie Jeffery; Edmund Juszczak; Marian Knight; Wei Shen Lim; Alan Montgomery; Andrew Mumford; Kathryn Rowan; Guy Thwaites; Richard Haynes; Martin J Landray", + "affiliations": "Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Liverpool University Hospitals NHS Foundation Trust; Centre for Clinical Infection, James Cook University Hospital, Middlesbrough, United Kingdom; Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; Milton Keynes University Hospital, Milton Keynes, United Kingdom; Sheffield Teaching Hospitals NHS Foundation Trust and University of Sheffield, Sheffield, United Kingdom; Wrightington, Wigan and Leigh Teaching Hospitals NHS Foundation Trust, Wigan, United Kingdom; University Hospitals Birmingham NHS Foundation Trust; North Tees and Hartlepool NHS Foundation Trust, Hartlepool, United Kingdom; Manchester University NHS Foundation Trust; Great Western Hospitals Foundation Trust, Swindon, United Kingdom; Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom; Centre for Musculoskeletal Research, University of Manchester, Manchester, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom; NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, ; Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom; Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Respiratory Medicine Department, Nottingham University Hospitals NHS Foundation Trust, Nottingham, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom; Intensive Care National Audit and Research Centre, London, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom", + "abstract": "BackgroundWe evaluated the use of baricitinib, a Janus kinase (JAK) 1/2 inhibitor, for the treatment of patients admitted to hospital because of COVID-19.\n\nMethodsThis randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple possible treatments in patients hospitalised for COVID-19. Eligible and consenting patients were randomly allocated (1:1) to either usual standard of care alone (usual care group) or usual care plus baricitinib 4 mg once daily by mouth for 10 days or until discharge if sooner (baricitinib group). The primary outcome was 28-day mortality assessed in the intention-to-treat population. A meta-analysis was conducted that included the results from the RECOVERY trial and all previous randomised controlled trials of baricitinib or other JAK inhibitor in patients hospitalised with COVID-19. The RECOVERY trial is registered with ISRCTN (50189673) and clinicaltrials.gov (NCT04381936).\n\nFindingsBetween 2 February 2021 and 29 December 2021, 8156 patients were randomly allocated to receive usual care plus baricitinib versus usual care alone. At randomisation, 95% of patients were receiving corticosteroids and 23% receiving tocilizumab (with planned use within the next 24 hours recorded for a further 9%). Overall, 513 (12%) of 4148 patients allocated to baricitinib versus 546 (14%) of 4008 patients allocated to usual care died within 28 days (age-adjusted rate ratio 0{middle dot}87; 95% CI 0{middle dot}77-0{middle dot}98; p=0{middle dot}026). This 13% proportional reduction in mortality was somewhat smaller than that seen in a meta-analysis of 8 previous trials of a JAK inhibitor (involving 3732 patients and 425 deaths) in which allocation to a JAK inhibitor was associated with a 43% proportional reduction in mortality (rate ratio 0.57; 95% CI 0.45-0.72). Including the results from RECOVERY into an updated meta-analysis of all 9 completed trials (involving 11,888 randomised patients and 1484 deaths) allocation to baricitinib or other JAK inhibitor was associated with a 20% proportional reduction in mortality (rate ratio 0.80; 95% CI 0.71-0.89; p<0.001). In RECOVERY, there was no significant excess in death or infection due to non-COVID-19 causes and no excess of thrombosis, or other safety outcomes.\n\nInterpretationIn patients hospitalised for COVID-19, baricitinib significantly reduced the risk of death but the size of benefit was somewhat smaller than that suggested by previous trials. The total randomised evidence to date suggests that JAK inhibitors (chiefly baricitinib) reduce mortality in patients hospitalised for COVID-19 by about one-fifth.\n\nFundingUK Research and Innovation (Medical Research Council) and National Institute of Health Research (Grant ref: MC_PC_19056).", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.02.24.22271466", @@ -2547,6 +2561,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2022.01.21.22269651", + "date": "2022-01-22", + "link": "https://medrxiv.org/cgi/content/short/2022.01.21.22269651", + "title": "Prior health-related behaviours in children (2014-2020) and association with a positive SARS-CoV-2 test during adolescence (2020-2021): a retrospective cohort study using survey data linked with routine health data in Wales, UK", + "authors": "Emily Marchant; Emily Lowthian; Tom Crick; Lucy Griffiths; Richard Fry; Kevin Dadaczynski; Orkan Okan; Michaela James; Laura Cowley; Fatemeh Torabi; Jonathan Kennedy; Ashley Akbari; Ronan Lyons; Sinead Brophy", + "affiliations": "Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Fulda University of Applied Sciences; Technical University Munich; Swansea University; Public Health Wales; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University", + "abstract": "ObjectivesExamine if pre-COVID-19 pandemic (prior March 2020) health-related behaviours during primary school are associated with i) being tested for SARS-CoV-2 and ii) testing positive between 1 March 2020 to 31 August 2021.\n\nDesignRetrospective cohort study using an online cohort survey (January 2018 to February 2020) linked to routine PCR SARS-CoV-2 test results.\n\nSettingChildren attending primary schools in Wales (2018-2020), UK who were part of the HAPPEN school network.\n\nParticipantsComplete linked records of eligible participants were obtained for n=7,062 individuals. 39.1% (n=2,764) were tested (age 10.6{+/-}0.9, 48.9% girls) and 8.1% (n=569) tested positive for SARS-CoV-2 (age 10.6{+/-}1.0, 54.5% girls).\n\nMain outcome measuresLogistic regression of health-related behaviours and demographics were used to determine Odds Ratios (OR) of factors associated with i) being tested for SARS-CoV-2 and ii) testing positive for SARS-CoV-2.\n\nResultsConsuming sugary snacks (1-2 days/week OR=1.24, 95% CI 1.04 - 1.49; 5-6 days/week 1.31, 1.07 - 1.61; reference 0 days) can swim 25m (1.21, 1.06 - 1.39) and age (1.25, 1.16 - 1.35) were associated with an increased likelihood of being tested for SARS-CoV-2. Eating breakfast (1.52, 1.01 - 2.27), weekly physical activity [≥] 60 mins (1-2 days 1.69, 1.04 - 2.74; 3-4 days 1.76, 1.10 - 2.82, reference 0 days), out of school club participation (1.06, 1.02 - 1.10), can ride a bike (1.39, 1.00 - 1.93), age (1.16, 1.05 - 1.28) and girls (1.21, 1.00 - 1.46) were associated with an increased likelihood of testing positive for SARS-CoV-2. Living in least deprived quintiles 4 (0.64, 0.46 - 0.90) and 5 (0.64, 0.46 - 0.89) compared to the most deprived quintile was associated with a decreased likelihood.\n\nConclusionsAssociations may be related to parental health literacy and monitoring behaviours. Physically active behaviours may include co-participation with others, and exposure to SARS-CoV-2. A risk versus benefit approach must be considered given the importance of health-related behaviours for development.\n\nSTRENGTHS AND LIMITATIONSO_LIInvestigation of the association of pre-pandemic child health-related behaviour measures with subsequent SARS-CoV-2 testing and infection.\nC_LIO_LIReporting of multiple child health behaviours linked at an individual-level to routine records of SARS-CoV-2 testing data through the SAIL Databank.\nC_LIO_LIChild-reported health behaviours were measured before the COVID-19 pandemic (1 January 2018 to 28 February 2020) which may not reflect behaviours during COVID-19.\nC_LIO_LIHealth behaviours captured through the national-scale HAPPEN survey represent children attending schools that engaged with the HAPPEN Wales primary school network and may not be representative of the whole population of Wales.\nC_LIO_LIThe period of study for PCR-testing for and testing positive for SARS-CoV-2 includes a time frame with varying prevalence rates, approaches to testing children (targeted and mass testing) and restrictions which were not measured in this study.\nC_LI", + "category": "public and global health", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "bioRxiv", "doi": "10.1101/2022.01.14.475727", @@ -2659,20 +2687,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.12.21.21268058", - "date": "2021-12-27", - "link": "https://medrxiv.org/cgi/content/short/2021.12.21.21268058", - "title": "Effectiveness of CoronaVac, ChAdOx1, BNT162b2 and Ad26.COV2.S among individuals with prior SARS-CoV-2 infection in Brazil", - "authors": "Thiago Cerqueira-Silva; Jason R Andrews; Viviane S Boaventura; Otavio T Ranzani; Vinicius de Araujo Oliveira; Enny S Paixao; Juracy Bertoldo Jr.; Tales Mota Machado; Matt D T Hitchings; Murilo Dorion; Margaret L Lind; Gerson O. Penna; Derek A.T. Cummings; Natalie E Dean; Guilherme Loureiro Werneck; Neil Pearce; Mauricio L Barreto; Albert I Ko; Julio Croda; Manoel Barral-Netto", - "affiliations": "Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA,USA; Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Universidade Federal da Bahia, Salvador, BA, Brazil; Barcelona Institute for Global Health, ISGlobal, Spain / Pulmonary Division, University of Sao Paulo; Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Healt; London School of Hygiene and Tropical Medicine, London, United Kingdom; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Health - Fiocruz, Salvador, BA, Brazil; Universidade Federal de Ouro Preto, Ouro Preto, MG, Brazil; Department of Biostatistics, College of Public Health & Health Professions, University of Florida, Gainesville, FL, USA; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Heaven, CT, USA; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Heaven, CT, USA; Nucleo de Medicina Tropical, Universidade de Brasilia, Brasilia, DF, Brazil; Escola Fiocruz de Governo, Fiocruz Brasilia. Brasilia, DF, Brazil; Department of Biology, University of Florida, Gainesville, FL, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA; Department of Biostatistics & Bioinformatics, Rollins School of Public Health, Emory University; Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil; London School of Hygiene and Tropical Medicine; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Health - Fiocruz, Salvador, BA, Brazil; Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Heaven, CT, USA; Universidade Federal de Mato Grosso do Sul, Campo Grande, MS, Brazil; Fiocruz Mato Grosso do Sul, Fundacao Oswaldo Cruz, Campo Grande, MS, Brazil; Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Healt", - "abstract": "BackgroundCOVID-19 vaccines have proven highly effective among SARS-CoV-2 naive individuals, but their effectiveness in preventing symptomatic infection and severe outcomes among individuals with prior infection is less clear.\n\nMethodsUtilizing national COVID-19 notification, hospitalization, and vaccination datasets from Brazil, we performed a case-control study using a test-negative design to assess the effectiveness of four vaccines (CoronaVac, ChAdOx1, Ad26.COV2.S and BNT162b2) among individuals with laboratory-confirmed prior SARS-CoV-2 infection. We matched RT-PCR positive, symptomatic COVID-19 cases with RT-PCR-negative controls presenting with symptomatic illnesses, restricting both groups to tests performed at least 90 days after an initial infection. We used multivariable conditional logistic regression to compare the odds of test positivity, and the odds of hospitalization or death due to COVID-19, according to vaccination status and time since first or second dose of vaccines.\n\nFindingsAmong individuals with prior SARS-CoV-2 infection, vaccine effectiveness against symptomatic infection [≥] 14 days from vaccine series completion was 39.4% (95% CI 36.1-42.6) for CoronaVac, 56.0% (95% CI 51.4-60.2) for ChAdOx1, 44.0% (95% CI 31.5-54.2) for Ad26.COV2.S, and 64.8% (95% CI 54.9-72.4) for BNT162b2. For the two-dose vaccine series (CoronaVac, ChAdOx1, and BNT162b2), effectiveness against symptomatic infection was significantly greater after the second dose compared with the first dose. Effectiveness against hospitalization or death [≥] 14 days from vaccine series completion was 81.3% (95% CI 75.3-85.8) for CoronaVac, 89.9% (95% CI 83.5-93.8) for ChAdOx1, 57.7% (95% CI -2.6-82.5) for Ad26.COV2.S, and 89.7% (95% CI 54.3-97.7) for BNT162b2.\n\nInterpretationAll four vaccines conferred additional protection against symptomatic infections and severe outcomes among individuals with previous SARS-CoV-2 infection. Provision of a full vaccine series to individuals following recovery from COVID-19 may reduce morbidity and mortality.\n\nFundingBrazilian National Research Council, Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro, Oswaldo Cruz Foundation, JBS S.A., Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, Generalitat de Catalunya.\n\nRESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed, medRxiv, and SSRN for articles published from January 1, 2020 until December 15, 2021, with no language restrictions, using the search terms \"vaccine effectiveness\" AND \"previous*\" AND (\"SARS-CoV-2\" OR \"COVID-19\"). We found several studies evaluating ChAdOx1 and BNT162b2, and one additionally reporting on mRNA-1273 and Ad26.COV2.S, which found that previously infected individuals who were vaccinated had lower risk of symptomatic SARS-CoV-2 infection. One study found that risk of hospitalization was lower for previously infected individuals after a full series of BNT162b2 or mRNA-1273. Limited evidence is available comparing effectiveness of one versus two doses among individuals with prior infection. No studies reported effectiveness of inactivated vaccines among previously infected individuals.\n\nAdded value of this studyWe used national databases of COVID-19 case surveillance, laboratory testing, and vaccination from Brazil to investigate effectiveness of CoronaVac, ChAdOx1, Ad26.COV2.S and BNT162b2 among individuals with a prior, laboratory-confirmed SARS-CoV-2 infection. We matched >22,000 RT-PCR-confirmed re-infections with >145,000 RT-PCR-negative controls using a test-negative design. All four vaccines were effective against symptomatic SARS-CoV-2 infections, with effectiveness from 14 days after series completion ranging from 39-65%. For vaccines with two-dose regimens, the second dose provided significantly increased effectiveness compared with one dose. Effectiveness against COVID-19-associated hospitalization or death from 14 days after series completion was >80% for CoronaVac, ChAdOx1and BNT162b2.\n\nImplications of all the available evidenceWe find evidence that four vaccines, using three different platforms, all provide protection to previously infected individuals against symptomatic SARS-CoV-2 infection and severe outcomes, with a second dose conferring significant additional benefits. These results support the provision of a full vaccine series among individuals with prior SARS-CoV-2 infection.", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.12.23.21268276", @@ -2841,20 +2855,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.12.16.21267906", - "date": "2021-12-16", - "link": "https://medrxiv.org/cgi/content/short/2021.12.16.21267906", - "title": "Workplace Contact Patterns in England during the COVID-19 Pandemic: Analysis of the Virus Watch prospective cohort study", - "authors": "Sarah Beale; Susan J Hoskins; Thomas Edward Byrne; Erica Wing Lam Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Annalan MD Navaratnam; Vincent Nguyen; Parth Patel; Alexei Yavlinsky; Anne M Johnson; Robert W Aldridge; Andrew Hayward", - "affiliations": "University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London", - "abstract": "BackgroundWorkplaces are an important potential source of SARS-CoV-2 exposure; however, investigation into workplace contact patterns is lacking. This study aimed to investigate how workplace attendance and features of contact varied between occupations and over time during the COVID-19 pandemic in England.\n\nMethodsData were obtained from electronic contact diaries submitted between November 2020 and November 2021 by employed/self-employed prospective cohort study participants (n=4,616). We used mixed models to investigate the main effects and potential interactions between occupation and time for: workplace attendance, number of people in shared workspace, time spent sharing workspace, number of close contacts, and usage of face coverings.\n\nFindingsWorkplace attendance and contact patterns varied across occupations and time. The predicted probability of intense space sharing during the day was highest for healthcare (78% [95% CI: 75-81%]) and education workers (64% [59%-69%]), who also had the highest probabilities for larger numbers of close contacts (36% [32%-40%] and 38% [33%-43%] respectively). Education workers also demonstrated relatively low predicted probability (51% [44%-57%]) of wearing a face covering during close contact. Across all occupational groups, levels of workspace sharing and close contact were higher and usage of face coverings at work lower in later phases of the pandemic compared to earlier phases.\n\nInterpretationMajor variations in patterns of workplace contact and mask use are likely to contribute to differential COVID-19 risk. Across occupations, increasing workplace contact and reduced usage of face coverings presents an area of concern given ongoing high levels of community transmission and emergence of variants.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.12.13.21267471", @@ -2981,6 +2981,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.11.29.21266847", + "date": "2021-11-30", + "link": "https://medrxiv.org/cgi/content/short/2021.11.29.21266847", + "title": "Population level impact of a pulse oximetry remote monitoring programme on mortality and healthcare utilisation in the people with covid-19 in England: a national analysis using a stepped wedge design", + "authors": "Thomas Beaney; Jonathan Clarke; Ahmed Alboksmaty; Kelsey Flott; Aidan Fowler; Jonathan R Benger; Paul Aylin; Sarah Elkin; Ana Luisa Neves; Ara Darzi", + "affiliations": "Imperial College London; Imperial College London; Imperial College London; Imperial College London; NHS England and Improvement; NHS Digital; Imperial College London; Imperial College London; Imperial College London; Imperial College London", + "abstract": "ObjectivesTo identify the population level impact of a national pulse oximetry remote monitoring programme for covid-19 (COVID Oximetry @home; CO@h) in England on mortality and health service use.\n\nDesignRetrospective cohort study using a stepped wedge pre- and post-implementation design.\n\nSettingAll Clinical Commissioning Groups (CCGs) in England implementing a local CO@h programme.\n\nParticipants217,650 people with a positive covid-19 polymerase chain reaction test result and symptomatic, from 1st October 2020 to 3rd May 2021, aged [≥]65 years or identified as clinically extremely vulnerable. Care home residents were excluded.\n\nInterventionsA pre-intervention period before implementation of the CO@h programme in each CCG was compared to a post-intervention period after implementation.\n\nMain outcome measuresFive outcome measures within 28 days of a positive covid-19 test: i) death from any cause; ii) any A&E attendance; iii) any emergency hospital admission; iv) critical care admission; and v) total length of hospital stay.\n\nResultsImplementation of the programme was not associated with mortality or length of hospital stay. Implementation was associated with increased health service utilisation with a 12% increase in the odds of A&E attendance (95% CI: 6%-18%) and emergency hospital admission (95% CI: 5%-20%) and a 24% increase in the odds of critical care admission in those admitted (95% CI: 5%-47%). In a secondary analysis of CO@h sites with at least 10% or 20% of eligible people enrolled, there was no significant association with any outcome measure. However, uptake of the programme was low, with enrolment data received for only 5,527 (2.5%) of the eligible population.\n\nConclusionsAt a population level, there was no association with mortality following implementation of the CO@h programme, and small increases in health service utilisation were observed. Low enrolment of eligible people may have diluted the effects of the programme at a population level.", + "category": "health systems and quality improvement", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.11.29.21266996", @@ -3009,6 +3023,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "bioRxiv", + "doi": "10.1101/2021.11.24.469860", + "date": "2021-11-26", + "link": "https://biorxiv.org/cgi/content/short/2021.11.24.469860", + "title": "Nanopore ReCappable Sequencing maps SARS-CoV-2 5' capping sites and provides new insights into the structure of sgRNAs", + "authors": "Camilla Ugolini; Logan Mulroney; Adrien Leger; Matteo Castelli; Elena Criscuolo; Maia Kavanagh Williamson; Andrew D Davidson; Abdulaziz Almuqrin; Roberto Giambruno; Miten Jain; Gianmaria Frig\u00e8; Hugh Olsen; George Tzertzinis; Ira Schildkraut; Madalee F Wulf; Ivan R. Corr\u00eaa Jr.; Laurence Ettwiller; Nicola Clementi; Massimo Clementi; Nicasio Mancini; Ewan Birney; Mark Akeson; Francesco Nicassio; David A Matthews; Tommaso Leonardi", + "affiliations": "Italian Institute of Technology; Italian Institute of Technology; Oxford Nanopore Technologies; Vita-Salute San Raffaele University; Vita-Salute San Raffaele University; University of Bristol; University of Bristol; University of Bristol; Istituto Italiano di Tecnologia; University of California Santa Cruz; Istituto Europeo di Oncologia; University of California Santa Cruz; New England Biolabs; New England Biolabs; New England Biolabs; New England Biolabs; New England Biolabs Inc; Vita-Salute San Raffaele University; Vita-Salute San Raffaele University; Universit\u00e0 Vita-Salute San Raffaele; European Bioinformatics Institute; University of California Santa Cruz; Istituto Italiano di Tecnologia; University of Bristol; Italian Institute of Technology", + "abstract": "The SARS-CoV-2 virus has a complex transcriptome characterised by multiple, nested sub genomic RNAs used to express structural and accessory proteins. Long-read sequencing technologies such as nanopore direct RNA sequencing can recover full-length transcripts, greatly simplifying the assembly of structurally complex RNAs. However, these techniques do not detect the 5' cap, thus preventing reliable identification and quantification of full-length, coding transcript models. Here we used Nanopore ReCappable Sequencing (NRCeq), a new technique that can identify capped full-length RNAs, to assemble a complete annotation of SARS-CoV-2 sgRNAs and annotate the location of capping sites across the viral genome. We obtained robust estimates of sgRNA expression across cell lines and viral isolates and identified novel canonical and non-canonical sgRNAs, including one that uses a previously un-annotated leader-to-body junction site. The data generated in this work constitute a useful resource for the scientific community and provide important insights into the mechanisms that regulate the transcription of SARS-CoV-2 sgRNAs.", + "category": "genomics", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.11.24.21266748", @@ -3485,20 +3513,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.09.27.21264166", - "date": "2021-09-29", - "link": "https://medrxiv.org/cgi/content/short/2021.09.27.21264166", - "title": "Prevalence and duration of detectable SARS-CoV-2 nucleocapsid antibody in staff and residents of long-term care facilities over the first year of the pandemic (VIVALDI study): prospective cohort study", - "authors": "Maria Krutikov; Tom Palmer; Gokhan Tut; Christopher Fuller; Borscha Azmi; Rebecca Giddings; Madhumita Shrotri; Nayandeep Kaur; Panagiota Sylla; Tara Lancaster; Aidan Irwin-Singer; Andrew Hayward; Paul Moss; Andrew Copas; Laura Shallcross", - "affiliations": "University College London; University College London; University of Birmingham, Medical School; University College London; University College London; University College London; University College London; University of Birmingham; University of Birmingham; University of Birmingham; Department of Health & Social Care; UCL; University of Birmingham; University College London; UCL", - "abstract": "BackgroundLong Term Care Facilities (LTCF) have reported high SARS-CoV-2 infection rates and related mortality, but the proportion infected amongst survivors and duration of the antibody response to natural infection is unknown. We determined the prevalence and stability of nucleocapsid antibodies - the standard assay for detection of prior infection - in staff and residents from 201 LTCFs.\n\nMethodsProspective cohort study of residents aged >65 years and staff of LTCFs in England (11 June 2020-7 May 2021). Serial blood samples were tested for IgG antibodies against SARS-CoV-2 nucleocapsid protein. Prevalence and cumulative incidence of antibody-positivity were weighted to the LTCF population. Cumulative incidence of sero-reversion was estimated from Kaplan-Meier curves.\n\nResults9488 samples were included, 8636 (91%) of which could be individually-linked to 1434 residents or 3288 staff members. The cumulative incidence of nucleocapsid seropositivity was 35% (95% CI: 30-40%) in residents and 26% (95% CI: 23-30%) in staff over 11 months. The incidence rate of loss of antibodies (sero-reversion) was 2{middle dot}1 per 1000 person-days at risk, and median time to reversion was around 8 months.\n\nInterpretationAt least one-quarter of staff and one-third of surviving residents were infected during the first two pandemic waves. Nucleocapsid-specific antibodies often become undetectable within the first year following infection which is likely to lead to marked underestimation of the true proportion of those with prior infection. Since natural infection may act to boost vaccine responses, better assays to identify natural infection should be developed.\n\nFundingUK Government Department of Health and Social Care.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSA search was conducted of Ovid MEDLINE and MedRxiv on 21 July 2021 to identify studies conducted in long term care facilities (LTCF) that described seroprevalence using the terms \"COVID-19\" or \"SARS-CoV-2\" and \"nursing home\" or \"care home\" or \"residential\" or \"long term care facility\" and \"antibody\" or \"serology\" without date or language restrictions. One meta-analysis was identified, published before the introduction of vaccination, that included 2 studies with a sample size of 291 which estimated seroprevalence as 59% in LTCF residents. There were 28 seroprevalence surveys of naturally-acquired SARS-CoV-2 antibodies in LTCFs; 16 were conducted in response to outbreaks and 12 conducted in care homes without known outbreaks. 16 studies included more than 1 LTCF and all were conducted in Autumn 2020 after the first wave of infection but prior to subsequent peaks. Seroprevalence studies conducted following a LTCF outbreak were biased towards positivity as the included population was known to have been previously infected. In the 12 studies that were conducted outside of known outbreaks, seroprevalence varied significantly according to local prevalence of infection. The largest of these was a cross-sectional study conducted in 9,000 residents and 10,000 staff from 362 LTCFs in Madrid, which estimated seroprevalence in staff as 31{middle dot}5% and 55{middle dot}4% in residents. However, as this study was performed in one city, it may not be generalisable to the whole of Spain and sequential sampling was not performed. Of the 28 studies, 9 undertook longitudinal sampling for a maximum of four months although three of these reported from the same cohort of LTCFs in London. None of the studies reported on antibody waning amongst the whole resident population.\n\nAdded value of this studyWe estimated the proportion of care home staff and residents with evidence of SARS-CoV-2 natural infection using data from over 3,000 staff and 1,500 residents in 201 geographically dispersed LTCFs in England. Population selection was independent of outbreak history and the sample is therefore more reflective of the population who reside and work in LTCFs. Our estimates of the proportion of residents with prior natural infection are substantially higher than estimates based on population-wide PCR testing, due to limited testing coverage at the start of the pandemic. 1361 individuals had at least one positive antibody test and participants were followed for up to 11 months, which allowed modelling of the time to loss of antibody in over 600 individuals in whom the date of primary infection could be reliably estimated. This is the longest reported serological follow up in a population of LTCF residents, a group who are known to be most at risk of severe outcomes following infection with SARS-CoV-2 and provides important evidence on the duration that nucleocapsid antibodies remained detectable over the first and second waves of the pandemic.\n\nImplications of all available researchA substantial proportion of the LTCF population will have some level of natural immunity to infection as a result of past infection. Immunological studies have highlighted greater antibody responses to vaccination in seropositive individuals, so vaccine efficacy in this population may be affected by this large pool of individuals who have survived past infection. In addition, although the presence of nucleocapsid-specific antibodies is generally considered as the standard marker for prior infection, we find that antibody waning is such that up to 50% of people will lose detectable antibody responses within eight months. Individual prior natural infection history is critical to assess the impact of factors such as vaccine response or protection against re-infection. These findings may have implications for duration of immunity following natural infection and indicate that alternative assays for prior infection should be developed.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.09.20.21263828", @@ -3513,20 +3527,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.09.16.21263684", - "date": "2021-09-22", - "link": "https://medrxiv.org/cgi/content/short/2021.09.16.21263684", - "title": "The removal of airborne SARS-CoV-2 and other microbial bioaerosols by air filtration on COVID-19 surge units", - "authors": "Andrew Conway Morris; Katherine Sharrocks; Rachel Bousfield; Leanne Kermack; Mailis Maes; Ellen Higginson; Sally Forrest; Joannna Pereira-Dias; Claire Cormie; Timothy Old; Sophie Brooks; Islam Hamed; Alicia Koenig; Andrew Turner; Paul White; R. Andres Floto; Gordon Dougan; Effrossyni Gkrania-Klotsas; Theodore Gouliouris; Stephen Baker; Vilas Navapurkar", - "affiliations": "University of Cambridge; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; University of Cambridge; University of Cambridge; Cambridge University Hospitals NHS Foundation trust; Cambridge University Hospitals NHS Foundation Trust; University of Cambridge; Cambridge University Hospitals", - "abstract": "BackgroundThe COVID-19 pandemic has overwhelmed the respiratory isolation capacity in hospitals; many wards lacking high-frequency air changes have been repurposed for managing patients infected with SARS-CoV-2 requiring either standard or intensive care. Hospital-acquired COVID-19 is a recognised problem amongst both patients and staff, with growing evidence for the relevance of airborne transmission. This study examined the effect of air filtration and ultra-violet (UV) light sterilisation on detectable airborne SARS-CoV-2 and other microbial bioaerosols.\n\nMethodsWe conducted a crossover study of portable air filtration and sterilisation devices in a repurposed surge COVID ward and surge ICU. National Institute for Occupational Safety and Health (NIOSH) cyclonic aerosol samplers and PCR assays were used to detect the presence of airborne SARS-CoV-2 and other microbial bioaerosol with and without air/UV filtration.\n\nResultsAirborne SARS-CoV-2 was detected in the ward on all five days before activation of air/UV filtration, but on none of the five days when the air/UV filter was operational; SARS-CoV-2 was again detected on four out of five days when the filter was off. Airborne SARS-CoV-2 was infrequently detected in the ICU. Filtration significantly reduced the burden of other microbial bioaerosols in both the ward (48 pathogens detected before filtration, two after, p=0.05) and the ICU (45 pathogens detected before filtration, five after p=0.05).\n\nConclusionsThese data demonstrate the feasibility of removing SARS-CoV-2 from the air of repurposed surge wards and suggest that air filtration devices may help reduce the risk of hospital-acquired SARS-CoV-2.\n\nFundingWellcome Trust, MRC, NIHR", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.09.17.21262724", @@ -3597,6 +3597,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.09.09.21263026", + "date": "2021-09-13", + "link": "https://medrxiv.org/cgi/content/short/2021.09.09.21263026", + "title": "The clinically extremely vulnerable to COVID: Identification and changes in health care while self-isolating (shielding) during the coronavirus pandemic", + "authors": "Jessica Erin Butler; Mintu Nath; Dimitra Blana; William P Ball; Nicola Beech; Corri Black; Graham Osler; Sebastien Peytrignet; Katie Wilde; Artur Wozniak; Simon Sawhney", + "affiliations": "University of Aberdeen; University of Aberdeen; University of Aberdeen; University of Aberdeen; NHS Grampian; NHS Grampian and University of Aberdeen; NHS Grampian; Health Foundation; University of Aberdeen; University of Aberdeen; NHS Grampian and University of Aberdeen", + "abstract": "BackgroundIn March 2020, the government of Scotland identified people deemed clinically extremely vulnerable to COVID due to their pre-existing health conditions. These people were advised to strictly self-isolate (shield) at the start of the pandemic, except for necessary healthcare. We examined who was identified as clinically extremely vulnerable, how their healthcare changed during isolation, and whether this process exacerbated healthcare inequalities.\n\nMethodsWe linked those on the shielding register in NHS Grampian, a health authority in Scotland, to healthcare records from 2015-2020. We described the source of identification, demographics, and clinical history of the cohort. We measured changes in out-patient, in-patient, and emergency healthcare during isolation in the shielding population and compared to the general non-shielding population.\n\nResultsThe register included 16,092 people (3% of the population), clinically vulnerable primarily due to a respiratory disease, immunosuppression, or cancer. Among them, 42% were not identified by national healthcare record screening but added ad hoc, with these additions including more children and fewer economically-deprived.\n\nDuring isolation, all forms of healthcare use decreased (25%-46%), with larger decreases in scheduled care than in emergency care. However, people shielding had better maintained scheduled care compared to the non-shielding general population: out-patient visits decreased 35% vs 49%; in-patient visits decreased 46% vs 81%. Notably, there was substantial variation in whose scheduled care was maintained during isolation: younger people and those with cancer had significantly higher visit rates, but there was no difference between sexes or socioeconomic levels.\n\nConclusionsHealthcare changed dramatically for the clinically extremely vulnerable population during the pandemic. The increased reliance on emergency care while isolating indicates that continuity of care for existing conditions was not optimal. However, compared to the general population, there was success in maintaining scheduled care, particularly in young people and those with cancer. We suggest that integrating demographic and primary care data would improve identification of the clinically vulnerable and could aid prioritising their care.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.09.03.21262888", @@ -3625,6 +3639,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.09.02.21262979", + "date": "2021-09-10", + "link": "https://medrxiv.org/cgi/content/short/2021.09.02.21262979", + "title": "Exponential growth, high prevalence of SARS-CoV-2 and vaccine effectiveness associated with Delta variant in England during May to July 2021", + "authors": "Paul Elliott; David J Haw; Haowei Wang; Oliver Eales; Caroline E Walters; Kylie E. C. Ainslie; Christina J Atchison; Claudio Fronterre; Peter Diggle; Andrew J Page; Alex Trotter; Sophie J Prosolek; - The COVID-19 Genomics UK (COG-UK) consortium; Deborah Ashby; Christl Donnelly; Wendy Barclay; Graham P Taylor; Graham Cooke; Helen Ward; Ara Darzi; Steven Riley", + "affiliations": "Imperial College London School of Public Health; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Lancaster University; Lancaster University; Quadram Institute; Quadram Institute Bioscience; Quadram Institute; The COVID-19 Genomics UK (COG-UK) consortium; Imperial College London; University of Oxford; Imperial College London; Imperial College London; Imperial College; Imperial College London; Imperial College London; Dept Inf Dis Epi, Imperial College", + "abstract": "BackgroundThe prevalence of SARS-CoV-2 infection continues to drive rates of illness and hospitalisations despite high levels of vaccination, with the proportion of cases caused by the Delta lineage increasing in many populations. As vaccination programs roll out globally and social distancing is relaxed, future SARS-CoV-2 trends are uncertain.\n\nMethodsWe analysed prevalence trends and their drivers using reverse transcription-polymerase chain reaction (RT-PCR) swab-positivity data from round 12 (between 20 May and 7 June 2021) and round 13 (between 24 June and 12 July 2021) of the REal-time Assessment of Community Transmission-1 (REACT-1) study, with swabs sent to non-overlapping random samples of the population ages 5 years and over in England.\n\nResultsWe observed sustained exponential growth with an average doubling time in round 13 of 25 days (lower Credible Interval of 15 days) and an increase in average prevalence from 0.15% (0.12%, 0.18%) in round 12 to 0.63% (0.57%, 0.18%) in round 13. The rapid growth across and within rounds appears to have been driven by complete replacement of Alpha variant by Delta, and by the high prevalence in younger less-vaccinated age groups, with a nine-fold increase between rounds 12 and 13 among those aged 13 to 17 years. Prevalence among those who reported being unvaccinated was three-fold higher than those who reported being fully vaccinated. However, in round 13, 44% of infections occurred in fully vaccinated individuals, reflecting imperfect vaccine effectiveness against infection despite high overall levels of vaccination. Using self-reported vaccination status, we estimated adjusted vaccine effectiveness against infection in round 13 of 49% (22%, 67%) among participants aged 18 to 64 years, which rose to 58% (33%, 73%) when considering only strong positives (Cycle threshold [Ct] values < 27); also, we estimated adjusted vaccine effectiveness against symptomatic infection of 59% (23%, 78%), with any one of three common COVID-19 symptoms reported in the month prior to swabbing. Sex (round 13 only), ethnicity, household size and local levels of deprivation jointly contributed to the risk of higher prevalence of swab-positivity.\n\nDiscussionFrom end May to beginning July 2021 in England, where there has been a highly successful vaccination campaign with high vaccine uptake, infections were increasing exponentially driven by the Delta variant and high infection prevalence among younger, unvaccinated individuals despite double vaccination continuing to effectively reduce transmission. Although slower growth or declining prevalence may be observed during the summer in the northern hemisphere, increased mixing during the autumn in the presence of the Delta variant may lead to renewed growth, even at high levels of vaccination.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.09.03.21263083", @@ -3723,20 +3751,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.08.19.21262231", - "date": "2021-08-24", - "link": "https://medrxiv.org/cgi/content/short/2021.08.19.21262231", - "title": "Symptoms and SARS-CoV-2 positivity in the general population in the UK", - "authors": "Karina-Doris Vihta; Koen B. Pouwels; Tim Peto; Emma Pritchard; David W. Eyre; Thomas House; Owen Gethings; Ruth Studley; Emma Rourke; Duncan Cook; Ian Diamond; Derrick Crook; Philippa C. Matthews; Nicole Stoesser; Ann Sarah Walker; - COVID-19 Infection Survey team", - "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Manchester; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; University of Oxford; University of Oxford; University of Oxford; ", - "abstract": "BackgroundSeveral community-based studies have assessed the ability of different symptoms to identify COVID-19 infections, but few have compared symptoms over time (reflecting SARS-CoV-2 variants) and by vaccination status.\n\nMethodsUsing data and samples collected by the COVID-19 Infection Survey at regular visits to representative households across the UK, we compared symptoms in new PCR-positives and comparator test-negative controls.\n\nResultsFrom 26/4/2020-7/8/2021, 27,869 SARS-CoV-2 PCR-positive episodes occurred in 27,692 participants (median 42 years (IQR 22-58)); 13,427 (48%) self-reported symptoms (\"symptomatic positive episodes\"). The comparator group comprised 3,806,692 test-negative visits (457,215 participants); 130,612 (3%) self-reported symptoms (\"symptomatic negative visit\"). Reporting of any symptoms in positive episodes varied over calendar time, reflecting changes in prevalence of variants, incidental changes (e.g. seasonal pathogens, schools re-opening) and vaccination roll-out. There was a small increase in sore throat reporting in symptomatic positive episodes and negative visits from April-2021. After May-2021 when Delta emerged there were substantial increases in headache and fever in positives, but not in negatives. Although specific symptom reporting in symptomatic positive episodes vs. negative visits varied by age, sex, and ethnicity, only small improvements in symptom-based infection detection were obtained; e.g. adding fatigue/weakness or all eight symptoms to the classic four symptoms (cough, fever, loss of taste/smell) increased sensitivity from 74% to 81% to 90% but tests per positive from 4.6 to 5.3 to 8.7.\n\nConclusionsWhilst SARS-CoV-2-associated symptoms vary by variant, vaccination status and demographics, differences are modest and do not warrant large-scale changes to targeted testing approaches given resource implications.\n\nSummaryWithin the COVID-19 Infection Survey, recruiting representative households across the UK general population, SARS-CoV-2-associated symptoms varied by viral variant, vaccination status and demographics. However, differences are modest and do not currently warrant large-scale changes to targeted testing approaches.", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.08.18.21262222", @@ -3779,20 +3793,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.08.13.21261889", - "date": "2021-08-18", - "link": "https://medrxiv.org/cgi/content/short/2021.08.13.21261889", - "title": "Robust SARS-CoV-2-specific and heterologous immune responses after natural infection in elderly residents of Long-Term Care Facilities", - "authors": "Gokhan Tut; Tara Lancaster; Megan S Butler; Panagiota Sylla; Eliska Spalkova; David Bone; Nayandeep Kaur; Christopher Bentley; Umayr Amin; Azar T Jadir; Samuel Hulme; Morenike Ayodele; Alexander C Dowell; Hayden Pearce; Sandra Margielewska-Davies; Kriti Verma; Samantha Nicol; Jusnara Begum; Elizabeth Jinks; Elif Tut; Rachel Bruton; Maria Krutikov; Madhumita Shrotri; Rebecca Giddings; Borscha Azmi; Chris Fuller; Aidan Irwin-Singer; Andrew Hayward; Andrew Copas; Laura Shallcross; Paul Moss", - "affiliations": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; Department of Health and Social Care, London, UK; Health Data Research UK; UCL Institute for Global Health, London, UK; UCL Institute of Health Informatics, London, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK", - "abstract": "Long term care facilities (LTCF) provide residential and/or nursing care support for frail and elderly people and many have suffered from a high prevalence of SARS-CoV-2 infection. Although mortality rates have been high in LTCF residents there is little information regarding the features of SARS-CoV-2-specific immunity after infection in this setting or how this may influence immunity to other infections. We studied humoral and cellular immunity against SARS-CoV-2 in 152 LTCF staff and 124 residents over a prospective 4-month period shortly after the first wave of infection and related viral serostatus to heterologous immunity to other respiratory viruses and systemic inflammatory markers. LTCF residents developed high levels of antibodies against spike protein and RBD domain which were stable over 4 months of follow up. Nucleocapsid-specific responses were also elevated in elderly donors but showed waning across all populations. Antibodies showed stable and equivalent levels of functional inhibition against spike-ACE2 binding in all age groups with comparable activity against viral variants of concern. SARS-CoV-2 seropositive donors showed high levels of antibodies to other beta-coronaviruses but serostatus did not impact humoral immunity to influenza or RSV. SARS-CoV-2-specific cellular responses were equivalent across the life course but virus-specific populations showed elevated levels of activation in older donors. LTCF residents who are survivors of SARS-CoV-2 infection thus show robust and stable immunity which does not impact responses to other seasonal viruses. These findings augur well for relative protection of LTCF residents to re-infection. Furthermore, they underlie the potent influence of previous infection on the immune response to Covid-19 vaccine which may prove to be an important determinant of future vaccine strategy.\n\nOne sentence summeryCare home residents show waning of nucleocapsid specific antibodies and enhanced expression of activation markers on SARS-CoV-2 specific cells", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.08.13.21261959", @@ -4171,6 +4171,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.07.02.21259897", + "date": "2021-07-05", + "link": "https://medrxiv.org/cgi/content/short/2021.07.02.21259897", + "title": "Anti-spike antibody response to natural SARS-CoV-2 infection in the general population", + "authors": "Jia Wei; Philippa C Matthews; Nicole Stoesser; Thomas Maddox; Luke Lorenzi; Ruth Studley; John I Bell; John N Newton; Jeremy Farrar; Ian Diamond; Emma Rourke; Alison Howarth; Brian D Marsden; Sarah Hoosdally; E Yvonne Jones; David I Stuart; Derrick W Crook; Tim E.A. Peto; Koen B. Pouwels; A. Sarah Walker; David W Eyre", + "affiliations": "University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; Office for National Statistics; Office for National Statistics; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; NIHR Oxford Biomedical Research Centre; University of Oxford; University of Oxford; University of Oxford; University of Oxford", + "abstract": "We estimated the duration and determinants of antibody response after SARS-CoV-2 infection in the general population using representative data from 7,256 United Kingdom COVID-19 infection survey participants who had positive swab SARS-CoV-2 PCR tests from 26-April-2020 to 14-June-2021. A latent class model classified 24% of participants as non-responders not developing anti-spike antibodies. These seronegative non-responders were older, had higher SARS-CoV-2 cycle threshold values during infection (i.e. lower viral burden), and less frequently reported any symptoms. Among those who seroconverted, using Bayesian linear mixed models, the estimated anti-spike IgG peak level was 7.3-fold higher than the level previously associated with 50% protection against reinfection, with higher peak levels in older participants and those of non-white ethnicity. The estimated anti-spike IgG half-life was 184 days, being longer in females and those of white ethnicity. We estimated antibody levels associated with protection against reinfection likely last 1.5-2 years on average, with levels associated with protection from severe infection present for several years. These estimates could inform planning for vaccination booster strategies.", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.06.28.21259452", @@ -4269,20 +4283,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.06.24.21259374", - "date": "2021-06-26", - "link": "https://medrxiv.org/cgi/content/short/2021.06.24.21259374", - "title": "A proteomic survival predictor for COVID-19 patients in intensive care", - "authors": "Vadim Demichev; Pinkus Tober-Lau; Tatiana Nazarenko; Simran Kaur Aulakh; Harry Whitwell; Oliver Lemke; Annika Roehl; Anja Freiwald; Mirja Mittermaier; Lukasz Szyrwiel; Daniela Ludwig; Clara Correia-Melo; Lena Lippert; Elisa T. Helbig; Paula Stubbemann; Nadine Olk; Charlotte Thibeault; Nana-Maria Gruening; Oleg Blyuss; Spyros Vernardis; Matthew White; Christoph B. Messner; Michael Joannidis; Thomas Sonnweber; Sebastian J. Klein; Alex Pizzini; Yvonne Wohlfarter; Sabina Sahanic; Richard Hilbe; Benedikt Schaefer; Sonja Wagner; Felix Machleidt; Carmen Garcia; Christoph Ruwwe-Gloesenkamp; Tilman Lingscheid; Laure Bosquillon de Jarcy; Miriam Stegemann; Moritz Pfeiffer; Linda Juergens; Sophy Denker; Daniel Zickler; Claudia Spies; Andreas Edel; Nils B. Mueller; Philipp Enghard; Aleksej Zelezniak; Rosa Bellmann-Weiler; Guenter Weiss; Archie Campbell; Caroline Hayward; David J. Porteous; Riccardo E. Marioni; Alexander Uhrig; Heinz Zoller; Judith Loeffler-Ragg; Markus A. Keller; Ivan Tancevski; John F. Timms; Alexey Zaikin; Stefan Hippenstiel; Michael Ramharter; Holger Mueller-Redetzky; Martin Witzenrath; Norbert Suttorp; Kathryn Lilley; Michael Muelleder; Leif Erik Sander; - PA-COVID- Study group; Florian Kurth; Markus Ralser", - "affiliations": "The Francis Crick Institute; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; University College London; The Francis Crick Institute; Imperial College London; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; The Francis Crick Institute; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; The Francis Crick Institute; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Lobachevsky University,; The Francis Crick Institute; The Francis Crick Institute; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; The Francis Crick Institute; Medical University of Innsbruck; Medical University of Innsbruck; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; University College London; University College London; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Bernhard Nocht Institute for Tropical Medicine; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; The University of Cambridge; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin", - "abstract": "Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Comprehensively capturing the host physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index and APACHE II score were poor predictors of survival. Plasma proteomics instead identified 14 proteins that showed concentration trajectories different between survivors and non-survivors. A proteomic predictor trained on single samples obtained at the first time point at maximum treatment level (i.e. WHO grade 7) and weeks before the outcome, achieved accurate classification of survivors in an exploratory (AUROC 0.81) as well as in the independent validation cohort (AUROC of 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that predictors derived from plasma protein levels have the potential to substantially outperform current prognostic markers in intensive care.\n\nTrial registrationGerman Clinical Trials Register DRKS00021688", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.06.21.21259254", @@ -4451,6 +4451,20 @@ "author_similarity": 97, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.06.09.21258556", + "date": "2021-06-13", + "link": "https://medrxiv.org/cgi/content/short/2021.06.09.21258556", + "title": "Safety, Immunogenicity, and Efficacy of a COVID-19 Vaccine (NVX-CoV2373) Co-administered With Seasonal Influenza Vaccines", + "authors": "Paul Heath; Seth Toback; Eva Galiza; Catherine Cosgrove; James Galloway; Anna L. Goodman; Pauline A. Swift; Sankarasubramanian Rajaram; Alison Graves-Jones; Jonathan Edelman; Fiona Burns; Angela M. Minassian; Iksung Cho; Lakshmi Kumar; Joyce S. Plested; E. Joy Rivers; Andreana Robertson; Filip Dubovsky; Greg Glenn", + "affiliations": "St Georges, University of London; Novavax; St. George's, University of London; St Georges University of London; Kings College London; Guy's and St Thomas' NHS Foundation Trust; Epsom and St. Helier University Hospitals NHS Trust; Seqirus; Seqirus; Seqirus; University College London, and Royal Free London NHS Foundation Trust; University of Oxford, and Oxford Health NHS Foundation Trust; Novavax; Novavax; Novavax; Novavax; Novavax; Novavax; Novavax", + "abstract": "BackgroundThe safety and immunogenicity profile of COVID-19 vaccines when administered concomitantly with seasonal influenza vaccines has not yet been reported.\n\nMethodsA sub-study on influenza vaccine co-administration was conducted as part of the phase 3 randomized trial of the safety and efficacy of NVX-CoV2373. The first [~]400 participants meeting main study entry criteria and with no contraindications to influenza vaccination were invited to join the sub-study. After randomization in a 1:1 ratio to receive NVX-CoV2373 (n=217) or placebo (n=214), sub-study participants received an age-appropriate, licensed, open-label influenza vaccine with dose 1 of NVX-CoV2373. Reactogenicity was evaluated via electronic diary for 7 days post-vaccination in addition to monitoring for unsolicited adverse events (AEs), medically-attended AEs (MAAEs), and serious AEs (SAEs). Influenza haemagglutination inhibition and SARS-CoV-2 anti-spike IgG assays were performed. Vaccine efficacy against PCR-confirmed, symptomatic COVID-19 was assessed. Comparisons were made between sub-study and main study participants.\n\nFindingsSub-study participants were younger, more racially diverse, and had fewer comorbid conditions than main study participants. Reactogenicity events more common in the co-administration group included tenderness (70.1% vs 57.6%) or pain (39.7% vs 29.3%) at injection site, fatigue (27.7% vs 19.4%), and muscle pain (28.3% vs 21.4%). Rates of unsolicited AEs, MAAEs, and SAEs were low and balanced between the two groups. Co-administration resulted in no change to influenza vaccine immune response, while a reduction in antibody responses to the NVX-CoV2373 vaccine was noted. Vaccine efficacy in the sub-study was 87.5% (95% CI: -0.2, 98.4) while efficacy in the main study was 89.8% (95% CI: 79.7, 95.5).\n\nInterpretationThis is the first study to demonstrate the safety, immunogenicity, and efficacy profile of a COVID-19 vaccine when co-administered with seasonal influenza vaccines. The results suggest concomitant vaccination may be a viable immunisation strategy.\n\nFundingThis study was funded by Novavax, Inc.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for research articles published from December 2019 until 1 April 2021 with no language restrictions for the terms \"SARS-CoV-2\", \"COVID-19\", \"vaccine\", \"co-administration\", and \"immunogenicity\". There were no peer-reviewed publications describing the simultaneous use of any SARS-CoV-2 vaccine and another vaccine. Several vaccine manufacturers had recent publications on phase 3 trials results (Pfizer/BioNTech, Moderna, AstraZeneca, Janssen, and the Gamaleya Research Institute of Epidemiology and Microbiology). Neither these publications nor their clinical trials protocols (when publicly available) described co-administration and they often had trial criteria specifically excluding those with recent or planned vaccination with any licenced vaccine near or at the time of any study injection.\n\nAdded value of this studyImmune interference and safety are always a concern when two vaccines are administered at the same time. This is the first study to demonstrate the safety and immunogenicity profile and clinical vaccine efficacy of a COVID-19 vaccine when co-administered with a seasonal influenza vaccine.\n\nImplications of all the available evidenceThis study provides much needed information to help guide national immunisation policy decision making on the critical issue of concomitant use of COVID-19 vaccines with influenza vaccines.", + "category": "allergy and immunology", + "match_type": "fuzzy", + "author_similarity": 95, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.06.08.21258533", @@ -5039,20 +5053,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.04.08.21255100", - "date": "2021-04-15", - "link": "https://medrxiv.org/cgi/content/short/2021.04.08.21255100", - "title": "REACT-1 round 10 report: Level prevalence of SARS-CoV-2 swab-positivity in England during third national lockdown in March 2021", - "authors": "Steven Riley; Oliver Eales; David Haw; Caroline E. Walters; Haowei Wang; Kylie E. C. Ainslie; Christina Atchinson; Claudio Fronterre; Peter J. Diggle; Deborah Ashby; Christl A Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott", - "affiliations": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear", - "abstract": "BackgroundIn England, hospitalisations and deaths due to SARS-CoV-2 have been falling consistently since January 2021 during the third national lockdown of the COVID-19 pandemic. The first significant relaxation of that lockdown occurred on 8 March when schools reopened.\n\nMethodsThe REal-time Assessment of Community Transmission-1 (REACT-1) study augments routine surveillance data for England by measuring swab-positivity for SARS-CoV-2 in the community. The current round, round 10, collected swabs from 11 to 30 March 2021 and is compared here to round 9, in which swabs were collected from 4 to 23 February 2021.\n\nResultsDuring round 10, we estimated an R number of 1.00 (95% confidence interval 0.81, 1.21). Between rounds 9 and 10 we estimated national prevalence has dropped by [~]60% from 0.49% (0.44%, 0.55%) in February to 0.20% (0.17%, 0.23%) in March. There were substantial falls in weighted regional prevalence: in South East from 0.36% (0.29%, 0.44%) in round 9 to 0.07% (0.04%, 0.12%) in round 10; London from 0.60% (0.48%, 0.76%) to 0.16% (0.10%, 0.26%); East of England from 0.47% (0.36%, 0.60%) to 0.15% (0.10%, 0.24%); East Midlands from 0.59% (0.45%, 0.77%) to 0.19% (0.13%, 0.28%); and North West from 0.69% (0.54%, 0.88%) to 0.31% (0.21%, 0.45%). Areas of apparent higher prevalence remain in parts of the North West, and Yorkshire and The Humber. The highest prevalence in March was found among school-aged children 5 to 12 years at 0.41% (0.27%, 0.62%), compared with the lowest in those aged 65 to 74 and 75 and over at 0.09% (0.05%, 0.16%). The close approximation between prevalence of infections and deaths (suitably lagged) is diverging, suggesting that infections may have resulted in fewer hospitalisations and deaths since the start of widespread vaccination.\n\nConclusionWe report a sharp decline in prevalence of infections between February and March 2021. We did not observe an increase in the prevalence of SARS-CoV-2 following the reopening of schools in England, although the decline of prevalence appears to have stopped. Future rounds of REACT-1 will be able to measure the rate of growth or decline from this current plateau and hence help assess the effectiveness of the vaccination roll-out on transmission of the virus as well as the potential size of any third wave during the ensuing months.", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.04.08.21255099", @@ -5501,6 +5501,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.03.10.21253173", + "date": "2021-03-12", + "link": "https://medrxiv.org/cgi/content/short/2021.03.10.21253173", + "title": "High household transmission of SARS-CoV-2 in the United States: living density, viral load, and disproportionate impact on communities of color", + "authors": "Carla Cerami; Tyler Rapp; Feng-Chang Lin; Kathleen Tompkins; Christopher Basham; Meredith Smith Muller; Maureen Whittelsey; Haoming Zhang; Srijana Bhattarai Chhetri; Judy Smith; Christy Litel; Kelly Lin; Mehal Churiwal; Salman Khan; Faith Claman; Rebecca Rubinstein; Katie Mollan; David Wohl; Lakshmanane Premkumar; Jonathan J. Juliano; Jessica T Lin", + "affiliations": "MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; University of North Carolina School of Medicine; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA", + "abstract": "BackgroundFew prospective studies of SARS-CoV-2 transmission within households have been reported from the United States, where COVID-19 cases are the highest in the world and the pandemic has had disproportionate impact on communities of color.\n\nMethods and FindingsThis is a prospective observational study. Between April-October 2020, the UNC CO-HOST study enrolled 102 COVID-positive persons and 213 of their household members across the Piedmont region of North Carolina, including 45% who identified as Hispanic/Latinx or non-white. Households were enrolled a median of 6 days from onset of symptoms in the index case. Secondary cases within the household were detected either by PCR of a nasopharyngeal (NP) swab on study day 1 and weekly nasal swabs (days 7, 14, 21) thereafter, or based on seroconversion by day 28. After excluding household contacts exposed at the same time as the index case, the secondary attack rate (SAR) among susceptible household contacts was 60% (106/176, 95% CI 53%-67%). The majority of secondary cases were already infected at study enrollment (73/106), while 33 were observed during study follow-up. Despite the potential for continuous exposure and sequential transmission over time, 93% (84/90, 95% CI 86%-97%) of PCR-positive secondary cases were detected within 14 days of symptom onset in the index case, while 83% were detected within 10 days. Index cases with high NP viral load (>10^6 viral copies/ul) at enrollment were more likely to transmit virus to household contacts during the study (OR 4.9, 95% CI 1.3-18 p=0.02). Furthermore, NP viral load was correlated within families (ICC=0.44, 95% CI 0.26-0.60), meaning persons in the same household were more likely to have similar viral loads, suggesting an inoculum effect. High household living density was associated with a higher risk of secondary household transmission (OR 5.8, 95% CI 1.3-55) for households with >3 persons occupying <6 rooms (SAR=91%, 95% CI 71-98%). Index cases who self-identified as Hispanic/Latinx or non-white were more likely to experience a high living density and transmit virus to a household member, translating into an SAR in minority households of 70%, versus 52% in white households (p=0.05).\n\nConclusionsSARS-CoV-2 transmits early and often among household members. Risk for spread and subsequent disease is elevated in high-inoculum households with limited living space. Very high infection rates due to household crowding likely contribute to the increased incidence of SARS-CoV-2 infection and morbidity observed among racial and ethnic minorities in the US. Quarantine for 14 days from symptom onset of the first case in the household is appropriate to prevent onward transmission from the household. Ultimately, primary prevention through equitable distribution of effective vaccines is of paramount importance.\n\nAUTHORS SUMMARYO_ST_ABSWhy was this study done?C_ST_ABSO_LIUnderstanding the secondary attack rate and the timing of transmission of SARS-CoV-2 within households is important to determine the role of household transmission in the larger pandemic and to guide public health policies about quarantine.\nC_LIO_LIProspective studies looking at the determinants of household transmission are sparse, particularly studies including substantial racial and ethnic minorities in the United States and studies with adequate follow-up to detect sequential transmission events.\nC_LIO_LIIdentifying individuals at high risk of transmitting and acquiring SARS-CoV-2 will inform strategies for reducing transmission in the household, or reducing disease in those exposed.\nC_LI\n\nWhat did the researchers do and find?O_LIBetween April-November 2020, the UNC CO-HOST study enrolled 102 households across the Piedmont region of North Carolina, including 45% with an index case who identified as racial or ethnic minorities.\nC_LIO_LIOverall secondary attack rate was 60% with two-thirds of cases already infected at study enrollment.\nC_LIO_LIDespite the potential for sequential transmission in the household, the majority of secondary cases were detected within 10 days of symptom onset of the index case.\nC_LIO_LIViral loads were correlated within families, suggesting an inoculum effect.\nC_LIO_LIHigh viral load in the index case was associated with a greater likelihood of household transmission.\nC_LIO_LISpouses/partners of the COVID-positive index case and household members with obesity were at higher risk of becoming infected.\nC_LIO_LIHigh household living density contributed to an increased risk of household transmission.\nC_LIO_LIRacial/ethnic minorities had an increased risk of acquiring SARS-CoV-2 in their households in comparison to members of the majority (white) racial group.\nC_LI\n\nWhat do these findings mean?O_LIHousehold transmission often occurs quickly after a household member is infected.\nC_LIO_LIHigh viral load increases the risk of transmission.\nC_LIO_LIHigh viral load cases cluster within households - suggesting high viral inoculum in the index case may put the whole household at risk for more severe disease.\nC_LIO_LIIncreased household density may promote transmission within racial and ethnic minority households.\nC_LIO_LIEarly at-home point-of-care testing, and ultimately vaccination, is necessary to effectively decrease household transmission.\nC_LI", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 92, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.03.11.21253189", @@ -6733,20 +6747,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.11.23.20237313", - "date": "2020-11-24", - "link": "https://medrxiv.org/cgi/content/short/2020.11.23.20237313", - "title": "Identifying optimal combinations of symptoms to trigger diagnostic work-up of suspected COVID-19 cases in vaccine trials: analysis from a community-based, prospective, observational cohort", - "authors": "Michela Antonelli; Joan Capdevila; Amol Chaudhari; Julia Granerod; Liane S Canas; Mark S Graham; Kerstin Klaser; Marc Modat; Erika Molteni; Ben Murray; Carole H Sudre; Richard Davies; Anna May; Long H Nguyen; David A Drew; Amit Joshi; Andrew T Chan; Jakob Cramer; Tim Spector; Jonathan Wolf; Sebastien Ourselin; Claire J Steves; Alfred E Loeliger", - "affiliations": "King's College London; Zoe Global; Coalition for Epidemic Preparedness Innovations; Coalition for Epidemic Preparedness Innovations; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; University College London; Zoe Global; Zoe Global; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Coalition for Epidemic Preparedness Innovations; King's College London; Zoe Global; King's College London; King's College London; Coalition for Epidemic Preparedness Innovations", - "abstract": "ObjectivesDiagnostic work-up following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify optimal symptom combinations to capture most cases using fewer tests with implications for COVID-19 vaccine developers across different resource settings and public health.\n\nMethodsUK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms and an RT-PCR test within seven days of symptom onset were included. Sensitivity, specificity, and number of RT-PCR tests needed to identify one case (test per case [TPC]) were calculated for different symptom combinations. A multi-objective evolutionary algorithm was applied to generate combinations with optimal trade-offs between sensitivity and specificity.\n\nFindingsUK and US cohorts included 122,305 (1,202 positives) and 3,162 (79 positive) individuals. Within three days of symptom onset, the COVID-19 specific symptom combination (cough, dyspnoea, fever, anosmia/ageusia) identified 69% of cases requiring 47 TPC. The combination with highest sensitivity (fatigue, anosmia/ageusia, cough, diarrhoea, headache, sore throat) identified 96% cases requiring 96 TPC.\n\nInterpretationWe confirmed the significance of COVID-19 specific symptoms for triggering RT-PCR and identified additional symptom combinations with optimal trade-offs between sensitivity and specificity that maximize case capture given different resource settings.\n\nHighlightsO_LIWidely recommended symptoms identified only [~]70% COVID-19 cases\nC_LIO_LIAdditional symptoms increased case finding to > 90% but tests needed doubled\nC_LIO_LIOptimal symptom combinations maximise case capture considering available resources\nC_LIO_LIImplications for COVID-19 vaccine efficacy trials and wider public health\nC_LI", - "category": "health informatics", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.11.19.20234120", @@ -7013,20 +7013,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.11.02.20224824", - "date": "2020-11-04", - "link": "https://medrxiv.org/cgi/content/short/2020.11.02.20224824", - "title": "The duration, dynamics and determinants of SARS-CoV-2 antibody responses in individual healthcare workers", - "authors": "Sheila F Lumley; Jia Wei; Nicole Stoesser; Philippa Matthews; Alison Howarth; Stephanie Hatch; Brian Marsden; Stuart Cox; Tim James; Liam Peck; Thomas Ritter; Zoe de Toledo; Richard Cornall; E Yvonne Jones; David I Stuart; Gavin Screaton; Daniel Ebner; Sarah Hoosdally; Derrick Crook; - Oxford University Hospitals Staff Testing Group; Christopher P Conlon; Koen Pouwels; Ann Sarah Walker; Tim EA Peto; Timothy M Walker; Katie Jeffery; David W Eyre", - "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; Oxford University Hospitals; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; ; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; University of Oxford", - "abstract": "BackgroundSARS-CoV-2 IgG antibody measurements can be used to estimate the proportion of a population exposed or infected and may be informative about the risk of future infection. Previous estimates of the duration of antibody responses vary.\n\nMethodsWe present 6 months of data from a longitudinal seroprevalence study of 3217 UK healthcare workers (HCWs). Serial measurements of IgG antibodies to SARS-CoV-2 nucleocapsid were obtained. Bayesian mixed linear models were used to investigate antibody waning and associations with age, gender, ethnicity, previous symptoms and PCR results.\n\nResultsIn this cohort of working age HCWs, antibody levels rose to a peak at 24 (95% credibility interval, CrI 19-31) days post-first positive PCR test, before beginning to fall. Considering 452 IgG seropositive HCWs over a median of 121 days (maximum 171 days) from their maximum positive IgG titre, the mean estimated antibody half-life was 85 (95%CrI, 81-90) days. The estimated mean time to loss of a positive antibody result was 137 (95%CrI 127-148) days. We observed variation between individuals; higher maximum observed IgG titres were associated with longer estimated antibody half-lives. Increasing age, Asian ethnicity and prior self-reported symptoms were independently associated with higher maximum antibody levels, and increasing age and a positive PCR test undertaken for symptoms with longer antibody half-lives.\n\nConclusionIgG antibody levels to SARS-CoV-2 nucleocapsid wane within months, and faster in younger adults and those without symptoms. Ongoing longitudinal studies are required to track the long-term duration of antibody levels and their association with immunity to SARS-CoV-2 reinfection.\n\nSummarySerially measured SARS-CoV-2 anti-nucleocapsid IgG titres from 452 seropositive healthcare workers demonstrate levels fall by half in 85 days. From a peak result, detectable antibodies last a mean 137 days. Levels fall faster in younger adults and following asymptomatic infection.", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.10.28.20221804", @@ -7195,20 +7181,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.10.26.20219550", - "date": "2020-10-27", - "link": "https://medrxiv.org/cgi/content/short/2020.10.26.20219550", - "title": "Human movement can inform the spatial scale of interventions against COVID-19 transmission", - "authors": "Hamish Gibbs; Emily Nightingale; Yang Liu; James Cheshire; Leon Danon; Liam Smeeth; Carl AB Pearson; Chris Grundy; - LSHTM CMMID COVID-19 Working Group; Adam J Kucharski; Rosalind M Eggo", - "affiliations": "London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University College London; University of Exeter; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; ; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine", - "abstract": "BackgroundIn 2020, the UK enacted an intensive, nationwide lockdown on March 23 to mitigate transmission of COVID-19. As restrictions began to ease, resurgences in transmission were targeted by geographically-limited interventions of various stringencies. Understanding the spatial scale of networks of human interaction, and how these networks change over time, is critical to inform interventions targeted at the most at-risk areas without unnecessarily restricting areas at low risk of resurgence.\n\nMethodsWe use detailed human mobility data aggregated from Facebook users to determine how the spatially-explicit network of movements changed before and during the lockdown period, in response to the easing of restrictions, and to the introduction of locally-targeted interventions. We also apply community detection techniques to the weighted, directed network of movements to identify geographically-explicit movement communities and measure the evolution of these community structures through time.\n\nFindingsWe found that the mobility network became more sparse and the number of mobility communities decreased under the national lockdown, a change that disproportionately affected long distance journeys central to the mobility network. We also found that the community structure of areas in which locally-targeted interventions were implemented following epidemic resurgence did not show reorganization of community structure but did show small decreases in indicators of travel outside of local areas.\n\nInterpretationWe propose that communities detected using Facebook or other mobility data be used to assess the impact of spatially-targeted restrictions and may inform policymakers about the spatial extent of human movement patterns in the UK. These data are available in near real-time, allowing quantification of changes in the distribution of the population across the UK, as well as changes in travel patterns to inform our understanding of the impact of geographically-targeted interventions.\n\nPutting Research Into ContextO_ST_ABSEvidence before this studyC_ST_ABSLarge-scale intensive interventions in response to the COVID-19 pandemic have been implemented globally, significantly affecting human movement patterns. Mobility data show spatially-explicit network structure, but it is not clear how that structure changed in response to national or locally-targeted interventions.\n\nAdded value of this studyWe used daily mobility data aggregated from Facebook users to quantify changes in the travel network in the UK during the national lockdown, and in response to local interventions. We identified changes in human behaviour in response to interventions and identified the community structure inherent in these networks. This approach to understanding changes in the travel network can help quantify the extent of strongly connected communities of interaction and their relationship to the extent of spatially-explicit interventions.\n\nImplications of all the available evidenceWe show that spatial mobility data available in near real-time can give information on connectivity that can be used to understand the impact of geographically-targeted interventions and in the future, to inform spatially-targeted intervention strategies.\n\nData SharingData used in this study are available from the Facebook Data for Good Partner Program by application. Code and supplementary information for this paper are available online (https://github.com/hamishgibbs/facebook_mobility_uk), alongside publication.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.10.26.20219642", @@ -7323,32 +7295,46 @@ }, { "site": "medRxiv", - "doi": "10.1101/2020.10.12.20211227", + "doi": "10.1101/2020.10.11.20210658", "date": "2020-10-14", - "link": "https://medrxiv.org/cgi/content/short/2020.10.12.20211227", - "title": "High and increasing prevalence of SARS-CoV-2 swab positivity in England during end September beginning October 2020: REACT-1 round 5 updated report", - "authors": "Steven Riley; Kylie E. C. Ainslie; Oliver Eales; Caroline E Walters; Haowei Wang; Christina J Atchison; Claudio Fronterre; Peter J Diggle; Deborah Ashby; Christl A. Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott", - "affiliations": "Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Lancaster University; Lancaster University; Imperial College London; Imperial College London; Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London School of Public Health", - "abstract": "BackgroundREACT-1 is quantifying prevalence of SARS-CoV-2 infection among random samples of the population in England based on PCR testing of self-administered nose and throat swabs. Here we report results from the fifth round of observations for swabs collected from the 18th September to 5th October 2020. This report updates and should be read alongside our round 5 interim report.\n\nMethodsRepresentative samples of the population aged 5 years and over in England with sample size ranging from 120,000 to 175,000 people at each round. Prevalence of PCR-confirmed SARS-CoV-2 infection, estimation of reproduction number (R) and time trends between and within rounds using exponential growth or decay models.\n\nResults175,000 volunteers tested across England between 18th September and 5th October. Findings show a national prevalence of 0.60% (95% confidence interval 0.55%, 0.71%) and doubling of the virus every 29 (17, 84) days in England corresponding to an estimated national R of 1.16 (1.05, 1.27). These results correspond to 1 in 170 people currently swab-positive for the virus and approximately 45,000 new infections each day. At regional level, the highest prevalence is in the North West, Yorkshire and The Humber and the North East with strongest regional growth in North West, Yorkshire and The Humber and West Midlands.\n\nConclusionRapid growth has led to high prevalence of SARS-CoV-2 virus in England, with highest rates in the North of England. Prevalence has increased in all age groups, including those at highest risk. Improved compliance with existing policy and, as necessary, additional interventions are required to control the spread of SARS-CoV-2 in the community and limit the numbers of hospital admissions and deaths from COVID-19.", - "category": "infectious diseases", + "link": "https://medrxiv.org/cgi/content/short/2020.10.11.20210658", + "title": "What is the evidence for transmission of COVID-19 by children in schools? A living systematic review", + "authors": "Wei Xu; Xue Li; Marshall Dozier; Yazhou He; Amir Kirolos; Zhongyu Lang; Catherine Mathews; Nandi Siegfried; Evropi Theodoratou", + "affiliations": "University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; South African Medical Research Council; South African Medical Research Council; University of Edinburgh", + "abstract": "BackgroundIt is of paramount importance to understand the transmission of SARS-CoV-2 in schools, which could support the decision-making about educational facilities closure or re-opening with effective prevention and control measures in place.\n\nMethodsWe conducted a systematic review and meta-analysis to investigate the extent of SARS-CoV-2 transmission in schools. We performed risk of bias evaluation of all included studies using the Newcastle-Ottawa Scale (NOS).\n\nResults2,178 articles were retrieved and 11 studies were included. Five cohort studies reported a combined 22 student and 21 staff index cases that exposed 3,345 contacts with 18 transmissions [overall infection attack rate (IAR): 0.08% (95% CI: 0.00%-0.86%)]. IARs for students and school staff were 0.15% (95% CI: 0.00%-0.93%) and 0.70% (95% CI: 0.00%-3.56%) respectively. Six cross-sectional studies reported 639 SARS-CoV-2 positive cases in 6,682 study participants tested [overall SARS-CoV-2 positivity rate: 8.00% (95% CI: 2.17%-16.95%)]. SARS-CoV-2 positivity rate was estimated to be 8.74% (95% CI: 2.34%-18.53%) among students, compared to 13.68% (95% CI: 1.68%-33.89%) among school staff. Gender differences were not found for secondary infection (OR: 1.44, 95% CI: 0.50-4.14, P= 0.49) and SARS-CoV-2 positivity (OR: 0.90, 95% CI: 0.72-1.13, P= 0.36) in schools. Fever, cough, dyspnea, ageusia, anosmia, rhinitis, sore throat, headache, myalgia, asthenia, and diarrhoea were all associated with the detection of SARS-CoV-2 antibodies (based on two studies). Overall, study quality was judged to be poor with risk of performance and attrition bias, limiting the confidence in the results.\n\nConclusionsThere is limited high-quality evidence available to quantify the extent of SARS-CoV-2 transmission in schools or to compare it to community transmission. Emerging evidence suggests lower IAR and SARS-CoV-2 positivity rate in students compared to school staff. Future prospective and adequately controlled cohort studies are necessary to confirm this finding.", + "category": "epidemiology", "match_type": "fuzzy", "author_similarity": 100, "affiliation_similarity": 100 }, { "site": "medRxiv", - "doi": "10.1101/2020.10.11.20210658", + "doi": "10.1101/2020.10.13.20211813", "date": "2020-10-14", - "link": "https://medrxiv.org/cgi/content/short/2020.10.11.20210658", - "title": "What is the evidence for transmission of COVID-19 by children in schools? A living systematic review", - "authors": "Wei Xu; Xue Li; Marshall Dozier; Yazhou He; Amir Kirolos; Zhongyu Lang; Catherine Mathews; Nandi Siegfried; Evropi Theodoratou", - "affiliations": "University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; South African Medical Research Council; South African Medical Research Council; University of Edinburgh", - "abstract": "BackgroundIt is of paramount importance to understand the transmission of SARS-CoV-2 in schools, which could support the decision-making about educational facilities closure or re-opening with effective prevention and control measures in place.\n\nMethodsWe conducted a systematic review and meta-analysis to investigate the extent of SARS-CoV-2 transmission in schools. We performed risk of bias evaluation of all included studies using the Newcastle-Ottawa Scale (NOS).\n\nResults2,178 articles were retrieved and 11 studies were included. Five cohort studies reported a combined 22 student and 21 staff index cases that exposed 3,345 contacts with 18 transmissions [overall infection attack rate (IAR): 0.08% (95% CI: 0.00%-0.86%)]. IARs for students and school staff were 0.15% (95% CI: 0.00%-0.93%) and 0.70% (95% CI: 0.00%-3.56%) respectively. Six cross-sectional studies reported 639 SARS-CoV-2 positive cases in 6,682 study participants tested [overall SARS-CoV-2 positivity rate: 8.00% (95% CI: 2.17%-16.95%)]. SARS-CoV-2 positivity rate was estimated to be 8.74% (95% CI: 2.34%-18.53%) among students, compared to 13.68% (95% CI: 1.68%-33.89%) among school staff. Gender differences were not found for secondary infection (OR: 1.44, 95% CI: 0.50-4.14, P= 0.49) and SARS-CoV-2 positivity (OR: 0.90, 95% CI: 0.72-1.13, P= 0.36) in schools. Fever, cough, dyspnea, ageusia, anosmia, rhinitis, sore throat, headache, myalgia, asthenia, and diarrhoea were all associated with the detection of SARS-CoV-2 antibodies (based on two studies). Overall, study quality was judged to be poor with risk of performance and attrition bias, limiting the confidence in the results.\n\nConclusionsThere is limited high-quality evidence available to quantify the extent of SARS-CoV-2 transmission in schools or to compare it to community transmission. Emerging evidence suggests lower IAR and SARS-CoV-2 positivity rate in students compared to school staff. Future prospective and adequately controlled cohort studies are necessary to confirm this finding.", + "link": "https://medrxiv.org/cgi/content/short/2020.10.13.20211813", + "title": "Precautionary breaks: planned, limited duration circuit breaks to control the prevalence of COVID-19", + "authors": "Matt J Keeling; Glen Guyver-Fletcher; Alexander Holmes; Louise J Dyson; Michael Tildesley; Edward M Hill; Graham F Medley", + "affiliations": "University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; London School of Hygiene and Tropical Medicine", + "abstract": "The COVID-19 pandemic in the UK has been characterised by periods of exponential growth and decline, as different non-pharmaceutical interventions (NPIs) are brought into play. During the early uncontrolled phase of the outbreak (early March 2020) there was a period of prolonged exponential growth with epidemiological observations such as hospitalisation doubling every 3-4 days (growth rate r {approx} 0.2). The enforcement of strict lockdown measures led to a noticeable decline in all epidemic quantities (r {approx} -0.06) that slowed during the summer as control measures were relaxed (r {approx} -0.02). Since August, infections, hospitalisations and deaths have been rising (precise estimation of the current growth rate is difficult due to extreme regional heterogeneity and temporal lags between the different epidemiological observations) and various NPIs have been applied locally throughout the UK in response.\n\nControlling any rise in infection is a compromise between public health and societal costs, with more stringent NPIs reducing cases but damaging the economy and restricting freedoms. Currently, NPI imposition is made in response to the epidemiological state, are of indefinite length and are often imposed at short notice, greatly increasing the negative impact. An alternative approach is to consider planned, limited duration periods of strict NPIs aiming to purposefully reduce prevalence before such emergency NPIs are required. These \"precautionary breaks\" may offer a means of keeping control of the epidemic, while their fixed duration and the forewarning may limit their society impact. Here, using simple analysis and age-structured models matched to the unfolding UK epidemic, we investigate the action of precautionary breaks. In particular we consider their impact on the prevalence of infection, as well as the total number of predicted hospitalisations and deaths. We find that precautionary breaks provide the biggest gains when the growth rate is low, but offer a much needed brake on increasing infection when the growth rate is higher, potentially allowing other measures (such as contact tracing) to regain control.", "category": "epidemiology", "match_type": "fuzzy", "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.10.11.20210625", + "date": "2020-10-13", + "link": "https://medrxiv.org/cgi/content/short/2020.10.11.20210625", + "title": "Mental health service activity during COVID-19 lockdown among individuals with learning disabilities: South London and Maudsley data on services and mortality from January to July 2020", + "authors": "Evangelia Martin; Eleanor Nuzum; Matthew Broadbent; Robert Stewart", + "affiliations": "King's College London; King's College London; South London and Maudsley NHS Foundation Trust; King's College London", + "abstract": "The lockdown and social distancing policy imposed due to the COVID-19 pandemic is likely to have had a widespread impact on mental healthcare service provision and use. Previous reports from the South London and Maudsley NHS Trust (SLaM; a large mental health service provider for 1.2m residents in South London) highlighted a shift to virtual contacts among those accessing community mental health and home treatment teams and an increase in deaths over the pandemics first wave. However, there is a need to quantify this for individuals with particular vulnerabilities, including those with learning disabilities and other neurodevelopmental disorders. Taking advantage of the Clinical Record Interactive Search (CRIS) data resource with 24-hourly updates of electronic mental health records data, this paper describes daily caseloads and contact numbers (face-to-face and virtual) for individuals with potential neurodevelopmental disorders across community, specialist, crisis and inpatient services. The report focussed on the period 1st January to 31st July 2020. We also report on daily accepted and discharged trust referrals, total trust caseloads and daily inpatient admissions and discharges for individuals with potential neurodevelopmental disorders. In addition, daily deaths are described for all current and previous SLaM service users with potential neurodevelopmental disorders over this period. In summary, comparing periods before and after 16th March 2020 there was a shift from face-to-face contacts to virtual contacts across all teams. The largest declines in caseloads and total contacts were seen in Home Treatment Team, Liaison/A&E and Older Adult teams. Reduced accepted referrals and inpatient admissions were observed and there was an 103% increase in average daily deaths in the period after 16th March, compared to the period 1st January to 15th March (or a 282% increase if the 2-month period from 16th March to 15th May was considered alone).", + "category": "psychiatry and clinical psychology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.10.08.20209411", @@ -7547,16 +7533,16 @@ }, { "site": "medRxiv", - "doi": "10.1101/2020.09.22.20194183", - "date": "2020-09-24", - "link": "https://medrxiv.org/cgi/content/short/2020.09.22.20194183", - "title": "Modelling optimal vaccination strategy for SARS-CoV-2.", - "authors": "Sam Moore; Edward M Hill; Louise Dyson; Michael Tildesley; Matt J Keeling", - "affiliations": "University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick", - "abstract": "The COVID-19 outbreak has highlighted our vulnerability to novel infections. Faced with this threat and no effective treatment, in line with many other countries, the UK adopted enforced social distancing (lockdown) to reduce transmission- successfully reducing the reproductive number, R, below one. However, given the large pool of susceptible individuals that remain, complete relaxation of controls is likely to generate a substantial second wave. Vaccination remains the only foreseeable means of both containing the infection and returning to normal interactions and behaviour. Here, we consider the optimal targeting of vaccination within the UK, with the aim of minimising future deaths or quality adjusted life year (QALY) losses. We show that, for a range of assumptions on the action and efficacy of the vaccine, targeting older age groups first is optimal and can avoid a second wave if the vaccine prevents transmission as well as disease.", - "category": "epidemiology", + "doi": "10.1101/2020.09.22.20199661", + "date": "2020-09-23", + "link": "https://medrxiv.org/cgi/content/short/2020.09.22.20199661", + "title": "Risk of adverse COVID-19 outcomes for people living with HIV: a rapid review and meta-analysis", + "authors": "Maya Mellor; Anne Bast; Nicholas Jones; Nia Roberts; Jose Ordonez-Mena; Alastair Reith; Christopher C Butler; Philippa C Matthews; Jienchi Dorward", + "affiliations": "Medical Sciences Division, University of Oxford, Oxford, UK; Medical Sciences Division, University of Oxford, Oxford, UK; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK; Outreach Librarian Knowledge Centre, Bodleian Health Care Libraries, Oxford, UK; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK and NIHR Biomedical Research Centre, Oxford University Hospitals NHS Found; Medical Sciences Division, University of Oxford, Oxford, UK; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.; Nuffield Department of Medicine, University of Oxford, Oxford, UK and Department of Infectious Diseases and Microbiology, Oxford University Hospitals NHS Founda; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK and Centre for the AIDS Programme of Research in South Africa, University ", + "abstract": "ObjectiveTo assess whether people living with HIV (PLWH) are at increased risk of COVID-19 mortality or adverse outcomes, and whether antiretroviral therapy (ART) influences this risk.\n\nDesignRapid review with meta-analysis and narrative synthesis.\n\nMethodsWe searched databases including Embase, Medline, medRxiv, and Google Scholar up to 26th August 2020 for studies describing COVID-19 outcomes in PLWH and conducted a meta-analysis of higher quality studies.\n\nResultsWe identified 1,908 studies and included 19 in the review. In a meta-analysis of five studies, PLWH had a higher risk of COVID-19 mortality (hazard ratio (HR) 1.93, 95% Confidence Interval (CI): 1.59-2.34) compared to people without HIV. Risk of death remained elevated for PLWH in a subgroup analysis of hospitalised cohorts (HR 1.54, 95% CI: 1.05-2.24) and studies of PLWH across all settings (HR 2.08, 95%CI: 1.69-2.56). Eight other studies assessed the association between HIV and COVID-19 outcomes, but provided inconclusive, lower-quality evidence due to potential confounding and selection bias.\n\nThere were insufficient data on the effect of CD4+ T cell count and HIV viral load on COVID-19 outcomes. Eleven studies reported COVID-19 outcomes by ART-regimen. In the two largest studies, tenofovir-disoproxil-fumarate (TDF)-based regimens were associated with a lower risk of adverse COVID-19 outcomes, although these analyses are susceptible to confounding by comorbidities.\n\nConclusionEvidence is emerging that suggests a moderately increased risk of COVID-19 mortality amongst PLWH. Further investigation into the relationship between COVID-19 outcomes and CD4+ T cell count, HIV viral load, ART and the use of TDF is warranted.", + "category": "hiv aids", "match_type": "fuzzy", - "author_similarity": 100, + "author_similarity": 91, "affiliation_similarity": 100 }, { @@ -7741,6 +7727,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.09.02.20185892", + "date": "2020-09-07", + "link": "https://medrxiv.org/cgi/content/short/2020.09.02.20185892", + "title": "Prognostic accuracy of emergency department triage tools for adults with suspected COVID-19: The PRIEST observational cohort study", + "authors": "Ben Thomas; Steve Goodacre; Ellen Lee; Laura Sutton; Amanda Loban; Simon Waterhouse; Richard Simmonds; Katie Biggs; Carl Marincowitz; Jose Schutter; Sarah Connelly; Elena Sheldon; Jamie Hall; Emma Young; Andrew Bentley; Kirsty Challen; Chris Fitzsimmons; Tim Harris; Fiona Lecky; Andrew Lee; Ian Maconochie; Darren Walter", + "affiliations": "University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; Manchester University NHS Foundation Trust; Lancashire Teaching Hospitals NHS Foundation Trust; Sheffield Children's NHS Foundation Trust; Barts Health NHS Trust; University of Sheffield; University of Sheffield; Imperial College Healthcare NHS Trust; Manchester University NHS Foundation Trust", + "abstract": "ObjectivesThe World Health Organisation (WHO) and National Institute for Health and Care Excellence (NICE) recommend various triage tools to assist decision-making for patients with suspected COVID-19. We aimed to estimate the accuracy of triage tools for predicting severe illness in adults presenting to the emergency department (ED) with suspected COVID-19 infection.\n\nMethodsWe undertook a mixed prospective and retrospective observational cohort study in 70 EDs across the United Kingdom (UK). We collected data from people attending with suspected COVID-19 between 26 March 2020 and 28 May 2020, and used presenting data to determine the results of assessment with the following triage tools: the WHO algorithm, NEWS2, CURB-65, CRB-65, PMEWS and the swine flu adult hospital pathway (SFAHP). We used 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome.\n\nResultsWe analysed data from 20892 adults, of whom 4672 (22.4%) died or received organ support (primary outcome), with 2058 (9.9%) receiving organ support and 2614 (12.5%) dying without organ support (secondary outcomes). C-statistics for the primary outcome were: CURB-65 0.75; CRB-65 0.70; PMEWS 0.77; NEWS2 (score) 0.77; NEWS2 (rule) 0.69; SFAHP (6-point) 0.70; SFAHP (7-point) 0.68; WHO algorithm 0.61. All triage tools showed worse prediction for receipt of organ support and better prediction for death without organ support.\n\nAt the recommended threshold, PMEWS and the WHO criteria showed good sensitivity (0.96 and 0.95 respectively), at the expense of specificity (0.31 and 0.27 respectively). NEWS2 showed similar sensitivity (0.96) and specificity (0.28) when a lower threshold than recommended was used.\n\nConclusionCURB-65, PMEWS and NEWS2 provide good but not excellent prediction for adverse outcome in suspected COVID-19, and predicted death without organ support better than receipt of organ support. PMEWS, the WHO criteria and NEWS2 (using a lower threshold than usually recommended) provide good sensitivity at the expense of specificity.\n\nRegistrationISRCTN registry, ISRCTN28342533, http://www.isrctn.com/ISRCTN28342533", + "category": "emergency medicine", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.09.03.20187377", @@ -8007,6 +8007,20 @@ "author_similarity": 92, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.08.12.20173690", + "date": "2020-08-14", + "link": "https://medrxiv.org/cgi/content/short/2020.08.12.20173690", + "title": "Antibody prevalence for SARS-CoV-2 in England following first peak of the pandemic: REACT2 study in 100,000 adults", + "authors": "Helen Ward; Christina J Atchison; Matthew Whitaker; Kylie E. C. Ainslie; Joshua Elliott; Lucy C Okell; Rozlyn Redd; Deborah Ashby; Christl A. Donnelly; Wendy Barclay; Ara Darzi; Graham Cooke; Steven Riley; Paul Elliott", + "affiliations": "Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Dept Inf Dis Epi, Imperial College; Imperial College London", + "abstract": "BackgroundEngland, UK has experienced a large outbreak of SARS-CoV-2 infection. As in USA and elsewhere, disadvantaged communities have been disproportionately affected.\n\nMethodsNational REal-time Assessment of Community Transmission-2 (REACT-2) prevalence study using a self-administered lateral flow immunoassay (LFIA) test for IgG among a random population sample of 100,000 adults over 18 years in England, 20 June to 13 July 2020.\n\nResultsData were available for 109,076 participants, yielding 5,544 IgG positive results; adjusted (for test performance) and re-weighted (for sampling) prevalence was 6.0% (95% Cl: 5.8, 6.1). Highest prevalence was in London (13.0% [12.3, 13.6]), among people of Black or Asian (mainly South Asian) ethnicity (17.3% [15.8, 19.1] and 11.9% [11.0, 12.8] respectively) and those aged 18-24 years (7.9% [7.3, 8.5]). Adjusted odds ratio for care home workers with client-facing roles was 3.1 (2.5, 3.8) compared with non-essential workers. One third (32.2%, [31.0-33.4]) of antibody positive individuals reported no symptoms. Among symptomatic cases, most (78.8%) reported symptoms during the peak of the epidemic in England in March (31.3%) and April (47.5%) 2020. We estimate that 3.36 million (3.21, 3.51) people have been infected with SARS-CoV-2 in England to end June 2020, with an overall infection fatality ratio (IFR) of 0.90% (0.86, 0.94); age-specific IFR was similar among people of different ethnicities.\n\nConclusionThe SARS-CoV-2 pandemic in England disproportionately affected ethnic minority groups and health and care home workers. The higher risk of infection in minority ethnic groups may explain their increased risk of hospitalisation and mortality from COVID-19.", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.08.13.20174227", @@ -8399,20 +8413,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.07.15.20151852", - "date": "2020-07-15", - "link": "https://medrxiv.org/cgi/content/short/2020.07.15.20151852", - "title": "Effect of Hydroxychloroquine in Hospitalized Patients with COVID-19: Preliminary results from a multi-centre, randomized, controlled trial.", - "authors": "Peter Horby; Marion Mafham; Louise Linsell; Jennifer L Bell; Natalie Staplin; Jonathan R Emberson; Martin Wiselka; Andrew Ustianowski; Einas Elmahi; Benjamin Prudon; Anthony Whitehouse; Timothy Felton; John Williams; Jakki Faccenda; Jonathan Underwood; J Kenneth Baillie; Lucy Chappell; Saul N Faust; Thomas Jaki; Katie Jeffery; Wei Shen Lim; Alan Montgomery; Kathryn Rowan; Joel Tarning; James A Watson; Nicholas J White; Edmund Juszczak; Richard Haynes; Martin J Landray", - "affiliations": "Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; University Hospitals fo Leicester NHS Trust and University of Leicester; Regional Infectious Diseases Unit, North Manchester General Hospital & University of Manchester, Manchester, UK; Research and Development Department, Northampton General Hospital, Northampton, United Kingdom; Department of Respiratory Medicine, North Tees & Hartlepool NHS Foundation Trust, Stockton-on-Tees, United Kingdom; University Hospitals Birmingham NHS Foundation Trust and Institute of Microbiology & Infection, University of Birmingham, United Kingdom; Univeristy of Manchester and Manchester University NHS Foundation Trust, Manchester, United Kingdom; James Cook University Hospital, Middlesbrough, United Kingdom; North West Anglia NHS Foundation Trust, Peterborough, United Kingdom; Department of Infectious Diseases, Cardiff and Vale University Health Board; Division of Infection and Immunity, Cardiff University, Cardiff, United Kingdom; Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom; School of Life Sciences, King's College London, London, United Kingdom; NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, ; Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom; MRC Biostatistics Unit, University of Cambridge, Cambridge, United Ki; Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; Respiratory Medicine Department, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; Intensive Care National Audit & Research Centre, London, United Kingdom; Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Centre for Tropical Medicine and Global Hea; Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Centre for Tropical Medicine and Global Hea; Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Centre for Tropical Medicine and Global Hea; Nuffield Department of Population Health, University of Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom", - "abstract": "BackgroundHydroxychloroquine and chloroquine have been proposed as treatments for coronavirus disease 2019 (COVID-19) on the basis of in vitro activity, uncontrolled data, and small randomized studies.\n\nMethodsThe Randomised Evaluation of COVID-19 therapy (RECOVERY) trial is a randomized, controlled, open-label, platform trial comparing a range of possible treatments with usual care in patients hospitalized with COVID-19. We report the preliminary results for the comparison of hydroxychloroquine vs. usual care alone. The primary outcome was 28-day mortality.\n\nResults1561 patients randomly allocated to receive hydroxychloroquine were compared with 3155 patients concurrently allocated to usual care. Overall, 418 (26.8%) patients allocated hydroxychloroquine and 788 (25.0%) patients allocated usual care died within 28 days (rate ratio 1.09; 95% confidence interval [CI] 0.96 to 1.23; P=0.18). Consistent results were seen in all pre-specified subgroups of patients. Patients allocated to hydroxychloroquine were less likely to be discharged from hospital alive within 28 days (60.3% vs. 62.8%; rate ratio 0.92; 95% CI 0.85-0.99) and those not on invasive mechanical ventilation at baseline were more likely to reach the composite endpoint of invasive mechanical ventilation or death (29.8% vs. 26.5%; risk ratio 1.12; 95% CI 1.01-1.25). There was no excess of new major cardiac arrhythmia.\n\nConclusionsIn patients hospitalized with COVID-19, hydroxychloroquine was not associated with reductions in 28-day mortality but was associated with an increased length of hospital stay and increased risk of progressing to invasive mechanical ventilation or death.\n\nFundingMedical Research Council and NIHR (Grant ref: MC_PC_19056).\n\nTrial registrationsThe trial is registered with ISRCTN (50189673) and clinicaltrials.gov (NCT04381936).", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.07.13.20152793", @@ -8581,20 +8581,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "bioRxiv", - "doi": "10.1101/2020.07.01.182709", - "date": "2020-07-01", - "link": "https://biorxiv.org/cgi/content/short/2020.07.01.182709", - "title": "Genetic architecture of host proteins interacting with SARS-CoV-2", - "authors": "Maik Pietzner; Eleanor Wheeler; Julia Carrasco-Zanini; Johannes Raffler; Nicola D. Kerrison; Erin Oerton; Victoria P.W. Auyeung; Chris Finan; Juan P. Casas; Rachel Ostroff; Steve A. Williams; Gabi Kastenm\u00fcller; Markus Ralser; Eric G. Gamazon; Nicholas J. Wareham; Aroon Dinesh Hingorani; Claudia Langenberg", - "affiliations": "University of Cambridge; University of Cambridge; University of Cambridge; Helmholtz Zentrum M\u00fcnchen - German Research Center for Environmental Health (GmbH); University of Cambridge; University of Cambridge; University of Cambridge; University College London; Harvard Medical School; SomaLogic Inc.; SomaLogic Inc.; Helmholtz Zentrum M\u00fcnchen - German Research Center for Environmental Health (GmbH); The Francis Crick Institute; Vanderbilt University Medical Center; University of Cambridge; University College London; University of Cambridge", - "abstract": "Strategies to develop therapeutics for SARS-CoV-2 infection may be informed by experimental identification of viral-host protein interactions in cellular assays and measurement of host response proteins in COVID-19 patients. Identification of genetic variants that influence the level or activity of these proteins in the host could enable rapid in silico assessment in human genetic studies of their causal relevance as molecular targets for new or repurposed drugs to treat COVID-19. We integrated large-scale genomic and aptamer-based plasma proteomic data from 10,708 individuals to characterize the genetic architecture of 179 host proteins reported to interact with SARS-CoV-2 proteins or to participate in the host response to COVID-19. We identified 220 host DNA sequence variants acting in cis (MAF 0.01-49.9%) and explaining 0.3-70.9% of the variance of 97 of these proteins, including 45 with no previously known protein quantitative trait loci (pQTL) and 38 encoding current drug targets. Systematic characterization of pQTLs across the phenome identified protein-drug-disease links, evidence that putative viral interaction partners such as MARK3 affect immune response, and establish the first link between a recently reported variant for respiratory failure of COVID-19 patients at the ABO locus and hypercoagulation, i.e. maladaptive host response. Our results accelerate the evaluation and prioritization of new drug development programmes and repurposing of trials to prevent, treat or reduce adverse outcomes. Rapid sharing and dynamic and detailed interrogation of results is facilitated through an interactive webserver (https://omicscience.org/apps/covidpgwas/).", - "category": "genomics", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.06.29.20142448", @@ -8623,20 +8609,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.06.26.20140921", - "date": "2020-06-28", - "link": "https://medrxiv.org/cgi/content/short/2020.06.26.20140921", - "title": "Short Communication: Vitamin D and COVID-19 infection and mortality in UK Biobank", - "authors": "Claire E Hastie; Jill P Pell; Naveed Sattar", - "affiliations": "University of Glasgow; University of Glasgow; University of Glasgow", - "abstract": "PurposeVitamin D has been proposed as a potential causal factor in COVID-19 risk. We aimed to establish whether blood 25-hydroxyvitamin D (25(OH)D) concentration was associated with COVID-19 mortality, and inpatient confirmed COVID-19 infection, in UK Biobank participants.\n\nMethodsUK Biobank recruited 502,624 participants aged 37-73 years between 2006 and 2010. Baseline exposure data, including 25(OH)D concentration, were linked to COVID-19 mortality. Univariable and multivariable Cox proportional hazards regression analyses were performed for the association between 25(OH)D and COVID-19 death, and poisson regression analyses for the association between 25(OH)D and severe COVID-19 infection.\n\nResultsComplete data were available for 341,484 UK Biobank participants, of which 656 had inpatient confirmed COVID-19 infection and 203 died of COVID-19 infection. Vitamin D was associated with severe COVID-19 infection and mortality univariably (mortality HR=0.99; 95% CI 0.98-0.998; p=0.016), but not after adjustment for confounders (mortality HR=0.998; 95% CI=0.99-1.01; p=0.696).\n\nConclusionsOur findings do not support a potential link between vitamin D concentrations and risk of severe COVID-19 infection and mortality. Recommendations for vitamin D supplementation to lessen COVID-19 risks may provide false reassurance.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.06.26.20139873", @@ -8651,20 +8623,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.06.24.20139048", - "date": "2020-06-25", - "link": "https://medrxiv.org/cgi/content/short/2020.06.24.20139048", - "title": "A geotemporal survey of hospital bed saturation across England during the first wave of the COVID-19 Pandemic", - "authors": "Bilal A Mateen; Harrison Wilde; John m Dennis; Andrew Duncan; Nicholas John Meyrick Thomas; Andrew P McGovern; Spiros Denaxas; Matt J Keeling; Sebastian J Vollmer", - "affiliations": "The Alan Turing Institute; University of Warwick; Kings College Hospital NHS Foundation Trust; University of Warwick, Department of Statistics; University of Exeter Medical School; The Alan Turing Institute; Imperial College London, Faculty of Natural Sciences; University of Exeter Medical School; Royal Devon and Exeter NHS Foundation Trust, Diabetes and Endocrinology; University of Exeter Medical School; University College London; University of Warwick; The Alan Turing Institute; University of Warwick, Department of Statistics", - "abstract": "BackgroundNon-pharmacological interventions were introduced based on modelling studies which suggested that the English National Health Service (NHS) would be overwhelmed by the COVID-19 pandemic. In this study, we describe the pattern of bed occupancy across England during the first wave of the pandemic, January 31st to June 5th 2020.\n\nMethodsBed availability and occupancy data was extracted from daily reports submitted by all English secondary care providers, between 27-Mar and 5-June. Two thresholds for safe occupancy were utilized (85% as per Royal College of Emergency Medicine and 92% as per NHS Improvement).\n\nFindingsAt peak availability, there were 2711 additional beds compatible with mechanical ventilation across England, reflecting a 53% increase in capacity, and occupancy never exceeded 62%. A consequence of the repurposing of beds meant that at the trough, there were 8{middle dot}7% (8,508) fewer general and acute (G&A) beds across England, but occupancy never exceeded 72%. The closest to (surge) capacity that any trust in England reached was 99{middle dot}8% for general and acute beds. For beds compatible with mechanical ventilation there were 326 trust-days (3{middle dot}7%) spent above 85% of surge capacity, and 154 trust-days (1{middle dot}8%) spent above 92%. 23 trusts spent a cumulative 81 days at 100% saturation of their surge ventilator bed capacity (median number of days per trust = 1 [range: 1 to 17]). However, only 3 STPs (aggregates of geographically co-located trusts) reached 100% saturation of their mechanical ventilation beds.\n\nInterpretationThroughout the first wave of the pandemic, an adequate supply of all bed-types existed at a national level. Due to an unequal distribution of bed utilization, many trusts spent a significant period operating above safe-occupancy thresholds, despite substantial capacity in geographically co-located trusts; a key operational issue to address in preparing for a potential second wave.\n\nFundingThis study received no funding.\n\nResearch In ContextO_ST_ABSEvidence Before This StudyC_ST_ABSWe identified information sources describing COVID-19 related bed and mechanical ventilator demand modelling, as well as bed occupancy during the first wave of the pandemic by performing regular searches of MedRxiv, PubMed and Google, using the terms COVID-19, mechanical ventilators, bed occupancy, England, UK, demand, and non-pharmacological interventions (NPIs), until June 20th, 2020. Two UK-specific studies were found that modelled the demand for mechanical ventilators, one of which incorporated sensitivity analysis based on the introduction of NPIs and found that their effects might prevent the healthcare system being overwhelmed. Separately, several news reports were found pertaining to a single hospital that reached ventilator capacity in England during the first wave of the pandemic, however, no single authoritative source was identified detailing impact across all hospital sites in England.\n\nAdded Value of This StudyThis national study of hospital-level bed occupancy in England provides unique and timely insight into bed-specific resource utilization during the first wave of the COVID-19 pandemic, nationally, and by specific (geographically defined) health footprints. We found evidence of an unequal distribution of resource utilization across England. Although occupancy of beds compatible with mechanical ventilation never exceeded 62% at the national level, 52 (30%) hospitals across England reached 100% saturation at some point during the first wave of the pandemic. Close examination of the geospatial data revealed that in the vast majority of circumstances there was relief capacity in geographically co-located hospitals. Over the first wave it was theoretically possible to markedly reduce (by 95.1%) the number of hospitals at 100% saturation of their mechanical ventilator bed capacity by redistributing patients to nearby hospitals.\n\nImplications Of All The Available EvidenceNow-casting using routinely collected administrative data presents a robust approach to rapidly evaluate the effectiveness of national policies introduced to prevent a healthcare system being overwhelmed in the context of a pandemic illness. Early investment in operational field hospital and an independent sector network may yield more overtly positive results in the winter, when G&A occupancy-levels regularly exceed 92% in England, however, during the first wave of the pandemic they were under-utilized. Moreover, in the context of the non-pharmacological interventions utilized during the first wave of COVID-19, demand for beds and mechanical ventilators was much lower than initially predicted, but despite this many trust spent a significant period of time operating above safe-occupancy thresholds. This finding demonstrates that it is vital that future demand (prediction) models reflect the nuances of local variation within a healthcare system. Failure to incorporate such geographical variation can misrepresent the likelihood of surpassing availability thresholds by averaging out over regions with relatively lower demand, and presents a key operational issue for policymakers to address in preparing for a potential second wave.", - "category": "health systems and quality improvement", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.06.21.20136853", @@ -8693,6 +8651,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.06.22.20137216", + "date": "2020-06-23", + "link": "https://medrxiv.org/cgi/content/short/2020.06.22.20137216", + "title": "Proteomic blood profiling in mild, severe and critical COVID-19 patients", + "authors": "Hamel Patel; Nicholas J Ashton; Richard J Dobson; Lars-magnus Anderson; Aylin Yilmaz; Kaj Blennow; Magnus Gisslen; Henrik Zetterberg", + "affiliations": "King's College London; University of Gothenburg; Kings College London; Sahlgrenska university hospital; University of Gothenburg; University of Gothenburg; University of Gothenburg; University of Gothenburg", + "abstract": "The recent SARS-CoV-2 pandemic manifests itself as a mild respiratory tract infection in the majority of individuals leading to COVID-19 disease. However, in some infected individuals, this can progress to severe pneumonia and acute respiratory distress syndrome (ARDS), leading to multi-organ failure and death. The purpose of this study is to explore the proteomic differences between mild, severe and critical COVID-19 positive patients. Blood protein profiling was performed on 59 COVID-19 mild (n=26), severe (n=9) or critical (n=24) cases and 28 controls using the OLINK inflammation, autoimmune, cardiovascular and neurology panels. Differential expression analysis was performed within and between disease groups to generate nine different analyses. From the 368 proteins measured per individual, more than 75% were observed to be significantly perturbed in COVID-19 cases. Six proteins (IL6, CKAP4, Gal-9, IL-1ra, LILRB4 and PD-L1) were identified to be associated with disease severity. The results have been made readily available through an interactive web-based application for instant data exploration and visualization, and can be accessed at https://phidatalab-shiny.rosalind.kcl.ac.uk/COVID19/. Our results demonstrate that dynamic changes in blood proteins that associate with disease severity can potentially be used as early biomarkers to monitor disease severity in COVID-19 and serve as potential therapeutic targets.", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.06.22.20137273", @@ -9015,20 +8987,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.06.01.20116608", - "date": "2020-06-03", - "link": "https://medrxiv.org/cgi/content/short/2020.06.01.20116608", - "title": "Is death from Covid-19 a multistep process?", - "authors": "Neil Pearce; Giovenale Moirano; Milena Maule; Manolis Kogevinas; Xavier Rodo; Deborah Lawlor; Jan Vandenbroucke; Christina Vandenbroucke-Grauls; Fernando P Polack; Adnan Custovic", - "affiliations": "London School of Hygiene and Tropical Medicine; University of Turin, Italy; University of Turin, Italy; ISGlobal; ISGlobal; University of Bristol; Leiden University Medical Center; Amsterdam UMC; Vanderbilt Unversity; Imperial College London", - "abstract": "Covid-19 death has a different relationship with age than is the case for other severe respiratory pathogens. The Covid-19 death rate increases exponentially with age, and the main risk factors are age itself, as well as having underlying conditions such as hypertension, diabetes, cardiovascular disease, severe chronic respiratory disease and cancer. Furthermore, the almost complete lack of deaths in children suggests that infection alone is not sufficient to cause death; rather, one must have gone through a number of changes, either as a result of undefined aspects of aging, or as a result of chronic disease. These characteristics of Covid-19 death are consistent with the multistep model of disease, a model which has primarily been used for cancer, and more recently for amyotrophic lateral sclerosis (ALS). We applied the multi-step model to data on Covid-19 case fatality rates (CFRs) from China, South Korea, Italy, Spain and Japan. In all countries we found that a plot of ln (CFR) against ln (age) was approximately linear with a slope of about 5. As a comparison, we also conducted similar analyses for selected other respiratory diseases. SARS showed a similar log-log age-pattern to that of Covid-19, albeit with a lower slope, whereas seasonal and pandemic influenza showed quite different age-patterns. Thus, death from Covid-19 and SARS appears to follow a distinct age-pattern, consistent with a multistep model of disease that in the case of Covid-19 is probably defined by comorbidities and age producing immune-related susceptibility. Identification of these steps would be potentially important for prevention and therapy for SARS-COV-2 infection.", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.06.01.20118943", @@ -9505,6 +9463,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.05.02.20078642", + "date": "2020-05-06", + "link": "https://medrxiv.org/cgi/content/short/2020.05.02.20078642", + "title": "Impact of ethnicity on outcome of severe COVID-19 infection. Data from an ethnically diverse UK tertiary centre", + "authors": "James T Teo; Daniel Bean; Rebecca Bendayan; Richard Dobson; Ajay Shah", + "affiliations": "Kings College Hospital NHS Foundation Trust; King's College London; King's College London; Kings College London; King's College London", + "abstract": "During the current COVID-19 pandemic, it has been suggested that BAME background patients may be disproportionately affected compared to White but few detailed data are available. We took advantage of near real-time hospital data access and analysis pipelines to look at the impact of ethnicity in 1200 consecutive patients admitted between 1st March 2020 and 12th May 2020 to Kings College Hospital NHS Trust in London (UK).\n\nOur key findings are firstly that BAME patients are significantly younger and have different co-morbidity profiles than White individuals. Secondly, there is no significant independent effect of ethnicity on severe outcomes (death or ITU admission) within 14-days of symptom onset, after adjustment for age, sex and comorbidities.", + "category": "intensive care and critical care medicine", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.05.02.20086231", @@ -9547,20 +9519,6 @@ "author_similarity": 94, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.04.28.20082222", - "date": "2020-05-03", - "link": "https://medrxiv.org/cgi/content/short/2020.04.28.20082222", - "title": "Risk prediction for poor outcome and death in hospital in-patients with COVID-19: derivation in Wuhan, China and external validation in London, UK", - "authors": "Huayu Zhang; Ting Shi; Xiaodong Wu; Xin Zhang; Kun Wang; Daniel Bean; Richard Dobson; James T Teo; Jiaxing Sun; Pei Zhao; Chenghong Li; Kevin Dhaliwal; Honghan Wu; Qiang Li; Bruce Guthrie", - "affiliations": "Centre for Medical Informatics, Usher Institute, University of Edinburgh, Scotland, United Kingdom; Centre for Global Health, Usher Institute, University of Edinburgh, Scotland, United Kingdom; Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China; Department of Pulmonary and Critical Care Medicine, Peoples Liberation Army Joint Logistic Support Force 920th Hospital, Yunnan, China; Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, England, United Kingdom; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, England, United Kingdom; Department of Stroke and Neurology, Kings College Hospital NHS Foundation Trust, London, England, United Kingdom; Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China; Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China; Department of Pulmonary and Critical Care Medicine, Wuhan Sixth Hospital, Jianghan University, Wuhan, China; Centre for Inflammation Research, Queens Medical Research Institute, University of Edinburgh, Scotland, United Kingdom; Centre for Medical Informatics, Usher Institute, University of Edinburgh, Scotland, United Kingdom; Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China; Centre for Population Health Sciences, Usher Institute, University of Edinburgh, Scotland, United Kingdom", - "abstract": "BackgroundAccurate risk prediction of clinical outcome would usefully inform clinical decisions and intervention targeting in COVID-19. The aim of this study was to derive and validate risk prediction models for poor outcome and death in adult inpatients with COVID-19.\n\nMethodsModel derivation using data from Wuhan, China used logistic regression with death and poor outcome (death or severe disease) as outcomes. Predictors were demographic, comorbidity, symptom and laboratory test variables. The best performing models were externally validated in data from London, UK.\n\nFindings4.3% of the derivation cohort (n=775) died and 9.7% had a poor outcome, compared to 34.1% and 42.9% of the validation cohort (n=226). In derivation, prediction models based on age, sex, neutrophil count, lymphocyte count, platelet count, C-reactive protein and creatinine had excellent discrimination (death c-index=0.91, poor outcome c-index=0.88), with good-to-excellent calibration. Using two cut-offs to define low, high and very-high risk groups, derivation patients were stratified in groups with observed death rates of 0.34%, 15.0% and 28.3% and poor outcome rates 0.63%, 8.9% and 58.5%. External validation discrimination was good (c-index death=0.74, poor outcome=0.72) as was calibration. However, observed rates of death were 16.5%, 42.9% and 58.4% and poor outcome 26.3%, 28.4% and 64.8% in predicted low, high and very-high risk groups.\n\nInterpretationOur prediction model using demography and routinely-available laboratory tests performed very well in internal validation in the lower-risk derivation population, but less well in the much higher-risk external validation population. Further external validation is needed. Collaboration to create larger derivation datasets, and to rapidly externally validate all proposed prediction models in a range of populations is needed, before routine implementation of any risk prediction tool in clinical care.\n\nFundingMRC, Wellcome Trust, HDR-UK, LifeArc, participating hospitals, NNSFC, National Key R&D Program, Pudong Health and Family Planning Commission\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSSeveral prognostic models for predicting mortality risk, progression to severe disease, or length of hospital stay in COVID-19 have been published.1 Commonly reported predictors of severe prognosis in patients with COVID-19 include age, sex, computed tomography scan features, C-reactive protein (CRP), lactic dehydrogenase, and lymphocyte count. Symptoms (notably dyspnoea) and comorbidities (e.g. chronic lung disease, cardiovascular disease and hypertension) are also reported to have associations with poor prognosis.2 However, most studies have not described the study population or intended use of prediction models, and external validation is rare and to date done using datasets originating from different Wuhan hospitals.3 Given different patterns of testing and organisation of healthcare pathways, external validation in datasets from other countries is required.\n\nAdded value of this studyThis study used data from Wuhan, China to derive and internally validate multivariable models to predict poor outcome and death in COVID-19 patients after hospital admission, with external validation using data from Kings College Hospital, London, UK. Mortality and poor outcome occurred in 4.3% and 9.7% of patients in Wuhan, compared to 34.1% and 42.9% of patients in London. Models based on age, sex and simple routinely available laboratory tests (lymphocyte count, neutrophil count, platelet count, CRP and creatinine) had good discrimination and calibration in internal validation, but performed only moderately well in external validation. Models based on age, sex, symptoms and comorbidity were adequate in internal validation for poor outcome (ICU admission or death) but had poor performance for death alone.\n\nImplications of all the available evidenceThis study and others find that relatively simple risk prediction models using demographic, clinical and laboratory data perform well in internal validation but at best moderately in external validation, either because derivation and external validation populations are small (Xie et al3) and/or because they vary greatly in casemix and severity (our study). There are three decision points where risk prediction may be most useful: (1) deciding who to test; (2) deciding which patients in the community are at high-risk of poor outcomes; and (3) identifying patients at high-risk at the point of hospital admission. Larger studies focusing on particular decision points, with rapid external validation in multiple datasets are needed. A key gap is risk prediction tools for use in community triage (decisions to admit, or to keep at home with varying intensities of follow-up including telemonitoring) or in low income settings where laboratory tests may not be routinely available at the point of decision-making. This requires systematic data collection in community and low-income settings to derive and evaluate appropriate models.", - "category": "public and global health", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.04.27.20081810", @@ -9897,20 +9855,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.03.24.20043018", - "date": "2020-03-27", - "link": "https://medrxiv.org/cgi/content/short/2020.03.24.20043018", - "title": "Age-dependent effects in the transmission and control of COVID-19 epidemics", - "authors": "Nicholas G Davies; Petra Klepac; Yang Liu; Kiesha Prem; Mark Jit; CMMID COVID-19 working group; Rosalind M Eggo", - "affiliations": "London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; ; London School of Hygiene and Tropical Medicine", - "abstract": "The COVID-19 pandemic has shown a markedly low proportion of cases among children. Age disparities in observed cases could be explained by children having lower susceptibility to infection, lower propensity to show clinical symptoms, or both. We evaluate these possibilities by fitting an age-structured mathematical model to epidemic data from six countries. We estimate that clinical symptoms occur in 25% (95% CrI: 19-32%) of infections in 10-19-year-olds, rising to 76% (68-82%) in over-70s, and that susceptibility to infection in under-20s is approximately half that of older adults. Accordingly, we find that interventions aimed at children may have a relatively small impact on total cases, particularly if the transmissibility of subclinical infections is low. The age-specific clinical fraction and susceptibility we have estimated has implications for the expected global burden of COVID-19 because of demographic differences across settings: in younger populations, the expected clinical attack rate would be lower, although it is likely that comorbidities in low-income countries will affect disease severity. Without effective control measures, regions with older populations may see disproportionally more clinical cases, particularly in the later stages of the pandemic.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.03.22.20040287", @@ -10051,6 +9995,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.01.31.20019265", + "date": "2020-02-02", + "link": "https://medrxiv.org/cgi/content/short/2020.01.31.20019265", + "title": "Effectiveness of airport screening at detecting travellers infected with 2019-nCoV", + "authors": "Billy Quilty; Sam Clifford; Stefan Flasche; Rosalind M Eggo", + "affiliations": "London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine", + "abstract": "As the number of novel coronavirus cases grows both inside and outside of China, public health authorities require evidence on the effectiveness of control measures such as thermal screening of arrivals at airports. We evaluated the effectiveness of exit and entry screening for 2019-nCoV infection. In our baseline scenario, we estimated that 46.5% (95%CI: 35.9 to 57.7) of infected travellers would not be detected, depending on the incubation period, sensitivity of exit and entry screening, and the proportion of cases which are asymptomatic. Airport screening is unlikely to detect a sufficient proportion of 2019-nCoV infected travellers to avoid entry of infected travellers. We developed an online tool so that results can be updated as new information becomes available.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.01.31.20019901", diff --git a/data/covid/raw-preprints.json b/data/covid/raw-preprints.json index 4f27557b..4c414b2d 100644 --- a/data/covid/raw-preprints.json +++ b/data/covid/raw-preprints.json @@ -1,11 +1,222 @@ [ + { + "rel_doi": "10.1101/2023.10.19.563209", + "rel_title": "Virological characteristics of the SARS-CoV-2 Omicron EG.5.1 variant", + "rel_date": "2023-10-21", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.10.19.563209", + "rel_abs": "In middle-late 2023, a sublineage of SARS-CoV-2 Omicron XBB, EG.5.1 (a progeny of XBB.1.9.2), is spreading rapidly around the world. Here, we performed multiscale investigations to reveal virological features of newly emerging EG.5.1 variant. Our phylogenetic-epidemic dynamics modeling suggested that two hallmark substitutions of EG.5.1, S:F456L and ORF9b:I5T, are critical to the increased viral fitness. Experimental investigations addressing the growth kinetics, sensitivity to clinically available antivirals, fusogenicity and pathogenicity of EG.5.1 suggested that the virological features of EG.5.1 is comparable to that of XBB.1.5. However, the cryo-electron microscopy reveals the structural difference between the spike proteins of EG.5.1 and XBB.1.5. We further assessed the impact of ORF9b:I5T on viral features, but it was almost negligible at least in our experimental setup. Our multiscale investigations provide the knowledge for understanding of the evolution trait of newly emerging pathogenic viruses in the human population.", + "rel_num_authors": 49, + "rel_authors": [ + { + "author_name": "Shuhei Tsujino", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Sayaka Deguchi", + "author_inst": "Kyoto University" + }, + { + "author_name": "Tomo Nomai", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Miguel Padilla-Blanco", + "author_inst": "Charles University" + }, + { + "author_name": "Arnon Plianchaisuk", + "author_inst": "The University of Tokyo" + }, + { + "author_name": "Lei Wang", + "author_inst": "Hokkaido University" + }, + { + "author_name": "MST Monira Begum", + "author_inst": "Kumamoto University" + }, + { + "author_name": "Keiya Uriu", + "author_inst": "The University of Tokyo" + }, + { + "author_name": "Keita Mizuma", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Naganori Nao", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Isshu Kojima", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Tomoya Tsubo", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Jingshu Li", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Yasufumi Matsumura", + "author_inst": "Kyoto University" + }, + { + "author_name": "Miki Nagao", + "author_inst": "Kyoto University" + }, + { + "author_name": "Yoshikata Oda", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Masumi Tsuda", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Yuki Anraku", + "author_inst": "Kyoto University" + }, + { + "author_name": "Shunsuke Kita", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Hisano Yajima", + "author_inst": "Kyoto University" + }, + { + "author_name": "Kaori Tabata", + "author_inst": "Kyushu University" + }, + { + "author_name": "Ziyi Guo", + "author_inst": "The University of Tokyo" + }, + { + "author_name": "Alfredo Amolong Hinay Jr.", + "author_inst": "The University of Tokyo" + }, + { + "author_name": "Kumiko Yoshimatsu", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Yuki Yamamoto", + "author_inst": "HiLung, Inc." + }, + { + "author_name": "Yetsuharu Nagamoto", + "author_inst": "HiLung, Inc." + }, + { + "author_name": "Hiroyuki Asakura", + "author_inst": "Tokyo Metropolitan Institute of Public Health" + }, + { + "author_name": "Mami Nagashima", + "author_inst": "Tokyo Metropolitan Institute of Public Health" + }, + { + "author_name": "Kenji Sadamasu", + "author_inst": "Tokyo Metropolitan Institute of Public Health" + }, + { + "author_name": "Kazuhisa Yoshimura", + "author_inst": "Tokyo Metropolitan Institute of Public Health" + }, + { + "author_name": "Hesham Nasser", + "author_inst": "Kumamoto University" + }, + { + "author_name": "Michael Jonathan", + "author_inst": "Kumamoto University" + }, + { + "author_name": "Olivia Putri", + "author_inst": "The University of Tokyo" + }, + { + "author_name": "Yoonjin Kim", + "author_inst": "The University of Tokyo" + }, + { + "author_name": "Luo Chen", + "author_inst": "The University of Tokyo" + }, + { + "author_name": "Rigel Suzuki", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Tomokazu Tamura", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Katsumi Maenaka", + "author_inst": "Hokkaido University" + }, + { + "author_name": "- The Genotype to Phenotype Japan (G2P-Japan) Consortium", + "author_inst": "-" + }, + { + "author_name": "Takashi Irie", + "author_inst": "Hiroshima University" + }, + { + "author_name": "Keita Matsuno", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Shinya Tanaka", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Jumpei Ito", + "author_inst": "The University of Tokyo" + }, + { + "author_name": "Terumasa Ikeda", + "author_inst": "Kumamoto University" + }, + { + "author_name": "Kazuo Takayama", + "author_inst": "Kyoto University" + }, + { + "author_name": "Jiri Zahradnik", + "author_inst": "Charles University" + }, + { + "author_name": "Takao Hashiguchi", + "author_inst": "Kyoto University" + }, + { + "author_name": "Takasuke Fukuhara", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Kei Sato", + "author_inst": "Institute of Medical Science, The University of Tokyo" + } + ], + "version": "1", + "license": "cc_by_nd", + "type": "new results", + "category": "microbiology" + }, { "rel_doi": "10.1101/2023.10.19.23297252", "rel_title": "SARS-CoV-2 lineage-specific disease symptoms and disease severity in Sao Caetano do Sul city, Brazil", "rel_date": "2023-10-20", "rel_site": "medRxiv", "rel_link": "https://medrxiv.org/cgi/content/short/2023.10.19.23297252", - "rel_abs": "Background: The city of Sao Caetano do Sul, Brazil, established a web-based platform to provide primary care to suspected COVID-19 patients, integrating clinical and demographic data and sample metadata. Here we describe lineage-specific spatiotemporal dynamics of infections, clinical symptoms, and disease severity during the first year of the epidemic. Methods: We selected and sequenced 879 PCR+ swab samples (8% of all reported cases), obtaining a spatially and temporally representative set of sequences. Daily lineage-specific prevalence was estimating using a moving-window approach, allowing inference of cumulative cases and symptom probability stratified by lineage using integrated data from the platform. Results: Most infections were caused by B.1.1.28 (41.3%), followed by Gamma (31.7%), Zeta (9.6%) and B1.1.33 (9.0%). Gamma and Zeta were associated with larger prevalence of dyspnoea (respectively 81.3% and 78.5%) and persistent fever (84.7% and 61.1%) compared to B.1.1.28 and B.1.1.33. Ageusia, anosmia, and coryza were respectively 18.9%, 20.3% and 17.8% less commonly caused by Gamma, while altered mental status was 108.9% more common in Zeta. Case incidence was spatially heterogeneous and larger in poorer and younger districts. Discussion: Our study demonstrates that Gamma was associated with more severe disease, emphasising the role of its increased disease severity in the heightened mortality levels in Brazil.", + "rel_abs": "BackgroundThe city of Sao Caetano do Sul, Brazil, established a web-based platform to provide primary care to suspected COVID-19 patients, integrating clinical and demographic data and sample metadata. Here we describe lineage-specific spatiotemporal dynamics of infections, clinical symptoms, and disease severity during the first year of the epidemic.\n\nMethodsWe selected and sequenced 879 PCR+ swab samples (8% of all reported cases), obtaining a spatially and temporally representative set of sequences. Daily lineage-specific prevalence was estimating using a moving-window approach, allowing inference of cumulative cases and symptom probability stratified by lineage using integrated data from the platform.\n\nResultsMost infections were caused by B.1.1.28 (41.3%), followed by Gamma (31.7%), Zeta (9.6%) and B1.1.33 (9.0%). Gamma and Zeta were associated with larger prevalence of dyspnoea (respectively 81.3% and 78.5%) and persistent fever (84.7% and 61.1%) compared to B.1.1.28 and B.1.1.33. Ageusia, anosmia, and coryza were respectively 18.9%, 20.3% and 17.8% less commonly caused by Gamma, while altered mental status was 108.9% more common in Zeta. Case incidence was spatially heterogeneous and larger in poorer and younger districts.\n\nDiscussionOur study demonstrates that Gamma was associated with more severe disease, emphasising the role of its increased disease severity in the heightened mortality levels in Brazil.", "rel_num_authors": 20, "rel_authors": [ { @@ -349,7 +560,7 @@ "rel_date": "2023-10-19", "rel_site": "medRxiv", "rel_link": "https://medrxiv.org/cgi/content/short/2023.10.09.23296726", - "rel_abs": "Background: XAV-19 is a glyco-humanized swine polyclonal antibody targeting SARS-CoV-2. The safety and clinical efficacy of XAV-19 was investigated in patients with a WHO score of 2 to 4 in the WHO 7-point ordinal scale. The activity of XAV-19 against Omicron and its subvariants was assessed in vitro. Methods: A phase II/III, multicentric randomized double-blind placebo-controlled, clinical trial was conducted to evaluate the safety and clinical efficacy of XAV-19 in inpatients with COVID-19 requiring or not oxygen therapy and outpatients not requiring oxygen (EUROXAV trial, NCT04928430). Most patients were not vaccinated. The primary endpoint was the proportion of patients with an aggravation of COVID-19 within 8 days after treatment. Binding and neutralization of Omicron or its subvariants by XAV-19 was investigated by ELISA or with a whole virus neutralization assay. Results: Patients received either 150mg of XAV-19 (N=139) or placebo (N=140). Low enrolment forced the premature trial termination. XAV-19 was well tolerated. No difference in the primary endpoint, nor in the proportion with an improvement at day 8 (secondary endpoint) was observed between the 2 groups. For patients not requiring oxygen therapy, XAV-19 reduced the time to improvement significantly (7 days vs 14 days p=0.0159). Neutralizing activity against Omicron and BA.2, BA2.12.1, BA.4/5 and BQ1.1 subvariants was shown in vitro. Conclusions: XAV-19 did not reduce the aggravation in COVID-19 patients. While it did not bring any benefit to patients requiring oxygen, it reduced the time to improvement for patients not requiring oxygen (WHO score 2 or 3). These preliminary clinical data might indicate a therapeutic potential for patients with mild to moderate COVID-19 requiring supplementation with anti-SARS-CoV-2 neutralizing antibodies.", + "rel_abs": "BackgroundXAV-19 is a glyco-humanized swine polyclonal antibody targeting SARS-CoV-2. The safety and clinical efficacy of XAV-19 was investigated in patients with a WHO score of 2 to 4 in the WHO 7-point ordinal scale. The activity of XAV-19 against Omicron and its subvariants was assessed in vitro.\n\nMethodsA phase II/III, multicentric randomized double-blind placebo-controlled, clinical trial was conducted to evaluate the safety and clinical efficacy of XAV-19 in inpatients with COVID-19 requiring or not oxygen therapy and outpatients not requiring oxygen (EUROXAV trial, NCT04928430). Most patients were not vaccinated. The primary endpoint was the proportion of patients with an aggravation of COVID-19 within 8 days after treatment. Binding and neutralization of Omicron or its subvariants by XAV-19 was investigated by ELISA or with a whole virus neutralization assay.\n\nResultsPatients received either 150mg of XAV-19 (N=139) or placebo (N=140). Low enrolment forced the premature trial termination. XAV-19 was well tolerated. No difference in the primary endpoint, nor in the proportion with an improvement at day 8 (secondary endpoint) was observed between the 2 groups. For patients not requiring oxygen therapy, XAV-19 reduced the time to improvement significantly (7 days vs 14 days p=0.0159). Neutralizing activity against Omicron and BA.2, BA2.12.1, BA.4/5 and BQ1.1 subvariants was shown in vitro.\n\nConclusionsXAV-19 did not reduce the aggravation in COVID-19 patients. While it did not bring any benefit to patients requiring oxygen, it reduced the time to improvement for patients not requiring oxygen (WHO score 2 or 3). These preliminary clinical data might indicate a therapeutic potential for patients with mild to moderate COVID-19 requiring supplementation with anti-SARS-CoV-2 neutralizing antibodies.", "rel_num_authors": 10, "rel_authors": [ { @@ -439,7 +650,7 @@ "rel_date": "2023-10-18", "rel_site": "medRxiv", "rel_link": "https://medrxiv.org/cgi/content/short/2023.10.17.23297174", - "rel_abs": "Background: The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) posed a significant public health challenge globally, with Brazil being no exception. Excess mortality during this period reached alarming levels. Cardiovascular diseases (CVD), Systemic Hypertension (HTN), and Diabetes Mellitus (DM) were associated with increased mortality. However, the specific impact of DM and HTN on mortality during the pandemic remains poorly understood. Methods: This study analyzed mortality data from Brazil's mortality system, covering the period from 2015 to 2022. Data included all causes of death as listed on death certificates, categorized by International Classification of Diseases 10th edition (ICD-10) codes. Population data were obtained from the Brazilian Census. Mortality ratios (MRs) were calculated by comparing death rates in 2020, 2021, and 2022 to the average rates from 2015 to 2019. Adjusted MRs were calculated using Poisson models. Results: Between 2015 and 2022, Brazil recorded a total of 11,423,288 deaths. Death rates remained relatively stable until 2019 but experienced a sharp increase in 2020 and 2021. In 2022, although a decrease was observed, it did not return to pre-pandemic levels. This trend persisted even when analyzing records mentioning DM, HTN, or CVD. Excluding death certificates mentioning COVID-19 codes, the trends still showed increases from 2020 through 2022, though less pronounced. Conclusion: This study highlights the persistent high mortality rates for DM and HTN in Brazil during the years 2020-2022, even after excluding deaths associated with COVID-19. These findings emphasize the need for continued attention to managing and preventing DM and HTN as part of public health strategies, both during and beyond the COVID-19 pandemic. There are complex interactions between these conditions and the pandemic's impact on mortality rates.", + "rel_abs": "BackgroundThe outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) posed a significant public health challenge globally, with Brazil being no exception. Excess mortality during this period reached alarming levels. Cardiovascular diseases (CVD), Systemic Hypertension (HTN), and Diabetes Mellitus (DM) were associated with increased mortality. However, the specific impact of DM and HTN on mortality during the pandemic remains poorly understood.\n\nMethodsThis study analyzed mortality data from Brazils mortality system, covering the period from 2015 to 2022. Data included all causes of death as listed on death certificates, categorized by International Classification of Diseases 10th edition (ICD-10) codes. Population data were obtained from the Brazilian Census. Mortality ratios (MRs) were calculated by comparing death rates in 2020, 2021, and 2022 to the average rates from 2015 to 2019. Adjusted MRs were calculated using Poisson models.\n\nResultsBetween 2015 and 2022, Brazil recorded a total of 11,423,288 deaths. Death rates remained relatively stable until 2019 but experienced a sharp increase in 2020 and 2021. In 2022, although a decrease was observed, it did not return to pre-pandemic levels. This trend persisted even when analyzing records mentioning DM, HTN, or CVD. Excluding death certificates mentioning COVID-19 codes, the trends still showed increases from 2020 through 2022, though less pronounced.\n\nConclusionThis study highlights the persistent high mortality rates for DM and HTN in Brazil during the years 2020-2022, even after excluding deaths associated with COVID-19. These findings emphasize the need for continued attention to managing and preventing DM and HTN as part of public health strategies, both during and beyond the COVID-19 pandemic. There are complex interactions between these conditions and the pandemics impact on mortality rates.", "rel_num_authors": 5, "rel_authors": [ { @@ -474,7 +685,7 @@ "rel_date": "2023-10-18", "rel_site": "medRxiv", "rel_link": "https://medrxiv.org/cgi/content/short/2023.10.17.23297146", - "rel_abs": "Background: National and large city mortality and morbidity data emerged during the early years of the COVID-19 pandemic, yet statewide data to assess the impact COVID-19 had across urban and rural landscapes on subpopulations was lacking. The SHOW COVID-19 cohort was established to provide descriptive and longitudinal data to examine the influence the social determinants of health had on COVID-19 related outcomes. Methods: Participants were recruited from the 5,742 adults in the Survey of the Health of Wisconsin (SHOW) cohort who were all residents of Wisconsin, United States when they joined the cohort between 2008-2019. Online surveys were administered at three timepoints during 2020-2021. Survey topics included COVID-19 exposure, testing and vaccination, COVID-19 impact on economic wellbeing, healthcare access, mental and emotional health, caregiving, diet, lifestyle behaviors, social cohesion, and resilience. Results: A total of 2,304 adults completed at least one COVID-19 online survey, with n=1,090 completing all three survey timepoints. Non-Whites were 2-3 times more likely to report having had COVID-19 compared to Whites, females were more likely than males to experience disruptions in their employment, and those with children in the home were more likely to report moderate to high levels of stress compared to adults without children. Conclusion: Longitudinal, statewide cohorts are important for investigating how the social determinants of health affect health and well-being during the first years of a pandemic and offer insight into future pandemic preparation. The data are available for researchers and cohort is active for continued and future follow-up.", + "rel_abs": "BackgroundNational and large city mortality and morbidity data emerged during the early years of the COVID-19 pandemic, yet statewide data to assess the impact COVID-19 had across urban and rural landscapes on subpopulations was lacking. The SHOW COVID-19 cohort was established to provide descriptive and longitudinal data to examine the influence the social determinants of health had on COVID-19 related outcomes.\n\nMethodsParticipants were recruited from the 5,742 adults in the Survey of the Health of Wisconsin (SHOW) cohort who were all residents of Wisconsin, United States when they joined the cohort between 2008-2019. Online surveys were administered at three timepoints during 2020-2021. Survey topics included COVID-19 exposure, testing and vaccination, COVID-19 impact on economic wellbeing, healthcare access, mental and emotional health, caregiving, diet, lifestyle behaviors, social cohesion, and resilience.\n\nResultsA total of 2,304 adults completed at least one COVID-19 online survey, with n=1,090 completing all three survey timepoints. Non-Whites were 2-3 times more likely to report having had COVID-19 compared to Whites, females were more likely than males to experience disruptions in their employment, and those with children in the home were more likely to report moderate to high levels of stress compared to adults without children.\n\nConclusionLongitudinal, statewide cohorts are important for investigating how the social determinants of health affect peoples lives, health, and well-being during the first years of a pandemic and offer insight into future pandemic preparation. The data are available for researchers and cohort is active for continued and future follow-up.\n\nKey MessagesO_LIMortality and morbidity data emerged during the early years of the COVID-19 pandemic at the national scale and in large cities, yet comprehensive social, cultural, and economic population-level data at the state level was lacking for identifying sub-population trends.\nC_LIO_LICOVID-19 disrupted lives and affected people differently based on socio-economic status, demographics, family dynamics, geography, health status, and employment.\nC_LIO_LISHOW COVID-19 cohort is a unique non-clinical, non-hospital-based sample with pre-COVID-19 baseline survey data and biospecimen and three waves of COVID-19 data and specimen available to examine effects of COVID-19 on the social determinants of health.\nC_LI", "rel_num_authors": 13, "rel_authors": [ { @@ -831,7 +1042,7 @@ "rel_date": "2023-10-16", "rel_site": "bioRxiv", "rel_link": "https://biorxiv.org/cgi/content/short/2023.10.13.562198", - "rel_abs": "This research offers a bioinformatics approach to forecasting both domestic and wild animals likelihood of being susceptible to SARS-CoV-2 infection. Genomic sequencing can resolve phylogenetic relationships between the virus and the susceptible host. The genome sequence of SARS-CoV-2 is highly interactive with the specific sequence region of the ACE2 receptor of the host species. We further evaluate this concept to identify the most important SARS-CoV-2 binding amino acid sites in the ACE2 receptor sequence through the common similarity of the last common amino acid sites (LCAS) in known susceptible host species. Therefore, the SARS-CoV-2 viral genomic interacting key amino acid region in the ACE2 receptor sequence of known susceptible human host was summarized and compared with other reported known SARS-CoV-2 susceptible host species. We identified the 10 most significant amino acid sites for interaction with SARS-CoV-2 infection from the ACE2 receptor sequence region based on the LCAS similarity pattern in known sensitive SARS-CoV-2 hosts. The most significant 10 LCAS were further compared with ACE2 receptor sequences of unknown species to evaluate the similarity of the last common amino acid pattern (LCAP). We predicted the probability of SARS-CoV-2 infection risk in unknown species through the LCAS similarity pattern. This method can be used as a screening tool to assess the risk of SARS-CoV-2 infection in domestic and wild animals to prevent outbreaks of infection.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC=\"FIGDIR/small/562198v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (25K):\norg.highwire.dtl.DTLVardef@1fdf055org.highwire.dtl.DTLVardef@ad6bd5org.highwire.dtl.DTLVardef@182726corg.highwire.dtl.DTLVardef@12651da_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_abs": "This research offers a bioinformatics approach to forecasting both domestic and wild animals likelihood of being susceptible to SARS-CoV-2 infection. Genomic sequencing can resolve phylogenetic relationships between the virus and the susceptible host. The genome sequence of SARS-CoV-2 is highly interactive with the specific sequence region of the ACE2 receptor of the host species. We further evaluate this concept to identify the most important SARS-CoV-2 binding amino acid sites in the ACE2 receptor sequence through the common similarity of the last common amino acid sites (LCAS) in known susceptible host species. Therefore, the SARS-CoV-2 viral genomic interacting key amino acid region in the ACE2 receptor sequence of known susceptible human host was summarized and compared with other reported known SARS-CoV-2 susceptible host species. We identified the 10 most significant amino acid sites for interaction with SARS-CoV-2 infection from the ACE2 receptor sequence region based on the LCAS similarity pattern in known sensitive SARS-CoV-2 hosts. The most significant 10 LCAS were further compared with ACE2 receptor sequences of unknown species to evaluate the similarity of the last common amino acid pattern (LCAP). We predicted the probability of SARS-CoV-2 infection risk in unknown species through the LCAS similarity pattern. This method can be used as a screening tool to assess the risk of SARS-CoV-2 infection in domestic and wild animals to prevent outbreaks of infection.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC=\"FIGDIR/small/562198v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (25K):\norg.highwire.dtl.DTLVardef@a2a806org.highwire.dtl.DTLVardef@c559a2org.highwire.dtl.DTLVardef@7fb09eorg.highwire.dtl.DTLVardef@124565a_HPS_FORMAT_FIGEXP M_FIG C_FIG", "rel_num_authors": 8, "rel_authors": [ { @@ -1491,123 +1702,63 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.10.13.23296903", - "rel_title": "Safety of Monovalent BNT162b2 (Pfizer-BioNTech), mRNA-1273 (Moderna), and NVX-CoV2373 (Novavax) COVID-19 Vaccines in US Children Aged 6 months to 17 years", + "rel_doi": "10.1101/2023.10.10.23296624", + "rel_title": "Evaluation of Stroke Risk Following COVID-19 mRNA Bivalent Vaccines Among U.S. Adults Aged >=65 Years", "rel_date": "2023-10-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.10.13.23296903", - "rel_abs": "ImportanceActive monitoring of health outcomes after COVID-19 vaccination provides early detection of rare outcomes that may not be identified in prelicensure trials.\n\nObjectiveTo conduct near real-time monitoring of health outcomes following COVID-19 vaccination in the United States (US) pediatric population aged 6 months to 17 years.\n\nDesignWe evaluated 21 pre-specified health outcomes; 15 were sequentially tested through near real-time surveillance, and 6 were monitored descriptively within a cohort of vaccinated children. We tested for increased rate of each outcome following vaccination compared to a historical comparator cohort.\n\nSettingThis population-based study was conducted under the US Food and Drug Administration public health surveillance mandate using three commercial claims databases.\n\nParticipantsChildren aged 6 months to 17 years were included if they received a monovalent COVID-19 vaccine dose before early 2023 and had continuous enrollment in a medical health insurance plan from the start of an outcome-specific clean window to the COVID-19 vaccination dose.\n\nExposureExposure was defined as receipt of a monovalent BNT162b2, mRNA-1273, or NVX-CoV2373 COVID-19 vaccine dose. The primary analysis evaluated dose 1 and dose 2 combined, and secondary analyses evaluated each dose separately. Follow-up time was censored at death, disenrollment, end of risk window, end of study period, or a subsequent dose administration.\n\nMain OutcomesTwenty-one prespecified health outcomes.\n\nResultsThe study included 4,102,016 enrollees aged 6 months to17 years. Thirteen of 15 outcomes sequentially tested did not meet the threshold for a statistical signal. In the primary analysis, myocarditis or pericarditis signals were detected following BNT162b2 vaccine in children aged 12-17 years old and seizures/convulsions signals were detected following vaccination with BNT162b2 and mRNA-1273 in children aged 2-4/5 years. However, in a post-hoc sensitivity analysis, the seizures/convulsions signal was sensitive to background rates selection and was not observed when 2022 background rates were selected instead of 2020 rates.\n\nConclusions and RelevanceOf the two signaled outcomes, the myocarditis or pericarditis signals are consistent with previously published reports. The new signal detected for seizures/convulsions among younger children should be further investigated in a robust epidemiological study with better confounding adjustment.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSDid active monitoring detect statistical signals for health outcomes following monovalent COVID-19 vaccination in the US children aged 6 months to 17 years?\n\nFindingsIn this study including 4,102,106 vaccinated enrollees from three commercial claims databases, myocarditis or pericarditis signaled after BNT162b2 (12-17 years) and a new signal was detected for seizures/convulsions after BNT162b2 (2-4 years) and mRNA1273 COVID-19 vaccinations (2-5 years).\n\nMeaningNear real-time monitoring of vaccines can rapidly identify potential safety concerns. While the myocarditis or pericarditis signal is consistent with existing evidence, the new seizures/convulsions signal should be interpreted cautiously given study limitations.", - "rel_num_authors": 26, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.10.10.23296624", + "rel_abs": "In January 2023, the United States Food and Drug Administration and the Centers for Disease Control and Prevention noted a safety concern for ischemic stroke in adults [≥]65 years receiving the BNT162b2; WT/OMI BA.4/BA.5 COVID-19 bivalent vaccine. This self-controlled case series analysis evaluated stroke risk among Medicare fee-for-service beneficiaries aged [≥]65 years receiving: 1) a Pfizer-BioNTech (BNT162b2; WT/OMI BA.4/BA.5) or Moderna (mRNA-1273.222) COVID-19 bivalent vaccine, 2) high-dose/adjuvanted influenza vaccines, and 3) concomitant COVID-19 bivalent vaccines and influenza vaccines, from August 31 to November 6, 2022.\n\nThe primary analysis did not find elevated stroke risk following COVID-19 bivalent vaccines. In the age subgroup analyses, only the [≥]85 year age group had a risk of NHS (Incident Rate Ratio (IRR)=1.36, 95% CI 1.09 - 1.69 [1-21 days]) and NHS/TIA (IRR=1.28, 95% CI 1.08 - 1.52 [1-21 days]) with BNT162b2 Bivalent WT/OMI BA.4/BA.5. Among beneficiaries receiving a concomitant COVID-19 bivalent vaccine and a high-dose/adjuvanted influenza vaccine, an increased risk was observed for NHS (IRR=1.20, 95% CI 1.01 - 1.42 [22-42 days]) with BNT162b2 Bivalent WT/OMI BA.4/BA.5 and for TIA (IRR=1.35, 95% CI 1.06 - 1.74 [1-21 days]) with mRNA-1273.222.\n\nResults of the secondary analyses showed a small increased risk of NHS following high-dose or adjuvanted influenza vaccines (IRR=1.09, 95% CI 1.02 - 1.17 [22-42 days]).", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Patricia C. Lloyd", - "author_inst": "US Food and Drug Administration, Silver Spring, MD, USA" - }, - { - "author_name": "Mao Hu", - "author_inst": "Acumen LLC, Burlingame, CA, USA" - }, - { - "author_name": "Azadeh Shoaibi", - "author_inst": "US Food and Drug Administration" - }, - { - "author_name": "Yuhui Feng", - "author_inst": "Acumen LLC, Burlingame, CA, USA" - }, - { - "author_name": "Hui Lee Wong", - "author_inst": "US Food and Drug Administration, Silver Spring, MD, USA" - }, - { - "author_name": "Elizabeth R. Smith", - "author_inst": "Acumen LLC, Burlingame, CA, USA" - }, - { - "author_name": "Kandace L. Amend", - "author_inst": "Optum Epidemiology, Boston, MA, USA" - }, - { - "author_name": "Annemarie Kline", - "author_inst": "CVS Health Clinical Trial Services, Blue Bell, PA, USA" - }, - { - "author_name": "Daniel C. Beachler", - "author_inst": "Carelon Research, Wilmington, DE, USA" - }, - { - "author_name": "Joann F. Gruber", - "author_inst": "US Food and Drug Administration, Silver Spring, MD, USA" - }, - { - "author_name": "Mahasweta Mitra", - "author_inst": "Acumen LLC, Burlingame, CA, USA" - }, - { - "author_name": "John D. Seeger", - "author_inst": "Optum Epidemiology, Boston, MA, USA" - }, - { - "author_name": "Charlalynn Harris", - "author_inst": "CVS Health Clinical Trial Services, Blue Bell, PA, USA" - }, - { - "author_name": "Alex Secora", - "author_inst": "IQVIA, Falls Church, VA, USA" + "author_name": "Yun Lu", + "author_inst": "Food and Drug Administration" }, { - "author_name": "Joyce Obidi", - "author_inst": "US Food and Drug Administration, Silver Spring, MD, USA" + "author_name": "Kathryn Matuska", + "author_inst": "Acumen, LLC" }, { - "author_name": "Jing Wang", - "author_inst": "Acumen LLC, Burlingame, CA, USA" + "author_name": "Gita Nadimpalli", + "author_inst": "Acumen, LLC" }, { - "author_name": "Jennifer Song", - "author_inst": "Optum Epidemiology, Boston, MA, USA" + "author_name": "Yuxin Ma", + "author_inst": "Acumen, LLC" }, { - "author_name": "Cheryl N. McMahill-Walraven", - "author_inst": "CVS Health Clinical Trial Services, Blue Bell, PA, USA" + "author_name": "Nathan Duma", + "author_inst": "Acumen, LLC" }, { - "author_name": "Christian Reich", - "author_inst": "IQVIA, Falls Church, VA, USA" + "author_name": "Henry Zhang", + "author_inst": "Food and Drug Administration" }, { - "author_name": "Rowan McEvoy", - "author_inst": "Acumen LLC, Burlingame, CA, USA" + "author_name": "Yiyun Chiang", + "author_inst": "Acumen, LLC" }, { - "author_name": "Rose Do", - "author_inst": "Acumen LLC, Burlingame, CA, USA" + "author_name": "Hai Lyu", + "author_inst": "Acumen, LLC" }, { "author_name": "Yoganand Chillarige", - "author_inst": "Acumen LLC, Burlingame, CA, USA" - }, - { - "author_name": "Robin Clifford", - "author_inst": "Optum Epidemiology, Boston, MA, USA" - }, - { - "author_name": "Danielle D. Cooper", - "author_inst": "CVS Health Clinical Trial Services, Blue Bell, PA, USA" + "author_inst": "Acumen, LLC" }, { "author_name": "Richard A. Forshee", - "author_inst": "US Food and Drug Administration, Silver Spring, MD, USA" + "author_inst": "Food And Drug Administration" }, { "author_name": "Steven A. Anderson", - "author_inst": "US Food and Drug Administration, Silver Spring, MD, USA" + "author_inst": "Food and Drug Administration" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.10.12.561995", @@ -3421,259 +3572,55 @@ "category": "physiology" }, { - "rel_doi": "10.1101/2023.10.08.561395", - "rel_title": "LETHAL COVID-19 ASSOCIATES WITH RAAS-INDUCED INFLAMMATION FOR MULTIPLE ORGAN DAMAGE INCLUDING MEDIASTINAL LYMPH NODES", + "rel_doi": "10.1101/2023.10.09.561473", + "rel_title": "The SARS-CoV-2 Spike is a virulence determinant and plays a major role on the attenuated phenotype of Omicron virus in a feline model of infection", "rel_date": "2023-10-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.10.08.561395", - "rel_abs": "Lethal COVID-19 outcomes are most often attributed to classic cytokine storm and attendant excessive immune signaling. We re-visit this question using RNA sequencing in nasopharyngeal and 40 autopsy samples from COVID-19-positive and negative individuals. In nasal swabs, the top 100 genes which significantly correlated with COVID-19 viral load, include many canonical innate immune genes. However, 22 much less studied \"non-canonical\" genes are found and despite the absence of viral transcripts, subsets of these are upregulated in heart, lung, kidney, and liver, but not mediastinal lymph nodes. An important regulatory potential emerges for the non-canonical genes for over-activating the renin-angiotensin-activation-system (RAAS) pathway, resembling this phenomenon in hereditary angioedema (HAE) and its overlapping multiple features with lethal COVID-19 infections. Specifically, RAAS overactivation links increased fibrin deposition, leaky vessels, thrombotic tendency, and initiating the PANoptosis death pathway, as suggested in heart, lung, and especially mediastinal lymph nodes, with a tightly associated mitochondrial dysfunction linked to immune responses. For mediastinal lymph nodes, immunohistochemistry studies validate the transcriptomic findings showing abnormal architecture, excess fibrin and collagen deposition, and pathogenic fibroblasts. Further, our findings overlap findings in COVID-19 infected hamsters, C57BL/6 and BALB/c mouse models, and importantly peripheral blood mononuclear cell (PBMC) and whole blood samples from COVID-19 patients infected with early variants and later SARS-CoV-2 Omicron strains. We thus present cytokine storm in lethal COVID-19 disease as an interplay between upstream immune gene signaling producing downstream RAAS overactivation with resultant severe organ damage, especially compromising mediastinal lymph node function.", - "rel_num_authors": 60, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.10.09.561473", + "rel_abs": "To assess the role of the Omicron BA.1 Spike (S) protein in the pathogenesis of the severe acute respiratory coronavirus 2 (SARS-CoV-2), we generated recombinant viruses harboring the S D614G mutation (rWA1-D614G) and the Omicron BA.1 S gene (rWA1-Omi-S) in the backbone of the ancestral SARS-CoV-2 WA1 strain genome. The recombinant viruses were characterized in vitro and in vivo. Viral entry, cell-cell fusion, viral plaque size, and viral replication kinetics of the rWA1-Omi-S virus were markedly impaired when compared to the rWA1-D614G virus, demonstrating a lower fusogenicity and ability to spread cell-to-cell of rWA1-Omi-S. To assess the contribution of the Omicron BA.1 S protein to SARS-CoV-2 pathogenesis the pathogenicity of rWA1-D614G and rWA1-Omi-S viruses were compared using a feline model of infection. While the rWA1-D614G-inoculated cats became lethargic and showed increased body temperatures on days 2 and 3 post-infection (pi), rWA1-Omi-S-inoculated cats remained subclinical and gained weight throughout the 14-day experimental period. Animals inoculated with rWA1-D614G presented higher levels of infectious virus shedding in nasal secretions, when compared to rWA1-Omi-S-inoculated animals. In addition, tissue replication of the rWA1-Omi-S was markedly reduced compared to the rWA1-D614G, as evidenced by lower in situ viral RNA and lower viral load in tissues on days 3 and 5 pi. Histologic examination of the nasal turbinate and lungs revealed intense inflammatory infiltration in rWA1-D614G-inoculated animals, whereas rWA1-Omi-S-inoculated cats presented only mild to modest inflammation. Together, these results demonstrate that the S protein is a major virulence determinant for SARS-CoV-2 playing a major role for the attenuated phenotype of the Omicron virus.\n\nAuthor summaryThe SARS-CoV-2 Omicron sublineage BA.1 spread rapidly across the globe in late 2021/early 2022. Experimental studies have shown an overall lower pathogenicity of Omicron BA.1 when compared to the ancestral SARS-CoV-2 lineage B.1 (D614G). Recently, we have demonstrated that the Omicron BA.1.1 variant presents lower pathogenicity when compared to D614G (B.1) lineage in a feline model of SARS-CoV-2 infection. There are over 50 mutations in the Omicron genome, of which more than two thirds are present in the S gene. To assess the role of the Omicron BA.1 S on virus pathogenesis, recombinant viruses harboring the S D614G mutation (rWA1-D614G) and the Omicron BA.1 Spike gene (rWA1-Omi-S) in the backbone of the ancestral SARS-CoV-2 WA1 were characterized in vitro and in vivo. While the Omicron BA.1 S gene results in early entry into cells, the rWA1-Omi-S presents impaired cell-cell spread and fusogenic activity. Inoculation of cats with the recombinant viruses revealed an attenuated phenotype of rWA1-Omi-S, demonstrating a critical role for S protein on the pathogenicity of SARS-CoV-2 and indicating that the Omi-S is a major determinant of the attenuated disease phenotype of Omicron strains.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Joseph W Guarnieri", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Michael Topper", - "author_inst": "Johns Hopkins School of Medicine" - }, - { - "author_name": "Katherine Beigel", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Jeff A Haltoom", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Amy Chadburn", - "author_inst": "Weill Cornell Medical College" - }, - { - "author_name": "Justin Frere", - "author_inst": "Icahn School of Medicine" - }, - { - "author_name": "Julia An", - "author_inst": "Johns Hopkins School of Medicine" - }, - { - "author_name": "Henry Cope", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Alain Borczuk", - "author_inst": "Weill Cornell Medical College" - }, - { - "author_name": "Saloni Sinha", - "author_inst": "Weill Cornell Medical College" - }, - { - "author_name": "Christine Lim", - "author_inst": "Weill Cornell Medical College" - }, - { - "author_name": "JangKeun Kim", - "author_inst": "Weill Cornell Medical College" - }, - { - "author_name": "Jiwoon Park", - "author_inst": "Weill Cornell Medical College" - }, - { - "author_name": "Cem Meydan", - "author_inst": "Weill Cornell Medical College" - }, - { - "author_name": "Jonathan Foox", - "author_inst": "Weill Cornell Medical College" - }, - { - "author_name": "Christopher Mozsary", - "author_inst": "Weill Cornell Medical College" - }, - { - "author_name": "Yaron Bram", - "author_inst": "Weill Cornell Medical College" - }, - { - "author_name": "Stephanie Richard", - "author_inst": "Uniformed Services University, Infectious Disease Clinical Research Program" - }, - { - "author_name": "Nusrat Epsi", - "author_inst": "Uniformed Services University, Infectious Disease Clinical Research Program & Henry M. Jackson Foundation for the Advancement of Military Medicine Inc" - }, - { - "author_name": "Brian Agan", - "author_inst": "Uniformed Services University, Infectious Disease Clinical Research Program & Henry M. Jackson Foundation for the Advancement of Military Medicine Inc" - }, - { - "author_name": "Josh Chenoweth", - "author_inst": "Henry M. Jackson Foundation for the Advancement of Military Medicine Inc" - }, - { - "author_name": "Mark Simons", - "author_inst": "Uniformed Services University, Infectious Disease Clinical Research Program" - }, - { - "author_name": "David Tribble", - "author_inst": "Uniformed Services University, Infectious Disease Clinical Research Program" - }, - { - "author_name": "Timothy Burgess", - "author_inst": "Uniformed Services University, Infectious Disease Clinical Research Program" - }, - { - "author_name": "Clifton L. Dalgard", - "author_inst": "Uniformed Services University of the Health Sciences" - }, - { - "author_name": "Mark T. Heise", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Nathaniel Moorman", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Victoria Baxter", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Emily A. Madden", - "author_inst": "University of North Carolina Chapel Hill" - }, - { - "author_name": "Sharon Taft-Benz", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Elizabeth Anderson", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Wes A. Sanders", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Rebekah J. Dickmander", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Gabrielle A. Widjaja", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Kevin Janssen", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Timothy Lie", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Deborah G Murdock", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Alessia Angelin", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Yentli E. S. Albrecht", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Arnold Olali", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Zimu Cen", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Joseph M. Dybas", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Waldemar Priebe", - "author_inst": "University of Texas MD Anderson Cancer Center" - }, - { - "author_name": "Mark R. Emmett", - "author_inst": "University of Texas Medical Branch" - }, - { - "author_name": "Sonja Best", - "author_inst": "NIAID/NIH" - }, - { - "author_name": "Maya Kelsey Johnson", - "author_inst": "Johns Hopkins School of Medicine" - }, - { - "author_name": "Kevin B. Clark", - "author_inst": "Cures Within Reach" - }, - { - "author_name": "Viktoria Zaksiene", - "author_inst": "University of Chicago & Clever Research Lab" - }, - { - "author_name": "Rob Miller", - "author_inst": "Morehouse School of Medicine" - }, - { - "author_name": "Peter Grabhamr", - "author_inst": "Columbia University" - }, - { - "author_name": "Jonathan C Schisler", - "author_inst": "The University of North Carolina at Chapel Hill" - }, - { - "author_name": "Pedro Moraes-Vieira", - "author_inst": "University of Campinas" + "author_name": "Mathias Martins", + "author_inst": "Cornell University College of Veterinary Medicine" }, { - "author_name": "Simon Pollett", - "author_inst": "Uniformed Services University, Infectious Disease Clinical Research Program & Henry M. Jackson Foundation for the Advancement of Military Medicine Inc" + "author_name": "Mohammed Nooruzzaman", + "author_inst": "Cornell University College of Veterinary Medicine" }, { - "author_name": "Christopher E. Mason", - "author_inst": "Weill Cornell Medical College" + "author_name": "Jessie Lee Cunningham", + "author_inst": "Cornell University College of Veterinary Medicine" }, { - "author_name": "Eve Syrkin Wurtele", - "author_inst": "Iowa State University" + "author_name": "Chengjin Ye", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Deanne Taylor", - "author_inst": "Children's Hospital of Philadelphia & University of Pennsylvania" + "author_name": "Leonardo Cardia Caserta", + "author_inst": "Cornell University College of Veterinary Medicine" }, { - "author_name": "Robert E. Schwartz", - "author_inst": "Weill Cornell Graduate School of Medical Sciences" + "author_name": "Nathaniel Jackson", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Afshin Beheshti", - "author_inst": "Broad Institute of MIT and Harvard & NASA Ames Research Center" + "author_name": "Luis Martinez-Sobrido", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Douglas C. Wallace", - "author_inst": "Children's Hospital of Philadelphia & University of Pennsylvania" + "author_name": "Ying Fang", + "author_inst": "University of Illinois Urbana-Champaign College of Veterinary Medicine" }, { - "author_name": "Stephen B. Baylin", - "author_inst": "Johns Hopkins University, School of Medicine" + "author_name": "Diego G. Diel", + "author_inst": "Cornell University College of Veterinary Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2023.10.09.23296732", @@ -5435,55 +5382,27 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.10.03.23296474", - "rel_title": "Prevalence and factors associated with fear of COVID-19 in military personnel during the second epidemic wave in Peru", + "rel_doi": "10.1101/2023.10.02.560514", + "rel_title": "A tale of two springs: contrasting forest soundscapes during the COVID-19 lockdown (2020) and after the record snowstorm Filomena (2021) from Central Spain", "rel_date": "2023-10-03", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.10.03.23296474", - "rel_abs": "There is few research in military members that provided protection and security during the COVID-19 crisis. We aimed to determine the prevalence and factors associated with fear of COVID-19 in military members. A cross-sectional study was conducted between November 02 and 09, 2021, during the second wave of the COVID-19 pandemic in the region of Lambayeque, Peru. The outcome was fear of COVID-19, measured with the Fear of COVID-19 Scale. The association with resilience (abbreviated CD-RISC), food insecurity (HFIAS), physical activity (IPAQ-S), eating disorder (EAT-26), and other socio-labor variables were assessed. Of 525 participants, the median age was 22, 95.8% were male, and 19.2% experienced fear of COVID-19. A higher prevalence of fear of COVID-19 was associated with age (PR=1.03; 95% CI: 1.01-1.06), religion (PP=2.05; 95% CI: 1.04-4.05), eating disorder (PR=2.95; 95% CI: 1.99-4.36), and having a relative with mental disorder (PR=2.13; 95% CI: 1.09-4.17). Overweight (PR=0.58; 95% IC: 0.37-0.90) and a high level of resilience (PR=0.63; 95% IC: 0.43-0.93) were associated with a lower prevalence of fear of COVID-19. Two out of ten military personnel were afraid of COVID-19. We recommend special attention to the factors associated with the development of suicide risk in military personnel.", - "rel_num_authors": 9, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.10.02.560514", + "rel_abs": "During the COVID-19 pandemic, humanity temporarily retired from the outdoors. The strict lockdown measures in Spain coincided with the onset of the nesting season of birds, thriving in an unusually quiet environment. Here, we have recorded in forests near San Lorenzo de El Escorial (Central Spain) during the lockdown period in 2020, and the closer to normal spring in 2021. We found strong differences in soundscapes by recording year and location, regardless of the effects of meteorology and human mobility. Species altered their behaviour by increasing their calling intensity during 2021 to cope with higher noise levels, however, acoustic activity was generally less diverse and complex. The difference between years was particularly detrimental for the highest-pitched biophony in 2021. We interpret that an extreme snowfall, Filomena, may have caused a mortality event with lasting effects in the community during the 2021 spring. Since extreme climatic events are likely going to keep happening in the area due to climate change, our data is a useful baseline to guide future conservation efforts, and examine how our activity and climate change are changing the soundscapes of Spanish Mediterranean forests.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Danai Valladares-Garrido", - "author_inst": "Universidad Cesar Vallejo" - }, - { - "author_name": "Helena Dominguez-Troncos", - "author_inst": "Universidad Nacional de Piura" - }, - { - "author_name": "Cinthia Karina Pic\u00f3n-Re\u00e1tegui", - "author_inst": "Universidad San Martin de Porres" - }, - { - "author_name": "Christopher Valdiviezo-Morales", - "author_inst": "Universidad Nacional de Piura" - }, - { - "author_name": "V\u00edctor J. Vera-Ponce", - "author_inst": "Universidad Ricardo Palma" - }, - { - "author_name": "Virgilio E. Failoc-Rojas", - "author_inst": "Universidad San Ignacio de Loyola" - }, - { - "author_name": "C\u00e9sar Johan Pereira-Victorio", - "author_inst": "Universidad Continental" - }, - { - "author_name": "Darwin A. Le\u00f3n - Figueroa", - "author_inst": "Universidad San Martin de Porres" + "author_name": "R\u00fcdiger Ortiz-\u00c1lvarez", + "author_inst": "Centre for Advanced Studies of Blanes (CEAB), Spanish Research Council (CSIC), 17300-Blanes, Spain" }, { - "author_name": "Mario J. Valladares-Garrido", - "author_inst": "Universidad Norbert Wiener" + "author_name": "Carmen Leiva-Due\u00f1as", + "author_inst": "Department of Bioscience, Aarhus University, Vejlsovej 25, DK-8600 Silkeborg, Denmark" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "ecology" }, { "rel_doi": "10.1101/2023.09.29.23296142", @@ -6551,7 +6470,7 @@ "rel_date": "2023-09-29", "rel_site": "bioRxiv", "rel_link": "https://biorxiv.org/cgi/content/short/2023.09.28.560070", - "rel_abs": "Turmeric extract (TE) with curcumin as its main active ingredient has been studied as a potential COVID-19 therapeutic. Curcumin has been studied in silico and in vitro against a naive SARS-CoV-2 virus, yet little is known about TEs impact on SARS-CoV-2 infection. Moreover, no study reveals the potentials of both curcumin and TE on the inhibition of SARS-CoV-2 cell-to-cell transmission. Here, we investigated the effects of both curcumin and TE on the inhibition of SARS-CoV-2 entry and cell-to-cell transmission using pseudovirus (PSV) and syncytia models. We performed PSV entry assay in 293T or 293 cells expressing hACE2. The cells were pretreated with curcumin or TE, then treated with PSV with or without the test samples. Next, we carried out syncytia assay by co-transfecting 293T cells with plasmids encoding Spike, hACE2, and TMPRSS2 to be treated with the test samples. The results showed that in PSV entry assay on 293T/hACE/TMPRSS2 cells, both curcumin and TE inhibited PSV entry at concentrations of 1 {micro}M and 10 {micro}M for curcumin and 1 {micro}g/ml and 10 {micro}g/ml for TE. Moreover, both curcumin and TE also reduced syncytia formation compared to control cells. Based on our study, both TE and curcumin are potential inhibitors of SARS-CoV-2 infection at entry points, either by direct or indirect infection models.\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=165 SRC=\"FIGDIR/small/560070v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (29K):\norg.highwire.dtl.DTLVardef@b3b2a1org.highwire.dtl.DTLVardef@1947dedorg.highwire.dtl.DTLVardef@1d791fdorg.highwire.dtl.DTLVardef@1b1a305_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_abs": "Turmeric extract (TE) with curcumin as its main active ingredient has been studied as a potential COVID-19 therapeutic. Curcumin has been studied in silico and in vitro against a naive SARS-CoV-2 virus, yet little is known about TEs impact on SARS-CoV-2 infection. Moreover, no study reveals the potentials of both curcumin and TE on the inhibition of SARS-CoV-2 cell-to-cell transmission. Here, we investigated the effects of both curcumin and TE on the inhibition of SARS-CoV-2 entry and cell-to-cell transmission using pseudovirus (PSV) and syncytia models. We performed PSV entry assay in 293T or 293 cells expressing hACE2. The cells were pretreated with curcumin or TE, then treated with PSV with or without the test samples. Next, we carried out syncytia assay by co-transfecting 293T cells with plasmids encoding Spike, hACE2, and TMPRSS2 to be treated with the test samples. The results showed that in PSV entry assay on 293T/hACE/TMPRSS2 cells, both curcumin and TE inhibited PSV entry at concentrations of 1 {micro}M and 10 {micro}M for curcumin and 1 {micro}g/ml and 10 {micro}g/ml for TE. Moreover, both curcumin and TE also reduced syncytia formation compared to control cells. Based on our study, both TE and curcumin are potential inhibitors of SARS-CoV-2 infection at entry points, either by direct or indirect infection models.\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=165 SRC=\"FIGDIR/small/560070v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (29K):\norg.highwire.dtl.DTLVardef@7bfb36org.highwire.dtl.DTLVardef@1a9b332org.highwire.dtl.DTLVardef@33c287org.highwire.dtl.DTLVardef@2842b6_HPS_FORMAT_FIGEXP M_FIG C_FIG", "rel_num_authors": 7, "rel_authors": [ { @@ -6941,55 +6860,43 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.09.28.559747", - "rel_title": "Efficient inhibition of fusion inhibitor HY3000 peptide to SARS-CoV-2 emerging EG.5, EG.5.1 and BA.2.86 variants", + "rel_doi": "10.1101/2023.09.27.23296231", + "rel_title": "An extended catalytic model to assess changes in risk for multiple reinfections with SARS-CoV-2", "rel_date": "2023-09-28", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.09.28.559747", - "rel_abs": "SARS-CoV-2 continues to evolve and spread. Recently, the Omicron EG.5 lineage, bearing an additional F456L mutation in spike (S) protein compared to its ancestor XBB.1.9.2, and its sub-variant EG.5.1, which carries a further Q52H mutation, have raised concerns due to their increased prevalence and extended immune escape properties. Additionally, an alarming variant, BA.2.86, has also garnered global concern because it contains over 30 amino acid mutations in its S protein compared to BA.2, including more than 10 changes in receptor-binding domain (RBD), reminiscent of the appearance of the Omicron variant in late 2021. Therefore, there is an urgent need to assess the effectiveness of current vaccines and therapeutics against EG.5, EG.5.1 and BA.2.86. In our previous work, we reported the design and broad-spectrum antiviral activity of a peptide fusion inhibitor HY3000 against SARS-CoV-2 and its variants including XBB.1.5. Here, we continued to evaluate the inhibitory potency of the HY3000 peptide against the prevailing EG.5 and EG.5.1, as well as XBB.1.16, FL.1.5.1, FY.3 and BA.2.86. Our data indicated that the peptide retained its potent inhibitory activities against these variants, indicating its potential as a good virus fusion inhibitor with broad-spectrum therapeutic effect against current and future SARS-CoV-2 variants. Currently, the HY3000 has been finished in Phase II clinical trial in China and has also been approved to conduct clinical investigation by U.S. Food and Drug Administration (FDA), suggesting a good application prospect against the ongoing COVID-19.", - "rel_num_authors": 9, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.27.23296231", + "rel_abs": "BackgroundThe SARS-CoV-2 pandemic has illustrated that monitoring trends in multiple infections can provide insight into the biological characteristics of new variants. Following several pandemic waves, many people have already been infected and reinfected by SARS-CoV-2 and therefore methods are needed to understand the risk of multiple reinfections.\n\nObjectivesIn this paper, we extended an existing catalytic model designed to detect increases in the risk of reinfection by SARS-CoV-2 to detect increases in the population-level risk of multiple reinfections.\n\nMethodsThe catalytic model assumes the risk of reinfection is proportional to observed infections and uses a Bayesian approach to fit model parameters to the number of nth infections among individuals whose (n - 1)th infection was observed at least 90 days before. Using a posterior draw from the fitted model parameters, a 95% projection interval of daily nth infections is calculated under the assumption of a constant nth infection hazard coefficient. An additional model parameter was introduced to consider the increased risk of reinfection detected during the Omicron wave. Validation was performed to assess the models ability to detect increases in the risk of third infections.\n\nKey FindingsThe model parameters converged when applying the models fitting and projection procedure to the number of observed third SARS-COV-2 infections in South Africa. No additional increase in the risk of third infection was detected after the increase detected during the Omicron wave. The validation of the third infections method showed that the model can successfully detect increases in the risk of third infections under different scenarios.\n\nLimitationsEven though the extended model is intended to detect the risk of nth infections, the method was only validated for detecting increases in the risk of third infections and not for four or more infections. The method is very sensitive to low numbers of nth infections, so it might not be usable in settings with small epidemics, low coverage of testing or early in an outbreak.\n\nConclusionsThe catalytic model to detect increases in the risk of reinfections was successfully extended to detect increases in the risk of nth infections and could contribute to future detection of increases in the risk of nth infections by SARS-CoV-2 or other similar pathogens.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Lili Wu", - "author_inst": "Institute of Microbiology, Chinese Academy of Sciences" - }, - { - "author_name": "Anqi Zheng", - "author_inst": "Institute of Microbiology, Chinese Academy of Sciences" - }, - { - "author_name": "Yangming Tang", - "author_inst": "Hybio Pharmaceutical Co., Ltd." - }, - { - "author_name": "Xiaoyun Wang", - "author_inst": "Institute of Microbiology, Chinese Academy of Sciences" + "author_name": "Belinda Lombard", + "author_inst": "Stellenbosch University" }, { - "author_name": "Yue Gao", - "author_inst": "Institute of Microbiology, Chinese Academy of Sciences" + "author_name": "Cheryl Cohen", + "author_inst": "University of the Witwatersrand Johannesburg; National Institute for Communicable Diseases" }, { - "author_name": "Wenwen Lei", - "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention" + "author_name": "Anne von Gottberg", + "author_inst": "National Institute for Communicable Diseases" }, { - "author_name": "Guizhen Wu", - "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention" + "author_name": "Jonathan Dushoff", + "author_inst": "McMaster University Faculty of Science" }, { - "author_name": "Qihui Wang", - "author_inst": "Institute of Microbiology, Chinese Academy of Sciences" + "author_name": "Cari van Schalkwyk", + "author_inst": "SACEMA, Stellenbosch University" }, { - "author_name": "George F. Gao", - "author_inst": "Institute of Microbiology, Chinese Academy of Sciences" + "author_name": "Juliet Pulliam", + "author_inst": "SACEMA, Stellenbosch University" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "microbiology" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.09.26.559580", @@ -8835,39 +8742,107 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.09.20.23295863", - "rel_title": "Effectiveness of Sinopharm's BBIBP-CorV Booster Vaccination Against COVID-19-Related Severe and Critical Cases and death in Morocco During the Omicron Wave", + "rel_doi": "10.1101/2023.09.22.23295541", + "rel_title": "Omicron Breakthrough Infection Elicits Superior Humoral and Mucosal Immune Responses to SARS-CoV-2 Variants than an Intramuscular Booster Dose", "rel_date": "2023-09-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.20.23295863", - "rel_abs": "ObjectiveThis study investigates the effectiveness of booster doses on the Omicron wave in Morocco against COVID-19 severe and critical hospitalizations and deaths;\n\nParticipants/methodsThis study uses nationally representative data on COVID-19 from 15 December 2021 to 31 January 2022. To investigate the effectiveness of the inactivated COVID-19 vaccine BBIBP-CorV (Vero Cells) Sinopharm booster doses on the Omicron wave in morocco by using real-world data established from nationally representative statistics on COVID-19 cases, deaths and vaccinations.\n\nStatistical AnalysesThe screening method was used to estimate vaccine effectiveness against COVID-19 severe or critical hospitalization and COVID-19-related deaths. The data were grouped by, age subgroup, sex, week, and geographical area and were analyzed by using binary logistic regression with an offset for vaccine coverage.\n\nResultsThe overall sinopharm VE estimate is 89% (95% CI 85 to 92) effective in curbing COVID-19 death, and 81% (95% CI 78 to 84 in curbing COVID-19 severe critical hospitalization. Death-related VE estimate was 86% (95% CI 81 to 90) for patients aged 1Z65 years, 96% (95% CI 90 to 98) for those aged < 65 years, 95% (95% CI 88 to 98) in no risk factor patient was, 91% (95% CI 85 to 94) with 1 risk factor; 90% (95% CI 83 to 95) with 2 risk factors; 72% (95% CI 52 to 84) in patient with 3 risk factors and more. Severe critical hospitalization VE, estimate was 78% (95% CI 74 to 82) for patients aged 1Z65 years, 87% (95% CI 82 to 90) for those aged < 65 years, 86% (95% CI 80 to 90) in no risk factor patient was, 80% (95% CI 73 to 84) with 1 risk factor; 80% (95% CI 70 to 85) with 2 risk factors; 80% (95% CI 68 to 86) in patient with 3 risk factors and more.\n\nConclusionsSinopharm Boosters are effective in increasing protection against Omicron variant-related COVID-19 death and severe critical hospitalization. The protection is reduced with older age and higher risk factors. These findings emphasize the importance of targeted vaccination strategies for different demographic groups and underscore the protective benefits of the third booster Sinopharm vaccine.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.22.23295541", + "rel_abs": "Our understanding of the quality of cellular and humoral immunity conferred by COVID-19 vaccination alone versus vaccination plus SARS-CoV-2 breakthrough (BT) infection remains incomplete. While the current (2023) SARS-CoV-2 immune landscape of Canadians is complex, in late 2021 most Canadians had either just received a third dose of COVID-19 vaccine, or had received their two dose primary series and then experienced an Omicron BT. Herein we took advantage of this coincident timing to contrast cellular and humoral immunity conferred by three doses of vaccine versus two doses plus BT. Our results show that mild BT infection induces cell-mediated immune responses to variants comparable to an intramuscular vaccine booster dose. In contrast, BT subjects had higher salivary IgG and IgA levels against the Omicron Spike and enhanced reactivity to the ancestral Spike for the IgA isotype, which also reacted with SARS-CoV-1. Serum neutralizing antibody levels against the ancestral strain and the variants were also higher after BT infection. Our results support the need for mucosal vaccines to emulate the enhanced mucosal and humoral immunity induced by Omicron without exposing individuals to the risks associated with SARS-CoV-2 infection.\n\nONE SENTENCE SUMMARYOmicron breakthrough elicits cross-reactive systemic and mucosal immune responses in fully vaccinated adults.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC=\"FIGDIR/small/23295541v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (27K):\norg.highwire.dtl.DTLVardef@343f4org.highwire.dtl.DTLVardef@624e55org.highwire.dtl.DTLVardef@4c430org.highwire.dtl.DTLVardef@ec39ae_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Jihane Belayachi", - "author_inst": "Mohammed V University in Rabat," + "author_name": "Sabryna Nantel", + "author_inst": "Sainte-Justine University Hospital and Research Center, Montreal, Quebec, Canada" }, { - "author_name": "Abdelkader Mhayi", - "author_inst": "Ministry of health and social protection, Rabat, Morocco" + "author_name": "Salma Sheikh-Mohamed", + "author_inst": "Department of Immunology, University of Toronto, Toronto, Ontario, Canada" }, { - "author_name": "Hind Mjidi", - "author_inst": "Ministry of health and social protection, Rabat, Morocco" + "author_name": "Gary Y. C. Chao", + "author_inst": "Department of Immunology, University of Toronto, Toronto, Ontario, Canada" }, { - "author_name": "EL FAHIME Elmostafa", - "author_inst": "National Center for Scientific and Technical Research , Rabat, Morocco" + "author_name": "Alexandra Kurtesi", + "author_inst": "Lunenfeld-Tunenbaum Research Institute at Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada" }, { - "author_name": "Redouane Abouqal", - "author_inst": "Mohamed V University in Rabat, Morocco" + "author_name": "Queenie Hu", + "author_inst": "Lunenfeld-Tunenbaum Research Institute at Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada" + }, + { + "author_name": "Heidi Wood", + "author_inst": "One Health Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada" + }, + { + "author_name": "Karen Colwill", + "author_inst": "Lunenfeld-Tunenbaum Research Institute at Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada" + }, + { + "author_name": "Zhijie Li", + "author_inst": "Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada" + }, + { + "author_name": "Ying Liu", + "author_inst": "Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada" + }, + { + "author_name": "Laurie Seifried", + "author_inst": "Department of Immunology, University of Toronto, Toronto, Ontario, Canada" + }, + { + "author_name": "Beno\u00eete Bourdin", + "author_inst": "Sainte-Justine University Hospital and Research Center, Montreal, Quebec, Canada" + }, + { + "author_name": "Allison McGeer", + "author_inst": "Lunenfeld-Tunenbaum Research Institute at Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada" + }, + { + "author_name": "William R. Hardy", + "author_inst": "Lunenfeld-Tunenbaum Research Institute at Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada" + }, + { + "author_name": "Olga L. Rojas", + "author_inst": "Department of Immunology, University of Toronto, Toronto, Ontario, Canada" + }, + { + "author_name": "Mario A. Ostrowski", + "author_inst": "Department of Immunology, University of Toronto, Toronto, Ontario, Canada" + }, + { + "author_name": "Mark A. Brockman", + "author_inst": "Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada" + }, + { + "author_name": "Ciriaco A. Piccirillo", + "author_inst": "Department of Microbiology and Immunology, McGill University, Montreal, Quebec, Canada" + }, + { + "author_name": "Caroline Quach", + "author_inst": "Sainte-Justine University Hospital and Research Center, Montreal, Quebec, Canada" + }, + { + "author_name": "James M. Rini", + "author_inst": "Departments of Molecular Genetics & Biochemistry, University of Toronto, Toronto, Ontario, Canada" + }, + { + "author_name": "Anne-Claude Gingras", + "author_inst": "Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada" + }, + { + "author_name": "H\u00e9l\u00e8ne Decaluwe", + "author_inst": "Sainte-Justine University Hospital and Research Center, Montreal, Quebec, Canada" + }, + { + "author_name": "Jennifer L. Gommerman", + "author_inst": "Department of Immunology, University of Toronto, Toronto, Ontario, Canada" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2023.09.21.23295891", @@ -10669,51 +10644,87 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2023.09.15.557994", - "rel_title": "Complete substitution with modified nucleotides suppresses the early interferon response and increases the potency of self-amplifying RNA", + "rel_doi": "10.1101/2023.09.14.23295379", + "rel_title": "A highly divergent SARS-CoV-2 lineage B.1.1 sample in a patient with long-term COVID-19", "rel_date": "2023-09-17", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.09.15.557994", - "rel_abs": "Self-amplifying RNA (saRNA) will revolutionize vaccines and in situ therapeutics by enabling protein expression for longer duration at lower doses. However, a major barrier to saRNA efficacy is the potent early interferon response triggered upon cellular entry, resulting in saRNA degradation and translational inhibition. Substitution of mRNA with modified nucleotides (modNTPs), such as N1-methylpseudouridine (N1m{Psi}), reduce the interferon response and enhance expression levels. Multiple attempts to use modNTPs in saRNA have been unsuccessful, leading to the conclusion that modNTPs are incompatible with saRNA, thus hindering further development. Here, contrary to the common dogma in the field, we identify multiple modNTPs that when incorporated into saRNA at 100% substitution confer immune evasion and enhance expression potency. Transfection efficiency enhances by roughly an order of magnitude in difficult to transfect cell types compared to unmodified saRNA, and interferon production reduces by >8 fold compared to unmodified saRNA in human peripheral blood mononuclear cells (PBMCs). Furthermore, we demonstrate expression of viral antigens in vitro and observe significant protection against lethal challenge with a mouse-adapted SARS-CoV-2 strain in vivo. A modified saRNA vaccine, at 100-fold lower dose than a modified mRNA vaccine, results in a statistically improved performance to unmodified saRNA and statistically equivalent performance to modified mRNA. This discovery considerably broadens the potential scope of self-amplifying RNA, enabling entry into previously impossible cell types, as well as the potential to apply saRNA technology to non-vaccine modalities such as cell therapy and protein replacement.", - "rel_num_authors": 8, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.14.23295379", + "rel_abs": "We report the genomic analysis of a highly divergent SARS-CoV-2 sample obtained in October 2022 from an HIV+ patient with presumably long-term COVID-19 infection. Phylogenetic analysis indicates that the sample is characterized by a gain of 89 mutations since divergence from its nearest sequenced neighbor, which had been collected in September 2020 and belongs to the B.1.1 lineage, largely extinct in 2022. 33 of these mutations were coding and occurred in the Spike protein. Of these, 17 are lineage-defining in some of the variants of concern (VOCs) or are in sites where another mutation is lineage-defining in a variant of concern, and/or shown to be involved in antibody evasion, and/or detected in other cases of persistent COVID-19; these include some \"usual suspects,\" such as Spike:L452R, E484Q, K417T, Y453F, and N460K. Molecular clock analysis indicates that mutations in this lineage accumulated at an increased rate compared to the ancestral B.1.1 strain. This increase is driven by the accumulation of nonsynonymous mutations, for an average dN/dS value of 2.2, indicating strong positive selection during within-patient evolution. Additionally, there is reason to believe that the virus had persisted for at least some time in the gastrointestinal tract, as evidenced by the presence of mutations that are rare in the general population samples but common in samples from wastewater. Our analysis adds to the growing body of research on evolution of SARS-CoV-2 in chronically infected patients and its relationship to the emergence of variants of concern.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Joshua E McGee", - "author_inst": "Boston University" + "author_name": "Elena Nabieva", + "author_inst": "A.A. Kharkevich Institute for Information Transmission Problems, Moscow, Russia" }, { - "author_name": "Jack R Kirsch", - "author_inst": "Boston University" + "author_name": "Andrey B. Komissarov", + "author_inst": "Smorodintsev Research Institute of Influenza, St. Petersburg, Russia" }, { - "author_name": "Devin Kenney", - "author_inst": "Boston University" + "author_name": "Galya V. Klink", + "author_inst": "A.A. Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences, Moscow, Russia;Skolkovo Institute of Science and Technology " }, { - "author_name": "Elizabeth Chavez", - "author_inst": "Boston University" + "author_name": "Stanislav V. Zaitsev", + "author_inst": "Kaluga Regional Specialized Centre for Infectious Diseases and AIDS, Kaluga, Russia" }, { - "author_name": "Ting-Yu Shih", - "author_inst": "Boston University" + "author_name": "Maria Sergeeva", + "author_inst": "Smorodintsev Research Institute of Influenza, St. Petersburg, Russia" }, { - "author_name": "Florian Douam", - "author_inst": "Boston University" + "author_name": "Artem V. Fadeev", + "author_inst": "Smorodintsev Research Institute of Influenza, St. Petersburg, Russia" }, { - "author_name": "Wilson W Wong", - "author_inst": "Boston University" + "author_name": "Kseniya Komissarova", + "author_inst": "Smorodintsev Research Institute of Influenza, St. Petersburg, Russia" }, { - "author_name": "Mark W Grinstaff", - "author_inst": "Boston University" + "author_name": "Anna Ivanova", + "author_inst": "Smorodintsev Research Institute of Influenza, St. Petersburg, Russia" + }, + { + "author_name": "Maria Pisareva", + "author_inst": "Smorodintsev Research Institute of Influenza, St. Petersburg, Russia" + }, + { + "author_name": "Kira Kudrya", + "author_inst": "Smorodintsev Research Institute of Influenza, St. Petersburg, Russia" + }, + { + "author_name": "Daria Danilenko", + "author_inst": "Smorodintsev Research Institute of Influenza, St. Petersburg, Russia" + }, + { + "author_name": "Dmitry Lioznov", + "author_inst": "Smorodintsev Research Institute of Influenza, St. Petersburg, Russia" + }, + { + "author_name": "Ryan Hisner", + "author_inst": "University of Cape Town, Rondebosch, South Africa" + }, + { + "author_name": "Federico Gueli", + "author_inst": "Independent researcher" + }, + { + "author_name": "Thomas P. Peacock", + "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" + }, + { + "author_name": "Cornelius Roemer", + "author_inst": "Biozentrum, University of Basel, Basel, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland" + }, + { + "author_name": "Georgii A. Bazykin", + "author_inst": "A.A. Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences, Moscow, Russia" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "bioengineering" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.09.14.557827", @@ -12175,43 +12186,39 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2023.09.11.557129", - "rel_title": "Expression Level Analysis of ACE2 Receptor Gene in African-American and Non-African-American COVID-19 Patients", + "rel_doi": "10.1101/2023.09.11.556872", + "rel_title": "Comparative Analysis of Association Networks Using Single-Cell RNA Sequencing Data Reveals Perturbation-Relevant Gene Signatures", "rel_date": "2023-09-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.09.11.557129", - "rel_abs": "BackgroundThe COVID-19 pandemic caused by SARS-CoV-2 has spread rapidly across the continents. While the incidence of COVID-19 has been reported to be higher among African-American individuals, the rate of mortality has been lower compared to that of non-African-Americans. ACE2 is involved in COVID-19 as SARS-CoV-2 uses the ACE2 enzyme to enter host cells. Although the difference in COVID-19 incidence can be explained by many factors such as low accessibility of health insurance among the African-American community, little is known about ACE2 expression in African-American COVID-19 patients compared to non-African-American COVID-19 patients. The variable expression of genes can contribute to this observed phenomenon.\n\nMethodologyIn this study, transcriptomes from African-American and non-African-American COVID-19 patients were retrieved from the sequence read archive and analyzed for ACE2 gene expression. HISAT2 was used to align the reads to the human reference genome, and HTseq-count was used to get raw gene counts. EdgeR was utilized for differential gene expression analysis, and enrichR was employed for gene enrichment analysis.\n\nResultsThe datasets included 14 and 33 transcriptome sequences from COVID-19 patients of African-American and non-African-American descent, respectively. There were 24,092 differentially expressed genes, with 7,718 upregulated (log fold change > 1 and FDR 0.05) and 16,374 downregulated (log fold change -1 and FDR 0.05). The ACE2 mRNA level was found to be considerably downregulated in the African-American cohort (p-value = 0.0242, p-adjusted value = 0.038).\n\nConclusionThe downregulation of ACE2 in the African-American cohort could indicate a correlation to the low COVID-19 severity observed among the African-American community.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.09.11.556872", + "rel_abs": "Single-cell RNA sequencing (scRNA-seq) data has elevated our understanding of systemic perturbations to organismal physiology at the individual cell level. However, despite the rich information content of scRNA-seq data, the relevance of genes to a perturbation is still commonly assessed through differential expression analysis. This approach provides a one-dimensional perspective of the transcriptomic landscape, risking the oversight of tightly controlled genes characterized by modest changes in expression but with profound downstream effects. We present GENIX (Gene Expression Network Importance eXamination), a novel platform for constructing gene association networks, equipped with an innovative network-based comparative model to uncover condition-relevant genes. To demonstrate the effectiveness of GENIX, we analyze influenza vaccine-induced immune responses in peripheral blood mononuclear cells (PBMCs) collected from recovered COVID-19 patients, shedding light on the mechanistic underpinnings of gender differences. Our methodology offers a promising avenue to identify genes relevant to perturbation responses in biological systems, expanding the scope of response signature discovery beyond differential gene expression analysis.\n\nHIGHLIGHTSO_LIConventional methods used to identify perturbation-relevant genes in scRNA-seq data rely on differential expression analysis, susceptible to overlooking essential genes.\nC_LIO_LIGENIX leverages cell-type-specific inferred gene association networks to identify condition-relevant genes and gene programs, irrespective of their specific expression alterations.\nC_LIO_LIGENIX provides insight into the gene-regulatory response to the influenza vaccine in naive and recovered COVID-19 patients, expanding on previously observed gender-specific differences.\nC_LI\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC=\"FIGDIR/small/556872v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (27K):\norg.highwire.dtl.DTLVardef@1837d3eorg.highwire.dtl.DTLVardef@1937860org.highwire.dtl.DTLVardef@c40114org.highwire.dtl.DTLVardef@22d3b9_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Marion Nyaboke Nyamari", - "author_inst": "Pwani University" - }, - { - "author_name": "Kauthar M. Omar", - "author_inst": "Pwani University" + "author_name": "Nima Nouri", + "author_inst": "Sanofi" }, { - "author_name": "Ayorinde F. Fayehun", - "author_inst": "University of Ibadan" + "author_name": "Giorgio Gaglia", + "author_inst": "Sanofi" }, { - "author_name": "Oumaima Dachi", - "author_inst": "University of Hassan II Casablanca" + "author_name": "Hamid Mattoo", + "author_inst": "Sanofi" }, { - "author_name": "Billiah Kemunto Bwana", - "author_inst": "University of Embu" + "author_name": "Emanuele de Rinaldis", + "author_inst": "Sanofi" }, { - "author_name": "Olaitan I. Awe", - "author_inst": "University of Ibadan, African Society for Bioinformatics and Computational Biology" + "author_name": "Virginia Savova", + "author_inst": "Sanofi" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "new results", - "category": "genetics" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2023.09.12.557347", @@ -14025,51 +14032,91 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.09.08.23295262", - "rel_title": "Comparison of COVID-19 and Influenza-Related Outcomes in the United States during Fall-Winter 2022-2023", - "rel_date": "2023-09-11", + "rel_doi": "10.1101/2023.09.08.23295268", + "rel_title": "Ventilation during COVID-19 in a school for students with intellectual and developmental disabilities (IDD).", + "rel_date": "2023-09-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.08.23295262", - "rel_abs": "BackgroundThree years into the pandemic, SARS-COV-2 remains a significant burden in comparison to other respiratory illnesses; however, many of the monitoring tools available during the early phase of the COVID-19 pandemic have been phased out, making it more difficult to track the current burden of outpatient medical encounters and hospitalizations, especially for at-risk groups. The objective of this analysis was to characterize the frequency and severity of medically-attended COVID-19 and influenza during peak influenza activity in the pediatric (0-17), adult (18-64), and older adult (65+) populations and characterize the prevalence of underlying medical conditions among patients hospitalized with COVID-19.\n\nMethodsThis was a cross-sectional analysis of individuals in the Veradigm Health Insights EHR Database linked to Komodo claims data with a medical encounter of claim between October 1, 2022, and March 31, 2023. We captured age, sex, and underlying medical conditions associated with higher risk for severe COVID-19 during a 12-month baseline period. We identified patients with medical encounters with a diagnosis of COVID-19 or influenza between October 1, 2022, and March 31, 2023, and stratified them into 5 mutually exclusive categories based on the highest level of care received with that diagnosis during the season (intensive care unit [ICU] > hospitalization without ICU > emergency department > urgent care > other outpatient).\n\nResultsAmong the 23,526,196 individuals in the dataset, 5.0% had a COVID-19-related medical encounter, and 3.0% had an influenza-related medical encounter during the 6 month observation period. The incidence of hospitalizations with a COVID-19 diagnosis was 4.6 times higher than the incidence of hospitalizations with an influenza diagnosis. Hospitalizations with COVID-19 were higher in all age groups. Nearly all adults hospitalized with COVID-19 had at least one underlying medical condition, but 25.8% of 0-5-year-olds and 18.3% of 6-17-year-olds had no underlying medical conditions.\n\nConclusionsCOVID-19 continues to place a heavy burden on the United States healthcare system and was associated with more medical encounters in all age groups, including hospitalizations, than influenza during a 6-month period that included the 2022-2023 peak influenza activity.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.08.23295268", + "rel_abs": "BackgroundThis study examined the correlation of classroom ventilation (air exchanges per hour (ACH)) and exposure to CO2 [≥]1,000 ppm with the incidence of SARS-CoV-2 over a 20-month period in a specialized school for students with intellectual and developmental disabilities (IDD). These students were at a higher risk of respiratory infection from SARS-CoV-2 due to challenges in tolerating mitigation measures (e.g. masking). One in-school measure proposed to help mitigate the risk of SARS-CoV-2 infection in schools is increased ventilation.\n\nMethodsWe established a community-engaged research partnership between the University of Rochester and the Mary Cariola Center school for students with IDD. Ambient CO2 levels were measured in 100 school rooms, and air changes per hour (ACH) were calculated. The number of SARS-CoV-2 cases for each room was collected over 20 months.\n\nResults97% of rooms had an estimated ACH[≤] 4.0, with 7% having CO2 levels[≥] 2,000 ppm for up to 3 hours per school day. A statistically significant correlation was found between the time that a room had CO2 levels [≥]1,000 ppm and SARS-CoV-2 PCR tests normalized to room occupancy, accounting for 43% of the variance. No statistically significant correlation was found for room ACH and per-room SARS-CoV-2 cases. Rooms with ventilation systems using MERV-13 filters had lower SARS-CoV-2-positive PCR counts. These findings led to ongoing efforts to upgrade the ventilation systems in this community-engaged research project.\n\nConclusionsThere was a statistically significant correlation between the total time of room CO2 concentrations [≥]1,000 and SARS-CoV-2 cases in an IDD school. Merv-13 filters appear to decrease the incidence of SARS-CoV-2 infection. This research partnership identified areas for improving in-school ventilation.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Hagit Kopel", - "author_inst": "Moderna, Inc." + "author_name": "Martin S Zand", + "author_inst": "University of Rochester Medical Center" }, { - "author_name": "Alina Bogdanov", - "author_inst": "Veradigm" + "author_name": "Samantha Spallina", + "author_inst": "University of Rochester Medical Center" }, { - "author_name": "Jessamine Winer-Jones", - "author_inst": "Veradigm" + "author_name": "Alexis Ross", + "author_inst": "Mary Cariola Center" }, { - "author_name": "Christopher Adams", - "author_inst": "Veradigm" + "author_name": "Karen Zandi", + "author_inst": "Mary Cariola Center" }, { - "author_name": "Isabelle Winer", - "author_inst": "Veradigm" + "author_name": "Anne Pawlowski", + "author_inst": "Mary Cariola Center" }, { - "author_name": "Mac Bonafede", - "author_inst": "Veradigm" + "author_name": "Christopher Seplaki", + "author_inst": "University of Rochester Medical Center" }, { - "author_name": "Van Hung Nguyen", - "author_inst": "VHN Consulting Inc." + "author_name": "Jonathan Herington", + "author_inst": "University of Rochester Medical Center" }, { - "author_name": "James A. Mansi", - "author_inst": "Moderna, Inc." + "author_name": "Anthony Corbett", + "author_inst": "University of Rochester Medical Center" + }, + { + "author_name": "Kimberly Kaukeinen", + "author_inst": "University of Rochester Medical Center" + }, + { + "author_name": "Edward Freedman", + "author_inst": "University of Rochester Medical Center" + }, + { + "author_name": "Jeanne Holden-Wiltse", + "author_inst": "University of Rochester Medical Center" + }, + { + "author_name": "Lisette Alcantara", + "author_inst": "University of Rochester Medical Center" + }, + { + "author_name": "Dongmei Li", + "author_inst": "University of Rochester Medical Center" + }, + { + "author_name": "Andrew Cameron", + "author_inst": "University of Rochester Medical Center" + }, + { + "author_name": "Nicole Beaumont", + "author_inst": "University of Rochester Medical Center" + }, + { + "author_name": "Ann Dozier", + "author_inst": "University of Rochester Medical Center" + }, + { + "author_name": "Stephen Dewhurst", + "author_inst": "University of Rochester Medical Center" + }, + { + "author_name": "John Foxe", + "author_inst": "University of Rochester Medical Center" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.09.08.23295246", @@ -16011,37 +16058,81 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2023.09.05.23295067", - "rel_title": "Emerging Links Between COVID-19 and Cardiovascular & Cerebrovascular Thromboembolic Events: A Systematic Review", + "rel_doi": "10.1101/2023.09.03.23294989", + "rel_title": "Differentiation of COVID-19 from other emergency infectious disease presentations using whole blood transcriptomics then rapid qPCR: a case-control and observational cohort study", "rel_date": "2023-09-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.05.23295067", - "rel_abs": "COVID-19, caused by the SARS-CoV-2 virus, initially identified as a respiratory illness, has increasingly been linked to a broader range of organ complications. This systematic review explores the impact of COVID-19 on cardiovascular and cerebrovascular health, focusing on thromboembolic events in post-COVID patients. A comprehensive literature search was conducted in PubMed and Google Scholar databases up to July 2023, utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies meeting eligibility criteria were analyzed for outcomes and associations between COVID-19 and cardiovascular and cerebrovascular events. The review includes 6 studies involving over 12 million patients, demonstrating a strong connection between COVID-19 and elevated risks of cardiovascular and cerebrovascular thromboembolic events. The risk of these events is evident in conditions such as ischemic heart disease, stroke, and cardiac arrhythmias. The burden of these events beyond the acute phase of the disease is concerning, warranting further exploration of long-term implications. Variability in event rates among different cohorts and healthcare settings underscores the need for understanding underlying factors influencing these differences. Potential mechanisms behind these events include endothelial dysfunction, systemic inflammation, and viral invasion. Implications for public health policies, clinical guidelines, and future research directions are discussed. This review serves as a valuable resource for healthcare providers, policymakers, and researchers to enhance patient care, outcomes, and preparedness for future waves of COVID-19 infections. However, there remain unexplored aspects of the COVID-19 and thromboembolic events relationship, urging further investigations into mechanistic insights and potential therapeutic interventions.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.03.23294989", + "rel_abs": "BackgroundThe overlapping clinical presentations of patients with acute respiratory disease can complicate disease diagnosis. Whilst PCR diagnostic methods to identify SARS-CoV-2 are highly sensitive, they have their shortcomings including false-positive risk and slow turnaround times. Changes in host gene expression can be used to distinguish between disease groups of interest, providing a viable alternative to infectious disease diagnosis.\n\nMethodsWe interrogated the whole blood gene expression profiles of patients with COVID-19 (n=87), bacterial infections (n=88), viral infections (n=36), and not-infected controls (n=27) to identify a sparse diagnostic signature for distinguishing COVID-19 from other clinically similar infectious and non-infectious conditions. The sparse diagnostic signature underwent validation in a new cohort using reverse transcription quantitative polymerase chain reaction (RT-qPCR) and then underwent further external validation in an independent in silico RNA-seq cohort.\n\nFindingsWe identified a 10-gene signature (OASL, UBP1, IL1RN, ZNF684, ENTPD7, NFKBIE, CDKN1C, CD44, OTOF, MSR1) that distinguished COVID-19 from other infectious and non-infectious diseases with an AUC of 87.1% (95% CI: 82.6%-91.7%) in the discovery cohort and 88.7% and 93.6% when evaluated in the RT-qPCR validation, and in silico cohorts respectively.\n\nInterpretationUsing well-phenotyped samples collected from patients admitted acutely with a spectrum of infectious and non-infectious syndromes, we provide a detailed catalogue of blood gene expression at the time of hospital admission. The findings result in the identification of a 10-gene host diagnostic signature to accurately distinguish COVID-19 from other infection syndromes presenting to hospital. This could be developed into a rapid point-of-care diagnostic test, providing a valuable syndromic diagnostic tool for future early pandemic use.\n\nFundingImperial COVID fund; NIHR Imperial BRC; UKRI (ISARIC-4C).\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSRapid diagnosis is fundamental for ensuring that high consequence infections are identified at an early stage, and that correct and timely treatment is started. Pathogen- focused diagnostic tools may not be available early in a pandemic. To determine if host-based syndromic diagnostic tools to identify acute COVID-19 in the emergency setting have been developed, we searched PubMed using the following search terms for all hits between January 2020-July 2023: \"COVID19\" AND \"viral\" AND \"whole blood\" AND (\"RNAseq\" OR \"RNA-Seq\" OR \"transcriptomic\" OR \"transcriptome\" OR \"gene expression\") AND (\"signature\" OR \"diagnosis\" OR \"classification\" OR \"classifier\"). This returned 16 studies, with two focused on paediatric populations and one focused on an elderly population. A further two studies explored utility of host gene expression in predicting viral infection severity and one study focused on exploring whole blood transcriptome profiles of patients with SARS-CoV-2, however only contrasting them to healthy controls rather than clinically similar disease cohorts. One study demonstrated that metabolomic biomarkers can distinguish COVID-19 and viral infections from other disease groups, and a further study showed that host gene expression (nasopharyngeal swabs and whole blood) differs between patients with COVID-19 and those with influenza, other seasonal coronaviruses, and bacterial sepsis, using classifiers with as few as 20 genes to perform diagnosis. These studies show that acute infection with SARS-CoV-2 can give rise to specific gene expression changes in the host that may differ from those seen in clinically similar infectious or non-infectious presentations. However to date there is no signature that has been adapted to a diagnostic platform, and none has been validated to discriminate SARS-CoV-2 from other infectious syndromes.\n\nAdded value of this studyOur study provides a unique snapshot of gene expression in a large cohort of well-phenotyped adults at the point of admission to an emergency department with a range of suspected infections including COVID-19. We identified a 10-gene signature, which outperformed common laboratory markers, such as CRP and white cell count for discriminating patients with COVID-19 from those with clinical similar infectious and non-infectious diseases. This signature has been shown to be effective in a completely independent cohort of patients recruited in the United States, as well as in a validation cohort from the emergency department, using a different quantitation platform (RT-qPCR). Taken together, these findings show that acute COVID-19 can be differentiated from other emergency presentations using a sparse combination of host transcripts in blood. The findings allow a gene expression signature to be developed into a rapid point-of-care diagnostic test to differentiate serious COVID-19-like infection from other similar presentations.\n\nImplications for practice or policy and future research combined with existing evidence.PCR-based diagnostic approaches have high sensitivity and specificity to detect SARS-CoV-2 and other viruses in the respiratory tract, however there are many situations where the results may not indicate active disease and can be misleading. Host response-based diagnostics can provide supporting evidence of an active viral infection, and could prove essential in the setting where emerging virus variants elude detection by PCR, or where no PCR diagnostic exists.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Abhimanyu Agarwal", - "author_inst": "Wake Forest University School of Medicine" + "author_name": "Ho Kwong Li", + "author_inst": "Imperial College London" }, { - "author_name": "Binay K Panjiyar", - "author_inst": "Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA" + "author_name": "Heather R. Jackson", + "author_inst": "Imperial College London" }, { - "author_name": "Dhwani Manishbhai Patel", - "author_inst": "Smt. NHL Medical College, Ahmedabad, India" + "author_name": "Luca Miglietta", + "author_inst": "Imperial College London" + }, + { + "author_name": "Dominic Habgood-Coote", + "author_inst": "Imperial College London;" + }, + { + "author_name": "Ewurabena Mills", + "author_inst": "Imperial College London" + }, + { + "author_name": "Ravi Mehta", + "author_inst": "Imperial College London" }, { - "author_name": "Monica Ghotra", - "author_inst": "Sri Guru Ram Dass Institute of Medical Sciences and Research, Vallah, Punjab, India" + "author_name": "Ali Hamady", + "author_inst": "Imperial College London" }, { - "author_name": "Mahato Gulam Nabi Husain", - "author_inst": "Nootan Medical College and Research Center, Visnagar, Gujarat, India" + "author_name": "Anna Haber", + "author_inst": "Imperial College Healthcare NHS Trust" }, { - "author_name": "Ronak Brijeshkumar Upadhyay", - "author_inst": "Nootan Medical College and Research Center, Visnagar, Gujarat, India" + "author_name": "Maisarah Amran", + "author_inst": "Imperial College Healthcare NHS Trust" + }, + { + "author_name": "Robert Hammond", + "author_inst": "Imperial College Healthcare NHS Trust" + }, + { + "author_name": "Dominique Arancon", + "author_inst": "Imperial College Healthcare NHS Trust" + }, + { + "author_name": "Graham S. Cooke", + "author_inst": "Imperial College" + }, + { + "author_name": "Mahdad Noursadeghi", + "author_inst": "University College London" + }, + { + "author_name": "Peter JM Openshaw", + "author_inst": "Imperial College London" + }, + { + "author_name": "Jesus Rodriguez Manzano", + "author_inst": "Imperial College London" + }, + { + "author_name": "Myrsini Kaforou", + "author_inst": "Imperial College London" + }, + { + "author_name": "Shiranee Sriskandan", + "author_inst": "Imperial College London" } ], "version": "1", @@ -17653,55 +17744,87 @@ "category": "primary care research" }, { - "rel_doi": "10.1101/2023.08.31.23294813", - "rel_title": "Observational Study of Repeat Immunoadsorption (RIA) in Post-COVID ME/CFS Patients with Elevated Beta-2-Adrenergic Receptor Autoantibodies", + "rel_doi": "10.1101/2023.08.30.23294821", + "rel_title": "Symptom experience before vs. after confirmed SARS-CoV-2 infection: a population and case control study using prospectively recorded symptom data.", "rel_date": "2023-09-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.31.23294813", - "rel_abs": "There is increasing evidence for an autoimmune aetiology in post-infectious Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). SARS-CoV-2 has now become the main trigger for ME/CFS. We have already conducted two small proof-of-concept studies of IgG depletion by immunoadsorption (IA) in post-infectious ME/CFS, which showed efficacy in most patients. This observational study aims to evaluate the efficacy of IA in patients with post-COVID-19 ME/CFS. The primary objective is to assess the improvement in functional ability. Due to the urgency of finding therapies for post-Covid-Syndrome (PCS), we report here the interim results of the first ten patients with seven responders defined by an increase of between 10 and 35 points in the Short-Form 36 Physical Function (SF36-PF) at week four after IA. The results of this observational study will provide the basis for patient selection for a randomised controlled trial (RTC) including sham apheresis and for a RTC combining IA with B-cell depletion therapy.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.30.23294821", + "rel_abs": "BackgroundSome individuals experience prolonged illness after acute COVID-19. We assessed whether pre-infection symptoms affected post-COVID illness duration.\n\nMethodsSurvival analysis was performed in adults (n=23,452) with community-managed SARC-CoV-2 infection prospectively self-logging data through the ZOE COVID Symptom Study app, at least weekly, from 8 weeks before to 12 weeks after COVID-19 onset, conditioned on presence vs. absence of baseline symptoms (4-8 weeks before COVID-19). A case-control study was performed in 1350 individuals with long illness ([≥]8 weeks, 906 [67.1%] with illness [≥]12 weeks), matched 1:1 (for age, sex, body mass index, testing week, prior infection, vaccination, smoking, index of multiple deprivation) with 1350 individuals with short illness (<4 weeks). Baseline symptoms were compared between the two groups; and against post-COVID symptoms.\n\nFindingsIndividuals reporting baseline symptoms had longer post-COVID symptom duration (from 10 to 15 days) with baseline fatigue nearly doubling duration. Two-thirds (910 of 1350 [67.4%]) of individuals with long illness were asymptomatic beforehand. However, 440 (32.6%) had baseline symptoms, vs. 255 (18.9%) of 1350 individuals with short illness (p<0.0001). Baseline symptoms increased the odds ratio for long illness (2.14 [CI: 1.78; 2.57]). Prior comorbidities were more common in individuals with long vs. short illness. In individuals with long illness, baseline symptomatic (vs. asymptomatic) individuals were more likely to be female, younger, and have prior comorbidities; and baseline and post-acute symptoms and symptom burden correlated strongly.\n\nInterpretationIndividuals experiencing symptoms before COVID-19 have longer illness duration and increased odds of long illness. However, many individuals with long illness are well before SARS-CoV-2 infection.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Elisa Stein", - "author_inst": "Charite Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin and Humboldt Universitaet zu Berlin, Institute for Medical Immunology" + "author_name": "Carole Helene Sudre", + "author_inst": "University College London" }, { - "author_name": "Cornelia Heindrich", - "author_inst": "Charite Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin and Humboldt Universitaet zu Berlin, Institute for Medical Immunology" + "author_name": "Michela Antonelli", + "author_inst": "King's College London" }, { - "author_name": "Kirsten Wittke", - "author_inst": "Charite Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin and Humboldt Universitaet zu Berlin, Institute for Medical Immunology" + "author_name": "Nathan J Cheetham", + "author_inst": "King's College London" }, { - "author_name": "Claudia Kedor", - "author_inst": "Charite Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin and Humboldt Universitaet zu Berlin, Institute for Medical Immunology" + "author_name": "Erika Molteni", + "author_inst": "King's College London" }, { - "author_name": "Laura Kim", - "author_inst": "Charite Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin and Humboldt Universitaet zu Berlin, Institute for Medical Immunology" + "author_name": "Liane S Canas", + "author_inst": "King's College London" }, { - "author_name": "Helma Freitag", - "author_inst": "Charite Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin and Humboldt Universitaet zu Berlin, Institute for Medical Immunology" + "author_name": "Vicky Bowyer", + "author_inst": "King's College London" + }, + { + "author_name": "Benjamin Murray", + "author_inst": "King's College London" + }, + { + "author_name": "Khaled Rjoob", + "author_inst": "University College London" }, { - "author_name": "Anne Krueger", - "author_inst": "Charite Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin and Humboldt Universitaet zu Berlin, Department of Nephrology and Medical Int" + "author_name": "Marc Modat", + "author_inst": "King's College London" }, { - "author_name": "Markus Toelle", - "author_inst": "Charite Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin and Humboldt Universitaet zu Berlin, Department of Nephrology and Medical Int" + "author_name": "Joan Capdevia Pujol", + "author_inst": "Zoe Ltd" }, { - "author_name": "Carmen Scheibenbogen", - "author_inst": "Charite Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin and Humboldt Universitaet zu Berlin, Institute for Medical Immunology" + "author_name": "Christina Hu", + "author_inst": "Zoe Ltd" + }, + { + "author_name": "Jonathan Wolf", + "author_inst": "Zoe Ltd" + }, + { + "author_name": "Timothy D Spector", + "author_inst": "King's College London" + }, + { + "author_name": "Alexander Hammers", + "author_inst": "King's College London" + }, + { + "author_name": "Claire J Steves", + "author_inst": "King's College London" + }, + { + "author_name": "Sebastien Ourselin", + "author_inst": "King's College London" + }, + { + "author_name": "Emma L Duncan", + "author_inst": "King's College London" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.08.29.23294793", @@ -19583,87 +19706,59 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.08.25.23294654", - "rel_title": "Prevalence and pattern of Post Covid-19 symptoms in recovered patients of Delhi: A Population-Based study", + "rel_doi": "10.1101/2023.08.25.554813", + "rel_title": "In Vivo Antiviral Efficacy of LCTG-002, a Pooled, Purified Human Milk Secretory IgA product, Against SARS-CoV-2 in a Murine Model of COVID-19", "rel_date": "2023-08-28", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.25.23294654", - "rel_abs": "BackgroundPost-coronavirus disease (COVID) is widely reported but the data of Post COVID-19 after infection with the Omicron variant is limited. This prospective study was conducted to determine the prevalence, pattern, and duration of symptoms related to Covid-19 recovered patients. Methods: Adults (>18 years old) in 11 districts of Delhi who had recovered from Covid-19 were followed up at 3 months and 6 months post-recovery. Results: The study found that the participants had a mean age of 42.07 years, with a standard deviation of 14.89. Additionally, a significant proportion of the participants (79.7%) experienced post-Covid symptoms. The participants elicited a history of Joint Pain (36%), Persistent dry cough (35.7%), anxiousness (28.4%) and shortness of breath (27.1%). The other symptoms reported were persistent fatigue (21.6%), persistent headache (20%), forgetfulness (19.7%) and weakness in limbs (18.6%). The longest duration of symptom was observed in participants reporting anxiousness (138.75 {+/-}54.14) followed by fatigue (137.57{+/-}48.33), shortness of breath (131.89{+/-}60.21) and joint pain/swelling (131.59{+/-}58.76). During the first follow-up, 2.2% of participants had an abnormal ECG reading, while no abnormalities were reported during the second follow-up. Additionally, 4.06% of participants had abnormal chest X-ray findings during the first follow-up, with this number decreasing to 2.16% during the second follow-up. Conclusion: Our study concluded that the clinical symptoms persist in participants until 6 months and a multi-system involvement is seen in the post-COVID period. Thus, the findings necessitate long-term, regular follow-ups.", - "rel_num_authors": 17, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.25.554813", + "rel_abs": "Immunoglobulin A (IgA) is the most abundant antibody (Ab) in human mucosal compartments including the respiratory tract, with the secretory form of IgA (sIgA) being dominant and uniquely stable in these environments. sIgA is naturally found in human milk, which could be considered a global resource for this biologic, justifying the development of human milk sIgA as a dedicated airway therapeutic for respiratory infections such as SARS-CoV-2. In the present study, methods were therefore developed to efficiently extract human milk sIgA from donors who were either immunologically naive to SARS-CoV-2 (pooled as a control IgA) or had recovered from a PCR-confirmed SARS-CoV-2 infection that elicited high-titer anti-SARS-CoV-2 Spike sIgA Abs in their milk (pooled together to make LCTG-002). Mass spectrometry determined that proteins with a relative abundance of 1.0% or greater were all associated with sIgA. None of the proteins exhibited statistically significant differences between batches. Western blot demonstrated all batches consisted predominantly of sIgA. Compared to control IgA, LCTG-002 demonstrated significantly higher binding to Spike, and was also capable of blocking the Spike - ACE2 interaction in vitro with 6.3x greater potency compared to control IgA (58% inhibition at [~]240ug/mL). LCTG-002 was then tested in vivo for its capacity to reduce viral burden in the lungs of K18+hACE2 transgenic mice inoculated with SARS-CoV-2. LCTG-002 was demonstrated to significantly reduce SARS-CoV-2 titers in the lungs compared to control IgA when administered at either 250ug/day or 1 mg/day, as measured by TCID50, plaque forming units (PFU), and qRT-PCR, with a maximum reduction of 4.9 logs. This innovative study demonstrates that LCTG-002 is highly pure, efficacious, and well tolerated in vivo, supporting further development of milk-derived, polyclonal sIgA therapeutics against SARS-CoV-2 and other mucosal infections.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Nidhi Bhatnagar", - "author_inst": "Maulana Azad Medical College, New Delhi, India" - }, - { - "author_name": "M M Singh", - "author_inst": "Maulana Azad Medical College, New Delhi, India" - }, - { - "author_name": "Hitakshi Sharma", - "author_inst": "Maulana Azad Medical College, New Delhi, India" - }, - { - "author_name": "Suruchi Mishra", - "author_inst": "Maulana Azad Medical College, New Delhi, India" - }, - { - "author_name": "Gurmeet Singh", - "author_inst": "Maulana Azad Medical College, New Delhi, India" - }, - { - "author_name": "Shivani Rao", - "author_inst": "Maulana Azad Medical College, New Delhi, India" + "author_name": "Viraj Mane", + "author_inst": "Lactiga US, Inc" }, { - "author_name": "Amod Borle", - "author_inst": "Maulana Azad Medical College, New Delhi, India" + "author_name": "Rikin Mehta", + "author_inst": "Lactiga US, Inc" }, { - "author_name": "Tanu Anand", - "author_inst": "ICMR, New Delhi, India" - }, - { - "author_name": "Naresh Kumar", - "author_inst": "Maulana Azad Medical College and LNH, New Delhi, India" - }, - { - "author_name": "Binita Goswami", - "author_inst": "Maulana Azad Medical College, New Delhi, India" + "author_name": "Nadine Alvarez", + "author_inst": "Hackensack Meridian Health Center for Discovery and Innovation" }, { - "author_name": "Sarika Singh", - "author_inst": "Maulana Azad Medical College, New Delhi, India" + "author_name": "Vijeta Sharma", + "author_inst": "Hackensack Meridian Health Center for Discovery and Innovation" }, { - "author_name": "Mahima Kapoor", - "author_inst": "Maulana Azad Medical College and LNH, New Delhi, India" + "author_name": "Steven Park", + "author_inst": "Hackensack Meridian Health Center for Discovery and Innovation" }, { - "author_name": "Sumeet Singla", - "author_inst": "Maulana Azad Medical College and LNH, New Delhi, India" + "author_name": "Alisa Fox", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Bembem Khuraijam", - "author_inst": "Maulana Azad Medical College, New Delhi, India" + "author_name": "Claire DeCarlo", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Nita Khurana", - "author_inst": "Maulana Azad Medical College, New Delhi, India" + "author_name": "Xiaoqi Yang", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Urvi Sharma", - "author_inst": "Directorate General Health Services, Delhi, India" + "author_name": "David S Perlin", + "author_inst": "Hackensack Meridian Health Center for Discovery and Innovation" }, { - "author_name": "Suneela Garg", - "author_inst": "NIHFW, New Delhi, India" + "author_name": "Rebecca L Powell", + "author_inst": "Icahn School of Medicine at Mount Sinai" } ], "version": "1", "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2023.08.26.554935", @@ -21181,35 +21276,47 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2023.08.23.23294511", - "rel_title": "COVID-19 Testing and Vaccination among US Older Adults with Vision Impairment: The National Health and Aging Trends Study 2021", + "rel_doi": "10.1101/2023.08.22.23294402", + "rel_title": "Risk of long COVID and associated symptoms after acute SARS-COV-2 infection in ethnic minorities: a Danish nationwide cohort study", "rel_date": "2023-08-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.23.23294511", - "rel_abs": "PurposeTo examine the associations between vision impairment (VI) and COVID-19 testing and vaccination services in older US adults.\n\nMethodsThis cross-sectional study assessed data from adults [≥]65 years who participated in the National Health and Aging Trends Study (year 2021), a nationally representative sample of Medicare beneficiaries. Exposure: Distance VI (<20/40), near VI (<20/40), contrast sensitivity impairment (CSI) (<1.55 logCS), and any VI (distance, near, or CSI). Outcomes: Self-reported COVID-19 testing and vaccination.\n\nResultsOf 2,822 older adults, the majority were female (weighted; 55%) and White (82%), and 32% had any VI. In fully-adjusted regression analyses, older adults with any VI had similar COVID-19 vaccination rates to adults without any VI (OR:0.77, 95% CI:0.54-1.09), but had lower odds of COVID-19 testing (OR:0.82, 95% CI:0.68-0.97). Older adults with distance (OR:0.47, 95% CI:0.22-0.99) and near (OR:0.68, 95% CI:0.47-0.99) VI were less likely to be vaccinated for COVID-19, while those with CSI were less likely to test for COVID-19 (OR:0.76, 95% CI:0.61- 0.95), as compared to peers without respective impairments. The remaining associations were not significant (p>.05).\n\nConclusions and RelevanceThese findings highlight inequities in the COVID-19 pandemic response for people with vision disability and emphasize the need for equitable prioritization of accessibility of healthcare services for all Americans.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.22.23294402", + "rel_abs": "BackgroundEthnic minorities living in high-income countries have been disproportionately affected by COVID-19 in terms of infection rates and hospitalisations; however, less is known about long COVID in this population. Our aim was to examine the risk of long COVID and associated symptoms among ethnic minorities.\n\nMethods and FindingsA Danish nationwide register-based cohort study of individuals diagnosed with COVID-19 aged [≥]18 years (n=2 334 271) between January 2020 and August 2022. We calculated the risk of long COVID diagnosis and long COVID symptoms among ethnic minorities compared with native Danes using multivariable Cox proportional hazard regression and logistic regression, respectively.\n\nEthnic minorities from North Africa (adjusted hazard ratio [aHR] 1.41; 95% CI 1.12-1.79), Middle East (aHR 1.38; 95% CI 1.24-1.55), Eastern Europe (aHR 1.35; 95% CI 1.22-1.49), and Asia (aHR 1.23; 95% CI 1.09-1.40) had significantly greater risk of long COVID diagnosis than native Danes in both unadjusted and adjusted models. In the analysis by largest countries of origin, the greater risks of long COVID diagnosis were found in Iraqis (aHR 1.56; 95% CI 1.30- 1.88), Turks (aHR 1.42; 95% CI 1.24-1.63), and Somalis (aHR 1.42; 95% CI 1.07-1.91) after adjustment for confounders. Significant factor associated with an increased risk of long COVID diagnosis was COVID-19 hospitalisation. Furthermore, the odds of reporting cardiopulmonary symptoms (including dyspnoea, cough, and chest pain) and any long COVID symptoms were higher among North African, Middle Eastern, Eastern European, and Asian than among native Danes in both unadjusted and adjusted models.\n\nConclusionsBelonging to an ethnic minority group was significantly associated with an increased risk of long COVID indicating the need to better understand long COVID drivers and address care and treatment strategies in this population.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Louay Almidani", - "author_inst": "Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland" + "author_name": "George Mkoma", + "author_inst": "University of Copenhagen Faculty of Health and Medical Sciences: Kobenhavns Universitet Sundhedsvidenskabelige Fakultet" }, { - "author_name": "Bonnielin K. Swenor", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Charles Agyemang", + "author_inst": "University of Amsterdam Faculty of Medicine: Amsterdam UMC Locatie AMC" + }, + { + "author_name": "Thomas Lars Benfield", + "author_inst": "Copenhagen University Hospital: Kobenhavns Universitetshospital" + }, + { + "author_name": "Mikael Rostila", + "author_inst": "Stockholm University: Stockholms Universitet" }, { - "author_name": "Joshua R. Ehrlich", - "author_inst": "Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor" + "author_name": "Agneta Cederstr\u00f6m", + "author_inst": "Stockholm University: Stockholms Universitet" }, { - "author_name": "Varshini Varadaraj", - "author_inst": "Johns Hopkins Wilmer Eye Institute" + "author_name": "J\u00f8rgen Holm Petersen", + "author_inst": "University of Copenhagen Faculty of Health Sciences: Kobenhavns Universitet Sundhedsvidenskabelige Fakultet" + }, + { + "author_name": "Marie Norredam", + "author_inst": "University of Copenhagen Faculty of Health and Medical Sciences: Kobenhavns Universitet Sundhedsvidenskabelige Fakultet" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "ophthalmology" + "category": "public and global health" }, { "rel_doi": "10.1101/2023.08.23.23293081", @@ -22835,95 +22942,87 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2023.08.16.23294112", - "rel_title": "Modeling geographic vaccination strategies for COVID-19 in Norway", + "rel_doi": "10.1101/2023.08.18.553908", + "rel_title": "Host factor PLAC8 is required for pancreas infection by SARS-CoV-2", "rel_date": "2023-08-21", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.16.23294112", - "rel_abs": "1Vaccination was a key intervention in controlling the COVID-19 pandemic globally. In early 2021, Norway faced significant regional variations in COVID-19 incidence and prevalence, with large differences in population density, necessitating efficient vaccine allocation to reduce infections and severe outcomes. This study explored alternative vaccination strategies to minimize health outcomes (infections, hospitalizations, ICU admissions, deaths) by varying regions prioritized, extra doses prioritized, and implementation start time.\n\nUsing two models (individual-based and meta-population), we simulated COVID-19 transmission during the primary vaccination period in Norway, covering the first 7 months of 2021. We investigated alternative strategies to allocate more vaccine doses to regions with a higher force of infection. We also examined the robustness of our results and highlighted potential structural differences between the two models.\n\nOur findings suggest that early vaccine prioritization could reduce COVID-19 related health outcomes by 8% to 20% compared to a baseline strategy without geographic prioritization. For minimizing infections, hospitalizations, or ICU admissions, the best strategy was to initially allocate all available vaccine doses to fewer high-risk municipalities, comprising approximately one-fourth of the population. For minimizing deaths, a moderate level of geographic prioritization, with approximately one-third of the population receiving doubled doses, gave the best outcomes by balancing the trade-off between vaccinating younger people in high-risk areas and older people in low-risk areas.\n\nThe actual strategy implemented in Norway was a two-step moderate level aimed at maintaining the balance and ensuring ethical considerations and public trust. However, it did not offer significant advantages over the baseline strategy without geographic prioritization. Earlier implementation of geographic prioritization could have more effectively addressed the main wave of infections, substantially reducing the national burden of the pandemic.\n\n2 Author summaryWe utilized two geographic-age-structured models (an individual-based model and a meta-population model) to conduct a scenario-based analysis aimed at evaluating strategies for geographic prioritization of COVID-19 vaccines in Norway. By reconstructing the dynamics of COVID-19 transmission from January to July of 2021, we compared various alternative vaccination strategies through model simulations, given the limited number of vaccine doses. We found that prioritization of vaccines based on geographic location, alongside considering age, was preferable to a baseline strategy without geographic prioritization. We assessed the selection of which municipalities to prioritize and the degree of prioritization they should receive. Our findings indicated that optimal strategies depended on whether the aim was to minimize infections, hospitalizations, ICU admissions, or deaths. Trade-offs in infection growth between municipalities and subsequent risk-class allocations (such as age groups) were the primary factors influencing optimal vaccine allocation. Furthermore, we found that earlier implementation of most geographic prioritization strategies was advantageous in reducing the overall burden of COVID-19.", - "rel_num_authors": 19, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.18.553908", + "rel_abs": "Although mounting evidence demonstrated that pancreas is infected by SARS-CoV-2 the severity and pathophysiology of pancreatic COVID-19 disease are still unclear. Here we investigated the consequences of SARS-CoV-2 infection of the pancreas and the role of Placenta-associated protein-8 (PLAC8). Our data showed pancreatic damage in patients who died from COVID-19. Notably, circulating pancreatic enzymes stratified patients according to COVID-19 severity and outcome. PLAC8 expression was associated with SARS-CoV-2 infection in postmortem analysis of COVID-19 patients and functional assays demonstrated the requirement of PLAC8 in SARS-CoV-2 pancreatic infection. Full SARS-CoV-2 infectious virus revealed a requirement of PLAC8 for efficient viral infection of pancreatic cell lines. Finally, we observed colocalization of PLAC8 and SARS-CoV-2 in the pancreas of deceased patients. In conclusion, our data confirm the human pancreas as a SARS-CoV-2 target and demonstrate the requirement of PLAC8 for SARS-CoV-2 pancreatic infection thereby opening new target opportunities for COVID-19-associated pancreatic pathogenesis.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Louis Yat Hin Chan", - "author_inst": "Norwegian Institute of Public Health: Folkehelseinstituttet" + "author_name": "Lesly Ibarguen Gonzalez", + "author_inst": "Health Research Institute of the Balearic Islands" }, { - "author_name": "Gunnar R\u00f8", - "author_inst": "Norwegian Institute of Public Health: Folkehelseinstituttet" + "author_name": "Sandra Heller", + "author_inst": "Institute of Molecular Oncology and Stem Cell Biology, Ulm, Germany" }, { - "author_name": "J\u00f8rgen Eriksson Midtb\u00f8", - "author_inst": "Norwegian Institute of Public Health: Folkehelseinstituttet" + "author_name": "Marta L DeDiego", + "author_inst": "Centro Nacional de Biotecnologia" }, { - "author_name": "Francesco Di Ruscio", - "author_inst": "Norwegian Institute of Public Health: Folkehelseinstituttet" + "author_name": "Dario Lopez-Garcia", + "author_inst": "Department of Molecular and Cell Biology, Centro Nacional de Biotecnologia (CNB-CSIC), Madrid, Spain" }, { - "author_name": "Sara Sofie Viksmoen Watle", - "author_inst": "Norwegian Institute of Public Health: Folkehelseinstituttet" + "author_name": "Alba M Gomez-Valero", + "author_inst": "Health Research Institute of the Balearic Islands" }, { - "author_name": "Lene Kristine Juvet", - "author_inst": "Norwegian Institute of Public Health: Folkehelseinstituttet" + "author_name": "Thomas FE Barth", + "author_inst": "Department of Pathology, Ulm University Hospital, Ulm, Germany" }, { - "author_name": "Jasper Littmann", - "author_inst": "Norwegian Institute of Public Health: Folkehelseinstituttet" - }, - { - "author_name": "Preben Aavitsland", - "author_inst": "Norwegian Institute of Public Health: Folkehelseinstituttet" + "author_name": "Patricia Gallego", + "author_inst": "Hospital Son Espases" }, { - "author_name": "Karin Maria Nygard", - "author_inst": "Norwegian Institute of Public Health: Folkehelseinstituttet" + "author_name": "Israel Fernandez-Cardenas", + "author_inst": "Stroke Pharmacogenomics and Genetics Group, Sant Pau Biomedical Research Institute, Barcelona, Spain" }, { - "author_name": "Are Stuwitz Berg", - "author_inst": "Norwegian Institute of Public Health: Folkehelseinstituttet" + "author_name": "Sayoa Alzate-Pinol", + "author_inst": "Stroke Pharmacogenomics and Genetics Group, Sant Pau Biomedical Research Institute, Barcelona, Spain" }, { - "author_name": "Geir Bukholm", - "author_inst": "Norwegian Institute of Public Health: Folkehelseinstituttet" + "author_name": "Catalina Crespi", + "author_inst": "Health Research Institute of the Balearic Islands" }, { - "author_name": "Anja Brathen Kristoffersen", - "author_inst": "Norwegian Institute of Public Health: Folkehelseinstituttet" + "author_name": "Julieth A Mena-Guerrero", + "author_inst": "Health Research Institute of the Balearic Islands" }, { - "author_name": "Kenth Eng\u00f8-Monsen", - "author_inst": "Smart Innovation Norway" + "author_name": "Maria Eugenia Cisneros-Barroso", + "author_inst": "Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain 8Internal Medicine Department, Son Llatzer University Hospital, Palma de Ma" }, { - "author_name": "Solveig Engebretsen", - "author_inst": "Norwegian Computing Center: Norsk Regnesentral" + "author_name": "Alejandro P Ugalde", + "author_inst": "Departamento de Bioquimica y Biologia Molecular, Instituto Universitario de Oncologia (IUOPA), Universidad de Oviedo, Oviedo, Spain." }, { - "author_name": "David Swanson", - "author_inst": "The University of Texas MD Anderson Cancer Center" + "author_name": "Gabriel Bretones", + "author_inst": "Universidad de Oviedo" }, { - "author_name": "Alfonso Diz-Lois Palomares", - "author_inst": "Norwegian Institute of Public Health: Folkehelseinstituttet" + "author_name": "Charlotte Steenblock", + "author_inst": "Department of Internal Medicine III, University Hospital Carl Gustav Carus, Technische Universitat Dresden, Dresden, Germany" }, { - "author_name": "Jonas Christoffer Lindstr\u00f8m", - "author_inst": "Norwegian Institute of Public Health: Folkehelseinstituttet" - }, - { - "author_name": "Arnoldo Frigessi", - "author_inst": "University of Oslo: Universitetet i Oslo" + "author_name": "Alexander Kleger", + "author_inst": "Ulm University" }, { - "author_name": "Birgitte Freiesleben de Blasio", - "author_inst": "Norwegian Institute of Public Health: Folkehelseinstituttet" + "author_name": "Carles Barcelo", + "author_inst": "Health Research Institute of the Balearic Islands" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "type": "new results", + "category": "cell biology" }, { "rel_doi": "10.1101/2023.08.20.554012", @@ -24557,57 +24656,41 @@ "category": "pain medicine" }, { - "rel_doi": "10.1101/2023.08.10.23293935", - "rel_title": "A Scoping Review of Pacing for Management of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS): Lessons Learned for the Long COVID Pandemic", + "rel_doi": "10.1101/2023.08.11.23293977", + "rel_title": "Digital Mental Health Service engagement changes during Covid-19 in children and young people across the UK: presenting concerns, service activity, and access by gender, ethnicity, and deprivation", "rel_date": "2023-08-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.10.23293935", - "rel_abs": "BackgroundControversy over treatment for people with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a barrier to appropriate treatment. Energy management or pacing is a prominent coping strategy for people with ME/CFS that involves regulating activity to avoid post exertional malaise (PEM), the worsening of symptoms after an activity. Until now, characteristics of pacing, and the effects on patients symptoms had not been systematically reviewed. This is problematic as the most common approach to pacing, pacing prescription, and the pooled efficacy of pacing was unknown. Collating evidence may help advise those suffering with similar symptoms, including long COVID, as practitioners would be better informed on methodological approaches to adopt, pacing implementation, and expected outcomes.\n\nObjectivesIn this scoping review of the literature, we aggregated type of, and outcomes of, pacing in people with ME/CFS.\n\nEligibility criteriaOriginal investigations concerning pacing were considered in participants with ME/CFS.\n\nSources of evidenceSix electronic databases (PubMed, Scholar, ScienceDirect, Scopus, Web of Science and the Cochrane Central Register of Controlled Trials [CENTRAL]) were searched; and websites MEPedia, Action for ME, and ME Action were also searched for grey literature.\n\nMethodsA scoping review was conducted. Review selection and characterisation was performed by two independent reviewers using pretested forms.\n\nResultsAuthors reviewed 177 titles and abstracts, resulting in included 17 studies: three randomised control trials (RCTs); one uncontrolled trial; one interventional case series; one retrospective observational study; two prospective observational studies; four cross-sectional observational studies; and five cross-sectional analytical studies. Studies included variable designs, durations, and outcome measures. In terms of pacing administration, studies used educational sessions and diaries for activity monitoring. Eleven studies reported benefits of pacing, four studies reported no effect, and two studies reported a detrimental effect in comparison to the control group.\n\nConclusionsHighly variable study designs and outcome measures, allied to poor to fair methodological quality resulted in heterogenous findings and highlights the requirement for more research examining pacing. Looking to the long COVID pandemic, future studies should be RCTs utilising objectively quantified digitised pacing, over a longer duration of examination, using the core outcome set for patient reported outcome measures.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.11.23293977", + "rel_abs": "The adoption of digital health technologies accelerated during Covid-19, with concerns over the equity of access due to digital exclusion. Using data from a text-based online mental health service for children and young people we explore the impact of the pandemic on service access and presenting concerns and whether differences were observed by sociodemographic characteristics in terms of access (gender, ethnicity and deprivation). We used interrupted time-series models to assess whether there was a change in the level and rate of service use during the Covid-19 pandemic (April 2020-April 2021) compared to pre-pandemic trends (June 2019-March 2020). Routinely collected data from 61221 service users were extracted for observation, those represented half of the service population as only those with consent to share their data were used. The majority of users identified as female (74%) and White (80%), with an age range between 13 and 20 years of age. There was evidence of a sudden increase (13%) in service access at the start of the pandemic (RR 1.13 95% CI 1.02, 1.25), followed by a reduced rate (from 25% to 21%) of engagement during the pandemic compared to pre-pandemic trends (RR 0.97 95% CI 0.95,0.98). There was a sudden increase in almost all presenting issues apart from physical complaints. There was evidence of a step increase in the number of contacts for Black/African/Caribbean/Black British (38% increase; 95% CI: 1%-90%) and White ethnic groups (14% increase; 95% CI: 2%-27%)), sudden increase in service use at the start of the pandemic for the most (58% increase; 95% CI: 1%-247%) and least (47% increase; 95% CI: 6%-204%) deprived areas. During the pandemic, contact rates decreased, and referral sources change at the start. Findings on access and service activity align with other studies observing reduced service utilization. The lack of differences in deprivation levels and ethnicity at lockdown suggests exploring equity of access to the anonymous service. The study provides unique insights into changes in digital mental health use during Covid-19 in the UK.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Nilihan Sanal-Hayes", - "author_inst": "University of the West of Scotland" - }, - { - "author_name": "Marie Mclaughlin", - "author_inst": "University of the West of Scotland" + "author_name": "Duleeka Knipe", + "author_inst": "University of Bristol School of Social and Community Medicine: University of Bristol Population Health Sciences" }, { - "author_name": "Lawrence D D Hayes", - "author_inst": "University of the West of Scotland" + "author_name": "Santiago de Ossorno Garcia", + "author_inst": "Kooth Digital Health" }, { - "author_name": "Jacqueline Mair", - "author_inst": "Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore" - }, - { - "author_name": "Jane Ormerod", - "author_inst": "Long COVID Scotland" + "author_name": "Louisa Salhi", + "author_inst": "Kooth Digital Health" }, { - "author_name": "David Carless", - "author_inst": "University of the West of Scotland" + "author_name": "Lily Mainstone-Cotton", + "author_inst": "Kooth Digital Health" }, { - "author_name": "Natalie Hilliard", - "author_inst": "Physios for ME" + "author_name": "Aaron Sefi", + "author_inst": "Kooth Digital Health" }, { - "author_name": "Rachel Meach", - "author_inst": "University of the West of Scotland" - }, - { - "author_name": "Joanne Ingram", - "author_inst": "University of the West of Scotland" - }, - { - "author_name": "Nicholas Sculthorpe", - "author_inst": "University of the West of Scotland" + "author_name": "Ann John", + "author_inst": "Swansea University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -25871,39 +25954,59 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.08.06.23293722", - "rel_title": "National Changes in Diabetes Care Practices during the COVID-19 Pandemic: Prospective Study of US Adults", + "rel_doi": "10.1101/2023.08.06.23293706", + "rel_title": "Long COVID in a highly vaccinated population infected during a SARS-CoV-2 Omicron wave - Australia, 2022", "rel_date": "2023-08-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.06.23293722", - "rel_abs": "BackgroundThere is a lack of nationally representative prospective data on the impact of the COVID-19 pandemic on diabetes care and management in adults with type 2 diabetes. We examined changes in diabetes care and management practices before and after the onset of the COVID-19 pandemic.\n\nMethodsUsing the National Health Interview Survey, we analyzed data from 870 adults living with type 2 diabetes who were interviewed in 2019 and re-interviewed between August and December 2020. Exposure to the COVID-19 pandemic was defined by year of survey (2019, pre-pandemic; 2020, pandemic). We estimated percent change in past year blood sugar check by a health professional and current use of blood sugar lowering medication overall and by sociodemographic subgroups.\n\nResultsReceiving an annual blood sugar test fell by -3.3 percentage points (pp) (95% CI -5.7, -1.0), from 98.3% in 2019 to 95.0% in late 2020. The reduction in annual blood glucose testing was largely consistent across socio-demographic groups and was particularly pronounced among adults not working and adults aged 65 years and older. In the same time period, current use of diabetes medications increased by +3.8 pp (0.7, 6.9), from 85.9% to 89.7%. The increase in medication use was most pronounced among individuals aged 40-64-year old, employed, and those living in large central metropolitan areas.\n\nConclusionsNationally, adults with Type 2 diabetes reported a reduction in annual blood glucose testing by a health professional and an increase in diabetes medication usage during the COVID-19 pandemic. If sustained after the end of the COVID-19 public health emergency, these changes have implications for national diabetes management and care.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.06.23293706", + "rel_abs": "ObjectiveTo characterise Long COVID in a highly vaccinated population infected by Omicron.\n\nDesignFollow-up survey of persons testing positive for SARS-CoV-2 in Western Australia, 16 July-3 August 2022.\n\nSettingCommunity\n\nParticipants22,744 persons with COVID-19 who had agreed to participate in research at the time of diagnosis were texted a survey link 90 days later; non-responders were telephoned. Post stratification weights were applied to responses from 11,697 (51.4%) participants, 94.0% of whom had received >= 3 vaccine doses.\n\nMain outcome measuresPrevalence of Long COVID - defined as reporting new or ongoing COVID-19 illness-related symptoms or health issues 90 days post diagnosis; associated health care utilisation, reductions in work/study and risk factors were assessed using log-binomial regression.\n\nResults18.2% (n=2,130) of respondents met case definition for Long COVID. Female sex, being 50-69 years of age, pre-existing health issues, residing in a rural or remote area, and receiving fewer vaccine doses were significant independent predictors of Long COVID (p < 0.05). Persons with Long COVID reported a median of 6 symptoms, most commonly fatigue (70.6%) and difficulty concentrating (59.6%); 38.2% consulted a GP and 1.6% reported hospitalisation in the month prior to the survey due to ongoing symptoms. Of 1,778 respondents with Long COVID who were working/studying before their COVID-19 diagnosis, 17.9% reported reducing/discontinuing work/study.\n\nConclusion90 days post Omicron infection, almost 1 in 5 respondents reported Long COVID symptoms; 1 in 15 of all persons with COVID-19 sought healthcare for associated health concerns >=2 months after the acute illness.\n\nSignificance of the studyO_ST_ABSThe knownC_ST_ABSThe prevalence of Long COVID varies widely across studies conducted in diverse settings globally (range: 9%-81%).\n\nThe newIn a highly vaccinated population (94% with >=3 vaccine doses), almost 20% of persons infected with the SARS-CoV-2 Omicron variant reported symptoms consistent with Long COVID 90 days post diagnosis. Long COVID was associated with sustained negative impacts on work/study and a substantial utilisation of GP services 2-3 months after the acute illness; however, ED presentations and hospitalisations for Long COVID were rare.\n\nThe implicationsGP clinics play a significant role in managing the burden of Long COVID in Australia.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Kushagra Vashist", - "author_inst": "Emory University School of Public Health" + "author_name": "Mulu Woldegiorgis", + "author_inst": "The Australian National University, Western Australia Department of Health" }, { - "author_name": "Saria Hassan", - "author_inst": "Emory University School of Medicine" + "author_name": "Gemma Cadby", + "author_inst": "Western Australia Department of Health" }, { - "author_name": "Mary Beth Weber", - "author_inst": "Emory University School of Public Health" + "author_name": "Sera Ngeh", + "author_inst": "Western Australia Department of Health" }, { - "author_name": "Rakale C Quarells", - "author_inst": "Morehouse School of Medicine" + "author_name": "Rosemary Korda", + "author_inst": "The Australian National University" }, { - "author_name": "Shivani A Patel", - "author_inst": "Emory University School of Public Health" + "author_name": "Paul Armstrong", + "author_inst": "Western Australia Department of Health" + }, + { + "author_name": "Jelena Maticevic", + "author_inst": "Western Australia Department of Health" + }, + { + "author_name": "Paul Knight", + "author_inst": "Western Australia Department of Health" + }, + { + "author_name": "Andrew Jardine", + "author_inst": "Western Australia Department of Health" + }, + { + "author_name": "Lauren Bloomfield", + "author_inst": "Western Australia Department of Health" + }, + { + "author_name": "Paul Effler", + "author_inst": "Western Australia Department of Health" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.08.06.23293729", @@ -27365,33 +27468,49 @@ "category": "primary care research" }, { - "rel_doi": "10.1101/2023.08.03.23293425", - "rel_title": "OUTCOME OF COVID-19 PATIENTS ON STEROID THERAPY: A LONGITUDINAL STUDY", + "rel_doi": "10.1101/2023.08.01.23293522", + "rel_title": "The post-COVID-19 population has a high prevalence of crossreactive antibodies to spikes from all Orthocoronavirinae genera", "rel_date": "2023-08-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.03.23293425", - "rel_abs": "IntroductionSARS-CoV-2 is responsible for global pandemic that originates from Wuhan, China (1). Patients presentation van be varied from asymptomatic to severe ARDS and multiorgan dysfunction likely due the dysregulated systemic inflammation (2). Glucocorticoids inhibits the inflammation by down streaming of cytokine receptor and promote resolution (3). The role of corticosteroid in COVID-19 still remains controversial. Corticosteroids associated with many long terms side effects. Previous MARS outbreak had experienced avascular necrosis with corticosteroid use (4).\n\nObjectivesThe aim of the study was to evaluate the outcome of covid-19 patients on the corticosteroid therapy and estimate mortality rate with corticosteroid therapy and investigate potential long-term adverse events associated with its use.\n\nMethodsWe did a longitudinal follow up study at the AIIMS Rishikesh to assess the side effects of corticosteroids in COVID-19 patients. Patients with moderate to severe COVID-19 pneumonia requiring the oxygen support were included in the study. According to the institutional protocol patients received conventional dose steroids versus pulse dose steroids. (Based on CT/ X-ray findings). Patients were followed up in the hospital till discharge/death for assessment of adverse events due to corticosteroids and all other biochemical parameters (Inflammatory markers) and SOFA score were obtained during hospitalisation till discharge. And at the 6 month follow up patient was assessed for infection and avascular necrosis of the femur.\n\nResultsA total of 600 patients were screened out of which 541 patients who received corticosteroids were included in this study. 71.3% were male and 26.6 % were females. Most prevalent comorbidity was systemic hypertension (38.8%) followed by diabetes mellitus (38%). Most common presenting symptoms was dyspnoea followed by fever and cough. Majority patients received dexamethasone (95%). 65.8 % patients received conventional dose while 34.2% of patients received pulse dose. Mortality was more associated with pulse dose (44%) then a conventional dose (30%) (p-value 0.0015). the median duration of the corticosteroids was 10 days with an IQR of 7-13 days. During the hospitalisation 142 patients (26.2%) develops hyperglycaemia. Hyperglycaemia was more prevalent in the pulse dose steroid group (16.8% versus 9.4%). One patient develops pancreatitis. There was a significant reduction in the levels of inflammatory markers (p<0.005) after steroid initiation. At the 6th month of follow patients were assessed for AVN and suspected infection. 25 patients (8.25%) had infection out of which 19 received pulse dose. Out of 25 patients cultures was available for 7 patients and 2 patients grows pathogenic organism in the urine (pseudomonas and E. coli). 02 patients develop non-specific joint pain at 6 months. No patient had AVN during the follow up.\n\nConclusionCorticosteroid therapy in the COVID-19 is associated with various adverse event, commonly hyperglycaemia and the risk of the same increased with the high dose corticosteroids. corticosteroids appear to be a double-edged sword in combat against COVID-19 and need to be used aptly considering the risk-benefit ratio. The outcome of COVID-19 patients on corticosteroid therapy varies due to the use of different doses of corticosteroids. Routine follow-up of the recovered patients is needed to detect early unwanted", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.01.23293522", + "rel_abs": "The Orthocoronaviridae subfamily is large comprising four highly divergent genera. Four seasonal coronaviruses were circulating in humans prior to the coronavirus disease 2019 (COVID-19) pandemic. Infection with these viruses induced antibody responses that are relatively narrow with little cross-reactivity to spike proteins of other coronaviruses. Here, we report that infection with and vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces broadly crossreactive binding antibodies to spikes from a wide range of coronaviruses including members of the sarbecovirus subgenus, betacoronaviruses including Middle Eastern respiratory syndrome coronavirus (MERS CoV), and extending to alpha-, gamma- and delta-coronavirus spikes. These data show that the coronavirus spike antibody landscape in humans has profoundly been changed and broadened as a result of the SARS-CoV-2 pandemic. While we do not understand the functionality of these crossreactive antibodies, they may lead to enhanced resistance of the population to infection with newly emerging coronaviruses with pandemic potential.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Anant Kataria", - "author_inst": "All India institute Of Medical Sciences" + "author_name": "Gagandeep Singh", + "author_inst": "Icahn School of Medicine at Mount Sini" }, { - "author_name": "Yogesh Bahurupi", - "author_inst": "All India Institute Of Medical Sciences, Rishikesh" + "author_name": "Anass Abbad", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Gaurav Chikara", - "author_inst": "All India Institute Of medical Sciences , Rishikesh" + "author_name": "Giulio Kleiner", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Komal Srivastava", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Charles Gleason", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Juan Manuel Carreno Quiroz", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Viviana Simon", + "author_inst": "Icahn School of Medicine" }, { - "author_name": "Prasan Panda", - "author_inst": "All India institute of medical sciences , rishikesh" + "author_name": "Florian Krammer", + "author_inst": "Icahn School of Medicine at Mount Sinai" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -29015,51 +29134,47 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2023.07.31.551381", - "rel_title": "Growth media affects susceptibility of air-lifted human nasal epithelial cell cultures to SARS-CoV2, but not Influenza A, virus infection.", + "rel_doi": "10.1101/2023.08.01.550767", + "rel_title": "The Human Microglia Atlas (HuMicA) Unravels Changes in Homeostatic and Disease-Associated Microglia Subsets across Neurodegenerative Conditions", "rel_date": "2023-08-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.31.551381", - "rel_abs": "Primary differentiated human epithelial cell cultures have been widely used by researchers to study viral fitness and virus-host interactions, especially during the COVID19 pandemic. These cultures recapitulate important characteristics of the respiratory epithelium such as diverse cell type composition, polarization, and innate immune responses. However, standardization and validation of these cultures remains an open issue. In this study, two different expansion medias were evaluated and the impact on the resulting differentiated culture was determined. Use of both Airway and Ex Plus media types resulted in high quality, consistent cultures that were able to be used for these studies. Upon histological evaluation, Airway-grown cultures were more organized and had a higher proportion of basal progenitor cells while Ex Plus-grown cultures had a higher proportion terminally differentiated cell types. In addition to having different cell type proportions and organization, the two different growth medias led to cultures with altered susceptibility to infection with SARS-CoV-2 but not Influenza A virus. RNAseq comparing cultures grown in different growth medias prior to differentiation uncovered a high degree of differentially expressed genes in cultures from the same donor. RNAseq on differentiated cultures showed less variation between growth medias but alterations in pathways that control the expression of human transmembrane proteases including TMPRSS11 and TMPRSS2 were documented. Enhanced susceptibility to SARS-CoV-2 cannot be explained by altered cell type proportions alone, rather serine protease cofactor expression also contributes to the enhanced replication of SARS-CoV-2 as inhibition with camostat affected replication of an early SARS-CoV-2 variant and a Delta, but not Omicron, variant showed difference in replication efficiency between culture types. Therefore, it is important for the research community to standardize cell culture protocols particularly when characterizing novel viruses.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.01.550767", + "rel_abs": "Dysregulated microglia activation, leading to neuroinflammation, is crucial in neurodegenerative disease development and progression. The initial M1/M2 dual activation classification for microglia is outdated. Even the disease-associated microglia (DAM) phenotype, firstly described in mice, falls short in representing the diverse microglia phenotypes in pathology. In this study, we have constructed a transcriptomic atlas of human brain immune cells by integrating single-nucleus (sn)RNA-seq datasets from multiple neurodegenerative conditions. Sixteen datasets were included, comprising 295 samples from patients with Alzheimers disease, autism spectrum disorder, epilepsy, multiple sclerosis, Lewy body diseases, COVID-19, and healthy controls. The integrated Human Microglia Atlas (HuMicA) dataset included 60,557 nuclei and revealed 11 microglial subpopulations distributed across all pathological and healthy conditions. Among these, we identified four different homeostatic clusters as well as pathological phenotypes. These included two stages of early and late activation of the DAM phenotype and the disease-inflammatory macrophage (DIM) phenotype, which was recently described in mice, and is also present in human microglia, as indicated by our analysis. The high versatility of microglia is evident through changes in subset distribution across various pathologies, suggesting their contribution in shaping pathological phenotypes. Our analysis showed overall depletion of four substates of homeostatic microglia, and expansion of niche subpopulations within the DAM and DIM spectrum across distinct neurodegenerative pathologies. The HuMicA is invaluable in advancing the study of microglia biology in both healthy and disease settings.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Jessica D Resnick", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" - }, - { - "author_name": "Jo L Wilson", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Ricardo Martins-Ferreira", + "author_inst": "Josep Carreras Leukaemia Resaerch Institute (IJC)" }, { - "author_name": "Eduardo U. Anaya", - "author_inst": "Johns Hopkins University Bloomberg School of Public Health" + "author_name": "Josep Calafell-Segura", + "author_inst": "Josep CarrerasLeukaemia Research Institute (IJC)" }, { - "author_name": "Abigail Conte", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Barbara Leal", + "author_inst": "Universidade do Porto" }, { - "author_name": "Maggie Li", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Javier Rodriguez-Ubreva", + "author_inst": "Josep Carreras Leukaemia Research Institute (IJC)" }, { - "author_name": "William Zhong", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Elisabetta Mereu", + "author_inst": "Josep Carreras Leukaemia Research Institute (IJC)" }, { - "author_name": "Mike Beer", - "author_inst": "Johns Hopkins Univ." + "author_name": "Paulo Pinho e Costa", + "author_inst": "Universidade do Porto" }, { - "author_name": "Andrew Pekosz", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Esteban Ballestar", + "author_inst": "Josep Carreras Leukaemia Research Institute (IJC)" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "neuroscience" }, { "rel_doi": "10.1101/2023.08.01.23293497", @@ -30937,79 +31052,91 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2023.07.25.23293116", - "rel_title": "The Impact of Post Embryo Transfer SARS-CoV-2 Infection on Pregnancy in In Vitro Fertilization: A Prospective Cohort Study", + "rel_doi": "10.1101/2023.07.28.550765", + "rel_title": "Prolonged exposure to lung-derived cytokines is associated with inflammatory activation of microglia in patients with COVID-19", "rel_date": "2023-07-28", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.25.23293116", - "rel_abs": "ImportanceLimited knowledge exists on the effects of SARS-CoV-2 infection after embryo transfer, despite an increasing number of studies exploring the impact of previous SARS-CoV-2 infection on IVF outcomes.\n\nObjectiveThis prospective cohort study aimed to assess the influence of SARS-CoV-2 infection at various time stages after embryo transfer on pregnancy outcomes in patients undergoing conventional in vitro fertilization/intracytoplasmic sperm injection-embryo transfer (IVF/ICSI) treatment.\n\nDesignThe study was conducted at a single public IVF center in China.\n\nSettingThis was a population-based prospective cohort study.\n\nParticipantsFemale patients aged 20 to 39 years, with a body mass index (BMI) between 18 and 30 kg/m2, undergoing IVF/ICSI treatment, were enrolled from September 2022 to December 2022, with follow-up until March 2023.\n\nExposureThe pregnancy outcome of patients was compared between those SARS-CoV-2-infected after embryo transfer and those noninfected during the follow-up period.\n\nMain Outcomes and MeasuresThe pregnancy outcomes included biochemical pregnancy rate, implantation rate, clinical pregnancy rate, and early miscarriage rate.\n\nResultsA total of 857 female patients undergoing IVF/ICSI treatment were included in the analysis. We observed the incidence of SARS-CoV-2 infection within 10 weeks after embryo transfer. The biochemical pregnancy rate and implantation rate were lower in the infected group than the uninfected group (58.1% vs 65.9%; 36.6% vs 44.0%, respectively), but no statistically significant. Although, the clinical pregnancy rate was significant lower in the infection group when compared with the uninfected group (49.1%vs 58.2%, p < 0.05), after adjustment for confounders, this increased risk was no longer significant between the two groups (adjusted OR, 0.736, 95% CI, 0.518-1.046). With continued follow-up, a slightly higher risk of early miscarriage in the infected group compared to the uninfected group (9.3% vs 8.8%), but it was not significant (adjusted OR, 0.907, 95% CI, 0.414-1.986).\n\nConclusions and RelevanceThe studys findings suggested that SARS-CoV-2 infection within 10 weeks after embryo transfer may have not significantly affect pregnancy outcomes. This evidence allays concerns and provides valuable insights for assisted reproduction practices.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSDid the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after embryo transfer affect pregnancy outcomes?\n\nFindingsIn this prospective cohort study involving 857 patients, we made a pioneering discovery that SARS-CoV-2 infection following embryo transfer did not exhibit adverse impact on the biochemical pregnancy rate, embryo implantation rate, clinical pregnancy rate, and early miscarriage rate.\n\nMeaningThe evidence from this study alleviates existing concerns and offers new insights into the actual risk of SARS-CoV-2 infection after embryo transfer in assisted reproduction.", - "rel_num_authors": 15, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.28.550765", + "rel_abs": "Neurological impairment is the most common finding in patients with post-acute sequelae of COVID-19. Furthermore, survivors of pneumonia from any cause have an elevated risk of dementia1-4. Dysfunction in microglia, the primary immune cell in the brain, has been linked to cognitive impairment in murine models of dementia and in humans5. Here, we report a transcriptional response in human microglia collected from patients who died following COVID-19 suggestive of their activation by TNF-[a] and other circulating pro-inflammatory cytokines. Consistent with these findings, the levels of 55 alveolar and plasma cytokines were elevated in a cohort of 341 patients with respiratory failure, including 93 unvaccinated patients with COVID-19 and 203 patients with other causes of pneumonia. While peak levels of pro-inflammatory cytokines were similar in patients with pneumonia irrespective of etiology, cumulative cytokine exposure was higher in patients with COVID-19. Corticosteroid treatment, which has been shown to be beneficial in patients with COVID-196, was associated with lower levels of CXCL10, CCL8, and CCL2--molecules that sustain inflammatory circuits between alveolar macrophages harboring SARS-CoV-2 and activated T cells7. These findings suggest that corticosteroids may break this cycle and decrease systemic exposure to lung-derived cytokines and inflammatory activation of microglia in patients with COVID-19.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Yu-Bin Ding", - "author_inst": "chongqing medical university" + "author_name": "Rogan A Grant", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA" }, { - "author_name": "Xue-Fei Li", - "author_inst": "Sichuan Jinxin Xinan Women & Children's Hospital" + "author_name": "Taylor A. Poor", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA" }, { - "author_name": "Yong-Jia Zhang", - "author_inst": "chongqing medical university" + "author_name": "Lango Sichizya", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA" }, { - "author_name": "Qi Wan", - "author_inst": "West China Second Hospital, Sichuan University" + "author_name": "Estefani Diaz", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA" }, { - "author_name": "Ying-Ling Yao", - "author_inst": "chongqing medical university" + "author_name": "Joseph I. Bailey", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA" }, { - "author_name": "Ming-Xing Chen", - "author_inst": "chongqing medical university" + "author_name": "Sahil Soni", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA" }, { - "author_name": "Meng-Di Wang", - "author_inst": "chong qing medical university" + "author_name": "Karolina J. Senkow", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA" }, { - "author_name": "Li-Li Wang", - "author_inst": "Sichuan Jinxin Xinan Women & Children's Hospital" + "author_name": "Xochitl G. Perez-Leonor", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA" }, { - "author_name": "Xin-Yue Hu", - "author_inst": "chongqing medical university" + "author_name": "Hiam Abdala-Valencia", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA" }, { - "author_name": "Xiao-Jun Tang", - "author_inst": "chongqing medical university" + "author_name": "Ziyan Lu", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA" }, { - "author_name": "Zhao-Hui Zhong", - "author_inst": "chongqing medical university" + "author_name": "Helen K. Donnelly", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA" }, { - "author_name": "Li-Juan Fu", - "author_inst": "chongqing medical university" + "author_name": "Robert M. Tighe", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, Duke University School of Medicine, Duke University, Durham, NC, USA" }, { - "author_name": "Xin Luo", - "author_inst": "the First Affiliated Hospital of Chongqing Medical University" + "author_name": "Jon W. Lomasney", + "author_inst": "Department of Pathology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA" + }, + { + "author_name": "Richard G. Wunderink", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA" + }, + { + "author_name": "Benjamin D. Singer", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA" + }, + { + "author_name": "Alexander V. Misharin", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA" }, { - "author_name": "Xing-Yu Lv", - "author_inst": "Sichuan Jinxin Xinan Women & Children's Hospital" + "author_name": "G.R. Scott Budinger", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA" }, { - "author_name": "Li-Hong Geng", - "author_inst": "Sichuan Jinxin Xinan Women & Children's Hospital" + "author_name": "- The NU SCRIPT Investigators", + "author_inst": "-" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "obstetrics and gynecology" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2023.07.26.550688", @@ -32683,31 +32810,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.07.22.550164", - "rel_title": "AmpliDiff: An Optimized Amplicon Sequencing Approach to Estimating Lineage Abundances in Viral Metagenomes", + "rel_doi": "10.1101/2023.07.23.549087", + "rel_title": "Biophysical principles predict fitness of SARS-CoV-2 variants", "rel_date": "2023-07-24", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.22.550164", - "rel_abs": "Metagenomic profiling algorithms commonly rely on genomic differences between lineages, strains, or species to infer the relative abundances of sequences present in a sample. This observation plays an important role in the analysis of diverse microbial communities, where targeted sequencing of 16S and 18S ribosomal RNA (rRNA), both well-known hypervariable genomic regions, have led to insights into microbial diversity and the discovery of novel organisms. However, the variable nature of discriminatory regions can also act as a double-edged sword, as the sought-after variability can make it difficult to design primers for their amplification through Polymerase Chain Reaction (PCR). Moreover, the most variable regions are not necessarily the most informative regions for the purpose of differentiation; one should focus on regions that maximize the number of lineages that can be distinguished. Here we present AmpliDiff, a computational tool that simultaneously finds such highly discriminatory genomic regions, as well as primers allowing for the amplification of these regions. We show that regions and primers found by AmpliDiff can be used to accurately estimate relative abundances of SARS-CoV-2 lineages, for example in wastewater sequencing data. We obtain mean absolute prediction errors that are comparable with using whole genome information to estimate relative abundances. Furthermore, our results show that AmpliDiff is robust against incomplete input data and that primers designed by AmpliDiff continue to bind to genomes originating from months after the primers were selected. With AmpliDiff we provide an effective and efficient alternative to whole genome sequencing for estimating lineage abundances in viral metagenomes.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.23.549087", + "rel_abs": "SARS-CoV-2 employs its spike proteins receptor binding domain (RBD) to enter host cells. The RBD is constantly subjected to immune responses, while requiring efficient binding to host cell receptors for successful infection. However, understanding how RBDs biophysical properties contribute to SARS-CoV-2 epidemiological fitness remains largely unexplored. Through a comprehensive approach, comprising large-scale sequence analysis of SARS-CoV-2 variants and the discovery of a fitness function based on protein folding and binding thermodynamics, we unravel the relationship between the fitness contribution of the RBD and its biophysical properties. We developed a biophysical model that uses statistical mechanics to map the molecular phenotype space, characterized by binding constants to cell receptors and antibodies, onto the fitness landscape for variants ranging from the ancestral Wuhan Hu-1 to the Omicron BA.1. We validate our findings through experimentally measured binding affinities and population data on frequencies of variants. Our model forms the basis for a comprehensive epistatic map, relating the genotype space to fitness. Our study thus delivers a tool for predicting the future epidemiological trajectory of previously unseen or emerging low frequency variants, and sheds light on the impact of specific mutations on viral fitness. These insights offer not only greater understanding of viral evolution but also potentially aid in guiding public health decisions in the battle against COVID-19 and future pandemics.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Jasper van Bemmelen", - "author_inst": "Delft, University of Technology" + "author_name": "Dianzhuo Wang", + "author_inst": "Harvard University" }, { - "author_name": "Davida S Smyth", - "author_inst": "Texas A&M San Antonio" + "author_name": "Marian Huot", + "author_inst": "Harvard University" }, { - "author_name": "Jasmijn A Baaijens", - "author_inst": "Delft University of Technology" + "author_name": "Vaibhav Mohanty", + "author_inst": "Harvard Medical School and Massachusetts Institute of Technology" + }, + { + "author_name": "Eugene I. Shakhnovich", + "author_inst": "Harvard University" } ], "version": "1", "license": "cc_by_nd", "type": "new results", - "category": "bioinformatics" + "category": "biophysics" }, { "rel_doi": "10.1101/2023.07.24.550352", @@ -34229,135 +34360,43 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.07.18.549530", - "rel_title": "ACE2 mimetic antibody potently neutralizes all SARS-CoV-2 variants and fully protects in XBB.1.5 challenged monkeys", + "rel_doi": "10.1101/2023.07.17.549408", + "rel_title": "SPLASH: a statistical, reference-free genomic algorithm unifies biological discovery", "rel_date": "2023-07-18", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.18.549530", - "rel_abs": "The rapid evolution of SARS-CoV-2 to variants with improved transmission efficiency and reduced sensitivity to vaccine-induced humoral immunity has abolished the protective effect of licensed therapeutic human monoclonal antibodies (mAbs). To fill this unmet medical need and protect vulnerable patient populations, we isolated the P4J15 mAb from a previously infected, vaccinated donor, with <20 ng/ml neutralizing activity against all Omicron variants including the latest XBB.2.3 and EG.1 sub-lineages. Structural studies of P4J15 in complex with Omicron XBB.1 Spike show that the P4J15 epitope shares [~]93% of its buried surface area with the ACE2 contact region, consistent with an ACE2 mimetic antibody. Although SARS-CoV-2 mutants escaping neutralization by P4J15 were selected in vitro, these displayed lower infectivity, poor binding to ACE2, and the corresponding escape mutations are accordingly rare in public sequence databases. Using a SARS-CoV-2 XBB.1.5 monkey challenge model, we show that P4J15 confers complete prophylactic protection. We conclude that the P4J15 mAb has potential as a broad-spectrum anti-SARS-CoV-2 drug.", - "rel_num_authors": 29, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.17.549408", + "rel_abs": "The authors have withdrawn this manuscript due to a duplicate posting of manuscript number BIORXIV/2022/497555. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author. The correct preprint can be found at doi: https://doi.org/10.1101/2022.06.24.497555", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Craig Fenwick", - "author_inst": "Lausanne University Hospital" - }, - { - "author_name": "Priscilla Turelli", - "author_inst": "EPFL" - }, - { - "author_name": "Yoan Duhoo", - "author_inst": "EPFL" - }, - { - "author_name": "Kelvin Lau", - "author_inst": "EPFL" - }, - { - "author_name": "Cecile Herate", - "author_inst": "University Paris-Saclay, Inserm, CEA" - }, - { - "author_name": "Romain Marlin", - "author_inst": "CEA Paris-Saclay Center - Fontenay-aux-Roses Site: Commissariat a l'energie atomique et aux energies alternatives Site de Fontenay-aux-Roses" - }, - { - "author_name": "Myriam Lamrayah", - "author_inst": "EPFL" - }, - { - "author_name": "Jeremy Campos", - "author_inst": "Lausanne University Hospital" - }, - { - "author_name": "Line Leuenberger", - "author_inst": "Lausanne University Hospital" - }, - { - "author_name": "Alex Farina", - "author_inst": "Lausanne University Hospital" - }, - { - "author_name": "charlene raclot", - "author_inst": "EPFL" - }, - { - "author_name": "Vanessa Genet", - "author_inst": "EPFL" - }, - { - "author_name": "Flurin Fiscalini", - "author_inst": "Lausanne University Hospital" - }, - { - "author_name": "Julien Cesborn", - "author_inst": "Lausanne University Hospital" - }, - { - "author_name": "Laurent Perez", - "author_inst": "University of Lausanne" - }, - { - "author_name": "Nathalie Bosquet", - "author_inst": "CEA" - }, - { - "author_name": "Vanessa Contreras", - "author_inst": "CEA Paris-Saclay Center - Fontenay-aux-Roses Site: Commissariat a l'energie atomique et aux energies alternatives Site de Fontenay-aux-Roses" - }, - { - "author_name": "Kyllian Lheureux", - "author_inst": "CEA" - }, - { - "author_name": "francis relouzat", - "author_inst": "CEA" - }, - { - "author_name": "Rana Abdelnabi", - "author_inst": "Rega Institute, KU Leuven" - }, - { - "author_name": "Caroline Shi-Yan Foo", - "author_inst": "Katholieke Universiteit Leuven" - }, - { - "author_name": "Johan Neyts", - "author_inst": "Rega Institute" - }, - { - "author_name": "pieter leyssen", - "author_inst": "KU Leuven" - }, - { - "author_name": "Yves Levy", - "author_inst": "VRI, Universite Paris-Est Creteil" + "author_name": "Kaitlin Chaung", + "author_inst": "Stanford University" }, { - "author_name": "Florence Pojer", - "author_inst": "EPFL" + "author_name": "Tavor Zvi Baharav", + "author_inst": "Stanford University" }, { - "author_name": "Henning Stahlberg", - "author_inst": "EPFL" + "author_name": "George Henderson", + "author_inst": "Stanford University" }, { - "author_name": "Roger Le Grand", - "author_inst": "CEA" + "author_name": "Peter Wang", + "author_inst": "Stanford University" }, { - "author_name": "Didier Trono", - "author_inst": "EPFL SV GHI LVG" + "author_name": "Ivan N. Zheludev", + "author_inst": "Stanford University" }, { - "author_name": "Giuseppe Pantaleo", - "author_inst": "Lausanne University Hospital" + "author_name": "Julia Salzman", + "author_inst": "Stanford University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "new results", - "category": "microbiology" + "category": "genomics" }, { "rel_doi": "10.1101/2023.07.17.549425", @@ -35919,51 +35958,39 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2023.07.14.549026", - "rel_title": "Performance of amplicon and capture based next-generation sequencing approaches for the epidemiological surveillance of Omicron SARS-CoV-2 and other variants of concern.", + "rel_doi": "10.1101/2023.07.13.23292575", + "rel_title": "Environmental Surface Monitoring as a Noninvasive Method for SARS-CoV-2 Surveillance in Community Settings: Lessons from a University Campus Study", "rel_date": "2023-07-14", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.14.549026", - "rel_abs": "To control the SARS-CoV-2 pandemic, healthcare systems have focused on ramping up their capacity for epidemiological surveillance through viral whole genome sequencing. In this paper, we tested the performance of two protocols of SARS-CoV-2 nucleic acid enrichment, an amplicon enrichment using different versions of the ARTIC primer panel and a hybrid-capture method using KAPA RNA Hypercap. We focused on the challenge of the Omicron variant sequencing, the advantages of automated library preparation and the influence of the bioinformatic analysis in the final consensus sequence. All 94 samples were sequenced using Illumina iSeq 100 and analysed with two bioinformatic pipelines: a custom-made pipeline and an Illumina-owned pipeline. We were unsuccessful in sequencing six samples using the capture enrichment due to low reads. On the other hand, amplicon dropout and mispriming caused the loss of mutation G21987A and the erroneous addition of mutation T15521A respectively using amplicon enrichment. Overall, we found high sequence agreement regardless of method of enrichment, bioinformatic pipeline or the use of automation for library preparation in eight different SARS-CoV-2 variants. Automation and the use of a simple app for bioinformatic analysis can simplify the genotyping process, making it available for more diagnostic facilities and increasing global vigilance.", - "rel_num_authors": 8, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.13.23292575", + "rel_abs": "Environmental testing of high-touch objects is a potential noninvasive approach for monitoring population-level trends of SARS-CoV-2 and other respiratory viruses within a defined setting. We aimed to determine the association between SARS-CoV-2 contamination on high-touch environmental surfaces, community level case incidence, and university student health data. Environmental swabs were collected from January 2022 to November 2022 from high-touch objects and surfaces from five locations on a large university campus in Florida, USA. RT-qPCR was used to detect and quantify viral RNA, and a subset of positive samples was analyzed by viral genome sequencing to identify circulating lineages. During the study period, we detected SARS-CoV-2 viral RNA on 90.7% of 162 tested samples. Levels of environmental viral RNA correlated with trends in community-level activity and case reports from the student health center. A significant positive correlation was observed between the estimated viral gene copy number in environmental samples and the weekly confirmed cases at the university. Viral sequencing data from environmental samples identified lineages contemporaneously circulating in the local community and state based on genomic surveillance data. Further, we detected emerging variants in environmental samples prior to their identification by clinical genomic surveillance. Our results demonstrate the utility of viral monitoring on high-touch environmental surfaces for SARS-CoV-2 surveillance at a community level. In communities with delayed or limited testing facilities, immediate environmental surface testing may considerably inform epidemic dynamics.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC=\"FIGDIR/small/23292575v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (21K):\norg.highwire.dtl.DTLVardef@1b467e5org.highwire.dtl.DTLVardef@1111651org.highwire.dtl.DTLVardef@d055baorg.highwire.dtl.DTLVardef@1ac57fe_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Carlos Davi\u00f1a-Nu\u00f1ez", - "author_inst": "Galicia Sur Health Research Institute: Instituto de Investigacion Sanitaria Galicia Sur" - }, - { - "author_name": "Sonia Perez", - "author_inst": "University Hospital of Vigo" - }, - { - "author_name": "Jorge Julio Cabrera-Alvargonz\u00e1lez", - "author_inst": "Galicia Sur Health Research Institute: Instituto de Investigacion Sanitaria Galicia Sur" - }, - { - "author_name": "Anniris Rinc\u00f3n-Quintero", - "author_inst": "Galicia Sur Health Research Institute: Instituto de Investigacion Sanitaria Galicia Sur" + "author_name": "Sobur Ali", + "author_inst": "College of Medicine, University of Central Florida, Orlando, Florida, USA" }, { - "author_name": "Ana Treinta-\u00c1lvarez", - "author_inst": "Vigo University Hospital Group: Complexo Hospitalario Universitario de Vigo" + "author_name": "Eleonora Cella", + "author_inst": "College of Medicine, University of Central Florida, Orlando, Florida, USA" }, { - "author_name": "Montse Godoy-Diz", - "author_inst": "CHUVI: Complexo Hospitalario Universitario de Vigo" + "author_name": "Catherine Johnston", + "author_inst": "College of Medicine, University of Central Florida, Orlando, Florida, USA" }, { - "author_name": "Silvia Su\u00e1rez-Luque", - "author_inst": "Conseller\u00eda de Sanidade e Servicio Galego de Sa\u00fade: Servicio Galego de Saude" + "author_name": "Michael Deichen", + "author_inst": "Student Health Services, University of Central Florida, Orlando, Florida, USA" }, { - "author_name": "Benito Regueiro-Garc\u00eda", - "author_inst": "Galicia Sur Health Research Institute: Instituto de Investigacion Sanitaria Galicia Sur" + "author_name": "Taj Azarian", + "author_inst": "College of Medicine, University of Central Florida, Orlando, Florida, USA" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.07.12.548630", @@ -37452,7 +37479,7 @@ "rel_date": "2023-07-09", "rel_site": "medRxiv", "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.08.23292389", - "rel_abs": "Antimicrobial peptides (AMPs) are a complex network of 10-100 amino acid sequence molecules, widely distributed in Nature. Even though more than 300 AMPs have been described in mammals, cathelicidins and defensins remain the most investigated to date.\n\nSome publications examined the role of AMPs in COVID-19, but the findings are preliminary and in vivo studies are still lacking. Here, we report the plasma levels of five AMPs (LL-37, -defensin 1, -defensin 3, {beta}-defensin 1 and {beta}-defensin 3) and five cytokines (tumor necrosis factor-, interleukin-1{beta}, interleukin-6, interleukin-10, interferon-{gamma} and monocyte chemoattractant protein-1), in 15 healthy volunteers, 36 COVID-19 patients without Acute Kidney Injury (AKI) and 17 COVID-19 patients with AKI, since AKI is a well-known marker of worse prognosis in Sars-CoV-2 infections.\n\nWe found increased levels of -defensin 1, -defensin 3 and {beta}-defensin 3, but not LL-37 or {beta}-defensin 3, in our COVID-19 population, when compared with the healthy controls, in conjunction with higher levels of interleukin-6, interleukin-10, interferon-{gamma} and monocyte chemoattractant protein-1, putting in evidence that these AMPs and cytokines may have an important role in the systemic inflammatory response and tissue damage that characterizes severe COVID-19.\n\nGraphic Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=152 SRC=\"FIGDIR/small/23292389v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (45K):\norg.highwire.dtl.DTLVardef@a78e41org.highwire.dtl.DTLVardef@6c8b49org.highwire.dtl.DTLVardef@2c86aaorg.highwire.dtl.DTLVardef@13d0e45_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_abs": "Antimicrobial peptides (AMPs) are a complex network of 10-100 amino acid sequence molecules, widely distributed in Nature. Even though more than 300 AMPs have been described in mammals, cathelicidins and defensins remain the most investigated to date.\n\nSome publications examined the role of AMPs in COVID-19, but the findings are preliminary and in vivo studies are still lacking. Here, we report the plasma levels of five AMPs (LL-37, -defensin 1, -defensin 3, {beta}-defensin 1 and {beta}-defensin 3) and five cytokines (tumor necrosis factor-, interleukin-1{beta}, interleukin-6, interleukin-10, interferon-{gamma} and monocyte chemoattractant protein-1), in 15 healthy volunteers, 36 COVID-19 patients without Acute Kidney Injury (AKI) and 17 COVID-19 patients with AKI, since AKI is a well-known marker of worse prognosis in Sars-CoV-2 infections.\n\nWe found increased levels of -defensin 1, -defensin 3 and {beta}-defensin 3, but not LL-37 or {beta}-defensin 3, in our COVID-19 population, when compared with the healthy controls, in conjunction with higher levels of interleukin-6, interleukin-10, interferon-{gamma} and monocyte chemoattractant protein-1, putting in evidence that these AMPs and cytokines may have an important role in the systemic inflammatory response and tissue damage that characterizes severe COVID-19.\n\nGraphic Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=152 SRC=\"FIGDIR/small/23292389v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (45K):\norg.highwire.dtl.DTLVardef@e75686org.highwire.dtl.DTLVardef@1e199baorg.highwire.dtl.DTLVardef@33b48aorg.highwire.dtl.DTLVardef@91e190_HPS_FORMAT_FIGEXP M_FIG C_FIG", "rel_num_authors": 5, "rel_authors": [ { @@ -37537,75 +37564,47 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2023.07.06.23292337", - "rel_title": "Association of Chronotype and Shiftwork with COVID-19 Infection", + "rel_doi": "10.1101/2023.07.07.23292399", + "rel_title": "Poor Hemorrhagic Stroke Outcomes During the COVID-19 Pandemic Are Driven by Socioeconomic Disparities", "rel_date": "2023-07-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.06.23292337", - "rel_abs": "ObjectiveThis study assesses whether chronotype is related to COVID-19 infection and whether there is an interaction with shift work.\n\nMethodsCross-sectional survey of 19,821 U.S. adults\n\nResultsCOVID-19 infection occurred in 40% of participants, 32.6% morning and 17.2% evening chronotypes. After adjusting for demographic and socioeconomic factors, shift work, sleep duration and comorbidities, morning chronotype was associated with a higher (aOR: 1.15, 95% CI 1.10-1.21) and evening chronotype with a lower (aOR: 0.82, 95% CI: 0.78-0.87) prevalence of COVID-19 infection in comparison to an intermediate chronotype. Working exclusively night shifts was not associated with higher prevalence of COVID-19. Morning chronotype and working some evening shifts was associated with the highest prevalence of previous COVID-19 infection (aOR: 1.87, 95% CI: 1.28-2.74).\n\nConclusionMorning chronotype and working a mixture of shifts increase risk of COVID-19 infection.\n\nLearning OutcomesO_LIDescribe the association between chronotype and prevalence of COVID-19 infection\nC_LIO_LISummarize the combined effect of chronotype and shift work on the prevalence of COVID-19 infection\nC_LI", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.07.23292399", + "rel_abs": "BackgroundNationally representative data demonstrating the impact of the COVID-19 pandemic on hemorrhagic stroke outcomes are lacking.\n\nMethodsIn this pooled cross-sectional analysis, we used the National Inpatient Sample (2016-2020) to identify adults (>=18 years) with primary intracerebral hemorrhage (ICH) or subarachnoid hemorrhage (SAH). We fit segmented logistic regression models to evaluate the differences in the rates of in-hospital outcomes (in-hospital mortality, home discharge, and receiving neurosurgical procedures) between the pre-pandemic (January 2016-February 2020) and pandemic periods (March 2020-December 2020). We used multivariable logistic regression models to evaluate the differences in mortality between patients admitted from April to December 2020, with and without COVID-19, and those admitted during a similar period in 2019. Stratified analyses were conducted among patients residing in low and high-income zip codes and among patients with extreme loss of function (E-LoF) and those with minor to major loss of function (MM-LoF).\n\nResultsOverall, 309,965 ICH patients (mean age [SD]: 68[14.8], 47% female, 56% low-income) and 112,210 SAH patients (mean age [SD]: 60.2[15.4], 62% female, 55% low-income) were analyzed. Pre-pandemic, ICH mortality was decreasing by {approx} 1 % per month (adjusted odds ratio, 95% confidence interval: 0.99, 0.99-1.00). However, during the pandemic, the overall ICH mortality rate increased by {approx} 2% per month (1.02, 1.00-1.02) and {approx} 4% per month among low-income patients (1.04, 1.01-1.07). However, there was no change in trend among high-income ICH patients during the pandemic (1.00, 0.97-1.03). Patients with comorbid COVID-19 in 2020 had significantly higher odds of mortality compared to the 2019 comparison cohort, overall (ICH: 1.83, 1.33-2.51; SAH: 2.76, 1.68-4.54), and among patients with MM-LoF (ICH: 2.15, 1.12-4.16; SAH: 5.77, 1.57-21.17). However, patients with E-LoF and comorbid COVID-19 had similar mortality rates with the 2019 cohort.\n\nConclusionSustained efforts are needed to address socioeconomic disparities in healthcare access, quality, and outcomes during public health emergencies.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Stuart Quan", - "author_inst": "Brigham and Women's Hospital" - }, - { - "author_name": "Matthew D Weaver", - "author_inst": "Brigham and Women's Hospital" - }, - { - "author_name": "Mark E Czeisler", - "author_inst": "Monash University" - }, - { - "author_name": "Laura K Barger", - "author_inst": "Brigham and Women's Hospital" - }, - { - "author_name": "Lauren A Booker", - "author_inst": "Monash University" - }, - { - "author_name": "Mark E Howard", - "author_inst": "Monash University" - }, - { - "author_name": "Melinda L Jackson", - "author_inst": "Monash University" + "author_name": "Abdulaziz T. Bako", + "author_inst": "Houston Methodist" }, { - "author_name": "Rashon I Lane", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Thomas B. H. Potter", + "author_inst": "Houston Methodist" }, { - "author_name": "Christine F McDonald", - "author_inst": "Monash University" + "author_name": "Alan P. Pan", + "author_inst": "Houston Methodist" }, { - "author_name": "Anna Ridgers", - "author_inst": "Austin Health" + "author_name": "Karim A. Borei", + "author_inst": "Houston Methodist Hospital" }, { - "author_name": "Rebecca Robbins", - "author_inst": "Brigham & Women's Hospital" + "author_name": "Taya Prince", + "author_inst": "Houston Methodist" }, { - "author_name": "Prerna Verma", - "author_inst": "Monash University" + "author_name": "Gavin Britz", + "author_inst": "Methodist Neurological Institute" }, { - "author_name": "Shantha MW Rajaratnam", - "author_inst": "Monash University" - }, - { - "author_name": "Charles A Czeisler", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Farhaan S Vahidy", + "author_inst": "Houston Methodist" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "neurology" }, { "rel_doi": "10.1101/2023.07.07.23292215", @@ -39599,59 +39598,91 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2023.06.22.23291702", - "rel_title": "Preclinical and Human Phase 1 Studies of Aerosolized Hydroxychloroquine: Implications for Antiviral COVID-19 Therapy", + "rel_doi": "10.1101/2023.07.01.23292108", + "rel_title": "Polymerized type I collagen down-regulates STAT-1 phosphorylation through engagement to LAIR-1 in M1-macrophages avoiding long COVID", "rel_date": "2023-07-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.22.23291702", - "rel_abs": "Based on early reports of the efficacy of hydroxychloroquine sulfate (HCQS) to inhibit SARS-CoV-2 viral replication in vitro, and since severe pulmonary involvement is the major cause of COVID-19 mortality, we assessed the safety and efficacy of aerosolized HCQS (aHCQS) therapy in animals and humans. In a Phase 1 study of aHCQS in healthy volunteers, doses up to 50 mg were well tolerated and estimated epithelial lining fluid concentrations immediately after inhalation (>2,000 M) exceeded the in vitro concentrations needed for suppression of viral replication ([≥]119 M). A study in rats comparing HCQS solution administered orally (13.3 mg/kg) and by intratracheal installation (IT 0.18 mg/kg, <5% of oral dose) demonstrated that at 2 minutes, IT administration was associated with 5X higher mean hydroxychloroquine (HCQ) concentrations in the lung (IT: 49.5 {+/-} 6.5 {micro}g HCQ/g tissue, oral: 9.9 {+/-} 3.4; p<0.01). A subsequent study of IT and intranasal HCQS in the Syrian hamster model of SARS-CoV-2 infection, however, failed to show clinical benefit. We conclude that aHCQS alone is unlikely to be effective for COVID-19, but based on our aHCQS pharmacokinetics and current viral entry data, adding oral HCQS to aHCQS, along with a transmembrane protease inhibitor, may improve efficacy.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.01.23292108", + "rel_abs": "BackgroundThe polymerized type I collagen (PTIC) is a {gamma}-irradiated mixture of pepsinized porcine type I collagen and polyvinylpyrrolidone (PVP). It has immunomodulatory properties. However, the receptor and signaling pathway through which it exerts its therapeutic effects has not yet been identified.\n\nAimTo evaluate LAIR-1 as a potential receptor for PTIC and the signaling pathway evoked by ligand-receptor binding.\n\nMethodsLAIR-1 binding assay was performed by incubating various concentrations of recombinant human LAIR-1 with native type I collagen or PTIC. Macrophages M1- derived from THP-1 cells were cultured with 2-10% PTIC for 24 h. Cell lysates from THP- 1, monocytes-like cells (MLCs), M1, M1+IFN-{gamma}, M1+LPS, and 2 or 10% PTIC treated M1 were analyzed by western blot for the transcription factors NF-{kappa}B (p65), p38, STAT-1, and pSTAT-1. Cytokines, Th1 cells, and M1/M2 macrophages were analyzed by luminometry and flow cytometry from blood samples of symptomatic COVID-19 outpatients on treatment with intramuscular administration of PTIC.\n\nResultsPTIC binds LAIR-1 with a similar affinity to native collagen. This binding decreases STAT-1 signaling IFN-{gamma}-induced and IL-1{beta} expression in M1 macrophages by down-regulating STAT-1 phosphorylation. Moreover, intramuscular PTIC treatment of symptomatic COVID-19 outpatients decreased at statistically significant levels the percentage of M1 macrophages and cytokines (IP-10, MIF, eotaxin, IL-8, IL-1RA, and M- CSF) associated with STAT-1 transcription factor and increased M2 macrophages and Th1 cells. The downregulation of inflammatory mediators was related to better oxygen saturation and decreased dyspnea, chest pain, cough, and chronic fatigue syndrome in the acute phase of infection and the long term.\n\nConclusionPTIC is an agonist of LAIR-1 and down-regulates STAT-1 phosphorylation. PTIC could be relevant for treating STAT-1-mediated inflammatory diseases, including COVID-19 and long COVID", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Ohad S Bentur", - "author_inst": "The Rockefeller University" + "author_name": "Elizabeth Olivares Martinez", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, Mexico" }, { - "author_name": "Richard Hutt", - "author_inst": "The Rockefeller Univesity" + "author_name": "Diego Francisco Hernandez-Ramirez", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" }, { - "author_name": "Donna Brassil", - "author_inst": "The Rockefeller University" + "author_name": "Carlos Alberto Nunez-Alvarez", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" }, { - "author_name": "Ana C Krieger", - "author_inst": "Weill Cornell Medical College, Cornell University" + "author_name": "Monica Chapa-Ibarguengoitia", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" }, { - "author_name": "Per Backman", - "author_inst": "Emmace Consulting AB, Sweden" + "author_name": "Silvia Mendez-Flores", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" }, { - "author_name": "B Lauren Charous", - "author_inst": "Pulmoquine Therapeutics Inc." + "author_name": "Angel Priego-Ranero", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" }, { - "author_name": "Homer Boushey", - "author_inst": "University of California, San Francisco, CA" + "author_name": "Daniel Azamar-Llamas", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" }, { - "author_name": "Igor Gonda", - "author_inst": "Respidex LLC, Dennis, MA" + "author_name": "Hector Olvera-Prado", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" }, { - "author_name": "Barry S Coller", - "author_inst": "The Rockefeller University" + "author_name": "Kenia Ilian Rivas-Redonda", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" }, { - "author_name": "Robert B MacArthur", - "author_inst": "The Rockefeller University" + "author_name": "Eric Ochoa-Hein", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" + }, + { + "author_name": "Luis Gerardo Lopez-Mosqueda", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" + }, + { + "author_name": "Estefano Rojas-Castaneda", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" + }, + { + "author_name": "Said Urbina-Teran", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" + }, + { + "author_name": "Luis Septien-Stute", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" + }, + { + "author_name": "Thierry Hernandez-Gilsoul", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" + }, + { + "author_name": "Diana Aguilar-Leon", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" + }, + { + "author_name": "Gonzalo Torres-Villalobos", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" + }, + { + "author_name": "Janette Furuzawa-Carballeda", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pharmacology and therapeutics" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2023.06.30.23292087", @@ -41817,71 +41848,139 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.06.23.23291835", - "rel_title": "Use of antimicrobials during the COVID-19 pandemic: a qualitative study among stakeholders in Nepal", - "rel_date": "2023-06-29", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.23.23291835", - "rel_abs": "IntroductionThe COVID-19 pandemic was a major public health threat and posed tremendous pressure to develop a cure for it. Apart from ongoing efforts in developing vaccines, a lot of empirical treatments were recommended, that may have expedited the use of antimicrobials. The main objective of this study was to explore if and how the pandemic posed pressure on antimicrobials in Nepal using semi-structured interviews (SSIs) among patients, clinicians and drug dispensers.\n\nMethodsA total of 30 stakeholders (10 each among clinicians, dispensers and COVID-19 patients) were identified purposively and were approached for SSIs. Clinicians and dispensers working in three tertiary hospitals in Kathmandu were first approached and were asked for their support to reach out to COVID-19 patients who were on follow-up at their out-patient department. SSIs were audio recorded, translated and transcribed into English, and were analyzed for thematic synthesis.\n\nResultsOver-the-counter (OTC) uses of antibiotics were widespread during the pandemic, and were mostly rooted to patients attempts to halt the potential severity due to respiratory like illnesses, and the fear of being identified as a COVID-19 patients. Being identified as a COVID-19 patient was feared because of the stigmatization and social isolation. Patients who visited the drug shops and physicians were reported to make demands on specific medicines including antibiotics that may have added pressure among physicians and dispensers. Clinicians reported a degree of uncertainty related to treatment and that may have added pressure to prescribe antimicrobials. All stakeholders, although mostly patients and dispensers with limited understanding of what constitutes antimicrobials and the mechanisms underpinning it reported that the pressure during the pandemic may have added to the adversities such as antimicrobials resistance.\n\nConclusionsCOVID-19 added a pressure to prescribe, dispense and overuse antimicrobials and may have accentuated the pre-existing OTC use of antimicrobials. Future pandemics including infectious disease outbreaks are major public health incidents that warrant a special caution on inappropriate pressure on antimicrobials. Strict policies related to the use of antimicrobials are urgent to redress their use during normal and pandemic situations.", - "rel_num_authors": 13, + "rel_doi": "10.1101/2023.06.27.546784", + "rel_title": "Efficacy of the oral nucleoside prodrug GS-5245 (Obeldesivir) against SARS-CoV-2 and coronaviruses with pandemic potential", + "rel_date": "2023-06-28", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.06.27.546784", + "rel_abs": "Despite the wide availability of several safe and effective vaccines that can prevent severe COVID-19 disease, the emergence of SARS-CoV-2 variants of concern (VOC) that can partially evade vaccine immunity remains a global health concern. In addition, the emergence of highly mutated and neutralization-resistant SARS-CoV-2 VOCs such as BA.1 and BA.5 that can partially or fully evade (1) many therapeutic monoclonal antibodies in clinical use underlines the need for additional effective treatment strategies. Here, we characterize the antiviral activity of GS-5245, Obeldesivir (ODV), an oral prodrug of the parent nucleoside GS-441524, which targets the highly conserved RNA-dependent viral RNA polymerase (RdRp). Importantly, we show that GS-5245 is broadly potent in vitro against alphacoronavirus HCoV-NL63, severe acute respiratory syndrome coronavirus (SARS-CoV), SARS-CoV-related Bat-CoV RsSHC014, Middle East Respiratory Syndrome coronavirus (MERS-CoV), SARS-CoV-2 WA/1, and the highly transmissible SARS-CoV-2 BA.1 Omicron variant in vitro and highly effective as antiviral therapy in mouse models of SARS-CoV, SARS-CoV-2 (WA/1), MERS-CoV and Bat-CoV RsSHC014 pathogenesis. In all these models of divergent coronaviruses, we observed protection and/or significant reduction of disease metrics such as weight loss, lung viral replication, acute lung injury, and degradation in pulmonary function in GS-5245-treated mice compared to vehicle controls. Finally, we demonstrate that GS-5245 in combination with the main protease (Mpro) inhibitor nirmatrelvir had increased efficacy in vivo against SARS-CoV-2 compared to each single agent. Altogether, our data supports the continuing clinical evaluation of GS-5245 in humans infected with COVID-19, including as part of a combination antiviral therapy, especially in populations with the most urgent need for more efficacious and durable interventions.", + "rel_num_authors": 30, "rel_authors": [ { - "author_name": "Binod Dhungel", - "author_inst": "Tribhuvan University Institute of Science and Technology" + "author_name": "David R. Martinez", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Upendra Thapa Shrestha", - "author_inst": "Tribhuvan University" + "author_name": "Fernando Moreira", + "author_inst": "The University of North Carolina at Chapel Hill" }, { - "author_name": "Sanjib Adhikari", - "author_inst": "TU IOST: Tribhuvan University Institute of Science and Technology" + "author_name": "Mark R Zweigart", + "author_inst": "University of North Carolina" }, { - "author_name": "Nabaraj Adhikari", - "author_inst": "Tribhuvan University" + "author_name": "Kendra L Gully", + "author_inst": "University of North Carolina" }, { - "author_name": "Alisha Bhattarai", - "author_inst": "Tribhuvan University Institute of Medicine" + "author_name": "Gabriela De la Cruz", + "author_inst": "The University of North Carolina at Chapel Hill" }, { - "author_name": "Sunil Pokharel", - "author_inst": "University of Oxford" + "author_name": "Ariane Brown", + "author_inst": "The University of North Carolina at Chapel Hill" }, { - "author_name": "Abhilasha Karkey", - "author_inst": "Patan Academy of Health Sciences" + "author_name": "Lily E. Adams", + "author_inst": "UNC Chapel Hill" }, { - "author_name": "Direk Limmathurotsakul", - "author_inst": "Mahidol-Oxford Tropical Medicine Research Unit" + "author_name": "Nicholas Catanzaro", + "author_inst": "University of North Carolina at Chapel Hill School of Medicine" }, { - "author_name": "Prakash Ghimire", - "author_inst": "Tribhuvan University Institute of Science and Technology" + "author_name": "Boyd Yount", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Komal Raj Rijal", - "author_inst": "Tribhuvan University" + "author_name": "Thomas J Baric", + "author_inst": "The University of North Carolina at Chapel Hill" }, { - "author_name": "Phaik Yeong Cheah", - "author_inst": "Mahidol University" + "author_name": "Michael Mallory", + "author_inst": "The University of North Carolina at Chapel Hill" }, { - "author_name": "Christopher Pell", - "author_inst": "University of Amsterdam: Universiteit van Amsterdam" + "author_name": "Helen Conrad", + "author_inst": "The University of North Carolina at Chapel Hill" }, { - "author_name": "Bipin Adhikari", - "author_inst": "University of Oxford" + "author_name": "Samantha R May", + "author_inst": "University of North Carolina" + }, + { + "author_name": "Stephanie Dong", + "author_inst": "University of North Carolina at Chapel Hill" + }, + { + "author_name": "Trevor D. Scobey", + "author_inst": "University of North Carolina at Chapel Hill" + }, + { + "author_name": "Stephanie Montgomery", + "author_inst": "The University of North Carolina at Chapel Hill" + }, + { + "author_name": "Jason K Perry", + "author_inst": "Gilead Sciences" + }, + { + "author_name": "Darius Babusis", + "author_inst": "Gilead Sciences, Inc" + }, + { + "author_name": "Kimberly Barrett", + "author_inst": "Gilead Sciences, Inc" + }, + { + "author_name": "Anh-Hoa Nguyen", + "author_inst": "Vona Health" + }, + { + "author_name": "Anh-Quan Nguyen", + "author_inst": "Gilead Sciences, Inc" + }, + { + "author_name": "Rao Kalla", + "author_inst": "Gilead Sciences, Inc" + }, + { + "author_name": "Roy Bannister", + "author_inst": "Gilead Sciences, Inc" + }, + { + "author_name": "John Bilello", + "author_inst": "Gilead Sciences" + }, + { + "author_name": "Joy Feng", + "author_inst": "Gilead Sciences" + }, + { + "author_name": "Tomas Cihlar", + "author_inst": "Gilead Sciences, Inc" + }, + { + "author_name": "Ralph S. Baric", + "author_inst": "University of North Carolina at Chapel Hill" + }, + { + "author_name": "Richard Mackman", + "author_inst": "Gilead Sciences" + }, + { + "author_name": "Alexandra Schaefer", + "author_inst": "University of North Carolina at Chapel Hill" + }, + { + "author_name": "Timothy P Sheahan", + "author_inst": "University of North Carolina at Chapel Hill" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2023.06.27.546790", @@ -43287,43 +43386,51 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2023.06.20.23291685", - "rel_title": "Multicenter analysis of COVID-19 hospitalizations and stacking machine learning algorithms for prediction of high-risk patients", + "rel_doi": "10.1101/2023.06.21.23291712", + "rel_title": "Enhanced real-time mass spectrometry breath analysis for the diagnosis of COVID-19", "rel_date": "2023-06-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.20.23291685", - "rel_abs": "ObjectiveTo create and validate an ensemble of machine learning algorithms to accurately predict ICU admission or mortality upon initial presentation to the emergency department.\n\nMethodsThis is a retrospective cohort study of a multicenter hospital system in the United States. The electronic health record was queried from March 2020 to December 2021 for patients who presented to the emergency department who were subsequently COVID-positive. Associated patient demographics, vitals, and laboratory vitals were obtained. High-risk individuals were defined as those who required ICU admission or died; low-risk individuals did not meet those criteria. The dataset was split into a 3:1 training to testing dataset. A machine learning ensemble stack was built to predict ICU admission and mortality.\n\nResultsOf the 3,142 hospital admissions with a COVID positive test, there were 1,128 (36%) individuals labeled as high-risk, and 2,014 (64%) as low-risk. We obtained 147 unique variables. CRP, LDH, procalcitonin, glucose, anion gap, creatinine, age, oxygen saturation, oxygen device, and obtainment of an ABG were chosen. Six machine learning models were then trained over model-specific hyperparameters, and then assessed on the testing dataset, generating an area under the receiver operator curve of 0.751, with a specificity of 95% in predicting high-risk individuals based on an initial emergency department assessment.\n\nConclusionA novel machine learning model was generated to predict ICU admission and patient mortality from a multicenter hospital system and validated on unseen data.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.21.23291712", + "rel_abs": "BackgroundAlthough rapid screening for and diagnosis of COVID-19 are still urgently needed, most current testing methods are either long, costly, and/or poorly specific. The objective of the present study was to determine whether or not artificial-intelligence-enhanced real-time MS breath analysis is a reliable, safe, rapid means of screening ambulatory patients for COVID-19.\n\nMethodsIn two prospective, open, interventional studies in a single university hospital, we used real-time, proton transfer reaction time-of-flight mass spectrometry to perform a metabolomic analysis of exhaled breath from adults requiring screening for COVID-19. Artificial intelligence and machine learning techniques were used to build mathematical models based on breath analysis data either alone or combined with patient metadata.\n\nResultsWe obtained breath samples from 173 participants, of whom 67 had proven COVID-19. After using machine learning algorithms to process breath analysis data and further enhancing the model using patient metadata, our method was able to differentiate between COVID-19-positive and -negative participants with a sensitivity of 98%, a specificity of 74%, a negative predictive value of 98%, a positive predictive value of 72%, and an area under the receiver operating characteristic curve of 0.961. The predictive performance was similar for asymptomatic, weakly symptomatic and symptomatic participants and was not biased by the COVID-19 vaccination status.\n\nConclusionsReal-time, non-invasive, artificial-intelligence-enhanced mass spectrometry breath analysis might be a reliable, safe, rapid, cost-effective, high-throughput method for COVID-19 screening.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Reid Shaw", - "author_inst": "Loyola University Medical Center" + "author_name": "Camille Roquencourt", + "author_inst": "Exhalomics, Hopital Foch, Suresnes, France" }, { - "author_name": "David Bassily", - "author_inst": "Loyola University Medical Center" + "author_name": "Helene Salvator", + "author_inst": "Exhalomics, Hopital Foch, Suresnes, France; Service de pneumologie, Hopital Foch, Suresnes, France; VIM Suresnes, UMR 0892, Universite Paris-Saclay, Suresnes, " }, { - "author_name": "Love Patel", - "author_inst": "Loyola University Medical Center" + "author_name": "Emmanuelle Bardin", + "author_inst": "Exhalomics, Hopital Foch, Suresnes, France; Universite Paris-Saclay, UVSQ, INSERM, Infection et inflammation (2I), U1173, Departement de Biotechnologie de la Sa" }, { - "author_name": "Timothy O'Connor", - "author_inst": "Loyola University Medical Center" + "author_name": "Elodie Lamy", + "author_inst": "Universite Paris-Saclay, UVSQ, INSERM, Infection et inflammation (2I), U1173, Departement de Biotechnologie de la Sante, Montigny le Bretonneux, France" }, { - "author_name": "Robert Rafidi", - "author_inst": "Loyola University Medical Center" + "author_name": "Eric Farfour", + "author_inst": "Service de biologie clinique, Hopital Foch, Suresnes, France" }, { - "author_name": "Perry Formanek", - "author_inst": "Loyola University Medical Center" + "author_name": "Emmanuel Naline", + "author_inst": "Exhalomics, Hopital Foch, Suresnes, France" + }, + { + "author_name": "Philippe Devillier", + "author_inst": "Exhalomics, Hopital Foch, Suresnes, France; Laboratoire de recherche en Pharmacologie Respiratoire - VIM Suresnes, UMR 0892, Universite Paris-Saclay, Suresnes, " + }, + { + "author_name": "Stanislas Grassin Delyle", + "author_inst": "Exhalomics, Hopital Foch, Suresnes, France; Universite Paris-Saclay, UVSQ, INSERM, Infection et inflammation (2I), U1173, Departement de Biotechnologie de la Sa" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2023.06.20.23291649", @@ -45093,59 +45200,139 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.06.16.23288870", - "rel_title": "The public health impact of Paxlovid COVID-19 treatment in the United States", - "rel_date": "2023-06-19", + "rel_doi": "10.1101/2023.06.13.23291329", + "rel_title": "Mitigating the psychological impacts of COVID-19 restrictions on older people: The UK Behavioural Activation in Social Isolation (BASIL+) COVID-19 Urgent Public Health (UPH) trial and living systematic review", + "rel_date": "2023-06-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.16.23288870", - "rel_abs": "The antiviral drug Paxlovid has been shown to rapidly reduce viral load. Coupled with vaccination, timely administration of safe and effective antivirals could provide a path towards managing COVID-19 without restrictive non-pharmaceutical measures. Here, we estimate the population-level impacts of expanding treatment with Paxlovid in the US using a multi-scale mathematical model of SARS-CoV-2 transmission that incorporates the within-host viral load dynamics of the Omicron variant. We find that, under a low transmission scenario (Re [~] 1.2) treating 20% of symptomatic cases would be life and cost saving, leading to an estimated 0.26 (95% CrI: 0.03, 0.59) million hospitalizations averted, 30.61 (95% CrI: 1.69, 71.15) thousand deaths averted, and US$52.16 (95% CrI: 2.62, 122.63) billion reduction in health- and treatment-related costs. Rapid and broad use of the antiviral Paxlovid could substantially reduce COVID-19 morbidity and mortality, while averting socioeconomic hardship.\n\nArticle Summary LineMass treatment of symptomatic COVID-19 cases with antivirals that rapidly arrest SARS-CoV-2 replication would substantially reduce the spread and burden of the pandemic.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.13.23291329", + "rel_abs": "BackgroundOlder adults were more likely to be socially isolated during the COVID-19 pandemic, with risk of depression and loneliness. Behavioural Activation (BA) could feasibly maintain mental health in the face of COVID isolation.\n\nMethodsWe undertook a multicentre randomised controlled trial [BASIL+ ISRCTN63034289] of BA to mitigate depression and loneliness among older people. BA was offered by telephone to intervention participants (n=218). Control participants received usual care, with existing COVID wellbeing resources (n=217).\n\nFindingsParticipants engaged with 5.2 (SD 2.9) of 8 remote BA sessions. Adjusted mean difference (AMD) for depression (PHQ-9) at 3 months [primary outcome] was -1.65 (95% CI -2.54 to -0.75, p<0.001). There was an effect for BA on emotional loneliness at 3 months (AMD -0.37, 95% CI -0.68 to -0.06, p=0.02), but not social loneliness (AMD -0.05, 95% CI -0.33 to 0.23, p=0.72). Other secondary outcomes at 3 months were anxiety (GAD-7: AMD -0.67, 95% CI -1.43 to 0.09, p=0.08) and quality of life (SF12 mental component: AMD 1.99, 95% CI 0.22 to 3.76, p=0.03; physical component: AMD - 0.50, 95% CI -2.14 to 1.10, p=0.53).\n\nBASIL+ trial results were incorporated into a living systematic review [PROSPERO CRD42021298788], and we found strong evidence of an impact of behavioural and/or cognitive strategies on depression [random effects pooled standardised mean difference -0.32, 95% CI -0.48 to -0.16, 10 studies, n=1,210 participants] and loneliness [random effects pooled standardised mean difference -0.44, 95%CI -0.64 to -0.24, 13 studies, n=1,421 participants] in the short-term (<6 months).\n\nInterpretationBA is an effective intervention that reduces depression and some aspects of loneliness in the short term. This adds to the range of strategies to improve population mental health, particularly among older adults with multiple long-term conditions. These results will be helpful to policy makers in preventing depression and loneliness beyond the pandemic.\n\nFundingNIHR RP-PG-0217-20006", + "rel_num_authors": 30, "rel_authors": [ { - "author_name": "Yuan Bai", - "author_inst": "University of Hong Kong" + "author_name": "Simon Gilbody", + "author_inst": "Mental Health and Addictions Research Group" }, { - "author_name": "Zhanwei Du", - "author_inst": "University of Hong Kong" + "author_name": "Elizabeth Littlewood", + "author_inst": "University of York Department of Health Sciences" }, { - "author_name": "Lin Wang", - "author_inst": "University of Hong Kong" + "author_name": "Dean McMillan", + "author_inst": "University of York Department of Health Sciences" }, { - "author_name": "Eric H. Y. Lau", - "author_inst": "University of Hong Kong" + "author_name": "Lucy Atha", + "author_inst": "University of York" }, { - "author_name": "Chun Hai Fung", - "author_inst": "Georgia Southern University" + "author_name": "Della Bailey", + "author_inst": "University of York Department of Health Sciences" }, { - "author_name": "Petter Holme", - "author_inst": "Aalto University" + "author_name": "Kalpita Baird", + "author_inst": "University of York Department of Health Sciences" }, { - "author_name": "Benjamin J. Cowling", - "author_inst": "University of Hong Kong" + "author_name": "Samantha Gascoyne", + "author_inst": "University of York Department of Health Sciences" }, { - "author_name": "Alison P. Galvani", - "author_inst": "Yale School of Public Health" + "author_name": "Lauren Burke", + "author_inst": "University of Manchester" }, { - "author_name": "Robert M. Krug", - "author_inst": "University of Texas at Austin" + "author_name": "Carolyn A. Chew-Graham", + "author_inst": "Keele University School of Medicine" }, { - "author_name": "Lauren Ancel Meyers", - "author_inst": "University of Texas at Austin" + "author_name": "Peter Coventry", + "author_inst": "University of York Department of Health Sciences" + }, + { + "author_name": "Suzanne Crosland", + "author_inst": "University of York" + }, + { + "author_name": "Caroline Fairhurst", + "author_inst": "University of York Department of Health Sciences" + }, + { + "author_name": "Andrew Henry", + "author_inst": "University of York" + }, + { + "author_name": "Kelly Hollingsworth", + "author_inst": "University of York" + }, + { + "author_name": "Elizabeth Newbronner", + "author_inst": "University of York" + }, + { + "author_name": "Eloise Ryde", + "author_inst": "University of York Department of Health Sciences" + }, + { + "author_name": "Leanne Shearsmith", + "author_inst": "University of Leeds" + }, + { + "author_name": "Han-i Wang", + "author_inst": "University of York" + }, + { + "author_name": "Judith Webster", + "author_inst": "Patient and Public Involvement Representative, UK" + }, + { + "author_name": "Rebecca Woodhouse", + "author_inst": "University of York Department of Health Sciences" + }, + { + "author_name": "Andrew Clegg", + "author_inst": "University of Leeds" + }, + { + "author_name": "Sarah Dexter Smith", + "author_inst": "Tees Esk and Wear Valleys NHS Foundation Trust" + }, + { + "author_name": "Tom Gentry", + "author_inst": "Age UK" + }, + { + "author_name": "Catherine Hewitt", + "author_inst": "University of York" + }, + { + "author_name": "Andrew Hill", + "author_inst": "University of Leeds" + }, + { + "author_name": "Karina Lovell", + "author_inst": "The University of Manchester" + }, + { + "author_name": "Claire Sloan", + "author_inst": "University of York Department of Health Sciences" + }, + { + "author_name": "Gemma Traviss-Turner", + "author_inst": "University of Leeds Leeds Institute of Health Sciences" + }, + { + "author_name": "Steven Pratt", + "author_inst": "NHS" + }, + { + "author_name": "David Ekers", + "author_inst": "University of York Department of Health Sciences" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2023.06.16.23291449", @@ -46915,51 +47102,31 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.06.08.23291102", - "rel_title": "Low Dose Naltrexone use for the management of post acute sequelae of COVID 19", + "rel_doi": "10.1101/2023.06.09.23291044", + "rel_title": "SARS-CoV-2 Spread Under the Controlled-Distancing Model of Rio Grande do Sul, Brazil", "rel_date": "2023-06-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.08.23291102", - "rel_abs": "Post-Acute Sequelae of SARS-CoV-2 (PASC), also known as Long COVID, is globally estimated to have affected up to 40-50% of individuals who were infected with SARS-CoV-2. The causes of PASC are being investigated, and there are no established therapies. One of the leading hypotheses for the cause of PASC is the persistent activation of innate immune cells with increased systemic inflammation. Naltrexone is a medication with anti-inflammatory and immunomodulatory properties that has been used in other conditions that overlap with PASC. In this study we performed retrospective review of a clinical cohort of 59 patients at a single academic center who received low-dose naltrexone (LDN) off-label as a potential therapeutic intervention for PASC. The use of LDN was associated with improved clinical symptoms (fatigue, brain fog, post exertional malaise/PEM, unrefreshing sleep, sleep pattern, and headache), fewer number of symptoms, and better functional status. This observational finding warrants further testing in rigorous, randomized, placebo-controlled clinical trials.\n\nHighlights- The off-label use of low-dose naltrexone is a promising drug intervention candidate for the management of post-COVID conditions.\n- Low-dose naltrexone has anti-inflammatory and immunomodulatory properties which may benefit those with PASC where persistent inflammation is the causative pathway.\n- This potential benefit of LDN warrants further testing in rigorous randomized, placebo-controlled clinical trials.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.09.23291044", + "rel_abs": "In early 2020, the government of Rio Grande do Sul established a public-health assessment-response framework to halt the spread of SARS-CoV-2, called controlled-distancing model (CDM). This framework subdivided the state in 21 regions where it evaluated a composite index of disease transmission and health-service capacity. Updated on a weekly basis, the index placed regions on a color-coded scale of flags, which guided adoption of non-pharmaceutical interventions. We aim to evaluate the extent to which the CDM accurately assessed transmission and the effectiveness of its responses throughout 2020. We estimated the weekly effective reproduction number (Rt) of SARS-CoV-2, for each region, using a renewal-equation-based statistical model of notified COVID-19 deaths. Using Rt estimates, we explored whether flag colors assigned by the CDM either reflected or affected SARS-CoV-2 dissemination. Flag assignments did reflect variations in Rt, to a limited extent, but we found no evidence that they affected Rt in the short term. Medium-term effects were apparent in only four regions after eight or more weeks of red-flag assignment. Analysis of Google movement metrics showed no evidence that people moved differently under different flags. The dissociation between flag colors and the propagation of SARS-CoV-2 does not support the claim that non-pharmaceutical interventions are ineffective. Our results show, however, that decisions made under the CDM framework were ineffective both for influencing the movement of people and for halting the spread of the virus.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Hector Bonilla", - "author_inst": "Stanford University" - }, - { - "author_name": "Lu Tian", - "author_inst": "Stanford University" - }, - { - "author_name": "Vincent Marconi", - "author_inst": "Emory University" - }, - { - "author_name": "Robert William Shafer", - "author_inst": "Stanford University" - }, - { - "author_name": "Grace Mccomsey", - "author_inst": "Case Western Reserve University and University hospitals of Cleveland" - }, - { - "author_name": "Mitchell G Miglis", - "author_inst": "Stanford University" + "author_name": "Ricardo Rohweder", + "author_inst": "Universidade Federal do Rio Grande do Sul" }, { - "author_name": "Phillip C Yang", - "author_inst": "Stanford University" + "author_name": "Lavinia Schuler-Faccini", + "author_inst": "Universidade Federal do Rio Grande do Sul" }, { - "author_name": "Linda N Geng", - "author_inst": "Stanford University" + "author_name": "Gon\u00e7alo Ferraz", + "author_inst": "Universidade Federal do Rio Grande do Sul" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pharmacology and therapeutics" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.06.09.23291201", @@ -48493,91 +48660,39 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2023.06.05.543758", - "rel_title": "Post-acute immunological and behavioral sequelae in mice after Omicron infection", + "rel_doi": "10.1101/2023.06.05.23290309", + "rel_title": "Upper limb functional recovery in chronic stroke patients after COVID-19-interrupted rehabilitation: An observational study", "rel_date": "2023-06-07", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.06.05.543758", - "rel_abs": "Progress in understanding long COVID and developing effective therapeutics is hampered in part by the lack of suitable animal models. Here we used ACE2-transgenic mice recovered from Omicron (BA.1) infection to test for pulmonary and behavioral post-acute sequelae. Through in-depth phenotyping by CyTOF, we demonstrate that naive mice experiencing a first Omicron infection exhibit profound immune perturbations in the lung after resolving acute infection. This is not observed if mice were first vaccinated with spike-encoding mRNA. The protective effects of vaccination against post-acute sequelae were associated with a highly polyfunctional SARS-CoV-2-specific T cell response that was recalled upon BA.1 breakthrough infection but not seen with BA.1 infection alone. Without vaccination, the chemokine receptor CXCR4 was uniquely upregulated on multiple pulmonary immune subsets in the BA.1 convalescent mice, a process previously connected to severe COVID-19. Taking advantage of recent developments in machine learning and computer vision, we demonstrate that BA.1 convalescent mice exhibited spontaneous behavioral changes, emotional alterations, and cognitive-related deficits in context habituation. Collectively, our data identify immunological and behavioral post-acute sequelae after Omicron infection and uncover a protective effect of vaccination against post-acute pulmonary immune perturbations.", - "rel_num_authors": 18, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.05.23290309", + "rel_abs": "BackgroundUpper limb function of chronic stroke patients declined when outpatient rehabilitation was interrupted, and outings restricted, due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. In this study, we investigated whether these patients recovered upper limb function after resumption of outpatient rehabilitation.\n\nMethodsIn this observational study, 43 chronic stroke hemiplegic patients with impaired upper extremity function were scored for limb function via Fugl-Meyer Assessment of the Upper Extremity (FMA-UE), Action Research Arm Test (ARAT) after a structured interview, evaluation, and intervention. Scores at 6 months and 3 months before and 3 months after rehabilitation interruption were examined retrospectively, and scores immediately after resumption of care and at 3 and 6 months after resumption of care were examined prospectively. The amount of change for each time period and an analysis of covariance was performed with time as a factor and the change in FMA-UE and ARAT scores as dependent variables and by setting statistical significance at 5%.\n\nResultsTime of evaluation significantly impacted total, part C, and part D of FMA-UE as well as total, pinch, and gross movement of ARAT. Post-hoc tests showed that the magnitude of change in limb function scores from immediately after resumption of rehabilitation to 3 months after resumption was significantly higher than the change from 3 months before to immediately after interruption for total, and part D of FMA-UE, and grip, and gross movement of ARAT (p<0.05).\n\nConclusionsThe results suggest that upper limb functional decline in chronic stroke patients, caused by the SARS-CoV-2 pandemic-related therapy interruption and outing restrictions, was resolved after approximately 3 months of resumption of rehabilitation therapy. Our data can serve as reference standards for planning and evaluating treatment for chronic stroke patients with impaired upper limb function due to inactivity.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Tongcui Ma", - "author_inst": "University of California, San Francisco; and Gladstone Institutes" - }, - { - "author_name": "Rahul K. Suryawanshi", - "author_inst": "University of California, San Francisco; and Gladstone Institutes" + "author_name": "Daigo Sakamoto", + "author_inst": "Jikei University School of Medicine: Tokyo Jikeikai Ika Daigaku" }, { - "author_name": "Stephanie R. Miller", - "author_inst": "University of California, San Francisco; and Gladstone Institutes" + "author_name": "Toyohiro Hamaguchi", + "author_inst": "Graduate School of Health Sciences, Saitama Prefectural University" }, { - "author_name": "Katie K. Ly", - "author_inst": "University of California, San Francisco; and Gladstone Institutes" + "author_name": "Yasuhide Nakayama", + "author_inst": "Jikei University School of Medicine: Tokyo Jikeikai Ika Daigaku" }, { - "author_name": "Reuben Thomas", - "author_inst": "Gladstone Institutes" + "author_name": "Takuya Hada", + "author_inst": "Jikei University School of Medicine: Tokyo Jikeikai Ika Daigaku" }, { - "author_name": "Natalie Elphick", - "author_inst": "Gladstone Institutes" - }, - { - "author_name": "Kailin Yin", - "author_inst": "University of California, San Francisco; and Gladstone Institutes" - }, - { - "author_name": "Xiaoyu Luo", - "author_inst": "University of California, San Francisco; and Gladstone Institutes" - }, - { - "author_name": "Nick Kaliss", - "author_inst": "University of California, San Francisco; and Gladstone Institutes" - }, - { - "author_name": "Irene P. Chen", - "author_inst": "University of California, San Francisco; and Gladstone Institutes" - }, - { - "author_name": "Mauricio Montano", - "author_inst": "University of California, San Francisco; and Gladstone Institutes" - }, - { - "author_name": "Bharath Sreekumar", - "author_inst": "University of California, San Francisco; and Gladstone Institutes" - }, - { - "author_name": "Ludger Standker", - "author_inst": "Ulm University" - }, - { - "author_name": "Jan Munch", - "author_inst": "Ulm University" - }, - { - "author_name": "F. Heath Damron", - "author_inst": "West Virginia University" - }, - { - "author_name": "Jorge J. Palop", - "author_inst": "University of California, San Francisco; and Gladstone Institutes" - }, - { - "author_name": "Melanie Ott", - "author_inst": "University of California, San Francisco; and Gladstone Institutes" - }, - { - "author_name": "Nadia R. Roan", - "author_inst": "University of California, San Francisco; and Gladstone Institutes" + "author_name": "Masahiro Abo", + "author_inst": "Jikei University School of Medicine: Tokyo Jikeikai Ika Daigaku" } ], "version": "1", "license": "cc_by_nd", - "type": "new results", - "category": "microbiology" + "type": "PUBLISHAHEADOFPRINT", + "category": "rehabilitation medicine and physical therapy" }, { "rel_doi": "10.1101/2023.06.06.23290826", @@ -50267,159 +50382,71 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2023.06.01.23290819", - "rel_title": "SARS-CoV-2 human challenge reveals single-gene blood transcriptional biomarkers that discriminate early and late phases of acute respiratory viral infections.", + "rel_doi": "10.1101/2023.05.31.23290798", + "rel_title": "EuroQol-5D-3L in Long Covid patients After Supplementation with EchA Marine, a Sea Urchin Eggs Extract: a double-blinded, multicentrical study.", "rel_date": "2023-06-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.01.23290819", - "rel_abs": "Evaluation of host-response blood transcriptional signatures of viral infection have so far failed to test whether these biomarkers reflect different biological processes that may be leveraged for distinct translational applications. We addressed this question in the SARS-CoV-2 human challenge model. We found differential time profiles for interferon (IFN) stimulated blood transcriptional responses represented by measurement of single genes. MX1 transcripts correlated with a rapid and transient wave of type 1 IFN stimulated genes (ISG) across all cell types, which may precede PCR detection of replicative infection. Another ISG, IFI27, showed a delayed but sustained response restricted to myeloid peripheral blood mononuclear cells, attributable to gene and cell-specific epigenetic regulation. These findings were reproducible in diverse respiratory virus challenges, and in natural infection with SARS-CoV-2 or unselected respiratory viruses. The MX1 response achieved superior diagnostic accuracy in early infection, correlation with viral load and identification of virus culture positivity, with potential to stratify patients for time sensitive antiviral treatment. IFI27 achieved superior diagnostic accuracy across the time course of symptomatic infection. Compared to blood, measurement of these responses in nasal mucosal samples was less sensitive and did not discriminate between early and late phases of infection.", - "rel_num_authors": 35, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.31.23290798", + "rel_abs": "Patients with Long COVID experience a significant decrease in their quality of life and the lack of effective treatment represents an unmet need in medical care and patient health. One proposed strategy for treating Long COVID is to increase the bodys ability to restore immune balance by controlling inflammation with anti-inflammatory substances. For this reason, the aim of this double-blind study was to evaluate the supplementation of patients with EchA Marine(R), a dietary supplement based on sea urchin eggs rich in Echinochrome A. This compound has demonstrated anti-inflammatory and antioxidant properties by activating the metabolism of glutathione and improving mitochondrial mass and performance. The EuroQol 5-Dimension (EQ-5D) is a standardized questionnaire assessing five dimensions of health: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression used as an instrument to measure health-related quality of life in clinical and economic studies. In this multicenter, double-blind, intervention study, we have demonstrated that the dietary supplement EchA Marine(R) can significantly enhance the quality of life of these patients, particularly in pain and discomfort; notably improving their quality of life and daily activitys ability. EchA Marine(R) is an effective treatment option for Long COVID patients and with further research its efficacy could be further strengthened.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Joshua Rosenheim", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "Valeria Brichetti", + "author_inst": "Hospital Donacion Francisco Santojanni" }, { - "author_name": "Rishi K Gupta", - "author_inst": "Institute of Health Informatics, University College London, London, UK" + "author_name": "Tamara Rubilar", + "author_inst": "IPAM UNPSJB - CESIMAR - CONICET" }, { - "author_name": "Claire Thakker", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "Julieta V Tejada", + "author_inst": "Hospital Donacion Francisco Santojanni" }, { - "author_name": "Tiffeney Mann", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "Priscila Montecino", + "author_inst": "Hospital Donacion Francisco Santojanni" }, { - "author_name": "Lucy CK Bell", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "Augusto C Crespi-Abril", + "author_inst": "IPAM-UNPSJB-CESIMAR-CONICET" }, { - "author_name": "Claire M Broderick", - "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" + "author_name": "Elena S Barbieri", + "author_inst": "IPAM-UNPSJB-CESIMAR-CONICET" }, { - "author_name": "Kieran Madon", - "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" + "author_name": "Maria R Nunez", + "author_inst": "Hospital General de Agudos Jose Maria Ramos Mejia" }, { - "author_name": "Loukas Papargyris", - "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" + "author_name": "Javier M Iriarte-Vasquez", + "author_inst": "Hospital General de Agudos Jose Maria Ramos Mejia" }, { - "author_name": "Pete Dayananda", - "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" + "author_name": "Nora Jajati", + "author_inst": "Hospital General de Agudos Jose Maria Ramos Mejia" }, { - "author_name": "Andrew J Kwok", - "author_inst": "Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK." - }, - { - "author_name": "James Greenan-Barrett", - "author_inst": "Department of Respiratory Medicine, University College London Hospitals NHS Foundation Trust, London, UK" - }, - { - "author_name": "Helen R Wagstaffe", - "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" - }, - { - "author_name": "Emily Conibear", - "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" - }, - { - "author_name": "Joe Fenn", - "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" - }, - { - "author_name": "Seran Hakki", - "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" - }, - { - "author_name": "Rik GH Lindeboom", - "author_inst": "Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK" - }, - { - "author_name": "Lisa Dratvia", - "author_inst": "Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK" - }, - { - "author_name": "Briac Lemetais", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" - }, - { - "author_name": "Caroline M Weight", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" - }, - { - "author_name": "Cristina Venturini", - "author_inst": "Infection, Immunity and Inflammation Department, Great Ormond Street Institute of Child Health, University College London, London, UK" - }, - { - "author_name": "Myrisni Kaforou", - "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" - }, - { - "author_name": "Michael Levin", - "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" + "author_name": "Clara Volonteri", + "author_inst": "CESIMAR-CONICET" }, { - "author_name": "Mariya Kalinova", - "author_inst": "hVIVO Services Ltd., London, UK" - }, - { - "author_name": "Alex Mann", - "author_inst": "hVIVO Services Ltd., London, UK" - }, - { - "author_name": "Andrew Catchpole", - "author_inst": "hVIVO Services Ltd., London, UK" - }, - { - "author_name": "Julian C Knight", - "author_inst": "Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK." - }, - { - "author_name": "Marko Z Nikoli\u0107", - "author_inst": "Division of Medicine, University College London, London, UK" - }, - { - "author_name": "Sarah A Teichmann", - "author_inst": "Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK" - }, - { - "author_name": "Ben Killingley", - "author_inst": "Department of Infectious Diseases, University College London Hospital NHS Foundation Trust, London, UK" - }, - { - "author_name": "Wendy Barclay", - "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" + "author_name": "Martin Sivori", + "author_inst": "Hospital General de Agudos Jose Maria Ramos Mejia" }, { - "author_name": "Benjamin M Chain", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "Gabriela de-larranaga", + "author_inst": "Hospital de Infecciosas Francisco Javier Muniz" }, { - "author_name": "Ajit Lalvani", - "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" - }, - { - "author_name": "Robert S Heyderman", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" - }, - { - "author_name": "Christopher Chiu", - "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" - }, - { - "author_name": "Mahdad Noursadeghi", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "Fernando Saldarini", + "author_inst": "Hospital Donacion Francisco Santojanni" } ], "version": "1", "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "pain medicine" }, { "rel_doi": "10.1101/2023.05.31.23290799", @@ -52557,47 +52584,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.05.25.23289996", - "rel_title": "Comparative analysis of symptom profile and risk of death associated with infection by SARS-CoV-2 and its variants in Hong Kong", + "rel_doi": "10.1101/2023.05.24.23290418", + "rel_title": "Impact of COVID-19 on Hepatitis B Screening in Sierra Leone: Insights from a Community Pharmacy Model of Care", "rel_date": "2023-05-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.25.23289996", - "rel_abs": "IntroductionThe recurrent multi-wave nature of COVID-19 necessitates updating its symptomatology. Before the omicron era, Hong Kong was relatively unscathed and had a low vaccine uptake rate among the old-old, giving us an opportunity to study the intrinsic severity of SARS-CoV-2 variants. A comparison of symptom patterns across variants and vaccination status in Hong Kong has yet to be undertaken. The intrinsic severity of variants and symptoms predictive of severe outcomes are also understudied as COVID-19 evolves. We therefore aim to characterize the effect of variants on symptom presentation, identify the symptoms predictive and protective of death, and quantify the effect of vaccination on symptom development.\n\nMethodsWith the COVID-19 case series in Hong Kong from inception to 25 August 2022, an iterative multi-tier text-matching algorithm was developed to identify symptoms from free text. Cases were fully vaccinated if they completed two doses. Multivariate regression was used to measure associations between variants, symptom development, death and vaccination status. A least absolute shrinkage and selection operator technique was used to identify a parsimonious set of symptoms jointly associated with death.\n\nResultsOverall, 70.9% (54450/76762) of cases were symptomatic. We identified a wide spectrum of symptoms (n=102), with cough, fever, runny nose and sore throat being the most common (8.16-47.0%). Intrinsically, the wild-type and delta variant caused similar symptoms, with runny nose, sore throat, itchy throat and headache more frequent in the delta cohort; whereas symptoms were heterogeneous between the wild-type and omicron variant, with seven symptoms (fatigue, fever, chest pain, runny nose, sputum production, nausea/vomiting and sore throat) more frequent in the omicron cohort. With full vaccination, omicron was still more likely than delta to cause fever. Fever, blocked nose and shortness of breath were robustly jointly predictive of death as the virus evolved. Number of vaccine doses required for reduction in occurrence varied by symptoms.\n\nDiscussionThis is the first large-scale study to evaluate the changing symptomatology by COVID-19 variants and vaccination status using free-text reporting by patients. We substantiate existing findings that omicron has a different clinical presentation compared to previous variants. Syndromic surveillance can be bettered with reduced reliance on symptom-based case identification, increased weighing on symptoms robustly predictive of mortality in outcome prediction, strengthened infection control in care homes through universal individual-based risk assessment to enable early risk stratification, adjusting the stockpile of medicine to tally with the changing symptom profiles across vaccine doses, and incorporating free-text symptom reporting by patients.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.24.23290418", + "rel_abs": "BackgroundThere are limited studies evaluating the impact of COVID-19-related interruptions on hepatitis B virus (HBV) screening in endemic countries in Sub-Saharan Africa.\n\nMethodsWe conducted a retrospective study of HBV testing in a community pharmacy in Freetown, Sierra Leone, from October 1, 2019, through September 30, 2022. We compared participant characteristics using Pearsons chi-square test. We evaluated trends in HBV screening and diagnosis using one-way ANOVA with Tukeys or Dunnetts post-test.\n\nFindingsOf 920 individuals screened, 161 had detectable HBsAg (seroprevalence 17.5% [95% CI 14.9-20.4]). There was a 100% decrease in HBV screening during January-June of 2020; however, screening increased by 27% and 23% in the first and second year after COVID-19, respectively. Mean quarterly tests showed a significant upward trend: 55 {+/-} 6 tests during January-March (baseline), 74 {+/-} 16 tests during April-June, 101 {+/-} 3 tests during July-September, and 107 {+/-} 17 tests during October-December (one-way ANOVA test for trend, F=7.7, p = 0.0254) but not the mean quarterly number of people diagnosed with HBV (F = 0.34, p = 0.7992).\n\nInterpretationCommunity-based HBV screening dramatically improved following temporary disruptions related to COVID-19. Seasonal variation in HBV screening, but not HBV diagnosis, may have implications for HBV elimination efforts in Sierra Leone and other West African countries.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Kin On KWOK", - "author_inst": "JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China" + "author_name": "Manal Ghazzawi", + "author_inst": "KnowHep Foundation Sierra Leone" + }, + { + "author_name": "Lawrence S Babawo", + "author_inst": "Njala University" + }, + { + "author_name": "Amir M. Mohareb", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Peter B James", + "author_inst": "Southern Cross University" }, { - "author_name": "Wan In WEI", - "author_inst": "JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China" + "author_name": "Sahr A Yendewa", + "author_inst": "Ministry of Health and Sanitation of Sierra Leone" }, { - "author_name": "Edward MCNEIL", - "author_inst": "JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China" + "author_name": "Samuel PE Massaquoi", + "author_inst": "Ministry of Health and Sanitation of Sierra Leone" }, { - "author_name": "Arthur TANG", - "author_inst": "School of Science, Engineering and Technology, RMIT University, Vietnam" + "author_name": "Peterlyn E Cummings", + "author_inst": "Ministry of Health and Sanitation of Sierra Leone" }, { - "author_name": "Julian TANG", - "author_inst": "Respiratory Sciences, University of Leicester, Leicester, United Kingdom; Clinical Microbiology, Leicester Royal Infirmary, Leicester, United Kingdom" + "author_name": "Sulaiman Lakoh", + "author_inst": "Ministry of Health and Sanitation of Sierra Leone" }, { - "author_name": "Samuel Yeung-Shan WONG", - "author_inst": "JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China" + "author_name": "Robert A Salata", + "author_inst": "Case Western Reserve University" }, { - "author_name": "Eng Kiong YEOH", - "author_inst": "Centre for Health Systems and Policy Research, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China" + "author_name": "George A Yendewa", + "author_inst": "Case Western Reserve University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.05.27.23290638", @@ -55163,85 +55202,101 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.05.24.541850", - "rel_title": "Cross-Protection Induced by Highly Conserved Human B, CD4+, and CD8+ T Cell Epitopes-Based Coronavirus Vaccine Against Severe Infection, Disease, and Death Caused by Multiple SARS-CoV-2 Variants of Concern", - "rel_date": "2023-05-24", + "rel_doi": "10.1101/2023.05.22.540829", + "rel_title": "Vaccine-mediated protection against merbecovirus and sarbecovirus challenge in mice", + "rel_date": "2023-05-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.24.541850", - "rel_abs": "BackgroundThe Coronavirus disease 2019 (COVID-19) pandemic has created one of the largest global health crises in almost a century. Although the current rate of SARS-CoV-2 infections has decreased significantly; the long-term outlook of COVID-19 remains a serious cause of high death worldwide; with the mortality rate still surpassing even the worst mortality rates recorded for the influenza viruses. The continuous emergence of SARS-CoV-2 variants of concern (VOCs), including multiple heavily mutated Omicron sub-variants, have prolonged the COVID-19 pandemic and outlines the urgent need for a next-generation vaccine that will protect from multiple SARS-CoV-2 VOCs.\n\nMethodsIn the present study, we designed a multi-epitope-based Coronavirus vaccine that incorporated B, CD4+, and CD8+ T cell epitopes conserved among all known SARS-CoV-2 VOCs and selectively recognized by CD8+ and CD4+ T-cells from asymptomatic COVID-19 patients irrespective of VOC infection. The safety, immunogenicity, and cross-protective immunity of this pan-Coronavirus vaccine were studied against six VOCs using an innovative triple transgenic h-ACE-2-HLA-A2/DR mouse model.\n\nResultsThe Pan-Coronavirus vaccine: (i) is safe; (ii) induces high frequencies of lung-resident functional CD8+ and CD4+ TEM and TRM cells; and (iii) provides robust protection against virus replication and COVID-19-related lung pathology and death caused by six SARS-CoV-2 VOCs: Alpha (B.1.1.7), Beta (B.1.351), Gamma or P1 (B.1.1.28.1), Delta (lineage B.1.617.2) and Omicron (B.1.1.529). Conclusions: A multi-epitope pan-Coronavirus vaccine bearing conserved human B and T cell epitopes from structural and non-structural SARS-CoV-2 antigens induced cross-protective immunity that cleared the virus, and reduced COVID-19-related lung pathology and death caused by multiple SARS-CoV-2 VOCs.", - "rel_num_authors": 18, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.22.540829", + "rel_abs": "The emergence of three distinct highly pathogenic human coronaviruses - SARS-CoV in 2003, MERS-CoV in 2012, and SARS-CoV-2 in 2019 - underlines the need to develop broadly active vaccines against the Merbecovirus and Sarbecovirus betacoronavirus subgenera. While SARS-CoV-2 vaccines are highly protective against severe COVID-19 disease, they do not protect against other sarbecoviruses or merbecoviruses. Here, we vaccinate mice with a trivalent sortase-conjugate nanoparticle (scNP) vaccine containing the SARS-CoV-2, RsSHC014, and MERS-CoV receptor binding domains (RBDs), which elicited live-virus neutralizing antibody responses and broad protection. Specifically, a monovalent SARS-CoV-2 RBD scNP vaccine only protected against sarbecovirus challenge, whereas the trivalent RBD scNP vaccine protected against both merbecovirus and sarbecovirus challenge in highly pathogenic and lethal mouse models. Moreover, the trivalent RBD scNP elicited serum neutralizing antibodies against SARS-CoV, MERS-CoV and SARS-CoV-2 BA.1 live viruses. Our findings show that a trivalent RBD nanoparticle vaccine displaying merbecovirus and sarbecovirus immunogens elicits immunity that broadly protects mice against disease. This study demonstrates proof-of-concept for a single pan-betacoronavirus vaccine to protect against three highly pathogenic human coronaviruses spanning two betacoronavirus subgenera.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Swayam Fnu Prakash", - "author_inst": "University of California Irvine" + "author_name": "David Martinez", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Nisha R Dhanushkodi", - "author_inst": "University of California Irvine" + "author_name": "Alexandra R. Schaefer", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Latifa Zayou", - "author_inst": "University of California Irvine" + "author_name": "Tyler Gavitt", + "author_inst": "Duke University" }, { - "author_name": "Izabela Coimbra Ibraim", - "author_inst": "University of California Irvine," + "author_name": "Michael Mallory", + "author_inst": "The University of North Carolina at Chapel Hill" }, { - "author_name": "Afshana Quadiri", - "author_inst": "University of California Irvine," + "author_name": "Esther Lee", + "author_inst": "Duke University" }, { - "author_name": "Pierre Gregoire Coulon", - "author_inst": "University of California Irvine" + "author_name": "Nicholas Catanzaro", + "author_inst": "The University of North Carolina at Chapel Hill" }, { - "author_name": "Delia F Tifrea", - "author_inst": "University of California Irvine" + "author_name": "Haiyan Chen", + "author_inst": "Duke University" }, { - "author_name": "Berfin Suzler", - "author_inst": "University of California Irvine" + "author_name": "Kendra Gully", + "author_inst": "The University of North Carolina at Chapel Hill" }, { - "author_name": "Mohamed Amin", - "author_inst": "University of California Irvine" + "author_name": "Trevor D. Scobey", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Amruth Chilukuri", - "author_inst": "University of California Irvine" + "author_name": "Pooja Korategere", + "author_inst": "Duke University" }, { - "author_name": "Robert A Edwards", - "author_inst": "University of California Irvine" + "author_name": "Alecia Brown", + "author_inst": "Duke University" }, { - "author_name": "Hawa Vahed", - "author_inst": "University of California Irvine" + "author_name": "Lena Smith", + "author_inst": "Duke University" }, { - "author_name": "Anthony B. Nesburn", - "author_inst": "University of California Irvine Gavin Herbert Eye Institute" + "author_name": "Robert Parks", + "author_inst": "Duke University" }, { - "author_name": "Baruch D Kuppermann", - "author_inst": "University of California Irvine" + "author_name": "Maggie Barr", + "author_inst": "Duke University" }, { - "author_name": "Jeffrey B Ulmer", - "author_inst": "TechImmune, LLC" + "author_name": "Amanda Newman", + "author_inst": "Duke University" }, { - "author_name": "Dan Gil", - "author_inst": "TechImmune, LLC" + "author_name": "Cindy Bowman", + "author_inst": "Duke University" }, { - "author_name": "Trevor M Jones", - "author_inst": "TechImmune, LLC" + "author_name": "John M. Powers", + "author_inst": "The University of North Carolina at Chapel Hill" }, { - "author_name": "Lbachir BenMohamed", - "author_inst": "GHEI/UCI School of Medecine" + "author_name": "Katayoun Mansouri", + "author_inst": "Duke University" + }, + { + "author_name": "Robert J Edwards", + "author_inst": "Duke University" + }, + { + "author_name": "Ralph S. Baric", + "author_inst": "University of North Carolina at Chapel Hill" + }, + { + "author_name": "Barton Haynes", + "author_inst": "Duke University" + }, + { + "author_name": "Kevin O'Neil Saunders", + "author_inst": "Duke Human Vaccine Institute" } ], "version": "1", @@ -56929,63 +56984,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.05.15.540806", - "rel_title": "Defining distinct RNA-protein interactomes of SARS-CoV-2 genomic and subgenomic RNAs", + "rel_doi": "10.1101/2023.05.15.540684", + "rel_title": "Mechanism Underlying the Immune Responses of a Sublingual Vaccine for SARS-CoV-2 with RBD Antigen and Adjuvant, Poly(I:C) or AddaS03, in Non-human Primates", "rel_date": "2023-05-16", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.15.540806", - "rel_abs": "Host RNA binding proteins recognize viral RNA and play key roles in virus replication and antiviral defense mechanisms. SARS-CoV-2 generates a series of tiered subgenomic RNAs (sgRNAs), each encoding distinct viral protein(s) that regulate different aspects of viral replication. Here, for the first time, we demonstrate the successful isolation of SARS-CoV-2 genomic RNA and three distinct sgRNAs (N, S, and ORF8) from a single population of infected cells and characterize their protein interactomes. Over 500 protein interactors (including 260 previously unknown) were identified as associated with one or more target RNA at either of two time points. These included protein interactors unique to a single RNA pool and others present in multiple pools, highlighting our ability to discriminate between distinct viral RNA interactomes despite high sequence similarity. The interactomes indicated viral associations with cell response pathways including regulation of cytoplasmic ribonucleoprotein granules and posttranscriptional gene silencing. We validated the significance of five protein interactors predicted to exhibit antiviral activity (APOBEC3F, TRIM71, PPP1CC, LIN28B, and MSI2) using siRNA knockdowns, with each knockdown yielding increases in viral production. This study describes new technology for studying SARS-CoV-2 and reveals a wealth of new viral RNA-associated host factors of potential functional significance to infection.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.15.540684", + "rel_abs": "A sublingual vaccine formulated with recombinant SARS-CoV-2 spike protein receptor binding domain (RBD) antigen and Poly(I:C)) adjuvant was assessed for its safety in non-human primates. This Poly(I:C)-adjuvanted sublingual vaccine was safe compared to the AddaS03-adjuvanted vaccine in blood tests and plasma CRP. The safety of the vaccine was also confirmed through quantitative reverse transcription PCR of six genes and ELISA of four cytokines associated with inflammation and related reactions. The Poly(I:C)- or AddaS03-adjuvanted sublingual vaccine produced RBD-specific IgA antibodies in nasal washings, saliva, and plasma. SARS-CoV-2 neutralizing antibodies were detected in plasma, suggesting that adjuvanted-sublingual vaccines protect against SARS-CoV-2 infection. \"Yin and Yang\"-like unique transcriptional regulation was observed through DNA microarray analyses of white blood cell RNAs from both vaccines, suppressing and enhancing immune responses and up- or downregulating genes associated with these immune responses. Poly(I:C) adjuvanted sublingual vaccination induced atypical up- or downregulation of genes related to immune suppression or tolerance; Treg differentiation; and T-cell exhaustion. Therefore, Poly(I:C) adjuvant is safe and favorable for sublingual vaccination and can induce a balanced \"Yin/Yang\" -like effect on immune responses.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Isabella T Whitworth", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Rachel Knoener", - "author_inst": "University of Wisconsin - Madison" - }, - { - "author_name": "Maritza Puray Chavez", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Peter Halfmann", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Sofia Romero", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Tetsuro Yamamoto", + "author_inst": "Innovation Research Center, EPS Holdings, Inc" }, { - "author_name": "M'bark Baddouh", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Fusako Mitsunaga", + "author_inst": "Biomedical Institute, NPO Primate Agora" }, { - "author_name": "Mark Scalf", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Kunihiko Wasaki", + "author_inst": "Research Center, EPS Innovative Medicine Co., Ltd" }, { - "author_name": "Yoshihiro Kawaoka", - "author_inst": "Division of Virology, Institute of Medical Science, University of Tokyo" + "author_name": "Atsushi Kotani", + "author_inst": "Research Center, EPS Innovative Medicine Co., Ltd" }, { - "author_name": "Sebla B Kutluay", - "author_inst": "Washington University School of Medicine" + "author_name": "Kazuki Tajima", + "author_inst": "Research Center, EPS Innovative Medicine Co., Ltd" }, { - "author_name": "Lloyd M Smith", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Masanori Tanji", + "author_inst": "EP Mediate Co., LTD" }, { - "author_name": "Nathan M Sherer", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Shin Nakamura", + "author_inst": "Intelligence and Technology Lab" } ], "version": "1", "license": "cc_by_nd", "type": "new results", - "category": "molecular biology" + "category": "immunology" }, { "rel_doi": "10.1101/2023.05.15.540756", @@ -58387,307 +58426,35 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2023.05.08.23289442", - "rel_title": "Cohort Profile: Post-hospitalisation COVID-19 study (PHOSP-COVID)", + "rel_doi": "10.1101/2023.05.09.23289572", + "rel_title": "Living with Long COVID: Implementing a living approach to the NICE guideline on managing the long-term effects of COVID-19", "rel_date": "2023-05-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.08.23289442", - "rel_abs": "O_LIPHOSP-COVID is a national UK multi-centre cohort study of patients who were hospitalised for COVID-19 and subsequently discharged.\nC_LIO_LIPHOSP-COVID was established to investigate the medium- and long-term sequelae of severe COVID-19 requiring hospitalisation, understand the underlying mechanisms of these sequelae, evaluate the medium- and long-term effects of COVID-19 treatments, and to serve as a platform to enable future studies, including clinical trials.\nC_LIO_LIData collected covered a wide range of physical measures, biological samples, and Patient Reported Outcome Measures (PROMs).\nC_LIO_LIParticipants could join the cohort either in Tier 1 only with remote data collection using hospital records, a PROMs app and postal saliva sample for DNA, or in Tier 2 where they were invited to attend two specific research visits for further data collection and biological research sampling. These research visits occurred at five (range 2-7) months and 12 (range 10-14) months post-discharge. Participants could also participate in specific nested studies (Tier 3) at selected sites.\nC_LIO_LIAll participants were asked to consent to further follow-up for 25 years via linkage to their electronic healthcare records and to be re-contacted for further research.\nC_LIO_LIIn total, 7935 participants were recruited from 83 UK sites: 5238 to Tier 1 and 2697 to Tier 2, between August 2020 and March 2022.\nC_LIO_LICohort data are held in a Trusted Research Environment and samples stored in a central biobank. Data and samples can be accessed upon request and subject to approvals.\nC_LI", - "rel_num_authors": 72, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.09.23289572", + "rel_abs": "ObjectivesThe aim of this paper is to describe the development, implementation and evaluation of a flexible living approach to maintaining NICEs long-term effects of COVID-19 (LTE) guideline and monitoring the uncertain evidence base of this condition.\n\nStudy Design and SettingThe NICE COVID-19 team reviewed its practical experiences of establishing a living approach to developing and maintaining the LTE guideline, including initial development, maintenance and eventual transition to a lower intensity model. The methods and processes were described narratively over the first 2 years of the guidelines lifespan. This was combined with quantitative data on emerging and cumulative evidence over the period to chart the evidence landscape.\n\nResultsFollowing publication, the initial timepoint-based update process evolved into a flexible living approach with remote topic expert engagement.\n\nExperts engaged with the new process with a 64% response rate to the online surveys.\n\nEmerging evidence increased rapidly following publication [11,405 studies assessed in 2021 and 13,181 in 2022] and was captured by continuous surveillance. There were no urgent triggers for updating from the studies identified in 2022 via the living approach, saving considerable resources over the timepoint based approach which would commit resources to planning and convening expert panel meetings.\n\nA total of 184 studies with a potential future impact were summarised to capture the cumulative evidence base. Experts highlighted ongoing research and implementation issues which have further informed surveillance of the guideline.\n\nAfter a sustained period without triggers for updating, the living approach was restricted to the highest priority areas with surveillance of ongoing studies.\n\nConclusionThis paper illustrates a flexible living approach taken to a novel condition with an evolving evidence landscape. Currency of some living guidelines can be maintained without the need for frequent updating.\n\nHighlights: What is new?O_LIIn an unpredictable pandemic context, novel conditions with uncertain aetiology, diagnosis, management and prognosis demand a flexible living approach to surveillance of initial recommendations, even where triggers for updating remain infrequent.\nC_LIO_LIMonitoring cumulative evidence with potential future impact is important for high priority areas lacking a strong evidence base.\nC_LIO_LIIn guidelines with previous scheduled updates, transition to a more reactive trigger-based approach can be both more efficient and productive, while maintaining currency of recommendations through continuous surveillance.\nC_LIO_LIDetermining when to transition between living and standard approaches to maintaining a guideline is dependent on multiple factors, including intelligence from the health and social care system, ongoing research and government policy.\nC_LI\n\nUse of NICE COVID-19 content internationallyOur COVID-19 rapid guidelines and evidence summaries are exempt from our overseas reuse application, licence and fee. This means you can:\n\nO_LIadopt the guidelines for your own healthcare setting\nC_LIO_LIadapt the guidelines by combining them with your own local content\nC_LIO_LItranslate the resultant outputs.\nC_LI\n\nWhen using content from our COVID-19 rapid guidelines and evidence summaries you must:\n\nO_LImake all your outputs reusing NICE content freely available to others\nC_LIO_LIacknowledge the use of NICE content, and link to the source content on our website\nC_LIO_LIonly use the NICE logo if the original NICE guidance publication is used in its entirety without including additional content\nC_LIO_LItell us how our content has been used by emailing reuseofcontent@nice.org.uk, to support the evaluation and development of our guidance.\nC_LI\n\nWe cannot accept responsibility or liability for the use of our content in third party outputs.\n\nFurther information on reuse of content is available on the NICE website.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Omer Elneima", - "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK" - }, - { - "author_name": "Hamish J C McAuley", - "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK" - }, - { - "author_name": "Olivia C Leavy", - "author_inst": "Department of Population Health Sciences, University of Leicester, Leicester, UK" - }, - { - "author_name": "James D Chalmers", - "author_inst": "University of Dundee, Ninewells Hospital and Medical School, Dundee, UK" - }, - { - "author_name": "Alex Horsley", - "author_inst": "Division of Infection, Immunity & Respiratory Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK" - }, - { - "author_name": "Ling-Pei Ho", - "author_inst": "MRC Human Immunology Unit, University of Oxford, Oxford, UK" - }, - { - "author_name": "Michael Marks", - "author_inst": "Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK" - }, - { - "author_name": "Krisnah Poinasamy", - "author_inst": "Asthma and Lung UK, London, UK" - }, - { - "author_name": "Betty Raman", - "author_inst": "Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK" - }, - { - "author_name": "Aarti Shikotra", - "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK" - }, - { - "author_name": "Amisha Singapuri", - "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK" - }, - { - "author_name": "Marco Sereno", - "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK" - }, - { - "author_name": "Victoria C Harris", - "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK" - }, - { - "author_name": "Linzy Houchen-Wolloff", - "author_inst": "Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre- Respiratory, University of Leicester, Leicester, UK" - }, - { - "author_name": "Ruth M Saunders", - "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK" - }, - { - "author_name": "Neil J Greening", - "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK" - }, - { - "author_name": "Matthew Richardson", - "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK" - }, - { - "author_name": "Jennifer K Quint", - "author_inst": "National Heart and Lung Institute, Imperial College London, London, UK" - }, - { - "author_name": "Andrew Briggs", - "author_inst": "London School of Hygiene & Tropical Medicine, London, UK" - }, - { - "author_name": "Annemarie B Docherty", - "author_inst": "Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK" - }, - { - "author_name": "Steven Kerr", - "author_inst": "The Roslin Institute, University of Edinburgh, Edinburgh, UK" - }, - { - "author_name": "Ewen M Harrison", - "author_inst": "Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK" - }, - { - "author_name": "Nazir I Lone", - "author_inst": "Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK" - }, - { - "author_name": "Mathew Thorpe", - "author_inst": "Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK" - }, - { - "author_name": "Liam G Heaney", - "author_inst": "Wellcome-Wolfson Institute for Experimental Medicine, Queens University Belfast, Belfast, UK" - }, - { - "author_name": "Keir E Lewis", - "author_inst": "Hywel Dda University Health Board, Wales, UK" - }, - { - "author_name": "Raminder Aul", - "author_inst": "St George's University Hospitals NHS Foundation Trust, London, UK" - }, - { - "author_name": "Paul Beirne", - "author_inst": "Leeds Teaching Hospitals NHS Trust, Leeds, UK" - }, - { - "author_name": "Charlotte E Bolton", - "author_inst": "NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK" - }, - { - "author_name": "Jeremy S Brown", - "author_inst": "UCL Respiratory, Department of Medicine, University College London, London, UK" - }, - { - "author_name": "Gourab Choudhury", - "author_inst": "Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK" - }, - { - "author_name": "Nawar Diar Bakerly", - "author_inst": "Salford Royal NHS Foundation Trust, Manchester, UK" - }, - { - "author_name": "Nicholas Easom", - "author_inst": "Infection Research Group, Hull University Teaching Hospitals, Hull, UK" - }, - { - "author_name": "Carlos Echevarria", - "author_inst": "Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, UK" - }, - { - "author_name": "Jonathan Fuld", - "author_inst": "Department of Respiratory Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK" - }, - { - "author_name": "Nick Hart", - "author_inst": "Lane Fox Respiratory Unit, Guy's and St Thomas' NHS Foundation Trust, London, UK" - }, - { - "author_name": "John R Hurst", - "author_inst": "Royal Free London NHS Foundation Trust, London, UK" - }, - { - "author_name": "Mark G Jones", - "author_inst": "Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK" - }, - { - "author_name": "Dhruv Parekh", - "author_inst": "Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Paul E Pfeffer", - "author_inst": "Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK" - }, - { - "author_name": "Najib M Rahman", - "author_inst": "NIHR Oxford Biomedical Research Centre, Oxford, UK" - }, - { - "author_name": "Sarah L Rowland-Jones", - "author_inst": "University of Sheffield, Sheffield, UK" - }, - { - "author_name": "AA Roger Thompson", - "author_inst": "University of Sheffield, Sheffield, UK" - }, - { - "author_name": "Caroline Jolley", - "author_inst": "Centre for Human & Applied Physiological Sciences, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK" - }, - { - "author_name": "Ajay M Shah", - "author_inst": "King's College London British Heart Foundation Centre, London, UK" - }, - { - "author_name": "Dan G Wootton", - "author_inst": "NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool, UK" - }, - { - "author_name": "Trudie Chalder", - "author_inst": "Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK" - }, - { - "author_name": "Melanie J Davies", - "author_inst": "NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK" - }, - { - "author_name": "Anthony De Soyza", - "author_inst": "Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK" - }, - { - "author_name": "John R Geddes", - "author_inst": "NIHR Oxford Health Biomedical Research Centre, University of Oxford, Oxford, UK" - }, - { - "author_name": "William Greenhalf", - "author_inst": "The CRUK Liverpool Experimental Cancer Medicine Centre, Liverpool, UK" - }, - { - "author_name": "Simon Heller", - "author_inst": "Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK" - }, - { - "author_name": "Luke S Howard", - "author_inst": "Imperial College Healthcare NHS Trust, London, UK" - }, - { - "author_name": "Joseph Jacob", - "author_inst": "Centre for Medical Image Computing, University College London, London, UK" - }, - { - "author_name": "R Gisli Jenkins", - "author_inst": "National Heart and Lung Institute, Imperial College London, London, UK" - }, - { - "author_name": "Janet M Lord", - "author_inst": "MRC-Versus Arthritis Centre for Musculoskeletal Ageing Research, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "William D-C Man", - "author_inst": "Royal Brompton & Harefield Hospitals, Guy's and St. Thomas' NHS Foundation Trust, London, UK" - }, - { - "author_name": "Gerry P McCann", - "author_inst": "Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester" - }, - { - "author_name": "Stefan Neubauer", - "author_inst": "NIHR Oxford Biomedical Research Centre, Oxford, UK" - }, - { - "author_name": "Peter JM Openshaw", - "author_inst": "National Heart and Lung Institute, Imperial College London, London, UK" - }, - { - "author_name": "Joanna C Porter", - "author_inst": "UCL Respiratory, Department of Medicine, University College London, London, UK" - }, - { - "author_name": "Matthew J Rowland", - "author_inst": "Kadoorie Centre for Critical Care Research, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK" - }, - { - "author_name": "Janet T Scott", - "author_inst": "MRC-University of Glasgow Center for Virus research" - }, - { - "author_name": "Malcolm G Semple", - "author_inst": "NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool, UK" - }, - { - "author_name": "Sally J Singh", - "author_inst": "Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK" - }, - { - "author_name": "David C Thomas", - "author_inst": "Department of Immunology and Inflammation, Imperial College London, London, UK" - }, - { - "author_name": "Mark Toshner", - "author_inst": "NIHR Cambridge Biomedical Research Centre, Cambridge, United Kingdom" - }, - { - "author_name": "Aziz Sheikh", - "author_inst": "Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK" - }, - { - "author_name": "Chris E Brightling", - "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK" + "author_name": "Steve Sharp", + "author_inst": "National Institute For Health and Care Excellence" }, { - "author_name": "Louise v Wain", - "author_inst": "Department of Population Health Sciences, University of Leicester, Leicester, UK" + "author_name": "Sarah Boyce", + "author_inst": "National Institute for Health and Care Excellence" }, { - "author_name": "Rachael A Evans", - "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK" + "author_name": "Justine Karpusheff", + "author_inst": "The Health Foundation" }, { - "author_name": "- on behalf of the PHOSP-COVID Collaborative Group", - "author_inst": "" + "author_name": "Fiona Glen", + "author_inst": "National Institute for Health and Care Excellence" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "public and global health" }, { "rel_doi": "10.1101/2023.05.09.540089", @@ -60265,43 +60032,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.05.04.539453", - "rel_title": "An inimitable proprotein convertase subtilisin kexin-9 (PCSK9) cleavage site VFAQ on Spike protein along with furin cleavage site makes SARS-CoV-2 unique", + "rel_doi": "10.1101/2023.05.04.539462", + "rel_title": "Paired associated SARS-CoV-2 spike variable positions: a network analysis approach to emerging variants", "rel_date": "2023-05-05", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.04.539453", - "rel_abs": "A novel coronavirus (2019-nCoV) or Severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) that affects humans has been discovered in Wuhan, China, in 2019. Its genome has been sequenced, and the genetic data was quickly made public. We discovered a novel proprotein convertase subtilisin kexin-9 (PCSK9) cleavage site in the Spike protein of the 2019-nCoV. The recent research also demonstrates that the previously found proprotein convertase 3 (PC3) or furin cleavage site, which was assumed to be unique, is already present in animal corona viruses. In this article, we suggest that the combination of the both proprotein convertase PC3 cleavage site and the PCSK9 site renders SARS-CoV-2 unique in terms of the pathogenicity, potential functional effects, and implications for the development of antiviral drugs.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.04.539462", + "rel_abs": "Amino acids in variable positions of proteins may be correlated, with potential structural and functional implications. Here, we apply exact tests of independence in R x C contingency tables to examine noise-free associations between variable positions of the SARS-CoV-2 spike protein, using as a paradigm sequences from Greece deposited in GISAID (N=6,683/1,078 full-length) for the period February 29, 2020 to April 26, 2021 that essentially covers the first three pandemic waves. We examine the fate and complexity of these associations by network analysis, using associated positions (exact p[≤]0.001 and Average Product Correction [≥]2) as links and the corresponding positions as nodes . We found a temporal linear increase of positional differences and a gradual expansion of the number of position associations over time, represented by a temporally evolving intricate web, resulting in a non-random complex network of 69 nodes and 252 links. Overconnected nodes corresponded to the most adapted variant positions in the population, suggesting a direct relation between network degree and position functional importance. Modular analysis revealed 25 k-cliques comprising three to 11 nodes. At different k- clique resolutions, one to four communities were formed, capturing epistatic associations of circulating variants (Alpha, Beta, B.1.1.318), but also Delta, which dominated the evolutionary landscape later in the pandemic. Cliques of aminoacidic positional associations tended to occur in single sequences, enabling the recognition of epistatic positions in real-world virus populations. Our findings provide a novel way of understanding epistatic relationships in viral proteins with potential applications in the design of virus control procedures.\n\nImportancePaired positional associations of adapted amino acids in virus proteins may provide new insights for understanding virus evolution and variant formation. We investigated potential intramolecular relationships between variable SARS-CoV-2 spike positions by exact tests of independence in R x C contingency tables, having applied Average Product Correction (APC) to eliminate background noise. Associated positions (exact p[≤]0.001 and APC[≥]2) formed a non- random, epistatic network of 25 cliques and 1-4 communities at different clique resolutions, revealing evolutionary ties between variable positions of circulating variants, and a predictive potential of previously unknown network positions. Cliques of different sizes represented theoretical combinations of changing residues in sequence space, allowing the identification of significant aminoacidic combinations in single sequences of real-world populations. Our analytic approach that links network structural aspects to mutational aminoacidic combinations in the spike sequence population offers a novel way to understand virus epidemiology and evolution.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Medha D Pandya", - "author_inst": "Department of Life Sciences, Maharaja Krishnakumarsinhji Bhavnagar University, Bhavnagar, Gujarat, India." - }, - { - "author_name": "Dhruvam Shukla", - "author_inst": "School of System Biology, George Mason University Manassas Virginia USA 20110" - }, - { - "author_name": "Sejal Shah", - "author_inst": "Department of Bioinformatics, Faculty of technology, Marwadi University, Rajkot, Gujarat, India" + "author_name": "Yiannis Manoussopoulos", + "author_inst": "Medical School, National and Kapodistrian University of Athens" }, { - "author_name": "Kajari Das", - "author_inst": "Department of Biotechnology, College of Basic Science and Humanities, Odisha University of Agriculture and Technology.Bhubaneswar-3, Odisha, India" + "author_name": "Cleo Anastassopoulou", + "author_inst": "Medical School, National and Kapodistrian University of Athens" }, { - "author_name": "Sushma Dave", - "author_inst": "Department of Applied Sciences, JIET Jodhpur, Rajasthan, India" + "author_name": "John Ioannidis", + "author_inst": "Stanford University" }, { - "author_name": "Jayashankar Das", - "author_inst": "Valnizen Healthcare, Vile Parle, West, Mumbai, 400056, Maharashtra, India" + "author_name": "Athanasios Tsakris", + "author_inst": "Medical School, National and Kapodistrian University of Athens" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", - "category": "evolutionary biology" + "category": "microbiology" }, { "rel_doi": "10.1101/2023.05.05.23289503", @@ -62239,13 +61998,13 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2023.05.02.539082", - "rel_title": "Discovery and characterization of highly potent and selective covalent inhibitors of SARS-CoV-2 PLpro", + "rel_doi": "10.1101/2023.05.01.538955", + "rel_title": "Diverging maternal and infant cord antibody functions from SARS-CoV-2 infection and vaccination in pregnancy", "rel_date": "2023-05-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.02.539082", - "rel_abs": "Coronavirus infections, such as the global COVID-19 pandemic, have had a profound impact on many aspects of our daily life including working style, economy, and the healthcare system. To prevent the rapid viral transmission and speed up recovery from the infection, many academic organizations and industry research labs have conducted extensive research on discovering new therapeutic options for SARS-CoV-2. Among those efforts, RNA-dependent RNA polymerase (RdRp) inhibitors such as Remdesivir, Molnupiravir and 3CLpro inhibitor such as Nirmatrelvir (Paxlovid) have been widely used as the therapeutic options. Given the recent emergence of several new variants that caused a resurgence of the virus, it would be beneficial to discover more diverse therapeutic options with novel anti-viral mechanisms. In this regard, PLpro has been highlighted since it, along with 3CLpro, is one of the two most important proteases that are required for SARS-CoV-2 viral processing. While 3CLpro inhibitors were extensively investigated in the light of Emergency Use Authorizations of Nirmatrelvir, PLpro inhibitors have not been thoroughly investigated even preclinically. Thus, discovery efforts on antivirals acting against PLpro will be valuable. PLpro inhibitors may exert their activity by inhibiting viral replication and enhancing the host defense system through blocking virus-induced cell signaling events for evading host immune response. In this study, we report the discovery and development of two covalent irreversible PLpro inhibitors, HUP0109 and its deuterated analog DX-027, out of our quest for novel anti-COVID 19 therapeutic agents for the past two and half years. HUP0109 selectively targets the viral catalytic cleft of PLpro and covalently modifies its active site cysteine residue (C111). Promising results from preclinical evaluation suggest that DX-027 can be developed as a potential COVID-19 treatment.", - "rel_num_authors": 16, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.01.538955", + "rel_abs": "Immunization in pregnancy is a critical tool that can be leveraged to protect the infant with an immature immune system but how vaccine-induced antibodies transfer to the placenta and protect the maternal-fetal dyad remains unclear. Here, we compare matched maternal-infant cord blood from individuals who in pregnancy received mRNA COVID-19 vaccine, were infected by SARS-CoV-2, or had the combination of these two immune exposures. We find that some but not all antibody neutralizing activities and Fc effector functions are enriched with vaccination compared to infection. Preferential transport to the fetus of Fc functions and not neutralization is observed. Immunization compared to infection enriches IgG1-mediated antibody functions with changes in antibody post-translational sialylation and fucosylation that impact fetal more than maternal antibody functional potency. Thus, vaccine enhanced antibody functional magnitude, potency and breadth in the fetus are driven more by antibody glycosylation and Fc effector functions compared to maternal responses, highlighting prenatal opportunities to safeguard newborns as SARS-CoV-2 becomes endemic.\n\nOne Sentence SummarySARS-CoV-2 vaccination in pregnancy induces diverging maternal and infant cord antibody functions", + "rel_num_authors": 10, "rel_authors": [ { "author_name": "", @@ -62283,39 +62042,15 @@ "author_name": "", "author_inst": "" }, - { - "author_name": "", - "author_inst": "" - }, - { - "author_name": "", - "author_inst": "" - }, - { - "author_name": "", - "author_inst": "" - }, - { - "author_name": "", - "author_inst": "" - }, - { - "author_name": "", - "author_inst": "" - }, - { - "author_name": "", - "author_inst": "" - }, { "author_name": "", "author_inst": "" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "pharmacology and toxicology" + "category": "immunology" }, { "rel_doi": "10.1101/2023.05.01.23289307", @@ -64641,39 +64376,139 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2023.04.25.23289035", - "rel_title": "The impact of long-term conditions and comorbidity patterns on COVID-19 infection and hospitalisation: a cohort study", + "rel_doi": "10.1101/2023.04.25.23288937", + "rel_title": "Potential biomarkers for fatal outcome prognosis in a cohort of hospitalized COVID-19 patients with pre-existing co-morbidities", "rel_date": "2023-04-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.25.23289035", - "rel_abs": "IntroductionOlder adults are usually more vulnerable to COVID-19 infections; however, little is known about which comorbidity patterns are related to a higher probability of COVID-19 infection. This study investigated the role of long-term conditions or comorbidity patterns on COVID-19 infection and related hospitalisations.\n\nMethodsThis study included 4,428 individuals from Waves 8 (2016-2017) and 9 (2018-2019) of the English Longitudinal Study of Ageing (ELSA), who also participated in the ELSA COVID-19 Substudy in 2020. Comorbidity patterns of chronic conditions were identified using an agglomerative hierarchical clustering method. The relationships between comorbidity patterns or long-term conditions and COVID-19 related outcomes were examined using multivariable logistic regression.\n\nResultsAmong a representative sample of community-dwelling older adults in England, those with cardiovascular disease (CVD) and complex comorbidities had an almost double risk of COVID-19 infection (OR=1.87, 95% CI=1.42-2.46) but not of COVID-19 related hospitalisation. A similar pattern was observed for the heterogeneous comorbidities cluster (OR=1.56, 95% CI=1.24-1.96). The individual investigations of long-term conditions with COVID-19 infection highlighted primary associations with CVD (OR=1.46, 95% CI=1.23-1.74), lung diseases (OR=1.40, 95% CI=1.17-1.69), psychiatric conditions (OR=1.40, 95% CI=1.16-1.68), retinopathy/eye diseases (OR=1.39, 95% CI=1.18-1.64), and arthritis (OR=1.27, 95% CI=1.09-1.48). In contrast, metabolic disorders and diagnosed diabetes were not associated with any COVID-19 outcomes.\n\nDiscussion/ConclusionThis study provides novel insights into the comorbidity patterns that are more vulnerable to COVID-19 infections and highlights the importance of CVD and complex comorbidities.\n\nThese findings facilitate crucial new evidence for appropriate screening measures and tailored interventions for older adults in the ongoing global outbreak.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.25.23288937", + "rel_abs": "BackgroundThe difficulty to predict fatal outcomes in COVID-19 patients, impacts in the general morbidity and mortality due to SARSCoV2 infection, as it wears out the hospital services that care for these patients. Unfortunately, in several of the candidates for prognostic biomarkers proposed, the predictive power is compromised when patients have pre-existing co-morbidities.\n\nMethodsA cohort of one hundred and forty-seven patients hospitalized for severe COVID19 was included in a descriptive, observational, single-center, and prospective study. Patients were recruited during the first COVID-19 pandemic wave (April-Nov, 2020). Data were collected from the clinical history while immunophenotyping by multiparameter flow cytometry analysis allowed us to assess the expression of surface markers on peripheral leukocytes. Patients were grouped according to the outcome in survivor or decease. The prognostic value of leukocytes, cytokines or HLA-DR, CD39, and CD73 was calculated.\n\nResultsHypertension and chronic renal failure but not obesity and diabetes were conditions more frequent among the decease group. Mixed hypercitokinemia, including inflammatory (IL-6) and anti-inflammatory (IL-10) cytokines, was more evident in deceased patients. In the decease group, lymphopenia with a higher NLR value was present. HLA-DR expression and the percentage of CD39+ cells were higher than non COVID-19 patients, but remain similar despite outcome. ROC analysis and cut-off value of NLR (69.6%, 9.4), pNLR (71.1%, 13.6), IL-6 (79.7%, 135.2 pg/mL).\n\nConclusionThe expression of HLA-DR, CD39, and CD73, as many serum cytokines (other than IL-6) and chemokines levels do not show prognostic potential compared to NLR and pNLR values.", + "rel_num_authors": 30, "rel_authors": [ { - "author_name": "Yun-Ting (Joyce) Huang", - "author_inst": "University of Manchester" + "author_name": "Ruth Lizzeth Madera-Sandoval", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS)." }, { - "author_name": "Andrew Steptoe", - "author_inst": "UCL: University College London" + "author_name": "Arturo Cerbulo-Vazquez Sr.", + "author_inst": "UNAM" }, { - "author_name": "Riyaz Patel", - "author_inst": "UCL" + "author_name": "Lourdes Andrea Arriaga-Pizano", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS)." }, { - "author_name": "Esme Fuller-Thomson", - "author_inst": "University of Toronto" + "author_name": "Graciela Libier Cabrera-Rivera", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS)." }, { - "author_name": "Dorina Cadar", - "author_inst": "Brighton and Sussex Medical School" + "author_name": "Edna Basilio-Galveza", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS)." + }, + { + "author_name": "Patricia Esther Miranda-Cruz", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS)." + }, + { + "author_name": "Maria Teresa Garcia de la Rosa", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS)." + }, + { + "author_name": "Jessica Lashkmin Prieto-Chavez", + "author_inst": "Centro de intrumentos. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS). Ciudad de Mexico, Mexico" + }, + { + "author_name": "Silvia Vanessa Rivero-Arredondo", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS)." + }, + { + "author_name": "Alonso Cruz-Cruz", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS)." + }, + { + "author_name": "Daniela Rodriguez-Hernandez", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS)." + }, + { + "author_name": "Maria Eugenia Salazar-Rios", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS)." + }, + { + "author_name": "Enrique Salazar-Rios", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS)." + }, + { + "author_name": "Esli David Serrano-Molina", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS)." + }, + { + "author_name": "Roberto Carlos De Lira-Barraza", + "author_inst": "Medicina Interna. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS). Ciudad de Mexico, Mexico" + }, + { + "author_name": "Abel Humberto Villanueva-Compean", + "author_inst": "Medicina Interna. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS). Ciudad de Mexico, Mexico" + }, + { + "author_name": "Alejandra Esquivel-Pineda", + "author_inst": "Medicina Interna. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS). Ciudad de Mexico, Mexico" + }, + { + "author_name": "Ruben Ramirez-Montes de Oca", + "author_inst": "Medicina Interna. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS). Ciudad de Mexico, Mexico" + }, + { + "author_name": "Omar Unzueta-Marta", + "author_inst": "Medicina Interna. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS). Ciudad de Mexico, Mexico" + }, + { + "author_name": "Guillermo Flores-Padilla", + "author_inst": "Medicina Interna. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS). Ciudad de Mexico, Mexico" + }, + { + "author_name": "Juan Carlos Anda-Garay", + "author_inst": "Medicina Interna. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS). Ciudad de Mexico, Mexico" + }, + { + "author_name": "Luis Alejandro Sanchez-Hurtado", + "author_inst": "Unidad de Cuidados Intensivos. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS). Ciudad de Mexico," + }, + { + "author_name": "Salvador Calleja-Alarcon", + "author_inst": "Unidad de Cuidados Intensivos. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS). Ciudad de Mexico," + }, + { + "author_name": "Laura Romero-Gutierrez", + "author_inst": "Unidad de Cuidados Intensivos. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS). Ciudad de Mexico," + }, + { + "author_name": "Rafael Torres-Rosas", + "author_inst": "Laboratorio de Inmunologia, Centro de Estudios en Ciencias de la Salud y la Enfermedad, Facultad de Odontologia, Universidad Autonoma Benito Juarez de Oaxaca (U" + }, + { + "author_name": "Laura C Bonifaz", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS)." + }, + { + "author_name": "Rosana Pelayo", + "author_inst": "Coordinacion de Investigacion en Salud, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Ciudad de Mexico, 06720, Mexico." + }, + { + "author_name": "Edna Marquez-Marquez", + "author_inst": "Servicio de Medicina Genomica, Hospital General de Mexico. Ciudad de Mexico, Mexico" + }, + { + "author_name": "Constantino III Roberto Lopez-Macias", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica. UMAE Hospital de Especialidades, Centro Medico Nacional Siglo XXI. Instituto Mexicano del Seguro Social (IMSS)." + }, + { + "author_name": "Eduardo Ferat-Osorio", + "author_inst": "Coordinacion de Investigacion en Salud, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Ciudad de Mexico, 06720, Mexico." } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.04.25.538294", @@ -66603,49 +66438,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.04.17.23288622", - "rel_title": "Racial disparities, environmental exposures, and SARS-CoV-2 infection rates: A racial map study in the USA", - "rel_date": "2023-04-24", + "rel_doi": "10.1101/2023.04.21.23288878", + "rel_title": "COVID-19 Prevalence and Trends Among Pregnant and Postpartum Individuals in Maine by Rurality and Pregnancy Conditions", + "rel_date": "2023-04-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.17.23288622", - "rel_abs": "Since the onset of the COVID-19 pandemic, researchers mainly examined how socio-economic, demographic, and environmental factors are related to disparities in SARS-CoV-2 infection rates. However, we dont know the extent to which racial disparities in environmental exposure are related to racial disparities in SARS-CoV-2 infection rates. To address this critical issue, we gathered black vs. white infection records from 1416 counties in the contiguous United States. For these counties, we used 30m-spatial resolution land cover data and racial mappings to quantify the racial disparity between black and white peoples two types of environmental exposure, including exposures to various types of landscape settings and urban development intensities. We found that racial disparities in SARS-CoV-2 infection rates and racial disparities in exposure to various types of landscapes and urban development intensities were significant and showed similar patterns. Specifically, less racial disparity in exposure to forests outside park, pasture/hay, and urban areas with low and medium development intensities were significantly associated with lower racial disparities in SARS-CoV-2 infection rates. Distance was also critical. The positive association between racial disparities in environmental exposures and racial disparity in SARS-CoV-2 infection rates was strongest within a comfortable walking distance (approximately 400m).\n\nHighlightsO_LIRacial dot map and landcover map were used for population-weighted analysis.\nC_LIO_LIRacial disparity in environmental exposures and SARS-CoV-2 infection were linked.\nC_LIO_LIForests outside park are the most beneficial landscape settings.\nC_LIO_LIUrban areas with low development intensity are the most beneficial urban areas.\nC_LIO_LILandscape and urban exposures within the 400m buffer distances are most beneficial.\nC_LI", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.21.23288878", + "rel_abs": "ObjectiveTo estimate COVID-19 diagnosis prevalence and trends among pregnant and postpartum individuals in Maine by rurality and common pregnancy conditions.\n\nMethodsWe used the Maine Health Data Organizations All Payer Claims Data to identify deliveries during 2020-2021. We identified COVID-19 during pregnancy (Apr 2020 to Dec 2021 deliveries) and during the first 6 months postpartum (Apr 2020 to Jun 2021 deliveries) using the ICD-10 diagnosis code U071 on medical claims. We used Joinpoint regression software to model trends. We stratified the analysis by rurality of residence (based on ZIP code) and by common pregnancy conditions: gestational diabetes (GDM), hypertensive disorders of pregnancy (HDP), and prenatal depression.\n\nResultsWe included 13,457 deliveries in our pregnancy and 9,143 deliveries in our postpartum analysis. COVID-19 diagnosis prevalence among pregnant individuals increased from 0.5% in Apr 2020 to 10.5% in Dec 2021 (Oct 2020 was the start of slope [0.43 per month], p<.01). COVID-19 diagnosis prevalence postpartum increased from 0.9% in Apr 2020 to 3.2% in June 2021 deliveries (slope=0.12 per month, p<.01). Trends in prevalence of COVID-19 diagnosis among pregnant individuals living in urban areas were distinct from those living in rural areas (p=.02), with a steeper slope during the first months of the pandemic in urban areas, followed by a later increase among rural residents. Trends among postpartum individuals living in urban areas were distinct from those living in rural areas (p=.03), with a steeper slope for rural residents over the course of the pandemic. Trends in persons with prenatal depression showed a steeper increase in COVID-19 diagnosis prevalence in pregnancy after Dec 2020 (p<.01) and postpartum overall (p<.01) compared to those without prenatal depression. Individuals without GDM and individuals without HDP had steeper increases in COVID-19 diagnosis prevalence in postpartum compared to those without GDM (p<.01) and those without HDP (p=.03).\n\nConclusionCOVID-19 diagnosis among pregnant and postpartum individuals in Maine showed distinct patterns by rurality of residence and select pregnancy conditions. This information can be used for assessing the impact of the COVID-19 pandemic on maternal and infant health.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Wenyan Xu", - "author_inst": "The University of Hong Kong" - }, - { - "author_name": "Bin Jiang", - "author_inst": "The University of Hong Kong" - }, - { - "author_name": "Chris Webster", - "author_inst": "The University of Hong Kong" - }, - { - "author_name": "William C. Sullivan", - "author_inst": "University of lllinois Urbana-Champaign" + "author_name": "Charlie O. Grantham", + "author_inst": "Muskie School of Public Service, University of Southern Maine, Portland, ME" }, { - "author_name": "Yi Lu", - "author_inst": "City University of Hong Kong" + "author_name": "Christina M. Ackerman-Banks", + "author_inst": "Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX" }, { - "author_name": "Na Chen", - "author_inst": "Hunan University" + "author_name": "Heather S. Lipkind", + "author_inst": "Department of Obstetrics and Gynecology, Weill Cornell Medical College, New York City, NY" }, { - "author_name": "Zhaowu Yu", - "author_inst": "Fudan University" + "author_name": "Kristin Palmsten", + "author_inst": "Pregnancy and Child Health Research Center, Health Partners Institute, Minneapolis, MN" }, { - "author_name": "Bin Chen", - "author_inst": "The University of Hong Kong" + "author_name": "Katherine A. Ahrens", + "author_inst": "Muskie School of Public Service, University of Southern Maine, Portland, ME" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -68897,57 +68720,65 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2023.04.12.23288500", - "rel_title": "Long-term effects of extreme smoke exposure on COVID-19: A cohort study", + "rel_doi": "10.1101/2023.04.13.23288481", + "rel_title": "Ethnic inequalities among NHS staff in England - workplace experiences during the COVID-19 pandemic", "rel_date": "2023-04-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.12.23288500", - "rel_abs": "In early 2014, the Hazelwood coalmine fire covered the regional Australian town of Morwell in smoke and ash for 45 days. One of the fires by-products, PM2.5, has been linked higher rates of COVID-19 infection to increased expression of the ACE2 receptor, which the COVID-19 virus uses to infect cells throughout the body. However, it is unclear whether the effect persists for years after exposure. In this study, we surveyed a cohort established prior to the pandemic to determine whether PM2.5 from the coalmine fire increased long-term vulnerability to COVID-19 infection and severe disease.\n\nIn late 2022, 612 members of the Hazelwood Health Studys adult cohort, established in 2016/17, participated in a follow-up survey including standardised items to capture COVID-19 infections, hospitalisations, and vaccinations. Associations were evaluated in crude and adjusted logistic regression models, applying statistical weighting for survey response and multiple imputation to account for missing data, with sensitivity analyses to test the robustness of results.\n\nA total of 271 (44%) participants self-reported or met symptom criteria for at least one COVID-19 infection. All models found a positive association, with odds of infection increasing by between 4-21% for every standard deviation (12.3{micro}g/m3) increase in mine fire-related PM2.5 exposure. However, this was not statistically significant in any model. There were insufficient hospitalisations to examine severity (n=7; 1%).\n\nThe findings were inconclusive in ruling out an effect of PM2.5 exposure from coalmine fire on long-term vulnerability to COVID-19 infection. Given the positive association that was robust to modelling variations as well as evidence for a causal mechanism, it would be prudent to treat PM2.5 from fire events as a risk factor for long-term COVID-19 vulnerability until more evidence accumulates.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.13.23288481", + "rel_abs": "ObjectivesTo determine how workplace experiences of NHS staff varied by ethnic group during the COVID-19 pandemic and examine how these experiences are associated with mental and physical health at the time of the study.\n\nMethodsAn online Inequalities Survey was conducted by the TIDES study (Tackling Inequalities and Discrimination Experiences in health Services) in collaboration with NHS CHECK. This Inequalities Survey collected measures relating to workplace experiences (such as personal protective equipment (PPE), risk assessments, redeployments, and discrimination) as well as mental health, and physical health from NHS staff working in the 18 trusts participating with the NHS CHECK study between February and October 2021 (N=4622).\n\nResultsRegression analysis revealed that staff from Black and Mixed/Other ethnic groups had greater odds of experiencing workplace harassment (adjusted odds ratio (AOR) = 2.43 [1.56-3.78] and 2.38 [1.12-5.07], respectively) and discrimination (AOR = 4.36 [2.73-6.96], and 3.94 [1.67-9.33], respectively) compared to White British staff. Staff from black ethnic groups also had greater odds than White British staff of reporting PPE unavailability (AOR = 2.16 [1.16-4.00]). Such workplace experiences were associated with negative physical and mental health outcomes, though this association varied by ethnicity. Conversely, understanding employment rights around redeployment, being informed about, and having the ability to inform redeployment decisions were associated with lower odds of poor health outcomes.\n\nConclusionsStructural changes to the way staff from ethnically minoritised groups are supported, and how their complaints are addressed by leaders within the NHS are urgently required to address racism and inequalities in the NHS.\n\nPolicy implicationsMaintaining transparency and implementing effective mechanisms for addressing poor working conditions, harassment, and discrimination is crucial in the NHS. This can be achieved through appointing a designated staff member, establishing a tracking system, and training HR managers in identifying and handling reports of racial discrimination. Incorporating diversity and inclusion considerations into professional development activities and providing staff with opportunities to actively participate in decision-making can also benefit their health. The NHS Workforce Race Equality Standard may need to broaden its scope to assess race equality effectively.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Tyler J Lane", - "author_inst": "Monash University" + "author_name": "Rebecca Rhead", + "author_inst": "King's College London Institute of Psychiatry Psychology and Neuroscience" }, { - "author_name": "Matthew Carroll", - "author_inst": "Monash University" + "author_name": "Lisa Harber-Aschan", + "author_inst": "King's College London" }, { - "author_name": "Brigitte Borg", - "author_inst": "The Alfred" + "author_name": "Juliana Onwumere", + "author_inst": "King's College London" }, { - "author_name": "Tracy McCaffrey", - "author_inst": "Monash University" + "author_name": "Catherine Polling", + "author_inst": "King's College London" }, { - "author_name": "Catherine Smith", - "author_inst": "Monash University" + "author_name": "Sarah Dorrington", + "author_inst": "King's College London" }, { - "author_name": "Caroline X Gao", - "author_inst": "Monash University" + "author_name": "Anna Ehsan", + "author_inst": "King's College London" }, { - "author_name": "David Brown", - "author_inst": "Monash University" + "author_name": "Sharon Stevelink", + "author_inst": "King's College London" }, { - "author_name": "David Poland", - "author_inst": "Monash University" + "author_name": "Kamlesh Khunti", + "author_inst": "University of Leicester" }, { - "author_name": "Shantelle Allgood", - "author_inst": "Monash University" + "author_name": "Ghazala Mir", + "author_inst": "University of Leeds" }, { - "author_name": "Jill F Ikin", - "author_inst": "Monash University" + "author_name": "Richard Morriss", + "author_inst": "University of Nottingham" }, { - "author_name": "Michael Abramson", - "author_inst": "Monash University" + "author_name": "Simon Wessely", + "author_inst": "King's College London" + }, + { + "author_name": "Charlotte Woodhead", + "author_inst": "King's College London Institute of Psychiatry Psychology and Neuroscience" + }, + { + "author_name": "Stephani Louise Hatch", + "author_inst": "King's College London Institute of Psychiatry Psychology and Neuroscience" } ], "version": "1", @@ -70583,55 +70414,18 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.04.10.536311", - "rel_title": "Comprehensive analysis of nasal IgA antibodies induced by intranasal administration of the SARS-CoV-2 spike protein", + "rel_doi": "10.1101/2023.04.10.23288360", + "rel_title": "Infants and young children generate more durable antibody responses to SARS-CoV-2 infection than adults", "rel_date": "2023-04-11", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.04.10.536311", - "rel_abs": "Intranasal vaccination is an attractive strategy for preventing COVID-19 disease as it stimulates the production of multimeric secretory immunoglobulin A (IgAs), the predominant antibody isotype in the mucosal immune system, at the target site of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entry. Currently, the evaluation of intranasal vaccine efficacy is based on the measurement of polyclonal antibody titers in nasal lavage fluid. However, how individual multimeric secretory IgA protects the mucosa from SARS-CoV-2 infection remains to be elucidated. To understand the precise contribution and molecular nature of multimeric secretory IgAs induced by intranasal vaccines, we developed 99 monoclonal IgAs from nasal mucosa and 114 monoclonal IgAs or IgGs from nonmucosal tissues of mice that were intranasally immunized with the SARS-CoV-2 spike protein. The nonmucosal IgAs exhibited shared origins and both common and unique somatic mutations with the related nasal IgA clones, indicating that the antigen-specific plasma cells in the nonmucosal tissues originated from B cells stimulated at the nasal mucosa. Comparing the spike protein binding reactivity, angiotensin-converting enzyme-2-blocking and SARS-CoV-2 virus neutralization of monomeric and multimeric IgA pairs recognizing different epitopes showed that even nonneutralizing monomeric IgA, which represents 70% of the nasal IgA repertoire, can protect against SARS-CoV-2 infection when expressed as multimeric secretory IgAs. Our investigation is the first to demonstrate the function of nasal IgAs at the monoclonal level, showing that nasal immunization can provide effective immunity against SARS-CoV-2 by inducing multimeric secretory IgAs at the target site of virus infection.", - "rel_num_authors": 9, - "rel_authors": [ - { - "author_name": "Kentarou Waki", - "author_inst": "University of Toyama" - }, - { - "author_name": "Hideki Tani", - "author_inst": "Toyama Institute of Health" - }, - { - "author_name": "Yumiko Saga", - "author_inst": "Toyama Institute of Health" - }, - { - "author_name": "Takahisa Shimada", - "author_inst": "Toyama institute of Health" - }, - { - "author_name": "Emiko Yamazaki", - "author_inst": "Toyama Institute of Health" - }, - { - "author_name": "Seiichi Koike", - "author_inst": "University of Toyama" - }, - { - "author_name": "Nana Okada", - "author_inst": "University of Toyama" - }, - { - "author_name": "Masaharu Isobe", - "author_inst": "University of Toyama" - }, - { - "author_name": "Nobuyuki Kurosawa", - "author_inst": "University of Toyama" - } - ], + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.10.23288360", + "rel_abs": "Since the emergence of SARS-CoV-2, research has shown that adult patients mount broad and durable immune responses to infection. However, response to infection remains poorly studied in infants/young children. In this study, we evaluated humoral responses to SARS-CoV-2 in 23 infants/young children before and after infection. We found that antibody responses to SARS-CoV-2 spike antigens peaked approximately 30 days after infection and were maintained up to 500 days with little apparent decay. While the magnitude of humoral responses was similar to an adult cohort recovered from mild/moderate COVID-19, both binding and neutralization titers to WT SARS-CoV-2 were more durable in infants/young children, with Spike and RBD IgG antibody half-life nearly 4X as long as in adults. The functional breadth of adult and infant/young children SARS-CoV-2 responses were comparable, with similar reactivity against panel of recent and previously circulating viral variants. Notably, IgG subtype analysis revealed that while IgG1 formed the majority of both adults and infants/young childrens response, IgG3 was more common in adults and IgG2 in infants/young children. These findings raise important questions regarding differential regulation of humoral immunity in infants/young children and adults and could have broad implications for the timing of vaccination and booster strategies in this age group.", + "rel_num_authors": 0, + "rel_authors": null, "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "immunology" + "license": "", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.04.11.23288409", @@ -72629,43 +72423,31 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2023.04.03.535453", - "rel_title": "Chemical-guided SHAPE sequencing (cgSHAPE-seq) informs the binding site of RNA-degrading chimeras targeting SARS-CoV-2 5' untranslated region", + "rel_doi": "10.1101/2023.04.03.535424", + "rel_title": "The Functional RNA Identification (FRID) Pipeline: Identification of Potential Pseudoknot-Containing RNA Elements as Therapeutic Targets for SARS-CoV-2", "rel_date": "2023-04-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.04.03.535453", - "rel_abs": "One of the hallmarks of RNA viruses is highly structured untranslated regions (UTRs) in their genomes. These conserved RNA structures are often essential for viral replication, transcription, or translation. In this report, we discovered and optimized a new coumarin derivative C30 that binds to a four-way RNA helix called SL5 in the 5 UTR of the SARS-CoV-2 RNA genome. To locate the binding site, we developed a novel sequencing-based method namely cgSHAPE-seq, in which the acylating chemical probe was directed to crosslink with the 2-OH groups of ribose at the ligand binding site. This crosslinked RNA could then create read-through mutations during reverse transcription (i.e., primer extension) at single-nucleotide resolution to uncover the acylation locations. cgSHAPE-seq unambiguously determined that a bulged G in SL5 was the primary binding site of C30 in the SARS-CoV-2 5 UTR, which was validated through mutagenesis and in vitro binding experiments. C30 was further used as a warhead in RNA-degrading chimeras (RIBOTACs) to reduce viral RNA expression levels. We demonstrated that replacing the acylating moiety in the cgSHAPE probe with ribonuclease L recruiter (RLR) moieties yielded RNA degraders active in the in vitro RNase L degradation assay and SARS-CoV-2 5 UTR expressing cells. We further explored another RLR conjugation site on the E ring of C30 and discovered potent activity in vitro and in cells. The optimized RIBOTAC C64 inhibited live virus replication in lung epithelial carcinoma cells.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.04.03.535424", + "rel_abs": "The COVID-19 pandemic persists despite the development of effective vaccines. As such, it remains crucial to identify new targets for antiviral therapies. The causative virus of COVID-19, SARS-CoV-2, is a positive-sense RNA virus with RNA structures that could serve as therapeutic targets. One such RNA with established function is the frameshift stimulatory element (FSE), which promotes programmed ribosomal frameshifting. To accelerate identification of additional functional RNA elements, we introduce a novel computational approach termed the Functional RNA Identification (FRID) pipeline. The guiding principle of our pipeline, which uses established component programs as well as customized component programs, is that functional RNA elements have conserved secondary and pseudoknot structures that facilitate function. To assess the presence and conservation of putative functional RNA elements in SARS-CoV-2, we compared over 6,000 SARS-CoV-2 genomic isolates. We identified 22 functional RNA elements from the SARS-CoV-2 genome, 14 of which have conserved pseudoknots and serve as potential targets for small molecule or antisense oligonucleotide therapeutics. The FRID pipeline is general and can be applied to identify pseudoknotted RNAs for targeted therapeutics in genomes or transcriptomes from any virus or organism.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Zhichao Tang", - "author_inst": "University of Kansas, Lawrence" - }, - { - "author_name": "Shalakha Hegde", - "author_inst": "University of Kansas, Lawrence" + "author_name": "Peter C Forstmeier", + "author_inst": "MD/PhD Program, Penn State College of Medicine" }, { - "author_name": "Siyuan Hao", - "author_inst": "University of Kansas Medical Center" + "author_name": "McCauley O Meyer", + "author_inst": "Department of Biochemistry and Molecular Biology, Pennsylvania State University" }, { - "author_name": "Manikandan Selvaraju", - "author_inst": "University of Kansas, Lawrence" - }, - { - "author_name": "Jianming Qiu", - "author_inst": "University of Kansas Medical Center" - }, - { - "author_name": "Jingxin Wang", - "author_inst": "University of Kansas" + "author_name": "Philip C Bevilacqua", + "author_inst": "Department of Chemistry and Department of Biochemistry and Molecular Biology, Pennsylvania State University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "biochemistry" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2023.04.03.23288102", @@ -74499,57 +74281,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.03.31.23288004", - "rel_title": "Covid-19 and post-acute sick leave: a hybrid register and questionnaire study in the adult Danish population", + "rel_doi": "10.1101/2023.03.31.23288018", + "rel_title": "Long-term duration of protection of ancestral-strain monovalent vaccines and effectiveness of the bivalent BA.1 boosters against COVID-19 hospitalisation during a period of BA.5, BQ.1, CH.1.1. and XBB.1.5 circulation in England", "rel_date": "2023-03-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.31.23288004", - "rel_abs": "Long covid follows 10-20% of first-time SARS-CoV-2 infections, but the societal burden of long covid and risk factors for the condition are not well-understood. Here, we report findings about self-reported sick leave and risk factors thereof from a hybrid survey and register study, which included 37,482 RT- PCR confirmed SARS-CoV-2 cases and 51,336 test-negative controls who were tested during the index and alpha waves. An additional 33 individuals per 1000 took substantial sick leave following acute infection compared to persons with no known history of infection, where substantial sick leave was defined as >1 month of sick leave within the period 1-9 months after the RT-PCR test date. Being female, [≥]50 years, and having certain pre-existing conditions such as fibromyalgia increased risks for taking substantial sick leave. Further research exploring this heterogeneity is urgently needed and may provide important evidence for more targeted preventative strategies.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.31.23288018", + "rel_abs": "BackgroundBivalent BA.1 booster vaccines were offered to adults aged 50 years and older and clinically vulnerable individuals as part of the autumn COVID-19 booster vaccination programme 2022 in England.\n\nMethodsA test-negative case-control study was used to estimate the duration of protection of the monovalent vaccines against hospitalisation as compared to those unvaccinated. In addition, the incremental VE of the bivalent BA.1 booster vaccines was estimated relative to those with waned immunity where the last dose was at least 6 months prior amongst those aged 50 years and older.\n\nFindingsThe protection conferred by the monovalent vaccines was well maintained long-term: absolute VE against hospitalisation amongst those aged 65 years and older who had received at least 3 doses plateaued from 6 months after the last dose at around 50%. Incremental VE (in addition to the protection from earlier vaccines) of the bivalent BA.1 boosters against hospitalisation peaked at 53.0% (95% C.I.; 47.9-57.5%) (equivalent to an absolute VE of approximately 75%) before waning to around 35.9% (95% C.I.; 31.4-40.1%) after 10 or more weeks.\n\nInterpretationThis study provides evidence of the long-term duration of protection of the monovalent vaccines, suggesting individuals at lower risk of severe disease who did not receive a booster in autumn 2022 may not require regular re-vaccination. Furthermore, this study finds good evidence that the bivalent BA.1 booster vaccines are highly effective against hospitalisation amongst those aged 50 years and older with the sub-lineages of Omicron present in the autumn/winter of 2022 in England.\n\nFundingNone.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Elisabeth O'Regan", - "author_inst": "Statens Serum Institut" - }, - { - "author_name": "Ingrid Bech Svaalgard", - "author_inst": "Statens Serum Institut" - }, - { - "author_name": "Anna Irene Vedel Soerensen", - "author_inst": "Statens Serum Institut" - }, - { - "author_name": "Lampros Spiliopoulos", - "author_inst": "Statens Serum Institut" - }, - { - "author_name": "Peter Bager", - "author_inst": "Statens Serum Institut" - }, - { - "author_name": "Nete Munk Nielsen", - "author_inst": "Statens Serum Institut" + "author_name": "Freja Kirsebom", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Joergen Vinsloev Hansen", - "author_inst": "Statens Serum Institut" + "author_name": "Nick Andrews", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Anders Koch", - "author_inst": "Statens Serum Institut" + "author_name": "Julia Stowe", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Steen Ethelberg", - "author_inst": "Statens Serum Institut" + "author_name": "Mary Ramsay", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Anders Hviid", - "author_inst": "Statens Serum Institut" + "author_name": "Jamie Lopez Bernal", + "author_inst": "UK Health Security Agency" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -76128,23 +75890,27 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.03.24.23287706", - "rel_title": "A gene network implicated in the joint-muscle pain, brain fog, chronic fatigue, and bowel irregularity of Ehlers-Danlos and \"long\" COVID19 syndromes.", + "rel_doi": "10.1101/2023.03.21.23287544", + "rel_title": "Informative Use of Cycle-Threshold Values to Account for Sampling Variability in Pathogen Detection", "rel_date": "2023-03-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.24.23287706", - "rel_abs": "ObjectivesCharacterization of tissue laxity and dysautonomia symptoms in Ehlers-Danlos syndrome (EDS) uncovered similarities with those of post-infectious SARS-CoV-2 or long COVID19, prompting detailed comparison of their findings and influencing genes.\n\nMethodsHolistic assessment of 1261 EDS outpatients for 120 history-physical findings populated a deidentified database that includes 568 patients with 317 variant genes obtained by commercial NextGen sequencing. Findings were compared to 15 of long COVID19 compiled in an extensive review, genes to 104 associated with COVID19 severity in multiple molecular studies.\n\nResultsFifteen symptoms common to Ehlers-Danlos versus long COVID19 ranged from brain fog (27-80 versus 30-70%), chronic fatigue (38-91; 30-60%), dyspnea (32-52; 29-52%) to irritable bowel (67-89; 14-78%), muscle weakness (22-49; 15-25%), and arthritis (32-94; 15-27%). Genes relevant to EDS included 6 identical to those influencing COVID19 severity (F2, LIFR, NLRP3, STAT1, T1CAM1, TNFRSF13B) and 18 similar including POLG-POLD4, SLC6A2-SLC6A20, and NFKB1-NFKB2. Both gene sets had broad genomic distribution, many mitochondrial genes influencing EDS and many involved with immunity-inflammation modifying COVID19 severity. Recurring DNA variants in EDS that merit evaluation in COVID19 resistance include those impacting connective tissue elements--51 in COL5 (joint), 29 in COL1/2/9/11 (bone), 13 in COL3 (vessel), and 18 in FBN1 (vessel-heart)--or neural function--93 in mitochondrial DNA, 28 in COL6/12, 16 in SCN9A/10A/11A, 14 in POLG, and 11 in genes associated with porphyria.\n\nConclusionsHolistic ascertainment of finding pattern and exome variation in EDS defined tissue laxity, neuromuscular, and autonomic correlations that transcend single abnormalities or types. Implied networks of nuclear and mitochondrial genes are linked to findings like brain fog, fatigue, and frailty in EDS, their similarity to long COVID19 supporting shared therapies for disorders affecting a minimum 0.1% of the global population.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.21.23287544", + "rel_abs": "Nucleic acid amplification tests, like real-time polymerase chain reaction, are widely used for pathogen detection; however, their interpretation rarely accounts for sampling variability. Instead, cycle threshold values are often categorized reducing precision. We describe how pathogen cycle threshold values can be normalized to endogenous host gene expression to correct for sampling variability and compare the validity of this approach to standardization with a standard curve. Normalization serves as a valid alternative to standardization, does not require making a standard curve, increases precision, accounts for sampling variability, and can be easily applied to large clinical or surveillance datasets for informative interpretation.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Golder N Wilson", - "author_inst": "Texas Tech University Health Sciences Center School of Medicine" + "author_name": "Aidan M Nikiforuk", + "author_inst": "The University of British Columbia" + }, + { + "author_name": "Agatha N Jassem", + "author_inst": "The University of British Columbia" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.03.25.534209", @@ -77850,67 +77616,51 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2023.03.22.23287583", - "rel_title": "Gut microbiome predicts atopic diseases in an infant cohort with reduced bacterial exposure due to social distancing", + "rel_doi": "10.1101/2023.03.21.23287529", + "rel_title": "Inter-rater reliability of the Infectious Disease Modeling Reproducibility Checklist (IDMRC) as applied to COVID-19 computational modeling research", "rel_date": "2023-03-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.22.23287583", - "rel_abs": "Several hypotheses link altered microbial exposure in affluent societies to increased prevalence of allergies, but none have been experimentally tested in humans. Here we capitalize on the opportunity to study a cohort of infants (CORAL) raised during COVID-19 associated social distancing measures to test the interactions between bacterial exposure and fecal microbiome composition with atopic outcomes. We show that fecal Clostridia levels were significantly lower in CORAL infants and correlated with a microbial exposure index. Microbiota composition was the most significant component of regression models predicting risk of atopic dermatitis (AUC 0.86) or food allergen sensitization (AUC 0.98) and mediated the effects of multiple environment factors on disease risk. Although diet had a larger effect on microbiota composition than environmental factors linked to dispersal, most effects were mediated through the microbiota. This study provides critical information to refine existing hypothesis on the importance of the gut microbiota to immune development.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.21.23287529", + "rel_abs": "BackgroundInfectious disease computational modeling studies have been widely published during the coronavirus disease 2019 (COVID-19) pandemic, yet they have limited reproducibility. Developed through an iterative testing process with multiple reviewers, the Infectious Disease Modeling Reproducibility Checklist (IDMRC) enumerates the minimal elements necessary to support reproducible infectious disease computational modeling publications. The primary objective of this study was to assess the reliability of the IDMRC and to identify which reproducibility elements were unreported in a sample of COVID-19 computational modeling publications.\n\nMethodsFour reviewers used the IDMRC to assess 46 preprint and peer reviewed COVID-19 modeling studies published between March 13th, 2020, and July 31st, 2020. The inter-rater reliability was evaluated by mean percent agreement and Fleiss kappa coefficients ({kappa}). Papers were ranked based on the average number of reported reproducibility elements, and average proportion of papers that reported each checklist item were tabulated.\n\nResultsQuestions related to the computational environment (mean {kappa} = 0.90, range = 0.90-0.90), analytical software (mean {kappa} = 0.74, range = 0.68-0.82), model description (mean {kappa} = 0.71, range = 0.58-0.84), model implementation (mean {kappa} = 0.68, range = 0.39-0.86), and experimental protocol (mean {kappa} = 0.63, range = 0.58-0.69) had moderate or greater ({kappa} > 0.41) inter-rater reliability. Questions related to data had the lowest values (mean {kappa} = 0.37, range = 0.23-0.59). Reviewers ranked similar papers in the upper and lower quartiles based on the proportion of reproducibility elements each paper reported. While over 70% of the publications provided data used in their models, less than 30% provided the model implementation.\n\nConclusionsThe IDMRC is the first comprehensive, quality-assessed tool for guiding researchers in reporting reproducible infectious disease computational modeling studies. The inter-rater reliability assessment found that most scores were characterized by moderate or greater agreement. These results suggests that the IDMRC might be used to provide reliable assessments of the potential for reproducibility of published infectious disease modeling publications. Results of this evaluation identified opportunities for improvement to the model implementation and data questions that can further improve the reliability of the checklist.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Katri Korpela", - "author_inst": "University of Helsinki" - }, - { - "author_name": "Sadhbh Hurley", - "author_inst": "RCSI" - }, - { - "author_name": "Sinead Ahearn-Ford", - "author_inst": "University College Cork" - }, - { - "author_name": "Ruth Franklin", - "author_inst": "RCSI" - }, - { - "author_name": "Susan Byrne", - "author_inst": "RCSI" + "author_name": "Darya Pokutnaya", + "author_inst": "University of Pittsburgh School of Public Health" }, { - "author_name": "Nonhlanhla Lunjani", - "author_inst": "University College Cork" + "author_name": "Willem G Van Panhuis", + "author_inst": "National Institute of Allergy and Infectious Diseases" }, { - "author_name": "Brian Forde", - "author_inst": "University College Cork" + "author_name": "Bruce Childers", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Ujjwal Neogi", - "author_inst": "Karolinska Institutet" + "author_name": "Marquis S Hawkins", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Carina Venter", - "author_inst": "University of Colorado" + "author_name": "Alice E Arcury-Quandt", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Jens Walter", - "author_inst": "University College Cork" + "author_name": "Meghan Matlack", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Jonathan Hourihane", - "author_inst": "RCSI" + "author_name": "Kharlya Carpio", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Liam O'Mahony", - "author_inst": "University College Cork" + "author_name": "Harry Hochheiser", + "author_inst": "University of Pittsburgh" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.03.22.23287577", @@ -79367,491 +79117,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.03.14.23287217", - "rel_title": "Genomic surveillance reveals dynamic shifts in the connectivity of COVID-19 epidemics", - "rel_date": "2023-03-19", + "rel_doi": "10.1101/2023.03.17.23287423", + "rel_title": "Chest CT findings and outcomes of COVID-19 in second wave: A cross-sectional study in a tertiary care centre in Northern India", + "rel_date": "2023-03-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.14.23287217", - "rel_abs": "The maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of SARS-CoV-2 lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of local when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.", - "rel_num_authors": 118, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.17.23287423", + "rel_abs": "IntroductionThe COVID-19 pandemic has posed a serious threat to global health, with developing nations like India being amongst the worst affected. Chest CT scans play a pivotal role in the diagnosis and evaluation of COVID-19, and certain CT features may aid in predicting the prognosis of COVID-19 illness.\n\nMethodsThis was a single-centre, hospital-based, cross-sectional study conducted at a tertiary care centre in Northern India during the second wave of the COVID-19 pandemic from May-June 2021. The study included 473 patients who tested positive for COVID-19. A high-resolution chest CT scan was performed within five days of hospitalization, and patient-related information was extracted retrospectively from medical records. Univariable and Multivariable analysis was done to study the predictors of poor outcome.\n\nResultsA total of 473 patients were included in the study, with 75.5% being males. The mean total CT score was 29.89 {+/-} 9.06. Fibrosis was present in 17.1% of patients, crazy paving in 3.6%, pneumomediastinum in 8.9%, and pneumothorax in 3.6%. Males had a significantly higher total score, while the patients who survived (30.00 {+/-} 9.55 vs 35.00 v 6.21, p value - <.001), received Steroids at day 2 (28.04 {+/-} 9.71 vs 31.66 {+/-} 7.12, p value - 0.002) or Remdesivir had lower total scores (28.04 {+/-} 9.71 vs 31.66 {+/-} 7.12, p-value - 0.002). Total CT score (aHR 1.05, 95% CI 1.02 - 1.08, p - 0.001), pneumothorax (aHR 1.38, 95 % CI 0.67 - 2.87, p - 0.385), pneumomediastinum (aHR 1.20, 95% CI 0.71 - 2.03, p=0.298) and cardiovascular accident (CVA, aHR 4.75, 95% CI 0.84 - 26.72, p - 0.077) were associated with increased mortality, but the results were not significant after adjusting with other variables on multiple regression analysis.\n\nConclusionThis study identifies several radiological parameters, including fibrosis, crazy paving, pneumomediastinum, and pneumothorax, that are associated with poor prognosis in COVID-19. These findings highlight the role of CT thorax in COVID-19 illness and the importance of timely identification and interventions in severe and critical cases of COVID-19 to reduce mortality and morbidity.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Nathaniel L Matteson", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" - }, - { - "author_name": "Gabriel W Hassler", - "author_inst": "Department of Computational Medicine, University of California, Los Angeles, CA, USA" - }, - { - "author_name": "Ezra Kurzban", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" - }, - { - "author_name": "Madison A Schwab", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" - }, - { - "author_name": "Sarah A Perkins", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" - }, - { - "author_name": "Karthik Gangavarapu", - "author_inst": "['Department of Biomathematics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA, USA', 'Department of Immunology and Microbio" - }, - { - "author_name": "Joshua I Levy", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" - }, - { - "author_name": "Edyth Parker", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" - }, - { - "author_name": "David Pride", - "author_inst": "['Department of Pathology, University of California San Diego, La Jolla, CA, USA.', 'Department of Medicine, University of California San Diego, La Jolla, CA, U" - }, - { - "author_name": "Abbas Hakim", - "author_inst": "['Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.', 'Department" - }, - { - "author_name": "Peter De Hoff", - "author_inst": "['Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.', 'Department" - }, - { - "author_name": "Willi Cheung", - "author_inst": "['Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.', 'Department" - }, - { - "author_name": "Anelizze Castro-Martinez", - "author_inst": "['Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.', 'Department" - }, - { - "author_name": "Andrea Rivera", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Anthony Veder", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Ariana Rivera", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Cassandra Wauer", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Jacqueline Holmes", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Jedediah Wilson", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Shayla N Ngo", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Ashley Plascencia", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Elijah S Lawrence", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Elizabeth W Smoot", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Emily R Eisner", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Rebecca Tsai", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Marisol Chacon", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Nathan A Baer", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Phoebe Seaver", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Rodolfo A Salido", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Stefan Aigner", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Toan T Ngo", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Tom Barber", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Tyler Ostrander", - "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Rebecca Fielding-Miller", - "author_inst": "['Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA.', 'Division of Infectious Disease" - }, - { - "author_name": "Elizabeth H Simmons", - "author_inst": "Academic Affairs, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Oscar E Zazueta", - "author_inst": "Department of Epidemiology. Secretaria de Salud de Baja California, Mexico" - }, - { - "author_name": "Idanya Serafin-Higuera", - "author_inst": "Centro de Diagnostico COVID-19 UABC Tijuana" - }, - { - "author_name": "Manuel Sanchez-Alavez", - "author_inst": "['Centro de Diagnostico COVID-19 UABC Tijuana', 'Department of Molecular Medicine, Scripps Research']" - }, - { - "author_name": "Jose L Moreno-Camacho", - "author_inst": "Clinical Laboratory Department, Salud Digna, A.C" - }, - { - "author_name": "Abraham Garcia-Gil", - "author_inst": "Clinical Laboratory Department, Salud Digna, A.C" - }, - { - "author_name": "Ashleigh R Murphy Schafer", - "author_inst": "County of San Diego Health and Human Services Agency, San Diego, CA, USA." - }, - { - "author_name": "Eric McDonald", - "author_inst": "County of San Diego Health and Human Services Agency, San Diego, CA, USA." - }, - { - "author_name": "Jeremy Corrigan", - "author_inst": "County of San Diego Health and Human Services Agency, San Diego, CA, USA." - }, - { - "author_name": "John D Malone", - "author_inst": "County of San Diego Health and Human Services Agency, San Diego, CA, USA." - }, - { - "author_name": "Sarah Stous", - "author_inst": "County of San Diego Health and Human Services Agency, San Diego, CA, USA." - }, - { - "author_name": "Seema Shah", - "author_inst": "County of San Diego Health and Human Services Agency, San Diego, CA, USA." - }, - { - "author_name": "Niema Moshiri", - "author_inst": "Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Alana Weiss", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" - }, - { - "author_name": "Catelyn Anderson", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" - }, - { - "author_name": "Christine M Aceves", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" - }, - { - "author_name": "Emily G Spencer", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" - }, - { - "author_name": "Emory C Hufbauer", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" - }, - { - "author_name": "Justin J Lee", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" - }, - { - "author_name": "Karthik S Ramesh", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" - }, - { - "author_name": "Kelly N Nguyen", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" - }, - { - "author_name": "Kieran Saucedo", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" - }, - { - "author_name": "Refugio Robles-Sikisaka", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" - }, - { - "author_name": "Kathleen M Fisch", - "author_inst": "['Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA.', 'Center for Computational Biology an" - }, - { - "author_name": "Steven L Gonias", - "author_inst": "Department of Pathology, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Amanda Birmingham", - "author_inst": "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Daniel McDonald", - "author_inst": "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Smruthi Karthikeyan", - "author_inst": "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Natasha K Martin", - "author_inst": "Division of Infectious Disease and Global Public Health, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Robert T Schooley", - "author_inst": "Division of Infectious Disease and Global Public Health, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Agustin J Negrete", - "author_inst": "Facultad de Ciencias de la Salud Universidad Autonoma de Baja California Valle de Las Palmas" - }, - { - "author_name": "Horacio J Reyna", - "author_inst": "Facultad de Ciencias de la Salud Universidad Autonoma de Baja California Valle de Las Palmas" - }, - { - "author_name": "Jose R Chavez", - "author_inst": "Facultad de Ciencias de la Salud Universidad Autonoma de Baja California Valle de Las Palmas" - }, - { - "author_name": "Maria L Garcia", - "author_inst": "Facultad de Ciencias de la Salud Universidad Autonoma de Baja California Valle de Las Palmas" - }, - { - "author_name": "Jose M Cornejo-Bravo", - "author_inst": "Facultad de Ciencias Quimicas e Ingenieria, Universidad Autonoma de Baja California, Mexico" - }, - { - "author_name": "David Becker", - "author_inst": "Helix, San Mateo, CA, USA." - }, - { - "author_name": "Magnus Isaksson", - "author_inst": "Helix, San Mateo, CA, USA." - }, - { - "author_name": "Nicole L Washington", - "author_inst": "Helix, San Mateo, CA, USA." - }, - { - "author_name": "William Lee", - "author_inst": "Helix, San Mateo, CA, USA." - }, - { - "author_name": "Richard S Garfein", - "author_inst": "Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Marco A Luna-Ruiz Esparza", - "author_inst": "Innovation and Research Department, Salud Digna, A.C, Tijuana, B.C., Mexico" - }, - { - "author_name": "Jonathan Alcantar-Fernandez", - "author_inst": "Innovation and Research Department, Salud Digna, A.C, Tijuana, B.C., Mexico" - }, - { - "author_name": "Benjamin Henson", - "author_inst": "Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Kristen Jepsen", - "author_inst": "Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Beatriz Olivares-Flores", - "author_inst": "Instituto de Diagnostico y Referencia Epidemiologicos (InDRE), Ciudad de Mexico, CDMX, Mexico" - }, - { - "author_name": "Gisela Barrera-Badillo", - "author_inst": "Instituto de Diagnostico y Referencia Epidemiologicos (InDRE), Ciudad de Mexico, CDMX, Mexico" - }, - { - "author_name": "Irma Lopez-Martinez", - "author_inst": "Instituto de Diagnostico y Referencia Epidemiologicos (InDRE), Ciudad de Mexico, CDMX, Mexico" - }, - { - "author_name": "Jose E Ramirez-Gonzalez", - "author_inst": "Instituto de Diagnostico y Referencia Epidemiologicos (InDRE), Ciudad de Mexico, CDMX, Mexico" - }, - { - "author_name": "Rita Flores-Leon", - "author_inst": "Instituto de Diagnostico y Referencia Epidemiologicos (InDRE), Ciudad de Mexico, CDMX, Mexico" - }, - { - "author_name": "Stephen F Kingsmore", - "author_inst": "Rady Children's Institute for Genomic Medicine, San Diego, CA, USA." - }, - { - "author_name": "Alison Sanders", - "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Allorah Pradenas", - "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Benjamin White", - "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Gary Matthews", - "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Matt Hale", - "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Ronald W McLawhon", - "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Sharon L Reed", - "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Terri Winbush", - "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Ian H McHardy", - "author_inst": "Scripps Health, San Diego, La Jolla, CA, USA" - }, - { - "author_name": "Russel A Fielding", - "author_inst": "Scripps Health, San Diego, La Jolla, CA, USA" - }, - { - "author_name": "Laura Nicholson", - "author_inst": "Scripps Health, San Diego, La Jolla, CA, USA" - }, - { - "author_name": "Michael M Quigley", - "author_inst": "Scripps Health, San Diego, La Jolla, CA, USA" - }, - { - "author_name": "Aaron Harding", - "author_inst": "Sharp Healthcare, San Diego, CA, USA." - }, - { - "author_name": "Art Mendoza", - "author_inst": "Sharp Healthcare, San Diego, CA, USA." - }, - { - "author_name": "Omid Bakhtar", - "author_inst": "Sharp Healthcare, San Diego, CA, USA." - }, - { - "author_name": "Sara H Browne", - "author_inst": "['Specialist in Global Health, Encinitas, CA, USA.', 'Division of Infectious Disease and Global Public Health, University of California San Diego, La Jolla, CA," - }, - { - "author_name": "Jocelyn Olivas Flores", - "author_inst": "['UniHealthMx, Tijuana, B.C., Mexico', 'Facultad de Ciencias Quimicas e Ingenieria, Universidad Autonoma de Baja California, Mexico']" - }, - { - "author_name": "Diana G Rincon Rodriguez", - "author_inst": "['UniHealthMx, Tijuana, B.C., Mexico', 'Facultad de Medicina, Universidad Xochicalco, Tijuana, B.C., Mexico']" - }, - { - "author_name": "Martin Gonzalez Ibarra", - "author_inst": "['UniHealthMx, Tijuana, B.C., Mexico', 'Facultad de Medicina, Universidad Xochicalco, Tijuana, B.C., Mexico']" - }, - { - "author_name": "Luis C Robles Ibarra", - "author_inst": "['UniHealthMx, Tijuana, B.C., Mexico', 'Instituto de Seguridad y Servicios Sociales de los Trabajadores del Estado, Tijuana, B.C., Mexico']" - }, - { - "author_name": "Betsy J Arellano Vera", - "author_inst": "['UniHealthMx, Tijuana, B.C., Mexico', 'Instituto Mexicano del Seguro Social, Tijuana, B.C., Mexico']" - }, - { - "author_name": "Jonathan Gonzalez Garcia", - "author_inst": "['UniHealthMx, Tijuana, B.C., Mexico', 'SIMNSA, Tijuana, B.C., Mexico']" - }, - { - "author_name": "Alicia Harvey-Vera", - "author_inst": "University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Rob Knight", - "author_inst": "['Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.', 'Department of Computer Science and Engineering, University of California S" - }, - { - "author_name": "Louise C Laurent", - "author_inst": "['Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.', 'Department" - }, - { - "author_name": "Gene W Yeo", - "author_inst": "['Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.', 'Sanford Co" - }, - { - "author_name": "Joel O Wertheim", - "author_inst": "Department of Medicine, University of California San Diego, La Jolla, CA, USA." - }, - { - "author_name": "Xiang Ji", - "author_inst": "Department of Mathematics, School of Science and Engineering, Tulane University, New Orleans, LA, USA" - }, - { - "author_name": "Michael Worobey", - "author_inst": "Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA" - }, - { - "author_name": "Marc A Suchard", - "author_inst": "Department of Human Genetics, University of California, Los Angeles, CA, USA" + "author_name": "Taranjeet Cheema", + "author_inst": "AIIMS Rishikesh" }, { - "author_name": "Kristian G Andersen", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" + "author_name": "Amit Saroha", + "author_inst": "AIIMS Rishikesh" }, { - "author_name": "Abraham Campos-Romero", - "author_inst": "Innovation and Research Department, Salud Digna, A.C, Tijuana, B.C., Mexico" + "author_name": "Arjun Kumar", + "author_inst": "AIIMS Rishikesh" }, { - "author_name": "Shirlee Wohl", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" + "author_name": "Prasan Kumar Panda", + "author_inst": "AIIMS Rishikesh" }, { - "author_name": "Mark Zeller", - "author_inst": "Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA" + "author_name": "Sudhir Saxena", + "author_inst": "AIIMS Rishikesh" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.03.17.23287396", @@ -81617,87 +80915,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.03.15.532728", - "rel_title": "An ancestral vaccine induces anti-Omicron antibodies by hypermutation", + "rel_doi": "10.1101/2023.03.14.532609", + "rel_title": "Epithelial galectin-3 induces mitochondrial complex inhibition and cell cycle arrest of CD8+ T Cells in severe/critical ill COVID-19", "rel_date": "2023-03-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.03.15.532728", - "rel_abs": "The immune escape of Omicron variants significantly subsides by the third dose of an mRNA vaccine. However, it is unclear how Omicron variant-neutralizing antibodies develop under repeated vaccination. We analyzed blood samples from 41 BNT162b2 vaccinees following the course of three injections and analyzed their B-cell receptor (BCR) repertoires at six time points in total. The concomitant reactivity to both ancestral and Omicron receptor-binding domain (RBD) was achieved by a limited number of BCR clonotypes depending on the accumulation of somatic hypermutation (SHM) after the third dose. Our findings suggest that SHM accumulation in the BCR space to broaden its specificity for unseen antigens is a counter protective mechanism against virus variant immune escape.", - "rel_num_authors": 17, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.03.14.532609", + "rel_abs": "Several studies have identified the presence of functionally depleted CD8+ T cells in COVID-19 patients, and particularly abnormally reduced CD8+ T cells in severe/critical patients, which may be a major cause of disease progression and poor prognosis. In this study, a proliferating-depleted CD8+ T cell phenotype was observed in severe/critical COVID-19 patients through scRNA-seq and scTCR-seq analysis. These CD8+ T cells were subsequently found to be characterized by cell cycle arrest and downregulation of mitochondrial biogenesis and respiratory chain complex genes. Cellchat analysis revealed that the Galectin signaling pathways between infected lung epithelial cells and CD8+ T cells play the key role in inducing CD8+ T cell reduction and dysfunction in severe/critical COVID-19. We used SARS-COV-2 ORF3a to transfect A549 epithelial cells, and co-cultured with CD8+ T cells. The ex vivo experiments confirmed that galectin-3 inhibited the transcription of mitochondrial respiratory chain complex III/IV genes in CD8+ T cells by suppressing the nuclear translocation of nuclear respiratory factor 1 (NRF1). In addition, the regulatory effect of galectin-3 was correlated with the activation of ERK signaling and/or the inhibition of Akt signaling. Galectin-3 inhibitor, TD-139, promoted nuclear translocation of NRF1, and enhanced mitochondrial respiratory chain complex III/IV gene expression and mitochondrial biogenesis, then restore the expansion ability of CD8+ T cells. Our study improved the understanding the immunopathogenesis and provided new target for the prevention and treatment of severe/critical COVID-19.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Seoryeong Park", - "author_inst": "Department of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul, Republic of Korea; Interdisciplinary Program in Cancer B" - }, - { - "author_name": "Jaewon Choi", - "author_inst": "Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, Republic of Korea; Integrated Major in Innovative Medical Science, Seoul National" - }, - { - "author_name": "Yonghee Lee", - "author_inst": "Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea" - }, - { - "author_name": "Jinsung Noh", - "author_inst": "Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea; Bio-MAX Institute, Seoul National University, Seoul, Rep" - }, - { - "author_name": "Namphil Kim", - "author_inst": "Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea" - }, - { - "author_name": "JinAh Lee", - "author_inst": "Zoonotic Virus Laboratory, Institut Pasteur Korea, Seongnam, Republic of Korea" - }, - { - "author_name": "Geummi Cho", - "author_inst": "Department of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul, Republic of Korea; Department of Biomedical Science, Seo" + "author_name": "Yudie Wang", + "author_inst": "Department of Biology and Genetics, College of Life Sciences and Health, Wuhan University of Science and Technology, Wuhan, China" }, { - "author_name": "Sujeong Kim", - "author_inst": "Department of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul, Republic of Korea; Department of Biomedical Science, Seo" + "author_name": "Cheng Yang", + "author_inst": "Department of Biology and Genetics, College of Life Sciences and Health, Wuhan University of Science and Technology, Wuhan, China" }, { - "author_name": "Duck Kyun Yoo", - "author_inst": "Department of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul, Republic of Korea; Department of Biomedical Science, Seo" + "author_name": "Zhongyi Wang", + "author_inst": "Department of Biology and Genetics, College of Life Sciences and Health, Wuhan University of Science and Technology, Wuhan, China" }, { - "author_name": "Chang Kyung Kang", - "author_inst": "Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea" + "author_name": "Yi Wang", + "author_inst": "Department of Biology and Genetics, College of Life Sciences and Health, Wuhan University of Science and Technology, Wuhan, China" }, { - "author_name": "Pyoeng Gyun Choe", - "author_inst": "Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea" + "author_name": "Qing Yan", + "author_inst": "Department of Biology and Genetics, College of Life Sciences and Health, Wuhan University of Science and Technology, Wuhan, China" }, { - "author_name": "Nam Joong Kim", - "author_inst": "Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea" + "author_name": "Ying Feng", + "author_inst": "Department of Biology and Genetics, College of Life Sciences and Health, Wuhan University of Science and Technology, Wuhan, China" }, { - "author_name": "Wan Beom Park", - "author_inst": "Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea" + "author_name": "Yanping Liu", + "author_inst": "Department of Biology and Genetics, College of Life Sciences and Health, Wuhan University of Science and Technology, Wuhan, China" }, { - "author_name": "Seungtaek Kim", - "author_inst": "Zoonotic Virus Laboratory, Institut Pasteur Korea, Seongnam, Republic of Korea" + "author_name": "Xiaolan Zhang", + "author_inst": "Department of Biology and Genetics, College of Life Sciences and Health, Wuhan University of Science and Technology, Wuhan, China" }, { - "author_name": "Myoung-don Oh", - "author_inst": "Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea" + "author_name": "Jingwei Zhao", + "author_inst": "Department of Biology and Genetics, College of Life Sciences and Health, Wuhan University of Science and Technology, Wuhan, China" }, { - "author_name": "Sunghoon Kwon", - "author_inst": "Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, Republic of Korea; Department of Electrical and Computer Engineering, Seoul Natio" + "author_name": "Juan Huang", + "author_inst": "Department of Medicine, Maternal and Child Health Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China" }, { - "author_name": "Junho Chung", - "author_inst": "Department of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul, Republic of Korea; Interdisciplinary Program in Cancer B" + "author_name": "Jingjiao Zhou", + "author_inst": "Department of Biology and Genetics, College of Life Sciences and Health, Wuhan University of Science and Technology, Wuhan, China" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "bioengineering" + "category": "immunology" }, { "rel_doi": "10.1101/2023.03.14.23287258", @@ -83283,33 +82557,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.03.11.23287133", - "rel_title": "Investigating the marginal and herd effects of COVID-19 vaccination for reducing case fatality rate: Evidence from the United States.", - "rel_date": "2023-03-12", + "rel_doi": "10.1101/2023.03.09.23287048", + "rel_title": "Cause of Death by Race and Ethnicity in Minnesota Before and During the COVID-19 Pandemic, 2019-2020", + "rel_date": "2023-03-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.11.23287133", - "rel_abs": "Vaccination campaigns have been rolled out in most countries to increase the vaccination coverage and protect against case mortality during the ongoing pandemic. To evaluate the effectiveness of COVID-19 vaccination, it is vital to disentangle the herd effect from the marginal effect and parameterize them separately in a model. To demonstrate this, we study the relationship between the COVID-19 vaccination coverage and case fatality rate (CFR) based on a U.S. vaccination coverage at county level, with daily records from March 11th, 2021 to Jan 26th, 2022 for 3109 U.S. counties. Using segmented regression, we discovered three breakpoints of the vaccination coverage, at which the herd effects could potentially exist. Controlling for county heterogeneity, we found the size of the marginal effect was not constant but actually enlarged as the vaccination coverage increased, and only the herd effect at the first breakpoint was statistically significant, which implied indirect benefit of vaccination may exist at the early stage of a vaccination campaign. Our results have demonstrated that public health researchers should carefully differentiate and quantify the herd and marginal effects in analyzing vaccination data, to better inform vaccination campaign strategies as well as evaluate vaccination effectiveness.", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.09.23287048", + "rel_abs": "ObjectivesTo measure changes in cause of death dynamics in 2019 and 2020 and the relationship between concurrent occurrence of the COVID-19 pandemic and mortality outcome by race and ethnicity.\n\nPatients and MethodsWe used resident mortality data from the Minnesota Department of Health (MDH) to conduct retrospective statistical analysis of deaths in Minnesota in 2019 relative to 2020 to assess changes in mortality in a pre-pandemic and pandemic period.\n\nResultsCOVID-19 strongly contributed to ethnicity-related mortality disparities in Minnesota. Not only was there a greater proportion of COVID-19 decedents within the Black and Hispanic populations, but their average decedent age was markedly lower relative to the White population. The Black population experienced a disproportionate increase in decedents with a 34% increase during 2020 compared to 2019.\n\nConclusionsThis retrospective analysis of death dynamics and mortality outcomes in Minnesota from 2019 to 2020 demonstrated an increase in adverse mortality outcomes relative to the pre-pandemic period that disproportionately impacted Black and Hispanic minority populations. Access to non-pharmaceutical interventions combating COVID-19 infection in Black and Hispanic communities should be expanded in Minnesota.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Tenglong Li", - "author_inst": "Xi'an Jiaotong-Liverpool University" + "author_name": "Madelyn Blake", + "author_inst": "University of Minnesota Twin Cities" }, { - "author_name": "Zilong Wang", - "author_inst": "Xi'an Jiaotong-Liverpool University" + "author_name": "Nicholas Marka", + "author_inst": "University of Minnesota Twin Cities" }, { - "author_name": "Shuyue He", - "author_inst": "Xi'an Jiaotong-Liverpool University" + "author_name": "Clifford Steer", + "author_inst": "University of Minnesota" }, { - "author_name": "Ying Chen", - "author_inst": "Xi'an Jiaotong-Liverpool University" + "author_name": "Jonathan Ravdin", + "author_inst": "University of Minnesota Medical School" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -85141,43 +84415,31 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2023.03.06.23286848", - "rel_title": "Comparative Effectiveness of Alternative Intervals between First and Second Doses of the mRNA COVID-19 Vaccines: a Trial Emulation Approach", + "rel_doi": "10.1101/2023.03.06.23286869", + "rel_title": "An Explainable Host Genetic Severity Predictor Model for COVID-19 Patients", "rel_date": "2023-03-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.06.23286848", - "rel_abs": "ImportancemRNA COVID-19 vaccines require two primary doses. The optimal timing of second dose administration with respect to vaccine effectiveness of the primary series has not been thoroughly evaluated and has implications for vaccination strategies.\n\nObjectiveTo assess whether the effectiveness of mRNA COVID-19 vaccines (Pfizer-BioNTech and Moderna) against SARS-CoV-2 infection differs by varying intervals between the first and second doses of the primary series among the general population.\n\nDesignWe employed a trial emulation approach (clone-censor weight analysis) to estimate the risk of SARS-CoV-2 infection after the first dose administration under the scenario where the total study population had followed each of the following interdose intervals: recommended by the Food and Drug Administration (FDA) (17-25 days for Pfizer-BioNTech; 24-32 days for Moderna), late-but-allowable (26-42 days for Pfizer-BioNTech; 33-49 days for Moderna), and late ([≥]43 days for Pfizer-BioNTech; [≥]50 days for Moderna).\n\nSettingGeorgia, USA.\n\nParticipantsIndividuals who received [≥]1 dose of mRNA COVID-19 vaccines in Georgia between December 13, 2020 and March 16, 2022.\n\nExposureDosing protocols based on the timing of the second dose administration.\n\nMain Outcomes and MeasuresSARS-CoV-2 infection was defined as a positive result by a real-time reverse transcriptase PCR or antigen test. The follow-up period began the day after the first dose administration and ended at the earliest of SARS-CoV-2 infection, protocol nonadherence, or end of study.\n\nResultsIn the short-term, the cumulative risk of SARS-CoV-2 infection was lowest under the FDA-recommended protocol (risk ratio (RR) on Day 50 after the first dose administration compared to the FDA-recommended protocol: 1.08 [95% confidence interval 1.07-1.10] under the late-but-allowable and 1.14 [1.12-1.16] under the late protocol). Longer-term, the late-but-allowable protocol resulted in the lowest risk (RR on Day 120: 0.83 [0.82-0.84] for the late-but-allowable and 1.10 [1.08-1.12] for the late protocol). The late protocol consistently yielded the highest risk among all protocols.\n\nConclusions and RelevanceDelaying the timing of the second dose administration by a week may provide stronger protection against SARS-CoV-2 infection, but a longer delay would increase the risk of infection.\n\nKEY POINTSO_ST_ABSQuestionC_ST_ABSDoes the effectiveness of mRNA COVID-19 vaccines differ by intervals between the first and second doses of the primary series?\n\nFindingsThis study of >6 million mRNA COVID-19 vaccine recipients in Georgia, US used a trial emulation approach to compare the risk of SARS-CoV-2 infection under three protocols based on the timing of the second dose (\"recommended,\" \"late-but-allowable,\" and \"late\"). The late-but-allowable protocol led to the lowest cumulative risk in a long term.\n\nMeaningDelaying the receipt of the second dose by a week may decrease the risk of SARS-CoV-2 infection, but a longer delay would increase the risk.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.06.23286869", + "rel_abs": "Understanding the COVID-19 severity and why it differs significantly among patients is a thing of concern to the scientific community. The major contribution of this study arises from the use of a voting ensemble host genetic severity predictor (HGSP) model we developed by combining several state-of-the-art machine learning algorithms (decision tree-based models: Random Forest and XGBoost classifiers). These models were trained using a genetic Whole Exome Sequencing (WES) dataset and clinical covariates (age and gender) formulated from a 5-fold stratified cross-validation computational strategy to randomly split the dataset to overcome model instability. Our study validated the HGSP model based on the 18 features (i.e., 16 identified candidate genetic variants and 2 covariates) identified from a prior study. We provided post-hoc model explanations through the ExplainerDashboard - an open-source python library framework, allowing for deeper insight into the prediction results. We applied the Enrichr and OpenTarget genetics bioinformatic interactive tools to associate the genetic variants for plausible biological insights, and domain interpretations such as pathways, ontologies, and disease/drugs. Through an unsupervised clustering of the SHAP feature importance values, we visualized the complex genetic mechanisms. Our findings show that while age and gender mainly influence COVID-19 severity, a specific group of patients experiences severity due to complex genetic interactions.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Kayoko Shioda", - "author_inst": "Emory University" - }, - { - "author_name": "Alexander Breskin", - "author_inst": "Regeneron Pharmaceuticals" - }, - { - "author_name": "Pravara Harati", - "author_inst": "Georgia Department of Public Health" - }, - { - "author_name": "Allison Chamberlain", - "author_inst": "Emory University" + "author_name": "Anthony Onoja", + "author_inst": "University of Surrey" }, { - "author_name": "Benjamin Lopman", - "author_inst": "Rollins School of Public Health at Emory University" + "author_name": "Francesco Raimondi", + "author_inst": "Scuola Normale Superiore" }, { - "author_name": "Elizabeth T Rogawski McQuade", - "author_inst": "Emory University" + "author_name": "Mirco Nanni", + "author_inst": "Istituto di Scienza e Tecnologie dell Informazione, National Research Council of Italy" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "health informatics" }, { "rel_doi": "10.1101/2023.03.06.23286877", @@ -86847,81 +86109,53 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2023.03.06.23286837", - "rel_title": "Prediction of SARS-CoV-2 transmission dynamics based on population-level cycle threshold values: A Machine learning and mechanistic modeling study", + "rel_doi": "10.1101/2023.03.03.23286775", + "rel_title": "Viral kinetics of sequential SARS-CoV-2 infections", "rel_date": "2023-03-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.06.23286837", - "rel_abs": "BackgroundPolymerase chain reaction (PCR) cycle threshold (Ct) values can be used to estimate the viral burden of Severe Acute Respiratory Syndrome Coronavirus type 2 (SARS-CoV-2) and predict population-level epidemic trends. We investigated the use of machine learning (ML) and epidemic transmission modeling based on Ct value distribution for SARS-CoV-2 incidence prediction during an Omicron-predominant period.\n\nMethodsUsing simulated data, we developed a ML model to predict the reproductive number based on Ct value distribution, and validated it on out-of-sample province-level data. We also developed an epidemiological model and fitted it to province-level data to accurately predict incidence.\n\nResultsBased on simulated data, the ML model predicted the reproductive number with highest performance on out-of-sample province-level data. The epidemiological model was validated on outbreak data, and fitted to province-level data, and accurately predicted incidence.\n\nConclusions\n\nThese modeling approaches can complement traditional surveillance, especially when diagnostic testing practices change over time. The models can be tailored to different epidemiological settings and used in real time to guide public health interventions.\n\nFundingThis work was supported by funding from Genome BC, Michael Smith Foundation for Health Research and British Columbia Centre for Disease Control Foundation to C.A.H. This work was also funded by the Public Health Agency of Canada COVID-19 Immunity Task Force COVID-19 Hot Spots Competition Grant (2021-HQ-000120) to M.G.R.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.03.23286775", + "rel_abs": "The impact of a prior SARS-CoV-2 infection on the progression of subsequent infections has been unclear. Using a convenience sample of 94,812 longitudinal RT-qPCR measurements from anterior nares and oropharyngeal swabs, we compared the SARS-CoV-2 viral kinetics of first vs. second infections, adjusting for viral variant, vaccination status, and age. Relative to first infections, second infections usually featured a lower peak viral concentration and faster clearance time, especially in individuals who received a vaccine dose between their first and second infection. Furthermore, a persons relative (rank-order) viral clearance time, compared to others infected with the same variant, was similar across first and second infections; that is, individuals who had a relatively fast clearance time in their first infection tended to also have a relatively fast clearance time in their second infection. These findings provide evidence that, like vaccination, immunity from a prior SARS-CoV-2 infection shortens the duration of subsequent acute SARS-CoV-2 infections principally by reducing viral clearance time. Additionally, there appears to be an inherent element of the immune response, or some other host factor, that shapes a persons relative ability to clear SARS-CoV-2 infection that persists across sequential infections.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Afraz Arif Khan", - "author_inst": "BC Centre for Disease Control" - }, - { - "author_name": "Hind Sbihi", - "author_inst": "BC Centre for Disease Control" - }, - { - "author_name": "Michael A Irvine", - "author_inst": "BC Centre for Disease Control" - }, - { - "author_name": "Agatha N Jassem", - "author_inst": "BC Centre for Disease Control" - }, - { - "author_name": "Yayuk Joffres", - "author_inst": "BC Centre for Disease Control" - }, - { - "author_name": "Braeden Klaver", - "author_inst": "BC Centre for Disease Control" - }, - { - "author_name": "Naveed Janjua", - "author_inst": "BC Centre for Disease Control" - }, - { - "author_name": "Aamir Bharmal", - "author_inst": "BC Centre for Disease Control" + "author_name": "Stephen M Kissler", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Carmen Ng", - "author_inst": "Fraser Health" + "author_name": "James A Hay", + "author_inst": "Harvard T H Chan School of Public Health" }, { - "author_name": "Amanda Wilmer", - "author_inst": "Kelowna General Hospital" + "author_name": "Joseph R Fauver", + "author_inst": "University of Nebraska Medical Center" }, { - "author_name": "John Galbraith", - "author_inst": "Victoria General Hospital" + "author_name": "Christina Mack", + "author_inst": "IQVIA" }, { - "author_name": "Marc G Romney", - "author_inst": "St. Paul's Hospital" + "author_name": "Caroline Tai", + "author_inst": "IQVIA" }, { - "author_name": "Bonnie Henry", - "author_inst": "Ministry of Health" + "author_name": "Deverick Anderson", + "author_inst": "Duke Center for Antimicrobial Stewardship and Infection Prevention" }, { - "author_name": "Linda Hoang", - "author_inst": "BC Centre for Disease Control" + "author_name": "David Ho", + "author_inst": "Vagelos College of Physicians and Surgeons, Columbia University" }, { - "author_name": "Mel Krajden", - "author_inst": "BC Centre for Disease Control" + "author_name": "Nathan Grubaugh", + "author_inst": "Yale School of Public Health" }, { - "author_name": "Catherine A Hogan", - "author_inst": "BC Centre for Disease Control" + "author_name": "Yonatan Grad", + "author_inst": "Harvard T. H. Chan School of Public Health" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -88497,87 +87731,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.02.28.23286535", - "rel_title": "A survey and antibody test following the surge of SARS-CoV-2 Omicron infection in China", + "rel_doi": "10.1101/2023.02.27.23286514", + "rel_title": "Maternal Characteristics and Pregnancy Outcomes During The Pandemic Covid-19 in Indonesian Tertiary Referral Hospital", "rel_date": "2023-03-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.28.23286535", - "rel_abs": "The surge of SARS-CoV-2 Omicron infection in most Chinese residents at the end of 2022 provided a unique opportunity to understand how the immune system responds to the Omicron infection in a population with limited contact to prior SARS-CoV-2 variants. Moreover, whether the prototype SARS-CoV-2 booster vaccination could help induce the antibody against Omicron variants? Here, we tested the level of IgG, IgA, and IgM specific to the prototype SARS-CoV-2 spike RBD (Receptor Binding Domain) from the collected blood samples from 636 individuals. Sequential inoculation of different vaccines showed higher IgG levels after infection. As the antibody level against Omicron BA.5, BF.7, and XBB 1.5 of the individuals has highly positive correlation with the antibody level against prototype SARS-CoV2, the IgG level specific to the prototype SARS-CoV-2 spike RBD could also represent the IgG level against Omicron variants. Furthermore, the 4th booster vaccination could induce a comparable antibody level against prototype, Omicron BA.5, BF.7, and XBB 1.5 variants in the patients with 2 or 3-dose vaccination and protect people from being infected. In conclusion, these data suggest that the prototype SARS-CoV-2 booster vaccination helps induce a high level of antibody against prototype, BA.5, BF.7, and XBB 1.5 variants after Omicron infection.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.27.23286514", + "rel_abs": "AimAnalyse differences in intervention and pregnancy outcomes characteristics in obstetric patients with a diagnosis of COVID-19 and non-COVID-19 at one of the Indonesia tertiary referral hospital in East Java.\n\nDesignThis was cross sectional study.\n\nMethodsThis study was performed 694 obstetric patients, the data for these patients were obtained from the hospital medical records Sampling was used simple random. This study used Mann-Whitney test to analyse the differences between the variables.\n\nResultsThere was a significant difference in the Length Of Stay (LOS), LOS of COVID-19 patients tends to be longer than that of non-COVID-19 patients. More than half of the patients gave birth by caesarean delivery, 83 for COVID-19 and 283 for Non COVID-19. Some of the most common complications among COVID-19 patients were maternal infectious and parasitic diseases (1.3% vs 0.0%), abnormalities of forces of labour (12.3% vs 9.6%), complication of puerperium (0.6 % vs 0.0%). 40.9% COVID-19 patient suffered Acute Respiratory Distress Syndrome (ARDS). COVID-19 infection had no significant effect on pregnancy outcomes.\n\nConclusionSeveral interventions need to be re-evaluated, such as cesarean delivery in COVID-19 and non-COVID-19 patients. The health-care delivery system must also be re-evaluated, and the tiered referral system must be strengthened.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Yichuan Yao", - "author_inst": "University of Science and Technology of China" - }, - { - "author_name": "Yunru Yang", - "author_inst": "University of Science and Technology of China" - }, - { - "author_name": "Qiqin Wu", - "author_inst": "University of Science and Technology of China" - }, - { - "author_name": "Mengyao Liu", - "author_inst": "University of Science and Technology of China" - }, - { - "author_name": "Wei Bao", - "author_inst": "University of Science and Technology of China" - }, - { - "author_name": "Qiutong Wang", - "author_inst": "University of Science and Technology of China" - }, - { - "author_name": "Meijun Cheng", - "author_inst": "University of Science and Technology of China" - }, - { - "author_name": "Yunuo Chen", - "author_inst": "University of Science and Technology of China" - }, - { - "author_name": "Yuan Cai", - "author_inst": "University of Science and Technology of China" - }, - { - "author_name": "Mei Zhang", - "author_inst": "University of Science and Technology of China" - }, - { - "author_name": "Jingxue Yao", - "author_inst": "University of Science and Technology of China" + "author_name": "Sofia Al Farizi", + "author_inst": "Universitas Airlangga Fakultas Kedokteran" }, { - "author_name": "Hongliang He", - "author_inst": "University of Science and Technology of China" + "author_name": "Dewi Al Setyowati", + "author_inst": "Airlangga University Faculty of Medicine: Universitas Airlangga Fakultas Kedokteran" }, { - "author_name": "Changjiang Jin", - "author_inst": "University of Science and Technology of China" + "author_name": "Fatmaningrum Ayu Dyah", + "author_inst": "Airlangga University Faculty of Medicine: Universitas Airlangga Fakultas Kedokteran" }, { - "author_name": "Tian Xue", - "author_inst": "University of Science and Technology of China" - }, - { - "author_name": "Changcheng Zheng", - "author_inst": "University of Science and Technology of China" + "author_name": "Azra Fauziyah Azyanti", + "author_inst": "Airlangga University Faculty of Medicine: Universitas Airlangga Fakultas Kedokteran" }, { - "author_name": "Tengchuan Jin", - "author_inst": "University of Science and Technology of China" - }, - { - "author_name": "Dali Tong", - "author_inst": "University of Science and Technology of China" + "author_name": "Candrakirana Kusuma Rahayu", + "author_inst": "Airlangga University Faculty of Medicine: Universitas Airlangga Fakultas Kedokteran" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "obstetrics and gynecology" }, { "rel_doi": "10.1101/2023.02.26.23286471", @@ -90295,59 +89481,47 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2023.02.23.23286374", - "rel_title": "Application of comprehensive evaluation framework to Coronavirus Disease 19 studies: A systematic review of translational aspects of artificial intelligence in health care", - "rel_date": "2023-02-26", + "rel_doi": "10.1101/2023.02.22.23286320", + "rel_title": "Bivalent COVID-19 vaccine antibody responses to Omicron variants suggest that responses to divergent variants would be improved with matched vaccine antigens", + "rel_date": "2023-02-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.23.23286374", - "rel_abs": "BackgroundDespite immense progress in artificial intelligence (AI) models, there has been limited deployment in healthcare environments. The gap between potential and actual AI applications is likely due to the lack of translatability between controlled research environments (where these models are developed) and clinical environments for which the AI tools are ultimately intended.\n\nObjectiveWe have previously developed the Translational Evaluation of Healthcare AI (TEHAI) framework to assess the translational value of AI models and to support successful transition to healthcare environments. In this study, we apply the TEHAI to COVID-19 literature in order to assess how well translational topics are covered.\n\nMethodsA systematic literature search for COVID-AI studies published between December 2019-2020 resulted in 3,830 records. A subset of 102 papers that passed inclusion criteria were sampled for full review. Nine reviewers assessed the papers for translational value and collected descriptive data (each study was assessed by two reviewers). Evaluation scores and extracted data were compared by a third reviewer for resolution of discrepancies. The review process was conducted on the Covidence software platform.\n\nResultsWe observed a significant trend for studies to attain high scores for technical capability but low scores for the areas essential for clinical translatability. Specific questions regarding external model validation, safety, non-maleficence and service adoption received failed scores in most studies.\n\nConclusionsUsing TEHAI, we identified notable gaps in how well translational topics of AI models are covered in the COVID-19 clinical sphere. These gaps in areas crucial for clinical translatability could, and should, be considered already at the model development stage to increase translatability into real COVID-19 healthcare environments.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.22.23286320", + "rel_abs": "We compared neutralizing antibody responses to BA.4/5, BQ.1.1, XBB, and XBB.1.5 Omicron SARS-CoV-2 variants after a bivalent or ancestral COVID-19 mRNA booster vaccine or post-vaccination infection. We found that the bivalent booster elicited moderately high antibody titers against BA.4/5 that were approximately two-fold higher against all Omicron variants than titers elicited by the monovalent booster. The bivalent booster elicited low but similar titers against both XBB and XBB.1.5 variants. These findings inform risk assessments for future COVID-19 vaccine recommendations and suggest that updated COVID-19 vaccines containing matched vaccine antigens to circulating divergent variants may be needed.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Aaron E Casey", - "author_inst": "South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia." - }, - { - "author_name": "Saba Ansari", - "author_inst": "School of Medicine, Deakin University, Geelong, Victoria, Australia" - }, - { - "author_name": "Bahareh Nakisa", - "author_inst": "School of Information Technology, Deakin University, Geelong, Victoria, Australia" - }, - { - "author_name": "Blair Kelly", - "author_inst": "Library, Deakin University, Geelong, Victoria, Australia" + "author_name": "Wei Wang", + "author_inst": "US Food and Drug Administraion" }, { - "author_name": "Pieta Brown", - "author_inst": "Orion Health, Auckland, Auckland, New Zealand" + "author_name": "Emilie Goguet", + "author_inst": "Uniformed Services University of the Health Sciences" }, { - "author_name": "Paul Cooper", - "author_inst": "School of Medicine, Deakin University, Geelong, Victoria, Australia" + "author_name": "Stephanie Paz Padilla", + "author_inst": "US Food and Drug Administration" }, { - "author_name": "Imran Muhammad", - "author_inst": "School of Medicine, Deakin University, Geelong, Victoria, Australia" + "author_name": "Russell Vassell", + "author_inst": "US Food and Drug Administration" }, { - "author_name": "Steven Livingstone", - "author_inst": "Orion Health, Auckland, Auckland, New Zealand" + "author_name": "Simon Pollett", + "author_inst": "Uniformed Services University of the Health Sciences" }, { - "author_name": "Sandeep Reddy", - "author_inst": "School of Medicine, Deakin University, Geelong, Victoria, Australia" + "author_name": "Edward Mitre", + "author_inst": "Uniformed Services University of the Health Sciences" }, { - "author_name": "Ville-Petteri E Makinen", - "author_inst": "South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia" + "author_name": "Carol Weiss", + "author_inst": "US Food and Drug Administration" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.02.19.23286159", @@ -92145,43 +91319,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.02.23.23286336", - "rel_title": "Event Rate and Predictors of Post-Acute COVID-19 Sequalae and the Average Time to Diagnosis in General Population", + "rel_doi": "10.1101/2023.02.20.23286166", + "rel_title": "Longitudinal Humoral and Cell-Mediated Immune Responses in a Population-Based Cohort in Zurich, Switzerland between March and June 2022 - Evidence for Protection against Omicron SARS-CoV-2 Infection by Neutralizing Antibodies and Spike-specific T cell responses", "rel_date": "2023-02-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.23.23286336", - "rel_abs": "BackgroundPost- COVID-19 sequalae involves a variety of new, returning or ongoing symptoms that people experience more than four weeks after getting COVID-19. The aims of this meta-analysis were to assess the prevalence of Post-Acute COVID-19 sequalae and estimate the average time to its diagnosis; and meta-regress for possible moderators.\n\nMethodsA standard search strategy was used in PubMed, and then later modified according to each specific database. Search terms included \"long COVID-19 or post-acute COVID-19 syndrome/sequalae\". The criteria for inclusion were published clinical articles reporting the long COVID-19, further, the average time to diagnosis of post-acute COVID-19 sequelae among primary infected patients with COVID-19. Random-effects model was used. Rank Correlation and Eggers tests were used to ascertain publication bias. Sub-group, sensitivity and meta-regression analysis were conducted. A 95% confidence intervals were presented and a p-value < 0.05 was considered statistically significant. Review Manager 5.4 and comprehensive meta-analysis version 4 (CMA V4) were used for the analysis. The trial was PROSPERO registered (CRD42022328509).\n\nResultsPrevalence of post-acute COVID-19 sequalae was 42.5% (95% confidence interval (CI) 36 % to 49.3%). The PACS event rates range was 25 % at four months and 66 % at two months and mostly, signs and symptoms of PASC were experienced at three (54.3%, P < 0.0001) to six months (57%, P < 0.0001), further increasing at 12 months (57.9%, P= 0.0148). At an average of two months, however with the highest event rate (66%), it was not significantly associated with PACS diagnosis (P=0.08). On meta-regression, comorbidities collectively contributed to 14% of PACS with a non-significant correlation (Q = 7.05, df = 8, p = 0.5313) (R2=0.14). A cardiovascular disorder especially hypertension as a stand-alone, showed an event rate of 32% and significantly associated with PACS, 0.322 (95% CI 0.166, 0.532) (P < 0.001). Chronic obstructive pulmonary disorder (COPD) and abnormal basal metabolic index (BMI) had higher event rates of PACS (59.8 % and 55.9 %) respectively, with a non-significant correlation (P > 0.05). With a significant association, hospital re-admission contributed to 17% (Q = 8.70, df = 1, p = 0.0032) (R2= 0.17) and the study design 26% (Q = 14.32, df = 3, p = 0.0025) (R2=0.26). All the covariates explained at least some of the variance in effect size on PACS at 53% (Q = 38.81, df = 19, p = 0.0047) (R2 analog = 0.53).\n\nConclusionThe prevalence of PACS in general population was 42.5%, of which cardiovascular disorders were highly linked with it with COPD and abnormal BMI also being possible conditions found in patients with PACS. Hospital re-admission predicted highly, an experience of PACS as well as prospective study design. Clinical and methodological characteristics in a specific study contributed to over 50% of PACS events. The PACS event rates ranged between 25 % at four months and 66 % at two months with most signs and symptoms experienced between three to six months increasing at 12 months.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.20.23286166", + "rel_abs": "BackgroundThe correlate(s) of protection against SARS-CoV-2 remain incompletely defined. Additional information regarding the combinations of antibody and T cell-mediated immunity which can protect against (re)infection are needed.\n\nMethodsWe conducted a population-based, longitudinal cohort study including 1044 individuals of varying SARS-CoV-2 vaccination and infection statuses. We assessed Spike (S)- and Nucleocapsid (N)-IgG and wildtype, delta, and omicron neutralizing antibodies. In a subset of 328 individuals, we evaluated S, Membrane (M) and N-specific T cells. 3 months later, we reassessed antibody (n=964) and T cell (n=141) responses and evaluated factors associated with protection from (re)infection.\n\nResultsAt study start, >98% of participants were S-IgG seropositive. N-IgG and M/N-T cell responses increased over time, indicating viral (re)exposure, despite existing S-IgG. Compared to N-IgG, M/N-T cells were a more sensitive measure of viral exposure. N-IgG titers in the top 33% of participants, omicron neutralizing antibodies in the top 25%, and S-specific T cell responses were all associated with reduced likelihood of (re)infection over time.\n\nConclusionsPopulation-level SARS-CoV-2 immunity is S-IgG-dominated, but heterogenous. M/N T cell responses can distinguish previous infection from vaccination, and monitoring a combination of N-IgG, omicron neutralizing antibodies and S-T cell responses may help estimate protection against SARS-CoV-2 (re)infection.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "JOHN KYALO MUTHUKA", - "author_inst": "KENYA MEDICAL TRAINING COLLEGE" + "author_name": "Kyra D Zens", + "author_inst": "University of Zurich" }, { - "author_name": "Caleb Mutua M", - "author_inst": "Kenya Medical Training College" + "author_name": "Daniel Llanas-Cornejo", + "author_inst": "University of Zurich" }, { - "author_name": "Japheth Nzioki Mativo", - "author_inst": "Jumeira University" + "author_name": "Dominik Menges", + "author_inst": "University of Zurich" }, { - "author_name": "Rosemary Nabaweesi", - "author_inst": "Meharry Medical College" + "author_name": "Jan Fehr", + "author_inst": "University of Zurich" }, { - "author_name": "Michael Kibet Kiptoo Sr.", - "author_inst": "South Eastern Kenya University" + "author_name": "Christian Munz", + "author_inst": "University of Zurich" }, { - "author_name": "Kelly J. Oluoch", - "author_inst": "Kenya Medical Training College" + "author_name": "Milo Puhan", + "author_inst": "University of Zurich" + }, + { + "author_name": "Anja Frei", + "author_inst": "University of Zurich" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2023.02.23.23286342", @@ -93919,67 +93097,35 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.02.18.23286127", - "rel_title": "Antipsychotic prescribing and mortality in people with dementia before and during the COVID-19 pandemic: retrospective cohort study", + "rel_doi": "10.1101/2023.02.18.23285810", + "rel_title": "Barriers to access to antiretroviral therapy by people living with HIV in Indonesia during the COVID-19 pandemic: A qualitative study", "rel_date": "2023-02-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.18.23286127", - "rel_abs": "BackgroundAntipsychotic drugs have been associated with increased mortality, stroke and myocardial infarction in people with dementia. Concerns have been raised that antipsychotic prescribing may have increased during the COVID-19 pandemic due to social restrictions imposed to limit the spread of the virus. We used multisource, routinely-collected healthcare data from Wales, UK, to investigate prescribing and mortality trends in people with dementia before and during the COVID-19 pandemic.\n\nMethodsWe used individual-level, anonymised, population-scale linked health data to identify adults aged [≥]60 years with a diagnosis of dementia in Wales, UK. We explored antipsychotic prescribing trends over 67 months between 1st January 2016 and 1st August 2021, overall and stratified by age and dementia subtype. We used time series analyses to examine all-cause, myocardial infarction (MI) and stroke mortality over the study period and identified the leading causes of death in people with dementia.\n\nFindingsOf 57,396 people with dementia, 11,929 (21%) were prescribed an antipsychotic at any point during follow-up. Accounting for seasonality, antipsychotic prescribing increased during the second half of 2019 and throughout 2020. However, the absolute difference in prescribing rates was small, ranging from 1253 to 1305 per 10,000 person-months. Prescribing in the 60-64 age group and those with Alzheimers disease increased throughout the 5-year period. All-cause and stroke mortality increased in the second half of 2019 and throughout 2020 but MI mortality declined. From January 2020, COVID-19 was the second commonest underlying cause of death in people with dementia.\n\nInterpretationDuring the COVID-19 pandemic there was a small increase in antipsychotic prescribing in people with dementia. The long-term increase in antipsychotic prescribing in younger people and in those with Alzheimers disease warrants further investigation.\n\nFundingBritish Heart Foundation (BHF) (SP/19/3/34678) via the BHF Data Science Centre led by HDR UK, and the Scottish Neurological Research Fund.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched Ovid MEDLINE for studies describing antipsychotic prescribing trends in people with dementia during the COVID-19 pandemic, published between 1st January 2020 and 22nd March 2022. The following search terms were used: (exp Antipsychotic Agents/ OR antipsychotic.mp OR neuroleptic.mp OR risperidone.mp OR exp Risperidone/ OR quetiapine.mp OR exp Quetiapine Fumarate/ OR olanzapine.mp OR exp Olanzapine/ OR exp Psychotropic Drugs/ or psychotropic.mp) AND (exp Dementia/ OR exp Alzheimer Disease/ or alzheimer.mp) AND (prescri*.mp OR exp Prescriptions/ OR exp Electronic Prescribing/ OR trend*.mp OR time series.mp). The search identified 128 published studies, of which three were eligible for inclusion. Two studies, based on data from England and the USA, compared antipsychotic prescribing in people with dementia before and during the COVID-19 pandemic. Both reported an increase in the proportion of patients prescribed an antipsychotic after the onset of the pandemic. A third study, based in the Netherlands, reported antipsychotic prescription trends in nursing home residents with dementia during the first four months of the pandemic, comparing prescribing rates to the timings of lifting of social restrictions, showing that antipsychotic prescribing rates remained constant throughout this period.\n\nAdded value of this studyWe conducted age-standardised time series analyses using comprehensive, linked, anonymised, individual-level routinely-collected, population-scale health data for the population of Wales, UK. By accounting for seasonal variations in prescribing and mortality, we demonstrated that the absolute increase in antipsychotic prescribing in people with dementia of any cause during the COVID-19 pandemic was small. In contrast, antipsychotic prescribing in the youngest age group (60-64 years) and in people with a subtype diagnosis of Alzheimers disease increased throughout the five-year study period. Accounting for seasonal variation, all-cause mortality rates in people with dementia began to increase in late 2019 and increased sharply during the first few months of the pandemic. COVID-19 became the leading non-dementia cause of death in people with dementia from 2020 to 2021. Stroke mortality increased during the pandemic, following a similar pattern to that of all-cause mortality, whereas myocardial infarction rates decreased.\n\nImplications of all the available evidenceDuring COVID-19 we observed a large increase in all-cause and stroke mortality in people with dementia. When seasonal variations are accounted for, antipsychotic prescribing rates in all-cause dementia increased by a small amount before and during the pandemic in the UK. The increased prescribing rates in younger age groups and in people with Alzheimers disease warrants further investigation.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.18.23285810", + "rel_abs": "BackgroundThe coronavirus disease (COVID-19) pandemic has a significant influence on access to healthcare services. This study aimed to understand the views and experiences of people living with HIV (PLHIV) about barriers to their access to antiretroviral therapy (ART) service in Belu district, Indonesia, during the COVID-19 pandemic.\n\nMethodsThis qualitative inquiry employed in-depth interviews to collect data from 21 participants who were recruited using a snowball sampling technique. Data analysis was guided by a thematic framework analysis.\n\nResultsThe findings showed that fear of contracting COVID-19 was a barrier that impeded participants access to ART service. Such fear was influenced by their awareness of their vulnerability to the infection, the possibility of unavoidable physical contact in public transport during a travelling to HIV clinic and the widespread COVID-19 infection in healthcare facilities. Lockdowns, COVID-19 restrictions and lack of information about the provision of ART service during the pandemic were also barriers that impeded their access to the service. Other barriers included the mandatory regulation for travellers to provide their COVID-19 vaccine certificate, financial difficulty, long-distance travel to the HIV clinic and a lack of public transport.\n\nConclusionsThe findings indicate the need for dissemination of information about the provision of ART service during the pandemic and the benefits of COVID-19 vaccination for the health of PLHIV. The findings also indicate the need for new strategies to bring ART service closer to PLHIV during the pandemic such as a community-based delivery system. Future large-scale studies exploring views and experiences of PLHIV about barriers to their access to ART service during the COVID-19 pandemic and new intervention strategies are recommended.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Christian Schnier", - "author_inst": "University of Edinburgh" + "author_name": "Nelsensius Klau Fauk", + "author_inst": "Centre for Public Health, Equity and Human Flourishing (PHEHF), Torrens University Australia" }, { - "author_name": "Aoife McCarthy", - "author_inst": "University of Edinburgh" + "author_name": "Hailay Abhra Gesesew", + "author_inst": "Centre for Public Health, Equity and Human Flourishing (PHEHF), Torrens University Australia" }, { - "author_name": "Daniel R Morales", - "author_inst": "University of Dundee" + "author_name": "Alfonsa Liquory Seran", + "author_inst": "Atapupu Public Health Centre, Health Department of Belu District" }, { - "author_name": "Ashley Akbari", - "author_inst": "Swansea University" - }, - { - "author_name": "Reecha Sofat", - "author_inst": "University of Liverpool" - }, - { - "author_name": "Caroline Dale", - "author_inst": "University of Liverpool" - }, - { - "author_name": "Rohan Takhar", - "author_inst": "University College London" - }, - { - "author_name": "Mamas Mamas", - "author_inst": "Keele University" - }, - { - "author_name": "Kamlesh Khunti", - "author_inst": "University of Leicester" - }, - { - "author_name": "Francesco Zaccardi", - "author_inst": "University of Leicester" - }, - { - "author_name": "Cathie LM Sudlow", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Tim Wilkinson", - "author_inst": "University of Edinburgh" + "author_name": "Paul Russell Ward", + "author_inst": "Centre for Public Health, Equity and Human Flourishing (PHEHF), Torrens University Australia" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "hiv aids" }, { "rel_doi": "10.1101/2023.02.18.23286136", @@ -95629,71 +94775,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.02.15.23285976", - "rel_title": "Factors associated with adverse outcomes among patients hospitalized at a COVID-19 treatment center run by Medecins sans Frontieres in Herat, Afghanistan", + "rel_doi": "10.1101/2023.02.15.528742", + "rel_title": "Construction of Fosmid-based SARS-CoV-2 replicons for antiviral drug screening and replication analyses in biosafety level 2 facilities", "rel_date": "2023-02-16", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.15.23285976", - "rel_abs": "BackgroundThough many studies on COVID have been published to date, data on COVID-19 epidemiology, symptoms, risk factors and severity in low- and middle-income countries (LMICS), such as Afghanistan are sparse.\n\nObjectiveTo describe clinical characteristics, severity, and outcomes of patients hospitalized in the MSF COVID-19 treatment center (CTC) in Herat, Afghanistan and to assess risk factors associated with severe outcomes.\n\nMethods1113 patients were included in this observational study between June 2020 and April 2022. Descriptive analysis was performed on clinical characteristics, complications, and outcomes of patients. Univariate description by Cox regression to identify risk factors for an adverse outcome was performed. Adverse outcome was defined as death or transfer to a level 3 intensive care located at another health facility. Finally, factors identified were included in a multivariate Cox survival analysis.\n\nResultsA total of 165 patients (14.8%) suffered from a severe disease course, with a median time of 6 days (interquartile range: 2-11 days) from admission to adverse outcome. In our multivariate model, we identified male gender, age over 50, high O2 flow administered during admission, lymphopenia, anemia and O2 saturation <=93% during the first three days of admission as predictors for a severe disease course (p<0.05).\n\nConclusionOur analysis concluded in a relatively low rate of adverse outcomes of 14.8%. This is possibly related to the fact, that the resources at an MSF-led facility are higher, in terms of human resources as well as supply of drugs and biomedical equipment, including oxygen therapy devices, compared to local hospitals. Predictors for severe disease outcomes were found to be comparable to other settings.", - "rel_num_authors": 13, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.02.15.528742", + "rel_abs": "The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has necessitated the global development of countermeasures since its outbreak. However, current therapeutics and vaccines to stop the pandemic are insufficient and this is mainly because of the emergence of resistant variants, which requires the urgent development of new countermeasures, such as antiviral drugs. Replicons, self-replicating RNAs that do not produce virions, are a promising system for this purpose because they safely recreate viral replication, enabling antiviral screening in biosafety level (BSL)-2 facilities. We herein constructed three pCC2Fos-based RNA replicons lacking some open reading frames (ORF) of SARS-CoV-2: the {Delta}orf2-8, {Delta}orf2.4, and {Delta}orf2 replicons, and validated their replication in Huh-7 cells. The functionalities of the {Delta}orf2-8 and {Delta}orf2.4 replicons for antiviral drug screening were also confirmed. We conducted puromycin selection following the construction of the {Delta}orf2.4-puro replicon by inserting a puromycin-resistant gene into the {Delta}orf2.4 replicon. We observed the more sustained replication of the {Delta}orf2.4-puro replicon by puromycin pressure. The present results will contribute to the establishment of a safe and useful replicon system for analyzing SARS-CoV-2 replication mechanisms as well as the development of novel antiviral drugs in BSL-2 facilities.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Ana klein", - "author_inst": "Epicentre" - }, - { - "author_name": "Mathieu Bastard", - "author_inst": "Epicentre" - }, - { - "author_name": "Hamayoun Hemat", - "author_inst": "MSF-USA: Doctors Without Borders" - }, - { - "author_name": "Saschveen Singh", - "author_inst": "MSF-USA: Doctors Without Borders" - }, - { - "author_name": "Bruno Muniz", - "author_inst": "MSF-USA: Doctors Without Borders" - }, - { - "author_name": "Guyguy Manangama", - "author_inst": "MSF-USA: Doctors Without Borders" - }, - { - "author_name": "Amber Alayyan", - "author_inst": "MSF-USA: Doctors Without Borders" - }, - { - "author_name": "Abdul Hakim Tamanna", - "author_inst": "Islamic Republic of Afghanistan Ministry of Public Health" - }, - { - "author_name": "Bashir Barakzaie", - "author_inst": "Islamic Republic of Afghanistan Ministry of Public Health" + "author_name": "Shunta Takazawa", + "author_inst": "Department of Public Health, Kobe University Graduate School of Health Sciences" }, { - "author_name": "Nargis Popal", - "author_inst": "Islamic Republic of Afghanistan Ministry of Public Health" + "author_name": "Tomohiro Kotaki", + "author_inst": "Osaka University: Osaka Daigaku" }, { - "author_name": "Mohammad Azeem Zmarial Kakar", - "author_inst": "Islamic Republic of Afghanistan Ministry of Public Health" + "author_name": "Satsuki Nakamura", + "author_inst": "Department of Public Health, Kobe University Graduate School of Health Sciences" }, { - "author_name": "Elisabeth Poulet", - "author_inst": "Epicentre" + "author_name": "Chie Utsubo", + "author_inst": "Department of Public Health, Kobe University Graduate School of Health Sciences" }, { - "author_name": "Flavio Finger", - "author_inst": "Epicentre" + "author_name": "Masanori Kameoka", + "author_inst": "Kobe University Graduate School of Health Sciences" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_no", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2023.02.16.23286008", @@ -97567,45 +96681,105 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.02.08.23285446", - "rel_title": "Use of machine learning for triage and transfer of ICU patients in the Covid-19 pandemic period: Scope Review", + "rel_doi": "10.1101/2023.02.11.23285507", + "rel_title": "Impact of COVID-19 Outbreak on Healthcare Workers in a Tertiary Healthcare Center in India - A cross sectional study", "rel_date": "2023-02-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.08.23285446", - "rel_abs": "ObjectiveTo map, summarize and analyze the available studies on the use of artificial intelligence, for both triage and transfer of patients in intensive care units in situations of bed shortage crisis so that health teams and organizations make decisions based on updated technological tools of triage and transfer.\n\nMethodsScope review made in the databases Pubmed, Embase, Web of Science, CINAHL, Cochrane, LILACS, Scielo, IEEE, ACM and the novel Rayyan Covid database were searched. Supplementary studies were searched in the references of the identified primary studies. The time restriction is from 2020, and there was no language restriction. All articles aiming at the use of machine learning within the field of artificial intelligence in healthcare were included, as well as studies using data analysis for triage and reallocation of elective patients to ICU vacancies within the specific context of crises, pandemics, and Covid-19 outbreak. Studies involving readmission of patients were excluded.\n\nResultsThe results excluded specific triage such as oncological patients, emergency room, telemedicine and non structured data.\n\nConclusionMachine learning can help ICU triage, bed management and patient transfer with the use of artificial intelligence in situations of crisis and outbreaks.\n\nDescriptorsArtificial Intelligence. Machine learning. Intensive Care Units. Triage. Patient Transfer. COVID-19.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.11.23285507", + "rel_abs": "Numerous speculations have continually emerged, trying to explore the association between COVID-19 infection and a varied range of demographic and clinical factors. Frontline healthcare workers have been at the forefront of this illness exposure. However, there is a paucity of large cohort-based association studies, performed among Indian health care professionals, exploring their potential risk and predisposing factors. This study aims to systematically utilize the demographic and clinical data of over 3000 healthcare workers from a tertiary hospital in India to gain significant insights on the associations between disease prevalence, severity, and post-infection symptoms.\n\nArticle SummaryPotential associations between various demographic and clinical factors with disease severity and post COVID syndromes among a large cohort of healthcare workers in India suggest that Smokers were discovered to be more vulnerable to COVID-19 infection because of their immunocompromised lung health and Blood group B, like previous studies, was found to possess an increased risk of predisposition to long COVIDs", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Lia Da Graca", - "author_inst": "UNIFESP" + "author_name": "Shahzad Mirza", + "author_inst": "Dr. D.Y. Patil Medical College" }, { - "author_name": "Lucio Padrini Andrade", - "author_inst": "UNIFESP" + "author_name": "Arvinden VR", + "author_inst": "CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB)" }, { - "author_name": "Richarlisson Borges Moraes", - "author_inst": "UNIFESP" + "author_name": "Mercy Rophina", + "author_inst": "Institute of Genomics and Integrative Biology" }, { - "author_name": "Anacleta Rodrigues Lima", - "author_inst": "UNIFESP" + "author_name": "Jitendra Bhawalkar", + "author_inst": "Dr. D.Y. Patil Medical College" }, { - "author_name": "Hugo Fernandes", - "author_inst": "UNIFESP" + "author_name": "Bhavin Chothani", + "author_inst": "Dr. D.Y. Patil Medical College" }, { - "author_name": "Alexandre Barbosa Lima", - "author_inst": "PUC" + "author_name": "Uzair Khan", + "author_inst": "Dr. D.Y. Patil Medical College" }, { - "author_name": "Monica Taminato", - "author_inst": "UNIFESP" + "author_name": "Shivankur Singh", + "author_inst": "Dr. D.Y. Patil Medical College" + }, + { + "author_name": "Tanya Sharma", + "author_inst": "Dr. D.Y. Patil Medical College" + }, + { + "author_name": "Aryan Dwivedi", + "author_inst": "Dr. D.Y. Patil Medical College" + }, + { + "author_name": "Ellora Pandey", + "author_inst": "Dr. D.Y. Patil Medical College" + }, + { + "author_name": "Shivam Garg", + "author_inst": "Dr. D.Y. Patil Medical College" + }, + { + "author_name": "Mukhida Sahjid Sadrudin", + "author_inst": "Dr. D.Y. Patil Medical College" + }, + { + "author_name": "Zeeshan Shabbir Ahmed Sange", + "author_inst": "Dr. D.Y. Patil Medical College" + }, + { + "author_name": "Shalini Bhaumik", + "author_inst": "Dr. D.Y. Patil Medical College" + }, + { + "author_name": "Jessin Varughese", + "author_inst": "Dr. D.Y. Patil Medical College" + }, + { + "author_name": "Vishwamohini Yallappa Devkar", + "author_inst": "Dr. D.Y. Patil Medical College" + }, + { + "author_name": "Jyoti Singh", + "author_inst": "Dr. D.Y. Patil Medical Hospital" + }, + { + "author_name": "Anju mol V K", + "author_inst": "Dr. D.Y. Patil Medical College" + }, + { + "author_name": "Veena K", + "author_inst": "Dr. D.Y. Patil Medical College" + }, + { + "author_name": "Husen Shabbir Husen Mandviwala", + "author_inst": "Dr. D.Y. Patil Medical College" + }, + { + "author_name": "Vinod Scaria", + "author_inst": "CSIR Institute of Genomics & Integrative Biology" + }, + { + "author_name": "Aayush Gupta", + "author_inst": "Dr. D.Y. Patil Medical College" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "health informatics" }, @@ -99281,43 +98455,47 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2023.02.06.23285543", - "rel_title": "Characteristics of COVID-19 in children and potential risk factors for requiring mechanical ventilation; an analysis of 22,490 cases from the United States", + "rel_doi": "10.1101/2023.02.06.23285535", + "rel_title": "Machine-learning-aided multiplexed nanobiosensor for COVID-19 population immunity profiling", "rel_date": "2023-02-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.06.23285543", - "rel_abs": "The pandemic of Coronavirus disease 2019 (COVID-19) has lasted more than two years and caused millions of deaths. While the characteristics and outcomes have been more widely studied in the adult population, we conducted an in-depth analysis via the 2020 National Inpatient Sample to understand the characteristics and predictors for the use of mechanical ventilation in patients of ages 18 and less in the United States. Twenty-two thousand four hundred ninety hospitalizations involving COVID-19-positive children were found. 52.7% (11850 cases) were females, 37.0% were Hispanics, 38.0% (8555 cases) were in the first percentile 0-25th of Median household income, and 66.9% used Medicaid. In total, 1140 cases (5.1%) needed mechanical ventilation. Among factors such as obesity (aOR 1.662, 95%CI 1.368-2.019, p<0.001), Blacks (vs. White) (aOR 1.472, 95%CI 1.23-1.761, p<0.001), private insurances (aOR 1.241, 95%CI 1.06-1.453, p=0.007) or remaining forms of payment other than Medicaid or private insurances (aOR 1.763, 95%CI 1.428-2.177, p<0.001, vs. Medicaid), ages 6 to 10 years (aOR 1.531, 95%CI 1.259-1.862, p<0.001, vs. ages 0-5) showed higher odds of needing mechanical ventilation. On the contrary, Females (aOR 0.54, 95%CI 0.472-0.617, p<0.001, vs. Males), hospitalized patients in November (aOR 0.542, 95%CI 0.399-0.736, p<0.001) and December (aOR 0.446, 95%CI 0.329-0.606, p<0.001) (vs. April), Hispanics (aOR 0.832, 95%CI 0.699-0.99, p=0.038, vs. White), ages 16-18 years (aOR 0.804, 95%CI 0.673-0.96, p=0.016, vs. 0-5years), and in the 76th-100th median household income percentile (aOR 0.783, 95%CI 0.628-0.976, p=0.03, vs. 0-25th percentile) showed reduced odds. 9.6% of patients on mechanical ventilation died.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.06.23285535", + "rel_abs": "Serological population surveillance can elucidate immunity landscapes against SARS-CoV-2 variants and are critical in monitoring infectious disease spread, evolution, and outbreak risks. However, current serological tests fall short of capturing complex humoral immune responses from different communities. Here, we report a machine-learning (ML)-aided nanobiosensor that can simultaneously quantify antibodies against the ancestral strain and Omicron variants of SARS-CoV-2 with epitope resolution. Our approach is based on a multiplexed, rapid, and label-free nanoplasmonic biosensor, which can detect past infection and vaccination status and is sensitive to SARS-CoV-2 variants. After training an ML model with antigen-specific antibody datasets from four COVID-19 immunity groups (naive, convalescent, vaccinated, and convalescent-vaccinated), we tested our approach on 100 blind blood samples collected in Dane County, WI. Our results are consistent with public epidemiological data, demonstrating that our user-friendly and field-deployable nanobiosensor can capture community-representative public health trends and help manage COVID-19 and future outbreaks.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Renuka Verma", - "author_inst": "Guru Gobind Singh Medical College, Punjab, India" + "author_name": "Aidana Beisenova", + "author_inst": "University of Wisconsin Madison" }, { - "author_name": "Kamleshun Ramphul", - "author_inst": "Independent Researcher, Mauritius" + "author_name": "Wihan Adi", + "author_inst": "University of Wisconsin Madison" }, { - "author_name": "Petras Lohana", - "author_inst": "Department of Nephrology, Jacobi Medical Centre, Bronx, New York" + "author_name": "S. Janna Bashar", + "author_inst": "University of Wisconsin Madison" }, { - "author_name": "Shaheen Sombans", - "author_inst": "Department of Pediatrics, Bharati Vidyapeeth Univ Med College and Hosp, Hyderabad, India" + "author_name": "Monniiesh Velmurugan", + "author_inst": "University of Wisconsin Madison" }, { - "author_name": "Yogeshwaree Ramphul", - "author_inst": "Sir Seewoosagur Ramgoolam National Hospital, Mauritius" + "author_name": "Kenzie B. Germanson", + "author_inst": "University of Wisconsin Madison" }, { - "author_name": "Prince Kwabla K Pekyi-Boateng", - "author_inst": "Greater Accra Regional Hospital" + "author_name": "Miriam A Shelef", + "author_inst": "University of Wisconsin Madison" + }, + { + "author_name": "Filiz Yesilkoy", + "author_inst": "University of Wisconsin Madison" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.02.06.23285542", @@ -100875,39 +100053,119 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.02.07.527501", - "rel_title": "Macrodomain Mac1 of SARS-CoV-2 Nonstructural Protein 3 Hydrolyzes Diverse ADP-ribosylated Substrates", + "rel_doi": "10.1101/2023.02.07.527406", + "rel_title": "Neutralization of SARS-CoV-2 BQ.1.1 and XBB.1.5 by Breakthrough Infection Sera from Previous and Current Waves in China", "rel_date": "2023-02-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.02.07.527501", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for a global pandemic that resulted in more than 6-million deaths worldwide. The virus encodes several non-structural proteins (Nsps) that contain elements capable of disrupting cellular processes. Among these Nsp proteins, Nsp3 contains macrodomains, e.g., Mac1, Mac2, Mac3, with potential effects on host cells. Mac1 has been shown to increase SARS-CoV-2 virulence and disrupt ADP-ribosylation pathways in mammalian cells. ADP-ribosylation results from the transfer of the ADP-ribose moiety of NAD+ to various acceptors, e.g., proteins, DNA, RNA, contributing on a cells biological processes. ADP-ribosylation is the mechanism of action of bacterial toxins, e.g., Pseudomonas toxins, diphtheria toxin that disrupt protein biosynthetic and signaling pathways. On the other hand, some viral macrodomains cleavage ADP-ribose-acceptor bond, generating free ADP-ribose. By this reaction, the macrodomain-containing proteins interfere ADP-ribose homeostasis in host cells. Here, we examined potential hydrolytic activities of SARS-CoV-2 Mac1, 2, and 3 on substrates containing ADP-ribose. Mac1 cleaved -NAD+, but not {beta}-NAD+, consistent with stereospecificity at the C-1\" bond. In contrast to ARH1 and ARH3, Mac1 did not require Mg2+ for optimal activity. Mac1 also hydrolyzed O-acetyl-ADP-ribose and ADP-ribose-1\"-phosphat, but not Mac2 and Mac3. However, Mac1 did not cleave -ADP-ribose-(arginine) and ADP-ribose-(serine)-histone H3 peptide, suggesting that Mac1 hydrolyzes ADP-ribose attached to O- and N-linked functional groups, with specificity at the catalytic site in the ADP-ribose moiety. We conclude that SARS-CoV-2 Mac1 may exert anti-viral activity by reversing host-mediated ADP-ribosylation. New insights on Nsp3 activities may shed light on potential SARS-CoV-2 therapeutic targets.\n\nIMPORTANCESARS-CoV-2, the virus responsible for COVID-19, encodes 3 macrodomain-containing proteins, e.g., Mac1, Mac2, Mac3, within non-structural proteins 3 (Nsp3). Mac1 was shown previously to hydrolyze ADP-ribose-phosphate. Inactivation of Mac1 reduced viral proliferation. Here we report that Mac1, but not Mac2 and Mac3, has multiple activities, i.e., Mac1 hydrolyzed. -NAD+ and O-acetyl-ADP-ribose. However, Mac1 did not hydrolyze {beta}-NAD+, ADP-ribose-serine on a histone 3 peptide (aa1-21), and ADP-ribose-arginine, exhibiting substrate selectivity. These data suggest that Mac1 may have multi-function as a -NAD+ consumer for viral replication and a disruptor of host-mediated ADP-ribosylation pathways. Understanding Mac1s mechanisms of action is important to provide possible therapeutic targets for COVID-19.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.02.07.527406", + "rel_abs": "SARS-CoV-2 is continuing to evolve and diversify, with an array of various Omicron sub-lineages, including BA.5, BA.2.75, BN.1, BF.7, BQ.1, BQ.1.1, XBB and XBB.1.5, now circulating globally at recent time. In this study, we evaluated the neutralization sensitivity of a comprehensive panel of Omicron subvariants to sera from different clinical cohorts, including individuals who received homologous or heterologous booster vaccinations, vaccinated people who had Delta or BA.2 breakthrough infection in previous waves, and patients who had BA.5 or BF.7 breakthrough infection in the current wave in China. All the Omicron subvariants exhibited substantial neutralization evasion, with BQ.1, BQ.1.1, XBB.1, and XBB.1.5 being the strongest escaped subvariants. Sera from Omicron breakthrough infection, especially the recent BA.5 or BF.7 breakthrough infection, exhibited higher neutralizing activity against all Omicron sub-lineages, indicating the chance of BA.5 and BF.7 being entirely replaced by BQ or XBB subvariants in China in a short-term might be low. We also demonstrated that the BQ and XBB subvariants were the most resistant viruses to monoclonal antibodies. Continuing to monitor the immune escape of SARS-CoV-2 emerging variants and developing novel broad-spectrum vaccines and antibodies are still crucial.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Chanbora Chea", - "author_inst": "National Institutes of Health" + "author_name": "Xun Wang", + "author_inst": "Fudan University" }, { - "author_name": "Duck-Yeon Lee", - "author_inst": "NHLBI, NIH" + "author_name": "Shuai Jiang", + "author_inst": "Fudan University" }, { - "author_name": "JIro Kato", - "author_inst": "NHLBI, NIH" + "author_name": "Shujun Jiang", + "author_inst": "Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine" }, { - "author_name": "Hiroko Ishiwata-Endo", - "author_inst": "NIH" + "author_name": "Xiangnan Li", + "author_inst": "Fudan University" }, { - "author_name": "Joel Moss", - "author_inst": "National Institutes of Health" + "author_name": "Jingwen Ai", + "author_inst": "Huashan Hospital, Fudan University" + }, + { + "author_name": "Ke Lin", + "author_inst": "Huashan Hospital, Fudan University" + }, + { + "author_name": "Shiyuan Lv", + "author_inst": "Beijing Youan Hospital, Capital Medical University" + }, + { + "author_name": "Shixuan Zhang", + "author_inst": "Fudan University" + }, + { + "author_name": "Minghui Li", + "author_inst": "Fudan University" + }, + { + "author_name": "Xinyi He", + "author_inst": "Fudan University" + }, + { + "author_name": "Dingding Li", + "author_inst": "Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine" + }, + { + "author_name": "Chen Li", + "author_inst": "Fudan University" + }, + { + "author_name": "Chaoyue Zhao", + "author_inst": "Fudan University" + }, + { + "author_name": "Xiaoyu Zhao", + "author_inst": "Fudan University" + }, + { + "author_name": "Rui Qiao", + "author_inst": "Fudan University" + }, + { + "author_name": "Yuchen Cui", + "author_inst": "Fudan University" + }, + { + "author_name": "Yanjia Chen", + "author_inst": "Fudan University" + }, + { + "author_name": "Jiayan Li", + "author_inst": "Fudan University" + }, + { + "author_name": "Guonan Cai", + "author_inst": "Fudan University" + }, + { + "author_name": "Jixi Li", + "author_inst": "Fudan University" + }, + { + "author_name": "Lili Dai", + "author_inst": "Beijing Youan Hospital, Capital Medical University" + }, + { + "author_name": "Zixin Hu", + "author_inst": "Fudan University" + }, + { + "author_name": "Wenhong Zhang", + "author_inst": "Huashan Hospital, Fudan University" + }, + { + "author_name": "Yanliang Zhang", + "author_inst": "Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine" + }, + { + "author_name": "Pengfei Wang", + "author_inst": "Fudan University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "biochemistry" + "category": "immunology" }, { "rel_doi": "10.1101/2023.02.05.527173", @@ -102677,33 +101935,73 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.01.31.23285246", - "rel_title": "Correlates of symptomatic remission among individuals with post-COVID-19 condition", + "rel_doi": "10.1101/2023.01.30.23285195", + "rel_title": "The emergence of SARS-CoV-2 lineages and associated antibody responses among asymptomatic individuals in a large university community", "rel_date": "2023-02-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.31.23285246", - "rel_abs": "ImportancePost-COVID-19 condition (PCC), or long COVID, has become prevalent. The course of this syndrome, and likelihood of remission, has not been characterized.\n\nObjectiveTo quantify the rates of remission of PCC, and the sociodemographic features associated with remission.\n\nDesign16 waves of a 50-state U.S. non-probability internet survey conducted between August 2020 and November 2022\n\nSettingPopulation-based\n\nParticipantsSurvey respondents age 18 and older\n\nMain Outcome and MeasurePCC remission, defined as reporting full recovery from COVID-19 symptoms among individuals who on a prior survey wave reported experiencing continued COVID-19 symptoms beyond 2 months after the initial month of symptoms.\n\nResultsAmong 423 survey respondents reporting continued symptoms more than 2 months after acute test-confirmed COVID-19 illness, who then completed at least 1 subsequent survey, mean age was 53.7 (SD 13.6) years; 293 (69%) identified as women, and 130 (31%) as men; 9 (2%) identified as Asian, 29 (7%) as Black, 13 (3%) as Hispanic, 15 (4%) as another category including Native American or Pacific Islander, and the remaining 357 (84%) as White. Overall, 131/423 (31%) of those who completed a subsequent survey reported no longer being symptomatic. In Cox regression models, male gender, younger age, lesser impact of PCC symptoms at initial visit, and infection when the Omicron strain predominated were all statistically significantly associated with greater likelihood of remission; presence of brain fog or shortness of breath were associated with lesser likelihood of remission.\n\nConclusions and RelevanceA minority of individuals reported remission of PCC symptoms, highlighting the importance of efforts to identify treatments for this syndrome or means of preventing it.\n\nTrial registrationN/A\n\nKey PointsO_ST_ABSQuestionC_ST_ABSHow often do individuals with post-COVID-19 condition, or long COVID, recover fully, and what predicts this recovery?\n\nFindingsAmong 423 individuals who initially reported post-COVID-19 condition and completed at least one subsequent survey, 131 (31%) later described symptomatic remission. Younger age, male gender, lesser symptom severity at initial survey, and infection during Omicron-predominance were associated with greater likelihood of reporting recovery.\n\nMeaningA minority of people with post-COVID-19 condition report spontaneous remission of symptoms, highlighting the importance of developing treatments for this syndrome.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.30.23285195", + "rel_abs": "SARS-CoV-2 (CoV2) infected, asymptomatic individuals are an important contributor to COVID transmission. CoV2-specific immunoglobulin (Ig)--as generated by the immune system following infection or vaccination--has helped limit CoV2 transmission from asymptomatic individuals to susceptible populations (e.g. elderly). Here, we describe the relationships between COVID incidence and CoV2 lineage, viral load, saliva Ig levels (CoV2-specific IgM, IgA and IgG) and inhibitory capacity in asymptomatic individuals between Jan 2021 and May 2022. These data were generated as part of a large university COVID monitoring program and demonstrate that COVID incidence among asymptomatic individuals occurred in waves which mirrored those in surrounding regions, with saliva CoV2 viral loads becoming progressively higher in our community until vaccine mandates were established. Among the unvaccinated, infection with each CoV2 lineage (pre-Omicron) resulted in saliva Spike-specific IgM, IgA and IgG responses, the latter increasing significantly post-infection and being more pronounced than N-specific IgG responses. Vaccination resulted in significantly higher Spike-specific IgG levels compared to unvaccinated infected individuals, and uninfected vaccinees saliva was more capable of inhibiting Spike function. Vaccinees with breakthrough Delta infections had Spike-specific IgG levels comparable to those of uninfected vaccinees; however, their ability to inhibit Spike binding was diminished. These data demonstrate that COVID vaccines achieved hoped-for effects in our community, including the generation of mucosal antibodies that inhibit Spike and lower community viral loads, and suggest breakthrough Delta infections were not due to an absence of vaccine-elicited Ig, but instead limited Spike binding activity in the face of high community viral loads.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Roy H Perlis", - "author_inst": "Massachusetts General Hospital" + "author_name": "Marlena R Merling", + "author_inst": "The Ohio State University" }, { - "author_name": "Mauricio Santillana", - "author_inst": "Northeastern University" + "author_name": "Amanda Williams", + "author_inst": "The Ohio State University" }, { - "author_name": "Katherine Ognyanova", - "author_inst": "Rutgers University" + "author_name": "Najmus Mahfooz", + "author_inst": "The Ohio State University" }, { - "author_name": "David Lazer", - "author_inst": "Northeastern University" + "author_name": "Marisa Ruane-Foster", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Jacob Smith", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Jeff Jahnes", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Leona Ayers", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Jose Bazan", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Alison Norris", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Abigail Norris Turner", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Michael Oglesbee", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Seth Faith", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Mikkel Quam", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Richard T Robinson", + "author_inst": "The Ohio State University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -104715,27 +104013,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.01.26.23285052", - "rel_title": "A Case Report of a COVID-19 Infection with Positive Sputum and Negative Nasopharyngeal Rapid Antigen-Based Testing: A Practical Method to Explore Sputome", + "rel_doi": "10.1101/2023.01.27.23285043", + "rel_title": "A large-scale machine learning study of sociodemographic factors contributing to COVID-19 severity", "rel_date": "2023-01-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.26.23285052", - "rel_abs": "Current COVID-19 antigen testing is primarily carried out by obtaining a specimen via nasopharyngeal swab and performing a rapid lateral flow immunoassay (LFIA) or related immunoassays. On average, a nasopharyngeal antigen-based LFIA for COVID-19 remains positive for approximately one week from symptom onset, and levels of infectivity and duration of the symptoms may depend primarily on carrying a high viral load enough to infect others. It has been proposed that patients with long-COVID, a syndrome in which patients continue to have complications of COVID with ongoing symptoms, may have occurring viral replication, despite testing negative via rapid COVID antigen testing.\n\nWe therefore propose a modified antigen-based method that exposes hidden or masked antigenic sites of viral specimens, or lingering fragments of viral proteins, present in sputum using a home-based rapid immunoassay for COVID-19. Almost all protocols for testing were performed according to LFIA kit manufacturers instructions for the detection of SARS-CoV-2 nucleocapsid protein antigen, one of the most predominant proteins encoded by the SARS-CoV-2 virus. However, in challenging the manufacturer instructions, one or more digestive enzymes and a detergent were added to the collected biosamples (nasopharyngeal, oropharyngeal, saliva, buccal, gargle, and sputum); this modified procedure expose hidden or masked antigenic sites of the coronavirus or cross-reactant antigenic sites of related or non-related viruses, or some of the plethora of epitopes generated by the sample corresponding microbiota to accomplish an optimal binding to the commercial antibody used in the diagnostic test. The modified protocol can enhance detection sensitivity by making the resultant test band in sputum samples visible, that would otherwise not be seen, and consequently may generate a false negative result, in a nasopharyngeal sample from a patient with mild symptoms of COVID-19 and/or low viral load. Therefore, a need exists for an improved sample pre-treatment extraction procedure that allows optimization of sample preparation to attain a more accurate test result. Although the experiments described here were performed using commercial platforms, with antibodies directed to SARS-CoV-2 nucleocapsid antigen, this method may also be viable for the detection of any other pathogen in sputum by using antibodies directed to the key antigens present in the pathogen of interest. Furthermore, this modified method to expose the content of sputum can be used as a simple protocol to study the sputome, the proteome of sputum, and other omics (sputomics). In summary, this simple method is non-invasive, rapid, inexpensive, accurate, and may provide increased sensitivity and specificity in the detection of COVID-19 antigens for several weeks or even months.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.27.23285043", + "rel_abs": "Understanding sociodemographic factors behind COVID-19 severity relates to significant methodological difficulties, such as differences in testing policies and epidemics phase, as well as a large number of predictors that can potentially contribute to severity. To account for these difficulties, we assemble 115 predictors for more than 3000 US counties and employ a well-defined COVID-19 severity measure derived from epidemiological dynamics modeling. We then use a number of advanced feature selection techniques from machine learning to determine which of these predictors significantly impact the disease severity. We obtain a surprisingly simple result, where only two variables are clearly and robustly selected - population density and proportion of African Americans. Possible causes behind this result are discussed. We argue that the approach may be useful whenever significant determinants of disease progression over diverse geographic regions should be selected from a large number of potentially important factors.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Norberto Guzman", - "author_inst": "Princeton Biochemicals, Inc." + "author_name": "Marko Tumbas", + "author_inst": "Quantitative Biology Group, Faculty of Biology, University of Belgrade, Serbia" + }, + { + "author_name": "Sofija Markovic", + "author_inst": "Quantitative Biology Group, Faculty of Biology, University of Belgrade, Serbia" + }, + { + "author_name": "Igor Salom", + "author_inst": "Institute of Physics Belgrade, National Institute of the Republic of Serbia, University of Belgrade, Serbia" }, { - "author_name": "Daniel E Guzman", - "author_inst": "Columbia University Irving Medical Center, New York, New York 10032" + "author_name": "Marko Djordjevic", + "author_inst": "Quantitative Biology Group, Faculty of Biology, University of Belgrade, Serbia" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2023.01.26.23285076", @@ -106501,47 +105807,63 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.01.25.525479", - "rel_title": "Coronaviruses use ACE2 monomers as entry receptors", + "rel_doi": "10.1101/2023.01.22.23284884", + "rel_title": "Shielding under endemic SARS-CoV-2 conditions is easier said than done: a model-based analysis", "rel_date": "2023-01-25", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.25.525479", - "rel_abs": "The angiotensin-converting enzyme 2 (ACE2) has been identified as entry receptor on cells enabling binding and infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) via trimeric spike (S) proteins protruding from the viral surface1,2. It has been suggested that trimeric S proteins preferably bind to plasma membrane areas with high concentrations of preferably multimeric ACE2 receptors to achieve a higher binding and infection efficiency1,3. However, our current knowledge about the influence of ACE2 expression and organization in the plasma membrane on SARS-CoV-2 infection efficiency remains elusive. Here we used direct stochastic optical reconstruction microscopy (dSTORM) in combination with different labeling approaches to visualize the distribution and quantify the expression of ACE2 on different cells. Our results reveal that endogenous ACE2 receptors are present as monomers in the plasma membrane with densities of only 1-2 receptors m-2. In addition, binding of trimeric S proteins does not induce clustering of ACE2 receptors in the plasma membrane. Supported by infection studies using vesicular stomatitis virus (VSV) particles bearing S proteins our data demonstrate that a single S protein interaction per virus particle with a monomeric ACE2 receptor is sufficient for infection which attests SARS-CoV-2 a high infectivity.", - "rel_num_authors": 7, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.22.23284884", + "rel_abs": "As the COVID-19 pandemic continues unabated, many governments and public-health bodies worldwide have ceased to implement concerted measures for limiting viral spread, placing the onus instead on the individual. In this paper, we examine the feasibility of this proposition using an agent-based model to simulate the impact of individual shielding behaviors on reinfection frequency. We derive estimates of heterogeneity in immune protection from a population pharmacokinetic (pop PK) model of antibody kinetics following infection and variation in contact rate based on published estimates. Our results suggest that individuals seeking to opt out of adverse outcomes upon SARS-CoV-2 infection will find it challenging to do so, as large reductions in contact rate are required to reduce the risk of infection. Our findings suggest the importance of a multilayered strategy for those seeking to reduce the risk of infection. This work also suggests the importance of public health interventions such as universal masking in essential venues and air quality standards to ensure individual freedom of choice regarding COVID-19.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Patrick Eiring", - "author_inst": "Department of Biotechnology and Biophysics, Biocenter, University of Wuerzburg, Am Hubland, 97074 Wuerzburg, Germany" + "author_name": "Madison Stoddard", + "author_inst": "Fractal Therapeutics" }, { - "author_name": "Teresa Klein", - "author_inst": "Department of Biotechnology and Biophysics, Biocenter, University of Wuerzburg, Am Hubland, 97074 Wuerzburg, Germany" + "author_name": "Lin Yuan", + "author_inst": "Fractal Therapeutics" }, { - "author_name": "Simone Backes", - "author_inst": "Institute for Virology and Immunbiology, University of Wuerzburg, Versbacher Str. 7, 97080 Wuerzburg, Germany" + "author_name": "Sharanya Sarkar", + "author_inst": "Dartmouth College" + }, + { + "author_name": "Matthew Mazewski", + "author_inst": "Independent Researcher" + }, + { + "author_name": "Debra Van Egeren", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Marcel Streit", - "author_inst": "Rudolf Virchow Center, Research Center for Integrative and Translational Bioimaging, University of Wuerzburg, Josef-Schneider-Str. 2, 97080 Wuerzburg, Germany" + "author_name": "Shruthi Mangalaganesh", + "author_inst": "Monash University" + }, + { + "author_name": "Ryan P. Nolan", + "author_inst": "Halozyme Therapeutics" + }, + { + "author_name": "Michael S. Rogers", + "author_inst": "Harvard Medical School" }, { - "author_name": "Soeren Doose", - "author_inst": "Department of Biotechnology and Biophysics, Biocenter, University of Wuerzburg, Am Hubland, 97074 Wuerzburg, Germany" + "author_name": "Greg Hather", + "author_inst": "Sage Therapeutics" }, { - "author_name": "Gerti Beliu", - "author_inst": "Rudolf Virchow Center, Research Center for Integrative and Translational Bioimaging, University of Wuerzburg, Josef-Schneider-Str. 2, 97080 Wuerzburg, Germany" + "author_name": "Laura White", + "author_inst": "Boston University" }, { - "author_name": "Markus Sauer", - "author_inst": "Department of Biotechnology and Biophysics, Biocenter, University of Wuerzburg, Am Hubland, 97074 Wuerzburg, Germany" + "author_name": "Arijit Chakravarty", + "author_inst": "Fractal Therapeutics" } ], "version": "1", "license": "cc_by", - "type": "new results", - "category": "molecular biology" + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.01.21.23284592", @@ -108371,49 +107693,61 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.01.20.23284851", - "rel_title": "Overcrowded Housing Reduces COVID-19 Mitigation Measures and Lowers Emotional Health Among San Diego Refugees from September to November of 2020", + "rel_doi": "10.1101/2023.01.20.23284493", + "rel_title": "Assessing the effectiveness of portable HEPA air cleaners for reducing particulate matter exposure in King County, Washington homeless shelters during the COVID-19 pandemic: implications for community congregate settings", "rel_date": "2023-01-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.20.23284851", - "rel_abs": "Refugee communities are vulnerable to housing insecurity, which drives numerous health disparity outcomes in a historically marginalized population. The COVID-19 pandemic has only worsened the ongoing affordable housing crisis in the United States while continuing to highlight disparities in health outcomes across populations. We conducted interviewer-administered surveys with refugee and asylum seekers in San Diego County at the height of the COVID-19 pandemic to understand the social effects and drivers of COVID-19 in one of the largest refugee communities in the United States. Staff from a community-based refugee advocacy and research organization administered the surveys from September - November 2020. 544 respondents participated in the survey, which captured the diversity of the San Diego refugee community including East African (38%), Middle Eastern (35%), Afghan (17%), and Southeast Asian (11%) participants. Nearly two-thirds of respondents (65%) reported living in overcrowded conditions (> 1 individual per room) and 30% in severely crowded conditions (> 1.5 individuals per room). Respondents living in affordable housing units or receiving section 8 housing vouchers had a 66% lower probability of living in severely crowded settings (aOR:0.34, 95% CI:0.19- 0.61). Refugees living in overcrowded and severely overcrowded housing had more than twice the odds to have not accessed COVID-19 testing since the pandemic began (OR: 2.28, 95% CI: 1.38 - 3.78) and had nearly 4 times the odds to report lower emotional health (OR: 3.90, 95% CI: 2.62 - 5.82). Longer United States residency was associated with a 7% reduction in the odds of living in crowded housing per additional year (aOR:0.93, 95% CI:0.90-0.97). Overcrowding housing is a structural burden that reduces COVID-19 risk mitigation behaviors. Improved access to affordable housing units or receiving vouchers could reduce overcrowded housing in vulnerable refugee communities.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.20.23284493", + "rel_abs": "Over four thousand portable air cleaners (PACs) with high-efficiency particulate air (HEPA) filters were distributed by Public Health - Seattle & King County to homeless shelters during the COVID-19 pandemic. This study aimed to evaluate the real-world effectiveness of these HEPA PACs in reducing indoor particles and understand the factors that affect their use in homeless shelters. Four rooms across three homeless shelters with varying geographic locations and operating conditions were enrolled in this study. At each shelter, multiple PACs were deployed based on the room volume and PACs clean air delivery rate rating. The energy consumption of these PACs was measured using energy data loggers at 1-min intervals to allow tracking of their use and fan speed for three two-week sampling rounds, separated by single-week gaps, between February and April 2022. Total optical particle number concentration (OPNC) was measured at 2-min intervals at multiple indoor locations and an outdoor ambient location. The empirical indoor and outdoor total OPNC were compared for each site. Additionally, linear mixed-effects regression models (LMERs) were used to assess the relationship between PAC use time and indoor/outdoor total OPNC ratios (I/OOPNC). Based on the LMER models, one percent increase in the hourly, daily and total time PACs were used significantly reduced I/OOPNC by 0.34 [95% CI: 0.28, 0.40], 0.51 [95% CI: 0.20, 0.78], 2.52 [95% CI: 1.50, 3.28], respectively, indicating that keeping PACs on resulted in significantly lower I/OOPNC or relatively lower indoor total OPNC than outdoors. The survey suggested that keeping PACs on and running was the main challenge when operating them in shelters. These findings suggested that HEPA PACs were an effective short-term strategy to reduce indoor particle levels in community congregate living settings during non-wildfire seasons and the need for formulating practical guidance for using them in such an environment.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Ashkan Hassani", - "author_inst": "University of California, San Diego" + "author_name": "Ching-Hsuan Huang", + "author_inst": "Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington" }, { - "author_name": "Vinton Omaleki", - "author_inst": "University of California, San Diego" + "author_name": "Thu Bui", + "author_inst": "Public Health - Seattle and King County" }, { - "author_name": "Jeanine Erikat", - "author_inst": "Partnership for the Advancement of New Americans" + "author_name": "Daniel Hwang", + "author_inst": "Public Health - Seattle and King County" }, { - "author_name": "Elizabeth Frost", - "author_inst": "University of California, San Diego" + "author_name": "Jeffry Shirai", + "author_inst": "Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington" }, { - "author_name": "Samantha Streuli", - "author_inst": "University of California, San Diego" + "author_name": "Elena Austin", + "author_inst": "Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington" }, { - "author_name": "Ramla Sahid", - "author_inst": "Partnership for the Advancement of New Americans" + "author_name": "Martin Cohen", + "author_inst": "Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington" }, { - "author_name": "Homayra Yusufi", - "author_inst": "Partnership for the Advancement of New Americans" + "author_name": "Timothy Gould", + "author_inst": "Department of Civil and Environmental Engineering, College of Engineering, University of Washington" }, { - "author_name": "Rebecca K Fielding-Miller", - "author_inst": "University of California, San Diego" + "author_name": "Timothy Larson", + "author_inst": "Department of Civil and Environmental Engineering, College of Engineering, University of Washington" + }, + { + "author_name": "Igor Novosselov", + "author_inst": "Department of Mechanical Engineering, College of Engineering, University of Washington, Seattle" + }, + { + "author_name": "Shirlee Tan", + "author_inst": "Public Health - Seattle & King County" + }, + { + "author_name": "Edmund Seto", + "author_inst": "Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -110029,97 +109363,185 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.01.16.23284630", - "rel_title": "Covid-19 affects taste independently of smell: results from a combined chemosensory home test and online survey from a global cohort (N=10,953)", + "rel_doi": "10.1101/2023.01.16.22283804", + "rel_title": "The central nervous systems proteogenomic and spatial imprint upon systemic viral infections with SARS-CoV-2", "rel_date": "2023-01-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.16.23284630", - "rel_abs": "People often confuse smell loss with taste loss, so it is unclear how much gustatory function is reduced in patients self-reporting taste loss. Our pre-registered cross-sectional study design included an online survey in 12 languages with instructions for self-administering chemosensory tests with ten household items. Between June 2020 and March 2021, 10,953 individuals participated. Of these, 3,356 self-reported a positive and 602 a negative COVID-19 diagnosis (COVID+ and COVID-, respectively); 1,267 were awaiting test results (COVID?). The rest reported no respiratory illness and were grouped by symptoms: sudden smell/taste changes (STC, N=4,445), other symptoms excluding smell or taste loss (OthS, N=832), and no symptoms (NoS, N=416). Taste, smell, and oral irritation intensities and self-assessed abilities were rated on visual analog scales. Compared to the NoS group, COVID+ was associated with a 21% reduction in taste (95% Confidence Interval (CI): 15-28%), 47% in smell (95%-CI: 37-56%), and 17% in oral irritation (95%-CI: 10-25%) intensity. In all groups, perceived intensity of smell (r=0.84), taste (r=0.68), and oral irritation (r=0.37) was correlated. Our findings suggest most reports of taste dysfunction with COVID-19 were genuine and not due to misinterpreting smell loss as taste loss (i.e., a classical taste-flavor confusion). Assessing smell and taste intensity of household items is a promising, cost-effective screening tool that complements self-reports and helps to disentangle taste loss from smell loss. However, it does not replace standardized validated psychophysical tests.", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.16.22283804", + "rel_abs": "In COVID-19 neurological alterations are noticed during the systemic viral infection. Various pathophysiological mechanisms on the central nervous system (CNS) have been suggested in the past two years, including the viral neurotropism hypothesis. Nevertheless, neurological complications can also occur independent of neurotropism and at different stages of the disease and may be persistent.\n\nPrevious autopsy studies of the CNS from patients with severe COVID-19 show infiltration of macrophages and T lymphocytes, especially in the perivascular regions as well as pronounced microglial activation, but without signs of viral encephalitis.\n\nHowever, there is an ongoing debate about long-term changes and cytotoxic effects in the CNS due to the systemic inflammation.\n\nHere, we show the brain-specific host response during and after COVID-19. We profile single-nucleus transcriptomes and proteomes of brainstem tissue from deceased COVID-19 patients who underwent rapid autopsy. We detect a disease phase-dependent inflammatory type-I interferon response in acute COVID-19 cases. Integrating single-nucleus RNA sequencing and spatial transcriptomics, we could localize two patterns of reaction to severe systemic inflammation. One neuronal with direct focus on cranial nerve nuclei and one diffusely affecting the whole brainstem, the latter reflecting a bystander effect that spreads throughout the vascular unit and alters the transcriptional state of oligodendrocytes, microglia and astrocytes.\n\nOur results indicate that even without persistence of SARS-CoV-2 in the CNS, the tissue activates highly protective mechanisms, which also cause functional disturbances that may explain the neurological symptoms of COVID-19, triggered by strong systemic type-I IFN signatures in the periphery.", + "rel_num_authors": 43, "rel_authors": [ { - "author_name": "Ha Nguyen", - "author_inst": "Monell Chemical Senses Center" + "author_name": "Josefine Radke", + "author_inst": "University Medicine, Greifswald" }, { - "author_name": "Javier Albayay", - "author_inst": "Universita degli Studi di Trento" + "author_name": "Jenny Meinhardt", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" }, { - "author_name": "Richard Hochenberger", - "author_inst": "Universite Paris-Saclay" + "author_name": "Tom Aschman", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" }, { - "author_name": "Surabhi Bhutani", - "author_inst": "San Diego State University" + "author_name": "Robert Lorenz Chua", + "author_inst": "Berlin Institute of Health at Charite Universitatsmedizin Berlin" }, { - "author_name": "Sanne Boesveldt", - "author_inst": "Wageningen University" + "author_name": "Vadim Farztdinov", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" }, { - "author_name": "Niko A. Busch", - "author_inst": "University of Munster" + "author_name": "Soren Lukkassen", + "author_inst": "Berlin Institute of Health at Charite Universitatsmedizin Berlin" }, { - "author_name": "Ilja Croijmans", - "author_inst": "Radboud University" + "author_name": "Foo Wei Ten", + "author_inst": "Berlin Institute of Health at Charite Universitatsmedizin Berlin" }, { - "author_name": "Keiland Cooper", - "author_inst": "University of California Irvine" + "author_name": "Friebel Ekaterina", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" }, { - "author_name": "Jasper H.B. de Groot", - "author_inst": "Radboud University" + "author_name": "Naveed Ishaque", + "author_inst": "Berlin Institute of Health at Charite Universitatsmedizin Berlin" }, { - "author_name": "Micheal C. Farruggia", - "author_inst": "Yale University School of Medicine" + "author_name": "Jonas Franz", + "author_inst": "University Medical Center Gottingen" }, { - "author_name": "Alexander W. Fjaeldstad", - "author_inst": "Godstrup Regional Hospital" + "author_name": "Valerie Helena Huhle", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" }, { - "author_name": "John E. Hayes", - "author_inst": "The Pennsylvania State University" + "author_name": "Ronja Mothes", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" }, { - "author_name": "Thomas Hummel", - "author_inst": "University of Dresden Medical School" + "author_name": "Kristin Peters", + "author_inst": "University Medicine, Greifswald" }, { - "author_name": "Paule V. Joseph", - "author_inst": "National Institutes of Health" + "author_name": "Carolina Thomas", + "author_inst": "University Medical Center Gottingen" }, { - "author_name": "Tatiana K. Laktionova", - "author_inst": "A N Severtsov Institute of Ecology and Evolution RAS" + "author_name": "Simon Streit", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" }, { - "author_name": "Thierry Thomas-Danguin", - "author_inst": "INRAE CSGA, Research Center for Smell Taste and Feeding Behavior" + "author_name": "Regina von Manitius", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" }, { - "author_name": "Maria G. Veldhuizen", - "author_inst": "Mersin Universitesi" + "author_name": "Peter Kortvelyessy", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" }, { - "author_name": "Vera V Voznessenskaya", - "author_inst": "A N Severtsov Institute of Ecology and Evolution RAS" + "author_name": "Stefan Vielhaber", + "author_inst": "Otto-von-Guerike-University Magdeburg" }, { - "author_name": "Valentina Parma", - "author_inst": "Monell Chemical Senses Center" + "author_name": "Dirk Reinhold", + "author_inst": "Otto-von-Guerike-University Magdeburg" }, { - "author_name": "Marta Yanina Pepino", - "author_inst": "University of Illinois at Urbana- Champaign" + "author_name": "Anja Hauser", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" }, { - "author_name": "Kathrin Ohla", - "author_inst": "Firmenich" + "author_name": "Anja Osterloh", + "author_inst": "Universitatsklinikum Ulm" + }, + { + "author_name": "Philipp Enghard", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" + }, + { + "author_name": "Jana Ihlow", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" + }, + { + "author_name": "Sefer Elezkurtaj", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" + }, + { + "author_name": "David Horst", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" + }, + { + "author_name": "Florian Kurth", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" + }, + { + "author_name": "Marcel A Muller", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" + }, + { + "author_name": "Nils C Gassen", + "author_inst": "University Hospital Bonn" + }, + { + "author_name": "Julia Schneider", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" + }, + { + "author_name": "Katharina Jechow", + "author_inst": "Berlin Institute of Health at Charite Universitatsmedizin Berlin" + }, + { + "author_name": "Bernd Timmermann", + "author_inst": "Max Planck Institute for Molecular Genetics" + }, + { + "author_name": "Camila Fernandez-Zapata", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" + }, + { + "author_name": "Chotima Bottcher", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" + }, + { + "author_name": "Werner Stenzel", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" + }, + { + "author_name": "Emanuel Wyler", + "author_inst": "Max-Delbruck-Center for Molecular Medicine (MDC)" + }, + { + "author_name": "Victor Corman", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" + }, + { + "author_name": "Christine Stadelmann-Nessler", + "author_inst": "University Medical Center Gottingen" + }, + { + "author_name": "Markus Ralser", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" + }, + { + "author_name": "Roland Eils", + "author_inst": "Berlin Institute of Health at Charite Universitatsmedizin Berlin" + }, + { + "author_name": "Frank L Heppner", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" + }, + { + "author_name": "Michael Mulleder", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" + }, + { + "author_name": "Christian Conrad", + "author_inst": "Berlin Institute of Health at Charite Universitatsmedizin Berlin" + }, + { + "author_name": "Helena Radbruch", + "author_inst": "Charite Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin and Humboldt Universitat zu Berlin" } ], "version": "1", @@ -111967,63 +111389,75 @@ "category": "genetics" }, { - "rel_doi": "10.1101/2023.01.14.524034", - "rel_title": "Exploration of the Link Between COVID-19 and Alcoholic Hepatitis from the Perspective of Bioinformatics and Systems Biology", - "rel_date": "2023-01-17", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.14.524034", - "rel_abs": "ObjectiveSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been suggested to purpose threats to health of mankind. Alcoholic hepatitis (AH) is a life-threatening acute and chronic liver failure that takes place in sufferers who drink excessively. During the epidemic, AH has an increasing incidence of severe illness and mortality. However, for these two diseases, the intrinsic relationship of molecular pathogenesis, as well as common therapeutic strategies are still poorly understood.\n\nMethodsThe transcriptome of the COVID-19 and AH has been compared to obtain the altered genes and hub genes were screened out through protein-protein interaction (PPI) network analysis. Via gene ontology (GO), pathway enrichment and transcription regulator analysis, a deeper appreciation of the interplay mechanism between hub genes were established.\n\nResultsWith 181 common differentially expressed genes (DEGs) of AH and COVID-19 were obtained, 10 hub genes were captured. Follow-up studies located that these 10 genes typically mediated the diseases occurrence by regulating the activities of the immune system. Other results suggest that the common pathways of the two ailments are enriched in regulating the function of immune cells and the release of immune molecules.\n\nConclusionThis study reveals the common pathogenesis of COVID-19 and AH and assist to discover necessary therapeutic targets to combat the ongoing pandemic induced via SARS-CoV-2 infection and acquire promising remedy strategies for the two diseases.", - "rel_num_authors": 11, + "rel_doi": "10.1101/2023.01.13.23284488", + "rel_title": "Variations in COVID-19 impacts by social vulnerability in Philadelphia, June 2020-December 2022", + "rel_date": "2023-01-14", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.13.23284488", + "rel_abs": "IntroductionThe study objective was to elucidate the relationship between social vulnerability and COVID-19 impacts in Philadelphia over a 2.5-year period, between June 2020 and December 2022.\n\nMethodsUsing publicly available COVID-19 case, test, hospitalization, and mortality data for Philadelphia (June 7, 2020-December 31, 2022) and area-level social vulnerability data, we compared the incidence, test positivity, hospitalization, and mortality rates in high and low vulnerability neighborhoods of Philadelphia, characterized as scoring above or below the national median score on the social vulnerability index. We used linear mixed effects models to test the association between social vulnerability and COVID-19 incidence, test positivity, hospitalization, and mortality rates, adjusting for time and age distribution.\n\nResults90.4% of Philadelphians (n = 1,430,153) live in neighborhoods classified as socially vulnerable, based on scoring above the national median score on the social vulnerability index. COVID-19 incidence, hospitalization, and mortality rates were significantly elevated in the more vulnerable communities, with p < 0.05, p < 0.005, and p < 0.001, respectively. The relative risks of COVID-19-related incidence, hospitalization, and death, comparing the more vulnerable neighborhoods to the less vulnerable neighborhoods, were 1.11 (95%CI: 1.10-1.12), 2.07 (95%CI: 1.93-2.20), and 2.06 (95%CI: 1.78-2.38), respectively. Thus, between June 7, 2020 and December 31, 2022, 32,573 COVID-19 cases, 9,409 hospitalizations, and 1,967 deaths would have been avoided in Philadelphias more vulnerable communities had they experienced the same rates of incidence, hospitalization, and death as the less vulnerable Philadelphia communities.\n\nConclusionsThese results highlight the disparate morbidity and mortality experienced by people living in more vulnerable neighborhoods in a large US city. Importantly, our findings illustrate the importance of designing public health policies and interventions with an equity-driven approach, with greater resources and more intensive prevention strategies applied in socially vulnerable communities.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Tengda Huang", - "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collabora" + "author_name": "Katherine M Strelau", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Bingxuan Yu", - "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collabora" + "author_name": "Rachel Feuerstein-Simon", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Xinyi Zhou", - "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collabora" + "author_name": "Nawar Naseer", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Hongyuan Pan", - "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collabora" + "author_name": "Megan Lang", + "author_inst": "Boston University" }, { - "author_name": "Ao Du", - "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collabora" + "author_name": "Kevin Rix", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Jincheng Bai", - "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collabora" + "author_name": "Eleanor J Murray", + "author_inst": "Boston University" }, { - "author_name": "Xiaoquan Li", - "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collabora" + "author_name": "Jeffrey S Morris", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Nan Jiang", - "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collabora" + "author_name": "Douglas J Wiebe", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Jinyi He", - "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collabora" + "author_name": "Hillary C. M. Nelson", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Zhen Wang", - "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collabora" + "author_name": "Ronald G Collman", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Kefei Yuan", - "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collabora" + "author_name": "Kyle G Rodino", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Frederic D Bushman", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Brendan J Kelly", + "author_inst": "University of Pennsylvania Perelman School of Medicine" + }, + { + "author_name": "Carolyn C Cannuscio", + "author_inst": "University of Pennsylvania" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "bioinformatics" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.01.13.23284341", @@ -113693,45 +113127,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.01.10.23284365", - "rel_title": "Bayesian sequential approach to monitor COVID-19 variants through positivity rate from wastewate", + "rel_doi": "10.1101/2023.01.10.23284386", + "rel_title": "Vaccine effectiveness against SARS-CoV-2 Delta and Omicron infection and infectiousness within households in the Netherlands between July 2021 and August 2022.", "rel_date": "2023-01-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.10.23284365", - "rel_abs": "Trends in COVID-19 infection have changed throughout the pandemic due to myriad factors, including changes in transmission driven by social behavior, vaccine development and uptake, mutations in the virus genome, and public health policies. Mass testing was an essential control measure for curtailing the burden of COVID-19 and monitoring the magnitude of the pandemic during its multiple phases. However, as the pandemic progressed, new preventive and surveillance mechanisms emerged. Implementing vaccine programs, wastewater (WW) surveillance, and at-home COVID-19 tests reduced the demand for mass severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing. This paper proposes a sequential Bayesian approach to estimate the COVID-19 positivity rate (PR) using SARS-CoV-2 RNA concentrations measured in WW through an adaptive scheme incorporating changes in virus dynamics. PR estimates are used to compute thresholds for WW data using the CDC thresholds for low, substantial, and high transmission. The effective reproductive number estimates are calculated using PR estimates from the WW data. This approach provides insights into the dynamics of the virus evolution and an analytical framework that combines different data sources to continue monitoring the COVID-19 trends. These results can provide public health guidance to reduce the burden of future outbreaks as new variants continue to emerge. The proposed modeling framework was applied to the City of Davis and the campus of the University of California Davis.", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.10.23284386", + "rel_abs": "IntroductionWe aimed to estimate vaccine effectiveness against infection (VE- infection) and infectiousness (VE-infectiousness) in a household setting during Delta and Omicron. Knowing these effects can aid policy makers in deciding which groups to prioritize for vaccination.\n\nMethodsParticipants with a positive SARS-CoV-2 test were asked about COVID-19 vaccination status and SARS-CoV-2 testing of their household members one month later. VE-infection and VE-infectiousness was estimated using GEE logistic regression adjusting for age and vaccination status, calendar week and household size.\n\nResults3,409 questionnaires concerning 4,123 household members were included. During the Delta-period, VE-infection of primary series was 47% (95% CI: -27%-78%) and VE-infectiousness of primary series was 70% (95% CI: 28%-87%). During the Omicron-period, VE-infection was -36% (95% CI: -88%-1%) for primary series and -30% (95% CI: -80%-6%) for booster vaccination. The VE-infectiousness was 45% (95% CI: -14%-74%) for primary series and 64% (95% CI: 31%-82%) for booster vaccination.\n\nDiscussionOur study shows that COVID-19 vaccination is effective against infection with SARS-CoV-2 Delta and against infectiousness of SARS-CoV-2 Delta and Omicron. Estimation of VE against infection with SARS-CoV-2 Omicron was limited by several factors. Our results support vaccination for those in close contact with vulnerable people to prevent transmission.", "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Jose Cricelio Montesinos Lopez", - "author_inst": "University of California Davis" + "author_name": "Christina E Hoeve", + "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and Environment" }, { - "author_name": "Maria L Daza-Torres", - "author_inst": "University of California, Davis" + "author_name": "Brechje de Gier", + "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and Environment" }, { - "author_name": "Yury E Garcia", - "author_inst": "University of California, Davis" + "author_name": "Anne J. Huiberts", + "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and Environment" }, { - "author_name": "Cesar Herrera", - "author_inst": "Purdue University" + "author_name": "Hester E de Melker", + "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and Environment" }, { - "author_name": "C. Winston Bess", - "author_inst": "University of California Davis" + "author_name": "Susan J.M. Hahne", + "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and Environment" }, { - "author_name": "Heather N. Bischel", - "author_inst": "University of California, Davis" + "author_name": "Susan van den Hof", + "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and Environment" }, { - "author_name": "Miriam Nuno", - "author_inst": "Univeristy of California, Davis" + "author_name": "Mirjam J Knol", + "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and Environment" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -115247,39 +114681,79 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.01.09.23284358", - "rel_title": "Differential COVID-19 mortality in the United States: Patterns, causes and policy implications", + "rel_doi": "10.1101/2023.01.09.523209", + "rel_title": "Identification of druggable host dependency factors shared by multiple SARS-CoV-2 variants of concern", "rel_date": "2023-01-09", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.09.23284358", - "rel_abs": "A \"two Americas\" narrative emerged in the summer of 2021: one with high demand for COVID-19 vaccines, and a second with widespread vaccine hesitancy and opposition to mask mandates. But our analysis of excess mortality shows that the U.S. has been a divided nation at least since the start of the pandemic. Through April, 2022, there were 1,335,292 excess deaths associated with COVID-19, 37% more than reported as such. After the first wave, death rates in the South were more than double those in the Northeast; 45% of deaths were in the South, with 38% of the population.\n\nWhile some regard vaccination and other measures as matters of personal choice, the population impact is striking. If every region had the same mortality rate as the lowest regional rate in each period, more than 418,763 COVID-19 deaths were \"avoidable,\" more than half (58%) in the South and almost half before vaccines were available. These results show that population-based COVID-19 policies can still play an important role in protecting those most vulnerable to severe disease and death and reducing the spread of the virus.\n\nThis example illustrates the importance of excess mortality measures as part of a comprehensive surveillance system. Official mortality counts rely on complete recording of COVID-19 as a cause of death, but COVID-19 deaths are under reported for many reasons. Indeed, the proportion of COVID-19 deaths reported as such varied markedly over time, and from 67% in the West to 87% the Northeast. In 2022, some regions cut back on testing making it harder to see a re-emergence of COVID-19 in those places. More extensive surveillance based on wastewater testing and other means that do not depend on testing are needed to get a more accurate picture. Excess mortality estimates are more tenuous years beyond the pre-pandemic period.", - "rel_num_authors": 5, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.09.523209", + "rel_abs": "The high mutation rate of SARS-CoV-2 leads to emergence of several variants, some of which are resistant to vaccines and drugs targeting viral elements. Targeting host dependency factors - cell proteins required for viral replication - would help avoid resistance. However, whether different SARS-CoV-2 variants induce conserved cell responses and exploit the same core host factors is still unclear.\n\nWe compared three variants of concern and observed that the host transcriptional response was conserved, differing only in kinetics and magnitude. By CRISPR screening we identified the host genes required for infection by each variant: most of the identified genes were shared by multiple variants, both in lung and colon cells. We validated our hits with small molecules and repurposed FDA-approved drugs. All drugs were highly effective against all tested variants, including delta and omicron, new variants that emerged during the study. Mechanistically, we identified ROS production as a pivotal step in early virus propagation. Antioxidant drugs, such as N-acetyl cysteine (NAC), were effective against all variants both in human lung cells, and in a humanised mouse model. Our study supports the use of available antioxidant drugs, such as NAC, as a general and effective anti-COVID-19 approach.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Michael A A Stoto", - "author_inst": "Georgetown University Medical Center" + "author_name": "Ilaria Frasson", + "author_inst": "Department of Molecular Medicine, University of Padua, Italy" }, { - "author_name": "Samantha Schlageter", - "author_inst": "Georgetown University Medical Center" + "author_name": "Linda Diamante", + "author_inst": "Department of Molecular Medicine, University of Padua, Italy" }, { - "author_name": "Duccio Gamannossi degl\u2019Innocenti", - "author_inst": "Universit\u00e0 Cattolica del Sacro Cuore: Universita Cattolica del Sacro Cuore" + "author_name": "Manuela Zangrossi", + "author_inst": "Department of Molecular Medicine, University of Padua, Italy" }, { - "author_name": "Fabiana Zollo", - "author_inst": "Universita Ca' Foscari" + "author_name": "Elena Carbognin", + "author_inst": "Department of Biology, University of Padua, Italy" }, { - "author_name": "John Kraemer", - "author_inst": "Georgetown University Medical Center" + "author_name": "Anna Dalla Pieta", + "author_inst": "Dept. of Surgery, Oncology and Gastroenterology, University of Padua, Italy" + }, + { + "author_name": "Alessandro Penna", + "author_inst": "Dept. of Surgery, Oncology and Gastroenterology, University of Padua, Italy" + }, + { + "author_name": "Antonio Rosato", + "author_inst": "Dept. of Surgery, Oncology and Gastroenterology, University of Padua, Italy" + }, + { + "author_name": "Ranieri Verin", + "author_inst": "Department of Comparative Biomedicine and Food Science, University of Padua, Italy" + }, + { + "author_name": "Filippo Torrigiani", + "author_inst": "Department of Comparative Biomedicine and Food Science, University of Padua, Italy" + }, + { + "author_name": "Cristiano Salata", + "author_inst": "Department of Molecular Medicine, University of Padua, Italy" + }, + { + "author_name": "Lorenzo Vaccaro", + "author_inst": "Telethon Institute of Genetics and Medicine, Pozzuoli, Italy" + }, + { + "author_name": "Davide Cacchiarelli", + "author_inst": "Telethon Institute of Genetics and Medicine, Pozzuoli, Italy" + }, + { + "author_name": "Sara N. Richter", + "author_inst": "Department of Molecular Medicine, University of Padua, Italy" + }, + { + "author_name": "Marco Montagner", + "author_inst": "Department of Molecular Medicine, University of Padua, Italy" + }, + { + "author_name": "Graziano Martello", + "author_inst": "Department of Biology, University of Padua, Italy" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2023.01.06.522349", @@ -117473,59 +116947,91 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.01.03.23284167", - "rel_title": "Diminished responses to mRNA-based SARS-CoV-2 vaccines in individuals with rheumatoid arthritis on immune modifying therapies", + "rel_doi": "10.1101/2023.01.04.22283762", + "rel_title": "Challenges in estimating waning effectiveness of two doses of BNT162b2 and ChAdOx1 COVID-19 vaccines beyond six months: an OpenSAFELY cohort study using linked electronic health records", "rel_date": "2023-01-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.03.23284167", - "rel_abs": "Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disorder that causes debilitating swelling and destruction of the joints. People with RA are treated with drugs that actively suppress one or more parts of their immune system, and these may alter their response to vaccination against SARS-CoV-2. In this study, we analyzed blood samples from a cohort of RA subjects after receiving a 2-dose mRNA COVID-19 vaccine regimen. Our data show that individuals on the CTLA4-Ig therapy abatacept have reduced levels of SARS-CoV-2-neutralizing antibodies after vaccination. At a cellular level, these subjects show reduced activation and class-switching of SARS-CoV-2-specific B cells, as well as reduced numbers and impaired helper cytokine production by SARS-CoV-2-specific CD4+ T cells. Individuals on methotrexate showed similar but less severe defects in vaccine response, whereas individuals on the B cell-depleting therapy rituximab had a near-total loss of antibody production after vaccination. These data define a specific cellular phenotype associated with impaired response to SARS-CoV-2 vaccination in RA subjects on different immune-modifying therapies, and help inform efforts to improve vaccination strategies in this vulnerable population.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.04.22283762", + "rel_abs": "Quantifying the waning effectiveness of second COVID-19 vaccination beyond six months and against the omicron variant is important for scheduling subsequent doses. With the approval of NHS England, we estimated effectiveness up to one year after second dose, but found that bias in such estimates may be substantial.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Samuel D Klebanoff", - "author_inst": "Benaroya Research Institute" + "author_name": "Elsie MF Horne", + "author_inst": "University of Bristol" }, { - "author_name": "Lauren B Rodda", - "author_inst": "University of Washington School of Medicine" + "author_name": "William J Hulme", + "author_inst": "University of Oxford" }, { - "author_name": "Chihiro Morishima", - "author_inst": "University of Washington School of Medicine" + "author_name": "Ruth H Keogh", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Mark H Wener", - "author_inst": "University of Washington School of Medicine" + "author_name": "Tom M Palmer", + "author_inst": "University of Bristol" }, { - "author_name": "Yevgeniy Yuzefpolskiy", - "author_inst": "Benaroya Research Institute" + "author_name": "Elizabeth Williamson", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Estelle Bettelli", - "author_inst": "Benaroya Research Institute" + "author_name": "Edward PK Parker", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Jane H Buckner", - "author_inst": "Benaroya Research Institute" + "author_name": "Venexia M Walker", + "author_inst": "University of Bristol" }, { - "author_name": "Cate Speake", - "author_inst": "Benaroya Research Institute" + "author_name": "Rochelle Knight", + "author_inst": "University of Bristol" }, { - "author_name": "Marion Pepper", - "author_inst": "University of Washington School of Medicine" + "author_name": "Yinghui Wei", + "author_inst": "University of Plymouth" }, { - "author_name": "Daniel J Campbell", - "author_inst": "Benaroya Research Institute" + "author_name": "Kurt Taylor", + "author_inst": "University of Bristol" + }, + { + "author_name": "Louis Fisher", + "author_inst": "University of Oxford" + }, + { + "author_name": "Jessica Morley", + "author_inst": "University of Oxford" + }, + { + "author_name": "Amir Mehrkar", + "author_inst": "University of Oxford" + }, + { + "author_name": "Iain Dillingham", + "author_inst": "University of Oxford" + }, + { + "author_name": "Sebastian CJ Bacon", + "author_inst": "University of Oxford" + }, + { + "author_name": "Ben Goldacre", + "author_inst": "University of Oxford" + }, + { + "author_name": "Jonathan AC Sterne", + "author_inst": "University of Bristol" + }, + { + "author_name": "- The OpenSAFELY Collaborative", + "author_inst": "-" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.01.04.522762", @@ -119419,127 +118925,79 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2023.01.03.522213", - "rel_title": "A Gamma-adapted recombinant subunit vaccine induces broadly neutralizing antibodies against SARS-CoV-2 variants and protects mice from SARS-CoV-2 infection.", + "rel_doi": "10.1101/2023.01.02.522449", + "rel_title": "Composition of nasopharyngeal microbiota in individuals with SARS-COV-2 infection across three COVID-19 waves in India", "rel_date": "2023-01-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.03.522213", - "rel_abs": "The COVID-19 pandemic continues with the emergence of successive new variants of concern (VOC). One strategy to prevent breakthrough infections is developing safe and effective broad-spectrum vaccines. Here, we present preclinical studies of a RBD recombinant vaccine candidate derived from the Gamma SARS-CoV-2 variant adjuvanted with alum. Gamma RBD-derived antigen elicited better neutralizing antibody and T cell responses than formulation containing ancestral RBD antigen. The Gamma-adapted subunit vaccine elicited a long-lasting antibody response with cross-neutralizing activity against different VOC including the Omicron variant. Additionally, Gamma variant RBD-adapted vaccine elicited robust T cells responses with induction of Th1 and CD8+ T cell responses in spleen and lung. Vaccine-induced immunity protected K18-hACE2 mice from intranasal challenge with SARS-CoV-2 increasing survival, reducing body weight loss and viral burden in the lungs and brain. Importantly, the subunit vaccine demonstrated a potent effect as heterologous booster of different vaccine platforms including the non-replicating adenovirus vaccine ChAdOx1-S, the mRNA vaccine BNT162b2 and the inactivated SARS-CoV-2 vaccine BBIBP-CorV, increasing cross-reactive antibody responses. Our study indicates that the adjuvanted Gamma RBD vaccine is highly immunogenic and a broad-spectrum vaccine candidate to combat SARS-CoV-2 variants including Omicron.", - "rel_num_authors": 27, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.02.522449", + "rel_abs": "Multiple variants of the SARS-CoV-2 virus have been plaguing the world through successive waves of infection over the past three years. Studies by independent research groups across geographies have shown that the microbiome composition in COVID-19 patients (CP) differ from that of healthy individuals (CN). However, such observations were based on limited-sized sample-sets collected primarily from the early days of the pandemic. Here, we study the nasopharyngeal microbiota in COVID-19 patients, wherein the samples have been collected across the three COVID-19 waves witnessed in India, which were driven by different variants of concern. We also present the variations in microbiota of symptomatic vs asymptomatic COVID-19 patients. The nasopharyngeal swabs were collected from 589 subjects providing samples for diagnostics purposes at Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India. CP showed a marked shift in the microbial diversity and composition compared to CN, in a wave-dependent manner. Rickettsiaceae was the only family that was noted to be consistently depleted in CP samples across the waves. The genera Staphylococcus, Anhydrobacter, Thermus, and Aerococcus were observed to be highly abundant in the symptomatic CP patients when compared to the asymptomatic group. In general, we observed a decrease in the burden of opportunistic pathogens in the host microbiota during the later waves of infection. To our knowledge, this is the first longitudinal study which was designed to understand the relation between the evolving nature of the virus and the changes in the human nasopharyngeal microbiota. Such studies not only pave way for better understanding of the disease pathophysiology but also help gather preliminary evidence on whether interventions to the host microbiota can help in better protection or faster recovery.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Lorena M Coria", - "author_inst": "Investigaciones Biotecnologicas, Universidad Nacional de San Martin. (UNSAM)- Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET). Escuela de B" - }, - { - "author_name": "Juan Manuel Rodriguez", - "author_inst": "Laboratorio Pablo Cassara. Unidad de I+D de Biofarmacos. C1440FFX, Ciudad Autonoma de Buenos Aires, Argentina. Fundacion Pablo Cassara. Unidad de I+D de Biofarm" - }, - { - "author_name": "Agostina Demaria", - "author_inst": "Investigaciones Biotecnologicas, Universidad Nacional de San Martin. (UNSAM)- Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET). Escuela de B" - }, - { - "author_name": "Laura A. Bruno", - "author_inst": "Investigaciones Biotecnologicas, Universidad Nacional de San Martin. (UNSAM)- Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET). Escuela de B" - }, - { - "author_name": "Mayra Rios Medrano", - "author_inst": "Investigaciones Biotecnologicas, Universidad Nacional de San Martin. (UNSAM)- Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET). Escuela de B" - }, - { - "author_name": "Celeste Pueblas Castro", - "author_inst": "Investigaciones Biotecnologicas, Universidad Nacional de San Martin. (UNSAM)- Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET). Escuela de B" - }, - { - "author_name": "Eliana F Castro", - "author_inst": "Investigaciones Biotecnologicas, Universidad Nacional de San Martin. UNSAM-CONICET. Escuela de Bio y Nanotecnologias (EByN), Universidad Nacional de San Martin." - }, - { - "author_name": "Sabrina A Del Priore", - "author_inst": "Laboratorio Pablo Cassara. Unidad de I+D de Biofarmacos. C1440FFX, Ciudad Autonoma de Buenos Aires, Argentina." - }, - { - "author_name": "Andres C Hernando Insua", - "author_inst": "Laboratorio Pablo Cassara. Unidad de I+D de Biofarmacos. C1440FFX, Ciudad Autonoma de Buenos Aires, Argentina. Fundacion Pablo Cassara. Unidad de I+D de Biofarm" - }, - { - "author_name": "Ingird G Kaufmann", - "author_inst": "Laboratorio Pablo Cassara. Unidad de I+D de Biofarmacos. C1440FFX, Ciudad Autonoma de Buenos Aires, Argentina." - }, - { - "author_name": "Lucas M Saposnik", - "author_inst": "Investigaciones Biotecnologicas, Universidad Nacional de San Martin. (UNSAM)- Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET). Escuela de B" - }, - { - "author_name": "William B Stone", - "author_inst": "Department of Entomology, College of Agriculture and Life Sciences, Fralin Life Science Institute, Virginia Polytechnic Institute and State University, Blacksbu" - }, - { - "author_name": "Lineia Prado", - "author_inst": "Investigaciones Biotecnologicas, Universidad Nacional de San Martin. (UNSAM)- Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET). Escuela de B" + "author_name": "Tungadri Bose", + "author_inst": "TCS Research, Tata Consultancy Services Ltd" }, { - "author_name": "Valeria Krum", - "author_inst": "Laboratorio Pablo Cassara. Unidad de I+D de Biofarmacos. C1440FFX, Ciudad Autonoma de Buenos Aires, Argentina." + "author_name": "Wasimuddin", + "author_inst": "CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India" }, { - "author_name": "Francisco M Zurvarra", - "author_inst": "Laboratorio Pablo Cassara, Unidad de I+D de Biofarmacos. C1440FFX, Ciudad Autonoma de Buenos Aires, Argentina. Fundacion Pablo Cassara. Unidad de I+D de Biofarm" + "author_name": "Varnali Acharya", + "author_inst": "CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India" }, { - "author_name": "Johanna E Sidabra", - "author_inst": "Laboratorio Pablo Cassara, Unidad de I+D de Biofarmacos. C1440FFX, Ciudad Autonoma de Buenos Aires, Argentina." + "author_name": "Nishal Kumar Pinna", + "author_inst": "TCS Research, Tata Consultancy Services Ltd" }, { - "author_name": "Ignacio Drehe", - "author_inst": "Laboratorio Pablo Cassara, Unidad de I+D de Biofarmacos. C1440FFX, Ciudad Autonoma de Buenos Aires, Argentina." + "author_name": "Harrisham Kaur", + "author_inst": "TCS Research, Tata Consultancy Services Ltd" }, { - "author_name": "Jonathan A Baque", - "author_inst": "Laboratorio Pablo Cassara, Unidad de I+D de Biofarmacos. C1440FFX, Ciudad Autonoma de Buenos Aires, Argentina." + "author_name": "Manish Ranjan", + "author_inst": "CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India" }, { - "author_name": "Mariana Li Causi", - "author_inst": "Laboratorio Pablo Cassara, Unidad de I+D de Biofarmacos. C1440FFX, Ciudad Autonoma de Buenos Aires, Argentina." + "author_name": "SaiKrishna Jandhyala", + "author_inst": "CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India" }, { - "author_name": "Analia V De Nichilo", - "author_inst": "Laboratorio Pablo Cassara, Unidad de I+D de Biofarmacos. C1440FFX, Ciudad Autonoma de Buenos Aires, Argentina. Fundacion Pablo Cassara. Unidad de I+D de Biofarm" + "author_name": "Tulasi Nagabandi", + "author_inst": "CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India" }, { - "author_name": "Cristian J Payes", - "author_inst": "Laboratorio Pablo Cassara, Unidad de I+D de Biofarmacos. C1440FFX, Ciudad Autonoma de Buenos Aires, Argentina." + "author_name": "Binuja Varma", + "author_inst": "Tata Consultancy Services" }, { - "author_name": "Albert J Auguste", - "author_inst": "Department of Entomology, College of Agriculture and Life Sciences, Fralin Life Science Institute, Virginia Polytechnic Institute and State University, Blacksbu" + "author_name": "Karthik Bharadwaj Tallapaka", + "author_inst": "CSIR- Centre for Cellular and Molecular Biology, Hyderabad, India" }, { - "author_name": "Julio C Vega", - "author_inst": "Fundacion Pablo Cassara, Unidad de I+D de Biofarmacos. C1440FFX, Ciudad Autonoma de Buenos Aires, Argentina." + "author_name": "Divya Tej Sowpati", + "author_inst": "CSIR - Centre for Cellular and Molecular Biology" }, { - "author_name": "Diego E Alvarez", - "author_inst": "Investigaciones Biotecnologicas, Universidad Nacional de San Martin. (UNSAM)- Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET). Escuela de B" + "author_name": "Mohammed Monzoorul Haque", + "author_inst": "TCS Research, Tata Consultancy Services Ltd" }, { - "author_name": "Juan M Flo", - "author_inst": "Laboratorio Pablo Cassara. Unidad de I+D de Biofarmacos. C1440FFX, Ciudad Autonoma de Buenos Aires, Argentina." + "author_name": "Anirban Dutta", + "author_inst": "Tata Consultancy Services" }, { - "author_name": "Karina A Pasquevich", - "author_inst": "Investigaciones Biotecnologicas, Universidad Nacional de San Martin. (UNSAM)- Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET). Escuela de B" + "author_name": "Archana Bharadwaj Siva", + "author_inst": "CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India" }, { - "author_name": "Juliana Cassataro", - "author_inst": "Investigaciones Biotecnologicas, Universidad Nacional de San Martin. (UNSAM)- Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET). Escuela de B" + "author_name": "Sharmila S Mande", + "author_inst": "Tata Consultancy Services Limited" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2023.01.01.522328", @@ -121129,51 +120587,31 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2022.12.27.22283890", - "rel_title": "Study protocol: Medium throughput proteomic characterization of children with PIMS-TS, and identification of candidate diagnostic biomarkers.", + "rel_doi": "10.1101/2022.12.26.22283062", + "rel_title": "The Effect of COVID-19 on Distracted Driving: A Survey Study", "rel_date": "2022-12-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.27.22283890", - "rel_abs": "SARS-CoV-2 infection in children results in a wide range of clinical outcomes. Paediatric Multisystem Inflammatory syndrome temporally associated with COVID-19(PIMS-TS) occurs weeks after a SARS-CoV-2 infection, and results in severe illness. This protocol describes a study to fully characterize the circulating proteome of children who have PIMS-TS, the proteome of healthy children who have previously been infected with SARS-CoV-2 and the proteome of febrile children with a confirmed invasive infection. Orthogonal proteomic techniques will be utilized to provide a deep proteomic characterization.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.26.22283062", + "rel_abs": "The COVID-19 pandemic caused a significant shift in peoples travel behaviors and distractions while driving. This paper aims to investigate the impacts of the COVID-19 pandemic on distracted driving by comparing their behavior before and during the pandemic (from 3/1/2019 to 3/1/2021) in the state of Maryland using a stated preference online survey. Some 158 people were recruited for the survey. Participants were asked about their risky driving behaviors and self-reported distraction both before and during the pandemic. To analyze the results, the Chi-square and posthoc tests with the Bonferroni adjustment were applied. The results showed that during the pandemic, distraction dropped from 25% to 21%. The highest reported distracted driving behavior during the pandemic was using hands-free cell phones (64%), using GPS (75%), and eating or drinking (57%). The respondents daily trips have significantly decreased - about 44% below prepandemic rates. Moreover, using a binary logistic regression, it was revealed that the odds of becoming distracted among participants who used a handheld cell phone before and during the pandemic were 4.5 and 6.6 times higher than others, respectively. The findings of this study shed light on the causes of distraction before and during the pandemic.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Cathal Roarty", - "author_inst": "Queen's University Belfast" - }, - { - "author_name": "Clare Mills", - "author_inst": "Queen's University Belfast" - }, - { - "author_name": "Claire Tonry", - "author_inst": "Queen's University Belfast" - }, - { - "author_name": "Peter Cosgrove", - "author_inst": "RBHSC" - }, - { - "author_name": "Hannah Norman-Bruce", - "author_inst": "RBHSC" - }, - { - "author_name": "Helen Groves", - "author_inst": "RBHSC" + "author_name": "Ramina Javid", + "author_inst": "Morgan State University" }, { - "author_name": "Chris Watson", - "author_inst": "Queen's University Belfast" + "author_name": "Eazaz Sadeghvaziri", + "author_inst": "Morgan State University" }, { - "author_name": "Thomas Waterfield", - "author_inst": "Queen's University Belfast" + "author_name": "Mansoureh Jeihani", + "author_inst": "Morgan State University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "transplantation" }, { "rel_doi": "10.1101/2022.12.23.22283884", @@ -123191,47 +122629,71 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2022.12.24.521858", - "rel_title": "Amplification and extraction free quantitative detection of viral nucleic acids and single-base mismatches using magnetic signal amplification circuit", + "rel_doi": "10.1101/2022.12.25.521651", + "rel_title": "Innovative, rapid, high throughput method for drug repurposing in a pandemic - a case study of SARS-CoV-2 and COVID-19", "rel_date": "2022-12-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.24.521858", - "rel_abs": "Established nucleic acid detection assays require extraction and purification before sequence amplification and/or enzymatic reactions, hampering their widespread applications in point-of-care (POC) formats. Magnetic immunoassays based on magnetic particle spectroscopy and magnetic nanoparticles (MNPs) are isothermal, extraction- and purification-free, and can be quantitative and benchtop, making them suitable for POC settings. Here, we demonstrate a Magnetic signal Amplification Circuit (MAC) that combines specificity of toehold-mediated DNA strand displacement with magnetic response of MNPs to a clustering/declustering process. Our MAC assays require neither amplification nor extraction of target nucleic acids, and reveal four times better sensitivity than that of a magnetic circuit without signal amplification. Using MAC, we detect a highly specific 43 nucleotides sequence of SARS-CoV-2 virus. The MAC enables sensing both DNA and RNA targets with varying lengths and resolving single-base mismatches. Our MAC can be a powerful tool for translating research of nucleic acids detection to the clinic.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.25.521651", + "rel_abs": "Several efforts to repurpose drugs for COVID-19 treatment have largely either failed to identify a suitable agent or agents identified did not translate to clinical use; either because of demonstrated lack of clinical efficacy in trials, inappropriate dose requirements and probably use of inappropriate pre-clinical laboratory surrogates of effectiveness. In this study, we used an innovative algorithm, that incorporates dissemination and implementation considerations, to identify potential drugs for COVID-19 using iterative computational and wet laboratory methods that highlight inhibition of viral induced cytopathic effect (CPE) as a laboratory surrogate of effectiveness. Erythromycin, pyridoxine, folic acid and retapamulin were found to inhibit SARS-CoV-2 induced CPE in Vero cells at concentrations that are clinically achievable. Additional studies may be required to further characterize the inhibitions of CPE and the possible mechanisms.\n\nFundingTETFund Covid-19 Special Intervention Research grant(grant number TETFund/DR&D/CE/ SI/COVID-19/UDUS/VOL 1)", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Enja Laureen Roesch", - "author_inst": "Institute for Electrical Measurement Science and Fundamental Electrical Engineering and Laboratory for Emerging Nanometrology (LENA)" + "author_name": "Shaibu Oricha Bello", + "author_inst": "Department of Pharmacology and Therapeutics, Faculty of Basic Clinical Sciences, College of Health Sciences, Usmanu Danfodiyo University, Sokoto, Nigeria" }, { - "author_name": "Rebecca Sack", - "author_inst": "Institute for Electrical Measurement Science and Fundamental Electrical Engineering and Laboratory for Emerging Nanometrology (LENA)" + "author_name": "Abdulmajeed Yunusa", + "author_inst": "Department of Pharmacology and Therapeutics, Faculty of Basic Clinical Sciences, College of Health Sciences, Usmanu Danfodiyo University, Sokoto, Nigeria" }, { - "author_name": "Mohammad Suman Chowdhury", - "author_inst": "Institute for Electrical Measurement Science and Fundamental Electrical Engineering and Laboratory for Emerging Nanometrology (LENA)" + "author_name": "Adamu Ahmed Adamu", + "author_inst": "Department of Pharmacology and Therapeutics, Faculty of Basic Clinical Sciences, College of Health Sciences, Usmanu Danfodiyo University, Sokoto, Nigeria" }, { - "author_name": "Florian Wolgast", - "author_inst": "Institute for Electrical Measurement Science and Fundamental Electrical Engineering and Laboratory for Emerging Nanometrology (LENA)" + "author_name": "Mustapha Umar Imam", + "author_inst": "Center for Advanced Medical Research and Training, Usmanu Danfodiyo University, Sokoto, Nigeria" }, { - "author_name": "Meinhard Schilling", - "author_inst": "Institute for Electrical Measurement Science and Fundamental Electrical Engineering and Laboratory for Emerging Nanometrology (LENA)" + "author_name": "Muhammad Bashir Bello", + "author_inst": "Department of Veterinary Microbiology, Faculty of Veterinary Medicine, Usmanu Danfodiyo University, sokoto, Nigeria" + }, + { + "author_name": "Abdulmalik Bello Shuaibu", + "author_inst": "Department of veterinary Microbiology, Usmanu Danfodiyo University, Sokoto, Nigeria" + }, + { + "author_name": "Ehimario Uche Igumbor", + "author_inst": "School of Public Health, University of the Western Cape, Cape Town, South Africa" }, { - "author_name": "Thilo Viereck", - "author_inst": "Institute for Electrical Measurement Science and Fundamental Electrical Engineering and Laboratory for Emerging Nanometrology (LENA)" + "author_name": "Zaiyad Garba Habib", + "author_inst": "Department of Medicine, University of Abuja Teaching Hospital, Gwagwalada, Abuja" }, { - "author_name": "Aidin Lak", - "author_inst": "Institute for Electrical Measurement Science and Fundamental Electrical Engineering and Laboratory for Emerging Nanometrology (LENA)" + "author_name": "Mustapha Ayodele Popoola", + "author_inst": "Nigerian COVID-19 Research Coalition, Nigerian Institute of Medical Research Institute, Abuja" + }, + { + "author_name": "Chinwe Lucia Ochu", + "author_inst": "Nigerian Centre for Disease Control and Prevention, Abuja, Nigeria" + }, + { + "author_name": "Aishatu Yahaya Bello", + "author_inst": "Department of Clinical pharmacy and Pharmacy Practice, Faculty of Pharmaceutical sciences, Usmanu Danfodiyo University, Sokoto, Nigeria" + }, + { + "author_name": "Yusuf Yahaya Deeni", + "author_inst": "Department of Microbiology and Biotechnology, Federal University of Dutse, Dutse, Nigeria" + }, + { + "author_name": "Ifeoma Okoye", + "author_inst": "University of Nigeria Centre for Clinical Trials, University of Nigeria Teaching Hospital, Enugu, Ituku Ozalla, Nigeria" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "biochemistry" + "category": "pharmacology and toxicology" }, { "rel_doi": "10.1101/2022.12.25.521784", @@ -124965,35 +124427,55 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2022.12.22.521558", - "rel_title": "Common dandelion (Taraxacum officinale) leaf extract efficiently inhibits SARS-CoV-2 Omicron infection in vitro", - "rel_date": "2022-12-22", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.22.521558", - "rel_abs": "As the COVID-19 pandemic continues to pose a health risk concern to humans, despite a significant increase in vaccination rates, an effective prevention and treatment of SARS-CoV-2 infection is being sought worldwide. Herbal medicines have been used for years and played a tremendous role in several epidemics of respiratory viral infections. Thus, they are considered as a promising platform to combat SARS-CoV-2. Previously, we reported that common dandelion (Taraxacum officinale) leaf extract and its high molecular weight compounds strongly suppressed in vitro lung cell infection by SARS-CoV-2 Spike D614 and Delta variant pseudotyped lentivirus. We now here demonstrate that T. officinale extract protects against the most prominent Omicron variant using hACE2-TMPRSS2 overexpressing A549 cells as in vitro model system. Notably, compared to the original D614, and the Delta variant, we could confirm a higher efficacy. Short-term interval treatment of only 30 min was then sufficient to block the infection by 80% at 10 mg/mL extract. Further subfractionation of the extract identified compounds larger than 50 kDa as effective ACE2-Spike binding inhibitors. In summary, the evolution of SARS-CoV-2 virus to the highly transmissible Omicron variant did not lead to resistance, but rather increased sensitivity to the preventive effect of the extract.", - "rel_num_authors": 4, + "rel_doi": "10.1101/2022.12.20.22283729", + "rel_title": "Stratification of hypertensive COVID-19 patients by quantitative NMR spectroscopy of serum metabolites, lipoproteins and inflammation markers", + "rel_date": "2022-12-21", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.20.22283729", + "rel_abs": "BackgroundThe exact pathophysiology of humans suffering from the multifaceted SARS-CoV-2 infection is not yet conclusively understood and risk stratification is needed. Novel diagnostic approaches like the nuclear magnetic resonance spectroscopy (NMR) based quantification of metabolites, lipoproteins, and inflammation markers has helped to identify typical alterations in the blood serum of COVID-19 patients. However, important confounders such as age, sex, and comorbidities, which strongly influence the metabolome, were often not considered. Therefore, the aim of this NMR study was to consider gender, as well as arterial hypertension (AHT) which affects more than 1.2 billion people worldwide, when investigating COVID-19-positive serum samples in a large age-matched cohort. As AHT is a risk factor for severe COVID-19 disease, this study focuses on comparing metabolomic characteristics of COVID-19 patients with and without AHT.\n\nMethods and FindingsNMR serum data from 329 COVID-19 patients were compared with 305 individuals from a healthy age and sex-matched control cohort. 134 of the 329 COVID-19 patients were affected by AHT. These were analyzed together with NMR data from 58 hypertensives without COVID-19. In addition to metabolite, lipoprotein, and glycoprotein data from NMR, common laboratory parameters were considered. Statistical comparison of the COVID-19 cohort with the control cohort reproduced results of previous studies. However, several differences emerged when AHT was considered. Especially, the previously described triglyceride-rich lipoprotein profile was no longer observed in COVID-19 patients, nor was an increase in ketone bodies. Typical metabolic changes that were apparent in COVID-19 patients in both sexes and with AHT were an increase in C-reactive protein (CRP) and the ratio of total glycoprotein (Glyc) to supramolecular phospholipids composite (SPC) which is an inflammatory NMR parameter. Further alterations were a decrease in glutamine, leucine, isoleucine, and lysine, citric acid, HDL-4 particles, and total cholesterol. Typical metabolic cardiovascular risk markers could be detected in hypertensive COVID-19 patients, as well as higher inflammatory NMR parameters than in normotensive COVID-19 patients.\n\nConclusionWe could show that a more precise picture of COVID-19 blood serum parameters emerge when AHT is considered which accordingly should be included in future studies and would help for a refined patient stratification.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Hoai T.T. Tran", - "author_inst": "Molecular Preventive Medicine, University Medical Center and Faculty of Medicine, University of Freiburg, 79108 Freiburg, Germany" + "author_name": "Jasmin Kazenwadel", + "author_inst": "Werner Siemens Imaging Center, Department for Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, Germany" }, { - "author_name": "Michael Gigl", - "author_inst": "Food Chemistry and Molecular Sensory Science, Technical University of Munich, 85354 Freising, Germany." + "author_name": "Georgy Berezhnoy", + "author_inst": "Werner Siemens Imaging Center, Department for Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, Germany" }, { - "author_name": "Corinna Dawid", - "author_inst": "Food Chemistry and Molecular Sensory Science, Technical University of Munich, 85354 Freising, Germany" + "author_name": "Claire Cannet", + "author_inst": "Bruker BioSpin GmbH, Applied Industrial and Clinical Division, Ettlingen, Germany" }, { - "author_name": "Evelyn Lamy", - "author_inst": "Molecular Preventive Medicine, University Medical Center and Faculty of Medicine, University of Freiburg, 79108 Freiburg, Germany" + "author_name": "Hartmut Schaefer", + "author_inst": "Bruker BioSpin GmbH, Applied Industrial and Clinical Division, Ettlingen, Germany" + }, + { + "author_name": "Tobias Geisler", + "author_inst": "Department of Internal Medicine III, Cardiology and Angiology, University Hospital Tuebingen, Tuebingen, Germany" + }, + { + "author_name": "Anne-Kathrin Rohlfing", + "author_inst": "Department of Internal Medicine III, Cardiology and Angiology, University Hospital Tuebingen, Tuebingen, Germany" + }, + { + "author_name": "Meinrad Gawaz", + "author_inst": "Department of Internal Medicine III, Cardiology and Angiology, University Hospital Tuebingen, Tuebingen, Germany" + }, + { + "author_name": "Uta Merle", + "author_inst": "Department of Internal Medicine IV, University Hospital Heidelberg, Heidelberg, Germany" + }, + { + "author_name": "Christoph Trautwein", + "author_inst": "Werner Siemens Imaging Center, Department for Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, Germany" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.12.21.521431", @@ -126703,35 +126185,123 @@ "category": "endocrinology" }, { - "rel_doi": "10.1101/2022.12.18.22283642", - "rel_title": "Changes in cancer prevention and management and patient needs during the COVID-19 pandemic: An umbrella review of systematic reviews", + "rel_doi": "10.1101/2022.12.16.22283585", + "rel_title": "COVID-19 Convalescent Plasma Outpatient Therapy to Prevent Outpatient Hospitalization: A Meta-analysis of Individual Participant Data From Five Randomized Trials", "rel_date": "2022-12-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.18.22283642", - "rel_abs": "IntroductionThe COVID-19 pandemic led to relocation and reconstruction of health care resources and systems, and to a decrease in healthcare utilization, and this may have affected the treatment, diagnosis, prognosis, and psychosocial well-being of cancer patients.\n\nObjectiveTo summarize and quantify the evidence on the impact of the COVID-19 pandemic on the full spectrum of cancer care.\n\nMethodsWe performed an umbrella review to summarize and quantify the findings from systematic reviews on impact of the COVID-19 pandemic on cancer treatment modification, delays, and cancellations; delays or cancellations in screening and diagnosis; psychosocial well-being, financial distress, and use of telemedicine as well as on other aspects of cancer care. PubMed was searched for relevant systematic reviews with or without meta-analysis published before November 29th, 2022. Abstract, full text screening and data extraction were performed by two independent reviewers. AMSTAR-2 was used for critical appraisal of included systematic reviews.\n\nResults45 systematic reviews evaluating different aspects of cancer care were included in our analysis. Most reviews were based on observational studies judged to be at medium and high risk of bias. Only 2 of the included reviews had high or moderate scores based on AMSTAR-2. Findings suggest treatment modifications in cancer care during the pandemic versus the pre-pandemic period were based on low level of evidence. Different degrees of delays and cancellations in cancer treatment, screening and diagnosis were observed, with low-and-middle income countries and countries that implemented lockdowns being disproportionally affected. A shift from in-person appointments to telemedicine use was observed, but utility of telemedicine, challenges in implementation and cost-effectiveness in different areas of cancer care were little explored. Evidence was consistent in suggesting psychosocial well-being (e.g., depression, anxiety, and social activities) of cancer patients deteriorated, and cancer patients experienced financial distress, albeit results were in general not compared to pre-pandemic levels. Impact of cancer care disruption during the pandemic on cancer prognosis was little explored.\n\nConclusionSubstantial but heterogenous impact of COVID-19 pandemic on cancer care has been observed. Evidence gaps exist on this topic, with mid- and long-term impact on cancer care being most uncertain.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.16.22283585", + "rel_abs": "BackgroundMonoclonal antibody and antiviral treatments for COVID-19 disease remain largely unavailable worldwide, and existing monoclonal antibodies may be less active against circulating omicron variants. Although treatment with COVID-19 convalescent plasma (CCP) is promising, randomized clinical trials (RCTs) among outpatients have shown mixed results.\n\nMethodsWe conducted an individual participant data meta-analysis from all outpatient CCP RCTs to assess the overall risk reduction for all-cause hospitalizations by day 28 in all participants who had transfusion initiated. Relevant trials were identified by searching MEDLINE, Embase, MedRxiv, WHO, Cochrane Library, and Web of Science from January 2020 to September 2022.\n\nResultsFive included studies from four countries enrolled and transfused 2,620 adult patients. Comorbidities were present in 1,795 (69%). The anti-Spike or virus neutralizing antibody titer range across all trials was broad. 160 (12.2%) of 1315 control patients were hospitalized, versus 111 (8.5%) of 1305 CCP-treated patients, yielding a 3.7% (95%CI: 1.3%-6.0%; p=.001) ARR and 30.1% RRR for all-cause hospitalization. The effect size was greatest in those with both early transfusion and high titer with a 7.6% ARR (95%CI: 4.0%-11.1%; p=.0001) accompanied by at 51.4% RRR. No significant reduction in hospitalization was seen with treatment > 5 days after symptom onset or in those receiving CCP with antibody titers below the median titer.\n\nConclusionsAmong outpatients with COVID-19, treatment with CCP reduced the rate of all-cause hospitalization. CCP may be most effective when given within 5 days of symptom onset and when antibody titer is higher.\n\nKey PointsWhile the outpatient COVID-19 randomized controlled trial meta-analysis indicated heterogeneity in participant risk factors and convalescent plasma, the combined CCP efficacy for reducing hospitalization was significant, improving with transfusion within 5 days of symptom onset and high antibody neutralization levels.", + "rel_num_authors": 26, "rel_authors": [ { - "author_name": "Taulant Muka", - "author_inst": "Institute of Social and Preventive Medicine, University of Bern" + "author_name": "Adam C Levine", + "author_inst": "Brown University" }, { - "author_name": "Joshua J X Li", - "author_inst": "Department of Anatomical and Cellular Pathology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong" + "author_name": "Yuriko Fukuta", + "author_inst": "Baylor College of Medicine" }, { - "author_name": "Sahar J. Farahani", - "author_inst": "Department of Pathology and Laboratory Medicine, Stony Brook University, Long Island, New York" + "author_name": "Moises Huaman", + "author_inst": "University of Cincinnati College of Medicine" }, { - "author_name": "John Ioannidis", - "author_inst": "Stanford University" + "author_name": "Jiangda Ou", + "author_inst": "Johns Hopkins University School of Medicine" + }, + { + "author_name": "Barry Meisenberg", + "author_inst": "Anne Arundel Medical Center," + }, + { + "author_name": "Bela Patel", + "author_inst": "University of Texas Health Science Center McGovern Medical School" + }, + { + "author_name": "James Paxton", + "author_inst": "Wayne State University School of Medicine" + }, + { + "author_name": "Daniel F Hanley", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Bart Rijnders", + "author_inst": "Erasmus MC" + }, + { + "author_name": "Arvind Gharbharan", + "author_inst": "Erasmus MC, University Medical Center" + }, + { + "author_name": "Casper Rokx", + "author_inst": "Erasmus Medical Centre: Erasmus MC" + }, + { + "author_name": "Jaap Jan Zwaginga", + "author_inst": "Leiden University Medical Centre," + }, + { + "author_name": "Andrea Alemany", + "author_inst": "Hospital Universitari Germans Trias i Pujol" + }, + { + "author_name": "Oriol Mitja", + "author_inst": "Fundacion de Lucha contra el Sida y las enfermedades infecciosas" + }, + { + "author_name": "Dan Ouchi", + "author_inst": "Hospital Universitari Germans Trias i Pujol" + }, + { + "author_name": "Pere Millat-Martinez", + "author_inst": "Universitat de Barcelona" + }, + { + "author_name": "Valerie Durkalski Mauldin", + "author_inst": "Medical University of South Carolina" + }, + { + "author_name": "Frederick K Korley", + "author_inst": "University of Michigan" + }, + { + "author_name": "Larry J Dumont", + "author_inst": "Vitalant Research Institute" + }, + { + "author_name": "Clifton W Callaway", + "author_inst": "University of Pittsburgh," + }, + { + "author_name": "Romina Libster", + "author_inst": "Fundacion INFANT" + }, + { + "author_name": "Gonzalo Perez Marc", + "author_inst": "17.\tFundacion INFANT" + }, + { + "author_name": "Diego Wappner", + "author_inst": "17.\tFundacion INFANT" + }, + { + "author_name": "Ignacio Esteban", + "author_inst": "17.\tFundacion INFANT" + }, + { + "author_name": "Fernando Polack", + "author_inst": "Vanderbilt University and Fundacion INFANT" + }, + { + "author_name": "David J Sullivan", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.12.16.22283554", @@ -128701,47 +128271,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.12.15.22283480", - "rel_title": "Prevalence of salivary anti-SARS-CoV-2 IgG antibodies in vaccinated children", + "rel_doi": "10.1101/2022.12.15.22283550", + "rel_title": "Depression and its associated factors among COVID-19 survivors in a middle income country", "rel_date": "2022-12-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.15.22283480", - "rel_abs": "Vaccination against COVID-19 has mitigated the impact of SARS-CoV-2 infection, decreasing the probability of progression to severe disease and death in vaccinated people.\n\nParallel to the development and administration of COVID-19 vaccines, the immune response induced by the different vaccine platforms has been investigated, mainly, in the adult population. However, since the approval of the vaccines for use in pediatric individuals was a posteriori, vaccination began later in this population. This, added to the difficulty in obtaining blood samples from pediatric individuals, has led to less knowledge about the humoral immune response following vaccination in children.\n\nIn this work, we analyzed the humoral response induced by vaccination in children through a non-invasive approach such as the measurement of specific salivary antibodies. Our results showed a high prevalence of specific salivary antibodies (81%), with the highest levels of antibodies being observed in those children who had three doses, a greater number of exposures and a shorter interval time between the last exposure to SARS-CoV-2 antigens and saliva collection. These results agree with those reported for the systemic humoral immune response in vaccinated adults, suggesting the administration of booster doses in children to maintain high antibody levels.\n\nTherefore, determination of salivary antibodies against SARS-CoV-2 could be a non-invasive tool for disease surveillance, vaccination follow-up and to assist vaccination strategies against COVID-19.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.15.22283550", + "rel_abs": "IntroductionCOVID-19 survivors who have mental health issues are more likely to have a lower quality of life, reduced work productivity, social troubles, and other health issues. However, information on the mental health of COVID-19 survivors is scarce. Therefore, we aimed to determine the COVID-19 survivors mental health status in the form of depression and its associated factors.\n\nMethodsThis was a cross-sectional study conducted in Malaysia, from July to September 2021, during a nationwide lockdown. Data was collected using an online questionnaire shared on social and news media. Socio-demographic variables, comorbidities, self-perception of health, information on the persons acute condition during COVID-19 infection, symptoms and duration of symptoms post-COVID, and state of depression were gathered. The Patient Health Questionnaire 9 was used to assess depression. Factors associated with mild to severe depression were analysed using both univariable and multivariable logistic regression analyses.\n\nResultsA total of 732 COVID-19 survivors responded to the survey. The respondents were mainly females and of younger age (in their 20s and 30s). Two-thirds perceived themselves to be in good health. One in five reported to have experienced Long COVID. Slightly less than half (47.3%) of the respondents had mild to severe depression (total PHQ-9 score of 5 -27). In the multivariable analysis, being female (aOR: 1.68; 95% CI: 1.08,2.62), of younger age (20s - aOR: 3.26; 95% CI: 1.47, 7.25; 30s - aOR: 2.08; 95% CI: 1.05, 4.15; and 40s - aOR: 2.43; 95% CI: 1.20, 4.90; compared to those in the 50s and above), being overweight/obese (aOR: 1.83; 95% CI: 1.18, 2.83), having Long COVID (aOR: 2.45; 95% CI: 1.45, 4.16) and perceiving to have poorer health (aOR: 4.54; 95% CI: 2.89, 7.13) were associated with mild to severe depression.\n\nConclusionFemales, younger age groups, being overweight/obese, having Long COVID and perceiving to be in poor health were factors associated with higher odds for mild to severe depression.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Maria Noel Badano", - "author_inst": "Instituto de Medicina Experimental (IMEX)-Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET), Academia Nacional de Medicina" - }, - { - "author_name": "Alejandra Duarte", - "author_inst": "Instituto de Medicina Experimental (IMEX)-Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET), Academia Nacional de Medicina" - }, - { - "author_name": "Gabriela Salamone", - "author_inst": "Instituto de Medicina Experimental (IMEX)-Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET), Academia Nacional de Medicina" - }, - { - "author_name": "Florencia Sabbione", - "author_inst": "Instituto de Medicina Experimental (IMEX)-Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET), Academia Nacional de Medicina" + "author_name": "Foong Ming Moy", + "author_inst": "University of Malaya Faculty of Medicine" }, { - "author_name": "Matias Javier Pereson", - "author_inst": "IBAVIM - Facultad de Farmacia y Bioquimica" + "author_name": "Eugene Ri Jian Lim", + "author_inst": "International Medical University" }, { - "author_name": "Roberto Chuit", - "author_inst": "Instituto de Investigaciones Epidemiologicas (IIE), Academia Nacional de Medicina" + "author_name": "Noran Naqiah Hairi", + "author_inst": "University of Malaya Faculty of Medicine" }, { - "author_name": "Patricia Bare", - "author_inst": "Instituto de Medicina Experimental (IMEX)-Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET), Academia Nacional de Medicina" + "author_name": "Awang Bulgiba", + "author_inst": "University of Malaya Faculty of Medicine" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.12.15.22282988", @@ -130459,263 +130017,79 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.12.13.22283391", - "rel_title": "The effects of sleep disturbance on dyspnoea and impaired lung function following COVID-19 hospitalisation: a prospective multi-centre cohort study", + "rel_doi": "10.1101/2022.12.12.22283285", + "rel_title": "Vendors' perceptions on the bushmeat trade dynamics across West Africa during the COVID-19 pandemic: lessons learned on sanitary measures and awareness campaigns", "rel_date": "2022-12-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.13.22283391", - "rel_abs": "BackgroundSleep disturbance is common following hospitalisation both for COVID-19 and other causes. The clinical associations are poorly understood, despite it altering pathophysiology in other scenarios. We, therefore, investigated whether sleep disturbance is associated with dyspnoea along with relevant mediation pathways.\n\nMethodsSleep parameters were assessed in a prospective cohort of patients (n=2,468) hospitalised for COVID-19 in the United Kingdom in 39 centres using both subjective and device-based measures. Results were compared to a matched UK biobank cohort and associations were evaluated using multivariable linear regression.\n\nFindings64% (456/714) of participants reported poor sleep quality; 56% felt their sleep quality had deteriorated for at least 1-year following hospitalisation. Compared to the matched cohort, both sleep regularity (44.5 vs 59.2, p<0.001) and sleep efficiency (85.4% vs 88.5%, p<0.001) were lower whilst sleep period duration was longer (8.25h vs 7.32h, p<0.001). Overall sleep quality (effect estimate 4.2 (3.0-5.5)), deterioration in sleep quality following hospitalisation (effect estimate 3.2 (2.0-4.5)), and sleep regularity (effect estimate 5.9 (3.7-8.1)) were associated with both dyspnoea and impaired lung function (FEV1 and FVC). Depending on the sleep metric, anxiety mediated 13-42% of the effect of sleep disturbance on dyspnoea and muscle weakness mediated 29-43% of this effect.\n\nInterpretationSleep disturbance is associated with dyspnoea, anxiety and muscle weakness following COVID-19 hospitalisation. It could have similar effects for other causes of hospitalisation where sleep disturbance is prevalent.\n\nFundingUK Research and Innovation, National Institute for Health Research, and Engineering and Physical Sciences Research Council.", - "rel_num_authors": 61, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.12.22283285", + "rel_abs": "In West Africa, the bushmeat trade is a major societal issue with contrasting implications on biodiversity, health and economy. We studied perceptions of the impact of the COVID-19 pandemic on the bushmeat trade dynamics through questionnaires addressed to 377 vendors across three West African countries. We showed that bushmeat vendors constitute a socio-economic category driven by ethnicity and gender bias, engaged in profitable, long-term careers. There was a general consensus among vendors that the COVID-19 pandemic and related governmental measures had a negative impact on their activities and the number of clients, a cost still perceived as visible at the time of the survey. However, we observed large discrepancies among the national trade dynamics relative to the constraints of the pandemic. Cote dIvoire was hardly hit by the bushmeat ban and perceived governmental measures as rather negative, whereas Cameroon generally did not report a temporary stop of bushmeat activities and engaged in the stockpiling of pangolins, and Benin mostly suffered from a weakened supply chain. Because such differences are rooted in the geography and political agenda of each country, predicting the impact of mitigation measures on the global dynamics of bushmeat markets might be an unrealistic task if national specificities are not taken into account. West African vendors generally did not believe that pangolins were involved in the pandemic, for the reason that people have always been eating pangolins and have never been sick. We recommend that future awareness campaigns through television and social networks also include education on microbial evolution and host shift.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Callum Jackson", - "author_inst": "Department of Mathematics, The University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom" - }, - { - "author_name": "Iain Stewart", - "author_inst": "National Heart & Lung Institute, Imperial College London, London, UK" - }, - { - "author_name": "Tatiana Plekhanova", - "author_inst": "Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK" - }, - { - "author_name": "Peter Cunningham", - "author_inst": "Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester M13 9PL United Kingdom" - }, - { - "author_name": "Andrew L. Hazel", - "author_inst": "Department of Mathematics, The University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom" - }, - { - "author_name": "Bashar Al-Sheklly", - "author_inst": "Manchester University NHS Foundation Trust & University of Manchester" - }, - { - "author_name": "Raminder Aul", - "author_inst": "St Georges Univeristy Hospitals NHS Foundation Trust, London, UK" - }, - { - "author_name": "Charlotte E. Bolton", - "author_inst": "NIHR Nottingham BRC respiratory theme, Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK" - }, - { - "author_name": "Trudie Chalder", - "author_inst": "Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom" - }, - { - "author_name": "James D. Chalmers", - "author_inst": "University of Dundee, Ninewells Hospital and Medical School, Dundee, UK" - }, - { - "author_name": "Nazia Chaudhuri", - "author_inst": "University Hospital of South Manchester NHS Foundation Trust" - }, - { - "author_name": "Annemaire B. Docherty", - "author_inst": "Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK" - }, - { - "author_name": "Gavin Donaldson", - "author_inst": "National Heart & Lung Institute, Imperial College London, London, UK" - }, - { - "author_name": "Charlotte L. Edwardson", - "author_inst": "Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK" - }, - { - "author_name": "Omer Elneima", - "author_inst": "NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK" - }, - { - "author_name": "Neil J Greening", - "author_inst": "NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK" - }, - { - "author_name": "Neil A. Hanley", - "author_inst": "Manchester University NHS Foundation Trust" - }, - { - "author_name": "Victoria C. Harris", - "author_inst": "NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK" - }, - { - "author_name": "Ewen M. Harrison", - "author_inst": "Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK" - }, - { - "author_name": "Ling-Pei Ho", - "author_inst": "Oxford University Hospitals NHS Foundation Trust & University of Oxford" - }, - { - "author_name": "Linzy Houchen-Wolloff", - "author_inst": "Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK" - }, - { - "author_name": "Luke S. Howard", - "author_inst": "National Heart & Lung Institute, Imperial College London, London, UK" - }, - { - "author_name": "Caroline J. Jolley", - "author_inst": "King's College London" - }, - { - "author_name": "Mark G. Jones", - "author_inst": "Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK" - }, - { - "author_name": "Olivia C. Leavy", - "author_inst": "Department of Health Sciences, Univeristy of Leicester, Leicester, UK" - }, - { - "author_name": "Keir E. Lewis", - "author_inst": "Swansea University, Swansea Welsh Network, Hywel Dda University Health Board" - }, - { - "author_name": "Nazir I. Lone", - "author_inst": "Usher Institute, University of Edinburgh, Edinburgh, UK" - }, - { - "author_name": "Michael Marks", - "author_inst": "Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK" - }, - { - "author_name": "Hamish J. C. McAuley", - "author_inst": "NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK" - }, - { - "author_name": "Melitta A. McNarry", - "author_inst": "Swansea University, Swansea Welsh Network, Hywel Dda University Health Board" - }, - { - "author_name": "Brijesh Patel", - "author_inst": "Royal Brompton and Harefield Clinical Group, Guys and St Thomas NHS Foundation trust" - }, - { - "author_name": "Karen Piper-Hanley", - "author_inst": "Manchester University NHS Foundation Trust & University of Manchester" - }, - { - "author_name": "Krisnah Poinasamy", - "author_inst": "Asthma UK and British Lung Foundation, London, UK" - }, - { - "author_name": "Betty Raman", - "author_inst": "Oxford University Hospitals NHS Foundation Trust & University of Oxford" - }, - { - "author_name": "Matthew Richardson", - "author_inst": "NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK" - }, - { - "author_name": "Pilar Rivera-Ortega", - "author_inst": "Manchester University NHS Foundation Trust" - }, - { - "author_name": "Sarah L. Rowland-Jones", - "author_inst": "University of Sheffield, Sheffield, UK" - }, - { - "author_name": "Alex V. Rowlands", - "author_inst": "Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK" - }, - { - "author_name": "Ruth M. Saunders", - "author_inst": "NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK" - }, - { - "author_name": "Janet T Scott", - "author_inst": "MRC - University of Glasgow Centre for Virus Research, Glasgow, UK" - }, - { - "author_name": "Marco Sereno", - "author_inst": "NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK" - }, - { - "author_name": "Ajay M. Shah", - "author_inst": "King's College Hospital NHS Foundation Trust & Kings College London" - }, - { - "author_name": "Aarti Shikotra", - "author_inst": "NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK" - }, - { - "author_name": "Amisha Singapuri", - "author_inst": "NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK" - }, - { - "author_name": "Stefan C. Stanel", - "author_inst": "Interstitial Lung Disease Unit, North West Lung Centre, Wythenshawe Hospital, Southmoor Rd, Wythenshawe, Manchester M23 9LT, UK" + "author_name": "Philippe Gaubert", + "author_inst": "IRD" }, { - "author_name": "Mathew Thorpe", - "author_inst": "Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK" + "author_name": "Chabi A.M.S. Djagoun", + "author_inst": "Universite d'Abomey Calavi" }, { - "author_name": "Daniel G. Wootton", - "author_inst": "Liverpool University Hospitals NHS Foundation Trust & University of Liverpool" + "author_name": "Alain Didier Missoup", + "author_inst": "Universite de Douala" }, { - "author_name": "Thomas Yates", - "author_inst": "Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK" + "author_name": "Nazif Ales", + "author_inst": "Universite d'Abomey Calavi" }, { - "author_name": "R Gisli Jenkins", - "author_inst": "National Heart & Lung Institute, Imperial College London, London, UK" + "author_name": "Claude Vianney Amougou", + "author_inst": "Universite de Douala" }, { - "author_name": "Sally Singh", - "author_inst": "University Hospitals of Leicester NHS Trust & University of Leicester" + "author_name": "Alain Din Dipita", + "author_inst": "Universite de Douala" }, { - "author_name": "William D-C. Man", - "author_inst": "National Heart & Lung Institute, Imperial College London, London, UK" + "author_name": "Joel Djagoun", + "author_inst": "Universite d'Abomey Calavi" }, { - "author_name": "Chris E. Brightling", - "author_inst": "University Hospitals of Leicester NHS Trust & University of Leicester" + "author_name": "Koffi Jules Gosse", + "author_inst": "Universite F. Houphouet Boigny" }, { - "author_name": "Louise V. Wain", - "author_inst": "NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK" + "author_name": "Cecilia Esperance Koffi", + "author_inst": "Universite F. Houphouet Boigny" }, { - "author_name": "Joanna C. Porter", - "author_inst": "Department of Respiratory Medicine, University College London WC1E 2JF" + "author_name": "Edwige Michele N'Goran", + "author_inst": "Universite F. Houphouet Boigny" }, { - "author_name": "A. A. Roger Thompson", - "author_inst": "Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield UK" + "author_name": "Yves Noma Noma", + "author_inst": "Universite F. Houphouet Boigny" }, { - "author_name": "Alexander Horsley", - "author_inst": "Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester M13 9PL United Kingdom" + "author_name": "Stanislas Zanvo", + "author_inst": "Universite d'Abomey Calavi" }, { - "author_name": "Phil L. Molyneaux", - "author_inst": "National Heart & Lung Institute, Imperial College London, London, UK" + "author_name": "Maurice Tindo", + "author_inst": "Universite de Douala" }, { - "author_name": "Rachael E. Evans", - "author_inst": "NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK" - }, - { - "author_name": "Samuel E. Jones", - "author_inst": "Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland" - }, - { - "author_name": "Martin K. Rutter", - "author_inst": "Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester M13 9PL United Kingdom" + "author_name": "Agostinho Antunes", + "author_inst": "University of Porto" }, { - "author_name": "John F. Blaikley", - "author_inst": "The University of Manchester" + "author_name": "Sery Gonedele Bi", + "author_inst": "Universite F. Houphouet Boigny" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "health policy" }, { "rel_doi": "10.1101/2022.12.12.22283367", @@ -132496,31 +131870,27 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.11.29.22282883", - "rel_title": "The protection gap under a social health protection initiative in the COVID-19 pandemic: A case study from Khyber Pakhtunkhwa, Pakistan.", + "rel_doi": "10.1101/2022.12.12.22283346", + "rel_title": "Estimating Subnation Excess Mortality in Times of Pandemic. An application to French Departements in 2020.", "rel_date": "2022-12-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.29.22282883", - "rel_abs": "BackgroundSehat Sahulat Programme (SSP) is a Social Health Protection (SHP) initiative by the Government of Khyber Pakhtunkhwa (GoKP), covering inpatient services for 100% of the provinces population. In this paper, we describe SSPs role in GoKPs COVID-19 response and draw inferences for similar programmes in Pakistan.\n\nMethodology and methodsWe conceptualised SSP as an instrumental case study and collected three complementary data sources. First, we studied GoKPs official documents to understand SSPs benefits package. Then we undertook in-depth interviews and collected non-participant observations at the SSP policy and implementation levels. We recruited participants through direct (verbal and email) and indirect (invitation posters) methods.\n\nUse of maximum variation sampling enabled us to understand contrasting views from various stakeholders on SSPs policy dimensions (i.e., coverage and financing), tensions between the policy directions (i.e., whether or not to cover COVID-19) and how policy decisions were made and implemented. We collected data from March 2021 to December 2021. Thematic analysis was conducted with the help of Nvivo12.\n\nFindingsThroughout 2020, SSP did not cover COVID-19 treatment. The insurer and GoKP officials considered the pandemic a standard exclusion to insurance coverage. One SSP official said: \"COVID-19 is not covered and not relevant to us\". GoKP had stopped non-emergency services at all hospitals. When routine services restarted, the insurer did not cover COVID-19 screening tests, which were mandatory prior to hospital admission.\n\nIn 2021, GoKP engaged 10 private SSP hospitals for COVID-19 treatment. The SSP Reserve Fund, rather than insurance pooled money, was used. The Reserve Fund was originally meant to cover high-cost organ transplants. In 2021, SSP had 1,002 COVID-19-related admissions, which represented 0.2% of all hospital admissions (N=544,841).\n\nAn advocacy group representative called the COVID-19 care under SSP \"too little too late\". In contrast, SSP officials suggested their insurance database and funds flow mechanism could help GoKP in future health emergencies.\n\nConclusionThe commercially focused interpretation of SHP arrangements led to a protection gap in the context of COVID-19. SSP and similar programmes in other provinces of Pakistan should emphasise the notion of protection and not let commercial interests lead to protection gaps.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.12.22283346", + "rel_abs": "The Covid-19 pandemic did not affect sub-national regions in a uniform way. Knowledge of the impact of the pandemic on mortality at the local level is therefore an important issue for better assessing its burden. Vital statistics are now available for an increasing number of countries for 2020 and 2021, and allow the calculation of sub-national excess mortality. However, this calculation faces two important methodological challenges: (1) it requires appropriate mortality projection models; (2) small populations implies important uncertainty in the estimates, commonly neglected. We address both issues by adopting a method to forecast mortality at sub-national level and by incorporating uncertainty in the computation of mortality measures. We illustrate our approach to French departements (NUTS 3, 95 geographical units) and produce estimates for 2020 and both sexes. Nonetheless, the proposed approach is so flexibility to allow estimation of excess mortality during Covid-19 in most demographic scenarios as well as for past pandemics.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Sheraz Ahmad Khan", - "author_inst": "The University of Edinburgh" - }, - { - "author_name": "Kathrin Cresswell", - "author_inst": "The University of Edinburgh College of Medicine and Veterinary Medicine" + "author_name": "Florian Bonnet", + "author_inst": "Institut National d'Etudes Demographiques" }, { - "author_name": "Aziz Sheikh", - "author_inst": "The University of Edinburgh College of Medicine and Veterinary Medicine" + "author_name": "Carlo Giovanni Camarda", + "author_inst": "Institut National d'Etudes Demographiques" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.12.07.22283234", @@ -134350,41 +133720,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.12.07.22283193", - "rel_title": "Causal Inference of CNS-regulated Hormones in COVID-19: A Bidirectional Two-sample Mendelian Randomization Study", + "rel_doi": "10.1101/2022.12.06.22283145", + "rel_title": "Serious harms of the COVID-19 vaccines: a systematic review", "rel_date": "2022-12-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.07.22283193", - "rel_abs": "ObjectivesWe assessed the causal association of three COVID-19 phenotypes with insulin-like growth factor 1 (IGF-1), estrogen, testosterone, dehydroepiandrosterone (DHEA), thyroid-stimulating hormone (TSH), thyrotropin-releasing hormone (TRH), luteinizing hormone (LH), and follicle-stimulating hormone (FSH).\n\nMethodsWe used a bidirectional two-sample univariate and multivariable Mendelian randomization (MR) analysis to evaluate the direction, specificity, and causality of the association between CNS-regulated hormones and COVID-19 phenotypes. Genetic instruments for CNS-regulated hormones were selected from the largest publicly available genome-wide association studies in the European population. Summary-level data on COVID-19 severity, hospitalization, and susceptibility were obtained from the COVID-19 host genetic initiative.\n\nResultsDHEA was associated with increased risks of very severe respiratory syndrome (OR=4.21, 95% CI: 1.41-12.59), consistent with the results in multivariate MR (OR=3.72, 95% CI: 1.20-11.51), and hospitalization (OR = 2.31, 95% CI: 1.13-4.72) in univariate MR. LH was associated with very severe respiratory syndrome (OR=0.83; 95% CI: 0.71-0.96) in univariate MR. Estrogen was negatively associated with very severe respiratory syndrome (OR=0.09, 95% CI: 0.02-0.51), hospitalization (OR=0.25, 95% CI: 0.08-0.78), and susceptibility (OR=0.50, 95% CI: 0.28-0.89) in multivariate MR.\n\nConclusionsWe found strong evidence for the causal relationship of DHEA, LH, and estrogen with COVID-19 phenotypes.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.06.22283145", + "rel_abs": "BACKGROUNDSerious and severe harms of the COVID-19 vaccines have been downplayed or deliberately excluded by the study sponsors in high impact medical journals.\n\nMETHODSSystematic review of papers with data on serious adverse events (SAEs) associated with a COVID-19 vaccine.\n\nRESULTSWe included 18 systematic reviews, 14 randomised trials, and 34 other studies with a control group. Most studies were of poor quality. A systematic review of regulatory data on the two pivotal trials of the mRNA vaccines found significantly more SAEs of special interest with the vaccines compared to placebo, and the excess risk was considerably larger than the benefit, the risk of hospitalisation. The adenovirus vector vaccines increased the risk of venous thrombosis and thrombocytopenia, and the mRNA-based vaccines increased the risk of myocarditis, with a mortality of about 1-2 per 200 cases. We found evidence of serious neurological harms, including Bells palsy, Guillain-Barre syndrome, myasthenic disorder and stroke, which are likely due to an autoimmune reaction. Severe harms, i.e. those that prevent daily activities, were underreported in the randomised trials. These harms were very common in studies of booster doses after a full vaccination and in a study of vaccination of previously infected people.\n\nCONCLUSIONSFurther randomised trials are needed. Authorities have recommended populationwide COVID-19 vaccination and booster doses. They do not consider that the balance between benefits and harms becomes negative in low-risk groups such as children and people who have already recovered from COVID-19 infection.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Yuxuan Sun", - "author_inst": "The Seventh Affiliated Hospital, Sun Yat-sen University" + "author_name": "Peter C Gotzsche", + "author_inst": "Institute for Scientific Freedom" }, { - "author_name": "Ziyi Ding", - "author_inst": "The Herbert Wertheim School of Public Health and Longevity, University of California San Diego" - }, - { - "author_name": "Yawei Guo", - "author_inst": "School of Public Health, Sun Yat-sen University" - }, - { - "author_name": "Jinqiu Yuan", - "author_inst": "The Seventh Affiliated Hospital, Sun Yat-sen University" - }, - { - "author_name": "Chengming Zhu", - "author_inst": "The Seventh Affiliated Hospital, Sun Yat-sen University" - }, - { - "author_name": "Yihang Pan", - "author_inst": "The Seventh Affiliated Hospital, Sun Yat-sen University" - }, - { - "author_name": "Rui Sun", - "author_inst": "The Seventh Affiliated Hospital, Sun Yatsen University" + "author_name": "Maryanne Demasi", + "author_inst": "Institute for Scientific Freedom" } ], "version": "1", @@ -136036,47 +135386,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.12.02.518611", - "rel_title": "New insights into the structure of Comirnaty Covid-19 vaccine: A theory on soft nanoparticles with mRNA-lipid supercoils stabilized by hydrogen bonds", + "rel_doi": "10.1101/2022.12.05.518843", + "rel_title": "Convergent evolution in SARS-CoV-2 Spike creates a variant soup that causes new COVID-19 waves.", "rel_date": "2022-12-05", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.02.518611", - "rel_abs": "Despite the worldwide success of mRNA-LNP Covid-19 vaccines, the nanoscale structure of these formulations is still poorly understood. To fill this gap, we used a combination of atomic force microscopy (AFM), dynamic light scattering (DLS), transmission electron microscopy (TEM), cryogenic transmission electron microscopy (cryo-TEM) and the determination of LNP pH gradient to analyze the nanoparticles (NPs) in BNT162b2 (Comirnaty), comparing it with the well characterized pegylated liposomal doxorubicin (Doxil). Comirnaty NPs had similar size to Doxil, however, unlike Doxil liposomes, wherein the stable ammonium and pH gradient enables accumulation of 14C-methylamine in the intraliposomal aqueous phase, Comirnaty LNPs lack such pH gradient in spite of the fact that the pH 4, at which LNPs are prepared, is raised to pH 7.2 after loading of the mRNA. Mechanical manipulation of Comirnaty NPs with AFM revealed soft, compliant structures. The sawtooth-like force transitions seen during cantilever retraction implies that molecular strands, corresponding to mRNA, can be pulled out of NPs, and the process is accompanied by stepwise rupture of mRNA-lipid bonds. Unlike Doxil, cryo-TEM of Comirnaty NPs revealed a granular, solid core enclosed by mono- and bilayers. Negative staining TEM shows 2-5 nm electron-dense spots in the liposoms interior that are aligned into strings, semicircles, or labyrinth-like networks, which may imply crosslink-stabilized supercoils. The neutral intra-LNP core questions the dominance of ionic interactions holding together this scaffold, raising the alternative possibility of hydrogen bonding between the mRNA and the lipids. Such interaction, described previously for another mRNA/lipid complex, is consistent with the steric structure of ionizable lipid in Comirnaty, ALC-0315, displaying free =O and -OH groups. It is hypothesized that the latter groups can get into steric positions that enable hydrogen bonding with the nitrogenous bases in the mRNA. These newly recognized structural features of mRNA-LNP may be important for the vaccines efficacy.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.05.518843", + "rel_abs": "The first 2 years of the COVID-19 pandemic were mainly characterized by convergent evolution of mutations of SARS-CoV-2 Spike protein at residues K417, L452, E484, N501 and P681 across different variants of concern (Alpha, Beta, Gamma, and Delta). Since Spring 2022 and the third year of the pandemic, with the advent of Omicron and its sublineages, convergent evolution has led to the observation of different lineages acquiring an additional group of mutations at different amino acid residues, namely R346, K444, N450, N460, F486, F490, Q493, and S494. Mutations at these residues have become increasingly prevalent during Summer and Autumn 2022, with combinations showing increased fitness. The most likely reason for this convergence is the selective pressure exerted by previous infection- or vaccine-elicited immunity. Such accelerated evolution has caused failure of all anti-Spike monoclonal antibodies, including bebtelovimab and cilgavimab. While we are learning how fast coronaviruses can mutate and recombine, we should reconsider opportunities for economically sustainable escape-proof combination therapies, and refocus antibody-mediated therapeutic efforts on polyclonal preparations that are less likely to allow for viral immune escape.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Janos Szebeni", - "author_inst": "Semmelweis University" - }, - { - "author_name": "Balint Kiss", - "author_inst": "Semmelweis University" - }, - { - "author_name": "Tamas Bozo", - "author_inst": "Semmelweis University" + "author_name": "Daniele Focosi", + "author_inst": "Azienda Ospedaliero-Universitaria Pisana, Italy" }, { - "author_name": "Keren Turjeman", - "author_inst": "Hebrew University-Hadassah Medical School" + "author_name": "Rodrigo Quiroga", + "author_inst": "Universidad Nacional de Cordoba, Argentina" }, { - "author_name": "Yael Levi-Kalisman", - "author_inst": "The Hebrew University of Jerusalem" + "author_name": "Scott McConnell", + "author_inst": "Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA" }, { - "author_name": "Yechezkel Barenholz", - "author_inst": "Hebrew University-Hadassah Medical School" + "author_name": "Marc C Johnson", + "author_inst": "University of Missouri, USA" }, { - "author_name": "Miklos Kellermayer", - "author_inst": "Semmelweis University" + "author_name": "Arturo Casadevall", + "author_inst": "Johns Hopkins School of Public Health, Baltimore, USA" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.12.03.518956", @@ -136423,8 +135765,8 @@ "rel_date": "2022-12-05", "rel_site": "bioRxiv", "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.03.518997", - "rel_abs": "Recent advancements in the use of single-cell technologies in large cohort studies enable the investigation of cellular response and mechanisms associated with disease outcome, including COVID-19. Several efforts have been made using single-cell RNA-sequencing to better understand the immune response to COVID-19 virus infection. Nonetheless, it is often difficult to compare or integrate data from multiple data sets due to challenges in data normalisation, metadata harmonisation, and having a common interface to quickly query and access this vast amount of data. Here we present Covidscope (http://covidsc.d24h.hk/), a well-curated open web resource that currently contains single-cell gene expression data and associated metadata of almost 5 million blood and immune cells extracted from almost 1,000 COVID-19 patients across 20 studies around the world. Our collection contains the integrated data with harmonised metadata and multi-level cell type annotations. By combining NoSQL and optimised index, our Covidscope achieves rapid subsetting of high-dimensional gene expression data based on both data set level, donor-level (e.g., age and sex of patients) and cell-level (e.g., expression of specific gene markers) metadata, enabling multiple efficient downstream single-cell meta-analysis.", - "rel_num_authors": 8, + "rel_abs": "With the recent advancement in single-cell technologies and the increased availability of integrative tools, challenges arise in easy and fast access to large collections of cell atlas. Existing cell atlas portals rarely are open sourced and adaptable, and do not support meta-analysis at cell level. Here, we present an open source, highly optimised and scalable architecture, named Scope+, to allow quick access, meta-analysis and cell-level selection of the atlas data. We applied this architecture to our well-curated 5 million Covid-19 blood and immune cells, as a portal, Covidscope (https://covidsc.d24h.hk/). We achieved efficient access to atlas-scale data via three strategies, such as server-side rendering, novel database optimization strategies and an innovative architectural design. Scope+ serves as an open source architecture for researchers to build on with their own atlas, and demonstrated its capability in the Covidscope portal for an effective meta-analysis to atlas data at cellular resolution for reproducible research.", + "rel_num_authors": 10, "rel_authors": [ { "author_name": "Danqing Yin", @@ -136450,6 +135792,14 @@ "author_name": "Yingxin Lin", "author_inst": "School of Mathematics and Statistics, University of Sydney" }, + { + "author_name": "Jiaxuan Zhang", + "author_inst": "Guangzhou National Laboratory" + }, + { + "author_name": "Jia Li", + "author_inst": "Guangzhou National Laboratory" + }, { "author_name": "Joshua W. K. Ho", "author_inst": "School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong" @@ -137990,123 +137340,91 @@ "category": "systems biology" }, { - "rel_doi": "10.1101/2022.12.02.518847", - "rel_title": "Viral burdens are associated with age and viral variant in a population-representative study of SARS-CoV-2 that accounts for time-since-infection related sampling bias.", + "rel_doi": "10.1101/2022.12.01.518541", + "rel_title": "Mice Humanized for Major Histocompatibility Complex and Angiotensin-Converting Enzyme 2 with High Permissiveness to SARS-CoV-2 Omicron Replication", "rel_date": "2022-12-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.02.518847", - "rel_abs": "In this study, we evaluated the impact of viral variant, in addition to other variables, on within-host viral burdens, by analysing cycle threshold (Ct) values derived from nose and throat swabs, collected as part of the UK COVID-19 Infection Survey. Because viral burden distributions determined from community survey data can be biased due to the impact of variant epidemiology on the time-since-infection of samples, we developed a method to explicitly adjust observed Ct value distributions to account for the expected bias. Analysing the adjusted Ct values using partial least squares regression, we found that among unvaccinated individuals with no known prior infection, the average Ct value was 0.94 lower among Alpha variant infections, compared those with the predecessor strain, B.1.177. However, among vaccinated individuals, it was 0.34 lower among Delta variant infections, compared to those with the Alpha variant. In addition, the average Ct value decreased by 0.20 for every 10 year age increment of the infected individual. In summary, within-host viral burdens are associated with age, in addition to the interplay of vaccination status and viral variant.", - "rel_num_authors": 26, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.01.518541", + "rel_abs": "Human Angiotensin-Converting Enzyme 2 (hACE2) is the major receptor enabling host cell invasion by SARS-CoV-2 via interaction with Spike glycoprotein. The murine ACE2 ortholog does not interact efficiently with SARS-CoV-2 Spike and therefore the conventional laboratory mouse strains are not permissive to SARS-CoV-2 replication. Here, we generated new hACE2 transgenic mice, which harbor the hACE2 gene under the human keratin 18 promoter, in C57BL/6 \"HHD-DR1\" background. HHD-DR1 mice are fully devoid of murine Major Histocompatibility Complex (MHC) molecules of class-I and -II and express only MHC molecules from Human Leukocyte Antigen (HLA) HLA 02.01, DRA01.01, DRB1.01.01 alleles, widely expressed in human populations. We selected three transgenic strains, with various hACE2 mRNA expression levels and distinctive profiles of lung and/or brain permissiveness to SARS-CoV-2 replication. Compared to the previously available B6.K18-ACE22Prlmn/JAX mice, which have limited permissiveness to SARS-CoV-2 Omicron replication, these three new hACE2 transgenic strains display higher levels of hACE2 mRNA expression, associated with high permissiveness to the replication of SARS-CoV-2 Omicron sub-variants. As a first application, one of these MHC- and ACE2-humanized strains was successfully used to show the efficacy of a lentiviral vector-based COVID-19 vaccine candidate.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Helen Fryer", - "author_inst": "University of Oxford" - }, - { - "author_name": "Tanya Golubchik", - "author_inst": "University of Oxford" - }, - { - "author_name": "Matthew David Hall", - "author_inst": "University of Oxford" - }, - { - "author_name": "Christophe Fraser", - "author_inst": "University of Oxford" - }, - { - "author_name": "Robert Hinch", - "author_inst": "University of Oxford" - }, - { - "author_name": "Luca Ferretti", - "author_inst": "University of Oxford" - }, - { - "author_name": "Laura Thomson", - "author_inst": "University of Oxford" - }, - { - "author_name": "Anel Nurtey", - "author_inst": "University of Oxford" - }, - { - "author_name": "Lorenzo Pellis", - "author_inst": "University of Oxford" + "author_name": "Fabien Le Chevalier", + "author_inst": "TheraVectys" }, { - "author_name": "George MackIntyre-Cockett", - "author_inst": "University of Oxford" + "author_name": "Pierre Authie", + "author_inst": "TheraVectys" }, { - "author_name": "Amy Trebes", - "author_inst": "University of Oxford" + "author_name": "Sebastien Chardenoux", + "author_inst": "Institut Pasteur" }, { - "author_name": "David Buck", - "author_inst": "University of Oxford" + "author_name": "Maryline Bourgine", + "author_inst": "Institut Pasteur" }, { - "author_name": "Paolo Piazza", - "author_inst": "University of Oxford" + "author_name": "Benjamin Vesin", + "author_inst": "TheraVectys" }, { - "author_name": "Angela Green", - "author_inst": "University of Oxford" + "author_name": "Delphine Cussigh", + "author_inst": "Institut Pasteur" }, { - "author_name": "Lorne J Lonie", - "author_inst": "University of Oxford" + "author_name": "Yohann Sassier", + "author_inst": "Institut Pasteur" }, { - "author_name": "Darren Smith", - "author_inst": "Northhumbria University" + "author_name": "Ingrid Fert", + "author_inst": "TheraVectys" }, { - "author_name": "Matthew Bashton", - "author_inst": "Northumbria University" + "author_name": "Amandine Noirat", + "author_inst": "TheraVectys" }, { - "author_name": "Matthew Crown", - "author_inst": "Northumbria University" + "author_name": "Kirill Nemirov", + "author_inst": "TheraVectys" }, { - "author_name": "Andrew Nelson", - "author_inst": "Northumbria University" + "author_name": "Francois ANNA", + "author_inst": "TheraVectys" }, { - "author_name": "Clare M McCann", - "author_inst": "Northumbria University" + "author_name": "Marion BERARD", + "author_inst": "Institut Pasteur" }, { - "author_name": "Adnan Tariq", - "author_inst": "Northumbria University" + "author_name": "Francoise Guinet", + "author_inst": "Institut Pasteur" }, { - "author_name": "Rui Nunes Dos Santos", - "author_inst": "Northumbria University" + "author_name": "David Hardy", + "author_inst": "Institut Pasteur" }, { - "author_name": "Zack Richards", - "author_inst": "Northumbria University" + "author_name": "Pierre Charneau", + "author_inst": "Institut Pasteur" }, { - "author_name": "- The COVID-19 Genomics UK (COG-UK) consortium", - "author_inst": "-" + "author_name": "Francois Lemonnier", + "author_inst": "INSERM" }, { - "author_name": "David Bonsall", - "author_inst": "University of Oxford" + "author_name": "Francina Langa-Vives", + "author_inst": "Institut Pasteur" }, { - "author_name": "Katrina Lythgoe", - "author_inst": "University of Oxford" + "author_name": "Laleh MAJLESSI", + "author_inst": "Institut Pasteur" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "genetics" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.12.01.518643", @@ -139660,83 +138978,75 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.11.29.22282899", - "rel_title": "Performance of antigen lateral flow devices in the United Kingdom during the Alpha, Delta, and Omicron waves of the SARS-CoV-2 pandemic", + "rel_doi": "10.1101/2022.11.28.22282818", + "rel_title": "Exploring a targeted approach for public health capacity restrictions during COVID-19 using a new computational model", "rel_date": "2022-11-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.29.22282899", - "rel_abs": "BackgroundAntigen lateral flow devices (LFDs) have been widely used to control SARS-CoV-2. Changes in LFD sensitivity and detection of infectious individuals during the pandemic with successive variants, vaccination, and changes in LFD use are incompletely understood.\n\nMethodsPaired LFD and PCR tests were collected from asymptomatic and symptomatic participants, across multiple settings in the UK between 04-November-2020 and 21-March-2022. Multivariable logistic regression was used to analyse LFD sensitivity and specificity, adjusting for viral load, LFD manufacturer, setting, age, sex, assistance, symptoms, vaccination, and variant. National contact tracing data were used to estimate the proportion of transmitting index cases (with [≥]1 PCR/LFD-positive contact) potentially detectable by LFDs over time, accounting for viral load, variant, and symptom status.\n\nFindings4131/75,382 (5.5%) participants were PCR-positive. Sensitivity vs. PCR was 63.2% (95%CI 61.7-64.6%) and specificity 99.71% (99.66-99.74%). Increased viral load was independently associated with being LFD-positive. There was no evidence LFD sensitivity differed between Delta vs. Alpha/pre-Alpha infections, but Omicron infections were more likely to be LFD positive. Sensitivity was higher in symptomatic participants, 68.7% (66.9-70.4%) than in asymptomatic participants, 52.8% (50.1-55.4%). 79.4% (68.6-81.3%) of index cases resulting in probable onward transmission with were estimated to have been detectable using LFDs, this proportion was relatively stable over time/variants, but lower in asymptomatic vs. symptomatic cases.\n\nInterpretationLFDs remained able to detect most SARS-CoV-2 infections throughout vaccine roll-out and different variants. LFDs can potentially detect most infections that transmit to others and reduce risks. However, performance is lower in asymptomatic compared to symptomatic individuals.\n\nFundingUK Government.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSLateral flow devices (LFDs; i.e. rapid antigen detection devices) have been widely used for SARS-CoV-2 testing. However, due to their imperfect sensitivity when compared to PCR and a lack of a widely available gold standard proxy for infectiousness, the performance and use of LFDs has been a source of debate. We conducted a literature review in PubMed and bioRxiv/medRxiv for all studies examining the performance of lateral flow devices between 01 January 2020 and 31 October 2022. We used the search terms SARS-CoV-2/COVID-19 and antigen/lateral flow test/lateral flow device. Multiple studies have examined the sensitivity and specificity of LFDs, including several systematic reviews. However, the majority of the studies are based on pre-Alpha infections. Large studies examining the test accuracy for different variants, including Delta and Omicron, and following vaccination are limited.\n\nAdded value of this studyIn this large national LFD evaluation programme, we compared the performance of three different LFDs relative to PCR in various settings. Compared to PCR testing, sensitivity was 63.2% (95%CI 61.7-64.6%) overall, and 71.6% (95%CI 69.8-73.4%) in unselected communitybased testing. Specificity was 99.71% (99.66-99.74%). LFDs were more likely to be positive as viral loads increased. LFD sensitivity was similar during Alpha/pre-Alpha and Delta periods but increased during the Omicron period. There was no association between sensitivity and vaccination status. Sensitivity was higher in symptomatic participants, 68.7% (66.9-70.4%) than in asymptomatic participants, 52.8% (50.1-55.4%). Using national contact tracing data, we estimated that 79.4% (68.6-81.3%) of index cases resulting in probable onward transmission (i.e. with [≥]1 PCR/LFD-positive contact) were detectable using LFDs. Symptomatic index cases were more likely to be detected than asymptomatic index cases due to higher viral loads and better LFD performance at a given viral load. The proportion of index cases detected remained relatively stable over time and with successive variants, with a slight increase in the proportion of asymptomatic index cases detected during Omicron.\n\nImplications of all the available evidenceOur data show that LFDs detect most SARS-CoV-2 infections, with findings broadly similar to those summarised in previous meta-analyses. We show that LFD performance has been relatively consistent throughout different variant-dominant phases of the pandemic and following the roll-out of vaccination. LFDs can detect most infections that transmit to others and can therefore be used as part of a risk reduction strategy. However, performance is lower in asymptomatic compared to symptomatic individuals and this needs to be considered when designing testing programmes.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.28.22282818", + "rel_abs": "This work introduces the Queens University Agent-Based Outbreak Outcome Model (QUABOOM), a new, data-driven, agent-based Monte Carlo simulation for modelling epidemics and informing public health policy in a wide range of population sizes. We demonstrate how the model can be used to quantitatively inform capacity restrictions for COVID-19 to reduce their impact on small businesses by showing that public health measures should target few locations where many individuals interact rather than many locations where few individuals interact. We introduce a new method for the calculation of the basic reproduction rate that can be applied to low statistics data such as small outbreaks. A novel parameter to quantify the number of interactions in the simulations is introduced which allows our agent-based model to be run using small population sizes and interpreted for larger populations, thereby improving computational efficiency.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "David W Eyre", - "author_inst": "University of Oxford" - }, - { - "author_name": "Matthias Futschik", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Sarah Tunkel", - "author_inst": "UK Health Security Agency" + "author_name": "Ashley Micuda", + "author_inst": "University of Western Ontario" }, { - "author_name": "Jia Wei", - "author_inst": "University of Oxford" + "author_name": "Mark R Anderson", + "author_inst": "Queen's University" }, { - "author_name": "Joanna Cole-Hamilton", - "author_inst": "UK Health Security Agency" + "author_name": "Irina Babayan", + "author_inst": "Queen's University" }, { - "author_name": "Rida Saquib", - "author_inst": "UK Health Security Agency" + "author_name": "Erin Bolger", + "author_inst": "Queen's University" }, { - "author_name": "Nick Germanacos", - "author_inst": "UK Health Security Agency" + "author_name": "Logan Cantin", + "author_inst": "Queen's University" }, { - "author_name": "Andrew Dodgson", - "author_inst": "UK Health Security Agency" + "author_name": "Gillian Groth", + "author_inst": "Queen's University" }, { - "author_name": "Paul E Klapper", - "author_inst": "University of Manchester" + "author_name": "Ry Pressman-Cyna", + "author_inst": "Queen's University" }, { - "author_name": "Malur Sudhanva", - "author_inst": "UK Health Security Agency" + "author_name": "Charlotte Z Reed", + "author_inst": "Queen's University" }, { - "author_name": "Chris Kenny", - "author_inst": "UK Health Security Agency" + "author_name": "Noah J Rowe", + "author_inst": "Queen's University" }, { - "author_name": "Peter Marks", - "author_inst": "UK Health Security Agency" + "author_name": "Mehdi Shafiee", + "author_inst": "Nazarbayev University" }, { - "author_name": "Edward Blandford", - "author_inst": "UK Health Security Agency" + "author_name": "Benjamin Tam", + "author_inst": "Queen's University" }, { - "author_name": "Susan Hopkins", - "author_inst": "UK Health Security Agency" + "author_name": "Marie C Vidal", + "author_inst": "Stanford University" }, { - "author_name": "Tim Peto", - "author_inst": "University of Oxford" + "author_name": "Tianai Ye", + "author_inst": "Queen's University" }, { - "author_name": "Tom Fowler", - "author_inst": "UK Health Security Agency" + "author_name": "Ryan D Martin", + "author_inst": "Queen's University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.11.25.22282676", @@ -141562,101 +140872,61 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.11.22.22282629", - "rel_title": "Global Expansion of SARS-CoV-2 Variants of Concern: Dispersal Patterns and Influence of Air Travel", + "rel_doi": "10.1101/2022.11.22.22282480", + "rel_title": "Community incidence patterns drive the risk of SARS-CoV-2 outbreaks and alter intervention impacts in a high-risk institutional setting", "rel_date": "2022-11-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.22.22282629", - "rel_abs": "In many regions of the world, the Alpha, Beta and Gamma SARS-CoV-2 Variants of Concern (VOCs) co-circulated during 2020-21 and fueled waves of infections. During 2021, these variants were almost completely displaced by the Delta variant, causing a third wave of infections worldwide. This phenomenon of global viral lineage displacement was observed again in late 2021, when the Omicron variant disseminated globally. In this study, we use phylogenetic and phylogeographic methods to reconstruct the dispersal patterns of SARS-CoV-2 VOCs worldwide. We find that the source-sink dynamics of SARS-CoV-2 varied substantially by VOC, and identify countries that acted as global hubs of variant dissemination, while other countries became regional contributors to the export of specific variants. We demonstrate a declining role of presumed origin countries of VOCs to their global dispersal: we estimate that India contributed <15% of all global exports of Delta to other countries and South Africa <1-2% of all global Omicron exports globally. We further estimate that >80 countries had received introductions of Omicron BA.1 100 days after its inferred date of emergence, compared to just over 25 countries for the Alpha variant. This increased speed of global dissemination was associated with a rebound in air travel volume prior to Omicron emergence in addition to the higher transmissibility of Omicron relative to Alpha. Our study highlights the importance of global and regional hubs in VOC dispersal, and the speed at which highly transmissible variants disseminate through these hubs, even before their detection and characterization through genomic surveillance.\n\nHighlightsO_LIGlobal phylogenetic analysis reveals relationship between air travel and speed of dispersal of SARS-CoV-2 variants of concern (VOCs)\nC_LIO_LIOmicron VOC spread to 5x more countries within 100 days of its emergence compared to all other VOCs\nC_LIO_LIOnward transmission and dissemination of VOCs Delta and Omicron was primarily from secondary hubs rather than initial country of detection during a time of increased global air travel\nC_LIO_LIAnalysis highlights highly connected countries identified as major global and regional exporters of VOCs\nC_LI", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.22.22282480", + "rel_abs": "Optimization of control measures for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in high-risk institutional settings (e.g., prisons, nursing homes, or military bases) depends on how transmission dynamics in the broader community influence outbreak risk locally. We calibrated an individual-based transmission model of a military training camp to the number of RT-PCR positive trainees throughout 2020 and 2021. The predicted number of infected new arrivals closely followed adjusted national incidence and increased early outbreak risk after accounting for vaccination coverage, masking compliance, and virus variants. Outbreak size was strongly correlated with the predicted number of off-base infections among staff during training camp. In addition, off-base infections reduced the impact of arrival screening and masking, while the number of infectious trainees upon arrival reduced the impact of vaccination and staff testing. Our results highlight the importance of outside incidence patterns for modulating risk and the optimal mixture of control measures in institutional settings.\n\nDisclaimerThe views expressed are those of the authors and should not be construed to represent the positions of the U.S. Army, the Department of Defense, or the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Houriiyah Tegally", - "author_inst": "Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa" - }, - { - "author_name": "Eduan Wilkinson", - "author_inst": "Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa" - }, - { - "author_name": "Darren Martin", - "author_inst": "Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-Africa), Cape Town, South Africa" - }, - { - "author_name": "Monika Moir", - "author_inst": "Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa" - }, - { - "author_name": "Anderson Brito", - "author_inst": "Instituto Todos pela Saude, Sao Paulo, Sao Paulo, Brazil" - }, - { - "author_name": "Marta Giovanetti", - "author_inst": "Laboratorio de Flavivirus, Fundacao Oswaldo Cruz, Rio de Janeiro, Brazil" - }, - { - "author_name": "Kamran Khan", - "author_inst": "BlueDot, Toronto, Canada" - }, - { - "author_name": "Carmen Huber", - "author_inst": "BlueDot, Toronto, Canada" - }, - { - "author_name": "Isaac I. Bogoch", - "author_inst": "Department of Medicine, Division of Infectious Diseases, University of Toronto, Toronto, Canada" - }, - { - "author_name": "James Emmanuel San", - "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa" + "author_name": "Sean M Moore", + "author_inst": "University of Notre Dame" }, { - "author_name": "Joseph L.-H. Tsui", - "author_inst": "Department of Biology, University of Oxford, Oxford, UK" + "author_name": "Guido Espana", + "author_inst": "University of Notre Dame" }, { - "author_name": "Jenicca Poongavanan", - "author_inst": "Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa" + "author_name": "T Alex Perkins", + "author_inst": "University of Notre Dame" }, { - "author_name": "Joicymara S. Xavier", - "author_inst": "Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa" + "author_name": "Robert M Guido", + "author_inst": "Moncrief Army Health Clinic, Fort Jackson" }, { - "author_name": "Darlan da S. Candido", - "author_inst": "MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Jameel Institute, School of Public Health, Imperial College" + "author_name": "Joaquin B Jucaban", + "author_inst": "Moncrief Army Health Clinic, Fort Jackson" }, { - "author_name": "Filipe Romero", - "author_inst": "MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Jameel Institute, School of Public Health, Imperial College" + "author_name": "Tara L Hall", + "author_inst": "Moncrief Army Health Clinic, Fort Jackson" }, { - "author_name": "Cheryl Baxter", - "author_inst": "Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa" + "author_name": "Mark E Huhtanen", + "author_inst": "United States Army Training Center, Fort Jackson" }, { - "author_name": "Oliver G. Pybus", - "author_inst": "Department of Biology, University of Oxford, Oxford, UK" - }, - { - "author_name": "Richard Lessells", - "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa" + "author_name": "Sheila A Peel", + "author_inst": "Walter Reed Army Institute of Research" }, { - "author_name": "Nuno R. Faria", - "author_inst": "MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Jameel Institute, School of Public Health, Imperial College" + "author_name": "Kayvon Modjarrad", + "author_inst": "Walter Reed Army Institute of Research" }, { - "author_name": "Moritz U.G. Kraemer", - "author_inst": "Department of Biology, University of Oxford, Oxford, UK" + "author_name": "Shilpa Hakre", + "author_inst": "Walter Reed Army Institute of Research" }, { - "author_name": "Tulio de Oliveira", - "author_inst": "Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa" + "author_name": "Paul T Scott", + "author_inst": "Walter Reed Army Institute of Research" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -143464,47 +142734,91 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.11.20.22282562", - "rel_title": "Perceived barriers to cervical cancer screening and motivators for at-home HPV self-sampling during the COVID-19 pandemic: A telephone survey of randomzed controlled trial participants", + "rel_doi": "10.1101/2022.11.21.22282580", + "rel_title": "It's poverty - not the pandemic: the impact of COVID-19 and socioeconomic status on psychological distress in cancer patients", "rel_date": "2022-11-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.20.22282562", - "rel_abs": "Home-based self-sample human papillomavirus (HPV) testing may be an alternative for women who do not attend clinic-based cervical cancer screening. We assessed barriers to care and motivators to use at-home HPV self-sampling kits during the COVID-19 pandemic as part of a randomized controlled trial evaluating kit effectiveness. Participants were women, aged 30-65 years and underscreened for cervical cancer in a safety-net healthcare system. We conducted telephone surveys in English/Spanish among a subgroup of trial participants, assessed differences between groups and determined statistical significance at p<0.05. Over half of 233 survey participants reported clinic-based screening (Pap) is uncomfortable (67.8%), embarrassing (52.4%), and discomfort seeing male providers (63.1%). The latter two factors were significantly more prevalent among Spanish versus English speakers (66.4% vs 30% and 69.9 vs 52.2%, respectively, p<0.01). Most women who completed the kit found Pap more embarrassing (69.3%), stressful (55.6%) and less convenient (55.6%) than the kit. The first factor was more prevalent among Spanish versus English speakers (79.6% vs 53.38%, p<0.05). The COVID-19 pandemic influenced most (59.5%) to participate in the trial due to fear of COVID, difficulty making appointments and ease of using kits. HPV self-sampling kits may reduce barriers among underscreened women in a safety-net system.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.21.22282580", + "rel_abs": "BackgroundThe COVID-19 pandemic has affected psychological wellbeing in many aspects, but its influence on cancer patients it not yet clear, and studies show mixed results.\n\nAimsWe aimed to investigate the impact of the pandemic on psychological symptom burden against the socio-economic background of cancer patients using data from routine assessments before and during the pandemic.\n\nMethodsStandardised assessment instruments were applied in N = 1,329 patients to screen for symptoms of anxiety, depression, post-traumatic stress, and fatigue from 2018 to 2022. Two MANOVAs with separate ANOVAs and Bonferroni pairwise comparisons as post-hoc tests were computed. First, only time was included as predictor to examine the isolated impact of the pandemic. Second, income level and education level were included as further predictors to additionally test the predictive power of socioeconomic risk factors. All tests were two-sided.\n\nResultsOnce indicators of socioeconomic status were included in the analysis, the seeming influence of the pandemic became negligible. Only income had a significant impact on all aspects of psychological symptom burden, with patients with low income being highly burdened (partial {eta}2 = .01, p = .023). The highest mean difference was found for depressive symptoms (MD = 0.13, CI = [0.07; 0.19], p < .001). The pandemic had no further influence on psychological distress.\n\nConclusionsAlthough the pandemic is a major stressor in many respects, poverty is by far the most important risk factor for psychological symptom burden in cancer outpatients and outweighs the impact of the pandemic.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Susan L Parker", - "author_inst": "Baylor College of Medicine" + "author_name": "Elisabeth Lucia Zeilinger", + "author_inst": "Medical University of Vienna" }, { - "author_name": "Ashish A Deshmukh", - "author_inst": "Medical University of South Carolina" + "author_name": "Matthias Knefel", + "author_inst": "Medical University of Vienna" }, { - "author_name": "Baojiang Chen", - "author_inst": "UTHealth School of Public Health Michael and Susan Dell Center for Healthy Living" + "author_name": "Carmen Schneckenreiter", + "author_inst": "Medical University of Vienna" }, { - "author_name": "David R Lairson", - "author_inst": "UTHealth School of Public Health" + "author_name": "Jakob Pietschnig", + "author_inst": "University of Vienna" }, { - "author_name": "Maria Daheri", - "author_inst": "Harri Health System" + "author_name": "Simone Lubowitzki", + "author_inst": "Medical University of Vienna" }, { - "author_name": "Sally W Vernon", - "author_inst": "UTHealth School of Public Health" + "author_name": "Matthias Unseld", + "author_inst": "Medical University of Vienna" }, { - "author_name": "Jane R Montealegre", - "author_inst": "Baylor College of Medicine" + "author_name": "Thorsten Fuereder", + "author_inst": "Medical University of Vienna" + }, + { + "author_name": "Rupert Bartsch", + "author_inst": "Medical University of Vienna" + }, + { + "author_name": "Eva Katharina Masel", + "author_inst": "Medical University of Vienna" + }, + { + "author_name": "Feroniki Adamidis", + "author_inst": "Medical University of Vienna" + }, + { + "author_name": "Lea Kum", + "author_inst": "Medical University of Vienna" + }, + { + "author_name": "Barbara Kiesewetter", + "author_inst": "Medical University of Vienna" + }, + { + "author_name": "Sabine Zoechbauer-Mueller", + "author_inst": "Medical University of Vienna" + }, + { + "author_name": "Markus Raderer", + "author_inst": "Medical University of Vienna" + }, + { + "author_name": "Maria Theresa Krauth", + "author_inst": "Medical University of Vienna" + }, + { + "author_name": "Philipp Staber", + "author_inst": "Medical University of Vienna" + }, + { + "author_name": "Peter Valent", + "author_inst": "Medical University of Vienna" + }, + { + "author_name": "Alexander Gaiger", + "author_inst": "Medical University of Vienna" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "oncology" }, { "rel_doi": "10.1101/2022.11.21.22282569", @@ -145150,79 +144464,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.11.17.515635", - "rel_title": "Hamsters are a model for COVID-19 alveolar regeneration mechanisms: an opportunity to understand post-acute sequelae of SARS-CoV-2", + "rel_doi": "10.1101/2022.11.18.22282448", + "rel_title": "Sex-specific neurodevelopmental outcomes in offspring of mothers with SARS-CoV-2 in pregnancy: an electronic health records cohort", "rel_date": "2022-11-18", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.11.17.515635", - "rel_abs": "A relevant number of coronavirus disease 2019 (COVID-19) survivors suffers from post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (PASC). Current evidence suggests a dysregulated alveolar regeneration in COVID-19 as a possible explanation for respiratory PASC symptoms, a phenomenon which deserves further investigation in a suitable animal model. This study investigates morphological, phenotypical and transcriptomic features of alveolar regeneration in SARS-CoV-2 infected Syrian golden hamsters. We demonstrate that CK8+ alveolar differentiation intermediate (ADI) cells occur following SARS-CoV-2-induced diffuse alveolar damage. A subset of ADI cells shows nuclear accumulation of TP53 at 6- and 14-days post infection (dpi), indicating a prolonged arrest in the ADI state. Transcriptome data show the expression of gene signatures driving ADI cell senescence, epithelial-mesenchymal transition, and angiogenesis. Moreover, we show that multipotent CK14+ airway basal cell progenitors migrate out of terminal bronchioles, aiding alveolar regeneration. At 14 dpi, presence of ADI cells, peribronchiolar proliferates, M2-type macrophages, and sub-pleural fibrosis is observed, indicating incomplete alveolar restoration. The results demonstrate that the hamster model reliably phenocopies indicators of a dysregulated alveolar regeneration of COVID-19 patients. The results provide important information on a translational COVID-19 model, which is crucial for its application in future research addressing pathomechanisms of PASC and in testing of prophylactic and therapeutic approaches for this syndrome.", - "rel_num_authors": 15, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.18.22282448", + "rel_abs": "ImportancePrior studies using large registries suggested a modest increase in risk for neurodevelopmental diagnoses among children of mothers with immune activation during pregnancy, and such risk may be sex-specific.\n\nObjectiveTo determine whether in utero exposure to the novel coronavirus SARS-CoV-2 is associated with sex-specific risk for neurodevelopmental disorders up to 18 months after birth, compared to unexposed offspring born during or prior to the pandemic period.\n\nDesignRetrospective cohort.\n\nParticipantsLive offspring of all mothers who delivered between March 2018 and May 2021 at any of eight hospitals across two health systems in Massachusetts.\n\nExposurePCR evidence of maternal SARS-CoV-2 infection during pregnancy.\n\nMain Outcome and MeasuresElectronic health record documentation of ICD-10 diagnostic codes corresponding to neurodevelopmental disorders.\n\nResultsThe pandemic cohort included 18,323 live births, including 877 (4.8%) to individuals with SARS-CoV-2 positivity during pregnancy. The cohort included 1806 (9.9%) Asian individuals, 1634 (8.9%) Black individuals, 1711 (9.3%) individuals of another race, and 12,694 (69%) White individuals; 2614 (14%) were of Hispanic ethnicity. Mean maternal age was 33.0 years (IQR 30.0-36.0). In adjusted regression models accounting for race, ethnicity, insurance status, hospital type (academic center vs. community), maternal age, and preterm status, SARS-CoV-2 positivity was associated with statistically significant elevation in risk for neurodevelopmental diagnoses among male offspring (adjusted OR 1.99, 95% CI 1.19-3.34; p=0.009) but not female offspring (adjusted OR 0.90, 95% CI 0.43-1.88; p=0.8). Similar effects were identified using matched analyses in lieu of regression.\n\nConclusion and RelevanceSARS-CoV-2 exposure in utero was associated with greater magnitude of risk for neurodevelopmental diagnoses among male offspring in the 12 months following birth. As with prior studies of maternal infection, substantially larger cohorts and longer follow-up will be required to reliably estimate or refute risk.\n\nTrial RegistrationNA\n\nKey PointsO_ST_ABSQuestionC_ST_ABSAre rates of neurodevelopmental disorder diagnoses greater among male or female children with COVID-19 exposure in utero compared to those with no such exposure?\n\nFindingsIn a cohort of 18,323 infants delivered after February 2020, males but not females born to mothers with a positive SARS-CoV-2 PCR test during pregnancy were more likely to receive a neurodevelopmental diagnosis in the first 12 months after delivery, even after accounting for preterm delivery.\n\nMeaningThese findings suggest that male offspring exposed to COVID-19 in utero may be at increased risk for neurodevelopmental disorders.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Laura Heydemann", - "author_inst": "Department of Pathology, University of Veterinary Medicine, Foundation, Hannover, Germany" - }, - { - "author_name": "Malgorzata Ciurkiewicz", - "author_inst": "Department of Pathology, University of Veterinary Medicine, Foundation, Hannover, Germany" - }, - { - "author_name": "Georg Beythien", - "author_inst": "Department of Pathology, University of Veterinary Medicine, Foundation, Hannover, Germany" - }, - { - "author_name": "Kathrin Becker", - "author_inst": "Department of Pathology, University of Veterinary Medicine, Foundation, Hannover, Germany" - }, - { - "author_name": "Klaus Schughart", - "author_inst": "Helmholtz Centre for Infection Research, Brunswick, Germany" - }, - { - "author_name": "Stephanie Stanelle-Bertram", - "author_inst": "Department for Viral Zoonoses-One Health, Leibniz Institute for Virology, Hamburg, Germany" - }, - { - "author_name": "Berfin Schaumburg", - "author_inst": "Department for Viral Zoonoses-One Health, Leibniz Institute for Virology, Hamburg, Germany" - }, - { - "author_name": "Nancy Mounogou-Kouassi", - "author_inst": "Department for Viral Zoonoses-One Health, Leibniz Institute for Virology, Hamburg, Germany" - }, - { - "author_name": "Sebastian Beck", - "author_inst": "Department for Viral Zoonoses-One Health, Leibniz Institute for Virology, Hamburg, Germany" - }, - { - "author_name": "Martin Zickler", - "author_inst": "Department for Viral Zoonoses-One Health, Leibniz Institute for Virology, Hamburg, Germany" + "author_name": "Andrea G. Edlow", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Mark Kuehnel", - "author_inst": "Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Member of the German Center for Lung Research (DZL), Hannover 30625, Germany and" + "author_name": "Victor M Castro", + "author_inst": "Mass General Brigham" }, { - "author_name": "Guelsah Gabriel", - "author_inst": "Department for Viral Zoonoses-One Health, Leibniz Institute for Virology, Hamburg, Germany" + "author_name": "Lydia Shook", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Andreas Beineke", - "author_inst": "Department of Pathology, University of Veterinary Medicine, Foundation, Hannover, Germany" + "author_name": "Sebastien Haneuse", + "author_inst": "Harvard School of Public Health" }, { - "author_name": "Wolfgang Baumgaertner", - "author_inst": "Department of Pathology, University of Veterinary Medicine, Foundation, Hannover, Germany" + "author_name": "Anjali J Kaimal", + "author_inst": "University of South Florida" }, { - "author_name": "Federico Armando", - "author_inst": "Department of Pathology, University of Veterinary Medicine, Foundation, Hannover, Germany" + "author_name": "Roy H Perlis", + "author_inst": "Massachusetts General Hospital" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "pathology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2022.11.17.22282473", @@ -146848,115 +146126,51 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.11.14.22282103", - "rel_title": "Long-term COVID-19 booster effectiveness by infection history and clinical vulnerability and immune imprinting", + "rel_doi": "10.1101/2022.11.14.22282195", + "rel_title": "The Paxlovid Rebound Study: A Prospective Cohort Study to Evaluate Viral and Symptom Rebound Differences Between Paxlovid and Untreated COVID-19 Participants", "rel_date": "2022-11-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.14.22282103", - "rel_abs": "BackgroundLong-term effectiveness of COVID-19 mRNA boosters in populations with different prior infection histories and clinical vulnerability profiles is inadequately understood.\n\nMethodsA national, matched, retrospective, target trial cohort study was conducted in Qatar to investigate effectiveness of a third mRNA (booster) dose, relative to a primary series of two doses, against SARS-CoV-2 omicron infection and against severe COVID-19. Associations were estimated using Cox proportional-hazards regression models.\n\nResultsBooster effectiveness relative to primary series was 41.1% (95% CI: 40.0-42.1%) against infection and 80.5% (95% CI: 55.7-91.4%) against severe, critical, or fatal COVID-19, over one-year follow-up after the booster. Among persons clinically vulnerable to severe COVID-19, effectiveness was 49.7% (95% CI: 47.8-51.6%) against infection and 84.2% (95% CI: 58.8-93.9%) against severe, critical, or fatal COVID-19. Effectiveness against infection was highest at 57.1% (95% CI: 55.9-58.3%) in the first month after the booster but waned thereafter and was modest at only 14.4% (95% CI: 7.3-20.9%) by the sixth month. In the seventh month and thereafter, coincident with BA.4/BA.5 and BA.2.75* subvariant incidence, effectiveness was progressively negative reaching -20.3% (95% CI: -55.0-29.0%) after one year of follow-up. Similar levels and patterns of protection were observed irrespective of prior infection status, clinical vulnerability, or type of vaccine (BNT162b2 versus mRNA-1273).\n\nConclusionsBoosters reduced infection and severe COVID-19, particularly among those clinically vulnerable to severe COVID-19. However, protection against infection waned after the booster, and eventually suggested an imprinting effect of compromised protection relative to the primary series. However, imprinting effects are unlikely to negate the overall public health value of booster vaccinations.", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.14.22282195", + "rel_abs": "IntroductionThe uptake of Paxlovid in individuals infected with COVID-19 has been significantly limited by concerns around the Paxlovid rebound phenomenon despite the scarcity of evidence around its epidemiology. The purpose of this study was to prospectively compare the epidemiology of Paxlovid rebound in treated and untreated participants with acute COVID-19 infection\n\nMethodsWe designed a decentralized, digital, prospective observational study in which participants who tested positive for COVID-19 using eMed Test-to-Treat telehealth kits and were clinically eligible for Paxlovid were recruited to be evaluated for viral and symptom clearance, as well as rebound. Participants were assigned to a Paxlovid or control group based on their decision to take Paxlovid. Following initial diagnosis based on a telehealth proctored test both groups were provided 12 telehealth proctored rapid antigen home tests and asked to test on a regular frequent schedule for 16 days and answer symptom surveys. Viral rebound based on test results and COVID-19 symptom rebound based on patient reported symptoms were evaluated.\n\nResultsViral rebound incidence was 14.2% in the Paxlovid group (n=127) and 9.3% in the control group (n=43). COVID-19 symptom rebound incidence was higher in the Paxlovid group (18.9%) compared to the control group (7.0%). There were no notable differences in viral rebound by age, gender, pre-existing conditions, or major symptom groups during the acute phase or at the 1-month interval.\n\nConclusionThis preliminary report of our prospective study suggests that rebound after clearance of test positivity or symptom resolution is higher than previously reported. However, we observed a similar rate of rebound in both in the Paxlovid and control groups. Large studies with diverse participants and extended follow-up are needed to better understand the rebound phenomena.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Hiam Chemaitelly", - "author_inst": "Weill Cornell Medicine-Qatar" - }, - { - "author_name": "Houssein Ayoub", - "author_inst": "Qatar University" - }, - { - "author_name": "Patrick Tang", - "author_inst": "Sidra Medicine" - }, - { - "author_name": "Peter Coyle", - "author_inst": "Hamad Medical Corporation" - }, - { - "author_name": "HADI M. YASSINE", - "author_inst": "Qatar University" - }, - { - "author_name": "Asmaa Althani", - "author_inst": "QU" - }, - { - "author_name": "Hebah A. Al-Khatib", - "author_inst": "Qatar University" - }, - { - "author_name": "Mohammad R. Hasan", - "author_inst": "Sidra Medicine" - }, - { - "author_name": "Zaina Al-Kanaani", - "author_inst": "Hamad Medical Corporation" - }, - { - "author_name": "Einas Al-Kuwari", - "author_inst": "Hamad Medical Corporation" - }, - { - "author_name": "Andrew Jeremijenko", - "author_inst": "Hamad Medical Corporation" - }, - { - "author_name": "Anvar Hassan Kaleeckal", - "author_inst": "Hamad Medical Corporation" - }, - { - "author_name": "Ali Nizar Latif", - "author_inst": "Hamad Medical Corporation" - }, - { - "author_name": "Riyazuddin Mohammad Shaik", - "author_inst": "Hamad Medical Corporation" - }, - { - "author_name": "Hanan F. Abdul-Rahim", - "author_inst": "Qatar University" - }, - { - "author_name": "Gheyath Nasrallah", - "author_inst": "Qatar University" - }, - { - "author_name": "Mohamed Ghaith Al-Kuwari", - "author_inst": "Primary Health Care Corporation" + "author_name": "Jay A Pandit", + "author_inst": "Scripps Research Translational Institute" }, { - "author_name": "Adeel A Butt", - "author_inst": "Hamad Medical Corporation" + "author_name": "Jennifer M Radin", + "author_inst": "Scripps Research Translational Institute" }, { - "author_name": "Hamad Eid Al-Romaihi", - "author_inst": "MoPH: Ministry of Public Health Qatar" + "author_name": "Danielle Chiang", + "author_inst": "Scripps Research Translational Institute" }, { - "author_name": "Mohammed Al-Thani", - "author_inst": "MoPH: Ministry of Public Health Qatar" + "author_name": "Emily G Spencer", + "author_inst": "Scripps Research Translational Institute" }, { - "author_name": "Abdullatif Al-Khal", - "author_inst": "Hamad Medical Corporation" + "author_name": "Jeff B Pawelek", + "author_inst": "Scripps Research Translational Institute" }, { - "author_name": "Roberto Bertollini", - "author_inst": "MoPH: Ministry of Public Health Qatar" + "author_name": "Mira Diwan", + "author_inst": "Scripps Research Translational Institute" }, { - "author_name": "Jeremy Samuel Faust", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Leila Roumani", + "author_inst": "eMed" }, { - "author_name": "Laith J Abu-Raddad", - "author_inst": "Weill Cornell Medicine-Qatar" + "author_name": "Michael J Mina", + "author_inst": "eMed" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.11.15.516323", @@ -148854,91 +148068,35 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.11.11.22282213", - "rel_title": "Health, socioeconomic and genetic predictors of COVID-19 vaccination uptake: a nationwide machine-learning study", + "rel_doi": "10.1101/2022.11.10.516025", + "rel_title": "Cotranslational formation of disulfides guides folding of the SARS CoV-2 receptor binding domain", "rel_date": "2022-11-11", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.11.22282213", - "rel_abs": "Reduced participation in COVID-19 vaccination programs is a key societal concern. Understanding factors associated with vaccination uptake can help in planning effective immunization programs. We considered 2,890 health, socioeconomic, familial, and demographic factors measured on the entire Finnish population aged 30 to 80 (N=3,192,505) and genome-wide information for a subset of 273,765 individuals. Risk factors were further classified into 12 thematic categories and a machine learning model was trained for each category. The main outcome was uptaking the first COVID-19 vaccination dose by 31.10.2021, which has occurred for 90.3% of the individuals.\n\nThe strongest predictor category was labor income in 2019 (AUC evaluated in a separate test set = 0.710, 95% CI: 0.708-0.712), while drug purchase history, including 376 drug classes, achieved a similar prediction performance (AUC = 0.706, 95% CI: 0.704-0.708). Higher relative risks of being unvaccinated were observed for some mental health diagnoses (e.g. dissocial personality disorder, OR=1.26, 95% CI : 1.24-1.27) and when considering vaccination status of first-degree relatives (OR=1.31, 95% CI:1.31-1.32 for unvaccinated mothers)\n\nWe derived a prediction model for vaccination uptake by combining all the predictors and achieved good discrimination (AUC = 0.801, 95% CI: 0.799-0.803). The 1% of individuals with the highest risk of not vaccinating according to the model predictions had an average observed vaccination rate of only 18.8%.\n\nWe identified 8 genetic loci associated with vaccination uptake and derived a polygenic score, which was a weak predictor of vaccination status in an independent subset (AUC=0.612, 95% CI: 0.601-0.623). Genetic effects were replicated in an additional 145,615 individuals from Estonia (genetic correlation=0.80, 95% CI: 0.66-0.95) and, similarly to data from Finland, correlated with mental health and propensity to participate in scientific studies. Individuals at higher genetic risk for severe COVID-19 were less likely to get vaccinated (OR=1.03, 95% CI: 1.02-1.05).\n\nOur results, while highlighting the importance of harmonized nationwide information, not limited to health, suggest that individuals at higher risk of suffering the worst consequences of COVID-19 are also those less likely to uptake COVID-19 vaccination. The results can support evidence-informed actions for COVID-19 and other areas of national immunization programs.", - "rel_num_authors": 18, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.11.10.516025", + "rel_abs": "Many secreted proteins contain multiple disulfide bonds. How disulfide formation is coupled to protein folding in the cell remains poorly understood at the molecular level. Here, we combine experiment and simulation to address this question as it pertains to the SARS-CoV-2 receptor binding domain (RBD). We show that, whereas RBD can refold reversibly when its disulfides are intact, their disruption causes misfolding into a nonnative molten-globule state that is highly prone to aggregation and disulfide scrambling. Thus, non-equilibrium mechanisms are needed to ensure disulfides form prior to folding in vivo. Our simulations suggest that co-translational folding may accomplish this, as native disulfide pairs are predicted to form with high probability at intermediate lengths, ultimately committing the RBD to its metastable native state and circumventing nonnative intermediates. This detailed molecular picture of the RBD folding landscape may shed light on SARS-CoV-2 pathology and molecular constraints governing SARS-CoV-2 evolution.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Tuomo Hartonen", - "author_inst": "Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland" - }, - { - "author_name": "Bradley Jermy", - "author_inst": "Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland" - }, - { - "author_name": "Hanna Sonajalg", - "author_inst": "Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia" - }, - { - "author_name": "Pekka Vartiainen", - "author_inst": "Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland" - }, - { - "author_name": "Kristi Krebs", - "author_inst": "Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia" - }, - { - "author_name": "Andrius Vabalas", - "author_inst": "Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland" - }, - { - "author_name": "- FinnGen", - "author_inst": "" - }, - { - "author_name": "- Estonian Biobank research team", - "author_inst": "" - }, - { - "author_name": "Tuija Leino", - "author_inst": "The Finnish Institute for Health and Welfare, Helsinki, Finland" - }, - { - "author_name": "Hanna Nohynek", - "author_inst": "The Finnish Institute for Health and Welfare, Helsinki, Finland" - }, - { - "author_name": "Jonas Sivela", - "author_inst": "The Finnish Institute for Health and Welfare, Helsinki, Finland" - }, - { - "author_name": "Reedik Magi", - "author_inst": "Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia" - }, - { - "author_name": "Mark J Daly", - "author_inst": "Institute for Molecular Medicine Finland (FIMM)" - }, - { - "author_name": "Hanna M Ollila", - "author_inst": "Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland" - }, - { - "author_name": "Lili Milani", - "author_inst": "University of Tartu" + "author_name": "Amir Bitran", + "author_inst": "Harvard University" }, { - "author_name": "Markus Perola", - "author_inst": "The Finnish Institute for Health and Welfare, Helsinki, Finland" + "author_name": "Kibum Park", + "author_inst": "Harvard University" }, { - "author_name": "Samuli Ripatti", - "author_inst": "FIMM" + "author_name": "Eugene Serebryany", + "author_inst": "Harvard University" }, { - "author_name": "Andrea Ganna", - "author_inst": "Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland" + "author_name": "Eugene Shakhnovich", + "author_inst": "Harvard University" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "biophysics" }, { "rel_doi": "10.1101/2022.11.09.22282120", @@ -150588,31 +149746,27 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.11.08.22281807", - "rel_title": "TRANSCUTANEOUS VAGUS NERVE STIMULATION IN THE TREATMENT OF LONG COVID-CHRONIC FATIGUE SYNDROME", + "rel_doi": "10.1101/2022.11.06.22282004", + "rel_title": "Too much is too much: influence of former stress levels on food cravings and weight gain during the COVID-19 period", "rel_date": "2022-11-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.08.22281807", - "rel_abs": "Many patients do not recover following Covid infection. The resulting illness is called Long Covid. Because there is no agreed upon treatment for this ailment, we decided to do an open label pilot study using non-invasive, transcutaneous stimulation of the auricular branch of the vagus nerve. Inclusion criteria required the patient to fulfill criteria for having chronic fatigue syndrome. Fourteen patients provided evaluable data. Eight of these fulfilled our requirements for treatment success. Since our criterion for a successful study was that at least a third of patients had to show a positive response to treatment, this was a successful pilot that warrants a follow up study that is appropriately sham controlled.\n\nAll authors have read and approved this manuscript for submission.\n\nThere are no competing interests and support for doing this study was via patient donations to support Dr Natelsons research activities.\n\nThe actual data summarized in Table 1 are available upon request\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@1f483a9org.highwire.dtl.DTLVardef@1f00297org.highwire.dtl.DTLVardef@3a2224org.highwire.dtl.DTLVardef@9793a8org.highwire.dtl.DTLVardef@15f2f36_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTABLE 1C_FLOATNO O_TABLECAPTIONList of Criteria Successfully Attained by Subject\n\nC_TABLECAPTION C_TBL", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.06.22282004", + "rel_abs": "The COVID-19 pandemic and associated social restrictions had an extensive effect on peoples lives. Increased rates of weight gain were widely reported, as were declines in the general populations mental health, including increases in perceived stress. This study investigated whether higher perceived levels of stress during the pandemic were associated with greater levels of weight gain, and whether poor prior levels of mental health were a factor in higher levels of both stress and weight gain during the pandemic. Underlying changes in eating behaviours and dietary consumption were also investigated. During January-February 2021, UK adults (n=179) completed a self-report online questionnaire to measure perceived levels of stress and changes (current versus pre-COVID-19 restrictions) in weight, eating behaviours, dietary consumption, and physical activity. Participants also reported on how COVID-19 had impacted their lives and their level of mental health prior to the pandemic. Participants with higher levels of stress were significantly more likely to report weight gain and twice as likely to report increased food cravings and comfort food consumption (OR=2.3 and 1.9-2.5, respectively). Participants reporting an increase in food cravings were 6-11 times more likely to snack and to have increased consumption of high sugar or processed foods (OR=6.3, 11.2 and 6.3, respectively). Females reported a far greater number of COVID-19 enforced lifestyle changes and both female gender and having poor mental health prior to the pandemic were significant predictors of higher stress and weight gain during the pandemic. Although COVID-19 and the pandemic restrictions were unprecedented, this study suggests that understanding and addressing the disparity of higher perceived stress in females and individuals previous levels of mental health, as well as the key role of food cravings, is key for successfully addressing the continuing societal issue of weight gain and obesity.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Benjamin Natelson", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Michelle Blate", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Rachel Louise Granger", + "author_inst": "Bangor University" }, { - "author_name": "Tiffany Soto", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Hans Peter Kubis", + "author_inst": "Bangor University College of Health and Behavioural Sciences: Bangor University College of Human Sciences" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.11.07.22282054", @@ -152242,29 +151396,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.11.03.22281783", - "rel_title": "Nirmatrelvir and the Risk of Post-Acute Sequelae of COVID-19", + "rel_doi": "10.1101/2022.11.03.22281881", + "rel_title": "Real-world effectiveness of nirmatrelvir/ritonavir use for COVID-19: A population-based cohort study in Ontario, Canada", "rel_date": "2022-11-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.03.22281783", - "rel_abs": "Long Covid - the disease encompassing the post-acute sequelae of SARS-CoV-2 (PASC) --affects millions of people around the world. Prevention of PASC is an urgent public health priority. In this work, we aimed to examine whether treatment with nirmatrelvir in the acute phase of COVID-19 is associated with reduced risk of post-acute sequelae. We used the healthcare databases of the US Department of Veterans Affairs to identify users of the health system who had a SARS-CoV-2 positive test between March 01, 2022 and June 30, 2022, were not hospitalized on the day of the positive test, had at least 1 risk factor for progression to severe COVID-19 illness and survived the first 30 days after SARS-CoV-2 diagnosis. We identify those who were treated with oral nirmatrelvir within 5 days after the positive test (n=9217) and those who received no COVID-19 antiviral or antibody treatment during the acute phase of SARS-CoV-2 infection (control group, n= 47,123). Inverse probability weighted survival models were used to estimate the effect of nirmatrelvir (versus control) on a prespecified panel of 12 post-acute COVID-19 outcomes and reported as hazard ratio (HR) and absolute risk reduction (ARR) in percentage at 90 days. Compared to the control group, treatment with nirmatrelvir was associated with reduced risk of PASC (HR 0.74 95% CI (0.69, 0.81), ARR 2.32 (1.73, 2.91)) including reduced risk of 10 of 12 post-acute sequelae in the cardiovascular system (dysrhythmia and ischemic heart disease), coagulation and hematologic disorders (deep vein thrombosis, and pulmonary embolism), fatigue, liver disease, acute kidney disease, muscle pain, neurocognitive impairment, and shortness of breath. Nirmatrelvir was also associated with reduced risk of post-acute death (HR 0.52 (0.35, 0.77), ARR 0.28 (0.14, 0.41)), and post-acute hospitalization (HR 0.70 (0.61, 0.80), ARR 1.09 (0.72, 1.46)). Nirmatrelvir was associated with reduced risk of PASC in people who were unvaccinated, vaccinated, and boosted, and in people with primary SARS-CoV-2 infection and reinfection. In sum, our results show that in people with SARS-CoV-2 infection who had at least 1 risk factor for progression to severe COVID-19 illness, treatment with nirmatrelvir within 5 days of a positive SARS-CoV-2 test was associated with reduced risk of PASC regardless of vaccination status and history of prior infection. The totality of findings suggests that treatment with nirmatrelvir during the acute phase of COVID-19 reduces the risk of post-acute adverse health outcomes.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.03.22281881", + "rel_abs": "BackgroundOur objective was to evaluate the real world effectiveness of nirmatrelvir/ritonavir to prevent severe COVID-19 while Omicron and its subvariants predominate.\n\nMethodsWe conducted a population based cohort study in Ontario, Canada including all residents >17 years of age who tested positive for SARS-CoV-2 by PCR between 4 April and 31 August 2022. We compared nirmatrelvir/ritonavir treated patients to unexposed patients and measured the primary outcome of hospitalization or death from COVID-19, and a secondary outcome of death 1-30 days. We used weighted logistic regression to calculate weighted odds ratios (wOR) with 95% confidence intervals (CIs) using inverse probability of treatment weighting (IPTW) to control for confounding.\n\nResultsThe final cohort included 177,545 patients with 8,876 (5.0%) exposed and 168,669 (95.0%) unexposed individuals. The groups were well balanced with respect to demographic and clinical characteristics after applying stabilized IPTW. Hospitalization or death within 30 days was lower in the nirmatrelvir/ritonavir treated group compared to unexposed individuals (2.1% vs 3.7%, wOR 0.56; 95%CI, 0.47-0.67). In the secondary analysis, the relative odds of death was also significantly reduced (1.6% vs 3.3%, wOR 0.49; 95%CI, 0.39-0.62). The number needed to treat to prevent one case of severe COVID-19 was 62 (95%CI 43 to 80). Findings were similar across strata of age, DDIs, vaccination status, and comorbidities.\n\nInterpretationNirmatrelvir/ritonavir was associated with significantly reduced risk of hospitalization and death from COVID-19 in this observational study, supporting ongoing use of this therapeutic to treat patients with mild COVID-19 at risk for severe disease.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Yan Xie", - "author_inst": "VA Saint Louis Health Care System" + "author_name": "Kevin L Schwartz", + "author_inst": "Public Health Ontario" }, { - "author_name": "Taeyoung Choi", - "author_inst": "VA Saint Louis Health Care System" + "author_name": "John Wang", + "author_inst": "Public Health Ontario" }, { - "author_name": "Ziyad Al-Aly", - "author_inst": "VA Saint Louis Health Care System" + "author_name": "Mina Tadrous", + "author_inst": "Leslie Dan Faculty of Pharmacy, University of Toronto" + }, + { + "author_name": "Bradley J Langford", + "author_inst": "Public Health Ontario" + }, + { + "author_name": "Nick Daneman", + "author_inst": "Public Health Ontario" + }, + { + "author_name": "Valerie Leung", + "author_inst": "Public Health Ontario" + }, + { + "author_name": "Tara Gomes", + "author_inst": "Li Ka Shing Knowledge Institute of St Michaels Hospital" + }, + { + "author_name": "Lindsay Friedman", + "author_inst": "Public Health Ontario" + }, + { + "author_name": "Peter Daley", + "author_inst": "Memorial University" + }, + { + "author_name": "Kevin A Brown", + "author_inst": "Public Health Ontario" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -153768,101 +152950,81 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2022.10.31.514592", - "rel_title": "Site of vulnerability on SARS-CoV-2 spike induces broadly protective antibody to antigenically distinct omicron SARS-CoV-2 subvariants", + "rel_doi": "10.1101/2022.10.31.514636", + "rel_title": "mRNA bivalent booster enhances neutralization against BA.2.75.2 and BQ.1.1", "rel_date": "2022-11-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.31.514592", - "rel_abs": "The rapid evolution of SARS-CoV-2 Omicron variants has emphasized the need to identify antibodies with broad neutralizing capabilities to inform future monoclonal therapies and vaccination strategies. Herein, we identify S728-1157, a broadly neutralizing antibody (bnAb) targeting the receptor-binding site (RBS) and derived from an individual previously infected with SARS-CoV-2 prior to the spread of variants of concern (VOCs). S728-1157 demonstrates broad cross-neutralization of all dominant variants including D614G, Beta, Delta, Kappa, Mu, and Omicron (BA.1/BA.2/BA.2.75/BA.4/BA.5/BL.1). Furthermore, it protected hamsters against in vivo challenges with wildtype, Delta, and BA.1 viruses. Structural analysis reveals that this antibody targets a class 1 epitope via multiple hydrophobic and polar interactions with its CDR-H3, in addition to common class 1 motifs in CDR-H1/CDR-H2. Importantly, this epitope is more readily accessible in the open and prefusion state, or in the hexaproline (6P)-stabilized spike constructs, as compared to diproline (2P) constructs. Overall, S728-1157 demonstrates broad therapeutic potential, and may inform target-driven vaccine design against future SARS-CoV-2 variants.", - "rel_num_authors": 21, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.31.514636", + "rel_abs": "The emergence of the highly divergent SARS-CoV-2 Omicron variant has jeopardized the efficacy of vaccines based on the ancestral spike. The bivalent COVID-19 mRNA booster vaccine within the United States is comprised of the ancestral and the Omicron BA.5 spike. Since its approval and distribution, additional Omicron subvariants have been identified with key mutations within the spike protein receptor binding domain that are predicted to escape vaccine sera. Of particular concern is the R346T mutation which has arisen in multiple subvariants, including BA.2.75.2 and BQ.1.1. Using a live virus neutralization assay, we evaluated serum samples from individuals who had received either one or two monovalent boosters or the bivalent booster to determine neutralizing activity against wild-type (WA1/2020) virus and Omicron subvariants BA.1, BA.5, BA.2.75.2, and BQ.1.1. In the one monovalent booster cohort, relative to WA1/2020, we observed a reduction in neutralization titers of 9-15-fold against BA.1 and BA.5 and 28-39-fold against BA.2.75.2 and BQ.1.1. In the BA.5-containing bivalent booster cohort, the neutralizing activity improved against all the Omicron subvariants. Relative to WA1/2020, we observed a reduction in neutralization titers of 3.7- and 4-fold against BA.1 and BA.5, respectively, and 11.5- and 21-fold against BA.2.75.2 and BQ.1.1, respectively. These data suggest that the bivalent mRNA booster vaccine broadens humoral immunity against the Omicron subvariants.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Siriruk Changrob", - "author_inst": "Weill Cornell Medicine" - }, - { - "author_name": "Peter J. Halfmann", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Hejun Liu", - "author_inst": "The Scripps Research Institute" - }, - { - "author_name": "Jonathan L. Torres", - "author_inst": "The Scripps Research Institute" - }, - { - "author_name": "Joshua J.C. McGrath", - "author_inst": "Weill Cornell Medicine" - }, - { - "author_name": "Gabriel Ozorowski", - "author_inst": "Scripps Research Institute" + "author_name": "Meredith E Davis-Gardner", + "author_inst": "Emory University" }, { - "author_name": "Lei Li", - "author_inst": "Weill Cornell Medicine" + "author_name": "Lilin Lai", + "author_inst": "Emory University" }, { - "author_name": "Makoto Kuroda", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Bushra Wali", + "author_inst": "Emory University" }, { - "author_name": "Tadashi Maemura", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Hady Samaha", + "author_inst": "Emory University" }, { - "author_name": "Min Huang", - "author_inst": "Weill Cornell Medicine" + "author_name": "Daniel Solis", + "author_inst": "Stanford University" }, { - "author_name": "Dewey G. Wilbanks", - "author_inst": "Weill Cornell Medicine" + "author_name": "Matthew Lee", + "author_inst": "Emory University" }, { - "author_name": "Nai-Ying Zheng", - "author_inst": "Weill Cornell Medicine" + "author_name": "Andrea Porter-Morrison", + "author_inst": "Emory University" }, { - "author_name": "Hannah L. Turner", - "author_inst": "The Scripps Research Institute" + "author_name": "Ian Thomas Hentenaar", + "author_inst": "Emory University" }, { - "author_name": "Steven A. Erickson", - "author_inst": "University of Chicago" + "author_name": "Fumiko Yamamoto", + "author_inst": "Stanford University" }, { - "author_name": "Yanbin Fu", - "author_inst": "Weill Cornell Medicine" + "author_name": "Sucheta Godbole", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Gagandeep Singh", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Daniel C Douek", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Florian Krammer", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Frances Eun-Hyung Lee", + "author_inst": "Emory University" }, { - "author_name": "Andrew B. Ward", - "author_inst": "The Scripps Research Institute" + "author_name": "Nadine Rouphael", + "author_inst": "Emory University" }, { - "author_name": "Ian A. Wilson", - "author_inst": "The Scripps Research Institute" + "author_name": "Alberto Moreno", + "author_inst": "Emory University" }, { - "author_name": "Yoshihiro Kawaoka", - "author_inst": "University of Tokyo, University of Wisconsin-Madison" + "author_name": "Benjamin A Pinsky", + "author_inst": "Stanford University" }, { - "author_name": "Patrick C. Wilson", - "author_inst": "Weill Cornell Medicine" + "author_name": "Mehul S Suthar", + "author_inst": "Emory University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "immunology" }, @@ -155157,51 +154319,115 @@ "category": "rheumatology" }, { - "rel_doi": "10.1101/2022.10.27.22281582", - "rel_title": "The relative contribution of COVID-19 infection versus COVID-19 related occupational stressors to insomnia in healthcare workers", + "rel_doi": "10.1101/2022.10.29.22281606", + "rel_title": "Protection against reinfection with SARS-CoV-2 omicron BA.2.75* sublineage", "rel_date": "2022-10-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.27.22281582", - "rel_abs": "Objective/BackgroundHealthcare workers have experienced high rates of psychiatric symptom burden and occupational attrition during the COVID-19 pandemic. Identifying contributory factors can inform prevention and mitigation measures. Here, we explore the potential contributions of occupational stressors vs COVID-19 infection to insomnia symptoms in US healthcare workers.\n\nPatients/MethodsAn online self-report survey was collected between September 2020 and July 2022 from N=594 US healthcare workers, with longitudinal follow-up up to 9 months. Assessments included the Insomnia Severity Index (ISI), the PTSD Checklist for DSM-5 (PCL-5), and a 13-item scale assessing COVID-19 related occupational stressors.\n\nResultsInsomnia was common (45% of participants reported at least moderate and 9.2% reported severe symptoms at one or more timepoint) and significantly associated with difficulty completing work-related tasks, increased likelihood of occupational attrition, and thoughts of suicide or self-harm (all p<.0001). In multivariable regression with age, gender, and family COVID-19 history as covariates, past two-week COVID-related occupational stressors, peak COVID-related occupational stressors, and personal history of COVID-19 infection were all significantly related to past two-week ISI scores ({beta}=1.7{+/-}0.14SE, {beta}=0.08{+/-}0.03, and {beta}=0.69{+/-}0.22 respectively). Although similar results were found for the PCL-5, when ISI and PCL-5 items were separated by factor, COVID-19 infection was significantly related only to the factor consisting of sleep-related items.\n\nConclusionsBoth recent occupational stress and personal history of COVID-19 infection were significantly associated with insomnia in healthcare workers. These results suggest that both addressing occupational stressors and reducing rates of COVID-19 infection are important to protect healthcare workers and the healthcare workforce.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.29.22281606", + "rel_abs": "The BA.2.75* sublineage of SARS-CoV-2 B.1.1.529 (omicron) variant escapes neutralizing antibodies. We estimated effectiveness of prior infection in preventing reinfection with BA.2.75* using a test-negative, case-control study design. Effectiveness of prior pre-omicron infection against BA.2.75* reinfection, irrespective of symptoms, was 6.0% (95% CI: 1.5-10.4%). Effectiveness of prior BA.1/BA.2 infection was 49.9% (95% CI: 47.6-52.1%) and of prior BA.4/BA.5 infection was 80.6% (95% CI: 71.2-87.0). Effectiveness of prior pre-omicron infection followed by BA.1/BA.2 infection against BA.2.75* reinfection was 56.4% (95% CI: 50.5-61.6). Effectiveness of prior pre-omicron infection followed by BA.4/BA.5 infection was 91.6% (95% CI: 65.1-98.0). Analyses stratified by time since prior infection indicated waning of protection since prior infection. Analyses stratified by vaccination status indicated that protection from prior infection is higher among those vaccinated, particularly among those ...", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Rebecca Cappel Hendrickson", - "author_inst": "VA Puget Sound Healthcare System" + "author_name": "Hiam Chemaitelly", + "author_inst": "Weill Cornell Medicine-Qatar" }, { - "author_name": "Catherine A McCall", - "author_inst": "VA Puget Sound Healthcare System" + "author_name": "Patrick Tang", + "author_inst": "Sidra Medicine" }, { - "author_name": "Aaron F Rosser", - "author_inst": "VA Puget Sound Healthcare System" + "author_name": "Peter Coyle", + "author_inst": "Hamad Medical Corporation" }, { - "author_name": "Kathleen F Pagulayan", - "author_inst": "University of Washington" + "author_name": "HADI M. YASSINE", + "author_inst": "Qatar University" }, { - "author_name": "Bernard P Chang", - "author_inst": "Columbia University" + "author_name": "Hebah A. Al Khatib", + "author_inst": "Qatar University" }, { - "author_name": "Ellen D Sano", - "author_inst": "Columbia University" + "author_name": "Maria K. Smatti", + "author_inst": "Qatar University" }, { - "author_name": "Ronald G Thomas", - "author_inst": "University of California San Diego" + "author_name": "Mohammad R. Hasan", + "author_inst": "Sidra Medicine" }, { - "author_name": "Murray A Raskind", - "author_inst": "VA Puget Sound Healthcare System" + "author_name": "Houssein Ayoub", + "author_inst": "Qatar University" + }, + { + "author_name": "Heba N. Altarawneh", + "author_inst": "Weill Cornell Medicine-Qatar" + }, + { + "author_name": "Zaina Al-Kanaani", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Einas Al-Kuwari", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Andrew Jeremijenko", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Anvar Hassan Kaleeckal", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Ali Nizar Latif", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Riyazuddin Mohammad Shaik", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Hanan F. Abdul-Rahim", + "author_inst": "Qatar University" + }, + { + "author_name": "Gheyath Nasrallah", + "author_inst": "Qatar University" + }, + { + "author_name": "Mohamed Ghaith Al-Kuwari", + "author_inst": "Primary Health Care Corporation" + }, + { + "author_name": "Adeel A Butt", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Hamad E. Al-Romaihi", + "author_inst": "MoPH: Ministry of Public Health Qatar" + }, + { + "author_name": "Mohammed H. J. Al-Thani", + "author_inst": "MoPH: Ministry of Public Health Qatar" + }, + { + "author_name": "Abdullatif Al-Khal", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Roberto Bertollini", + "author_inst": "MOPH: Ministry of Public Health Qatar" + }, + { + "author_name": "Laith J Abu-Raddad", + "author_inst": "Weill Cornell Medicine-Qatar" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.10.27.22281632", @@ -157499,59 +156725,51 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.10.26.22281537", - "rel_title": "Bell's Palsy Following SARS-CoV-2 Vaccines: A Systematic Review and Meta-Analysis", + "rel_doi": "10.1101/2022.10.25.22281493", + "rel_title": "A rapid review of Supplementary air filtration systems in health service settings. September 2022.", "rel_date": "2022-10-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.26.22281537", - "rel_abs": "Background and ObjectiveBells palsy (BP) has been considered as a serious adverse event following the SARS-CoV-2 vaccination. Many studies have reported BP following vaccination, although neither a causative relationship nor a prevalence of the condition higher than the general population has been established. The outcomes of interest were to compare BP incidence among (a) SARS-CoV-2 vaccine recipients, (b) nonrecipients in the placebo or unvaccinated cohorts, (c) different types of SARS-CoV-2 vaccines, and (d) SARS-CoV-2 infected vs. SARS-CoV-2 vaccinated individuals.\n\nMethodsWe performed a systematic search through MEDLINE (via PubMed), Web of Science, Scopus, Cochrane library, and Google Scholar from the inception to August 15, 2022. We included articles reporting individuals receiving any SARS-CoV-2 vaccine in whom BP had occurred. Studies reporting facial paralysis due to etiologies other than BP were excluded. Random- and fixed-effects meta-analyses using the Mantel-Haenszel method were conducted for the quantitative synthesis. Newcastle-Ottawa scale (NOS) was used to assess the quality. The study was conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline, and the protocol was registered with PROSPERO (CRD42022313299). Analyses were carried out using the R, version 4.2.1 (R package meta version 5.2-0).\n\nResultsFifty studies were included, of which 17 entered the quantitative synthesis. First, pooling four phase-3 randomized controlled trials (RCT) indicated BP occurrence was significantly higher in SARS-CoV-2 vaccines (77, 525 doses) compared to placebo (66, 682 doses) (OR = 3.00, 95% CI = 1.10 - 8.18, I2 = 0%). Second, pooling nine observational studies of mRNA SARS-CoV-2 vaccine doses (13, 518,026) and matched unvaccinated individuals (13, 510,701) revealed no significant increase in the odds of BP in the vaccinated group compared to the unvaccinated group (OR: 0.70 (95% CI 0.42-1.16), I2=94%). The third meta-analysis suggested that post-vaccination BP among first dose Pfizer/BioNTech recipients (22,760,698) did not significantly differ from that in first dose Oxford/AstraZeneca recipients (22,978,880) (OR = 0.97, 95% CI = 0.82 - 1.15, I2 = 0%). According to the fourth meta-analysis, BP was significantly more commonly reported after SARS-CoV-2 infection (2,641,398) than after SARS-CoV-2 vaccinations (36,988,718) (RR = 4.03, 95% CI = 1.78 - 9.12, I2 = 96%).\n\nConclusionOur meta-analysis suggests a higher incidence of BP among vaccinated vs. placebo groups. BP occurrence did not significantly differ between Pfizer/BioNTech and Oxford/AstraZeneca vaccines. SARS-CoV-2 infection posed a significantly greater risk for BP than SARS-CoV-2 vaccines.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.25.22281493", + "rel_abs": "The aerosol spread of SARS-CoV-2 has been a major challenge for healthcare facilities and there has been increased use of supplementary air filtration to mitigate SARS-CoV-2 transmission. Appropriately sized supplementary room air filtration systems could greatly reduce aerosol levels throughout ward spaces. Portable air filtration systems, such as those combining high efficiency particulate air (HEPA) filters and ultraviolet (UVC) light sterilisation, may be a scalable solution for removing respiratory viruses such as SARS-CoV-2. This rapid review aimed to assess the effectiveness of supplementary air cleaning devices in health service settings such as hospitals and dental clinics (including, but not limited to HEPA filtration, UVC light and mobile UVC light devices) to reduce the transmission of SARS-CoV-2.\n\nOne systematic review (Daga et al. 2021), three observational studies (Conway Morris et al. 2022, Thuresson et al. 2022, Sloof et al. 2022), one modelling study, (Buchan et al. 2020) and two experimental studies (Barnewall & Bischoff 2021, Snelling et al. 2022) were found. Outcome measures included symptom scores, presence of SARS-CoV-2 RNA in sample counts, general particulate matter counts, viral counts, and relative risk of SARS-CoV-2 exposure. From real world settings, the systematic review assessed the effectiveness of HEPA filtration in dental clinics (Daga et al. 2021), two additional observational studies assessed HEPA and UV light in UK hospital settings (Conway Morris et al. 2022, Sloof et al. 2022) and one observational study included mobile HEPA-filtration units in Swedish hospitals (Thuresson et al. 2022). Studies were published from 2020 onwards.\n\nReal world evidence suggests supplementary air systems have the potential to reduce SARS-CoV-2 in the air and subsequently reduce transmission or infection rates but further research, with study designs having lower risk of bias, is required. HEPA filters alongside UVC light could provide the most notable reductions in SARS-CoV-2 counts, although the supporting evidence relates to HEPA/UVC filtration, and this review does not provide evidence on the effectiveness of other potential supplementary air filtration systems that could be used. Evidence is limited on the optimum air changes per hour needed and the positioning of air filtration units in rooms.\n\nFunding statementThe Wales Centre for Evidence Based Care was funded for this work by the Wales COVID-19 Evidence Centre, itself funded by Health & Care Research Wales on behalf of Welsh Government.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Ali Rafati", - "author_inst": "School of Medicine, Iran University of Medical Sciences." - }, - { - "author_name": "Yeganeh Pasebani", - "author_inst": "School of Medicine, Iran University of Medical Sciences." - }, - { - "author_name": "Melika Jameie", - "author_inst": "Iranian Center of Neurological Research, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran." + "author_name": "Charlotte Marie Bowles", + "author_inst": "Health Technology Wales" }, { - "author_name": "Yuchen Yang", - "author_inst": "Department of Neurology and Otolaryngology-Head & Neck Surgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA." + "author_name": "Tom Winfield", + "author_inst": "Health Technology Wales" }, { - "author_name": "Mana Jameie", - "author_inst": "Cardiovascular Diseases Research Institute, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran." + "author_name": "Lauren Elston", + "author_inst": "Health Technology Wales" }, { - "author_name": "Saba Ilkhani", - "author_inst": "Center for Surgery and Public Health, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA." + "author_name": "Elise Hasler", + "author_inst": "Health Technology Wales" }, { - "author_name": "Mobina Amanollahi", - "author_inst": "Iranian Center of Neurological Research, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran." + "author_name": "Antonia Needham", + "author_inst": "Health Technology Wales" }, { - "author_name": "Delaram Sakhaei", - "author_inst": "School of Medicine, Sari branch, Islamic Azad University, Sari, Iran." + "author_name": "Alison Cooper", + "author_inst": "Wales COVID-19 Evidence Centre" }, { - "author_name": "Mehran Rahimlou", - "author_inst": "Department of Nutrition, School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran." + "author_name": "Ruth Lewis", + "author_inst": "Wales COVID-19 Evidence Centre" }, { - "author_name": "Amir Kheradmand", - "author_inst": "Departments of Neurology, Neuroscience, Otolaryngology-Head & Neck Surgery, and Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins Universi" + "author_name": "Adrian Edwards", + "author_inst": "Wales COVID-19 Evidence Centre" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "otolaryngology" + "category": "health policy" }, { "rel_doi": "10.1101/2022.10.25.22281247", @@ -159833,29 +159051,41 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.10.18.22281181", - "rel_title": "Development of Loop-mediated Isothermal Amplification (LAMP) Assays Using Five Primers Reduces the False-positive Rate in COVID-19 Diagnosis", + "rel_doi": "10.1101/2022.10.21.22281366", + "rel_title": "Impact of the COVID-19 pandemic on the circulation of other pathogens in England", "rel_date": "2022-10-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.18.22281181", - "rel_abs": "The reverse-transcription loop-mediated isothermal amplification (RT-LAMP) is a cheaper and faster testing alternative for detecting SARS-CoV-2. However, high false-positive rate due to misamplification is one of the major limitations. To overcome misamplifications, we developed colorimetric and fluorometric RT-LAMP assays. The assay performances was verified by the gold-standard RT-qPCR technique on 150 clinical samples. Compared to other primer sets with six primers (N, S, and RdRp), E-ID1 primer set, including five primers, performed superbly on both colorimetric and fluorometric assays, yielding sensitivities of 89.5% and 100%, respectively, with a limit of detection of 20 copies/{micro}L. The colorimetric RT-LAMP had a specificity of 97.2% and an accuracy of 94.5%, while the fluorometric RT-LAMP obtained 96.9% and 98%, respectively. No misamplification was evident even after 120 minutes, which is crucial for the success of this technique. These findings are important to support the use of RT-LAMP in the healthcare systems in fighting COVID-19.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.21.22281366", + "rel_abs": "The COVID-19 pandemic and the associated prevention measures did not only impact on the transmission of COVID-19 but also on the spread of other infectious diseases in an unprecedented natural experiment. Here, we analysed the transmission patterns of 22 different infectious diseases during the COVID-19 pandemic in England. Our results show that the COVID-19 prevention measures generally reduced the spread of pathogens that are transmitted via the air and the faecal-oral route. Moreover, the COVID-19 prevention measures resulted in the sustained suppression of vaccine-preventable infectious diseases also after the removal of restrictions, while non-vaccine preventable diseases displayed a rapid rebound. Despite concerns that a lack of exposure to common pathogens may affect population immunity and result in large outbreaks by various pathogens post-COVID-19, only four of the 22 investigated diseases and disease groups displayed higher post-than pre-pandemic levels without an obvious causative relationship. Notably, this included chickenpox for which an effective vaccine is available but not used in the UK, which provides strong evidence supporting the inclusion of the chickenpox vaccination into the routine vaccination schedule in the UK. In conclusion, our findings provide unique, novel insights into the impact of non-pharmaceutical interventions on the spread of a broad range of infectious diseases.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Galyah Alhamid", - "author_inst": "Imam Abdulrahman bin Faisal University" + "author_name": "Lauren Hayes", + "author_inst": "University of Kent" }, { - "author_name": "Huseyin Tombuloglu", - "author_inst": "Imam Abdulrahman bin Faisal University" + "author_name": "Hannah Uri", + "author_inst": "University of Kent" }, { - "author_name": "Ebtesam Al-Suhaimi", - "author_inst": "Imam Abdulrahman bin Faisal University" + "author_name": "Denisa Bojkova", + "author_inst": "Goethe-University" + }, + { + "author_name": "Jindrich Cinatl Jr.", + "author_inst": "Goethe-University" + }, + { + "author_name": "Mark N Wass", + "author_inst": "University of Kent" + }, + { + "author_name": "Martin Michaelis", + "author_inst": "University of Kent" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -161771,135 +161001,83 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2022.10.19.512979", - "rel_title": "Ancestral SARS-CoV-2 driven antibody repertoire diversity in an unvaccinated individual correlates with expanded neutralization breadth", + "rel_doi": "10.1101/2022.10.19.512891", + "rel_title": "Distinct Neutralizing Antibody Escape of SARS-CoV-2 Omicron Subvariants BQ.1, BQ.1.1, BA.4.6, BF.7 and BA.2.75.2", "rel_date": "2022-10-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.19.512979", - "rel_abs": "Understanding the quality of immune repertoire triggered during natural infection can provide vital clues that form the basis for development of humoral immune response in some individuals capable of broadly neutralizing pan SARS-CoV-2 variants. We assessed the diversity of neutralizing antibody responses developed in an unvaccinated individual infected with ancestral SARS-CoV-2 by examining the ability of the distinct B cell germline-derived monoclonal antibodies (mAbs) in neutralizing known and currently circulating Omicron variants by pseudovirus and authentic virus neutralization assays. The ability of the antibodies developed post vaccination in neutralizing Omicron variants was compared to that obtained at baseline of the same individual and to those obtained from Omicron breakthrough infected individuals by pseudovirus neutralization assay. Broadly SARS-CoV-2 neutralizing mAbs representing unique B cell lineages with non-overlapping epitope specificities isolated from a single donor varied in their ability to neutralize Omicron variants. Plasma antibodies developed post vaccination from this individual demonstrated neutralization of Omicron BA.1, BA.2 and BA.4 with increased magnitude and found to be comparable with those obtained from other vaccinated individuals who were infected with ancestral SARS-CoV-2. Development of B cell repertoire capable of producing antibodies with distinct affinity and specificities for the antigen immediately after infection capable of eliciting broadly neutralizing antibodies offers highest probability in protecting against evolving SARS-CoV-2 variants.\n\nImportanceDevelopment of robust neutralizing antibodies in SARS-CoV-2 convalescent individuals is known, however varies at population level. We isolated monoclonal antibodies from an individual infected with ancestral SARS-CoV-2 in early 2020 that not only varied in their B cell lineage origin but also varied in their capability and potency to neutralize all the known VOC and currently circulating Omicron variants. This indicated establishment of unique lineages that contributed in forming B cell repertoire in this particular individual immediately following infection giving rise to diverse antibody responses that could compensate each other in providing broadly neutralizing polyclonal antibody response. Individuals who were able to produce such potent polyclonal antibody responses after infection have a higher chance of being protected from evolving SARS-CoV-2 variants.", - "rel_num_authors": 29, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.19.512891", + "rel_abs": "Continued evolution of SARS-CoV-2 has led to the emergence of several new Omicron subvariants, including BQ.1, BQ. 1.1, BA.4.6, BF.7 and BA.2.75.2. Here we examine the neutralization resistance of these subvariants, as well as their ancestral BA.4/5, BA.2.75 and D614G variants, against sera from 3-dose vaccinated health care workers, hospitalized BA.1-wave patients, and BA.5-wave patients. We found enhanced neutralization resistance in all new subvariants, especially the BQ.1 and BQ.1.1 subvariants driven by a key N460K mutation, and to a lesser extent, R346T and K444T mutations, as well as the BA.2.75.2 subvariant driven largely by its F486S mutation. The BQ.1 and BQ.1.1 subvariants also exhibited enhanced fusogenicity and S processing dictated by the N460K mutation. Interestingly, the BA.2.75.2 subvariant saw an enhancement by the F486S mutation and a reduction by the D1199N mutation to its fusogenicity and S processing, resulting in minimal overall change. Molecular modelling revealed the mechanisms of receptor-binding and non-receptor binding monoclonal antibody-mediated immune evasion by R346T, K444T, F486S and D1199N mutations. Altogether, these findings shed light on the concerning evolution of newly emerging SARS-CoV-2 Omicron subvariants.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Suprit Deshpande", - "author_inst": "Translational Health Science & Technology Institute" - }, - { - "author_name": "Mohammed Yousuf Ansari", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Jyoti Sutar", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Payel Das", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Nitin Hingankar", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Sohini Mukherjee", - "author_inst": "International AIDS Vaccine Initiative" - }, - { - "author_name": "Priyanka Jayal", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Savita Singh", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Anbalagan Anantharaj", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Janmejay Singh", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Souvick Chattopadhyay", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Sreevatsan Raghavan", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Mudita Gosain", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Supriya Chauhan", - "author_inst": "Translational Health Science and Technology Institute" + "author_name": "Panke Qu", + "author_inst": "The Ohio State University" }, { - "author_name": "Shweta Shrivas", - "author_inst": "Translational Health Science and Technology Institute" + "author_name": "John P. Evans", + "author_inst": "The Ohio State University" }, { - "author_name": "Chaman Prasad", - "author_inst": "Translational Health Science and Technology Institute" + "author_name": "Julia Faraone", + "author_inst": "The Ohio State University" }, { - "author_name": "Sangeeta Chauhan", - "author_inst": "Translational Health Science and Technology Institute" + "author_name": "Yi-Min Zheng", + "author_inst": "The Ohio State University" }, { - "author_name": "Neha Sharma", - "author_inst": "Translational Health Science and Technology Institute" + "author_name": "Claire Carlin", + "author_inst": "The Ohio State University" }, { - "author_name": "Pradipta Jana", - "author_inst": "Translational Health Science and Technology Institute" + "author_name": "Mirela Anghelina", + "author_inst": "The Ohio State University" }, { - "author_name": "Ramachandran Thiruvengadam", - "author_inst": "Translational Health Science and Technology Institute" + "author_name": "Patrick Stevens", + "author_inst": "The Ohio State University" }, { - "author_name": "Pallavi Kshetrapal", - "author_inst": "Translational Health Science and Technology Institute" + "author_name": "Soledad Fernandez", + "author_inst": "The Ohio State University" }, { - "author_name": "Nitya Wadhwa", - "author_inst": "Translational Health Science and Technology Institute" + "author_name": "Daniel Jones", + "author_inst": "The Ohio State University" }, { - "author_name": "Bhabatosh Das", - "author_inst": "Translational Health Science and Technology Institute" + "author_name": "Gerard Lozanski", + "author_inst": "The Ohio State University" }, { - "author_name": "Gaurav Batra", - "author_inst": "Translational Health Science and Technology Institute" + "author_name": "Ashish Panchal", + "author_inst": "The Ohio State University" }, { - "author_name": "Guruprasad R. Medigeshi", - "author_inst": "Translational Health Science and Technology Institute" + "author_name": "Linda J. Saif", + "author_inst": "The Ohio State University" }, { - "author_name": "Devin Sok", - "author_inst": "International AIDS Vaccine Initiative" + "author_name": "Eugene M. Oltz", + "author_inst": "The Ohio State University" }, { - "author_name": "Shinjini Bhatnagar", - "author_inst": "Translational Health Science and Technology Institute" + "author_name": "Kai Xu", + "author_inst": "The Ohio State University" }, { - "author_name": "Pramod Garg", - "author_inst": "Translational Health Science and Technology Institute" + "author_name": "Richard J. Gumina", + "author_inst": "The Ohio State University" }, { - "author_name": "Jayanta Bhattacharya", - "author_inst": "Translational Health Science & Technology Institute" + "author_name": "Shan-Lu Liu", + "author_inst": "The Ohio State University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.10.20.512999", @@ -163945,53 +163123,65 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2022.10.14.22281075", - "rel_title": "Incidence and severity of SARS-CoV-2 infections in people with primary ciliary dyskinesia", + "rel_doi": "10.1101/2022.10.16.22281135", + "rel_title": "Parental COVID-19 vaccine hesitancy and vaccine uptake among children and adolescents in the US: Findings from a prospective national cohort", "rel_date": "2022-10-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.14.22281075", - "rel_abs": "ImportanceEarly in the COVID-19 pandemic, chronic respiratory disease was considered a risk factor for severe COVID-19 disease. Studies have confirmed a higher risk of intensive care unit admission and mortality in people with chronic pulmonary obstructive disease and cystic fibrosis, but there is little data in people with primary ciliary dyskinesia (PCD).\n\nObjectiveTo study incidence of SARS-CoV-2 and its risk factors in people with PCD from May 2020 to May 2022. We also describe the severity of COVID-19 symptoms in this population and factors associated with severity.\n\nDesign, setting, and participantsWe used data from COVID-PCD, an international participatory cohort study following people with PCD through the COVID-19 pandemic. The study is based on self-reported weekly online questionnaires, available in five languages, adapted to children, adolescents, and adults. COVID-PCD invites people with PCD of any age to participate.\n\nExposuresSARS-CoV-2\n\nMain OutcomesIncidence of reported positive test of SARS-CoV-2 and reported severity of symptoms.\n\nResultsBy May 2022, 728 people with PCD participated (40% male, median age 27 years; range 0-85). The median weeks of follow-up was 60 (range 1-100). Eighty-seven (12%) reported a SARS-CoV-2 infection at baseline or during follow-up and 62 people reported an incident SARS-CoV-2 infection during 716 person-years of follow-up (incidence rate 9 per 100 person years; 95%CI 7-11). Using Poisson regression, we found that age above 14 years was associated with lower risk of infection (IRR 0.42, 95%CI 0.21-0.85) but the strongest predictors were exposure to Delta (IRR 4.52, 95%CI 1.92-10.6) and Omicron variants (IRR 13.3, 95%CI 5.2-33.8) compared to the original strain. Severity of disease was mainly mild; 12 (14%) were asymptomatic and 75 (86%) had symptoms among whom 4 were hospitalized. None needed intensive care and nobody died. Using Poisson regression, we found that comorbidity (IRR 1.93, 95%CI 1.40-2.64) and being infected during the period when the Delta variant was predominant (IRR 1.43, 95%CI 1.07-1.92) were associated with more reported symptoms.\n\nConclusion and RelevancePeople with PCD do not seem to have a higher incidence of SARS-CoV-2 infections nor higher risk of severe COVID-19 disease than people from the general population.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat is the incidence and severity of COVID-19 in people with primary ciliary dyskinesia and which factors are associated with reporting a SARS-CoV-2 infection and risk of severe disease?\n\nFindingsThis international cohort of 728 people with primary ciliary dyskinesia followed for two years during the COVID-19 pandemic found a low incidence of reported SARS-CoV-2 in people with primary ciliary dyskinesia and mainly mild disease. The strongest predictor of incidence and severity was virus variant.\n\nMeaningPeople with PCD do not seem to have a higher incidence of SARS-CoV-2 infections nor higher risk of severe COVID-19 disease than people from the general population.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.16.22281135", + "rel_abs": "ObjectivesOur aim was to measure COVID-19 vaccine uptake among children aged 5-17 years old via parents participating in the CHASING COVID Cohort and identify sociodemographic factors associated with it.\n\nMethodsIn this longitudinal study, parents of school-aged children were asked about their own vaccination status and that of their children at three time points between June 2021-January 2022, along with reasons for vaccinating immediately or delaying vaccinations for their children. Multivariable log binomial models were used to identify correlates of vaccine uptake among children.\n\nResultsOf the 1,583 children aged 5-17 years, 64.9% were vaccinated. Over 40% of parents of 5-11 year old children who intended to delay vaccinating their child in June 2021 had still not vaccinated them by January 2022, including 30% of the parents who were vaccinated. After adjusting for measured confounders, parents vaccination status was associated with higher likelihood of childrens vaccine uptake (age-specific adjusted odds ratios [aORs]: aOR16-17 3.7, 95% CI 2.3, 5.9, aOR12-15 3.7, 95% CI 2.6, 5.3; aOR5-11 10.6, 95% CI 5.4, 20.9). Parents education (aOR16-17 1.4, 95% CI 1.1, 1.8, aOR12-15 1.5, 95% CI 1.2, 1.9; aOR5-11 2.1, 95% CI 1.5, 2.9) and worry about others getting infected (aOR5-11 1.4, 95% CI 1.1, 1.6) were also associated with higher vaccine uptake among children. A higher proportion of parents of 5-11 year olds (vs. 12-17 year olds) had concerns about vaccine safety and effectiveness.\n\nConclusionTo increase vaccination coverage among young children, vaccination campaigns should focus on both vaccinated and unvaccinated parents and messaging should be specific to the childs age.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Eva Sophie Lunde Pedersen", - "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland" + "author_name": "Madhura S. Rane", + "author_inst": "City University of New York" }, { - "author_name": "Leonie Daria Schreck", - "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland" + "author_name": "McKaylee S. Robertson", + "author_inst": "CUNY ISPH" }, { - "author_name": "Myrofora Goutaki", - "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Paediatric Respiratory Medicine, Childrens University Hospital of Bern, Univ" + "author_name": "Drew A Westmoreland", + "author_inst": "City University of New York" }, { - "author_name": "Sara Bellu", - "author_inst": "Associazione italiana Discinesia Ciliare Primaria Sindrome di Kartagener Onlus, Italy" + "author_name": "Rebecca Zimba", + "author_inst": "CUNY Graduate School of Public Health and Health Policy" }, { - "author_name": "Fiona Copeland", - "author_inst": "PCD support UK, London, United Kingdom" + "author_name": "Sarah G Kulkarni", + "author_inst": "CUNY ISPH" }, { - "author_name": "Jane S Lucas", - "author_inst": "Primary Ciliary Dyskinesia Centre, NIHR Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK; University of Southam" + "author_name": "Yanhan Shen", + "author_inst": "CUNY ISPH" }, { - "author_name": "Marcel Zwahlen", - "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland" + "author_name": "Amanda Berry", + "author_inst": "CUNY ISPH" }, { - "author_name": "- COVID-PCD patient advisory group", - "author_inst": "" + "author_name": "Mindy Chang", + "author_inst": "CUNY ISPH" }, { - "author_name": "Claudia E. Kuehni", - "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland: Paediatric Respiratory Medicine, Childrens University Hospital of Bern, Univ" + "author_name": "William You", + "author_inst": "The CUNY Institute for Implementation Science in Population Health" + }, + { + "author_name": "Christian Grov", + "author_inst": "CUNY ISPH" + }, + { + "author_name": "Denis Nash", + "author_inst": "City University of New York School of Public Health" + }, + { + "author_name": "- CHASING COVID Cohort Team", + "author_inst": "-" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -165775,53 +164965,117 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.10.12.22280928", - "rel_title": "Real-time surveillance of international SARS-CoV-2 prevalence using systematic traveller arrival screening", + "rel_doi": "10.1101/2022.10.12.22281019", + "rel_title": "Impact of COVID-19 on mortality in coastal Kenya: a longitudinal open cohort study", "rel_date": "2022-10-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.12.22280928", - "rel_abs": "BackgroundEffective COVID-19 response relies on good knowledge of infection dynamics, but owing to under-ascertainment and delays in symptom-based reporting, obtaining reliable infection data has typically required large dedicated local population studies. Although many countries implemented SARS-CoV-2 testing among travellers, interpretation of arrival testing data has typically been challenging because arrival testing data were rarely reported systematically, and pre-departure testing was often in place as well, leading to non-representative infection status among arrivals.\n\nMethodsIn French Polynesia, testing data were reported systematically with enforced pre-departure testing type and timing, making it possible to adjust for non-representative infection status among arrivals. Combining statistical models of PCR positivity with data on international travel protocols, we reconstructed estimates of prevalence at departure using only testing data from arrivals. We then applied this estimation approach to the USA and France, using data from over 220,000 tests from travellers arriving into French Polynesia between July 2020 and March 2022.\n\nFindingsWe estimated a peak infection prevalence at departure of 2.8% (2.3-3.6%) in France and 1.1% (0.81-3.1%) in the USA in late 2020/early 2021, with prevalence of 5.4% (4.8-6.1%) and 5.5% (4.6-6.6%) respectively estimated for the Omicron BA.1 waves in early 2022. We found that our infection estimates were a leading indicator of later reported case dynamics, as well as being consistent with subsequent observed changes in seroprevalence over time.\n\nInterpretationAs well as elucidating previously unmeasured infection dynamics in these countries, our analysis provides a proof-of-concept for scalable tracking of global infections during future pandemics.\n\nFundingWellcome (206250/Z/17/Z)", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.12.22281019", + "rel_abs": "BackgroundThere is uncertainty about the mortality impact of the COVID-19 pandemic in Africa because of poor ascertainment of cases and limited national civil vital registration. We analysed excess mortality from 1st January 2020-5th May 2022 in a Health and Demographic Surveillance Study in Coastal Kenya where the SARS-CoV-2 seroprevalence reached 75% among adults in March 2022 despite vaccine uptake of only 17%.\n\nMethodsWe modelled expected mortality in 2020-2022 among a population of 306,000 from baseline surveillance data between 2010-2019. We calculated excess mortality as the ratio of observed/expected deaths in 5 age strata for each month and for each national wave of the pandemic. We estimated cumulative mortality risks as the total number of excess deaths in the pandemic per 100,000 population. We investigated observed deaths using verbal autopsy.\n\nFindingWe observed 16,236 deaths among 3,410,800 person years between 1st January 2010 and 5th May 2022. Across 5 waves of COVID-19 cases during 1st April 2020-16th April 2022, population excess mortality was 4.1% (95% PI -0.2%, 7.9%). Mortality was elevated among those aged [≥]65 years at 14.3% (95% PI 7.4%, 21.6%); excess deaths coincided with wave 2 (wild-type), wave 4 (Delta) and wave 5 (Omicron BA1). Among children aged 1-14 years there was negative excess mortality of -20.3% (95% PI -29.8%, -8.1%). Verbal autopsy data showed a transient reduction in deaths from acute respiratory infections in 2020 at all ages. For comparison with other studies, cumulative excess mortality risk for January 2020-December 2021, age-standardized to the Kenyan population, was 47.5/100,000.\n\nInterpretationNet excess mortality during the pandemic was substantially lower in Coastal Kenya than in many high income countries. However, adults, aged [≥]65 years, experienced substantial excess mortality suggesting that targeted COVID-19 vaccination of older persons may limit further COVID-19 deaths by protecting the residual pool of naive individuals.\n\nFundingWellcome Trust", + "rel_num_authors": 26, "rel_authors": [ { - "author_name": "Adam Kucharski", - "author_inst": "London School of Hygiene & Tropical Medicine" + "author_name": "Mark O Otiende", + "author_inst": "KEMRI-Wellcome Trust Research Programme" }, { - "author_name": "Kiyojiken Chung", - "author_inst": "Institut Louis Malarde" + "author_name": "Amek Nyaguara", + "author_inst": "KEMRI-Wellcome Research Trust Programme, Kilifi, Kenya" }, { - "author_name": "Maite Aubry", - "author_inst": "Institut Louis Malarde" + "author_name": "Christian Bottomley", + "author_inst": "Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK" }, { - "author_name": "Iotefa Teiti", - "author_inst": "Institut Louis Malarde" + "author_name": "David Walumbe", + "author_inst": "KEMRI-Wellcome Research Trust Programme, Kilifi, Kenya" }, { - "author_name": "Anita Teissier", - "author_inst": "Institut Louis Malarde" + "author_name": "George Mochamah", + "author_inst": "KEMRI-Wellcome Research Trust Programme, Kilifi, Kenya" }, { - "author_name": "Vaea Richard", - "author_inst": "Institut Louis Malarde" + "author_name": "David Amadi", + "author_inst": "KEMRI-Wellcome Research Trust Programme, Kilifi, Kenya" }, { - "author_name": "Timothy Russell", - "author_inst": "London School of Hygiene & Tropical Medicine" + "author_name": "Christopher Nyundo", + "author_inst": "KEMRI-Wellcome Research Trust Programme, Kilifi, Kenya" }, { - "author_name": "Raphaelle Bos", - "author_inst": "Institut Louis Malarde" + "author_name": "Eunice Kagucia", + "author_inst": "KEMRI-Wellcome Research Trust Programme, Kilifi, Kenya" }, { - "author_name": "Sophie Olivier", - "author_inst": "Institut Louis Malarde" + "author_name": "Anthony Etyang'", + "author_inst": "KEMRI-Wellcome Research Trust Programme, Kilifi, Kenya" }, { - "author_name": "Van-Mai Cao-Lormeau", - "author_inst": "Institut Louis Malarde" + "author_name": "Ifedayo Adetifa", + "author_inst": "Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK" + }, + { + "author_name": "Sam PC Brand", + "author_inst": "The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick" + }, + { + "author_name": "Eric Maitha", + "author_inst": "Department of Health, Kilifi County, Kenya" + }, + { + "author_name": "Elwyn Chondo", + "author_inst": "Department of Health, Kilifi County, Kenya" + }, + { + "author_name": "Eddy Nzomo", + "author_inst": "Kilifi County Hospital, Kilifi, Kenya" + }, + { + "author_name": "Rashid Aman", + "author_inst": "Ministry of Health, Government of Kenya, Nairobi, Kenya" + }, + { + "author_name": "Mercy Mwangangi", + "author_inst": "Ministry of Health, Government of Kenya, Nairobi, Kenya" + }, + { + "author_name": "Patrick Amoth", + "author_inst": "Ministry of Health, Government of Kenya, Nairobi, Kenya" + }, + { + "author_name": "Kadondi Kasera", + "author_inst": "Ministry of Health, Government of Kenya, Nairobi, Kenya" + }, + { + "author_name": "Wangari Ng'ang'a", + "author_inst": "Presidential Policy and Strategy Unit, The Presidency, Government of Kenya, Nairobi, Kenya" + }, + { + "author_name": "Edwine Barasa", + "author_inst": "KEMRI-Wellcome Research Trust Programme, Kilifi, Kenya" + }, + { + "author_name": "Benjamin Tsofa", + "author_inst": "KEMRI-Wellcome Research Trust Programme, Kilifi, Kenya" + }, + { + "author_name": "Joseph Mwangangi", + "author_inst": "KEMRI-Wellcome Research Trust Programme, Kilifi, Kenya" + }, + { + "author_name": "Philip Bejon", + "author_inst": "KEMRI-Wellcome Research Trust Programme, Kilifi, Kenya" + }, + { + "author_name": "Ambrose Agweyu", + "author_inst": "KEMRI-Wellcome Research Trust Programme, Kilifi, Kenya" + }, + { + "author_name": "Tom Williams", + "author_inst": "KEMRI-Wellcome Research Trust Programme, Kilifi, Kenya" + }, + { + "author_name": "Anthony Scott", + "author_inst": "KEMRI-Wellcome Research Trust Programme, Kilifi, Kenya" } ], "version": "1", @@ -167745,33 +166999,169 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.10.10.22280896", - "rel_title": "Assessing the epidemic impact of protests during the COVID-19 pandemic", + "rel_doi": "10.1101/2022.10.10.22280824", + "rel_title": "SARS-CoV-2 seroprevalence and implications for population immunity: Evidence from two Health and Demographic Surveillance System sites in Kenya, February-June 2022", "rel_date": "2022-10-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.10.22280896", - "rel_abs": "Protests during the COVID-19 pandemic present a complex trade-off between democratic rights of freedom of assembly and an epidemic risk, and have created a need for careful assessment of protest-driven infections. Here, we build a coupled disease transmission model and assess the impact of protests on the COVID-19 spread in the continental US using a dataset of 4,121 protests and 1.66 million protesters between April and June of 2020. We find that protests in 2020 had limited effects, creating tens of additional daily cases country-wide, due to their small size. However, a simple scaling relation of protest-driven infections derived from our simulations reveals that very large protests with over millions of participants can significantly boost outbreaks and impact the healthcare system. In the worst-case scenario, very large protests can add over 20,000 daily cases and over 7,000 ICU admissions over the continental US. We hope our model can aid the policy rationale to maintain freedom of assembly in the current and future pandemics, while providing estimates for preparations for a healthcare surge in the worst-case setting.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.10.22280824", + "rel_abs": "BackgroundUp-to-date SARS-CoV-2 antibody seroprevalence estimates are important for informing public health planning, including priorities for Coronavirus disease 2019 (COVID-19) vaccination programs. We sought to estimate infection- and vaccination-induced SARS-CoV-2 antibody seroprevalence within representative samples of the Kenyan population approximately two years into the COVID-19 pandemic and approximately one year after rollout of the national COVID-19 vaccination program.\n\nMethodsWe conducted cross-sectional serosurveys within random, age-stratified samples of Kilifi Health and Demographic Surveillance System (HDSS) and Nairobi Urban HDSS residents. Anti-spike (anti-S) immunoglobulin G (IgG) and anti-nucleoprotein (anti-N) IgG were measured using validated in-house ELISAs. Target-specific Bayesian population-weighted seroprevalence was calculated overall, by sex and by age, with adjustment for test performance as appropriate. Anti-S IgG concentrations were estimated with reference to the WHO International Standard (IS) for anti-SARS-CoV-2 immunoglobulin and their reverse cumulative distributions plotted.\n\nResultsBetween February and June 2022, 852 and 851 individuals within the Kilifi HDSS and the Nairobi Urban HDSS, respectively, were sampled. Only 11.0% (95% confidence interval [CI] 9.0-13.3) of all Kilifi HDSS participants and 33.4% (95%CI 30.2-36.6) of all Nairobi Urban HDSS participants had received any doses of COVID-19 vaccine. Population-weighted anti-S IgG seroprevalence was 69.1% (95% credible interval [CrI] 65.8-72.3) within the Kilifi HDSS and 88.5% (95%CrI 86.1-90.6) within the Nairobi Urban HDSS. Among COVID-unvaccinated residents of the Kilifi HDSS and Nairobi Urban HDSS, it was 66.7% (95%CrI 63.3-70.0) and 85.3% (95%CrI 82.1-88.2), respectively. Population-weighted, test-adjusted anti-N IgG seroprevalence within the Kilifi HDSS was 53.5% (95%CrI 46.5-61.1) and 65.5% (95%CrI 56.0-75.6) within the Nairobi Urban HDSS. The prevalence of anti-N antibodies was similar in vaccinated and unvaccinated subgroups in both HDSS populations. Anti-S IgG concentrations were significantly lower among Kilifi HDSS residents than among Nairobi Urban HDSS residents (p< 0.001).\n\nConclusionsApproximately, 7 in 10 Kilifi residents and 9 in 10 Nairobi residents were seropositive for anti-S IgG by May 2022 and June 2022, respectively. Given COVID-19 vaccination coverage, anti-S IgG seropositivity among COVID-unvaccinated individuals, and anti-N IgG seroprevalence, population-level anti-S IgG seroprevalence was predominantly derived from infection. Interventions to improve COVID-19 vaccination uptake should be targeted to individuals in rural Kenya who are at high risk of severe COVID-19.", + "rel_num_authors": 38, "rel_authors": [ { - "author_name": "Inho Hong", - "author_inst": "Max Planck Institute for Human Development" + "author_name": "E Wangeci Kagucia", + "author_inst": "KEMRI-Wellcome Trust Research Programme" }, { - "author_name": "Leonardo Nascimento Ferreira", - "author_inst": "University of Oxford" + "author_name": "Abdhalah K Ziraba", + "author_inst": "African Population and Health Research Center" }, { - "author_name": "Alex Rutherford", - "author_inst": "Max Planck Institute for Human Development" + "author_name": "James Nyagwange", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Manuel Cebrian", - "author_inst": "Universidad Carlos III de Madrid" + "author_name": "Bernadette Kutima", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Makobu Kimani", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Donald Akech", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Maurine Ng'oda", + "author_inst": "African Population and Health Research Center" + }, + { + "author_name": "Antipa Sigilai", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Daisy Mugo", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Henry Karanja", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "John Gitonga", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Angela Karani", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Monica Toroitich", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Boniface Karia", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Mark Otiende", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Anne Njeri", + "author_inst": "African Population and Health Research Center" + }, + { + "author_name": "R. A. Aman", + "author_inst": "Ministry of Health, Kenya" + }, + { + "author_name": "P. Amoth", + "author_inst": "Ministry of Health, Kenya" + }, + { + "author_name": "M. Mwangangi", + "author_inst": "Ministry of Health, Kenya" + }, + { + "author_name": "K. Kasera", + "author_inst": "Ministry of Health, Kenya" + }, + { + "author_name": "W. Ng'ang'a", + "author_inst": "Presidential Policy and Strategy Unit, The Presidency, Government of Kenya" + }, + { + "author_name": "S Voller", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya; London School of Hygiene and Tropical Medicine, UK" + }, + { + "author_name": "L I Ochola-Oyier", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Christian Bottomley", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "A Nyaguara", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "P K Munywoki", + "author_inst": "US Centers of Disease Control and Prevention, Center for Global Health, Division for Global Health Protection, Nairobi, Kenya" + }, + { + "author_name": "G Bigogo", + "author_inst": "KEMRI Centre for Global Health Research, Kisumu, Kenya" + }, + { + "author_name": "E Maitha", + "author_inst": "Department of Health, Kilifi County, Kenya" + }, + { + "author_name": "Sophie Uyoga", + "author_inst": "KEMRI Wellcome Trust Research Programme" + }, + { + "author_name": "K E Gallagher", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya; London School of Hygiene and Tropical Medicine, UK" + }, + { + "author_name": "Anthony O Etyang", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "Edwine Barasa", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "J Mwangangi", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "P Bejon", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, Oxford University, UK" + }, + { + "author_name": "Ifedayo M. O Adetifa", + "author_inst": "KEMRI-Wellcome Trust Research Programme; London School of Hygiene and Tropical Medicine, UK" + }, + { + "author_name": "George M Warimwe", + "author_inst": "KEMRI-Wellcome Trust Research Programme; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, Oxford University, UK" + }, + { + "author_name": "J AG Scott", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya; London School of Hygiene and Tropical Medicine, UK" + }, + { + "author_name": "A Agweyu", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -169611,49 +169001,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.10.06.22280775", - "rel_title": "The Incidence of Immune Mediated Inflammatory Diseases Following COVID-19: a Matched Cohort Study in UK Primary Care", + "rel_doi": "10.1101/2022.10.05.22280754", + "rel_title": "COVID-19: impact of original, Gamma, Delta, and Omicron variants of SARS-CoV-2 in vaccinated and unvaccinated pregnant and postpartum women", "rel_date": "2022-10-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.06.22280775", - "rel_abs": "ObjectiveTo assess whether there is an association between Severe Acute Respiratory Syndrome Coronavirus 2 (SARS CoV-2) infection and the incidence of immune mediated inflammatory diseases (IMIDs).\n\nDesignMatched cohort study.\n\nSettingPrimary care electronic health record data from the Clinical Practice Research Datalink Aurum database.\n\nParticipantsThe exposed cohort included 458,147 adults aged 18 years and older with a confirmed SARS CoV-2 infection by reverse transcriptase polymerase chain reaction (RT-PCR) or lateral flow antigen test, and no prior diagnosis of IMIDs. They were matched on age, sex, and general practice to 1,818,929 adults in the unexposed cohort with no diagnosis of confirmed or suspected SARS CoV-2 infection and no prior diagnosis of IMIDs.\n\nMain Outcome MeasuresThe primary outcome measure was a composite of the incidence of any of the following IMIDs: 1. autoimmune thyroiditis, 2. coeliac disease, 3. inflammatory bowel disease (IBD), 4. myasthenia gravis, 5. pernicious anaemia, 6. psoriasis, 7. rheumatoid arthritis (RA), 8. Sjogrens syndrome, 9. systemic lupus erythematosus (SLE), 10. type 1 diabetes mellitus (T1DM), and 11. vitiligo. The secondary outcomes were the incidence of each of these conditions separately. Cox proportional hazards models were used to estimate adjusted hazard ratios (aHR) and 95% confidence intervals (CI) for the primary and secondary outcomes comparing the exposed to the unexposed cohorts, and adjusting for age, sex, ethnic group, smoking status, body mass index, relevant infections, and medications.\n\nResults537 patients (0.11%) in the exposed cohort developed an IMID during the follow-up period over 0.29 person years, giving a crude incidence rate of 3.54 per 1000 person years. This was compared 1723 patients (0.09%) over 0.29 person years in the unexposed cohort, with an incidence rate of 2.82 per 1000 person years. Patients in the exposed cohort had a 22% relative increased risk of developing an IMID, compared to the unexposed cohort (aHR 1.22, 95% CI 1.10 to 1.34). The incidence of three IMIDs were statistically significantly associated with SARS CoV-2 infection. These were T1DM (aHR 1.56, 95% CI 1.09 to 2.23), IBD (1.52, 1.23 to 1.88), and psoriasis (1.23, 1.05 to 1.42).\n\nConclusionsSARS CoV-2 was associated with an increased incidence of IMIDs including T1DM, IBD and psoriasis. Further research is needed to replicate these findings in other populations and to measure autoantibody profiles in cohorts of individuals with COVID-19, including Long COVID and matched controls.\n\nSummary Box\n\nWhat is already known on this topicO_LIA subsection of the population who tested positive for SARS CoV-2 is suffering from post-Covid-19 condition or long COVID.\nC_LIO_LIPreliminary findings, such as case reports of post-COVID-19 IMIDs, increased autoantibodies in COVID-19 patients, and molecular mimicry of the SARS-CoV-2 virus have given rise to the theory that long COVID may be due in part to a deranged immune response.\nC_LI\n\nWhat this study addsO_LICOVID-19 exposure was associated with a 22% relative increase in the risk of developing certain IMIDs, including type 1 diabetes mellitus, inflammatory bowel disease, and psoriasis.\nC_LIO_LIThese findings provide further support to the hypothesis that a subgroup of Long Covid may be caused by immune mediated mechanisms.\nC_LI", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.05.22280754", + "rel_abs": "IntroductionThis study compares the clinical characteristics and disease progression of vaccinated and unvaccinated pregnant and postpartum women positive for the original, Gamma, Delta, and Omicron variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using Brazilian epidemiological data.\n\nMethodsData of pregnant or postpartum patients with coronavirus disease 2019 (COVID-19) SARS-CoV-2 confirmed using polymerase chain reaction from February 2020 to July 2022 were extracted from a Brazilian national database. The patients were divided based on vaccination status and viral variant (original, Gamma, Delta, and Omicron). The patients demographic data, clinical characteristics, comorbidities, signs, symptoms, and outcomes were retrospectively compared.\n\nResultsData from 10,003 pregnant and 2,361 postpartum women were extracted from the database. Among unvaccinated patients, postpartum women were more likely to be admitted to the intensive care unit (ICU). These patients were more likely to require invasive ventilation when infected with the original, Gamma, and Omicron variants and were more likely to die when infected with the original and Gamma variants. Patients who were vaccinated had reduced adverse outcomes including ICU admission, requirement for invasive ventilation, and death.\n\nConclusionPostpartum women were more likely to develop severe COVID-19 that required ICU admission or invasive ventilatory support or led to death, among all variants, especially when the patients were unvaccinated. Therefore, the risk of severe COVID-19 should not be underestimated after delivery. Vaccinated patients had a lower risk of severe outcomes. Vaccination should be a top priority in pregnant and postpartum patients.\n\nWHAT IS ALREADY KNOWN ON THIS TOPICThe obstetric population has a higher risk of adverse outcomes due to coronavirus disease 2019 (COVID-19). Few studies have compared the outcomes of pregnant and postpartum patients or vaccinated and unvaccinated patients; however, no studies have separately investigated the effects of each viral variant.\n\nWHAT THIS STUDY ADDSPostpartum women are more likely to have adverse outcomes, including the requirements for intensive care and invasive ventilation and death, compared with pregnant women. Vaccinated women had fewer adverse outcomes. The viral variants did not significantly affect the outcomes of these patients.\n\nHOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE, OR POLICYThe risks of COVID-19 infection should not be underestimated in postpartum women. Postpartum women infected with COVID-19, especially those who are not vaccinated, should be monitored carefully. Vaccination should be a top priority in pregnant and postpartum women.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Umer Syed", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Anuradhaa Subramanian", - "author_inst": "Institute of Applied Health Research, University of Birmingham" - }, - { - "author_name": "David Wraith", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham" - }, - { - "author_name": "Janet M Lord", - "author_inst": "Institute of Inflammation and Ageing, University of Birmingham" + "author_name": "Fabiano Serra", + "author_inst": "University of Sao Paulo" }, { - "author_name": "Kirsty C Mcgee", - "author_inst": "Institute of Inflammation and Ageing, University of Birmingham" + "author_name": "Elias Ribeiro Rosa Jr.", + "author_inst": "Federal University of Espirito Santo" }, { - "author_name": "Krishna Margadhamane Ghokale", - "author_inst": "Institute of Applied Health Research, University of Birmingham" + "author_name": "Patricia de Rossi", + "author_inst": "University of Santo Amaro" }, { - "author_name": "Krishnarajah Nirantharakumar", - "author_inst": "Institute of Applied Health Research, University of Birmingham" + "author_name": "Rossana Pulcineli Francisco", + "author_inst": "University of Sao Paulo" }, { - "author_name": "Shamil Haroon", - "author_inst": "University of Birmingham" + "author_name": "Agatha Sacramento Rodrigues", + "author_inst": "Federal University of Espirito Santo" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -171441,45 +170819,93 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.10.03.22280661", - "rel_title": "Plasma cytokine levels reveal deficiencies in IL-8 and gamma interferon in Long-COVID", + "rel_doi": "10.1101/2022.10.05.22280728", + "rel_title": "Non-patient related SARS-CoV-2 exposure to colleagues and household members impose the highest infection risk for hospital employees with and without patient contact in a German university hospital: follow-up of the prospective Co-HCW Seroprevalence study", "rel_date": "2022-10-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.03.22280661", - "rel_abs": "Up to half of individuals who contract SARS-CoV-2 develop symptoms of long-COVID approximately three months after initial infection. These symptoms are highly variable, and the mechanisms inducing them are yet to be understood. We compared plasma cytokine levels from individuals with long-COVID to healthy individuals and found that those with long-COVID had 100% reductions in circulating levels of interferon gamma (IFN{gamma}) and interleukin-8 (IL-8). Additionally, we found significant reductions in levels of IL-6, IL-2, IL-17, IL-13, and IL-4 in individuals with long-COVID. We propose immune exhaustion as the driver of long-COVID, with the complete absence of IFN{gamma} and IL-8 preventing the lungs and other organs from healing after acute infection, and reducing the ability to fight off subsequent infections, both contributing to the myriad of symptoms suffered by those with long-COVID.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.05.22280728", + "rel_abs": "BackgroundThe Co-HCW study is a prospective, longitudinal single center observational study on the SARS-CoV-2 seroprevalence and infection status in staff members of Jena University Hospital (JUH) in Jena, Germany.\n\nMaterial and MethodsThis follow-up study covers the observation period from 19th May 2020 to 22nd June 2021. At each out of three voluntary study visits, participants filled out a questionnaire on individual SARS-CoV-2 exposure. In addition, serum samples to assess specific SARS-CoV-2 antibodies were collected. Participants with antibodies against nucleocapsid and/or spike protein without previous vaccination and/or a reported positive SARS-CoV-2 PCR test were regarded as participants with detected SARS-CoV-2 infection. Multivariable logistic regression modeling was applied to identify potential risk factors for infected compared to non-infected participants.\n\nResultsOut of 660 participants that were included during the first study visit, 406 participants (61.5%) were eligible for final analysis as they did not change the COVID-19 risk area (high-risk n=76; intermediate-risk n=198; low-risk n=132) during the study. Forty-four participants (10.8%, 95% confidence interval (95%CI) 8.0%-14.3%) had evidence of a current or past SARS-CoV-2 infection detected by serology (n=40) and/or PCR (n=28). No association of any SARS-CoV-2 infection with the COVID-19 risk group according to working place could be detected. But exposure to a SARS-CoV-2 positive household member (adjusted OR (AOR) 4.46, 95%CI 2.06-9.65) or colleague (AOR 2.30, 95%CI 1.10-4.79) significantly increased the risk of a SARS-CoV-2 infection.\n\nConclusionOur results demonstrate that non-patient-related SARS-CoV-2 exposure imposed the highest infection risk in hospital staff members of JUH.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Elizabeth S C P Williams", - "author_inst": "University of Utah School of Medicine" + "author_name": "Christina Bahrs", + "author_inst": "Institute for Infectious Diseases and Infection Control, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany" }, { - "author_name": "Thomas B Martins", - "author_inst": "ARUP Institute for Clinical Research" + "author_name": "Sebastian Weis", + "author_inst": "Institute for Infectious Diseases and Infection Control, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany. Leibniz Institute for Natural Pr" }, { - "author_name": "Harry R Hill", - "author_inst": "University of Utah School of Medicine" + "author_name": "Miriam Kesselmeier", + "author_inst": "Institute of Medical Statistics, Computer and Data Sciences, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany" }, { - "author_name": "Mayte Coiras", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Juliane Ankert", + "author_inst": "Institute for Infectious Diseases and Infection Control, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany" }, { - "author_name": "Kevin S Shah", - "author_inst": "University of Utah School of Medicine" + "author_name": "Stefan Hagel", + "author_inst": "Institute for Infectious Diseases and Infection Control, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany" }, { - "author_name": "Vicente Planelles", - "author_inst": "University of Utah School of Medicine" + "author_name": "Stefanie Beier", + "author_inst": "Institute for Infectious Diseases and Infection Control, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany" }, { - "author_name": "Adam M Spivak", - "author_inst": "University of Utah School of Medicine" + "author_name": "Jens Maschmann", + "author_inst": "Medical Executive Board, Wuerzburg University Hospital, Germany" + }, + { + "author_name": "Andreas Stallmach", + "author_inst": "Department of Internal Medicine IV, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany" + }, + { + "author_name": "Andrea Steiner", + "author_inst": "Department of Occupational Health, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany" + }, + { + "author_name": "Michael Bauer", + "author_inst": "Department of Anestehsiology and Intensive Care Therapy, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany" + }, + { + "author_name": "Wilhelm Behringer", + "author_inst": "Department of Emergency Medicine, Medical University of Vienna, Vienna, Austria" + }, + { + "author_name": "Michael Baier", + "author_inst": "Institute of Medical Microbiology, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany" + }, + { + "author_name": "Cora Richert", + "author_inst": "Department of Clinical Chemistry and Laboratory Medicine, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany" + }, + { + "author_name": "Florian Zepf", + "author_inst": "Department of Child and Adolescent Psychiatry, Psychosomatic Medicine and Psychotherapy, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany" + }, + { + "author_name": "Martin Walter", + "author_inst": "Department of Psychiatry and Psychotherapy, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany" + }, + { + "author_name": "Andre Scherag", + "author_inst": "Institute of Medical Statistics, Computer and Data Sciences, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany" + }, + { + "author_name": "Michael Kiehntopf", + "author_inst": "Department of Clinical Chemistry and Laboratory Medicine, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany" + }, + { + "author_name": "Bettina Loeffler", + "author_inst": "Institute of Medical Microbiology, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany" + }, + { + "author_name": "Mathias Pletz", + "author_inst": "Institute for Infectious Diseases and Infection Control, Jena University Hospital/Friedrich-Schiller-University, Jena, Germany" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -173703,87 +173129,79 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.09.30.22280573", - "rel_title": "Effectiveness of mRNA-1273 against infection and COVID-19 hospitalization with SARS-CoV-2 Omicron subvariants: BA.1, BA.2, BA.2.12.1, BA.4, and BA.5", + "rel_doi": "10.1101/2022.09.30.22280166", + "rel_title": "COVID-19 vaccine antibody response is associated with side-effects, chronic health conditions, and vaccine type in a large Northern California cohort", "rel_date": "2022-10-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.30.22280573", - "rel_abs": "Studies have reported reduced natural SARS-CoV-2 infection- and vaccine-induced neutralization against Omicron BA.4/BA.5 compared with earlier Omicron subvariants. We conducted a test-negative case-control study evaluating mRNA-1273 vaccine effectiveness (VE) against infection and hospitalization with Omicron subvariants. The study included 30,809 SARS-CoV-2 positive and 92,427 SARS-CoV-2 negative individuals aged [≥]18 years tested during 1/1/2022-6/30/2022. While 3-dose VE against BA.1 infection was high and waned slowly, VE against BA.2, BA.2.12.1, BA.4, and BA.5 infection was initially moderate to high (61.0%-90.6% 14-30 days post third dose) and waned rapidly. The 4-dose VE against infection with BA.2, BA.2.12.1, and BA.4 ranged between 64.3%-75.7%, and was low (30.8%) against BA.5 14-30 days post fourth dose, disappearing beyond 90 days for all subvariants. The 3-dose VE against hospitalization for BA.1, BA.2, and BA.4/BA.5 was 97.5%, 82.0%, and 72.4%, respectively; 4-dose VE against hospitalization for BA.4/BA.5 was 88.5%. Evaluation of the updated bivalent booster is warranted.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.30.22280166", + "rel_abs": "As vaccines have become available for COVID-19, it is important to understand factors that may impact response. The objective of this study is to describe vaccine response in a well-characterized Northern California cohort, including differences in side-effects and antibody response by vaccine type, sex, and age, as well as describe responses in subjects with pre-existing health conditions that are known risk factors for more severe COVID-19 infection. From July 2020 to March 2021, [~]5,500 adults from the East Bay Area in Northern California were followed as part of a longitudinal cohort study. Comprehensive questionnaire data and biospecimens for COVID-19 antibody testing were collected at multiple time-points. All subjects were at least 18 years of age and members of the East-Bay COVID-19 cohort who answered questionnaires related to vaccination status and side-effects at two time-points. Three vaccines, Moderna (2 doses), Pfizer-BioNTech (2 doses), and Johnson & Johnson (single dose), were examined as exposures. Additionally, pre-existing health conditions were assessed. The main outcomes of interest were anti-SARS-CoV-2 Spike antibody response (measured by S/C ratio in the Ortho VITROS assay) and self-reporting of 11 potential vaccine side effects. When comparing both doses of the Moderna vaccine to respective doses of Pfizer-BioNTech, participants receiving the Moderna vaccine had higher odds of many reported side-effects. The same was true comparing the single-dose Johnson & Johnson vaccine to dose 2 of the Pfizer-BioNTech vaccine. The antibody S/C ratio also increased with each additional side-effect after the second dose. S/C ratios after vaccination were lower in participants aged 65 and older, and higher in females. At all vaccination timepoints, Moderna vaccine recipients had a higher S/C ratio. Individuals who were fully vaccinated with Pfizer-BioNTech had a 72.4% lower S/C ratio compared to those who were fully vaccinated with Moderna. Subjects with asthma, diabetes, and cardiovascular disease all demonstrated more than a 20% decrease in S/C ratio. In support of previous findings, we show that antibody response to the Moderna vaccine is higher than the Pfizer-BioNTech vaccine. We also observed that antibody response was associated with side-effects, and participants with a history of asthma, diabetes, and cardiovascular disease had lower antibody responses. This information is important to consider as further vaccines are recommended.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Hung Fu Tseng", - "author_inst": "Kaiser Permanente Southern California, Kaiser Permanente Bernard J. Tyson School of Medicine" - }, - { - "author_name": "Bradley K. Ackerson", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Katia J. Bruxvoort", - "author_inst": "University of Alabama at Birmingham, Kaiser Permanente Southern California" + "author_name": "Olivia Solomon", + "author_inst": "University of California, Berkeley, Berkeley, CA" }, { - "author_name": "Lina S. Sy", - "author_inst": "Kaiser Permanente Southern California" + "author_name": "Cameron Adams", + "author_inst": "University of California, Berkeley, Berkeley, CA" }, { - "author_name": "Julia E. Tubert", - "author_inst": "Kaiser Permanente Southern California" + "author_name": "Mary Horton", + "author_inst": "University of California, Berkeley, Berkeley, CA" }, { - "author_name": "Gina S. Lee", - "author_inst": "Kaiser Permanente Southern California" + "author_name": "Marcus P Wong", + "author_inst": "University of California, Berkeley, Berkeley, CA" }, { - "author_name": "Jennifer H. Ku", - "author_inst": "Kaiser Permanente Southern California" + "author_name": "Michelle Meas", + "author_inst": "University of California, Berkeley, Berkeley, CA" }, { - "author_name": "Ana Florea", - "author_inst": "Kaiser Permanente Southern California" + "author_name": "Xiaorong Shao", + "author_inst": "University of California, Berkeley, Berkeley, CA" }, { - "author_name": "Yi Luo", - "author_inst": "Kaiser Permanente Southern California" + "author_name": "Indro Fedrigo", + "author_inst": "University of California, Berkeley, Berkeley, CA" }, { - "author_name": "Sijia Qiu", - "author_inst": "Kaiser Permanente Southern California" + "author_name": "Samantha Hernandez", + "author_inst": "University of California, Berkeley, Berkeley, CA" }, { - "author_name": "Soon Kyu Choi", - "author_inst": "Kaiser Permanente Southern California" + "author_name": "Hong L. Quach", + "author_inst": "University of California, Berkeley, Berkeley, CA" }, { - "author_name": "Harpreet S. Takhar", - "author_inst": "Kaiser Permanente Southern California" + "author_name": "Diana L. Quach", + "author_inst": "University of California, Berkeley, Berkeley, CA" }, { - "author_name": "Michael Aragones", - "author_inst": "Kaiser Permanente Southern California" + "author_name": "Anna L Barcellos", + "author_inst": "University of California, Berkeley, Berkeley, CA" }, { - "author_name": "Yamuna D. Paila", - "author_inst": "Moderna, Inc." + "author_name": "Josefina Coloma", + "author_inst": "University of California, Berkeley, Berkeley, CA" }, { - "author_name": "Scott Chavers", - "author_inst": "Moderna, Inc." + "author_name": "Michael P Busch", + "author_inst": "Vitalant Research Institute, San Francisco, California, USA" }, { - "author_name": "Carla A. Talarico", - "author_inst": "Moderna, Inc." + "author_name": "Eva Harris", + "author_inst": "University of California, Berkeley, Berkeley, CA" }, { - "author_name": "Lei Qian", - "author_inst": "Kaiser Permanente Southern California" + "author_name": "Lisa F Barcellos", + "author_inst": "University of California, Berkeley, Berkeley, CA" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.09.30.22280586", @@ -175373,137 +174791,137 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.09.25.22280267", - "rel_title": "Predictive model for BNT162b2 vaccine response in cancer patients based on cytokines and growth factors", + "rel_doi": "10.1101/2022.09.26.22280395", + "rel_title": "A gene expression-based diagnostic classifier for identification of severe COVID-19 and multisystem inflammatory syndrome in children (MIS-C)", "rel_date": "2022-09-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.25.22280267", - "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSPatients with cancer, especially haematological cancer, are at increased risk for breakthrough COVID-19 infection. However, so far, a predictive biomarker that can assess compromised vaccine-induced anti-SARS-CoV-2 immunity in cancer patients has not been proposed.\n\nMethodsHere, we employed machine learning approaches to identify a biomarker signature based on blood cytokine and growth factors linked to vaccine response from 199 cancer patients receiving BNT162b2 vaccine.\n\nResultsWe show that C-reactive protein (CRP; general marker of inflammation), interleukin (IL)-15 (a pro-inflammatory cytokine), IL-18 (interferon-gamma inducing factor), and placental growth factor (an angiogenic cytokine) can correctly classify patients with a diminished vaccine response assessed at day 49 with >80% accuracy. Amongst these, CRP showed the highest predictive value for poor response to vaccine administration. Importantly, this unique signature of vaccine response was present at different studied timepoints both before and after vaccination and was not majorly affected by different anti-cancer treatments.\n\nConclusionWhile we propose a blood-based signature of cytokines and growth factors that can be employed in identifying cancer patients at continued risk of COVID-19, our data also importantly suggest that such a signature could reflect the inherent make-up of some cancer patients who are also refractive to immunotherapy.", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.26.22280395", + "rel_abs": "MIS-C is a severe hyperinflammatory condition with involvement of multiple organs that occurs in children who had COVID-19 infection. Accurate diagnostic tests are needed to guide management and appropriate treatment and to inform clinical trials of experimental drugs and vaccines, yet the diagnosis of MIS-C is highly challenging due to overlapping clinical features with other acute syndromes in hospitalized patients. Here we developed a gene expression-based classifier for MIS-C by RNA-Seq transcriptome profiling and machine learning based analyses of 195 whole blood RNA and 76 plasma cell-free RNA samples from 191 subjects, including 95 MIS-C patients, 66 COVID-19 infected patients with moderately severe to severe disease, and 30 uninfected controls. We divided the group into a training set (70%) and test set (30%). After selection of the top 300 differentially expressed genes in the training set, we simultaneously trained 13 classification models to distinguish patients with MIS-C and COVID-19 from controls using five-fold cross-validation and grid search hyperparameter tuning. The final optimal classifier models had 100% diagnostic accuracy for MIS-C (versus non-MIS-C) and 85% accuracy for severe COVID-19 (versus mild/asymptomatic COVID-19). Orthogonal validation of a random subset of 11 genes from the final models using quantitative RT-PCR confirmed the differential expression and ability to discriminate MIS-C and COVID-19 from controls. These results underscore the utility of a gene expression classifier for diagnosis of MIS-C and severe COVID-19 as specific and objective biomarkers for these conditions.", "rel_num_authors": 31, "rel_authors": [ { - "author_name": "Angelina Konnova", - "author_inst": "Molecular Pathology Group, Laboratory of Cell Biology & Histology, Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, Wilrijk" + "author_name": "Alicia Sotomayor-Gonzalez", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Fien HR De Winter", - "author_inst": "Molecular Pathology Group, Laboratory of Cell Biology & Histology, Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, Wilrijk" + "author_name": "Conor J Loy", + "author_inst": "Cornell University" }, { - "author_name": "Akshita Gupta", - "author_inst": "Molecular Pathology Group, Laboratory of Cell Biology & Histology, Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, Wilrijk" + "author_name": "Jenny Nguyen", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Lise Verbruggen", - "author_inst": "Multidisciplinary Oncological Center Antwerp (MOCA), Antwerp University Hospital, Drie Eikenstraat 655, 2650 Edegem, Belgium" + "author_name": "Venice Servellita", + "author_inst": "University of California, San Francisco" }, { - "author_name": "An Hotterbeekx", - "author_inst": "Molecular Pathology Group, Laboratory of Cell Biology & Histology, Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, Wilrijk" + "author_name": "Sanchita Bhattacharya", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Matilda Berkell", - "author_inst": "Laboratory of Medical Microbiology, Vaccine and Infectious disease Institute, University of Antwerp, Universiteitsplein 1, Wilrijk, B-2610, Belgium" + "author_name": "Joan Lenz", + "author_inst": "Cornell University" }, { - "author_name": "Laure-Anne Teuwen", - "author_inst": "Center for Oncological Research (CORE), Integrated Personalized and Precision Oncology Network (IPPON), University of Antwerp, Universiteitsplein 1, 2610 Wilrij" + "author_name": "Meagen E Williams", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Greetje Vanhoutte", - "author_inst": "Multidisciplinary Oncological Center Antwerp (MOCA), Antwerp University Hospital, Drie Eikenstraat 655, 2650 Edegem, Belgium" + "author_name": "William Suslovic", + "author_inst": "Children's National Hospital" }, { - "author_name": "Bart Peeters", - "author_inst": "Department of Laboratory Medicine, Antwerp University Hospital, Drie Eikenstraat 655, 2650 Edegem, Belgium" + "author_name": "Alexandre P Cheng", + "author_inst": "Cornell University" }, { - "author_name": "Silke Raats", - "author_inst": "Multidisciplinary Oncological Center Antwerp (MOCA), Antwerp University Hospital, Drie Eikenstraat 655, 2650 Edegem, Belgium" + "author_name": "Andrew Bliss", + "author_inst": "Cornell University" }, { - "author_name": "Isolde Van der Massen", - "author_inst": "Multidisciplinary Oncological Center Antwerp (MOCA), Antwerp University Hospital, Drie Eikenstraat 655, 2650 Edegem, Belgium" + "author_name": "Prachi Saldhi", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Sven De Keersmaecker", - "author_inst": "Multidisciplinary Oncological Center Antwerp (MOCA), Antwerp University Hospital, Drie Eikenstraat 655, 2650 Edegem, Belgium" + "author_name": "Jessica Streithorst", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Yana Debie", - "author_inst": "Multidisciplinary Oncological Center Antwerp (MOCA), Antwerp University Hospital, Drie Eikenstraat 655, 2650 Edegem, Belgium" + "author_name": "Hee Jae Huh", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Manon Huizing", - "author_inst": "Biobank Antwerp, Drie Eikenstraat 655, 2650 Edegem, Belgium" + "author_name": "Kafaya Foresythe", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Pieter Pannus", - "author_inst": "Scientific Directorate Epidemiology and Public Health, Sciensano, Rue Juliette Wytsmanstraat 14, 1050 Brussels, Belgium" + "author_name": "Miriam Oseguera", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Kristof Y Neven", - "author_inst": "Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium" + "author_name": "Katrina de la Cruz", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Kevin K Ari\u00ebn", - "author_inst": "Virology Unit, Institute of Tropical Medicine Antwerp, Nationalestraat 155, B-2000 Antwerp, Belgium" + "author_name": "Noah Brazer", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Geert A Martens", - "author_inst": "Department of Laboratory Medicine, AZ Delta General Hospital, Roeselare, Belgium" + "author_name": "Nathan Wood", + "author_inst": "UCSF Benioff Children's Hospital Oakland" }, { - "author_name": "Marc Van Den Bulcke", - "author_inst": "Scientific Directorate Epidemiology and Public Health, Sciensano, Rue Juliette Wytsmanstraat 14, 1050 Brussels, Belgium" + "author_name": "Charlotte Hsieh", + "author_inst": "UCSF Benioff Children's Hospital Oakland" }, { - "author_name": "Ella Roelant", - "author_inst": "Clinical Trial Center (CTC), CRC Antwerp, Antwerp University Hospital, University of Antwerp, Drie Eikenstraat 655, 2650 Edegem, Belgium" + "author_name": "Burak Bahar", + "author_inst": "Children's National Hospital" }, { - "author_name": "Isabelle Desombere", - "author_inst": "Service Immune response, Scientific Directorate Infectious Diseases in Humans, Sciensano, Rue Juliette Wytsmanstraat 14, 1050 Brussels, Belgium" + "author_name": "Amelia Gliwa", + "author_inst": "University of California, San Francisco" }, { - "author_name": "S\u00e9bastien Anguille", - "author_inst": "Center for Oncological Research (CORE), Integrated Personalized and Precision Oncology Network (IPPON), University of Antwerp, Universiteitsplein 1, 2610 Wilrij" + "author_name": "Kushmita Bhakta", + "author_inst": "Emory University" }, { - "author_name": "Zwi Berneman", - "author_inst": "Center for Oncological Research (CORE), Integrated Personalized and Precision Oncology Network (IPPON), University of Antwerp, Universiteitsplein 1, 2610 Wilrij" + "author_name": "Maria A. Perez", + "author_inst": "Emory University" }, { - "author_name": "Maria E Goossens", - "author_inst": "Scientific Directorate Infectious Diseases in Humans, Sciensano, Rue Juliette Wytsmanstraat 14, 1050 Brussels, Belgium" + "author_name": "Evan J Anderson", + "author_inst": "Emory University" }, { - "author_name": "Herman Goossens", - "author_inst": "Laboratory of Medical Microbiology, Vaccine and Infectious disease Institute, University of Antwerp, Universiteitsplein 1, Wilrijk, B-2610, Belgium" + "author_name": "Ann Chahroudi", + "author_inst": "Emory University" }, { - "author_name": "Surbhi Malhotra-Kumar", - "author_inst": "Laboratory of Medical Microbiology, Vaccine and Infectious disease Institute, University of Antwerp, Universiteitsplein 1, Wilrijk, B-2610, Belgium" + "author_name": "Meghan Delaney", + "author_inst": "Emory University" }, { - "author_name": "Evelina Taconelli", - "author_inst": "Division of Infectious Diseases, Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37134, Verona, Italy" + "author_name": "Atul J Butte", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Timon Vandamme", - "author_inst": "Multidisciplinary Oncological Center Antwerp (MOCA), Antwerp University Hospital, Drie Eikenstraat 655, 2650 Edegem, Belgium" + "author_name": "Roberta DeBiasi", + "author_inst": "Children's National Hospital" }, { - "author_name": "Marc Peeters", - "author_inst": "Multidisciplinary Oncological Center Antwerp (MOCA), Antwerp University Hospital, Drie Eikenstraat 655, 2650 Edegem, Belgium" + "author_name": "Christina A. Rostad", + "author_inst": "Emory University" }, { - "author_name": "Peter van Dam", - "author_inst": "Multidisciplinary Oncological Center Antwerp (MOCA), Antwerp University Hospital, Drie Eikenstraat 655, 2650 Edegem, Belgium" + "author_name": "Iwijn De Vlaminck", + "author_inst": "Cornell University" }, { - "author_name": "Samir Kumar-Singh", - "author_inst": "Molecular Pathology Group, Laboratory of Cell Biology & Histology, Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, Wilrijk" + "author_name": "Charles Y Chiu", + "author_inst": "University of California, San Francisco" } ], "version": "1", @@ -177407,59 +176825,59 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2022.09.25.509426", - "rel_title": "Spatial transcriptomic profiling of coronary endothelial cells in SARS-CoV-2 myocarditis", + "rel_doi": "10.1101/2022.09.23.509252", + "rel_title": "Zymosan-induced leukocyte and cytokine changes in pigs: a new model for streamlined drug testing against severe COVID-19", "rel_date": "2022-09-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.25.509426", - "rel_abs": "ObjectivesOur objective was to examine coronary endothelial and myocardial programming in patients with severe COVID-19 utilizing digital spatial transcriptomics.\n\nBackgroundSevere acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has well-established links to thrombotic and cardiovascular events. Endothelial cell infection was initially proposed to initiate vascular events; however, this paradigm has sparked growing controversy. The significance of myocardial infection also remains unclear.\n\nMethodsAutopsy-derived cardiac tissue from control (n = 4) and COVID-19 (n = 8) patients underwent spatial transcriptomic profiling to assess differential expression patterns in myocardial and coronary vascular tissue. Our approach enabled transcriptional profiling in situ with preserved anatomy and unaltered local SARS-CoV-2 expression. In so doing, we examined the paracrine effect of SARS-CoV-2 infection in cardiac tissue.\n\nResultsWe observed heterogeneous myocardial infection that tended to colocalize with CD31 positive cells within coronary capillaries. Despite these differences, COVID-19 patients displayed a uniform and unique myocardial transcriptional profile independent of local viral burden. Segmentation of tissues directly infected with SARS-CoV-2 showed unique, pro-inflammatory expression profiles including upregulated mediators of viral antigen presentation and immune regulation. Infected cell types appeared to primarily be capillary endothelial cells as differentially expressed genes included endothelial cell markers. However, there was limited differential expression within the endothelium of larger coronary vessels.\n\nConclusionsOur results highlight altered myocardial programming during severe COVID-19 that may in part be associated with capillary endothelial cells. However, similar patterns were not observed in larger vessels, diminishing endotheliitis and endothelial activation as key drivers of cardiovascular events during COVID-19.\n\nCondensed AbstractSARS-CoV-2 is linked to thrombotic and cardiovascular events; however, the mechanism remains uncertain. Our objective was to examine coronary endothelial and myocardial programming in patients with severe COVID-19 utilizing digital spatial transcriptomics. Autopsy-derived coronary arterial and cardiac tissues from control and COVID-19 patients underwent spatial transcriptomic profiling. Our approach enabled transcriptional profiling in situ with preserved anatomy and unaltered local SARS-CoV-2 expression. We observed unique, pro-inflammatory expression profiles among all COVID-19 patients. While heterogeneous viral expression was noted within the tissue, SARS-CoV-2 tended to colocalize with CD31 positive cells within coronary capillaries and was associated with unique expression profiles. Similar patterns were not observed in larger coronary vessels. Our results highlight altered myocardial programming during severe COVID-19 that may in part be associated with capillary endothelial cells. Such results diminish coronary arterial endotheliitis and endothelial activation as key drivers of cardiovascular events during COVID-19 infection.\n\nLIST OF HIGHLIGHTSO_LISARS-CoV-2 has variable expression patterns within the myocardium of COVID-19 patients\nC_LIO_LISARS-CoV-2 infection induces a unique myocardial transcriptional programming independent of local viral burden\nC_LIO_LISARS-CoV-2 myocarditis is predominantly associated with capillaritis, and tissues directly infected with SARS-CoV-2 have unique, pro-inflammatory expression profiles\nC_LIO_LIDiffuse endothelial activation of larger coronary vessels was absent, diminishing large artery endotheliitis as a significant contributor to cardiovascular events during COVID-19 infection.\nC_LI", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.23.509252", + "rel_abs": "Injection of 0.1 mg/kg zymosan in pigs i.v. elicited transient hemodynamic disturbance within minutes, without major blood cell changes. In contrast, infusion of 1 mg/kg zymosan triggered maximal pulmonary hypertension with tachycardia, lasting for 30 min. This change was followed by a transient granulopenia with a trough at 1 h, and then, up to about 6 h, a major granulocytosis, resulting in a 3-4-fold increase of neutrophil-to-lymphocyte ratio (NLR). In parallel with the changes in WBC differential, qRT-PCR and ELISA analyses showed increased transcription and/or release of inflammatory cytokines and chemokines into blood, including IL-6, TNF-, CCL-2, CXCL-10, and IL-1RA. The expression of IL-6 peaked at already 1.5-2.5 h, and we observed significant correlation between lymphopenia and IL-6 gene expression. While these changes are consistent with zymosans known stimulatory effect on both the humoral and cellular arms of the innate immune system, what gives novel clinical relevance to the co-manifestation of above hemodynamic, hematological, and immune changes is that they represent independent bad prognostic indicators in terminal COVID-19 and other diseases involving cytokine storm. Thus, within a 6 h experiment, the model enables consecutive reproduction of a symptom triad that is characteristic of late-stage COVID-19. Given the limitations of modeling cytokine storm in animals and effectively treating severe COVID-19, the presented relatively simple large animal model may advance the R&D of drugs against these conditions. One of these disease markers (NLR), obtained from a routine laboratory endpoint (WBC differential), may also enable streamlining the model for high throughput drug screening against innate immune overstimulation.", "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Camilla Margaroli", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Gabor Kokeny", + "author_inst": "Semmelweis University" }, { - "author_name": "Paul Benson", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Tamas Bakos", + "author_inst": "Semmelweis University" }, { - "author_name": "Maria G Gastanadui", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Balint A. Barta", + "author_inst": "Semmelweis University" }, { - "author_name": "Chunyan Song", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Georgina V. Nagy", + "author_inst": "Semmelweis University" }, { - "author_name": "Liliana Viera", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Tamas Meszaros", + "author_inst": "Seroscience.com" }, { - "author_name": "Dongqi Xing", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Gergely T. Kozma", + "author_inst": "Seroscience LLC" }, { - "author_name": "J Michael Wells", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Andras Szabo", + "author_inst": "Semmelweis University" }, { - "author_name": "Rakesh Patel", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Janos Szebeni", + "author_inst": "Semmelweis University" }, { - "author_name": "Amit Gaggar", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Bela Merkely", + "author_inst": "Semmelweis University" }, { - "author_name": "Gregory A Payne", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Tamas Radovits", + "author_inst": "Semmelweis University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "pathology" + "category": "immunology" }, { "rel_doi": "10.1101/2022.09.26.509459", @@ -180137,51 +179555,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.09.22.22280216", - "rel_title": "Commercial immunoglobulin products now contain neutralising antibodies against SARS-CoV-2 spike antibody which are detectable in patient serum", + "rel_doi": "10.1101/2022.09.22.22280217", + "rel_title": "Intensity of sample processing methods impacts wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes", "rel_date": "2022-09-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.22.22280216", - "rel_abs": "Antibody-deficient patients respond poorly to COVID-19 vaccination and are at risk of severe or prolonged infection. Prophylaxis with anti-SARS-CoV-2 monoclonal antibodies has been considered. We here demonstrate that many immunoglobulin preparations now contain neutralising anti-SARS-CoV-2 antibodies which are transmitted to patients in good concentrations, albeit with significant differences between products.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.22.22280217", + "rel_abs": "Wastewater SARS-CoV-2 surveillance has been deployed since the beginning of the COVID-19 pandemic to monitor dynamics in virus burden in local communities. Genomic surveillance of SARS-CoV-2 in wastewater, particularly the efforts for whole genome sequencing for variant tracking or identification, are comparatively challenging due to low target concentration, complex microbial and chemical background, and lack of robust nucleic acid recovery experimental procedures. The intrinsic sample limitations are inherent to wastewater. In this study, we evaluated impacts from sample types, certain sample intrinsic features, and processing and sequencing methods on sequencing outcomes with a specific focus on the breadth of genome coverage. We collected 184 composite and grab wastewater samples from the Chicago area between March to October 2021 for SARS-CoV-2 quantification and genomic surveillance. Samples were processed using a mixture of processing methods reflecting different homogenization intensities (HA+Zymo beads, HA+glass beads, and Nanotrap), and were sequenced using two sequencing library preparation kits (the Illumina COVIDseq kit and the QIAseq DIRECT kit). A synthetic SARS-CoV-2 RNA experiment was performed to validate the potential impacts of processing methods on sequencing outcomes. Our findings suggested that 1) wastewater SARS-CoV-2 whole genome sequencing outcomes were associated with sample types and processing methods 2) in less intensive method processed samples (HA+glass beads), higher genome breadth of coverage in sequencing (over 80%) was associated with N1 concentration > 105 cp/L, while in intensive method (HA+Zymo beads), qPCR results were inconsistent with sequencing outcomes, and 3) sample processing methods and sequencing kits, rather than the extraction methods or intrinsic features of wastewater samples, played important roles in wastewater SARS-CoV-2 amplicon sequencing. Overall, extra attention should be paid to wastewater sample processing (e.g., concentration and homogenization) for sufficient, good quality RNA yield for downstream sequencing.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Vinit Upasani", - "author_inst": "University College London" - }, - { - "author_name": "Fernando Moreira", - "author_inst": "Royal Free London NHS Foundation Trust" - }, - { - "author_name": "Sarita Workman", - "author_inst": "Royal Free London NHS Foundation Trust" + "author_name": "Shuchen Feng", + "author_inst": "Northwestern University" }, { - "author_name": "Andrew Symes", - "author_inst": "Royal Free London NHS Foundation Trust" + "author_name": "Sarah M. Owens", + "author_inst": "Argonne National Laboratory" }, { - "author_name": "Siobhan O Burns", - "author_inst": "University College London" + "author_name": "Abhilasha Shrestha", + "author_inst": "University of Illinois Chicago" }, { - "author_name": "Susan Tadros", - "author_inst": "Royal Free London NHS Foundation Trust" + "author_name": "Rachel Poretsky", + "author_inst": "University of Illinois Chicago" }, { - "author_name": "Laura E McCoy", - "author_inst": "University College London" + "author_name": "Erica M. Hartmann", + "author_inst": "Northwestern University" }, { - "author_name": "David M Lowe", - "author_inst": "University College London" + "author_name": "George Wells", + "author_inst": "Northwestern University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2022.09.22.22280222", @@ -182107,27 +181517,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.09.19.508610", - "rel_title": "PrimedSherlock: A tool for rapid design of highly specific CRISPR-Cas12 crRNAs", + "rel_doi": "10.1101/2022.09.19.22280127", + "rel_title": "Responding to disruption: Exploring the transition to telehealth in mental-health occupational therapy during the COVID-19 pandemic", "rel_date": "2022-09-20", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.19.508610", - "rel_abs": "BackgroundCRISPR-Cas based diagnostic assays provide a portable solution which bridges the benefits of qRT-PCR and serological assays in terms of portability, specificity and ease of use. CRISPR-Cas assays are rapidly fieldable, specific and have been rigorously validated against a number of targets, including HIV and vector-borne pathogens. Recently, CRISPR-Cas12 and CRISPR-Cas13 diagnostic assays have been granted FDA approval for the detection of SARS-CoV-2. A critical step in utilizing this technology requires the design of highly-specific and efficient CRISPR RNAs (crRNAs) and isothermal primers. This process involves intensive manual curation and stringent parameters for design in order to minimize off-target detection while also preserving detection across divergent strains. As such, a single, streamlined bioinformatics platform for rapidly designing crRNAs for use with the CRISPR-Cas12 platform is needed. Here we offer PrimedSherlock, an automated, computer guided process for selecting highly-specific crRNAs and primers for targets of interest.\n\nResultsUtilizing PrimedSherlock and publicly available databases, crRNAs were designed against a selection of Flavivirus genomes, including West Nile, Zika and all four serotypes of Dengue. Using outputs from PrimedSherlock in concert with both wildtype A.s Cas12a and Alt-R Cas12a Ultra nucleases, we demonstrated sensitive detection of nucleic acids of each respective arbovirus in in-vitro fluorescence assays. Moreover, primer and crRNA combinations facilitated the detection of their intended targets with minimal off-target background noise.\n\nConclusionsPrimedSherlock is a novel crRNA design tool, specific for CRISPR-Cas12 diagnostic platforms. It allows for the rapid identification of highly conserved crRNA targets from user-provided primer pairs or PrimedRPA output files. Initial testing of crRNAs against arboviruses of medical importance demonstrated a robust ability to distinguish multiple strains by exploiting polymorphisms within otherwise highly conserved genomic regions. As a freely-accessible software package, PrimedSherlock could significantly increase the efficiency of CRISPR-Cas12 diagnostics. Conceptually, the portability of detection kits could also be enhanced when coupled with isothermal amplification technologies.", - "rel_num_authors": 2, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.19.22280127", + "rel_abs": "BackgroundCOVID-19 presented significant challenges for occupational therapy (OT) services in Ireland. Public health guidelines necessitated a transition of services from face-to-face delivery to the use of telehealth modalities. Telehealth has yet to be extensively researched within mental health OT, with a particular need for an increased understanding of therapeutic processes when conducted remotely.\n\nAimTo explore the experiences of occupational therapists transitioning to telehealth service provision.\n\nMaterial and MethodsThis study employed a qualitative, descriptive design to examine the experiences of therapists transitioning from face-to-face to telehealth services within a mental health service. Data was collected using comprehensive, semi-structured interviews with four participants and analysed thematically.\n\nResultsThis study yielded three major themes: 1) responding to disruption, 2) reconsidering practice with technology and 3) therapeutic use of the virtual self.\n\nConclusionsAdaptation to telehealth provision requires planned, gradual transition but offers unique opportunities for therapeutic engagement. How space is considered in therapy as well as therapists communication styles are components of practice which are altered when conducted remotely.\n\nSignificanceThe disruption caused by COVID-19 presented opportunities for considering the delivery of OT services. As services emerge from social restrictions it is likely that their recent experiences will be utilised in reconfiguring the future delivery of mental-health OT services.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Ronald Jason Pitts", - "author_inst": "Baylor University" + "author_name": "Aislinn Duffy", + "author_inst": "University College Cork College of Medicine and Health" }, { - "author_name": "James G Mann", - "author_inst": "Baylor University" + "author_name": "Bryan Boyle", + "author_inst": "University College Cork College of Medicine and Health" + }, + { + "author_name": "Eoin Gorman", + "author_inst": "University College Cork College of Medicine and Health" + }, + { + "author_name": "Sarah Hayes", + "author_inst": "University College Cork College of Medicine and Health" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "molecular biology" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "health informatics" }, { "rel_doi": "10.1101/2022.09.20.22280135", @@ -183857,43 +183275,71 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.09.12.22279872", - "rel_title": "The impact of access to financial services on mitigating COVID-19 mortality globally", + "rel_doi": "10.1101/2022.09.14.508057", + "rel_title": "SARS-CoV-2 infection of human neurons requires endosomal cell entry and can be blocked by inhibitors of host phosphoinositol-5 kinase", "rel_date": "2022-09-16", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.12.22279872", - "rel_abs": "The COVID-19 pandemic has disproportionately affected different social and demographic groups, deepening the negative health implications of social and economic inequalities and highlighting the importance of social determinants of health. Despite a deep literature on pandemic-related disparities, specifically regarding social determinants and health outcomes, the influence of the accessibility of financial services on health outcomes during COVID-19 remains largely unexplored. Modeling (pre-omicron) COVID-19 mortality across 142 nations, we assess the impact of national-level usage and access to formal financial services. Two financial access indexes constructed through principal component analysis capture (1) usage of and access to formal financial tools and (2) reliance on alternative and informal financial tools. On average, nations with higher pre-pandemic use of and access to formal financial services had substantially lower population mortality risk from COVID-19, controlling for key population health, demographic, and socioeconomic covariates. The scale of effect is similar in magnitude--but opposite in direction--to major risk factors identified in previous literature, such as lung cancer, hypertension, and income inequality. Findings suggest that financial services deserve greater attention both in the public health literature related to COVID-19 and more broadly in policy discussions about fostering better public health overall.", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.14.508057", + "rel_abs": "COVID-19 is a disease caused by coronavirus SARS-CoV-2. In addition to respiratory illness, COVID-19 patients exhibit neurological symptoms that can last from weeks to months (long COVID). It is unclear whether these neurological manifestations are due to infection of brain cells. We found that a small fraction of cortical neurons, but not astrocytes, were naturally susceptible to SARS-CoV-2. Based on the inhibitory effect of blocking antibodies, the infection seemed to depend on the receptor angiotensin-converting enzyme 2 (ACE2), which was expressed at very low levels. Although only a limited number of neurons was infectable, the infection was productive, as demonstrated by the presence of double-stranded RNA in the cytoplasm (the hallmark of viral replication), abundant synthesis of viral late genes localized throughout the neuronal cell, and an increase in viral RNA in the culture medium within the first 48 h of infection (viral release). The productive entry of SARS-CoV-2 requires the fusion of the viral and cellular membranes, which results in the delivery of viral genome into the cytoplasm of the target cell. The fusion is triggered by proteolytic cleavage of the viral surface protein spike, which can occur at the plasma membrane or from endo/lysosomes. Using specific combinations of small-molecule inhibitors, we found that SARS-CoV-2 infection of human neurons was insensitive to nafamostat and camostat, which inhibit cellular serine proteases found on the cell surface, including TMPRSS2. In contrast, the infection was blocked by apilimod, an inhibitor of phosphatidyl-inositol 5 kinase (PIK5K) that regulates endosomal maturation.\n\nImportanceCOVID-19 is a disease caused by coronavirus SARS-CoV-2. Millions of patients display neurological symptoms, including headache, impairment of memory, seizures and encephalopathy, as well as anatomical abnormalities such as changes in brain morphology. Whether these symptoms are linked to brain infection is not clear. The mechanism of the virus entry into neurons has also not been characterized. Here we investigated SARS-CoV-2 infection using a human iPSC-derived neural cell model and found that a small fraction of cortical neurons was naturally susceptible to infection. The infection depended on the ACE2 receptor and was productive. We also found that the virus used the late endosomal/lysosomal pathway for cell entry and that the infection could be blocked by apilimod, an inhibitor of the cellular phosphatidyl-inositol 5 kinase.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Todd A. Watkins", - "author_inst": "Lehigh University" + "author_name": "Pinja Pauliina Kettunen", + "author_inst": "University of Helsinki" }, { - "author_name": "Khue Nguyen", - "author_inst": "Lehigh University" + "author_name": "Angelina Lesnikova", + "author_inst": "University of Helsinki" }, { - "author_name": "Hamza Ali", - "author_inst": "Lehigh University" + "author_name": "Noora R\u00e4s\u00e4nen", + "author_inst": "University of Helsinki" }, { - "author_name": "Rishikesh Gummakonda", - "author_inst": "Lehigh University" + "author_name": "Ravi Ojha", + "author_inst": "University of Helsinki" }, { - "author_name": "Jacques Pelman", - "author_inst": "Lehigh University" + "author_name": "Leena Palmunen", + "author_inst": "University of Helsinki" }, { - "author_name": "Brianna Taracena", - "author_inst": "Lehigh University" + "author_name": "Markku Laakso", + "author_inst": "University of Eastern Finland" + }, + { + "author_name": "\u0160\u00e1rka Lehtonen", + "author_inst": "University of Eastern Finland, University of Helsinki" + }, + { + "author_name": "Johanna Kuusisto", + "author_inst": "University of Eastern Finland" + }, + { + "author_name": "Olli Pietil\u00e4inen", + "author_inst": "University of Helsinki" + }, + { + "author_name": "Olli Vapalahti", + "author_inst": "University of Helsinki" + }, + { + "author_name": "Jari Koistinaho", + "author_inst": "University of Helsinki" + }, + { + "author_name": "Taisia Rolova", + "author_inst": "University of Helsinki" + }, + { + "author_name": "Giuseppe Balistreri", + "author_inst": "University of Helsinki" } ], "version": "1", "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "type": "new results", + "category": "neuroscience" }, { "rel_doi": "10.1101/2022.09.15.507787", @@ -185923,63 +185369,43 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2022.09.13.507876", - "rel_title": "Validation and Establishment of a SARS-CoV-2 Lentivirus Surrogate Neutralization Assay as a pre-screening tool for the Plaque Reduction Neutralization Test", + "rel_doi": "10.1101/2022.09.14.507947", + "rel_title": "Structure and Epitope of a Neutralizing Monoclonal Antibody that Targets the Stem Helix of \u03b2 Coronaviruses", "rel_date": "2022-09-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.13.507876", - "rel_abs": "Neutralization assays are important in understanding and quantifying neutralizing antibody responses towards SARS-CoV-2. The SARS-CoV-2 Lentivirus Surrogate Neutralization Assay (SCLSNA) can be used in biosafety level 2 (BSL-2) laboratories and has been shown to be a reliable, alternative approach to the plaque reduction neutralization test (PRNT). In this study, we optimized and validated the SCLSNA to assess its ability as a comparator and pre-screening method to support the PRNT. Comparability between the PRNT and SCLSNA was determined through clinical sensitivity and specificity evaluations. Clinical sensitivity and specificity produced acceptable results with 100% (95% CI: 94-100) specificity and 100% (95% CI: 94-100) sensitivity against ancestral Wuhan spike pseudotyped lentivirus. The sensitivity and specificity against B.1.1.7 spike pseudotyped lentivirus resulted in 88.3% (95% CI: 77.8 to 94.2) and 100% (95% CI: 94-100), respectively. Assay precision measuring intra-assay variability produced acceptable results for High (1:[≥] 640 PRNT50), Mid (1:160 PRNT50) and Low (1:40 PRNT50) antibody titer concentration ranges based on the PRNT50, with %CV of 14.21, 12.47, and 13.28 respectively. Intermediate precision indicated acceptable ranges for the High and Mid concentrations, with %CV of 15.52 and 16.09, respectively. However, the Low concentration did not meet the acceptance criteria with a %CV of 26.42. Acceptable ranges were found in the robustness evaluation for both intra-assay and inter-assay variability. In summary, the validation parameters tested met the acceptance criteria, making the SCLSNA method fit for its intended purpose, which can be used to support the PRNT.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.14.507947", + "rel_abs": "Monoclonal antibodies (MAbs) that retain neutralizing activity against distinct coronavirus (CoV) lineages and variants of concern (VoC) must be developed to protect against future pandemics. These broadly neutralizing MAbs (BNMAbs) may be used as therapeutics and/or to assist in the rational design of vaccines that induce BNMAbs. 1249A8 is a BNMAb that targets the stem helix (SH) region of CoV spike (S) protein and neutralizes Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) original strain, delta, and omicron VoC, Severe Acute Respiratory Syndrome CoV (SARS-CoV) and Middle East Respiratory Syndrome CoV (MERS-CoV). To understand its mechanism of action, the crystal structure of 1249A8 bound to a MERS-CoV SH peptide was determined at 2.1[A] resolution. BNMAb 1249A8 mimics the SARS-CoV-2 S loop residues 743-749, which interact with the C-terminal end of the SH helix in the S postfusion conformation. The crystal structure shows that BNMAb 1249A8 disrupts SH secondary structure and packing rearrangements required for CoV S to adopt its prefusion conformation that mediates membrane fusion and ultimately infection. The mechanisms regulating BNMAb 1249A8 CoV S specificity are also defined. This study provides novel insights into the neutralization mechanisms of SH-targeting CoV BNMAbs that may inform vaccine development and the design of optimal BNMAb therapeutics.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "John Merluza", - "author_inst": "Public Health Agency of Canada" - }, - { - "author_name": "Johnny Ung", - "author_inst": "Public Health Agency of Canada" - }, - { - "author_name": "Kai Makowski", - "author_inst": "Public Health Agency of Canada" - }, - { - "author_name": "Alyssia Robinson", - "author_inst": "Public Health Agency of Canada" - }, - { - "author_name": "Kathy J Manguiat", - "author_inst": "Public Health Agency of Canada" - }, - { - "author_name": "Nicole Mueller", - "author_inst": "Public Health Agency of Canada" + "author_name": "Ashlesha Deshpande", + "author_inst": "University of Alabama at Birmingham" }, { - "author_name": "Jonathan Audet", - "author_inst": "National Microbiology Laboratory" + "author_name": "Norbert Schormann", + "author_inst": "University of Alabama at Birmingham" }, { - "author_name": "Julie Chih-yu Chen", - "author_inst": "Public Health Agency of Canada" + "author_name": "Michael Scott Piepenbrink", + "author_inst": "University of Alabama at Birmingham" }, { - "author_name": "James Eric Strong", - "author_inst": "Public Health Agency of Canada" + "author_name": "Luis Martinez-Sobrido", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Heidi Wood", - "author_inst": "Public Health Agency of Canada" + "author_name": "James Kobie", + "author_inst": "University of Alabama at Birmingham" }, { - "author_name": "Alexander Bello", - "author_inst": "National Microbiology Laboratory" + "author_name": "Mark R Walter", + "author_inst": "University of Alabama at Birmingham" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", - "category": "scientific communication and education" + "category": "immunology" }, { "rel_doi": "10.1101/2022.09.14.507948", @@ -187605,129 +187031,53 @@ "category": "health economics" }, { - "rel_doi": "10.1101/2022.09.09.507363", - "rel_title": "Treatment with anti-inflammatory viral serpin modulates immuno-thrombotic responses and improves outcomes in SARS-CoV-2 infected mice", + "rel_doi": "10.1101/2022.09.09.507342", + "rel_title": "Targeting intracellular Neu1 for Coronavirus Infection Treatment", "rel_date": "2022-09-11", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.09.507363", - "rel_abs": "1.Severe acute respiratory distress syndrome (ARDS) during SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) infection, manifests as uncontrolled lung inflammation and systemic thrombosis with high mortality. Anti-viral drugs and monoclonal antibodies can reduce COVID-19 severity if administered in the early viremic phase, but treatments for later stage immuno-thrombotic syndrome and long COVID are limited. Serine protease inhibitors (SERPINS) regulate activated proteases during thrombotic, thrombolytic and immune responses. The myxoma poxvirus-derived Serp-1 protein is a secreted immunomodulatory serpin that targets activated coagulation and complement protease pathways as part of a self-defense strategy to combat viral clearance by the innate immune system. When purified and utilized as an anti-immune therapeutic, Serp-1 is effective as an anti-inflammatory drug in multiple animal models of inflammatory lung disease and vasculitis. Here, we describe systemic treatment with purified PEGylated Serp-1 (PEGSerp-1) as a therapy for immuno-thrombotic complications during ARDS. Treatment with PEGSerp-1 in two distinct mouse-adapted SARS-CoV-2 models in C57Bl/6 and BALB/c mice reduced lung and heart inflammation, with improved clinical outcomes. PEGSerp-1 significantly reduced M1 macrophage invasion in the lung and heart by modifying urokinase-type plasminogen activator receptor (uPAR) and complement membrane attack complex (MAC). Sequential changes in urokinase-type plasminogen activator receptor (uPAR) and serpin gene expression were observed in lung and heart with PEGSerp-1 treatment. PEGSerp-1 is a highly effective immune-modulator with therapeutic potential for treatment of severe viral ARDS with additional potential to reduce late SARS-CoV-2 complications related to immune-thrombotic events that persist during long COVID.\n\nSignificanceSevere acute respiratory distress syndrome (ARDS) in SARS-CoV-2 infection manifests as uncontrolled tissue inflammation and systemic thrombosis with high mortality. Anti-viral drugs and monoclonal antibodies reduce COVID-19 severity if administered early, but treatments for later stage immuno-thrombosis are limited. Serine protease inhibitors (SERPINS) regulate thrombotic, thrombolytic and complement pathways. We investigate here systemic treatment with purified poxvirus-derived PEGSerp-1 as a therapeutic for immuno-thrombotic complications in viral ARDS. PEGSerp-1 treatment in two mouse-adapted SARS-CoV-2 models (C57Bl/6 and BALB/c) significantly reduced lung and heart inflammation and improved clinical outcomes, with sequential changes in thrombolytic (uPAR) and complement expression. PEGSerp-1 is a highly effective immune-modulator with therapeutic potential for immune-thrombotic complications in severe viral ARDS and has potential benefit for long COVID.", - "rel_num_authors": 29, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.09.507342", + "rel_abs": "There are no effective therapies for COVID-19 or antivirals against SARS-CoV-2. Furthermore, current vaccines appear less efficacious for new SARS-CoV-2 variants. Thus, there is an urgent need to better understand the virulence mechanisms of SARS-CoV-2 and the host response to develop therapeutic agents. Here, we show host Neu1 regulates coronavirus replication by controlling sialylation on coronavirus nucleocapsid protein. Coronavirus nucleocapsid proteins in COVID-19 patients and in coronavirus HCoV-OC43-infected cells were heavily sialylated; this sialylation controlled the RNA binding activity and replication of coronavirus. Neu1 overexpression increased HCoV-OC43 replication, whereas Neu1 knockdown reduced HCoV-OC43 replication. Moreover, a newly developed Neu1 inhibitor, Neu5Ac2en-OAcOMe, selectively targeted intracellular sialidase, which dramatically reduced HCoV-OC43 and SARS-CoV-2 replication in vitro and rescued mice from HCoV-OC43 infection-induced death. Our findings suggest that Neu1 inhibitors could be used to limit SARS-CoV-2 replication in patients with COVID-19, making Neu1 a potential therapeutic target for COVID-19 and future coronavirus pandemics.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Liqiang Zhang", - "author_inst": "Biodesign Institute, Arizona State University" - }, - { - "author_name": "Yize Henry Li", - "author_inst": "Biodesign Institute, ASU" - }, - { - "author_name": "Karen Kibler", - "author_inst": "Biodesign Institute, ASU" - }, - { - "author_name": "Simona Kraberger", - "author_inst": "Biodesign Institute, ASU" - }, - { - "author_name": "Arvind Varsani", - "author_inst": "Biodesign Institute, ASU" - }, - { - "author_name": "Julie Turk", - "author_inst": "Biodesign Institute, ASU" + "author_name": "Darong Yang", + "author_inst": "UTHSC, Department of Pedatrics" }, { - "author_name": "Nora Elmadbouly", - "author_inst": "Biodesign Institute, ASU" - }, - { - "author_name": "Emily Aliskevich", - "author_inst": "Biodesign Institute, ASU" - }, - { - "author_name": "Laurel Spaccarelli", - "author_inst": "Biodesign Institute, ASU" - }, - { - "author_name": "Bereket Estifanos", - "author_inst": "Biodesign Institute, ASU" - }, - { - "author_name": "Junior Enow", - "author_inst": "Biodesign Institute, ASU" - }, - { - "author_name": "Isabela Rivabem Zanetti", - "author_inst": "Biodesign Institute, ASU" - }, - { - "author_name": "Nicholas Saldevar", - "author_inst": "Biodesign Institute, ASU" - }, - { - "author_name": "Efrem Lim", - "author_inst": "Arizona State University" - }, - { - "author_name": "Kyle Browder", - "author_inst": "Biodesign Institute, ASU" - }, - { - "author_name": "Anjali Wilson", - "author_inst": "Biodesign Institute, ASU" - }, - { - "author_name": "Fernando Arcos Juan", - "author_inst": "Biodesign Institute, ASU" - }, - { - "author_name": "Aubrey Pinteric", - "author_inst": "Biodesign Institute, ASU" - }, - { - "author_name": "Aman Garg", - "author_inst": "Biodesign Institute, ASU" - }, - { - "author_name": "Savanah Gisriel", - "author_inst": "Yale University" - }, - { - "author_name": "Bertram Jacobs", - "author_inst": "Biodesign Institute, ASU" + "author_name": "Yin Wu", + "author_inst": "UTHSC, Department of Pedatrics" }, { - "author_name": "Timothy L Karr", - "author_inst": "Biodesign Institute, ASU" + "author_name": "Isaac Turan", + "author_inst": "Department of Chemistry, Chemical and Biomedical Engineering and Center for Gene Regulation of Health and Disease (GRHD), Cleveland State University" }, { - "author_name": "Esther Borges Florsheim", - "author_inst": "Biodesign Institute, ASU" + "author_name": "Joseph Keil", + "author_inst": "Department of Chemistry, Chemical and Biomedical Engineering and Center for Gene Regulation of Health and Disease (GRHD), Cleveland State University" }, { - "author_name": "Vivek Kumar", - "author_inst": "NJIT" + "author_name": "Kui Li", + "author_inst": "Department of Microbiology, Immunology and Biochemistry, UTHSC University of Tennessee Health Science Center" }, { - "author_name": "John Wallen", - "author_inst": "Colt Advisors" + "author_name": "Michael H Chen", + "author_inst": "UTHSC, Department of Pedatrics" }, { - "author_name": "Masmudur Rahman", - "author_inst": "Biodesign Institute, ASU" + "author_name": "Runhua Liu", + "author_inst": "University of Alabama at Birmingham, Birmingham" }, { - "author_name": "Douglas Grant McFadden", - "author_inst": "Biodesign Institute, ASU" + "author_name": "Lizhong Wang", + "author_inst": "University of Alabama at Birmingham, Birmingham" }, { - "author_name": "Brenda Hogue", - "author_inst": "Biodesign Institute, ASU" + "author_name": "Xue-Long Sun", + "author_inst": "Department of Chemistry, Chemical and Biomedical Engineering and Center for Gene Regulation of Health and Disease (GRHD), Cleveland State University" }, { - "author_name": "Alexandra R Lucas", - "author_inst": "Biodesign Institute" + "author_name": "Guoyun Chen", + "author_inst": "UTHSC, Department of Pedatrics" } ], "version": "1", @@ -189955,71 +189305,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.09.09.22279751", - "rel_title": "Serial cross-sectional estimation of vaccine and infection-induced SARS-CoV-2 sero-prevalence in children and adults, British Columbia, Canada: March 2020 to August 2022", + "rel_doi": "10.1101/2022.09.08.22279731", + "rel_title": "Dynamics of SARS-CoV-2 seroassay sensitivity: a systematic review and modeling study", "rel_date": "2022-09-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.09.22279751", - "rel_abs": "BackgroundWe chronicle SARS-CoV-2 sero-prevalence through eight cross-sectional sero-surveys (snapshots) in the Lower Mainland (Greater Vancouver and Fraser Valley), British Columbia, Canada from March 2020 to August 2022.\n\nMethodsAnonymized-residual sera were obtained from children and adults attending an outpatient laboratory network. Sera were tested with at least three immuno-assays per snapshot to detect spike (S1) and/or nucleocapsid protein (NP) antibodies. Sero-prevalence was defined by dual-assay positivity, including any or infection-induced, the latter requiring S1+NP antibody detection from January 2021 owing to vaccine availability. Infection-induced estimates were used to assess the extent to which surveillance case reports under-estimated infections.\n\nResultsSero-prevalence was [≤]1% by the 3rd snapshot in September 2020 and <5% by January 2021 (4th). Following vaccine roll-out, sero-prevalence increased to >55% by May/June 2021 (5th), [~]80% by September/October 2021 (6th), and >95% by March 2022 (7th). In all age groups, infection-induced sero-prevalence remained <15% through September/October 2021, increasing through subsequent Omicron waves to [~]40% by March 2022 (7th) and [~]60% by July/August 2022 (8th). By August 2022, at least 70-80% of children [≤]19 years, 60-70% of adults 20-59 years, but [~]40% of adults [≥]60 years had been infected. Surveillance case reports under-estimated infections by 12-fold between the 6th-7th and 92-fold between the 7th-8th snapshots.\n\nInterpretationBy August 2022, most children and adults had acquired SARS-CoV-2 vaccine and infection exposures, resulting in more robust hybrid immunity. Conversely the elderly, still at greatest risk of severe outcomes, remain largely-dependent on vaccine-induced protection alone, and should be prioritized for additional doses.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.08.22279731", + "rel_abs": "BackgroundSerological surveys have been the gold standard to estimate the numbers of SARS-CoV-2 infections, epidemic dynamics, and disease severity. Serological assays have decaying sensitivity with time that can bias their results, but there is a lack of guidelines to account for this phenomenon for SARS-CoV-2.\n\nAimOur goal is to assess the sensitivity decay of seroassays for detecting SARS-CoV-2 infections, the dependence of this decay on assay characteristics, and to provide a simple method to correct for this phenomenon.\n\nMethodsWe performed a systematic review and meta-analysis of SARS-CoV-2 serology studies. We included studies testing previously diagnosed individuals, without any SARS-CoV-2 vaccines, and excluded studies of cohorts highly unrepresentative of the general population (e.g. hospitalised patients).\n\nResultsOf the 488 screened studies, 76 studies reporting on 50 different seroassays were included in the analysis. Sensitivity decay depends strongly on the antigen and the analytic technique used by the assay, with average sensitivities ranging between 26% and 98% at 6 months after infection, depending on assay characteristics. We find that a third of the included assays depart considerably from manufacturer specifications after 6 months.\n\nConclusionsSeroassay sensitivity decay depends on assay characteristics, and for some types of assays it can make manufacturer specifications highly unreliable. We provide a tool to correct for this phenomenon, and to assess the risk of decay for a given assay. Our analysis can guide the design and interpretation of serosurveys for SARS-CoV-2 and other pathogens, and quantify systematic biases in the existing serology literature.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Danuta M Skowronski", - "author_inst": "BC Centre for Disease Control" - }, - { - "author_name": "Samantha E Kaweski", - "author_inst": "BC Centre for Disease Control" - }, - { - "author_name": "Michael A Irvine", - "author_inst": "BC Centre for Disease Control" - }, - { - "author_name": "Shinhye Kim", - "author_inst": "BC Centre for Disease Control" - }, - { - "author_name": "Erica SY Chuang", - "author_inst": "BC Centre for Disease Control" - }, - { - "author_name": "Suzana Sabaiduc", - "author_inst": "BC Centre for Disease Control" - }, - { - "author_name": "Mieke Fraser", - "author_inst": "BC Centre for Disease Control" - }, - { - "author_name": "Romina C Reyes", - "author_inst": "LifeLabs" - }, - { - "author_name": "Bonnie Henry", - "author_inst": "Office of the Provincial Health Officer, Ministry of Health" + "author_name": "Nana Owusu-Boaitey", + "author_inst": "School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA" }, { - "author_name": "Paul N Levett", - "author_inst": "University of British Columbia, Department of Pathology and Laboratory Medicine" + "author_name": "Timothy W. Russell", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Martin Petric", - "author_inst": "University of British Columbia, Department of Pathology and Laboratory Medicine" + "author_name": "Gideon Meyerowitz-Katz", + "author_inst": "University of Wollongong" }, { - "author_name": "Mel Krajden", - "author_inst": "BC Centre for Disease Control" + "author_name": "Andrew T Levin", + "author_inst": "Dartmouth College" }, { - "author_name": "Inna Sekirov", - "author_inst": "BC Centre for Disease Control" + "author_name": "Daniel Herrera-Esposito", + "author_inst": "Department of Psychology, University of Pennsylvania" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.09.05.22279623", @@ -191757,65 +191075,61 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.09.06.506799", - "rel_title": "Omicron-induced interferon signalling prevents influenza A virus infection", + "rel_doi": "10.1101/2022.09.05.506628", + "rel_title": "Resistance of SARS-CoV-2 Omicron Subvariant BA.4.6 to Antibody Neutralization", "rel_date": "2022-09-06", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.06.506799", - "rel_abs": "Recent findings in permanent cell lines suggested that SARS-CoV-2 Omicron BA.1 induces a stronger interferon response than Delta. Here, we show that BA.1 and BA.5 but not Delta induce an antiviral state in air-liquid interface (ALI) cultures of primary human bronchial epithelial (HBE) cells and primary human monocytes. Both Omicron subvariants caused the production of biologically active type I (/{beta}) and III ({lambda}) interferons and protected cells from super-infection with influenza A viruses. Notably, abortive Omicron infection of monocytes was sufficient to protect monocytes from influenza A virus infection. Interestingly, while influenza-like illnesses surged during the Delta wave in England, their spread rapidly declined upon the emergence of Omicron. Mechanistically, Omicron-induced interferon signalling was mediated via double-stranded RNA recognition by MDA5, as MDA5 knock-out prevented it. The JAK/ STAT inhibitor baricitinib inhibited the Omicron-mediated antiviral response, suggesting it is caused by MDA5-mediated interferon production, which activates interferon receptors that then trigger JAK/ STAT signalling. In conclusion, our study 1) demonstrates that only Omicron but not Delta induces a substantial interferon response in physiologically relevant models, 2) shows that Omicron infection protects cells from influenza A virus super-infection, and 3) indicates that BA.1 and BA.5 induce comparable antiviral states.", - "rel_num_authors": 12, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.05.506628", + "rel_abs": "SARS-CoV-2 Omicron subvariants BA.4.6, BA.4.7, and BA.5.9 have recently emerged, and BA.4.6 appears to be expanding even in the presence of BA.5 that is globally dominant. Compared to BA.5, these new subvariants harbor a mutation at R346 residue in the spike glycoprotein, raising concerns for further antibody evasion. We compared the viral receptor binding affinity of the new Omicron subvariants with BA.5 by surface plasmon resonance. We also performed VSV-based pseudovirus neutralization assays to evaluate their antigenic properties using sera from individuals who received three doses of a COVID-19 mRNA vaccine (boosted) and patients with BA.1 or BA.2 breakthrough infection, as well as using a panel of 23 monoclonal antibodies (mAbs). Compared to the BA.5 subvariant, BA.4.6, BA.4.7, and BA.5.9 showed similar binding affinities to hACE2 and exhibited similar resistance profiles to boosted and BA.1 breakthrough sera, but BA.4.6 was slightly but significantly more resistant than BA.5 to BA.2 breakthrough sera. Moreover, BA.4.6, BA.4.7, and BA.5.9 showed heightened resistance over to a class of mAbs due to R346T/S/I mutation. Notably, the authorized combination of tixagevimab and cilgavimab completely lost neutralizing activity against these three subvariants. The loss of activity of tixagevimab and cilgavimab against BA.4.6 leaves us with bebtelovimab as the only therapeutic mAb that has retained potent activity against all circulating forms of SARS-CoV-2. As the virus continues to evolve, our arsenal of authorized mAbs may soon be depleted, thereby jeopardizing the wellbeing of millions of immunocompromised persons who cannot robustly respond to COVID-19 vaccines.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Denisa Bojkova", - "author_inst": "Institute of Medical Virology" - }, - { - "author_name": "Marco Bechtel", - "author_inst": "Goethe-University" + "author_name": "Qian Wang", + "author_inst": "Columbia University Irving Medical Center" }, { - "author_name": "Tamara Rothenburger", - "author_inst": "Goethe-University" + "author_name": "Zhiteng Li", + "author_inst": "Columbia University Irving Medical Center" }, { - "author_name": "Joshua D Kandler", - "author_inst": "Goethe-University" + "author_name": "Jerren Ho", + "author_inst": "Columbia University Irving Medical Center" }, { - "author_name": "Lauren Hayes", - "author_inst": "University of Kent" + "author_name": "Yicheng Guo", + "author_inst": "Columbia University Irving Medical Center" }, { - "author_name": "Ruth Olmer", - "author_inst": "Hannover Medical School" + "author_name": "Andre Yanchen Yeh", + "author_inst": "School of Medicine, National Taiwan University" }, { - "author_name": "Ulrich Martin", - "author_inst": "Hannover Medical School" + "author_name": "Michael Liu", + "author_inst": "Columbia University Irving Medical Center" }, { - "author_name": "Danny Jonigk", - "author_inst": "Hannover Medical School" + "author_name": "Maple Wang", + "author_inst": "Columbia University Irving Medical Center" }, { - "author_name": "Sandra Ciesek", - "author_inst": "Goethe Universtiy Frankfurt" + "author_name": "Jian Yu", + "author_inst": "Columbia University Irving Medical Center" }, { - "author_name": "Mark N Wass", - "author_inst": "University of Kent" + "author_name": "Zizhang Sheng", + "author_inst": "Columbia University Irving Medical Center" }, { - "author_name": "Martin Michaelis", - "author_inst": "University of Kent" + "author_name": "Lihong Liu", + "author_inst": "Columbia University Irving Medical Center" }, { - "author_name": "Jindrich Cinatl Jr.", - "author_inst": "Klinikum der Goethe-Universitaet" + "author_name": "David D Ho", + "author_inst": "Columbia University Irving Medical Center" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "microbiology" }, @@ -193831,45 +193145,45 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2022.09.02.506332", - "rel_title": "SARS-CoV-2 nucleocapsid protein inhibits the stress response through RNA-binding domain N2b", + "rel_doi": "10.1101/2022.09.02.506368", + "rel_title": "White-tailed deer (Odocoileus virginianus) may serve as a wildlife reservoir for nearly extinct SARS-CoV-2 variants of concern", "rel_date": "2022-09-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.02.506332", - "rel_abs": "The nucleocapsid protein N of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enwraps and condenses the viral genome for packaging but is also an antagonist of the innate antiviral defense. It suppresses the integrated stress response (ISR), purportedly by interacting with stress granule (SG) assembly factors G3BP1 and 2, and inhibits type I interferon responses. To elucidate its mode of action, we systematically deleted and over-expressed distinct regions and domains. We show that N via domain N2b blocks PKR-mediated ISR activation, as measured by suppression of ISR-induced translational arrest and SG formation. N2b mutations that prevent dsRNA binding abrogate these activities also when introduced in the intact N protein. Substitutions reported to block post-translation modifications of N or its interaction with G3BP1/2 did not have a detectable additive effect. In an encephalomyocarditis virus-based infection model, N2b - but not a derivative defective in RNA binding - prevented PKR activation, inhibited {beta}-interferon expression and promoted virus replication. Apparently, SARS-CoV-2 N inhibits innate immunity by sequestering dsRNA to prevent activation of PKR and RIG-I-like receptors. Similar observations were made for the N protein of human coronavirus 229E, suggesting that this may be a general trait conserved among members of other orthocoronavirus (sub)genera.\n\nSIGNIFICANCE STATEMENTSARS-CoV-2 nucleocapsid protein N is an antagonist of innate immunity but how it averts virus detection by intracellular sensors remains subject to debate. We provide evidence that SARS-CoV-2 N, by sequestering dsRNA through domain N2b, prevents PKR-mediated activation of the integrated stress response as well as detection by RIG-I-like receptors and ensuing type I interferon expression. This function, conserved in human coronavirus 229E, is not affected by mutations that prevent posttranslational modifications, previously implicated in immune evasion, or that target its binding to stress granule scaffold proteins. Our findings further our understanding of how SARS-CoV-2 evades innate immunity, how this may drive viral evolution and why increased N expression may have been a selective advantage to SARS-CoV-2 variants of concern.", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.02.506368", + "rel_abs": "The spillover of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from humans into white-tailed deer (WTD) and its ability to transmit from deer-to-deer raised concerns about the role of WTD in the epidemiology and ecology of the virus. In the present study, we conducted a comprehensive investigation to assess the prevalence, genetic diversity, and evolution of SARS-CoV-2 in WTD in the State of New York (NY). A total of 5,462 retropharyngeal lymph node (RPLN) samples collected from free-ranging hunter-harvested WTD during the hunting seasons of 2020 (Season 1, September-December 2020, n=2,700) and 2021 (Season 2, September-December 2021, n=2,762) were tested by SARS-CoV-2 real-time RT-PCR. SARS-CoV-2 RNA was detected in 17 samples (0.6%) from Season 1 and in 583 (21.1%) samples from Season 2. Hotspots of infection were identified in multiple confined geographic areas of NY. Sequence analysis of SARS-CoV-2 genomes from 164 samples demonstrated the presence multipls SARS-CoV-2 lineages as well as the co-circulation of three major variants of concern (VOCs) (Alpha, Gamma, and Delta) in WTD. Our analysis suggests the occurrence of multiple spillover events (human-to-deer) of the Alpha and Delta lineages with subsequent deer-to-deer transmission of the viruses. Detection of Alpha and Gamma variants in WTD long after their broad circulation in humans in NY suggests that WTD may serve as a wildlife reservoir for VOCs no longer circulating in humans. Thus, implementation of continuous surveillance programs to monitor SARS-CoV-2 dynamics in WTD are warranted, and measures to minimize virus transmission between humans and animals are urgently needed.\n\nSIGNIFICANCEWhite-tailed deer (WTD) are highly susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and are known to efficiently transmit the virus to other susceptible animals. Evidence of natural exposure or infection of wild WTD in North America raised significant concerns about their role on the ecology of the virus and its impact on the control of the coronavirus disease 2019 (COVID-19) pandemic. This comprehensive study demonstrates widespread infection of SARS-CoV-2 in the WTD populations across the State of New York. Additionally, we showed co-circulation of three major SARS-CoV-2 variants of concern (VOCs) in this wildlife population, long after their broad circulation in humans. These findings indicate that WTD - the most abundant large mammal in North America - may serve as a reservoir for variant SARS-CoV-2 strains that no longer circulate in the human population.", "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Chiara Aloise", - "author_inst": "Utrecht University" + "author_name": "Leonardo C Caserta", + "author_inst": "Cornell University" }, { - "author_name": "Jelle G. Schipper", - "author_inst": "Utrecht University" + "author_name": "Mathias Martins", + "author_inst": "Cornell University" }, { - "author_name": "Arno van Vliet", - "author_inst": "Utrecht University" + "author_name": "Salman L. Butt", + "author_inst": "Cornell University" }, { - "author_name": "Judith Oymans", - "author_inst": "Utrecht University" + "author_name": "Nicholas Hollingshead", + "author_inst": "Cornell University College of Veterinary Medicine" }, { - "author_name": "Tim Donselaar", - "author_inst": "Utrecht University" + "author_name": "Lina M. Covaleda", + "author_inst": "Cornell University" }, { - "author_name": "Daniel L. Hurdiss", - "author_inst": "Utrecht University" + "author_name": "Mia Everts", + "author_inst": "Cornell University" }, { - "author_name": "Raoul J de Groot", - "author_inst": "Utrecht University" + "author_name": "Krysten Schuler", + "author_inst": "Cornell University College of Veterinary Medicine" }, { - "author_name": "Frank J.M. van Kuppeveld", - "author_inst": "Utrecht University" + "author_name": "Diego G. Diel", + "author_inst": "Cornell University College of Veterinary Medicine" } ], "version": "1", @@ -195573,73 +194887,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.08.29.22279355", - "rel_title": "Metformin is Associated with Reduced COVID-19 Severity in Patients with Prediabetes", + "rel_doi": "10.1101/2022.08.29.22279317", + "rel_title": "A Phase I, Prospective, Randomized, Open-labeled Study to Evaluate the Safety, Tolerability, and Immunogenicity of Booster Dose with MVC-COV1901 or MVC-COV1901(Beta) SARS-CoV-2 Vaccine in Adults", "rel_date": "2022-08-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.29.22279355", - "rel_abs": "BackgroundWith the continuing COVID-19 pandemic, identifying medications that improve COVID-19 outcomes is crucial. Studies suggest that use of metformin, an oral antihyperglycemic, is associated with reduced COVID-19 severity in individuals with diabetes compared to other antihyperglycemic medications. Some patients without diabetes, including those with polycystic ovary syndrome (PCOS) and prediabetes, are prescribed metformin for off-label use, which provides an opportunity to further investigate the effect of metformin on COVID-19.\n\nParticipantsIn this observational, retrospective analysis, we leveraged the harmonized electronic health record data from 53 hospitals to construct cohorts of COVID-19 positive, metformin users without diabetes and propensity-weighted control users of levothyroxine (a medication for hypothyroidism that is not known to affect COVID-19 outcome) who had either PCOS (n = 282) or prediabetes (n = 3136). The primary outcome of interest was COVID-19 severity, which was classified as: mild, mild ED (emergency department), moderate, severe, or mortality/hospice.\n\nResultsIn the prediabetes cohort, metformin use was associated with a lower rate of COVID-19 with severity of mild ED or worse (OR: 0.630, 95% CI 0.450 - 0.882, p < 0.05) and a lower rate of COVID-19 with severity of moderate or worse (OR: 0.490, 95% CI 0.336 - 0.715, p < 0.001). In patients with PCOS, we found no significant association between metformin use and COVID-19 severity, although the number of patients was relatively small.\n\nConclusionsMetformin was associated with less severe COVID-19 in patients with prediabetes, as seen in previous studies of patients with diabetes. This is an important finding, since prediabetes affects between 19 and 38% of the US population, and COVID-19 is an ongoing public health emergency. Further observational and prospective studies will clarify the relationship between metformin and COVID-19 severity in patients with prediabetes, and whether metformin usage may reduce COVID-19 severity.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.29.22279317", + "rel_abs": "BackgroundThe use of variant-based severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine as a booster is being evaluated to overcome reduced neutralisation of variants induced by the original SARS-CoV-2 vaccine and waning protection over time.\n\nMethodsThis is a phase one, prospective, randomized, and open-labeled trial to study the safety and immunogenicity of a booster dose consisting of a subunit vaccine based on the stabilized prefusion SARS-CoV-2 spike protein, MVC-COV1901 or its Beta version, MVC-COV1901-Beta. One-hundred and seven participants aged [≥]18 and <55 years, who received two or three prior doses of MVC-COV1901 vaccines, were enrolled and were to receive a booster dose of either 15 mcg of MVC-COV1901, 15 mcg or 25 mcg of MVC-COV1901-Beta in 1:1:1 ratio. The primary endpoints were the incidences of adverse events and immunogenicity of the booster dose from Visit 2 (the day of the booster) to Visit 5 (four weeks after the booster). Cellular immunity was also investigated with memory B cell (MBC) and T cell assays.\n\nFindingsAdverse reactions after either MVC-COV1901 or MVC-COV1901-Beta booster doses after two or three doses of MVC-COV1901 were comparable and mostly mild and transient. At four weeks after the booster dose, participants with two prior doses of MVC-COV1901 exhibited numerically higher levels of neutralising antibodies against SARS-CoV-2 or Beta variant than participants with three prior doses of MVC-COV1901 regardless of the type of booster used. However, compared to 15 mcg of MVC-COV1901, 25 mcg of MVC-COV1901-Beta significantly improved neutralising antibody titre against Beta variant and BA.4/BA.5 Omicron variant pseudoviruses. The booster dose also significantly increased the proportion of spike-specific MBCs, including those of Beta and Omicron variants.\n\nInterpretationMVC-COV1901-Beta can be effectively used as a booster dose against SARS-CoV-2, including the circulating BA.4/BA.5 Omicron variant.\n\nFundingMedigen Vaccine Biologics Corporation", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Lauren E Chan", - "author_inst": "Oregon State University" - }, - { - "author_name": "Elena Casiraghi", - "author_inst": "Universita degli Studi di Milano" - }, - { - "author_name": "Bryan J Laraway", - "author_inst": "University of Colorado Anschutz Medical Campus" - }, - { - "author_name": "Ben Coleman", - "author_inst": "The Jackson Laboratory for Genomic Medicine" - }, - { - "author_name": "Hannah Blau", - "author_inst": "The Jackson Laboratory for Genomic Medicine" - }, - { - "author_name": "Adnin Zaman", - "author_inst": "University of Colorado Anschutz Medical Campus" + "author_name": "Chia En Lien", + "author_inst": "Medigen Vaccine Biologics Corp." }, { - "author_name": "Nomi L Harris", - "author_inst": "Lawrence Berkeley National Laboratory" + "author_name": "Ming-Che Liu", + "author_inst": "Taipei Medical University" }, { - "author_name": "Kenneth Wilkins", - "author_inst": "National Institute of Diabetes and Digestive and Kidney Diseases" + "author_name": "Ning-Chi Wang", + "author_inst": "Tri-Service General Hospital" }, { - "author_name": "Giorgio Valentini", - "author_inst": "Universita degli Studi di Milano" + "author_name": "Luke Tzu -Chi Liu", + "author_inst": "Medigen Vaccine Biologics Corp" }, { - "author_name": "David Sahner", - "author_inst": "Axle Informatics" + "author_name": "Chung-Chin Wu", + "author_inst": "Medigen Vaccine Biologics Corp" }, { - "author_name": "Melissa A Haendel", - "author_inst": "University of Colorado Anschutz Medical Campus" + "author_name": "Wei-Hsuan Tang", + "author_inst": "Medigen Vaccine Biologics Corp" }, { - "author_name": "Peter N Robinson", - "author_inst": "The Jackson Laboratory for Genomic Medicine" + "author_name": "Wei-Cheng Lian", + "author_inst": "Meidgen Vaccine Biologics Corp" }, { - "author_name": "Carolyn T Bramante", - "author_inst": "University of Minnesota" + "author_name": "Kuan-Ying A Huang", + "author_inst": "Chang Gung University" }, { - "author_name": "Justin T Reese", - "author_inst": "Lawrence Berkeley National Laboratory" + "author_name": "Charles Chen", + "author_inst": "Medigen Vaccine Biologics Corp" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -197247,105 +196541,225 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.08.25.22279158", - "rel_title": "Homologous and heterologous boosting with CoronaVac and BNT162b2: a randomized trial (the Cobovax study)", + "rel_doi": "10.1101/2022.08.25.22279181", + "rel_title": "International Multicenter Study Comparing Cancer to Non-Cancer Patients with COVID-19: Impact of Risk Factors and Treatment Modalities on Survivorship", "rel_date": "2022-08-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.25.22279158", - "rel_abs": "BackgroundThere are few trials comparing homologous and heterologous third doses of COVID-19 vaccination with inactivated vaccines and mRNA vaccines.\n\nMethodsWe conducted an open-label randomized trial in adults >=18 years of age who received two doses of inactivated vaccine (CoronaVac) or mRNA vaccine (BNT162b2) >=6 months earlier, randomised in 1:1 ratio to receive a third dose of either vaccine. We compared the reactogenicity, immunogenicity and cell-mediated immune responses, and assessed vaccine efficacy against infections during follow-up.\n\nResultsWe enrolled 219 adults who previously received two doses of CoronaVac and randomised to CoronaVac (\"CC-C\", n=101) or BNT162b2 (\"CC-B\", n=118) third dose; and 232 adults who previously received BNT162b2 and randomised to CoronaVac (\"BB-C\", n=118) or BNT162b2 (\"BB-B\", n=114). There were more frequent reports of mild reactions in recipients of third-dose BNT162b2, which generally subsided within 7 days. Antibody responses against the ancestral virus, Omicron BA.1 and BA.2 subvariant by surrogate neutralization and PRNT50 were stronger for the recipients of a third dose of BNT162b2 over CoronaVac irrespective of prior vaccine type. CD4+ T cells boost only occurred in CoronaVac-primed arms. We did not identify differences in CD4+ and CD8+ T cell responses between arms. When Omicron BA.2 was circulating, we identified 58 infections with cumulative incidence of 15.3% and 15.4% in the CC-C and CC-B (p=0.93), and 16.7% and 14.0% in the BB-C and BB-B arms, respectively (p=0.56).\n\nConclusionsSimilar levels of incidence of infection in each arm suggest all third dose combinations may provide similar degrees of protection against prevalent Omicron BA.2 infection, despite very weak antibody responses to BA.2 in the recipients of a CoronaVac third dose. Further research is warranted to identify appropriate correlates of protection for inactivated COVID-19 vaccines.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.25.22279181", + "rel_abs": "BackgroundIn this international multicenter study we aimed to determine the independent risk factors associated with increased 30-day mortality and the impact of novel treatment modalities in a large group of cancer and non-cancer patients with COVID-19 from multiple countries.\n\nMethodsWe retrospectively collected de-identified data on a cohort of cancer and non-cancer patients diagnosed with COVID-19 between January and November 2020, from 16 international centers.\n\nResultsWe analyzed 3966 COVID-19 confirmed patients, 1115 cancer and 2851 non-cancer patients. Cancer patients were more likely to be pancytopenic, and have a smoking history, pulmonary disorders, hypertension, diabetes mellitus, and corticosteroid use in the preceding two weeks (p[≤]0.01). In addition, they were more likely to present with higher inflammatory biomarkers (D-dimer, ferritin and procalcitonin), but were less likely to present with clinical symptoms (p[≤]0.01). By multivariable logistic regression analysis, cancer was an independent risk factor for 30-day mortality (OR 1.46; 95% CI 1.03 to 2.07; p=0.035). Older age ([≥]65 years) was the strongest predictor of 30-day mortality in all patients (OR 4.55; 95% CI 3.34 to6.20; p< 0.0001). Remdesivir was the only therapeutic agent independently associated with decreased 30-day mortality (OR 0.58; CI 0.39-0.88; p=0.009). Among patients on low-flow oxygen at admission, patients who received remdesivir had a lower 30-day mortality rate than those who did not (5.9% vs 17.6%; p=0.03).\n\nConclusionsCancer is an independent risk factor for increased 30-day all-cause mortality from COVID-19. Remdesivir, particularly in patients receiving low-flow oxygen, can reduce 30-day all-cause mortality.\n\nCondensed AbstractIn this large multicenter worldwide study of 4015 patients with COVID-19 that included 1115 patients with cancer, we found that cancer is an independent risk factor for increased 30-day all-cause mortality. Remdesivir is a promising treatment modality to reduce 30-day all-cause mortality.", + "rel_num_authors": 52, "rel_authors": [ { - "author_name": "Nancy H. L. Leung", - "author_inst": "The University of Hong Kong" + "author_name": "Issam Raad", + "author_inst": "Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA" }, { - "author_name": "Samuel M. S. Cheng", - "author_inst": "The University of Hong Kong" + "author_name": "Ray Hachem", + "author_inst": "UT MD Anderson Cancer Center" }, { - "author_name": "Carolyn A. Cohen", - "author_inst": "The University of Hong Kong" + "author_name": "Masayuki Nigo", + "author_inst": "The University of Texas Houston Health Science Center at Houston" }, { - "author_name": "Mario Martin-Sanchez", - "author_inst": "The University of Hong Kong" + "author_name": "Tarcila Datoguia", + "author_inst": "Medica Hematologista Hospital Israelita" }, { - "author_name": "Niki Y. M. Au", - "author_inst": "The University of Hong Kong" + "author_name": "Hiba Dagher", + "author_inst": "UT MD Anderson Cancer Center" }, { - "author_name": "Leo L. H. Luk", - "author_inst": "The University of Hong Kong" + "author_name": "Ying Jiang", + "author_inst": "UT MD Anderson Cancer Center" }, { - "author_name": "Leo C. H. Tsang", - "author_inst": "The University of Hong Kong" + "author_name": "Vivek Subbiah", + "author_inst": "\"Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA MD Anderson Cancer Network, UT MD And" }, { - "author_name": "Kelvin K. H. Kwan", - "author_inst": "The University of Hong Kong" + "author_name": "Bilal Siddiqui", + "author_inst": "Department of Hematology Oncology, Community Health Network, Indiana, USA" }, { - "author_name": "Sara Chaothai", - "author_inst": "The University of Hong Kong" + "author_name": "Arnaud Bayle", + "author_inst": "Gustave Roussy Universite Paris-Saclay, Villejuif, France" }, { - "author_name": "Lison W. C. Fung", - "author_inst": "The University of Hong Kong" + "author_name": "Robert Somer", + "author_inst": "Cooper Medical School of Rowan University, Cooper University Health Care, Camden, New Jersey, USA" }, { - "author_name": "Alan W. L. Cheung", - "author_inst": "The University of Hong Kong" + "author_name": "Ana Fernandez-Cruz", + "author_inst": "Hospital Universitario Puerta de Hierro" }, { - "author_name": "Karl C. K. Chan", - "author_inst": "The University of Hong Kong" + "author_name": "Edward Gorak", + "author_inst": "Department of Hematology Oncology, Baptist Health, Jacksonville, Florida, USA" }, { - "author_name": "John K. C. Li", - "author_inst": "The University of Hong Kong" + "author_name": "Arvinder Bhinder", + "author_inst": "Department of Hematology/Oncology, Ohio Health Marion, Ohio, USA" }, { - "author_name": "Yvonne Y. Ng", - "author_inst": "The University of Hong Kong" + "author_name": "Mori Nobuyoshi", + "author_inst": "Department of Infectious Diseases, St. Luke's International Hospital, Tokyo, Japan" }, { - "author_name": "Prathanporn Kaewpreedee", - "author_inst": "The University of Hong Kong" + "author_name": "Nelson Hamerschlak", + "author_inst": "Medica Hematologista Hospital Israelita Albert Einstein, Sao Paulo, Brasil" }, { - "author_name": "Janice Z. Jia", - "author_inst": "The University of Hong Kong" + "author_name": "Samuel Shelanski", + "author_inst": "Division of Cancer Medicine, Banner MD Anderson Cancer Center, Gilbert, Arizona, USA" }, { - "author_name": "Dennis K. M. Ip", - "author_inst": "The University of Hong Kong" + "author_name": "Tomislav Dragovich", + "author_inst": "Banner MD Anderson Cancer Center, North Colorado, Greely, Colorado, USA Division of Cancer Medicine, Banner MD Anderson Cancer Center, Gilbert, Arizona, USA" }, { - "author_name": "Leo L. M. Poon", - "author_inst": "The University of Hong Kong" + "author_name": "Yee Elise Vong Kiat", + "author_inst": "Department of Medical Oncology, Tan Tock Seng Hospital, Singapore" }, { - "author_name": "Gabriel M. Leung", - "author_inst": "The University of Hong Kong" + "author_name": "Suha Fakhreddine", + "author_inst": "Department of Infectious Diseases, Rafik Hariri University Hospital, Beirut, Lebanon" }, { - "author_name": "Malik Peiris", - "author_inst": "The University of Hong Kong" + "author_name": "Pierre Abi Hanna", + "author_inst": "Department of Infectious Diseases, Rafik Hariri University Hospital, Beirut, Lebanon" }, { - "author_name": "Sophie A. Valkenburg", - "author_inst": "The University of Hong Kong" + "author_name": "Roy F Chemaly", + "author_inst": "Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA" }, { - "author_name": "Benjamin J. Cowling", - "author_inst": "The University of Hong Kong" + "author_name": "Victor Mulanovich", + "author_inst": "Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA" + }, + { + "author_name": "Javier A Adachi", + "author_inst": "Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA" + }, + { + "author_name": "Jovan Borjan", + "author_inst": "Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA" + }, + { + "author_name": "Fareed Khawaja", + "author_inst": "Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA" + }, + { + "author_name": "Bruno Granwehr", + "author_inst": "UT MD Anderson Cancer Center" + }, + { + "author_name": "Teny John", + "author_inst": "Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA" + }, + { + "author_name": "Eduardo Yepez Guevara", + "author_inst": "Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA" + }, + { + "author_name": "Harrys Torres", + "author_inst": "Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA" + }, + { + "author_name": "Natraj Reddy Ammakkanavar", + "author_inst": "Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA" + }, + { + "author_name": "Marcel Yibirin", + "author_inst": "Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA" + }, + { + "author_name": "Cielito Reyes", + "author_inst": "UT MD Anderson Cancer Center" + }, + { + "author_name": "Mala Pande", + "author_inst": "UT MD Anderson Cancer Center" + }, + { + "author_name": "Noman Ali", + "author_inst": "Department of Hospital Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas" + }, + { + "author_name": "Raniv Rojo", + "author_inst": "UT MD Anderson Cancer Center" + }, + { + "author_name": "Shahnoor Ali", + "author_inst": "Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA" + }, + { + "author_name": "Rita Deeba", + "author_inst": "Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA" + }, + { + "author_name": "Patrick Chaftari", + "author_inst": "Department of Emergency Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas" + }, + { + "author_name": "Takahiro Matsuo", + "author_inst": "Department of Infectious Diseases, St. Luke's International Hospital, Tokyo, Japan" + }, + { + "author_name": "Kazuhiro Ishikawa", + "author_inst": "Department of Infectious Diseases, St. Luke's International Hospital, Tokyo, Japan" + }, + { + "author_name": "Ryo Hasegawa", + "author_inst": "Department of Infectious Diseases, St. Luke's International Hospital, Tokyo, Japan" + }, + { + "author_name": "Ramon Aguado-Noya", + "author_inst": "Oncology Department, Hospital Universitario Puerta de Hierro-Majadahonda, Madrid, Spain" + }, + { + "author_name": "Alvaro Garcia Garcia", + "author_inst": "Hematology Department, Hospital Universitario Puerta de Hierro-Majadahonda, Madrid, Spain" + }, + { + "author_name": "Cristina Traseira Puchol", + "author_inst": "Oncology Department, Hospital Universitario Puerta de Hierro-Majadahonda, Madrid, Spain" + }, + { + "author_name": "Dong-Gun Lee", + "author_inst": "Division of Infectious Diseases, Department of Internal Medicine, Vaccine Bio Research Institute, The Catholic University of Korea, Seoul, Korea" + }, + { + "author_name": "Monica Slavin", + "author_inst": "Department of Infectious Diseases and National Centre for Infections in Cancer, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia" + }, + { + "author_name": "Benjamin W Teh", + "author_inst": "Peter MacCallum Cancer Centre" + }, + { + "author_name": "Cesar A Arias", + "author_inst": "The University of Texas Health Science Center at Houston, Houston, Texas, USA" + }, + { + "author_name": "- Data-Driven Determinants for COVID-19 Oncology Discovery Effort (D3CODE) Team", + "author_inst": "-" + }, + { + "author_name": "Dimitrios Kontoyiannis", + "author_inst": "Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA" + }, + { + "author_name": "Alexandre E. Malek", + "author_inst": "Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA" + }, + { + "author_name": "Anne Marie Chaftari", + "author_inst": "UT MD Anderson Cancer Center" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -199077,43 +198491,51 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.08.23.22279132", - "rel_title": "A Deep Learning Approach to Forecast Short-Term COVID-19 Cases and Deaths in the US", + "rel_doi": "10.1101/2022.08.23.504798", + "rel_title": "Integrated Immunopeptidomics and Proteomics Study Reveals Imbalanced Innate and Adaptive Immune Responses to SARS-Cov-2 Infection", "rel_date": "2022-08-24", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.23.22279132", - "rel_abs": "Since the US reported its first COVID-19 case on January 21, 2020, the science community has been applying various techniques to forecast incident cases and deaths. To date, providing an accurate and robust forecast at a high spatial resolution has proved challenging, even in the short term. Here we present a novel multi-stage deep learning model to forecast the number of COVID-19 cases and deaths for each US state at a weekly level for a forecast horizon of 1 to 4 weeks. The model is heavily data driven, and relies on epidemiological, mobility, survey, climate, and demographic. We further present results from a case study that incorporates SARS-CoV-2 genomic data (i.e. variant cases) to demonstrate the value of incorporating variant cases data into model forecast tools. We implement a rigorous and robust evaluation of our model - specifically we report on weekly performance over a one-year period based on multiple error metrics, and explicitly assess how our model performance varies over space, chronological time, and different outbreak phases. The proposed model is shown to consistently outperform the CDC ensemble model for all evaluation metrics in multiple spatiotemporal settings, especially for the longer-term (3 and 4 weeks ahead) forecast horizon. Our case study also highlights the potential value of virus genomic data for use in short-term forecasting to identify forthcoming surges driven by new variants. Based on our findings, the proposed forecasting framework improves upon the available forecasting tools currently used to support public health decision making with respect to COVID-19 risk.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSA systematic review of the COVID-19 forecasting and the EPIFORGE 2020 guidelines reveal the lack of consistency, reproducibility, comparability, and quality in the current COVID-19 forecasting literature. To provide an updated survey of the literature, we carried out our literature search on Google Scholar, PubMed, and medRxi, using the terms \"Covid-19,\" \"SARS-CoV-2,\" \"coronavirus,\" \"short-term,\" \"forecasting,\" and \"genomic surveillance.\" Although the literature includes a significant number of papers, it remains lacking with respect to rigorous model evaluation, interpretability and translation. Furthermore, while SARS-CoV-2 genomic surveillance is emerging as a vital necessity to fight COVID-19 (i.e. wastewater sampling and airport screening), to our knowledge, no published forecasting model has illustrated the value of virus genomic data for informing future outbreaks.\n\nAdded value of this studyWe propose a multi-stage deep learning model to forecast COVID-19 cases and deaths with a horizon window of four weeks. The data driven model relies on a comprehensive set of input features, including epidemiological, mobility, behavioral survey, climate, and demographic. We present a robust evaluation framework to systematically assess the model performance over a one-year time span, and using multiple error metrics. This rigorous evaluation framework reveals how the predictive accuracy varies over chronological time, space, and outbreak phase. Further, a comparative analysis against the CDC ensemble, the best performing model in the COVID-19 ForecastHub, shows the model to consistently outperform the CDC ensemble for all evaluation metrics in multiple spatiotemporal settings, especially for the longer forecasting windows. We also conduct a feature analysis, and show that the role of explanatory features changes over time. Specifically, we note a changing role of climate variables on model performance in the latter half of the study period. Lastly, we present a case study that reveals how incorporating SARS-CoV-2 genomic surveillance data may improve forecasting accuracy compared to a model without variant cases data.\n\nImplications of all the available evidenceResults from the robust evaluation analysis highlight extreme model performance variability over time and space, and suggest that forecasting models should be accompanied with specifications on the conditions under which they perform best (and worst), in order to maximize their value and utility in aiding public health decision making. The feature analysis reveals the complex and changing role of factors contributing to COVID-19 transmission over time, and suggests a possible seasonality effect of climate on COVID-19 spread, but only after August 2021. Finally, the case study highlights the added value of using genomic surveillance data in short-term epidemiological forecasting models, especially during the early stage of new variant introductions.", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.23.504798", + "rel_abs": "We present an integrated immunopeptidomics and proteomics study of SARS-Cov-2 infection to comprehensively decipher the changes in host cells in response to viral infection. Our results indicated that innate immune response in Calu-3 cells was initiated by TLR3, followed by activation of interferon signaling pathway. Host cells also present viral antigens to the cell surface through both Class I and Class II MHC system for recognition by adaptive immune system. SARS-Cov-2 infection led to the disruption of antigen presentation as demonstrated by higher level of HLA proteins from the flow-through of MHC immunoprecipitation. Glycosylation analysis of HLA proteins from the elution and flow-through of immunoprecipitation revealed that the synthesis and degradation of HLA protein was affected by SARS-Cov-2 infection. This study provided many useful information to study the host response to SARS-Cov-2 infection and would be helpful for the development of therapeutics and vaccine for Covid-19 and future pandemic.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Hongru Du", - "author_inst": "Johns hopkins university" + "author_name": "Rui Chen", + "author_inst": "National Research Council Canada" }, { - "author_name": "Ensheng Dong", - "author_inst": "Johns Hopkins University" + "author_name": "Kelly M Fulton", + "author_inst": "National Research Council Canada" }, { - "author_name": "Hamada S. Badr", - "author_inst": "Johns Hopkins University" + "author_name": "Anh Tran", + "author_inst": "National Reseach Council Canada" }, { - "author_name": "Mary Petrone", - "author_inst": "Yale University" + "author_name": "Diana Duque", + "author_inst": "National Research Council Canada" }, { - "author_name": "Nathan Grubaugh", - "author_inst": "Yale School of Public Health" + "author_name": "Kevin Kovalchik", + "author_inst": "CHU Sainte-Justine Research Center" }, { - "author_name": "Lauren Marie Gardner", - "author_inst": "Johns Hopkins University" + "author_name": "Etienne Caron", + "author_inst": "CHU Sainte-Justine Research Center" + }, + { + "author_name": "Susan M Twine", + "author_inst": "National Research Council Canada" + }, + { + "author_name": "Jianjun Li", + "author_inst": "National Research Council Canada" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2022.08.23.505031", @@ -200863,109 +200285,65 @@ "category": "nutrition" }, { - "rel_doi": "10.1101/2022.08.21.22278967", - "rel_title": "Proteomics Investigation of Diverse Serological Patterns in COVID-19", + "rel_doi": "10.1101/2022.08.19.22278876", + "rel_title": "Seroprevalence of anti-SARS-CoV-2 IgG antibodies in admitted patients at a tertiary referral centre in North India", "rel_date": "2022-08-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.21.22278967", - "rel_abs": "Serum antibodies IgM and IgG are elevated during COVID-19 to defend against viral attack. Atypical results such as negative and abnormally high antibody expression were frequently observed whereas the underlying molecular mechanisms are elusive. In our cohort of 144 COVID-19 patients, 3.5% were both IgM and IgG negative whereas 29.2% remained only IgM negative. The remaining patients exhibited positive IgM and IgG expression, with 9.3% of them exhibiting over 20-fold higher titers of IgM than the others at their plateau. IgG titers in all of them were significantly boosted after vaccination in the second year. To investigate the underlying molecular mechanisms, we classed the patients into four groups with diverse serological patterns and analyzed their two-year clinical indicators. Additionally, we collected 111 serum samples for TMTpro-based longitudinal proteomic profiling and characterized 1494 proteins in total. We found that the continuously negative IgM and IgG expression during COVID-19 were associated with mild inflammatory reactions and high T cell responses. Low levels of serum IgD, inferior complement 1 activation of complement cascades, and insufficient cellular immune responses might collectively lead to compensatory serological responses, causing overexpression of IgM. Serum CD163 was positively correlated with antibody titers during seroconversion. This study suggests that patients with negative serology still developed cellular immunity for viral defense, and that high titers of IgM might not be favorable to COVID-19 recovery.", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.19.22278876", + "rel_abs": "BackgroundSeroprevalence of IgG antibodies against SARS-CoV-2 is an important tool to estimate true burden of infection in a given population. Serosurveys, though being conducted in different parts of India, are not readily published in entirety and often do not report on the different characteristics of the population studied. In this present study, we aimed to serially estimate the seroprevalence of anti-SARS-CoV-2 IgG antibody over 11 months at one of the largest government hospital in India.\n\nMethodIn this cross-sectional study which was conducted between between 9th June 2020 and 27th April 2021, consecutive patients admitted to medicine wards or intensive care units, who were negative for SARS-CoV-2 by RT-PCR or CBNAAT were included. The 2linic-demographic features of the subjects were recorded in pre-formed questionnaires. Anti-SARS-CoV2 antibody levels targeting recombinant spike receptor-binding domain (RBD) protein of SARS CoV-2 were estimated in serum sample by the ELISA method.\n\nResultsA total of 916 patients were recruited over 11 months with mean age({+/-}SD) 39.79{+/-}14.9 of years and 55% of population being males. In total 264(28.8%) patients were found to be seropositive. Residency in Delhi and non-smoking status conferred a higher risk for seropositivity. The adjusted odds ratio for seropositivity with regards to no smoking and residence out of Delhi were .31{+/-}.09 (Odds ratio {+/-} S.E) and .65 {+/-} .1 (Odds ratio {+/-} S.E) respectively. No other factors like age, socio-economic status, contact history etc showed significant relationship with seropositivity.\n\nConclusionThe seropositivity rate among hospitalized patients was found to increase with time (from 8.45% to 38%) over a period of 9 months. Residence in Delhi and non-smokers had higher risk for seropositivity on multivariate analysis.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Xiao Liang", - "author_inst": "Westlake University" - }, - { - "author_name": "Rui Sun", - "author_inst": "Westlake University" - }, - { - "author_name": "Jing Wang", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" - }, - { - "author_name": "Kai Zhou", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" - }, - { - "author_name": "Jun Li", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" - }, - { - "author_name": "Shiyong Chen", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" - }, - { - "author_name": "Mengge Lyu", - "author_inst": "Westlake University" - }, - { - "author_name": "Sainan Li", - "author_inst": "Westlake University" - }, - { - "author_name": "Zhangzhi Xue", - "author_inst": "Westlake University" - }, - { - "author_name": "Yingqiu Shi", - "author_inst": "Westlake University" - }, - { - "author_name": "Yuting Xie", - "author_inst": "Westlake University" - }, - { - "author_name": "Qiushi Zhang", - "author_inst": "Westlake Omics Biotechnology Co., Ltd." + "author_name": "Animesh Ray", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Xiao Yi", - "author_inst": "Westlake Omics Biotechnology Co., Ltd." + "author_name": "Komal Singh", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Juan Pan", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" + "author_name": "Farha Mehdi", + "author_inst": "Translational Health Science and Technology Institute, Faridabad, Haryana" }, { - "author_name": "Donglian Wang", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" + "author_name": "Souvick Chattopadhyay", + "author_inst": "Translational Health Science and Technology Institute, Faridabad, Haryana" }, { - "author_name": "Jiaqin Xu", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" + "author_name": "Ranveer Singh Jadon", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Hongguo Zhu", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" + "author_name": "Neeraj Nischal", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Guangjun Zhu", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" + "author_name": "Manish Soneja", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Jiansheng Zhu", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" + "author_name": "Prayas Sethi", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Yi Zhu", - "author_inst": "Westlake University" + "author_name": "Ved Prakash Meena", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Yufen Zheng", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" + "author_name": "Anjan Trikha", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Bo Shen", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" + "author_name": "Gaurav Batra", + "author_inst": "Translational Health Science and Technology Institute, Faridabad, Haryana" }, { - "author_name": "Tiannan Guo", - "author_inst": "Westlake University" + "author_name": "Naveet Wig", + "author_inst": "All India Institute of Medical Sciences, New Delhi" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -202669,79 +202047,55 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.08.17.22278894", - "rel_title": "Cohort monitoring of 29 Adverse Events of Special Interest prior to and after COVID-19 vaccination in four large European electronic healthcare data sources", - "rel_date": "2022-08-20", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.17.22278894", - "rel_abs": "SettingPrimary and/or secondary health care data from four European countries: Italy, the Netherlands, the United Kingdom, Spain\n\nParticipantsIndividuals with complete data for the year preceding enrollment or those born at the start of observation time. The cohort comprised 25,720,158 subjects.\n\nInterventionsFirst and second dose of Pfizer, AstraZeneca, Moderna, or Janssen COVID-19 vaccine.\n\nMain outcome measures29 adverse events of special interest (AESI): acute aseptic arthritis, acute coronary artery disease, acute disseminated encephalomyelitis (ADEM), acute kidney injury, acute liver injury, acute respiratory distress syndrome, anaphylaxis, anosmia or ageusia, arrhythmia, Bells palsy, chilblain-like lesions death, erythema multiforme, Guillain Barre Syndrome (GBS), generalized convulsion, haemorrhagic stroke, heart failure, ischemic stroke, meningoencephalitis, microangiopathy, multisystem inflammatory syndrome, myo/pericarditis, myocarditis, narcolepsy, single organ cutaneous vasculitis (SOCV), stress cardiomyopathy, thrombocytopenia, thrombotic thrombocytopenia syndrome (TTS) venous thromboembolism (VTE)\n\nResults12,117,458 individuals received at least a first dose of COVID-19 vaccine: 54% with Comirnaty (Pfizer), 6% Spikevax (Moderna), 38% Vaxzevria (AstraZeneca) and 2% Janssen Covid-19 vaccine. AESI were very rare <10/100,000 PY in 2020, only thrombotic and cardiac events were uncommon. After adjustment for factors associated with severe COVID, 10 statistically significant associations of pooled incidence rate ratios remained based on dose 1 and 2 combined. These comprised anaphylaxis after AstraZeneca vaccine, TTS after both AstraZeneca and Janssen vaccine, erythema multiforme after Moderna, GBS after Janssen vaccine, SOCV after Janssen vaccine, thrombocytopenia after Janssen and Moderna vaccine and VTE after Moderna and Pfizer vaccines. The pooled rate ratio was more than two-fold increased only for TTS, SOCV and thrombocytopenia.\n\nConclusionWe showed associations with several AESI, which remained after adjustment for factors that determined vaccine roll out. Hypotheses testing studies are required to establish causality.", - "rel_num_authors": 15, + "rel_doi": "10.1101/2022.08.18.504268", + "rel_title": "A syntenin inhibitor blocks endosomal entry of SARS-CoV-2 and a panel of RNA viruses", + "rel_date": "2022-08-19", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.18.504268", + "rel_abs": "Viruses are dependent on interactions with host factors in order to efficiently establish an infection and replicate. Targeting such interactions provides an attractive strategy to develop novel antivirals. Syntenin is a protein known to regulate the architecture of cellular membranes by its involvement in protein trafficking, and has previously been shown to be important for HPV infection. Here we show that a highly potent and metabolically stable peptide inhibitor that binds to the PDZ1 domain of syntenin inhibits SARS-CoV-2 infection by blocking the endosomal entry of the virus. Furthermore, we found that the inhibitor also hampered chikungunya infection, and strongly reduced flavivirus infection, which are completely dependent on receptor mediated endocytosis for their entry. In conclusion, we have identified a novel pan-viral inhibitor that efficiently target a broad range of RNA viruses.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Miriam CJM Sturkenboom", - "author_inst": "University Medical Center Utrecht, department of Data Science and Biostatistics, The Netherlands" - }, - { - "author_name": "Davide Messina", - "author_inst": "Agenzia Regionale di Sanita, Toscana, Italy" - }, - { - "author_name": "Olga Paoletti", - "author_inst": "Agenzia Regionale di Sanita, Toscana, Italy" - }, - { - "author_name": "Airam Burgos Gonzalez", - "author_inst": "Spanish Agency for Medicines and Medical Devices (AEMPS), Madrid, Spain" - }, - { - "author_name": "Patricia Garcia-Poza", - "author_inst": "Spanish Agency for Medicines and Medical Devices (AEMPS), Madrid, Spain" - }, - { - "author_name": "Ana Llorente- Garcia", - "author_inst": "Spanish Agency for Medicines and Medical Devices (AEMPS), Madrid, Spain" - }, - { - "author_name": "Consuelo Huerta", - "author_inst": "Spanish Agency for Medicines and Medical Devices (AEMPS), Madrid, Spain" + "author_name": "Richard Lindqvist", + "author_inst": "Umea University" }, { - "author_name": "Mar Martin-Perez", - "author_inst": "Spanish Agency for Medicines and Medical Devices (AEMPS), Madrid, Spain" + "author_name": "Caroline Benz", + "author_inst": "Uppsala University" }, { - "author_name": "Ivonne Martin", - "author_inst": "Department of Datascience & Biostatistics, Julius Center for Health Sciences and Primary Health. University Medical Center Utrecht, The Netherlands" + "author_name": "Vita Sereikaite", + "author_inst": "Copenhagen University" }, { - "author_name": "Jetty Overbeek", - "author_inst": "PHARMO Institute for Drug Outcomes Research, Utrecht, the Netherlands" + "author_name": "Lars Maassen", + "author_inst": "Uppsala University" }, { - "author_name": "Marc Padros-Goossens", - "author_inst": "Department of Datascience & Biostatistics, Julius Center for Health Sciences and Primary Health. University Medical Center Utrecht, The Netherlands" + "author_name": "Louise Laursen", + "author_inst": "Uppsala University" }, { - "author_name": "Patrick Souverein", - "author_inst": "Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, The Netherlands" + "author_name": "Per Jemth", + "author_inst": "Uppsala University" }, { - "author_name": "Karin Swart-Polinder", - "author_inst": "PHARMO Institute for Drug Outcomes Research, Utrecht, the Netherlands" + "author_name": "Kristian Stromgaard", + "author_inst": "University of Copenhagen" }, { - "author_name": "Olaf Klungel", - "author_inst": "Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, The Netherlands" + "author_name": "Ylva Ivarsson", + "author_inst": "Uppsala University" }, { - "author_name": "Rosa Gini", - "author_inst": "Agenzia Regionale di Sanita, Florence Toscana, Italy" + "author_name": "Anna K Overby", + "author_inst": "Umea university" } ], "version": "1", - "license": "cc_by_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "biochemistry" }, { "rel_doi": "10.1101/2022.08.17.504362", @@ -204299,113 +203653,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.08.12.22278720", - "rel_title": "Dynamics of SARS-CoV-2 VOC neutralization and novel mAb reveal protection against Omicron", + "rel_doi": "10.1101/2022.08.12.22278567", + "rel_title": "Performance of the Cue COVID-19 Molecular Test for Point of Care: Insights from a multi-site clinic service model", "rel_date": "2022-08-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.12.22278720", - "rel_abs": "To evaluate SARS-CoV-2 variants we isolated SARS-CoV-2 temporally during the pandemic starting with first appearance of virus in the Western hemisphere near Seattle, WA, USA, and isolated each known major variant class, revealing the dynamics of emergence and complete take-over of all new cases by current Omicron variants. We assessed virus neutralization in a first-ever full comparison across variants and evaluated a novel monoclonal antibody (Mab). We found that convalescence greater than 5-months provides little-to-no protection against SARS-CoV-2 variants, vaccination enhances immunity against variants with the exception of Omicron BA.1, and paired testing of vaccine sera against ancestral virus compared to Omicron BA.1 shows that 3-dose vaccine regimen provides over 50-fold enhanced protection against Omicron BA.1 compared to a 2-dose regimen. We also reveal a novel Mab that effectively neutralizes Omicron BA.1 and BA.2 variants over clinically-approved Mabs. Our observations underscore the need for continued vaccination efforts, with innovation for vaccine and Mab improvement, for protection against variants of SARS-CoV-2.\n\nSummaryWe isolated SARS-CoV-2 temporally starting with emergence of virus in the Western hemisphere. Neutralization analyses across all variant lineages show that vaccine-boost regimen provides protection against Omicron BA.1. We reveal a Mab that protects against Omicron BA.1 and BA.2 variants.", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.12.22278567", + "rel_abs": "The COVID-19 pandemic highlighted the critical need for rapid and accurate molecular diagnostic testing. The Cue COVID-19 Point of Care Test (Cue POCT) is a nucleic acid amplification test (NAAT), authorized by Health Canada and FDA as a POCT for SARS-CoV-2 detection. Cue POCT was deployed at a network of clinics in Ontario, Canada with n=13,848 patrons tested between July 17, 2021 to January 31, 2022. The clinical performance and operational experience with Cue POCT was examined for this testing population composed mostly of asymptomatic individuals (93.7%). A head-to-head prospective clinical verification was performed between July 17 to October 4 for all POCT service clients (n= 3037) with paired COVID-19 testing by Cue and RT-PCR. Prospective verification demonstrated a clinical sensitivity of 100% and clinical specificity of 99.4% for Cue COVID-19 POCT. The lack of false negatives and low false positive rate (0.64%), underscores the high accuracy (99.4%) of Cue POCT to provide rapid PCR quality results. Low error rates (cancellation rate of 0% and invalid rate of 0.63%) with the current software version were additionally noted. Together these findings highlight the value of accurate molecular COVID-19 POCT in a distributed service delivery model to rapidly detect cases in the community with the potential to curb transmission in high exposure settings (i.e. in-flight, congregate workplace and social events). The insights gleaned from this operational implementation are readily transferable to future POCT diagnostic services.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Linhui Hao", - "author_inst": "Department of Immunology, Center for Innate Immunity and Immune Disease, University of Washington, Seattle, WA" - }, - { - "author_name": "Tien-Ying Hsiang", - "author_inst": "Department of Immunology, Center for Innate Immunity and Immune Disease, University of Washington, Seattle, WA" - }, - { - "author_name": "Ronit R. Dalmat", - "author_inst": "International Clinical Research Center, Department of Global Health, Schools of Medicine and Public Health, University of Washington, Seattle, WA" - }, - { - "author_name": "Renee Ireton", - "author_inst": "Department of Immunology, Center for Innate Immunity and Immune Disease, University of Washington, Seattle, WA" - }, - { - "author_name": "Jennifer Morton", - "author_inst": "International Clinical Research Center, Department of Global Health, Schools of Medicine and Public Health, University of Washington, Seattle, WA" - }, - { - "author_name": "Caleb Stokes", - "author_inst": "Department of Immunology, Center for Innate Immunity and Immune Disease, University of Washington, Seattle, WA" - }, - { - "author_name": "Jason Netland", - "author_inst": "Department of Immunology, Center for Innate Immunity and Immune Disease, University of Washington, Seattle, WA" - }, - { - "author_name": "Malika Hale", - "author_inst": "Department of Immunology, Center for Innate Immunity and Immune Disease, University of Washington, Seattle, WA" - }, - { - "author_name": "Chris Thouvenel", - "author_inst": "Department of Immunology, Center for Innate Immunity and Immune Disease, University of Washington, Seattle, WA" - }, - { - "author_name": "Anna Wald", - "author_inst": "Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA" + "author_name": "Any Rebbapragada", + "author_inst": "FH Health" }, { - "author_name": "Nicholas M Franko", - "author_inst": "Division of Allergy and Infectious Diseases, Department of Medicine, School of Medicine, University of Washington, Seattle, WA" + "author_name": "Lane Cariazo", + "author_inst": "FH Health" }, { - "author_name": "Kristen Huden", - "author_inst": "Division of Allergy and Infectious Diseases, Department of Medicine, School of Medicine, University of Washington, Seattle, WA" + "author_name": "David Elchuk", + "author_inst": "FH Health" }, { - "author_name": "Helen Chu", - "author_inst": "Division of Allergy and Infectious Diseases, Department of Medicine, School of Medicine, University of Washington, Seattle, WA" + "author_name": "Hossam Abdelrahman", + "author_inst": "FH Health" }, { - "author_name": "Alex Greninger", - "author_inst": "Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA" + "author_name": "Dang Pham", + "author_inst": "FH Health" }, { - "author_name": "Sasha Tilles", - "author_inst": "Center for Emerging & Re-emerging Infectious Diseases, University of Washington, Seattle, WA" + "author_name": "Nirochile Joseph", + "author_inst": "FH Health" }, { - "author_name": "Lynn K. Barrett", - "author_inst": "Center for Emerging & Re-emerging Infectious Diseases, University of Washington, Seattle, WA" + "author_name": "Elena Gouzenkova", + "author_inst": "FH Health" }, { - "author_name": "Wesley C. Van Voorhis", - "author_inst": "Center for Emerging & Re-emerging Infectious Diseases, University of Washington, Seattle, WA" - }, - { - "author_name": "Jennifer Munt", - "author_inst": "Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill NC" - }, - { - "author_name": "Trevor Scobey", - "author_inst": "Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill NC" - }, - { - "author_name": "Ralph S. Baric", - "author_inst": "Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill NC" - }, - { - "author_name": "David Rawlings", - "author_inst": "Department of Immunology, Center for Innate Immunity and Immune Disease, University of Washington, Seattle, WA" - }, - { - "author_name": "Marion Pepper", - "author_inst": "Department of Immunology, Center for Innate Immunity and Immune Disease, University of Washington, Seattle, WA" - }, - { - "author_name": "Paul K. Drain", - "author_inst": "International Clinical Research Center, Department of Global Health, Schools of Medicine and Public Health, University of Washington, Seattle, WA" + "author_name": "Harpreet Gill", + "author_inst": "FH Health" }, { - "author_name": "Michael Gale Jr.", - "author_inst": "Department of Immunology, Center for Innate Immunity and Immune Disease, University of Washington, Seattle, WA" + "author_name": "Peter Blecher", + "author_inst": "FH Health" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -206221,79 +205515,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.08.10.22278636", - "rel_title": "Phylodynamics of SARS-CoV-2 transmissions in France, Europe and the world during 2020", + "rel_doi": "10.1101/2022.08.10.22278643", + "rel_title": "Open Science and COVID-19 Randomized Controlled Trials: Examining Open Access, Preprinting, and Data Sharing-Related Practices During the Pandemic", "rel_date": "2022-08-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.10.22278636", - "rel_abs": "BackgroundAlthough France was one of the most affected European countries by the COVID-19 pandemic in 2020, the dynamics of SARS-CoV-2 transmissions within France, Europe and worldwide remain only partially characterized during the first year of the pandemic.\n\nMethodsHere, we analyzed GISAID deposited sequences from January to December 2020 (n = 638,706 sequences). To tackle the huge number of sequences without the bias of analyzing a single sequence subset, we produced 100 independent and randomly selected sequence datasets and related phylogenetic trees for different geographic scales (worldwide, European countries and French administrative regions) and time periods (first and second half of 2020). We applied a maximum likelihood discrete trait phylogeographic method to date transmission events and to estimate the geographic spread of SARS-CoV-2 to, from and within France, Europe and worldwide.\n\nResultsThe results unraveled two different patterns of inter- and intra-territory transmission events between the first and second half of 2020. Throughout the year, Europe was systematically associated with most of the intercontinental transmissions, for which France has played a pivotal role. SARS-CoV-2 transmissions with France were concentrated with North America and Europe (mainly Italy, Spain, United Kingdom, Belgium and Germany) during the first wave, and were limited to neighboring countries without strong intercontinental transmission during the second one. Regarding French administrative regions, the Paris area was the main source of transmissions during the first wave. But, for the second epidemic wave, it equally contributed to virus spread with Lyon and Marseille area, the two other most densely populated cities in France.\n\nConclusionBy enabling the inclusion of tens of thousands of viral sequences, this original phylogenetic strategy enabled us to robustly depict SARS-CoV-2 transmissions through France, Europe and worldwide in 2020.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.10.22278643", + "rel_abs": "The COVID-19 pandemic has brought substantial attention to the systems used to communicate biomedical research. In particular, the need to rapidly and credibly communicate research findings has led many stakeholders to encourage researchers to adopt open science practices such as posting preprints and sharing data. To examine the degree to which this has led to the adoption of such practices, we examined the \"openness\" of a sample of 539 published papers describing the results of randomized controlled trials testing interventions to prevent or treat COVID-19. The majority (56%) of the papers in this sample were free to read at the time of our investigation and 23.56% were preceded by preprints. However, there is no guarantee that the papers without an open license will be available without a subscription in the future, and only 49.61% of the preprints we identified were linked to the subsequent peer-reviewed version. Of the 331 papers in our sample with statements identifying if (and how) related datasets were available, only a paucity indicated that data was available in a repository that facilitates rapid verification and reuse. Our results demonstrate that, while progress has been made, there is still a significant mismatch between aspiration and the practice of open science in an important area of the COVID-19 literature.\n\nOpen MaterialsWe are committed to making the details of our research process as open as possible. The data and code that underlie our analyses are archived and published through the Dryad Data Repository (https://doi.org/10.5061/dryad.mkkwh7137). Documentation and instructions for manuscript screening and data extraction are available on Protocols.io (https://dx.doi.org/10.17504/protocols.io.x54v9jx7zg3e/v1). Author contributions are outlined in Supplementary Table 1.\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@774764org.highwire.dtl.DTLVardef@f03612org.highwire.dtl.DTLVardef@6e16ccorg.highwire.dtl.DTLVardef@19ac3eborg.highwire.dtl.DTLVardef@1b47f40_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOSupplementary Table 1.C_FLOATNO O_TABLECAPTIONAuthor Information and Contributions\n\nC_TABLECAPTION C_TBL", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Romain Copp\u00e9e", - "author_inst": "Universit\u00e9 Paris Cit\u00e9" - }, - { - "author_name": "Fran\u00e7ois Blanquart", - "author_inst": "Universit\u00e9 Paris Cit\u00e9" - }, - { - "author_name": "Aude Jary", - "author_inst": "Sorbonne Universit\u00e9" - }, - { - "author_name": "Valentin Leducq", - "author_inst": "Sorbonne Universit\u00e9" - }, - { - "author_name": "Valentine Marie Ferr\u00e9", - "author_inst": "Universit\u00e9 Paris Cit\u00e9" - }, - { - "author_name": "Anna Maria Franco Yusti", - "author_inst": "Universit\u00e9 Paris Cit\u00e9" - }, - { - "author_name": "L\u00e9na Daniel", - "author_inst": "Universit\u00e9 Paris Cit\u00e9" - }, - { - "author_name": "Charlotte Charpentier", - "author_inst": "Universit\u00e9 Paris Cit\u00e9" - }, - { - "author_name": "Samuel Lebourgeois", - "author_inst": "Universit\u00e9 Paris Cit\u00e9" - }, - { - "author_name": "Karen Zafilaza", - "author_inst": "Sorbonne Universit\u00e9" + "author_name": "John A Borghi", + "author_inst": "Stanford University" }, { - "author_name": "Vincent Calvez", - "author_inst": "Sorbonne Universit\u00e9" + "author_name": "Cheyenne Payne", + "author_inst": "Stanford University" }, { - "author_name": "Diane Descamps", - "author_inst": "Universit\u00e9 Paris Cit\u00e9" + "author_name": "Lily Ren", + "author_inst": "Stanford University" }, { - "author_name": "Anne-Genevi\u00e8ve Marcelin", - "author_inst": "Sorbonne Universit\u00e9" + "author_name": "Amanda L Woodward", + "author_inst": "Stanford University" }, { - "author_name": "Benoit Visseaux", - "author_inst": "Universit\u00e9 Paris Cit\u00e9" + "author_name": "Connie Wong", + "author_inst": "Stanford University" }, { - "author_name": "Antoine Bridier-Nahmias", - "author_inst": "Universit\u00e9 Paris Cit\u00e9" + "author_name": "Christopher Stave", + "author_inst": "Stanford University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "health policy" }, { "rel_doi": "10.1101/2022.08.08.22278550", @@ -208703,59 +207961,103 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.08.08.503256", - "rel_title": "Activation of the urotensin-II receptor by anti-COVID-19 drug remdesivir induces cardiomyocyte dysfunction", + "rel_doi": "10.1101/2022.08.08.503239", + "rel_title": "A replicon RNA vaccine induces durable protective immunity from SARS-CoV-2 in nonhuman primates after neutralizing antibodies have waned", "rel_date": "2022-08-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.08.503256", - "rel_abs": "Remdesivir is an antiviral drug used for COVID-19 treatment worldwide. Cardiovascular (CV) side effects have been associated with remdesivir; however, the underlying molecular mechanism remains unknown. Here, we performed a large-scale G-protein-coupled receptor (GPCR) screening in combination with structural modeling and found that remdesivir is a selective agonist for urotensin-II receptor (UTS2R). Functionally, remdesivir treatment induced prolonged field potential in human induced pluripotent stem cell (iPS)-derived cardiomyocytes and reduced contractility in neonatal rat cardiomyocytes, both of which mirror the clinical pathology. Importantly, remdesivir-mediated cardiac malfunctions were effectively attenuated by antagonizing UTS2R signaling. Finally, we characterized the effect of 110 single-nucleotide variants (SNVs) in UTS2R gene reported in genome database and found four missense variants that show gain-of-function effects in the receptor sensitivity to remdesivir. Collectively, our study illuminates a previously unknown mechanism underlying remdesivir-related CV events and that genetic variations of UTS2R gene can be a potential risk factor for CV events during remdesivir treatment, which collectively paves the way for a therapeutic opportunity to prevent such events in the future.\n\nOne Sentence SummaryRemdesivir s activity as a selective agonist of urotensin-II receptor underlies its known cardiotoxicity in anti-viral therapy.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.08.503239", + "rel_abs": "The global SARS-CoV-2 pandemic prompted rapid development of COVID-19 vaccines. Although several vaccines have received emergency approval through various public health agencies, the SARS-CoV-2 pandemic continues. Emergent variants of concern, waning immunity in the vaccinated, evidence that vaccines may not prevent transmission and inequity in vaccine distribution have driven continued development of vaccines against SARS-CoV-2 to address these public health needs. In this report, we evaluated a novel self-amplifying replicon RNA vaccine against SARS-CoV-2 in a pigtail macaque model of COVID-19 disease. We found that this vaccine elicited strong binding and neutralizing antibody responses. While binding antibody responses were sustained, neutralizing antibody waned to undetectable levels after six months but were rapidly recalled and conferred protection from disease when the animals were challenged 7 months after vaccination as evident by reduced viral replication and pathology in the lower respiratory tract, reduced viral shedding in the nasal cavity and lower concentrations of pro-inflammatory cytokines in the lung. Cumulatively, our data demonstrate in pigtail macaques that a self-amplifying replicon RNA vaccine can elicit durable and protective immunity to SARS-CoV-2 infection. Furthermore, these data provide evidence that this vaccine can provide durable protective efficacy and reduce viral shedding even after neutralizing antibody responses have waned to undetectable levels.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Fan-Yan Wei", - "author_inst": "Institute of Development, Aging and Cancer, Tohoku University" + "author_name": "David W. Hawman", + "author_inst": "Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rocky Mountain La" }, { - "author_name": "Asuka Inoue", - "author_inst": "Tohoku University" + "author_name": "Kimberly Meade-White", + "author_inst": "Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rocky Mountain La" }, { - "author_name": "Akiko Ogawa", - "author_inst": "Tohoku University" + "author_name": "Shanna Leventhal", + "author_inst": "Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rocky Mountain La" }, { - "author_name": "Seiya Ohira", - "author_inst": "Tohoku University" + "author_name": "Wenjun Song", + "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (Seattle, Washington)" }, { - "author_name": "Tatsuya Ikuta", - "author_inst": "Tohoku University" + "author_name": "Samantha Randall", + "author_inst": "HDT Bio (1616 Eastlake Ave E #280, Seattle, Washington)" }, { - "author_name": "Yuri Kato", - "author_inst": "Kyushu University" + "author_name": "Jacob Archer", + "author_inst": "HDT Bio (1616 Eastlake Ave E #280, Seattle, Washington)" }, { - "author_name": "Shota Yanagida", - "author_inst": "National Institute of Health Sciences" + "author_name": "Thomas B. Lewis", + "author_inst": "Department of Microbiology, University of Washington (750 Republican St., Seattle, Washington)" }, { - "author_name": "Yukina Ishii", - "author_inst": "Kyushu University" + "author_name": "Brieann Brown", + "author_inst": "Department of Microbiology, University of Washington (750 Republican St., Seattle, Washington)" }, { - "author_name": "Yasunari Kanda", - "author_inst": "National Institute of Health Sciences" + "author_name": "Naoto Iwayama", + "author_inst": "Washington National Primate Research Center, University of Washington (1705 NE Pacific Street, Seattle, Washington)" }, { - "author_name": "Motohiro Nishida", - "author_inst": "Kyushu university" + "author_name": "Chul Ahrens", + "author_inst": "Washington National Primate Research Center, University of Washington (1705 NE Pacific Street, Seattle, Washington)" + }, + { + "author_name": "William Garrison", + "author_inst": "Washington National Primate Research Center, University of Washington (1705 NE Pacific Street, Seattle, Washington)" + }, + { + "author_name": "Solomon Wangari", + "author_inst": "Washington National Primate Research Center, University of Washington (1705 NE Pacific Street, Seattle, Washington)" + }, + { + "author_name": "Kathryn A. Guerriero", + "author_inst": "Washington National Primate Research Center, University of Washington (1705 NE Pacific Street, Seattle, Washington)" + }, + { + "author_name": "Patrick Hanley", + "author_inst": "Rocky Mountain Veterinary Branch, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rocky M" + }, + { + "author_name": "Jamie Lovaglio", + "author_inst": "Rocky Mountain Veterinary Branch, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rocky M" + }, + { + "author_name": "Greg Saturday", + "author_inst": "Rocky Mountain Veterinary Branch, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rocky M" + }, + { + "author_name": "Paul T. Edlefsen", + "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (Seattle, Washington)" + }, + { + "author_name": "Amit Khandhar", + "author_inst": "HDT Bio (1616 Eastlake Ave E #280, Seattle, Washington)" + }, + { + "author_name": "Heinz Feldmann", + "author_inst": "Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rocky Mountain La" + }, + { + "author_name": "Deborah Heydenburg Fuller", + "author_inst": "Department of Microbiology, University of Washington (750 Republican St., Seattle, Washington)" + }, + { + "author_name": "Jesse H. Erasmus", + "author_inst": "HDT Bio (1616 Eastlake Ave E #280, Seattle, Washington)" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "pharmacology and toxicology" + "category": "immunology" }, { "rel_doi": "10.1101/2022.08.08.503231", @@ -210709,23 +210011,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.08.08.503157", - "rel_title": "Protein Geometry, Function and Mutation", + "rel_doi": "10.1101/2022.08.04.22278404", + "rel_title": "A Plagiarism Paperdemic - Plagiarism in infection journals in the era of COVID-19", "rel_date": "2022-08-08", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.08.503157", - "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWThis survey for mathematicians summarizes several works by the author on protein geometry and protein function with applications to viral glycoproteins in general and the spike glycoprotein of the SARS-CoV-2 virus in particular. Background biology and biophysics are sketched. This body of work culminates in a postulate that protein secondary structure regulates mutation, with backbone hydrogen bonds materializing in critical regions to avoid mutation, and disappearing from other regions to enable it.", - "rel_num_authors": 1, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.04.22278404", + "rel_abs": "BackgroundThe COVID-19 pandemic has caused drastic changes in the publishing framework in order to quickly review and publish vital information during this public health emergency. The quality of the academic work being published may have been compromised. One area of concern is plagiarism, where the work of others is directly copied and represented as ones own. The purpose of this study is to determine the presence of plagiarism in infection journals in papers relating to the COVID-19 pandemic.\n\nMethodsConsecutively occurring original research or reviews relating to the COVID-19 pandemic, published in infection journals as ranked by SCOPUS Journal finder were collected. Each manuscript was optimized and uploaded to the Turnitin program. Similarity reports were then manually checked for true plagiarism within the text, where any sentence with more than 80% copying was deemed plagiarised.\n\nResultsA total of 310 papers were analyzed in this cross-sectional study. Papers from a total of 23 journals among 4 quartiles were examined. Of the papers we examined, 41.6% were deemed plagiarised (n=129). Among the plagiarised papers, the average number of copied sentences was 5.42{+/-}9.18. The highest recorded similarity report was 60%, and the highest number of copied sentences was 85. Plagiarism was higher in papers published in the year 2020. The most problematic area in the manuscripts was the discussion section. Self plagiarism was identified in 31 papers. Average time to judge all manuscripts was 2.45{+/-}3.09. Among all the plagiarized papers 72% belonged to papers where the similarity report was [≤]15% (n=93). Papers published from core anglosphere speaking countries were not associated with higher rates of plagiarism. No significant differences were found with regards to plagiarism events among the quartiles.\n\nConclusionPlagiarism is prevalent in COVID19 related publications in infection journals among various quartiles. It is not enough to rely only on similarity reports. Such reports must be accompanied by manual curation of the results with an appropriate threshold to be able to appropriately determine if plagiarism is occurring. The majority of plagiarism is occurring in reports of less than 15% similarity, and this is a blind spot. Incorporating a manual judge could save future time in avoiding retractions and improving the quality of papers in these journals.\n\n\"A poor original is better than a good imitation.\"\n\n-- Ella Wheeler Wilcox", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Robert Clark Penner", - "author_inst": "Institut des Hautes Etudes Scientifiques" + "author_name": "Rahma Menshawey", + "author_inst": "Cairo University Kasr al Ainy Faculty of Medicine" + }, + { + "author_name": "Esraa Menshawey", + "author_inst": "Cairo University Kasr Al Ainy School of Medicine" + }, + { + "author_name": "Ahmed Mitkees", + "author_inst": "Cairo University Kasr al Ainy Faculty of Medicine" + }, + { + "author_name": "Bilal A Mahamud", + "author_inst": "Cairo University Kasr al Ainy Faculty of Medicine" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "biophysics" + "type": "PUBLISHAHEADOFPRINT", + "category": "medical ethics" }, { "rel_doi": "10.1101/2022.08.06.22278449", @@ -212871,115 +212185,59 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.08.03.22278304", - "rel_title": "The association between experience of COVID-19-related discrimination and psychological distress among healthcare workers for six national medical research centers in Japan", + "rel_doi": "10.1101/2022.08.03.22278392", + "rel_title": "Association of mortality and aspirin use for COVID-19 residents at VA Community Living Center Nursing Homes", "rel_date": "2022-08-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.03.22278304", - "rel_abs": "BackgroundDiscrimination has been identified as an important determinant of negative mental health outcomes. This study determined the association between the experience of COVID-19-related discrimination and psychological distress among healthcare workers (HCWs) in Japan.\n\nMethodsThis cross-sectional study conducted a health survey among 5,703 HCWs of six national medical and research centers in Japan from October 2020 to March 2021. COVID-19-related discrimination was defined either when participants or their family members were badmouthed or when they felt discriminated against in some way. We used the Kessler Psychological Distress Scale (K6) to assess the presence of severe psychological distress ([≥]13 points). We used logistic regression models to examine the association between discrimination and psychological distress. We also identified job-related factors associated with discrimination.\n\nResultsOf the participants, 484 (8.4%) reported COVID-19-related discrimination and 486 (8.5%) had severe psychological distress. HCWs who were female vs. male (odds ratio [OR]=1.41, 95% confidence interval [CI]=1.28-1.55), had high vs. low viral exposure (OR=2.31, 95%CI=1.81-2.93), and worked for more than 10 hours/day vs. <8 hours/day (OR=1.42, 95%CI=1.35-1.49) were more likely to have experienced COVID-19-related discrimination. The OR (95%CI) of severe psychological distress was 1.83 (1.29-2.59) among those who experienced discrimination. The analysis was stratified by sociodemographic and job-related factors and the associations trended in the same direction across subgroups.\n\nConclusionExperience of COVID-19-related discrimination was associated with severe psychological distress among HCWs. During the pandemic, effective measures should be taken to prevent the development of negative mental health outcomes in HCWs who experience discrimination.", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.03.22278392", + "rel_abs": "Background/ObjectivesCoronavirus disease 2019 (COVID-19) is associated with a hypercoagulable state and increased thrombotic risk in infected individuals. Several complex and varied coagulation abnormalities were proposed for this association1. Acetylsalicylic acid(ASA, aspirin) is known to have inflammatory, antithrombotic properties and its use was reported as having potency to reduce RNA synthesis and replication of some types of coronaviruses including human coronavirus-299E (CoV-229E) and Middle East Respiratory Syndrome (MERS)-CoV 2,3. We hypothesized that chronic low dose aspirin use may decrease COVID-19 mortality relative to ASA non-users.\n\nMethodsThis is a retrospective, observational cohort analysis of residents residing at Veterans Affairs Community Living Centers from December 13, 2020, to September 18, 2021, with a positive SARS-CoV-2 PCR test. Low dose aspirin users had low dose (81mg) therapy (10 of 14 days) prior to the positive COVID date and were compared to aspirin non-users (no ASA in prior 14 days). The primary outcome was mortality at 30 and 56 days post positive test and hospitalization.\n\nResultsWe identified 1.823 residents who had SARS-CoV-2 infection and 1,687 residents were eligible for the study. Aspirin use was independently associated with a reduced risk of 30 days of mortality (adjusted HR, 0.60, 95% CI, 0.40-0.90) and 56 days of mortality (adjusted HR, 0.67, 95% CI, 0.47-0.95)\n\nConclusionChronic low dose aspirin use for primary or secondary prevention of cardiovascular events is associated with lower COVID-19 mortality. Although additional randomized controlled trials are required to understand these associations and the potential implications more fully for improving care, aspirin remains a medication with known side effects and clinical practice should not change based on these findings.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Rachana Manandhar Shrestha", - "author_inst": "National Center for Global Health and Medicine" - }, - { - "author_name": "Yosuke Inoue", - "author_inst": "National Center for Global Health and Medicine" - }, - { - "author_name": "Shohei Yamamoto", - "author_inst": "National Center for Global Health and Medicine" - }, - { - "author_name": "Ami Fukunaga", - "author_inst": "National Center for Global Health and Medicine" - }, - { - "author_name": "Makiko Sampei", - "author_inst": "Nippon Sport Science University" - }, - { - "author_name": "Ryo Okubo", - "author_inst": "National Center of Neurology and Psychiatry" - }, - { - "author_name": "Naho Morisaki", - "author_inst": "National Research Institute for Child Health and Development" - }, - { - "author_name": "Norio Ohmagari", - "author_inst": "National Center for Global Health and Medicine" - }, - { - "author_name": "Takanori Funaki", - "author_inst": "National Center for Child Health and Development" - }, - { - "author_name": "Kazue Ishitsuka", - "author_inst": "National Research Institute for Child Health and Development, Tokyo" - }, - { - "author_name": "Koushi Yamaguchi", - "author_inst": "National Center for Child Health and Development" - }, - { - "author_name": "Yohei Sasaki", - "author_inst": "National Center of Neurology and Psychiatry" - }, - { - "author_name": "Kazuyoshi Takeda", - "author_inst": "National Center of Neurology and Psychiatry" - }, - { - "author_name": "Takeshi Miyama", - "author_inst": "National Center of Neurology and Psychiatry" - }, - { - "author_name": "Masayo Kojima", - "author_inst": "National Center for Geriatrics and Gerontology" + "author_name": "Yasin Abul", + "author_inst": "Center of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, RI and Division of Geriatric and Palliative Medicine, Warren " }, { - "author_name": "Takeshi Nakagawa", - "author_inst": "National Center for Geriatrics and Gerontology" + "author_name": "Frank Devone", + "author_inst": "Center of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, RI" }, { - "author_name": "Kunihiro Nishimura", - "author_inst": "National Cerebral and Cardiovascular Center" + "author_name": "Thomas Bayer", + "author_inst": "Center of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, RI" }, { - "author_name": "Soshiro Ogata", - "author_inst": "National Cerebral and Cardiovascular Center" + "author_name": "Christopher Halladay", + "author_inst": "Center of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, RI" }, { - "author_name": "Jun Umezawa", - "author_inst": "National Cancer Center" + "author_name": "Kevin McConeghy", + "author_inst": "Center of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, RI" }, { - "author_name": "Shiori Tanaka", - "author_inst": "National Cancer Center" + "author_name": "Nadia Mujahid", + "author_inst": "Division of Geriatric and Palliative Medicine, Warren Alpert Medical School of Brown University, Providence, RI" }, { - "author_name": "Manami Inoue", - "author_inst": "National Cancer Center" + "author_name": "Mriganka Singh", + "author_inst": "Division of Geriatric and Palliative Medicine, Warren Alpert Medical School of Brown University, Providence, RI" }, { - "author_name": "Maki Konishi", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "Ciera Leeder", + "author_inst": "Division of Geriatric and Palliative Medicine, Warren Alpert Medical School of Brown University, Providence, RI" }, { - "author_name": "Kengo Miyo", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "Stefan Gravenstein", + "author_inst": "Center of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, RI and Division of Geriatric and Palliative Medicine, Warren " }, { - "author_name": "Tetsuya Mizoue", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "James L Rudolph", + "author_inst": "Center of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, RI and Division of Geriatric and Palliative Medicine, Warren " } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "geriatric medicine" }, { "rel_doi": "10.1101/2022.08.03.22278363", @@ -214613,43 +213871,103 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.08.01.22278264", - "rel_title": "Does Influenza vaccination reduce the risk of contracting COVID-19?", + "rel_doi": "10.1101/2022.08.01.502390", + "rel_title": "SARS-CoV-2 Omicron BA.1 and BA.2 are attenuated in rhesus macaques as compared to Delta", "rel_date": "2022-08-02", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.01.22278264", - "rel_abs": "The concurrent timing of the COVID-19 pandemic and the seasonal occurrence of influenza, makes it especially important to analyze the possible effect of the influenza vaccine on the risk of contracting COVID-19, or in reducing the complications caused by both diseases, especially in vulnerable populations. There is very little scientific information on the possible protective role of the influenza vaccine against the risk of contracting COVID-19, particularly in groups at high-risk of influenza complications. Reducing the risk of contracting COVID-19 in high-risk patients (those with a higher risk of infection, complications, and death) is essential to improve public well-being and to reduce hospital pressure and the collapse of primary health centers. Apart from overlapping in time, COVID-19 and flu share common aspects of transmission, so that measures to protect against flu might be effective in reducing the risk of contracting COVID-19.\n\nIn this study, we conclude that the risk of contracting COVID-19 is reduced if patients are vaccinated against flu, but the reduction is small (0.22%) and therefore not clinically important. When this reduction is analysed based on the risk factor suffered by the patient, statistically significant differences have been obtained for patients with cardiovascular problems, diabetics, chronic lung and chronic kidney, in all four cases the reduction in the risk of contagion does not reach 1%.\n\nIt is worth highlighting the behaviour that is completely different from the rest of the data for institutionalized patients. The data for these patients does not suggest a reduction in the risk of contagion for patients vaccinated against the flu, but rather the opposite, a significant increase of 6%.\n\nSocioeconomic conditions, as measured by the MEDEA deprivation index, explain increases in the risk of contracting COVID-19, and awareness campaigns should be increased to boost vaccination programs.", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.01.502390", + "rel_abs": "Since the emergence of SARS-CoV-2, five different variants of concern (VOCs) have been identified: Alpha, Beta, Gamma, Delta, and Omicron. Due to confounding factors in the human population, such as pre-existing immunity, comparing severity of disease caused by different VOCs is challenging. Here, we investigate disease progression in the rhesus macaque model upon inoculation with the Delta, Omicron BA.1, and Omicron BA.2 VOCs. Disease severity in rhesus macaques inoculated with Omicron BA.1 or BA.2 was lower than those inoculated with Delta and resulted in significantly lower viral loads in nasal swabs, bronchial cytology brush samples, and lung tissue in rhesus macaques. Cytokines and chemokines were upregulated in nasosorption samples of Delta animals compared to Omicron BA.1 and BA.2 animals. Overall, these data suggests that in rhesus macaques, Omicron replicates to lower levels than the Delta VOC, resulting in reduced clinical disease.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Francesc Alos", - "author_inst": "Institut Catala de la Salut" + "author_name": "Neeltje van Doremalen", + "author_inst": "NIH" }, { - "author_name": "Yoseba Canovas-Zaldua", - "author_inst": "Institut Catala de la Salut" + "author_name": "Manmeet Singh", + "author_inst": "NIH" }, { - "author_name": "M Victoria Feijoo", - "author_inst": "Institut Catala de la Salut" + "author_name": "Taylor Saturday", + "author_inst": "NIH" }, { - "author_name": "Jose Luis del val", - "author_inst": "Institut Catala de la Salut" + "author_name": "Kwe Claude Yinda", + "author_inst": "NIH" }, { - "author_name": "Andrea Sanchez-Callejas", - "author_inst": "Institut Catala de la Salut" + "author_name": "Lizzette Perez-Perez", + "author_inst": "NIH" + }, + { + "author_name": "W. Forrest Bohler", + "author_inst": "NIH" + }, + { + "author_name": "Zack Weishampel", + "author_inst": "NIH" }, { - "author_name": "M Angels Colomer", - "author_inst": "Department of Mathematics ETSEA, University of Lleida, 25198, Lleida, Spain" + "author_name": "Matthew Lewis", + "author_inst": "NIH" + }, + { + "author_name": "Jonathan Schulz", + "author_inst": "NIH" + }, + { + "author_name": "Brandi Williamson", + "author_inst": "NIH" + }, + { + "author_name": "Kimberly Meade-White", + "author_inst": "NIAID/NIH" + }, + { + "author_name": "Shane Gallogly", + "author_inst": "NIH" + }, + { + "author_name": "Atsushi Okumura", + "author_inst": "NIAID/NIH" + }, + { + "author_name": "Friederike Feldmann", + "author_inst": "NIAID/NIH" + }, + { + "author_name": "Jamie Lovaglio", + "author_inst": "National Institute of Allergy and Infectious Diseases" + }, + { + "author_name": "Patrick Hanley", + "author_inst": "National Institute of Allergy and Infectious Diseases" + }, + { + "author_name": "Carl Shaia", + "author_inst": "NIAID/NIH" + }, + { + "author_name": "Heinz Feldmann", + "author_inst": "NIAID, NIH" + }, + { + "author_name": "Emmie de Wit", + "author_inst": "NIAID, NIH" + }, + { + "author_name": "Vincent Munster", + "author_inst": "NIAID" + }, + { + "author_name": "Kyle Rosenke", + "author_inst": "NIAID" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "primary care research" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2022.08.02.502439", @@ -216519,35 +215837,39 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2022.07.28.22278140", - "rel_title": "Institutional trust in times of Corona", + "rel_doi": "10.1101/2022.07.30.22278240", + "rel_title": "Modelling the role of quarantine escapees on COVID-19 dynamics", "rel_date": "2022-07-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.28.22278140", - "rel_abs": "During the corona pandemic, governments of all countries appealed strongly to the trust of their populations by implementing drastic social and economic measures to prevent the spread of the virus. This study seeks to understand mechanisms that influence the level of institutional trust at the time of the corona pandemic. We are specifically interested in how three explanatory factors (socioeconomic status, experienced economic insecurity and dissatisfaction with the implemented corona policies) can, in mutual association, explain differences in institutional trust. This study is based on data from a large-scale panel survey on the social impact of COVID-19, carried out by Kieskompas research agency (N=22,696). Using a serial mediation analysis, we show that SES has both a direct and indirect effect on the level of institutional trust. People with higher SES experience less economic insecurity and have less dissatisfaction with the corona policies and, partly as a result of this, stronger institutional trust. It is also true that economic insecurity increases dissatisfaction with the corona policies and, partly as a result of this, weakens the level of trust.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.30.22278240", + "rel_abs": "The recent outbreak of the novel coronavirus (COVID-19) pandemic which originated from the Wuhan City of China has devastated many parts of the globe. At present, non-pharmaceutical interventions are the widely available measures being used in combating and controlling this disease. There is great concern over the rampant unaccounted cases of individuals skipping the border during this critical period in time. We develop a deterministic compartmental model to investigate the impact of escapees on the transmission dynamics of COVID-19 in Zimbabwe. A suitable Lyapunov function has been used to show that the disease-free equilibrium is globally asymptotically stable provided [R]0 < 1. We performed global sensitivity analysis using the Latin-hyper cube sampling method and partial rank correlation coefficients to determine the most influential model parameters on the short and long term dynamics of the pandemic, so as to minimize uncertainties associated with our variables and parameters. Results confirm that there is a positive correlation between the number of escapees and the reported number of COVID-19 cases. It is shown that escapees are largely responsible for the rapid increase in local transmissions. Also, the results from sensitivity analysis show that an increase in the governmental role actions and a reduction in immigration rate will help to control and contain the disease spread.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Erik Snel Dr.", - "author_inst": "Erasmus University Rotterdam, Erasmus School of Social and Behavioural Sciences (ESSB)" + "author_name": "Josaih Mushanyu", + "author_inst": "University of Zimbabwe" }, { - "author_name": "Btissame El Farisi MSc", - "author_inst": "Erasmus University Rotterdam, Erasmus School of Social and Behavioural Sciences (ESSB)" + "author_name": "Chinwendu Emilian Madubueze", + "author_inst": "University of Agriculture, Makurdi" }, { - "author_name": "Godfried Engbersen Prof.", - "author_inst": "Erasmus University Rotterdam, Erasmus School of Social and Behavioural Sciences (ESSB)" + "author_name": "Zviiteyi Chazuka", + "author_inst": "Department of Mathematics and Applied Mathematics, University of Johannesburg, Auckland Park 2006, South Africa" + }, + { + "author_name": "Williams Chukwu", + "author_inst": "University of Johannesburg" }, { - "author_name": "Andre Krouwel Dr.", - "author_inst": "Free University Amsterdam" + "author_name": "Chisara Ogbogbo", + "author_inst": "Department of Mathematics, University of Ghana, Ghana" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.07.30.22278213", @@ -218377,55 +217699,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.07.27.22277602", - "rel_title": "Risk of BA.5 infection in individuals exposed to prior SARS-CoV-2 variants", + "rel_doi": "10.1101/2022.07.27.501726", + "rel_title": "Sequential in vitro enzymatic N-glycoprotein modification reveals site-specific rates of glycoenzyme processing", "rel_date": "2022-07-28", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.27.22277602", - "rel_abs": "The SARS-CoV-2 omicron BA.5 subvariant is progressively displacing earlier subvariants, BA.1 and BA.2, in many countries. One possible explanation is the ability of BA.5 to evade immune responses elicited by prior BA.1 and BA.2 infections. The impact of BA.1 infection on the risk of reinfection with BA.5 is a critical issue because adapted vaccines under current clinical development are based on BA.1.\n\nWe used the national Portuguese COVID-19 registry to analyze the risk of BA.5 infection in individuals without a documented infection or previously infected during periods of distinct variants predominance (Wuhan-Hu-1, alpha, delta, BA.1/BA.2). National predominance periods were established according to the national SARS-CoV-2 genetic surveillance data (when one variant represented >90% of the sample isolates).\n\nWe found that prior SARS-CoV-2 infection reduced the risk for BA.5 infection. The protection effectiveness, related to the uninfected group, for a first infection with Wuhan-Hu-1 was 52.9% (95% CI, 51.9 - 53.9%), for Alpha 54.9% (51.2 - 58.3%), for Delta 62.3% (61.4 - 63.3%), and for BA.1/BA.2 80.0% (79.7 - 80.2%).\n\nThe results ought to be interpreted in the context of breakthrough infections within a population with a very high vaccine coverage (>98% of the study population completed the primary vaccination series).\n\nIn conclusion, infection with BA.1/BA.2 reduces the risk for breakthrough infections with BA.5 in a highly vaccinated population. This finding is critical to appraise the current epidemiological situation and the development of adapted vaccines.", - "rel_num_authors": 9, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.07.27.501726", + "rel_abs": "N-glycosylation is an essential eukaryotic post-translational modification that affects various glycoprotein properties, including folding, solubility, protein-protein interactions, and half-life. N-glycans are processed in the secretory pathway to form varied ensembles of structures, and diversity at a single site on a glycoprotein is termed microheterogeneity. To understand the factors that influence glycan microheterogeneity, we hypothesized that local steric and electrostatic factors surrounding each site influences glycan availability to enzymatic modification. We tested this hypothesis by expression of a panel of reporter N-linked glycoproteins in MGAT1- null HEK293 cells to produce immature Man5GlcNAc2 glycoforms (38 glycan sites total). These glycoproteins were then sequentially modified in vitro from high-mannose to hybrid and on to biantennary, core fucosylated, complex structures by a panel of N-glycosylation enzymes and each reaction time-course was quantified by LC-MS/MS. Substantial differences in rates of in vitro enzymatic modification were observed between glycan sites on the same protein and differences in modification rates varied depending on the glycoenzyme being evaluated. By comparison, proteolytic digestion of the reporters prior to N-glycan processing eliminated differences in in vitro enzymatic modification. Comparison of in vitro rates of enzymatic modification with the glycan structures found on the mature reporters expressed in wild type cells correlate well with the enzymatic bottlenecks found in vitro. These data suggest that higher-order local structures surrounding each glycosylation site contribute to the efficiency of modification both in vitro and in vivo to establish the spectrum of site-specific microheterogeneity found on N-linked glycoproteins.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Joao Malato", - "author_inst": "Instituto de Medicina Molecular, Faculdade de Medicina, Centro Academico de Medicina de Lisboa, Universidade de Lisboa, Lisboa, Portugal" - }, - { - "author_name": "Ruy M Ribeiro", - "author_inst": "Instituto de Medicina Molecular, Faculdade de Medicina, Centro Academico de Medicina de Lisboa, Universidade de Lisboa, Lisboa, Portugal; 5.\tTheoretical Biology" - }, - { - "author_name": "Pedro Pinto Leite", - "author_inst": "Direcao de Servicos de Informacao e Analise, Direcao Geral da Saude, Lisboa, Portugal" - }, - { - "author_name": "Pedro Casaca", - "author_inst": "Direcao de Servicos de Informacao e Analise, Direcao Geral da Saude, Lisboa, Portugal" - }, - { - "author_name": "Eugenia Fernandes", - "author_inst": "Direcao de Servicos de Informacao e Analise, Direcao Geral da Saude, Lisboa, Portugal" + "author_name": "Trevor M Adams", + "author_inst": "University of Georgia" }, { - "author_name": "Carlos Antunes", - "author_inst": "Faculdade de Ciencias, Universidade de Lisboa, Lisboa, Portugal" + "author_name": "Peng Zhao", + "author_inst": "University of Georgia" }, { - "author_name": "Valter R Fonseca", - "author_inst": "Instituto de Medicina Molecular, Faculdade de Medicina, Centro Academico de Medicina de Lisboa, Universidade de Lisboa, Lisboa, Portugal; Comissao Tecnica de Va" + "author_name": "Digantkumar Chapla", + "author_inst": "University of Georgia" }, { - "author_name": "Manuel Carmo Gomes", - "author_inst": "Faculdade de Ciencias, Universidade de Lisboa, Lisboa, Portugal" + "author_name": "Kelley W Moremen", + "author_inst": "University of Georgia" }, { - "author_name": "Luis Graca", - "author_inst": "Instituto de Medicina Molecular, Faculdade de Medicina, Centro Academico de Medicina de Lisboa, Universidade de Lisboa, Lisboa, Portugal; Comissao Tecnica de Va" + "author_name": "Lance Wells", + "author_inst": "University of Georgia" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_by", + "type": "new results", + "category": "biochemistry" }, { "rel_doi": "10.1101/2022.07.27.501719", @@ -220107,63 +219413,99 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.07.25.22277985", - "rel_title": "Comparisons of the rate of acute myocardial infarction between COVID-19 patients and individuals received COVID-19 vaccines: a population-based study", + "rel_doi": "10.1101/2022.07.24.22277978", + "rel_title": "Genomic epidemiology and phylodynamics for county-to-county transmission of SARS-CoV-2 in Minnesota, from 19A to Omicron", "rel_date": "2022-07-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.25.22277985", - "rel_abs": "BackgroundBoth Coronavirus Disease-2019 (COVID-19) infection and COVID-19 vaccination have been associated with the development of acute myocardial infarction (AMI). This study compared the rates of AMI after COVID-19 infection and among the COVID-19 vaccinated populations in Hong Kong.\n\nMethodsThis was a population-based cohort study from Hong Kong, China. Patients with positive real time-polymerase chain reaction (RT-PCR) test for COVID-19 between January 1st, 2020 and June 30th, 2021 were included. The data of the vaccinated and unvaccinated population was obtained from the \"Reference Data of Adverse Events in Public Hospitals\" published by the local government. The individuals who were vaccinated with COVID-19 vaccination prior the observed period (December 6th, 2021 to January 2nd, 2022) in Hong Kong were also included. The vaccination data of other countries were obtained by searching PubMed using the terms [\"COVID-19 vaccine\" AND \"Myocardial infarction\"] from its inception to February 1st, 2022. The main exposures were COVID-19 test positivity or previous COVID-19 vaccination. The primary outcome was the development of AMI within 28 days observed period.\n\nResultsThis study included 11441 COVID-19 patients, of whom 25 suffered from AMI within 28 days of exposure (rate per million: 2185; 95% confidence interval [CI]: 1481-3224). The rates of AMI were much higher than those who were not vaccinated by the COVID-19 vaccine before December 6th, 2021 (rate per million: 162; 95% CI: 147-162) with a rate ratio of 13.5 (95% CI: 9.01-20.2). Meanwhile, the rate of AMI was lower amongst the vaccinated population (rate per million: 47; 95% CI: 41.3-53.5) than COVID-19 infection with a rate ratio of 0.02 (0.01, 0.03). Regarding post-vaccination AMI, COVID-19 infection was associated with a significantly higher rate of AMI than post-COVID-19 vaccination AMI in other countries.\n\nConclusionsCOVID-19 infection was associated with a higher rate of AMI than the vaccinated general population, and those immediately after COVID-19 vaccination.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.24.22277978", + "rel_abs": "SARS-CoV-2 has had an unprecedented impact on human health and highlights the need for genomic epidemiology studies to increase our understanding of virus evolution and spread, and to inform policy decisions. We sequenced viral genomes from over 22,000 patient samples tested at Mayo Clinic Laboratories between 2020-2022 and use Bayesian phylodynamics to describe county and regional spread in Minnesota.\n\nThe earliest introduction into Minnesota was to Hennepin County from a domestic source around January 22, 2020; six weeks before the first confirmed case in the state. This led to the virus spreading to Northern Minnesota, and eventually, the rest of the state. International introductions were most abundant in Hennepin (home to the Minneapolis/St. Paul International (MSP) airport) totaling 45 (out of 107) over the two-year period. Southern Minnesota counties were most common for domestic introductions with 19 (out of 64), potentially driven by bordering states such as Iowa and Wisconsin as well as Illinois which is nearby. Hennepin also was, by far, the most dominant source of in-state transmissions to other Minnesota locations (n=772) over the two-year period.\n\nWe also analyzed the diversity of the location source of SARS-CoV-2 viruses in each county and noted the timing of state-wide policies as well as trends in clinical cases. Neither the number of clinical cases or major policy decisions, such as the end of the lockdown period in 2020 or the end of all restrictions in 2021, appeared to have impact on virus diversity across each individual county.\n\nImportanceWe analyzed over 22,000 SARS-CoV-2 genomes of patient samples tested at Mayo Clinic Laboratories during a two-year period in the COVID-19 pandemic that included Alpha, Delta, and Omicron VoCs to examine the roles and relationships of Minnesota virus transmission.\n\nWe found that Hennepin County, the most populous county, drove the transmission of SARS-CoV-2 viruses in the state after including the formation of earlier clades including 20A, 20C, and 20G, as well as variants of concern Alpha and Delta. We also found that Hennepin County was the source for most of the county-to-county introductions after its initial introduction with the virus in early 2020 from an international source, while other counties acted as transmission \"sinks\". In addition, major policies such as the end of the lockdown period in 2020 or the end of all restrictions in 2021, did not appear to have an impact on virus diversity across individual counties.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Oscar Hou In Chou", - "author_inst": "Cardiovascular Analytics Group" + "author_name": "Matthew Scotch", + "author_inst": "Arizona State University" }, { - "author_name": "Cheuk To Chung", - "author_inst": "Cardiovascular Analytics Group" + "author_name": "Kimberly Lauer", + "author_inst": "Mayo Clinic" }, { - "author_name": "Danish Iltaf Satti", - "author_inst": "Cardiovascular Analytics Group, Hong Kong, China-UK Collaboration" + "author_name": "Eric D Wieben", + "author_inst": "Mayo Clinic" }, { - "author_name": "Jiandong Zhou", - "author_inst": "University of Oxford" + "author_name": "Yesesri Cherukuri", + "author_inst": "Mayo Clinic" }, { - "author_name": "Teddy Tai Loy Lee", - "author_inst": "Cardiovascular Analytics Group" + "author_name": "Julie M Cunningham", + "author_inst": "Mayo Clinic" }, { - "author_name": "Abraham Ka Chung Wai", - "author_inst": "HKU" + "author_name": "Eric W Klee", + "author_inst": "Mayo Clinic" }, { - "author_name": "Tong Liu", - "author_inst": "Tianjin Medical University" + "author_name": "Jonathan J Harrington", + "author_inst": "Mayo Clinic" }, { - "author_name": "Sharen Lee", - "author_inst": "Cardiovascular Analytics Group" + "author_name": "Julie S Lau", + "author_inst": "Mayo Clinic" }, { - "author_name": "Vassilios S Vassiliou", - "author_inst": "University of East Anglia" + "author_name": "Samantha J McDonough", + "author_inst": "Mayo Clinic" }, { - "author_name": "Bernard Man Yung Cheung", - "author_inst": "HKU" + "author_name": "Mark Mutawe", + "author_inst": "Mayo Clinic" }, { - "author_name": "Gary Tse", - "author_inst": "Tianjin Medical University" + "author_name": "John C O'Horo", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "Chad E Rentmeester", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "Nicole R Schlicher", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "Valerie T White", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "Susan K Schneider", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "Peter T Vedell", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "Xiong Wang", + "author_inst": "Minnesota Department of Health" + }, + { + "author_name": "Joseph D Yao", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "Bobbi S Pritt", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "Andrew P Norgan", + "author_inst": "Mayo Clinic" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "cardiovascular medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.07.24.22277968", @@ -221757,87 +221099,75 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.07.22.22277885", - "rel_title": "Duration of BA.5 neutralization in sera and nasal swabs from SARS-CoV-2 vaccinated individuals, with or without Omicron breakthrough infection.", + "rel_doi": "10.1101/2022.07.20.500860", + "rel_title": "A linear DNA vaccine candidate encoding the SARS-CoV-2 Receptor Binding Domain elicits protective immunity in domestic cats", "rel_date": "2022-07-22", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.22.22277885", - "rel_abs": "Since early 2022, Omicron BA.1 has been eclipsed by BA.2, which was in turn outcompeted by BA.5, that displays enhanced antibody escape properties. Here, we evaluated the duration of the neutralizing antibody (Nab) response, up to 16 months after Pfizer BNT162b2 vaccination, in individuals with or without BA.1/BA.2 breakthrough infection. We measured neutralization of the ancestral D614G lineage, Delta and Omicron BA.1, BA.2, BA.5 variants in 291 sera and 35 nasal swabs from 27 individuals. Upon vaccination, serum Nab titers were reduced by 10-, 15-and 25-fold for BA.1, BA.2 and BA.5, respectively, compared with D614G. The duration of neutralization was markedly shortened, from an estimated period of 11.5 months post-boost with D614G to 5.5 months with BA.5. After breakthrough, we observed a sharp increase of Nabs against Omicron subvariants, followed by a plateau and a slow decline after 4-5 months. In nasal swabs, infection, but not vaccination, triggered a strong IgA response and a detectable Omicron neutralizing activity. Thus, BA.5 spread is partly due to abbreviated vaccine efficacy, particularly in individuals who were not infected with previous Omicron variants.", - "rel_num_authors": 17, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.07.20.500860", + "rel_abs": "Since its first detection in China in late 2019, SARS-CoV-2, the etiologic agent of COVID-19 pandemic, has infected a wide range of animal species, especially mammals, all over the world. Indeed, as reported by the American Veterinary Medical Association, besides human-to-human transmission, human-to-animal transmission has been observed in some wild animals and pets, especially in cats. With animal models as an invaluable tool in the study of infectious diseases combined with the fact that the intermediate animal source of SARS-CoV-2 is still unknown, researchers have demonstrated that cats are permissive to COVID-19 and are susceptible to airborne infections. Given the high transmissibility potential of SARS-CoV-2 to different host species and the close contact between humans and animals, it is crucial to find mechanisms to prevent the transmission chain and reduce the risk of spillover to susceptible species. Here, we show results from a randomized Phase I/II clinical study conducted in domestic cats to assess safety and immunogenicity of a linear DNA (\"linDNA\") vaccine encoding the RBD domain of SARS-CoV-2. No significant adverse events occurred and both RBD-specific binding/neutralizing antibodies and T cells were detected. These findings demonstrate the safety and immunogenicity of a genetic vaccine against COVID-19 administered to cats and strongly support the development of vaccines for preventing viral spread in susceptible species, especially those in close contact with humans.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Delphine Planas", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Isabelle Staropoli", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Francoise Porrot", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Florence Guivel-Benhassine", - "author_inst": "Institut Pasteur" + "author_name": "Antonella Conforti", + "author_inst": "Evvivax" }, { - "author_name": "Lynda Handala", - "author_inst": "CHRU de Tours" + "author_name": "Elisa Sanchez", + "author_inst": "Veterinary Oncology Services" }, { - "author_name": "Matthieu Prot", - "author_inst": "Pasteur Institute" + "author_name": "Erika Salvatori", + "author_inst": "Takis Biotech" }, { - "author_name": "William Henry Bolland", - "author_inst": "Institut Pasteur" + "author_name": "Lucia Lione", + "author_inst": "Takis Biotech" }, { - "author_name": "Julien Puech", - "author_inst": "Hopital Europeen Georges Pompidou" + "author_name": "Mirco Compagnone", + "author_inst": "Neomatrix Biotech" }, { - "author_name": "Helene Pere", - "author_inst": "APHP" + "author_name": "Eleonora Pinto", + "author_inst": "Takis Biotech" }, { - "author_name": "David Veyer", - "author_inst": "AP-HP" + "author_name": "Fabio Palombo", + "author_inst": "Neomatrix Biotech" }, { - "author_name": "Aymeric Seve", - "author_inst": "CHR Orleans" + "author_name": "Yuhua Sun", + "author_inst": "ADNAS" }, { - "author_name": "Etienne Simon-Loriere", - "author_inst": "Institut Pasteur" + "author_name": "Brian Viscount", + "author_inst": "ADNAS" }, { - "author_name": "Timothee Bruel", - "author_inst": "Institut Pasteur" + "author_name": "James Hayward", + "author_inst": "ADNAS" }, { - "author_name": "thierry prazuck", - "author_inst": "CHR Orleans" + "author_name": "Clay Shorrock", + "author_inst": "ADNAS" }, { - "author_name": "Karl Stefic", - "author_inst": "CHRU de Tours" + "author_name": "Diego G Diel", + "author_inst": "Cornell University" }, { - "author_name": "Laurent Hocqueloux", - "author_inst": "CHR Orleans" + "author_name": "Joseph A Impellizeri", + "author_inst": "Veterinary Oncology Services" }, { - "author_name": "Olivier Schwartz", - "author_inst": "Institut Pasteur" + "author_name": "Luigi Aurisicchio", + "author_inst": "Evvivax" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2022.07.21.501010", @@ -223547,71 +222877,87 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.07.19.500626", - "rel_title": "Monovalent and trivalent VSV-based COVID-19 vaccines elicit potent neutralizing antibodies and immunodominant CD8+ T cells against diverse SARS-CoV-2 variants", + "rel_doi": "10.1101/2022.07.18.499583", + "rel_title": "Discovering host protein interactions specific for SARS-CoV-2 RNA genome", "rel_date": "2022-07-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.07.19.500626", - "rel_abs": "Recombinant vesicular stomatitis virus (rVSV) vaccines expressing Spike proteins of Wuhan, Beta and/or Delta variants of SARS-CoV-2 were generated and tested for induction of antibody and T cell immune responses in mice. rVSV-Wuhan and rVSV-Delta vaccines and a rVSV-Trivalent (mixed rVSV-Wuhan, -Beta, -Delta) vaccine elicited potent neutralizing antibodies (nAbs) against live SARS-CoV-2 Wuhan (USAWA1), Beta (B.1.351), Delta (B.1.617.2) and Omicron (B.1.1.529) viruses. Prime-boost vaccination with rVSV-Beta was less effective in this capacity. Heterologous boosting of rVSV-Wuhan with rVSV-Delta induced strong nAb responses against Delta and Omicron viruses, with rVSV-Trivalent vaccine consistently effective in inducing nAbs against all the SARS-CoV-2 variants tested. All vaccines, including rVSV-Beta, elicited a spike-specific immunodominant CD8+ T cell response. Collectively, rVSV vaccines targeting SARS-CoV-2 variants of concern may be considered in the global fight against COVID-19.", - "rel_num_authors": 13, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.07.18.499583", + "rel_abs": "SARS-CoV-2, a positive single-stranded RNA virus, interacts with host cell proteins throughout its life cycle. These interactions are necessary for the host to recognize and hinder the replication of SARS-CoV-2. For the virus, to translate, transcribe and replicate its genetic material. However, many details of these interactions are still missing. We focused on the proteins binding to the highly structured 5 and 3 end regions of SARS-CoV-2 RNA that were predicted by the catRAPID algorithm to attract numerous proteins, exploiting RNA-Protein Interaction Detection coupled with Mass Spectrometry (RaPID-MS) technology. The validated interactors, which agreed with our predictions, include pseudouridine synthase PUS7 that binds to both ends of the viral RNA. Nanopore direct-RNA sequencing confirmed that the RNA virus is heavily modified, and PUS7 consensus regions were found in both SARS-CoV-2 RNA end regions. Notably, a modified site was detected in the viral Transcription Regulatory Sequence - Leader (TRS-L) and can influence the viral RNA structure and interaction propensity. Overall, our data map host protein interactions within SARS-CoV-2 UTR regions, pinpointing to a potential role of pseudouridine synthases and post-transcriptional modifications in the viral life cycle. These findings contribute to understanding virus-host dynamics and may guide the development of targeted therapies.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Kate A. Parham", - "author_inst": "University of Western Ontario" + "author_name": "Roberto Giambruno", + "author_inst": "Institute of Biomedical Technologies, National Research Council, ITB - CNR; Istituto Italiano di Tecnologia - IIT" }, { - "author_name": "Gyoung Nyoun Kim", - "author_inst": "University of Western Ontario" + "author_name": "Elsa Zacco", + "author_inst": "Italian Institute of Technology - IIT" }, { - "author_name": "Nasrin Saeedian", - "author_inst": "University of Western Ontario" + "author_name": "Camilla Ugolini", + "author_inst": "Italian Institute of Technology - IIT" }, { - "author_name": "Marina Ninkov", - "author_inst": "University of Western Ontario" + "author_name": "Andrea Vandelli", + "author_inst": "Italian Institute of Technology - IIT" }, { - "author_name": "Connor G. Richer", - "author_inst": "University of Western Ontario" + "author_name": "Logan Mulroney", + "author_inst": "Italian Institute of Technology - IIT; European Molecular Biology Laboratory - EMBL" }, { - "author_name": "Yue Li", - "author_inst": "University of Western Ontario" + "author_name": "Manfredi D'Onghia", + "author_inst": "Italian Institute of Technology - IIT" }, { - "author_name": "Kunyu Wu", - "author_inst": "University of Western Ontario" + "author_name": "Bianca Giuliani", + "author_inst": "Italian Institute of Technology - IIT" }, { - "author_name": "Rasheduzzaman Rashu", - "author_inst": "University of Western Ontario" + "author_name": "Elena Criscuolo", + "author_inst": "Vita-Salute San Raffaele University" }, { - "author_name": "Stephen D. Barr", - "author_inst": "University of Western Ontario" + "author_name": "Matteo Castelli", + "author_inst": "Vita-Salute San Raffaele University" }, { - "author_name": "Eric J. Arts", - "author_inst": "University of Western Ontario" + "author_name": "Nicola Clementi", + "author_inst": "Vita-Salute San Raffaele University; IRCCS San Raffaele Scientific Institute" }, { - "author_name": "S.M. Mansour Haeryfar", - "author_inst": "University of Western Ontario" + "author_name": "Massimo Clementi", + "author_inst": "Vita-Salute San Raffaele University; IRCCS San Raffaele Scientific Institute" }, { - "author_name": "C. Yong Kang", - "author_inst": "University of Western Ontario" + "author_name": "Nicasio Mancini", + "author_inst": "Universita Vita-Salute San Raffaele; IRCCS San Raffaele Scientific Institute" }, { - "author_name": "Ryan M. Troyer", - "author_inst": "University of Western Ontario" + "author_name": "Tiziana Bonaldi", + "author_inst": "European Institute of Oncology; University of Milan" + }, + { + "author_name": "Stefano Gustincich", + "author_inst": "IIT- Center for Human Technologies (CHT)" + }, + { + "author_name": "Tommaso Leonardi", + "author_inst": "Italian Institute of Technology - IIT" + }, + { + "author_name": "Gian Gaetano Tartaglia", + "author_inst": "Italian Institute of Technology - IIT" + }, + { + "author_name": "Francesco Nicassio", + "author_inst": "Italian Institute of Technology - IIT" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2022.07.18.22277694", @@ -225381,63 +224727,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.07.15.22277678", - "rel_title": "Influence of vitamin D supplementation on SARS-CoV-2 vaccine efficacy and immunogenicity", + "rel_doi": "10.1101/2022.07.15.22277696", + "rel_title": "Ethnic homophily affects vaccine prioritization strategies", "rel_date": "2022-07-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.15.22277678", - "rel_abs": "SUMMARYO_ST_ABSBackground & AimsC_ST_ABSVitamin D deficiency has been reported to associate with impaired development of antigen-specific responses following vaccination. We aimed to determine whether vitamin D supplements might boost immunogenicity and efficacy of SARS-CoV-2 vaccination.\n\nMethodsWe conducted three sub-studies nested within the CORONAVIT randomised controlled trial, which investigated effects of offering vitamin D supplements at a dose of 800 IU/day or 3200 IU/day vs. no offer on risk of acute respiratory infections, including COVID-19, in UK adults with circulating 25-hydroxyvitamin D concentrations <75 nmol/L. Sub-study 1 (n=2808) investigated effects of vitamin D supplementation on risk of breakthrough SARS-CoV-2 infection following two doses of SARS-CoV-2 vaccine. Sub-study 2 (n=1853) investigated effects of vitamin D supplementation on titres of combined IgG, IgA and IgM (IgGAM) anti-Spike antibodies in eluates of dried blood spots collected after SARS-CoV-2 vaccination. Sub-study 3 (n=100) investigated effects of vitamin D supplementation on neutralising antibody and cellular responses in venous blood samples collected after SARS-CoV-2 vaccination.\n\nResults1945/2808 (69.3%) sub-study 1 participants received two doses of ChAdOx1 nCoV-19 (Oxford-AstraZeneca); the remainder received two doses of BNT162b2 (Pfizer). Vitamin D supplementation did not influence risk of breakthrough SARS-CoV-2 infection (800 IU/day vs. no offer: adjusted hazard ratio 1.28, 95% CI 0.89 to 1.84; 3200 IU/day vs. no offer: 1.17, 0.81 to 1.70). Neither did it influence IgGAM anti-Spike titres, neutralising antibody titres or IFN-{gamma} concentrations in supernatants of S peptide-stimulated whole blood.\n\nConclusionsAmong adults with sub-optimal baseline vitamin D status, vitamin D replacement at a dose of 800 or 3200 IU/day did not influence protective efficacy or immunogenicity of SARS-CoV-2 vaccination.\n\nClinical Trial RegistrationClinicalTrials.gov NCT04579640.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.15.22277696", + "rel_abs": "People are more likely to interact with other people of their ethnicity--a phenomenon known as ethnic homophily. In the United States, people of color are known to hold proportionately more high-contact jobs and are thus more at risk of virus infection. At the same time, these ethnic groups are on average younger than the rest of the population. This gives rise to interesting disease dynamics and non-trivial trade-offs that should be taken into consideration when developing prioritization strategies for future mass vaccine roll-outs.\n\nHere, we study the spread of COVID-19 through the U.S. population, stratified by age, ethnicity, and occupation, using a detailed, previously-developed compartmental disease model. Based on historic data from the U.S. mass COVID-19 vaccine roll-out that began in December 2020, we show, (i) how ethnic homophily affects the choice of optimal vaccine allocation strategy, (ii) that, notwithstanding potential ethical concerns, differentiating by ethnicity in these strategies can improve outcomes (e.g., fewer deaths), and (iii) that the most likely social context in the United States is very different from the standard assumptions made by models which do not account for ethnicity and this difference affects which allocation strategy is optimal.\n\nHighlightsO_LIA social mixing model accounting for ethnic homophily and variable job-related risk level is developed.\nC_LIO_LIA scenario that differs strongly from standard homogeneous mixing assumptions best matches U.S. ethnicity-specific death and case counts.\nC_LIO_LITwo trade-offs are explored: Should (i) old or young, and (ii) people of color or White and Asian people first receive COVID-19 vaccines?\nC_LIO_LIExhaustive simulation of a compartmental disease model identifies the optimal allocation strategy for different demographic groups.\nC_LIO_LIOptimal strategies depend on the underlying mixing pattern and strategies that differentiate vaccine access by ethnicity outperform others.\nC_LI", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "David A Jolliffe", - "author_inst": "Queen Mary University of London" - }, - { - "author_name": "Giulia Vivaldi", - "author_inst": "Queen Mary University of London" - }, - { - "author_name": "Emma S Chambers", - "author_inst": "Queen Mary University of London" - }, - { - "author_name": "Weigang Cai", - "author_inst": "Queen Mary University of London" - }, - { - "author_name": "Wenhao Li", - "author_inst": "Queen Mary University of London" - }, - { - "author_name": "Sian E Faustini", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Joseph M Gibbons", - "author_inst": "Barts and The London School of Medicine and Dentistry Blizard Institute" + "author_name": "Claus Kadelka", + "author_inst": "Iowa State University" }, { - "author_name": "Corinna Pade", - "author_inst": "Queen Mary University of London" + "author_name": "Md Rafiul Islam", + "author_inst": "Iowa State University" }, { - "author_name": "Alex Richter", - "author_inst": "University of Birminghan" + "author_name": "Audrey McCombs", + "author_inst": "Iowa State University" }, { - "author_name": "Aine McKnight", - "author_inst": "Barts and The London School of Medicine and Dentistry Blizard Institute" + "author_name": "Jake Alston", + "author_inst": "Iowa State University" }, { - "author_name": "Adrian R Martineau", - "author_inst": "Queen Mary University of London" + "author_name": "Noah Morton", + "author_inst": "Iowa State University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.07.15.22277497", @@ -227623,29 +226945,57 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.07.13.22277596", - "rel_title": "COVID-19 pandemic surges can induce bias in trials using response adaptive randomization: A simulation study", + "rel_doi": "10.1101/2022.07.14.22277616", + "rel_title": "SARS-CoV-2 infection dynamics and genomic surveillance reveals early variant transmission in urban wastewater", "rel_date": "2022-07-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.13.22277596", - "rel_abs": "Response-adaptive randomization is being used in COVID-19 trials, but it is unknown whether outcome rate changes during surges of COVID-19 will lead to bias in trial results. In response-adaptive randomization, allocation ratios are adjusted according to interim analyses to assign more patients to promising interventions. Although it is known that response-adaptive randomization may give biased estimates if outcome rates drift over time, observed mortality fluctuations in the COVID-19 pandemic are more extreme than any previously tested in simulation. We hypothesized that pandemic surges induce bias in trials using response-adaptive randomization, and that adjustment for time will alleviate that bias. Bayesian 4-arm superiority trials with a mortality outcome were simulated to investigate bias in treatment effect, comparing complete and response-adaptive randomization under different pandemic scenarios based on data from New York, Spain, and Italy. Relative bias in the odds ratio associated with treatment ranged from 0.3% to 11% and was largest in trials with a surge and an effective intervention that did not adjust for time. Bias was attenuated by adjustment for time without compromising the false-positive rate. Trials using response-adaptive randomization were more likely to identify effective interventions but were slower to drop ineffective interventions. Even with variation in outcome rates similar to observed pandemic surges, COVID-19 trials using response-adaptive randomization that adjust for time can provide accurate estimates of treatment effects.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.14.22277616", + "rel_abs": "Environmental surveillance (ES) of a pathogen is crucial for understanding the community load of disease. As an early warning system, ES for SARS-CoV-2 has complemented routine diagnostic surveillance by capturing near real-time virus circulation at a population level. In this longitudinal study in 28 sewershed sites in Bangalore city, we quantified SARS-CoV-2 RNA to track infection dynamics and provide evidence of change in the relative abundance of emerging variants. We describe an early warning system using the exponentially weighted moving average control chart and demonstrate how SARS-CoV-2 RNA concentrations in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 8-14 days earlier in wastewater than in clinical data. This was further corroborated by showing that the estimated number of infections is strongly correlated with SARS-CoV-2 RNA copies detected in the wastewater. Using a deconvolution matrix, we detected emerging variants of concern up to two months earlier in wastewater samples. In addition, we found a huge diversity in variants detected in wastewater compared to clinical samples. Our study highlights that quantifying viral titres, correlating it with a known number of cases in the area, and combined with genomic surveillance helps in tracking VOCs over time and space, enabling timely and making informed policy decisions.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Christopher J Yarnell", - "author_inst": "University of Toronto Interdepartmental Division of Critical Care Medicine, Toronto, Canada" + "author_name": "Sanjay Lamba", + "author_inst": "Tata Institute for Genetics and Society" }, { - "author_name": "Robert A Fowler", - "author_inst": "Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada" + "author_name": "Sutharan G.", + "author_inst": "Tata Institute for Genetics and Society" + }, + { + "author_name": "Namrta Daroch", + "author_inst": "Tata Institute for Genetics and Society" + }, + { + "author_name": "Kiran Paul", + "author_inst": "Tata Institute for Genetics and Society" + }, + { + "author_name": "Soumya Gopal Joshi", + "author_inst": "Tata Institute for Genetics and Society" + }, + { + "author_name": "Darshan S", + "author_inst": "National Centre for Biological Sciences" + }, + { + "author_name": "Annamalai N", + "author_inst": "Tata Institute for Genetics and Society" + }, + { + "author_name": "Vishwanath S", + "author_inst": "Biome Environmental Trust" + }, + { + "author_name": "Rakesh K Mishra", + "author_inst": "Tata Institute for Genetics and Society" }, { - "author_name": "Lillian Sung", - "author_inst": "Division of Haematology/Oncology, The Hospital for Sick Children, Toronto, Canada" + "author_name": "Uma Ramakrishnan", + "author_inst": "National Centre for Biological Sciences" }, { - "author_name": "George Tomlinson", - "author_inst": "Department of Medicine, University Health Network and Sinai Health System, Toronto, Canada; Institute of Health Policy, Management and Evaluation, University of" + "author_name": "Farah Ishtiaq", + "author_inst": "Tata Institute for Genetics and Society" } ], "version": "1", @@ -229197,69 +228547,129 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.07.11.22277490", - "rel_title": "COVID-19 Vaccination Uptake and Self-Reported Side Effects among Healthcare Workers in Mbale City Eastern Uganda", + "rel_doi": "10.1101/2022.07.11.22277481", + "rel_title": "Age stratified seroprevalence of antibodies against SARS CoV 2 in the pre and post vaccination era, February 2020 to March 2022, Japan", "rel_date": "2022-07-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.11.22277490", - "rel_abs": "BackgroundFear of anticipated side effects has hindered the COVID-19 vaccination program globally. We report the uptake and the self-reported side effects (SEs) of the COVID-19 vaccine among Healthcare workers (HCWs) in Mbale City Eastern Uganda.\n\nMethodsA cross-sectional survey of HCWs at seven different level health facilities was conducted from 6th September to 7th October 2021 using a structured self-administered questionnaire.\n\nResultsCOVID-19 vaccine had been received by 119 (69%) participants of which 79 (66%) received the two recommended doses of the AstraZeneca vaccine. Getting vaccinated was associated with working in a lower health facility (aOR= 14.1, 95% CI: 4.9 - 39.6, P=0.000), perceived minor risk of contracting COVID-19 (aOR= 12.3, 95% CI: 1.0 - 44.6, p=0.047), and agreeing that COVID-19 vaccine is protective (aOR= 16.7, 95% CI: 5.6 - 50.4, p=0.000). 97 (82%) of participants experienced side effects to at least one dose of which most were mild on both the first (n=362, 51%) and second dose (n=135, 69%). The most frequently reported side effects on the first and second dose were fever (79% and 20%), injection site pain (71% and 25%), and Fatigue (69% and 20%) respectively.\n\nConclusionsThe majority of the HCWs in Mbale City had received at least one dose of the COVID-19 vaccine and experienced a side effect. The side effects were mostly mild on either dose thus the vaccines are generally safe.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.11.22277481", + "rel_abs": "Japan has reported a small number of COVID-19 cases relative to other countries. Because not all infected people receive diagnostic tests for COVID-19, the reported number of COVID-19 cases must be lower than the actual number of infections. Assessments of the presence of antibodies against the spike protein of SARS-CoV-2 can retrospectively determine the history of natural infection and vaccination. In this study, we assessed SARS-CoV-2 seroprevalence by analyzing over 60,000 samples collected in Japan from February 2020 to March 2022. The results showed that about 5% of the Japanese population had been infected with the virus by January 2021. The seroprevalence increased with the administration of vaccinations to adults; however, among the elderly, it was not as high as the vaccination rate, probably due to poor immune responses to the vaccines and waning immunity. The infection was spread during the epidemic waves caused by the SARS-CoV-2 Delta and Omicron variants among children who were not eligible for vaccination. Nevertheless, their seroprevalence was as low as 10% as of March 2022. Our study underscores the low incidence of SARS-CoV-2 infection in Japan and the effects of vaccination on immunity at the population level.", + "rel_num_authors": 28, "rel_authors": [ { - "author_name": "Gabriel Madut Madut Akech", - "author_inst": "Busitema University" + "author_name": "Seiya Yamayoshi", + "author_inst": "University of Tokyo" }, { - "author_name": "Andrew Marvin Kanyike", - "author_inst": "Busitema University" + "author_name": "Kiyoko Iwatsuki-Horimoto", + "author_inst": "University of Tokyo" }, { - "author_name": "Ashah Galabuzi Nassozi", - "author_inst": "Busitema University" + "author_name": "Moe Okuda", + "author_inst": "University of Tokyo" }, { - "author_name": "Beatrice Aguti", - "author_inst": "Busitema University" + "author_name": "Michiko Ujie", + "author_inst": "University of Tokyo" }, { - "author_name": "Ashley Winfred Nakawuki", - "author_inst": "Busitema University" + "author_name": "Atsuhiro Yasuhara", + "author_inst": "University of Tokyo" + }, + { + "author_name": "Jurika Murakami", + "author_inst": "University of Tokyo" }, { - "author_name": "Denis Kimbugwe", - "author_inst": "Mbale Regional Referral Hospital" + "author_name": "Calvin Duong", + "author_inst": "University of Tokyo" }, { - "author_name": "Josen Kiggundu", - "author_inst": "Mbale Hospital: Mbale Regional Referral Hospital" + "author_name": "Taiki Hamabata", + "author_inst": "University of Tokyo" }, { - "author_name": "Robert Maiteki", - "author_inst": "Mbale Hospital: Mbale Regional Referral Hospital" + "author_name": "Mutsumi Ito", + "author_inst": "University of Tokyo" }, { - "author_name": "Dorothy Mukyala", - "author_inst": "Mbale Regional Referral Hospital" + "author_name": "Shiho Chiba", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Felix Bongomin", - "author_inst": "Gulu University Faculty of Medicine" + "author_name": "Ryo Kobayashi", + "author_inst": "Sapporo Medical University Hospital" }, { - "author_name": "Samuel Baker Obakiro", - "author_inst": "Busitema University" + "author_name": "Satoshi Takahash", + "author_inst": "Sapporo Medical University School of Medicine" }, { - "author_name": "Nekaka Rebecca", - "author_inst": "Busitema University" + "author_name": "Keiko Mitamura", + "author_inst": "Eiju General Hospital" }, { - "author_name": "Jacob Stanley Iramiot", - "author_inst": "Busitema University" + "author_name": "Masao Hagihara", + "author_inst": "Eiju General Hospital" + }, + { + "author_name": "Akimichi Shibata", + "author_inst": "Japanese Red Cross Ashikaga Hospital" + }, + { + "author_name": "Yoshifumi Uwamino", + "author_inst": "Keio University School of Medicine" + }, + { + "author_name": "Naoki Hasegawa", + "author_inst": "Keio University School of Medicine" + }, + { + "author_name": "Toshiaki Ebina", + "author_inst": "Yokohama City University Medical Center" + }, + { + "author_name": "Akihiko Izumi", + "author_inst": "Yokohama City University Medical Center" + }, + { + "author_name": "Hideaki Kato", + "author_inst": "Yokohama City University Hospital" + }, + { + "author_name": "Hideaki Nakajima", + "author_inst": "Yokohama City University Graduate School of Medicine" + }, + { + "author_name": "Norio Sugaya", + "author_inst": "Keio University School of Medicine" + }, + { + "author_name": "Yuki Seki", + "author_inst": "Keiyu Hospital" + }, + { + "author_name": "Asef Iqbal", + "author_inst": "National Hospital Organization Saitama Hospital" + }, + { + "author_name": "Isamu Kamimaki", + "author_inst": "National Hospital Organization Saitama Hospital" + }, + { + "author_name": "Masahiko Yamazaki", + "author_inst": "Zama Childrens Clinic" + }, + { + "author_name": "Yoshihiro Kawaoka", + "author_inst": "University of Tokyo" + }, + { + "author_name": "Yuki Furuse", + "author_inst": "Nagasaki University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -231255,61 +230665,49 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.07.07.22277204", - "rel_title": "SHEAR Saliva Collection Device Augments Sample Properties for Improved Analytical Performance.", + "rel_doi": "10.1101/2022.07.07.22277391", + "rel_title": "Modeling the impact of the Omicron infection wave in Germany", "rel_date": "2022-07-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.07.22277204", - "rel_abs": "Despite human saliva representing a convenient and non-invasive clinical substrate for disease diagnosis and biomonitoring, its widespread utilization has been hampered by technical challenges. The non-Newtonian, heterogenous and highly viscous nature of clinical saliva samples complicate the development of automated fluid handling processes that are vital for accurate diagnoses. Furthermore, conventional saliva processing methods are either resource and/or time intensive precluding certain testing capabilities in low- and middle-income countries, with these challenges aggravated during a pandemic outbreak. The conventional approaches can also potentially alter analyte structure, reducing application opportunities in Point-of-Care diagnostics. To overcome these challenges, we introduce the SHEAR saliva collection device that preprocesses saliva for enhanced interfacing with downstream assays. We demonstrate the devices impact on reducing salivas viscosity, improving sample uniformity and, increasing diagnostic performance of COVID-19 Rapid Antigen Tests. Importantly, in addition to reporting technical advances and to address downstream implementation factors, we conducted a formal user experience study, which resulted in generally positive comments. Effective implementation of this device could be of support to realize the potential of saliva, particularly in large-scale and/or resource-limited settings for global and community health diagnostics.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.07.22277391", + "rel_abs": "BACKGROUNDIn November 2021, the first case of SARS-CoV-2 \"variant of concern\" (VOC) B.1.1.529 (\"Omicron\") was reported in Germany, alongside global reports of reduced vaccine efficacy against infections with this variant. The potential threat posed by the rapid spread of this variant in Germany remained, at the time, elusive.\n\nMETHODSWe developed a variant-dependent population-averaged susceptible-exposed-infected-recovered (SEIR) infectious disease model. The model was calibrated on the observed fixation dynamics of the Omicron variant in December 2021, and allowed us to estimate potential courses of upcoming infection waves in Germany, focusing on the corresponding burden on intensive care units (ICUs) and the efficacy of contact reduction strategies.\n\nRESULTSA maximum median incidence of approximately 300 000 (50% PI in 1000: [181,454], 95% PI in 1000: [55,804]) reported cases per day was expected with the median peak occurring in the mid of February 2022, reaching a cumulative Omicron case count of 16.5 million (50% PI in mio: [11.4, 21.3], 95% PI in mio: [4.1, 27.9]) until Apr 1, 2022. These figures were in line with the actual Omicron waves that were subsequently observed in Germany with respective peaks occurring in mid February (peak: 191k daily new cases) and mid March (peak: 230k daily new cases), cumulatively infecting 14.8 million individuals during the study period. The model peak incidence was observed to be highly sensitive to variations in the assumed generation time and decreased with shorter generation time. Low contact reductions were expected to lead to containment. Early, strict, and short contact reductions could have led to a strong \"rebound\" effect with high incidences after the end of the respective non-pharmaceutical interventions. Higher vaccine uptake would have led to a lower outbreak size. To ensure that ICU occupancy remained below maximum capacity, a relative risk of requiring ICU care of 10%-20% was necessary (after infection with Omicron vs. infection with Delta).\n\nCONCLUSIONSWe expected a large cumulative number of infections with the VOC Omicron in Germany with ICU occupancy likely remaining below capacity nevertheless, even without additional non-pharmaceutical interventions. Our estimates were in line with the retrospectively observed waves. The results presented here informed legislation in Germany. The methodology developed in this study might be used to estimate the impact of future waves of COVID-19 or other infectious diseases.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Shang Wei Song", - "author_inst": "National University of Singapore" - }, - { - "author_name": "Rashi Gupta", - "author_inst": "National University of Singapore" - }, - { - "author_name": "Jothilingam Niharika", - "author_inst": "National University of Singapore" - }, - { - "author_name": "Xinlei Qian", - "author_inst": "National University of Singapore" + "author_name": "Benjamin F Maier", + "author_inst": "Robert Koch Institute" }, { - "author_name": "Yue Gu", - "author_inst": "National University of Singapore" + "author_name": "Angelique Burdinski", + "author_inst": "Robert Koch Institute" }, { - "author_name": "V Vien Lee", - "author_inst": "National University of Singapore" + "author_name": "Marc Wiedermann", + "author_inst": "Robert Koch Institute" }, { - "author_name": "Yoann Sapanel", - "author_inst": "National University of Singapore" + "author_name": "Annika H Rose", + "author_inst": "Robert Koch Institute" }, { - "author_name": "David Michael Allen", - "author_inst": "National University of Singapore" + "author_name": "Matthias an der Heiden", + "author_inst": "Robert Koch Institute" }, { - "author_name": "John Eu Li Wong", - "author_inst": "National University of Singapore" + "author_name": "Ole Wichmann", + "author_inst": "Robert Koch Institute" }, { - "author_name": "Paul A MacAry", - "author_inst": "National University of Singapore" + "author_name": "Thomas Harder", + "author_inst": "Robert Koch Institute" }, { - "author_name": "Dean Ho", - "author_inst": "National University of Singapore" + "author_name": "Frank Schlosser", + "author_inst": "Robert Koch Institute" }, { - "author_name": "Agata Blasiak", - "author_inst": "National University of Singapore" + "author_name": "Dirk Brockmann", + "author_inst": "Robert Koch Institute" } ], "version": "1", @@ -233457,75 +232855,67 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.07.06.22277318", - "rel_title": "Understanding the dynamic relation between wastewater SARS-CoV-2 signal and clinical metrics throughout the pandemic", + "rel_doi": "10.1101/2022.07.07.22277360", + "rel_title": "Racial Disparities in Hesitancy and Utilization of Monoclonal Antibody Infusion Treatment of COVID-19", "rel_date": "2022-07-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.06.22277318", - "rel_abs": "Wastewater surveillance (WWS) of SARS-CoV-2 was proven to be a reliable and complementary tool for population-wide monitoring of COVID-19 disease incidence but was not as rigorously explored as an indicator for disease burden throughout the pandemic. Prior to global mass immunization campaigns and during the spread of the wildtype COVID-19 and the Alpha variant of concern (VOC), viral measurement of SARS-CoV-2 in wastewater was a leading indicator for both COVID-19 incidence and disease burden in communities. As the two-dose vaccination rates escalated during the spread of the Delta VOC in Jul. 2021 through Dec. 2021, relations weakened between wastewater signal and community COVID-19 disease incidence and maintained a strong relationship with clinical metrics indicative of disease burden (new hospital admissions, ICU admissions, and deaths). Further, with the onset of the vaccine-resistant Omicron BA.1 VOC in Dec. 2021 through Mar. 2022, wastewater again became a strong indicator of both disease incidence and burden during a period of limited natural immunization (no recent infection), vaccine escape, and waned vaccine effectiveness. Lastly, with the populations regaining enhanced natural and vaccination immunization shortly prior to the onset of the Omicron BA.2 VOC in mid-Mar 2022, wastewater is shown to be a strong indicator for both disease incidence and burden. Hospitalization-to-wastewater ratio is further shown to be a good indicator of VOC virulence when widespread clinical testing is limited. In the future, WWS is expected to show moderate indication of incidence and strong indication of disease burden in the community during future potential seasonal vaccination campaigns.\n\nHighlightsO_LINeed to elucidate interpretation of CoV-2 WWS for seasonal vaccination campaigns.\nC_LIO_LIWWS to incidence relation weakens with peak natural and vaccination immunization.\nC_LIO_LIWWS to hospitalization remains strong with natural and vaccination immunization.\nC_LIO_LIWWS as indicator of hospitalization during future seasonal vaccination campaigns.\nC_LIO_LIWWS/hospitalization as indicator of VOC virulence with limited clinical testing.\nC_LI", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.07.22277360", + "rel_abs": "Background and MethodsWe conducted a single center cross-sectional study to investigate racial disparities in the hesitancy and utilization of monoclonal antibody (mAb) treatment of COVID-19 among treatment eligible patients who were referred to the infusion center between January 4, 2021 and May 14, 2021.\n\nResultsAmong the 2,406 eligible participants, African Americans were significantly more likely to underutilize mAb treatment (OR 1.8; 95% CI 1.5-2.1) and miss treatment opportunities due to monoclonal hesitancy (OR 1.7, 95% CI 1.3-2.1).\n\nConclusionAddressing racial disparities in mAb delivery is an opportunity to bridge the racial inequities in COVID-19 care.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Nada Hegazy", - "author_inst": "University of Ottawa" - }, - { - "author_name": "Aaron Cowan", - "author_inst": "University of Ottawa" - }, - { - "author_name": "Patrick M. D'Aoust", - "author_inst": "University of Ottawa" + "author_name": "Yahya Shaikh", + "author_inst": "MITRE Corporation, Baltimore, Maryland, USA" }, { - "author_name": "Elisabeth Mercier", - "author_inst": "University of Ottawa" + "author_name": "Ishaan Gupta", + "author_inst": "Johns Hopkins University School of Medicine" }, { - "author_name": "Syeda Tasneem Towhid", - "author_inst": "University of Ottawa" + "author_name": "Sophia Purekal", + "author_inst": "Baltimore Convention Center Field Hospital, Baltimore, Maryland, USA" }, { - "author_name": "Jian-Jun Jia", - "author_inst": "University of Ottawa" + "author_name": "MaryJane E. Vaeth", + "author_inst": "Baltimore Convention Center Field Hospital, Baltimore, Maryland, USA" }, { - "author_name": "Shen Wan", - "author_inst": "University of Ottawa" + "author_name": "Maisha Foyez", + "author_inst": "Baltimore Convention Center Field Hospital, Baltimore, Maryland, USA" }, { - "author_name": "Zhihao Zhang", - "author_inst": "University of Ottawa" + "author_name": "Charles D. Callahan", + "author_inst": "Department of Population Health, University of Maryland Medical Center, Baltimore, Maryland, USA" }, { - "author_name": "Md Pervez Kabir", - "author_inst": "University of Ottawa" + "author_name": "Maryam Elhabashy", + "author_inst": "University of Maryland, Baltimore County, Maryland, USA" }, { - "author_name": "Wanting Fang", - "author_inst": "University of Ottawa" + "author_name": "James R Ficke", + "author_inst": "Department of Orthopaedic Surgery, Johns Hopkins University, Baltimore, Maryland, USA" }, { - "author_name": "Tyson E. Graber", - "author_inst": "Children's Hospital of Eastern Ontario Research Institute" + "author_name": "Albert W. Wu", + "author_inst": "Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA" }, { - "author_name": "Alex E. MacKenzie", - "author_inst": "Children's Hospital of Eastern Ontario Research Institute" + "author_name": "Paul Auwaerter", + "author_inst": "The Sherrilyn and Ken Fisher Center for Environmental Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA" }, { - "author_name": "Stephanie Guilherme", - "author_inst": "University of Ottawa" + "author_name": "Melinda E. Kantsiper", + "author_inst": "Division of Hospital Medicine, Johns Hopkins Bayview Medical Center, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA" }, { - "author_name": "Robert Delatolla", - "author_inst": "University of Ottawa" + "author_name": "Zishan K. Siddiqui", + "author_inst": "Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.07.06.22277303", @@ -236475,17 +235865,17 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2022.07.03.22277191", - "rel_title": "Basic reproduction number projection for novel pandemics and variants. Ancestral SARS-CoV2 R0 projection", + "rel_doi": "10.1101/2022.07.02.22276577", + "rel_title": "Revisiting biological sex as a risk factor for COVID-19: a fact or mirage of numbers?", "rel_date": "2022-07-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.03.22277191", - "rel_abs": "The recently derived Hybrid-Incidence Susceptible-TransmissibleRemoved (HI-STR) prototype is a deterministic epidemic compartment model and an alternative to the Susceptible-Infected-Removed (SIR) model prototype. The HI-STR predicts that pathogen transmission depends on host population characteristics including population size, population density and some common host behavioural characteristics.\n\nThe HI-STR prototype is applied to the ancestral Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) to show that the original estimates of the Coronavirus Disease 2019 (COVID-19) basic reproduction number ([R]0) for the United Kingdom (UK) could have been projected on the individual states of the United States of America (USA) prior to being detected in the USA.\n\nThe Imperial College London (ICL) groups[R] 0 estimate for the UK is projected onto each USA state. The difference between these projections and ICLs estimates for USA states is either not statistically significant on the paired student t-test or epidemiologically insignificant.\n\nProjection provides a baseline for evaluating the real-time impact of an intervention. Sensitivity analysis was conducted because of considerable variance in parameter estimates across studies. Although the HI-STR predicts that in-creasing symptomatic ratio and inherently immune ratio reduce[R] 0, relative to the uncertainty in the estimates of[R] 0 for the ancestral SARS-CoV2, the projection is insensitive to the inherently immune ratio and the symptomatic ratio.", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.02.22276577", + "rel_abs": "Biological sex is considered a risk factor for COVID-19. The prevailing view supposes males are about two-fold more impacted than females based on early-stage studies. The observed higher male deaths in COVID-19 are purportedly a result of biological differences that make males more vulnerable to adverse outcomes in infectious diseases. Research and policy paradigms seem to follow a similar line of thought to mitigate COVID-19 impact on populations. The analysis of sex-disaggregated data could help us evaluate the veracity of assertions for a preferred evidence-guided response. The analysis of the sex-disaggregated data available for the top 70 countries contributing about 80% of total deaths (as of 15 September 2021; on average two waves of infections experienced) indicates average Case Sex (Male: Female) ratio (CSR) of 1.09{+/-}0.35 (marginally more male cases) and Death Sex ratio (DSR) of 1.48{+/-} 0.47. Consideration of only laboratory-confirmed cases indicates the mortality sex ratio (MSR) in COVID-19 (MSR-COVID) to be 1.37{+/-}0.30. The prevailing MSR for the same countries was 1.758{+/-}0.409. The relative change in the mortality rate for males as compared to females in COVID-19 (ratio: MSR-COVID/prevailing MSR-PP) was 0.818{+/-}0.261 much lower than anticipated (2 or higher). Overall, over three-fold more countries (51/70) experienced a higher rate of female mortality than male mortality (15/70). Together, it suggests a more disproportionately severe impact of COVID-19 on females than on males, contrary to the prevailing view. Identification and analysis of country-specific factors contributing to differential impact on sexes, whether biological or environmental, seem warranted.", "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Ryan L Benjamin", - "author_inst": "Lancet Laboratories" + "author_name": "Samer Singh", + "author_inst": "Banaras Hindu University" } ], "version": "1", @@ -238493,47 +237883,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.07.01.22277061", - "rel_title": "The changing landscape of respiratory viruses contributing to respiratory hospitalisations: results from a hospital-based surveillance in Quebec, Canada, 2012-13 to 2021-22", + "rel_doi": "10.1101/2022.07.01.22277108", + "rel_title": "Self-Reported Use of COVID-19 Immunologic Test Results to Inform Decisions About Daily Activities and COVID-19 Vaccination", "rel_date": "2022-07-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.01.22277061", - "rel_abs": "BackgroundA comprehensive description of the combined effect of SARS-CoV-2 and respiratory viruses (RV) other than SARS-CoV-2 (ORV) on hospitalisations is lacking.\n\nAimTo compare viral etiology of acute respiratory infections (ARI) hospitalisations before and during two pandemic years from a surveillance network in Quebec, Canada.\n\nMethodWe compared detection of ORV and SARS-CoV-2 during 2020-21 and 2021-22 to 8 pre-pandemic influenza seasons in patients hospitalised with ARI who were tested systematically by a multiplex PCR.\n\nResultsDuring pre-pandemic influenza seasons, overall RV detection was 92.7% (1,493) (48.3% respiratory syncytial virus (RSV)) in children and 62.8% (4,339) (40.1% influenza) in adults. Overall RV detection in 2020-21 was 58.6% (29) in children (all ORV) and 43.7% (333) in adults (3.4% ORV, 40.3% SARS-CoV2, both including coinfections). In 2021-22 overall RV detection was 91.0% (201) in children (82.8% ORV, 8.1% SARS-CoV-2, both including coinfections) and 55.5% (527) in adults (14.1% ORV, 41.4% SARS-CoV-2, both including coinfections).\n\nVirtually no influenza was detected in 2020-21 and in 2021-22 up to epi-week 2022-9 presented here; no RSV was detected in 2020-21. In 2021-22, detection of RSV was comparable to pre-pandemic years but with an unusually early season. There were significant differences in ORV and SARS-CoV-2 detection between time periods and age groups.\n\nConclusionSignificant continuous shifts in age distribution and viral etiology of ARI hospitalisations occurred during two pandemic years. This reflects evolving RV epidemiology and underscores the need for increased scrutiny of ARI hospitalisation etiology to inform tailored public health recommendations.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.01.22277108", + "rel_abs": "ImportanceDespite widespread use of clinical diagnostic tests to assess prior exposure to SARS-CoV-2, limited evidence exists regarding how test results affect patient behaviors and decision-making.\n\nObjectiveTo understand the rationale behind ordering diagnostic T-cell receptor (TCR) immunosequencing for assessment of prior SARS-CoV-2 infection and evaluate how test results affect patient behaviors, including day-to-day activities and decisions about vaccination.\n\nDesignMandatory demographic information and clinical characteristics were collected for all individuals ordering T-Detect COVID. Study participants completed a one-time survey that included additional questions about demographics and clinical characteristics, relevant interactions with healthcare providers, reasons for ordering diagnostic TCR immunosequencing, and the utility of test results.\n\nSettingUS participants ordering T-Detect COVID between February 2021 and March 2022.\n\nParticipantsOf the 806 individuals who underwent diagnostic TCR immunosequencing, provided informed consent, and were sent the email survey, 718 completed the survey (response rate, 89.1%). At the time of receiving the test report, 25.5% of participants had been vaccinated against COVID-19, 29.7% reported a previous COVID-19 infection, and 25.6% were immunocompromised.\n\nMain Outcome(s) and Measure(s)Patient demographics and clinical characteristics were reported using descriptive statistics. Additional analyses explored trends in reported data over time and evaluated reasons for ordering diagnostic TCR immunosequencing and behaviors among participant subgroups (vaccinated or unvaccinated individuals and those with positive or negative test results). Logistic regression analysis evaluated factors that increased the likelihood of post-test vaccination.\n\nResultsStudy participants ordered diagnostic TCR immunosequencing to understand their health status (55.0%) and to inform decision-making about daily activities (43.6%) and vaccination (38.3%). Most participants (92.1%) ordered diagnostic TCR immunosequencing for themselves without consulting their physician. Testing negative for prior SARS-CoV-2 infection was associated with increased likelihood of subsequent COVID-19 vaccination (31.0% vs 6.9%; median time to vaccination, 17.0 days vs 47.5 days), which was confirmed by logistic regression analysis.\n\nConclusions and RelevanceThis report presents patient-reported clinical utility of a commercial COVID-19 assay based on an immune response readout. Our findings suggest that participants used diagnostic TCR immunosequencing results to inform decisions about daily activities and COVID-19 vaccination.\n\nTrial RegistrationNot applicable.\n\nKEY POINTSO_LIWe aimed to understand the factors driving immunologic testing for SARS-CoV-2 and characterize the actions and decisions spurred by test results.\nC_LIO_LIResults of this study suggest that individuals frequently ordered immunologic testing for themselves to understand their health status and to inform decision-making about daily activities and vaccination.\nC_LIO_LIAmong unvaccinated participants, testing negative for prior SARS-CoV-2 infection was associated with increased likelihood of undergoing vaccination and shorter time to vaccination.\nC_LIO_LIThis study provides the first real-world evidence of patient-perceived utility of a COVID-19 immunologic test for decision-making related to vaccination and lifestyle.\nC_LI", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Rodica Gilca", - "author_inst": "INSPQ" - }, - { - "author_name": "Rachid Amini", - "author_inst": "INSPQ" + "author_name": "Miao Jiang", + "author_inst": "Adaptive Biotechnologies" }, { - "author_name": "Sara Carazo", - "author_inst": "INSPQ" + "author_name": "Nicholas K. Akers", + "author_inst": "Adaptive Biotechnologies" }, { - "author_name": "Charles Frenette", - "author_inst": "CUSM" + "author_name": "Darcy B. Gill", + "author_inst": "Adaptive Biotechnologies" }, { - "author_name": "Guy Boivin", - "author_inst": "Research Centre CHU de Quebec- Universite Laval" + "author_name": "Benjamin Eckhert", + "author_inst": "Adaptive Biotechnologies" }, { - "author_name": "Hugues Charest", - "author_inst": "INSPQ" + "author_name": "Emily Svejnoha", + "author_inst": "Adaptive Biotechnologies" }, { - "author_name": "Jeannot Dumaresq", - "author_inst": "CISSS de Chaudiere-Appalaches" + "author_name": "Harlan S Robins", + "author_inst": "Adaptive Biotechnologies" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.07.01.22277163", @@ -240143,93 +239529,57 @@ "category": "rehabilitation medicine and physical therapy" }, { - "rel_doi": "10.1101/2022.06.28.22276654", - "rel_title": "Persistence of pneumococcal carriage among older adults in the community despite COVID-19 mitigation measures", + "rel_doi": "10.1101/2022.06.28.22276794", + "rel_title": "Safety and immunogenicity of an inactivated SARS-CoV-2 vaccine, KD-414, in healthy adult and elderly subjects: a randomized, double-blind, placebo-controlled, phase 1/2 clinical study in Japan", "rel_date": "2022-06-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.28.22276654", - "rel_abs": "BackgroundReported rates of invasive pneumococcal disease were markedly lower than normal during the 2020/2021 winter in the Northern Hemisphere, the first year after the start of the COVID-19 pandemic. However, little is known about rates of carriage of pneumococcus among adults during this period.\n\nMethodsBetween October 2020-August 2021, couples living in the Greater New Haven Area were enrolled if both individuals were aged 60 years and above and did not have any individuals under the age of 60 years living in the household. Saliva samples and questionnaires regarding social activities and contacts and medical history were obtained every 2 weeks for a period of 10 weeks. Following culture-enrichment, extracted DNA was tested using qPCR for pneumococcus-specific sequences piaB and lytA. Individuals were considered positive for pneumococcal carriage when Ct-values for piaB were less than 40.\n\nResultsWe collected 567 saliva samples from 95 individuals aged 60 years and above (47 household pairs and one singleton). Of those, 7.1% of samples tested positive for pneumococcus by either piaB only (n=6) or both piaB and lytA (n=34), representing 22/95 (23.2%) individuals and 16/48 (33.3%) households over the course of the 10-week study period. Study participants attended few social events during this period. However, many participants continued to have regular contact with children. Individuals who had regular contact with preschool and school aged children (i.e., 2-9 year olds) had a higher prevalence of carriage (15.9% vs 5.4%).\n\nConclusionsDespite COVID-19-related disruptions, a large proportion of older adults carried pneumococcus at least once during the 10-week study period. Prevalence was particularly high among those who had contact with school-aged children, but carriage was not limited to this group.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.28.22276794", + "rel_abs": "BackgroundIn the current protracted COVID-19 pandemic, SARS-CoV-2 vaccines that have the ability to be used safely and to prevent onset or severe disease are still highly needed. A Phase 1/2 study was conducted in healthy adults and the elderly in Japan to evaluate the immunogenicity, safety, and tolerability of an inactivated whole-virus vaccine (KD-414) that is under development.\n\nMethodsIn this double-blind, randomized, placebo-controlled, Phase 1/2 study, adults aged 20 to 64 years and elderly participants aged 65 years or older without a history of COVID-19 were randomly allocated to the following groups: the L group (2.5 g/dose), M group (5 g/dose), or H group (10 g/dose) with KD-414, or the placebo group (2:2:2:1). The participants received KD-414 or the placebo intramuscularly twice at intervals of 28 days. To determine the go-forward dose, safety after the first dosing and neutralizing antibody titers against SARS-CoV-2 at 28 days after the second dosing were evaluated for each group. Additionally, after unblinding, participants in the H group received a third dose of KD-414 (H) approximately 6 months after the second dosing for an exploratory evaluation of the safety and neutralizing antibody titers to be conducted.\n\nResultsA total of 210 participants were enrolled: 105 adults aged 20 to 64 years, and 105 elderly participants aged 65 years or older. Of these participants, 105 adults and 104 elderly participants completed the second dosing, and 28 adults and 31 elderly participants in the H group received a third dose of KD-414 (H). The incidence of adverse reactions from the first dosing to 28 days after the second dosing was 19 of 30 (63.3%), 22 of 31 (71.0%), 22 of 29 (75.9%), and six of 15 (40.0%) for adults, and 14 of 30 (46.7%), 14 of 29 (48.3%), 15 of 31 (48.4%), and six of 15 (40.0%) for elderly participants in the L, M, H, and placebo groups, respectively. No differences in incidence were shown among the KD-414 groups. The most common adverse reaction was injection site pain. Fever that resolved the following day was observed in only 1 adult in the H group after the second dosing; this was a sole Grade 3 or higher adverse reaction. For immunogenicity, the neutralizing antibody seroconversion rate (95% confidence intervals [CI]) against SARS-CoV-2 (vaccine strain) 28 days after the second dosing was 36.7% (19.9-56.1), 38.7% (21.8-57.8), and 72.4% (52.8-87.3) in adults, and 33.3% (17.3-52.8), 31.0% (15.3-50.8), and 45.2% (27.3-64.0) in elderly participants in the L, M, and H groups, respectively, showing a dose response by KD-414. The stratified analysis by age-range for the H group, which observed the highest immunogenicity, also showed an age dependency in the neutralizing antibody responses. Based on these results up to the second dosing, the H (10 g/dose) dosage was determined as the recommended dosage for further clinical development of KD-414. In addition, there was no particular difference between the incidence of adverse reactions after the third dosing and that after the second dosing with KD-414 (H) in participants. Moreover, the geometric mean neutralizing antibody titers (GMTs) against SARS-CoV-2 (vaccine strain) 28 days after the third dosing were 2-fold higher than those at 28 days after the second dosing, and the GMTs 13 weeks after the third dosing were 3-fold higher than those at 13 weeks after the second dosing. The stratified analysis by age-range of Pseudovirus SARS-CoV-2 (D614) spike protein neutralizing antibody titers showed 100.0% neutralizing antibody seroconversion rate and high neutralizing antibody titers in participants aged [≤] 40 years.\n\nConclusionKD-414 was well tolerated in healthy adults and the elderly at all doses evaluated. In view of the dose-response and age-dependency of the immunogenicity of KD-414 (H) (10 g/dose), it is expected to induce high neutralizing antibody titers, particularly in the age range of 20 to 40 years. A Phase 2/3 study (Japan Registry of Clinical Trials [jRCT] 2071210081), a Phase 3 study (jRCT 2031210679), and a Phase 2/3 study in pediatric participants aged 6 months to 17 years (jRCT 2031220032) using KD-414 (H) are ongoing.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Anne L Wyllie", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Sidiya Mbodj", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Darani A Thammavongsa", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Maikel S Hislop", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Devyn Yolda-Carr", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Pari Waghela", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Maura Nakahata", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Anne E Watkins", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Noel J Vega", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Anna York", - "author_inst": "Yale School of Public Health" + "author_name": "Mitsuyoshi Tanishima", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" }, { - "author_name": "Orchid M Allicock", - "author_inst": "Yale School of Public Health" + "author_name": "Kayo Ibaraki", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" }, { - "author_name": "Geisa Wilkins", - "author_inst": "Yale Center for Clinical Investigation" + "author_name": "Keishi Kido", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" }, { - "author_name": "Andrea Ouyang", - "author_inst": "Yale Center for Clinical Investigation" + "author_name": "Shun Nakayama", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" }, { - "author_name": "Laura Siqueiros", - "author_inst": "Yale Center for Clinical Investigation" + "author_name": "Shun Nakayama", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" }, { - "author_name": "Yvette Strong", - "author_inst": "Yale Center for Clinical Investigation" + "author_name": "Kohei Ata", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" }, { - "author_name": "Kelly Anastasio", - "author_inst": "Yale Center for Clinical Investigation" + "author_name": "Hideki Nakamura", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" }, { - "author_name": "Ronika Alexander-Parrish", - "author_inst": "Pfizer Inc" + "author_name": "Yasuhiko Shinmura", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" }, { - "author_name": "Adriano Arguedas", - "author_inst": "Pfizer Inc" + "author_name": "Kengo Sonoda", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" }, { - "author_name": "Bradford D Gessner", - "author_inst": "Pfizer Inc" + "author_name": "Kohji Ueda", + "author_inst": "Professor emeritus, Kyushu University, Fukuoka, Japan" }, { - "author_name": "Daniel Weinberger", - "author_inst": "Yale School of Public Health" + "author_name": "Yoshiaki Oda", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" } ], "version": "1", @@ -242009,27 +241359,71 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.06.24.22276836", - "rel_title": "The 2020 U.S. cancer screening deficit and the timing of adults' most recent screen: A population-based quasi-experiment", + "rel_doi": "10.1101/2022.06.23.22276820", + "rel_title": "IMMUNE PROFILES TO DISTINGUISH HOSPITALIZED VERSUS AMBULATORY COVID-19 CASES IN OLDER PATIENTS", "rel_date": "2022-06-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.24.22276836", - "rel_abs": "In 2020, cancer screenings declined, then rebounded, resulting in a cancer screening deficit. The significance of this deficit, however, has yet to be quantified from a population health perspective. Our study addresses this evidence gap by examining how the pandemic changed the timing of American adults most recent cancer screen. We obtained population-based, cancer screening data from the Behavioral Risk Factor Surveillance System. Mammograms, pap smears, and colonoscopies were each specified as a variable of mutually exclusive categories to indicate the timing since the most recent screening (never, 0-1 years, 1-2 years, 3+ years). Our quasi-experimental design restricts the sample to adults surveyed in January, February, or March. We then leverage a quirk in the BRFSS implementation and consider adults surveyed in the second year of each survey wave as the quasi-treatment cohort. Next, we constructed Linear and Logistic regression models which control for exogenous sociodemographic characteristics, state fixed effects, and temporal trends. Our results suggest that the deficit in 2020 was largely due to a one year delay among adults who receive annual screening, as the proportion of adults reporting a cancer screen in the past year declined by a nearly identical proportion of adults reporting their most recent cancer screen 1-2 years ago (3% to 4% points). However, the relative change was higher for mammograms and pap smears (17%) than colonoscopies (4%). We also found some evidence that the proportion of women reporting never having completed a mammogram declined in 2020, but the mechanisms for this finding should be further explored with the release of future data. Our estimates for the pandemics effect on cancer screening rates are smaller than prior studies, but because we account for temporal trends we believe prior studies overestimated the effect of the pandemic and underestimated the overall downward trend in cancer screenings across the country leading up to 2020.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.23.22276820", + "rel_abs": "BackgroundA fraction of COVID-19 patients develops severe disease requiring hospitalization, while the majority, including high-risk individuals, experience mild symptoms. Severe disease has been associated with higher levels of antibodies and inflammatory cytokines, but the association has often resulted from comparison of patients with diverse demographics and comorbidity status. This study examined patients with defined demographic risk factors for severe COVID-19 who developed mild vs. severe COVID-19.\n\nMethodsThis study evaluated hospitalized vs. ambulatory COVID-19 patients in the James J. Peters VA Medical Center, Bronx, NY. This cohort presented demographic risk factors for severe COVID-19: median age of 63, >80% male, >85% black and/or Hispanic. Sera were collected four to 243 days after symptom onset and evaluated for binding and functional antibodies as well as 48 cytokines/chemokines.\n\nFindingsAmbulatory and hospitalized patients showed no difference in SARS-CoV-2-specific antibody levels and functions. However, a strong correlation between anti-S2 antibody levels and the other antibody parameters was observed in hospitalized but not in ambulatory cases. Cytokine/chemokine levels also revealed differences, with notably higher IL-27 levels in hospitalized patients. Hence, among the older, mostly male patients studied here, SARS-CoV-2-specific antibody levels and functions did not distinguish hospitalized and ambulatory cases but a discordance in S2-specific antibody responses was noted in ambulatory patients, and elevated levels of specific cytokines were maintained in convalescent sera of hospitalized cases.\n\nInterpretationThe data indicate that antibodies against the relatively conserved S2 spike subunit and immunoregulatory cytokines such as IL-27 are potential immune determinants of COVID-19.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSPrevious studies demonstrated that high levels of SARS-CoV-2 spike binding antibodies and neutralizing antibodies were associated with COVID-19 disease severity. However, the comparisons were often made without considering demographics and comorbidities. Correlation was similarly shown between severe disease and marked elevation of several plasma cytokines but again, most analyses of cytokine responses to COVID-19 were conducted by comparison of patient cohorts with diverse demographic characteristics and risk factors.\n\nAdded value of this studyWe evaluated here a comprehensive profile of SARS-CoV-2-specific antibodies (total Ig, isotypes/subtypes, Fab- and Fc-mediated functions) and a panel of 48 cytokines and chemokines in serum samples from a cohort of SARS-CoV-2-infected patients with demographic risk factors for severe COVID-19: 81% were male, 79% were >50 years old (median of 63), and 85% belonged to US minority groups (black and/or Hispanic). Comparison of hospitalized vs. ambulatory patients within this cohort revealed two features that differed between severe vs. mild COVID-19 cases: a discordant Ab response to the S2 subunit of the viral spike protein in the mild cases and an elevated response of specific cytokines and chemokines, notably IL-27, in the severe cases.\n\nImplications of all the available evidenceData from the study identified key immunologic markers for severe vs. mild COVID-19 that provide a path forward for investigations of their roles in minimizing or augmenting disease severity.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Jason Semprini", - "author_inst": "University of Iowa" + "author_name": "Jeromine Klingler", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Radhika Ranganathan", - "author_inst": "University of South Carolina" + "author_name": "Gregory S Lambert", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Juan C Bandres", + "author_inst": "James J. Peters VA Medical Center" + }, + { + "author_name": "Rozita Emami-Gorizi", + "author_inst": "James J. Peters VA Medical Center" + }, + { + "author_name": "Arthur Nadas", + "author_inst": "NYU School of Medicine" + }, + { + "author_name": "Kasopefoluwa Y Oguntuyo", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Fatima Amanat", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "- PARIS Study Team", + "author_inst": "" + }, + { + "author_name": "Viviana Simon", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Benhur Lee", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Susan Zolla-Pazner", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Chitra Upadhyay", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Catarina E Hioe", + "author_inst": "Icahn School of Medicine at Mount Sinai" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.06.24.22276852", @@ -243603,49 +242997,89 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.06.25.22276445", - "rel_title": "SARS-CoV-2 evolution and evasion from multiple antibody treatments in a cancer patient", + "rel_doi": "10.1101/2022.06.24.22276703", + "rel_title": "A Bivalent Omicron-containing Booster Vaccine Against Covid-19", "rel_date": "2022-06-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.25.22276445", - "rel_abs": "Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in immunocompromised patients may lead to accelerated viral mutation rate, immune evasion and persistent viral shedding over many months. Here we report the case of a severely immunocompromised cancer patient infected with the Delta variant of SARS-CoV-2 for over 8 months. Genome sequencing of samples taken after repeated monoclonal antibody treatments reveal the emergence and accumulation of mutations enabling escape from neutralization by antibodies. Mutations emerging in accessory and non-structural viral proteins target specific residues of immunomodulatory domains, potentially leading to loss of some functions, while preserving others. The mutated virus managed to completely overcome neutralization by monoclonal antibodies while remaining viable and infective. Our results suggest that the loss of specific immunomodulatory viral functions might confer a selective advantage in immunocompromised hosts. We also compare between mutations emerging in the presence and absence of neutralizing antibodies.\n\nHighlightsO_LISARS-CoV-2 undergoes rapid evolution in an immunocompromised, chronically infected cancer patient, overcoming neutralization by two monoclonal antibody cocktail treatments\nC_LIO_LIReceptor binding domain (RBD) mutations emerging after monoclonal antibody treatment enable effective escape from neutralization in the absence of adaptive immunity\nC_LIO_LISome emerging mutations are predicted to disrupt immunomodulatory viral proteins, including prevention of ORF8 homodimerization, mis-localization of ORF3a in host cells and alteration of the host-suppressive function of NSP1\nC_LI", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.24.22276703", + "rel_abs": "BackgroundUpdated vaccination strategies against acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern are needed. Interim results of the safety and immunogenicity of the bivalent omicron-containing mRNA-1273.214 booster candidate are presented.\n\nMethodsIn this ongoing, phase 2/3 trial, the 50-g bivalent vaccine mRNA-1273.214 (25-g each ancestral Wuhan-Hu-1 and omicron B.1.1.529 spike SARS-CoV-2 mRNAs) was compared to the authorized 50-g mRNA-1273 booster in adults who previously received 2-dose primary series of 100-g mRNA-1273 and a first booster dose of 50-g mRNA-1273 at least 3 months prior. Primary objectives were safety and reactogenicity, and immunogenicity of 50-g mRNA-1273.214 compared with 50-g mRNA-1273. Immunogenicity data 28 days after the booster dose are presented.\n\nResultsFour hundred thirty-seven and 377 participants received 50-g of mRNA-1273.214, or mRNA-1273, respectively. Median time between first and second booster doses of mRNA-1273.214 and mRNA-1273 were similar (136 and 134 days, respectively). In participants with no prior SARS-CoV-2 infection, observed omicron neutralizing antibody geometric mean titers (GMTs [95% confidence interval]) after the mRNA-1273.214 and mRNA-1273 booster doses, were 2372.4 (2070.6-2718.2) and 1473.5 (1270.8-1708.4) respectively and the model-based GMT ratio (97.5% confidence interval) was 1.75 (1.49-2.04). All pre-specified non-inferiority (ancestral SARS-CoV-2 with D614G mutation [D614G] GMT ratio; ancestral SARS-CoV-2 [D614G] and omicron seroresponse rates difference) and superiority primary objectives (omicron GMT ratio) for mRNA-1273.214 compared to mRNA-1273 were met. Additionally, mRNA-1273.214 50-g induced a potent neutralizing antibody response against omicron subvariants BA.4/BA.5 and higher binding antibody responses against alpha, beta, gamma, delta and omicron variants. Safety and reactogenicity profiles were similar and well-tolerated for both vaccines groups.\n\nConclusionThe bivalent vaccine mRNA-1273.214 50-g was well-tolerated and elicited a superior neutralizing antibody response against omicron, compared to mRNA-1273 50-g, and a non-inferior neutralizing antibody response against the ancestral SARS-CoV-2 (D614G), 28 days after immunization, creating a new tool as we respond to emerging SARS-CoV-2 variants.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Guy Shapira", - "author_inst": "Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel" + "author_name": "Spyros Chalkias", + "author_inst": "Moderna, Inc." }, { - "author_name": "Chen Weiner", - "author_inst": "Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel" + "author_name": "Charles Harper", + "author_inst": "Meridian Clinical Research" }, { - "author_name": "Reut Sorek Abramovich", - "author_inst": "Shamir Medical Center, Shamir Medical Center (Assaf Harofeh), Zerifin, Israel" + "author_name": "Keith Vrbicky", + "author_inst": "Meridian Clinical Research" }, { - "author_name": "Odit Gutwein", - "author_inst": "Department of Hematology, Shamir Medical Center (Assaf Harofeh), Zerifin, Israel" + "author_name": "Stephen R Walsh", + "author_inst": "Brigham and Women's Hospital" }, { - "author_name": "Nir Rainy", - "author_inst": "Shamir Medical Center, Shamir Medical Center (Assaf Harofeh), Zerifin, Israel" + "author_name": "Brandon Essink", + "author_inst": "Meridian Clinical Research" }, { - "author_name": "Patricia Benveniste-Levkovitz", - "author_inst": "Shamir Medical Center, Shamir Medical Center (Assaf Harofeh), Zerifin, Israel" + "author_name": "Adam Brosz", + "author_inst": "Meridian Clinical Research" }, { - "author_name": "Ezra Gordon", - "author_inst": "Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel" + "author_name": "Nichole McGhee", + "author_inst": "Moderna, Inc." }, { - "author_name": "Adina Bar Chaim", - "author_inst": "Shamir Medical Center, Shamir Medical Center (Assaf Harofeh), Zerifin, Israel" + "author_name": "Joanne E Tomassini", + "author_inst": "Moderna, Inc." }, { - "author_name": "Noam Shomron", - "author_inst": "Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel" + "author_name": "Xing Chen", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Ying Chang", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Andrea Sutherland", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "David C Montefiori", + "author_inst": "Duke University" + }, + { + "author_name": "Bethany Girard", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Darin K Edwards", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Jing Feng", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Honghong Zhou", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Lindsey R Baden", + "author_inst": "Brigham and Women's Hospital" + }, + { + "author_name": "Jacqueline M Miller", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Rituparna Das", + "author_inst": "Moderna, Inc." } ], "version": "1", @@ -245369,69 +244803,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.06.21.22276668", - "rel_title": "Persistence of SARS-CoV-2 omicron variant in children and utility of rapid antigen testing as an indicator of culturable virus", + "rel_doi": "10.1101/2022.06.20.22276662", + "rel_title": "Multiple cohort study of hospitalized SARS-CoV-2 in-host infection dynamics: parameter estimates, sensitivity and the eclipse phase profile", "rel_date": "2022-06-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.21.22276668", - "rel_abs": "We screened 65 longitudinally-collected nasal swab samples from 31 children aged 0-16 years who were positive for SARS-CoV-2 omicron BA.1. By day 7 after onset of symptoms 48% of children remained positive by rapid antigen test. In a sample subset we found 100% correlation between antigen test results and virus culture.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.20.22276662", + "rel_abs": "Within-host SARS-CoV-2 modelling studies have been published throughout the COVID-19 pandemic. These studies contain highly variable numbers of individuals and capture varying timescales of pathogen dynamics; some studies capture the time of disease onset, the peak viral load and subsequent heterogeneity in clearance dynamics across individuals, while others capture late-time post-peak dynamics. In this study, we curate multiple previously published SARS-CoV-2 viral load data sets, fit these data with a consistent modelling approach, and estimate the variability of in-host parameters including the basic reproduction number, R0. We find that fitted dynamics can be highly variable across data sets, and highly variable within data sets, particularly when key components of the dynamic trajectories (e.g. peak viral load) are not represented in the data. Further, we investigated the role of the eclipse phase time distribution in fitting SARS-CoV-2 viral load data. By varying the shape parameter of an Erlang distribution, we demonstrate that models with either no eclipse phase, or with an exponentially-distributed eclipse phase, offer significantly worse fits to these data, whereas models with less dispersion around the mean eclipse time (shape parameter two or more) offered the best fits to the available data.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Zoe M Lohse", - "author_inst": "Emerging Pathogens Institute, University of Florida" - }, - { - "author_name": "Jerne J Shapiro", - "author_inst": "College of Public Health and Health Professions, University of Florida" - }, - { - "author_name": "John A Lednicky", - "author_inst": "Emerging Pathogens Institute, University of Florida" - }, - { - "author_name": "Melanie N. Cash", - "author_inst": "College of Medicine, University of Florida" - }, - { - "author_name": "Inyoung Jun", - "author_inst": "College of Public Health and Health Professions, University of Florida" - }, - { - "author_name": "Carla Mavian", - "author_inst": "College of Medicine, University of Florida" - }, - { - "author_name": "Massimiliano S Tagliamonte", - "author_inst": "College of Medicine, University of Florida" + "author_name": "Chapin S. Korosec", + "author_inst": "York University" }, { - "author_name": "Cyrus Saleem", - "author_inst": "Emerging Pathogens Institute, University of Florida" + "author_name": "Matthew I. Betti", + "author_inst": "Mount Allison University" }, { - "author_name": "Yang Yang", - "author_inst": "University of Florida" + "author_name": "David W Dick", + "author_inst": "York University" }, { - "author_name": "Eric Jorge Nelson", - "author_inst": "University of Florida" + "author_name": "Hsu Kiang Ooi", + "author_inst": "National Research Council Canada" }, { - "author_name": "Marco Salemi", - "author_inst": "University of Florida" + "author_name": "Iain R. Moyles", + "author_inst": "York University" }, { - "author_name": "Kathleen Ann Ryan", - "author_inst": "College of Medicine, University of Florida" + "author_name": "Lindi M. Wahl", + "author_inst": "Western University" }, { - "author_name": "John Glenn Morris Jr.", - "author_inst": "Emerging Pathogens Institute, University of Florida" + "author_name": "Jane M Heffernan", + "author_inst": "York University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -247343,67 +246753,23 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.06.20.22276574", - "rel_title": "Adult mortality before and during the COVID-19 pandemic in nine communities of Yemen: a key informant study", + "rel_doi": "10.1101/2022.06.15.22276447", + "rel_title": "Ventilation Requirements and Recommendations for Controlling SARS-CoV-2 and Variants Outbreaks in Indoor Gathering Places with Close Contact", "rel_date": "2022-06-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.20.22276574", - "rel_abs": "IntroductionWidespread armed conflict has affected Yemen since 2014. To date, the mortality toll of seven years of crisis, and any excess due to the COVID-19 pandemic, are not well quantified. We attempted to estimate population mortality during the pre-pandemic and pandemic periods in nine purposively selected urban and rural communities of southern and central Yemen (Aden and Taiz governorates), totalling > 100,000 people.\n\nMethodsWithin each study site, we collected lists of decedents between January 2014-March 2021 by interviewing different categories of key community informants, including community leaders, imams, healthcare workers, senior citizens and others. After linking records across lists based on key variables, we applied two-, three- or four-list capture-recapture analysis to estimate total death tolls. We also computed death rates by combining these estimates with population denominators, themselves subject to estimation.\n\nResultsAfter interviewing 138 disproportionately (74.6%) male informants, we identified 2445 unique decedents. While informants recalled deaths throughout the study period, reported deaths among children were sparse: we thus restricted analysis to persons aged [≥]15 years old. We noted a peak in reported deaths during May-July 2020, plausibly coinciding with the first COVID-19 wave. Death rate estimates featured uninformatively large confidence intervals, but appeared elevated compared to the non-crisis baseline, particularly in two sites where a large proportion of deaths were attributed to war injuries. There was no clear-cut evidence of excess mortality during the pandemic period.\n\nConclusionsWe found some evidence of a peak in mortality during the early phase of the pandemic, but death rate estimates were otherwise too imprecise to enable strong inference on trends. Estimates suggested substantial mortality elevations from baseline during the crisis period, but are subject to serious potential biases. The study highlighted challenges of data collection in this insecure, politically contested environment.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.15.22276447", + "rel_abs": "Unexpected rapid infection involving SARS-CoV-2 variant Omicron known as the fifth wave of outbreak occurred since early January 2022 in Hong Kong. Almost 1.2 million citizens were infected in three months. Ventilation provisions in some gathering places with close contact such as restaurants were found to be lower than requirements, believed to be one of the main causes of transmission in these indoor spaces. At the end of the fifth outbreak in mid-May 2022, group infections were still found in several such gathering places including restaurants and pubs due to inadequate ventilation provisions. There are worries about triggering the sixth wave of outbreak.\n\nKey points related to ventilation requirements in such gathering places are discussed in this paper. Adequate ventilation of 6 air changes per hour minimum must be provided to avoid direct air transmission of virus. Indoor aerodynamics induced by ventilation system must be considered too. However, it is difficult to measure ventilation rate quickly and accurately. A control scheme on virus outbreaks is proposed on installing mechanical ventilation energy use meters and carbon dioxide sensors for checking ventilation provisions adequacy quickly.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Mervat Alhaffar", - "author_inst": "London School of Hygiene & Tropical Medicine" - }, - { - "author_name": "Huda BaSaleem", - "author_inst": "Department of Community Medicine and Public Health, Faculty of Medicine and Health Science University of Aden, Aden, Yemen" - }, - { - "author_name": "Fouad Othman", - "author_inst": "Faculty of Medicine and Health Science Taiz University, Taiz, Yemen" - }, - { - "author_name": "Khaled Alsakkaf", - "author_inst": "Department of Community Medicine and Public Health, Faculty of Medicine and Health Science University of Aden, Aden, Yemen" - }, - { - "author_name": "Sena Mohammed Mohsen Alkhteeb", - "author_inst": "Epidemiology Surveillance Office, Taiz Governorate Health Office, Taiz, Yemen" - }, - { - "author_name": "Hussein Kolaise", - "author_inst": "Department of Internal Medicine, Faculty of Medicine and Health Science University of Aden, Aden, Yemen" - }, - { - "author_name": "Abdullah K. Babattah", - "author_inst": "Primary Health Care Program, Health Sector, HUMAN ACCESS for Partnership and Development Aden, Yemen" - }, - { - "author_name": "Yaseen Abdulmalik Mahyoub Salem", - "author_inst": "Epidemiology Surveillance Office, Taiz Governorate Health Office, Taiz, Yemen" - }, - { - "author_name": "Hannah Brindle", - "author_inst": "Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK" - }, - { - "author_name": "Najwa Yahya", - "author_inst": "Yemen Public Health Network, Aden, Yemen" - }, - { - "author_name": "Pasquale Pepe", - "author_inst": "Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK" - }, - { - "author_name": "Francesco Checchi", - "author_inst": "Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK" + "author_name": "W.K. Chow", + "author_inst": "The Hong Kong Polytechnic University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "health policy" }, { "rel_doi": "10.1101/2022.06.20.22276596", @@ -249309,75 +248675,83 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.06.17.22276433", - "rel_title": "It hurts your heart: frontline healthcare worker experiences of moral injury during the COVID-19 pandemic", + "rel_doi": "10.1101/2022.06.16.22276480", + "rel_title": "Immunogenicity following two doses of BBIBP-CorV vaccine and a third booster dose with viral vector and mRNA COVID-19 vaccines against delta and omicron variants in prime immunized adults with two doses of BBIBP-CorV vaccine", "rel_date": "2022-06-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.17.22276433", - "rel_abs": "BackgroundMoral injury is defined as the strong emotional and cognitive reactions following events which clash with someones moral code, values or expectations. During the COVID-19 pandemic, increased exposure to potentially morally injurious events (PMIEs) has placed healthcare workers (HCWs) at risk of moral injury. Yet little is known about the lived experience of cumulative PMIE exposure and how NHS staff respond to this.\n\nObjectiveWe sought to rectify this knowledge gap by qualitatively exploring the lived experiences and perspectives of clinical frontline NHS staff who responded to COVID-19.\n\nMethodsWe recruited a diverse sample of 30 clinical frontline HCWs from the NHS CHECK study cohort, for single time point qualitative interviews. All participants endorsed at least one item on the 9-item Moral Injury Events Scale (MIES) (Nash et al., 2013) at six month follow up. Interviews followed a semi-structured guide and were analysed using reflexive thematic analysis.\n\nResultsHCWs described being routinely exposed to ethical conflicts, created by exacerbations of pre-existing systemic issues including inadequate staffing and resourcing. We found that HCWs experienced a range of mental health symptoms primarily related to perceptions of institutional betrayal as well as feeling unable to fulfil their duty of care towards patients.\n\nConclusionThese results suggest that a multi-facetted organisational strategy is warranted to prepare for PMIE exposure, promote opportunities for resolution of symptoms associated with moral injury and prevent organisational disengagement.\n\nHighlightsO_LIClinical frontline healthcare workers (HCWs) have been exposed to an accumulation of potentially morally injurious events (PMIEs) throughout the COVID-19 pandemic, including feeling betrayed by both government and NHS leaders as well as feeling unable to provide duty of care to patients\nC_LIO_LIHCWs described the significant adverse impact of this exposure on their mental health, including increased anxiety and depression symptoms and sleep disturbance\nC_LIO_LIMost HCWs interviewed believed that organisational change within the NHS was necessary to prevent excess PMIE exposure and promote resolution of moral distress\nC_LI", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.16.22276480", + "rel_abs": "Coronavirus disease 2019 (COVID-19) booster vaccination is being comprehensively evaluated globally due to waning immunity and the emergence of new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Therefore, this study aimed to evaluate antibody responses in individuals vaccinated with two doses of BBIBP-CorV vaccine and to explore the boosting effect of the different vaccine platforms in BBIBP-CorV-primed healthy adults, including viral vector vaccine (AZD122) and mRNA vaccines (BNT162b2 and mRNA-1273). The results showed that, in the BBIBP-CorV prime group, the total receptor-binding domain (RBD) immuno-globulin (Ig) and anti-RBD IgG levels waned significantly at 3 months after receiving the second dose. However, after the booster, RBD-specific binding antibody levels increased. Neutralizing antibody measured by a surrogate neutralization test showed of inhibition over 90% against the SARS-CoV-2 delta variant but less than 70% against omicron variant after the third dose on day 28. All booster vaccines could induce the total IFN-{square} T-cell response. The reactogenicity was acceptable and well tolerated without serious adverse events. This study supported administration of the third dose with either viral vector or mRNA vaccine for the BBIBP-CorV-primed individuals to stimulate antibody and T cell responses.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Siobhan Hegarty", - "author_inst": "King's College London" + "author_name": "Jira Chansaenroj", + "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University" }, { - "author_name": "Danielle Lamb", - "author_inst": "UCL" + "author_name": "Nungruthai Suntronwong", + "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University" }, { - "author_name": "Sharon Stevelink", - "author_inst": "King's College London" + "author_name": "Sitthichai Kanokudom", + "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University" }, { - "author_name": "Rupa Bhundia", - "author_inst": "King's College London" + "author_name": "Suvichada Assawakosri", + "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University" }, { - "author_name": "Rosalind Raine", - "author_inst": "University College London" + "author_name": "Ritthideach Yorsaeng", + "author_inst": "Faculty of Medicine, Chulalongkorn University" }, { - "author_name": "Mary Jane Docherty", - "author_inst": "South London and Maudsley NHS Foundation Trust" + "author_name": "Preeyaporn Vichaiwattana", + "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University" }, { - "author_name": "Hannah Rachel Scott", - "author_inst": "King's College London" + "author_name": "Sirapa Klinfueng", + "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University" }, { - "author_name": "Anne Marie Rafferty", - "author_inst": "King's College London" + "author_name": "Lakana Wongsrisang", + "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University" }, { - "author_name": "Victoria Williamson", - "author_inst": "King's College London" + "author_name": "Donchida Srimuan", + "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University" }, { - "author_name": "Sarah Dorrington", - "author_inst": "King's College London" + "author_name": "Thaksaporn Thatsanatorn", + "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University" }, { - "author_name": "Matthew hotopf", - "author_inst": "King's College London" + "author_name": "Thanunrat Thongmee", + "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University" }, { - "author_name": "Reza Razavi", - "author_inst": "King's College London" + "author_name": "Chompoonut Auphimai", + "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University" }, { - "author_name": "Neil Greenberg", - "author_inst": "King's College London" + "author_name": "Pornjarim Nilyanimit", + "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University" }, { - "author_name": "Simon Wessely", - "author_inst": "King's College London" + "author_name": "Nasamon Wanlapakorn", + "author_inst": "Division of Academic Affairs, Faculty of Medicine, Chulalongkorn University" + }, + { + "author_name": "Natthinee Sudhinaraset", + "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University" + }, + { + "author_name": "yong Poovorawan", + "author_inst": "Chulalongkorn University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.06.16.22276392", @@ -251171,71 +250545,79 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.06.14.22276236", - "rel_title": "Titers and capacity of neutralizing antibodies against SARS-CoV-2 variants after heterologous booster vaccination in health care workers primed with two doses of ChAdOx1 nCov-19: a single-blinded, randomized clinical trial", + "rel_doi": "10.1101/2022.06.14.22276166", + "rel_title": "Overt and occult hypoxemia in patients hospitalized with novel coronavirus disease 2019", "rel_date": "2022-06-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.14.22276236", - "rel_abs": "BackgroundBooster vaccination is important because of waning immunity and variant immune evasion. We conducted a single-blinded, randomized trial to evaluate the safety, reactogenicity, and immunogenicity of heterologous booster vaccination in health care workers (HCW) who had received two doses of ChAdOx1 nCov-19.\n\nMethods and findingsHCW at least 90 days after the second dose were enrolled to receive one of the four vaccines: BNT162b2, half-dose mRNA-1273, mRNA-1273, and MVC-COV1901. The primary outcomes were humoral and cellular immunogenicity and the secondary outcomes safety and reactogenicity 28 days post-booster. 340 HCW were enrolled: 83 received BNT162b2 (2 excluded), 85 half-dose mRNA-1273, 85 mRNA-1273, and 85 MVC-COV1901. mRNA vaccines had more reactogenicity than protein vaccine.\n\nAnti-spike IgG increased by a fold of 8.4 for MCV-COV1901, 32.2 for BNT162b2, 47.6 for half-dose mRNA-1273 and 63.2 for mRNA1273. The live virus microneutralization assay (LVMNA) against the wild type, alpha and delta variants were consistent with anti-spike IgG for all booster vaccines. The LVMNA in the four groups against omicron variant were 6.4 to 13.5 times lower than those against the wild type. Serum neutralizing antibody against omicron variant was undetectable in 60% of the participants who received MCV-COV1901 as a booster by LVMNA. By using pseudovirus neutralizing assay, we found that neutralization activity in the four groups against omicron variant were 4.6 to 5.2 times lower than that against the D614G. All booster vaccines induced comparable T cell response.\n\nConclusionsThird dose booster not only increases neutralizing antibody titer but also enhances antibody capacity against SARS-CoV-2 variants. mRNA vaccines are preferred booster vaccines for those after primary series of ChAdOx1 nCov-19.\n\nTrial registrationClinicalTrials.gov NCT05132855", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.14.22276166", + "rel_abs": "BackgroundProgressive hypoxemia is the predominant mode of deterioration in COVID-19. Among hypoxemia measures, the ratio of the partial pressure of arterial oxygen to the fraction of inspired oxygen (P/F ratio) has optimal construct validity but poor availability because it requires arterial blood sampling. Pulse oximetry reports oxygenation continuously, but occult hypoxemia can occur in Black patients because the technique is affected by skin color. Oxygen dissociation curves allow non-invasive estimation of P/F ratios (ePFR) but this approach remains unproven.\n\nResearch QuestionCan ePFRs measure overt and occult hypoxemia?\n\nStudy Design and methodsWe retrospectively studied COVID-19 hospital encounters (n=5319) at two academic centers (University of Virginia [UVA] and Emory University). We measured primary outcomes (death or ICU transfer within 24 hours), ePFR, conventional hypoxemia measures, baseline predictors (age, sex, race, comorbidity), and acute predictors (National Early Warning Score (NEWS) and Sepsis-3). We updated predictors every 15 minutes. We assessed predictive validity using adjusted odds ratios (AOR) and area under receiver operating characteristics curves (AUROC). We quantified disparities (Black vs non-Black) in empirical cumulative distributions using the Kolmogorov-Smirnov (K-S) two-sample test.\n\nResultsOvert hypoxemia (low ePFR) predicted bad outcomes (AOR for a 100-point ePFR drop: 2.7 [UVA]; 1.7 [Emory]; p<0.01) with better discrimination (AUROC: 0.76 [UVA]; 0.71 [Emory]) than NEWS (AUROC: 0.70 [UVA]; 0.70 [Emory]) or Sepsis-3 (AUROC: 0.68 [UVA]; 0.65 [Emory]). We found racial differences consistent with occult hypoxemia. Black patients had better apparent oxygenation (K-S distance: 0.17 [both sites]; p<0.01) but, for comparable ePFRs, worse outcomes than other patients (AOR: 2.2 [UVA]; 1.2 [Emory], p<0.01).\n\nInterpretationThe ePFR was a valid measure of overt hypoxemia. In COVID-19, it may outperform multi-organ dysfunction models like NEWS and Sepsis-3. By accounting for biased oximetry as well as clinicians real-time responses to it (supplemental oxygen adjustment), ePFRs may enable statistical modelling of racial disparities in outcomes attributable to occult hypoxemia.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Chih-Hsien Chuang", - "author_inst": "St. Paul's Hospital" + "author_name": "Shrirang Mukund Gadrey", + "author_inst": "University of Virginia" }, { - "author_name": "Chung-Guei Huang", - "author_inst": "Linkou Chang Gung Memorial Hospital: Chang Gung Memorial Hospital" + "author_name": "Piyus Mohanty", + "author_inst": "Emory University" }, { - "author_name": "Ching-Tai Huang", - "author_inst": "Chang Gung Memorial Hospital Taoyuan Branch: Taoyuan Chang Gung Memorial Hospital" + "author_name": "Sean P Haughey", + "author_inst": "University of Virginia" }, { - "author_name": "Yi-Ching Chen", - "author_inst": "Chang Gung Memorial Hospital Linkou Main Branch: Chang Gung Memorial Hospital" + "author_name": "Beck A Jacobsen", + "author_inst": "University of Virginia" }, { - "author_name": "Yu-An Kung", - "author_inst": "Chang Gung University College of Medicine" + "author_name": "Kira J Dubester", + "author_inst": "University of Virginia" }, { - "author_name": "Chih-Jung Chen", - "author_inst": "Chang Gung Memorial Hospital Linkou Main Branch: Chang Gung Memorial Hospital" + "author_name": "Katherine M Webb", + "author_inst": "University of Virginia" }, { - "author_name": "Tzu-Chun Chuang", - "author_inst": "Chang Gung Memorial Hospital Linkou Main Branch: Chang Gung Memorial Hospital" + "author_name": "Rebecca L Kowalski", + "author_inst": "University of Virginia" }, { - "author_name": "Ching-Chi Liu", - "author_inst": "Chang Gung Memorial Hospital Linkou Main Branch: Chang Gung Memorial Hospital" + "author_name": "Jessica J Dreicer", + "author_inst": "University of Virginia" }, { - "author_name": "Po-Wei Huang", - "author_inst": "Chang Gung Memorial Hospital Linkou Main Branch: Chang Gung Memorial Hospital" + "author_name": "Robert T Andris", + "author_inst": "University of Virginia" }, { - "author_name": "Shu-Li Yang", - "author_inst": "Chang Gung Memorial Hospital Linkou Main Branch: Chang Gung Memorial Hospital" + "author_name": "Matthew T Clark", + "author_inst": "Nihon Kohden Digital Health Solutions Inc" }, { - "author_name": "Po-Wen Gu", - "author_inst": "Chang Gung Memorial Hospital Linkou Main Branch: Chang Gung Memorial Hospital" + "author_name": "Christopher C Moore", + "author_inst": "University of Virginia" }, { - "author_name": "Shin-Ru Shih", - "author_inst": "Chang Gung University College of Medicine" + "author_name": "Andre Holder", + "author_inst": "Emory University" }, { - "author_name": "Cheng-Hsun Chiu", - "author_inst": "Chang Gung Memorial Hospital" + "author_name": "Rishi Kamaleswaran", + "author_inst": "Emory University" + }, + { + "author_name": "Sarah J Ratcliffe", + "author_inst": "University of Virginia" + }, + { + "author_name": "J Randall Moorman", + "author_inst": "University of Virginia" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2022.06.13.22276339", @@ -253417,51 +252799,35 @@ "category": "neurology" }, { - "rel_doi": "10.1101/2022.06.13.22276341", - "rel_title": "Telemedicine Ready or Not? a cross-sectional assessment of telemedicine maturity of federally funded tertiary health institutions in Nigeria.", + "rel_doi": "10.1101/2022.06.09.22275881", + "rel_title": "Effect of HIV disease and the associated moderators on COVID-19 related Mortality", "rel_date": "2022-06-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.13.22276341", - "rel_abs": "Background and ObjectiveTelemedicine (TM) has solidified its place as a means for continuity of healthcare services and a cost-effective approach for improving health equity as demonstrated during the COVID-19 pandemic. Preparedness of health systems for telemedicine is an indicator of the scalability of their services, especially during disasters. We aimed to assess the maturity and preparedness of federally funded tertiary health institutions (FFTHIs) in Nigeria, to deploy and integrate telemedicine\n\nMethodsWe conducted a cross-sectional study of randomly selected FFTHIs in Nigeria using PAHOs tool for assessing the maturity level of health institutions to implement telemedicine services. Descriptive statistics were used for overall maturity levels and non-parametric tests to compare scores for overall maturity and specific PAHO domains per region. The level of significance was set at p value <0.05.\n\nResultsTwenty-four of thirty randomly polled FFTHIs responded (response rate of 77.4%). Overall, the median TM maturity level was 2.0 (1.75) indicating beginner level. No significant inter-zonal difference in median overall maturity level (p=0.87). The median maturity levels for telemedicine readiness in specific domains were organizational readiness - 2.0 (2.0), processes 1.0 (1.0), digital environment 2.0 (3.0), human resources 2.0 (1.0), regulatory issues- 1.5 (1.0) and expertise 2.0 (2.0); mostly at beginner level, with no inter-zonal differences. Most participating institutions had no initiatives in place for domains of processes and regulatory issues.\n\nConclusionsThe current status of telemedicine maturity of FFTHIs in Nigeria behoves policy makers to advance the implementation of telemedicine across the country as part of national digital quality healthcare.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.09.22275881", + "rel_abs": "IntroductionEstablished predictors for COVID 19 related mortalities are diverse. The impact of these several risk factors on coronavirus mortality have been previously reported in several meta-analyses limited by small sample sizes and premature data. The objective of this systematic review and meta-analysis coupled with meta-regression was to evaluate the updated evidence on the risk of COVID 19 related mortality by HIV serostatus using published data, and account for possible moderators.\n\nMethodElectronic databases including Google Scholar, Cochrane Library, Web of Sciences (WOS), EMBASE, Medline/PubMed, COVID 19 Research Database, and Scopus, were systematically searched till 30th February, 2022. All human studies were included irrespective of publication date or region. Twenty-two studies with a total of 19,783,097 patients detailing COVID 19 related mortality were included. To pool the estimate, a random effects model with risk ratio as the effect measure was used. Moreover, publication bias and sensitivity analysis were evaluated followed by meta-regression. The trial was registered (CRD42021264761) on the PROSPERO register.\n\nResultsThe findings were consistent in stating the contribution of HIV infection for COVID-19 related mortality. The cumulative COVID-19 related mortality was 110270 (0.6%) and 48863 (2.4%) with total events of 2010 (3.6%), 108260 (0.5%) among HIV-positive and negative persons respectively. HIV infection showed an increased risk of COVID-19 related mortality [RR=1.19, 95% CI (1.02, 1.39) (P=0.00001)] with substantial heterogeneity (I squared > 80%). The true effects size in 95% of all the comparable populations fell between 0.64 to 2.22. Multiple Centre studies and COVID-19 mortality with HIV infection showed a significant association [RR = 1.305, 95% CI (1.092, 1.559) (P = 0.003)], similar to studies conducted in America (RR=1.422, 95% CI 1.233, 1.639) and South Africa (RR=202;1.123, 95% CI 1.052, 1.198). HIV infection showed a risk for ICU admission [(P=0.00001) (I squared = 0%)] and mechanical ventilation [(P=0.04) (I squared = 0%)] which are predictors of COVID-19 severity prior to death. Furthermore, risk of COVID 19 related mortality is influenced by the region of study (R squared = 0.60). The variance proportion explained by covariates was significant (I squared = 87.5%, Q = 168.02, df = 21, p = 0.0000) (R squared = 0.67).\n\nConclusionOur updated meta-analysis indicated that HIV infection was significantly associated with an increased risk for both COVID 19 mortality, which might be modulated by the regions. We believe the updated data further will contribute to more substantiation of the findings reported by similar earlier studies (Dong et al., 2021; K. W. Lee et al., 2021; Massarvva, 2021; Mellor et al., 2021; Ssentongo et al., 2021)", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Tolulope F. Olufunlayo", - "author_inst": "College of Medicine of the University of Lagos and Lagos University Teaching Hospital, Idi-araba, Lagos." - }, - { - "author_name": "Oluwadamilola O. Ojo", - "author_inst": "College of Medicine, University of Lagos and Lagos University Teaching Hospital, Idi-araba, Lagos." - }, - { - "author_name": "Obianuju B. Ozoh", - "author_inst": "College of Medicine, University of Lagos and Lagos University Teaching Hospital, Idi-araba, Lagos." - }, - { - "author_name": "Olufemi A. Fasanmade", - "author_inst": "College of Medicine, University of Lagos and Lagos University Teaching Hospital, Idi-araba, Lagos." - }, - { - "author_name": "Osigwe P. Agabi", - "author_inst": "College of Medicine, University of Lagos and Lagos University Teaching Hospital, Idi-araba, Lagos." + "author_name": "JOHN KYALO MUTHUKA", + "author_inst": "KENYA MEDICAL TRAINING COLLEGE" }, { - "author_name": "Funmilola T. Taiwo", - "author_inst": "University College Hospital, Ibadan, Oyo State." + "author_name": "Francis Wambura", + "author_inst": "Kenya MedicalTraining College" }, { - "author_name": "Chuks R. Opara", - "author_inst": "Lagos University Teaching Hospital, Idi-araba, Lagos." + "author_name": "Kelly Oluoch", + "author_inst": "Kenya Medical Training College" }, { - "author_name": "Njideka U. Okubadejo", - "author_inst": "College of Medicine, University of Lagos and Lagos University Teaching Hospital, Idi-araba, Lagos" + "author_name": "Japeth Nzioki Mativo", + "author_inst": "Jumeira University, UAE" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.06.09.22276030", @@ -255367,43 +254733,47 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.06.10.22275998", - "rel_title": "Media coverage and speculation about the impact of the COVID-19 pandemic on suicide: A content analysis of UK news.", + "rel_doi": "10.1101/2022.06.12.495816", + "rel_title": "Two ligand-binding sites on SARS-CoV-2 non-structural protein 1 revealed by fragment-based x-ray screening", "rel_date": "2022-06-13", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.10.22275998", - "rel_abs": "ObjectivesSince the start of the COVID-19 pandemic, there has been much concern and speculation about rises in suicide rates, despite evidence that suicides did not in fact increase in the first year of the pandemic in most countries with real-time suicide data. This public narrative is potentially harmful, as well as misleading, and is likely to be perpetuated by sensational news coverage.\n\nMethodWe conducted a systematic analysis of UK news coverage (including opinion pieces) on the impact of COVID-19 on suicidality, to examine the content and quality of such reporting as the pandemic developed, and as different coronavirus restrictions were imposed.\n\nResultsWe identified 372 stories about COVID-19 and suicidality in online and print news between the first UK lockdown (March 2020) and May 2021 (when restrictions were significantly eased in the UK). Throughout this period, over a third of articles (39.2%) and headlines (41.4%) claimed or predicted a rise in suicide, often attributed to feelings of entrapment and poor mental health (especially amongst young people), and fueled by expert commentary and speculation. Almost a third of reports were rated as being of poor overall quality (116, 31.2%), and at least half included no signposting to help and support. However, reporting improved in phases of less stringent COVID-19 restrictions and over time, with later articles and headlines including fewer negative statements and predictions about rises in suicides, and greater reliance on academic evidence.\n\nConclusionsAs the longer-term consequences of the pandemic develop, and other national and global events unfold, it is increasingly important that the media, and the wider community of experts shaping its narratives, strive for a positive and evidence-informed approach to news coverage of suicide.\n\nStrengths and Limitations of this StudyO_LIThis is the first systematic analysis of UK news coverage on the impact of COVID-19 on suicidality.\nC_LIO_LIFindings are based on a well-established, evidence-informed news monitoring database.\nC_LIO_LIHowever, this analysis cannot account for the impact of news coverage on different audiences, nor for its reach\nC_LIO_LIOur focus did not extend to broadcasts or other media formats.\nC_LI", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.12.495816", + "rel_abs": "The regular reappearance of coronavirus (CoV) outbreaks over the past 20 years has caused significant health consequences and financial burdens worldwide. The most recent and still ongoing novel CoV pandemic, caused by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) has brought a range of devastating consequences. Due to the exceptionally fast development of vaccines, the mortality rate of the virus has been curbed to a significant extent. However, the limitations of vaccination efficiency and applicability, coupled with the still high infection rate, emphasise the urgent need for discovering safe and effective antivirals against SARS-CoV-2 through suppressing its replication and or attenuating its virulence. Non-structural protein 1 (nsp1), a unique viral and conserved leader protein, is a crucial virulence factor for causing host mRNA degradation, suppressing interferon (IFN) expression and host antiviral signalling pathways. In view of the essential role of nsp1 in the CoV life cycle, it is regarded as an exploitable target for antiviral drug discovery. Here, we report a variety of fragment hits against SARS-CoV-2 nsp1 identified by fragment-based screening via X-ray crystallography. We also determined the structure of nsp1 at atomic resolution (0.95 [A]). Binding affinities of hits against nsp1 were determined by orthogonal biophysical assays such as microscale thermophoresis and thermal sift assays. We identified two ligand-binding sites on nsp1, one deep and one shallow pocket, which are not conserved between the three medially relevant SARS, SARS-CoV-2 and MERS coronaviruses. Our study provides an excellent starting point for the development of more potent nsp1-targeting inhibitors and functional studies on SARS-CoV-2 nsp1.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Lisa Marzano", - "author_inst": "Middlesex University" + "author_name": "Shumeng Ma", + "author_inst": "UCL School of Pharmacy" }, { - "author_name": "Monica Hawley", - "author_inst": "Samaritans" + "author_name": "Shymaa Damfo", + "author_inst": "UCL School of Pharmacy" }, { - "author_name": "Lorna Fraser", - "author_inst": "Samaritans" + "author_name": "Jiaqi Lou", + "author_inst": "UCL School of Pharmacy" }, { - "author_name": "Yasmine Lainez", - "author_inst": "Middlesex University" + "author_name": "Nikos Pinotsis", + "author_inst": "Birkbeck College" }, { - "author_name": "James Marsh", - "author_inst": "University of Oxford" + "author_name": "Matthew W Bowler", + "author_inst": "European Molecular Biology Laboratory" }, { - "author_name": "Keith Hawton", - "author_inst": "University of Oxford" + "author_name": "Shozeb Haider", + "author_inst": "University College London School of Pharmacy" + }, + { + "author_name": "Frank Gerhard Kozielski", + "author_inst": "University College London" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_no", + "type": "new results", + "category": "biochemistry" }, { "rel_doi": "10.1101/2022.06.12.495779", @@ -256965,75 +256335,55 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2022.06.06.22275981", - "rel_title": "\u03b12,6-Sialylation is Upregulated in Severe COVID-19 Implicating the Complement Cascade", + "rel_doi": "10.1101/2022.06.07.493653", + "rel_title": "COVID-MVP: an interactive visualization for tracking SARS-CoV-2 mutations, variants, and prevalence, enabled by curated functional annotations and portable genomics workflow", "rel_date": "2022-06-08", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.06.22275981", - "rel_abs": "Better understanding of the mechanisms of COVID-19 severity is desperately needed in current times. Although hyper-inflammation drives severe COVID-19, precise mechanisms triggering this cascade and what role glycosylation might play therein is unknown. Here we report the first high-throughput glycomic analysis of COVID-19 plasma samples and autopsy tissues. We find 2,6-sialylation is upregulated in plasma of patients with severe COVID-19 and in the lung. This glycan motif is enriched on members of the complement cascade, which show higher levels of sialylation in severe COVID-19. In the lung tissue, we observe increased complement deposition, associated with elevated 2,6-sialylation levels, corresponding to elevated markers of poor prognosis (IL-6) and fibrotic response. We also observe upregulation of the 2,6-sialylation enzyme ST6GAL1 in patients who succumbed to COVID-19. Our work identifies a heretofore undescribed relationship between sialylation and complement in severe COVID-19, potentially informing future therapeutic development.", - "rel_num_authors": 14, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.07.493653", + "rel_abs": "The SARS-CoV-2 pandemic has reemphasized the importance of genomic epidemiology to track the evolution of the virus, dynamics of epidemics, geographic origins, and the emerging variants. It is vital in understanding the epidemiological spread of the virus on global, national, and local scales. Several analytical (bioinformatics) resources have been developed for molecular surveillance. However, a resource that combines genetic mutations and functional annotations on the impact of these mutations has been lacking in SARS-CoV-2 genomics surveillance. COVID-MVP provides an interactive visualization application that summarizes the mutations and their prevalence in SARS-CoV-2 viral lineages and provides functional annotations from the literature curated in an ongoing effort, Pokay. COVID-MVP is a tool that can be used for routine surveillance including spatio-temporal analyses. We have powered the visualization through a scalable and reproducible genomic analysis workflow nf-ncov-voc wrapped in Nextflow. COVID-MVP allows users to interactively explore data and download summarized surveillance reports. COVID-MVP, Pokay, and nf-ncov-voc are open-source tools available under the Massachusetts Institute of Technology (MIT) and GPL-3.0 licenses. COVID-MVP source code is available at https://github.com/cidgoh/COVID-MVP and an instance is hosted at https://covidmvp.cidgoh.ca.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Rui Qin", - "author_inst": "University of Alberta" - }, - { - "author_name": "Emma Kurz", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Shuhui Chen", - "author_inst": "New York University" - }, - { - "author_name": "Brianna Zeck", - "author_inst": "NYU Langone" - }, - { - "author_name": "Luis Chiriboga", - "author_inst": "NYU Langone" + "author_name": "Muhammad Zohaib Anwar", + "author_inst": "Centre for Infectious Disease Genomics and One Health, Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada" }, { - "author_name": "Dana Jackson", - "author_inst": "University of Alberta Hospital" - }, - { - "author_name": "Alex Herchen", - "author_inst": "University of Alberta Hospital" + "author_name": "Ivan S Gill", + "author_inst": "Centre for Infectious Disease Genomics and One Health, Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada" }, { - "author_name": "Tyson Attia", - "author_inst": "University of Alberta Hospital" + "author_name": "Madeline Iseminger", + "author_inst": "Centre for Infectious Disease Genomics and One Health, Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada" }, { - "author_name": "Michael A Carlock", - "author_inst": "University of Georgia, Athens, Georgia" + "author_name": "Anoosha Sehar", + "author_inst": "Centre for Infectious Disease Genomics and One Health, Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada" }, { - "author_name": "Amy Rapkiewicz", - "author_inst": "NYU Long Island School of Medicine" + "author_name": "Kenyi D Igwacho", + "author_inst": "Centre for Infectious Disease Genomics and One Health, Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada" }, { - "author_name": "Dafna Bar-Sagi", - "author_inst": "NYU Grossman School of Medicine" + "author_name": "Khushi Vora", + "author_inst": "Centre for Health Genomics and Informatics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada" }, { - "author_name": "Bruce Ritchie", - "author_inst": "University of Alberta" + "author_name": "Gary Van Domselaar", + "author_inst": "National Microbiology Laboratory, Public health Agency of Canada, Winnipeg, MB, Canada" }, { - "author_name": "Ted M. Ross", - "author_inst": "University System of Georgia" + "author_name": "Paul M. K. Gordon", + "author_inst": "Centre for Health Genomics and Informatics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada" }, { - "author_name": "Lara K. Mahal", - "author_inst": "University of Alberta" + "author_name": "William WL Hsiao", + "author_inst": "Centre for Infectious Disease Genomics and One Health, Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by", + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2022.06.07.495170", @@ -259023,55 +258373,103 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.06.06.22276038", - "rel_title": "Cross-Cultural Adaptation and Validation of the 5C Scale to Identify Factors Associated With COVID-19 and Influenza Vaccine Hesitancy Among Healthcare Workers in Cape Town, South Africa - A Protocol", + "rel_doi": "10.1101/2022.06.05.494897", + "rel_title": "Discovery of Chlorofluoroacetamide-Based Covalent Inhibitors for SARS-CoV-2 3CL Protease", "rel_date": "2022-06-06", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.06.22276038", - "rel_abs": "BackgroundHealthcare workers are at an increased risk of acquiring vaccine-preventable diseases and are known to be reliable source of information for the patients and their relatives. Knowledge and attitudes of Healthcare workers about vaccines are thus important determinants of their own vaccination uptake and their intention to recommend vaccinations to their patients. However, culturally adapted tools and studies to address vaccine uptake and hesitancy as well as related behaviours among Healthcare workers in the Global South are limited.\n\nMethodsWe propose a mixed methods project to understand the extent and determinants of vaccination hesitancy among Healthcare workers and construct a validated scale to measure this complex and context-specific phenomenon in Cape Town. We will summarise responses as counts and percentages for categorical variables and means with standard deviations (or median with inter quartile ranges) for continuous variables. We will run the Shapiro-Wilks test to assess the normality. Analysis of the variance, chi-square tests, and equivalents will be conducted as appropriate for group comparisons. Logistic regression models will also be performed to assess association between variables.\n\nWe will focus on the seasonal influenza and COVID-19 vaccine. We will use an existing tool developed and validated in Germany and the United States of America to measure five psychological determinants of vaccination (referred to as the 5C scale), as the basis to develop and validate a scale to measure the scope and determinants of vaccine hesitancy and acceptance among Healthcare workers in Cape Town.\n\nDiscussion and conclusionThrough this study, we hope to expand the scientific evidence based on vaccination acceptance and demand among Healthcare workers in South Africa and build resources to enable better understanding of, detection, and response to vaccination hesitancy in Cape Town.", - "rel_num_authors": 9, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.05.494897", + "rel_abs": "The pandemic of coronavirus disease 2019 (COVID-19) has urgently necessitated the development of antiviral agents against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The 3C-like protease (3CLpro) is a promising target for COVID-19 treatment. Here, we report the new class of covalent inhibitors for 3CLpro possessing chlorofluoroacetamide (CFA) as a cysteine reactive warhead. Based on the aza-peptide scaffold, we synthesized the series of CFA derivatives in enantiopure form and evaluated their biochemical efficiencies. The data revealed that 8a (YH-6) with R configuration at the CFA unit strongly blocks the SARS-CoV-2 replication in the infected cells and this potency is comparable to that of nirmatrelvir. The X-ray structural analysis shows that 8a (YH-6) forms a covalent bond with Cys145 at the catalytic center of 3CLpro. The strong antiviral activity and sufficient pharmacokinetics property of 8a (YH-6) suggest its potential as a lead compound for treatment of COVID-19.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Samuel Muabe Alobwede", - "author_inst": "University of Cape Town Faculty of Health Sciences" + "author_name": "Yuya Hirose", + "author_inst": "Kyushu University" }, { - "author_name": "Patrick Katoto", - "author_inst": "South African Medical Research Council" + "author_name": "Naoya Shindo", + "author_inst": "Kyushu University" }, { - "author_name": "Sara Cooper", - "author_inst": "South African Medical Research Council" + "author_name": "Makiko Mori", + "author_inst": "Kyushu University" }, { - "author_name": "Evelyn Lumngwena", - "author_inst": "Wits University: University of the Witwatersrand" + "author_name": "Satsuki Onitsuka", + "author_inst": "Kyushu University" }, { - "author_name": "Elvis Kidzeru", - "author_inst": "University of Cape Town" + "author_name": "Hikaru Isogai", + "author_inst": "Kyushu University" }, { - "author_name": "Rene Goliath", - "author_inst": "University of Cape Town Faculty of Health Sciences" + "author_name": "Rui Hamada", + "author_inst": "Kyushu University" }, { - "author_name": "Amanda Jackson", - "author_inst": "University of Cape Town Faculty of Health Sciences" + "author_name": "Tadanari Hiramoto", + "author_inst": "Kyushu University" }, { - "author_name": "Charles Wiysonge", - "author_inst": "South African Medical Research Council" + "author_name": "Jinta Ochi", + "author_inst": "Kyushu University" }, { - "author_name": "Muki Shey", - "author_inst": "University of Cape Town Faculty of Health Sciences" + "author_name": "Daisuke Takahashi", + "author_inst": "Kyushu University" + }, + { + "author_name": "Tadashi Ueda", + "author_inst": "Kyushu University" + }, + { + "author_name": "Jose M. M. Caaveiro", + "author_inst": "Kyushu University" + }, + { + "author_name": "Yuya Yoshida", + "author_inst": "Kyushu University" + }, + { + "author_name": "Shigehiro Ohdo", + "author_inst": "Kyushu University" + }, + { + "author_name": "Naoya Matsunaga", + "author_inst": "Kyushu University" + }, + { + "author_name": "Shinsuke Toba", + "author_inst": "Hokkaido University, Shionogi & Co. Ltd." + }, + { + "author_name": "Michihito Sasaki", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Yasuko Orba", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Hirofumi Sawa", + "author_inst": "Hokkaido University, Global Virus Network" + }, + { + "author_name": "Akihiko Sato", + "author_inst": "Hokkaido University, Shionogi & Co. Ltd." + }, + { + "author_name": "Eiji Kawanishi", + "author_inst": "Kyushu University" + }, + { + "author_name": "Akio Ojida", + "author_inst": "Kyushu University" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "biochemistry" }, { "rel_doi": "10.1101/2022.06.05.494856", @@ -260661,65 +260059,157 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.06.03.22275958", - "rel_title": "Waning of two-dose BNT162b2 and mRNA-1273 vaccine effectiveness against symptomatic SARS-CoV-2 infection is robust to depletion-of-susceptibles bias", + "rel_doi": "10.1101/2022.06.02.22275932", + "rel_title": "Distinct smell and taste disorder phenotype of post-acute COVID-19 sequelae", "rel_date": "2022-06-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.03.22275958", - "rel_abs": "Concerns about the duration of protection conferred by COVID-19 vaccines have arisen in postlicensure evaluations. However, \"depletion of susceptibles\" bias driven by differential accrual of infection among vaccinated and unvaccinated individuals may contribute to the appearance of waning vaccine effectiveness (VE) in epidemiologic studies, potentially hindering interpretation of estimates. We enrolled California residents who received molecular SARS-CoV-2 tests in a matched, test-negative design case-control study to estimate VE of mRNA-based COVID-19 vaccines between 23 February and 5 December 2021. We analyzed waning protection following 2 vaccine doses using conditional logistic regression models. Additionally, we used data from case-based surveillance along with estimated case-to-infection ratios from a population-based serological study to quantify the potential contribution of the \"depletion-of-susceptibles\" bias to time-varying VE estimates for 2 doses. We also estimated VE for 3 doses relative to 0 doses and 2 doses, by time since second dose receipt. Pooled VE of BNT162b2 and mRNA-1273 against symptomatic SARS-CoV-2 infection was 91.3% (95% confidence interval: 83.8-95.4%) at 14 days after second-dose receipt and declined to 50.8% (31.2-75.6%) at 7 months. Accounting for differential depletion-of-susceptibles among vaccinated and unvaccinated individuals, we estimated VE was 53.2% (23.6-71.2%) at 7 months among individuals who had completed the primary series (2 doses). With receipt of a third dose of BN162b2 or mRNA-1273, VE increased to 95.0% (82.8-98.6%), compared with zero doses. These findings confirm that observed waning of protection is not attributable to epidemiologic bias and support ongoing efforts to administer additional vaccine doses to mitigate burden of COVID-19.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.02.22275932", + "rel_abs": "BackgroundOlfactory dysfunction (OD) often accompanies acute coronavirus disease 2019 (COVID-19) and its sequelae. Herein, we investigated OD during COVID-19 recovery in the context of other symptoms, quality of life, physical and mental health.\n\nMethodsSymptom recovery patterns were analyzed in a bi-national, ambulatory COVID-19 survey (n = 906, [≥] 90 days follow-up) and a multi-center observational cross-sectional cohort of ambulatory and hospitalized individuals (n = 108, 360 days follow-up) with multi-dimensional scaling, association rule mining and partitioning around medoids clustering.\n\nResultsBoth in the ambulatory collective (72%, n = 655/906) and the cross-sectional ambulatory and hospitalized cohort (41%, n = 44/108) self-reported OD was frequent during acute COVID-19, displayed a slow recovery pace (ambulatory: 28 days, cross-sectional: 90 days median recovery time) and commonly co-occurred with taste disorders. In the ambulatory collective, a predominantly young, female, comorbidity-free group of convalescents with persistent OD and taste disorder (>90 days) was identified. This post-acute smell and taste disorder phenotype was characterized by a low frequency of other leading post-acute symptoms including fatigue, respiratory and neurocognitive complaints. Despite a protracted smell and taste dysfunction, this subset had high ratings of physical performance, mental health, and quality of life.\n\nConclusionOur results underline the clinical heterogeneity of post-acute COVID-19 sequelae calling for tailored management strategies. The persistent smell and taste disorder phenotype may represent a distinct COVID-19 recovery pathway characterized by a good recovery of other COVID-19 related symptoms.\n\nStudy registrationClinicalTrials.gov: NCT04661462 (ambulatory collective), NCT04416100 (cross-sectional cohort).", + "rel_num_authors": 35, "rel_authors": [ { - "author_name": "Kristin L Andrejko", - "author_inst": "University of California at Berkeley" + "author_name": "Verena Rass", + "author_inst": "Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria" }, { - "author_name": "Jake M Pry", - "author_inst": "California Department of Public Health" + "author_name": "Piotr Tymoszuk", + "author_inst": "Data Analytics As a Service Tirol, Innsbruck, Austria" }, { - "author_name": "Jennifer F Myers", - "author_inst": "California Department of Public Health" + "author_name": "Sabina Sahanic", + "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck Austria" }, { - "author_name": "Megha Mehrotra", - "author_inst": "California Department of Public Health" + "author_name": "Beatrice Heim", + "author_inst": "Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria" }, { - "author_name": "Katherine Lamba", - "author_inst": "California Department of Public Health" + "author_name": "Dietmar Ausserhofer", + "author_inst": "Institute of General Practice and Public Health, Claudiana College of Health Professions, Bolzano, Italy" }, { - "author_name": "Esther Lim", - "author_inst": "California Department of Public Health" + "author_name": "Anna Lindner", + "author_inst": "Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria" }, { - "author_name": "Nozomi Fukui", - "author_inst": "California Department of Public Health" + "author_name": "Mario Kofler", + "author_inst": "Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria" }, { - "author_name": "Jennifer L. DeGuzman", - "author_inst": "California Department of Public Health" + "author_name": "Philipp Mahlknecht", + "author_inst": "Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria" }, { - "author_name": "John Openshaw", - "author_inst": "California Department of Public Health" + "author_name": "Anna Boehm", + "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck Austria" }, { - "author_name": "James Watt", - "author_inst": "California Department of Public Health" + "author_name": "Katharina H\u00fcfner", + "author_inst": "Department of Psychiatry, Psychotherapy, Psychosomatics and Medical Psychology, University Hospital for Psychiatry II, Medical University of Innsbruck, Innsbruc" }, { - "author_name": "Seema Jain", - "author_inst": "California Department of Public Health" + "author_name": "Alex Pizzini", + "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck Austria" }, { - "author_name": "Joseph A. Lewnard", - "author_inst": "University of California Berkeley" + "author_name": "Thomas Sonnweber", + "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck Austria" + }, + { + "author_name": "Katharina Kurz", + "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck Austria" + }, + { + "author_name": "Bernhard Pfeifer", + "author_inst": "Tyrolean Federal Institute for Integrated Care, Innsbruck, Austria" + }, + { + "author_name": "Stefan Kiechl", + "author_inst": "Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria" + }, + { + "author_name": "Marina Peball", + "author_inst": "Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria" + }, + { + "author_name": "Philipp Kindl", + "author_inst": "Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria" + }, + { + "author_name": "Lauma Putnina", + "author_inst": "Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria" + }, + { + "author_name": "Elena Fava", + "author_inst": "Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria" + }, + { + "author_name": "Atbin Djamshidian", + "author_inst": "Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria" + }, + { + "author_name": "Andreas Huber", + "author_inst": "Tyrolean Federal Institute for Integrated Care, Innsbruck, Austria" + }, + { + "author_name": "Christian J Wiedermann", + "author_inst": "Institute of General Practice and Public Health, Claudiana College of Health Professions, Bolzano, Italy" + }, + { + "author_name": "Barbara Sperner-Unterweger", + "author_inst": "Department of Psychiatry, Psychotherapy, Psychosomatics and Medical Psychology, University Hospital for Psychiatry II, Medical University of Innsbruck, Innsbruc" + }, + { + "author_name": "Ewald W\u00f6ll", + "author_inst": "Department of Internal Medicine, St. Vinzenz Hospital, Zams, Austria" + }, + { + "author_name": "Ronny Beer", + "author_inst": "Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria" + }, + { + "author_name": "Alois Josef Schiefecker", + "author_inst": "Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria" + }, + { + "author_name": "Rosa Bellmann-Weiler", + "author_inst": "Department of Internal Medicine, St. Vinzenz Hospital, Zams, Austria" + }, + { + "author_name": "Herbert Bachler", + "author_inst": "Institute of General Medicine, Medical University of Innsbruck, Innsbruck, Austria" + }, + { + "author_name": "Ivan Tancevski", + "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck Austria" + }, + { + "author_name": "Bettina Pfausler", + "author_inst": "Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria" + }, + { + "author_name": "Giuliano Piccoliori", + "author_inst": "Institute of General Practice and Public Health, Claudiana College of Health Professions, Bolzano, Italy" + }, + { + "author_name": "Klaus Seppi", + "author_inst": "Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria" + }, + { + "author_name": "G\u00fcnter Weiss", + "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck Austria" + }, + { + "author_name": "Judith L\u00f6ffler-Ragg", + "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck Austria" + }, + { + "author_name": "Raimund Helbok", + "author_inst": "Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -262531,31 +262021,59 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2022.05.31.494262", - "rel_title": "SUMOylation of SARS-CoV-2 Nucleocapsid protein enhances its interaction affinity and plays a critical role for its nuclear translocation", + "rel_doi": "10.1101/2022.06.01.494101", + "rel_title": "Antiviral immune responses, cellular metabolism and adhesion are differentially modulated by SARS-CoV-2 ORF7a or ORF7b", "rel_date": "2022-06-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.31.494262", - "rel_abs": "Viruses, such as SARS-CoV-2, infect hosts and take advantages of host cellular machinery for their genome replication and new virion production. Identification and elucidation of host pathways for viral infection are critical for understanding the viral life cycle and novel therapeutics development. SARS-CoV-2 N protein is critical for viral RNA(vRNA) genome packaging in new virion formation, Here, we report that identification of SUMOylation sites of SARS-CoV-2 N protein and role of SUMO modification in N protein interaction affinity with itself using our qFRET/MS coupled method. We found, for the first time, that the SUMO modification of N protein can significantly increase its interaction affinity with itself and may support its oligomer formation. One of the identified Lys residues, K65 was critical for N protein translocation to nucleus, where the vRNA replication and packaging take place. The in vitro assessment of the affinity of N protein to N protein with SUMO mutants provides insight of the oligomerized N protein formation after SUMO modification. These results suggest that the host human SUMOylation pathway may be very critical for N protein functions in viral replication. The host SUMOylation pathway may be a critical host factor for the SARS-CoV-2 virus life cycle. Identification and inhibition of critical host SUMOyaltion could provide a novel strategy for future anti-viral therapeutics development, such as SARS-CoV-2 and other viruses.\n\nImportanceThe SARS-CoV-2 virus N protein plays a critical role critical for viral RNA(vRNA) genome packaging in host cell nucleus for new virion formation. Therefore, deciphering the molecular mechanisms modulating N activity could be a strategy to identify potential targets amenable to therapeutics. Here, we identify a comprehensive SUMOylation sites of N proteins using an in vitro reconstitute SUMOyaltion assay containing SUMO E1 activating enzyme, E2 conjugating enzyme, and E3 ligase. We find that SUMOylation modification of N protein can significantly enhance it interaction affinity with itself, indicating an increased oligomerization capability, which is critical for N protein activity for vRNA genome packaging. In addition, we find one of SUMOylation sites of N protein is critical for its nucleus translocation, which is a critical for viral genome packaging. The SUMOylation modification may represent novel potential approach to design new antivirals with the ability to modulate SARS-CoV-2 virus replication.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.01.494101", + "rel_abs": "SARS-CoV-2, the causative agent of the present COVID-19 pandemic, possesses eleven accessory proteins encoded in its genome, and some have been implicated in facilitating infection and pathogenesis through their interaction with cellular components. Among these proteins, accessory protein ORF7a and ORF7b functions are poorly understood. In this study, A549 cells were transduced to express ORF7a and ORF7b, respectively, to explore more in depth the role of each accessory protein in the pathological manifestation leading to COVID-19. Bioinformatic analysis and integration of transcriptome results identified defined canonical pathways and functional groupings revealing that after expression of ORF7a or ORF7b, the lung cells are potentially altered to create conditions more favorable for SARS-CoV-2, by inhibiting the IFN-I response, increasing proinflammatory cytokines release, and altering cell metabolic activity and adhesion. Based on these results, it is reasonable to suggest that ORF7a and ORF7b could be targeted by new therapies or used as future biomarkers during this pandemic.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Jiayu Liao", - "author_inst": "University of California" + "author_name": "Transito Garcia-Garcia", + "author_inst": "Immunogenomics and Molecular Pathogenesis BIO365 Group, Department of Genetics, University of Cordoba, Cordoba, Spain" }, { - "author_name": "Vipul Madahar", - "author_inst": "University of California" + "author_name": "Raul Fernandez-Rodriguez", + "author_inst": "Immunogenomics and Molecular Pathogenesis BIO365 Group, Department of Genetics, University of Cordoba, Cordoba, Spain" }, { - "author_name": "Victor G.J. Rodgers", - "author_inst": "University of California" + "author_name": "Natalia Redondo", + "author_inst": "Molecular Biomedicine Department, Centro de Investigaciones Biologicas Margarita Salas (CIB), CSIC, Madrid, Spain" + }, + { + "author_name": "Ana de Lucas-Rius", + "author_inst": "Molecular Biomedicine Department, Centro de Investigaciones Biologicas Margarita Salas (CIB), CSIC, Madrid, Spain" + }, + { + "author_name": "Sara Zaldivar-Lopez", + "author_inst": "Immunogenomics and Molecular Pathogenesis BIO365 Group, Department of Genetics, University of Cordoba, Cordoba, Spain" + }, + { + "author_name": "Blanca Dies Lopez-Ayllon", + "author_inst": "Molecular Biomedicine Department, Centro de Investigaciones Biologicas Margarita Salas (CIB), CSIC, Madrid, Spain" + }, + { + "author_name": "Jose M. Suarez-Cardenas", + "author_inst": "Immunogenomics and Molecular Pathogenesis BIO365 Group, Department of Genetics, University of Cordoba, Cordoba, Spain" + }, + { + "author_name": "Angeles Jimenez-Marin", + "author_inst": "Immunogenomics and Molecular Pathogenesis BIO365 Group, Department of Genetics, University of Cordoba, Cordoba, Spain" + }, + { + "author_name": "Maria Montoya", + "author_inst": "Molecular Biomedicine Department, Centro de Investigaciones Biologicas Margarita Salas (CIB), CSIC, Madrid, Spain" + }, + { + "author_name": "Juan J. Garrido", + "author_inst": "Immunogenomics and Molecular Pathogenesis BIO365 Group, Department of Genetics, University of Cordoba, Cordoba, Spain" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "bioengineering" + "category": "immunology" }, { "rel_doi": "10.1101/2022.05.31.22274501", @@ -264125,59 +263643,55 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.05.30.22275733", - "rel_title": "Specifying uniform eligibility criteria to strengthen causal inference studies of long-term outcomes of COVID-19", + "rel_doi": "10.1101/2022.05.27.22275630", + "rel_title": "Incidence of SARS-CoV-2 infection among unvaccinated US adults during the Omicron wave", "rel_date": "2022-05-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.30.22275733", - "rel_abs": "BackgroundCausal interpretation of findings from existing epidemiological studies on long-term clinical outcomes of coronavirus disease 2019 (COVID-19) may be limited by the choice of comparator (control) group.\n\nObjectiveWe compare two approaches to control group selection (based on requirement for negative SARS-CoV-2 test for eligibility) in long-term clinical outcomes after COVID-19 in patients with history of heart failure (HF).\n\nDesignRetrospective cohort study using data from February 1, 2020 to July 31, 2021. Setting: Veteran Health Administration (VHA).\n\nParticipantsWe studied two cohorts of Veterans with COVID-19 and history of HF which selected comparison group using two different approaches. In Cohort I, Veterans with HF who tested for positive for SARS-CoV-2 were age, sex, and race matched to Veterans with no evidence of COVID-19 in 1:5 ratio. In Cohort II Veterans with HF who tested positive for SARS-CoV-2 were age, sex, and race matched with Veterans with HF who tested negative for SARS-CoV-2 within +/-15 days of the positive test date within the same VHA facility.\n\nExposureCOVID-19 as determined by a positive SARS-CoV-2 test.\n\nMain Outcomes and Measures1-year all-cause mortality and hospital admissions beyond the first 30 days after COVID-19 diagnosis. Adjusted hazard ratios (HRs) accounting for comorbidity and 95% confidence intervals were calculated.\n\nResultsCohort I comprised 13,722 Veterans with HF with COVID-19 (mean [SD] age 72.0 [10.2] years, 2.4% female, 71.1% White) and 60,956 matched controls not known to have COVID-19. Cohort II comprised 6,725 Veterans with HF with COVID-19 (mean [SD] age 72.5 [7.5] years, 0.1% female, 80.8% White) and 6,726 matched controls with negative SARS-CoV-2 test. The adjusted HRs for 1-year mortality and hospital admission beyond the first 30 days after diagnosis of COVID-19 were 1.40 (1.32-1.49) and 1.34 (1.28-1.41), respectively, in analysis of Cohort-I (where the comparator group was not required to test negative for SARS-CoV-2). However, in Cohort-II (using the second comparator group specifying negative SARS-CoV-2 test for eligibility), the associations were markedly attenuated; adjusted HRs 1.05 (0.95-1.17) and 1.07 (0.96-1.19), respectively.\n\nConclusionsWe found significant attenuation of associations between COVID-19 and long-term risk of mortality and hospital admissions beyond the first 30 days among patient with existing HF, when comparing with a control group selected based on a negative SARS-CoV-2 test versus control group not known to have COVID-19. The findings have implications for the design of studies of long-term CVD (and non-CVD) outcome of COVID-19.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.27.22275630", + "rel_abs": "As of 4/20/2022, approximately 23% of the eligible US population was unvaccinated. We studied COVID-19 infections during the Omicron (B.1.1.529) wave in unvaccinated US adults, stratified by pre-Omicron antibody levels. Anti-spike serologic testing was performed prior to the Omicron wave in the United States (9/23/21-11/5/21) and participants were surveilled to determine incident COVID-19. Only 12% of those who entered the wave with antibodies reported a test-confirmed COVID-19 infection, compared to 35% of those without antibodies prior to the Omicron wave. Effectiveness of these anti-RBD antibodies in this unvaccinated population was 67%. Among people with antibodies, titer did not appear to be associated with risk of test-confirmed Omicron infection.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Sebhat Erqou", - "author_inst": "Providence VA Medical Center" - }, - { - "author_name": "Andrew R. Zullo", - "author_inst": "Brown University" + "author_name": "Jennifer L Alejo", + "author_inst": "Johns Hopkins Medical Institutions" }, { - "author_name": "Lan Jiang", - "author_inst": "Providence VA Medical Center" + "author_name": "Teresa Po-Yu Chiang", + "author_inst": "Johns Hopkins Medical Institutions" }, { - "author_name": "Vishal Khetpal", - "author_inst": "Alpert Medical School of Brown University" + "author_name": "Jonathan Mitchell", + "author_inst": "Johns Hopkins Medical Institutions" }, { - "author_name": "Julia Berkowitz", - "author_inst": "Alpert Medical School of Brown University" + "author_name": "Aura T Abedon", + "author_inst": "Johns Hopkins Medical Institutions" }, { - "author_name": "Nishant R Shah", - "author_inst": "Providence VA Medical Center" + "author_name": "Alexa Jefferis", + "author_inst": "Johns Hopkins Medical Institutions" }, { - "author_name": "Justin B Echouffo-Tcheugui", - "author_inst": "Johns Hopkins University" + "author_name": "William A Werbel", + "author_inst": "Johns Hopkins Medical Institutions" }, { - "author_name": "James L Rudolph", - "author_inst": "Providence VA Medical Center" + "author_name": "Allan B Massie", + "author_inst": "NYU Langone Medical Center" }, { - "author_name": "Gaurav Choudhary", - "author_inst": "Providence VA Medical Center" + "author_name": "Martin A Makary", + "author_inst": "Johns Hopkins Medical Institutions" }, { - "author_name": "Wen-Chih Wu", - "author_inst": "Providence VA Medical Center" + "author_name": "Dorry L Segev", + "author_inst": "NYU Langone Medical Center" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.05.29.22275277", @@ -265803,69 +265317,85 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.05.26.22274729", - "rel_title": "Pseudotemporal whole blood transcriptional profiling of COVID-19 patients stratified by clinical severity reveals differences in immune responses and possible role of monoamine oxidase B", + "rel_doi": "10.1101/2022.05.25.22273991", + "rel_title": "Development and scaling of a sequencing pipeline for genomic surveillance of SARS-CoV-2 in New York City", "rel_date": "2022-05-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.26.22274729", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with highly variable clinical outcomes. Studying the temporal dynamics of host whole blood gene expression during SARS-CoV-2 infection can elucidate the biological processes that underlie these diverse clinical phenotypes. We employed a novel pseudotemporal approach using MaSigPro to model and compare the trajectories of whole blood transcriptomic responses in patients with mild, moderate and severe COVID-19 disease. We identified 5,267 genes significantly differentially expressed (SDE) over pseudotime and between severity groups and clustered these genes together based on pseudotemporal trends. Pathway analysis of these gene clusters revealed upregulation of multiple immune, coagulation, platelet and senescence pathways with increasing disease severity and downregulation of T cell, transcriptional and cellular metabolic pathways. The gene clusters exhibited differing pseudotemporal trends. Monoamine oxidase B was the top SDE gene, upregulated in severe>moderate>mild COVID-19 disease. This work provides new insights into the diversity of the host response to SARS-CoV-2 and disease severity and highlights the utility of pseudotemporal approaches in studying evolving immune responses to infectious diseases.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.25.22273991", + "rel_abs": "In the ongoing COVID-19 pandemic, detecting the appearance and spread of variants of concern (VOC) is a critical capability in the fight to quell the virus and return to normalcy. Genomic surveillance of the emergence, propagation, and geographical spread of VOCs is thus an important tool for public health officials and government leaders to make policy decisions and advise the public. As part of our role as a major SARS-CoV-2 diagnostic testing facility in New York City, the Pandemic Response Lab (PRL) has been performing genomic surveillance on the large number of positive samples processed by the facility on a daily basis from throughout the New York metropolitan area. Here we describe the development and optimization of a high-throughput SARS-CoV-2 genome sequencing facility at PRL serving New York City.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Claire Broderick", - "author_inst": "Imperial College London" + "author_name": "Michael J Hammerling", + "author_inst": "Pandemic Response Lab" }, { - "author_name": "Irene Rivero Calle", - "author_inst": "Hospital Clinico Universitario de Santiago" + "author_name": "Shinyoung Clair Kang", + "author_inst": "Cultivarium" }, { - "author_name": "Alberto Gomez Carballa", - "author_inst": "Hospital Clinico Universitario de Santiago" + "author_name": "William Ward", + "author_inst": "Pandemic Response Lab" }, { - "author_name": "Jose Gomez-Rial", - "author_inst": "Hospital Clinico Universitario de Santiago" + "author_name": "Isabel Fernandez Escapa", + "author_inst": "Pandemic Response Lab" }, { - "author_name": "Ho Kwong Li", - "author_inst": "Imperial College London" + "author_name": "Pradeep Bugga", + "author_inst": "Kern Systems" }, { - "author_name": "Ravi Mehta", - "author_inst": "Imperial College London" + "author_name": "Cybill Del Castillo", + "author_inst": "Pandemic Response Lab" }, { - "author_name": "Heather Jackson", - "author_inst": "Imperial College London" + "author_name": "Melissa Hopkins", + "author_inst": "Pandemic Response Lab" }, { - "author_name": "Antonio Salas", - "author_inst": "Universidad de Santiago de Compostela" + "author_name": "Steven Chase", + "author_inst": "Pandemic Response Lab" }, { - "author_name": "Federico Martinon-Torres", - "author_inst": "Hospital Clinico Universitario de Santiago" + "author_name": "Sol Rey", + "author_inst": "Pandemic Response Lab" }, { - "author_name": "Shiranee Sriskandan", - "author_inst": "Imperial College London" + "author_name": "Dylan Law", + "author_inst": "Pandemic Response Lab" }, { - "author_name": "Michael Levin", - "author_inst": "Imperial College London" + "author_name": "Alexander Carpio", + "author_inst": "Pandemic Response Lab" }, { - "author_name": "Myrsini Kaforou", - "author_inst": "Imperial College London" + "author_name": "Kate Nelson", + "author_inst": "Pandemic Response Lab" }, { - "author_name": "- BioAID Consortium", - "author_inst": "" + "author_name": "Simran Chhabria", + "author_inst": "Pandemic Response Lab" }, { - "author_name": "- GEN-COVID Study Group", - "author_inst": "" + "author_name": "Simran Gupta", + "author_inst": "Pandemic Response Lab" + }, + { + "author_name": "Tiara Rivera", + "author_inst": "Pandemic Response Lab" + }, + { + "author_name": "Jon M Laurent", + "author_inst": "Pandemic Response Lab" + }, + { + "author_name": "Haiping Hao", + "author_inst": "Pandemic Response Lab" + }, + { + "author_name": "Henry H Lee", + "author_inst": "Cultivarium" } ], "version": "1", @@ -268265,59 +267795,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.05.25.493467", - "rel_title": "Inhibition of major histocompatibility complex-I antigen presentation by sarbecovirus ORF7a proteins", + "rel_doi": "10.1101/2022.05.26.22275585", + "rel_title": "Long Covid stigma: estimating burden and validating scale in a UK-based sample", "rel_date": "2022-05-26", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.25.493467", - "rel_abs": "Viruses employ a variety of strategies to escape or counteract immune responses, including depletion of cell surface major histocompatibility complex class I (MHC-I), that would ordinarily present viral peptides to CD8+ cytotoxic T cells. As part of a screen to elucidate biological activities associated with individual SARS-CoV-2 viral proteins, we found that ORF7a reduced cell surface MHC-I levels by approximately 5-fold. Nevertheless, in cells infected with SARS-CoV-2, surface MHC-I levels were reduced even in the absence of ORF7a, suggesting additional mechanisms of MHC-I downregulation. ORF7a proteins from a sample of sarbecoviruses varied in their ability to induce MHC-I downregulation and, unlike SARS-CoV-2, the ORF7a protein from SARS-CoV lacked MHC-I downregulating activity. A single-amino acid at position 59 (T/F) that is variable among sarbecovirus ORF7a proteins governed the difference in MHC-I downregulating activity. SARS-CoV-2 ORF7a physically associated with the MHC-I heavy chain and inhibited the presentation of expressed antigen to CD8+ T-cells. Speficially, ORF7a prevented the assembly of the MHC-I peptide loading complex and causing retention of MHC-I in the endoplasmic reticulum. The differential ability of ORF7a proteins to function in this way might affect sarbecovirus dissemination and persistence in human populations, particularly those with infection- or vaccine-elicited immunity.", - "rel_num_authors": 10, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.26.22275585", + "rel_abs": "BackgroundStigma can be experienced as perceived or actual disqualification from social and institutional acceptance on the basis of one or more physical, behavioural or other attributes deemed to be undesirable. Long Covid is a predominantly multisystem condition that occurs in people with a history of SARSCoV2 infection, often resulting in functional disability.\n\nAimTo develop and validate a Long Covid Stigma Scale (LCSS); and to quantify the burden of Long Covid stigma.\n\nDesign and SettingFollow-up of a co-produced community-based Long Covid online survey using convenience non-probability sampling.\n\nMethodThirteen questions on stigma were designed to develop the LCSS capturing three domains - enacted (overt experiences of discrimination), internalised (internalising negative associations with Long Covid and accepting them as self-applicable) and anticipated (expectation of bias/poor treatment by others) stigma. Confirmatory factor analysis tested whether LCSS consisted of the three hypothesised domains. Model fit was assessed and prevalence was calculated.\n\nResults966 UK-based participants responded (888 for stigma questions), with mean age 48 years (SD: 10.7) and 85% female. Factor loadings for enacted stigma were 0.70-0.86, internalised 0.75-0.84, anticipated 0.58-0.87, and model fit was good. The prevalence of experiencing stigma at least sometimes and often/always was 95% and 76% respectively. Anticipated and internalised stigma were more frequently experienced than enacted stigma. Those who reported having a clinical diagnosis of Long Covid had higher stigma prevalence than those without.\n\nConclusionThis study establishes a scale to measure Long Covid stigma and highlights common experiences of stigma in people living with Long Covid.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Fengwen Zhang", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Trinity Zang", - "author_inst": "The Rockefeller University" - }, - { - "author_name": "Eva M Stevenson", - "author_inst": "Weill Cornell Medicine" - }, - { - "author_name": "Xiao Lei", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Dennis C Copertino", - "author_inst": "Weil Cornell Medicine" + "author_name": "Marija Pantelic", + "author_inst": "University of Sussex" }, { - "author_name": "Talia M Mota", - "author_inst": "Weil Cornell Medicine" + "author_name": "Nida Ziauddeen", + "author_inst": "University of Southampton" }, { - "author_name": "Julie Boucau", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Mark Boyes", + "author_inst": "Curtin University" }, { - "author_name": "Wilfredo F Garcia-Beltran", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Margaret E O'Hara", + "author_inst": "Long Covid Support" }, { - "author_name": "R. Brad F Jones", - "author_inst": "Cornell University Joan and Sanford I Weill Medical College" + "author_name": "Claire Hastie", + "author_inst": "Long Covid Support" }, { - "author_name": "Paul D Bieniasz", - "author_inst": "The Rockefeller University" + "author_name": "Nisreen A Alwan", + "author_inst": "University of Southampton" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2022.05.26.493529", @@ -270175,39 +269689,59 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2022.05.23.493138", - "rel_title": "Reconstitution of the SARS-CoV-2 ribonucleosome provides insights into genomic RNA packaging and regulation by phosphorylation", - "rel_date": "2022-05-24", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.23.493138", - "rel_abs": "The nucleocapsid (N) protein of coronaviruses is responsible for compaction of the [~]30-kb RNA genome in the [~]100-nm virion. Cryo-electron tomography suggests that each virion contains 35-40 viral ribonucleoprotein (vRNP) complexes, or ribonucleosomes, arrayed along the genome. There is, however, little mechanistic understanding of the vRNP complex. Here, we show that N protein, when combined with viral RNA fragments in vitro, forms cylindrical 15-nm particles similar to the vRNP structures observed within coronavirus virions. These vRNPs form in the presence of stem-loop-containing RNA and depend on regions of N protein that promote protein-RNA and protein-protein interactions. Phosphorylation of N protein in its disordered serine/arginine (SR) region weakens these interactions and disrupts vRNP assembly. We propose that unmodified N binds stem-loop-rich regions in genomic RNA to form compact vRNP complexes within the nucleocapsid, while phosphorylated N maintains uncompacted viral RNA to promote the proteins transcriptional function.", - "rel_num_authors": 5, + "rel_doi": "10.1101/2022.05.23.22275442", + "rel_title": "Assessment of subtle cognitive impairments in patients with post-COVID syndrome with the tablet-based Oxford Cognitive Screen-Plus (OCS-Plus).", + "rel_date": "2022-05-23", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.23.22275442", + "rel_abs": "Background and objectivesCognitive symptoms persisting beyond three months following COVID-19 present a considerable disease burden. We aimed to establish a domain-specific cognitive profile of post-COVID syndrome (PCS) and relationships with subjective cognitive complaints and clinical variables to provide relevant information for the understanding of cognitive dysfunction and its predictors in a clinical cohort with PCS.\n\nMethodsIn this cross-sectional study, we compared cognitive performance on the clinically viable Oxford Cognitive Screen-Plus between a large post-COVID cohort (n = 282) and a socio-demographically matched healthy control group (n = 52). We assessed group differences in terms of fatigue and depression as well as relationships between cognitive dysfunction and clinical and patient-reported outcomes.\n\nResultsOn a group-level, patients scored significantly lower on delayed verbal memory (non-parametric effect size r = .13), attention (r = .1), and executive functioning (r=.1) than healthy controls. In each of these domains, 10-20% of patients performed more than 1.5 SD below the healthy control mean. Delayed Memory was particularly affected and a small proportion of its variance was explained by hospitalisation ({beta} = -.72, p < .01) and age ({beta} = -.03, p < .05; R2adj. = .08). Attention scores were significantly predicted by hospitalisation ({beta} = -.78, p < .01) and fatigue ({beta} = -.04, p < .05; R2adj. = .06).\n\nDiscussionPCS is associated with long-term cognitive dysfunction, particularly in delayed verbal memory, attention, and executive functioning. Deficits in delayed memory performance seem to be of particular relevance to patients subjective experience of impairment. Initial disease severity, current level of fatigue, and age seem to predict cognitive performance, while time since infection, depression, and pre-existing conditions do not. Longitudinal data are needed to map long-term course of cognitive dysfunction in PCS.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Christopher Carlson", - "author_inst": "UCSF" + "author_name": "Valeska Kozik", + "author_inst": "Jena University Hospital" }, { - "author_name": "Armin Adly", - "author_inst": "UCSF" + "author_name": "Philipp Reuken", + "author_inst": "Department of Internal Medicine IV (Gastroenterology, Hepatology and Infectious Diseases), Jena University Hospital, Jena, Germany" }, { - "author_name": "Maxine Bi", - "author_inst": "UCSF" + "author_name": "Isabelle Utech", + "author_inst": "Department of Neurology, Jena University Hospital Jena, Germany" }, { - "author_name": "Yifan Cheng", - "author_inst": "UCSF" + "author_name": "Judith Gramlich", + "author_inst": "Department of Internal Medicine IV (Gastroenterology, Hepatology and Infectious Diseases), Jena University Hospital, Jena, Germany" }, { - "author_name": "David O. Morgan", - "author_inst": "University of California San Francisco" + "author_name": "Zoe Stallmach", + "author_inst": "Department of Internal Medicine IV (Gastroenterology, Hepatology and Infectious Diseases), Jena University Hospital, Jena, Germany" + }, + { + "author_name": "Nele Demeyere", + "author_inst": "Department of Experimental Psychology, University of Oxford, Radcliffe Observatory Quarter, Oxford OX2 6GG, UK" + }, + { + "author_name": "Florian Rakers", + "author_inst": "Department of Neurology, Jena University Hospital Jena, Germany" + }, + { + "author_name": "Matthias Schwab", + "author_inst": "Department of Neurology, Jena University Hospital Jena, Germany" + }, + { + "author_name": "Andreas Stallmach", + "author_inst": "Department of Internal Medicine IV (Gastroenterology, Hepatology and Infectious Diseases), Jena University Hospital, Jena, Germany; Center for Sepsis Control an" + }, + { + "author_name": "Kathrin Finke", + "author_inst": "Department of Neurology, Jena University Hospital, Jena, Germany; Department of Psychology, Ludwig-Maximilians-University, Munich" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "biochemistry" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.05.20.22275407", @@ -272313,47 +271847,39 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.05.18.22275234", - "rel_title": "Early experience with modified dose nirmatrelvir/ritonavir in dialysis patients with coronavirus disease-2019", + "rel_doi": "10.1101/2022.05.18.22275217", + "rel_title": "Bias-adjusted predictions of county-level vaccination coverage from the COVID-19 Trends and Impact Survey", "rel_date": "2022-05-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.18.22275234", - "rel_abs": "IntroductionNirmatrelvir/Ritonavir was approved for use in high risk outpatients with coronavirus disease (COVID-19). However, patients with severe chronic kidney disease, including patients on dialysis, were excluded from the phase 3 trial, and currently the drug is not recommended below a glomerular filtration rate of 30 ml/min/1.73m2. Based on available pharmacological data and principles, we developed a modified dose which was lower, and administered at longer intervals.We administered nirmatrelvir/ritonavir as 300/100 mg on day one, followed by 150/100 mg daily from day two to day five. In this case series, we report the initial experience with this modified dose regimen.\n\nMethodsThis is a retrospective chart review, conducted after obtaining institutional board approval. Demographic and outcome data was abstracted from the electronic medical record for dialysis patients who developed COVID-19 during the period of study and received nirmatrelvir/ritonavir. The principal outcomes we describe are symptom resolution, and safety data with the modified dose regimen in the dialysis patients.\n\nResults19 patients developed COVID-19 during the period of study of whom 15 received nirmatrelvir/ritonavir. 47% of them were female and 67% had diabetes. Most patients had received three doses of the vaccine (80%) while 13% were unvaccinated. Potential drug interactions concerns were common (median 2 drugs per patient) with amlodipine and atorvastatin being the commonest drugs requiring dose modification. Nirmatrelvir/ritonavir use was associated with symptom resolution in all patients, and was well tolerated. One patient had a rebound of symptoms, which improved in 2 more days. There were no COVID-19 related hospitalizations or deaths in any of the patients.\n\nConclusionIn this case series of 15 hemodialysis patients with COVID-19, a modified dose of nirmatrelvir/ritonavir use, with pharmacist support for drug interaction management, was associated with symptom resolution, and was well tolerated with no serious adverse effects.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.18.22275217", + "rel_abs": "The potential for bias in non-representative, large-scale, low-cost survey data can limit their utility for population health measurement and public health decision-making. We developed a multi-step regression framework to bias-adjust vaccination coverage predictions from the large-scale US COVID-19 Trends and Impact Survey that included post-stratification to the American Community Survey and secondary normalization to an unbiased reference indicator. As a case study, we applied this framework to generate county-level predictions of long-run vaccination coverage among children ages 5 to 11 years. Our vaccination coverage predictions suggest a low ceiling on long-term national coverage (46%), detect substantial geographic heterogeneity (ranging from 11% to 91% across counties in the US), and highlight widespread disparities in the pace of scale-up in the three months following Emergency Use Authorization of COVID-19 vaccination for 5 to 11 year-olds. Generally, our analysis demonstrates an approach to leverage differing strengths of multiple sources of information to produce estimates on the time-scale and geographic-scale necessary for proactive decision-making. The utility of large-scale, low-cost survey data for improving population health measurement is amplified when these data are combined with other representative sources of data.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Pierre Antoine Brown", - "author_inst": "University of Ottawa" - }, - { - "author_name": "Michaeline McGuinty", - "author_inst": "University of Ottawa" - }, - { - "author_name": "Christos P Argyropoulos", - "author_inst": "University of New Mexico" + "author_name": "Marissa B Reitsma", + "author_inst": "Stanford University" }, { - "author_name": "Edward G Clark", - "author_inst": "University of Ottawa" + "author_name": "Sherri Rose", + "author_inst": "Stanford University" }, { - "author_name": "David Colantonio", - "author_inst": "University of Ottawa" + "author_name": "Alex Reinhart", + "author_inst": "Carnegie Mellon University" }, { - "author_name": "Pierre Giguere", - "author_inst": "The Ottawa Hospital" + "author_name": "Jeremy D Goldhaber-Fiebert", + "author_inst": "Stanford University" }, { - "author_name": "Swapnil Hiremath", - "author_inst": "University of Ottawa" + "author_name": "Joshua A Salomon", + "author_inst": "Stanford University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "nephrology" + "category": "health policy" }, { "rel_doi": "10.1101/2022.05.18.22275283", @@ -274123,67 +273649,107 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.05.17.22275034", - "rel_title": "Analytical performance of rapid antigen tests for the detection of SARS-CoV-2 during widespread circulation of the Omicron variant", + "rel_doi": "10.1101/2022.05.18.22275209", + "rel_title": "Reduced antibody acquisition with increasing age following vaccination with BNT162b2: results from a large study performed in the general population aged 12 to 92 years", "rel_date": "2022-05-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.17.22275034", - "rel_abs": "IntroductionAntigen testing is essential in the clinical management of COVID-19. However, most evaluations of antigen tests have been performed before the emergence of the Omicron variant. Thus, an assessment of the diagnostic performance of antigen tests for the detection of SARS-CoV-2 during the circulation of Omicron variant is required.\n\nMethodsThis prospective observational study evaluated QuickNavi-COVID19 Ag, a rapid antigen detection test between December 2021 and February 2022 in Japan, using real-time reverse transcription (RT)-PCR as a reference. Two nasopharyngeal samples were simultaneously collected for antigen testing and for RT-PCR. Variant analysis of the SARS-CoV-2 genomic sequencing was also performed.\n\nResultsIn total, nasopharyngeal samples were collected from 1,073 participants (417 positive; 919 symptomatic; 154 asymptomatic) for analysis. Compared with those of RT-PCR, the sensitivity, specificity, positive predictive value, and negative predictive value were 94.2% (95% CI: 91.6%-96.3%), 99.5% (95% CI: 98.7%-99.9%), 99.2% (95% CI: 97.8%-99.8%), and 96.5% (95% CI: 94.8%-97.7%), respectively. The sensitivity among symptomatic individuals was 94.3% (95% CI: 91.5%-96.4%). Overall, 85.9% of sequences were classified as Omicron sublineage BA.1, 12.4% were Omicron sublineage BA.2, and 1.6% were Delta B.1.617.2. (Delta variant). Most of the samples (87.1%) had Ct values <25.\n\nConclusionsThe QuickNavi-COVID19 Ag test showed high diagnostic performance for the detection of the SARS-CoV-2 Omicron sublineages BA.1 and BA.2 from nasopharyngeal samples.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.18.22275209", + "rel_abs": "Vaccine-induced protection of the population against severe COVID-19, hospitalization and death is of utmost importance, especially in the elderly. However, limited data are available on humoral immune responses following COVID-19 vaccination in the general population across a broad age range. We performed an integrated analysis of the effect of age, sex and prior SARS-CoV-2 infection on Spike S1-specific (S1) IgG concentrations up to three months post BNT162b2 vaccination. 1{middle dot}735 persons, eligible for COVID-19 vaccination through the national program, were recruited from the general population (12 to 92 years old). Sixty percent were female and the median vaccination interval was 35 days (interquartile range, IQR: 35-35). All participants had seroconverted to S1 one month after two doses of vaccine. S1 IgG was higher in participants with a history of SARS-CoV-2 infection (median: 4{middle dot}535 BAU/ml, IQR: 2{middle dot}341-7{middle dot}205) compared to infection-naive persons (1{middle dot}842 BAU/ml, 1{middle dot}019-3{middle dot}116) after two doses, p<0.001. In infection-naive persons, linear mixed effects regression showed a strong negative association between age and S1 IgG one month after the first vaccination (p<0.001) across the entire age range. The association was still present after the second vaccination, but less pronounced. Females had higher S1 IgG than males after both the first and second vaccination (p<0.001); although this difference was lower after the second dose. In persons with an infection history, age nor sex was associated with peak S1 IgG. As IgG decreased with age and time since vaccination, older persons may become at risk of infection, especially with escape variants such as Omicron.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Hiromichi Suzuki", - "author_inst": "Department of Infectious Diseases, Faculty of Medicine, University of Tsukuba" + "author_name": "Lotus Leonie van den Hoogen", + "author_inst": "RIVM" }, { - "author_name": "Yusaku Akashi", - "author_inst": "Department of Infectious Diseases, Faculty of Medicine, University of Tsukuba" + "author_name": "Mardi C. Boer", + "author_inst": "RIVM" }, { - "author_name": "Daisuke Kato", - "author_inst": "Denka Co., Ltd. Gosen Site, Research & Development Division, Reagent R&D Department" + "author_name": "Abigail Postema", + "author_inst": "RIVM" }, { - "author_name": "Yuto Takeuchi", - "author_inst": "Department of Infectious Diseases, University of Tsukuba Hospital" + "author_name": "Lia de Rond", + "author_inst": "RIVM" }, { - "author_name": "Yoshihiko Kiyasu", - "author_inst": "Department of Infectious Diseases, Faculty of Medicine, University of Tsukuba" + "author_name": "Mary-lene de Zeeuw-Brouwer", + "author_inst": "RIVM" }, { - "author_name": "Norihiko Terada", - "author_inst": "Department of Infectious Diseases, Faculty of Medicine, University of Tsukuba" + "author_name": "Inge Pronk", + "author_inst": "RIVM" }, { - "author_name": "Yoko Kurihara", - "author_inst": "Department of Infectious Diseases, University of Tsukuba Hospital" + "author_name": "Alienke J. Wijmenga-Monsuur", + "author_inst": "RIVM" }, { - "author_name": "Miwa Kuwahara", - "author_inst": "Denka Co., Ltd. Gosen Site, Research & Development Division, Reagent R&D Department" + "author_name": "Elske Bijvank", + "author_inst": "RIVM" }, { - "author_name": "Shino Muramatsu", - "author_inst": "Denka Co., Ltd. Gosen Site, Research & Development Division, Reagent R&D Department" + "author_name": "Caitlyn Kruiper", + "author_inst": "RIVM" }, { - "author_name": "Atsuo Ueda", - "author_inst": "Department of Clinical Laboratory, Tsukuba Medical Center Hospital" + "author_name": "Lisa Beckers", + "author_inst": "RIVM" }, { - "author_name": "Shigeyuki Notake", - "author_inst": "Department of Clinical Laboratory, Tsukuba Medical Center Hospital" + "author_name": "Marjan Bogaard-van Maurik", + "author_inst": "RIVM" }, { - "author_name": "Koji Nakamura", - "author_inst": "Department of Clinical Laboratory, Tsukuba Medical Center Hospital" + "author_name": "Ilse Zutt", + "author_inst": "RIVM" + }, + { + "author_name": "Jeffrey van Vliet", + "author_inst": "RIVM" + }, + { + "author_name": "Rianne van Bergen", + "author_inst": "RIVM" + }, + { + "author_name": "Marjan Kuijer", + "author_inst": "RIVM" + }, + { + "author_name": "Gaby Smits", + "author_inst": "RIVM" + }, + { + "author_name": "W.M. Monique Verschuren", + "author_inst": "RIVM" + }, + { + "author_name": "H. Susan J. Picavet", + "author_inst": "RIVM" + }, + { + "author_name": "Fiona R.M. van der Klis", + "author_inst": "RIVM" + }, + { + "author_name": "Gerco den Hartog", + "author_inst": "RIVM" + }, + { + "author_name": "Robert S. van Binnendijk", + "author_inst": "RIVM" + }, + { + "author_name": "Anne-Marie Buisman", + "author_inst": "RIVM" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2022.05.14.22275075", @@ -275745,67 +275311,27 @@ "category": "transplantation" }, { - "rel_doi": "10.1101/2022.05.17.491668", - "rel_title": "The ATLAS\u2122 screening assay reveals distinct CD4+ and CD8+ SARS-CoV-2 antigen response profiles which have implications to Omicron cellular immunity", + "rel_doi": "10.1101/2022.05.15.22275107", + "rel_title": "WHAT ARE EFFECTIVE STRATEGY TO CONSTRAIN COVID-19 PANDEMIC CRISIS? LESSONS LEARNED FROM A COMPARATIVE POLICY ANALYSIS BETWEEN ITALIAN REGIONS TO COPE WITH NEXT PANDEMIC IMPACT", "rel_date": "2022-05-17", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.17.491668", - "rel_abs": "The emergence of SARS-CoV-2 variants are a persistent threat to the efficacy of currently developed prophylactic vaccines and therapeutic antibodies. These variants accumulate mutations in the spike protein which encodes the epitopes necessary for neutralizing antibody binding. Moreover, emerging evidence suggest that robust antibody responses are insufficient to prevent severe disease and long-lasting viral immunity requires T cells. Thus, understanding how the T cell antigen landscape evolves in the context of these emerging variants remains crucial. T cells responses are durable and recognize a wider breadth of epitopes reducing the possibility of immune escape through mutation. Here, we deploy the ATLAS assay which identifies CD4+ and CD8+ T cell antigens by utilizing the endogenous HLA class-I and class-II peptide processing pathways. Profiling of T cells from exposed and unexposed donors revealed rich and complex patterns which highlighted the breadth of antigenic potential encoded in SARS-CoV-2. ATLAS revealed several common or frequent antigenic regions as well as an abundance of responses in the unexposed cohort potentially the result of pre-exposure to related coronaviruses. ORF10 was a common CD4+ response in the unexposed cohort while spike was identified as a common and frequent target in both cohorts. Moreover, the spike response profiles allowed us to accurately predict the impact of Omicron spike mutations. This analysis could thus be applied to study the impact of future emerging VOCs.", - "rel_num_authors": 12, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.15.22275107", + "rel_abs": "The pandemic of Coronavirus Disease 2019 (COVID-19) and its variants is rapidly spreading all over the world, generating a high number of infections, deaths and negative impact on socioeconomic system of countries. As vaccines and appropriate drugs for treatment of the COVID-19 can reduce the effectiveness in the presence of variants and/or new viral agents, one of the questions in social studies of medicine is effective public policy responses to reduce the impact of COVID-19 global pandemic and similar infectious diseases on health of people and on economies. This study analyzes public policy responses to the pandemic crisis across Italian regions that were the first areas to experience a rapid increase in confirmed cases and deaths of COVID-19. The analysis of regional strategies, from January to July 2020, reveals differences in public policy responses to delay and reduce the height of epidemic peak and to afford health-care systems more time to expand and respond to this new emergency. Veneto Region in North-East Italy has managed health policy responses with: a) a timely and widespread testing of individuals, b) units of epidemiological investigation for tracing all contacts of infected people in an effective contact tracing system. This public policy response has reduced total deaths and the final size of COVID-19 pandemic on health of people. Other regions have done public interventions without a clear strategy and goals to cope with diffusion of COVID-19 and as a consequence, they have had a higher negative impact on public health. Lesson learned can be important to design an effective public policy that can be generalized in different regional and national systems to prevent and/or reduce future epidemics or pandemics similar to the COVID-19.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "James J Foti", - "author_inst": "Genocea Biosciences" - }, - { - "author_name": "Kevin Lema", - "author_inst": "Genocea Biosciences" - }, - { - "author_name": "Justin Strickland", - "author_inst": "Genocea Biosciences" - }, - { - "author_name": "Emily Tjon", - "author_inst": "Genocea Biosciences" - }, - { - "author_name": "Adrienne Li", - "author_inst": "Genocea Biosciences" - }, - { - "author_name": "Amalia Rivera", - "author_inst": "Genocea Biosciences" - }, - { - "author_name": "Crystal Cabral", - "author_inst": "Genocea Biosciences" - }, - { - "author_name": "Laura Cormier", - "author_inst": "Genocea Biosciences" - }, - { - "author_name": "Louisa Dowal", - "author_inst": "Genocea Biosciences" - }, - { - "author_name": "Sudhir Rao", - "author_inst": "Genocea Biosciences" - }, - { - "author_name": "Vijetha Vemulapalli", - "author_inst": "Genocea Biosciences" + "author_name": "Mario Coccia", + "author_inst": "National Research Council of Italy" }, { - "author_name": "Jessica B Flechtner", - "author_inst": "Genocea Biosciences" + "author_name": "Igor Benati", + "author_inst": "IRCRES-CNR Italy" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "immunology" + "type": "PUBLISHAHEADOFPRINT", + "category": "health policy" }, { "rel_doi": "10.1101/2022.05.17.22275027", @@ -277475,59 +277001,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.05.15.22274976", - "rel_title": "Effects of social support on depression risk during the COVID-19 pandemic: What support types and for whom?", + "rel_doi": "10.1101/2022.05.11.22274952", + "rel_title": "Assessment of oxidative stress markers in elderly patients with SARS-CoV-2 infection and potential prognostic implications. An observational study", "rel_date": "2022-05-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.15.22274976", - "rel_abs": "BackgroundRates of depression have increased worldwide during the COVID-19 pandemic. One known protective factor for depression is social support, but more work is needed to quantify the extent to which social support could reduce depression risk during a global crisis, and specifically to identify which types of support are most helpful, and who might benefit most.\n\nMethodsData were obtained from participants in the All of Us Research Program who responded to the COVID-19 Participant Experience (COPE) survey administered monthly from May 2020 to July 2020 (N=69,066, 66% female). Social support was assessed using 10 items measuring emotional/informational support (e.g., someone to confide in or talk to about yourself or your problems), positive social interaction support (e.g., someone to do things with to help you get your mind off things), and tangible support (e.g., someone to help with daily chores if sick). Elevated depression symptoms were defined based on having a moderate-to-severe ([≥]10) score on the Patient Health Questionnaire (PHQ-9). Mixed-effects logistic regression models were used to test associations across time between overall social support and its subtypes with depression, adjusting for age, sex, race, ethnicity, and socioeconomic factors. We then assessed interactions between social support and potential effect modifiers: age, sex, pre-pandemic mood disorder, and pandemic-related stressors (e.g., financial insecurity).\n\nResultsApproximately 16% of the sample experienced elevated depressive symptoms. Overall social support was associated with significantly reduced odds of depression (adjusted odds ratio, aOR [95% CI]=0.44 [0.42-0.45]). Among subtypes, emotional/informational support (aOR=0.42 [0.41-0.43]) and positive social interactions (aOR=0.43 [0.41-0.44]) showed the largest protective associations with depression, followed by tangible support (aOR=0.63 [0.61-0.65]). Sex, age, and pandemic-related financial stressors were statistically significant modifiers of the association between social support and depression.\n\nConclusionsIndividuals reporting higher levels of social support were at reduced risk of depression during the early COVID-19 pandemic. The perceived availability of emotional support and positive social interactions, more so than tangible support, was key. Individuals more vulnerable to depression (e.g., women, younger individuals, and those experiencing financial stressors) may particularly benefit from enhanced social support, supporting a precision prevention approach.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.11.22274952", + "rel_abs": "The aim of the study was to evaluate the correlation of plasma levels of thiobarbituric acid reactive substances (TBARS) and reduced thiols with morbidity, mortality and immune response in SARS-CoV-2 infection. This was an observational study that included inpatients with SARS-CoV-2 infection greater than 65 years old. Individuals were followed up until 12 months after hospital discharge. Demographic, clinical and laboratory variables were collected. Plasma levels of TBARS and reduced thiols were quantified as a measure of lipid and protein oxidation, respectively. Events of interest (fatal and non-fatal) were quantified at hospital discharge, third, sixth and twelfth-month post-discharge. The outcomes were differences in oxidative stress markers between groups of interest and time to a negative RT-qPCR and to significant anti-SARS-CoV-2 IgM titers. There were 61 patients (57% women) with a mean age of 83 years old. Patients with higher levels of TBARS and lower levels of reduced thiols had more risk of fatal and non-fatal events between admission and the first 12 months post-discharge. The presence of any event (fatal or non-fatal) at the end of the first 12 months post-discharge was correlated with TBARS levels, anti-SARS-CoV-2 IgM titers, lactate dehydrogenase, platelet count and neutrophil and lymphocyte count. We found a correlation between plasma reduced thiols and time to achieve significant anti-SARS-CoV-2 IgM titers. Assessment of some parameters related to oxidative stress could help to identify groups of patients with a higher risk of morbidity and mortality during and after SARS-CoV-2 infection.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Karmel W Choi", - "author_inst": "Massachusetts General Hospital" + "author_name": "Nestor Vazquez-Agra", + "author_inst": "University Hospital of Santiago de Compostela: Complejo Hospitalario Universitario de Santiago de Compostela" }, { - "author_name": "Younga H Lee", - "author_inst": "Massachusetts General Hospital" + "author_name": "Ana-Teresa Marques-Afonso", + "author_inst": "University Hospital of Santiago de Compostela: Complejo Hospitalario Universitario de Santiago de Compostela" }, { - "author_name": "Zhaowen Liu", - "author_inst": "Massachusetts General Hospital" + "author_name": "Anton Cruces-Sande", + "author_inst": "University of Santiago de Compostela: Universidade de Santiago de Compostela" }, { - "author_name": "Daniel Fatori", - "author_inst": "Faculdade de Medicina da Universidade de S\u00e3o Paulo" + "author_name": "Ignacio Novo-Veleiro", + "author_inst": "University Hospital of Santiago de Compostela: Complejo Hospitalario Universitario de Santiago de Compostela" }, { - "author_name": "Joshua R Bauermeister", - "author_inst": "University of Oxford" + "author_name": "Antonio Pose-Reino", + "author_inst": "University Hospital of Santiago de Compostela: Complejo Hospitalario Universitario de Santiago de Compostela" }, { - "author_name": "Rebecca A Luh", - "author_inst": "Massachusetts General Hospital" + "author_name": "Estefania Mendez-Alvarez", + "author_inst": "University of Santiago de Compostela: Universidade de Santiago de Compostela" }, { - "author_name": "Cheryl R Clark", - "author_inst": "Brigham and Women's Hospital" - }, - { - "author_name": "Andr\u00e9 R Brunoni", - "author_inst": "Faculdade de Medicina da Universidade de S\u00e3o Paulo" - }, - { - "author_name": "Sarah Bauermeister", - "author_inst": "University of Oxford" + "author_name": "Ramon Soto-Otero", + "author_inst": "University of Santiago de Compostela: Universidade de Santiago de Compostela" }, { - "author_name": "Jordan W Smoller", - "author_inst": "Massachusetts General Hospital" + "author_name": "alvaro hermida-Ameijeiras", + "author_inst": "University Hospital of Santiago de Compostela: Complejo Hospitalario Universitario de Santiago de Compostela" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "geriatric medicine" }, { "rel_doi": "10.1101/2022.05.14.491911", @@ -279125,41 +278643,37 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.05.12.491584", - "rel_title": "Low immune response after 1.5 years of primary SARS-CoV-2 infection and Covishield vaccination lead to SARS-CoV-2 reinfection", + "rel_doi": "10.1101/2022.05.10.491349", + "rel_title": "Biochemical Characterization of Emerging SARS-CoV-2 Nsp15 Endoribonuclease Variants", "rel_date": "2022-05-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.12.491584", - "rel_abs": "We have investigated six COVID recovered cases with two doses of Covishield vaccination followed by reinfection. The primary SARS-CoV-2 infection found to occur with B.1 and reinfection with Omicron BA.1 and BA.2 variants. The genomic characterization and duration between two infections confirms these cases as SARS-CoV-2 reinfection. The mutation analysis of the reinfection cases correlated with immune evasion potential of BA.1 and BA.2 sub lineages. The immune response determined at different time intervals demonstrated boost post two dose vaccination, decline in pre-reinfection sera post 7 months and rise post reinfection. Apparently, these cases suffered from SARS-CoV-2 reinfection with the declined hybrid immunity acquired from primary infection and two dose covishield vaccination. This suggests the need for booster dose of vaccination. Besides this, multiple non-pharmaceutical interventions should be used to cope up with SARS-CoV-2 infection.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.10.491349", + "rel_abs": "Global sequencing efforts from the ongoing COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, continue to provide insight into the evolution of the viral genome. Coronaviruses encode 16 nonstructural proteins, within the first two-thirds of their genome, that facilitate viral replication and transcription as well as evasion of the host immune response. However, many of these viral proteins remain understudied. Nsp15 is a uridine-specific endoribonuclease conserved across all coronaviruses. The nuclease activity of Nsp15 helps the virus evade triggering an innate immune response. Understanding how Nsp15 has changed over the course of the pandemic, and how mutations affect its RNA processing function, will provide insight into the evolution of an oligomerization-dependent endoribonuclease and inform drug design. In combination with previous structural data, bioinformatics analyses of 1.9+ million SARS-CoV-2 sequences revealed mutations across Nsp15s three structured domains (N-terminal, Middle, EndoU). Selected Nsp15 variants were characterized biochemically and compared to wild type Nsp15. We found that mutations to important catalytic residues decreased cleavage activity but increased the hexamer/monomer ratio of the recombinant protein. Many of the highly prevalent variants we analyzed led to decreased nuclease activity as well as an increase in the inactive, monomeric form. Overall, our work establishes how Nsp15 variants seen in patient samples affect nuclease activity and oligomerization, providing insight into the effect of these variants in vivo.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Anita M Shete", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" - }, - { - "author_name": "Deepak Y Patil", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" + "author_name": "Isha M Wilson", + "author_inst": "National Institute of Environmental Health Sciences" }, { - "author_name": "Rima R Sahay", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" + "author_name": "Meredith N Frazier", + "author_inst": "National Institute of Environmental Health Sciences" }, { - "author_name": "Gajanan N Sapkal", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" + "author_name": "Jian-Liang N Li", + "author_inst": "National Institute of Environmental Health Sciences" }, { - "author_name": "Gururaj R Deshpande", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" + "author_name": "Thomas A. Randall", + "author_inst": "National Institute of Environmental Health Sciences, NIH" }, { - "author_name": "Pragya Yadav", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" + "author_name": "Robin E Stanley", + "author_inst": "National Institute of Environmental Health Sciences" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "new results", "category": "microbiology" }, @@ -281155,33 +280669,57 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.05.09.22274870", - "rel_title": "Time series modeling to estimate unrecorded burden of 12 symptomatic medical conditions among United States Medicare beneficiaries during the COVID-19 pandemic", + "rel_doi": "10.1101/2022.05.09.22274838", + "rel_title": "Socio-economic determinants of SARS-CoV-2 infection: results from a population-based serosurvey in Geneva, Switzerland", "rel_date": "2022-05-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.09.22274870", - "rel_abs": "ObjectiveU.S. healthcare utilization declined during the COVID-19 pandemic, potentially leading to spurious drops in disease incidence recorded in administrative healthcare datasets used for public health surveillance. We used time series modeling to characterize the magnitude and duration of the COVID-19 pandemics impact on claims-based monthly incidence of 12 symptomatic conditions among Medicare beneficiaries aged [≥]65 years.\n\nMethodsTime series of observed monthly incidence of each condition were generated using Medicare claims data from January 2016-May 2021. Incidence time series were decomposed through seasonal and trend decomposition using Loess, resulting in seasonal, trend, and remainder components. We fit a non-linear mixed effects model to remainder time series components and used it to estimate underlying incidence and number of unrecorded cases of each condition during the pandemic period.\n\nResultsObserved incidence of all 12 conditions declined steeply in March 2020 with nadirs in April 2020, generally followed by return to pre-pandemic trends. The relative magnitude of the decrease varied by condition, but month of onset and duration did not. Estimated unrecorded cases during March 2020-May 2021 ranged from 9,543 (95% confidence interval [CI]: 854-15,703) for herpes zoster to 236,244 (95% CI: 188,583-292,369) for cataracts.\n\nConclusionsDue to reduced healthcare utilization during the COVID-19 pandemic, claims-based data underestimate incidence of non-COVID-19 conditions. Time series modeling can be used to quantify this underestimation, facilitating longitudinal analyses of disease incidence pre- and post-pandemic.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.09.22274838", + "rel_abs": "BackgroundSARS-CoV-2 infection and its health consequences have disproportionally affected disadvantaged socio-economic groups globally. This study aimed to analyze the association between socio-economic conditions and having developed anti-SARS-CoV-2 antibodies in a population-based sample in the canton of Geneva, Switzerland.\n\nMethodsData was obtained from a population-based serosurvey of adults in Geneva and their household members, between November and December, 2020, towards the end of the second pandemic wave in the canton. Participants were tested for anti-SARS-CoV-2 antibodies. Socio-economic conditions representing different dimensions were self-reported. Mixed effects logistic regressions were conducted for each predictor to test its association with seropositive status as the main outcome.\n\nResults2,889 adults completed the study questionnaire and were included in the final analysis. Retired participants and those living in suburban areas had lower odds of a seropositive result when compared to employed participants (OR 0.42, 95% CI - 0.20 - 0.87) and those living in urban areas (OR 0.67, 95% CI - 0.46 - 0.97), respectively. People facing financial hardship for less than a year had higher odds of a seropositive result compared to those who had never faced them (OR 2.23, 95% CI - 1.01 - 4.95). Educational level, occupational position and household income were not associated with being seropositive, nor were ethnicity or country of birth.\n\nDiscussionWhile traditional measures of socio-economic position did not seem to be related to the risk of being infected in this sample, this study sheds lights on the importance of examining the broader social determinants of health when evaluating the differential impact of the pandemic within the population.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Michael Melgar", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Hugo Alejandro Santa-Ramirez", + "author_inst": "Unit of Population Epidemiology, Division of Primary Care, Geneva University Hospitals" }, { - "author_name": "Jessica Leung", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Ania Wisniak", + "author_inst": "Unit of Population Epidemiology, Division of Primary Care, Geneva University Hospitals - Institute of Global Health, Faculty of Medicine, University of Geneva," }, { - "author_name": "Jeffrey Colombe", - "author_inst": "The MITRE Corporation" + "author_name": "Nick Pullen", + "author_inst": "Unit of Population Epidemiology, Division of Primary Care, Geneva University Hospitals" }, { - "author_name": "Kathleen Dooling", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Maria Eugenia Zaballa", + "author_inst": "Unit of Population Epidemiology, Division of Primary Care, Geneva University Hospitals" + }, + { + "author_name": "Francesco Pennacchio", + "author_inst": "Unit of Population Epidemiology, Division of Primary Care, Geneva University Hospitals" + }, + { + "author_name": "Elsa Lorthe", + "author_inst": "Unit of Population Epidemiology, Division of Primary Care, Geneva University Hospitals" + }, + { + "author_name": "Roxane Dumont", + "author_inst": "Unit of Population Epidemiology, Division of Primary Care, Geneva University Hospitals" + }, + { + "author_name": "Helene Baysson", + "author_inst": "Unit of Population Epidemiology, Division of Primary Care, Geneva University Hospitals" + }, + { + "author_name": "Idris Guessous", + "author_inst": "Unit of Population Epidemiology, Division of Primary Care, Geneva University Hospitals - Department of Health and Community Medicine, Faculty of Medicine, Unive" + }, + { + "author_name": "Silvia Stringhini", + "author_inst": "Unit of Population Epidemiology, Division of Primary Care, Geneva University Hospitals - Department of Health and Community Medicine, Faculty of Medicine, Unive" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -282841,95 +282379,87 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.05.04.22274208", - "rel_title": "Decreased cerebral blood flow in non-hospitalized adults who self-isolated due to COVID-19", + "rel_doi": "10.1101/2022.05.06.22274658", + "rel_title": "STIMULATE-ICP-CAREINEQUAL - Defining usual care and examining inequalities in Long Covid support: protocol for a mixed-methods study (part of STIMULATE-ICP: Symptoms, Trajectory, Inequalities and Management: Understanding Long-COVID to Address and Transform Existing Integrated Care Pathways).", "rel_date": "2022-05-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.04.22274208", - "rel_abs": "The long-term consequences of coronavirus disease 2019 (COVID-19) on brain physiology and function are not yet well understood. From the recently described NeuroCOVID-19 study, we examined cerebral blood flow (CBF) in 50 participants recruited to one of two groups: 1) adults who previously self-isolated at home due to COVID-19 (n = 39; 116.5 {+/-} 62.2 days since positive diagnosis), or 2) controls who experienced flu-like symptoms but had a negative COVID-19 diagnosis (n = 11). Participants underwent arterial spin labeling magnetic resonance imaging at 3 T to yield measures of CBF. Voxel-wise analyses of CBF were performed to assess for between-group differences, after controlling for age and sex. Relative to controls, the COVID-19 group exhibited decreased CBF in the thalamus, orbitofrontal cortex, and regions of the basal ganglia. Within the COVID-19 group, CBF differences in occipital and parietal regions were observed between those with (n = 11) and without (n = 28) self-reported on-going fatigue. These results suggest long-term changes in brain physiology in adults across the post-COVID-19 timeframe. Moreover, CBF may aid in understanding the heterogeneous symptoms of the post-COVID-19 condition. Future longitudinal studies are needed to further characterize the consequences of COVID-19 on the brain.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.06.22274658", + "rel_abs": "IntroductionIndividuals with Long Covid represent a new and growing patient population. In England, fewer than 90 Long Covid clinics deliver assessment and treatment informed by NICE guidelines. However, a paucity of clinical trials or longitudinal cohort studies means that the epidemiology, clinical trajectory, healthcare utilisation and effectiveness of current Long Covid care are poorly documented, and that neither evidence-based treatments nor rehabilitation strategies exist. In addition, and in part due to pre-pandemic health inequalities, access to referral and care varies, and patient experience of the Long Covid care pathways can be poor.\n\nIn a mixed methods study, we therefore aim to: (1) describe the usual healthcare, outcomes and resource utilisation of individuals with Long Covid; (2) assess the extent of inequalities in access to Long Covid care, and specifically to understand Long Covid patients experiences of stigma and discrimination.\n\nMethods and analysisA mixed methods study will address our aims. Qualitative data collection from patients and health professionals will be achieved through surveys, interviews and focus group discussions, to understand their experience and document the function of clinics. A patient cohort study will provide an understanding of outcomes and costs of care. Accessible data will be further analysed to understand the nature of Long Covid, and the care received.\n\nEthics and disseminationEthical approval was obtained from South Central - Berkshire Research Ethics Committee (reference 303958). The dissemination plan will be decided by the patient and public involvement and engagement (PPIE) group members and study Co-Is, but will target 1) policy makers, and those responsible for commissioning and delivering Long Covid services, 2) patients and the public, and 3) academics.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "William S.H. Kim", - "author_inst": "Sunnybrook Research Institute" - }, - { - "author_name": "Xiang Ji", - "author_inst": "Sunnybrook Research Institute" - }, - { - "author_name": "Eugenie Roudaia", - "author_inst": "Rotman Research Institute" + "author_name": "Mel Ramasawmy", + "author_inst": "Institute of Health Informatics, University College London" }, { - "author_name": "J. Jean Chen", - "author_inst": "Rotman Research Institute" + "author_name": "Yi Mu", + "author_inst": "Institute of Health Informatics, University College London" }, { - "author_name": "Asaf Gilboa", - "author_inst": "Rotman Research Institute" + "author_name": "Donna Clutterbuck", + "author_inst": "School of Primary Care, Population Sciences and Medical Education, University of Southampton" }, { - "author_name": "Allison B. Sekuler", - "author_inst": "Rotman Research Institute" + "author_name": "Marija Pantelic", + "author_inst": "Brighton and Sussex Medical School, University of Sussex" }, { - "author_name": "Fuqiang Gao", - "author_inst": "Sunnybrook Research Institute" + "author_name": "Gregory Y.H. Lip", + "author_inst": "Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool, United Kingdom; and Department of Clinical" }, { - "author_name": "Zhongmin Lin", - "author_inst": "Sunnybrook Research Institute" + "author_name": "Christina Van der Feltz-Cornelis", + "author_inst": "Department of Health Sciences, HYMS, University of York, and Institute of Health Informatics, University College London" }, { - "author_name": "Aravinthan Jegatheesan", - "author_inst": "Sunnybrook Research Institute" + "author_name": "Dan Wootton", + "author_inst": "Institute of Infection Veterinary and Ecological Sciences, University of Liverpool" }, { - "author_name": "Mario Masellis", - "author_inst": "Sunnybrook Research Institute" + "author_name": "Nefyn H Williams", + "author_inst": "Department of Primary Care and Mental Health, University of Liverpool" }, { - "author_name": "Maged Goubran", - "author_inst": "Sunnybrook Research Institute" + "author_name": "Hugh Montgomery", + "author_inst": "Centre for Human Health and Performance, Department of Medicine, University College London" }, { - "author_name": "Jennifer S. Rabin", - "author_inst": "Sunnybrook Research Institute" + "author_name": "Rita Mallinson Cookson", + "author_inst": "PPIE Representative" }, { - "author_name": "Benjamin Lam", - "author_inst": "Sunnybrook Research Institute" + "author_name": "Emily Attree", + "author_inst": "PPIE Representative" }, { - "author_name": "Ivy Cheng", - "author_inst": "Sunnybrook Research Institute" + "author_name": "Mark Gabbay", + "author_inst": "Department of Primary Care and Mental Health, University of Liverpool" }, { - "author_name": "Robert Fowler", - "author_inst": "Sunnybrook Research Institute" + "author_name": "Melissa J Heightman", + "author_inst": "University College London Hospitals NHS Trust" }, { - "author_name": "Chinthaka Heyn", - "author_inst": "Sunnybrook Research Institute" + "author_name": "Nisreen A Alwan", + "author_inst": "School of Primary Care, Population Sciences and Medical Education, University of Southampton; NIHR Southampton Biomedical Research Centre, University of Southam" }, { - "author_name": "Sandra E. Black", - "author_inst": "Sunnybrook Research Institute" + "author_name": "Amitava Banerjee", + "author_inst": "Institute of Health Informatics, University College London" }, { - "author_name": "Simon J. Graham", - "author_inst": "Sunnybrook Research Institute" + "author_name": "Paula Lorgelly", + "author_inst": "School of Population Health and Department of Economics, University of Auckland" }, { - "author_name": "Bradley J. MacIntosh", - "author_inst": "Sunnybrook Research Institute" + "author_name": "- STIMULATE-ICP consortium", + "author_inst": "" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "health systems and quality improvement" }, { "rel_doi": "10.1101/2022.05.06.22274782", @@ -284595,43 +284125,67 @@ "category": "gastroenterology" }, { - "rel_doi": "10.1101/2022.05.03.22274641", - "rel_title": "Correlation of Suspected COVID-19 Symptoms with COVID-19 Positivity in Children", + "rel_doi": "10.1101/2022.05.04.22274659", + "rel_title": "What innovations can address inequalities experienced by women and girls due to the COVID-19 pandemic across the different areas of life/domains: work, health, living standards, personal security, participation and education? Rapid Review", "rel_date": "2022-05-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.03.22274641", - "rel_abs": "BackgroundEarly in the pandemic, COVID-19 was found to infect adults at higher rates than children, leaving limited data on disease presentation in children. Further understanding of the epidemiology of COVID-19 symptoms among children is needed. Our aim was to explore how symptoms vary between children testing positive for COVID-19 infection versus children testing negative.\n\nMethodsData analysis of symptom prevalence among pediatric patients presenting to emergency departments (ED) in the Johns Hopkins Health System (JHHS) with concern for COVID-19 who subsequently received COVID-19 testing. Inclusion criteria included patients 0-17 years-of-age, ED evaluation between March 15th, 2020 - May 11th, 2020, and those who were ordered for COVID-19 testing. Chart review was performed to document symptoms using ED provider notes. Comparisons were made using chi-squared t-tests and Students t-tests.\n\nResultsFever (62.6%) and cough (47.9%) were the most prevalent symptoms among children with suspected COVID-19 infection. Compared to children with a negative COVID-19 test, children who tested positive had higher prevalence of myalgia (21.7% vs 6.0%) and loss of taste/smell (15.2% vs 0.9%). Over half of the children who tested positive for COVID-19 had public insurance (52.2%) and 58.7% of the positive tests occurred among children with Hispanic ethnicity.\n\nConclusionsMyalgia and loss of taste/smell were found to be significantly more prevalent among COVID-19 positive children compared to children testing negative. Additionally, children with public insurance and those with Hispanic ethnicity were more likely to test positive, emphasizing the importance of social factors in the screening and decision-making process.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.04.22274659", + "rel_abs": "TOPLINE SUMMARYO_ST_ABSWhat is a Rapid Review?C_ST_ABSOur rapid reviews use a variation of the systematic review approach, abbreviating or omitting some components to generate the evidence to inform stakeholders promptly whilst maintaining attention to bias. They follow the methodological recommendations and minimum standards for conducting and reporting rapid reviews, including a structured protocol, systematic search, screening, data extraction, critical appraisal and evidence synthesis to answer a specific question and identify key research gaps. They take one to two months, depending on the breadth and complexity of the research topic/question(s), the extent of the evidence base and type of analysis required for synthesis.\n\nBackground / Aim of Rapid ReviewThe COVID-19 pandemic has led to differential economic, health and social impacts illuminating prevailing gender inequalities (WEN Wales, 2020). This rapid review investigated evidence for effectiveness of interventions to address gender inequalities across the domains of work, health, living standards, personal security, participation, and education.\n\nKey FindingsO_ST_ABSExtent of the evidence baseC_ST_ABSO_LI21 studies were identified: 7 reviews, 6 commentaries and 8 primary studies\nC_LIO_LILimited evidence for the effectiveness of identified innovations in minority groups\nC_LIO_LIA lack of evaluation data for educational interventions\nC_LIO_LIA lack of evidence for cost-effectiveness of the identified interventions\nC_LIO_LI14 additional articles were identified in the grey literature but not used to inform findings (apart from the Education domain, where there was a lack of peer-reviewed evidence).\nC_LI\n\nRecency of the evidence baseO_LIAll studies were published in 2020-2021\nC_LI\n\nSummary of findingsSome evidence supported interventions/innovations related to work: O_LIPermanent contracts, full-time hours, and national childcare programmes to increase income for women and thereby decrease the existing gender wage gap.\nC_LIO_LIMore frequent use of online platforms in the presentation of professional work can reduce gender disparities due to time saved in travel away from home.\nC_LI Some evidence supported interventions/innovations related to health: O_LILeadership in digital health companies could benefit from women developing gender-friendly technology that meets the health needs of women.\nC_LIO_LICreate authentic partnerships with black women and female-led organisations to reduce maternal morbidity and mortality (Bray & McLemore, 2021).\nC_LI Some evidence supported interventions/innovations related to living standards including: O_LIMulti-dimensional care provided to women and their children experiencing homelessness.\nC_LI Limited evidence supported interventions/innovations related to personal security including: O_LISpecific training of social workers, psychologists and therapists to empower women to use coping strategies and utilise services to gain protection from abusive partners.\nC_LIO_LIHelplines, virtual safe spaces smart phone applications and online counselling to address issues of violence and abuse for women and girls.\nC_LI Very limited evidence supported interventions/innovations related to participation including: O_LIUse of online platforms to reduce gender disparities in the presentation of academic/professional work.\nC_LIO_LIEnsuring equal representation, including women and marginalised persons, in pandemic response and recovery planning and decision-making.\nC_LI Limited evidence from the grey literature described interventions/innovations related to education including: O_LITeacher training curricula development to empower teachers to understand and challenge gender stereotypes in learning environments.\nC_LIO_LIEducation for girls to enable participation in STEM.\nC_LI\n\nPolicy ImplicationsThis evidence can be used to map against existing policies to identify which are supported by the evidence, which are not in current policy and could be implemented and where further research/evaluation is needed.\n\nFurther research is needed to evaluate the effectiveness of educational innovations, the effectiveness of the innovations in minority groups and the social value gained from interventions to address gender inequalities.\n\nStrength of EvidenceOne systematic review on mobile interventions targeting common mental disorders among pregnant and postpartum women was rated as high quality (Saad et al., 2021). The overall confidence in the strength of evidence was rated as low due to study designs. Searches did not include COVID specific resources or pre-prints. There may be additional interventions/innovations that have been implemented to reduce inequalities experienced by women and girls due to the COVID-19 pandemic but have not been evaluated or published in the literature and are therefore not included here.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Sanika Satoskar", - "author_inst": "Northeast Ohio Medical University College of Medicine" + "author_name": "Llinos Haf Spencer", + "author_inst": "Bangor University" }, { - "author_name": "Daniel Hindman", - "author_inst": "Johns Hopkins School of Medicine: Johns Hopkins University School of Medicine" + "author_name": "Ned Hartfiel", + "author_inst": "Bangor University" }, { - "author_name": "Amyna Husain", - "author_inst": "Johns Hopkins School of Medicine: Johns Hopkins University School of Medicine" + "author_name": "Annie Hendry", + "author_inst": "Bangor University" }, { - "author_name": "Laura Prichett", - "author_inst": "Johns Hopkins School of Medicine: Johns Hopkins University School of Medicine" + "author_name": "Bethany Fern Anthony", + "author_inst": "Bangor University" }, { - "author_name": "Oluwakemi Badaki", - "author_inst": "Johns Hopkins School of Medicine: Johns Hopkins University School of Medicine" + "author_name": "Abraham Makanjuola", + "author_inst": "Bangor University" }, { - "author_name": "Ann Kane", - "author_inst": "Johns Hopkins School of Medicine: Johns Hopkins University School of Medicine" + "author_name": "Kalpa Pisavadia", + "author_inst": "Bangor University" + }, + { + "author_name": "Jacob Davies", + "author_inst": "Bangor University" + }, + { + "author_name": "Nathan Bray", + "author_inst": "Bangor University" + }, + { + "author_name": "Dyfrig A. Hughes", + "author_inst": "Bangor University" + }, + { + "author_name": "Clare Wilkinson", + "author_inst": "Bangor University" + }, + { + "author_name": "Deborah Fitzsimmons", + "author_inst": "Swansea University" + }, + { + "author_name": "Rhiannon Tudor Edwards", + "author_inst": "Bangor University" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.05.02.22274456", @@ -286777,43 +286331,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.04.29.22274454", - "rel_title": "Effectiveness of Covid-19 vaccines against SARS-CoV-2 Omicron variant (B.1.1.529): A systematic review with meta-analysis and meta-regression", + "rel_doi": "10.1101/2022.05.01.22274540", + "rel_title": "Keeping it close: The role of a Campus COVID Support Team (CCST) in sustaining a safe and healthy university campus during COVID-19", "rel_date": "2022-05-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.29.22274454", - "rel_abs": "BackgroundThere is a need for evaluation regarding vaccine effectiveness (VE) and the urgency of booster vaccination against Covid-19 B.1.1.529 (Omicron) variant.\n\nMethodsSystematic search was conducted on April 6th, 2022, on databases (PubMed, ScienceDirect, CENTRAL, Web of Science, Scopus). VE difference (VED) estimates were assessed using random-effects model and DerSimonian-Laird tau estimators. Two models result, i.e., within 3 months and within 3 months or more, are compared. VE versus time meta-regression analysis was evaluated using mixed-effects model with Restricted-Maximum Likelihood tau estimators and Hartung-Knapp adjustments.\n\nFindingsAd26.COV2.S, BNT162b2, ChAdOx1 nCov-19, and mRNA-1273 vaccines were included in the analyses. Compared to full dose, booster dose of overall vaccines provided better protection against any (VED=22% (95%CI 15%-29%), p<0.001), severe (VED=20% (95%CI 8%-32%), p=0.001) and symptomatic (VED=22% (95%CI 11%-34%), p<0.001) Omicron infections within 3 months, as well as within 3 months or more (VED=30% (95%CI 24%-37%), p<0.001 for any, VED=18% (95%CI 13%-23%), p<0.001 for severe and VED=37% (95%CI 29%-46%), p<0.001 for symptomatic infections). The meta-regression analysis of overall vaccines revealed that the full dose VE against any and symptomatic Omicron infections were significantly reduced each month by 3.0% (95%CI 0.9%-4.8%, p=0.004) and 5.2% (95%CI 3.3%-7.1%, p=0.006), respectively; whereas booster dose effectiveness against severe and symptomatic Omicron infections were decreased by 3.7% (95%CI 5.1%-12.6%, p=0.030) and 3.9% (95%CI 1.2%-6.5%, p=0.006), respectively.\n\nInterpretationCompared to full dose only, a booster dose addition provides better protection against B.1.1.529 infection. Although the VE estimates of Ad26.COV2.S, BNT162b2, ChAdOx1 nCov-19, and mRNA-1273 vaccines against B.1.1.529 infection after both full and booster doses are generally moderate, and the booster dose provides excellent protection against severe infection, it is important to note that the VE estimates decline over time, suggesting the need for a regular Covid-19 booster injection after certain period of time to maintain VE.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.01.22274540", + "rel_abs": "It has been over 24 months since the start of the COVID-19 pandemic forced university campuses to shut down and then reopen under new safety guidelines. Now as we move into the subsequent years of the pandemic, we can look back and evaluate what has worked, improvements to be made, and plans for providing a sustained response for a campus community. In this article we detail one campus response to the COVID-19 pandemic and directions being taken to ensure a sustained campus COVID support team (CCST) is in hand to ensure the health and safety of the university community. The CCST was created to serve as a one-stop-shop to help the university community navigate COVID-19 policies and procedures. The responsibilities of the CCST include conducting case investigations for any positive COVID-19 tests within the university community, contact tracing for authorized university affiliates, epidemiological surveillance and mitigation efforts, and communication through real-time analysis and dashboards. Continuous monitoring procedures demonstrated the CCST conducted all case investigations within the post-testing 24-hour window, thus keeping the university test-positivity rate below 3%. Quality improvement surveys demonstrated a high level of satisfaction with the CCST efforts and provided areas for improvement and sustainability. Having a public health faculty led CCST enabled the university to act swiftly when COVID-19 positive cases were emerging and deter widespread campus COVID-19 outbreaks. The CCST timeliness and connectivity to the campus has demonstrated benefits to the health and safety of the campus.\n\nHighlightsO_LIUniversities are their own communities and having on campus COVID support teams can mitigate potential COVID-19 outbreaks.\nC_LIO_LIHaving a public health driven Campus COVID Support Team that can conduct case investigations within 24 hours of a positive test result has demonstrated benefits to taking responsive measures.\nC_LIO_LIContinuous quality improvement efforts including surveys of the Campus COVID Support Team should be implemented for any COVID service efforts.\nC_LI", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Nando Reza Pratama", - "author_inst": "Faculty of Medicine, Airlangga University" - }, - { - "author_name": "Ifan Ali Wafa", - "author_inst": "Faculty of Medicine, Airlangga University" + "author_name": "Karen A McDonnell", + "author_inst": "The George Washington University, Milken Institute School of Public Health" }, { - "author_name": "David Setyo Budi", - "author_inst": "Faculty of Medicine, Airlangga University" + "author_name": "Amanda D Castel", + "author_inst": "The George Washington University Milken Institute School of Public Health" }, { - "author_name": "Henry Sutanto", - "author_inst": "Department of Physiology and Pharmacology, State University of New York (SUNY) Downstate Health Sciences University" + "author_name": "Amita B Vyas", + "author_inst": "The George Washington University, Milken Institute School of Public Health" }, { - "author_name": "Tri Pudy Asmarawati", - "author_inst": "Department of Internal Medicine, Universitas Airlangga Hospital, Universitas Airlangga, Indonesia" + "author_name": "Nitasha C Nagaraj", + "author_inst": "The George Washington University, Milken Institute School of Public Health" }, { - "author_name": "Citrawati Dyah Kencono Wungu", - "author_inst": "Department of Physiology and Medical Biochemistry, Faculty of Medicine, Universitas Airlangga" + "author_name": "Megan Landry", + "author_inst": "The George Washington University, Milken Institute School of Public Health" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.05.01.490203", @@ -288771,55 +288321,55 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.04.28.22273177", - "rel_title": "Occupational differences in SARS-CoV-2 infection: Analysis of the UK ONS Coronavirus (COVID-19) Infection Survey", + "rel_doi": "10.1101/2022.04.28.489859", + "rel_title": "Argon plasma-modified bacterial cellulose filters for protection against respiratory pathogens", "rel_date": "2022-04-29", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.28.22273177", - "rel_abs": "BackgroundConsiderable concern remains about how occupational SARS-CoV-2 risk has evolved during the COVID-19 pandemic. We aimed to ascertain which occupations had the greatest risk of SARS-CoV-2 infection and explore how relative differences varied over the pandemic.\n\nMethodsAnalysis of cohort data from the UK Office of National Statistics Coronavirus (COVID-19) Infection Survey from April 2020 to November 2021. This survey is designed to be representative of the UK population and uses regular PCR testing. Cox and multilevel logistic regression to compare SARS-CoV-2 infection between occupational/sector groups, overall and by four time periods with interactions, adjusted for age, sex, ethnicity, deprivation, region, household size, urban/rural neighbourhood and current health conditions.\n\nResultsBased on 3,910,311 observations from 312,304 working age adults, elevated risks of infection can be seen overall for social care (HR 1.14; 95% CI 1.04 to 1.24), education (HR 1.31; 95% CI 1.23 to 1.39), bus and coach drivers (1.43; 95% CI 1.03 to 1.97) and police and protective services (HR 1.45; 95% CI 1.29 to 1.62) when compared to non-essential workers. By time period, relative differences were more pronounced early in the pandemic. For healthcare elevated odds in the early waves switched to a reduction in the later stages. Education saw raises after the initial lockdown and this has persisted. Adjustment for covariates made very little difference to effect estimates.\n\nConclusionsElevated risks among healthcare workers have diminished over time but education workers have had persistently higher risks. Long-term mitigation measures in certain workplaces may be warranted.\n\nWhat is already known on this topicSome occupational groups have observed increased rates of disease and mortality relating to COVID-19.\n\nWhat this study addsRelative differences between occupational groups have varied during different stages of the COVID-19 pandemic with risks for healthcare workers diminishing over time and workers in the education sector seeing persistent elevated risks.\n\nHow this study might affect research, practice or policyIncreased long term mitigation such as ventilation should be considered in sectors with a persistent elevated risk. It is important for workplace policy to be responsive to evolving pandemic risks.", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.28.489859", + "rel_abs": "Due to the global spread of the SARS-CoV-2 virus and the resultant pandemic, there has been a major surge in the demand for surgical masks, respirators, and other air filtration devices. Unfortunately, the fact that these filters are made of petrochemical-derived, non-biodegradable polymers means that the surge in production has also led to a surge in plastic waste. In this work, we present novel, sustainable filters based on bacterial cellulose (BC) functionalized with low-pressure argon plasma (LPP-Ar). The \"green\" production process involved BC biosynthesis by Komagataeibacter xylinus, followed by simple purification, homogenization, lyophilization, and finally LPP-Ar treatment. The obtained LPP-Ar-functionalized BC-based material (LPP-Ar-BC-bM) showed excellent antimicrobial and antiviral properties, with no cytotoxicity versus murine fibroblasts in vitro. Further, filters consisting of three layers of LPP-Ar-BC-bM had >99% bacterial and viral filtration efficiency, while maintaining sufficiently low airflow resistance (6 mbar at an airflow of 95 L/min). Finally, as a proof-of-concept, we were able to prepare 80 masks with LPP-Ar-BC-bM filter and ~85% of volunteer medical staff assessed them as good or very good in terms of comfort. We conclude that our novel sustainable, biobased, biodegradable filters are suitable for respiratory personal protective equipment (PPE), such as surgical masks and respirators. Further, with scale-up, they may be adapted for indoor air handling filtration in hospitals or schools.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC=\"FIGDIR/small/489859v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (46K):\norg.highwire.dtl.DTLVardef@99ae8dorg.highwire.dtl.DTLVardef@192c4eforg.highwire.dtl.DTLVardef@bf2acborg.highwire.dtl.DTLVardef@92907a_HPS_FORMAT_FIGEXP M_FIG C_FIG", "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Sarah Rhodes", - "author_inst": "University of Manchester" + "author_name": "Anna Zywicka", + "author_inst": "Department of Microbiology and Biotechnology, Faculty of Biotechnology and Animal Husbandry, West Pomeranian University of Technology in Szczecin" }, { - "author_name": "Jack Wilkinson", - "author_inst": "University of Manchester" + "author_name": "Daria Ciecholewska-Jusko", + "author_inst": "West Pomeranian University of Technology in Szczecin" }, { - "author_name": "Neil Pearce", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Magdalena Szymanska", + "author_inst": "Department of Microbiology and Biotechnology, Faculty of Biotechnology and Animal Husbandry, West Pomeranian University of Technology in Szczecin" }, { - "author_name": "Will Mueller", - "author_inst": "Institute of Occupational Medicine" + "author_name": "Radoslaw Drozd", + "author_inst": "Department of Microbiology and Biotechnology, Faculty of Biotechnology and Animal Husbandry, West Pomeranian University of Technology in Szczecin" }, { - "author_name": "Mark Cherrie", - "author_inst": "Institute of Occupational Medicine" + "author_name": "Peter Sobolewski", + "author_inst": "Department of Polymer and Biomaterials Science, West Pomeranian University of Technology in Szczecin, Faculty of Chemical Technology and Engineering" }, { - "author_name": "Katie Stocking", - "author_inst": "University of Manchester" + "author_name": "Adam Junka", + "author_inst": "Department of Pharmaceutical Microbiology and Parasitology, Faculty of Pharmacy, Wroclaw Medical University" }, { - "author_name": "Matthew Gittins", - "author_inst": "University of Manchester" + "author_name": "Selestina Gorgieva", + "author_inst": "Institute of Engineering Materials and Design, Faculty of Mechanical Engineering, University of Maribor" }, { - "author_name": "Srinivasa Vittal Katikireddi", - "author_inst": "University of Glasgow" + "author_name": "Miroslawa El Fray", + "author_inst": "Department of Polymer and Biomaterials Science, West Pomeranian University of Technology in Szczecin, Faculty of Chemical Technology and Engineering" }, { - "author_name": "Martie van Tongeren", - "author_inst": "University of Manchester" + "author_name": "Karol Fijalkowski", + "author_inst": "Department of Microbiology and Biotechnology, Faculty of Biotechnology and Animal Husbandry, West Pomeranian University of Technology in Szczecin" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "type": "new results", + "category": "bioengineering" }, { "rel_doi": "10.1101/2022.04.28.489942", @@ -290769,47 +290319,67 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.04.27.489750", - "rel_title": "Ligand Binding Prediction using Protein Structure Graphs and Residual Graph Attention Networks", + "rel_doi": "10.1101/2022.04.27.489747", + "rel_title": "Two types of human TCR differentially regulate reactivity to self and non-self antigens", "rel_date": "2022-04-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.27.489750", - "rel_abs": "MotivationComputational prediction of ligand-target interactions is a crucial part of modern drug discovery as it helps to bypass high costs and labor demands of in vitro and in vivo screening. As the wealth of bioactivity data accumulates, it provides opportunities for the development of deep learning (DL) models with increasing predictive powers. Conventionally, such models were either limited to the use of very simplified representations of proteins or ineffective voxelization of their 3D structures. Herein, we present the development of the PSG-BAR (Protein Structure Graph -Binding Affinity Regression) approach that utilizes 3D structural information of the proteins along with 2D graph representations of ligands. The method also introduces attention scores to selectively weight protein regions that are most important for ligand binding.\n\nResultsThe developed approach demonstrates the state-of-the-art performance on several binding affinity benchmarking datasets. The attention-based pooling of protein graphs enables identification of surface residues as critical residues for protein-ligand binding. Finally, we validate our model predictions against an experimental assay on a viral main protease (Mpro)- the hallmark target of SARS-CoV-2 coronavirus.\n\nAvailabilityThe code for PSG-BAR is made available at https://github.com/diamondspark/PSG-BAR\n\nContactacherkasov@prostatecentre.com", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.27.489747", + "rel_abs": "Based on analyses of TCR sequences from over 1,000 individuals, we report that the TCR repertoire is composed of two ontogenically and functionally distinct types of TCRs. Their production is regulated by variations in thymic output and terminal deoxynucleotidyl transferase (TDT) activity. Neonatal TCRs derived from TDT-negative progenitors persist throughout life, are highly shared among subjects, and are polyreactive to self and microbial antigens. Thus, >50% of cord blood TCRs are responsive to SARS-CoV2 and other common pathogens. TDT- dependent TCRs present distinct structural features and are less shared among subjects. TDT- dependent TCRs are produced in maximal numbers during infancy when thymic output and TDT activity reach a summit, are more abundant in subjects with AIRE mutations, and seem to play a dominant role in graft-versus-host disease. Factors decreasing thymic output (age, male sex) negatively impact TCR diversity. Males compensate for their lower repertoire diversity via hyperexpansion of selected TCR clonotypes.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Mohit Pandey", - "author_inst": "Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada." + "author_name": "Assya Trofimov", + "author_inst": "Institute for Research in Immunology and Cancer (IRIC), Department of Computer Science and Research Operations - University of Montreal" }, { - "author_name": "Mariia Radaeva", - "author_inst": "Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada." + "author_name": "Philippe Brouillard", + "author_inst": "Department of Computer Science and Research Operations - University of Montreal" }, { - "author_name": "Hazem Mslati", - "author_inst": "Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada." + "author_name": "Jean-David Larouche", + "author_inst": "Institute for Research in Immunology and Cancer (IRIC), Department of Medicine - University of Montreal" }, { - "author_name": "Olivia Garland", - "author_inst": "Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada." + "author_name": "Jonathan Seguin", + "author_inst": "Institute for Research in Immunology and Cancer (IRIC)" }, { - "author_name": "Michael Fernandez", - "author_inst": "Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada." + "author_name": "Jean-Philippe Laverdure", + "author_inst": "Institute for Research in Immunology and Cancer (IRIC)" }, { - "author_name": "Martin Ester", - "author_inst": "School of Computing Science, Simon Fraser University, Burnaby, British Columbia, Canada" + "author_name": "Ann Brasey", + "author_inst": "Maisonneuve-Rosemont Hospital" }, { - "author_name": "Artem Cherkasov", - "author_inst": "Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada." + "author_name": "Gregory Ehx", + "author_inst": "Institute for Research in Immunology and Cancer (IRIC), Interdisciplinary Cluster for Applied Geno-Proteomics (GIGA-I3) - University of Liege" + }, + { + "author_name": "Denis-Claude Roy", + "author_inst": "Maisonneuve-Rosemont Hospital" + }, + { + "author_name": "Lambert Busque", + "author_inst": "Maisonneuve-Rosemont Hospital" + }, + { + "author_name": "Silvy Lachance", + "author_inst": "Department of Medicine - University of Montreal, Maisonneuve-Rosemont Hospital" + }, + { + "author_name": "Sebastien Lemieux", + "author_inst": "Institute for Research in Immunology and Cancer (IRIC), Department of Computer Science and Research Operations - University of Montreal, Department of Biochemis" + }, + { + "author_name": "Claude Perreault", + "author_inst": "Institute for Research in Immunology and Cancer (IRIC), Department of Medicine - University of Montreal, Maisonneuve-Rosemont Hospital" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "new results", - "category": "bioinformatics" + "category": "immunology" }, { "rel_doi": "10.1101/2022.04.28.489850", @@ -292387,89 +291957,105 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.04.24.22273395", - "rel_title": "Shared N417-dependent epitope on the SARS-CoV-2 Omicron, Beta and Delta-plus variants", + "rel_doi": "10.1101/2022.04.20.22274076", + "rel_title": "Safety, tolerability and immunogenicity of Biological Es CORBEVAX vaccine in children and adolescents: A Prospective, Randomised, Double-blind, Placebo controlled, Phase-2/3 Study.", "rel_date": "2022-04-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.24.22273395", - "rel_abs": "As SARS-CoV-2 continues to evolve, several variants of concern (VOCs) have arisen which are defined by multiple mutations in their spike proteins. These VOCs have shown variable escape from antibody responses, and have been shown to trigger qualitatively different antibody responses during infection. By studying plasma from individuals infected with either the original D614G, Beta or Delta variants, we show that the Beta and Delta variants elicit antibody responses that are overall more cross-reactive than those triggered by D614G. Patterns of cross-reactivity varied, and the Beta and Delta variants did not elicit cross-reactive responses to each other. However, Beta-elicited plasma was highly cross-reactive against Delta plus (Delta+) which differs from Delta by a single K417N mutation in the receptor binding domain, suggesting the plasma response targets the N417 residue. To probe this further, we isolated monoclonal antibodies from a Beta-infected individual with plasma responses against Beta, Delta+ and Omicron, which all possess the N417 residue. We isolated a N417-dependent antibody, 084-7D, which showed similar neutralization breadth to the plasma. The 084-7D mAb utilized the IGHV3-23*01 germline gene and had similar somatic hypermutations compared to previously described public antibodies which target the 417 residue. Thus, we have identified a novel antibody which targets a shared epitope found on three distinct VOCs, enabling their cross-neutralization. Understanding antibodies targetting escape mutations such as K417N, which repeatedly emerge through convergent evolution in SARS-CoV-2 variants, may aid in the development of next-generation antibody therapeutics and vaccines.\n\nImportanceThe evolution of SARS-CoV-2 has resulted in variants of concern (VOCs) with distinct spike mutations conferring varying immune escape profiles. These variable mutations also influence the cross-reactivity of the antibody response mounted by individuals infected with each of these variants. This study sought to understand the antibody responses elicited by different SARS-CoV-2 variants, and to define shared epitopes. We show that Beta and Delta infection resulted in antibody responses that were more cross-reactive compared to the original D614G variant, but each with differing patterns of cross-reactivity. We further isolated an antibody from Beta infection, which targeted the N417 site, enabling cross-neutralization of Beta, Delta+ and Omicron, all of which possess this residue. The discovery of antibodies which target escape mutations common to multiple variants highlights conserved epitopes to target in future vaccines and therapeutics.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.20.22274076", + "rel_abs": "BackgroundAfter establishing safety and immunogenicity of Biological Es CORBEVAX vaccine in adult population (18-80 years) in Phase 1-3 studies, vaccine is further tested in children and adolescents in this study.\n\nMethodsThis is a phase-2/3 prospective, randomised, double-blind, placebo controlled, study evaluating safety, reactogenicity, tolerability and immunogenicity of CORBEVAX vaccine in children and adolescents of either gender between <18 to [≥]12 years of age in Phase-II and <18 to [≥]5 years of age in Phase-III with placebo as a control. This study has two age sub groups; age subgroup-1 with subjects <18 to [≥]12 years of age and age subgroup-2 with subjects <12 to [≥]5 years of age. In both age sub groups eligible subjects (SARS-CoV-2 RT-PCR negative and seronegative at baseline) were randomized to receive either CORBEVAX vaccine or Placebo in 3: 1 ratio.\n\nFindingsThe safety profile of CORBEVAX vaccine in both pediatric cohorts was comparable to the placebo control group. Majority of reported adverse events (AEs) were mild in nature. No severe or serious AEs, medically attended AEs (MAAEs) or AEs of special interest (AESI) were reported during the study period and all the reported AEs resolved without any sequelae. In both pediatric age groups, CORBEVAX vaccinated subjects showed significant improvement in humoral immune-responses in terms of anti-RBD-IgG concentrations, anti-RBD-IgG1 titers, neutralizing antibody (nAb)-titers against Ancestral Wuhan and Delta strains. Significantly high interferon gamma immune response (cellular) was elicited by CORBEVAX vaccinated subjects with minimal effect on IL-4 cytokine secretion.\n\nInterpretationsThe safety profile of CORBEVAX vaccine in <18 to [≥]5 years children and adolescents was found to be safe and tolerable. The adverse event profile was also found to be acceptable. Significant increase in anti-RBD IgG and nAb titers and IFN-gamma immune responses were observed post vaccination in both pediatric age sub groups. Both humoral and cellular immune responses were found to be non-inferior to the immune responses induced by CORBEVAX vaccine in adult population. This study shows that CORBEVAX vaccine is highly immunogenic and can be safely administered to pediatric population as young as 5 years old.\n\nThe study was prospectively registered with clinical trial registry of India-CTRI/2021/10/037066", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Thandeka Moyo-Gwete", - "author_inst": "National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa" + "author_name": "Subhash Thuluva", + "author_inst": "Biological E. Limited" }, { - "author_name": "Mashudu Madzivhandila", - "author_inst": "National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa." + "author_name": "Vikram Paradkar", + "author_inst": "Biological E Limited" }, { - "author_name": "Nonhlanhla N Mkhize", - "author_inst": "National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa." + "author_name": "Subbareddy Gunneri", + "author_inst": "Biological E Limited" }, { - "author_name": "Prudence Kgagudi", - "author_inst": "National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa." + "author_name": "Vijay Yerroju", + "author_inst": "Biological E Limited" }, { - "author_name": "Frances Ayres", - "author_inst": "National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa." + "author_name": "Rammohan Mogulla", + "author_inst": "Biological E Limited" }, { - "author_name": "Bronwen E Lambson", - "author_inst": "National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa." + "author_name": "Suneetha Venkata Pothakamuri", + "author_inst": "Biological E Limited" }, { - "author_name": "Nelia P Manamela", - "author_inst": "National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa." + "author_name": "Kishore Turaga", + "author_inst": "Biological E Limited" }, { - "author_name": "Simone I Richardson", - "author_inst": "National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa." + "author_name": "Mahesh Kyasani", + "author_inst": "Biological E Limited" }, { - "author_name": "Zanele Makhado", - "author_inst": "National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa." + "author_name": "Senthilkumar Manoharan", + "author_inst": "Biological E Limited" }, { - "author_name": "Mieke van der Mescht", - "author_inst": "Department of Immunology, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa." + "author_name": "Srikanth Adabala", + "author_inst": "Biological E Limited" }, { - "author_name": "Zelda de Beer", - "author_inst": "Tshwane District Hospital, Pretoria, South Africa." + "author_name": "Aditya Sri Javvadi", + "author_inst": "Biological E Limited" }, { - "author_name": "Talita Roma de Villiers", - "author_inst": "Tshwane District Hospital, Pretoria, South Africa." + "author_name": "Guruprasad R Medigeshi", + "author_inst": "Translational Health Science and Technology Institute" }, { - "author_name": "Wendy A Burgers", - "author_inst": "5Institute of Infectious Disease and Molecular Medicine, Division of Medical Virology, Department of Pathology, University of Cape Town, Cape Town, South Africa" + "author_name": "Janmejay Singh", + "author_inst": "Translational Health Science and Technology Institute" }, { - "author_name": "Ntobeko AB Ntusi", - "author_inst": "Division of Cardiology, Department of Medicine, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa." + "author_name": "Heena Shaman", + "author_inst": "Translational Health Science and Technology Institute" }, { - "author_name": "Theresa Rossouw", - "author_inst": "Department of Immunology, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa." + "author_name": "Akshay Binayke", + "author_inst": "Translational Health Science and Technology Institute" }, { - "author_name": "Veronica Ueckermann", - "author_inst": "Division for Infectious Diseases, Department of Internal Medicine, Steve Biko Academic Hospital and University of Pretoria, Pretoria, South Africa." + "author_name": "Zaheer Aymaan", + "author_inst": "Translational Health Science and Technology Institute" }, { - "author_name": "Michael T Boswell", - "author_inst": "Division for Infectious Diseases, Department of Internal Medicine, Steve Biko Academic Hospital and University of Pretoria, Pretoria, South Africa." + "author_name": "Amit Awasthi", + "author_inst": "Translational Health Science and Technology Institute" }, { - "author_name": "Penny L Moore", - "author_inst": "National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa." + "author_name": "Manish Narang", + "author_inst": "Guru Teg Bahadur Hospital" + }, + { + "author_name": "Pradeep N", + "author_inst": "Cheluvamba Hospital, Mysore" + }, + { + "author_name": "Niranjan Mahantshetti", + "author_inst": "KLES Dr. Prabhakar Kore Hospital & Medical Research Centre, Belagavi" + }, + { + "author_name": "Bishan Swarup Garg", + "author_inst": "Mahatma Gandhi Institute of Medical Sciences (MGIMS), Wardha" + }, + { + "author_name": "Mandal Ravi", + "author_inst": "ESIC Medical College & Hospital, Faridabad" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -294177,33 +293763,85 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2022.04.21.22274131", - "rel_title": "Risks and challenges in COVID-19 infection prevention and control in a hospital setting: perspectives of healthcare workers in Thailand", + "rel_doi": "10.1101/2022.04.21.22274060", + "rel_title": "Effectiveness of the neutralizing antibody sotrovimab among high-risk patients with mild to moderate SARS-CoV-2 in Qatar", "rel_date": "2022-04-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.21.22274131", - "rel_abs": "In hospital settings, awareness of, and responsiveness to, COVID-19 are crucial to reducing the risk of transmission among healthcare workers (HCWs) and protecting them from infection. Healthcare professionals can offer insights into the practicalities of infection prevention and control measures and on how the protective equipment and training could best be delivered during the pandemic. This study aimed to inform the development of future recommendations to optimise compliance with appropriate use of these measures, and to improve the guidance to reduce their risk of the disease. Drawing on in-depth interviews with HCWs in a hospital in Thailand, several factors influence the use of multiple prevention measures: concerns about infection, availability of the equipment supply, barriers to work performance, and physical limitations in the hospital setting. Setting a ventilated outdoor space for screening and testing, and interaction through mobile technology, were perceived to reduce the transmission risk for staff and patients. Adequate training, clear guidelines, streamlined communications, and management support are crucial to encourage appropriate use of, and adherence to, implementation of infection prevention and control (IPC) measures among HCW. Further study should explore the perceptions and experience of health professionals in local health facilities and community-based workers during the pandemic, particularly in resource-limited settings.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.21.22274060", + "rel_abs": "Effectiveness of sotrovimab against severe, critical, or fatal COVID-19 was investigated in Qatar using a case-control study design at a time when BA.2 Omicron subvariant dominated incidence. Adjusted odds ratio of progression to severe, critical, or fatal COVID-19, comparing those sotrovimab-treated to those untreated, was 2.67-fold higher (95% CI: 0.60-11.91).", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Monnaphat Jongdeepaisal", - "author_inst": "Faculty of Tropical Medicine, Mahidol University" + "author_name": "Ahmed Zaqout", + "author_inst": "Hamad Medical Corporation" }, { - "author_name": "Puri Chunekamrai", - "author_inst": "Srinkharinwirot University" + "author_name": "Muna A. Almaslamani", + "author_inst": "Hamad Medical Corporation" }, { - "author_name": "Rapeephan R Maude", - "author_inst": "Faculty of Medicine Ramathibodi Hospital" + "author_name": "Hiam Chemaitelly", + "author_inst": "Weill Cornell Medicine-Qatar" }, { - "author_name": "Richard James Maude", - "author_inst": "Faculty of Tropical Medicine, Mahidol University" + "author_name": "Samar A. Hashim", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Ajithkumar Ittaman", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Abeir Alimam", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Fatma Rustom", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Joanne Daghfal", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Mohammed Abukhattab", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Sawsan AlMukdad", + "author_inst": "Weill Cornell Medicine-Qatar" + }, + { + "author_name": "Anvar Hassan Kaleeckal", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Ali Nizar Latif", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Adeel A Butt", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Roberto Bertollini", + "author_inst": "Ministry of Public Health" + }, + { + "author_name": "Abdullatif Al-Khal", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Ali S. Omrani", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Laith J Abu-Raddad", + "author_inst": "Weill Cornell Medicine-Qatar" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -297523,65 +297161,85 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.04.19.488826", - "rel_title": "Compellingly high SARS-CoV-2 susceptibility of Golden Syrian hamsters suggests multiple zoonotic infections of pet hamsters during the COVID-19 pandemic", + "rel_doi": "10.1101/2022.04.20.488895", + "rel_title": "Emergence of new subgenomic mRNAs in SARS-CoV-2", "rel_date": "2022-04-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.19.488826", - "rel_abs": "Golden Syrian hamsters (Mesocricetus auratus) are used as a research model for severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2). Millions of Golden Syrian hamsters are also kept as pets in close contact to humans. To determine the minimum infective dose (MID) for assessing the zoonotic transmission risk, and to define the optimal infection dose for experimental studies, we orotracheally inoculated hamsters with SARS-CoV-2 doses from 1*105 to 1*10-4 tissue culture infectious dose 50 (TCID50). Body weight and virus shedding were monitored daily. 1*10-3 TCID50 was defined as the MID, and this was still sufficient to induce virus shedding at levels up to 102.75 TCID50/ml, equaling the estimated MID for humans. Virological and histological data revealed 1*102 TCID50 as the optimal dose for experimental infections. This compellingly high susceptibility resulting in productive infections in Golden Syrian hamsters needs to be considered also as a source of SARS-CoV-2 infections in humans.", - "rel_num_authors": 12, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.20.488895", + "rel_abs": "Two mutations occurred in SARS-CoV-2 early during the COVID-19 pandemic that have come to define circulating virus lineages1: first a change in the spike protein (D614G) that defines the B.1 lineage and second, a double substitution in the nucleocapsid protein (R203K, G204R) that defines the B.1.1 lineage, which has subsequently given rise to three Variants of Concern: Alpha, Gamma and Omicron. While the latter mutations appear unremarkable at the protein level, there are dramatic implications at the nucleotide level: the GGG[->]AAC substitution generates a new Transcription Regulatory Sequence (TRS) motif, driving SARS-CoV-2 to express a novel subgenomic mRNA (sgmRNA) encoding a truncated C-terminal portion of nucleocapsid (N.iORF3), which is an inhibitor of type I interferon production. We find that N.iORF3 also emerged independently within the Iota variant, and further show that additional TRS motifs have convergently evolved to express novel sgmRNAs; notably upstream of Spike within the nsp16 coding region of ORF1b, which is expressed during human infection. Our findings demonstrate that SARS-CoV-2 is undergoing evolutionary changes at the functional RNA level in addition to the amino acid level, reminiscent of eukaryotic evolution. Greater attention to this aspect in the assessment of emerging strains of SARS-CoV-2 is warranted.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Claudia Blaurock", - "author_inst": "Friedrich-Loeffler-Institut, Institute of Novel and Emerging Infectious Diseases" + "author_name": "Harriet V Mears", + "author_inst": "RNA Virus Replication Laboratory, The Francis Crick Institute, London, UK" }, { - "author_name": "Angele Breithaupt", - "author_inst": "Friedrich-Loeffler-Institut, Department of Experimental Animal Facilities and Biorisk Management" + "author_name": "George R Young", + "author_inst": "RNA Virus Replication Laboratory & Bioinformatics and Biostatistics STP, The Francis Crick Institute, London, UK" }, { - "author_name": "Saskia Weber", - "author_inst": "Friedrich-Loeffler-Institut, Institute of Novel and Emerging Infectious Diseases" + "author_name": "Theo Sanderson", + "author_inst": "Malaria Biochemistry Laboratory, The Francis Crick Institute, London, UK" }, { - "author_name": "Claudia Wylezich", - "author_inst": "Friedrich-Loeffler-Institut, Institute of Diagnostic Virology" + "author_name": "Ruth Harvey", + "author_inst": "Worldwide Influenza Centre, The Francis Crick Institute, London, UK" }, { - "author_name": "Markus Keller", - "author_inst": "Friedrich-Loeffler-Institut, Institute of Novel and Emerging Infectious Diseases" + "author_name": "Margaret Crawford", + "author_inst": "Advanced Sequencing Facility, The Francis Crick Institute, London, UK" }, { - "author_name": "Bjoern-Patrick Mohl", - "author_inst": "Friedrich-Loeffler-Institut, Institute of Novel and Emerging Infectious Diseases" + "author_name": "Daniel M Snell", + "author_inst": "Advanced Sequencing Facility, The Francis Crick Institute, London, UK" }, { - "author_name": "Dirk Goerlich", - "author_inst": "Max Planck Institute for Multidisciplinary Sciences" + "author_name": "Ashley S Fowler", + "author_inst": "Advanced Sequencing Facility, The Francis Crick Institute, London, UK" }, { - "author_name": "Martin H. Groschup", - "author_inst": "Friedrich-Loeffler-Institut, Institute of Novel and Emerging Infectious Diseases" + "author_name": "Saira Hussain", + "author_inst": "RNA Virus Replication Laboratory, The Francis Crick Institute, London, UK" }, { - "author_name": "Balal Sadeghi", - "author_inst": "Friedrich-Loeffler-Institut, Institute of Novel and Emerging Infectious Diseases" + "author_name": "Jerome Nicod", + "author_inst": "Advanced Sequencing Facility, The Francis Crick Institute, London, UK" }, { - "author_name": "Dirk Hoeper", - "author_inst": "Friedrich-Loeffler-Institut, Institute of Diagnostic Virology" + "author_name": "Edward Emmott", + "author_inst": "Centre for Proteome Research, Department of Biochemistry & Systems Biology, Institute of Systems Molecular & Integrative Biology, University of Liverpool, Liver" }, { - "author_name": "Thomas C. Mettenleiter", - "author_inst": "Friedrich-Loeffler-Institut" + "author_name": "Katja Finsterbusch", + "author_inst": "Immunoregulation Laboratory, The Francis Crick Institute, London, UK" }, { - "author_name": "Anne Balkema-Buschmann", - "author_inst": "Friedrich-Loeffler-Institut, Institute of Novel and Emerging Infectious Diseases" + "author_name": "Jakub Luptak", + "author_inst": "MRC Laboratory of Molecular Biology, Cambridge, UK" + }, + { + "author_name": "Emma Wall", + "author_inst": "Crick/UCLH Legacy Study, The Francis Crick Institute, London, UK; and National Institute for Health Research (NIHR) University College London Hospitals (UCLH) B" + }, + { + "author_name": "Bryan Williams", + "author_inst": "University College London; and National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK" + }, + { + "author_name": "Sonia Gandhi", + "author_inst": "Neurodegeneration Biology Laboratory, The Francis Crick Institute, London, UK" + }, + { + "author_name": "Charles Swanton", + "author_inst": "Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK" + }, + { + "author_name": "David LV Bauer", + "author_inst": "RNA Virus Replication Laboratory, The Francis Crick Institute, London, UK" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "new results", "category": "microbiology" }, @@ -299213,27 +298871,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.04.19.488803", - "rel_title": "Nonstructural protein 1 (nsp1) widespread RNA decay phenotype varies among Coronaviruses", + "rel_doi": "10.1101/2022.04.16.22273937", + "rel_title": "Global reports of takotsubo (stress) cardiomyopathy following COVID-19 vaccination: First systematic review and meta-analysis", "rel_date": "2022-04-19", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.19.488803", - "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWExtensive remodeling of the host gene expression environment by coronaviruses nsp1 proteins is a well-documented and conserved piece of the coronavirus-host takeover battle. However, whether and how the underlying mechanism of regulation or the transcriptional target landscape differ amongst coronaviruses remains mostly uncharacterized. In this study we use comparative transcriptomics to investigate the diversity of transcriptional targets between four different coronavirus nsp1 proteins (from MERS, SARS1, SARS2 and 229E). In parallel, we performed Affinity Purification followed by Mass-Spectrometry to identify common and divergent interactors between these different nsp1. For all four nsp1 tested, we detected widespread RNA destabilization, confirming that both - and {beta}-Coronavirus nsp1 broadly affect the host transcriptome. Surprisingly, we observed that even closely related nsp1 showed little similarities in the clustering of genes targeted. Additionally, we show that the RNA targeted by nsp1 from the -CoV 229E partially overlapped with MERS nsp1 targets. Given MERS nsp1 preferential targeting of nuclear transcripts, these results may indicate that these nsp1 proteins share a similar targeting mechanism. Finally, we show that the interactome of these nsp1 proteins differ widely. Intriguingly, our data indicate that the 229E nsp1, which is the smallest of the nsp1 proteins tested here, interacts with the most host proteins, while MERS nsp1 only engaged with a few host proteins. Collectively, our work highlights that while nsp1 is a rather well-conserved protein with conserved functions across different coronaviruses, its precise effects on the host cell is virus specific.\n\nSO_SCPLOWIGNIFICANCEC_SCPLOWCoronaviruses extensively co-opt their host gene expression machinery in order to quicky benefit from the host resources. The viral protein nsp1 plays a major role in this takeover as nsp1 is known to induce a widespread shutdown of the host gene expression, both at the RNA and the translational level. Previous work characterized the molecular basis for nsp1-mediated host shutdown. However, this was mostly conducted in the context of {beta}-coronaviruses and in particular SARS-CoV1, CoV2 and MERS due to the important public health burden that these viruses represent. Here instead, we explored the impact of nsp1 on the host using a comparative approach, defining the influence of 4 nsp1 protein from - and {beta}-coronaviruses. We delineated the impact of these 4 nsp1 on the host transcriptome and mapped their interactome. We revealed that host target range and interactomes vary widely among different nsp1, suggesting a viral-specific targeting. Understanding how these differences shape infection will be important to better inform antiviral drug development.", - "rel_num_authors": 2, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.16.22273937", + "rel_abs": "Concerns have been raised recently about takotsubo cardiomyopathy (TCM) after receiving COVID-19 vaccines, particularly the messenger RNA (mRNA) vaccines. The goal of this study was to compile case reports to provide a comprehensive overview of takotsubo cardiomyopathy (TCM) associated with COVID-19 vaccines. A systematic literature search was conducted in PubMed, Scopus, Embase, Web of Science, and Google Scholar between 2020 and June 1, 2022. The study included individuals who developed cardiac takotsubo cardiomyopathy from receiving COVID-19 vaccinations. Ten studies, including 10 cases, participated in the current systematic review. The mean age was 61.8 years; 90% were female, while 10% were male. 80% of the patients received the mRNA COVID-19 vaccine, while 20% received other types. In addition, takotsubo cardiomyopathy (TCM) occurred in 50% of patients receiving the first dose and another 40% after the second dose of COVID-19 vaccines. Moreover, the mean number of days to the onset of symptoms was 2.62 days. All cases had an elevated troponin test and abnormal ECG findings. The left ventricular ejection fraction (LVEF) was lower than 50% in 90% of patients. In terms of the average length of hospital stay, 50% stayed for 10.2 days, and all cases recovered from their symptoms. In conclusion, takotsubo (stress) cardiomyopathy (TCM) complications associated with COVID-19 vaccination are rare but can be life-threatening. Chest pain should be considered an alarming symptom, especially in those who have received the first and second doses of the COVID-19 vaccine.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Jacob Miles", - "author_inst": "University of Massachusetts, Amherst" + "author_name": "Sirwan Khalid Ahmed", + "author_inst": "Department of Emergency, Rania Pediatric & Maternity Teaching Hospital, Rania, Sulaimani, Kurdistan-region, Iraq" }, { - "author_name": "Mandy Muller", - "author_inst": "University of Massachusetts, Amherst" + "author_name": "Mona Gamal Mohamed", + "author_inst": "Department of Adult Nursing, RAK Medical and Health Sciences University, Ras Al Khaimah, UAE" + }, + { + "author_name": "Rawand Abdulrahman Essa", + "author_inst": "Department of Emergency, Rania Pediatric & Maternity Teaching Hospital, Rania, Sulaimani, Kurdistan-region, Iraq" + }, + { + "author_name": "Eman Abdelazizi Ahmed Rashad Dabou", + "author_inst": "Department of Adult Nursing, RAK Medical and Health Sciences University, Ras Al Khaimah, UAE" + }, + { + "author_name": "Salar Omar Abdulqadir", + "author_inst": "Department of Nursing, University of Raparin, Ranya, Sulaimani, Kurdistan-region, Iraq" + }, + { + "author_name": "Rukhsar Muhammad Omar", + "author_inst": "Department of Nursing, University of Raparin, Ranya, Sulaimani, Kurdistan-region, Iraq" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "microbiology" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2022.04.14.22273868", @@ -300875,63 +300549,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.04.13.22273829", - "rel_title": "Previous SARS-CoV-2 infection or a third dose of vaccine elicited cross-variant neutralizing antibodies in vaccinated solid organ transplant recipients", + "rel_doi": "10.1101/2022.04.15.22273907", + "rel_title": "Multi-faceted analysis of COVID-19 epidemic in the Republic of Korea considering Omicron variant: Mathematical modeling-based study", "rel_date": "2022-04-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.13.22273829", - "rel_abs": "The SARS-CoV-2 pandemic poses a great threat to global health, particularly in solid organ transplant recipients (SOTRs). Although a 3-dose mRNA vaccination protocol has been implemented for the majority of SOTRs, its effectiveness was still largely unknown. We analyzed 113 vaccinated SOTRs, and 30 healthy controls (HCs), some of whom had recovered from COVID, for their immune responses against the original vaccine strain and variants of concern (VOC), including the highly mutated-omicron variant. Here, we report that 3 doses of the mRNA vaccine had only a modest effect in eliciting anti-viral responses against all viral strains in the fully vaccinated SOTRs who did not contract the virus. Only 34.0% (16/47) of this group of patients demonstrated both detectable anti-RBD IgG and neutralization activities against alpha, beta, and delta variants, and only 8.5% (4/47) of them showed additional omicron-neutralizing capacities. In contrast, 79.5% (35/44) of the vaccinated recovered-SOTRs demonstrated both higher anti-RBD IgG levels and neutralizing activities against all VOC, including omicron. These findings illustrate a significant impact of previous infection on the development of anti-COVID immune responses in vaccinated SOTRs and highlight the need for alternative strategies to protect a subset of a lesser-vaccine responsive population.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.15.22273907", + "rel_abs": "BackgroundThe most recent variant of concern, Omicron (B.1.1.529), has caused numerous cases worldwide including the Republic of Korea due to its fast transmission and reduced vaccine effectiveness.\n\nMethodsA mathematical model considering age-structure, vaccine, antiviral treatment, and influx of the Omicron variant was developed. We estimated transmission rates among age groups using maximum likelihood estimation for the age-structured model. The impact of nonpharmaceutical interventions (in community and border), quantified by a parameter in the force of infection, and vaccination were examined through a multi-faceted analysis. A theory-based endemic equilibrium study was performed to find the manageable number of cases according to Omicron-and healthcare-related factors.\n\nResultsBy fitting the model to the available data, the estimated values of ranged from 0.31 to 0.73, representing the intensity of nonpharmaceutical interventions such as social distancing level. If < 0.55 and 300,000 booster shots were administered daily from February 3, 2022, the number of severe cases was forecasted to exceed the severe bed capacity. Moreover, the number of daily cases is reduced as the timing of screening measures is delayed. If screening measure was intensified as early as November 24, 2021 and the number of overseas entrant cases was contained to 1 case per 10 days, simulations showed that the daily incidence by February 3, 2022 could have been reduced by 87%. Furthermore, we found that the incidence number in mid-December 2021 exceeded the theory-driven manageable number of daily cases.\n\nConclusionNonpharmaceutical interventions, vaccination, and antiviral therapy influence the spread of Omicron and number of severe cases in the Republic of Korea. Intensive and early screening measures during the emergence of a new variant is key in controlling the epidemic size. Using the endemic equilibrium of the model, a formula for the manageable daily cases depending on the severity rate and average length of hospital stay was derived so that the number of severe cases does not surpass the severe bed capacity.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Chih-Chao Chang", - "author_inst": "Columbia University" - }, - { - "author_name": "George Vlad", - "author_inst": "Columbia University" - }, - { - "author_name": "Elena Rodica Vasilescu", - "author_inst": "Columbia University" - }, - { - "author_name": "Ping Li", - "author_inst": "Columbia University" + "author_name": "Youngsuk Ko", + "author_inst": "Department of Mathematics, Konkuk University, Seoul, Korea" }, { - "author_name": "Syed A Husain", - "author_inst": "Columbia Unversity" + "author_name": "Victoria May Mendoza", + "author_inst": "Department of Mathematics, Konkuk University, Seoul, Korea" }, { - "author_name": "Elaine A Silvia", - "author_inst": "Colulmbia University" + "author_name": "Renier Mendoza", + "author_inst": "Department of Mathematics, Konkuk University, Seoul, Korea" }, { - "author_name": "David J Cohen", - "author_inst": "Columbia University" + "author_name": "Yu Bin Seo", + "author_inst": "Division of Infectious Disease, Department of Internal Medicine, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea" }, { - "author_name": "Lloyd E Ratner", - "author_inst": "Columbia University" + "author_name": "Jacob Lee", + "author_inst": "Division of Infectious Disease, Department of Internal Medicine, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea" }, { - "author_name": "Wei-Zen Sun", - "author_inst": "National Taiwan University" + "author_name": "Jonggul Lee", + "author_inst": "Division of Public Health Emergency Response Research, Korea Disease Control and Prevention Agency, Cheongju, Korea" }, { - "author_name": "Sumit Mohan", - "author_inst": "Columbia University" + "author_name": "Donghyok Kwon", + "author_inst": "Division of Public Health Emergency Response Research, Korea Disease Control and Prevention Agency, Cheongju, Korea" }, { - "author_name": "Nicole Suciu-Foca", - "author_inst": "Columbia University" + "author_name": "Eunok Jung", + "author_inst": "Department of Mathematics, Konkuk University, Seoul, Korea" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.04.18.22273970", @@ -302577,27 +302239,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.04.14.22273886", - "rel_title": "To mask, or not to mask, Alice and Bob's dating dilemma", + "rel_doi": "10.1101/2022.04.11.22273599", + "rel_title": "The dynamic reproduction index: accurate determination from incidence and application for an early warning system", "rel_date": "2022-04-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.14.22273886", - "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWFace masking in current COVID-19 pandemic seems to be a deceivingly simple decision-making problem due to its multifaceted nature. Questions arising from masking span biomedicine, epidemiology, physics, and human behaviors. While science has shown masks work generally, human behaviors (particularly under influences of politics) complicate the problem significantly given science generally assumes rationality and our minds are not always rational and/or honest. Minding minds, a legitimate concern, can also make masking legitimately confusing. To disentangle the potential confusions, particularly, the ramifications of irrationality and dishonesty, here we resort to evolutionary game theory. Specifically, we formulate and analyze the masking problem with a fictitious pair of young lovers, Alice and Bob, as a Sir Philip Sydney (SPS) evolutionary game, inspired by the handicap principle in evolutionary biology and cryptography figures in computer science. With the proposed ABD (Alice and Bobs dating dilemma) as an asymmetric four-by-four strategic-form game, 16 strategic interactions were identified, and six of which may reach equilibriums with different characteristics such as separating, pooling, and polymorphic hybrid, being Nash, evolutionarily stable or neutrally stable. The six equilibrium types seem to mirror the diverse behaviors of mask believers, skeptics, converted, universal masking, voluntarily masking, coexisted and/or divided world of believers and skeptics. We suggest that the apparently simple ABD game is sufficiently general not only for studying masking policies for populations (via replicator dynamics), but also for investigating other complex decision-making problems with COVID-19 pandemic including lockdown vs. reopening, herd immunity vs. quarantines, and aggressive tracing vs. privacy protection.", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.11.22273599", + "rel_abs": "Two methods of calculating the reproduction index from daily new infection data are considered, one by using the generation time tG as a shift (RG), and an incidence-based method directly derived from the differential equation system of an SIR epidemic dynamics model (RI). While the former is shown to have few in common with the true reproduction index, we find that the latter provides a sensitive detection device for intervention effects and other events affecting the epidemic, making it well-suited for diagnostic purposes in policy making. Furthermore, we introduce a similar quantity, [Formula], which can be calculated directly from RG. It shows largely the same behaviour as RI, with less fine structure. However, it is accurate in particular in the vicinity of R = 1, where accuracy is important for the corrrect prediction of epidemic dynamics. We introduce an entirely new, self-consistent method to derive, from both quantities, an improved [Formula] which is both accurate and contains the details of the epidemic spreading dynamics. Hence we obtain R accurately from data on daily new infections (incidence) alone. Moreover, by using RI instead of RG in plots of R versus incidence, orbital trajectories of epidemic waves become visible in a particularly insightful way, demonstrating that the widespread use of only incidence as a diagniostic tool is clearly inappropriate.\n\nPACS numbers:", "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Zhanshan (Sam) Ma", - "author_inst": "Chinese Academy of Sciences" + "author_name": "Robert N.J. Conradt", + "author_inst": "CONRADT Mess- und Regeltechnik" }, { - "author_name": "Ya-Ping Zhang", - "author_inst": "Chinese Academy of Sciences" + "author_name": "Stephan Herminghaus", + "author_inst": "Max Planck Institute for Dynamics and Self-Organization (MPI-DS), Goettingen, Germany" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.04.11.22273702", @@ -304215,35 +303877,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.04.13.22273821", - "rel_title": "Slight increase in fomite route transmission risk of SARS-CoV-2 Omicron variant compared with the ancestral strain in households", + "rel_doi": "10.1101/2022.04.12.22273792", + "rel_title": "Health behaviours the month prior to COVID-19 infection and the development of self-reported long COVID and specific long COVID symptoms: A longitudinal analysis of 1,811 UK adults", "rel_date": "2022-04-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.13.22273821", - "rel_abs": "The Omicron SARS-CoV-2 variant has become the dominant lineage worldwide, and experimental study had shown that SARS-CoV-2 Omicron variant was more stable on various environmental surfaces than ancestral strain. However, how the changes of stability on surfaces would influence the role of fomite route in SARS-CoV-2 transmission is still unknown. In this study, we modeled the Omicron and ancestral strain SARS-CoV-2 transmission within a household over 1-day period from multiple pathways, i.e., airborne, droplet and contact route. We assumed there were 2 adults and 1 child in the household, and one of the adults was infected with SARS-CoV-2. We assume a scenario of pre-/asymptomatic infection, i.e., SARS-CoV-2 was emitted by breathing and talking, and symptomatic infection, i.e., SARS-CoV-2 was emitted by breathing, talking, and coughing. In pre-/asymptomatic infection, all three routes contributed a role, contact route contribute most (37%-45%), followed by airborne route (34%-38%) and droplet route (21%-28%). In symptomatic infection, droplet route was the dominant pathway (48%-71%), followed by contact route (25%-42%), airborne route played a negligible role (<10%). In the contact route, indirect contact (fomite) route dominated (contributed more than 97%). Compared with ancestral strain, though the contribution of contact route increased in Omicron variant transmission, the increase was slight, from 25%-41% to 30%-45%.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.12.22273792", + "rel_abs": "BackgroundDemographic and infection-related characteristics have been identified as risk factors for long COVID, but research on the influence of health behaviours (e.g., exercise, smoking) immediately preceding the index infection is lacking.\n\nMethods1,811 UK adults from the UCL COVID-19 Social Study and who had previously been infected with COVID-19 were analysed. Health behaviours in the month before infection were weekly exercise frequency, days of fresh air per week, sleep quality, smoking, consuming more than the number of recommended alcoholic drinks per week (>14), and the number of mental health care behaviours (e.g., online mental health programme). Logistic regressions controlling for covariates (e.g., COVID-19 infection severity and pre-existing health conditions) examined the impact of health behaviours on long COVID and three long COVID symptoms (difficulty with mobility, cognition, and self-care).\n\nResultsIn the month before infection with COVID-19, poor quality sleep increased the odds of long COVID (odds ratio [OR]: 3.53; (95% confidence interval [CI]: 2.01 to 6.21), as did average quality sleep (OR: 2.44; 95% CI: 1.44 to 4.12). Having smoked (OR: 8.39; 95% CI: 1.86 to 37.91) increased and meeting recommended weekly physical activity guidelines (3+ hours) (OR: 0.05; 95% CI: 0.01 to 0.39) reduced the likelihood of difficulty with self-care (e.g., washing all over or dressing) amongst those with long COVID.\n\nConclusionResults point to the importance of sleep quality for long COVID, potentially helping to explain previously demonstrated links between stress and long COVID. Results also suggest that exercise and smoking may be modifiable risk factors for preventing the development of difficulty with self-care.\n\nFundingThe Nuffield Foundation [WEL/FR-000022583], the MARCH Mental Health Network funded by the Cross-Disciplinary Mental Health Network Plus initiative supported by UK Research and Innovation [ES/S002588/1], and the Wellcome Trust [221400/Z/20/Z and 205407/Z/16/Z].\n\nWhat is already known on the topicLong COVID is rapidly becoming a public health concern. Although existing evidence to date has identified health characteristics such as obesity as risk factors, hardly any research on modifiable risk factors such as health behaviours has been conducted.\n\nWhat this study addsThis study adds to the dearth of evidence on modifiable risk factors occurring before COVID-19 infection. Findings suggest a role of poor sleep quality for the development of long COVID, and for meeting physical activity guidelines (3+ hours per week) and not smoking as modifiable risk factors for self-care difficulties amongst those with long COVID.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Shuyi Ji", - "author_inst": "School of Public Health, Zhejiang University, Hangzhou, P.R. China" - }, - { - "author_name": "Shenglan Xiao", - "author_inst": "School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, P.R. China" - }, - { - "author_name": "Huaibin Wang", - "author_inst": "School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, P.R. China" + "author_name": "Elise Paul", + "author_inst": "University College London" }, { - "author_name": "Hao Lei", - "author_inst": "School of Public Health, Zhejiang University, Hangzhou, P.R. China" + "author_name": "Daisy Fancourt", + "author_inst": "University College London" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.04.12.22273804", @@ -305930,18 +305584,103 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.04.12.22273722", - "rel_title": "Measures for infection prevention and control of SARS-CoV-2 in Belgian schools between December 2020 and June 2021: a prospective cohort study", + "rel_doi": "10.1101/2022.04.11.22272784", + "rel_title": "Evolution of a globally unique SARS-CoV-2 Spike E484T monoclonal antibody escape mutation in a persistently infected, immunocompromised individual.", "rel_date": "2022-04-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.12.22273722", - "rel_abs": "IntroductionAs the role of school-aged children was unclear at the onset of the COVID-19 pandemic, public health authorities recommended to implement infection prevention and control (IPC) measures in school settings. Few studies evaluated the implementation of these measures and their effect on SARS-CoV-2 infection rates among pupils and staff.\n\nAimTo describe the implementation of IPC measures in Belgian primary and secondary schools and assess its relation to the prevalence of anti-SARS-CoV-2 antibodies among pupils and staff.\n\nMethodsWe conducted a prospective cohort study in a representative sample of primary and secondary schools in Belgium. Implementation of IPC measures in schools was assessed using an online questionnaire. Saliva samples were collected from pupils and staff to determine the SARS-CoV-2 seroprevalence.\n\nResultsA variety of IPC measures (ventilation, hygiene and physical distancing) was implemented by more than 60% of primary and secondary schools with most attention for hygiene measures. Almost no differences in implementation coverage were observed between primary and secondary schools or the Dutch and French language network. Poor implementation of IPC measures was associated with an increased anti-SARS-CoV-2 antibody prevalence among pupils from 8.6% (95% CI: 4.5 - 16.6) to 16.7% (95% CI: 10.2 - 27.4) and staff from 11.5% (95% CI: 8.1 - 16.4) to 17.6% (95% CI: 11.5 - 27.0). This association was statistically significant for all IPC measures and pupils and staff combined.\n\nConclusionBelgian schools were relatively compliant with recommended IPC measures at the school level. Poor implementation of IPC measures was associated with higher SARS-CoV-2 seroprevalence among pupils and staff.\n\nTrial registration numberTrial registration number: NCT04613817", - "rel_num_authors": 0, - "rel_authors": null, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.11.22272784", + "rel_abs": "Prolonged infections in immunocompromised individuals may be a source for novel SARS-CoV-2 variants, particularly when both the immune system and antiviral therapy fail to clear the infection, thereby promoting adaptation. Here we describe an approximately 16-month case of SARS-CoV-2 infection in an immunocompromised individual. Following monotherapy with the monoclonal antibody Bamlanivimab, the individuals virus was resistant to this antibody via a globally unique Spike amino acid variant (E484T) that evolved from E484A earlier in infection. With the emergence and spread of the Omicron Variant of Concern, which also contains Spike E484A, E484T may arise again as an antibody-resistant derivative of E484A.", + "rel_num_authors": 21, + "rel_authors": [ + { + "author_name": "Peter Halfmann", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Nicholas R. Minor", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Luis A. Haddock III", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Robert Maddox", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Gage K. Moreno", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Katarina Braun", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "David Baker", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Kasen Riemersma", + "author_inst": "University of Wisconsin, Madison" + }, + { + "author_name": "Ankur Prasad", + "author_inst": "University of Wisconsin Hospitals and Clinics" + }, + { + "author_name": "Kirsten J. Alman", + "author_inst": "University of Wisconsin Hospitals and Clinics" + }, + { + "author_name": "Matthew C. Lambert", + "author_inst": "University of Wisconsin Hospitals and Clinics" + }, + { + "author_name": "Kelsey Florek", + "author_inst": "Wisconsin State Laboratory of Hygiene" + }, + { + "author_name": "Allen Bateman", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Ryan Westergaard", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Nasia Safdar", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "David R. Andes", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Yoshihiro Kawaoka", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Madiha Fida", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "Joseph D. Yao", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "Thomas Friedrich", + "author_inst": "University of Wisconsin Madison" + }, + { + "author_name": "David H. O'Connor", + "author_inst": "University of Wisconsin-Madison" + } + ], "version": "1", - "license": "", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.04.07.22273561", @@ -307423,67 +307162,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.04.07.487347", - "rel_title": "Plant-produced RBD and cocktail-based vaccine candidates are highly effective against SARS-CoV-2, independently of its emerging variants", + "rel_doi": "10.1101/2022.04.07.487415", + "rel_title": "The Delta variant SARS-CoV-2 spike protein uniquely promotes aggregation of pseudotyped viral particles", "rel_date": "2022-04-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.07.487347", - "rel_abs": "SARS-CoV-2 is a novel and highly pathogenic coronavirus, which has caused an outbreak in Wuhan City, China, in 2019 and then spread rapidly throughout the world. Although several COVID-19 vaccines are currently available for mass immunization, they are less effective against emerging SARS-CoV-2 variants, especially the Omicron (B.1.1.529). Recently, we successfully produced receptor-binding domain (RBD) variants of spike (S) protein of SARC-CoV-2 and an antigen cocktail in Nicotiana benthamiana, which are highly produced in plants and elicited high-titer antibodies with potent neutralizing activity against SARS-CoV-2. In this study, we demonstrate that these protein-based vaccine candidates are highly effective against Delta and Omicron variants. These data support that plant produced RBD and cocktail-based antigens are most promising vaccine candidates and may protect against Delta and Omicron-mediated COVID-19. Based on the neutralization ability, plant produced RBD and cocktail-based vaccine candidates are highly effective against SARS-CoV-2, independently of its emerging variants.", - "rel_num_authors": 12, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.07.487415", + "rel_abs": "Individuals infected with the SARS-CoV-2 Delta variant, lineage B.1.617.2, exhibit faster initial infection with a higher viral load than prior variants, and pseudotyped particles bearing the SARS-CoV-2 Delta variant spike protein induce a faster initial infection rate of target cells compared to those bearing other SARS-CoV-2 variant spikes. Here, we show that pseudotyped particles bearing the Delta variant spike form unique aggregates, as evidenced by negative stain and cryogenic electron microscopy (EM), flow cytometry, and nanoparticle tracking analysis. Viral particles pseudotyped with other SARS-CoV-2 spike variants do not show aggregation by any of these criteria. The contribution to infection kinetics of the Delta spikes unique property to aggregate is discussed with respect to recent evidence for collective infection by other viruses. Irrespective of this intriguing possibility, spike-dependent aggregation is a new functional parameter of spike-expressing viral particles to evaluate in future spike protein variants.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Tarlan Mammedov", - "author_inst": "Akdeniz University" - }, - { - "author_name": "Damla Yuksel", - "author_inst": "Akdeniz University" - }, - { - "author_name": "Irem Grbzaslan", - "author_inst": "Akdeniz University" - }, - { - "author_name": "Merve Ilgn", - "author_inst": "Akdeniz University" - }, - { - "author_name": "Burcu Gulec", - "author_inst": "Akdeniz University" - }, - { - "author_name": "Gulshan Mammadova", - "author_inst": "Akdeniz University" + "author_name": "Jennifer D Petersen", + "author_inst": "Section on Integrative Biophysics, Division of Basic and Translational Biophysics, Eunice Kennedy Shriver National Institute of Child Health and Human Developme" }, { - "author_name": "Aykut Ozdarendeli", - "author_inst": "Erciyes University" + "author_name": "Jianming Lu", + "author_inst": "Codex BioSolutions, Inc., 12358 Parklawn Dr., Suite 250, North Bethesda, MD" }, { - "author_name": "Shaikh Terkis Islam Pavel", - "author_inst": "Erciyes University" + "author_name": "Wendy Fitzgerald", + "author_inst": "Section on Intercellular Interactions, Division of Basic and Translational Biophysics, Eunice Kennedy Shriver National Institute of Child Health and Human Devel" }, { - "author_name": "Hazel Yetiskin", - "author_inst": "Erciyes University" + "author_name": "Fei Zhou", + "author_inst": "Unit on Structural Biology, Division of Basic and Translational Biophysics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Nat" }, { - "author_name": "Busra Kaplan", - "author_inst": "Erciyes University" + "author_name": "Paul S Blank", + "author_inst": "Section on Integrative Biophysics, Division of Basic and Translational Biophysics, Eunice Kennedy Shriver National Institute of Child Health and Human Developme" }, { - "author_name": "Muhammet Ali Uygut", - "author_inst": "Erciyes University" + "author_name": "Doreen Matthies", + "author_inst": "Unit on Structural Biology, Division of Basic and Translational Biophysics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Nat" }, { - "author_name": "Gulnara Hasanova", - "author_inst": "Akdeniz University" + "author_name": "Joshua Zimmerberg", + "author_inst": "Section on Integrative Biophysics, Division of Basic and Translational Biophysics, Eunice Kennedy Shriver National Institute of Child Health and Human Developme" } ], "version": "1", - "license": "cc_no", + "license": "cc0", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.04.07.487520", @@ -309417,89 +309136,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.04.04.22273320", - "rel_title": "Monitoring of SARS-CoV-2 variant dynamics in wastewater by digital RT-PCR : from Alpha to Omicron BA.2 VOC", + "rel_doi": "10.1101/2022.04.05.22273434", + "rel_title": "Analysis of immunization, adverse events, and efficacy of a fourth dose of BNT162b2 vaccine", "rel_date": "2022-04-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.04.22273320", - "rel_abs": "Throughout the COVID-19 pandemic, new variants have continuously emerged and spread in populations. Among these, variants of concern (VOC) have been the main culprits of successive epidemic waves, due to their transmissibility, pathogenicity or ability to escape the immune response. Quantification of the SARS-CoV-2 genomes in raw wastewater is a reliable approach well-described and widely deployed worldwide to monitor the spread of SARS-CoV-2 in human populations connected to sewage systems. Discrimination of VOCs in wastewater is also a major issue and can be achieved by genome sequencing or by detection of specific mutations suggesting the presence of VOCs. This study aimed to date the emergence of these VOCs (from Alpha to Omicron BA.2) by monitoring wastewater from the greater Paris area, France, but also to model the propagation dynamics of these VOCs and to characterize the replacement kinetics of the majority populations. These dynamics were compared to various individual-centered public health data, such as regional incidence and proportions of VOCs identified by sequencing of isolated patient strains. The viral dynamics in wastewater highlighted the impact of the vaccination strategy on the viral circulation in human populations but also suggested its potential effect on the selection of variants most likely to be propagated in immunized populations. Normalization of concentrations to capture population movements appeared statistically more reliable using variations in local drinking water consumption rather than using PMMoV concentrations because PMMoV fecal shedding was subject to variability and was not sufficiently relevant in this study. The dynamics of viral spread was observed earlier (about 13 days on the wave related to Omicron VOC) in raw wastewater than the regional incidence alerting to a possible risk of decorrelation between incidence and actual virus circulation probably resulting from a lower severity of infection in vaccinated populations.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.05.22273434", + "rel_abs": "ImportanceScarce information exists concerning the seroconversion and adverse events after immunization (AEFI) of the fourth dose of a SARS-COV-2 vaccine.\n\nObjectiveCorrelate the magnitude of the antibody response to vaccination with previous clinical conditions and AEFI of the fourth dose of BNT162b2 mRNA.\n\nDesignObservational study where SARS-CoV-2 spike 1-2 IgG antibodies IgG titers were measured 21-28 days after the exposition of the first, and second dose, three months after the second dose, 1-7 days after the third dose, before the fourth dose, and 21-28 days after the fourth dose of BNT162b2 mRNA.\n\nSettingThe study was conducted on healthcare workers of a private hospital in Northern Mexico.\n\nParticipantsInclusion criteria were healthcare workers of both genders, any age, who planned to conclude the immunization regimen. The exclusion criteria were previously given any SARS-CoV-2 vaccine prior to study entry.\n\nInterventionSubjects were exposed to four doses of the BNT162b2 mRNA vaccine.\n\nMain Outcome and Measures:\n\nThe anti-S1 and anti-S2 IgG antibodies against SARS-CoV-2 in plasma samples were measured with chemiluminescence immunoassay developed by DiaSorin.\n\nResultsWe recruited 112 subjects [43 (SD 9) years old, 74% women].\n\nAfter the first dose, subjects had a median (IQR) AU/ml IgG of 122(1904), with an increase to 1875 (2095) after the second dose, 3020 (2330) after the third dose, and 4230 (3393) after 21-28 of a fourth dose (p<0.01). The number (%) of any AEFI between doses was 90 (80.4), 89(79), 65(58), 69 (61.5), after first, second, third, and fourth, respectively, p<0.001. After the fourth dose, the most frequent AEFI was pain at the injection site (87%). Fever was slightly more frequent after the third and fourth doses, 9 (13.8) and 8 (11.4%) cases, respectively, and adenopathy was more frequent after the fourth dose [in11(15.7%) cases]. There was a correlation between AEFI in the fourth dose with gender and antibody levels (p<0.05). The highest proportion of AEFI was considered mild after the fourth dose. During the Omicron outbreak, 6 (5.3%) had mild SARS-CoV-2 during 8-28 days of the fourth dose.\n\nConclusions and RelevanceThe fourth dose of BNT162b2mRNA increases S1/S2 IgG 33.6 times with mild adverse events.\n\nRegistration numberNCT05228912\n\nKey pointsO_ST_ABSQuestionC_ST_ABSWhat is the magnitude of antibody response to vaccination and adverse events after immunization (AEFI) of a fourth dose of BNT162b2 mRNA?\n\nFindingsThis cohort included 112 healthcare workers. We measured S1/S2 IgG vs. SARS-CoV-2 after the first, second, third and fourth dose. Compared to the first dose, antibodies increased 33.6 times the antibody levels after the fourth dose. We found minimal to moderate adverse events. The change in antibodies correlated with AEFI. During the Omicron outbreak 6 (5.3%) had mild SARS-CoV-2.\n\nMeaningA fourth dose of BNT162b2mRNA increases S1/S2 IgG with mild to moderate adverse events.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Sebastien Wurtzer", - "author_inst": "Eau de Paris" - }, - { - "author_name": "Morgane Levert", - "author_inst": "Sorbonne universite" - }, - { - "author_name": "Eloise Dhenain", - "author_inst": "Sorbonne universite" - }, - { - "author_name": "Heberte Accrombessi", - "author_inst": "Eau de Paris" - }, - { - "author_name": "Sandra Manco", - "author_inst": "Eau de Paris" - }, - { - "author_name": "Nathalie Fagour", - "author_inst": "Eau de Paris" - }, - { - "author_name": "Marion Goulet", - "author_inst": "Eau de Paris" - }, - { - "author_name": "Nicolas Boudaud", - "author_inst": "Actalia" - }, - { - "author_name": "Lucie Gaillard", - "author_inst": "Actalia" - }, - { - "author_name": "Isabelle Bertrand", - "author_inst": "LCPME" - }, - { - "author_name": "Julie Challant", - "author_inst": "LCPME" + "author_name": "Maria Elena Romero-Ibarguengoitia", + "author_inst": "Hospital Clinica Nova" }, { - "author_name": "Sophie Masnada", - "author_inst": "SIAM" + "author_name": "Arnulfo Gonzalez-Cantu", + "author_inst": "Hospital Clinica Nova" }, { - "author_name": "Sam Azimi", - "author_inst": "SIAAP" + "author_name": "Diego Rivera-Salinas", + "author_inst": "Hospital Clinica Nova" }, { - "author_name": "Miguel Gillon-Ritz", - "author_inst": "Ville de Paris" + "author_name": "Yodira Guadalupe Hernandez-Ruiz", + "author_inst": "Hospital Clinica Nova" }, { - "author_name": "Alban Robin", - "author_inst": "Eau de Paris" + "author_name": "Ana Gabriela Armendariz-Vazquez", + "author_inst": "Hospital Clinica Nova" }, { - "author_name": "Jean-Marie Mouchel", - "author_inst": "Sorbonne universite" + "author_name": "Irene Antonieta Barco-Flores", + "author_inst": "Hospital Clinica Nova" }, { - "author_name": "- SIG OBEPINE", - "author_inst": "" + "author_name": "Rosalinda Gonzalez-Facio", + "author_inst": "Hospital Clinica Nova" }, { - "author_name": "Laurent Moulin", - "author_inst": "Eau de Paris" + "author_name": "Miguel Angel Sanz-Sanchez", + "author_inst": "Hospital Clinica Nova" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -311175,61 +310854,37 @@ "category": "cancer biology" }, { - "rel_doi": "10.1101/2022.04.04.22273356", - "rel_title": "EARLY OUTPATIENT TREATMENT OF COVID-19: A RETROSPECTIVE ANALYSIS OF 392 CASES IN ITALY", + "rel_doi": "10.1101/2022.03.31.22273181", + "rel_title": "Cannabis potential effects to prevent or attenuate SARS-COV2 contagion", "rel_date": "2022-04-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.04.22273356", - "rel_abs": "IntroductionThe pandemic of severe acute respiratory syndrome (SARS)-coronavirus-2 (CoV-2) disease 2019 (COVID-19) was declared in march 2020. Knowledge of COVID-19 pathophysiology soon provided a strong rationale for the early use of anti-inflammatory, antiplatelet and anticoagulant drugs, however the evidence was only slowly and partially incorporated into institutional guidelines. Unmet needs of COVID-19 outpatients were soon taken care of by networks of physicians and researchers, using pharmacotherapeutic approaches based on the best available experiences.\n\nMethodsObservational retrospective study investigating characteristics, management and outcomes in COVID-19 patients taken care of in Italy by physicians volunteering within the IppocrateOrg Association, one of the main international assistance networks, between 1st november 2020 and 31st march 2021.\n\nResultsTen doctors took part in the study and provided data about 392 consecutive COVID-19 patients. Patients mean age was 48,5 years (range: 0,5-97). They were 51,3% females and were taken care of when in COVID-19 stage 0 (15,6%), 1 (50,0%), 2a (28,8%), 2b (5,6%). Many patients were overweight (26%) or obese (11,5%), with chronic comorbidities (34,9%), mainly cardiovascular (23%) and metabolic (13,3%). Drugs most frequently prescribed included: vitamins and supplements (98,7%), aspirin (66,1%), antibiotics (62%), glucocorticoids (41,8%), hydroxychloroquine (29,6%), enoxaparin (28,6%), colchicine (8,9%), oxygen therapy (6,9%), ivermectin (2,8%). Hospitalization occurred in 5,8% of total cases, mainly in patients taken care of when in stage 2b (27,3%). Altogether, 390 patients (99,6%) recovered, one patient (0,2%) was lost at follow up, and one patient (0,2%) died after hospitalization. One doctor reported one grade 1 adverse drug reaction (ADR) (transient or mild discomfort), and 3 doctors reported in total 8 grade 2 ADR (mild to moderate limitation in activity).\n\nConclusionsThis is the first study describing attitudes and behaviors of physicians caring for COVID-19 outpatients, and the effectiveness and safety of COVID-19 early treatment in the real world. COVID-19 lethality in our cohort was 0,2%, while the overall COVID-19 lethality in Italy in the same period was between 3% and 3,8%. The use of individual drugs and drug combinations described in this study appears therefore effective and safe, as indicated by the few and mild ADR reported. Present evidence should be carefully considered by physicians caring for COVID-19 patients as well as by political decision makers managing the current global crisis.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.31.22273181", + "rel_abs": "Medical cannabis has gained an exponential interest in recent years. Therapeutic targets have been broadened from specific applications over pain control, chemotherapy side effects, treatment-resistant epilepsies and multiple sclerosis, among others. Several in vitro and animal studies, along with few human controlled studies, suggest cannabinoids have a potential therapeutic role over medical conditions comporting inflammatory mechanisms. Given the tremendous world-wide impact of the COVID-19 pandemic, research efforts are converging towards the use of cannabinoids to attenuate severe or fatal forms of the disease. The present survey aims to explore possible correlations between cannabis use, either recreational or medical, over the presence of SARS-COV-2 contagion, along with the symptoms severity. 4026 surveys were collected via electronic form. Results suggest a relation between any type of cannabis use and a lower risk of SARS-COV-2 contagion (p=0,004; OR=0,689, IC95% 0,534-0,889). Despite several methodological limitations, the present survey steps up the urge to expand our understanding on cannabinoids potential use on human controlled studies, that can better arm us in the fight against the current COVID-19 pandemic.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Marco Cosentino", - "author_inst": "University of Insubria" + "author_name": "Paula Herrera-Gomez", + "author_inst": "Universidad Tecnologica de Pereira" }, { - "author_name": "Veronica Vernocchi", - "author_inst": "IppocrateOrg Association, Lugano, Switzerland" + "author_name": "Luis Felipe Echeveri-Catano", + "author_inst": "Fundacion Universitaria de las Americas, Pereira Colombia" }, { - "author_name": "Stefano Martini", - "author_inst": "Center for Research in Medical Pharmacology, University of Insubria, Varese, Italy" + "author_name": "Yerson Andres Ruiz Colorado", + "author_inst": "Universidad Tecnologica de Pereira, Colombia" }, { - "author_name": "Franca Marino", - "author_inst": "Center for Research in Medical Pharmacology, University of Insubria, Varese, Italy" + "author_name": "Sebastian Giraldo Galeano", + "author_inst": "Universidad Tecnologica de Pereira, Colombia" }, { - "author_name": "Barbara Allasino", - "author_inst": "IppocrateOrg Association, Lugano, Switzerland" - }, - { - "author_name": "Maria Balzola", - "author_inst": "IppocrateOrg Association, Lugano, Switzerland" - }, - { - "author_name": "Fabio Burigana", - "author_inst": "IppocrateOrg Association, Lugano, Switzerland" - }, - { - "author_name": "Alberto Dallari", - "author_inst": "IppocrateOrg Association, Lugano, Switzerland" - }, - { - "author_name": "Carlo Servo Florio Pagano", - "author_inst": "IppocrateOrg Association, Lugano, Switzerland" - }, - { - "author_name": "Antonio Palma", - "author_inst": "IppocrateOrg Association, Lugano, Switzerland" - }, - { - "author_name": "Mauro Rango", - "author_inst": "IppocrateOrg Association, Lugano, Switzerland" + "author_name": "Alberto Velez van Meerbeke", + "author_inst": "Universidad del Rosario, Bogota Colombia" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "pharmacology and therapeutics" }, @@ -313201,71 +312856,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.04.03.486830", - "rel_title": "Transcriptional reprogramming from innate immune functions to a pro-thrombotic signature upon SARS-CoV-2 sensing by monocytes in COVID-19", + "rel_doi": "10.1101/2022.03.31.22273239", + "rel_title": "Epidemiological topology data analysis links severe COVID-19 to RAAS andhyperlipidemia associated metabolic syndrome conditions", "rel_date": "2022-04-03", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.03.486830", - "rel_abs": "Alterations in the myeloid immune compartment have been observed in COVID-19, but the specific mechanisms underlying these impairments are not completely understood. Here we examined the functionality of classical CD14+ monocytes as a main myeloid cell component in well-defined cohorts of patients with mild and moderate COVID-19 during the acute phase of infection and compared them to that of healthy individuals. We found that ex vivo isolated CD14+ monocytes from mild and moderate COVID-19 patients display specific patterns of costimulatory and inhibitory receptors that clearly distinguish them from healthy monocytes, as well as altered expression of histone marks and a dysfunctional metabolic profile. Decreased NF{kappa}B activation in COVID-19 monocytes ex vivo is accompanied by an intact type I IFN antiviral response. Subsequent pathogen sensing ex vivo led to a state of functional unresponsiveness characterized by a defect in pro-inflammatory cytokine expression, NF{kappa}B-driven cytokine responses and defective type I IFN response in moderate COVID-19 monocytes. Transcriptionally, COVID-19 monocytes switched their gene expression signature from canonical innate immune functions to a pro-thrombotic phenotype characterized by increased expression of pathways involved in hemostasis and immunothrombosis. In response to SARS-CoV-2 or other viral or bacterial components, monocytes displayed defects in the epigenetic remodelling and metabolic reprogramming that usually occurs upon pathogen sensing in innate immune cells. These results provide a potential mechanism by which innate immune dysfunction in COVID-19 may contribute to disease pathology.", - "rel_num_authors": 13, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.31.22273239", + "rel_abs": "The emergence of COVID19 created incredible worldwide challenges but offers unique opportunities to understand the physiology of its risk factors and their interactions with complex disease conditions, such as metabolic syndrome. Epidemiological analysis powered by topological data analysis (TDA) is a novel approach to uncover these clinically relevant interactions. Here TDA utilized Explorys data to discover associations among severe COVID19 and metabolic syndrome, and it explored the probative value of drug prescriptions to capture the involvement of RAAS and hypertension with COVID19 as well as modification of risk factor impact by hyperlipidemia on severe COVID19.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Allison K Maher", - "author_inst": "Imperial College London" - }, - { - "author_name": "Katie L Burnham", - "author_inst": "Wellcome Sanger Institute" - }, - { - "author_name": "Emma Jones", - "author_inst": "Imperial College London" - }, - { - "author_name": "Laury Baillon", - "author_inst": "Imperial College London" + "author_name": "Daniel E. Platt", + "author_inst": "IBM Research, Yorktown Heights, NY" }, { - "author_name": "Claudia Selck", - "author_inst": "Imperial College London" - }, - { - "author_name": "Nicolas Giang", - "author_inst": "Imperial College London" - }, - { - "author_name": "Charlotte-Eve Short", - "author_inst": "Imperial College London" - }, - { - "author_name": "Rachael Quinlan", - "author_inst": "Imperial College London" - }, - { - "author_name": "Wendy S Barclay", - "author_inst": "Imperial College London" - }, - { - "author_name": "Nichola Cooper", - "author_inst": "Imperial College London" + "author_name": "Aritra Bose", + "author_inst": "IBM Research, Yorktown Heights, NY" }, { - "author_name": "Graham P Taylor", - "author_inst": "Imperial College London" + "author_name": "Chaya Levovitz", + "author_inst": "IBM Research, Yorktown Heights, NY" }, { - "author_name": "Emma E Davenport", - "author_inst": "Wellcome Sanger Institute" + "author_name": "Kahn Rhrissorrakrai", + "author_inst": "IBM Research, Yorktown Heights, NY" }, { - "author_name": "Margarita Dominguez-Villar", - "author_inst": "Imperial College London" + "author_name": "LAXMI PARIDA", + "author_inst": "IBM Research, Yorktown Heights, NY" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "immunology" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "health informatics" }, { "rel_doi": "10.1101/2022.04.02.22273333", @@ -314919,29 +314542,49 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.03.31.22273274", - "rel_title": "Effect of vaccination rates on the prevalence and mortality of COVID-19", + "rel_doi": "10.1101/2022.03.31.22273208", + "rel_title": "COVID-19 in people with neurofibromatosis 1, neurofibromatosis 2, or schwannomatosis", "rel_date": "2022-04-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.31.22273274", - "rel_abs": "By looking at trends in global epidemic data, we evaluate the effectiveness of vaccines on the incidence and mortality from the delta variant of COVID-19. By comparing countries of varying vaccination levels, we find that more vaccinated countries have lower deaths while not having lower cases. This cannot be explained by testing rates or restrictions, but can be partly explained by the most susceptible countries also being the highest vaccinated countries. We also find that during the period when many countries have high vaccination rates, cases and deaths are both increasing in time. This seems to be caused by the waning of the protection vaccines grant against infection.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.31.22273208", + "rel_abs": "PurposePeople with pre-existing conditions may be more susceptible to severe Coronavirus disease 2019 (COVID-19) when infected by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The relative risk and severity of SARS-CoV-2 infection in people with rare diseases like neurofibromatosis (NF) type 1 (NF1), neurofibromatosis type 2 (NF2), or schwannomatosis (SWN) is unknown.\n\nMethodsWe investigated the proportions of SARS-CoV-2 positive or COVID-19 patients in people with NF1, NF2, or SWN in the National COVID Collaborative Cohort (N3C) electronic health record dataset.\n\nResultsThe cohort sizes in N3C were 2,501 (NF1), 665 (NF2), and 762 (SWN). We compared these to N3C cohorts of other rare disease patients (98 - 9844 individuals) and the general non-NF population of 5.6 million. The site- and age-adjusted proportion of people with NF1, NF2, or SWN who tested positive for SARS-CoV-2 or were COVID-19 patients (collectively termed positive cases) was not significantly higher than in individuals without NF or other selected rare diseases. There were no severe outcomes reported in the NF2 or SWN cohorts. The proportion of patients experiencing severe outcomes was no greater for people with NF1 than in cohorts with other rare diseases or the general population.\n\nConclusionHaving NF1, NF2, or SWN does not appear to increase the risk of being SARS-CoV-2 positive or of being a COVID-19 patient, or of developing severe complications from SARS-CoV-2.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Jacob Westerhout", - "author_inst": "The University of Queensland" + "author_name": "Jineta Banerjee", + "author_inst": "Sage Bionetworks, Seattle, WA" }, { - "author_name": "Hamid Khataee", - "author_inst": "The University of Queensland" + "author_name": "Jan M Friedman", + "author_inst": "University of British Columbia, Vancouver, BC" }, { - "author_name": "Zoltan Neufeld", - "author_inst": "University of Queensland" + "author_name": "Laura J Klesse", + "author_inst": "University of Texas Southwestern Medical Center, Dallas, TX" + }, + { + "author_name": "Kaleb Yohay", + "author_inst": "Comprehensive Neurofibromatosis Center at NYU Langone Health, New York, NY" + }, + { + "author_name": "Justin T Jordan", + "author_inst": "Massachusetts General Hospital, Boston, MA" + }, + { + "author_name": "Scott Plotkin", + "author_inst": "Massachusetts General Hospital, Boston, MA" + }, + { + "author_name": "Robert J Allaway", + "author_inst": "Sage Bionetworks, Seattle, WA" + }, + { + "author_name": "Jaishri O Blakeley", + "author_inst": "Johns Hopkins University School of Medicine, Baltimore, MD" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "health informatics" }, @@ -316841,71 +316484,35 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.03.25.22272927", - "rel_title": "Changing characteristics over time of individuals receiving COVID-19 vaccines in Denmark: A population-based descriptive study of vaccine uptake", + "rel_doi": "10.1101/2022.03.31.22273238", + "rel_title": "Size of societal volunteering predicts COVID-19 mortality", "rel_date": "2022-03-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.25.22272927", - "rel_abs": "AimsThe Danish authorities implemented a differential rollout of the COVID-19 vaccines where individuals at high risk of COVID-19 were prioritized. We describe the temporal uptake of COVID-19 vaccines and changing characteristics of vaccine recipients in Denmark.\n\nMethodsUsing the Danish national health care registries, we identified all Danish residents [≥]5 years of age who received at least one dose of a COVID-19 vaccine from December 27th, 2020, to January 29th, 2022. We charted the daily number of newly vaccinated individuals and the cumulative vaccine coverage over time, stratified by vaccine type, age groups, and vaccination priority groups. In addition, we described characteristics of vaccine recipients during 2-months-intervals and in vaccination priority groups.\n\nResultsBy January 29th, 2022, 86%, 84% and 63% of Danish residents [≥]5 years had received a first, second, and third dose, respectively, of a COVID-19 vaccine, most commonly the BNT162b2 vaccine (84% of vaccinated individuals). Vaccine uptake ranged from 48% in 5-11-year-olds up to 98% in 65-74-year-olds. Individuals vaccinated before June 2021 were older (median age 61-70 years vs. 10-35 years in later periods) and had more comorbidities such as hypertension (22-28% vs. 0.77-2.8% in later periods), chronic lung disease (9.4-15% vs. 3.7-4.6% in later periods), and diabetes (9.3-12% vs. 0.91-2.4% in later periods).\n\nConclusionsThe uptake of the COVID-19 vaccines is high in Denmark. We document substantial changes over time in characteristics of vaccine recipients which should be considered when designing and interpreting studies on the effectiveness and safety of COVID-19 vaccines.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.31.22273238", + "rel_abs": "IntroductionDifferent countries responded differently to the COVID-19 pandemic in terms of timing and stringency of measures, and in types of policies adopted. Typically, policy makers tried to balance the capacity of healthcare systems to take care of the ill (as determined by ICU capacity, availability of nurses, etc.), with safeguarding economic output (preventing total lockdown of the labor force, etc.). Later on, also a broader array of considerations such as impact on schooling or the need for social contact were taken into account to varying degrees.\n\nThe broad and relatively fast availability of data on healthcare and economic capacity, together with the political estimate that these were the most critical determinants for maintaining societal structure and compliance with the measures taken, in many countries prioritized decision-making. What received far less attention, in part due to the difficulty of obtaining reliable data in a timely manner, was the opposite question: to what extent do societal structures - besides healthcare and economic systems - contribute to a countrys resilience during catastrophes such as the pandemic? While it is commonly understood that the impact of a pandemic goes beyond its death count, perhaps the death count itself is impacted by the way societies are structured.\n\nOne example of such societal structure is the contribution of volunteers during the COVID-19 response. Volunteers may contribute to well-functioning societies in different ways, both through practical actions (e.g. knitting face masks) as by strengthening societal cohesion (e.g. encouraging fellow citizens to comply with measures). This paper quantifies the association between COVID-19 mortality and the size of societal volunteering, using the unique context of the COVID-19 crisis with its intensity, sudden onset and global spread.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Mette Reilev", - "author_inst": "University of Southern Denmark" + "author_name": "Fritz Schiltz", + "author_inst": "Belgian Red Cross, Mechelen, Belgium" }, { - "author_name": "Morten Olesen", - "author_inst": "University of Southern Denmark" + "author_name": "Hans Van Remoortel", + "author_inst": "Centre for Evidence-Based Practice, Belgian Red Cross, Mechelen, Belgium; Department of Public Health and Primary Care, Leuven Institute for Healthcare Policy, " }, { - "author_name": "Helene Kildegaard", - "author_inst": "University of Southern Denmark" + "author_name": "Hans Scheers", + "author_inst": "Centre for Evidence-Based Practice, Belgian Red Cross, Mechelen, Belgium; Department of Public Health and Primary Care, Leuven Institute for Healthcare Policy, " }, { - "author_name": "Henrik Stovring", - "author_inst": "University of Southern Denmark" - }, - { - "author_name": "Jacob H Andersen", - "author_inst": "University of Southern Denmark" - }, - { - "author_name": "Jesper Hallas", - "author_inst": "University of Southern Denmark" - }, - { - "author_name": "Lars Christian Lund", - "author_inst": "University of Southern Denmark" - }, - { - "author_name": "Louise Ladebo", - "author_inst": "University of Southern Denmark" - }, - { - "author_name": "Martin Thomsen Ernst", - "author_inst": "University of Southern Denmark" - }, - { - "author_name": "Per Damkier", - "author_inst": "University of Southern Denmark" - }, - { - "author_name": "Peter B Jensen", - "author_inst": "University of Southern Denmark" - }, - { - "author_name": "Anton Pottegard", - "author_inst": "University of Southern Denmark" - }, - { - "author_name": "Lotte Rasmussen", - "author_inst": "University of Southern Denmark" + "author_name": "Philippe Vandekerckhove", + "author_inst": "Belgian Red Cross, Mechelen, Belgium; Department of Public Health and Primary Care, Leuven Institute for Healthcare Policy, KU Leuven, Leuven, Belgium; Centre f" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.03.31.22273226", @@ -319495,51 +319102,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.03.28.22273068", - "rel_title": "SARS-CoV-2 spike-binding antibody longevity and protection from re-infection with antigenically similar SARS-CoV-2 variants", + "rel_doi": "10.1101/2022.03.29.22273041", + "rel_title": "Emerging Therapies for COVID-19: the value of information from more clinical trials", "rel_date": "2022-03-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.28.22273068", - "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWThe PARIS (Protection Associated with Rapid Immunity to SARS-CoV-2) cohort follows health care workers with and without documented coronavirus disease 2019 (COVID-19) since April 2020. We report our findings regarding SARS-CoV-2 spike binding antibody stability and protection from infection in the pre-variant era. We analyzed data from 400 healthcare workers (150 seropositive and 250 seronegative at enrollment) for a median of 84 days. The SARS-CoV-2 spike binding antibody titers were highly variable with antibody levels decreasing over the first three months, followed by a relative stabilization. We found that both more advanced age (>40 years) and female sex were associated with higher antibody levels (1.6-fold and 1.4-fold increases, respectively). Only six percent of the initially seropositive participants \"seroreverted\". We documented a total of 11 new SARS-CoV-2 infections (ten naive participants, one previously infected participant without detectable antibodies, p<0.01) indicating that spike antibodies limit the risk of re-infection. These observations, however, only apply to SARS-CoV-2 variants antigenically similar to the ancestral SARS-CoV-2 ones. In conclusion, SARS-CoV-2 antibody titers mounted upon infection are stable over several months in most people and provide protection from infection with antigenically similar viruses.\n\nsummaryThe levels of SARS-CoV-2 spike binding antibodies mounted upon infection with ancestral SARS-CoV-2 variants are highly variable, stabilize at an individual level after three months and provide protection from infection with homologous virus.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.29.22273041", + "rel_abs": "ObjectivesThe COVID-19 pandemic necessitates time-sensitive policy and implementation decisions regarding new therapies in the face of uncertainty. The aim of this study was to quantify consequences of approving therapies or pursuing further research: either immediate approval, use only in research, approval with research (e.g., Emergency Use Authorization), or reject.\n\nMethodsUsing a cohort state-transition model for hospitalized COVID-19 patients, we estimated quality-adjusted life years (QALYs) and costs associated with the following interventions: Hydroxychloroquine, Remdesivir, Casirivimab-Imdevimab, Dexamethasone, Baricitinib-Remdesivir, Tocilizumab, Lopinavir-Ritonavir, and Interferon beta-1a, and usual care. We used the model outcomes to conduct cost-effectiveness and value of information analyses from a US healthcare perspective and a lifetime horizon.\n\nResultsAssuming a $100,000-per-QALY willingness-to-pay-threshold, only Remdesivir, Casirivimab-Imdevimab, Dexamethasone, Baricitinib-Remdesivir and Tocilizumab were (cost-) effective (incremental net health benefit 0.252, 0.164, 0.545, 0.668 and 0.524 QALYs and incremental net monetary benefit $25,249, $16,375, $54,526, $66,826 and $52,378). Our value of information analyses suggest that most value can be obtained if these 5 therapies are approved for immediate use rather than requiring additional RCTs (net value $20.6 Billion, $13.4 Billion, $7.4 Billion, $54.6 Billion and $7.1 Billion); Hydroxychloroquine (net value $198 Million) only used in further RCTs if seeking to demonstrate decremental cost-effectiveness, and otherwise rejected; and Interferon beta-1a and Lopinavir-Ritonavir are rejected (i.e., neither approved nor additional RCTs).\n\nConclusions and RelevanceEstimating the real-time value of collecting additional evidence during the pandemic can inform policymakers and clinicians about the optimal moment to implement therapies and whether to perform further research.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "John Kubale", - "author_inst": "University of Michigan School of Public Health" - }, - { - "author_name": "Charles R Gleason", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Juan Manuel Carre\u00f1o", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Stijntje W. Dijk", + "author_inst": "Erasmus University Medical Center Rotterdam" }, { - "author_name": "Komal Srivastava", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Eline M. Krijkamp", + "author_inst": "Erasmus University Medical Center Rotterdam" }, { - "author_name": "- PARIS Study Team", - "author_inst": "" + "author_name": "Natalia Kunst", + "author_inst": "Harvard Medical School & Harvard Pilgrim Health Care Institute, Yale University School of Medicine" }, { - "author_name": "Aubree Gordon", - "author_inst": "University of Michigan" + "author_name": "Cary P. Gross", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Florian Krammer", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "John B. Wong", + "author_inst": "Tufts Medical Center" }, { - "author_name": "Viviana Simon", - "author_inst": "Icahn School of Medicine" + "author_name": "M.G. Myriam Hunink", + "author_inst": "Erasmus University Medical Center, Harvard T.H. Chan School of Public Health" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "health economics" }, { "rel_doi": "10.1101/2022.03.29.486173", @@ -322113,57 +321712,57 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.03.23.485575", - "rel_title": "Optimized production and fluorescent labelling of SARS-CoV-2 Virus-Like-Particles to study virus assembly and entry.", + "rel_doi": "10.1101/2022.03.23.485570", + "rel_title": "Engineering a Vaccine Platform using Rotavirus A to Express SARS-CoV-2 Spike Epitopes", "rel_date": "2022-03-27", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.23.485575", - "rel_abs": "SARS-CoV-2 is an RNA enveloped virus responsible for the COVID-19 pandemia that conducted in 6 million deaths worldwide so far. SARS-CoV-2 particles are mainly composed of the 4 main structural proteins M, N, E and S to form 100nm diameter viral particles. Based on productive assays, we propose an optimal transfected plasmid ratio mimicking the virus RNA ratio allowing SARS-CoV-2 Virus-Like Particle (VLPs) formation composed of the viral structural proteins M, N, E and S. Furthermore, monochrome, dual-color fluorescent or photoconvertible VLPs were produced. Thanks to live fluorescence and super-resolution microscopy, we quantified VLPs size and concentration. It shows a diameter of 110 and 140 nm respectively for MNE-VLPs and MNES-VLPs with a minimum concentration of 10e12 VLP/ml. SARS-CoV-2 VLPs could tolerate the integration of fluorescent N and M tagged proteins without impairing particle assembly. In this condition, we were able to establish incorporation of the mature Spike in fluorescent VLPs. The Spike functionality was then shown by monitoring fluorescent MNES-VLPs docking and endocytosis in human pulmonary cells expressing the receptor hACE2. This work provides new insights on the use of non-fluorescent and fluorescent VLPs to study and visualize the SARS-CoV-2 viral life cycle in a safe environment (BSL-2 instead of BSL-3). Moreover, optimized SARS-CoV-2 VLP production can be further adapted to vaccine design strategies.", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.23.485570", + "rel_abs": "Human rotavirus (RV) vaccines used worldwide have been developed using live attenuated platforms. The recent development of a reverse genetics system for RVs has delivered the possibility of engineering chimeric viruses expressing heterologous peptides from other virus species to generate polyvalent vaccines. We tested the feasibility of this using two approaches. Firstly, we inserted short SARS-CoV-2 spike peptides into the hypervariable region of the simian SA11 RV strain viral protein (VP) 4. Secondly, we fused the receptor binding domain (RBD) of the SARS-CoV-2 spike protein, or the shorter receptor binding motif (RBM) nested within the RBD, to the C-terminus of non-structural protein (NSP) 3 of the bovine RF strain RV, with or without an intervening T2A peptide. Mutating the hypervariable region of SA11 VP4 impeded viral replication, and for these mutants no cross-reactivity with spike antibodies was detected. To rescue NSP3 mutants, we established a plasmid-based reverse genetics system for the bovine RF strain. Except for the RBD mutant, all NSP3 mutants delivered endpoint titres and replication kinetics comparable to that of the WT virus. In ELISAs, cell lysates of an NSP3 mutant expressing the RBD peptide showed cross reactivity with a SARS-CoV-2 RBD antibody. 3D bovine gut enteroids were susceptible to infection by all NSP3 mutants but only RBM mutant showed cross reactivity with SARS-CoV-2 RBD antibody. The tolerability of large peptide insertions in the NSP3 segment highlights the potential for this approach in the development of vaccine vectors targeting multiple enteric pathogens simultaneously.\n\nIMPORTANCEWe explored the use of rotaviruses (RVs) to express heterologous peptides, using SARS-CoV-2 as an exemplar. Small SARS-CoV-2 peptide insertion (<34 amino acids) into the hypervariable region of the viral protein 4 (VP4) of RV SA11 strain resulted in reduced viral titre and replication, thus limiting its use as a potential vaccine expression platform. To test RF strain for its tolerance for peptide insertions, we constructed a reverse genetics system. NSP3 was C-terminally tagged with SARS-CoV-2 spike peptides of up to 193 amino acids. With a T2A-separated 193 amino acid tag on NSP3, there was little effect on the viral rescue efficiency, titre and replication. Tagged NSP3 elicited cross-reactivity with SARS-CoV-2 spike antibodies in ELISA. This is the first report describing epitope tagging of VP4, and of a reverse genetics system for the RF strain. We highlight the potential for development of RV vaccine vectors targeting multiple enteric pathogens simultaneously.", "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Delphine Muriaux", - "author_inst": "CNRS & University of Montpellier" + "author_name": "Ola Diebold", + "author_inst": "The University of Edinburgh" }, { - "author_name": "Manon Gourdelier", - "author_inst": "CNRS & University of Montpellier" + "author_name": "Victoria Gonzalez", + "author_inst": "The Roslin Institute" }, { - "author_name": "Jitendriya M Swain", - "author_inst": "CNRS & University of Montpellier" + "author_name": "Luca Venditti", + "author_inst": "University of Cambrdige" }, { - "author_name": "Coline Arone", - "author_inst": "CNRS & University of Montpellier" + "author_name": "Colin Sharp", + "author_inst": "The Roslin Institute" }, { - "author_name": "Anita Mouttou", - "author_inst": "CNRS & University of Montpellier" + "author_name": "Rosemary A Blake", + "author_inst": "The Roslin Institute" }, { - "author_name": "David Bracquemond", - "author_inst": "CNRS & University of Montpellier" + "author_name": "Joanne Stevens", + "author_inst": "The Roslin Institute" }, { - "author_name": "Peggy Merida", - "author_inst": "CNRS" + "author_name": "Sarah Caddy", + "author_inst": "Cambridge Institute of Therapeutic Immunology and Infectious Disease" }, { - "author_name": "Saveez Saffarian", - "author_inst": "University of Utah" + "author_name": "Paul Digard", + "author_inst": "University of Edinburgh" }, { - "author_name": "Sebastien Lyonnais", - "author_inst": "CNRS" + "author_name": "Alexander Borodavka", + "author_inst": "University of Cambrdige" }, { - "author_name": "Cyril Favard", - "author_inst": "CNRS & University of Montpellier" + "author_name": "Eleanor Gaunt", + "author_inst": "The Roslin Institute" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "microbiology" }, @@ -323587,61 +323186,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.03.22.22272691", - "rel_title": "COVID-19 Vaccine Effectiveness against the Omicron BA.2 variant in England", + "rel_doi": "10.1101/2022.03.23.22272836", + "rel_title": "Risk factors for SARS-CoV-2 transmission in student residences: a case-ascertained study in Leuven, Belgium from October 2020 until May 2021", "rel_date": "2022-03-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.22.22272691", - "rel_abs": "The BA.1 sub-lineage of the Omicron (B.1.1.529) variant, first detected in the UK in mid-November 2021, rapidly became the dominant strain partly due to reduced vaccine effectiveness. An increase in a second Omicron sub-lineage BA.2 was observed in early January 2022. In this study we use a test-negative case control study design to estimate vaccine effectiveness against symptomatic disease with BA.1 and BA.2 after one or two doses of BNT162b2, ChAdOx1-S or mRNA-1273, and after booster doses of BNT162b2 or mRNA-1273 during a period of co-circulation. Overall, there was no evidence that vaccine effectiveness against symptomatic disease is reduced following infection with the BA.2 sub-lineage as compared to BA.1. Furthermore, similar rates of waning were observed after the second and booster dose for each sub-lineage. These data provide reassuring evidence of the effectiveness of the vaccines currently in use against symptomatic disease caused by BA.2.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.23.22272836", + "rel_abs": "BackgroundStudent residences are at high risk for rapid COVID-transmission due to crowding and frequent close contact.\n\nAimWe aimed to investigate the overall secondary attack rates (SAR) in student residences and to discern risk factors for higher transmission in order to improve the evidence base for screening efforts and preventive measures.\n\nMethodsIn this retrospective case-ascertained study, we analysed data from student residences screened in Leuven, Belgium between October 2020 and May 2021, following detection of a COVID-19 case in the residence. We investigated the impact on the SAR in the living units screened of delay-time until follow-up, shared use of kitchen or sanitary facilities, presence of an external infection source and occurrence of social gatherings attended by the index case.\n\nResultsWe included 200 residence units, representing 2326 screened residents, of which 68 units showed secondary transmission. The overall SAR was estimated at 0.0813 (95%CI 0.0705-0.0936). Both sharing sanitary facilities (p=0.04) and social gatherings attended by the index case (p=0.033) significantly impacted SAR, which increased from 3% to 13% when both risk factors were present compared to absent.\n\nConclusionsWe identify risk factors which should be considered when selecting students for screening during an outbreak of COVID-19 in student residences to improve comprehensiveness and proportionality of testing. The identified risk factors improve the evidence base for preventive measures aimed at limiting social gatherings and improving ventilation of shared spaces in outbreak-prone settings. Lastly, they should be considered when designing student accommodation and other shared households.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Freja Kirsebom", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Nick Andrews", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Julia Stowe", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Samuel Toffa", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Ruchira Sachdeva", - "author_inst": "UK Health Security Agency" + "author_name": "Marte Vanbesien", + "author_inst": "KU Leuven" }, { - "author_name": "Eileen Gallagher", - "author_inst": "UK Health Security Agency" + "author_name": "Geert Molenberghs", + "author_inst": "UHasselt, KU Leuven" }, { - "author_name": "Natalie Groves", - "author_inst": "UK Health Security Agency" + "author_name": "Caspar Geenen", + "author_inst": "KU Leuven" }, { - "author_name": "Anne-Marie O'Connell", - "author_inst": "UK Health Security Agency" + "author_name": "Jonathan Thibaut", + "author_inst": "KU Leuven" }, { - "author_name": "Meera Chand", - "author_inst": "UK Health Security Agency" + "author_name": "Sarah Gorissen", + "author_inst": "KU Leuven" }, { - "author_name": "Mary Ramsay", - "author_inst": "UK Health Security Agency" + "author_name": "Emmanuel Andre", + "author_inst": "KU Leuven, UZ Leuven" }, { - "author_name": "Jamie Lopez Bernal", - "author_inst": "Public Health England" + "author_name": "Joren raymenants", + "author_inst": "KU Leuven" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -325357,293 +324940,29 @@ "category": "otolaryngology" }, { - "rel_doi": "10.1101/2022.03.22.22272739", - "rel_title": "The efficacy, safety and immunogenicity Nanocovax: results of a randomized, double-blind, placebo-controlled Phase 3 trial.", + "rel_doi": "10.1101/2022.03.23.22272811", + "rel_title": "Association of COVID-19 with risks of hospitalization and mortality from other disorders post-infection: A study of the UK Biobank", "rel_date": "2022-03-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.22.22272739", - "rel_abs": "BackgroundNanocovax is a recombinant severe acute respiratory syndrome coronavirus 2 subunit vaccine composed of full-length prefusion stabilized recombinant SARS-CoV-2 spike glycoproteins (S-2P) and aluminum hydroxide adjuvant. In a Phase 1 and 2 studies, (NCT04683484) the vaccine was found to be safe and induce a robust immune response in healthy adult participants.\n\nMethodsWe conducted a multicenter, randomized, double-blind, placebo-controlled study to evaluate the safety, immunogenicity, and protective efficacy of the Nanocovax vaccine against Covid-19 in approximately 13,007 volunteers aged 18 years and over. The immunogenicity was assessed based on Anti-S IgG antibody response, surrogate virus neutralization, wild-type SARS-CoV-2 neutralization and the types of helper T-cell response by intracellular staining (ICS) for interferon gamma (IFNg) and interleukin-4 (IL-4). The vaccine efficacy (VE) was calculated basing on serologically confirmed cases of Covid-19.\n\nFindingsUp to day 180, incidences of solicited and unsolicited adverse events (AE) were similar between vaccine and placebo groups. 100 serious adverse events (SAE) were observed in both vaccine and placebo groups (out of total 13007 participants). 96 out of these 100 SAEs were determined to be unrelated to the investigational products. 4 SAEs were possibly related, as determined by the Data and Safety Monitoring Board (DSMB) and investigators. Reactogenicity was absent or mild in the majority of participants and of short duration. These findings highlight the excellent safety profile of Nanocovax.\n\nRegarding immunogenicity, Nanocovax induced robust IgG and neutralizing antibody responses. Importantly, Anti S-IgG levels and neutralizing antibody titers on day 42 were higher than those of natural infected cases. Nanocovax was found to induce Th2 polarization rather than Th1.\n\nPost-hoc analysis showed that the VE against symptomatic disease was 51.5% (95% confidence interval [CI] was [34.4%-64.1%]. VE against severe illness and death were 93.3% [62.2-98.1]. Notably, the dominant strain during the period of this study was Delta variant.\n\nInterpretationNanocovax 25 microgram (mcg) was found to be safe with the efficacy against symptomatic infection of Delta variant of 51.5%.\n\nFundingResearch was funded by Nanogen Pharmaceutical Biotechnology JSC., and the Ministry of Science and Technology of Vietnam; ClinicalTrials.gov number, NCT04922788.", - "rel_num_authors": 70, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.23.22272811", + "rel_abs": "ObjectiveTo study whether COVID-19 infection may be associated with increased hospitalization and mortality from other diseases.\n\nDesignCohort study.\n\nSettingThe UK Biobank.\n\nParticipantsAll subjects in the UK Biobank with available hospitalization records and alive as of 31-Jan-2020 (N= 412,096; age 50-87).\n\nMain outcome measuresWe investigated associations of COVID-19 with hospitalization and mortality due to different diseases post-infection. We conducted a comprehensive survey on disorders from all systems (up to 135 disease categories). Multivariable Cox and Poisson regression was conducted controlling for main confounders. For sensitivity analysis, we also conducted separate analysis for new-onset and recurrent cases, and other analysis such as the prior event rate adjustment(PERR) approach to minimize effects of unmeasured confounders. We also performed association analyses stratified by vaccination status. Time-dependent effects on subsequent hospitalization and mortality were also tested.\n\nResultsCompared to individuals with no known history of COVID-19, those with severe COVID-19 (requiring hospitalization) exhibited higher hazards of hospitalization and/or mortality due to multiple disorders (median follow-up=608 days), including disorders of respiratory, cardiovascular, neurological, gastrointestinal, genitourinary and musculoskeletal systems. Increased hazards of hospitalizations and/or mortality were also observed for injuries due to fractures, various infections and other non-specific symptoms. These results remained largely consistent after sensitivity analyses. Severe COVID-19 was also associated with increased all-cause mortality (HR=14.700, 95% CI: 13.835-15.619).\n\nMild (non-hospitalized) COVID-19 was associated with modestly increased risk of all-cause mortality (HR=1.237, 95% CI 1.037-1.476) and mortality from neurocognitive disorders, as well as hospital admission from a few disorders such as aspiration pneumonitis, musculoskeletal pain and other general signs/symptoms.\n\nAll-cause mortalities and hospitalizations from other disorders post-infection were generally higher in the pre-vaccination era. The deleterious effect of COVID-19 was observed to wane over time, with maximum HR in the initial phase.\n\nConclusionsIn conclusion, this study revealed increased risk of hospitalization and mortality from a wide variety of pulmonary and extra-pulmonary diseases after COVID-19, especially for severe infections. Mild disease was also associated with increased all-cause mortality. Causality however cannot be established due to observational nature of the study. Further studies are required to replicate our findings.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Thuy Phuong Nguyen", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" - }, - { - "author_name": "Quyet Do", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Lan Trong Phan", - "author_inst": "Pasteur Institute in Ho Chi Minh city" - }, - { - "author_name": "Dang Duc Anh", - "author_inst": "National Institute of Hygiene and Epidemiology" - }, - { - "author_name": "Hiep Khong", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" - }, - { - "author_name": "Duc Viet Dinh", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Luong Van Hoang", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Thuong Vu Nguyen", - "author_inst": "Pasteur Institute in Ho Chi Minh city" - }, - { - "author_name": "Hung Ngoc Pham", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Men Van Chu", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Toan Trong Nguyen", - "author_inst": "Pasteur Institute in Ho Chi Minh city" - }, - { - "author_name": "Tri Minh Le", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" - }, - { - "author_name": "Tuyen Thi Ngoc Trang", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" - }, - { - "author_name": "Thanh Thi Dinh", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" - }, - { - "author_name": "Thuong Van Vo", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" - }, - { - "author_name": "Thao Thi Vu", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" - }, - { - "author_name": "Quynh Bao Phuong Nguyen", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" - }, - { - "author_name": "Vuong Tan Phan", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" - }, - { - "author_name": "Luong Viet Nguyen", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Giang Truong Nguyen", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Phong Minh Tran", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Thuan Duc Nghiem", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Tien Viet Tran", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Tien Gia Nguyen", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Tuynh Quang Tran", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Linh Tung Nguyen", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Anh Tuan Do", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Dung Dang Nguyen", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Son Anh Ho", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Viet Thanh Nguyen", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Dung T Pham", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Hieu B Tran", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Son T Vu", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Su Xuan Hoang", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Trung Minh Do", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Xuan Thanh Nguyen", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Giang Quynh Le", - "author_inst": "Vietnam Military Medical University" - }, - { - "author_name": "Ton Tran", - "author_inst": "Pasteur Institute in Ho Chi Minh city" - }, - { - "author_name": "Thang Minh Cao", - "author_inst": "Pasteur Institute in Ho Chi Minh city" - }, - { - "author_name": "Huy Manh Dao", - "author_inst": "Pasteur Institute in Ho Chi Minh city" - }, - { - "author_name": "Thao Thi Thanh Nguyen", - "author_inst": "Pasteur Institute in Ho Chi Minh city" - }, - { - "author_name": "Uyen Y Doan", - "author_inst": "Pasteur Institute in Ho Chi Minh city" - }, - { - "author_name": "Vy Thi Tuong Le", - "author_inst": "Pasteur Institute in Ho Chi Minh city" - }, - { - "author_name": "Linh Phuong Tran", - "author_inst": "Pasteur Institute in Ho Chi Minh city" - }, - { - "author_name": "Ngoc Minh Nguyen", - "author_inst": "Pasteur Institute in Ho Chi Minh city" - }, - { - "author_name": "Ngoc Thu Nguyen", - "author_inst": "Pasteur Institute in Ho Chi Minh city" - }, - { - "author_name": "Hang Thi Thu Pham", - "author_inst": "Pasteur Institute in Ho Chi Minh city" - }, - { - "author_name": "Quan Hoang Nguyen", - "author_inst": "Pasteur Institute in Ho Chi Minh city" - }, - { - "author_name": "Quang Duy Pham", - "author_inst": "Pasteur Institute in Ho Chi Minh city" - }, - { - "author_name": "Hieu Trung Nguyen", - "author_inst": "Pasteur Institute in Ho Chi Minh city" - }, - { - "author_name": "Hang Le Khanh Nguyen", - "author_inst": "National Institute of Hygiene and Epidemiology" - }, - { - "author_name": "Nguyen Van Trang", - "author_inst": "National Institute of Hygiene and Epidemiology" - }, - { - "author_name": "Lan Anh Thi Nguyen", - "author_inst": "National Institute of Hygiene and Epidemiology" - }, - { - "author_name": "Linh Thuy Nguyen", - "author_inst": "National Institute of Hygiene and Epidemiology" - }, - { - "author_name": "Nhung Thi Hong Trinh", - "author_inst": "National Institute of Hygiene and Epidemiology" - }, - { - "author_name": "Ly Thi Khanh Le", - "author_inst": "National Institute of Hygiene and Epidemiology" - }, - { - "author_name": "Van Thi Bao Tran", - "author_inst": "National Institute of Hygiene and Epidemiology" - }, - { - "author_name": "Mai Thi Ngoc Chu", - "author_inst": "National Institute of Hygiene and Epidemiology" - }, - { - "author_name": "My Ha Phan", - "author_inst": "National Institute of Hygiene and Epidemiology" - }, - { - "author_name": "Hoa Thi Hong Nguyen", - "author_inst": "National Institute of Hygiene and Epidemiology" - }, - { - "author_name": "Vinh The Tran", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" - }, - { - "author_name": "Mai Thi Nhu Tran", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" - }, - { - "author_name": "Truc Thi Thanh Nguyen", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" - }, - { - "author_name": "Phat Tan Ha", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" - }, - { - "author_name": "Hieu Trong Huynh", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" - }, - { - "author_name": "Khanh Duy Nguyen", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" - }, - { - "author_name": "Thuan Trong Ung", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" + "author_name": "Yong XIANG", + "author_inst": "The Chinese University of Hong Kong" }, { - "author_name": "Nghia Hoang Trong Duong", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" + "author_name": "Ruoyu ZHANG", + "author_inst": "The Chinese University of Hong Kong" }, { - "author_name": "Chung Chinh Doan", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" + "author_name": "Jinghong QIU", + "author_inst": "The Chinese University of Hong Kong" }, { - "author_name": "Si Minh Do", - "author_inst": "Nanogen Pharmaceutical Biotechnology JSC" + "author_name": "Hon-Cheong So", + "author_inst": "Chinese University of Hong Kong" } ], "version": "1", @@ -327367,33 +326686,81 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.03.18.22272553", - "rel_title": "15-month follow-up of anti-spike receptor binding domain (RBD) SARS-CoV-2 antibodies among healthcare workers in Boston, MA", + "rel_doi": "10.1101/2022.03.18.22272607", + "rel_title": "Multi-organ impairment and Long COVID: a 1-year prospective, longitudinal cohort study", "rel_date": "2022-03-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.18.22272553", - "rel_abs": "Over 15-months we found that anti-spike RBD SARS-CoV-2 antibody concentrations follow different trends with combinations and permutations of COVID-19 infection and vaccination among healthcare workers in Boston, MA. A majority of HCWs remain well above the positivity threshold for anti-spike RBD IgG antibodies for at least 9 months following vaccination regardless of infection history. Of interest, those with COVID-19 infection before vaccination had significantly higher median serum antibody concentrations in comparison to HCWs with no prior infection at each follow-up timepoint. These findings further support what is known regarding the decline in serum antibody concentrations following natural infection and vaccination, adding knowledge of serum antibodies up to 15 months post infection and 11 months post vaccination.\n\nImportanceBoston Medical Center (BMC) is a safety net hospital in Boston and from the initial wave of COVID-19 there has been overwhelming concern about the exposure of healthcare workers to SARS-CoV-2. We conceived a longitudinal study to assess virus exposure and trends in SARS-CoV-2 antibodies amongst healthcare workers at BMC over 15 months. We have followed HCWs through three waves of COVID-19, including the Delta variant wave from June through mid-December 2021, assessing anti-spike receptor binding domain IgG, anti-nucleocapsid IgG, and anti-spike IgM at approximately three-month intervals. Current literature largely describes antibody durability six months post vaccination. These data add to the literature by describing antibody durability and trend differences according to infection history and vaccination status. These longitudinal data contribute to a greater understanding of the ongoing COVID-19 pandemic and can help inform future research and public health decision-making regarding vaccine uptake, breakthrough infections, and overall pandemic response.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.18.22272607", + "rel_abs": "ImportanceMulti-organ impairment associated with Long COVID is a significant burden to individuals, populations and health systems, presenting challenges for diagnosis and care provision. Standardised assessment across multiple organs over time is lacking, particularly in non-hospitalised individuals.\n\nObjectiveTo determine the prevalence of organ impairment in Long COVID patients at 6 and at 12 months after initial symptoms and to explore links to clinical presentation.\n\nDesignThis was a prospective, longitudinal study in individuals following recovery from acute COVID-19. We assessed symptoms, health status, and multi-organ tissue characterisation and function, using consensus definitions for single and multi-organ impairment. Physiological and biochemical investigations were performed at baseline on all individuals and those with organ impairment were reassessed, including multi-organ MRI, 6 months later.\n\nSettingTwo non-acute settings (Oxford and London).\n\nParticipants536 individuals (mean 45 years, 73% female, 89% white, 32% healthcare workers, 13% acute COVID-19 hospitalisation) completed baseline assessment (median: 6 months post-COVID-19). 331 (62%) with organ impairment or incidental findings had follow up, with reduced symptom burden from baseline (median number of symptoms: 10 and 3, at 6 and 12 months).\n\nExposureSARS-CoV-2 infection 6 months prior to first assessment.\n\nMain outcomePrevalence of single and multi-organ impairment at 6 and 12 months post-COVID-19.\n\nResultsExtreme breathlessness (36% and 30%), cognitive dysfunction (50% and 38%) and poor health-related quality of life (EQ-5D-5L<0.7; 55% and 45%) were common at 6 and 12 months, and associated with female gender, younger age and single organ impairment. At baseline, there was fibro-inflammation in the heart (9%), pancreas (9%), kidney (15%) and liver (11%); increased volume in liver (7%), spleen (8%) and kidney (9%); decreased capacity in lungs (2%); and excessive fat deposition in the liver (25%) and pancreas (15%). Single and multi-organ impairment were present in 59% and 23% at baseline, persisting in 59% and 27% at follow-up.\n\nConclusion and RelevanceOrgan impairment was present in 59% of individuals at 6 months post-COVID-19, persisting in 59% of those followed up at 1 year, with implications for symptoms, quality of life and longer-term health, signalling need for prevention and integrated care of Long COVID.\n\nTrial RegistrationClinicalTrials.gov Identifier: NCT04369807\n\nKey pointsO_LIQuestion: What is the prevalence of organ impairment in Long COVID at 6- and 12-months post-COVID-19?\nC_LIO_LIFindings: In a prospective study of 536 mainly non-hospitalised individuals, symptom burden decreased, but single organ impairment persisted in 59% at 12 months post-COVID-19.\nC_LIO_LIMeaning: Organ impairment in Long COVID has implications for symptoms, quality of life and longer-term health, signalling need for prevention and integrated care of Long COVID.\nC_LI", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Maura Clare Dodge", - "author_inst": "Boston Medical Center" + "author_name": "Andrea Dennis", + "author_inst": "Perspectum Ltd" }, { - "author_name": "Manisha Cole", - "author_inst": "Boston Medical Center" + "author_name": "Daniel J Cuthbertson", + "author_inst": "University of Liverpool" }, { - "author_name": "Elizabeth R Duffy", - "author_inst": "Boston Medical Center" + "author_name": "Dan Wootton", + "author_inst": "University of Liverpool" }, { - "author_name": "Martha M Werler", - "author_inst": "Boston University" + "author_name": "Michael Crooks", + "author_inst": "University of Hull" }, { - "author_name": "Yachana Kataria", - "author_inst": "Boston Medical Center" + "author_name": "Mark Gabbay", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Nicole Eichert", + "author_inst": "Perspectum Ltd" + }, + { + "author_name": "Sofia Mouchti", + "author_inst": "Perspectum Ltd" + }, + { + "author_name": "Michele Pansini", + "author_inst": "Perspectum Ltd" + }, + { + "author_name": "Adriana Roca-Fernandez", + "author_inst": "Perspectum Diagnostics" + }, + { + "author_name": "Helena Thomaides-Brears", + "author_inst": "Perspectum Ltd" + }, + { + "author_name": "Matt Kelly", + "author_inst": "Perspectum Ltd" + }, + { + "author_name": "Matthew Robson", + "author_inst": "Perspectum Ltd" + }, + { + "author_name": "Lyth Hishmeh", + "author_inst": "Long COVID SoS" + }, + { + "author_name": "Emily Attree", + "author_inst": "UKDoctors#Longcovid" + }, + { + "author_name": "Melissa J Heightman", + "author_inst": "UCLH" + }, + { + "author_name": "Rajarshi Banerjee", + "author_inst": "Perspectum Ltd" + }, + { + "author_name": "Amitava Banerjee", + "author_inst": "University College London" } ], "version": "1", @@ -329573,47 +328940,51 @@ "category": "neurology" }, { - "rel_doi": "10.1101/2022.03.19.22272575", - "rel_title": "Breakthrough Covid-19 cases despite tixagevimab and cilgavimab (Evusheld\u2122) prophylaxis in kidney transplant recipients", - "rel_date": "2022-03-19", + "rel_doi": "10.1101/2022.03.17.22272555", + "rel_title": "Relative effectiveness of booster vs. 2-dose mRNA Covid-19 vaccination in the Veterans Health Administration: Self-controlled risk interval analysis", + "rel_date": "2022-03-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.19.22272575", - "rel_abs": "While the combination of casirivimab-imdevimab (Ronapreve Roche Regeneron) has been shown to confer satisfactory protection against the delta variant kidney transplant recipients (KTRs) with COVID-19, it has limited neutralizing activity against the current variants of concern (Omicron BA.1, BA.1.1 and BA.2). In contrast, cilgavimab-tixagevimab combination (Evusheld, Astra Zeneca) retains a partial neutralizing activity against omicron in vitro. We examined whether preexposure prophylaxis with Evusheld can effectively protect kidney transplant recipients (KTRs) against the Omicron variant.\n\nOf the 416 KTRs who received intramuscular prophylactic injections of Evusheld (150 mg tixagevimab and 150 mg cilgavimab), 39 (9.4%) developed COVID-19. With the exception of one patient, all KTRs were symptomatic. Hospitalization and admission to an intensive care unit were required for 14 (35.9%) and three patients, respectively. Two KTRs died of COVID-19-related acute respiratory distress syndrome. SARS-CoV-2 sequencing was carried out in 15 cases (BA.1, n = 5; BA.1.1, n = 9; BA.2, n=1). Viral neutralizing activity of the serum against BA.1 variant was negative in the 12 tested patients, suggesting that this prophylaxis strategy provides insufficient protection against this variant of concern.\n\nPreexposure prophylaxis with Evusheld does not adequately protect KTRs against Omicron. Further clarification of the optimal dosing can assist in our understanding of how best to harness its protective potential.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.17.22272555", + "rel_abs": "ImportancePrevious studies have analyzed effectiveness of booster mRNA Covid-19 vaccination and compared it with 2-dose primary series for both Delta and Omicron variants. Observational studies that estimate effectiveness by comparing outcomes among vaccinated and unvaccinated individuals may suffer from residual confounding and exposure misclassification.\n\nObjectiveTo estimate relative effectiveness of booster vaccination versus the 2-dose primary series with self-controlled study design\n\nDesign, Setting and ParticipantsWe used the Veterans Health Administration (VHA) Corporate Data Warehouse to identify U.S. Veterans enrolled in care [≥]2 years who received the 2-dose primary mRNA Covid-19 vaccine series and a mRNA Covid-19 booster following expanded recommendation for booster vaccination, and who had a positive SARS-CoV-2 test during the Delta (9/23/2021-11/30/2021) or Omicron (1/1/22-3/1/22) predominant period. Among them, we conducted a self-controlled risk interval (SCRI) analysis to compare odds of SARS-CoV-2 infection during a booster exposure interval versus a control interval.\n\nExposurescontrol interval (days 4-6 post-booster vaccination, presumably prior to gain of booster immunity), and booster exposure interval (days 14-16 post-booster vaccination, presumably following gain of booster immunity)\n\nOutcomes and MeasuresPositive PCR or antigen SARS-CoV-2 test. Separately for Delta and Omicron periods, we used conditional logistic regression to calculate odds ratios (OR) of a positive test for the booster versus control interval and calculated relative effectiveness of booster versus 2-dose primary series as (1-OR)*100. The SCRI approach implicitly controlled for time-fixed confounders.\n\nResultsWe found 42 individuals with a positive SARS-CoV-2 test in the control interval and 14 in the booster exposure interval during Delta period, and 137 and 66, respectively, in Omicron period. For the booster versus 2-dose primary series, the odds of infection were 70% (95%CI: 42%, 84%) lower during the Delta period and 56% (95%CI: 38%, 67%) lower during Omicron. Results were similar for ages <65 and [≥]65 years in the Omicron period. In sensitivity analyses among those with prior Covid-19 history, and age stratification, ORs were similar to the main analysis.\n\nConclusionsBooster vaccination was more effective relative to a 2-dose primary series, the relative effectiveness was consistent across age groups and was higher during the Delta predominant period than during the Omicron period.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Ilies Benotmane", - "author_inst": "Hopitaux universitaires de Strasbourg" + "author_name": "Caroline Korves", + "author_inst": "White River Junction Veterans Affairs Medical Center, White River Junction, VT" }, { - "author_name": "Aur\u00e9lie Velay", - "author_inst": "Hopitaux universitaires de Strasbourg" + "author_name": "Hector Izurieta", + "author_inst": "Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, United States Food and Drug Administration, White Oak, MD" }, { - "author_name": "Gabriela Gautier-Vargas", - "author_inst": "Hopitaux universitaires de Strasbourg" + "author_name": "Jeremy Smith", + "author_inst": "White River Junction Veterans Affairs Medical Center, White River Junction, VT" }, { - "author_name": "J\u00e9r\u00f4me Olagne", - "author_inst": "Hopitaux universitaires de Strasbourg" + "author_name": "Gabrielle M Zwain", + "author_inst": "White River Junction Veterans Affairs Medical Center, White River Junction, VT" }, { - "author_name": "Samira Fafi-Kremer", - "author_inst": "Hopitaux universitaires de Strasbourg" + "author_name": "Ethan I Powell", + "author_inst": "White River Junction Veterans Affairs Medical Center, White River Junction, VT" }, { - "author_name": "Olivier Thaunat", - "author_inst": "CHU de Lyon" + "author_name": "Abirami Balajee", + "author_inst": "White River Junction Veterans Affairs Medical Center, White River Junction, VT" }, { - "author_name": "Sophie Caillard", - "author_inst": "Hopitaux Universitaires de Strasbourg" + "author_name": "Kathryn Ryder", + "author_inst": "Veterans Affairs Pacific Island Health Care" + }, + { + "author_name": "Yinong Young-Xu", + "author_inst": "White River Junction Veterans Affairs Medical Center, White River Junction, VT" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.03.16.22272527", @@ -331527,35 +330898,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.03.16.22272463", - "rel_title": "Examining Drivers of COVID-19 Vaccine Hesitancy in Ghana: The Roles of Political Allegiance, Misinformation Beliefs, and Sociodemographic Factors", + "rel_doi": "10.1101/2022.03.16.22272485", + "rel_title": "Pride and adversity among nurses and physicians during the pandemic in two US healthcare systems: a mixed methods analysis", "rel_date": "2022-03-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.16.22272463", - "rel_abs": "The vast majority of people in the world who are unvaccinated against COVID-19 reside in LMIC countries in sub-Saharan Africa. This includes Ghana, where only 15.9% of the country are fully vaccinated as of April 2022. A key factor negatively impacting vaccination campaigns is vaccine hesitancy, defined as the delay in the acceptance, or blunt refusal, of vaccines. Four online cross-sectional surveys of Ghanaian citizens were conducted in August 2020 (N = 3048), March 2021 (N = 1558), June 2021 (N = 1295), and February 2022 (N = 424) to observe temporal trends of vaccine hesitancy in Ghana, and to examine key groups associated with hesitancy. Overall hesitancy decreased from 36.8% (95% CI: 35.1%-38.5%) in August 2020 to 17.2% (95% CI: 15.3%-19.1%) in March 2021. However, hesitancy increased to 23.8% (95% CI: 21.5%-26.1%) in June 2021, and then again to 52.2% (95% CI: 47.4%-57.0%) in February 2022. Key reasons included not having enough vaccine-related information (50.6%) and concerns over vaccine safety (32.0%). Hesitant groups included Christians, urban dwellers, opposition political party voters, people with more years of education, females, people who received COVID-19 information from internet sources, and people who expressed uncertainty about COVID-19 misinformation beliefs.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.16.22272485", + "rel_abs": "Our aims were to examine themes of the most difficult or distressing events reported by healthcare workers during the first wave of COVID-19 pandemic in two US health care systems in order to identify common themes and to relate them to both behavioral theory and measures of anxiety and depression.\n\nWe conducted a cross-sectional survey during the early phases of the COIVD-19 pandemic in the US. We measured symptoms of anxiety and depression separately, captured demographics, and asked two open-ended questions regarding events that were the most difficult or stressful, and reinforced pride. The open-end questions were independently coded into themes developed by the authors and mapped to factors related to fostering well-being according to the Self-Determination Theory.\n\nWe recruited 874 nurses and 248 physicians. About a half shared their most distressing experiences as well as those experiences they were most proud of related to their professions. Themes that emerged from these narratives were congruent with prediction of Self-Determination theory that autonomy-supportive experiences will foster pride, while autonomy-thwarting experiences will cause distress. Those who reported distressful events were more anxious and depressed compared to those who did not. Among those who reported incidences that reinforced pride in the profession, depression was rarer compared to those who did not. These trends were evident after allowing for medical history and other covariates in logistic regressions.\n\nCausal claims from our analysis should be made with caution due to the research design, a cross-sectional study design. Understanding of perceptions of the pandemic by nurses and physicians may help identify sources of distress and means of reinforcing pride in the professions, thereby helping nurses and physicians cope with disasters, and shape workplace policies during disasters that foster well-being among first responders.\n\nNo Patient or Public Contribution: We studied physicians and nurses themselves.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Ken Brackstone", - "author_inst": "University of Southampton" - }, - { - "author_name": "Kirchuffs Atengble", - "author_inst": "PACKS Africa" - }, - { - "author_name": "Michael G Head", - "author_inst": "University of Southampton" + "author_name": "Igor Burstyn", + "author_inst": "Dornsife School of Public Health, Drexel University" }, { - "author_name": "Laud A Boateng", - "author_inst": "University of Southampton" + "author_name": "Karyn Holt", + "author_inst": "School of Nursing, the University of Nevada Las Vegas, Las Vegas, NV, USA" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2022.03.14.22272342", @@ -333221,71 +332584,39 @@ "category": "rheumatology" }, { - "rel_doi": "10.1101/2022.03.15.484448", - "rel_title": "Pulmonary lesions following inoculation with the SARS-CoV-2 Omicron BA.1 (B.1.1.529) variant in Syrian golden hamsters", + "rel_doi": "10.1101/2022.03.14.22272351", + "rel_title": "Super-spreaders of novel coronaviruses that cause SARS, MERS and COVID-19 : A systematic review", "rel_date": "2022-03-15", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.15.484448", - "rel_abs": "The Omicron BA.1 (B.1.1.529) SARS-CoV-2 variant is characterized by a high number of mutations in the viral genome, associated with immune-escape and increased viral spread. It remains unclear whether milder COVID-19 disease progression observed after infection with Omicron BA.1 in humans is due to reduced pathogenicity of the virus or due to pre-existing immunity from vaccination or previous infection. Here, we inoculated hamsters with Omicron BA.1 to evaluate pathogenicity and kinetics of viral shedding, compared to Delta (B.1.617.2) and to animals re-challenged with Omicron BA.1 after previous SARS-CoV-2 614G infection. Omicron BA.1 infected animals showed reduced clinical signs, pathological changes, and viral shedding, compared to Delta-infected animals, but still showed gross- and histopathological evidence of pneumonia. Pre-existing immunity reduced viral shedding and protected against pneumonia. Our data indicate that the observed decrease of disease severity is in part due to intrinsic properties of the Omicron BA.1 variant.", - "rel_num_authors": 13, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.14.22272351", + "rel_abs": "OBJECTIVEMost index cases with novel coronavirus infections transmit disease to just 1 or 2 other individuals, but some individuals super-spread - they are infection sources for many secondary cases. Understanding common factors that super-spreaders may share could inform outbreak models.\n\nMETHODSWe conducted a comprehensive search in MEDLINE, Scopus and preprint servers to identify studies about persons who were each documented as transmitting SARS, MERS or COVID-19 to at least nine other persons. We extracted data from and applied quality assessment to eligible published scientific articles about super-spreaders to describe them demographically: by age, sex, location, occupation, activities, symptom severity, any underlying conditions and disease outcome. We included scientific reports published by mid June 2021.\n\nRESULTSThe completeness of data reporting was often limited, which meant we could not identify traits such as patient age, sex, occupation, etc. Where demographic information was available, for these coronavirus diseases, the most typical super-spreader was a male age 40+. Most SARS or MERS super-spreaders were very symptomatic and died in hospital settings. In contrast, COVID-19 super-spreaders often had a very mild disease course and most COVID-19 super-spreading happened in community settings.\n\nCONCLUSIONAlthough SARS and MERS super-spreaders were often symptomatic, middle- or older-age adults who had a high mortality rate, COVID-19 super-spreaders often had a mild disease course and were documented to be any adult age (from 18 to 91 years old). More outbreak reports should be published with anonymised but useful demographic information to improve understanding of super-spreading, super-spreaders, and the settings that super-spreading happens in.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Melanie Rissmann", - "author_inst": "Erasmus Medical Center" - }, - { - "author_name": "Danny Noack", - "author_inst": "Erasmus Medical Center" - }, - { - "author_name": "Debby van Riel", - "author_inst": "Erasmus Medical Center" - }, - { - "author_name": "Katharina S. Schmitz", - "author_inst": "Erasmus Medical Center" - }, - { - "author_name": "Rory Dylan de Vries", - "author_inst": "Erasmus Medical Center" - }, - { - "author_name": "Peter van Run", - "author_inst": "Erasmus Medical Center" - }, - { - "author_name": "Mart Matthias Lamers", - "author_inst": "Erasmus Medical Center" - }, - { - "author_name": "Corine GeurtsvanKessel", - "author_inst": "Erasmus Medical Center" - }, - { - "author_name": "Marion Koopmans", - "author_inst": "Erasmus Medical Center" + "author_name": "Julii Suzanne Brainard", + "author_inst": "University of East Anglia" }, { - "author_name": "Ron Fouchier", - "author_inst": "Erasmus Medical Center" + "author_name": "Natalia R. Jones", + "author_inst": "University of East Anglia" }, { - "author_name": "Thijs Kuiken", - "author_inst": "Erasmus Medical Center" + "author_name": "Florence Harrison", + "author_inst": "University of East Anglia" }, { - "author_name": "Bart Haagmans", - "author_inst": "Erasmus Medical Center" + "author_name": "Charlotte C Hammer", + "author_inst": "Downing College, Cambridge" }, { - "author_name": "Barry Rockx", - "author_inst": "Erasmus Medical Center" + "author_name": "Iain R. Lake", + "author_inst": "University of East Anglia" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.03.14.22272368", @@ -335075,43 +334406,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.03.10.22272097", - "rel_title": "Time-Varying Death Risk After SARS-CoV-2-Infection in Swedish Long-Term Care Facilities", + "rel_doi": "10.1101/2022.03.10.22272213", + "rel_title": "Cov2clusters: genomic clustering of SARS-CoV-2 sequences", "rel_date": "2022-03-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.10.22272097", - "rel_abs": "BackgroundSARS-CoV-2 confers high risk of short-term death in residents of long-term care (LTC) facilities, but longer-term risk among survivors is unclear.\n\nMethodsWe extended the follow-up period of a previous, propensity score-matched retrospective cohort study based on the Swedish Senior Alert register. N=3731 LTC residents with documented SARS-CoV-2 until 15 September 2020 were matched to 3731 uninfected controls using time-dependent propensity scores on age, sex, health status, comorbidities, and prescription medications. In a sensitivity analysis, matching included also geographical region and Senior Alert registration time. The outcome was all-cause mortality over 8 months (until October 24, 2020). The absolute risk of death was examined using Kaplan-Meier plots. Hazard ratios (HR) for death over time were estimated using flexible parametric models with restricted cubic splines. Cox regression was used to estimate HRs and 95% confidence intervals (CIs) in 30-day intervals of follow-up until 210 days.\n\nResultsThe median age was 87 years and 65% were women. Excess mortality was highest 5 days after documented infection (HR 19.1, 95% CI, 14.6-24.8), after which excess mortality decreased. From the second month onwards, mortality rate became lower in infected residents than controls. The HR for death during days 61-210 of follow-up was 0.41 in the main analysis (95% CI, 0.34-0.50) and 0.76 (95% CI, 0.62-0.93) in the sensitivity analysis. Median survival of uninfected controls was 1.6 years, which was much lower than the national life expectancy in Sweden at age 87 (5.05 years in men, 6.07 years in women).\n\nConclusionsNo excess mortality was observed in LTC residents who survived the acute SARS-CoV-2 infection. Life expectancy of uninfected residents was much lower than that of the general population of the same age and sex. This suggests that LTC resident status should be accounted for in years-of-life-lost estimates for COVID-19 burden of disease calculations.\n\nImpact statementWe certify that this work is novel. This research adds to the literature by showing there was no excess mortality observed in long-term care facility residents who survived the acute SARS-CoV-2 infection, and that life expectancy of uninfected residents was much lower than that of the general population of same age and sex. This has major repercussions for estimation of years of life lost in infected long term care facility residents.\n\nKey pointsO_LISARS-CoV-2 infection sharply increased mortality risk among residents of long-term care (LTC) facilities in the first month.\nC_LIO_LIAfter the first month, the mortality risk in infected residents rapidly returned to baseline and dropped below the mortality risk of uninfected controls, where it remained lower for 8 months of follow-up.\nC_LIO_LIMedian survival of uninfected controls was 1.6 years, which was much lower than national life expectancy in Sweden at age 87.\nC_LI\n\nWhy does this matter?O_LIWhereas LTC residents who recover from SARS-CoV-2 infection may be concerned about having residual debilitation caused by the infection, we found no excess mortality was in those who survived the acute infection.\nC_LIO_LIBecause life expectancy of uninfected residents was much lower than that of the general population of same age and sex, LTC resident status should be accounted for in estimations of years of life lost.\nC_LI", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.10.22272213", + "rel_abs": "BackgroundThe COVID-19 pandemic remains a global public health concern. Advances in sequencing technologies has allowed for high numbers of SARS-CoV-2 whole genome sequence (WGS) data and rapid sharing of sequences through global repositories to enable almost real-time genomic analysis of the pathogen. WGS data has been used previously to group genetically similar viral pathogens to reveal evidence of transmission, including methods that identify distinct clusters on a phylogenetic tree. Identifying clusters of linked cases can aid in the regional surveillance and management of the disease. In this study, we present a novel method for producing stable genomic clusters of SARS-CoV-2 cases, cov2clusters, and compare the sensitivity and stability of our approach to previous methods used for phylogenetic clustering using real-world SARS-CoV-2 sequence data obtained from British Columbia, Canada,\n\nResultsWe found that cov2clusters produced more stable clusters than previously used phylogenetic clustering methods when adding sequence data through time, mimicking an increase in sequence data through the pandemic. Our method also showed high sensitivity when compared to epidemiologically informed clusters.\n\nConclusionsOur new approach allows for the identification of stable clusters of SARS-CoV-2 from WGS data. Producing high-resolution SARS-CoV-2 clusters from sequence data alone can a challenge and, where possible, both genomic and epidemiological data should be used in combination.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Marcel Ballin", - "author_inst": "Department of Community Medicine and Rehabilitation, Unit of Geriatric Medicine, Ume\u00e5 University" + "author_name": "Benjamin Sobkowiak", + "author_inst": "Simon Fraser University" }, { - "author_name": "John P.A Ioannidis", - "author_inst": "Department of Medicine, Stanford University School of Medicine, Department of Epidemiology and Population Health, Stanford University School of Medicine" + "author_name": "Kimia Kamelian", + "author_inst": "British Columbia Centre for Disease Control" }, { - "author_name": "Jonathan Bergman", - "author_inst": "Department of Community Medicine and Rehabilitation, Unit of Geriatric Medicine, Ume\u00e5 University" + "author_name": "James Zlosnik", + "author_inst": "British Columbia Centre for Disease Control" }, { - "author_name": "Miia Kivipelto", - "author_inst": "Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Medical Unit" + "author_name": "John Tyson", + "author_inst": "British Columbia Centre for Disease Control" }, { - "author_name": "Anna Nordstr\u00f6m", - "author_inst": "Department of Community Medicine and Rehabilitation, Unit of Geriatric Medicine, Department of Public Health and Clinical Medicine, Section of Sustainable Healt" + "author_name": "Anders Gon\u00e7alves da Silva", + "author_inst": "University of Melbourne" }, { - "author_name": "Peter Nordstr\u00f6m", - "author_inst": "Department of Community Medicine and Rehabilitation, Unit of Geriatric Medicine, Ume\u00e5 University," + "author_name": "Linda Hoang", + "author_inst": "BC Centre for Disease Control" + }, + { + "author_name": "Natalie Prystajecky", + "author_inst": "University of British Columbia" + }, + { + "author_name": "Caroline Colijn", + "author_inst": "Simon Fraser University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.03.10.22272123", @@ -336925,63 +336264,39 @@ "category": "pharmacology and therapeutics" }, { - "rel_doi": "10.1101/2022.03.11.22271887", - "rel_title": "Different Covid-19 Outcomes Among Systemic Rheumatic Diseases: A Nation-wide Cohort Study", + "rel_doi": "10.1101/2022.03.04.22271934", + "rel_title": "Prevention of SARS-CoV-2 airborne transmission in a workplace based on CO2 sensor network", "rel_date": "2022-03-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.11.22271887", - "rel_abs": "BackgroundNationwide data at a country level on Covid-19 in unvaccinated patients with rheumatoid arthritis (RA), ankylosing spondylitis (AS), psoriatic arthritis (PsA), systemic lupus erythematosus (SLE) and systemic sclerosis (SSc) are scarce.\n\nMethodsBy interlinking data from national electronic registries, covering nearly 99% of the Greek population (approximately 11,000,000), between March 2020 and February 2021, when vaccination became available, we recorded confirmed infections and Covid-19-associated hospitalizations and deaths in essentially all adult patients with RA, AS, PsA, SLE, and SSc under treatment (n=74,970, median age of 67.5, 51.2, 58.1, 56.2, 62.2 years, respectively) and in individually matched (1:5) on age, sex, and region of domicile random comparators from the general population.\n\nResultsBinary logistic regression analysis after adjusting for age, sex and biologic agents, revealed that RA, PsA, SLE and SSc, but not AS patients, had significantly higher risk of infection (by 43%, 25%, 20% and 49%, respectively), and hospitalization for Covid-19 (by 81%, 56%, 94%, and 111%, respectively), possibly due, at least in part, to increased testing and lower threshold for admission. Patients with RA and SSc had indeed higher Covid-19 associated mortality rates [OR:1.86 (95% CI 1.37 to 2.52) and OR:2.90 (95% CI 0.97 to 8.67), respectively] compared to the general population. Each additional year of age increased the risk of hospitalization for Covid-19 by 3% (OR 1.030, 95% CI: 1.028 to 1.034) and the risk of Covid-19 related death by 8% (OR 1.08, 95% CI: 1.07 to 1.09), independently of gender, systemic rheumatic disease, and biologic agents. A further analysis using AS patients as the reference category, adjusting again for age, sex and use of biologic agents showed that patients with SSc had increased mortality (OR: 6.90, 95% CI: 1.41 to 33.72), followed by SLE (OR: 4.05 95% CI: 0.96 to 17.12) and RA patients (OR: 3.65, 95% CI: 1.06 to 12.54), whereas PsA patients had comparable mortality risk with AS patients.\n\nConclusionComparing to the general population, Covid-19 may have a more severe impact in real-world patients with systemic rheumatic disease. Covid-19 related mortality is increased in subgroups of patients with specific rheumatic diseases, especially in older ones, underscoring the need for priority vaccination policies and access to targeted treatments.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.04.22271934", + "rel_abs": "We measured the compartmental air change per hour (ACH) using a CO2 sensor network in an office space where a cluster of COVID-19 infections attributed to aerosol transmission occurred. Generalized linear mixed models and dynamic time warping were used for a time series data analysis, and the results indicated that the ventilation conditions were poor at the time of the cluster outbreak, and that the low ACH in the room likely contributed to the outbreak. In addition, the adverse effects of inappropriate partitions and the effectiveness of ventilation improvements were investigated in detail. ACH of less than 2 /h was considered a main contributor for the formation of the COVID-19 cluster in the studied facility.\n\nPractical ImplicationsA systematic method for measuring and evaluating indoor ventilation to prevent the spread of infectious diseases caused by aerosols is presented. Ventilation bias caused by ventilation pathways and inappropriate use of plastic sheeting can be detected by a CO2 sensor network and time series data analysis. Estimated ventilation rate will be a good index to suppress the formation of the COVID-19 cluster.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Vasiliki-Kalliopi Bournia", - "author_inst": "Joint Academic Rheumatology Program, National and Kapodistrian University of Athens, Medical School, Athens, Greece" - }, - { - "author_name": "George Fragoulis", - "author_inst": "Joint Academic Rheumatology Program, National and Kapodistrian University of Athens, Medical School, Athens, Greece" - }, - { - "author_name": "Panagiota Mitrou", - "author_inst": "Hellenic Ministry of Health, Athens, Greece" - }, - { - "author_name": "Konstantinos Mathioudakis", - "author_inst": "IDIKA SA-e-Government Center for Social Security Services, Athens, Greece" - }, - { - "author_name": "Anastasios Tsolakidis", - "author_inst": "IDIKA SA-e-Government Center for Social Security Services, Athens, Greece" - }, - { - "author_name": "George Konstantonis", - "author_inst": "Joint Academic Rheumatology Program, National and Kapodistrian University of Athens, Medical School, Athens, Greece" - }, - { - "author_name": "Ioulia Tseti", - "author_inst": "Uni-Pharma S.A., 14564, Kifissia, Greece" + "author_name": "Shinji Yokogawa", + "author_inst": "The University of Electro-Communications" }, { - "author_name": "Georgia Vourli", - "author_inst": "Department of Hygiene Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece" + "author_name": "Yo Ishigaki", + "author_inst": "University of Electro-Communications" }, { - "author_name": "Maria G Tektonidou", - "author_inst": "Joint Academic Rheumatology Program, National and Kapodistrian University of Athens, Medical School, Athens, Greece" + "author_name": "Hiroko Kitamura", + "author_inst": "University of Occupational and Environmental Health" }, { - "author_name": "Dimitrios Paraskevis", - "author_inst": "Department of Hygiene Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece" + "author_name": "Akira Saito", + "author_inst": "Miyagi Anti-Tuberculosis Association" }, { - "author_name": "Petros P Sfikakis", - "author_inst": "Joint Academic Rheumatology Program, National and Kapodistrian University of Athens, Medical School, Athens, Greece" + "author_name": "Yuto Kawauchi", + "author_inst": "University of Electro-communications" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "rheumatology" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2022.03.09.22272113", @@ -339307,35 +338622,27 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.03.09.483703", - "rel_title": "SARS-CoV-2 Omicron variant is more stable than the ancestral strain on various surfaces", + "rel_doi": "10.1101/2022.03.10.483726", + "rel_title": "More or less deadly? A mathematical model that predicts SARS-CoV-2 evolutionary direction.", "rel_date": "2022-03-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.09.483703", - "rel_abs": "The Omicron BA.1 SARS-CoV-2 variant of concern spreads quickly around the world and outcompetes other circulating strains. We examined the stability of this SARS-CoV-2 variant on various surfaces and revealed that the Omicron variant is more stable than its ancestral strain on smooth and porous surfaces.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.10.483726", + "rel_abs": "SARS-CoV-2 has caused tremendous deaths world wild. It is of great value to predict the evolutionary direction of SARS-CoV-2. In this paper, we proposed a novel mathematical model that could predict the evolutionary trend of SARS-CoV-2. We focus on the mutational effects on viral assembly capacity. A robust coarse-grained mathematical model is constructed to simulate the virus dynamics in the host body. Both virulence and transmissibility can be quantified in this model. The relationship between virulence and transmissibility can be simulated. A delicate equilibrium point that optimizing the transmissibility can be numerically obtained. Based on this model, we predict the virulence of SARS-CoV-2 might further decrease, accompanied by an enhancement of transmissibility. However, this trend is not continuous; its virulence will not disappear but remains at a relatively stable range. We can also explain the cross-species transmission phenomenon of certain RNA virus based on this model. A small-scale model which simulates the virus packing process is also proposed. It can be explained why a small number of mutations would lead to a significant divergence in clinical performance, both in the overall particle formation quantity and virulence. This research provides a mathematical attempt to elucidate the evolutionary driving force in RNA virus evolution.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Alex Chin", - "author_inst": "The University of Hong Kong" - }, - { - "author_name": "Alison Lai", - "author_inst": "The University of Hong Kong" - }, - { - "author_name": "Malik Peiris", - "author_inst": "The University of Hong Kong" + "author_name": "Zhaobin Xu", + "author_inst": "Dezhou University" }, { - "author_name": "Leo Poon", - "author_inst": "The University of Hong Kong" + "author_name": "Qiangcheng Zeng", + "author_inst": "Dezhou University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "new results", - "category": "microbiology" + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2022.03.10.483790", @@ -341353,43 +340660,135 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.03.07.481737", - "rel_title": "Anti-spike antibody response to natural infection with SARS-CoV-2 and its activity against emerging variants", + "rel_doi": "10.1101/2022.03.08.481609", + "rel_title": "The origins and molecular evolution of SARS-CoV-2 lineage B.1.1.7 in the UK", "rel_date": "2022-03-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.07.481737", - "rel_abs": "The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has substantially impacted human health globally. Spike-specific antibody response plays a major role in protection against SARS-CoV-2. Here, we demonstrated that acute SARS-CoV-2 infection elicits rapid and robust spike-binding and ACE2-blocking antibody responses, which wane approximately 11 months after infection. Serological responses were found to be correlated with the frequency of spike-specific memory B cell responses to natural infections. Further, significantly higher spike-binding, ACE2-blocking, and memory B cell responses were detected in patients with fever and pneumonia. Spike-specific antibody responses were found to be greatly affected by spike mutations in emerging variants, especially the Beta and Omicron variants. These results warrant continued surveillance of spike-specific antibody responses to natural infections and highlight the importance of maintaining functional anti-spike antibodies through immunization.\n\nImportanceAs spike protein-specific antibody responses play a major role in protection against SARS-CoV-2, we examined the spike-binding and ACE2-blocking antibody responses in SARS-CoV-2 infection at different time points. We found robust responses following acute infection, which waned approximately 11 months after infection. Further, the serological responses were correlated with the frequency of spike-specific memory B cell responses to natural infections. Patients with fever and pneumonia showed significantly stronger spike-binding, ACE2-blocking antibody, and memory B cell responses. Moreover, the spike-specific antibody responses were substantially affected by the emerging variants, especially the Beta and Omicron variants. These results warrant continued surveillance of spike-specific antibody responses to natural infections and highlight the importance of maintaining functional anti-spike antibodies through immunization.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.08.481609", + "rel_abs": "The first SARS-CoV-2 variant of concern (VOC) to be designated was lineage B.1.1.7, later labelled by the World Health Organisation (WHO) as Alpha. Originating in early Autumn but discovered in December 2020, it spread rapidly and caused large waves of infections worldwide. The Alpha variant is notable for being defined by a long ancestral phylogenetic branch with an increased evolutionary rate, along which only two sequences have been sampled. Alpha genomes comprise a well-supported monophyletic clade within which the evolutionary rate is more typical of SARS-CoV-2. The Alpha epidemic continued to grow despite the continued restrictions on social mixing across the UK, and the imposition of new restrictions, in particular the English national lockdown in November 2020. While these interventions succeeded in reducing the absolute number of cases, the impact of these non-pharmaceutical interventions was predominantly to drive the decline of the SARS-CoV-2 lineages which preceded Alpha. We investigate the only two sampled sequences that fall on the branch ancestral to Alpha. We find that one is likely to be a true intermediate sequence, providing information about the order of mutational events that led to Alpha. We explore alternate hypotheses that can explain how Alpha acquired a large number of mutations yet remained largely unobserved in a region of high genomic surveillance: an under-sampled geographical location, a non-human animal population, or a chronically-infected individual. We conclude that the last hypothesis provides the best explanation of the observed behaviour and dynamics of the variant, although we find that the individual need not be immunocompromised, as persistently-infected immunocompetent hosts also display a higher within-host rate of evolution. Finally, we compare the ancestral branches and mutation profiles of other VOCs to each other, and identify that Delta appears to be an outlier both in terms of the genomic locations of its defining mutations, and its lack of rapid evolutionary rate on the ancestral branch. As new variants, such as Omicron, continue to evolve (potentially through similar mechanisms) it remains important to investigate the origins of other variants to identify ways to potentially disrupt their evolution and emergence.", + "rel_num_authors": 29, "rel_authors": [ { - "author_name": "Cheng-Pin Chen", - "author_inst": "Department of Internal Medicine, Taoyuan General Hospital" + "author_name": "Verity Hill", + "author_inst": "The University of Edinburgh" }, { - "author_name": "Shin-Ru Shih", - "author_inst": "Chang Gung University, Taoyuan, Taiwan" + "author_name": "Louis du Plessis", + "author_inst": "University of Oxford" }, { - "author_name": "Yi-Chun Lin", - "author_inst": "Taoyuan General Hospital, Ministry of Health and Welfare, Taiwan" + "author_name": "Thomas P Alexander Peacock", + "author_inst": "University College London (UCL)" }, { - "author_name": "Chien-Yu Cheng", - "author_inst": "Department of Internal Medicine, Taoyuan General Hospital" + "author_name": "Dinesh Aggarwal", + "author_inst": "University of Cambridge" }, { - "author_name": "Yhu-Chering Huang", - "author_inst": "Linkou Chang Gung Memorial Hospital" + "author_name": "Alessandro Carabelli", + "author_inst": "University of Cambridge" }, { - "author_name": "Shu-Hsing Cheng", - "author_inst": "Taoyuan General Hospital, Ministry of Health Welfare, Taoyuan; School of Public Health, College of Public Health and Nutrition, Taipei Medical University, Taipe" + "author_name": "Rachel Colquhoun", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Nicholas Ellaby", + "author_inst": "UK Health Security Agency" + }, + { + "author_name": "Eileen Gallagher", + "author_inst": "Uk Health Security Agency" + }, + { + "author_name": "Natalie Groves", + "author_inst": "UK Health Security Agency" + }, + { + "author_name": "Ben Jackson", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "JT McCrone", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Anna Price", + "author_inst": "Cardiff University" + }, + { + "author_name": "Theo Sanderson", + "author_inst": "Sanger Institute" + }, + { + "author_name": "Emily Scher", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Joel Alexander Southgate", + "author_inst": "Cardiff University" + }, + { + "author_name": "Erik Volz", + "author_inst": "Imperial College London" + }, + { + "author_name": "- The COVID-19 genomics UK (COG-UK) consortium", + "author_inst": "-" + }, + { + "author_name": "Wendy S Barclay", + "author_inst": "Imperial College London" + }, + { + "author_name": "Jeffrey Barrett", + "author_inst": "Sanger Institute" + }, + { + "author_name": "Meera Chand", + "author_inst": "UK Health Security Agency" + }, + { + "author_name": "Thomas R Connor", + "author_inst": "Cardiff University" + }, + { + "author_name": "Ian G. Goodfellow", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Ravindra K Gupta", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Ewan Harrison", + "author_inst": "Sanger Institute" + }, + { + "author_name": "Nicholas Loman", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Richard Myers", + "author_inst": "UK Health Security Agency" + }, + { + "author_name": "David L Robertson", + "author_inst": "University of Glasgow" + }, + { + "author_name": "Oliver Pybus", + "author_inst": "University of Oxford" + }, + { + "author_name": "Andrew Rambaut", + "author_inst": "University of Edinburgh" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "new results", - "category": "immunology" + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2022.03.08.483429", @@ -343315,27 +342714,39 @@ "category": "medical education" }, { - "rel_doi": "10.1101/2022.03.04.22270966", - "rel_title": "Social connections at work and mental health during the first wave of the COVID-19 pandemic: Evidence from employees in Germany", + "rel_doi": "10.1101/2022.03.04.22271915", + "rel_title": "Severity of SARS-CoV-2 Infection in Pregnancy in Ontario: A Matched Cohort Analysis", "rel_date": "2022-03-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.04.22270966", - "rel_abs": "Empirical evidence on the social and psychological impact of the COVID-19 pandemic in the workplace and the resulting consequences for the mental health of employees is still sparse. As a result, research on this subject is urgently needed to develop appropriate countermeasures. This study builds on Person-Environment fit theory to investigate social connections at work and mental health during the first wave of the COVID-19 pandemic. It analyses employees needs for social connections and how social connections affect different mental health measures. Survey data were collected in May 2020 in an online survey of employees across Germany and analysed using response surface analysis. Mental health was measured as positive mental health and mental health disorders. Social connections were measured as social support and social interactions. 507 employees participated in the survey and more than one third reported having less social support and social interaction at work than they desired (p < .001). This was associated with a decrease in mental health. In contrast, having more than the desired amount of social support was associated with a decrease and having more than the desired amount of social interaction with an increase in mental health. This study provides important early evidence on the impact of the first wave of the COVID-19 pandemic in the workplace. With it, we aim to stimulate further research in the field and provide early evidence on potential mental health consequences of social distancing measures - while also opening avenues to combat them.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.04.22271915", + "rel_abs": "BackgroundPregnancy represents a physiological state associated with increased vulnerability to severe outcomes from infectious diseases, both for the pregnant person and developing infant. The SARS-CoV-2 pandemic may have important health consequences for pregnant individuals, who may also be more reluctant than non-pregnant people to accept vaccination. We sought to estimate the degree to which increased severity of SARS-CoV-2 outcomes can be attributed to pregnancy.\n\nMethodsOur study made use of a population-based SARS-CoV-2 case file from Ontario, Canada. Due to both varying propensity to receive vaccination, and changes in dominant circulating viral strains over time, a time-matched cohort study was performed to evaluate the relative risk of severe illness in pregnant women with SARS-CoV-2 compared to other SARS-CoV-2 infected women of childbearing age (10 to 49 years old). Risk of severe SARS-CoV-2 outcomes (hospitalization or intensive care unit (ICU) admission) was evaluated in pregnant women and time-matched non-pregnant controls using multivariable conditional logistic regression.\n\nResultsCompared to the rest of the population, non-pregnant women of childbearing age had an elevated risk of infection (standardized morbidity ratio (SMR) 1.28), while risk of infection was reduced among pregnant women (SMR 0.43). After adjustment for age, comorbidity, healthcare worker status, vaccination, and infecting viral variant, pregnant women had a markedly elevated risk of hospitalization (adjusted OR 4.96, 95% CI 3.86 to 6.37) and ICU admission (adjusted OR 6.58, 95% CI 3.29 to 13.18). The relative increase in hospitalization risk associated with pregnancy was greater in women without comorbidities than in those with comorbidities (P for heterogeneity 0.004).\n\nInterpretationA time-matched cohort study suggests that while pregnant women may be at a decreased risk of infection relative to the rest of the population, their risk of severe illness is markedly elevated if infection occurs. Given the safety of SARS-CoV-2 vaccines in pregnancy, risk-benefit calculus strongly favours SARS-CoV-2 vaccination in pregnant women.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Jonas Breetzke", - "author_inst": "University of Hamburg: Universitat Hamburg" + "author_name": "Kiera Murison", + "author_inst": "University of Toronto" + }, + { + "author_name": "Alicia Grima", + "author_inst": "University of Toronto" + }, + { + "author_name": "Alison Simmons", + "author_inst": "University of Toronto" }, { - "author_name": "Eva-Maria Wild", - "author_inst": "University of Hamburg: Universitat Hamburg" + "author_name": "Ashleigh Tuite", + "author_inst": "University of Toronto" + }, + { + "author_name": "David Fisman", + "author_inst": "University of Toronto" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.03.04.22271890", @@ -345005,55 +344416,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.03.03.22271504", - "rel_title": "Precision recruitment for high-risk participants in a COVID-19 research study", + "rel_doi": "10.1101/2022.03.03.22271787", + "rel_title": "Association between COVID-19 Risk-Mitigation Behaviors and Specific Mental Disorders in Youth", "rel_date": "2022-03-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.03.22271504", - "rel_abs": "Studies for developing diagnostics and treatments for infectious diseases usually require observing the onset of infection during the study period. However, when the infection base rate incidence is low, the cohort size required to measure an effect becomes large, and recruitment becomes costly and prolonged. We describe an approach for reducing recruiting time and resources in a COVID-19 study by targeting recruitment to high-risk individuals. Our approach is based on direct and longitudinal connection with research participants and computes individual risk scores from individually permissioned data about socioeconomic and behavioural data, in combination with predicted local prevalence data. When we used these scores to recruit a balanced cohort of participants for a COVID-19 detection study, we obtained a 4-7-fold greater COVID-19 infection incidence compared with similar real-world study cohorts.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.03.22271787", + "rel_abs": "ImportanceAlthough studies of adults show that pre-existing mental disorders increase risk for COVID-19 infection and severity, there is limited information about this association among youth. Mental disorders in general as well as specific types of disorders may influence their ability to comply with risk-mitigation strategies to reduce COVID-19 infection and transmission.\n\nObjectiveTo examine associations between specific mental disorders and COVID-19 risk-mitigation practices among 314 female and 514 male youth.\n\nDesignYouth compliance (rated as \"Never,\" \"Sometimes,\" \"Often,\" or \"Very often/Always\") with risk mitigation was reported by parents on the CoRonavIruS Health Impact Survey (CRISIS) in January 2021. Responses were summarized using factor analysis of risk mitigation, and their associations with lifetime mental disorders (assessed via structured diagnostic interviews) were identified with linear regression analyses (adjusted for covariates). All analyses used R Project for Statistical Computing for Mac (v.4.0.5).\n\nSettingThe Healthy Brain Network (HBN) in New York City Participants. 314 female and 514 male youth (ages 5-21)\n\nMain Outcome(s) and Measure(s)COVID-19 risk mitigation behaviors among youth\n\nResultsA two-factor model was the best-fitting solution. Factor 1 (avoidance behaviors) included avoiding groups, indoor settings, and other peoples homes; avoidance was more likely among youth with any anxiety disorder (p=.01). Factor 2 (hygiene behaviors) included using hand sanitizer, washing hands, and maintaining social distance; practicing hygiene was less likely among youth with ADHD (combined type) (p=.02). Mask wearing, which did not load on either factor, was not associated with any mental health disorder.\n\nConclusion and RelevanceFindings suggest that education and monitoring of risk-mitigation strategies in certain subgroups of youth may reduce risk of exposure to COVID-19 and other contagious diseases. Additionally, they highlight the need for greater attention to vaccine prioritization for individuals with ADHD.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSAre mental disorders among youth associated with COVID-19 risk-mitigation behaviors?\n\nFindingsBased on the parent CoRonavIruS Health Impact Survey (CRISIS) of 314 females and 514 males aged 5-21, youth with anxiety disorders were more likely to avoid high-risk exposure settings, and those with ADHD (combined type) were less likely to follow hygiene practices. In contrast, mask wearing was not associated with youth mental disorders.\n\nMeaningSpecific types of disorders in youth may interfere with their ability to employ risk-mitigation strategies that may lead to greater susceptibility to COVID-19.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Aziz Mezlini", - "author_inst": "Evidation Health, Inc." - }, - { - "author_name": "Eamon Caddigan", - "author_inst": "Evidation Health, Inc." + "author_name": "Kevin Conway", + "author_inst": "National Institute of Mental Health" }, { - "author_name": "Allison Shapiro", - "author_inst": "Evidation Health, Inc." + "author_name": "Kriti Bhardwaj", + "author_inst": "Child Mind Institute" }, { - "author_name": "Ernesto Ramirez", - "author_inst": "Evidation Health, Inc." + "author_name": "Emmanuella Michel", + "author_inst": "National Institute of Mental Health" }, { - "author_name": "Helena Kondow-McConaghy", - "author_inst": "Oak Ridge Institute of Science and Education" + "author_name": "Diana Paksarian", + "author_inst": "National Institute of Mental Health, New York State Office of Mental Health" }, { - "author_name": "Justin Yang", - "author_inst": "Biomedical Advanced Research and Development Authority (BARDA), Office of the Assistant Secretary for Preparedness and Response (ASPR), U.S. Department of Healt" + "author_name": "Aki Nikolaidis", + "author_inst": "Child Mind Institute" }, { - "author_name": "Kerry DeMarco", - "author_inst": "Biomedical Advanced Research and Development Authority (BARDA), Office of the Assistant Secretary for Preparedness and Response (ASPR), U.S. Department of Healt" + "author_name": "Minji Kang", + "author_inst": "Child Mind Institute" }, { - "author_name": "Pejman Naraghi-Arani", - "author_inst": "Biomedical Advanced Research and Development Authority (BARDA), Office of the Assistant Secretary for Preparedness and Response (ASPR), U.S. Department of Healt" + "author_name": "Kathleen Ries Merikangas", + "author_inst": "National Institute of Mental Health" }, { - "author_name": "Luca Foschini", - "author_inst": "Evidation Health, Inc." + "author_name": "Michael Milham", + "author_inst": "Child Mind Institute" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2022.03.02.22271806", @@ -346627,221 +346034,149 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2022.02.24.22271475", - "rel_title": "Multicenter analysis of neutrophil extracellular trap dysregulation in adult and pediatric COVID-19", + "rel_doi": "10.1101/2022.03.02.22271623", + "rel_title": "Baricitinib in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial and updated meta-analysis", "rel_date": "2022-03-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.24.22271475", - "rel_abs": "Dysregulation in neutrophil extracellular trap (NET) formation and degradation may play a role in the pathogenesis and severity of COVID-19; however, its role in the pediatric manifestations of this disease including MIS-C and chilblain-like lesions (CLL), otherwise known as \"COVID toes\", remains unclear. Studying multinational cohorts, we found that, in CLL, NETs were significantly increased in serum and skin. There was geographic variability in the prevalence of increased NETs in MIS-C, in association with disease severity. MIS-C and CLL serum samples displayed decreased NET degradation ability, in association with C1q and G-actin or anti-NET antibodies, respectively, but not with genetic variants of DNases. In adult COVID-19, persistent elevations in NETs post-disease diagnosis were detected but did not occur in asymptomatic infection. COVID-19-affected adults displayed significant prevalence of impaired NET degradation, in association with anti-DNase1L3, G-actin, and specific disease manifestations, but not with genetic variants of DNases. NETs were detected in many organs of adult patients who died from COVID-19 complications. Infection with the Omicron variant was associated with decreased levels of NETs when compared to other SARS-CoV-2 strains. These data support a role for NETs in the pathogenesis and severity of COVID-19 in pediatric and adult patients.\n\nSummaryNET formation and degradation are dysregulated in pediatric and symptomatic adult patients with various complications of COVID-19, in association with disease severity. NET degradation impairments are multifactorial and associated with natural inhibitors of DNase 1, G-actin and anti-DNase1L3 and anti-NET antibodies. Infection with the Omicron variant is associated with decreased levels of NETs when compared to other SARS-CoV-2 strains.", - "rel_num_authors": 51, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.02.22271623", + "rel_abs": "BackgroundWe evaluated the use of baricitinib, a Janus kinase (JAK) 1/2 inhibitor, for the treatment of patients admitted to hospital because of COVID-19.\n\nMethodsThis randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple possible treatments in patients hospitalised for COVID-19. Eligible and consenting patients were randomly allocated (1:1) to either usual standard of care alone (usual care group) or usual care plus baricitinib 4 mg once daily by mouth for 10 days or until discharge if sooner (baricitinib group). The primary outcome was 28-day mortality assessed in the intention-to-treat population. A meta-analysis was conducted that included the results from the RECOVERY trial and all previous randomised controlled trials of baricitinib or other JAK inhibitor in patients hospitalised with COVID-19. The RECOVERY trial is registered with ISRCTN (50189673) and clinicaltrials.gov (NCT04381936).\n\nFindingsBetween 2 February 2021 and 29 December 2021, 8156 patients were randomly allocated to receive usual care plus baricitinib versus usual care alone. At randomisation, 95% of patients were receiving corticosteroids and 23% receiving tocilizumab (with planned use within the next 24 hours recorded for a further 9%). Overall, 513 (12%) of 4148 patients allocated to baricitinib versus 546 (14%) of 4008 patients allocated to usual care died within 28 days (age-adjusted rate ratio 0{middle dot}87; 95% CI 0{middle dot}77-0{middle dot}98; p=0{middle dot}026). This 13% proportional reduction in mortality was somewhat smaller than that seen in a meta-analysis of 8 previous trials of a JAK inhibitor (involving 3732 patients and 425 deaths) in which allocation to a JAK inhibitor was associated with a 43% proportional reduction in mortality (rate ratio 0.57; 95% CI 0.45-0.72). Including the results from RECOVERY into an updated meta-analysis of all 9 completed trials (involving 11,888 randomised patients and 1484 deaths) allocation to baricitinib or other JAK inhibitor was associated with a 20% proportional reduction in mortality (rate ratio 0.80; 95% CI 0.71-0.89; p<0.001). In RECOVERY, there was no significant excess in death or infection due to non-COVID-19 causes and no excess of thrombosis, or other safety outcomes.\n\nInterpretationIn patients hospitalised for COVID-19, baricitinib significantly reduced the risk of death but the size of benefit was somewhat smaller than that suggested by previous trials. The total randomised evidence to date suggests that JAK inhibitors (chiefly baricitinib) reduce mortality in patients hospitalised for COVID-19 by about one-fifth.\n\nFundingUK Research and Innovation (Medical Research Council) and National Institute of Health Research (Grant ref: MC_PC_19056).", + "rel_num_authors": 33, "rel_authors": [ { - "author_name": "Carmelo Carmona-Rivera", - "author_inst": "NIAMS" - }, - { - "author_name": "Yu Zhang", - "author_inst": "NIAID" - }, - { - "author_name": "Kerry Dobbs", - "author_inst": "NIAID" - }, - { - "author_name": "Tovah Markowitz", - "author_inst": "NIAID" - }, - { - "author_name": "Clifton Dalgard", - "author_inst": "USUHS" - }, - { - "author_name": "Andrew Oler", - "author_inst": "NIAID" - }, - { - "author_name": "Dillon Claybaugh", - "author_inst": "NIAMS" - }, - { - "author_name": "Deborah Draper", - "author_inst": "NIAID" - }, - { - "author_name": "Meng Truong", - "author_inst": "NIAID" - }, - { - "author_name": "Ottavi Delmonte", - "author_inst": "NIAID" - }, - { - "author_name": "Francesco Licciardi", - "author_inst": "University of Turin" - }, - { - "author_name": "Ugo Ramenghi", - "author_inst": "University of Turin" - }, - { - "author_name": "Nicoletta Crescenzio", - "author_inst": "University of Turin" - }, - { - "author_name": "Luisa Imberti", - "author_inst": "Spedali Civili di Brescia" - }, - { - "author_name": "Alessandra Sottini", - "author_inst": "Spedali Civili di Brescia" - }, - { - "author_name": "Virginia Quaresima", - "author_inst": "Spedali Civili di Brescia" - }, - { - "author_name": "Chiara Fiorini", - "author_inst": "Spedali Civili di Brescia" - }, - { - "author_name": "Valentina Discepolo", - "author_inst": "University of Naples Federico II" - }, - { - "author_name": "Andrea Lovecchio", - "author_inst": "University of Naples Federico II" + "author_name": "Peter W Horby", + "author_inst": "Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Alfredo Guarino", - "author_inst": "University of Naples Federico II" + "author_name": "Jonathan R Emberson", + "author_inst": "MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Luca Pierri", - "author_inst": "University of Naples Federico II" + "author_name": "Marion Mafham", + "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Andrea Catzola", - "author_inst": "University of NaplesFederico II" + "author_name": "Mark Campbell", + "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Andrea Biondi", - "author_inst": "University of Milano-Bicocca" + "author_name": "Leon Peto", + "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Paolo Bonfanti", - "author_inst": "University of Milano-Bicocca" + "author_name": "Guilherme Pessoa-Amorim", + "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Maria Cecilia Poli Harlowe", - "author_inst": "Universidad del Desarrollo" + "author_name": "Enti Spata", + "author_inst": "MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Yasmin Espinosa", - "author_inst": "Hospital Roberto del Rio" + "author_name": "Natalie Staplin", + "author_inst": "MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Camila Astudillo", - "author_inst": "Hospital Roberto del Rio" + "author_name": "Catherine Lowe", + "author_inst": "Liverpool University Hospitals NHS Foundation Trust" }, { - "author_name": "Emma rey-Jurado", - "author_inst": "Universidad del Desarrollo" + "author_name": "David R Chadwick", + "author_inst": "Centre for Clinical Infection, James Cook University Hospital, Middlesbrough, United Kingdom" }, { - "author_name": "Cecilia Vial", - "author_inst": "Universidad del Desarrollo" + "author_name": "Christopher Brightling", + "author_inst": "Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester, Leicester, United Kingdom" }, { - "author_name": "Javiera De la Cruz", - "author_inst": "Universidad del Desarrollo" + "author_name": "Richard Stewart", + "author_inst": "Milton Keynes University Hospital, Milton Keynes, United Kingdom" }, { - "author_name": "Ricardo Gonzalez", - "author_inst": "Hospital Exequiel Gonzalez Cortes" + "author_name": "Paul Collini", + "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust and University of Sheffield, Sheffield, United Kingdom" }, { - "author_name": "Cecilia Pinera", - "author_inst": "University of Chile" + "author_name": "Abdul Ashish", + "author_inst": "Wrightington, Wigan and Leigh Teaching Hospitals NHS Foundation Trust, Wigan, United Kingdom" }, { - "author_name": "Jacqueline Mays", - "author_inst": "NIDCR" + "author_name": "Christopher A Green", + "author_inst": "University Hospitals Birmingham NHS Foundation Trust" }, { - "author_name": "Ashley Ng", - "author_inst": "University of Wisconsin" + "author_name": "Benjamin Prudon", + "author_inst": "North Tees and Hartlepool NHS Foundation Trust, Hartlepool, United Kingdom" }, { - "author_name": "Andrew Platt", - "author_inst": "NIAID" + "author_name": "Tim Felton", + "author_inst": "Manchester University NHS Foundation Trust" }, { - "author_name": "Beth Drolet", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Anthony Kerry", + "author_inst": "Great Western Hospitals Foundation Trust, Swindon, United Kingdom" }, { - "author_name": "John Moon", - "author_inst": "University of Wisconsin-Madison" + "author_name": "J Kenneth Baillie", + "author_inst": "Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom" }, { - "author_name": "Edward Cowen", - "author_inst": "NIAMS" + "author_name": "Maya H Buch", + "author_inst": "Centre for Musculoskeletal Research, University of Manchester, Manchester, United Kingdom" }, { - "author_name": "Heather Kenney", - "author_inst": "NIAID" + "author_name": "Jeremy N Day", + "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom" }, { - "author_name": "Sarah Weber", - "author_inst": "NIAID" + "author_name": "Saul N Faust", + "author_inst": "NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, " }, { - "author_name": "Riccardo Castagnoli", - "author_inst": "NIAID" + "author_name": "Thomas Jaki", + "author_inst": "Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom" }, { - "author_name": "Mary Magliocco", - "author_inst": "NIAID" + "author_name": "Katie Jeffery", + "author_inst": "Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom" }, { - "author_name": "M Austin Stack", - "author_inst": "NIAID" + "author_name": "Edmund Juszczak", + "author_inst": "School of Medicine, University of Nottingham, Nottingham, United Kingdom" }, { - "author_name": "Gina Montealegre", - "author_inst": "NIAID" + "author_name": "Marian Knight", + "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Karyl Barron", - "author_inst": "NIAID" + "author_name": "Wei Shen Lim", + "author_inst": "Respiratory Medicine Department, Nottingham University Hospitals NHS Foundation Trust, Nottingham, United Kingdom" }, { - "author_name": "Stephen Hewitt", - "author_inst": "NCI" + "author_name": "Alan Montgomery", + "author_inst": "School of Medicine, University of Nottingham, Nottingham, United Kingdom" }, { - "author_name": "Lisa Arkin", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Andrew Mumford", + "author_inst": "School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom" }, { - "author_name": "Daniel Chertow", - "author_inst": "NIAID" + "author_name": "Kathryn Rowan", + "author_inst": "Intensive Care National Audit and Research Centre, London, United Kingdom" }, { - "author_name": "Helen Su", - "author_inst": "NIAID" + "author_name": "Guy Thwaites", + "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom" }, { - "author_name": "Luigi Daniele Notarangelo", - "author_inst": "National Institute of Allergy and Infectious Diseases, NIH" + "author_name": "Richard Haynes", + "author_inst": "MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Mariana J Kaplan", - "author_inst": "National Institute of Arthritis and Musculoskeletal and Skin Diseases, NIH" + "author_name": "Martin J Landray", + "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" } ], "version": "1", - "license": "cc0", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -348665,63 +348000,51 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.03.01.482548", - "rel_title": "Immunological memory to Common Cold Coronaviruses assessed longitudinally over a three-year period", + "rel_doi": "10.1101/2022.03.01.22271740", + "rel_title": "Treatment Outline and Clinical Outcome of Hospitalized COVID-19 Patients: Experiences from a Combined Military Hospital of Bangladesh", "rel_date": "2022-03-02", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.01.482548", - "rel_abs": "Understanding immune memory to Common Cold Coronaviruses (CCCs) is relevant for assessing its potential impact on the outcomes of SARS-CoV-2 infection, and for the prospects of pan-corona vaccines development. We performed a longitudinal analysis, of pre-pandemic samples collected from 2016-2019. CD4+ T cells and antibody responses specific for CCC and to other respiratory viruses, and chronic or ubiquitous pathogens were assessed. CCC-specific memory CD4+ T cells were detected in most subjects, and their frequencies were comparable to those for other common antigens. Notably, responses to CCC and other antigens such as influenza and Tetanus Toxoid (TT) were sustained over time. CCC-specific CD4+ T cell responses were also associated with low numbers of HLA-DR+CD38+ cells and their magnitude did not correlate with yearly changes in the prevalence of CCC infections. Similarly, spike RBD-specific IgG responses for CCC were stable throughout the sampling period. Finally, high CD4+ T cell reactivity to CCC, but not antibody responses, was associated with high pre-existing SARS-CoV-2 immunity. Overall, these results suggest that the steady and sustained CCC responses observed in the study cohort are likely due to a relatively stable pool of CCC-specific memory CD4+ T cells instead of fast decaying responses and frequent reinfections.", - "rel_num_authors": 11, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.01.22271740", + "rel_abs": "BackgroundGlobal knowledge of treatment and outcomes of COVID-19 has been evolving since the onset of the pandemic.\n\nMaterials and MethodsThe objective of this cross-sectional study was to explore treatment and outcome of COVID-19 patients admitted in a Combined Military Hospital of Bangladesh. Data were collected from treatment records of patients of the CMH Bogura during the period of June 2020 to August 2020. Total 219 RT-PCR positive admitted patients were included as study population.\n\nResultAmong 219 patients, 78.6% were male and 21.5% were female, mean age of patients was 34.3 {+/-} 12.2. About14.6% patients had one or more comorbidities. Most (83.1%) of the admitted patients were diagnosed as mild cases. Antimicrobials were used in 98.8% cases, and frequent use of doxycycline (80.4%) and ivermectine (77.2%) was found. Anticoagulant and steroid therapy were used in 42.0% and 15.5% patients respectively. O2 therapy was required in 6.0% cases and intensive care unit (ICU) support was needed in 2.3% cases.Duration of hospital stay was 12.1{+/-} 4.4 days and 100% of patients were discharged from hospital. There was no single mortality during the study period.\n\nConclusionHigh prevalence of antimicrobials use was observed among the hospitalized COVID-19 patients in this single center study.Supportive care was effective with no incidence of mortality.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Esther Dawen", - "author_inst": "La Jolla Institute for Immunology" - }, - { - "author_name": "Tara M Narowski", - "author_inst": "University of North Carolina School of Medicine" - }, - { - "author_name": "Eric Wang", - "author_inst": "La Jolla Institute for Immunology" - }, - { - "author_name": "Emily Garrigan", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Sabiha Mahboob", + "author_inst": "CMH Bogura" }, { - "author_name": "Jose Mateus", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Fatema Johora", + "author_inst": "Army Medical College Bogura" }, { - "author_name": "April Frazier", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Asma Akter Abbasy", + "author_inst": "Brahmanbaria Medical College, Bangladesh" }, { - "author_name": "Daniela Weiskopf", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Fatiha Tasmin Jeenia", + "author_inst": "Chattogram International Medical College, Bangladesh" }, { - "author_name": "Alba Grifoni", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Mohammad Ali", + "author_inst": "Asgar Ali Hospital Ltd, Bangladesh" }, { - "author_name": "Lakshmanane Premkumar", - "author_inst": "University of North Carolina School of Medicine" + "author_name": "Md Humayun Kabir", + "author_inst": "Armed forces Institute of Pathology, Bangladesh" }, { - "author_name": "Alessandro Sette", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Ferdaush Ahmed Sojib", + "author_inst": "101 Field ambulance, Ramu cantonment, Bangladesh" }, { - "author_name": "Ricardo da Silva Antunes", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Jannatul Ferdoush", + "author_inst": "BGC Trust Medical College, Chattogram, Bangladesh" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "immunology" + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.03.02.22271385", @@ -350483,67 +349806,143 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.02.17.22270829", - "rel_title": "Drivers of adaptive evolution during chronic SARS-CoV-2 infections", + "rel_doi": "10.1101/2022.02.25.482049", + "rel_title": "Efficient Neutralization of SARS-CoV-2 Omicron and Other VOCs by a Broad Spectrum Antibody 8G3", "rel_date": "2022-02-28", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.17.22270829", - "rel_abs": "In some immunocompromised patients with chronic SARS-CoV-2 infection, dramatic adaptive evolution occurs, with substitutions reminiscent of those in variants of concern (VOCs). Here, we searched for drivers of VOC-like emergence by consolidating sequencing results from a set of twenty-seven chronic infections. Most substitutions in this set reflected lineage-defining VOC mutations, yet a subset of mutations associated with successful global transmission was absent from chronic infections. The emergence of these mutations might dictate when variants from chronic infections can dramatically spread onwards. Next, we tested the ability to predict antibody-evasion mutations from patient- and viral-specific features, and found that viral rebound is strongly associated with the emergence of antibody-evasion. We found evidence for dynamic polymorphic viral populations in most patients, suggesting that a compromised immune system selects for antibody-evasion in particular niches in a patients body. We suggest that a trade-off exists between antibody-evasion and transmissibility that potentially constrains VOC emergence, and that monitoring chronic infections may be a means to predict future VOCs.", - "rel_num_authors": 12, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.25.482049", + "rel_abs": "Numerous mutations in the spike protein of SARS-CoV-2 B.1.1.529 Omicron variant pose a crisis for antibody-based immunotherapies. The efficacy of emergency use authorized (EUA) antibodies that developed in early SARS-CoV-2 pandemic seems to be in flounder. We tested the Omicron neutralization efficacy of an early B cell antibody repertoire as well as several EUA antibodies in pseudovirus and authentic virus systems. More than half of the antibodies in the repertoire that showed good activity against WA1/2020 previously had completely lost neutralizing activity against Omicron, while antibody 8G3 displayed non-regressive activity. EUA antibodies Etesevimab, Casirivimab, Imdevimab and Bamlanivimab were entirely desensitized by Omicron. Only Sotrovimab targeting the non-ACE2 overlap epitope showed a dramatic decrease activity. Antibody 8G3 efficiently neutralized Omicron in pseudovirus and authentic virus systems. The in vivo results showed that Omicron virus was less virulent than the WA1/2020 strain, but still caused deterioration of health and even death in mice. Treatment with 8G3 quickly cleared virus load of mice. Antibody 8G3 also showed excellent activity against other variants of concern (VOCs), especially more efficient against authentic Delta plus virus. Collectively, our results suggest that neutralizing antibodies with breadth remains broad neutralizing activity in tackling SARS-CoV-2 infection despite the universal evasion from EUA antibodies by Omicron variant.", + "rel_num_authors": 31, "rel_authors": [ { - "author_name": "Sheri Harari", - "author_inst": "Tel Aviv University" + "author_name": "Hang Ma", + "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University" }, { - "author_name": "Maayan Tahor", - "author_inst": "Tel Aviv University" + "author_name": "Chien-Te K. Tseng", + "author_inst": "Departments of Microbiology and Immunology, University of Texas Medical Branch" }, { - "author_name": "Natalie Rutsinsky", - "author_inst": "Tel Aviv University" + "author_name": "Huifang Zong", + "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University" }, { - "author_name": "Suzy Meijer", - "author_inst": "Tel Aviv Sourasky Medical Center" + "author_name": "Yunji Liao", + "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University" }, { - "author_name": "Danielle Miller", - "author_inst": "Tel Aviv University" + "author_name": "Yong Ke", + "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University" }, { - "author_name": "Oryan Henig", - "author_inst": "Tel Aviv Sourasky Medical Center" + "author_name": "Haoneng Tang", + "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University" }, { - "author_name": "Ora Halutz", - "author_inst": "Tel Aviv Sourasky Medical Center" + "author_name": "Lei Wang", + "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University" }, { - "author_name": "Katia Levytskyi", - "author_inst": "Tel Aviv Sourasky Medical Center" + "author_name": "Zhenyu Wang", + "author_inst": "Jecho Biopharmaceuticals Co., Ltd." }, { - "author_name": "Ronen Ben-Ami", - "author_inst": "Tel Aviv Sourasky Medical Center" + "author_name": "Yang He", + "author_inst": "Jecho Biopharmaceuticals Co., Ltd." }, { - "author_name": "Amos Adler", - "author_inst": "Tel Aviv Sourasky Medical Center" + "author_name": "Yunsong Chang", + "author_inst": "Jecho Biopharmaceuticals Co., Ltd." }, { - "author_name": "Yael Paran", - "author_inst": "Tel Aviv Sourasky Medical Center" + "author_name": "Shusheng Wang", + "author_inst": "Jecho Laboratories, Inc." }, { - "author_name": "Adi Stern", - "author_inst": "Tel Aviv University" + "author_name": "Aleksandra Drelich", + "author_inst": "Neurosciences, Cell Biology, and Anatomy, University of Texas Medical Branch" + }, + { + "author_name": "Jason Hsu", + "author_inst": "Pathology, University of Texas Medical Branch" + }, + { + "author_name": "Vivian Tat", + "author_inst": "Center for Biodefense and Emerging Disease, University of Texas Medical Branch" + }, + { + "author_name": "Yunsheng Yuan", + "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University" + }, + { + "author_name": "Mingyuan Wu", + "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University" + }, + { + "author_name": "Junjun Liu", + "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University" + }, + { + "author_name": "Yali Yue", + "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University" + }, + { + "author_name": "Wenbo Xu", + "author_inst": "National Institute for Viral Disease Control and Prevention, China CDC" + }, + { + "author_name": "Hua Chen", + "author_inst": "Jecho Laboratories, Inc." + }, + { + "author_name": "Yanlin Bian", + "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University" + }, + { + "author_name": "Baohong Zhang", + "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University" + }, + { + "author_name": "Haiyang Yin", + "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University" + }, + { + "author_name": "En Zhang", + "author_inst": "School of Agriculture and Biology, Shanghai Jiao Tong University" + }, + { + "author_name": "Xiaoxiao Zhang", + "author_inst": "Pathology, University of Texas Medical Branch" + }, + { + "author_name": "John Gilly", + "author_inst": "Jecho Biopharmaceuticals Co., Ltd." + }, + { + "author_name": "Tao Sun", + "author_inst": "School of Agriculture and Biology, Shanghai Jiao Tong University" + }, + { + "author_name": "Lei Han", + "author_inst": "Jecho Institute, Co., Ltd." + }, + { + "author_name": "Yueqing Xie", + "author_inst": "Jecho Laboratories, Inc." + }, + { + "author_name": "Hua Jiang", + "author_inst": "Jecho Biopharmaceuticals Co., Ltd." + }, + { + "author_name": "Jianwei Zhu", + "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University" } ], "version": "1", - "license": "cc_by_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "cell biology" }, { "rel_doi": "10.1101/2022.02.27.482153", @@ -352449,39 +351848,51 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.02.24.22271484", - "rel_title": "The effect of job strain and worksite social support on reported side effects of COVID-19 vaccine: a prospective study of employees in Japan", + "rel_doi": "10.1101/2022.02.24.481866", + "rel_title": "Mouse models of COVID-19 recapitulate inflammatory pathways rather than gene expression", "rel_date": "2022-02-26", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.24.22271484", - "rel_abs": "ObjectivesThis prospective study aimed to examine the association of job demands, job control, and the lack of supervisor and coworker support with side effects after receiving COVID-19 vaccination in a sample of employees in Japan.\n\nMethodsThe data were retrieved from an online panel of full-time employees (E- COCO- J). The analysis included participants who were employed and were not vaccinated at baseline (June 2021) but received vaccination at a four-month follow-up (October 2021). An 11-item scale measured the side effects of COVID-19 vaccines. Four types of psychosocial working conditions (i.e., job demands, job control, and supervisor and coworker support) were measured using the Brief Job Stress Questionnaire (BJSQ). Multiple linear regression analyses were conducted to examine the relationship between the psychosocial working conditions and side effects of COVID-19 vaccines, adjusting for gender, age, educational attainment, marital status, occupation, chronic disease, dose of vaccination, anxiety from potential side effects of vaccines, fear and worry about COVID-19, and psychological distress at baseline.\n\nResultsOverall, 747 employees were included in the analysis. The average number of side effects was 3.78 (SD=2.19): Arm pain (81.1%), fatigues (64.1%), muscle pains (63.3%), and fever (37.5 degrees Celsius +) (53.5%) were reported more frequently. Coworker support score was significantly and negatively associated with the numbers of side effects (standardized {beta}=-0.122, p=0.017). Women, young age, second time vaccination, and high psychological distress were significantly associated with several side effects.\n\nConclusionsEmployees with low coworker support may be more likely to have side effects after COVID-19 vaccinations. The findings of this study could inform employees with low coworker support that increasing workplace support may reduce the side effects.\n\nHighlights The effect of poor psychosocial working conditions on side effects after COVID-19 vaccinations was unknown.\n Poor coworker support at baseline was significantly associated with increased side effects after COVID-19 vaccinations.\n Informing workers with low coworker support about the findings may help them prepare for the side effect and motivate them to improve coworker support to reduce side effects.", - "rel_num_authors": 5, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.24.481866", + "rel_abs": "BACKGROUNDHow well mouse models recapitulate the transcriptional profiles seen in humans remains debatable, with both conservation and diversity identified in various settings. The K18-hACE2 mouse model has been widely used for evaluation of new interventions for COVID-19.\n\nMETHODHerein we use RNA-Seq data and bioinformatics approaches to compare the transcriptional responses in the SARS-CoV-2 infected lungs of K18-hACE2 mice with those seen in humans.\n\nRESULTSOverlap in differentially expressed genes was generally poor ({approx}20-30%), even when multiple studies were combined. The overlap was not substantially improved when a second mouse model was examined wherein hACE was expressed from the mouse ACE2 promoter. In contrast, analyses of immune signatures and inflammatory pathways illustrated highly significant concordances between the species.\n\nCONCLUSIONAs immunity and immunopathology are the focus of most studies, these hACE2 transgenic mouse models can thus be viewed as representative and relevant models of COVID-19.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Natsu Sasaki", - "author_inst": "The University of Tokyo" + "author_name": "Cameron R Bishop", + "author_inst": "QIMR Berghofer Medical Research Institute" }, { - "author_name": "Reiko Kuroda", - "author_inst": "The University of Tokyo" + "author_name": "Troy Dumenil", + "author_inst": "QIMR Berghofer Medical Research Institute" }, { - "author_name": "Kanami Tsuno", - "author_inst": "Kanagawa University of Human Services" + "author_name": "Daniel J Rawle", + "author_inst": "QIMR Berghofer Medical Research Institute" }, { - "author_name": "Kotaro Imamura", - "author_inst": "The University of Tokyo" + "author_name": "Thuy Le", + "author_inst": "QIMR Berghofer Medical Research Institute" }, { - "author_name": "Norito Kawakami", - "author_inst": "The University of Tokyo" + "author_name": "Kexin Yan", + "author_inst": "QIMR Berghofer Medical Research Institute" + }, + { + "author_name": "Bing Tang", + "author_inst": "QIMR Berghofer Medical Research Institute" + }, + { + "author_name": "Gunter Hartel", + "author_inst": "QIMR Berghofer Medical Research Institute" + }, + { + "author_name": "Andreas Suhrbier", + "author_inst": "QIMR Berghofer Medical Research Institute" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "license": "cc_by_nd", + "type": "new results", + "category": "molecular biology" }, { "rel_doi": "10.1101/2022.02.24.481684", @@ -354239,71 +353650,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.02.24.22271002", - "rel_title": "A mixture model to estimate SARS-CoV-2 seroprevalence in Chennai, India", + "rel_doi": "10.1101/2022.02.18.22271151", + "rel_title": "Health Provider and Sexual and Gender Minority Service User Perspectives on Provision of Mental Health Services During the Early Phase of the COVID-19 Pandemic in British Columbia, Canada", "rel_date": "2022-02-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.24.22271002", - "rel_abs": "BackgroundSerological assays used to estimate SARS-CoV-2 seroprevalence rely on manufacturer cut-offs established based on more severe early cases who tended to be older.\n\nMethodsWe conducted a household-based serosurvey of 4,677 individuals from 2,619 households in Chennai, India from January to May, 2021. Samples were tested for SARS-CoV-2 IgG antibodies to the spike (S) and nucelocapsid (N) proteins. We calculated seroprevalence using manufacturer cut-offs and using a mixture model in which individuals were assigned a probability of being seropositive based on their measured IgG, accounting for heterogeneous antibody response across individuals.\n\nResultsThe SARS-CoV-2 seroprevalence to anti-S and anti-N IgG was 62.0% (95% confidence interval [CI], 60.6 to 63.4) and 13.5% (95% CI, 12.6 to 14.5), respectively applying the manufacturers cut-offs, with low inter-assay agreement (Cohens kappa 0.15). With the mixture model, estimated anti-S IgG and anti-N IgG seroprevalence was 64.9% (95% Credible Interval [CrI], 63.8 to 66.0) and 51.5% (95% CrI, 50.2 to 52.9) respectively, with high inter-assay agreement (Cohens kappa 0.66). Age and socioeconomic factors showed inconsistent relationships with anti-S IgG and anti-N IgG seropositivity using manufacturers cut-offs, but the mixture model reconciled these differences. In the mixture model, age was not associated with seropositivity, and improved household ventilation was associated with lower seropositivity odds.\n\nConclusionsWith global vaccine scale-up, the utility of the more stable anti-S IgG assay may be limited due to the inclusion of the S protein in several vaccines. SARS-CoV-2 seroprevalence estimates using alternative targets must consider heterogeneity in seroresponse to ensure seroprevalence is not underestimated and correlates not misinterpreted.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.18.22271151", + "rel_abs": "While the COVID-19 pandemic impacted everyone, social determinants of health and structural inequities have had compounding effects that shaped the experiences of some sub-populations during the pandemic. Stigmatization, discrimination, and exclusion contribute to a disproportionately high burden of mental health concerns among sexual minority (i.e., lesbian, gay, bisexual, queer, and other sexually-diverse) and gender minority people. Pre-pandemic, these health inequities are exacerbated by barriers to adequate mental health services including cost, waitlists, and experiences of sexual and gender minority stigma when accessing providers. During the COVID-19 pandemic, these barriers were further complicated by drastic changes in service delivery and access during the pandemic--i.e., a shift to online/virtual provision of care to reduce risk of COVID-19 transmission. To better understand the experiences of sexual and gender minority people accessing mental health services during the first three to nine months of the COVID-19 pandemic, we conducted semi-structured interviews with a purposive sample of 15 health care providers and administrators (summer 2020) and 14 sexual and gender minority individuals interested in accessing mental health services (fall 2020) in British Columbia, Canada. We used interpretive description to inductively analyze interview data. Triangulating between the provider and service user datasets, we examined changes in mental health and coping during the COVID-19 pandemic. We recorded increases in isolation and lack of identity affirmation; inequities in accessing mental health services during the pandemic, perceived opportunities for mental health support, and avenues for reducing mental health inequities through system-level changes that deserve particular attention during the pandemic.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Matt D.T. Hitchings", - "author_inst": "University of Florida" - }, - { - "author_name": "Eshan U. Patel", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" - }, - { - "author_name": "Rifa Khan", - "author_inst": "YR Gaitonde Centre for AIDS Research and Education (YRGCARE)" - }, - { - "author_name": "Aylur K Srikrishnan", - "author_inst": "YR Gaitonde Centre for AIDS Research and Education (YRGCARE)" - }, - { - "author_name": "Mark Anderson", - "author_inst": "Abbott Laboratories" - }, - { - "author_name": "K. S. Kumar", - "author_inst": "YR Gaitonde Centre for AIDS Research and Education (YRGCARE)" + "author_name": "Angel M Kennedy", + "author_inst": "Simon Fraser University" }, { - "author_name": "Amy P. Wesolowski", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "St\u00e9phanie Black", + "author_inst": "Simon Fraser University" }, { - "author_name": "Syed H. Iqbal", - "author_inst": "YR Gaitonde Centre for AIDS Research and Education (YRGCARE)" + "author_name": "Sarah Watt", + "author_inst": "Simon Fraser University and BC Centre for Disease Control" }, { - "author_name": "Mary A. Rodgers", - "author_inst": "Abbott Laboratories" - }, - { - "author_name": "Shruti H. Mehta", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Natasha Vitkin", + "author_inst": "Simon Fraser University" }, { - "author_name": "Gavin Cloherty", - "author_inst": "Abbott Laboratories" + "author_name": "James Young", + "author_inst": "Simon Fraser University" }, { - "author_name": "Derek A.T. Cummings", - "author_inst": "University of Florida" + "author_name": "Rowdy Reeves", + "author_inst": "Simon Fraser University" }, { - "author_name": "Sunil S. Solomon", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Travis Salway", + "author_inst": "Simon Fraser University; BC Centre for Disease Control; Centre for Gender and Sexual Health Equity" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.02.24.22271468", @@ -355853,25 +355240,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.02.23.22271382", - "rel_title": "Fourth Wave of COVID-19 in India : Statistical Forecasting", + "rel_doi": "10.1101/2022.02.23.22271394", + "rel_title": "Dynamics of the Delta and Omicron variants of SARS-CoV-2 in the United States: the battle of supremacy in the presence of vaccination, mask usage and antiviral treatment", "rel_date": "2022-02-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.23.22271382", - "rel_abs": "The spread of COVID-19 pandemic has wave nature. This article proposes a statistical methodology to study and forecast the future waves. The methodology is applied to COVID-19 data from India to statistically forecast the occurrence of fourth wave in India. In the course of this study, the data is fitted by the mixture of Gaussian distribution, and Bootstrap methodology is used to compute the confidence interval of the time point of peak of the fourth wave. This methodology can also be used to forecast the fourth and other waves in other countries also.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.23.22271394", + "rel_abs": "The effectiveness of control interventions against COVID-19 is threatened by the emergence of SARS-CoV-2 variants of concern. We present a mathematical model for studying the transmission dynamics of two of these variants (Delta and Omicron) in the United States, in the presence of vaccination, treatment of individuals with clinical symptoms of the disease and the use of face masks. The model is parameterized and cross-validated using observed daily case data for COVID-19 in the United States for the period from November 2021 (when Omicron first emerged) to March 2022. Rigorous qualitative analysis of the model shows that the disease-free equilibrium of the model is locally-asymptotically stable when the control reproduction number of the model (denoted by [R]c) is less than one. This equilibrium is shown to be globally-asymptotically stable for a special case of the model, where disease-induced mortality is negligible and both vaccine-derived immunity in fully-vaccinated individuals and natural immunity do not wane, when the associated reproduction number is less than one. The epidemiological implication of the latter result is that the combined vaccination-boosting strategy can lead to the elimination of the pandemic if its implementation can bring (and maintain) the associated reproduction number to a value less than one. An analytical expression for the vaccine-derived herd immunity threshold is derived. Using this expression, together with the baseline values of the parameters of the parameterized model, we showed that the vaccine-derived herd immunity can be achieved in the United States (so that the pandemic will be eliminated) if at least 68% of the population is fully-vaccinated with two of the three vaccines approved for use in the United States (Pfizer or Moderna vaccine). Furthermore, this study showed (as of the time of writing in March 2022) that the control reproduction number of the Omicron variant was approximately 3.5 times that of the Delta variant (the reproduction of the latter is computed to be {approx} 0.2782), indicating that Delta had practically died out and that Omicron has competitively-excluded Delta (to become the predominant variant in the United States). Based on our analysis and parameterization at the time of writing of this paper (March 2022), our study suggests that SARS-CoV-2 elimination is feasible by June 2022 if the current baseline level of the coverage of fully-vaccinated individuals is increased by about 20%. The prospect of pandemic elimination is significantly improved if vaccination is combined with a face mask strategy that prioritizes moderately effective and high-quality masks. Having a high percentage of the populace wearing the moderately-effective surgical mask is more beneficial to the community than having low percentage of the populace wearing the highly-effective N95 masks. We showed that waning natural and vaccine-derived immunity (if considered individually) offer marginal impact on disease burden, except for the case when they wane at a much faster rate (e.g., within three months), in comparison to the baseline (estimated to be within 9 months to a year). Treatment of symptomatic individuals has marginal effect in reducing daily cases of SARS-CoV-2, in comparison to the baseline, but it has significant impact in reducing daily hospitalizations. Furthermore, while treatment significantly reduces daily hospitalizations (and, consequently, deaths), the prospects of COVID-19 elimination in the United States are significantly enhanced if investments in control resources are focused on mask usage and vaccination rather than on treatment.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Sabara Parshad Rajeshbhai", - "author_inst": "IIT Kanpur, India" + "author_name": "Calistus N Ngonghala", + "author_inst": "University of Florida" }, { - "author_name": "Subhra Sankar Dhar", - "author_inst": "IIT Kanpur" + "author_name": "Hemaho B Taboe", + "author_inst": "University of Abomey-Calavi" }, { - "author_name": "Shalabh Shalabh", - "author_inst": "IIT Kanpur, India" + "author_name": "Salman Safdar", + "author_inst": "Arizona State University" + }, + { + "author_name": "Abba B Gumel", + "author_inst": "Arizona State University" } ], "version": "1", @@ -357514,165 +356905,53 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.02.20.481163", - "rel_title": "Efficient recall of Omicron-reactive B cell memory after a third dose of SARS-CoV-2 mRNA vaccine", + "rel_doi": "10.1101/2022.02.19.481110", + "rel_title": "Omicron booster in ancestral strain vaccinated mouse augments protective immunities against both the Delta and Omicron variants", "rel_date": "2022-02-22", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.20.481163", - "rel_abs": "Despite a clear role in protective immunity, the durability and quality of antibody and memory B cell responses induced by mRNA vaccination, particularly by a 3rd dose of vaccine, remains unclear. Here, we examined antibody and memory B cell responses in a cohort of individuals sampled longitudinally for [~]9-10 months after the primary 2-dose mRNA vaccine series, as well as for [~]3 months after a 3rd mRNA vaccine dose. Notably, antibody decay slowed significantly between 6- and 9-months post-primary vaccination, essentially stabilizing at the time of the 3rd dose. Antibody quality also continued to improve for at least 9 months after primary 2-dose vaccination. Spike- and RBD-specific memory B cells were stable through 9 months post-vaccination with no evidence of decline over time, and [~]40-50% of RBD-specific memory B cells were capable of simultaneously recognizing the Alpha, Beta, Delta, and Omicron variants. Omicron-binding memory B cells induced by the first 2 doses of mRNA vaccine were boosted significantly by a 3rd dose and the magnitude of this boosting was similar to memory B cells specific for other variants. Pre-3rd dose memory B cell frequencies correlated with the increase in neutralizing antibody titers after the 3rd dose. In contrast, pre-3rd dose antibody titers inversely correlated with the fold-change of antibody boosting, suggesting that high levels of circulating antibodies may limit reactivation of immunological memory and constrain further antibody boosting by mRNA vaccines. These data provide a deeper understanding of how the quantity and quality of antibody and memory B cell responses change over time and number of antigen exposures. These data also provide insight into potential immune dynamics following recall responses to additional vaccine doses or post-vaccination infections.\n\nGraphical Summary\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=123 SRC=\"FIGDIR/small/481163v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (20K):\norg.highwire.dtl.DTLVardef@123d2d9org.highwire.dtl.DTLVardef@e7db82org.highwire.dtl.DTLVardef@1fc73deorg.highwire.dtl.DTLVardef@11b21f9_HPS_FORMAT_FIGEXP M_FIG C_FIG", - "rel_num_authors": 37, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.19.481110", + "rel_abs": "A booster vaccination is called for constraining the evolving epidemic of SARS-CoV-2. However, the necessity of a new COVID-19 vaccine is currently unclear. To compare the effect of an Omicron-matched S DNA vaccine and an ancestral S DNA vaccine in boosting cross-reactive immunities, we firstly immunized mice with two-dose of a DNA vaccine encoding the spike protein of the ancestral Wuhan strain. Then the mice were boosted with DNA vaccines encoding spike proteins of either the Wuhan strain or the Omicron variant. Specific antibody and T cell responses were measured at 4 weeks post boost. Our data showed that the Omicron-matched vaccine efficiently boosted RBD binding antibody and neutralizing antibody responses against both the Delta and the Omicron variants. Of note, antibody responses against the Omicron variant elicited by the Omicron-matched vaccine were much stronger than those induced by the ancestral S DNA vaccine. Meanwhile, CD8+ T cell responses against both the ancestral Wuhan strain and the Omicron strain also tended to be higher in mice boosted by the Omicron-matched vaccine than those in mice boosted with the ancestral S DNA vaccine, albeit no significant difference was observed. Our findings suggest that an Omicron-matched vaccine is preferred for boosting cross-reactive immunities.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Rishi R Goel", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Mark M Painter", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Kendall A Lundgreen", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Sokratis A Apostolidis", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Amy E Baxter", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Josephine R Giles", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Divij Mathew", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Ajinkya Pattekar", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Arnold Reynaldi", - "author_inst": "University of New South Wales" - }, - { - "author_name": "David S Khoury", - "author_inst": "University of New South Wales" - }, - { - "author_name": "Sigrid Gouma", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Philip Hicks", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Sarah Dysinger", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Amanda Hicks", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Harsh Sharma", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Sarah Herring", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Scott Korte", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Wumesh KC", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Derek A Oldridge", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Rachel I Erickson", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Madison E Weirick", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Christopher M McAllister", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Moses Awofolaju", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Nicole Tanenbaum", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Jeanette Dougherty", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Sherea Long", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Jacob T Hamilton", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Maura McLaughlin", - "author_inst": "University of Pennsylvania" + "author_name": "Liqiu Jia", + "author_inst": "Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Bio" }, { - "author_name": "Justine C Williams", - "author_inst": "University of Pennsylvania" + "author_name": "Yang Zhou", + "author_inst": "Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Bio" }, { - "author_name": "Sharon Adamski", - "author_inst": "University of Pennsylvania" + "author_name": "Shaoshuai Li", + "author_inst": "Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Bio" }, { - "author_name": "Oliva Kuthuru", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Elizabeth M Drapeau", - "author_inst": "University of Pennsylvania" + "author_name": "Yifan Zhang", + "author_inst": "Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Bio" }, { - "author_name": "Miles P Davenport", - "author_inst": "University of New South Wales" + "author_name": "Dongmei Yan", + "author_inst": "Department of Immunology, School of Basic Medical, Jiamusi University, Jiamusi, China" }, { - "author_name": "Scott E Hensley", - "author_inst": "University of Pennsylvania" + "author_name": "Wanhai Wang", + "author_inst": "Department of Medical Laboratory, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China" }, { - "author_name": "Paul Bates", - "author_inst": "University of Pennsylvania" + "author_name": "Wenhong Zhang", + "author_inst": "Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Bio" }, { - "author_name": "Allison R Greenplate", - "author_inst": "University of Pennsylvania" + "author_name": "Yan min Wan", + "author_inst": "Huashan Hospital Fudan University" }, { - "author_name": "E. John Wherry", - "author_inst": "University of Pennsylvania" + "author_name": "Chao Qiu", + "author_inst": "Institutes of biomedical sciences & Shanghai Key Laboratory of Medical Epigenetics, Fudan University, Shanghai, China" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "new results", "category": "immunology" }, @@ -359740,51 +359019,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.02.17.22269638", - "rel_title": "The effects of COVID-19 on European healthcare provision for people with major depressive disorder: a scoping review protocol", + "rel_doi": "10.1101/2022.02.17.22271080", + "rel_title": "Should COVID-specific arrangements for abortion continue? The views of women experiencing abortion in Britain during the pandemic.", "rel_date": "2022-02-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.17.22269638", - "rel_abs": "Even before the pandemic, the treatment gaps in depression care were substantial, with issues ranging from rates of depression detection and intervention to a lack of follow-up after treatment initiation and access to secondary care services. The COVID-19 pandemic, which has had major effects on global healthcare systems, is almost certain to have impacted the MDD care pathway, though it is unclear what changes have manifested and what opportunities have arisen in response to COVID-19. The extent to which patients receive best-practice care is likely closely linked to clinical outcomes (and therefore disability burden) and as such, it is important to examine treatment gaps on the MDD care pathway during the pandemic. Here, we outline a protocol for a scoping review that investigates this broad topic, focusing on continuity of care and novel methods (e.g. digital approaches) used to mitigate care disruption. This scoping review protocol was designed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) standards and will culminate in a narrative synthesis of evidence.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.17.22271080", + "rel_abs": "BackgroundDuring the COVID-19 pandemic, the British governments issued temporary approvals enabling the use of both pills for medical abortion at home. This permitted the introduction of a fully telemedical model of abortion care with consultations taking place via phone or video call and medications delivered to womens homes. The approvals in England and Wales will expire at the end of March 2022, while that in Scotland remains under consultation.\n\nMethodsWe interviewed 30 women who had undergone an abortion in England, Scotland or Wales between August and December 2021. We explored their views on the changes in abortion service configuration during the pandemic and whether abortion via telemedicine and use of abortion medications at home should continue.\n\nResultsSupport for continuation of the permission to use mifepristone and misoprostol at home was overwhelmingly positive. Reasons cited included convenience, comfort, reduced stigma, privacy, and respect for autonomy. A telemedical model was also highly regarded for similar reasons but for some its necessity was linked to safety measures during the pandemic and an option to have an in-person interaction with a health professional at some point in the care pathway was endorsed.\n\nConclusionsThe approval to use abortion pills at home via telemedicine are supported by women having abortions in Great Britain. The respective governments in England, Scotland, and Wales, should be responsive to the patient voice and move to make permanent these important advances in abortion care.\n\nWhat is already known on this topicDuring the COVID-pandemic, specific permission to use both pills for medical abortion at home was granted in England, Scotland and Wales leading to the widespread implementation of a telemedical model with direct-to-patient delivery of medications. The safety, effectiveness, and acceptability of this model of care had been well-documented prior to and during the pandemic.\n\nWhat this study addsThis study adds the voices of women undergoing abortion during the pandemic regarding the specific changes that led to the transformation of medical abortion care in Britain. Amongst 30 women interviewed, there was endorsement for the continuation of permissions to use medical abortion pills at home via telemedicine.\n\nHow this study might affect research, practice, or policyThe UK governments vision of health provision puts patients and the public first, where \"no decision about me, without me\" is the norm. Our findings support law and policy makers in applying this principle to recent developments in abortion care by making the permissions permanent.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Dilveer Sually", - "author_inst": "King's College London" + "author_name": "Patricia Lohr", + "author_inst": "BPAS" }, { - "author_name": "Win Lee Edwin Wong", - "author_inst": "King's College London" + "author_name": "Maria Lewandowska", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Diego Hidalgo-Mazzei", - "author_inst": "King's College London; University of Barcelona" + "author_name": "Rebecca Meiksin", + "author_inst": "LSHTM" }, { - "author_name": "Vinciane Quoidbach", - "author_inst": "European Brain Council" + "author_name": "Rachel Scott", + "author_inst": "LSHTM" }, { - "author_name": "Judit Simon", - "author_inst": "Medical University of Vienna" + "author_name": "Jennifer Reiter", + "author_inst": "London Borough of Lambeth" }, { - "author_name": "Patrice Boyer", - "author_inst": "University Paris-Diderot; University of Ottawa" + "author_name": "Natasha Salaria", + "author_inst": "LSHTM" }, { - "author_name": "Rebecca Strawbridge", - "author_inst": "King's College London" + "author_name": "Sharon Cameron", + "author_inst": "NHS Lothian" }, { - "author_name": "Allan H. Young", - "author_inst": "King's College London" + "author_name": "Melissa Palmer", + "author_inst": "LSHTM" + }, + { + "author_name": "Rebecca French", + "author_inst": "LSHTM" + }, + { + "author_name": "Kaye Wellings", + "author_inst": "LSHTM" + }, + { + "author_name": "- SACHA Study", + "author_inst": "" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "sexual and reproductive health" }, { "rel_doi": "10.1101/2022.02.16.22270690", @@ -361606,125 +360897,117 @@ "category": "pharmacology and therapeutics" }, { - "rel_doi": "10.1101/2022.02.17.480751", - "rel_title": "An ACE2-blocking antibody confers broad neutralization and protection against Omicron and other SARS-CoV-2 variants", + "rel_doi": "10.1101/2022.02.17.480851", + "rel_title": "Intramuscular mRNA BNT162b2 vaccine against SARS-CoV-2 induces robust neutralizing salivary IgA", "rel_date": "2022-02-17", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.17.480751", - "rel_abs": "The ongoing evolution of SARS-CoV-2 has resulted in the emergence of Omicron, which displays striking immune escape potential. Many of its mutations localize to the spike protein ACE2 receptor-binding domain, annulling the neutralizing activity of most therapeutic monoclonal antibodies. Here we describe a receptor-blocking human monoclonal antibody, 87G7, that retains ultrapotent neutralization against SARS-CoV-2 variants including the Alpha, Beta, Gamma, Delta and Omicron (BA.1/BA.2) Variants-of-Concern (VOCs). Structural analysis reveals that 87G7 targets a patch of hydrophobic residues in the ACE2-binding site that are highly conserved in SARS-CoV-2 variants, explaining its broad neutralization capacity. 87G7 protects mice and/or hamsters against challenge with all current SARS-CoV-2 VOCs. Our findings may aid the development of sustainable antibody-based strategies against COVID-19 that are more resilient to SARS-CoV-2 antigenic diversity.\n\nOne sentence summaryA human monoclonal antibody confers broad neutralization and protection against Omicron and other SARS-CoV-2 variants", - "rel_num_authors": 27, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.17.480851", + "rel_abs": "Intramuscularly administered vaccines stimulate robust serum neutralizing antibodies, yet they are often less competent in eliciting sustainable sterilizing immunity at the mucosal level. Our study uncovers, strong neutralizing mucosal component (NT50 [≤] 50pM), emanating from intramuscular administration of an mRNA vaccine. We show that saliva of BNT162b2 vaccinees contains temporary IgA targeting the Receptor-Binding-Domain (RBD) of SARS-CoV-2 spike protein and demonstrate that these IgAs are key mediators of potent neutralization. RBD-targeting IgAs were found to associate with the Secretory Component, indicating their bona-fide transcytotic origin and their dimeric tetravalent nature. The mechanistic understanding of the exceptionally high neutralizing activity provided by mucosal IgA, acting at the first line of defence, will advance vaccination design and surveillance principles, pointing to novel treatment approaches, and to new routes of vaccine administration and boosting.\n\nSignificance statementWe unveiled powerful mucosal neutralization upon BNT162b2 vaccination, mediated by temporary polymeric IgA and explored its longitudinal properties. We present a model, whereby the molecular architecture of polymeric mucosal IgA and its spatial properties are responsible for the outstanding SARS-CoV-2 neutralization potential. We established a methodology for quantitative comparison of immunoreactivity and neutralization for IgG and IgAs in serum and saliva in molar equivalents for standardization in diagnostics, surveillance of protection and for vaccine evaluations.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Wenjuan Du", - "author_inst": "Utrecht University" - }, - { - "author_name": "Daniel L. Hurdiss", - "author_inst": "Utrecht University" - }, - { - "author_name": "Dubravka Drabek", - "author_inst": "Erasmus Medical Center" + "author_name": "Miri Stolovich-Rain", + "author_inst": "The Hebrew University-Hadassah Medical School" }, { - "author_name": "Anna Z Mykytyn", - "author_inst": "Erasmus Medical Center" + "author_name": "Sujata Kumari", + "author_inst": "The Hebrew University of Jerusalem" }, { - "author_name": "Franziska Kaiser", - "author_inst": "University of Veterinary Medicine Hannover" + "author_name": "Ahuva Friedman", + "author_inst": "The Hebrew University of Jerusalem" }, { - "author_name": "Mariana Gonzalez-Hernandez", - "author_inst": "University of Veterinary Medicine Hannover" + "author_name": "Saveliy Kirillov", + "author_inst": "The Hebrew University of Jerusalem; National Center for Biotechnology, Nur-Sultan, Kazakhstan; L.N. Gumilyov Eurasian National University, Nur-Sultan, Kazakhst" }, { - "author_name": "Diego Munoz-Santos", - "author_inst": "National Center for Biotechnology-Spanish National Research Council" + "author_name": "Yakov Socol", + "author_inst": "The Hebrew University of Jerusalem" }, { - "author_name": "Mart M. Lamers", - "author_inst": "Erasmus Medical Center" + "author_name": "Maria Billan", + "author_inst": "The Hebrew University of Jerusalem" }, { - "author_name": "Rien van Haperen", - "author_inst": "Erasmus Medical Center" + "author_name": "Ritesh Ranjan Pal", + "author_inst": "The Hebrew University of Jerusalem" }, { - "author_name": "Wentao Li", - "author_inst": "Utrecht University" + "author_name": "Peretz Golding", + "author_inst": "The Hebrew University of Jerusalem" }, { - "author_name": "Ieva Drulyte", - "author_inst": "Thermo Fisher Scientific" + "author_name": "Esther Oiknine-Djian", + "author_inst": "Hadassah Hebrew University Medical Center, Jerusalem" }, { - "author_name": "Chunyan Wang", - "author_inst": "Utrecht University" + "author_name": "Salim Sirhan", + "author_inst": "The Hebrew University of Jerusalem" }, { - "author_name": "Isabel Sola", - "author_inst": "National Center for Biotechnology-Spanish National Research Council" + "author_name": "Michal Bejerano Sagie", + "author_inst": "The Hebrew University of Jerusalem" }, { - "author_name": "Federico Armando", - "author_inst": "University of Veterinary Medicine Hannover" + "author_name": "Einav Cohen-Kfir", + "author_inst": "The Hebrew University" }, { - "author_name": "Georg Beythien", - "author_inst": "University of Veterinary Medicine Hannover" + "author_name": "Maya Elgrably-Weiss", + "author_inst": "The Hebrew University" }, { - "author_name": "Malgorzata Ciurkiewicz", - "author_inst": "University of Veterinary Medicine Hannover" + "author_name": "Bing Zhou", + "author_inst": "The Hebrew University of Jerusalem" }, { - "author_name": "Wolfgang Baumgartner", - "author_inst": "University of Veterinary Medicine Hannover" + "author_name": "Miriam Ravins", + "author_inst": "The Hebrew University of Jerusalem" }, { - "author_name": "Kate Guilfoyle", - "author_inst": "Viroclinics Xplore" + "author_name": "Yair E Gatt", + "author_inst": "The Hebrew University of Jerusalem" }, { - "author_name": "Tony Smits", - "author_inst": "Utrecht University" + "author_name": "Kathakali Das", + "author_inst": "The Hebrew University of Jerusalem" }, { - "author_name": "Joline van der Lee", - "author_inst": "Utrecht University" + "author_name": "Orly Zelig", + "author_inst": "Hadassah Hebrew University Medical Center, Jerusalem" }, { - "author_name": "Frank J.M. van Kuppeveld", - "author_inst": "Utrecht University" + "author_name": "Reuven Wiener", + "author_inst": "Hebrew University" }, { - "author_name": "Geert van Amerongen", - "author_inst": "Viroclinics Xplore" + "author_name": "Dana Wolf", + "author_inst": "The Hebrew University-Hadassah Medical School" }, { - "author_name": "Bart L. Haagmans", - "author_inst": "Erasmus Medical Center" + "author_name": "Hila Elinav", + "author_inst": "Hadassah Hebrew University Medical Center, Jerusalem" }, { - "author_name": "Luis Enjuanes", - "author_inst": "National Center for Biotechnology-Spanish National Research Council" + "author_name": "Jacob Strahilevitz", + "author_inst": "Hebrew University - Hadassah Medical School" }, { - "author_name": "Albert DME Osterhaus", - "author_inst": "University of Veterinary Medicine Hannover" + "author_name": "Dan Padawer", + "author_inst": "Hadassah Hebrew University Medical Center, Jerusalem" }, { - "author_name": "Frank Grosveld", - "author_inst": "Erasmus Medical Center" + "author_name": "Leah Baraz", + "author_inst": "The Hebrew University of Jerusalem; Hadassah Academic College, Jerusalem, Israel" }, { - "author_name": "Berend Jan Bosch", - "author_inst": "Utrecht University" + "author_name": "Alexander Rouvinski", + "author_inst": "The Hebrew University of Jerusalem, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "microbiology" }, @@ -363392,37 +362675,105 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.02.13.22270891", - "rel_title": "Combined oropharyngeal/nares and nasopharyngeal swab sampling remain effective for molecular detection of SARS-CoV-2 Omicron variant", + "rel_doi": "10.1101/2022.02.14.22270857", + "rel_title": "Clinical and immunological features of SARS-CoV-2 breakthrough infections in vaccinated individuals requiring hospitalization", "rel_date": "2022-02-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.13.22270891", - "rel_abs": "The world has experienced several waves of SARS-CoV-2 variants of concern (VoCs) throughout the COVID-19 pandemic since the first cases in December 2019. The Omicron VoC has increased transmission, compared to its predecessors, and can present with sore throat and other cold-like symptoms. Given the predominance of throat symptoms, and previous work demonstrating better sensitivity using antigen-based rapid detection tests when a throat swab is included in the standard nasal sampling, this quality improvement project sought to ensure ongoing suitability of both combined oropharyngeal/nares (OPN) and nasopharyngeal (NP) swab sampling used throughout the pandemic. Consenting participants meeting Public Health testing criteria (mostly symptomatic or a close contact of a known case) were enrolled, and paired NP and OPN swabs collections were subjected to nucleic acid amplification testing (NAAT). Comparing paired specimens from 392 participants sensitivity of NP swabs was 89.1% (95% CI, 78.8-94.9), and that of OPN was 98.4% (95% CI: 90.9->99.9) (p-value 0.052). This project demonstrated that both NP and combined OPN swabs detected the Omicron variant with similar sensitivity by NAAT, supporting the continued use of either swab collection for SARS-CoV-2 molecular detection.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.14.22270857", + "rel_abs": "BackgroundWaning immunity and the surge of SARS-CoV-2 variants are responsible for breakthrough infections, i.e. infections in fully vaccinated individuals. Although the majority of vaccinated infected subjects reports mild or no symptoms, some others require hospitalization. The clinical and immunological features of vaccinated hospitalized COVID-19 patients are currently unknown.\n\nMethods29 unvaccinated and 36 vaccinated hospitalized COVID-19 patients were prospectively enrolled and clinical and laboratory data. Immunophenotyping of leukocytes subsets, T and B cell SARS-CoV-2 specific responses were evaluated via flow cytometry. Anti-IFN- autoantibodies were measured via ELISA.\n\nResultsDespite vaccinated patients were older and with more comorbidities, unvaccinated subjects showed higher levels of pro-inflammatory markers, more severe disease and increased mortality rate. Accordingly, they presented significant alterations in the circulating leukocyte composition, typical of severe COVID-19. Vaccinated patients displayed higher levels of anti-Spike IgGs and Spike-specific B cells. Of all participants, survivors showed higher levels of anti-Spike IgGs and S-specific CD4+ T cells than non-survivors. At hospital admission, 6 out of 65 patients (9.2%) displayed high serum concentrations of autoantibodies targeting IFN-. Remarkably, 3 were unvaccinated and eventually died, while the other 3 were vaccinated and survived.\n\nConclusionDespite more severe pre-existing clinical conditions, vaccinated patients have good outcome. A rapid activation of anti-SARS-CoV-2-specific immunity is fundamental for the resolution of the infection. Therefore, prior immunization through vaccination provides a significant contribute to prevention of disease worsening and can even overcome the presence of high-risk factors (i.e. older age, comorbidities, anti-IFN- autoantibodies positivity).", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Glenn Patriquin", - "author_inst": "Nova Scotia Health" + "author_name": "Giulia Lamacchia", + "author_inst": "University of Florence" }, { - "author_name": "Jason J LeBlanc", - "author_inst": "Nova Scotia Health" + "author_name": "Alessio Mazzoni", + "author_inst": "University of Florence" }, { - "author_name": "Holly A Gillis", - "author_inst": "Nova Scotia Health" + "author_name": "Michele Spinicci", + "author_inst": "University of Florence" }, { - "author_name": "Gregory R McCracken", - "author_inst": "Nova Scotia Health" + "author_name": "Anna Vanni", + "author_inst": "University of Florence" }, { - "author_name": "Janice J Pettipas", - "author_inst": "Nova Scotia Health" + "author_name": "Lorenzo Salvati", + "author_inst": "University of Florence" }, { - "author_name": "Todd F Hatchette", - "author_inst": "Nova Scotia Health" + "author_name": "Benedetta Peruzzi", + "author_inst": "University of Florence" + }, + { + "author_name": "Sara Bencini", + "author_inst": "University of Florence" + }, + { + "author_name": "Manuela Capone", + "author_inst": "University of Florence" + }, + { + "author_name": "Alberto Carnasciali", + "author_inst": "University of Florence" + }, + { + "author_name": "Parham Farahvachi", + "author_inst": "University of Florence" + }, + { + "author_name": "Arianna Rocca", + "author_inst": "University of Florence" + }, + { + "author_name": "Seble Tekle Kiros", + "author_inst": "University of Florence" + }, + { + "author_name": "Lucia Graziani", + "author_inst": "University of Florence" + }, + { + "author_name": "Lorenzo Zammarchi", + "author_inst": "University of Florence" + }, + { + "author_name": "Jessica Mencarini", + "author_inst": "University of Florence" + }, + { + "author_name": "Maria Grazia Colao", + "author_inst": "University of Florence" + }, + { + "author_name": "Roberto Caporale", + "author_inst": "University of Florence" + }, + { + "author_name": "Francesco Liotta", + "author_inst": "University of Florence" + }, + { + "author_name": "Lorenzo Cosmi", + "author_inst": "University of Florence" + }, + { + "author_name": "Gian Maria Rossolini", + "author_inst": "University of Florence" + }, + { + "author_name": "Alessandro Bartoloni", + "author_inst": "University of Florence" + }, + { + "author_name": "Laura Maggi", + "author_inst": "University of Florence" + }, + { + "author_name": "Francesco Annunziato", + "author_inst": "University of Florence" } ], "version": "1", @@ -365662,59 +365013,39 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.02.13.22270904", - "rel_title": "Reliable estimation of SARS-CoV-2 anti-spike protein IgG titers from single dilution optical density values in serologic surveys", + "rel_doi": "10.1101/2022.02.13.22270890", + "rel_title": "Is this Herpes or Syphilis?: Latent Dirichlet Allocation Analysis of Sexually Transmitted Disease-Related Reddit Posts During the COVID-19 Pandemic", "rel_date": "2022-02-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.13.22270904", - "rel_abs": "BackgroundAs the COVID-19 pandemic evolves, there is a need for reliable and scalable seroepidemiology methods to estimate incidence, monitor the dynamics of population-level immunity, and guide mitigation and immunization policies. Our aim was to evaluate the reliability of normalized ELISA optical density (nOD) at a single dilution as a predictor of SARS-CoV-2 immunoglobulin titers derived from serial dilutions.\n\nMethodsWe conducted serial serological surveys of a community-based cohort from the city of Salvador, Brazil after two sequential COVID-19 epidemic waves. Anti-SARS-CoV-2 spike protein immunoglobulin G (anti-S IgG) ELISA (Euroimmun AG) was performed with serial 3-fold dilutions of sera from 54 of the 1101 cohort participants. We estimated interpolated ELISA titers, used parametric models to fit the relationship between nOD at a single 1:100 dilution and interpolated titers, and assessed the correlation between changes in nOD and changes in titers.\n\nResultsThe relationship between nOD at a single 1:100 dilution and interpolated titers fit a log-log curve, with a residual standard error of 0.304. We derived a conversion table of nOD to interpolated titer values. Additionally, there was a high correlation between changes in nOD and changes in interpolated titers between paired serial samples (r = 0.836, {rho} = 0.873). Changes in nOD reliably predicted increases and decreases in titers, with 98.1% agreement ({kappa} = 95.9%).\n\nConclusionSingle nOD measurements can reliably estimate SARS-CoV-2 antibody titers, significantly reducing time, labor, and resource needs when conducting large-scale serological surveys to ascertain population-level changes in exposure and immunity.\n\nHighlightsO_LIOptical density at a single dilution reliably estimates SARS-CoV-2 antibody titers\nC_LIO_LISerial optical density measurements accurately identify changes in serostatus\nC_LIO_LIUsing single optical density values can significantly reduce resource use in serosurveys\nC_LI", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.13.22270890", + "rel_abs": "BackgroundSexually Transmitted Diseases (STDs) are common and costly, impacting approximately one in five people annually. Reddit, the sixth most used internet site in the world, is a user-generated social media discussion platform that may be useful in monitoring discussion about STD symptoms and exposure.\n\nObjectiveThis study sought to define and identify patterns and insights into STD related discussions on Reddit over the course of the COVID-19 pandemic.\n\nMethodsWe extracted posts from Reddit from March 2019 through July 2021. We used a machine learning text mining method, Latent Dirichlet Allocation (LDA), to conduct a text analysis to identify the most common topics discussed in the Reddit posts. We then used word clouds, qualitative topic labelling, and spline regression to characterize the content and distribution of topics observed.\n\nResultsOur extraction resulted in 24,311 total posts. LDA Coding showed that with 8 topics for each time period we achieved high coherence values (pre-COVID=0.41, pre-vaccine=0.42; post-vaccine=0.44). While most topic categories remained the same over time, the relative proportion of topics changed and new topics emerged. Spline regression revealed some key terms had variability in the percentage of posts that coincided with COVID-19 pre- and post-periods, while others were uniform across the study periods.\n\nConclusionsOur studys use of Reddit is a novel way to gain insights into STD symptoms experienced, potential exposures, testing decisions, common questions, and behavior patterns (e.g., during lock down periods). For example, reduction in STD screening may result in observed negative health outcomes due to missed cases, which also impacts onward transmission. As Reddit use is anonymous, users may discuss sensitive topics with greater detail, and more freely than in clinical encounters. Data from anonymous Reddit posts may be leveraged to enhance understanding of the distribution of disease and need for targeted outreach/screening programs. This study demonstrates Reddit has feasibility and utility to enhance understanding of sexual behaviors, STD experiences, and needed health engagement with the public.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Emillia M.M. Andrade Belitardo", - "author_inst": "Instituto Goncalo Moniz Fundacao Oswaldo Cruz" - }, - { - "author_name": "Nivison Nery Jr", - "author_inst": "Instituto Goncalo Moniz Fundacao Oswaldo Cruz" - }, - { - "author_name": "Juan P. Aguilar Ticona", - "author_inst": "Instituto Goncalo Moniz Fundacao Oswaldo Cruz" - }, - { - "author_name": "Moyra M. Portilho", - "author_inst": "Instituto Goncalo Moniz Fundacao Oswaldo Cruz" - }, - { - "author_name": "Guilherme S. Riberiro", - "author_inst": "Instituto Goncalo Moniz Fundacao Oswaldo Cruz" - }, - { - "author_name": "Mitermayer G. Reis", - "author_inst": "Instituto Goncalo Moniz Fundacao Oswaldo Cruz" + "author_name": "Amy K Johnson", + "author_inst": "Ann & Robert H. Lurie Children's Hospital of Chicago" }, { - "author_name": "Federico Costa", - "author_inst": "Universidade Federal da Bahia" + "author_name": "Runa Bhaumik", + "author_inst": "University of Illinois at Chicago" }, { - "author_name": "Derek A.T. Cummings", - "author_inst": "University of Florida" + "author_name": "Debarghya Nandi", + "author_inst": "University of Illinois at Chicago" }, { - "author_name": "Albert I. Ko", - "author_inst": "Yale University" + "author_name": "Abhishikta Roy", + "author_inst": "University of Illinois at Chicago" }, { - "author_name": "Mariam O. Fofana", - "author_inst": "Yale University" + "author_name": "Supriya D Mehta", + "author_inst": "Rush University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "sexual and reproductive health" }, { "rel_doi": "10.1101/2022.02.14.22270958", @@ -367620,47 +366951,35 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.02.13.480238", - "rel_title": "SARS-CoV-2 Permissive Glioblastoma Cell Line for High Throughput Antiviral Screening", + "rel_doi": "10.1101/2022.02.13.480261", + "rel_title": "Omicron Spike protein has a positive electrostatic surface that promotes ACE2 recognition and antibody escape", "rel_date": "2022-02-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.13.480238", - "rel_abs": "Despite the great success of the administered vaccines against SARS-CoV-2, the virus can still spread, as evidenced by the current circulation of the highly contagious Omicron variant. This emphasizes the additional need to develop effective antiviral countermeasures. In the context of early preclinical studies for antiviral assessment, robust cellular infection systems are required to screen drug libraries. In this study, we reported the implementation of a human glioblastoma cell line, stably expressing ACE2, in a SARS-CoV-2 cytopathic effect (CPE) reduction assay. These glioblastoma cells, designated as U87.ACE2+, expressed ACE2 and cathepsin B abundantly, but had low cellular levels of TMPRSS2 and cathepsin L. The U87.ACE2+ cells fused highly efficiently and quickly with SARS-CoV-2 spike expressing cells. Furthermore, upon infection with SARS-CoV-2 wild-type virus, the U87.ACE2+ cells displayed rapidly a clear CPE that resulted in complete cell lysis and destruction of the cell monolayer. By means of several readouts we showed that the U87.ACE2+ cells actively replicate SARS-CoV-2. Interestingly, the U87.ACE2+ cells could be successfully implemented in an MTS-based colorimetric CPE reduction assay, providing IC50 values for Remdesivir in the low nanomolar range. Lastly, the U87.ACE2+ cells were consistently permissive to all tested SARS-CoV-2 variants of concern, including the current Omicron variant. Thus, ACE2 expressing glioblastoma cells are highly permissive to SARS-CoV-2 with productive viral replication and with the induction of a strong CPE that can be utilized in high-throughput screening platforms.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.13.480261", + "rel_abs": "High transmissibility is a hallmark of the Omicron variant of SARS-CoV-2. Understanding the molecular determinants of Omicrons transmissibility will impact development of intervention strategies. Here we map the electrostatic potential surface of the Spike protein to show that major SARS-CoV-2 variants have accumulated positive charges in solvent-exposed regions of the Spike protein, especially its ACE2-binding interface. Significantly, the Omicron Spike-ACE2 complex has complementary electrostatic surfaces. In contrast, interfaces between Omicron and neutralizing antibodies tend to have similar positively charged surfaces. Structural modeling demonstrates that the electrostatic property of Omicrons Spike receptor binding domain (S RBD) plays a role in enhancing ACE2 recognition and destabilizing Spike-antibody complexes. Collectively, our structural analysis implies that Omicron S RBD interaction interfaces have been optimized to simultaneously promote access to human ACE2 receptors and evade antibodies. These findings suggest that electrostatic interactions are a major contributing factor for increased Omicron transmissibility relative to other variants.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Emiel Vanhulle", - "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology & Chemotherapy" - }, - { - "author_name": "Joren Stroobants", - "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology & Chemotherapy" - }, - { - "author_name": "Becky Provinciael", - "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology & Chemotherapy" - }, - { - "author_name": "Anita Camps", - "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology & Chemotherapy" + "author_name": "Hin Hark Gan", + "author_inst": "New York University" }, { - "author_name": "Sam Noppen", - "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology & Chemotherapy" + "author_name": "John Zinno", + "author_inst": "New York University" }, { - "author_name": "Piet Maes", - "author_inst": "KU Leuven, Rega Institute for Medical Research" + "author_name": "Fabio Piano", + "author_inst": "NYU" }, { - "author_name": "Kurt Vermeire", - "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology & Chemotherapy" + "author_name": "Kris Gunsalus", + "author_inst": "New York University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2022.02.10.22270744", @@ -369369,69 +368688,81 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.02.08.22270495", - "rel_title": "First cases of infection with the 21L/BA.2 Omicron variant in Marseille, France", + "rel_doi": "10.1101/2022.02.09.22270718", + "rel_title": "Differential antibody production by symptomatology in SARS-CoV-2 convalescent individuals", "rel_date": "2022-02-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.08.22270495", - "rel_abs": "The SARS-CoV-2 21K/BA.1, 21L/BA.2, and BA.3 Omicron variants have recently emerged worldwide. To date, the 21L/BA.2 Omicron variant has remained very minority globally but became predominant in Denmark instead of the 21K/BA.1 variant. Here we describe the first cases diagnosed with this variant in south-eastern France. We identified thirteen cases using variant-specific qPCR and next-generation sequencing between 28/11/2021 and 31/01/2022, the first two cases being diagnosed in travellers returning from Tanzania. Overall, viral genomes displayed a mean ({+/-}standard deviation) number of 65.9{+/-}2.5 (range, 61-69) nucleotide substitutions and 31.0{+/-}8.3 (27-50) nucleotide deletions, resulting in 49.6{+/-}2.2 (45-52) amino acid substitutions (including 28 in the spike protein) and 12.4{+/-}1.1 (12-15) amino acid deletions. Phylogeny showed the distribution in three different clusters of these genomes, which were most closely related to genomes from England and South Africa, from Singapore and Nepal, or from France and Denmark. Structural predictions pointed out a significant enlargement and flattening of the 21L/BA.2 N-terminal domain surface compared with that of the 21K/BA.2 Omicron variant, which may facilitate initial viral interactions with lipid rafts. Close surveillance is needed at global, country and center scales to monitor the incidence and clinical outcome of the 21L/BA.2 Omicron variant.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.09.22270718", + "rel_abs": "The association between COVID-19 symptoms and antibody responses against SARS-CoV-2 is poorly characterized. We analyzed antibody levels in individuals with known SARS-CoV-2 infection to identify potential antibody-symptom associations. Convalescent plasma from 216 SARS-CoV-2 RNA+ individuals with symptomatology information were tested for the presence of IgG to the spike S1 subunit (Euroimmun ELISA), IgG to receptor binding domain (RBD, CoronaCHEK rapid test), and for IgG, IgA, and IgM to nucleocapsid (N, Bio-Rad ELISA). Logistic regression was used to estimate the odds of having a COVID-19 symptom from the antibody response, adjusting for sex and age. Cough strongly associated with antibodies against S1 (adjusted odds ratio [aOR]= 5.33; 95% CI from 1.51 to 18.86) and RBD (aOR=4.36; CI 1.49, 12.78). In contrast, sore throat significantly associated with the absence of antibodies to S1 and N (aOR=0.25; CI 0.08, 0.80 and aOR=0.31; 0.11, 0.91). Similarly, lack of symptoms associated with the absence of antibodies to N and RBD (aOR=0.16; CI 0.03, 0.97 and aOR=0.16; CI 0.03, 1.01). Cough appeared to be correlated with a seropositive result, suggesting that SARS-CoV-2 infected individuals exhibiting lower respiratory symptoms generate a robust antibody response. Conversely, those without symptoms or limited to a sore throat while infected with SARS-CoV-2 were likely to lack a detectable antibody response. These findings strongly support the notion that severity of infection correlates with robust antibody response.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Philippe Colson", - "author_inst": "IHU Mediterranee Infection" + "author_name": "Sharada Saraf", + "author_inst": "NIAID DIR: National Institute of Allergy and Infectious Diseases Division of Intramural Research" }, { - "author_name": "Jeremy Delerce", - "author_inst": "IHU Mediterranee Infection" + "author_name": "Xianming Zhu", + "author_inst": "Johns Hopkins University - Homewood Campus: Johns Hopkins University" }, { - "author_name": "Mamadou Beye", - "author_inst": "IHU Mediterranee Infection" + "author_name": "Ruchee Shrestha", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Anthony LEVASSEUR", - "author_inst": "Aix-Marseille University" + "author_name": "Tania S. Bonny", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Celine Boschi", - "author_inst": "IHU Mediterranee Infection" + "author_name": "Owen R. Baker", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Linda Houhamdi", - "author_inst": "IHU Mediterranee Infection" + "author_name": "Evan J. Beck", + "author_inst": "NIAID DIR: National Institute of Allergy and Infectious Diseases Division of Intramural Research" }, { - "author_name": "Herve Tissot-Dupont", - "author_inst": "IHU Mediterranee Infection" + "author_name": "Reinaldo E. Fernandez", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Nouara Yahi", - "author_inst": "Aix-Marseille university" + "author_name": "Yolanda Eby", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Matthieu Million", - "author_inst": "IHU Mediterranee Infection" + "author_name": "Olivia Akinde", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Bernard LA SCOLA", - "author_inst": "IHU Mediterranee Infection" + "author_name": "Jessica E. Ruff", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Jacques Fantini", - "author_inst": "Aix-Marseille University" + "author_name": "Patrizio Caturegli", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Didier Raoult", - "author_inst": "Aix Marseille Universite IHU Mediterranee Infection" + "author_name": "Andrew D. Redd", + "author_inst": "NIAID DIR: National Institute of Allergy and Infectious Diseases Division of Intramural Research" }, { - "author_name": "Pierre-Edouard Fournier", - "author_inst": "IHU Mediterranee Infection" + "author_name": "Evan M. Bloch", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Thomas C. Quinn", + "author_inst": "NIAID DIR: National Institute of Allergy and Infectious Diseases Division of Intramural Research" + }, + { + "author_name": "Aaron AR Tobian", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Oliver Laeyendecker", + "author_inst": "NIAID" } ], "version": "1", - "license": "cc_by", + "license": "cc0", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -371195,73 +370526,97 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.02.07.479306", - "rel_title": "Antibody Evasion Properties of SARS-CoV-2 Omicron Sublineages", + "rel_doi": "10.1101/2022.02.07.479419", + "rel_title": "Boosting with Omicron-matched or historical mRNA vaccines increases neutralizing antibody responses and protection against B.1.1.529 infection in mice", "rel_date": "2022-02-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.07.479306", - "rel_abs": "The identification of the Omicron variant (B.1.1.529.1 or BA.1) of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) in Botswana in November 20211 immediately raised alarms due to the sheer number of mutations in the spike glycoprotein that could lead to striking antibody evasion. We2 and others3-6 recently reported results in this Journal confirming such a concern. Continuing surveillance of Omicron evolution has since revealed the rise in prevalence of two sublineages, BA.1 with an R346K mutation (BA.1+R346K) and B.1.1.529.2 (BA.2), with the latter containing 8 unique spike mutations while lacking 13 spike mutations found in BA.1. We therefore extended our studies to include antigenic characterization of these new sublineages. Polyclonal sera from patients infected by wild-type SARS-CoV-2 or recipients of current mRNA vaccines showed a substantial loss in neutralizing activity against both BA.1+R346K and BA.2, with drops comparable to that already reported for BA.12,3,5,6. These findings indicate that these three sublineages of Omicron are antigenically equidistant from the wild-type SARS-CoV-2 and thus similarly threaten the efficacies of current vaccines. BA.2 also exhibited marked resistance to 17 of 19 neutralizing monoclonal antibodies tested, including S309 (sotrovimab)7, which had retained appreciable activity against BA.1 and BA.1+R346K2-4,6. This new finding shows that no presently approved or authorized monoclonal antibody therapy could adequately cover all sublineages of the Omicron variant.", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.07.479419", + "rel_abs": "The B.1.1.529 Omicron variant jeopardizes vaccines designed with early pandemic spike antigens. Here, we evaluated in mice the protective activity of the Moderna mRNA-1273 vaccine against B.1.1.529 before or after boosting with preclinical mRNA-1273 or mRNA-1273.529, an Omicron-matched vaccine. Whereas two doses of mRNA-1273 vaccine induced high levels of serum neutralizing antibodies against historical WA1/2020 strains, levels were lower against B.1.1.529 and associated with infection and inflammation in the lung. A primary vaccination series with mRNA-1273.529 potently neutralized B.1.1.529 but showed limited inhibition of historical or other SARS-CoV-2 variants. However, boosting with mRNA-1273 or mRNA-1273.529 vaccines increased serum neutralizing titers and protection against B.1.1.529 infection. Nonetheless, the levels of inhibitory antibodies were higher, and viral burden and cytokines in the lung were slightly lower in mice given the Omicron-matched mRNA booster. Thus, in mice, boosting with mRNA-1273 or mRNA-1273.529 enhances protection against B.1.1.529 infection with limited differences in efficacy measured.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Sho Iketani", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Baoling Ying", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Lihong Liu", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Suzanne M. Scheaffer", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Yicheng Guo", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Bradley Whitener", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Liyuan Liu", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Chieh-Yu Liang", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Yiming Huang", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Oleksandr Dmytrenko", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Maple Wang", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Samantha Mackin", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Yang Luo", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Kai Wu", + "author_inst": "Moderna, Inc." }, { - "author_name": "Jian Yu", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Diana Lee", + "author_inst": "Moderna, Inc." }, { - "author_name": "Michael T. Yin", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Laura E. Avena", + "author_inst": "Moderna, Inc." }, { - "author_name": "Magdalena E. Sobieszczyk", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Zhenlu Chong", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Yaoxing Huang", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "James Brett Case", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Harris H. Wang", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "LingZhi Ma", + "author_inst": "Moderna, Inc." }, { - "author_name": "Zizhang Sheng", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Thu Kim", + "author_inst": "Moderna, Inc." }, { - "author_name": "David D. Ho", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Caralyn Sein", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Angela Woods", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Andrea Carfi", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Sayda M. Elbashir", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Darin K Edwards", + "author_inst": "Moderna Inc" + }, + { + "author_name": "Larissa B. Thackray", + "author_inst": "Washington University School of Medicine" + }, + { + "author_name": "Michael S. Diamond", + "author_inst": "Washington University School of Medicine" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "microbiology" }, @@ -373237,155 +372592,35 @@ "category": "gastroenterology" }, { - "rel_doi": "10.1101/2022.02.05.22270327", - "rel_title": "SARS-CoV-2 infects, replicates, elevates angiotensin II and activates immune cells in human testes", + "rel_doi": "10.1101/2022.02.06.22270549", + "rel_title": "COVID-19 excess death rate in Eastern European countries associated with weaker regulation implementation and lower vaccination coverage", "rel_date": "2022-02-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.05.22270327", - "rel_abs": "Although much has been published since the first cases of COVID-19, there remain unanswered questions regarding SARS-CoV-2 impact on testes and the potential consequences for reproductive health. We investigated testicular alterations in deceased COVID-19-patients, the precise location of the virus, its replicative activity, and the molecules involved in the pathogenesis. We found that SARS-CoV-2 testicular tropism is higher than previously thought and that reliable viral detection in the testis requires sensitive nanosensoring or RT-qPCR using a specific methodology. Macrophages and spermatogonial cells are the main SARS-CoV-2 lodging sites and where new virions form inside the Endoplasmic Reticulum Golgi Intermediate Complex. Moreover, we showed infiltrative infected monocytes migrating into the testicular parenchyma. SARS-CoV-2 maintains its replicative and infective abilities long after the patients infection, suggesting that the testes may serve as a viral sanctuary. Further, infected testes show thickening of the tunica propria, germ cell apoptosis, Sertoli cell barrier loss, evident hemorrhage, angiogenesis, Leydig cell inhibition, inflammation, and fibrosis. Finally, our findings indicate that high angiotensin II levels and activation of mast cells and macrophages may be critical for testicular pathogenesis. Importantly, our data suggest that patients who become critically ill exhibit severe damages and may harbor the active virus in testes.", - "rel_num_authors": 34, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.06.22270549", + "rel_abs": "AimThe objective of this analysis was to assess the association of excess COVID-19 mortality with regulation enforcement and vaccination rate in selected countries.\n\nMethodsThis analysis included 50 countries pertinent to the WHO European Region, in addition to USA and Canada. Excess mortality and vaccination data were retrieved from \"Our World In Data\" database, while regulation implementation was measured from a well-respected, standardized measure. Outpatient visits were also included in the analysis. Multiple linear regression was used to assess the independent association between excess mortality and each covariate.\n\nResultsExcess mortality increased by 4.1/100 000 for every percent decrease in vaccination rate and with 6/100 000 for every decreased unit in the regulatory implementation score a country achieved in the Rule of Law Index.\n\nConclusionDegree of regulation enforcement, likely including public health measure enforcement, may be an important factor in controlling COVID-19s deleterious health impacts.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Guilherme M J Costa", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Samyra MSN Lacerda", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Andre F.A. Figueiredo", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Natalia T. Wnuk", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Marcos R. Brener", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Gabriel H. Campolina-Silva", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Andrea Kauffmann-Zeh", - "author_inst": "Clinica MF Fertilidade Masculina" - }, - { - "author_name": "Lucila GG Pacifico", - "author_inst": "Clinica MF Fertilidade Masculina" - }, - { - "author_name": "Alice F. Versiani", - "author_inst": "Department of Pathology, University of Texas Medical Branch, Galveston, Texas, U.S.A." - }, - { - "author_name": "Lidia M. Andrade", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Maisa M. Antunes", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Fernanda R. Souza", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Geovanni D. Cassali", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Andre L. Caldeira-Brant", - "author_inst": "Department of Obstetrics, Gynecology, and Reproductive Sciences, Magee-Womens Research Institute, University of Pittsburgh School of Medicine, Pittsburgh, USA" - }, - { - "author_name": "Helio Chiarini-Garcia", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Vivian V. Costa", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Flavio G da Fonseca", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Mauricio L Nogueira", - "author_inst": "Faculdade de Medicina de Sao Jose do Rio Preto" - }, - { - "author_name": "Guilherme R. F. Campos", - "author_inst": "Faculdade de Medicina de Sao Jose do Rio Preto" - }, - { - "author_name": "Lucas M. Kangussu", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Estefania M. N. Martins", - "author_inst": "Centro de Desenvolvimento da Tecnologia Nuclear-CDTN/CNEN" - }, - { - "author_name": "Loudiana M. Antonio", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Cintia Bittar", - "author_inst": "Universidade Estadual Paulista, Sao Jose do Rio Preto" - }, - { - "author_name": "Paula Rahal", - "author_inst": "Universidade Estadual Paulista, Sao Jose do Rio Preto" - }, - { - "author_name": "Renato S. Aguiar", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Barbara P. Mendes", - "author_inst": "Clinica MF Fertilidade Masculina" - }, - { - "author_name": "Marcela S. Procopio", - "author_inst": "Clinica MF Fertilidade Masculina" - }, - { - "author_name": "Thiago P. Furtado", - "author_inst": "Clinica MF Fertilidade Masculina" - }, - { - "author_name": "Yuri L Guimaraes", - "author_inst": "Departamentos de Urologia e de Reproducao Humana da Rede Mater Dei de Saude" - }, - { - "author_name": "Gustavo B Menezes", - "author_inst": "Universidade Federal de Minas Gerais" - }, - { - "author_name": "Ana Martinez-Marchal", - "author_inst": "Department of Obstetrics, Gynecology, and Reproductive Sciences, Magee-Womens Research Institute, University of Pittsburgh School of Medicine, Pittsburgh, USA" + "author_name": "Alban Ylli", + "author_inst": "Tirana University of Medicine. Faculty of Medicine" }, { - "author_name": "Miguel Brieno-Enriquez", - "author_inst": "Department of Obstetrics, Gynecology, and Reproductive Sciences, Magee-Womens Research Institute, University of Pittsburgh School of Medicine, Pittsburgh, USA" + "author_name": "Genc Burazeri", + "author_inst": "Tirana University of Medicine, Albania. Department of International Health, School CAPHRI (Care and Public Health Research Institute), Maastricht University, Ma" }, { - "author_name": "Kyle E. Orwig", - "author_inst": "Department of Obstetrics, Gynecology, and Reproductive Sciences, Magee-Womens Research Institute, University of Pittsburgh School of Medicine, Pittsburgh, USA" + "author_name": "Yan Yan Wu", + "author_inst": "Office of Public Health Studies, University of Hawaii at Manoa, Honolulu, Hawaii, USA" }, { - "author_name": "Marcelo H. Furtado", - "author_inst": "Clinica MF Fertilidade Masculina" + "author_name": "Tetine Sentell", + "author_inst": "Office of Public Health Studies, University of Hawaii at Manoa, Honolulu, Hawaii, USA" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "sexual and reproductive health" + "category": "health policy" }, { "rel_doi": "10.1101/2022.02.07.22270555", @@ -375331,43 +374566,51 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.02.05.479221", - "rel_title": "Mechanistic origin of different binding affinities of SARS-CoV and SARS-CoV-2 spike RBDs to human ACE2", + "rel_doi": "10.1101/2022.02.07.479348", + "rel_title": "An mRNA vaccine candidate for the SARS-CoV-2 Omicron variant", "rel_date": "2022-02-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.05.479221", - "rel_abs": "The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein mediates viral entry into host cells through binding to the cell-surface receptor angiotensin-converting enzyme 2 (ACE2). It has been shown that SARS-CoV-2 RBD (RBDCoV2) has a higher binding affinity to human ACE2 than its highly homologous SARS-CoV RBD (RBDCoV), for which the mechanistic reasons still remain to be elucidated. Here, we used the multiple-replica molecular dynamics (MD) simulations, molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) binding free energy calculations, and interface residue contact network (IRCN) analysis approach to explore the mechanistic origin of different ACE2 binding affinities of these two RBDs. The results demonstrate that, when compared to the RBDCoV2-ACE2 complex, the RBDCoV-ACE2 complex features the enhanced overall structural fluctuations and inter-protein positional movements and increased conformational entropy and diversity. The inter-protein electrostatic attractive interactions are a dominant force in determining the high ACE2 affinities of both RBDs, while the significantly strengthened electrostatic forces of attraction of ACE2 to RBDCoV2 determine the higher ACE2 binding affinity of RBDCoV2 than of RBDCoV. Comprehensive comparative analyses of the residue binding free energy components and IRCNs reveal that, although any RBD residue substitution involved in the charge change can significantly impact the inter-protein electrostatic interaction strength, it is the substitutions at the RBD interface that lead to the overall stronger electrostatic attractive force of RBDCoV2-ACE2, which in turn not only tightens the interface packing and suppresses the dynamics of RBDCoV2-ACE2, but also enhances the ACE2 binding affinity of RBDCoV2 compared to that of RBDCoV. Since the RBD residue substitutions involving gain/loss of the positively/negatively charged residues, in particular those near/at the binding interfaces with the potential to form hydrogen bonds and/or salt bridges with ACE2, can greatly enhance the ACE2 binding affinity, the SARS-CoV-2 variants carrying such mutations should be paid special attention to.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.07.479348", + "rel_abs": "The newly emerged Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) contains more than 30 mutations on the spike protein, 15 of which are located within the receptor binding domain (RBD). Consequently, Omicron is able to extensively escape existing neutralizing antibodies and may therefore compromise the efficacy of current vaccines based on the original strain, highlighting the importance and urgency of developing effective vaccines against Omicron. Here we report the rapid generation and evaluation of an mRNA vaccine candidate specific to Omicron. This mRNA vaccine encodes the RBD of Omicron (designated RBD-O) and is formulated with lipid nanoparticle. Two doses of the RBD-O mRNA vaccine efficiently induce neutralizing antibodies in mice; however, the antisera are effective only on the Omicron variant but not on the wildtype and Delta strains, indicating a narrow neutralization spectrum. It is noted that the neutralization profile of the RBD-O mRNA vaccine is opposite to that observed for the mRNA vaccine expressing the wildtype RBD (RBD-WT). Our work demonstrates the feasibility and potency of an RBD-based mRNA vaccine specific to Omicron, providing important information for further development of bivalent or multivalent SARS-CoV-2 vaccines with broad-spectrum efficacy.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Zhi-Bi Zhang", - "author_inst": "State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan & School of Life Sciences, Yunnan University, Kunming 650091, China;Yunnan Key " + "author_name": "Jinkai Zang", + "author_inst": "Institut Pasteur of Shanghai Chinese Academy of Sciences" }, { - "author_name": "Yuan-Ling Xia", - "author_inst": "State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan & School of Life Sciences, Yunnan University, Kunming 650091, China" + "author_name": "Chao Zhang", + "author_inst": "Institut Pasteur of Shanghai, Chinese Academy of Sciences" }, { - "author_name": "Jian-Xin Shen", - "author_inst": "State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan & School of Life Sciences, Yunnan University, Kunming 650091, China" + "author_name": "Yannan Yin", + "author_inst": "Institut Pasteur of Shanghai, Chinese Academy of Sciences" }, { - "author_name": "Wen-Wen Du", - "author_inst": "State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan & School of Life Sciences, Yunnan University, Kunming 650091, China" + "author_name": "Shiqi Xu", + "author_inst": "Institut Pasteur of Shanghai, Chinese Academy of Sciences" }, { - "author_name": "Yun-Xin Fu", - "author_inst": "Human Genetics Center and Division of Biostatistics, School of Public Health, the University of Texas Health Science Center, Houston, TX 77030, USA" + "author_name": "Weihua Qiao", + "author_inst": "Institut Pasteur of Shanghai, Chinese Academy of Sciences" }, { - "author_name": "Shu-Qun Liu", - "author_inst": "State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan & School of Life Sciences, Yunnan University, Kunming 650091, China" + "author_name": "Dimitri LAVILLETTE", + "author_inst": "Institut Pasteur Shanghai Chine Academy of Sciences" + }, + { + "author_name": "HaiKun Wang", + "author_inst": "Institut Pasteur of Shanghai Chinese Academy of Sciences" + }, + { + "author_name": "Zhong Huang", + "author_inst": "Institut Pasteur of Shanghai" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "biophysics" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.02.06.479332", @@ -377833,163 +377076,23 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.02.04.22270474", - "rel_title": "Interactions among 17 respiratory pathogens: a cross-sectional study using clinical and community surveillance data", + "rel_doi": "10.1101/2022.02.04.22270491", + "rel_title": "USA Winter 2021 CoVID-19 Resurgence Post-Christmas Update", "rel_date": "2022-02-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.04.22270474", - "rel_abs": "BackgroundCo-circulating respiratory pathogens can interfere with or promote each other, leading to important effects on disease epidemiology. Estimating the magnitude of pathogen-pathogen interactions from clinical specimens is challenging because sampling from symptomatic individuals can create biased estimates.\n\nMethodsWe conducted an observational, cross-sectional study using samples collected by the Seattle Flu Study between 11 November 2018 and 20 August 2021. Samples that tested positive via RT-qPCR for at least one of 17 potential respiratory pathogens were included in this study. Semi-quantitative cycle threshold (Ct) values were used to measure pathogen load. Differences in pathogen load between monoinfected and coinfected samples were assessed using linear regression adjusting for age, season, and recruitment channel.\n\nResults21,686 samples were positive for at least one potential pathogen. Most prevalent were rhinovirus (33{middle dot}5%), Streptococcus pneumoniae (SPn, 29{middle dot}0%), SARS-CoV-2 (13.8%) and influenza A/H1N1 (9{middle dot}6%). 140 potential pathogen pairs were included for analysis, and 56 (40%) pairs yielded significant Ct differences (p < 0.01) between monoinfected and co-infected samples. We observed no virus-virus pairs showing evidence of significant facilitating interactions, and found significant viral load decrease among 37 of 108 (34%) assessed pairs. Samples positive with SPn and a virus were consistently associated with increased SPn load.\n\nConclusionsViral load data can be used to overcome sampling bias in studies of pathogen-pathogen interactions. When applied to respiratory pathogens, we found evidence of viral-SPn facilitation and several examples of viral-viral interference. Multipathogen surveillance is a cost-efficient data collection approach, with added clinical and epidemiological informational value over single-pathogen testing, but requires careful analysis to mitigate selection bias.", - "rel_num_authors": 36, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.04.22270491", + "rel_abs": "We have successfully modeled every USA CoVID-19 wave using: O_FD O_INLINEFIG[Formula 1]C_INLINEFIGM_FD(1)C_FD where N (t) is the total number of new CoVID-19 cases above a prior baseline, and tR sets the doubling time tdbl = tR (ln 2). The new parameters {S ;{delta} o} measure mitigation efforts among the uninfected population, with {S > 0} being associated with Social Distancing and vaccinations ; while {{delta}o > 0 }is associated with mask-wearing, which gives a faster [Formula] post-peak drop-off. The predicted pandemic wave end is when N (t) no longer increases.\n\nUsing data from 11/15/21-12/30/21, our prior medrxiv.org preprint* showed this initial Omicron CoVID-19 wave had values that matched the initial stage of the prior USA Winter 2020 resurgence {tR {approx}8 05 days ; S {approx} 0 011 / day}, when practically no one was vaccinated. In addition, this initial Winter 2021 wave showed virtually no mask-wearing {{delta}o{approx} x 0 001 10-3 / day}, making it capable of infecting virtually everyone. These parameter values indicated that the Omicron variant was likely evading the vaccines in people who thought they were protected.\n\nAs a result, stopping the Omicron CoVID-19 spread must once again rely on enhanced Social Distancing and mask-wearing, just like the initial pandemic wave in March 2020. Analyzing the USA follow-on data from 12/25/21-1/31/22 shows that people did exactly that after the Christmas Holiday season, resulting in the following model parameters and values: O_FD O_INLINEFIG[Formula 2]C_INLINEFIGM_FD(2)C_FD for this wave by itself, with all prior waves subtracted out as a baseline. Combining all the USA CoVID-19 waves gives these updated totals: O_FD O_INLINEFIG[Formula 3]C_INLINEFIGM_FD(3)C_FD assuming no future CoVID-19 Resurgence (with 4 Figures).\n\n*(10.1101_2021.10.15.21265078)", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Roy Burstein", - "author_inst": "Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA" - }, - { - "author_name": "Bejamin M Althouse", - "author_inst": "Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA; Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA" - }, - { - "author_name": "Amanda Adler", - "author_inst": "Seattle Children's Research Institute, Seattle WA USA" - }, - { - "author_name": "Adam Akullian", - "author_inst": "Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA" - }, - { - "author_name": "Elizabeth Brandstetter", - "author_inst": "Department of Medicine, University of Washington, Seattle WA USA" - }, - { - "author_name": "Shari Cho", - "author_inst": "Brotman Baty Institute for Precision Medicine, Seattle WA USA" - }, - { - "author_name": "Erin Chung", - "author_inst": "Department of Pediatrics, University of Washington, Seattle Children's Hospital, Seattle" - }, - { - "author_name": "Anne Emmanuels", - "author_inst": "Department of Medicine, University of Washington, Seattle WA USA" - }, - { - "author_name": "Kairsten Fay", - "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA" - }, - { - "author_name": "Luis Gamboa", - "author_inst": "Brotman Baty Institute for Precision Medicine, Seattle WA USA" - }, - { - "author_name": "Peter Han", - "author_inst": "Brotman Baty Institute for Precision Medicine, Seattle WA USA" - }, - { - "author_name": "Kristen Huden", - "author_inst": "Department of Medicine, University of Washington, Seattle WA USA" - }, - { - "author_name": "Misja Ilcisin", - "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA" - }, - { - "author_name": "Mandy Izzo", - "author_inst": "Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA" - }, - { - "author_name": "Michael L Jackson", - "author_inst": "Kaiser Permanente Washington Health Research Institute, Seattle WA USA" - }, - { - "author_name": "Ashley E Kim", - "author_inst": "Department of Medicine, University of Washington, Seattle WA USA" - }, - { - "author_name": "Louise Kimball", - "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA" - }, - { - "author_name": "Kirstein Lacombe", - "author_inst": "Seattle Children's Research Institute, Seattle WA USA" - }, - { - "author_name": "Jover Lee", - "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA" - }, - { - "author_name": "Jennifer K Logue", - "author_inst": "Department of Medicine, University of Washington, Seattle WA USA" - }, - { - "author_name": "Julia Rogers", - "author_inst": "Department of Medicine, University of Washington, Seattle WA USA" - }, - { - "author_name": "Thomas R Sibley", - "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA" - }, - { - "author_name": "Katrina Van Raay", - "author_inst": "Brotman Baty Institute for Precision Medicine, Seattle WA USA" - }, - { - "author_name": "Edward Wenger", - "author_inst": "Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA" - }, - { - "author_name": "Caitlin R Wolf", - "author_inst": "Department of Medicine, University of Washington, Seattle WA USA" - }, - { - "author_name": "Michael Boeckh", - "author_inst": "Department of Medicine, University of Washington, Seattle WA USA; Brotman Baty Institute for Precision Medicine, Seattle WA USA; Vaccine and Infectious Disease " - }, - { - "author_name": "Helen Chu", - "author_inst": "Department of Medicine, University of Washington, Seattle WA USA" - }, - { - "author_name": "Jeff Duchin", - "author_inst": "Department of Medicine, University of Washington, Seattle WA USA; Public Health Seattle & King County, Seattle WA USA" - }, - { - "author_name": "Mark Reider", - "author_inst": "Brotman Baty Institute for Precision Medicine, Seattle WA USA" - }, - { - "author_name": "Jay Shendure", - "author_inst": "Brotman Baty Institute for Precision Medicine, Seattle WA USA; Department of Genome Sciences, University of Washington, Seattle WA USA; Howard Hughes Medical In" - }, - { - "author_name": "Lea M Starita", - "author_inst": "Brotman Baty Institute for Precision Medicine, Seattle WA USA; Department of Genome Sciences, University of Washington, Seattle WA USA" - }, - { - "author_name": "Cecile Viboud", - "author_inst": "Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA." - }, - { - "author_name": "Trevor Bedfor", - "author_inst": "Brotman Baty Institute for Precision Medicine, Seattle WA USA; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA; " - }, - { - "author_name": "Janet A Englund", - "author_inst": "Seattle Children's Research Institute, Seattle WA USA; Brotman Baty Institute for Precision Medicine, Seattle WA USA" - }, - { - "author_name": "Michael Famulare", - "author_inst": "Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA" - }, - { - "author_name": "- Seattle Flu Study and SCAN Investigators", - "author_inst": "" + "author_name": "Genghmun Eng", + "author_inst": "Retired Scientist" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.02.04.22270433", @@ -379839,255 +378942,75 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2022.02.03.22270410", - "rel_title": "SurvMaximin: Robust Federated Approach to Transporting Survival Risk Prediction Models", + "rel_doi": "10.1101/2022.02.03.478946", + "rel_title": "Antibody affinity and concentration of convalescent sera provide context for reduced SARS-CoV-2 Omicron spike affinity of therapeutic antibodies", "rel_date": "2022-02-04", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.03.22270410", - "rel_abs": "ObjectiveFor multi-center heterogeneous Real-World Data (RWD) with time-to-event outcomes and high-dimensional features, we propose the SurvMaximin algorithm to estimate Cox model feature coefficients for a target population by borrowing summary information from a set of health care centers without sharing patient-level information.\n\nMaterials and MethodsFor each of the centers from which we want to borrow information to improve the prediction performance for the target population, a penalized Cox model is fitted to estimate feature coefficients for the center. Using estimated feature coefficients and the covariance matrix of the target population, we then obtain a SurvMaximin estimated set of feature coefficients for the target population. The target population can be an entire cohort comprised of all centers, corresponding to federated learning, or can be a single center, corresponding to transfer learning.\n\nResultsSimulation studies and a real-world international electronic health records application study, with 15 participating health care centers across three countries (France, Germany, and the U.S.), show that the proposed SurvMaximin algorithm achieves comparable or higher accuracy compared with the estimator using only the information of the target site and other existing methods. The SurvMaximin estimator is robust to variations in sample sizes and estimated feature coefficients between centers, which amounts to significantly improved estimates for target sites with fewer observations.\n\nConclusionsThe SurvMaximin method is well suited for both federated and transfer learning in the high-dimensional survival analysis setting. SurvMaximin only requires a one-time summary information exchange from participating centers. Estimated regression vectors can be very heterogeneous. SurvMaximin provides robust Cox feature coefficient estimates without outcome information in the target population and is privacy-preserving.", - "rel_num_authors": 59, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.03.478946", + "rel_abs": "We assessed the affinities of the therapeutic monoclonal antibodies (mAbs) cilgavimab, tixagevimab, sotrovimab, casirivimab, and imdevimab to the receptor binding domain (RBD) of wild type, Delta, and Omicron spike. The Omicron RBD affinities of cilgavimab, tixagevimab, casirivimab, and imdevimab decreased by at least two orders of magnitude relative to their wild type equivalents, whereas sotrovimab binding was less severely impacted. These affinity reductions correlate with reduced antiviral activities of these antibodies, suggesting that simple affinity measurements can serve as an indicator for activity before challenging and time-consuming virus neutralization assays are performed. We also compared the properties of these antibodies to serological fingerprints (affinities and concentrations) of wild type RBD specific antibodies in 74 convalescent sera. The affinities of the therapeutic mAbs to wild type and Delta RBD were in the same range as the polyclonal response in the convalescent sera indicative of their high antiviral activities against these variants. However, for Omicron RBD, only sotrovimab retained affinities that were within the range of the polyclonal response, in agreement with its high activity against Omicron. Serological fingerprints thus provide important context to affinities and antiviral activity of mAb drugs and could guide the development of new therapeutics.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Xuan Wang", - "author_inst": "Harvard T. H. Chan School of Public Health" - }, - { - "author_name": "Harrison G Zhang", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Xin Xiong", - "author_inst": "Harvard T. H. Chan School of Public Health" - }, - { - "author_name": "Chuan Hong", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Griffin M Weber", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Gabriel A Brat", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Clara-Lea Bonzel", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Yuan Luo", - "author_inst": "Northwestern University" - }, - { - "author_name": "Rui Duan", - "author_inst": "Harvard University" - }, - { - "author_name": "Nathan P Palmer", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Meghan R Hutch", - "author_inst": "Northwestern University" - }, - { - "author_name": "Alba Guti\u00e9rrez-Sacrist\u00e1n", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Riccardo Bellazzi", - "author_inst": "University of Pavia, Italy" - }, - { - "author_name": "Luca Chiovato", - "author_inst": "Istituti Clinici Scientifici Maugeri SpA SB IRCCS" - }, - { - "author_name": "Kelly Cho", - "author_inst": "VA Boston Healthcare System" - }, - { - "author_name": "Arianna Dagliati", - "author_inst": "University of Pavia, Italy" - }, - { - "author_name": "Hossein Estiri", - "author_inst": "Massachusetts General Hospital" - }, - { - "author_name": "Noelia Garc\u00eda-Barrio", - "author_inst": "Hospital Universitario 12 de Octubre, Madrid, Spain" - }, - { - "author_name": "Romain Griffier", - "author_inst": "Bordeaux University Hospital / ERIAS - Inserm U1219 BPH" - }, - { - "author_name": "David A Hanauer", - "author_inst": "University of Michigan" - }, - { - "author_name": "Yuk-Lam Ho", - "author_inst": "VA Boston Healthcare System" - }, - { - "author_name": "John H Holmes", - "author_inst": "University of Pennsylvania Perelman School of Medicine" - }, - { - "author_name": "Mark S Keller", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Jeffrey G Klann", - "author_inst": "Massachusetts General Hospital" - }, - { - "author_name": "Sehi L'Yi", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Sara Lozano-Zahonero", - "author_inst": "Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany" - }, - { - "author_name": "Sarah E Maidlow", - "author_inst": "University of Michigan" - }, - { - "author_name": "Adeline Makoudjou", - "author_inst": "Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany" - }, - { - "author_name": "Alberto Malovini", - "author_inst": "Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Italy." - }, - { - "author_name": "Bertrand Moal", - "author_inst": "Bordeaux University Hospital" - }, - { - "author_name": "Jason H Moore", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Michele Morris", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Danielle L Mowery", - "author_inst": "University of Pennsylvania Perelman School of Medicine" - }, - { - "author_name": "Shawn N Murphy", - "author_inst": "Massachusetts General Hospital" - }, - { - "author_name": "Antoine Neuraz", - "author_inst": "H\u00f4pital Necker-Enfants Malade, Assistance Publique H\u00f4pitaux de Paris (APHP), University of Paris" - }, - { - "author_name": "Kee Yuan Ngiam", - "author_inst": "National University Health Systems Singapore" - }, - { - "author_name": "Gilbert S Omenn", - "author_inst": "University of Michigan" - }, - { - "author_name": "Lav P Patel", - "author_inst": "University Of Kansas Medical Center" - }, - { - "author_name": "Miguel Pedrera-Jim\u00e9nez", - "author_inst": "Hospital Universitario 12 de Octubre, Madrid, Spain" - }, - { - "author_name": "Andrea Prunotto", - "author_inst": "Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany" - }, - { - "author_name": "Malarkodi Jebathilagam Samayamuthu", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Fernando J Sanz Vidorreta", - "author_inst": "David Geffen School of Medicine at UCLA" - }, - { - "author_name": "Emily R Schriver", - "author_inst": "University of Pennsylvania Health System" - }, - { - "author_name": "Petra Schubert", - "author_inst": "VA Boston Healthcare System" - }, - { - "author_name": "Pablo Serrano-Balazote", - "author_inst": "Hospital Universitario 12 de Octubre, Madrid, Spain" - }, - { - "author_name": "Andrew M South", - "author_inst": "Brenner Children's, Wake Forest School of Medicine" + "author_name": "Sebastian Fiedler", + "author_inst": "Fluidic Analytics" }, { - "author_name": "Amelia LM Tan", - "author_inst": "Harvard Medical School" + "author_name": "Sean R. A. Devenish", + "author_inst": "Fluidic Analytics" }, { - "author_name": "Byorn W.L. Tan", - "author_inst": "National University Hospital, Singapore" + "author_name": "Alexey S. Morgunov", + "author_inst": "Fluidic Analytics" }, { - "author_name": "Valentina Tibollo", - "author_inst": "Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Italy." + "author_name": "Alison Ilsley", + "author_inst": "Fluidic Analytics" }, { - "author_name": "Patric Tippmann", - "author_inst": "Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany" + "author_name": "Francesco Ricci", + "author_inst": "Fluidic Analytics" }, { - "author_name": "Shyam Visweswaran", - "author_inst": "University of Pittsburgh" + "author_name": "Marc Emmenegger", + "author_inst": "Institute of Neuropathology" }, { - "author_name": "Zongqi Xia", - "author_inst": "University of Pittsburgh" + "author_name": "Vasilis Kosmoliaptsis", + "author_inst": "University of Cambridge" }, { - "author_name": "William Yuan", - "author_inst": "Harvard Medical School" + "author_name": "Elitza S. Theel", + "author_inst": "Mayo Clinic" }, { - "author_name": "Daniela Z\u00f6ller", - "author_inst": "Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany" + "author_name": "John R. Mills", + "author_inst": "Mayo Clinic" }, { - "author_name": "Isaac S Kohane", - "author_inst": "Harvard Medical School" + "author_name": "Anton M. Sholukh", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "- The Consortium for Clinical Characterization of COVID-19 by EHR (4CE)", - "author_inst": "Harvard Medical School" + "author_name": "Adriano A. A. Aguzzi", + "author_inst": "University of Zurich" }, { - "author_name": "Paul Avillach", - "author_inst": "Harvard Medical School" + "author_name": "Akiko Iwasaki", + "author_inst": "Yale University School of Medicine" }, { - "author_name": "Zijian Guo", - "author_inst": "Rutgers, The State University of New Jersey" + "author_name": "Andrew K. Lynn", + "author_inst": "Fluidic Analytics" }, { - "author_name": "Tianxi Cai", - "author_inst": "Harvard Medical School" + "author_name": "Tuomas P. J. Knowles", + "author_inst": "University of Cambridge" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by_nd", + "type": "new results", + "category": "biochemistry" }, { "rel_doi": "10.1101/2022.02.03.22270401", @@ -381769,79 +380692,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.02.02.22270337", - "rel_title": "Impact of SARS-CoV-2 variants on inpatient clinical outcome", + "rel_doi": "10.1101/2022.02.03.21265607", + "rel_title": "BNT162b2, mRNA-1273, and Sputnik V vaccines induce comparable immune responses on a par with severe course of COVID-19", "rel_date": "2022-02-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.02.22270337", - "rel_abs": "BackgroundPrior observation has shown differences in COVID-19 hospitalization rates between SARS-CoV-2 variants, but limited information describes differences in hospitalization outcomes.\n\nMethodsPatients admitted to 5 hospitals with COVID-19 were included if they had hypoxia, tachypnea, tachycardia, or fever, and data to describe SARS-CoV-2 variant, either from whole genome sequencing, or inference when local surveillance showed [≥]95% dominance of a single variant. The average effect of SARS-CoV-2 variant on 14-day risk of severe disease, defined by need for advanced respiratory support, or death was evaluated using models weighted on propensity scores derived from baseline clinical features.\n\nResultsSevere disease or death within 14 days occurred for 950 of 3,365 (28%) unvaccinated patients and 178 of 808 (22%) patients with history of vaccination or prior COVID-19. Among unvaccinated patients, the relative risk of 14-day severe disease or death for Delta variant compared to ancestral lineages was 1.34 (95% confidence interval [CI] 1.13-1.55). Compared to Delta variant, this risk for Omicron patients was 0.78 (95% CI 0.62-0.97) and compared to ancestral lineages was 1.04 (95% CI 0.84-1.24). Among Omicron and Delta infections, patients with history of vaccination or prior COVID-19 had one-half the 14-day risk of severe disease or death (adjusted hazard ratio 0.46, IQR 0.34-0.62) but no significant outcome difference between Delta and Omicron infections.\n\nConclusionsAlthough the risk of severe disease or death for unvaccinated patients with Omicron was lower than Delta, it was similar to ancestral lineages. Severe outcomes were less common in vaccinated patients, but there was no difference between Delta and Omicron infections.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.03.21265607", + "rel_abs": "Vaccines against the severe acute respiratory syndrome coronavirus 2, which have been in urgent need and development since the beginning of 2020, are aimed to induce a prominent immune system response capable of recognizing and fighting future infection. Here we analyzed the levels of IgG antibodies against the receptor-binding domain (RBD) of the viral spike protein after the administration of three types of popular vaccines, BNT162b2, mRNA-1273, or Sputnik V, using the same ELISA assay to compare their effects. An efficient immune response was observed in the majority of cases. The obtained ranges of signal values were wide, presumably reflecting specific features of the immune system of individuals. At the same time, these ranges were comparable among the three studied vaccines. The anti-RBD IgG levels after vaccination were also similar to those in the patients with moderate/severe course of the COVID-19, and significantly higher than in the individuals with asymptomatic or light symptomatic courses of the disease. No significant correlation was observed between the levels of anti-RBD IgG and sex or age of the vaccinated individuals. The signals measured at different time points for several individuals after full Sputnik V vaccination did not have a significant tendency to lower within many weeks. The rate of neutralization of the interaction of the RBD with the ACE2 receptor after vaccination with Sputnik V was on average slightly higher than in patients with a moderate/severe course of COVID-19. The importance of the second dose administration of the two-dose Sputnik V vaccine was confirmed: while several individuals had not developed detectable levels of the anti-RBD IgG antibodies after the first dose of Sputnik V, after the second dose the antibody signal became positive for all tested individuals and raised on average 5.4 fold. Finally, we showed that people previously infected with SARS-CoV-2 developed high levels of antibodies, efficiently neutralizing interaction of RBD with ACE2 after the first dose of Sputnik V, with almost no change after the second dose.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Matthew L Robinson", - "author_inst": "Johns Hopkins School of Medicine" - }, - { - "author_name": "C Paul Morris", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Joshua Betz", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Anna Kaznadzey", + "author_inst": "VirIntel, LLC, Gaithersburg, MD, 20877, USA; Institute for Information Transmission Problems, RAS, Bolshoy Karetny per. 19, Moscow, 127051, Russia" }, { - "author_name": "Yifan Zhang", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Maria Tutukina", + "author_inst": "Skolkovo Institute of Science and Technology; Institute of Cell Biophysics, RAS; Institute for Information Transmission Problems, RAS" }, { - "author_name": "David R Thieman", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Tatiana Bessonova", + "author_inst": "Institute of Cell Biophysics, RAS" }, { - "author_name": "Amary Fall", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Maria Kireeva", + "author_inst": "VirIntel, LLC, Gaithersburg, MD, 20877, USA" }, { - "author_name": "Raghda E Eldesouki", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Julie M Norton", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "David C Gaston", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Michael Forman", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Chun Huai Luo", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Scott L Zeger", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" - }, - { - "author_name": "Amita Gupta", - "author_inst": "Johns Hopkins School of Medicine" - }, - { - "author_name": "Brian T Garibaldi", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Heba H Mostafa", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Ilya Mazo", + "author_inst": "VirIntel, LLC, Gaithersburg, MD, 20877, USA; Argentys Informatics, LLC, Gaithersburg, MD, 20877, USA" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2022.02.03.22270391", @@ -383767,51 +382650,67 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.02.01.478647", - "rel_title": "Why SARS-CoV-2 Omicron variant is milder? A single high-frequency mutation of structural envelope protein matters.", + "rel_doi": "10.1101/2022.02.01.478628", + "rel_title": "USP22 controls type III interferon signaling and SARS-CoV-2 infection through activation of STING", "rel_date": "2022-02-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.01.478647", - "rel_abs": "SARS-CoV-2 Omicron variant is highly transmissible and extensive morbidity, which has raised concerns for antiviral therapy. In addition, the molecular basis for the attenuated pathogenicity and replication capacity of Omicron remains elusive. Here, we report for the first time that a high-frequency mutation T9I on 2-E of SARS-CoV-2 variant Omicron forms a non-selective ion channel with abolished calcium permeability and reduced acid sensitivity compared to the WT channel. In addition, T9I caused less cell death and a weaker cytokine production. The channel property changes might be responsible for the Omicron variant releases less efficiently and induces a comparatively lower level of cell damage in the infected cells. Our study gives valuable insights into key features of the Omicron variant, further supporting 2-E is a promising drug target against SARS-CoV-2 and providing critical information for the COVID-19 treatment.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.01.478628", + "rel_abs": "Pattern recognition receptors (PRRs) and interferons (IFNs) serve as essential antiviral defense against SARS-CoV-2, the causative agent of the COVID-19 pandemic. Type III IFN (IFN-{lambda}) exhibit cell-type specific and long-lasting functions in autoinflammation, tumorigenesis and antiviral defense. Here, we identify the deubiquitinating enzyme USP22 as central regulator of basal IFN-{lambda} secretion and SARS-CoV-2 infections in native human intestinal epithelial cells (hIECs). USP22-deficient hIECs strongly upregulate genes involved in IFN signaling and viral defense, including numerous IFN-stimulated genes (ISGs), with increased secretion of IFN-{lambda} and enhanced STAT1 signaling, even in the absence of exogenous IFNs or viral infection. Interestingly, USP22 controls basal and 23-cGAMP-induced STING activation and loss of STING reversed STAT activation and ISG and IFN-{lambda} expression. Intriguingly, USP22-deficient hIECs are protected against SARS-CoV-2 infection, viral replication and the formation of de novo infectious particles, in a STING-dependent manner. These findings reveal USP22 as central host regulator of STING and type III IFN signaling, with important implications for SARS-CoV-2 infection and antiviral defense.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Bingqing Xia", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" + "author_name": "Rebekka Karlowitz", + "author_inst": "Institute for Experimental Cancer Research in Pediatrics, Goethe University Frankfurt" }, { - "author_name": "Yi Wang", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" + "author_name": "Megan L Stanifer", + "author_inst": "Department of Molecular Genetics and Microbiology, University of Florida College of Medicine, Gainesville, Florida" }, { - "author_name": "Xiaoyan Pan", - "author_inst": "Wuhan institute of virology, Chinese academy of sciences" + "author_name": "Jens Roedig", + "author_inst": "Institute for Experimental Cancer Research in Pediatrics, Goethe University Frankfurt" }, { - "author_name": "Xi Cheng", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" + "author_name": "Geoffroy Andrieux", + "author_inst": "Institute of Medical Bioinformatics and Systems Medicine, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg" }, { - "author_name": "Hongying Ji", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" + "author_name": "Denisa Bojkova", + "author_inst": "Institute of Medical Virology, University Hospital Frankfurt, Goethe University" }, { - "author_name": "Xiaoli Zuo", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" + "author_name": "Sonja Smith", + "author_inst": "Institute for Experimental Cancer Research in Pediatrics, Goethe University Frankfurt" }, { - "author_name": "Jia Li", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" + "author_name": "Lisa Kowald", + "author_inst": "Institute for Experimental Cancer Research in Pediatrics, Goethe University Frankfurt" }, { - "author_name": "Zhaobing Gao", - "author_inst": "Shanghai Institute of Materia Media" + "author_name": "Ralf Schubert", + "author_inst": "Division for Allergy, Pneumology and Cystic Fibrosis, Department for Children and Adolescents, University Hospital Frankfurt, Goethe University" + }, + { + "author_name": "Melanie Boerries", + "author_inst": "Institute of Medical Bioinformatics and Systems Medicine, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg" + }, + { + "author_name": "Jindrich Cinatl Jr.", + "author_inst": "Institute of Medical Virology, University Hospital Frankfurt, Goethe University" + }, + { + "author_name": "Steeve Boulant", + "author_inst": "Department of Molecular Genetics and Microbiology, University of Florida College of Medicine, Gainesville, Florida" + }, + { + "author_name": "Sjoerd JL van Wijk", + "author_inst": "Institute for Experimental Cancer Research in Pediatrics, Goethe University Frankfurt" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "cell biology" }, { "rel_doi": "10.1101/2022.02.01.478632", @@ -385453,107 +384352,111 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.02.01.478657", - "rel_title": "Influenza virus-like particle-based hybrid vaccine containing RBD induces immunity against influenza and SARS-CoV-2 viruses", + "rel_doi": "10.1101/2022.02.01.478504", + "rel_title": "Engineering SARS-CoV-2 cocktail antibodies into a bispecific format improves neutralizing potency and breadth", "rel_date": "2022-02-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.01.478657", - "rel_abs": "Several approaches have produced an effective vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the influence of immune responses induced by other vaccinations on the durability and efficacy of the immune response to SARS-CoV-2 vaccine is still unknown. We have developed a hybrid vaccine for SARS-CoV-2 and influenza viruses using influenza virus-like particles (VLP) incorporated by protein transfer with glycosylphosphatidylinositol (GPI)-anchored SARS-CoV-2 S1 RBD fused to GM-CSF as an adjuvant. GPI-RBD-GM-CSF fusion protein was expressed in CHO-S cells, purified and incorporated onto influenza VLPs to develop the hybrid vaccine. Our results show that the hybrid vaccine induced a strong antibody response and protected mice from both influenza virus and mouse-adapted SARS-CoV-2 challenges, with vaccinated mice having significantly lower lung viral titers compared to naive mice. These results suggest that the hybrid vaccine strategy is a promising approach for developing multivalent vaccines to prevent influenza A and SARS-CoV-2 infections.", - "rel_num_authors": 22, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.01.478504", + "rel_abs": "One major limitation of neutralizing antibody-based COVID-19 therapy is the requirement of costly cocktails to reduce antibody resistance. We engineered two bispecific antibodies (bsAbs) using distinct designs and compared them with parental antibodies and their cocktail. Single molecules of both bsAbs block the two epitopes targeted by parental antibodies on the receptor-binding domain (RBD). However, bsAb with the IgG-(scFv)2 design (14-H-06) but not the CrossMAb design (14-crs-06) increases antigen-binding and virus-neutralizing activities and spectrum against multiple SARS-CoV-2 variants including the Omicron, than the cocktail. X-ray crystallography and computational simulations reveal distinct neutralizing mechanisms for individual cocktail antibodies and suggest higher inter-spike crosslinking potentials by 14-H-06 than 14-crs-06. In mouse models of infections by SARS-CoV-2 and the Beta, Gamma, and Delta variants, 14-H-06 exhibits higher or equivalent therapeutic efficacy than the cocktail. Rationally engineered bsAbs represent a cost-effective alternative to antibody cocktails and a promising strategy to improve potency and breadth.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Ramireddy Bommireddy", - "author_inst": "Emory University" + "author_name": "Zhiqiang Ku", + "author_inst": "Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA" }, { - "author_name": "Shannon Stone", - "author_inst": "Georgia State University" + "author_name": "Xuping Xie", + "author_inst": "Department of Biochemistry and Molecular Biology, Institute for Human Infection and Immunity, Sealy Institute for Vaccine Sciences, Sealy Center for Structural " }, { - "author_name": "Noopur Bhatnagar", - "author_inst": "Georgia State University" + "author_name": "Jianqing Lin", + "author_inst": "NTU Institute of Structural Biology and School of Biological Sciences, Nanyang Technological University, 636921, Singapore" }, { - "author_name": "Pratima Kumari", - "author_inst": "Georgia State University" + "author_name": "Peng Gao", + "author_inst": "Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA" }, { - "author_name": "Luis E Munoz", - "author_inst": "Emory University" + "author_name": "Abbas El Sahili", + "author_inst": "NTU Institute of Structural Biology and School of Biological Sciences, Nanyang Technological University, 636921, Singapore" }, { - "author_name": "Judy Oh", - "author_inst": "Georgia State University" + "author_name": "Hang Su", + "author_inst": "Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA" }, { - "author_name": "Ki-Hye Kim", - "author_inst": "Georgia State University" + "author_name": "Yang Liu", + "author_inst": "Department of Biochemistry and Molecular Biology, Institute for Human Infection and Immunity, Sealy Institute for Vaccine Sciences, Sealy Center for Structural " }, { - "author_name": "Jameson TL Berry", - "author_inst": "Emory University" + "author_name": "Xiaohua Ye", + "author_inst": "Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA" }, { - "author_name": "Kristen Jacobsen", - "author_inst": "Metaclipse Therapeutics Corporation" + "author_name": "Xin Li", + "author_inst": "Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA" }, { - "author_name": "Jaafar Lahcen", - "author_inst": "Metaclipse Therapeutics Corporation" + "author_name": "Xuejun Fan", + "author_inst": "Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA" }, { - "author_name": "Swe-Htet Naing", - "author_inst": "Metaclipse Therapeutics Corporation" + "author_name": "Boon Chong Goh", + "author_inst": "NTU Institute of Structural Biology and School of Biological Sciences, Nanyang Technological University, 636921, Singapore" }, { - "author_name": "Allison N Blackerby", - "author_inst": "Metaclipse Therapeutics Corporation" + "author_name": "Wei Xiong", + "author_inst": "Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA" }, { - "author_name": "Tori Van der Gaag", - "author_inst": "Metaclipse Therapeutics Corporation" + "author_name": "Hannah Boyd", + "author_inst": "Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA" }, { - "author_name": "Chloe N Wright", - "author_inst": "Metaclipse Therapeutics Corporation" + "author_name": "Antonio E. Muruato", + "author_inst": "Department of Biochemistry and Molecular Biology, Institute for Human Infection and Immunity, Sealy Institute for Vaccine Sciences, Sealy Center for Structural " }, { - "author_name": "Lilin Lai", - "author_inst": "Emory University" + "author_name": "Hui Deng", + "author_inst": "Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA" }, { - "author_name": "Christopher D Pack", - "author_inst": "Metaclipse Therapeutics Corporation" + "author_name": "Hongjie Xia", + "author_inst": "Department of Biochemistry and Molecular Biology, Institute for Human Infection and Immunity, Sealy Institute for Vaccine Sciences, Sealy Center for Structural " }, { - "author_name": "Sampath Ramachandiran", - "author_inst": "Metaclipse Therapeutics Corporation" + "author_name": "Zou Jing", + "author_inst": "Department of Biochemistry and Molecular Biology, Institute for Human Infection and Immunity, Sealy Institute for Vaccine Sciences, Sealy Center for Structural " }, { - "author_name": "Mehul S Suthar", - "author_inst": "Emory University" + "author_name": "Birte K. Kalveram", + "author_inst": "Department of Biochemistry and Molecular Biology, Institute for Human Infection and Immunity, Sealy Institute for Vaccine Sciences, Sealy Center for Structural " }, { - "author_name": "Sang-Moo Kang", - "author_inst": "Georgia State University" + "author_name": "Vineet D. Menachery", + "author_inst": "Department of Microbiology & Immunology, University of Texas Medical Branch, Galveston, TX, 77555, USA" }, { - "author_name": "Mukesh Kumar", - "author_inst": "Georgia State University" + "author_name": "Ningyan Zhang", + "author_inst": "Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA" }, { - "author_name": "Shaker JC Reddy", - "author_inst": "Metaclipse Therapeutics Corporation" + "author_name": "Julien Lescar", + "author_inst": "NTU Institute of Structural Biology and School of Biological Sciences, Nanyang Technological University, 636921, Singapore" }, { - "author_name": "Periasamy Selvaraj", - "author_inst": "Emory University" + "author_name": "Pei-Yong Shi", + "author_inst": "Department of Biochemistry and Molecular Biology, Institute for Human Infection and Immunity, Sealy Institute for Vaccine Sciences, Sealy Center for Structural " + }, + { + "author_name": "Zhiqiang An", + "author_inst": "Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.01.29.22270074", @@ -387255,35 +386158,27 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2022.01.31.22270163", - "rel_title": "Good work in the COVID-19 recovery: priorities and changes for the future", + "rel_doi": "10.1101/2022.01.29.22270072", + "rel_title": "The course of COVID-19 in allergic rhinitis patients receiving allergen-specific immunotherapy", "rel_date": "2022-01-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.31.22270163", - "rel_abs": "Employment is a wider determinant of health, and the COVID-19 pandemic has disrupted working lives, with individuals having to adapt to new ways of working. These new experiences may shape what kind of work people want in future. This research used a sample of working adults in Wales to identify the workforces priorities for future work, and the employment changes that they have considered making since the start of the COVID-19 pandemic. Data was collected at two time-points (May-June 2020; December 2020-January 2021) in a nationally-representative longitudinal household survey across Wales.\n\nWork priorities remained largely stable throughout the pandemic, however the desire to work close to home increased as the pandemic progressed. Those in poorer health prioritised flexibility, and were more likely to consider retiring than their healthier counterparts. Becoming self-employed was more likely to be considered by those with limiting pre-existing conditions or low mental well-being. Over 20% of the total sample had considered retraining, with those with low mental well-being, younger individuals and those experiencing financial insecurity being more likely to consider doing so. Furloughed individuals were more likely to consider retraining, becoming self-employed, securing permanent employment and compressing their working hours.\n\nThose prone to facing insecurity within their working lives (those that were furloughed, those experiencing financial insecurity, and those in ill-health) were all more likely to consider changing their employment conditions - these groups may require additional support in accessing secure and flexible work. Action is needed to ensure that good work, that is good for health, is equally accessible for all.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.29.22270072", + "rel_abs": "IntroductionThe aims of presenting study were trying to expose the course of SARS-CoV-2 (severe acute respiratory syndrome-related coronavirus) in patients with allergic rhinitis (AR), to compare the prevalence of SARS-CoV-2 infection, hospitalization and pneumonia rates in patients with AR receiving allergen immunotherapy (AIT) and patients did not receive AIT (non-receivers) and to define possible risk factors for SARS-CoV-2 positivity in patients with AR.\n\nMaterials and MethodsA total of 419 patients with AR who were being followed up in a tertiary allergy clinic between 1 June 2020 and 31 December 2020, were selected for the study. Only patients who were receiving active-continuous treatment for allergic rhinitis during the study period, were included in the study.\n\nResultsSeventy-nine patients (18.9%) became infected with the SARS-CoV-2 [32 patients (19.6%) in AR patients with AIT and 47 patients (19.0%) in non-receivers] and the rate of pneumonia was 2.4% [12.7% of SARS-CoV-2 (+) patients]. There was no significant difference was determined between the AR patients with AIT and the non-receivers in regard to the rate of SARS-CoV-2 infection, pneumonia, and hospitalization (p: 0.864, p: 0.081, p: 0.113). There was a significant difference between the groups in terms of gender, duration of disease, sensitivity to allergens (atopy), and serum IgE levels (p: 0.009, p: 0.001, p: 0.001, and p: 0.001). The accompanying comorbidities, eosinophil count, AIT, and duration of AIT were not found to be associated with an increased risk SARS-CoV-2 PCR positivity. However, the female gender was shown to be associated with a decreased risk for SARS-CoV-2 PCR positivity (OR, 0.571; 95% confidence interval, 0.330-0.987; p: 0.045)\n\nConclusionThe course of SARS-CoV-2 is similar in patients with AR who underwent AIT and patients with AR who did not undergo AIT, and AIT does not seem to increase the risk for SARS-CoV-2 infection.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Melda Lois Griffiths", - "author_inst": "Research and Evaluation Division, Public Health Wales" - }, - { - "author_name": "Benjamin J Gray", - "author_inst": "Research and Evaluation Division, Public Health Wales" - }, - { - "author_name": "Richard G Kyle", - "author_inst": "Academy of Nursing, University of Exeter" + "author_name": "EMEL ATAYIK", + "author_inst": "Department of Immunology and Allergy, Konya City Hospital, Konya, Turkey" }, { - "author_name": "Alisha R Davies", - "author_inst": "Research and Evaluation Division, Public Health Wales" + "author_name": "Gokhan Aytekin", + "author_inst": "Department of Immunology and Allergy, Konya City Hospital, Konya, Turkey" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2022.01.30.22269980", @@ -389221,69 +388116,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.28.22269990", - "rel_title": "Hybrid immunity from SARS-CoV-2 delta variant surge induced low to undetectable levels of neutralizing antibodies against Omicron variant", + "rel_doi": "10.1101/2022.01.27.22269978", + "rel_title": "A Machine Learning Approach to Differentiate Between COVID-19 and Influenza Infection Using Synthetic Infection and Immune Response Data", "rel_date": "2022-01-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.28.22269990", - "rel_abs": "The Omicron variant of SARS-CoV-2 is capable of infecting unvaccinated, vaccinated and previously-infected individuals due to its ability to evade neutralization by antibodies. With three sub-lineages of Omicron emerging in the last four months, there is inadequate information on the quantitative antibody response generated upon natural infection with Omicron variant and whether these antibodies offer cross-protection against other sub-lineages of Omicron variant. In this study, we characterized the growth kinetics of Kappa, Delta and Omicron variants of SARS-CoV-2 in Calu-3 cells. Relatively higher amounts infectious virus titers, cytopathic effect and disruption of epithelial barrier functions was observed with Delta variant whereas infection with Omicron variant led to a more robust induction of interferon pathway, lower level of virus replication and mild effect on epithelial barrier. The replication kinetics of BA.1 and BA.2 sub-lineages of the Omicron variant were comparable in cell culture and natural Omicron infection in a subset of individuals led to a significant increase in binding and neutralizing antibodies to both BA.1 and BA.2 sub-lineages but these levels were lower than that produced against the Delta variant. Finally, we show that Cu2+, Zn2+ and Fe2+ salts inhibited in vitro RdRp activity but only Cu2+ and Fe2+ inhibited both the Delta and Omicron variants in cell culture. Thus, our results suggest that high levels of interferons induced upon infection with Omicron variant may counter virus replication and spread. Waning neutralizing antibody titers rendered subjects susceptible to infection by Omicron variant and natural Omicron infection elicits neutralizing antibodies that can cross-react with other sub-lineages of Omicron and other variants of concern.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.27.22269978", + "rel_abs": "Data analysis is widely used to generate new insights into human disease mechanisms and provide better treatment methods. In this work, we used the mechanistic models of viral infection to generate synthetic data of influenza and COVID-19 patients. We then developed and validated a supervised machine learning model that can distinguish between the two infections. Influenza and COVID-19 are contagious respiratory illnesses that are caused by different pathogenic viruses but appeared with similar initial presentations. While having the same primary signs COVID-19 can produce more severe symptoms, illnesses, and higher mortality. The predictive model performance was externally evaluated by the ROC AUC metric (area under the receiver operating characteristic curve) on 100 virtual patients from each cohort and was able to achieve at least AUC=91% using our multiclass classifier. The current investigation highlighted the ability of machine learning models to accurately identify two different diseases based on major components of viral infection and immune response. The model predicted a dominant role for viral load and productively infected cells through the feature selection process.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Janmejay Singh", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Aleksha Panwar", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Anbalagan Anantharaj", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Chitra Rani", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Monika Bhardwaj", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Parveen Kumar", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Kamal Pargai", - "author_inst": "Translational Health Science and Technology Institute" - }, - { - "author_name": "Partha Chattopadhyay", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology" - }, - { - "author_name": "Priti Devi", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology" - }, - { - "author_name": "Ranjeet Maurya", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology" + "author_name": "Suzan Farhang-Sardroodi", + "author_inst": "York university" }, { - "author_name": "Pallavi Mishra", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology" + "author_name": "Mohammadsajjad Ghaemi", + "author_inst": "National Research Council" }, { - "author_name": "Anil Kumar Pandey", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology" + "author_name": "Morgan Craig", + "author_inst": "University of Montreal" }, { - "author_name": "Rajesh Pandey", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology" + "author_name": "Hsu Kiang Ooi", + "author_inst": "National Research Council" }, { - "author_name": "Guruprasad R Medigeshi", - "author_inst": "Translational Health Science and Technology Institute" + "author_name": "Jane M Heffernan", + "author_inst": "York University" } ], "version": "1", @@ -391095,51 +389954,63 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2022.01.26.22269903", - "rel_title": "IMPACT OF WEEKNIGHT AND WEEKEND CURFEWS USING MOBILITY DATA: A CASE STUDY OF BENGALURU URBAN", + "rel_doi": "10.1101/2022.01.26.22269854", + "rel_title": "A model-based approach to improve intranasal sprays for respiratory viral infections", "rel_date": "2022-01-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.26.22269903", - "rel_abs": "Karnataka imposed weeknight and weekend curfews to mitigate the spread of the Omicron variant of SARS-CoV-2. We attempt to assess the impact of curfew using community mobility reports published by Google. Then, we quantify the impact of such restrictions via a simulation study. The pattern of weeknight and weekend curfew, followed by relaxations during the weekdays, seems, at best, to slow and delay the Omicron spread. The simulation outcomes suggest that Omicron eventually spreads and affects nearly as much of the population as it would have without the restrictions. Further, if Karnataka cases trajectory follows the South African Omicron wave trend and the hospitalisation is similar to that observed in well-vaccinated countries (2% of the confirmed cases), then the healthcare requirement is likely within the capacity of Bengaluru Urban when the caseload peaks, with or without the mobility restrictions. On the other hand, if Karnataka cases trajectory follows both the South African Omicron wave trend and the hospitalisation requirement observed there (6.9%), then the healthcare capacity may be exceeded at peak, with or without the mobility restrictions.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.26.22269854", + "rel_abs": "Drug delivery for viral respiratory infections, such as SARS-CoV-2, can be enhanced significantly by targeting the nasopharynx, which is the dominant initial infection site in the upper airway, for example by nasal sprays. However, under the standard recommended spray usage protocol (\"Current Use\", or CU), the nozzle enters the nose almost vertically, resulting in sub-optimal deposition of drug droplets at the nasopharynx. Using computational fluid dynamics simulations in two anatomic nasal geometries, along with experimental validation of the generic findings in a different third subject, we have identified a new \"Improved Use\" (or, IU) spray protocol. It entails pointing the spray bottle at a shallower angle (almost horizontally), aiming slightly toward the cheeks. We have simulated the performance of this protocol for conically injected spray droplet sizes of 1 - 24 m, at two breathing rates: 15 and 30 L/min. The lower flowrate corresponds to resting breathing and follows a viscous-laminar model; the higher rate, standing in for moderate breathing conditions, is turbulent and is tracked via Large Eddy Simulation. The results show that (a) droplets sized between [~] 6 - 14 m are most efficient at direct landing over the nasopharyngeal viral infection hot-spot; and (b) targeted drug delivery via IU outperforms CU by approximately 2 orders-of-magnitude, under the two tested inhalation conditions. Also quite importantly, the improved delivery strategy, facilitated by the IU protocol, is found to be robust to small perturbations in spray direction, underlining the practical utility of this simple change in nasal spray administration protocol.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Aniruddha Adiga", - "author_inst": "University of Virginia" + "author_name": "Saikat Basu", + "author_inst": "South Dakota State University" }, { - "author_name": "Siva Athreya", - "author_inst": "Indian Statistical Institute" + "author_name": "Mohammad Mehedi Hasan Akash", + "author_inst": "South Dakota State University" }, { - "author_name": "Madhav Marathe", - "author_inst": "University of Virginia" + "author_name": "Yueying Lao", + "author_inst": "Boston University" }, { - "author_name": "Jagadish Midthala", - "author_inst": "Indian Institute of Science" + "author_name": "Pallavi A Balivada", + "author_inst": "Boston University" }, { - "author_name": "Nihesh Rathod", - "author_inst": "Indian Institute of Science" + "author_name": "Phoebe Ato", + "author_inst": "Boston University" }, { - "author_name": "Rajesh Sundaresan", - "author_inst": "Indian Institute of Science" + "author_name": "Nogaye K Ka", + "author_inst": "Boston University" }, { - "author_name": "Srinivasan Venkataramanan", - "author_inst": "University of Virginia" + "author_name": "Austin Mituniewicz", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Sarath Yasodharan", - "author_inst": "Indian Institute of Science" + "author_name": "Zachary Silfen", + "author_inst": "Boston University" + }, + { + "author_name": "Julie Suman", + "author_inst": "Next Breath - an Aptar Pharma company" + }, + { + "author_name": "Arijit Chakravarty", + "author_inst": "Fractal Therapeutics" + }, + { + "author_name": "Diane Joseph-McCarthy", + "author_inst": "Boston University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2022.01.26.22269874", @@ -393137,97 +392008,101 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.19.22268871", - "rel_title": "Cohort Profile: The United Kingdom Research study into Ethnicity And COVID-19 outcomes in Healthcare workers (UK-REACH)", + "rel_doi": "10.1101/2022.01.17.22269278", + "rel_title": "Kinetics and persistence of the cellular and humoral immune responses to BNT162b2 mRNA vaccine in SARS-CoV-2-naive and -experienced subjects", "rel_date": "2022-01-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.19.22268871", - "rel_abs": "Key Features of the UK-REACH Cohort (Profile in a nutshell)\n\nO_LIThe UK-REACH Cohort was established to understand why ethnic minority healthcare workers (HCWs) are at risk of poorer outcomes from COVID-19 when compared to their white ethnic counterparts in the United Kingdom (UK). Through study design, it contains a uniquely high percentage of participants from ethnic minority backgrounds about whom a wide range of qualitative and quantitative data has been collected.\nC_LIO_LIA total of 17891 HCWs aged 16-89 years (mean age: 44) have been recruited from across the UK via all major healthcare regulators, individual National Health Service (NHS) hospital trusts and UK HCW membership bodies who advertised the study to their registrants/staff to encourage participation in the study.\nC_LIO_LIData available include linked healthcare records for 25 years from the date of consent and consent to obtain genomic sequencing data collected via saliva. Online questionnaires include information on demographics, COVID-19 exposures at work and home, redeployment in the workforce due to COVID-19, mental health measures, workforce attrition, and opinions on COVID-19 vaccines, with baseline (n=15 119), 6 (n=5632) and 12-month follow-up data captured.\nC_LIO_LIRequest data access and collaborations by following documentation found at https://www.uk-reach.org/main/data_sharing.\nC_LI", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.17.22269278", + "rel_abs": "BackgroundUnderstanding and measuring the individual level of immune protection and its persistence at both humoral and cellular levels after SARS-CoV-2 vaccination is mandatory for the management of the vaccination booster campaign. Our prospective study was designed to assess the immunogenicity of the BNT162b2 mRNA vaccine in triggering the humoral and the cellular immune response in healthcare workers up to 6 months after two doses vaccination.\n\nMethodsThis prospective study enrolled 208 healthcare workers from the Liege University Hospital (CHU) of Liege in Belgium. All participants received two doses of BioNTech/Pfizer COVID-19 vaccine (BNT162b2). Fifty participants were SARS-CoV-2 experienced (self-reported SARS-CoV-2 infection) and 158 were naive (no reported SARS-CoV-2 infection) before the vaccination. Blood sampling was performed at the day of the first (T0) and second (T1) vaccine doses administration, then at 2 weeks (T2), 4 weeks (T3) and 6 months (T4) after the 1st vaccine dose administration. A total of 1024 blood samples were collected. All samples were tested for the presence of anti-Spike antibodies using DiaSorin LIAISON SARS-CoV-2 TrimericS IgG assay. Neutralizing antibodies against the SARS-CoV-2 Wuhan-like variant strain were quantified in all samples using a Vero E6 cell-based neutralization-based assay. Cell-mediated immune response was evaluated at T4 on 80 participants by measuring the secretion of IFN-{gamma} on peripheral blood lymphocytes using the QuantiFERON Human IFN-{gamma} SARS-CoV-2, Qiagen. All participants were monitored on weekly-basis for the novo SARS-COV-2 infection for 4 weeks after the 1st vaccine dose administration. We analyzed separately the naive and experienced participants.\n\nFindingsWe found that anti-spike antibodies and neutralization capacity levels were significantly higher in SARS-CoV-2 experienced healthcare workers (HCWs) compared to naive HCWs at all time points analyzed. Cellular immune response was similar in the two groups six months following 2nd dose of the vaccine. Reassuringly, most participants had a detectable cellular immune response to SARS-CoV-2 six months after vaccination. Besides the impact of SARS-CoV-2 infection history on immune response to BNT162b2 mRNA vaccine, we observed a significant negative correlation between age and persistence of humoral response. Cellular immune response was, however, not significantly correlated to age, although a trend towards a negative impact of age was observed.\n\nConclusionsOur data strengthen previous findings demonstrating that immunization through vaccination combined with natural infection is better than 2 vaccine doses immunization or natural infection alone. It may have implications for personalizing mRNA vaccination regimens used to prevent severe COVID-19 and reduce the impact of the pandemic on the healthcare system. More specifically, it may help prioritizing vaccination, including for the deployment of booster doses.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Luke Bryant", - "author_inst": "University of Leicester" + "author_name": "Salome Desmecht", + "author_inst": "University of Liege" }, { - "author_name": "Robert C Free", - "author_inst": "University of Leicester" + "author_name": "Aleksandr Tashkeev", + "author_inst": "University of Liege" }, { - "author_name": "Katherine Woolf", - "author_inst": "UCL" + "author_name": "Nicole Marechal", + "author_inst": "Liege University Hospital" }, { - "author_name": "Carl Melbourne", - "author_inst": "University of Leicester" + "author_name": "Helene Peree", + "author_inst": "University of Liege" }, { - "author_name": "Anna Louise Guyatt", - "author_inst": "University of Leicester" + "author_name": "Yumie Tokunaga", + "author_inst": "University of Liege" }, { - "author_name": "Catherine John", - "author_inst": "University of Leicester" + "author_name": "Celine Fombellida Lopez", + "author_inst": "University of Liege" }, { - "author_name": "Amit Gupta", - "author_inst": "Oxford University Hospitals NHS Foundation Trust" + "author_name": "Barbara Polese", + "author_inst": "University of Liege" }, { - "author_name": "Laura J Grey", - "author_inst": "University of Leicester" + "author_name": "Celine Legrand", + "author_inst": "University of Liege" }, { - "author_name": "Laura Nellums", - "author_inst": "University of Nottingham" + "author_name": "Marie Wery", + "author_inst": "University of Liege" }, { - "author_name": "Christopher A Martin", - "author_inst": "University of Leicester" + "author_name": "Myriam Mni", + "author_inst": "University of Liege" }, { - "author_name": "Ian Christopher McManus", - "author_inst": "University College London" + "author_name": "Nicolas Fouillien", + "author_inst": "University of Liege" }, { - "author_name": "Claire Garwood", - "author_inst": "University of Leicester" + "author_name": "Francoise Toussaint", + "author_inst": "Liege University Hospital" }, { - "author_name": "Vishant Modhawdia", - "author_inst": "University of Leicester" + "author_name": "Laurent Gillet", + "author_inst": "University of Liege" }, { - "author_name": "Sue Carr", - "author_inst": "University Hospitals of Leicester" + "author_name": "Fabrice Bureau", + "author_inst": "University of Liege" }, { - "author_name": "Louise V Wain", - "author_inst": "University of Leicester" + "author_name": "Laurence Lutteri", + "author_inst": "Liege University Hospital" }, { - "author_name": "Martin D Tobin", - "author_inst": "University of Leicester" + "author_name": "Marie-Pierre Hayette", + "author_inst": "Liege University Hospital" }, { - "author_name": "Kamlesh Khunti", - "author_inst": "University of Leicester" + "author_name": "Michel Moutschen", + "author_inst": "Liege University Hospital" }, { - "author_name": "Ibrahim Akubakar", - "author_inst": "University College London" + "author_name": "Christelle Meuris", + "author_inst": "Liege University Hospital" }, { - "author_name": "Manish Pareek", - "author_inst": "University of Leicester" + "author_name": "Daniel Desmecht", + "author_inst": "Liege University" }, { - "author_name": "- UK-REACH Collaborative Group", - "author_inst": "" + "author_name": "Souad Rahmouni", + "author_inst": "University of Liege" + }, + { + "author_name": "Darcis Gilles", + "author_inst": "Liege University Hospital" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -395503,47 +394378,35 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.01.18.22269401", - "rel_title": "Comparative diagnostic performance of the new chromatographic Affimer(R)-based rapid antigen detection against SARS-CoV-2 and other standard antigen tests for COVID-19 in a clinical setting.", - "rel_date": "2022-01-26", + "rel_doi": "10.1101/2022.01.23.22269442", + "rel_title": "The Epidemiology of Hundreds of Individuals Infected with Omicron BA.1 in Middle-Eastern Jordan", + "rel_date": "2022-01-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.18.22269401", - "rel_abs": "The availability of accurate and rapid diagnostic tools for COVID-19 is essential for tackling the ongoing pandemic. In this context, researchers in the UK have started testing a new Lateral Flow Device (LFD) based on proprietary Biotinylated anti SARS-CoV-2 S1 Affimer(R) technology that binds to the SARS-CoV2-S1 protein in anterior nasal swab samples, generating an ultra-sensitive method for detection. This international study aimed to compare its performance against other available antigen-detecting rapid diagnostic tests (Ag-RDTs) in a real-world clinical setting. The study was completed under the frame of Project SENSORNAS RTC-20176501 in collaboration with MiRNAX Biosens Ltd. and Hospital Carlos III, it was documented internally and deposited in agreement to the ISO 13485 norm. All the data obtained are currently under submission and review from the Ethics Committee of Universidad Autonoma de Madrid.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.23.22269442", + "rel_abs": "In less than two months of its detection in Jordan, lineage B.1.1.529 recognized as Omicron, is constituting 55% of all confirmed coronavirus disease of 2019 (COVID-19) infections causing a rise in the daily cases in the country. Herein, we report on 500 cases, among the first identified Omicron infections in Jordan. We also report on the genomic diversity of 25 Omicron viruses identified in nasopharyngeal swabs from Jordan. Our results indicated that 96% of study participants were vaccinated who had asymptomatic, mild or moderate disease. One unvaccinated individual developed severe disease. The median age of Omicron cases was 30 years, and most frequent disease symptoms were: fever, coughing, sore throat, runny nose, general fatigue and muscle/joint pain. Viral genomic analysis results revealed that the BA.1 is the dominant Omicron sublineage in Jordan, with 45 to 58 total mutations. We identified a few amino acid modifications that could impact the accuracy of some polymerase chain reaction (PCR) tests. In summary, infections caused by BA.1 seem milder than earlier infections. However, it is unknown whether this change is due to alterations in the immunity landscape of the infected population or is the result of viral genetic mutations that reduced viral virulence. Hence, comparing similar studies from different countries is likely to give us a get a better understanding of this variant, its behavior and the impact on disease characteristics.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "A.I. Gil-Garcia", - "author_inst": "Unidad de Desarrollo de Herramientas Moleculares para Diagnostico e Investigacion Clinica (UDHM-DC), MiRNAX Biosens in collaboration with Hospital Carlos III/IS" - }, - { - "author_name": "A. Lopez-Lopez", - "author_inst": "Unidad de Desarrollo de Herramientas Moleculares para Diagnostico e Investigacion Clinica (UDHM-DC), MiRNAX Biosens in collaboration with Hospital Carlos III/IS" - }, - { - "author_name": "J.M. Rubio", - "author_inst": "Centro Nacional de Microbiologia, Instituto de Salud Carlos III." - }, - { - "author_name": "J.J. Montoya", - "author_inst": "Departamento de Radiologia, Rehabilitacion y Fisioterapia. Facultad de Medicina, Universidad Complutense de Madrid." + "author_name": "Rima Hajjo", + "author_inst": "Al-Zaytoonah University of Jordan, UNC-Chapel Hill, Jordan CDC" }, { - "author_name": "Y. Ouahid", - "author_inst": "Unidad de Desarrollo de Herramientas Moleculares para Diagnostico e Investigacion Clinica (UDHM-DC), MiRNAX Biosens in collaboration with Hospital Carlos III/IS" + "author_name": "Mahmoud M. AbuAlSamen", + "author_inst": "Jordan CDC" }, { - "author_name": "A. Madejon", - "author_inst": "Centro de Investigacion Biomedica en Red (CIBER)." + "author_name": "Hamed M. Alzoubi", + "author_inst": "Mutah University of Jordan, Jordan CDC" }, { - "author_name": "P. Castan", - "author_inst": "Unidad de Desarrollo de Herramientas Moleculares para Diagnostico e Investigacion Clinica (UDHM-DC), MiRNAX Biosens in collaboration with Hospital Carlos III/IS" + "author_name": "Raeda Alqutob", + "author_inst": "Jordan CDC" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.01.23.22269669", @@ -397001,67 +395864,103 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.24.22269758", - "rel_title": "The MU Study of Seropositivity and Risk for SARS-CoV-2 and COVID-19: Crucial Behavioral and Immunological Data from Midwestern College Students", + "rel_doi": "10.1101/2022.01.25.22269616", + "rel_title": "Functional proteomic profiling links deficient DNA clearance to mortality in patients with severe COVID-19 pneumonia", "rel_date": "2022-01-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.24.22269758", - "rel_abs": "ObjectiveWe describe our Fall 2020 study of college students COVID-19 related behaviors, attitudes, and antibody test results.\n\nParticipantsThe study included 1,446 randomly selected and self-enrolled undergraduate and graduate students from a midwestern university.\n\nMethodsAn online survey was distributed to a sample of students, between September and December 2020. A sub-group also participated in a SARS-CoV-2 antibody blood draw.\n\nResultsNearly half of students reported a prior COVID-19 test with 22% indicating a positive test, which represents an 11% positivity rate across all student participants. Of those who participated in antibody testing, 15.1% tested positive for SARS-CoV-2 antibodies. Seventy-seven percent of participants said they would get vaccinated. One-third of students reported moderate to severe generalized anxiety disorder and 13% reported moderate to severe depression.\n\nConclusionsThis study informed campus decisions in Fall 2020. The importance of effective public health messaging on campus should continue in the future.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.25.22269616", + "rel_abs": "Hyperinflammation, coagulopathy and immune dysfunction are prominent in patients with severe infections. Extracellular chromatin clearance by plasma DNases suppresses such pathologies in mice but whether severe infection interferes with these pathways is unclear. Here, we show that patients with severe SARS-CoV-2 infection or microbial sepsis exhibit low extracellular DNA clearance capacity associated with the release of the DNase inhibitor actin. Unlike naked DNA degradation (DNase), neutrophil extracellular trap degradation (NETase) was insensitive to G-actin, indicating distinct underlying mechanisms. Activity-based proteomic profiling of severely ill SARS-CoV-2 patient plasma revealed that patients with high NETase and DNase activities exhibited 18-fold higher survival compared to patients with low activity proteomic profiles. Remarkably, low DNA clearance capacity was also prominent in healthy individuals with chronic inflammation, suggesting that pre-existing inflammatory conditions may increase the risk for mortality upon infection. Hence, functional proteomic profiling illustrates that non-redundant DNA clearance activities protect critically ill patients from mortality, uncovering protein combinations that can accurately predict mortality in critically ill patients.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Tyler W. Myroniuk", - "author_inst": "University of Missouri, Department of Public Health" + "author_name": "Venizelos Papayannopoulos", + "author_inst": "The Francis Crick Institute" }, { - "author_name": "Joan M. Hermsen", - "author_inst": "University of Missouri, Department of Sociology" + "author_name": "Dennis Hoving", + "author_inst": "The Francis Crick Institute, Antimicrobial Defence Laboratory, London, United Kingdom." }, { - "author_name": "Christal Hamilton", - "author_inst": "University of Missouri, Harry S. Truman School of Government and Public Affairs" + "author_name": "Spyros Vernardis", + "author_inst": "The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London, United Kingdom." + }, + { + "author_name": "Martha Tin", + "author_inst": "The Francis Crick Institute, Antimicrobial Defence Laboratory, London, United Kingdom." }, { - "author_name": "Ifeolu David", - "author_inst": "University of Missouri, School of Health Professions" + "author_name": "Vadim Demichev", + "author_inst": "The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London, United Kingdom." }, { - "author_name": "Michelle Teti", - "author_inst": "University of Missouri, Department of Public Health" + "author_name": "Elisa Theresa Helbig", + "author_inst": "Charit\u00e9-Universit\u00e4tsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, Berlin, Germany." }, { - "author_name": "Yerina S. Ranjit", - "author_inst": "University of Missouri, Department of Communication" + "author_name": "Lena Lippert", + "author_inst": "Charit\u00e9-Universit\u00e4tsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, Berlin, Germany." }, { - "author_name": "Shannen N. Woodrey", - "author_inst": "University of Missouri, Department of Emergency Medicine" + "author_name": "Klaus Stahl", + "author_inst": "Department of Gastroenterology, Hepatology and Endocrinology, Medical School Hannover, Hannover." }, { - "author_name": "Julie A.W. Stilley", - "author_inst": "University of Missouri, Department of Emergency Medicine" + "author_name": "Marianna Ioannou", + "author_inst": "The Francis Crick Institute, Antimicrobial Defence Laboratory, London, United Kingdom." }, { - "author_name": "Emma Teixeiro", - "author_inst": "University of Missouri, Department of Molecular Microbiology and Immunology, Department of Surgery" + "author_name": "Mia I Temkin", + "author_inst": "The Francis Crick Institute, Antimicrobial Defence Laboratory, London, United Kingdom." }, { - "author_name": "Yue Guan", - "author_inst": "University of Missouri, Department of Molecular Microbiology and Immunology" + "author_name": "Matthew White", + "author_inst": "The Francis Crick Institute, Antimicrobial Defence Laboratory, London, United Kingdom." }, { - "author_name": "Mark Daniels", - "author_inst": "University of Missouri, Department of Molecular Microbiology and Immunology, Department of Surgery" + "author_name": "Helena Radbruch", + "author_inst": "Charit\u00e9-University of Medicine" + }, + { + "author_name": "Jana Ihlow", + "author_inst": "Charit\u00e9-Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "David Horst", + "author_inst": "Charit\u00e9-Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Scott T Chiesa", + "author_inst": "University College London" + }, + { + "author_name": "John E Deanfield", + "author_inst": "Institute of Cardiovascular Science, University College London, London, UK" + }, + { + "author_name": "Sascha David", + "author_inst": "Institute for Intensive Care Medicine, University Hospital Zurich, Zurich, Switzerland." + }, + { + "author_name": "Christian Bode", + "author_inst": "Department of Anaesthesiology and Critical Care, University Hospital Bonn, Bonn, Germany" }, { - "author_name": "Enid Schatz", - "author_inst": "University of Missouri, Department of Public Health" + "author_name": "Florian Kurth", + "author_inst": "Charit\u00e9-Universist\u00e4tsmedizin Berlin" + }, + { + "author_name": "Markus Ralser", + "author_inst": "Charit\u00e9-Universit\u00e4tsmedizin, Department of Biochemistry, 10117 Berlin, Germany." + }, + { + "author_name": "Iker Valle Aramburu", + "author_inst": "The Francis Crick Institute, Antimicrobial Defence Laboratory, London, United Kingdom." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.01.25.22269735", @@ -398707,27 +397606,23 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2022.01.23.22269704", - "rel_title": "Are allergic diseases a risk factor for systemic side effects after COVID-19 vaccines?", + "rel_doi": "10.1101/2022.01.22.22269700", + "rel_title": "Estimated Fraction of Incidental COVID Hospitalizations in a Cohort of 250 High-Volume Hospitals Located in 164 Counties", "rel_date": "2022-01-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.23.22269704", - "rel_abs": "Background/ aimMass vaccination seems to be the most effective way to turn back to the pre-pandemic period and end the pandemic. Unfortunately, COVID-19 vaccines have some side effects. In phase studies of currently-approved COVID-19 vaccines, patients with a known allergy or a history of anaphylaxis were excluded from the studies. This situation creates doubts about the course of atopy and the presence of allergic disease related to the side effects of COVID-19 vaccines in patients with allergic diseases. Therefore, our aim with this study was to evaluate local side effects (LSE) and systemic side effects (SSE) after COVID-19 vaccines in patients with allergic diseases and to determine possible risk factors.\n\nMaterials and MethodsSix hundred forty-eight adult patients who received any COVID-19 vaccine between April 1, 2021 and September 30, 2021 and agreed to participate in the study were included in this case-control retrospective study.\n\nResultsSix hundred forty-eight adult patients [Female: 446 (68.8%), Male: 202 (32.2%)] participated in the study. After the 1st dose of COVID-19 vaccine, 24.1% of patients reported SSE. After the 2nd dose of COVID-19 vaccine, 67 patients (12.3%) developed SSE. Female gender (OR: 1.757, 95%Cl: 1.143-2.702, p: 0.010), history of previous COVID-19 infection (OR: 1.762, 95%Cl: 1.068-2.906, p: 0.026), and COVID-19 vaccine type administered (OR: 4.443, 95% CI: 2.640-7.476, p<0.001) were found to be independent risk factors for SSE after COVID-19 vaccines. Premedication (OR: 0.454, 95% Cl: 0.281-0.733, p<0.001), was found to be a protective factor for SSE developing after COVID-19 vaccines.\n\nConclusionCoronoVac and Pfizer-BioNTech COVID-19 vaccines are shown to be well tolerated. Patients with allergic disease do not have an increased risk for SSE that may develop after COVID-19 vaccines. Moreover, doubts or fears about possible side effects in the allergic patient group should not be an obstacle to COVID-19 vaccination.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.22.22269700", + "rel_abs": "BackgroundSome reports have suggested that as many as one-half of all hospital inpatients identified as COVID-19-positive during the Omicron BA.1 variant-driven wave were incidental cases admitted primarily for reasons other than their viral infections. To date, however, there are no prospective longitudinal studies of a representative panel of hospitals based on pre-established criteria for determining whether a patient was in fact admitted as a result of the disease.\n\nMaterials and MethodsTo fill this gap, we developed a formula to estimate the fraction of incidental COVID-19 hospitalizations that relies upon measurable, population-based parameters. We applied our approach to a longitudinal panel of 164 counties throughout the United States, covering a 4-week interval ending in the first week of January 2022.\n\nResultsWithin this panel, we estimated that COVID-19 incidence was rising exponentially at a rate of 9.34% per day (95% CI, 8.93-9.87). Assuming that only one-quarter of all Omicron BA.1 infections had been reported by public authorities, we further estimated the aggregate prevalence of active SARS-CoV-2 infection during the first week of January to be 3.45%. During the same week, among 250 high-COVID-volume hospitals within our 164-county panel, an estimated 1 in 4 inpatients was COVID-positive. Based upon these estimates, we computed that 10.6% of such COVID-19-positive hospitalized patients were incidental infections. Across individual counties, the median fraction of incidental COVID-19 hospitalizations was 9.5%, with an interquartile range of 6.7 to 12.7%.\n\nConclusionIncidental COVID-19 infections appear to have been a nontrivial fraction of all COVID-19-positive hospitalized patients during the Omicron BA.1 wave. In the aggregate, however, the burden of patients admitted for complications of their viral infections was far greater.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "EMEL ATAYIK", - "author_inst": "Konya City Hospital, Immunology and Allergy" - }, - { - "author_name": "Gokhan Aytekin", - "author_inst": "Konya City Hospital" + "author_name": "Jeffrey E Harris", + "author_inst": "Massachusetts Institute of Technology" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.01.23.22269716", @@ -400753,83 +399648,75 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.01.21.22269165", - "rel_title": "Quantifying post-vaccination protective anti-SARS-CoV-2 IgG antibodies in blood and saliva with a fully automated, high throughput digital immunoassay", + "rel_doi": "10.1101/2022.01.21.22269651", + "rel_title": "Prior health-related behaviours in children (2014-2020) and association with a positive SARS-CoV-2 test during adolescence (2020-2021): a retrospective cohort study using survey data linked with routine health data in Wales, UK", "rel_date": "2022-01-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.21.22269165", - "rel_abs": "BackgroundAntibodies induced by COVID-19 vaccination have been shown to wane over time. Current tests for assessing virus-neutralizing antibodies are complex and time-intensive. There is a need for a simple diagnostic test that measures levels of protective antibodies to help monitor immunity status.\n\nMethodUsing a commercially available FDA-authorized semi-quantitative SARS-CoV-2 IgG test, we monitored the duration of the immune response in dried blood microsamples (DBS) and saliva to vaccination by 3 different vaccines across prospective cohorts of 8 COVID-19 naive and 29 COVID-19 recovered individuals over a six-month period. We correlated the results to a binding blockade assay validated to a live virus neutralization assay to validate the test for measurement of protective antibodies.\n\nResultsThe immune response characteristics between the two mRNA vaccines were similar over the 6-month period in both the COVID-19 naive and recovered cohorts. IgG titers in DBS were generally 3-4 orders of magnitude higher than in saliva, and longitudinal profiles were highly correlated between the two matrices (Rm = 0.80). Median IgG concentrations post-vaccination declined to <10% neutralization capacity with all vaccines by six months.\n\nConclusionsThe potential of a simple, fully automated high throughput anti-SARS-CoV-2 IgG test to quantitatively measure protective antibodies in samples collected remotely or at the point of care was demonstrated. The IgG immune response and protective immunity was shown to decline significantly by six months.\n\nPlain Language SummaryIn response to infection the immune system produces proteins called antibodies that recognize and bind to foreign invaders. Vaccines train the immune system to recognize and produce antibodies against specific invaders, such as SAR-CoV-2. Measurement of antibody levels in blood help monitor a persons response to vaccination and have been shown to correlate with protection against disease, which wanes over time following vaccination. It is desirable to have an easy test that predicts protection against infection and measuring antibody levels may provide a solution, however different tests report results differently hindering the establishment of a cutoff for protected vs. not. We quantified antibody levels in saliva and dried blood microsamples (DBS) following vaccination using an automated semi-quantitative IgG test. By reporting concentration of antibodies, and if anchored to an international standard, this test could help establish a cutoff of protection that would be transferable across the multiple different test types. Furthermore, by measuring in saliva and DBS we demonstrate an easy path to at-home or point-of-care sample collection, which could allow wide-scale monitoring of immune protection against SARS-CoV-2.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.21.22269651", + "rel_abs": "ObjectivesExamine if pre-COVID-19 pandemic (prior March 2020) health-related behaviours during primary school are associated with i) being tested for SARS-CoV-2 and ii) testing positive between 1 March 2020 to 31 August 2021.\n\nDesignRetrospective cohort study using an online cohort survey (January 2018 to February 2020) linked to routine PCR SARS-CoV-2 test results.\n\nSettingChildren attending primary schools in Wales (2018-2020), UK who were part of the HAPPEN school network.\n\nParticipantsComplete linked records of eligible participants were obtained for n=7,062 individuals. 39.1% (n=2,764) were tested (age 10.6{+/-}0.9, 48.9% girls) and 8.1% (n=569) tested positive for SARS-CoV-2 (age 10.6{+/-}1.0, 54.5% girls).\n\nMain outcome measuresLogistic regression of health-related behaviours and demographics were used to determine Odds Ratios (OR) of factors associated with i) being tested for SARS-CoV-2 and ii) testing positive for SARS-CoV-2.\n\nResultsConsuming sugary snacks (1-2 days/week OR=1.24, 95% CI 1.04 - 1.49; 5-6 days/week 1.31, 1.07 - 1.61; reference 0 days) can swim 25m (1.21, 1.06 - 1.39) and age (1.25, 1.16 - 1.35) were associated with an increased likelihood of being tested for SARS-CoV-2. Eating breakfast (1.52, 1.01 - 2.27), weekly physical activity [≥] 60 mins (1-2 days 1.69, 1.04 - 2.74; 3-4 days 1.76, 1.10 - 2.82, reference 0 days), out of school club participation (1.06, 1.02 - 1.10), can ride a bike (1.39, 1.00 - 1.93), age (1.16, 1.05 - 1.28) and girls (1.21, 1.00 - 1.46) were associated with an increased likelihood of testing positive for SARS-CoV-2. Living in least deprived quintiles 4 (0.64, 0.46 - 0.90) and 5 (0.64, 0.46 - 0.89) compared to the most deprived quintile was associated with a decreased likelihood.\n\nConclusionsAssociations may be related to parental health literacy and monitoring behaviours. Physically active behaviours may include co-participation with others, and exposure to SARS-CoV-2. A risk versus benefit approach must be considered given the importance of health-related behaviours for development.\n\nSTRENGTHS AND LIMITATIONSO_LIInvestigation of the association of pre-pandemic child health-related behaviour measures with subsequent SARS-CoV-2 testing and infection.\nC_LIO_LIReporting of multiple child health behaviours linked at an individual-level to routine records of SARS-CoV-2 testing data through the SAIL Databank.\nC_LIO_LIChild-reported health behaviours were measured before the COVID-19 pandemic (1 January 2018 to 28 February 2020) which may not reflect behaviours during COVID-19.\nC_LIO_LIHealth behaviours captured through the national-scale HAPPEN survey represent children attending schools that engaged with the HAPPEN Wales primary school network and may not be representative of the whole population of Wales.\nC_LIO_LIThe period of study for PCR-testing for and testing positive for SARS-CoV-2 includes a time frame with varying prevalence rates, approaches to testing children (targeted and mass testing) and restrictions which were not measured in this study.\nC_LI", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Joseph M Johnson", - "author_inst": "Quanterix Corporation" - }, - { - "author_name": "Syrena C Fernandes", - "author_inst": "Quanterix Corporation" - }, - { - "author_name": "Danica L Wuelfing", - "author_inst": "Quanterix Corporation" + "author_name": "Emily Marchant", + "author_inst": "Swansea University" }, { - "author_name": "Aaron R Baillargeon", - "author_inst": "Quanterix Corporation" + "author_name": "Emily Lowthian", + "author_inst": "Swansea University" }, { - "author_name": "Evan L MacLure", - "author_inst": "Quanterix Corporation" + "author_name": "Tom Crick", + "author_inst": "Swansea University" }, { - "author_name": "Soyoon Hwang", - "author_inst": "Quanterix Corporation" + "author_name": "Lucy Griffiths", + "author_inst": "Swansea University" }, { - "author_name": "Andrew J Ball", - "author_inst": "Quanterix Corporation" + "author_name": "Richard Fry", + "author_inst": "Swansea University" }, { - "author_name": "Narayanaiah Cheedarla", - "author_inst": "Emory University" + "author_name": "Kevin Dadaczynski", + "author_inst": "Fulda University of Applied Sciences" }, { - "author_name": "Hans P Verkerke", - "author_inst": "Emory University" + "author_name": "Orkan Okan", + "author_inst": "Technical University Munich" }, { - "author_name": "Sindhu Potlapalli", - "author_inst": "Emory University" + "author_name": "Michaela James", + "author_inst": "Swansea University" }, { - "author_name": "Kaleb Benjamin McLendon", - "author_inst": "Emory University" + "author_name": "Laura Cowley", + "author_inst": "Public Health Wales" }, { - "author_name": "Andrew Neish", - "author_inst": "Emory University" + "author_name": "Fatemeh Torabi", + "author_inst": "Swansea University" }, { - "author_name": "William O'Sick", - "author_inst": "Emory University" + "author_name": "Jonathan Kennedy", + "author_inst": "Swansea University" }, { - "author_name": "John D Roback", - "author_inst": "Emory University" + "author_name": "Ashley Akbari", + "author_inst": "Swansea University" }, { - "author_name": "David H Wilson", - "author_inst": "Quanterix Corporation" + "author_name": "Ronan Lyons", + "author_inst": "Swansea University" }, { - "author_name": "Dawn Mattoon", - "author_inst": "Quanterix Corporation" + "author_name": "Sinead Brophy", + "author_inst": "Swansea University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.01.17.475291", @@ -402607,39 +401494,87 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.01.20.22269253", - "rel_title": "PBPK-led guidance for the treatment of cystic fibrosis patients taking elexacaftor-tezacaftor-ivacaftor with the newly approved fixed dose combination nirmatrelvir-ritonavir (PAXLOVID) for the treatment of COVID-19", + "rel_doi": "10.1101/2022.01.21.22269423", + "rel_title": "Aerosol measurement identifies SARS-CoV 2 PCR positive adults compared with healthy controls", "rel_date": "2022-01-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.20.22269253", - "rel_abs": "BackgroundCystic fibrosis transmembrane conductance regulator (CFTR) modulating therapies including elexacaftor, tezacaftor, and ivacaftor (ETI) are primarily eliminated through cytochrome P450 (CYP) 3A-mediated metabolism. This creates a therapeutic challenge to the treatment of COVID-19 with nirmatrelvir-ritonavir in people with cystic fibrosis (pwCF) due to the potential for significant drug-drug interactions (DDI). However, pwCF are more at risk of serious illness following COVID-19 infection and hence it is important to manage the DDI risk and provide treatment options.\n\nMethodsCYP3A-mediated DDI of ETI was evaluated using a physiologically based pharmacokinetic (PBPK) modeling approach. Modeling was performed incorporating physiological information and drug dependent parameters of ETI to predict the effect of ritonavir (the CYP3A4 inhibiting component of the combination) on pharmacokinetics of ETI. The ETI models were verified using independent clinical pharmacokinetic and DDI data of ETI with a range of CYP3A modulators.\n\nResultsWhen ritonavir was administered on day 1 through 5, the predicted AUC ratio of ivacaftor (the most sensitive CYP3A substrate) on day 6 was 9.31, indicating that its metabolism was strongly inhibited. Based on the predicted DDI, the dose of ETI should be reduced when co-administered with nirmatrelvir-ritonavir to elexacaftor 200mg-tezacaftor 100mg-ivacaftor 150mg on days 1 and 5, with resumption of full dose ETI on day 9, considering the residual inhibitory effect of ritonavir as a mechanism-based inhibitor.\n\nConclusionsCoadministration of nirmatrelvir-ritonavir requires a significant reduction in the ETI dosing frequency with delayed resumption of full dose due to the mechanism-based inhibition with ritonavir.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.21.22269423", + "rel_abs": "BackgroundSARS-CoV-2 is spread primarily through droplets and aerosols. Exhaled aerosols are generated in the lung periphery by reopening of collapsed airways. Aerosol measuring may detect highly contagious individuals (\"super spreaders or super-emitters\") and discriminate between SARS-CoV-2 infected and non-infected individuals. This is the first study comparing exhaled aerosols in SARS-CoV-2 infected individuals and healthy controls.\n\nDesignA prospective observational cohort study in 288 adults, comprising 64 patients testing positive by SARS CoV-2 PCR before enrollment, and 224 healthy adults testing negative (matched control sample) at the University Hospital Frankfurt, Germany, from February to June 2021. Study objective was to evaluate the concentration of exhaled aerosols during physiologic breathing in SARS-CoV-2 PCR-positive and -negative subjects. Secondary outcome measures included correlation of aerosol concentration to SARS-CoV-2 PCR results, change in aerosol concentration due to confounders, and correlation between clinical symptoms and aerosol.\n\nResultsThere was a highly significant difference in respiratory aerosol concentrations between SARS-CoV-2 PCR-positive (median 1490.5/L) and -negative subjects (median 252.0/L; p<0.0001). There were no significant differences due to age, sex, smoking status, or body mass index. ROC analysis showed an AUC of 0.8918.\n\nConclusionsMeasurements of respiratory aerosols were significantly elevated in SARS-CoV-2 positive individuals and may become a helpful tool in detecting highly infectious individuals via a noninvasive breath test.\n\nClinical Trial NumberClinicalTrials.gov Identifier: NCT04739020.\n\nSummary of the main pointIn this prospective, comparative cohort study, higher numbers of exhaled respiratory aerosols correlate with a positive PCR test for SARS-CoV-2. Measurement of exhaled aerosols may become a helpful tool in detecting contagious individuals via a readily available breath test.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Eunjin Hong", - "author_inst": "University of Southern California" + "author_name": "Desiree Gutmann", + "author_inst": "University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany" }, { - "author_name": "Lisa M. Almond", - "author_inst": "Certara UK Ltd, Simcyp Division" + "author_name": "Gerhard Scheuch", + "author_inst": "GS Bio-Inhalation GmbH, Headquarters & Logistics, Gemuenden, Germany" }, { - "author_name": "Peter S. Chung", - "author_inst": "University of Southern California" + "author_name": "Timon Lehmkuhler", + "author_inst": "University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany" }, { - "author_name": "Adupa P. Rao", - "author_inst": "University of Southern California" + "author_name": "Laura-Sabine Herrlich", + "author_inst": "University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany" }, { - "author_name": "Paul M. Beringer", - "author_inst": "University of Southern California" + "author_name": "Martin Hutter", + "author_inst": "University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany" + }, + { + "author_name": "Christoph Stephan", + "author_inst": "University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany" + }, + { + "author_name": "Maria Vehreschild", + "author_inst": "University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany" + }, + { + "author_name": "Yascha Khodamoradi", + "author_inst": "University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany" + }, + { + "author_name": "Ann-Kathrin Gossmann", + "author_inst": "Palas GmbH, Partikel- und Lasermesstechnik, Greschbachstrasse 3b; 76229 Karlsruhe, Germany" + }, + { + "author_name": "Florian King", + "author_inst": "Palas GmbH, Partikel- und Lasermesstechnik, Greschbachstrasse 3b; 76229 Karlsruhe, Germany" + }, + { + "author_name": "Frederik Weis", + "author_inst": "Palas GmbH, Partikel- und Lasermesstechnik, Greschbachstrasse 3b; 76229 Karlsruhe, Germany" + }, + { + "author_name": "Maximilian Weiss", + "author_inst": "Palas GmbH, Partikel- und Lasermesstechnik, Greschbachstrasse 3b; 76229 Karlsruhe, Germany." + }, + { + "author_name": "Holger F Rabenau", + "author_inst": "University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany." + }, + { + "author_name": "Juergen Graf", + "author_inst": "University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany." + }, + { + "author_name": "Helena Donath", + "author_inst": "University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany" + }, + { + "author_name": "Ralf Schubert", + "author_inst": "University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany" + }, + { + "author_name": "Stefan Zielen", + "author_inst": "University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "pharmacology and therapeutics" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2022.01.20.22269321", @@ -404489,127 +403424,67 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.01.19.476693", - "rel_title": "SARS-CoV-2 impairs interferon production via NSP2-induced repression of mRNA translation", - "rel_date": "2022-01-20", + "rel_doi": "10.1101/2022.01.17.476556", + "rel_title": "Structural basis for Nirmatrelvir in vitro efficacy against the Omicron variant of SARS-CoV-2", + "rel_date": "2022-01-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.19.476693", - "rel_abs": "Viruses evade the innate immune response by suppressing the production or activity of cytokines such as type I interferons (IFNs). Here we report the discovery of a novel mechanism by which the SARS-CoV-2 virus co-opts an intrinsic cellular machinery to suppress the production of the key immunostimulatory cytokine IFN-{beta}. We reveal that the SARS-CoV-2 encoded Non-Structural Protein 2 (NSP2) directly interacts with the cellular GIGYF2 protein. This interaction enhances the binding of GIGYF2 to the mRNA cap-binding protein 4EHP, thereby repressing the translation of the Ifnb1 mRNA. Depletion of GIGYF2 or 4EHP significantly enhances IFN-{beta} production, leading to reduced viral infection. Our findings reveal a new target for rescuing the antiviral innate immune response to SARS-CoV-2 and other RNA viruses.", - "rel_num_authors": 27, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.17.476556", + "rel_abs": "The COVID-19 pandemic continues to be a public health threat with emerging variants of SARS-CoV-2. Nirmatrelvir (PF-07321332) is a reversible, covalent inhibitor targeting the main protease (Mpro) of SARS-CoV-2 and the active protease inhibitor in PAXLOVID (nirmatrelvir tablets and ritonavir tablets). We evaluated the in vitro catalytic activity and in vitro potency of nirmatrelvir against the main protease (Mpro) of prevalent variants of concern (VOC) or variants of interest (VOI): Alpha (, B.1.1.7), Beta ({beta}, B.1.351), Delta ({delta}, B1.617.2), Gamma ({gamma}, P.1), Lambda ({lambda}, B.1.1.1.37/C37), Omicron (o, B.1.1.529) as well as the original Washington or wildtype strain. These VOC/VOI carry prevalent mutations at varying frequencies in the Mpro specifically for: , {beta},{gamma} (K90R), {lambda} (G15S) and o (P132H). In vitro biochemical enzymatic assay characterization of the enzyme kinetics of the mutant Mpros demonstrate that they are catalytically comparable to wildtype. Nirmatrelvir has similar potency against each mutant Mpro including P132H that is observed in the Omicron variant with a Ki of 0.635 nM as compared to a Ki of 0.933nM for wildtype. The molecular basis for these observations were provided by solution-phase structural dynamics and structural determination of nirmatrelvir bound to the o, {lambda} and {beta} Mpro at 1.63 - 2.09 [A] resolution. These in vitro data suggest that PAXLOVID has the potential to maintain plasma concentrations of nirmatrelvir many-fold times higher than the amount required to stop the SARS-CoV-2 VOC/VOI, including Omicron, from replicating in cells (1).", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Jung-Hyun Choi", - "author_inst": "McGill University" - }, - { - "author_name": "Xu Zhang Sr.", - "author_inst": "McGill University" - }, - { - "author_name": "Christine Zhang", - "author_inst": "University of Manitoba" - }, - { - "author_name": "David L. Dai", - "author_inst": "University Health Network, University of Toronto" - }, - { - "author_name": "Jun Luo", - "author_inst": "McGill University" - }, - { - "author_name": "Reese Ladak", - "author_inst": "McGill University" - }, - { - "author_name": "Qian Li", - "author_inst": "McGill University" - }, - { - "author_name": "Shane Wiebe", - "author_inst": "McGill University" - }, - { - "author_name": "Alex C.H. Liu", - "author_inst": "University Health Network, University of Toronto" - }, - { - "author_name": "Xiaozhuo Ran", - "author_inst": "University Health network, University of Toronto" - }, - { - "author_name": "Jiaqi Yang", - "author_inst": "University Health Network, University of Toronto" - }, - { - "author_name": "Parisa Naeli", - "author_inst": "Queen University Belfast" - }, - { - "author_name": "Aitor Garzia", - "author_inst": "The Rockefeller University" - }, - { - "author_name": "Lele Zhou", - "author_inst": "McGill University" - }, - { - "author_name": "Niaz Mahmood", - "author_inst": "McGill University" - }, - { - "author_name": "Qiyun Deng", - "author_inst": "McGill University" + "author_name": "Samantha E Greasley", + "author_inst": "Pfizer" }, { - "author_name": "Mohamed Elaish", - "author_inst": "University of Alberta" + "author_name": "Stephen Noell", + "author_inst": "Pfizer" }, { - "author_name": "Rongtuan Lin", - "author_inst": "McGill University" + "author_name": "Olga Plotnikova", + "author_inst": "Pfizer" }, { - "author_name": "Tom Hobman", - "author_inst": "University of Alberta" + "author_name": "Rose Ann Ferre", + "author_inst": "Pfizer" }, { - "author_name": "Jerry Pelletier", - "author_inst": "McGill University" + "author_name": "Wei Liu", + "author_inst": "Pfizer" }, { - "author_name": "Tommy Alain", - "author_inst": "University of Ottawa" + "author_name": "Ben Bolanos", + "author_inst": "Pfizer" }, { - "author_name": "Silvia Vidal", - "author_inst": "McGill University" + "author_name": "Kimberly F. Fennell", + "author_inst": "Pfizer" }, { - "author_name": "Thomas Duchaine", - "author_inst": "McGill University" + "author_name": "Jennifer Nicki", + "author_inst": "Pfizer" }, { - "author_name": "Mohammad Mazhab-Jafari", - "author_inst": "University Health network, University of Toronto" + "author_name": "Timothy Craig", + "author_inst": "Pfizer" }, { - "author_name": "XiaoJuan Mao", - "author_inst": "University of Manitoba" + "author_name": "Yuao Zhu", + "author_inst": "Pfizer" }, { - "author_name": "Seyed Mehdi Jafarnejad", - "author_inst": "Queen University Belfast" + "author_name": "Al E Stewart", + "author_inst": "Pfizer" }, { - "author_name": "Nahum Sonenberg", - "author_inst": "McGill University" + "author_name": "Claire M Steppan", + "author_inst": "Pfizer" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2022.01.17.476644", @@ -406514,59 +405389,27 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2022.01.17.22269440", - "rel_title": "Systematic recovery of building plumbing-associated microbial communities after extended periods of altered water demand during the COVID-19 pandemic.", + "rel_doi": "10.1101/2022.01.13.476194", + "rel_title": "Second Climate Survey of Biomedical PhD Students in the Time of Covid", "rel_date": "2022-01-18", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.17.22269440", - "rel_abs": "Building closures related to the coronavirus disease (COVID-19) pandemic resulted in increased water stagnation in commercial building plumbing systems that heightened concerns related to the microbiological safety of drinking water post re-opening. The exact impact of extended periods of reduced water demand on water quality is currently unknown due to the unprecedented nature of widespread building closures. We analyzed 420 tap water samples over a period of six months, starting the month of phased reopening (i.e., June 2020), from sites at three commercial buildings that were subjected to reduced capacity due to COVID-19 social distancing policies and four occupied residential households. Direct and derived flow cytometric measures along with water chemistry characterization were used to evaluate changes in plumbing-associated microbial communities with extended periods of altered water demand. Our results indicate that prolonged building closures impacted microbial communities in commercial buildings as indicated by increases in microbial cell counts, encompassing greater proportion cells with high nucleic acids. While flushing reduced cell counts and increased disinfection residuals, the microbial community composition in commercial buildings were still distinct from those at residential households. Nonetheless, increased water demand post-reopening enhanced systematic recovery over a period of months, as microbial community fingerprints in commercial buildings converged with those in residential households. Overall, our findings suggest that sustained and gradual increases in water demand may play a more important role in the recovery of building plumbing-associated microbial communities as compared to short-term flushing, after extended periods of altered water demand that result in reduced flow volumes.", - "rel_num_authors": 10, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.13.476194", + "rel_abs": "In July 2021, sixteen months into the Covid-19 pandemic, the institutional climate for PhD training in the School of Medicine was assessed for a second time. This survey of graduate students occurred 1 year after initial surveys of graduate students and training faculty in July 2020. The 2021 survey was completed by 99 PhD students in 11 PhD-granting programs. To allow comparisons between years, most of the 2021 questions were repeated with only minor edits. A few items were added to assess impacts of school-wide town hall meetings, a new PhD career club program, and enlarged mental health services. Several themes emerged. Students remain extremely concerned about the pandemics impact upon their training and long-term career prospects. They worry specifically about pandemic related reductions in research productivity and networking opportunities. Many students successfully adapted to laboratory research under pandemic restrictions but suffer from the continuing lack of social interaction even after in-person work hours increased. Symptoms of anxiety and/or depression persist amongst 46% of the students, as compared to 51% in 2020. Nearly 80% of students continue to report strong satisfaction with mentoring relationships with their dissertation advisors, but to lesser extents with programs (66%), departments or centers (71%), the School of Medicine (32%) and the University (49%). Students (26%) express interest in the Ombuds office that was announced in late 2021. Some students wrote that the medical school could do a better job in embracing diversity and inclusion and in mentor training, and many stated that town hall meetings do not serve them well. Coping mechanisms shared by some students demonstrate impressive resilience. These results present a mixed picture. While aspects of biomedical PhD training have begun to recover as the pandemic continues, long-term consequences of the disruption raise challenges that must be addressed by efforts to restore and improve the learning environment required for 21st century research education.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Solize Vosloo", - "author_inst": "Northeastern University" - }, - { - "author_name": "Linxuan Huo", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "Umang Chauhan", - "author_inst": "Northeastern University" - }, - { - "author_name": "Irmarie Cotto", - "author_inst": "Northeastern University" - }, - { - "author_name": "Benjamin Gincley", - "author_inst": "Northeastern University" - }, - { - "author_name": "Katherine J Vilardi", - "author_inst": "Northeastern University" - }, - { - "author_name": "Byungman Yoon", - "author_inst": "Northeastern University" - }, - { - "author_name": "Kelsey J Pieper", - "author_inst": "Northeastern University" - }, - { - "author_name": "Aron Stubbins", - "author_inst": "Northeastern University" + "author_name": "Deepti Ramadoss", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Ameet J Pinto", - "author_inst": "Georgia Institute of Technology" + "author_name": "John P Horn", + "author_inst": "University of Pittsburgh" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "type": "new results", + "category": "scientific communication and education" }, { "rel_doi": "10.1101/2022.01.14.22269074", @@ -408168,47 +407011,119 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.01.14.22269312", - "rel_title": "Students as Community Vaccinators: Implementation of a Service-Learning COVID-19 Vaccination Program", + "rel_doi": "10.1101/2022.01.13.22269257", + "rel_title": "Viral dynamics and duration of PCR positivity of the SARS-CoV-2 Omicron variant", "rel_date": "2022-01-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.14.22269312", - "rel_abs": "BackgroundService-learning is an integral component of medical education. While the COVID-19 pandemic has caused massive educational disruptions, it has also catalyzed innovation in service-learning as real-time responses to pandemic-related problems. For example, the limited number of qualified providers was a potential barrier to local and national SARS-CoV-2 vaccination efforts. Foreseeing this hurdle, New York State temporarily allowed healthcare professional trainees to vaccinate, enabling medical students to support an overwhelmed healthcare system and contribute to the community. Yet, it was the responsibility of medical schools to interpret these rules and implement the vaccination programs. Here the authors describe a service-learning vaccination program directed towards underserved communities.\n\nMethodsWeill Cornell Medicine (WCM) rapidly developed a faculty-led curriculum to prepare students to communicate with patients about the COVID-19 vaccines and to administer intramuscular injections. Qualified students were deployed to public vaccination clinics located in underserved neighborhoods across New York City in collaboration with an established community partner. The educational value of the program was evaluated with retrospective survey.\n\nResultsThroughout the program, which lasted from February to June 2021, 128 WCM students worked at 103 local events, helping to administer 26,889 vaccine doses. Analysis of student evaluations revealed this program taught fundamental clinical skills, increasing comfort giving intramuscular injection from 2% to 100% and increasing comfort talking to patients about the COVID-19 vaccine from 30% to 100%. Qualitatively participants described the program as a transformative service-learning experience.\n\nConclusionAs new virus variants emerge, nations battle recurrent waves of infection, and vaccine eligibility expands to include children and boosters, the need for effective vaccination plans continues to grow. The program described here offers a novel framework that academic medical centers could adapt to increase vaccine access in their local community and provide students with a uniquely meaningful educational experience.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.13.22269257", + "rel_abs": "BackgroundThe combined impact of immunity and SARS-CoV-2 variants on viral kinetics during infections has been unclear.\n\nMethodsWe characterized 2,875 infections from the National Basketball Association occupational health cohort identified between June 2020 and January 2022 using serial RT-qPCR testing. Logistic regression and semi-mechanistic viral RNA kinetics models were used to quantify the effect of variant, symptom status, age, infection history, vaccination and antibody titer to founder SARS-CoV-2 strain on the duration of potential infectiousness and overall viral kinetics. The frequency of viral rebounds was quantified under multiple cycle threshold (Ct) value-based definitions.\n\nResultsAmong individuals detected partway through their infection, 51.0% (95% credible interval [CrI]: 48.2-53.6%) remained potentially infectious (Ct<30) five days post detection, with small differences across variants and vaccination history. Only seven viral rebounds (0.7%; N=999) were observed, with rebound defined as 3+ days with Ct<30 following an initial clearance of 3+ days with Ct[≥]30. High antibody titers against the founder SARS-CoV-2 strain predicted lower peak viral loads and shorter durations of infection. Among Omicron BA.1 infections, boosted individuals had lower pre-booster antibody titers and longer clearance times than non-boosted individuals.\n\nConclusionsSARS-CoV-2 viral kinetics are partly determined by immunity and variant but dominated by individual-level variation. Since booster vaccination protects against infection, longer clearance times for BA.1-infected, boosted individuals may reflect a less effective immune response, more common in older individuals, that increases infection risk and reduces viral RNA clearance rate. The shifting landscape of viral kinetics underscores the need for continued monitoring to optimize isolation policies and to contextualize the health impacts of therapeutics and vaccines.\n\nFundingSupported in part by CDC contract 200-2016-91779, Emergent Ventures at the Mercatus Center, the Huffman Family Donor Advised Fund, the MorrisSinger Fund, the National Basketball Association, and the National Basketball Players Association.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Andrew R. Griswold", - "author_inst": "Weill Cornell Medicine" + "author_name": "James A Hay", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Julia Klein", - "author_inst": "Weill Cornell Medicine" + "author_name": "Stephen M Kissler", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Neville Dusaj", - "author_inst": "Weill Cornell Medicine" + "author_name": "Joseph R Fauver", + "author_inst": "Yale School of Public Health" }, { - "author_name": "Jeff Zhu", - "author_inst": "Weill Cornell Medicine" + "author_name": "Christina Mack", + "author_inst": "IQVIA, Real World Solutions" }, { - "author_name": "Allegra Keeler", - "author_inst": "Weill Cornell Medicine" + "author_name": "Caroline G Tai", + "author_inst": "IQVIA, Real World Solutions" }, { - "author_name": "Erika L. Abramson", - "author_inst": "Weill Cornell Medicine" + "author_name": "Radhika M Samant", + "author_inst": "IQVIA, Real World Solutions" }, { - "author_name": "Dana Gurvitch", - "author_inst": "Weill Cornell Medicine" + "author_name": "Sarah Connolly", + "author_inst": "IQVIA, Real World Solutions" + }, + { + "author_name": "Deverick J Anderson", + "author_inst": "Duke Center for Antimicrobial Stewardship and Infection Prevention" + }, + { + "author_name": "Gaurav Khullar", + "author_inst": "TEMPUS Labs" + }, + { + "author_name": "Matthew MacKay", + "author_inst": "TEMPUS Labs" + }, + { + "author_name": "Miral Patel", + "author_inst": "TEMPUS Labs" + }, + { + "author_name": "Shannan Kelly", + "author_inst": "TEMPUS Labs" + }, + { + "author_name": "April Manhertz", + "author_inst": "TEMPUS Labs" + }, + { + "author_name": "Isaac Eiter", + "author_inst": "TEMPUS Labs" + }, + { + "author_name": "Daisy Salgado", + "author_inst": "TEMPUS Labs" + }, + { + "author_name": "Tim Baker", + "author_inst": "TEMPUS Labs" + }, + { + "author_name": "Ben Howard", + "author_inst": "TEMPUS Labs" + }, + { + "author_name": "Joel T Dudley", + "author_inst": "TEMPUS Labs" + }, + { + "author_name": "Christopher E Mason", + "author_inst": "TEMPUS Labs" + }, + { + "author_name": "Manoj Nair", + "author_inst": "Columbia University Vagelos College of Physicians and Surgeons" + }, + { + "author_name": "Yaoxing Huang", + "author_inst": "Columbia University Vagelos College of Physicians and Surgeons" + }, + { + "author_name": "John DiFiori", + "author_inst": "National Basketball Association, New York, NY, USA" + }, + { + "author_name": "David D Ho", + "author_inst": "Columbia University Vagelos College of Physicians and Surgeons" + }, + { + "author_name": "Nathan D Grubaugh", + "author_inst": "Yale School of Public Health" + }, + { + "author_name": "Yonatan H Grad", + "author_inst": "Harvard T.H. Chan School of Public Health" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "medical education" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.01.11.22269069", @@ -410078,281 +408993,25 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.01.11.22268631", - "rel_title": "Development and validation of the MMCD score to predict kidney replacement therapy in COVID-19 patients", + "rel_doi": "10.1101/2022.01.13.22269154", + "rel_title": "Antigenic evolution of SARS-CoV-2 in immunocompromised hosts", "rel_date": "2022-01-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.11.22268631", - "rel_abs": "BackgroundAcute kidney injury (AKI) is frequently associated with COVID-19 and the need for kidney replacement therapy (KRT) is considered an indicator of disease severity. This study aimed to develop a prognostic score for predicting the need for KRT in hospitalized COVID-19 patients.\n\nMethodsThis study is part of the multicentre cohort, the Brazilian COVID-19 Registry. A total of 5,212 adult COVID-19 patients were included between March/2020 and September/2020. We evaluated four categories of predictor variables: (1) demographic data; (2) comorbidities and conditions at admission; (3) laboratory exams within 24 h; and (4) the need for mechanical ventilation at any time during hospitalization. Variable selection was performed using generalized additive models (GAM) and least absolute shrinkage and selection operator (LASSO) regression was used for score derivation. The accuracy was assessed using the area under the receiver operating characteristic curve (AUC-ROC). Risk groups were proposed based on predicted probabilities: non-high (up to 14.9%), high (15.0 - 49.9%), and very high risk ([≥] 50.0%).\n\nResultsThe median age of the model-derivation cohort was 59 (IQR 47-70) years, 54.5% were men, 34.3% required ICU admission, 20.9% evolved with AKI, 9.3% required KRT, and 15.1% died during hospitalization. The validation cohort had similar age, sex, ICU admission, AKI, required KRT distribution and in-hospital mortality. Thirty-two variables were tested and four important predictors of the need for KRT during hospitalization were identified using GAM: need for mechanical ventilation, male gender, higher creatinine at admission, and diabetes. The MMCD score had excellent discrimination in derivation (AUROC = 0.929; 95% CI 0.918-0.939) and validation (AUROC = 0.927; 95% CI 0.911-0.941) cohorts an good overall performance in both cohorts (Brier score: 0.057 and 0.056, respectively). The score is implemented in a freely available online risk calculator (https://www.mmcdscore.com/).\n\nConclusionThe use of the MMCD score to predict the need for KRT may assist healthcare workers in identifying hospitalized COVID-19 patients who may require more intensive monitoring, and can be useful for resource allocation.", - "rel_num_authors": 66, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.13.22269154", + "rel_abs": "Prolonged infections of immunocompromised individuals have been proposed as a crucial source of new variants of SARS-CoV-2 during the COVID-19 pandemic. In principle, sustained within-host antigenic evolution in immunocompromised hosts could allow novel immune escape variants to emerge more rapidly, but little is known about how and when immunocompromised hosts play a critical role in pathogen evolution. Here, we use a simple mathematical model to understand the effects of immunocompromised hosts on the emergence of immune escape variants in the presence and absence of epistasis. We show that when the pathogen does not have to cross a fitness valley for immune escape to occur (no epistasis), immunocompromised individuals have no qualitative effect on antigenic evolution (although they may accelerate immune escape if within-host evolutionary dynamics are faster in immunocompromised individuals). But if a fitness valley exists between immune escape variants at the between-host level (epistasis), then persistent infections of immunocompromised individuals allow mutations to accumulate, therefore facilitating rather than simply speeding up antigenic evolution. Our results suggest that better genomic surveillance of infected immunocompromised individuals and better global health equality, including improving access to vaccines and treatments for individuals who are immunocompromised (especially in lower- and middle-income countries), may be crucial to preventing the emergence of future immune escape variants of SARS-CoV-2.\n\nLay SummaryWe study the role that immunocompromised individuals may play in the evolution of novel variants of the coronavirus responsible for the COVID-19 pandemic. We show that immunocompromised hosts can be crucial for the evolution of immune escape variants. Targeted treatment and surveillance may therefore prevent the emergence of new variants.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Flavio Azevedo Figueiredo", - "author_inst": "UFLA" - }, - { - "author_name": "Lucas Emanuel Ferreira Ramos", - "author_inst": "UFMG" - }, - { - "author_name": "Rafael Tavares Silva", - "author_inst": "UFMG" - }, - { - "author_name": "Magda Carvalho Pires", - "author_inst": "UFMG" - }, - { - "author_name": "Daniela Ponce", - "author_inst": "UNESP" - }, - { - "author_name": "Rafael Lima Rodrigues de Carvalho", - "author_inst": "Institute for Health Technology Assessment (IATS)" - }, - { - "author_name": "Alexandre Vargas Schwarzbold", - "author_inst": "UFSM" - }, - { - "author_name": "Amanda de Oliveira Maurilio", - "author_inst": "Hospital Sao Joao de Deus" - }, - { - "author_name": "Ana Luiza Bahia Alves Scotton", - "author_inst": "Hospital Regional Antonio Dias" - }, - { - "author_name": "Andresa Fontoura Garbini", - "author_inst": "Hospital Nossa Senhora da Conceicao" - }, - { - "author_name": "Barbara Lopes Farace", - "author_inst": "Hospital Risoleta Tolentino Neves" - }, - { - "author_name": "Barbara Machado Garcia", - "author_inst": "FCMMG" - }, - { - "author_name": "Carla Thais Candida Alves Silva", - "author_inst": "Faculdade de Ciencias Humanas de Curvelo" - }, - { - "author_name": "Christiane Correa Rodrigues Cimini Cimini", - "author_inst": "Universidade Federal dos Vales do Jequitinhonha e Mucuri" - }, - { - "author_name": "Cintia Alcantara de Carvalho", - "author_inst": "Hospital Joao XXIII" - }, - { - "author_name": "Cristiane dos Santos Dias", - "author_inst": "UFMG" - }, - { - "author_name": "Daniel Vitorio Silveira", - "author_inst": "Hospital UNIMED BH" - }, - { - "author_name": "Euler Roberto Fernandes Manenti", - "author_inst": "Hospital Mae de Deus" - }, - { - "author_name": "Evelin Paola de Almeida Cenci", - "author_inst": "Hospital Nossa Senhora da Gracas" - }, - { - "author_name": "Fernando Anschau", - "author_inst": "Hospital Nossa Senhora da Conceicao" - }, - { - "author_name": "Fernando Graca Aranha", - "author_inst": "Hospital SOS Cardio" - }, - { - "author_name": "Filipe Carrilho de Aguiar", - "author_inst": "UFPE" - }, - { - "author_name": "Frederico Bartolazzi", - "author_inst": "Hospital Santo Antonio" - }, - { - "author_name": "Giovanna Grunewald Vietta", - "author_inst": "Hospital SOS Cardio" - }, - { - "author_name": "Guilherme Fagundes Nascimento", - "author_inst": "Hospital UNIMED BH" - }, - { - "author_name": "Helena Carolina Noal", - "author_inst": "UFSM" - }, - { - "author_name": "Helena Duani", - "author_inst": "UFMG" - }, - { - "author_name": "Heloisa Reniers Vianna", - "author_inst": "Hospital Universitario Ciencias Medicas" - }, - { - "author_name": "Henrique Cerqueira Guimaraes", - "author_inst": "Hospital Risoleta Tolentino Neves" - }, - { - "author_name": "Joice Coutinho de Alvarenga", - "author_inst": "Hospital Joao XXIII" - }, - { - "author_name": "Jose Miguel Chatkin", - "author_inst": "Hospital Sao Lucas da PUCRS" - }, - { - "author_name": "Julia Parreiras Drumond de Moraes", - "author_inst": "Hospital Universitario Ciencias Medicas" - }, - { - "author_name": "Juliana Machado Rugolo", - "author_inst": "UNESP" - }, - { - "author_name": "Karen Brasil Ruschel", - "author_inst": "Institute for Health Technology Assessment (IATS)" - }, - { - "author_name": "Karina Paula Medeiros Prado Martins", - "author_inst": "UFMG" - }, - { - "author_name": "Luanna Silva Monteiro Menezes", - "author_inst": "Hospital Luxemburgo" - }, - { - "author_name": "Luciana Siuves Ferreira Couto", - "author_inst": "Hospital Luxemburgo" - }, - { - "author_name": "Luis Cesar de Castro", - "author_inst": "UFSM" - }, - { - "author_name": "Luiz Antonio Nasi", - "author_inst": "Hospital Moinhos de Vento" - }, - { - "author_name": "Maderson Alvares de Souza Cabral", - "author_inst": "UFMG" - }, - { - "author_name": "Maiara Anschau Floriani", - "author_inst": "Hospital Moinho de Ventos" - }, - { - "author_name": "Maira Dias Souza", - "author_inst": "Hospital Odilon Behrens" - }, - { - "author_name": "Maira Viana Rego Souza e Silva", - "author_inst": "UFMG" - }, - { - "author_name": "Marcelo Carneiro", - "author_inst": "Hospital Santa Cruz" - }, - { - "author_name": "Mariana Frizzo de Godoy", - "author_inst": "Hospital Sao Lucas PUCRS" - }, - { - "author_name": "Maria Aparecida Camargos Bicalho", - "author_inst": "UFMG" - }, - { - "author_name": "Maria Clara Pontello Barbosa Lima", - "author_inst": "UFOP" - }, - { - "author_name": "Matheus Carvalho Alves Nogueira", - "author_inst": "Hospitais da Rede Mater Dei" - }, - { - "author_name": "Matheus Fernandes Lopes Martins", - "author_inst": "Hospital Marcio Cunha" - }, - { - "author_name": "Milton Henriques Guimaraes-Junior", - "author_inst": "Hospital Marcio Cunha" - }, - { - "author_name": "Natalia da Cunha Severino Sampaio", - "author_inst": "Hospital Eduardo de Menezes" - }, - { - "author_name": "Neimy Ramos de Oliveira", - "author_inst": "Hospital Eduardo de Menezes" - }, - { - "author_name": "Patricia Klarmann Ziegelmann", - "author_inst": "UFRGS" - }, - { - "author_name": "Pedro Guido Soares Andrade", - "author_inst": "Hospital Semper" - }, - { - "author_name": "Pedro Ledic Assaf", - "author_inst": "Hospital Metropolitano Doutor Celio de Castro." - }, - { - "author_name": "Petronio Jose de Lima Martelli", - "author_inst": "UFPE" - }, - { - "author_name": "POLIANNA DELFINO PEREIRA", - "author_inst": "UFMG" - }, - { - "author_name": "Raphael Castro Martins", - "author_inst": "UFRGS" - }, - { - "author_name": "Rochele Mosmann Menezes", - "author_inst": "Caja Petrolera de Salud - Hospital Santa Cruz" - }, - { - "author_name": "Saionara Cristina Francisco", - "author_inst": "Hospital Metropolitano Doutor Celio de Castro" - }, - { - "author_name": "Silvia Ferreira Araujo", - "author_inst": "Hospital Marcio Cunha" - }, - { - "author_name": "Talita Fischer Oliveira", - "author_inst": "Hospital Metropolitano Odilon Behrens" - }, - { - "author_name": "Thainara Conceicao de Oliveira", - "author_inst": "Hospital Universitario Canoas" - }, - { - "author_name": "Thais Lorenna Souza Sales", - "author_inst": "Institute for Health Technology Assessment (IATS)" - }, - { - "author_name": "Yuri Carlotto Ramires", - "author_inst": "Hospital Bruno Born" + "author_name": "Cameron A Smith", + "author_inst": "University of Bath" }, { - "author_name": "Milena Soriano Marcolino", - "author_inst": "Universidade Federal de Minas Gerais" + "author_name": "Ben Ashby", + "author_inst": "University of Bath; Simon Fraser University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -412368,43 +411027,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.12.22269138", - "rel_title": "Change in profile of COVID-19 deaths in the Western Cape during the fourth wave", + "rel_doi": "10.1101/2022.01.10.475722", + "rel_title": "UV-C light completely blocks highly contagious Delta SARS-CoV-2 aerosol transmission in hamsters", "rel_date": "2022-01-12", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.12.22269138", - "rel_abs": "Fewer COVID-19 deaths have been reported in this fourth wave, with clinicians reporting less admissions due to severe COVID-19 pneumonia when compared to previous waves. We therefore aimed to rapidly compare the profile of deaths in wave 4 with wave 3 using routinely collected data on admissions to public sector hospitals in the Western Cape province of South Africa. Findings show that there have been fewer COVID-19 pneumonia deaths in the Omicron-driven fourth wave compared to the third wave, which confirms anecdotal reports and lower bulk oxygen consumption by hospitals in the province.", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.10.475722", + "rel_abs": "Behavioral and medical control measures are not effective in containing the spread of SARS-CoV-2. Here we report on the effectiveness of a preemptive environmental strategy using UV-C light to prevent airborne transmission of the virus in a hamster model and show that UV-C exposure completely prevents airborne transmission between individuals", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Masudah Paleker", - "author_inst": "Western Cape Government: Health" + "author_name": "Robert Fischer", + "author_inst": "NIAID" }, { - "author_name": "Mary-Ann Davies", - "author_inst": "Western Cape Government: Health" + "author_name": "Julia Rebecca Port", + "author_inst": "NIAID Rocky Mountain Laboratories" }, { - "author_name": "Peter Raubenheimer", - "author_inst": "University of Cape Town" + "author_name": "Myndi Holbrook", + "author_inst": "NIAID Rocky Mountain Laboratories" }, { - "author_name": "Jonathan Naude", - "author_inst": "University of Cape Town" + "author_name": "Kwe Claude Yinda", + "author_inst": "NIAID" }, { - "author_name": "Andrew Boulle", - "author_inst": "Western Cape Government: Health" + "author_name": "Martin Creusen", + "author_inst": "Signify" }, { - "author_name": "Hannah Hussey", - "author_inst": "Western Cape Government: Health" + "author_name": "Jeroen ter Stege", + "author_inst": "UVConsult" + }, + { + "author_name": "Marc de Samber", + "author_inst": "Signify" + }, + { + "author_name": "Vincent Munster", + "author_inst": "NIAID" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc0", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2022.01.11.475947", @@ -414090,61 +412757,129 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.10.22269010", - "rel_title": "Infectious viral load in unvaccinated and vaccinated patients infected with SARS-CoV-2 WT, Delta and Omicron", + "rel_doi": "10.1101/2022.01.10.22269008", + "rel_title": "Hydroxychloroquine/Chloroquine for the Treatment of Hospitalized Patients with COVID-19: An Individual Participant Data Meta-Analysis", "rel_date": "2022-01-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.10.22269010", - "rel_abs": "BackgroundViral load (VL) is one determinant of secondary transmission of SARS-CoV-2. Emergence of variants of concerns (VOC) Alpha and Delta was ascribed, at least partly, to higher VL. Furthermore, with parts of the population vaccinated, knowledge on VL in vaccine-breakthrough infections is crucial. As RNA VL is only a weak proxy for infectiousness, studies on infectious virus presence by cell culture isolation are of importance.\n\nMethodsWe assessed nasopharyngeal swabs of COVID-19 patients for quantitative infectious viral titres (IVT) by focus-forming assay and compared to overall virus isolation success and RNA genome copies. We assessed IVTs during the first 5 symptomatic days in a total of 384 patients: unvaccinated individuals infected with pre-VOC SARS-CoV-2 (n= 118) or Delta (n= 127) and vaccine breakthrough infections with Delta (n= 121) or Omicron (n=18).\n\nFindingsCorrelation between RNA copy number and IVT was low for all groups. No correlation between IVTs and age or sex was seen. We observed higher RNA genome copies in pre-VOC SARS-CoV-2 compared to Delta, but significantly higher IVTs in Delta infected individuals. Vaccinated Delta infected individuals had significantly lower RNA genome copies and IVTs compared to unvaccinated subjects and cleared virus faster. In addition, vaccinated individuals with Omicron infection had comparable IVTs to Delta breakthrough infections.\n\nInterpretationQuantitative IVTs can give detailed insights into virus shedding kinetics. Vaccination was associated with lower infectious titres and faster clearance for Delta, showing that vaccination would also lower transmission risk. Omicron vaccine-breakthrough infections did not show elevated IVTs compared to Delta, suggesting that other mechanisms than increase VL contribute to the high infectiousness of Omicron.\n\nFundingThis work was supported by the Swiss National Science Foundation 196644, 196383, NRP (National Research Program) 78 Covid-19 Grant 198412, the Fondation Ancrage Bienfaisance du Groupe Pictet and the Fondation Privee des Hopitaux Universitaires de Geneve.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.10.22269008", + "rel_abs": "BackgroundResults from observational studies and randomized clinical trials (RCTs) have led to the consensus that hydroxychloroquine (HCQ) and chloroquine (CQ) are not effective for COVID-19 prevention or treatment. Pooling individual participant data, including unanalyzed data from trials terminated early, enables more detailed investigation of the efficacy and safety of HCQ/CQ among subgroups of hospitalized patients.\n\nMethodsWe searched ClinicalTrials.gov in May and June 2020 for US-based RCTs evaluating HCQ/CQ in hospitalized COVID-19 patients in which the outcomes defined in this study were recorded or could be extrapolated. The primary outcome was a 7-point ordinal scale measured between day 28 and 35 post enrollment; comparisons used proportional odds ratios. Harmonized de-identified data were collected via a common template spreadsheet sent to each principal investigator. The data were analyzed by fitting a prespecified Bayesian ordinal regression model and standardizing the resulting predictions.\n\nResultsEight of 19 trials met eligibility criteria and agreed to participate. Patient-level data were available from 770 participants (412 HCQ/CQ vs 358 control). Baseline characteristics were similar between groups. We did not find evidence of a difference in COVID-19 ordinal scores between days 28 and 35 post-enrollment in the pooled patient population (odds ratio, 0.97; 95% credible interval, 0.76-1.24; higher favors HCQ/CQ), and found no convincing evidence of meaningful treatment effect heterogeneity among prespecified subgroups. Adverse event and serious adverse event rates were numerically higher with HCQ/CQ vs control (0.39 vs 0.29 and 0.13 vs 0.09 per patient, respectively).\n\nConclusionsThe findings of this individual participant data meta-analysis reinforce those of individual RCTs that HCQ/CQ is not efficacious for treatment of COVID-19 in hospitalized patients.", + "rel_num_authors": 28, "rel_authors": [ { - "author_name": "Olha Puhach", - "author_inst": "University of Geneva" + "author_name": "Leon Di Stefano", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" }, { - "author_name": "Kenneth Adea", - "author_inst": "University of Geneva" + "author_name": "Elizabeth L Ogburn", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" }, { - "author_name": "Nicolas Hulo", - "author_inst": "Universityof Geneva" + "author_name": "Malathi Ram", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" }, { - "author_name": "Pascale Sattonnet-Roche", - "author_inst": "University of Geneva" + "author_name": "Daniel O Scharfstein", + "author_inst": "University of Utah School of Medicine" }, { - "author_name": "Camille Genecand", - "author_inst": "Cantonal Health Service Geneva" + "author_name": "Tianjing Li", + "author_inst": "University of Colorado Denver" }, { - "author_name": "Anne Iten", - "author_inst": "University Hospital Geneva" + "author_name": "Preeti Khanal", + "author_inst": "Johns Hopkins University School of Medicine" }, { - "author_name": "Frederique Jacquerioz Bausch", - "author_inst": "University Hospital Geneva" + "author_name": "Sheriza N Baksh", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" }, { - "author_name": "Laurent Kaiser", - "author_inst": "University of Geneva Hospitals" + "author_name": "Nichol McBee", + "author_inst": "Johns Hopkins University School of Medicine" }, { - "author_name": "Pauline Vetter", - "author_inst": "Geneva University Hospitals" + "author_name": "Joshua Gruber", + "author_inst": "Johns Hopkins University School of Medicine" }, { - "author_name": "Isabella Eckerle", - "author_inst": "University Hospital of Geneva" + "author_name": "Marianne R Gildea", + "author_inst": "Johns Hopkins University School of Medicine" }, { - "author_name": "Benjamin Meyer", - "author_inst": "University of Geneva" + "author_name": "Megan R Clark", + "author_inst": "Johns Hopkins University School of Medicine" + }, + { + "author_name": "Neil A Goldenberg", + "author_inst": "Johns Hopkins University School of Medicine" + }, + { + "author_name": "Yussef Bennani", + "author_inst": "Louisiana State University Health Sciences Center" + }, + { + "author_name": "Samuel M Brown", + "author_inst": "Intermountain Medical Center/University of Utah" + }, + { + "author_name": "Whitney R Buckel", + "author_inst": "Intermountain Healthcare" + }, + { + "author_name": "Meredith E Clement", + "author_inst": "Louisiana State University Health Sciences Center" + }, + { + "author_name": "Mark J Mulligan", + "author_inst": "New York University Grossman School of Medicine" + }, + { + "author_name": "Jane A O'Halloran", + "author_inst": "Washington University in St. Louis School of Medicine" + }, + { + "author_name": "Adriana M Rauseo", + "author_inst": "Washington University in St. Louis School of Medicine" + }, + { + "author_name": "Wesley H Self", + "author_inst": "Vanderbilt University Medical Center" + }, + { + "author_name": "Matthew W Semler", + "author_inst": "Vanderbilt University Medical Center" + }, + { + "author_name": "Todd Seto", + "author_inst": "University of Hawaii John A. Burns School of Medicine" + }, + { + "author_name": "Jason E Stout", + "author_inst": "Duke University Medical Center" + }, + { + "author_name": "Robert J Ulrich", + "author_inst": "NYU Grossman School of Medicine" + }, + { + "author_name": "Jennifer Victory", + "author_inst": "Bassett Research Institute" + }, + { + "author_name": "Barbara E Bierer", + "author_inst": "Brigham and Women's Hospital" + }, + { + "author_name": "Daniel F Hanley", + "author_inst": "Johns Hopkins University School of Medicine" + }, + { + "author_name": "Daniel Freilich", + "author_inst": "Bassett Medical Center" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -415843,83 +414578,75 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2022.01.07.475330", - "rel_title": "RelCoVax(R), a two antigen subunit protein vaccine candidate against SARS-CoV-2 induces strong immune responses in mice", + "rel_doi": "10.1101/2022.01.10.475377", + "rel_title": "Molnupiravir combined with different repurposed drugs further inhibits SARS-CoV-2 infection in human nasal epithelium in vitro", "rel_date": "2022-01-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.07.475330", - "rel_abs": "The COVID-19 pandemic has spurred an unprecedented movement to develop safe and effective vaccines against the SARS-CoV-2 virus to immunize the global population. The first set of vaccine candidates that received emergency use authorization targeted the spike (S) glycoprotein of the SARS-CoV-2 virus that enables virus entry into cells via the receptor binding domain (RBD). Recently, multiple variants of SARS-CoV-2 have emerged with mutations in S protein and the ability to evade neutralizing antibodies in vaccinated individuals. We have developed a dual RBD and nucleocapsid (N) subunit protein vaccine candidate named RelCoVax(R) through heterologous expression in mammalian cells (RBD) and E. coli (N). The RelCoVax(R) formulation containing a combination of aluminum hydroxide (alum) and a synthetic CpG oligonucleotide as adjuvants elicited high antibody titers against RBD and N proteins in mice after a prime and boost dose regimen administered 2 weeks apart. The vaccine also stimulated cellular immune responses with a potential Th1 bias as evidenced by increased IFN-{gamma} release by splenocytes from immunized mice upon antigen exposure particularly N protein. Finally, the serum of mice immunized with RelCoVax(R) demonstrated the ability to neutralize two different SARS-CoV-2 viral strains in vitro including the Delta strain that has become dominant in many regions of the world and can evade vaccine induced neutralizing antibodies. These results warrant further evaluation of RelCoVax(R) through advanced studies and contribute towards enhancing our understanding of multicomponent subunit vaccine candidates against SARS-CoV-2.", - "rel_num_authors": 16, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.10.475377", + "rel_abs": "The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first identified in late 2019, has caused a worldwide pandemic with unprecedented economic and societal impact. Currently, several vaccines are available, and multitudes of antiviral treatments have been proposed and tested. Although many of the vaccines show high clinical efficacy, they are not equally accessible worldwide. Additionally, due to the continuous emergence of new virus variants, and generally short duration of immunity, the development of safe and effective antiviral treatments remains of the utmost importance. Since the emergence of SARS-CoV-2, substantial efforts have been undertaken to repurpose existing and approved drugs for accelerated clinical testing and potential emergency use authorizations. However, drug-repurposing using high throughput screenings in cellular assays, often identify hits that later prove ineffective in clinical studies. Our approach was to evaluate the activity of compounds that have either been tested clinically or already undergone extensive preclinical profiling, using a standardized in vitro model of human nasal epithelium. Secondly, we evaluated drug combinations using sub-maximal doses of each active single compound. Here, we report the antiviral effects of 95 single compounds and 30 combinations. The data show that selected drug combinations including 10 M of molnupiravir, a viral RNA-dependent RNA polymerase (RdRp) inhibitor, effectively inhibit SARS-CoV-2 replication. This indicates that such combinations are worthy of further evaluation as potential treatment strategies against coronavirus disease 2019 (COVID-19).", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Abhishek Phatarphekar", - "author_inst": "Reliance Life Sciences Pvt. Ltd." - }, - { - "author_name": "GEC Vidyadhar Reddy", - "author_inst": "Reliance Life Sciences Pvt. Ltd." - }, - { - "author_name": "Abhiram Gokhale", - "author_inst": "Reliance Life Sciences Pvt. Ltd." + "author_name": "Hulda R Jonsdottir", + "author_inst": "Spiez Laboratory" }, { - "author_name": "Gopala Karanam", - "author_inst": "Reliance Life Sciences Pvt. Ltd." + "author_name": "Denise Siegrist", + "author_inst": "Spiez Laboratory" }, { - "author_name": "Pushpa Kuchroo", - "author_inst": "Reliance Life Sciences Pvt. Ltd." + "author_name": "Thomas Julien", + "author_inst": "VirNext and Centre International de Recherche en Infectiologie" }, { - "author_name": "Ketaki Shinde", - "author_inst": "Reliance Life Sciences Pvt. Ltd." + "author_name": "Blandine Padey", + "author_inst": "Centre International de Recherche en Infectiologie" }, { - "author_name": "Girish Masand", - "author_inst": "Reliance Life Sciences Pvt. Ltd." + "author_name": "Mendy Bouveret", + "author_inst": "Epithelix SARL" }, { - "author_name": "Shyam Pagare", - "author_inst": "Reliance Life Sciences Pvt. Ltd." + "author_name": "Olivier Terrier", + "author_inst": "Centre International de Recherche en Infectiologie" }, { - "author_name": "Nilesh Khadpe", - "author_inst": "Reliance Life Sciences Pvt. Ltd." + "author_name": "Andres Pizzorno", + "author_inst": "Centre International de Recherche en Infectiologie" }, { - "author_name": "Sangita S Pai", - "author_inst": "Reliance Life Sciences Pvt. Ltd." + "author_name": "Song Huang", + "author_inst": "Epithelix SARL" }, { - "author_name": "Vijita Vijayan", - "author_inst": "Reliance Life Sciences Pvt. Ltd." + "author_name": "Kirandeep Samby", + "author_inst": "Medicines for Malaria Venture" }, { - "author_name": "Ramnath RL", - "author_inst": "Reliance Life Sciences Pvt. Ltd." + "author_name": "Timothy Wells", + "author_inst": "Medicines for Malaria Venture" }, { - "author_name": "K. Pratap Reddy", - "author_inst": "Reliance Life Sciences Pvt. Ltd." + "author_name": "Bernadett Boda", + "author_inst": "Epithelix SARL" }, { - "author_name": "Praveen Rao", - "author_inst": "Reliance Life Sciences Pvt. Ltd." + "author_name": "Manuel Rosa-Calatrava", + "author_inst": "VirNext and Centre International de Recherche en Infectiologie" }, { - "author_name": "S. Harinarayana Rao", - "author_inst": "Reliance Life Sciences Pvt. Ltd" + "author_name": "Olivier Engler", + "author_inst": "Spiez Laboratory" }, { - "author_name": "Venkata Ramana", - "author_inst": "Reliance Life Sciences Pvt. Ltd." + "author_name": "Samuel Constant", + "author_inst": "Epithelix SARL" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.01.07.475248", @@ -417909,95 +416636,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.01.06.475282", - "rel_title": "Mild SARS-CoV-2 infection in rhesus macaques is associated with viral control prior to antigen-specific T cell responses in tissues", + "rel_doi": "10.1101/2022.01.07.475295", + "rel_title": "Covariant Fitness Clusters Reveal Structural Evolution of SARS-CoV-2 Polymerase Across the Human Population", "rel_date": "2022-01-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.06.475282", - "rel_abs": "SARS-CoV-2 primarily replicates in mucosal sites, and more information is needed about immune responses in infected tissues. We used rhesus macaques to model protective primary immune responses in tissues during mild COVID-19. Viral RNA levels were highest on days 1-2 post-infection and fell precipitously thereafter. 18F-fluorodeoxyglucose (FDG)-avid lung abnormalities and interferon (IFN)-activated myeloid cells in the bronchoalveolar lavage (BAL) were found on days [~]3-4. Virus-specific effector CD8 and CD4 T cells were detectable in the BAL and lung tissue on days [~]7-10, after viral RNA, lung inflammation, and IFN-activated myeloid cells had declined. Notably, SARS-CoV-2-specific T cells were not detectable in the nasal turbinates, salivary glands, and tonsils on day 10 post-infection. Thus, SARS-CoV-2 replication wanes in the lungs prior to T cell responses, and in the nasal and oral mucosa despite the apparent lack of Ag-specific T cells, suggesting that innate immunity efficiently restricts viral replication during mild COVID-19.\n\nONE SENTENCE SUMMARYSARS-CoV-2 infection leads to mild, focal lung inflammation, and type I IFN activated myeloid cells that mostly resolve prior to the influx of virus-specific effector T cells or antibody responses in rhesus macaques.", - "rel_num_authors": 19, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.07.475295", + "rel_abs": "Understanding the fitness landscape of viral mutations is crucial for uncovering the evolutionary mechanisms contributing to pandemic behavior. Here, we apply a Gaussian process regression (GPR) based machine learning approach that generates spatial covariance (SCV) relationships to construct stability fitness landscapes for the RNA-dependent RNA polymerase (RdRp) of SARS- CoV-2. GPR generated fitness scores capture on a residue-by-residue basis a covariant fitness cluster centered at the C487-H642-C645-C646 Zn2+ binding motif that iteratively evolves since the early phase pandemic. In the Alpha and Delta variant of concern (VOC), multi-residue SCV interactions in the NiRAN domain form a second fitness cluster contributing to spread. Strikingly, a novel third fitness cluster harboring a Delta VOC basal mutation G671S augments RdRp structural plasticity to potentially promote rapid spread through viral load. GPR principled SCV provides a generalizable tool to mechanistically understand evolution of viral genomes at atomic resolution contributing to fitness at the pathogen-host interface.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Christine E. Nelson", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Sivaranjani Namasivayam", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Taylor W. Foreman", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Keith D. Kauffman", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Shunsuke Sakai", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Danielle E. Dorosky", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Nickiana E. Lora", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "- NIAID/DIR Tuberculosis Imaging Program", - "author_inst": "-" - }, - { - "author_name": "Kelsie Brooks", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "E. Lake Potter", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Mario Roederer", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Alan Sher", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Daniela Weiskopf", - "author_inst": "La Jolla Institute For Allergy & Immunology" - }, - { - "author_name": "Alessandro Sette", - "author_inst": "La Jolla Institute for Allergy & Immunology" - }, - { - "author_name": "Emmie de Wit", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Heather D. Hickman", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Jason M. Brenchley", - "author_inst": "National Institutes of Health" + "author_name": "Chao Wang", + "author_inst": "Department of Molecular Medicine, Scripps Research, La Jolla, California, 92037, USA." }, { - "author_name": "Laura E. Via", - "author_inst": "National Institutes of Health" + "author_name": "Nadia Elghobashi-Meinhardt", + "author_inst": "Department of Physical and Theoretical Chemistry, Technical University of Berlin, 10623 Berlin, Germany" }, { - "author_name": "Daniel L. Barber", - "author_inst": "National Institutes of Health" + "author_name": "William E Balch", + "author_inst": "Department of Molecular Medicine, Scripps Research, La Jolla, California, 92037, USA." } ], "version": "1", - "license": "cc0", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2022.01.06.475246", @@ -419734,23 +418397,95 @@ "category": "nephrology" }, { - "rel_doi": "10.1101/2022.01.03.22268709", - "rel_title": "Should rapid antigen tests be government funded in Australia? An economic evaluation", + "rel_doi": "10.1101/2022.01.03.22268684", + "rel_title": "Burden of SARS-CoV-2 and protection from symptomatic second infection in children", "rel_date": "2022-01-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.03.22268709", - "rel_abs": "ObjectiveEasy and equitable access to testing is a cornerstone of the public health response to COVID-19. Currently in Australia, testing using Polymerase Chain Reaction (PCR) tests for COVID-19 is free-to-the-user, but the public purchase their own Rapid Antigen Tests (RATs). We conduct an economic analysis of government-funded RATs in Australia.\n\nDesignAn interactive decision tree model was developed to compare one policy in which government-funded RATs are free-to-the-user, and one in which individuals purchase their own RATs. The decision tree represents RAT and PCR testing pathways for a cohort of individuals without COVID-19-like symptoms, to estimate the likelihood of COVID-19 positive individuals isolating prior to developing symptoms and the associated costs of testing, from a government perspective.\n\nData sourcesTest costs and detection rates were informed by published studies, other input parameter values are unobservable and uncertain, for which a range of scenario analyses are presented.\n\nData synthesisAssuming 10% prevalence of COVID-19 in a cohort of 10,000 individuals who would use government-funded RATs, the model estimates an additional 464 individuals would isolate early at a cost to the government of around $52,000. Scenario analyses indicate that the incremental cost per additional COVID-19 positive individual isolating with no symptoms remains at a few hundred dollars at 5% prevalence, rising to $2,052 at 1% prevalence.\n\nConclusionsBased on the presented decision tree model, even only minor reductions in COVID-19 transmission rates due to early isolation would justify the additional costs associated with a policy of government-funded RATs.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.03.22268684", + "rel_abs": "ImportanceThe impact of the SARS-CoV-2 pandemic on children remains unclear. Better understanding of the burden of COVID-19 among children and their protection against re-infection is crucial as they will be among the last groups vaccinated.\n\nObjectiveTo characterize the burden of COVID-19 and assess how protection from symptomatic re-infection among children may vary by age.\n\nDesignA prospective, community-based pediatric cohort study conducted from March 1, 2020 through October 15, 2021.\n\nSettingThe Nicaraguan Pediatric Influenza Cohort is a community-based cohort in District 2 of Managua, Nicaragua.\n\nParticipantsA total of 1964 children aged 0-14 years participated in the cohort. Non-immunocompromised children were enrolled by random selection from a previous pediatric influenza cohort. Additional newborn infants aged [≤]4 weeks were randomly selected and enrolled monthly, via home visits.\n\nExposuresPrior COVID-19 infection as confirmed by positive anti SARS-CoV-2 antibodies (receptor binding domain [RBD] and spike protein) or real time RT-PCR confirmed COVID-19 infection [≥]60 days prior to current COVID-19.\n\nMain Outcomes and MeasuresSymptomatic COVID-19 cases confirmed by real time RT-PCR and hospitalization within 28 days of symptom onset of confirmed COVID-19 case.\n\nResultsOverall, 49.8% of children tested were seropositive over the course of the study. There were also 207 PCR-confirmed COVID-19 cases, 12 (6.4%) of which were severe enough to require hospitalization. Incidence of COVID-19 was highest among children aged <2 years--16.1 per 100 person-years (95% Confidence Interval [CI]: 12.5, 20.5)--approximately three times that of children in any other age group assessed. Additionally, 41 (19.8%) symptomatic SARS-CoV-2 episodes were re-infections, with younger children slightly more protected against symptomatic reinfection. Among children aged 6-59 months, protection was 61% (Rate Ratio [RR]:0.39, 95% CI:0.2,0.8), while protection among children aged 5-9 and 10-14 years was 64% (RR:0.36,0.2,0.7), and 49% (RR:0.51,0.3-0.9), respectively.\n\nConclusions and RelevanceIn this prospective community-based pediatric cohort rates of symptomatic and severe COVID-19 were highest among the youngest participants, with rates stabilizing around age 5. Reinfections represent a large proportion of PCR-positive cases, with children <10 years displaying greater protection from symptomatic reinfection. A vaccine for children <5 years is urgently needed.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat is the burden of COVID-19 among young children and how does protection from re-infection vary with age?\n\nFindingsIn this study of 1964 children aged 0-14 years children <5 years had the highest rates of symptomatic and severe COVID-19 while also displaying greater protection against re-infection compared to children [≥]10 years.\n\nMeaningGiven their greater risk of infection and severe disease compared to older children, effective vaccines against COVID-19 are urgently needed for children under 5.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Jonathan Karnon", - "author_inst": "Flinders University" + "author_name": "John T Kubale", + "author_inst": "University of Michigan School of Public Health" + }, + { + "author_name": "Angel Balmaseda", + "author_inst": "Centro Nacional de Diagnostico y Referencia, Ministry of Health, Managua, Nicaragua" + }, + { + "author_name": "Aaron M Frutos", + "author_inst": "Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA." + }, + { + "author_name": "Nery Sanchez", + "author_inst": "Sustainable Sciences Institute, Managua, Nicaragua. Centro de Salud Socrates Flores Vivas, Ministry of Health, Managua, Nicaragua." + }, + { + "author_name": "Miguel Plazaola", + "author_inst": "Sustainable Sciences Institute, Managua, Nicaragua." + }, + { + "author_name": "Sergio Ojeda", + "author_inst": "Sustainable Sciences Institute, Managua, Nicaragua. Centro de Salud Socrates Flores Vivas, Ministry of Health, Managua, Nicaragua." + }, + { + "author_name": "Saira Saborio", + "author_inst": "Centro Nacional de Diagnostico y Referencia, Ministry of Health, Managua, Nicaragua. Sustainable Sciences Institute, Managua, Nicaragua." + }, + { + "author_name": "Roger Lopez", + "author_inst": "Centro Nacional de Diagnostico y Referencia, Ministry of Health, Managua, Nicaragua. Sustainable Sciences Institute, Managua, Nicaragua." + }, + { + "author_name": "Carlos Barilla", + "author_inst": "Centro Nacional de Diagnostico y Referencia, Ministry of Health, Managua, Nicaragua." + }, + { + "author_name": "Gerald Vasquez", + "author_inst": "Centro Nacional de Diagnostico y Referencia, Ministry of Health, Managua, Nicaragua." + }, + { + "author_name": "Hanny Moreira", + "author_inst": "Centro Nacional de Diagnostico y Referencia, Ministry of Health, Managua, Nicaragua." + }, + { + "author_name": "Anna Gajewski", + "author_inst": "Sustainable Sciences Institute, Managua, Nicaragua." + }, + { + "author_name": "Lora Campredon", + "author_inst": "Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA." + }, + { + "author_name": "Hannah Maier", + "author_inst": "Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA." + }, + { + "author_name": "Mahboob Chowdhury", + "author_inst": "Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA." + }, + { + "author_name": "Cristhiam Cerpas", + "author_inst": "Centro Nacional de Diagnostico y Referencia, Ministry of Health, Managua, Nicaragua. Sustainable Sciences Institute, Managua, Nicaragua." + }, + { + "author_name": "Eva Harris", + "author_inst": "Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, Berkeley, California, USA." + }, + { + "author_name": "Guillermina Kuan", + "author_inst": "Sustainable Sciences Institute, Managua, Nicaragua. Centro de Salud Socrates Flores Vivas, Ministry of Health, Managua, Nicaragua." + }, + { + "author_name": "Aubree Gordon", + "author_inst": "Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA." } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.01.03.22268704", @@ -421468,39 +420203,79 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.01.04.22268772", - "rel_title": "Development of the one-step qualitative RT-PCR assay to detect SARS-CoV-2 Omicron (B.1.1.529) variant in respiratory specimens", + "rel_doi": "10.1101/2022.01.05.21268251", + "rel_title": "Exploring the impact of shielding advice on the health and wellbeing of individuals identified as extremely vulnerable and advised to shield in Southwest England amid the COVID-19 pandemic: A mixed-methods evaluation", "rel_date": "2022-01-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.04.22268772", - "rel_abs": "A new SARS-CoV-2 Omicron (B.1.1.529) Variant of Concern has been emerging worldwide. We are seeing an unprecedented surge in patients due to Omicron in this COVID-19 pandemic. A rapid and accurate molecular test that effectively differentiates Omicron from other SARS-CoV-2 variants would be important for both epidemiologic value and for directing variant-specific therapies such as monoclonal antibody infusions. In this study, we developed a real-time RT-PCR assay for the qualitative detection of Omicron from routine clinical specimens sampling the upper respiratory tract. The limit of detection of the SARS-CoV-2 Omicron variant RT-PCR assay was 2 copies/l. Notably, the assay did not show any cross-reactivity with other SARS-CoV-2 variants including Delta (B.1.617.2). This SARS-CoV-2 Omicron variant RT-PCR laboratory-developed assay is sensitive and specific to detect Omicron in nasopharyngeal and nasal swab specimens.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.05.21268251", + "rel_abs": "ObjectiveExplore the impact and responses to public health advice on the health and wellbeing of individuals identified as clinically extremely vulnerable (CEV) and advised to shield (not leave home for 12 weeks at start of the pandemic) in Southwest England during the first COVID-19 lockdown.\n\nDesignMixed-methods study; structured survey and follow-up semi-structured interviews.\n\nSettingCommunities served by Bristol, North Somerset & South Gloucestershire Clinical Commissioning Group.\n\nParticipants204 people (57% female, 54% >69 years, 94% White British, 64% retired) in Southwest England identified as CEV and were advised to shield completed the survey. Thirteen survey respondents participated in follow-up interviews (53% female, 40% >69years, 100% White British, 61% retired).\n\nResultsReceipt of official communication from NHS England or General Practitioner (GP) was considered by participants as the legitimate start of shielding. 80% of survey responders felt they received all relevant advice needed to shield, yet interviewees criticised the timing of advice and often sought supplementary information. Shielding behaviours were nuanced, adapted to suit personal circumstances, and waned over time. Few interviewees received community support, although food boxes and informal social support were obtained by some. Worrying about COVID-19 was common for survey responders (90%). Since shielding had begun, physical and mental health reportedly worsened for 35% and 42% of survey responders respectively. 21% of survey responders scored [≥]10 on the PHQ-9 questionnaire indicating possible depression and 15% scored [≥]10 on the GAD-7 questionnaire indicating possible anxiety.\n\nConclusionsThis research highlights the difficulties in providing generic messaging that is applicable and appropriate given the diversity of individuals identified as CEV and the importance of sharing tailored and timely advice to inform shielding decisions. Providing messages that reinforce self-determined action and assistance from support services could reduce the negative impact of shielding on mental health and feelings of social isolation.\n\nO_TEXTBOXStrengths and limitations of this study\n\nO_LIThe mixed-methods study examines the experiences of clinically extremely vulnerable (CEV) people at the height of the COVID-19 crisis, immediately after the first lockdown in England.\nC_LIO_LIThe use of an existing list of individuals identified as needing to \"shield\" from Bristol, North Somerset & South Gloucestershire (BNSSG) Clinical Commissioning Group (CCG) allowed for access to key patient groups at the height of the crisis.\nC_LIO_LIFindings may not be applicable to wider CEV populations due to demographic bias.\nC_LI\n\nC_TEXTBOX", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Tung Phan", - "author_inst": "University of Pittsburgh Medical Center" + "author_name": "Gemma Lasseter", + "author_inst": "University of Bristol" }, { - "author_name": "Stephanie Boes", - "author_inst": "UPMC Hospital System" + "author_name": "Polly Compston", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Melissa McCullough", - "author_inst": "UPMC Hospital System" + "author_name": "Charlotte Robin", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Jamie Gribschaw", - "author_inst": "UPMC Hospital System" + "author_name": "Helen Lambert", + "author_inst": "University of Bristol" }, { - "author_name": "Alan Wells", - "author_inst": "University of Pittsburgh" + "author_name": "Matthew Hickman", + "author_inst": "University of Bristol" + }, + { + "author_name": "Sarah Denford", + "author_inst": "University of Bristol" + }, + { + "author_name": "Rosy Reynolds", + "author_inst": "University of Bristol" + }, + { + "author_name": "Juan Zhang", + "author_inst": "University of Bristol" + }, + { + "author_name": "Shenghan Cai", + "author_inst": "University of Bristol" + }, + { + "author_name": "Tingting Zhang", + "author_inst": "University of Bristol" + }, + { + "author_name": "Louise E. Smith", + "author_inst": "King's College London" + }, + { + "author_name": "James Rubin", + "author_inst": "King's College London" + }, + { + "author_name": "Lucy Yardley", + "author_inst": "University of Bristol" + }, + { + "author_name": "Richard Amlot", + "author_inst": "UK Health Security Agency" + }, + { + "author_name": "Isabel Oliver", + "author_inst": "UK Health Security Agency" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pathology" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.01.05.22268637", @@ -423438,175 +422213,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.01.03.22268599", - "rel_title": "Antibody response to SARS-CoV-2 mRNA vaccine in lung cancer patients: Reactivity to vaccine antigen and variants of concern.", + "rel_doi": "10.1101/2021.12.25.474149", + "rel_title": "Expanded ACE2 dependencies of diverse SARS-like coronavirus receptor binding domains", "rel_date": "2022-01-03", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.03.22268599", - "rel_abs": "PurposeWe investigated SARS-CoV-2 mRNA vaccine-induced binding and live-virus neutralizing antibody response in NSCLC patients to the SARS-CoV-2 wild type strain and the emerging Delta and Omicron variants.\n\nMethods82 NSCLC patients and 53 healthy adult volunteers who received SARS-CoV-2 mRNA vaccines were included in the study. Blood was collected longitudinally, and SARS-CoV-2-specific binding and live-virus neutralization response to 614D (WT), B.1.617.2 (Delta), B.1.351 (Beta) and B.1.1.529 (Omicron) variants were evaluated by Meso Scale Discovery (MSD) assay and Focus Reduction Neutralization Assay (FRNT) respectively. We determined the longevity and persistence of vaccine-induced antibody response in NSCLC patients. The effect of vaccine-type, age, gender, race and cancer therapy on the antibody response was evaluated.\n\nResultsBinding antibody titer to the mRNA vaccines were lower in the NSCLC patients compared to the healthy volunteers (P=<0.0001). More importantly, NSCLC patients had reduced live-virus neutralizing activity compared to the healthy vaccinees (P=<0.0001). Spike and RBD-specific binding IgG titers peaked after a week following the second vaccine dose and declined after six months (P=<0.001). While patients >70 years had lower IgG titers (P=<0.01), patients receiving either PD-1 monotherapy, chemotherapy or a combination of both did not have a significant impact on the antibody response. Binding antibody titers to the Delta and Beta variants were lower compared to the WT strain (P=<0.0001). Importantly, we observed significantly lower FRNT50 titers to Delta (6-fold), and Omicron (79-fold) variants (P=<0.0001) in NSCLC patients.\n\nConclusionsBinding and live-virus neutralizing antibody titers to SARS-CoV-2 mRNA vaccines in NSCLC patients were lower than the healthy vaccinees, with significantly lower live-virus neutralization of B.1.617.2 (Delta), and more importantly, the B.1.1.529 (Omicron) variant compared to the wild-type strain. These data highlight the concern for cancer patients given the rapid spread of SARS-CoV-2 Omicron variant.", - "rel_num_authors": 39, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.25.474149", + "rel_abs": "Viral spillover from animal reservoirs can trigger public health crises and cripple the world economy. Knowing which viruses are primed for zoonotic transmission can focus surveillance efforts and mitigation strategies for future pandemics. Successful engagement of receptor protein orthologs is necessary during cross-species transmission. The clade 1 sarbecoviruses including SARS-CoV and SARS-CoV-2 enter cells via engagement of ACE2, while the receptor for clade 2 and clade 3 remains largely uncharacterized. We developed a mixed cell pseudotyped virus infection assay to determine whether various clade 2 and 3 sarbecovirus spike proteins can enter HEK 293T cells expressing human or Rhinolophus horseshoe bat ACE2 proteins. The receptor binding domains from BtKY72 and Khosta-2 used human ACE2 for entry, while BtKY72 and Khosta-1 exhibited widespread use of diverse rhinolophid ACE2s. A lysine at ACE2 position 31 appeared to be a major determinant of the inability of these RBDs to use a certain ACE2 sequence. The ACE2 protein from R. alcyone engaged all known clade 3 and clade 1 receptor binding domains. We observed little use of Rhinolophus ACE2 orthologs by the clade 2 viruses, supporting the likely use of a separate, unknown receptor. Our results suggest that clade 3 sarbecoviruses from Africa and Europe use Rhinolophus ACE2 for entry, and their spike proteins appear primed to contribute to zoonosis under the right conditions.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Rajesh Valanparambil", - "author_inst": "Emory University" - }, - { - "author_name": "Jennifer Carlisle", - "author_inst": "Winship Cancer Institute" - }, - { - "author_name": "Susanne Linderman", - "author_inst": "Emory University" - }, - { - "author_name": "Akil Akthar", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Ralph Linwood Millett", - "author_inst": "Winship Cancer Institute" - }, - { - "author_name": "Lilin Lai", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Andres Chang", - "author_inst": "Winship Cancer Institute" - }, - { - "author_name": "Ashley McCook", - "author_inst": "Winship Cancer Institute" - }, - { - "author_name": "Jeffrey Switchenko", - "author_inst": "Winship Cancer Institute" - }, - { - "author_name": "Tahseen Nasti", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Manpreet Saini", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Andreas Wieland Andreas Wieland", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Kelly Manning", - "author_inst": "Emory Vaccine Center" - }, - { - "author_name": "Madison Ellis", - "author_inst": "Emory Vaccine Center" - }, - { - "author_name": "Kathryn Moore", - "author_inst": "Emory Vaccine Center" - }, - { - "author_name": "Stephanie Foster", - "author_inst": "Emory Vaccine Center" - }, - { - "author_name": "Katharine Floyd", - "author_inst": "Emory Vaccine Center" - }, - { - "author_name": "Meredith Davis-Gardner", - "author_inst": "Emory Vaccine Center" - }, - { - "author_name": "Venkata Viswanadh Edara", - "author_inst": "Emory Vaccine Center" - }, - { - "author_name": "Mit Patel", - "author_inst": "Emory Vaccine Center" - }, - { - "author_name": "Conor Steur", - "author_inst": "Winship Cancer Institute" - }, - { - "author_name": "Ajay Nooka", - "author_inst": "Winship Cancer Institute" - }, - { - "author_name": "Felicia Green", - "author_inst": "Winship Cancer Institute" - }, - { - "author_name": "Margaret Johns", - "author_inst": "Winship Cancer Institute" - }, - { - "author_name": "Fiona O Brein", - "author_inst": "Winship Cancer Institute" - }, - { - "author_name": "Uma Shanmugasundaram", - "author_inst": "Winship Cancer Institute" - }, - { - "author_name": "Veronika Zarnitsyna", - "author_inst": "Emory University School of" - }, - { - "author_name": "Hasan Ahmed", - "author_inst": "Emory University School of Biology" - }, - { - "author_name": "Lindsay Nyhoff", - "author_inst": "Department of Pediatrics Emory University" - }, - { - "author_name": "Grace Mantus", - "author_inst": "Department of Pediatrics Emory University" - }, - { - "author_name": "Michael Garett", - "author_inst": "Hope Clinic of Emory Vaccine Center" - }, - { - "author_name": "Srilatha Edupuganti", - "author_inst": "Hope Clinic of Emory Vaccine Center" - }, - { - "author_name": "Madhusmita Behra", - "author_inst": "Winship Cancer Institute" - }, - { - "author_name": "Rustom Antia", - "author_inst": "Emory University School of Biology" - }, - { - "author_name": "Jens Wrammert", - "author_inst": "Department of Pediatrics Emory University" + "author_name": "Sarah M Roelle", + "author_inst": "Case Western Reserve University School of Medicine" }, { - "author_name": "Mehul Suthar", - "author_inst": "Emory Vaccine Center" + "author_name": "Nidhi Shukla", + "author_inst": "Case Western Reserve University School of Medicine" }, { - "author_name": "Madhav Dhodapkar", - "author_inst": "Winship Cancer Institute" + "author_name": "Anh T Pham", + "author_inst": "Case Western Reserve University School of Medicine" }, { - "author_name": "Suresh Ramalingam", - "author_inst": "Winship Cancer Institute" + "author_name": "Anna M Bruchez", + "author_inst": "Case Western Reserve University School of Medicine" }, { - "author_name": "Rafi Ahmed", - "author_inst": "Emory University School of Medicine" + "author_name": "Kenneth A Matreyek", + "author_inst": "Case Western Reserve University School of Medicine" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "oncology" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2022.01.02.22268629", @@ -425356,75 +423995,99 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.12.29.21268516", - "rel_title": "A Web-based Spatial Decision Support System of Wastewater Surveillance for COVID-19 Monitoring: A Case Study of a University Campus", + "rel_doi": "10.1101/2021.12.30.21268560", + "rel_title": "Early signals of significantly increased vaccine breakthrough, decreased hospitalization rates, and less severe disease in patients with COVID-19 caused by the Omicron variant of SARS-CoV-2 in Houston, Texas", "rel_date": "2022-01-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.29.21268516", - "rel_abs": "The ongoing COVID-19 pandemic has produced substantial impacts on our society. Wastewater surveillance has increasingly been introduced to support the monitoring, and thus mitigation, of COVID-19 outbreaks and transmission. Monitoring of buildings and sub-sewershed areas via a wastewater surveillance approach has been a cost-effective strategy for mass testing of residents in congregate living situations such as universities. A series of spatial and spatiotemporal data are involved with wastewater surveillance, and these data must be interpreted and integrated with other information to better serve as guidance on response to a positive wastewater signal. The management and analysis of these data poses a significant challenge, in particular, for the need of supporting timely decision making. In this study, we present a web-based spatial decision support system framework to address this challenge. Our study area is the main campus of the University of North Carolina at Charlotte. We develop a spatiotemporal data model that facilitates the management of space-time data related to wastewater surveillance. We use spatiotemporal analysis and modeling to discover spatio-temporal patterns of COVID-19 virus abundance at wastewater collection sites that may not be readily apparent in wastewater data as they are routinely collected. Web-based GIS dashboards are implemented to support the automatic update and sharing of wastewater testing results. Our web-based SDSS framework enables the efficient and automated management, analytics, and sharing of spatiotemporal data of wastewater testing results for our study area. This framework provides substantial support for informing critical decisions or guidelines for the prevention of COVID-19 outbreak and the mitigation of virus transmission on campus.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.30.21268560", + "rel_abs": "Genetic variants of SARS-CoV-2 continue to dramatically alter the landscape of the COVID-19 pandemic. The recently described variant of concern designated Omicron (B.1.1.529) has rapidly spread worldwide and is now responsible for the majority of COVID-19 cases in many countries. Because Omicron was recognized very recently, many knowledge gaps exist about its epidemiology, clinical severity, and disease course. A genome sequencing study of SARS-CoV-2 in the Houston Methodist healthcare system identified 4,468 symptomatic patients with infections caused by Omicron from late November 2021 through January 5, 2022. Omicron very rapidly increased in only three weeks to cause 90% of all new COVID-19 cases, and at the end of the study period caused 98% of new cases. Compared to patients infected with either Alpha or Delta variants in our healthcare system, Omicron patients were significantly younger, had significantly increased vaccine breakthrough rates, and were significantly less likely to be hospitalized. Omicron patients required less intense respiratory support and had a shorter length of hospital stay, consistent with on average decreased disease severity. Two patients with Omicron \"stealth\" sublineage BA.2 also were identified. The data document the unusually rapid spread and increased occurrence of COVID-19 caused by the Omicron variant in metropolitan Houston, and address the lack of information about disease character among US patients.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Wenwu Tang", - "author_inst": "University of North Carolina at Charlotte" + "author_name": "Paul A Christensen", + "author_inst": "Houston Methodist Research Institute" }, { - "author_name": "Tianyang Chen", - "author_inst": "University of North Carolina at Charlotte" + "author_name": "Randall James Olsen", + "author_inst": "Houston Methodist Research Institute" }, { - "author_name": "Zachery Slocum", - "author_inst": "University of North Carolina at Charlotte" + "author_name": "Scott Wesley Long", + "author_inst": "Houston Methodist Research Institute" }, { - "author_name": "Yu Lan", - "author_inst": "University of North Carolina at Charlotte" + "author_name": "Richard Snehal", + "author_inst": "Houston Methodist Research Institute" }, { - "author_name": "Eric Delmelle", - "author_inst": "University of North Carolina at Charlotte and University of Eastern Finland" + "author_name": "James J Davis", + "author_inst": "Argonne National Laboratory" }, { - "author_name": "Don Chen", - "author_inst": "University of North Carolina at Charlotte" + "author_name": "Matthew Ojeda Saavedra", + "author_inst": "Houston Methodist Research Institute" }, { - "author_name": "Neha Mittal", - "author_inst": "University of North Carolina at Charlotte" + "author_name": "Kristina Reppond", + "author_inst": "Houston Methodist Research Institute" }, { - "author_name": "Jacelyn Rice-Boayue", - "author_inst": "University of North Carolina at Charlotte" + "author_name": "Madison N Shyer", + "author_inst": "Houston Methodist Research Institute" }, { - "author_name": "Tarini Shuka", - "author_inst": "University of North Carolina at Charlotte" + "author_name": "Jessica Cambric", + "author_inst": "Houston Methodist Research Institute" }, { - "author_name": "Sophia Lin", - "author_inst": "University of North Carolina at Charlotte" + "author_name": "Ryan Gadd", + "author_inst": "Houston Methodist Research Institute" }, { - "author_name": "Srinivas Akella", - "author_inst": "University of North Carolina at Charlotte" + "author_name": "Rashi M Thakur", + "author_inst": "Houston Methodist Research Institute" }, { - "author_name": "Jessica Schlueter", - "author_inst": "University of North Carolina at Charlotte" + "author_name": "Akanksha Batajoo", + "author_inst": "Houston Methodist Research Institute" }, { - "author_name": "Mariya Munir", - "author_inst": "University Of North Carolina Charlotte" + "author_name": "Regan Mangham", + "author_inst": "Houston Methodist Research Institute" }, { - "author_name": "Cynthia J Gibas", - "author_inst": "University of North Carolina at Charlotte" + "author_name": "Sindy Pena", + "author_inst": "Houston Methodist Research Institute" + }, + { + "author_name": "Trina Trinh", + "author_inst": "Houston Methodist Research Institute" + }, + { + "author_name": "Jacob C Kinskey", + "author_inst": "Houston Methodist Research Institute" + }, + { + "author_name": "Guy Williams", + "author_inst": "Houston Methodist Research Institute" + }, + { + "author_name": "Robert Olson", + "author_inst": "Argonne National Laboratory" + }, + { + "author_name": "Jimmy Gollihar", + "author_inst": "Houston Methodist Research Institute" + }, + { + "author_name": "James M Musser", + "author_inst": "Houston Methodist Research Institute" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pathology" }, { "rel_doi": "10.1101/2021.12.29.21268529", @@ -427542,71 +426205,179 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.24.474138", - "rel_title": "Homologous or Heterologous Booster of Inactivated Vaccine Reduces SARS-CoV-2 Omicron Variant Escape from Neutralizing Antibodies", + "rel_doi": "10.1101/2021.12.23.21268244", + "rel_title": "Effectiveness of casirivimab and imdevimab, and sotrovimab during Delta variant surge: a prospective cohort study and comparative effectiveness randomized trial", "rel_date": "2021-12-30", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.24.474138", - "rel_abs": "The massive and rapid transmission of SARS-CoV-2 has led to the emergence of several viral variants of concern (VOCs), with the most recent one, B.1.1.529 (Omicron), which accumulated a large number of spike mutations, raising the specter that this newly identified variant may escape from the currently available vaccines and therapeutic antibodies. Using VSV-based pseudovirus, we found that Omicron variant is markedly resistant to neutralization of sera form convalescents or individuals vaccinated by two doses of inactivated whole-virion vaccines (BBIBP-CorV). However, a homologous inactivated vaccine booster or a heterologous booster with protein subunit vaccine (ZF2001) significantly increased neutralization titers to both WT and Omicron variant. Moreover, at day 14 post the third dose, neutralizing antibody titer reduction for Omicron was less than that for convalescents or individuals who had only two doses of the vaccine, indicating that a homologous or heterologous booster can reduce the Omicron escape from neutralizing. In addition, we tested a panel of 17 SARS-CoV-2 monoclonal antibodies (mAbs). Omicron resists 7 of 8 authorized/approved mAbs, as well as most of the other mAbs targeting distinct epitopes on RBD and NTD. Taken together, our results suggest the urgency to push forward the booster vaccination to combat the emerging SARS-CoV-2 variants.", - "rel_num_authors": 13, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.23.21268244", + "rel_abs": "IMPORTANCEThe effectiveness of monoclonal antibodies (mAbs), casirivimab and imdevimab, and sotrovimab, for patients with mild to moderate COVID-19 from the Delta variant is unknown.\n\nOBJECTIVETo evaluate the effectiveness of mAbs for the Delta variant compared to no treatment, and the comparative effectiveness between mAbs.\n\nDESIGN, SETTING, AND PARTICIPANTSTwo parallel studies among patients who met Emergency Use Authorization criteria for mAbs from July 14, 2021 to September 29, 2021: i.) prospective observational cohort study comparing mAb treatment to no mAb treatment and, ii.) Bayesian adaptive randomized trial comparing the effectiveness of casirivimab-imdevimab versus sotrovimab. In the observational study, we compared eligible patients who received mAb at an outpatient infusion center at UPMC, to nontreated patients with a positive SARS-CoV-2 test. In the comparative effectiveness trial, we randomly allocated casirivimab-imdevimab or sotrovimab to patients presenting to infusion centers and emergency departments, per system therapeutic interchange policy.\n\nEXPOSUREIntravenous mAb per their EUA criteria.\n\nMAIN OUTCOMES AND MEASURESFor the observational study, risk ratio estimates for hospitalization or death by 28 days were compared between mAb treatment to no mAb treatment using propensity matched models. For the comparative effectiveness trial, the primary outcome was hospital-free days (days alive and free of hospital) within 28 days, where patients who died were assigned -1 day) in a Bayesian cumulative logistic model, adjusted for treatment location, age, sex, and time. Inferiority was defined as a 99% posterior probability of an odds ratio <1. Equivalence was defined as a 95% posterior probability that the odds ratio is within a given bound.\n\nRESULTSAmong 3,558 patients receiving mAb, the mean age was 54 (SD 18 years), 1,511 (43%) were treated in an infusion center, and 450 (13%) were hospitalized or died by day 28. In propensity matched models, mAb treatment was associated with reduced risk of hospitalization or death compared to no treatment (risk ratio (RR)=0.40, 95% CI: 0.28-0.57). Both casirivimab and imdevimab (RR=0.31, 95% CI: 0.20-0.50), and sotrovimab (RR=0.60, 95% CI: 0.37-1.00) reduced hospitalization or death compared to no mAb treatment. Among patients allocated randomly to casirivimab and imdevimab (n=2,454) or sotrovimab (n=1,104), the median hospital-free days were 28 (IQR 28-28) for both groups, 28-day mortality was 0.5% (n=12) and 0.6% (n=7), and hospitalization by day 28 was 12% (n=291) and 12% (n=140), respectively. Compared to casirivimab and imdevimab, the median adjusted odds ratio for hospital-free days was 0.88 (95% credible interval, 0.70-1.11) for sotrovimab. This odds ratio yielded 86% probability of inferiority of sotrovimab versus casirivimab and imdevimab, and 79% probability of equivalence.\n\nCONCLUSIONS AND RELEVANCEIn non-hospitalized patients with mild to moderate COVID-19 due to the Delta variant, casirivimab and imdevimab and sotrovimab were both associated with a reduced risk of hospitalization or death. The comparative effectiveness of mAbs appeared similar, though prespecified criteria for statistical inferiority or equivalence were not met.\n\nTRIAL REGISTRATIONClinicalTrials.gov: NCT04790786\n\nKey PointsO_ST_ABSQuestionC_ST_ABSIn non-hospitalized patients with mild to moderate COVID-19 due to the Delta variant, what is the effectiveness of monoclonal antibodies (mAb) compared to no treatment, and what is the comparative effectiveness between mAb?\n\nFindingsAmong 3,069 patients, mAb treatment (casirivimab and imdevimab or sotrovimab) was associated with reduced risk of hospitalization or death by 28 days compared to no treatment (risk ratio=0.40, 95% CI: 0.28-0.57). In a Bayesian randomized comparative effectiveness trial of casirivimab and imdevimab vs. sotrovimab in 3,558 patients, the median hospital-free days were 28 days for both groups. Compared to casirivimab-imdevimab, the median adjusted odds ratio for hospital-free days was 0.88 (95% credible interval, 0.70-1.11) for sotrovimab, an 86% probability of inferiority of sotrovimab versus casirivimab and imdevimab, and 79% probability of equivalence.\n\nMeaningIn non-hospitalized patients with mild to moderate COVID-19 due to the Delta variant, casirivimab and imdevimab and sotrovimab were associated with reduced risk of hospitalization or death compared to no treatment. The comparative effectiveness of mAbs appeared similar, though prespecified criteria for statistical inferiority or equivalence were not met.", + "rel_num_authors": 40, "rel_authors": [ { - "author_name": "Xun Wang", - "author_inst": "School of Life Sciences, Fudan University, Shanghai 200438, China" + "author_name": "David T. Huang", + "author_inst": "Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" }, { - "author_name": "Xiaoyu Zhao", - "author_inst": "School of Life Sciences, Fudan University, Shanghai 200438, China" + "author_name": "Erin K. McCreary", + "author_inst": "Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" }, { - "author_name": "Jieyu Song", - "author_inst": "Department of Infectious Diseases, Huashan Hospital affiliated with Fudan University, Shanghai 200040, China" + "author_name": "J. Ryan Bariola", + "author_inst": "Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" }, { - "author_name": "Jing Wu", - "author_inst": "Department of Infectious Diseases, Huashan Hospital, Fudan University" + "author_name": "Tami E. Minnier", + "author_inst": "Wolff Center, UPMC, Pittsburgh, PA, USA" }, { - "author_name": "Yuqi Zhu", - "author_inst": "School of Life Sciences, Fudan University, Shanghai 200438, China" + "author_name": "Richard J. Wadas", + "author_inst": "Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" }, { - "author_name": "Minghui Li", - "author_inst": "School of Life Sciences, Fudan University, Shanghai 200438, China" + "author_name": "Judith A. Shovel", + "author_inst": "Wolff Center, UPMC, Pittsburgh, PA, USA" }, { - "author_name": "Yuchen Cui", - "author_inst": "School of Life Sciences, Fudan University, Shanghai 200438, China" + "author_name": "Debbie Albin", + "author_inst": "Supply Chain Management/HC Pharmacy, UPMC, Pittsburgh, PA, USA" }, { - "author_name": "Yanjia Chen", - "author_inst": "School of Life Sciences, Fudan University, Shanghai 200438, China" + "author_name": "Oscar C. Marroquin", + "author_inst": "Clinical Analytics, UPMC, Pittsburgh, PA, USA" }, { - "author_name": "Lulu Yang", - "author_inst": "School of Life Sciences, Fudan University, Shanghai 200438, China" + "author_name": "Kevin E. Kip", + "author_inst": "Clinical Analytics, UPMC, Pittsburgh, PA, USA" }, { - "author_name": "Jun Liu", - "author_inst": "School of Life Sciences, Fudan University, Shanghai 200438, China" + "author_name": "Kevin Collins", + "author_inst": "Clinical Analytics, UPMC, Pittsburgh, PA, USA" }, { - "author_name": "Huanzhang Zhu", - "author_inst": "School of Life Sciences, Fudan University, Shanghai 200438, China" + "author_name": "Mark Schmidhofer", + "author_inst": "Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" }, { - "author_name": "Shibo Jiang", - "author_inst": "Fudan University" + "author_name": "Mary Kay Wisniewski", + "author_inst": "Wolff Center, UPMC, Pittsburgh, PA, USA" }, { - "author_name": "Pengfei Wang", - "author_inst": "Fudan University" + "author_name": "David A. Nace", + "author_inst": "Division of Geriatric Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" + }, + { + "author_name": "Colleen Sullivan", + "author_inst": "Clinical Research Investigation and Systems Modeling of Acute Illness (CRISMA) Center, Department of Critical Care Medicine, University of Pittsburgh School of " + }, + { + "author_name": "Meredith Axe", + "author_inst": "Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" + }, + { + "author_name": "Russell Meyers", + "author_inst": "Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" + }, + { + "author_name": "Alexandra Weissman", + "author_inst": "Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" + }, + { + "author_name": "William Garrard", + "author_inst": "Clinical Analytics, UPMC, Pittsburgh, PA, USA" + }, + { + "author_name": "Octavia M. Peck-Palmer", + "author_inst": "Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" + }, + { + "author_name": "Alan A. Wells", + "author_inst": "Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" + }, + { + "author_name": "Robert D. Bart", + "author_inst": "Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" + }, + { + "author_name": "Anne Yang", + "author_inst": "Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" + }, + { + "author_name": "Lindsay R. Berry", + "author_inst": "Berry Consultants, Austin, TX, USA" + }, + { + "author_name": "Scott Berry", + "author_inst": "Berry Consultants, Austin, TX, USA" + }, + { + "author_name": "Amy M. Crawford", + "author_inst": "Berry Consultants, Austin, TX, USA" + }, + { + "author_name": "Anna McGlothlin", + "author_inst": "Berry Consultants, Austin, TX, USA" + }, + { + "author_name": "Tina Khadem", + "author_inst": "Health System Office of Healthcare Innovation, UPMC, Pittsburgh, PA, USA" + }, + { + "author_name": "Kelsey Linstrum", + "author_inst": "Clinical Research Investigation and Systems Modeling of Acute Illness (CRISMA) Center, Department of Critical Care Medicine, University of Pittsburgh School of " + }, + { + "author_name": "Stephanie K. Montgomery", + "author_inst": "Clinical Research Investigation and Systems Modeling of Acute Illness (CRISMA) Center, Department of Critical Care Medicine, University of Pittsburgh School of " + }, + { + "author_name": "Daniel Ricketts", + "author_inst": "Clinical Research Investigation and Systems Modeling of Acute Illness (CRISMA) Center, Department of Critical Care Medicine, University of Pittsburgh School of " + }, + { + "author_name": "Jason N. Kennedy", + "author_inst": "Clinical Research Investigation and Systems Modeling of Acute Illness (CRISMA) Center, Department of Critical Care Medicine, University of Pittsburgh School of " + }, + { + "author_name": "Caroline J. Pidro", + "author_inst": "Clinical Research Investigation and Systems Modeling of Acute Illness (CRISMA) Center, Department of Critical Care Medicine, University of Pittsburgh School of " + }, + { + "author_name": "Rachel L. Zapf", + "author_inst": "Wolff Center, UPMC, Pittsburgh, PA, USA" + }, + { + "author_name": "Paula L. Kip", + "author_inst": "Wolff Center, UPMC, Pittsburgh, PA, USA" + }, + { + "author_name": "Ghady Haidar", + "author_inst": "Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" + }, + { + "author_name": "Graham M. Snyder", + "author_inst": "Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" + }, + { + "author_name": "Bryan J. McVerry", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" + }, + { + "author_name": "Donald M. Yealy", + "author_inst": "Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" + }, + { + "author_name": "Derek C. Angus", + "author_inst": "Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" + }, + { + "author_name": "Christopher W. Seymour", + "author_inst": "Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.24.474110", @@ -429524,35 +428295,99 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.29.474439", - "rel_title": "Capturing a crucial 'disorder-to-order transition' at the heart of the coronavirus molecular pathology - triggered by highly persistent, interchangeable salt-bridges", + "rel_doi": "10.1101/2021.12.28.21268477", + "rel_title": "Safety and immunogenicity of BNT162b2 mRNA COVID-19 vaccine in Japanese patients after allogeneic stem cell transplantation.", "rel_date": "2021-12-29", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.29.474439", - "rel_abs": "The COVID-19 origin debate has greatly been influenced by Genome comparison studies of late, revealing the seemingly sudden emergence of the Furin-Like Cleavage Site at the S1/S2 junction of the SARS-CoV-2 Spike (FLCSSpike) containing its 681PRRAR685 motif, absent in other related respiratory viruses. Being the rate-limiting (i.e., the slowest) step, the host Furin cleavage is instrumental in the abrupt increase in transmissibility in COVID-19, compared to earlier onsets of respiratory viral diseases. In such a context, the current paper entraps a disorder-to-order transition of the FLCSSpike (concomitant to an entropy arrest) upon binding to Furin. The interaction clearly seems to be optimized for a more efficient proteolytic cleavage in SARS-CoV-2. The study further shows the formation of dynamically interchangeable and persistent networks of salt-bridges at the Spike-Furin interface in SARS-CoV-2 involving the three arginines (R682, R683, R685) of the FLCSSpike with several anionic residues (E230, E236, D259, D264, D306) coming from Furin, strategically distributed around its catalytic triad. Multiplicity and structural degeneracy of plausible salt-bridge network archetypes seems the other key characteristic features of the Spike-Furin binding in SARS-CoV-2 allowing the system to breathe - a trademark of protein disorder transitions. Interestingly, with respect to the homologous interaction in SARS-CoV (2002/2003) taken as a baseline, the Spike-Furin binding events generally in the coronavirus lineage seems to have a preference for ionic bond formation, even with lesser number of cationic residues at their potentially polybasic FLCSSpike patches. The interaction energies are suggestive of a characteristic metastabilities attributed to Spike-Furin interactions generally to the coronavirus lineage - which appears to be favorable for proteolytic cleavages targeted at flexible protein loops. T he current findings not only offer novel mechanistic insights into the coronavirus molecular pathology and evolution but also add substantially to the existing theories of proteolytic cleavages.", - "rel_num_authors": 4, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.28.21268477", + "rel_abs": "Patients who have undergone hematopoietic stem cell transplantation (HSCT) for hematological disease experience high mortality when infected by coronavirus disease 2019 (COVID-19). However, the safety and efficacy of COVID-19 vaccine in HSCT patients remains to be investigated. We prospectively evaluated the safety and immunogenicity of BNT162b2 mRNA COVID-19 vaccine (Pfizer BioNTech) in 25 Japanese allogeneic HSCT patients in comparison with 19 healthy volunteers. While anti-S1 antibody titers in almost all healthy volunteers after the second dose were higher than the cut-off value reported previously, levels in HSCT patients after the second dose were diverse. Nineteen patients (76%) got seroconversion of anti-S1 IgG. Median optical density of antibody levels in HSCT patients with low IgG levels (< 600 mg/dL), steroid treatment, or low lymphocytes (< 1000 /L) was significantly lower than that in the other HSCT patients. There were no serious adverse events (> Grade 3), no new development or exacerbation of graft-versus-host disease after vaccination. We concluded BNT162b2 mRNA vaccine is safe and effective in Japanese allogeneic HSCT patients.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Sourav Roy", - "author_inst": "Dept of Microbiology and Immunology, Brody School of Medicine, East Carolina University, Greenville, NC, 27834, USA" + "author_name": "Marika Watanabe", + "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + }, + { + "author_name": "Kimikazu Yakushijin", + "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + }, + { + "author_name": "Yohei Funakoshi", + "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + }, + { + "author_name": "Goh Ohji", + "author_inst": "Division of Infectious Disease Therapeutics, Department of Microbiology and Infectious Diseases, Kobe University Graduate School of Medicine, Kobe, Japan" + }, + { + "author_name": "Hironori Sakai", + "author_inst": "R&D, Cellspect Co., Ltd., Morioka, Iwate, Japan" + }, + { + "author_name": "Wataru Hojo", + "author_inst": "R&D, Cellspect Co., Ltd., Morioka, Iwate, Japan" + }, + { + "author_name": "Miki Saeki", + "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" }, { - "author_name": "Prithwi Ghosh", - "author_inst": "Department of Botany, Narajole Raj College, Narajole, Paschim Medinipur, West Bengal, India" + "author_name": "Yuri Hirakawa", + "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + }, + { + "author_name": "Sakuya Matsumoto", + "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" }, { - "author_name": "Abhirup Bandyapadhyay", - "author_inst": "Theoretical Neurosciences Group, Institute De Neurosciences Des Systems, Aix-Marseille University, France" + "author_name": "Rina Sakai", + "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + }, + { + "author_name": "Shigeki Nagao", + "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + }, + { + "author_name": "Akihito Kitao", + "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + }, + { + "author_name": "Yoshiharu Miyata", + "author_inst": "BioResource Center, Kobe University Hospital, Kobe, Japan" + }, + { + "author_name": "Taiji Koyama", + "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + }, + { + "author_name": "Yasuyuki Saito", + "author_inst": "Division of Molecular and Cellular Signaling, Kobe University Graduate School of Medicine, Kobe, Japan" + }, + { + "author_name": "Shinichiro Kawamoto", + "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + }, + { + "author_name": "Mitsuhiro Ito", + "author_inst": "Laboratory of Hematology, Division of Medical Biophysics, Kobe University Graduate School of Health Sciences, Kobe, Japan" + }, + { + "author_name": "Tohru Murayama", + "author_inst": "Hematology Division, Hyogo Cancer Center, Akashi, Japan" + }, + { + "author_name": "Hiroshi Matsuoka", + "author_inst": "BioResource Center, Kobe University Hospital, Kobe, Japan" }, { - "author_name": "Sankar Basu", - "author_inst": "Department of Microbiology, Asutosh College (affiliated to University of Calcutta), 92, Shyama Prasad Mukherjee Rd, Bhowanipore, Kolkata, West Bengal 700026, In" + "author_name": "Hironobu Minami", + "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" } ], "version": "1", "license": "cc_no", - "type": "new results", - "category": "biophysics" + "type": "PUBLISHAHEADOFPRINT", + "category": "hematology" }, { "rel_doi": "10.1101/2021.12.27.21268459", @@ -431626,117 +430461,57 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.12.27.474307", - "rel_title": "Structural basis for potent antibody neutralization of SARS-CoV-2 variants including B.1.1.529", + "rel_doi": "10.1101/2021.12.27.474250", + "rel_title": "Structural analysis of the Spike of the Omicron SARS-COV-2 variant by Cryo-EM and implications for immune evasion", "rel_date": "2021-12-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.27.474307", - "rel_abs": "With B.1.1.529 SARS-CoV-2 variants rapid spread and substantially increased resistance to neutralization by vaccinee and convalescent sera, monoclonal antibodies with potent neutralization are eagerly sought. To provide insight into effective neutralization, we determined cryo-EM structures and evaluated potent receptor-binding domain (RBD) antibodies for their ability to bind and neutralize this new variant. B.1.1.529 RBD mutations altered 16% of the RBD surface, clustering on a ridge of this domain proximal to the ACE2-binding surface and reducing binding of most antibodies. Significant inhibitory activity was retained, however, by select monoclonal antibodies including A19-58.1, B1-182.1, COV2-2196, S2E12, A19-46.1, S309 and LY-CoV1404, which accommodated these changes and neutralized B.1.1.529 with IC50s between 5.1-281 ng/ml, and we identified combinations of antibodies with potent synergistic neutralization. Structure-function analyses delineated the impact of resistance mutations and revealed structural mechanisms for maintenance of potent neutralization against emerging variants.\n\nSummary SentenceWe show potent B.1.1.529 neutralization by select antibodies and use EM structures to reveal how potency can be retained.", - "rel_num_authors": 25, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.27.474250", + "rel_abs": "Investigation of potential hosts of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is crucial to understanding future risks of spillover and spillback. SARS-CoV-2 has been reported to be transmitted from humans to various animals after requiring relatively few mutations.[1] There is significant interest in describing how the virus interacts with mice as they are well adapted to human environments, are used widely as infection models and can be infected.[2] Structural and binding data of the mouse ACE2 receptor with the Spike protein of newly identified SARS-CoV-2 variants are needed to better understand the impact of immune system evading mutations present in variants of concern (VOC). Previous studies have developed mouse-adapted variants and identified residues critical for binding to heterologous ACE2 receptors.[3,4] Here we report the cryo-EM structures of mouse ACE2 bound to trimeric Spike ectodomains of four different VOC: Beta, Omicron BA.1, Omicron BA.2.12.1 and Omicron BA.4/5. These variants represent the oldest to the newest variants known to bind the mouse ACE2 receptor. Our high-resolution structural data complemented with bio-layer interferometry (BLI) binding assays reveal a requirement for a combination of mutations in the Spike protein that enable binding to the mouse ACE2 receptor.\n\nAUTHOR SUMMARYThe SARS-CoV-2 virus can infect different types of animals beyond humans. The virus uses its Spike protein on its surface to bind to cells. These cells have a protein called ACE2 that the Spike protein recognizes. Animals have slightly different ACE2 receptors compared to humans. Mice are widely used as a research animal and live in the same environments as humans so scientists are particularly interested. Understanding how Spike proteins binds to the mouse ACE2 receptor allows us to understand the impact of immune evading mutations found in new variants. We use a high resolution imaging technique called cryo-electron microscopy to look at how different Spike variants bind to the ACE2 receptor from mouse at a resolution where we can see the amino acids. We can see directly the individual amino acids and mutations on the Spike protein that interact with the mouse ACE2 receptor. Many of the mutations found in variants of concern also increase the strength of binding to the mouse ACE2 receptor. This result suggests that mutations in the Spike protein of future variants may have an additional effect in influencing how it binds to not only human ACE2 receptors but to mice and also different animals.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Tongqing Zhou", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" - }, - { - "author_name": "Lingshu Wang", - "author_inst": "VRC/NIAID/NIH" - }, - { - "author_name": "John Misasi", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Amarendra Pegu", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" - }, - { - "author_name": "Yi Zhang", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" - }, - { - "author_name": "Darcy R. Harris", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" - }, - { - "author_name": "Adam S. Olia", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" - }, - { - "author_name": "Chloe Adrienna Talana", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" - }, - { - "author_name": "Eun Sung Yang", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" - }, - { - "author_name": "Man Chen", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" - }, - { - "author_name": "Misook Choe", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" - }, - { - "author_name": "Wei Shi", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" - }, - { - "author_name": "I-Ting Teng", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" - }, - { - "author_name": "Adrian Creanga", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" - }, - { - "author_name": "Claudia Jenkins", - "author_inst": "Frederick National Laboratory for Cancer Research" - }, - { - "author_name": "Kwanyee Leung", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" + "author_name": "Dongchun Ni", + "author_inst": "EPFL-SB-IPHYS-LBEM" }, { - "author_name": "Tracy Liu", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" + "author_name": "Kelvin Lau", + "author_inst": "EPFL-SV-PTECH-PTPSP" }, { - "author_name": "Erik-Stephane D. Stancofski", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" + "author_name": "Priscilla Turelli", + "author_inst": "EPFL-SV-GHI-LVG" }, { - "author_name": "Tyler Stephens", - "author_inst": "Frederick National Laboratory for Cancer Research" + "author_name": "Charlene Raclot", + "author_inst": "EPFL-SV-GHI-LVG" }, { - "author_name": "Baoshan Zhang", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" + "author_name": "Bertrand Beckert", + "author_inst": "DCI (EPFL-UNIL-UNIGE)" }, { - "author_name": "Yaroslav Tsybovsky", - "author_inst": "Frederick National Laboratory for Cancer Research" + "author_name": "Sergey Nazarov", + "author_inst": "DCI (EPFL-UNIL-UNIGE)" }, { - "author_name": "Barney Graham", - "author_inst": "VRC/NIAID/NIH" + "author_name": "Florence Pojer", + "author_inst": "EPFL-SV-PTECH-PTPSP" }, { - "author_name": "John R. Mascola", - "author_inst": "Vaccine Research Center, NIAID, NIH" + "author_name": "Alexander Myasnikov", + "author_inst": "DCI (EPFL-UNIL-UNIGE)" }, { - "author_name": "Nancy Sullivan", - "author_inst": "VRC, NIH" + "author_name": "Henning Stahlberg", + "author_inst": "EPFL-SB-IPHYS-LBEM" }, { - "author_name": "Peter D. Kwong", - "author_inst": "National Institute of Allergy and Infectious Diseases" + "author_name": "Didier Trono", + "author_inst": "EPFL-SV-GHI-LVG" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "new results", "category": "immunology" }, @@ -433844,99 +432619,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.21.21268058", - "rel_title": "Effectiveness of CoronaVac, ChAdOx1, BNT162b2 and Ad26.COV2.S among individuals with prior SARS-CoV-2 infection in Brazil", + "rel_doi": "10.1101/2021.12.25.474155", + "rel_title": "The SARS-CoV-2 nucleocapsid protein preferentially binds long and structured RNAs", "rel_date": "2021-12-27", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.21.21268058", - "rel_abs": "BackgroundCOVID-19 vaccines have proven highly effective among SARS-CoV-2 naive individuals, but their effectiveness in preventing symptomatic infection and severe outcomes among individuals with prior infection is less clear.\n\nMethodsUtilizing national COVID-19 notification, hospitalization, and vaccination datasets from Brazil, we performed a case-control study using a test-negative design to assess the effectiveness of four vaccines (CoronaVac, ChAdOx1, Ad26.COV2.S and BNT162b2) among individuals with laboratory-confirmed prior SARS-CoV-2 infection. We matched RT-PCR positive, symptomatic COVID-19 cases with RT-PCR-negative controls presenting with symptomatic illnesses, restricting both groups to tests performed at least 90 days after an initial infection. We used multivariable conditional logistic regression to compare the odds of test positivity, and the odds of hospitalization or death due to COVID-19, according to vaccination status and time since first or second dose of vaccines.\n\nFindingsAmong individuals with prior SARS-CoV-2 infection, vaccine effectiveness against symptomatic infection [≥] 14 days from vaccine series completion was 39.4% (95% CI 36.1-42.6) for CoronaVac, 56.0% (95% CI 51.4-60.2) for ChAdOx1, 44.0% (95% CI 31.5-54.2) for Ad26.COV2.S, and 64.8% (95% CI 54.9-72.4) for BNT162b2. For the two-dose vaccine series (CoronaVac, ChAdOx1, and BNT162b2), effectiveness against symptomatic infection was significantly greater after the second dose compared with the first dose. Effectiveness against hospitalization or death [≥] 14 days from vaccine series completion was 81.3% (95% CI 75.3-85.8) for CoronaVac, 89.9% (95% CI 83.5-93.8) for ChAdOx1, 57.7% (95% CI -2.6-82.5) for Ad26.COV2.S, and 89.7% (95% CI 54.3-97.7) for BNT162b2.\n\nInterpretationAll four vaccines conferred additional protection against symptomatic infections and severe outcomes among individuals with previous SARS-CoV-2 infection. Provision of a full vaccine series to individuals following recovery from COVID-19 may reduce morbidity and mortality.\n\nFundingBrazilian National Research Council, Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro, Oswaldo Cruz Foundation, JBS S.A., Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, Generalitat de Catalunya.\n\nRESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed, medRxiv, and SSRN for articles published from January 1, 2020 until December 15, 2021, with no language restrictions, using the search terms \"vaccine effectiveness\" AND \"previous*\" AND (\"SARS-CoV-2\" OR \"COVID-19\"). We found several studies evaluating ChAdOx1 and BNT162b2, and one additionally reporting on mRNA-1273 and Ad26.COV2.S, which found that previously infected individuals who were vaccinated had lower risk of symptomatic SARS-CoV-2 infection. One study found that risk of hospitalization was lower for previously infected individuals after a full series of BNT162b2 or mRNA-1273. Limited evidence is available comparing effectiveness of one versus two doses among individuals with prior infection. No studies reported effectiveness of inactivated vaccines among previously infected individuals.\n\nAdded value of this studyWe used national databases of COVID-19 case surveillance, laboratory testing, and vaccination from Brazil to investigate effectiveness of CoronaVac, ChAdOx1, Ad26.COV2.S and BNT162b2 among individuals with a prior, laboratory-confirmed SARS-CoV-2 infection. We matched >22,000 RT-PCR-confirmed re-infections with >145,000 RT-PCR-negative controls using a test-negative design. All four vaccines were effective against symptomatic SARS-CoV-2 infections, with effectiveness from 14 days after series completion ranging from 39-65%. For vaccines with two-dose regimens, the second dose provided significantly increased effectiveness compared with one dose. Effectiveness against COVID-19-associated hospitalization or death from 14 days after series completion was >80% for CoronaVac, ChAdOx1and BNT162b2.\n\nImplications of all the available evidenceWe find evidence that four vaccines, using three different platforms, all provide protection to previously infected individuals against symptomatic SARS-CoV-2 infection and severe outcomes, with a second dose conferring significant additional benefits. These results support the provision of a full vaccine series among individuals with prior SARS-CoV-2 infection.", - "rel_num_authors": 20, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.25.474155", + "rel_abs": "The SARS-CoV-2 nucleocapsid protein (NCAP) functions in viral RNA genome packaging, virion assembly, RNA synthesis and translation, and regulation of host immune response. RNA-binding is central to these processes. Little is known how NCAP selects its binding partners in the myriad of host and viral RNAs. To address this fundamental question, we employed electrophoresis mobility shift and competition assays to compare NCAP binding to RNAs that are of SARS-CoV-2 vs. non-SARS-CoV-2, long vs. short, and structured vs. unstructured. We found that although NCAP can bind all RNAs tested, it primarily binds structured RNAs, and their association suppresses strong interaction with single-stranded RNAs. NCAP prefers long RNAs, especially those containing multiple structures separated by single-stranded linkers that presumably offer conformational flexibility. Additionally, all three major regions of NCAP bind RNA, including the low complexity domain and dimerization domain that promote formation of NCAP oligomers, amyloid fibrils and liquid-liquid phase separation. Combining these observations, we propose that NCAP-NCAP interactions that mediate higher-order structures during packaging also drive recognition of the genomic RNA and call this mechanism recognition-by-packaging. This study provides a biochemical basis for understanding the complex NCAP-RNA interactions in the viral life cycle and a broad range of similar biological processes.\n\nHIGHLIGHTSO_LINCAP primarily binds structured RNAs.\nC_LIO_LINCAP prefers multiple RNA structures separated by single-stranded linkers.\nC_LIO_LINCAP favors binding to long RNAs.\nC_LI", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Thiago Cerqueira-Silva", - "author_inst": "Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil" - }, - { - "author_name": "Jason R Andrews", - "author_inst": "Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA,USA" - }, - { - "author_name": "Viviane S Boaventura", - "author_inst": "Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Universidade Federal da Bahia, Salvador, BA, Brazil" - }, - { - "author_name": "Otavio T Ranzani", - "author_inst": "Barcelona Institute for Global Health, ISGlobal, Spain / Pulmonary Division, University of Sao Paulo" - }, - { - "author_name": "Vinicius de Araujo Oliveira", - "author_inst": "Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Healt" - }, - { - "author_name": "Enny S Paixao", - "author_inst": "London School of Hygiene and Tropical Medicine, London, United Kingdom" - }, - { - "author_name": "Juracy Bertoldo Jr.", - "author_inst": "Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Health - Fiocruz, Salvador, BA, Brazil" - }, - { - "author_name": "Tales Mota Machado", - "author_inst": "Universidade Federal de Ouro Preto, Ouro Preto, MG, Brazil" - }, - { - "author_name": "Matt D T Hitchings", - "author_inst": "Department of Biostatistics, College of Public Health & Health Professions, University of Florida, Gainesville, FL, USA" - }, - { - "author_name": "Murilo Dorion", - "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Heaven, CT, USA" + "author_name": "Christen E Tai", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Margaret L Lind", - "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Heaven, CT, USA" + "author_name": "Einav Tayeb-Fligelman", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Gerson O. Penna", - "author_inst": "Nucleo de Medicina Tropical, Universidade de Brasilia, Brasilia, DF, Brazil; Escola Fiocruz de Governo, Fiocruz Brasilia. Brasilia, DF, Brazil" + "author_name": "Sarah Griner", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Derek A.T. Cummings", - "author_inst": "Department of Biology, University of Florida, Gainesville, FL, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA" + "author_name": "Lukasz Salwinski", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Natalie E Dean", - "author_inst": "Department of Biostatistics & Bioinformatics, Rollins School of Public Health, Emory University" + "author_name": "Jeannette T Bowler", + "author_inst": "University of California, Log Angeles" }, { - "author_name": "Guilherme Loureiro Werneck", - "author_inst": "Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil" + "author_name": "Romany Abskharon", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Neil Pearce", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Xinyi Cheng", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Mauricio L Barreto", - "author_inst": "Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Health - Fiocruz, Salvador, BA, Brazil" + "author_name": "Paul M Seidler", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Albert I Ko", - "author_inst": "Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Heaven, CT, USA" + "author_name": "Yi Xiao Jiang", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Julio Croda", - "author_inst": "Universidade Federal de Mato Grosso do Sul, Campo Grande, MS, Brazil; Fiocruz Mato Grosso do Sul, Fundacao Oswaldo Cruz, Campo Grande, MS, Brazil" + "author_name": "David S Eisenberg", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Manoel Barral-Netto", - "author_inst": "Instituto Goncalo Moniz, Fiocruz, Salvador, BA, Brazil; Universidade Federal da Bahia, Salvador, BA, Brazil; Center for Data and Knowledge Integration for Healt" + "author_name": "Feng Guo", + "author_inst": "University of California, Los Angeles" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "biochemistry" }, { "rel_doi": "10.1101/2021.12.26.473325", @@ -436210,63 +434949,87 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.12.24.474086", - "rel_title": "The omicron (B.1.1.529) SARS-CoV-2 variant of concern does not readily infect Syrian hamsters", - "rel_date": "2021-12-26", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.24.474086", - "rel_abs": "The emergence of SARS-CoV-2 variants of concern (VoCs) has exacerbated the COVID-19 pandemic. End of November 2021, a new SARS-CoV-2 variant namely the omicron (B.1.1.529) emerged. Since this omicron variant is heavily mutated in the spike protein, WHO classified this variant as the 5th variant of concern (VoC). We previously demonstrated that the other SARS-CoV-2 VoCs replicate efficiently in Syrian hamsters, alike also the ancestral strains. We here wanted to explore the infectivity of the omicron variant in comparison to the ancestral D614G strain. Strikingly, in hamsters that had been infected with the omicron variant, a 3 log10 lower viral RNA load was detected in the lungs as compared to animals infected with D614G and no infectious virus was detectable in this organ. Moreover, histopathological examination of the lungs from omicron-infecetd hamsters revealed no signs of peri-bronchial inflammation or bronchopneumonia. Further experiments are needed to determine whether the omicron VoC replicates possibly more efficiently in the upper respiratory tract of hamsters than in their lungs.", - "rel_num_authors": 11, + "rel_doi": "10.1101/2021.12.23.21267853", + "rel_title": "Effectiveness of BNT162b2 and mRNA-1273 Second Doses and Boosters for SARS-CoV-2 infection and SARS-CoV-2 Related Hospitalizations: A Statewide Report from the Minnesota Electronic Health Record Consortium", + "rel_date": "2021-12-25", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.23.21267853", + "rel_abs": "Using vaccine data combined with electronic health records, we report that mRNA boosters provide greater protection than a two-dose regimen against SARS-CoV-2 infection and related hospitalizations. The benefit of a booster was more evident in the elderly and those with comorbidities. These results support the case for COVID-19 boosters.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Rana Abdelnabi", - "author_inst": "Rega Institute, KU Leuven" + "author_name": "Paul E Drawz", + "author_inst": "Division of Nephrology and Hypertension, University of Minnesota Medical School, Minneapolis, MN" }, { - "author_name": "Caroline Shi-Yan Foo", - "author_inst": "Katholieke Universiteit Leuven" + "author_name": "Malini DeSilva", + "author_inst": "HealthPartners Institute, Minneapolis, MN" }, { - "author_name": "Xin Zhang", - "author_inst": "Rega Institute, KU Leuven" + "author_name": "Peter Bodurtha", + "author_inst": "Health, Homelessness, and Criminal Justice Lab, Hennepin Healthcare Research Institute, Minneapolis, MN" }, { - "author_name": "Viktor Lemmens", - "author_inst": "Rega Institute, KU Leuven" + "author_name": "Gabriela Vazquez Benitez", + "author_inst": "HealthPartners Institute, Minneapolis, MN" }, { - "author_name": "Piet Maes", - "author_inst": "KU Leuven, Rega Institute for Medical Research" + "author_name": "Anne Murray", + "author_inst": "Berman Center for Clinical Research, Hennepin Healthcare Research Institute" }, { - "author_name": "Bram Slechten", - "author_inst": "Department of Laboratory Medicine, UZ Leuven Hospital, 3000 Leuven, Belgium" + "author_name": "Alanna M Chamberlain", + "author_inst": "Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN" }, { - "author_name": "Joren Raymenants", - "author_inst": "Rega Institute, KU Leuven" + "author_name": "R Adams Dudley", + "author_inst": "Center for Care Delivery and Outcomes Research, Minneapolis Veterans Affairs Medical Center, Minneapolis, MN" }, { - "author_name": "Emmanuel Andre", - "author_inst": "Rega Institute, KU Leuven" + "author_name": "Stephen Waring", + "author_inst": "Essentia Institute of Rural Health, Duluth, MN" }, { - "author_name": "Birgit Weynand", - "author_inst": "UZ leuven" + "author_name": "Anupam B Kharbanda", + "author_inst": "Department of Pediatric Emergency Medicine, Childrens Minnesota, Minneapolis, MN" }, { - "author_name": "Kai Dallmeier", - "author_inst": "KU Leuven Rega Institute" + "author_name": "Daniel Murphy", + "author_inst": "Division of Nephrology and Hypertension, University of Minnesota Medical School, Minneapolis, MN" }, { - "author_name": "Johan Neyts", - "author_inst": "Rega Institute" + "author_name": "Miriam Halstead Muscoplat", + "author_inst": "Division of Infectious Disease, Epidemiology and Infection Control, Minnesota Department of Health, Saint Paul, MN" + }, + { + "author_name": "Victor Melendez", + "author_inst": "Allina Health, Minneapolis, MN" + }, + { + "author_name": "Karen L Margolis", + "author_inst": "HealthPartners Institute, Minneapolis, MN" + }, + { + "author_name": "Lynn McFarling", + "author_inst": "CentraCare, St. Cloud, MN" + }, + { + "author_name": "Roxana Lupu", + "author_inst": "Sanford Health, Sioux Falls, SD" + }, + { + "author_name": "Tyler N A Winkelman", + "author_inst": "Health, Homelessness, and Criminal Justice Lab, Hennepin Healthcare Research Institute, Minneapolis, MN" + }, + { + "author_name": "Steve Johnson", + "author_inst": "Institute for Health Informatics, University of Minnesota, Minneapolis, MN" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.23.21267374", @@ -437976,85 +436739,53 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.12.24.21268360", - "rel_title": "Serum anti-Spike antibody titers before and after heterologous booster with mRNA-1273 SARS-CoV-2 vaccine following two doses of inactivated whole-virus CoronaVac vaccine", + "rel_doi": "10.1101/2021.12.22.21268246", + "rel_title": "Saliva swabs are the preferred sample for Omicron detection", "rel_date": "2021-12-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.24.21268360", - "rel_abs": "BackgroundThe inactivated whole-virus vaccine CoronaVac (SinoVac) is the COVID-19 vaccine most administered worldwide. However, data on its immunogenicity and reactogenicity to heterologous boosting with mRNA vaccines are lacking.\n\nMethodsIn a cohort of hospital staff in Jakarta, Indonesia, who received two-dose CoronaVac six months prior (median 190 days, IQR165-232), we measured anti-Spike IgG titers on paired serum samples taken before and 28 days after a 100g mRNA-1273 (Moderna) booster. We performed correlations and multivariable ordinal regressions.\n\nFindingsAmong 304 participants, the median age was 31 years (range 21-59), 235 (77.3%) were women, 197 (64.8%) had one or more previous SARS-CoV-2 infections (including 155 [51.0%] who had a post-CoronaVac breakthrough infection. Pre-boost IgG titers correlated negatively with the time since the latest documented \"virus exposure\" (either by the second CoronaVac or SARS-CoV-2-infection whichever most recent). Previous SARS-CoV-2 infection and a longer time interval between second vaccine and mRNA-1273 boost were associated with a higher pre-boost IgG titer. Post-booster, the median IgG titer increased 9.3-fold, from 250 (IQR32-1389) to 2313 (IQR1226-4324) binding antibody units (BAU/mL) (p<0.001). All participants, including seven whose pre-boost IgG was below assay detection limits, became seropositive and all reached a substantial post-boost titer ([≥]364 BAU/mL). Post-boost IgG was not associated with pre-boost titer or previous SARS-CoV-2 infection. Booster reactogenicity was acceptable, with 7.9% of participants experiencing short-lived impairment of activities of daily living (ADL).\n\nInterpretationA heterologous, high-dose mRNA-1273 booster after two-dose CoronaVac was highly immunogenic and safe, including in those most in need of improved immunity.\n\nFundingWellcome Trust, UK\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThe inactivated whole-virus vaccine CoronaVac (SinoVac) is the COVID-19 vaccine most administered worldwide, at around 2 billion doses in 54 countries. Concerns that CoronaVac has lower immunogenicity than virus vector or mRNA vaccines, with pronounced decreases of neutralising antibody titres within a few months, and reduced effectiveness in the older population, highlight the urgent need for immunogenic, safe and well-tolerated booster schedules, especially with Omicron rapidly emerging.\n\nWe used the terms \"SARS-CoV-2\", \"COVID-19\", \"vaccine\", \"booster\" to search PubMed and medRxiv up to Dec 22th, 2021, with no language or date restrictions, to identify clinical trials and real-world studies reporting on the immune responses and reactogenicity to a \"third booster\" of currently approved COVID-19 vaccines. Previous research reported that neutralising antibody responses elicited by all currently approved vaccines (mRNA, adenovirus-vectored, inactivated, and protein subunit) declined to varying degrees after 6-8 months after full-schedule vaccination. Several clinical trials have evaluated heterologous (\"mix and match\") vaccination schedules, demonstrating robust immune responses in adults. After two-dose CoronaVac, BNT162b2 (Pfizer-BioNTech) boost was significantly more immunogenic than a homologous booster against wild-type and Variants of Concern (VOCs) Beta, Gamma and Delta, and AZD1222 boost increased spike RBD-specific IgG 9-10-fold, with high neutralizing activity against the wild type and VOCs. Compared to previous SARS-CoV-2 variants, current vaccine boosters appeared to neutralise Delta to a slightly lesser degree, and Omicron to a substantially lesser degree, although preliminary data from Moderna found that the authorised dose (50g) of the mRNA-1273 boost increased antibodies 37-fold and the high-dose (100g) boost 83-fold.\n\nAdded value of this studyTo our knowledge, this study is the first to provide critical real-world evidence that heterologous boosting with high-dose mRNA-1273 vaccine after CoronaVac is highly immunogenic, safe and well-tolerated in adults. After a primary course of two-dose CoronaVac, we found that a high-dose (100g) mRNA-1273 booster was immunogenic for all participants in a highly exposed cohort of hospital staff in Jakarta, Indonesia, in the context of Delta predominance, particularly for those with the lowest pre-boost antibody levels. All participants became seropositive and all reached a substantial post-boost titer ([≥]364 BAU/mL), up to a median 9.3-fold increase. Booster reactogenicity was acceptable, with 7.9% of participants experiencing short-lived impairment of activities of daily living\n\nImplications of all the available evidenceThe study findings contribute to informing policy makers on flexible options in deploying COVID-19 vaccines in mix-and-match schedules, with particular relevance for countries that are largely dependent on inactivated vaccines. Further trials are warranted that assess clinical endpoints of optimized doses of mRNA-1273 booster, and variant-specific or multivalent vaccines in response to decreased protection against emerging SARS-CoV-2 VOCs.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.22.21268246", + "rel_abs": "The Omicron variant is characterised by more than 50 distinct mutations, the majority of which are located in the spike protein. The implications of these mutations for disease transmission, tissue tropism and diagnostic testing are still to be determined. We evaluated the relative performance of saliva and mid-turbinate swabs as RT-PCR samples for the Delta and Omicron variants. The positive percent agreement (PPA) of saliva swabs and mid-turbinate swabs to a composite standard was 71% (95% CI: 53-84%) and 100% (95% CI: 89-100%), respectively, for the Delta variant. However, for the Omicron variant saliva and mid-turbinate swabs had a 100% (95% CI: 90-100%) and 86% (95% CI: 71-94%) PPA, respectively. This finding supports ex-vivo data of altered tissue tropism from other labs for the Omicron variant. Reassessment of the diagnostic testing standard-of-care may be required as the Omicron variant become the dominant variant worldwide.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Robert Sinto", - "author_inst": "Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia" - }, - { - "author_name": "Dwi Utomo", - "author_inst": "Pasar Minggu Hospital, Jakarta, Indonesia" - }, - { - "author_name": "Suwarti Suwarti", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" - }, - { - "author_name": "Erni J Nelwan", - "author_inst": "Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia" - }, - { - "author_name": "Henry Surendra", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" - }, - { - "author_name": "Cindy Natasha", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" - }, - { - "author_name": "Fransiska Fransiska", - "author_inst": "St Carolus Hospital, Jakarta, Indonesia" - }, - { - "author_name": "Deborah Theresia", - "author_inst": "St Carolus Hospital, Jakarta, Indonesia" - }, - { - "author_name": "Adella F Ranitria", - "author_inst": "Pasar Minggu Hospital, Jakarta, Indonesia" + "author_name": "Gert Johannes Kruger Marais", + "author_inst": "University of Cape Town" }, { - "author_name": "Decy Subekti", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" + "author_name": "Nei-yuan Hsiao", + "author_inst": "University of Cape Town" }, { - "author_name": "Nunung Nuraeni", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" + "author_name": "Arash Iranzadeh", + "author_inst": "University of Cape Town" }, { - "author_name": "Winahyu Handayani", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" + "author_name": "Deelan Doolabh", + "author_inst": "University of Cape Town" }, { - "author_name": "Mutia Rahardjani", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" + "author_name": "Annabel Enoch", + "author_inst": "National Health Laboratory Service" }, { - "author_name": "J. Kevin Baird", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" + "author_name": "Chun Yat Chu", + "author_inst": "University of Cape Town" }, { - "author_name": "Susanna Dunachie", - "author_inst": "University of Oxford, Centre for Tropical Medicine and Global Health, Oxford, UK" + "author_name": "Carolyn Williamson", + "author_inst": "University of Cape Town" }, { - "author_name": "Anuraj H Shankar", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" + "author_name": "Adrian Brink", + "author_inst": "University of Cape Town" }, { - "author_name": "Raph L Hamers", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" + "author_name": "Diana Ruth Hardie", + "author_inst": "University of Cape Town" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -439953,85 +438684,89 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.21.21267733", - "rel_title": "Maternal transfer of IgA and IgG SARS-CoV-2 specific antibodies transplacentally and via breastfeeding", + "rel_doi": "10.1101/2021.12.23.21266126", + "rel_title": "SARS-CoV-2 detection in multi-sample pools in a real pandemic scenario: a screening strategy of choice for active surveillance", "rel_date": "2021-12-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.21.21267733", - "rel_abs": "Although there have been many studies on antibody responses to SARS-CoV-2 in breastmilk, very few have looked at the fate of these in the baby. We carried out a study in 22 mother/baby pairs (mothers who breastfed and who were SARS-CoV-2 vaccinated before or after delivery) looking at mother blood, mother milk, baby blood, baby nose, and baby stool. Breastfed infants only acquired systemic anti-SARS-CoV-2 IgG antibodies if their mothers were vaccinated antepartum. None of the infants had SARS-CoV-2-specific IgA in the blood, but surprisingly, half of the infants in the Antepartum group had high titer SARS-CoV-2-specific IgA in the nose that exceeded titers found in breastmilk. Vaccination antepartum followed by breastfeeding appears to be the best way to provide systemic and local anti-SARS-CoV-2 antibodies for infants.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.23.21266126", + "rel_abs": "BackgroundThe current COVID-19 pandemic has overloaded the diagnostic capacity of laboratories by the gold standard method rRT-PCR. This disease has a high spread rate and almost a quarter of infected individuals never develop symptoms. In this scenario, active surveillance is crucial to stop the virus propagation.\n\nMethodsBetween July 2020 and April 2021, 11580 oropharyngeal swab samples collected in closed and semi-closed institutions were processed for SARS-CoV-2 detection in pools, implementing this strategy for the first time in Cordoba, Argentina. Five-sample pools were constituted before nucleic acid extraction and amplification by rRT-PCR. Comparative analysis of cycle threshold (Ct) values from positive pools and individual samples along with a cost-benefit report of the whole performance of the results was performed.\n\nResultsFrom 2314 5-sample pools tested, 158 were classified as positive (6.8%), 2024 as negative (87.5%), and 132 were categorized as indeterminate (5.7%). The Ct value shift due to sample dilution showed an increase in Ct of 2.6{+/-}1.53 cycles for N gene and 2.6{+/-}1.78 for ORF1ab gene. Overall, 290 pools were disassembled and 1450 swabs were analyzed individually. This strategy allowed correctly identifying 99.8% of the samples as positive (7.6%) or negative (92.2%), avoiding the execution of 7,806 rRT-PCR reactions which represents a cost saving of 67.5%.\n\nConclusionThis study demonstrates the feasibility of pooling samples to increase the number of tests performed, helping to maximize molecular diagnostic resources and reducing the work overload of specialized personnel during active surveillance of the COVID-19 pandemic.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Mohammad M. Sajadi", - "author_inst": "Institute of Human Virology at University of Maryland School of Medicine" + "author_name": "Andr\u00e9s Marcos Castellaro", + "author_inst": "Dpto. de Bioquimica Clinica. Facultad de Ciencias Quimicas, Universidad Nacional de Cordoba (UNC), CIBICI-CONICET-UNC." }, { - "author_name": "Narjes Shokatpour", - "author_inst": "Institute of Human Virology at University of Maryland School of Medicine" + "author_name": "Pablo Velez", + "author_inst": "Unidad de Biologia Molecular, Centro de Excelencia en Productos y Procesos de Cordoba (CEPROCOR), Cordoba, Argentina" }, { - "author_name": "Allison Bathula", - "author_inst": "University of Maryland Medical Center" + "author_name": "Guillermo Giaj Merlera", + "author_inst": "Unidad de Biologia Molecular, Centro de Excelencia en Productos y Procesos de Cordoba (CEPROCOR), Cordoba, Argentina" }, { - "author_name": "Zahra Tehrani", - "author_inst": "Institute of Human Virology at University of Maryland School of Medicine" + "author_name": "Juan Rondan Duenas", + "author_inst": "Unidad de Biologia Molecular, Centro de Excelencia en Productos y Procesos de Cordoba (CEPROCOR), Cordoba, Argentina" }, { - "author_name": "Allison Lankford", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Felix Condat", + "author_inst": "Unidad de Biologia Molecular, Centro de Excelencia en Productos y Procesos de Cordoba (CEPROCOR), Cordoba, Argentina" }, { - "author_name": "Madeleine Purcell", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Jesica Gallardo", + "author_inst": "Unidad de Biologia Molecular, Centro de Excelencia en Productos y Procesos de Cordoba (CEPROCOR), Cordoba, Argentina" }, { - "author_name": "James D. Campbell", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Aylen Makhoul", + "author_inst": "Unidad de Biologia Molecular, Centro de Excelencia en Productos y Procesos de Cordoba (CEPROCOR), Cordoba, Argentina" }, { - "author_name": "Elizabeth Adrianne Duque Hammershaimb", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Camila Cinalli", + "author_inst": "Unidad de Biologia Molecular, Centro de Excelencia en Productos y Procesos de Cordoba (CEPROCOR), Cordoba, Argentina" }, { - "author_name": "Kristopher B. Deatrick", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Lorenzo Rosales Cavaglieri", + "author_inst": "Unidad de Biologia Molecular, Centro de Excelencia en Productos y Procesos de Cordoba (CEPROCOR), Cordoba, Argentina" }, { - "author_name": "Casey Bor", - "author_inst": "University of Maryland Medical Center" + "author_name": "Guadalupe Di Cola", + "author_inst": "Instituto de Virologia Dr. J. M. Vanella, -INVIV- CONICET- Facultad de Ciencias Medicas, UNC" }, { - "author_name": "Dawn M. Parsell", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Paola Sicilia", + "author_inst": "Laboratorio Central, Ministerio de Salud de la Provincia de Cordoba." }, { - "author_name": "Colleen Dugan", - "author_inst": "University of Maryland Medical Center" + "author_name": "Laura Lopez", + "author_inst": "Direccion de epidemiologia, Ministerio de Salud de la Provincia de Cordoba." }, { - "author_name": "Andrea Levine", - "author_inst": "University of Maryland School of Medicine" + "author_name": "- Facultad de Ciencias Quimicas UNC Group", + "author_inst": "Facultad de Ciencias Quimicas, Universidad Nacional de Cordoba (UNC), Cordoba" }, { - "author_name": "Sabrina C. Ramelli", - "author_inst": "National Institutes of Health" + "author_name": "Jose Luis Bocco", + "author_inst": "Dpto. de Bioquimica Clinica. Facultad de Ciencias Quimicas, Universidad Nacional de Cordoba (UNC), CIBICI-CONICET-UNC." }, { - "author_name": "Daniel Chertow", - "author_inst": "National Institutes of Health" + "author_name": "Maria Gabriela Barbas", + "author_inst": "Secretaria de prevencion y promocion de la salud, Ministerio de Salud de la Provincia de Cordoba." }, { - "author_name": "Daniel L. Herr", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Maria Belen Pisano", + "author_inst": "Instituto de Virologia Dr. J. M. Vanella, -INVIV- CONICET- Facultad de Ciencias Medicas, UNC" }, { - "author_name": "George K. Lewis", - "author_inst": "Institute of Human Virology at University of Maryland School of Medicine" + "author_name": "Viviana R\u00e9", + "author_inst": "Instituto de Virologia Dr. J. M. Vanella, -INVIV- CONICET- Facultad de Ciencias Medicas, UNC" }, { - "author_name": "Alison Grazioli", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Andrea Belaus", + "author_inst": "Unidad de Biologia Molecular, Centro de Excelencia en Productos y Procesos de Cordoba (CEPROCOR), Cordoba, Argentina" + }, + { + "author_name": "Gonzalo Castro", + "author_inst": "Laboratorio Central, Ministerio de Salud de la Provincia de Cordoba." } ], "version": "1", @@ -442039,41 +440774,69 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2021.12.18.473309", - "rel_title": "APOBEC-mediated Editing of SARS-CoV-2 Genomic RNA Impacts Viral Replication and Fitness", + "rel_doi": "10.1101/2021.12.18.473303", + "rel_title": "A highly sensitive cell-based luciferase assay for high-throughput automated screening of SARS-CoV-2 nsp5/3CLpro inhibitors", "rel_date": "2021-12-21", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.18.473309", - "rel_abs": "During COVID-19 pandemic, mutations of SARS-CoV-2 produce new strains that can be more infectious or evade vaccines. Viral RNA mutations can arise from misincorporation by RNA-polymerases and modification by host factors. Analysis of SARS-CoV-2 sequence from patients showed a strong bias toward C-to-U mutation, suggesting a potential mutational role by host APOBEC cytosine deaminases that possess broad anti-viral activity. We report the first experimental evidence demonstrating that APOBEC3A, APOBEC1, and APOBEC3G can edit on specific sites of SARS-CoV-2 RNA to produce C-to-U mutations. However, SARS-CoV-2 replication and viral progeny production in Caco-2 cells are not inhibited by the expression of these APOBECs. Instead, expression of wild-type APOBEC3 greatly promotes viral replication/propagation, suggesting that SARS-CoV-2 utilizes the APOBEC-mediated mutations for fitness and evolution. Unlike the random mutations, this study suggests the predictability of all possible viral genome mutations by these APOBECs based on the UC/AC motifs and the viral genomic RNA structure.\n\nOne-sentence summaryEfficient Editing of SARS-CoV-2 genomic RNA by Host APOBEC deaminases and Its Potential Impacts on the Viral Replication and Emergence of New Strains in COVID-19 Pandemic", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.18.473303", + "rel_abs": "Effective drugs against SARS-CoV-2 are urgently needed to treat severe cases of infection and for prophylactic use. The main viral protease (nsp5 or 3CLpro) represents an attractive and possibly broad-spectrum target for drug development as it is essential to the virus life cycle and highly conserved among betacoronaviruses. Sensitive and efficient high-throughput screening methods are key for drug discovery. Here we report the development of a gain-of-signal, highly sensitive cell-based luciferase assay to monitor SARS-CoV-2 nsp5 activity and show that it is suitable for high-throughput screening of compounds in a 384-well format. A benefit of miniaturisation and automation is that screening can be performed in parallel on a wild-type and a catalytically inactive nsp5, which improves the selectivity of the assay. We performed molecular docking-based screening on a set of 14,468 compounds from an in-house chemical database, selected 359 candidate nsp5 inhibitors and tested them experimentally. We identified four molecules, including the broad-spectrum antiviral merimepodib/VX-497, which show anti-nsp5 activity and inhibit SARS-CoV-2 replication in A549-ACE2 cells with IC50 values in the 4-21 {micro}M range. The here described assay will allow the screening of large-scale compound libraries for SARS-CoV-2 nsp5 inhibitors. Moreover, we provide evidence that this assay can be adapted to other coronaviruses and viruses which rely on a viral protease.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Kyumin Kim Sr.", - "author_inst": "University of Southern California" + "author_name": "Kuang-Yu Chen", + "author_inst": "RNA Biology and Influenza Virus Unit, Institut Pasteur, CNRS UMR3569, Universite de Paris, Paris, France" }, { - "author_name": "Peter Calabrese", - "author_inst": "University of Southern California" + "author_name": "Tim Krischuns", + "author_inst": "RNA Biology and Influenza Virus Unit, Institut Pasteur, CNRS UMR3569, Universite de Paris, Paris, France" }, { - "author_name": "Shanshan Wang", - "author_inst": "University of Southern California" + "author_name": "Laura Ortega Varga", + "author_inst": "Structural Bioinformatics Unit, Institut Pasteur, Paris, France" }, { - "author_name": "Chao Qin", - "author_inst": "University of Southern California" + "author_name": "Emna Harigua-Souiai", + "author_inst": "Laboratory of Molecular Epidemiology and Experimental Pathology, LR16IPT04, Institut Pasteur de Tunis, Universite de Tunis El Manar, Tunis, Tunisia" }, { - "author_name": "Youliang Rao", - "author_inst": "University of Southern California" + "author_name": "Sylvain Paisant", + "author_inst": "RNA Biology and Influenza Virus Unit, Institut Pasteur, CNRS UMR3569, Universite de Paris, Paris, France" }, { - "author_name": "Pinghui Feng", - "author_inst": "University of Southern California" + "author_name": "Agnes Zettor", + "author_inst": "Chemogenomic and Biological Screening Platform, Institut Pasteur, Paris, France" }, { - "author_name": "Xiaojiang Chen", - "author_inst": "University of Southern California" + "author_name": "Jeanne Chiaravalli", + "author_inst": "Chemogenomic and Biological Screening Platform, Institut Pasteur, Paris, France" + }, + { + "author_name": "David Courtney", + "author_inst": "RNA Biology and Influenza Virus Unit, Institut Pasteur, CNRS UMR3569, Universite de Paris, Paris, France" + }, + { + "author_name": "Susan Baker", + "author_inst": "Department of Microbiology and Immunology, Loyola University Chicago, Stritch School of Medicine, Maywood, IL, USA" + }, + { + "author_name": "Catherine Isel", + "author_inst": "RNA Biology and Influenza Virus Unit, Institut Pasteur, CNRS UMR3569, Universite de Paris, Paris, France" + }, + { + "author_name": "Fabrice Agou", + "author_inst": "Chemogenomic and Biological Screening Platform, Institut Pasteur, Paris, France" + }, + { + "author_name": "Yves Jacob", + "author_inst": "Molecular Genetics of RNA Viruses, Institut Pasteur, CNRS UMR3569, Universite de Paris, Paris, France" + }, + { + "author_name": "Arnaud Blondel", + "author_inst": "Structural Bioinformatics Unit, Institut Pasteur, Paris, France" + }, + { + "author_name": "Nadia Naffakh", + "author_inst": "RNA Biology and Influenza Virus Unit, Institut Pasteur, CNRS UMR3569, Universite de Paris, Paris, France" } ], "version": "1", @@ -444413,18 +443176,135 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.12.15.472745", - "rel_title": "Sentimental Tweets Classification of Symptomatic COVID 19", + "rel_doi": "10.1101/2021.12.18.473317", + "rel_title": "Temporal associations of B and T cell immunity with robust vaccine responsiveness in a 16-week interval BNT162b2 regimen", "rel_date": "2021-12-21", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.15.472745", - "rel_abs": "The approach I described is straightforward, related to COVID-19 SARS based tweets and the symptoms, that people tweet about. Also, social media mining for health application reports was shared in many different tasks of 2021. The motto at the back of this observe is to analyses tweets of COVID-19 based symptoms. By performing BERT model and text classification with XLNET with which uses to classify text and purpose of the texts (i.e.) tweets. So that I can get a deep understanding of the texts. When developing the system, I used two models the XLNet and DistilBERT for the text sorting task, but the outcome was XLNET out-performs the given approach to the best accuracy achieved. Now I discover a whole lot vital for as it should be categorizing tweets as encompassing self-said COVID-19 indications. Whether or not a tweets associated with COVID-19 is a non-public report or an information point out to the virus. Which gives test accuracy to an F1 score of 96%.", - "rel_num_authors": 0, - "rel_authors": null, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.18.473317", + "rel_abs": "Spacing of the BNT162b2 mRNA doses beyond 3 weeks raised concerns about vaccine efficacy. We longitudinally analyzed B cell, T cell and humoral responses to two BNT162b2 mRNA doses administered 16 weeks apart in 53 SARS-CoV-2 naive and previously-infected donors. This regimen elicited robust RBD-specific B cell responses whose kinetics differed between cohorts, the second dose leading to increased magnitude in naive participants only. While boosting did not increase magnitude of CD4+ T cell responses further compared to the first dose, unsupervised clustering analyses of single-cell features revealed phenotypic and functional shifts over time and between cohorts. Integrated analysis showed longitudinal immune component-specific associations, with early Thelper responses post-first dose correlating with B cell responses after the second dose, and memory Thelper generated between doses correlating with CD8 T cell responses after boosting. Therefore, boosting elicits a robust cellular recall response after the 16-week interval, indicating functional immune memory.", + "rel_num_authors": 29, + "rel_authors": [ + { + "author_name": "Manon Nayrac", + "author_inst": "University of Montreal" + }, + { + "author_name": "Mathieu Dube", + "author_inst": "CHUM Research Center" + }, + { + "author_name": "Geremy Sannier", + "author_inst": "University of Montreal" + }, + { + "author_name": "Alexandre Nicolas", + "author_inst": "University of Montreal" + }, + { + "author_name": "Lorie Marchitto", + "author_inst": "University of Montreal" + }, + { + "author_name": "Olivier Tastet", + "author_inst": "CHUM Research Center" + }, + { + "author_name": "Alexandra Tauzin", + "author_inst": "University of Montreal" + }, + { + "author_name": "Nathalie Brassard", + "author_inst": "CHUM Research Center" + }, + { + "author_name": "Guillaume Beaudoin-Bussieres", + "author_inst": "University of Montreal" + }, + { + "author_name": "Dani Vezina", + "author_inst": "CHUM Research Center" + }, + { + "author_name": "Shang Yu Gong", + "author_inst": "McGill University" + }, + { + "author_name": "Mehdi Benlarbi", + "author_inst": "CHUM Research Center" + }, + { + "author_name": "Romain Gasser", + "author_inst": "University of Montreal" + }, + { + "author_name": "Annemarie Laumaea", + "author_inst": "University of Montreal" + }, + { + "author_name": "Catherine Bourassa", + "author_inst": "CHUM Research Center" + }, + { + "author_name": "Gabrielle Gendron-Lepage", + "author_inst": "CHUM Research Center" + }, + { + "author_name": "Halima Medjahed", + "author_inst": "CHUM Research Center" + }, + { + "author_name": "Guillaume Goyette", + "author_inst": "CHUM Research Center" + }, + { + "author_name": "Gloria-Gabrielle Ortega-Delgado", + "author_inst": "CHUM Research Center" + }, + { + "author_name": "Melanie Laporte", + "author_inst": "CHUM Research Center" + }, + { + "author_name": "Julia Niessl", + "author_inst": "Karolinska Institute" + }, + { + "author_name": "Laurie Gokool", + "author_inst": "CHUM Research Center" + }, + { + "author_name": "Chantal Morrisseau", + "author_inst": "CHUM Research Center" + }, + { + "author_name": "Pascale Arlotto", + "author_inst": "CHUM Research Center" + }, + { + "author_name": "Jonathan Richard", + "author_inst": "CHUM Research Center" + }, + { + "author_name": "Cecile Tremblay", + "author_inst": "University of Montreal" + }, + { + "author_name": "Valerie Martel-Laferriere", + "author_inst": "University of Montreal" + }, + { + "author_name": "Andres Finzi", + "author_inst": "University of Montreal" + }, + { + "author_name": "Daniel E Kaufmann", + "author_inst": "University of Montreal" + } + ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "scientific communication and education" + "category": "immunology" }, { "rel_doi": "10.1101/2021.12.20.21268134", @@ -446254,35 +445134,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.12.21.21267955", - "rel_title": "Immunity acquired by a minority active fraction of the population could explain COVID-19 spread in Greater Buenos Aires (June-November 2020)", + "rel_doi": "10.1101/2021.12.20.21268140", + "rel_title": "Spatiotemporal patterns and progression of the Delta variant of COVID-19 and their health intervention linkages in Southeast Asia", "rel_date": "2021-12-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.21.21267955", - "rel_abs": "The COVID-19 pandemic had an uneven development in different countries. In Argentina, the pandemic began in march 2020 and, during the first 3 months, the vast majority of cases were concentrated in a densely populated region that includes the city of Buenos Aires (country capital) and the Greater Buenos Aires area that surrounds it. This work focuses on the spread of COVID-19 between June and November 2020 in Greater Buenos Aires. Within this period of time there was no vaccine, basically only the early wild strain of SARS-CoV-2 was present, and the official restriction and distancing measures in this region remained more or less constant. Under these particular conditions, the incidences show a sharp rise from June 2020 and begin to decrease towards the end of August until the end of November 2020. In this work we study, through mathematical modelling and available epidemiological information, the spread of COVID-19 in this region and period of time. We show that a coherent explanation of the evolution of incidences can be obtained assuming that only a minority fraction of the population got involved in the spread process, so that the incidences decreased as this group of people was becoming immune. The observed evolution of the incidences could then be a consequence at the population level of lasting immunity conferred by SARS-CoV-2.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.20.21268140", + "rel_abs": "The global pandemic of COVID-19 presented an unprecedented challenge to all countries in the world, among which Southeast Asia (SEA) countries managed to maintain and mitigate the first wave of COVID-19 in 2020. However, these countries were caught in the crisis after the Delta variant was introduced to SEA, though many countries had immediately implemented non-pharmaceutical intervention (NPI) measures along with vaccination in order to contain the disease spread. To investigate the potential linkages between epidemic dynamics and public health interventions, we adopted a prospective space-time scan method to conduct spatiotemporal analysis at the district level in the seven selected countries in SEA from June 2021 to October 2021. Results reveal the spatial and temporal propagation and progression of COVID-19 risks relative to public health measures implemented by different countries. Our research benefits continuous improvements of public health strategies in preventing and containing this pandemic.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Gabriel Fabricius", - "author_inst": "Instituto de Investigaciones Fisicoqu\u00edmicas Te\u00f3ricas y Aplicadas (INIFTA), Consejo Nacional de Investigaciones Cient\u00edficas y T\u00e9cnicas (CONICET) and Facultad de" + "author_name": "Wei Luo", + "author_inst": "National University of Singapore" + }, + { + "author_name": "Zhaoyin Liu", + "author_inst": "National University of Singapore" + }, + { + "author_name": "Yuxuan Zhou", + "author_inst": "National University of Singapore" }, { - "author_name": "Rodolfo Borzi", - "author_inst": "Instituto de F\u00edsica de L\u00edquidos y Sistemas Biol\u00f3gicos (IFLySiB), Consejo Nacional de Investigaciones Cient\u00edficas y T\u00e9cnicas (CONICET) and Facultad de Cs. Exact" + "author_name": "Yumin Zhao", + "author_inst": "National University of Singapore" }, { - "author_name": "Jos\u00e9 Caminos", - "author_inst": "Instituto de F\u00edsica de L\u00edquidos y Sistemas Biol\u00f3gicos (IFLySiB), Consejo Nacional de Investigaciones Cient\u00edficas y T\u00e9cnicas (CONICET) and Facultad de Cs. Exact" + "author_name": "Yunyue Elita Li", + "author_inst": "Purdue University" }, { - "author_name": "Tom\u00e1s S. Grigera", - "author_inst": "Instituto de F\u00edsica de L\u00edquidos y Sistemas Biol\u00f3gicos (IFLySiB), Consejo Nacional de Investigaciones Cient\u00edficas y T\u00e9cnicas (CONICET) and Facultad de Cs. Exacta" + "author_name": "Arif Masrur", + "author_inst": "Pennsylvania State University" + }, + { + "author_name": "Manzhu Yu", + "author_inst": "Pennsylvania State University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.12.21.21267983", @@ -448460,43 +447352,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.12.18.21267261", - "rel_title": "A comprehensive systematic review and meta-analysis of the global data involving 61,532 cancer patients with SARS-CoV-2 infection.", + "rel_doi": "10.1101/2021.12.18.21268002", + "rel_title": "COVID-19 endgame: from pandemic to endemic? Vaccination, reopening and evolution in a well-vaccinated population", "rel_date": "2021-12-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.18.21267261", - "rel_abs": "BackgroundSARS-CoV-2 have been shown to be associated with more severe disease and death in cancer patient. A systematic review and meta-analysis was conducted to determine the risk by age, tumour type and treatment of infection with SARS-CoV-2 in cancer patients.\n\nMethodsSystematic review by searching PubMed, Web of Science, and Scopus for articles published in English up to June 14, 2021 of SARS-CoV-2 infection in >10 patients with malignant disease. Outcomes included factors in patients with malignant disease that may predict a poor outcome from COVID-19 compared to patients without malignant disease, including patient demographics, tumour subtype and cancer treatments. A meta-analysis was performed using random effects model.\n\nResults81 studies were included, totalling 61,532 cancer patients. Haematological malignancies comprised 22.1% (9,672 of 43,676) of cases. Relative risk (RR) of mortality when age and sex matched was 1.69 (95% CI, 1.46-1.95; p<0.001; I2=51%). RR of mortality, versus non-cancer patients, was associated with decreasing age (exp(b)0.96; 95% CI, 0.922-0.994; p=0.028) but not male sex (exp(b)1.89; 95% CI, 0.222-6.366; p=0.83). RR of mortality in those with haematological malignancies versus non-cancer control was 1.81 (95% CI, 1.53-2.95; I2=0.0%). Compared to other cancers, increased risk of death was seen for lung (RR 1.68, 95% CI, 1.45-1.94; p<0.001), genitourinary (RR 1.11; 95% CI, 1.00-1.24; p=0.059) and haematological malignancies (RR 1.42; 95% CI, 1.31-1.54; p<0.001). Breast (RR 0.51; 95% CI, 0.36-0.71; p<0.001) and gynaecological cancers (RR 0.76; 95% CI, 0.62-0.93; p=0.009) had lower risk of death. Receipt of chemotherapy had greatest overall pooled mortality risk of 30% (95% CI, 25-36%; I2=86.97%) and endocrine therapy the lowest at 11% (95% CI, 6-16%; I2=70.7%).\n\nConclusionsCancer patients, particularly younger cancer patients, appear at increased risk of mortality from COVID-19 compared to non-cancer patients. Differences in outcomes were seen based on tumour types and treatment.\n\nHighlights- To our knowledge this is the largest review and meta-analysis of COVID-19 in cancer patients with insights into tumour types and therapies.\n- In unadjusted analysis cancer doubles the risk of COVID-19 related mortality. This decreased when adjusted for age and sex.\n- Younger cancer patients have the highest risk of mortality when compared to non-cancer COVID-19 patient of a similar age.\n- Patients with lung, genitourinary and haematological malignancies are at increased risk of mortality, breast and gynaecological cancers are at lower risk.\n- Patients on chemotherapy have the highest pooled mortality risk with those on endocrine therapy the lowest.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.18.21268002", + "rel_abs": "COVID-19 remains a major public health concern, with large resurgences even where there has been widespread uptake of vaccines. Waning immunity and the emergence of new variants will shape the long-term burden and dynamics of COVID-19. We explore the transition to the endemic state, and the endemic incidence, using a combination of modelling approaches. We compare gradual and rapid reopening and reopening at different vaccination levels. We examine how the eventual endemic state depends on the duration of immunity, the rate of importations, the efficacy of vaccines and the transmissibility. These depend on the evolution of the virus, which continues to undergo selection. Slower reopening leads to a lower peak level of incidence and fewer overall infections: as much as a 60% lower peak and a 10% lower total in some illustrative simulations; under realistic parameters, reopening when 70% of the population is vaccinated leads to a large resurgence in cases. The long-term endemic behaviour may stabilize as late as January 2023, with further waves of high incidence occurring depending on the transmissibility of the prevalent variant, duration of immunity, and antigenic drift. We find that long term endemic levels are not necessarily lower than current pandemic levels: in a population of 100,000 with representative parameter settings (Reproduction number 5, 1-year duration of immunity, vaccine efficacy at 80% and importations at 3 cases per 100K per day) there are over 100 daily incident cases in the model. The consequent burden on health care systems depends on the severity of infection in immunized or previously infected individuals.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Emma Khoury", - "author_inst": "University of Liverpool, Institute of Translational Medicine, Department of Molecular and Clinical Cancer Medicine, UK; University of Liverpool, School of Medic" - }, - { - "author_name": "Sarah Nevitt", - "author_inst": "Department of Health Data Science, Institute of Population Health, University of Liverpool, UK" + "author_name": "Elisha B. Are", + "author_inst": "Simon Fraser University" }, { - "author_name": "William Rohde Madsen", - "author_inst": "Department of Political Science & School of Public Policy, University College London, UK; University of Copenhagen, Department of Political Science" + "author_name": "Yexuan Song", + "author_inst": "Simon Fraser University" }, { - "author_name": "Lance Turtle", - "author_inst": "Tropical and Infectious Disease Unit, Liverpool University Hospitals NHS Foundation Trust, member of Liverpool Health Partners, UK." + "author_name": "Jessica E. Stockdale", + "author_inst": "Simon Fraser University" }, { - "author_name": "Gerry Davies", - "author_inst": "University of Liverpool Department of Clinical Infection Microbiology and Immunology, Department of Clinical Infection, Liverpool, UK; University of Liverpool I" + "author_name": "Paul Tupper", + "author_inst": "Simon Fraser University" }, { - "author_name": "Carlo Palmieri", - "author_inst": "University of Liverpool, Institute of Translational Medicine, Department of Molecular and Clinical Cancer Medicine, UK; The Clatterbridge Cancer Centre NHS Foun" + "author_name": "Caroline Colijn", + "author_inst": "Simon Fraser University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "oncology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.18.21267819", @@ -449822,585 +448710,69 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2021.12.16.21267889", - "rel_title": "A machine learning-based approach to determine infection status in recipients of BBV152 whole virion inactivated SARS-CoV-2 vaccine for serological surveys", + "rel_doi": "10.1101/2021.12.16.21267866", + "rel_title": "Real-world response of COVID-19 patients in Mexico", "rel_date": "2021-12-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.16.21267889", - "rel_abs": "Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the effectiveness of interventions. Asymptomatic breakthrough infections have been a major problem during the ongoing surge of Delta variant globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines used in the higher-income regions. Here, we show for the first time how statistical and machine learning (ML) approaches can discriminate SARS-CoV-2 infection from immune response to an inactivated whole virion vaccine (BBV152, Covaxin, India), thereby permitting real-world vaccine effectiveness assessments from cohort-based serosurveys in Asia and Africa where such vaccines are commonly used. Briefly, we accessed serial data on Anti-S and Anti-NC antibody concentration values, along with age, sex, number of doses, and number of days since the last vaccine dose for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine (SVM) model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, 724 were classified as infected. Since the vaccine contains wild-type virus and the antibodies induced will neutralize wild type much better than Delta variant, we determined the relative ability of a random subset of such samples to neutralize Delta versus wild type strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, Delta variant, was neutralized more effectively than the wild type, which cannot happen without infection. The fraction rose to 71.8% (28 of 39) in subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%-80.2%) over the same period.", - "rel_num_authors": 142, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.16.21267866", + "rel_abs": "ObjectiveTo analyze the treatment outcomes for COVID-19 during the early stages of the pandemic at the Mexican Institute of Social Security.\n\nMaterial and MethodsIn this retrospective observational study, we investigated 130,216 patients with COVID-19 treated in two Mexican states during 2020. A competing risk analysis was performed using death and recovery as possible outcomes, followed by a cox-regression and Kaplan-Meier analysis. Additionally, machine learning models were built to predict the outcomes at fixed times.\n\nResultsHigher prevalence of obesity, diabetes, and heart disease comorbidities were found, which is consistent with Mexicos epidemiological profile. Mortality occurred around 15-20 days from the start of symptoms. Patients undertaking cephalosporin in combination with neuraminidase inhibitors (NAIs) had the worst survival rates, while patients undertaking adamantane, fluoroquinolone, or penicillin had the best survival rates.\n\nConclusionsOur findings recommend against using specific treatment combinations, and should help improve the countrys clinical guidelines.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Prateek Singh", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology, New Delhi, India" - }, - { - "author_name": "Rajat Ujjainiya", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology, New Delhi, India" - }, - { - "author_name": "Satyartha Prakash", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology, New Delhi, India" - }, - { - "author_name": "Salwa Naushin", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology, New Delhi, India" - }, - { - "author_name": "Viren Sardana", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology, New Delhi, India" - }, - { - "author_name": "Nitin Bhatheja", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology, New Delhi, India" - }, - { - "author_name": "Ajay Pratap Singh", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology, New Delhi, India" - }, - { - "author_name": "Joydeb Barman", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology, New Delhi, India" - }, - { - "author_name": "Kartik Kumar", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology, New Delhi, India" - }, - { - "author_name": "Raju Khan", - "author_inst": "CSIR-Advanced Materials and Processes Research Institute, Bhopal, India" - }, - { - "author_name": "Karthik Bharadwaj Tallapaka", - "author_inst": "CSIR-Centre for Cellular Molecular Biology, Hyderabad, India" - }, - { - "author_name": "Mahesh Anumalla", - "author_inst": "CSIR-Centre for Cellular Molecular Biology, Hyderabad, India" - }, - { - "author_name": "Amit Lahiri", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "Susanta Kar", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "Vivek Bhosale", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "Mrigank Srivastava", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "Madhav Nilakanth Mugale", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "C.P Pandey", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "Shaziya Khan", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "Shivani Katiyar", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "Desh Raj", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "Sharmeen Ishteyaque", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "Sonu Khanka", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "Ankita Rani", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "Promila", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "Jyotsna Sharma", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "Anuradha Seth", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "Mukul Dutta", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "Nishant Saurabh", - "author_inst": "CSIR-Central Drug Research Institute, Lucknow, India" - }, - { - "author_name": "Murugan Veerapandian", - "author_inst": "CSIR- Central Electrochemical Research Institute, Karaikudi, India" - }, - { - "author_name": "Ganesh Venkatachalam", - "author_inst": "CSIR- Central Electrochemical Research Institute, Karaikudi, India" - }, - { - "author_name": "Deepak Bansal", - "author_inst": "CSIR-Central Electronics Engineering Research Institute, Pilani, India" - }, - { - "author_name": "Dinesh Gupta", - "author_inst": "CSIR-Central Electronics Engineering Research Institute, Pilani, India" - }, - { - "author_name": "Prakash M Halami", - "author_inst": "CSIR-Central Food Technological Research Institute, Mysore, India" - }, - { - "author_name": "Muthukumar Serva Peddha", - "author_inst": "CSIR-Central Food Technological Research Institute, Mysore, India" - }, - { - "author_name": "Gopinath M Sundaram", - "author_inst": "CSIR-Central Food Technological Research Institute, Mysore, India" - }, - { - "author_name": "Ravindra P Veeranna", - "author_inst": "CSIR-Central Food Technological Research Institute, Mysore, India" - }, - { - "author_name": "Anirban Pal", - "author_inst": "CSIR-Central Institute of Medicinal Aromatic Plants, Lucknow, India" - }, - { - "author_name": "Ranvijay Kumar Singh", - "author_inst": "CSIR-Central Institute of Mining and Fuel Research, Dhanbad, India" - }, - { - "author_name": "Suresh Kumar Anandasadagopan", - "author_inst": "CSIR-Central Leather Research Institute, Chennai, India" - }, - { - "author_name": "Parimala Karuppanan", - "author_inst": "CSIR-Central Leather Research Institute, Chennai, India" - }, - { - "author_name": "Syed Nasar Rahman", - "author_inst": "CSIR-Central Leather Research Institute, Chennai, India" - }, - { - "author_name": "Gopika Selvakumar", - "author_inst": "CSIR-Central Leather Research Institute, Chennai, India" - }, - { - "author_name": "Subramanian Venkatesan", - "author_inst": "CSIR-Central Leather Research Institute, Chennai, India" - }, - { - "author_name": "MalayKumar Karmakar", - "author_inst": "CSIR-Central Mechanical Engineering Research Institute, Durgapur , India" - }, - { - "author_name": "Harish Kumar Sardana", - "author_inst": "CSIR-Central Scientific Instruments Organization, Chandigarh, India" - }, - { - "author_name": "Animika Kothari", - "author_inst": "CSIR-Central Scientific Instruments Organization, Chandigarh, India" - }, - { - "author_name": "DevendraSingh Parihar", - "author_inst": "CSIR-Central Scientific Instruments Organization, Chandigarh, India" - }, - { - "author_name": "Anupma Thakur", - "author_inst": "CSIR-Central Scientific Instruments Organization, Chandigarh, India" - }, - { - "author_name": "Anas Saifi", - "author_inst": "CSIR-Central Scientific Instruments Organization, Chandigarh, India" - }, - { - "author_name": "Naman Gupta", - "author_inst": "CSIR-Central Scientific Instruments Organization, Chandigarh, India" - }, - { - "author_name": "Yogita Singh", - "author_inst": "CSIR-Central Scientific Instruments Organization, Chandigarh, India" - }, - { - "author_name": "Ritu Reddu", - "author_inst": "CSIR-Central Scientific Instruments Organization, Chandigarh, India" - }, - { - "author_name": "Rizul Gautam", - "author_inst": "CSIR-Central Scientific Instruments Organization, Chandigarh, India" - }, - { - "author_name": "Anuj Mishra", - "author_inst": "CSIR-Central Scientific Instruments Organization, Chandigarh, India" - }, - { - "author_name": "Avinash Mishra", - "author_inst": "CSIR- Central Salt Marine Chemicals Research Institute, Bhavnagar, India" - }, - { - "author_name": "Iranna Gogeri", - "author_inst": "CSIR Fourth Paradigm Institute, Bengaluru, India" - }, - { - "author_name": "Geethavani Rayasam", - "author_inst": "CSIR- Headquarters, Rafi Marg, New Delhi, India" - }, - { - "author_name": "Yogendra Padwad", - "author_inst": "CSIR-Institute of Himalayan Bioresource Technology, Palampur, India" - }, - { - "author_name": "Vikram Patial", - "author_inst": "CSIR-Institute of Himalayan Bioresource Technology, Palampur, India" - }, - { - "author_name": "Vipin Hallan", - "author_inst": "CSIR-Institute of Himalayan Bioresource Technology, Palampur, India" - }, - { - "author_name": "Damanpreet Singh", - "author_inst": "CSIR-Institute of Himalayan Bioresource Technology, Palampur, India" - }, - { - "author_name": "Narendra Tirpude", - "author_inst": "CSIR-Institute of Himalayan Bioresource Technology, Palampur, India" - }, - { - "author_name": "Partha Chakrabarti", - "author_inst": "CSIR-Indian Institute of Chemical Biology, Kolkata, India" - }, - { - "author_name": "Sujay Krishna Maity", - "author_inst": "CSIR-Indian Institute of Chemical Biology, Kolkata, India" - }, - { - "author_name": "Dipyaman Ganguly", - "author_inst": "CSIR-Indian Institute of Chemical Biology, Kolkata, India" - }, - { - "author_name": "Ramakrishna Sistla", - "author_inst": "CSIR-Indian Institute of Chemical Technology, Hyderabad, India" - }, - { - "author_name": "Narender Kumar Balthu", - "author_inst": "CSIR-Indian Institute of Chemical Technology, Hyderabad, India" - }, - { - "author_name": "Kiran Kumar A", - "author_inst": "CSIR-Indian Institute of Chemical Technology, Hyderabad, India" - }, - { - "author_name": "Siva Ranjith", - "author_inst": "CSIR-Indian Institute of Chemical Technology, Hyderabad, India" - }, - { - "author_name": "Vijay B Kumar", - "author_inst": "CSIR-Indian Institute of Chemical Technology, Hyderabad, India" - }, - { - "author_name": "Piyush Singh Jamwal", - "author_inst": "CSIR-Indian Institute of Integrative Medicine, Jammu, India" - }, - { - "author_name": "Anshu Wali", - "author_inst": "CSIR-Indian Institute of Integrative Medicine, Jammu, India" - }, - { - "author_name": "Sajad Ahmed", - "author_inst": "CSIR-Indian Institute of Integrative Medicine, Jammu, India" - }, - { - "author_name": "Rekha Chouhan", - "author_inst": "CSIR-Indian Institute of Integrative Medicine, Jammu, India" - }, - { - "author_name": "Sumit G Gandhi", - "author_inst": "CSIR-Indian Institute of Integrative Medicine, Jammu, India" - }, - { - "author_name": "Nancy Sharma", - "author_inst": "CSIR-Indian Institute of Integrative Medicine, Jammu, India" - }, - { - "author_name": "Garima Rai", - "author_inst": "CSIR-Indian Institute of Integrative Medicine, Jammu, India" - }, - { - "author_name": "Faisal Irshad", - "author_inst": "CSIR-Indian Institute of Integrative Medicine, Jammu, India" - }, - { - "author_name": "Vijay Lakshmi Jamwal", - "author_inst": "CSIR-Indian Institute of Integrative Medicine, Jammu, India" - }, - { - "author_name": "MasroorAhmad Paddar", - "author_inst": "CSIR-Indian Institute of Integrative Medicine, Jammu, India" - }, - { - "author_name": "Sameer Ullah Khan", - "author_inst": "CSIR-Indian Institute of Integrative Medicine, Jammu, India" - }, - { - "author_name": "Fayaz Malik", - "author_inst": "CSIR-Indian Institute of Integrative Medicine, Jammu, India" - }, - { - "author_name": "Debashish Ghosh", - "author_inst": "CSIR-Indian Institute of Petroleum, Dehradun, India" - }, - { - "author_name": "Ghanshyam Thakkar", - "author_inst": "CSIR-Indian Institute of Petroleum, Dehradun, India" - }, - { - "author_name": "Saroj K Barik", - "author_inst": "CSIR-National Botanical Research Institute, Lucknow , India" - }, - { - "author_name": "Prabhanshu Tripathi", - "author_inst": "CSIR-Indian Institute of Toxicology Research, Lucknow , India" - }, - { - "author_name": "Yatendra Kumar Satija", - "author_inst": "CSIR-Indian Institute of Toxicology Research, Lucknow , India" - }, - { - "author_name": "Sneha Mohanty", - "author_inst": "CSIR-Indian Institute of Toxicology Research, Lucknow , India" - }, - { - "author_name": "Md. Tauseef Khan", - "author_inst": "CSIR-Indian Institute of Toxicology Research, Lucknow , India" - }, - { - "author_name": "Umakanta Subudhi", - "author_inst": "CSIR-Institute of Minerals and Materials Technology, Bhubaneswar, India" - }, - { - "author_name": "Pradip Sen", - "author_inst": "CSIR-Institute of Microbial Technology, Chandigarh, India" - }, - { - "author_name": "Rashmi Kumar", - "author_inst": "CSIR-Institute of Microbial Technology, Chandigarh, India" - }, - { - "author_name": "Anshu Bhardwaj", - "author_inst": "CSIR-Institute of Microbial Technology, Chandigarh, India" - }, - { - "author_name": "Pawan Gupta", - "author_inst": "CSIR-Institute of Microbial Technology, Chandigarh, India" - }, - { - "author_name": "Deepak Sharma", - "author_inst": "CSIR-Institute of Microbial Technology, Chandigarh, India" - }, - { - "author_name": "Amit Tuli", - "author_inst": "CSIR-Institute of Microbial Technology, Chandigarh, India" - }, - { - "author_name": "Saumya Ray Chaudhuri", - "author_inst": "CSIR-Institute of Microbial Technology, Chandigarh, India" - }, - { - "author_name": "Srinivasan Krishnamurthi", - "author_inst": "CSIR-Institute of Microbial Technology, Chandigarh, India" - }, - { - "author_name": "Prakash L", - "author_inst": "CSIR- National Aerospace Laboratories, Bengaluru, India" - }, - { - "author_name": "Ch V Rao", - "author_inst": "CSIR-National Botanical Research Institute, Lucknow , India" - }, - { - "author_name": "B N Singh", - "author_inst": "CSIR-National Botanical Research Institute, Lucknow , India" - }, - { - "author_name": "Arvindkumar Chaurasiya", - "author_inst": "CSIR-National Chemical Laboratory, Pune, India" - }, - { - "author_name": "Meera Chaurasiyar", - "author_inst": "CSIR-National Chemical Laboratory, Pune, India" - }, - { - "author_name": "Mayuri Bhadange", - "author_inst": "CSIR-National Chemical Laboratory, Pune, India" - }, - { - "author_name": "Bhagyashree Likhitkar", - "author_inst": "CSIR-National Chemical Laboratory, Pune, India" - }, - { - "author_name": "Sharada Mohite", - "author_inst": "CSIR-National Chemical Laboratory, Pune, India" - }, - { - "author_name": "Yogita Patil", - "author_inst": "CSIR-National Chemical Laboratory, Pune, India" - }, - { - "author_name": "Mahesh Kulkarni", - "author_inst": "CSIR-National Chemical Laboratory, Pune, India" - }, - { - "author_name": "Rakesh Joshi", - "author_inst": "CSIR-National Chemical Laboratory, Pune, India" - }, - { - "author_name": "Vaibhav Pandya", - "author_inst": "CSIR-National Chemical Laboratory, Pune, India" - }, - { - "author_name": "Amita Patil", - "author_inst": "CSIR-National Chemical Laboratory, Pune, India" - }, - { - "author_name": "Rachel Samson", - "author_inst": "CSIR-National Chemical Laboratory, Pune, India" - }, - { - "author_name": "Tejas Vare", - "author_inst": "CSIR-National Chemical Laboratory, Pune, India" + "author_name": "Gilberto Gonzalez-Arroyo", + "author_inst": "Amphora Health" }, { - "author_name": "Mahesh Dharne", - "author_inst": "CSIR-National Chemical Laboratory, Pune, India" - }, - { - "author_name": "Ashok Giri", - "author_inst": "CSIR-National Chemical Laboratory, Pune, India" - }, - { - "author_name": "Shilpa Paranjape", - "author_inst": "CSIR-National Environmental Engineering Research Institute, Nagpur, India" - }, - { - "author_name": "G. Narahari Sastry", - "author_inst": "CSIR-North - East Institute of Science and Technology, Jorhat, India" - }, - { - "author_name": "Jatin Kalita", - "author_inst": "CSIR-North - East Institute of Science and Technology, Jorhat, India" - }, - { - "author_name": "Tridip Phukan", - "author_inst": "CSIR-North - East Institute of Science and Technology, Jorhat, India" - }, - { - "author_name": "Prasenjit Manna", - "author_inst": "CSIR-North - East Institute of Science and Technology, Jorhat, India" - }, - { - "author_name": "Wahengbam Romi", - "author_inst": "CSIR-North - East Institute of Science and Technology, Jorhat, India" - }, - { - "author_name": "Pankaj Bharali", - "author_inst": "CSIR-North - East Institute of Science and Technology, Jorhat, India" - }, - { - "author_name": "Dibyajyoti Ozah", - "author_inst": "CSIR-North - East Institute of Science and Technology, Jorhat, India" - }, - { - "author_name": "Ravi Kumar Sahu", - "author_inst": "CSIR-North - East Institute of Science and Technology, Jorhat, India" - }, - { - "author_name": "Prachurjya Dutta", - "author_inst": "CSIR-North - East Institute of Science and Technology, Jorhat, India" - }, - { - "author_name": "Moirangthem Goutam Singh", - "author_inst": "CSIR-North - East Institute of Science and Technology, Jorhat, India" - }, - { - "author_name": "Gayatri Gogoi", - "author_inst": "CSIR-North - East Institute of Science and Technology, Jorhat, India" - }, - { - "author_name": "Yasmin Begam Tapadar", - "author_inst": "CSIR-North - East Institute of Science and Technology, Jorhat, India" - }, - { - "author_name": "Elapavalooru VSSK Babu", - "author_inst": "CSIR- National Geophysical Research Institute, Hyderabad, India" - }, - { - "author_name": "Rajeev K Sukumaran", - "author_inst": "CSIR-National Institute for Interdisciplinary Science and Technology, Thiruvananthapuram, India" + "author_name": "Salvador Gomez Garcia", + "author_inst": "IMSS" }, { - "author_name": "Aishwarya R Nair", - "author_inst": "CSIR-National Institute for Interdisciplinary Science and Technology, Thiruvananthapuram, India" + "author_name": "Anel Gomez Garcia", + "author_inst": "IMSS" }, { - "author_name": "Anoop Puthiyamadam", - "author_inst": "CSIR-National Institute for Interdisciplinary Science and Technology, Thiruvananthapuram, India" + "author_name": "Adan Pacifuentes Orozco", + "author_inst": "IMSS" }, { - "author_name": "PrajeeshKooloth Valappil", - "author_inst": "CSIR-National Institute for Interdisciplinary Science and Technology, Thiruvananthapuram, India" + "author_name": "Felipe M Rodriguez-Moran", + "author_inst": "Amphora Health" }, { - "author_name": "Adrash Velayudhan Pillai Prasannakumari", - "author_inst": "CSIR-National Institute for Interdisciplinary Science and Technology, Thiruvananthapuram, India" + "author_name": "Maricela Garcia Arreola", + "author_inst": "IMSS" }, { - "author_name": "Kalpana Chodankar", - "author_inst": "CSIR- National Institute of Oceanography, Goa, India" + "author_name": "Karla Guadalupe Lopez Lopez", + "author_inst": "IMSS" }, { - "author_name": "Samir Damare", - "author_inst": "CSIR- National Institute of Oceanography, Goa, India" + "author_name": "Tonatihu Ortiz Castillo", + "author_inst": "IMSS" }, { - "author_name": "Ved Varun Agrawal", - "author_inst": "CSIR-National Physical Laboratory, New Delhi, India" + "author_name": "Noga Or-Geva", + "author_inst": "Stanford University" }, { - "author_name": "Kumardeep Chaudhary", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology, New Delhi, India" + "author_name": "Sonia Moreno-Grau", + "author_inst": "Stanford University" }, { - "author_name": "Anurag Agrawal", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology, New Delhi, India" + "author_name": "Cleto Alvarez Aguilar", + "author_inst": "IMSS" }, { - "author_name": "Shantanu Sengupta", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology, New Delhi, India" + "author_name": "Carlos D Bustamante", + "author_inst": "Stanford University" }, { - "author_name": "Debasis Dash", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology, New Delhi, India" + "author_name": "Arturo Lopez Pineda", + "author_inst": "Amphora Health" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "health informatics" }, @@ -452040,75 +450412,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.16.21267906", - "rel_title": "Workplace Contact Patterns in England during the COVID-19 Pandemic: Analysis of the Virus Watch prospective cohort study", + "rel_doi": "10.1101/2021.12.15.21267784", + "rel_title": "Change in the trend of long-term care service usage following COVID-19 pandemic in Japan: a survey using nationwide statistical summary in 2018-2021", "rel_date": "2021-12-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.16.21267906", - "rel_abs": "BackgroundWorkplaces are an important potential source of SARS-CoV-2 exposure; however, investigation into workplace contact patterns is lacking. This study aimed to investigate how workplace attendance and features of contact varied between occupations and over time during the COVID-19 pandemic in England.\n\nMethodsData were obtained from electronic contact diaries submitted between November 2020 and November 2021 by employed/self-employed prospective cohort study participants (n=4,616). We used mixed models to investigate the main effects and potential interactions between occupation and time for: workplace attendance, number of people in shared workspace, time spent sharing workspace, number of close contacts, and usage of face coverings.\n\nFindingsWorkplace attendance and contact patterns varied across occupations and time. The predicted probability of intense space sharing during the day was highest for healthcare (78% [95% CI: 75-81%]) and education workers (64% [59%-69%]), who also had the highest probabilities for larger numbers of close contacts (36% [32%-40%] and 38% [33%-43%] respectively). Education workers also demonstrated relatively low predicted probability (51% [44%-57%]) of wearing a face covering during close contact. Across all occupational groups, levels of workspace sharing and close contact were higher and usage of face coverings at work lower in later phases of the pandemic compared to earlier phases.\n\nInterpretationMajor variations in patterns of workplace contact and mask use are likely to contribute to differential COVID-19 risk. Across occupations, increasing workplace contact and reduced usage of face coverings presents an area of concern given ongoing high levels of community transmission and emergence of variants.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.15.21267784", + "rel_abs": "AimSocial restriction due to coronavirus disease 2019 (COVID-19) pandemic forced long-term care (LTC) service users to refrain from using services as before, of which degree of change we aim to evaluate in this study.\n\nMethodsWe retrospectively analyzed publicly-distributed nationwide statistics summarizing the monthly number of public LTC insurance users in Japan in the period between April 2018 and March 2021. The degree of decline was quantified as odds ratio (OR), where the ratio of a certain month to the reference month was divided by the ratio in the previous year.\n\nResultsThe use of LTC services showed unimodal serial change: it started to decline in March 2020 and reached its largest decline in May 2020, which had insufficiently recovered even as of late 2020. The degree of decline was specifically large in services provided in facilities for community-dwelling elderly individuals (adjusted OR 0.719 (95%CI: 0.664 [~] 0.777) in short-stay services and adjusted OR 0.876 (95%CI: 0.820 [~] 0.935) in outpatient services) but was non-significant in other types of service, including those provided for elderly individuals living in nursing homes.\n\nConclusionsCurrent study showed that community-dwelling elderly individuals who had used outpatient or short-stay services were the segments which were specifically affected by the COVID-19 pandemic in 2020 Japan. It underlines the need for further investigation for the medium- or long-term influence on the mental and physical health of these LTC service users as well as their family caregivers.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Sarah Beale", - "author_inst": "University College London" - }, - { - "author_name": "Susan J Hoskins", - "author_inst": "Univerity College London" - }, - { - "author_name": "Thomas Edward Byrne", - "author_inst": "University College London" - }, - { - "author_name": "Erica Wing Lam Fong", - "author_inst": "University College London" - }, - { - "author_name": "Ellen Fragaszy", - "author_inst": "University College London" - }, - { - "author_name": "Cyril Geismar", - "author_inst": "University College London" - }, - { - "author_name": "Jana Kovar", - "author_inst": "University College London" - }, - { - "author_name": "Annalan MD Navaratnam", - "author_inst": "University College London" - }, - { - "author_name": "Vincent Nguyen", - "author_inst": "University College London" - }, - { - "author_name": "Parth Patel", - "author_inst": "University College London" - }, - { - "author_name": "Alexei Yavlinsky", - "author_inst": "University College London" + "author_name": "Kenichiro Sato", + "author_inst": "University of Tokyo Hospital" }, { - "author_name": "Anne M Johnson", - "author_inst": "University College London" + "author_name": "Yoshiki Niimi", + "author_inst": "University of Tokyo Hospital" }, { - "author_name": "Robert W Aldridge", - "author_inst": "University College London" + "author_name": "Takeshi Iwatsubo", + "author_inst": "University of Tokyo" }, { - "author_name": "Andrew Hayward", - "author_inst": "University College London" + "author_name": "Shinya Ishii", + "author_inst": "Hiroshima University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "geriatric medicine" }, { "rel_doi": "10.1101/2021.12.16.21267902", @@ -454261,39 +452593,59 @@ "category": "pathology" }, { - "rel_doi": "10.1101/2021.12.14.472704", - "rel_title": "Simulation of the omicron variant of SARS-CoV-2 shows broad antibody escape, weakened ACE2 binding, and modest increase in furin binding", + "rel_doi": "10.1101/2021.12.15.21267793", + "rel_title": "Antibody-mediated Immunogenicity against SARS-CoV-2 following priming, boosting and hybrid immunity: insights from 11 months of follow-up of a healthcare worker cohort in Israel, December 2020-October 2021", "rel_date": "2021-12-15", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.14.472704", - "rel_abs": "The recent emergence of the omicron variant of the SARS-CoV-2 virus with large numbers of mutations has raised concern about a potential new surge in infections. Here we use molecular dynamics to study the biophysics of the interface of the omicron spike protein binding to (i) the ACE2 receptor protein, (ii) antibodies from all known binding regions, and (iii) the furin binding domain. Our simulations suggest that while there is significant reduction of antibody binding strength corresponding to escape, the omicron spike pays a cost in terms of weaker receptor binding. The furin cleavage domain is the same or weaker binding than the alpha variant, suggesting less viral load and disease intensity than the extant delta variant.", - "rel_num_authors": 5, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.15.21267793", + "rel_abs": "BackgroundWe determined circulating anti-S SARS-CoV-2 IgG antibody titres in a vaccinated healthcare workers (HCWs) cohort from Northern Israel in the 11 months following primary vaccination according to age, ethnicity, boosting timing and previous infection status.\n\nMethodsAll consenting HCWs were invited to have their circulating IgG levels measured before vaccination and at 6 subsequent timepoints. All HCWs with suspected COVID-19 were PCR tested. We described trends in circulating IgG geometric mean concentration by age, ethnicity, timing of boosting and previous infection status and compared strata using Kruskall-Wallis tests.\n\nResultsAmong 985 vaccinated HCWs. IgG titres gradually decreased in all groups over the study duration. Younger or previously infected individuals had higher initial IgG levels (p<0.001 in both cases); differences substantially decreased or disappeared at 7-9 months, before boosting. Pre-infection IgG levels in infected participants were similar to levels measured at the same timepoint in HCWs who remained uninfected (p>0.3). IgG GMC in those boosted 6-7 months after dose 2 was lower compared with those boosted 8-9 months after (1999-vs 2736, p=0.02).\n\nConclusionsImmunity waned 6 months post-priming in all age groups and in previously infected individuals, reversed by boosting. IgG titres decrease among previously infected individuals and the proportion of reinfected individuals in this group, comparable to the proportion of breakthrough infection in previously uninfected individuals suggests individuals with hybrid immunity (infection+vaccination) may also require further doses. Our study also highlights the difficulty in determining protective IgG levels and the need to clarify the optimal timing in 3 dose regimens", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Muhammad- Zaki Jawaid", - "author_inst": "University of California Davis" + "author_name": "Michael Edelstein", + "author_inst": "Ziv Medical Centre. Azrieli Faculty of Medicine, Bar Ilan University, Safed, Israel" }, { - "author_name": "Avinash Baidya", - "author_inst": "Department of Physics, UC Davis" + "author_name": "Karine Beiruti", + "author_inst": "Ziv Medical Centre, Safed, Israel" }, { - "author_name": "Rustin Mahboubi-Ardakani", - "author_inst": "Department of Physics, UC Davis" + "author_name": "Hila Ben Amram", + "author_inst": "Ziv Medical Centre, Safed,Israel" }, { - "author_name": "Richard L Davis", - "author_inst": "Protein Architects Corp." + "author_name": "Naor Bar Zeev", + "author_inst": "International Vaccine Access Center, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA" }, { - "author_name": "Daniel L Cox", - "author_inst": "University of California Davis" + "author_name": "Christian Sussan", + "author_inst": "Ziv Medical Centre, Safed, Israel" + }, + { + "author_name": "Hani Assulin", + "author_inst": "Ziv Medical Centre, Safed, Israel" + }, + { + "author_name": "David Strauss", + "author_inst": "Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel" + }, + { + "author_name": "Younes Bathish", + "author_inst": "Ziv Medical Centre. Azrieli Faculty of Medicine, Bar Ilan University, Safed, Israel" + }, + { + "author_name": "Salman Zarka", + "author_inst": "Ziv Medical Centre. Azrieli Faculty of Medicine, Bar Ilan University" + }, + { + "author_name": "Kamal Abu Jabal", + "author_inst": "Ziv Medical Centre. Azrieli Faculty of Medicine, Bar Ilan University" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "biophysics" + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.12.13.21267368", @@ -456551,27 +454903,39 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2021.12.13.21267732", - "rel_title": "Modelling the recovery of elective waiting lists following COVID-19: scenario projections for England", + "rel_doi": "10.1101/2021.12.12.21267573", + "rel_title": "The age-dependent immunogenicity after two doses of MVC-COV1901 vaccine.", "rel_date": "2021-12-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.13.21267732", - "rel_abs": "BackgroundA significant indirect impact of COVID-19 has been the increasing elective waiting times observed in many countries. In Englands National Health Service, the waiting list has grown from 4.4 million in February 2020 to 5.7m by August 2021.\n\nAimsThe objective of this study was to estimate the trajectory of future waiting list size and waiting times to December 2025.\n\nMethodsA scenario analysis was performed using computer simulation and publicly available data as of November 2021. Future demand assumed a phased return of various proportions (0, 25, 50 and 75%) of the estimated 7.1 million referrals missed during the pandemic. Future capacity assumed 90, 100 and 110% of that provided in the 12 months immediately before the pandemic.\n\nResultsAs a worst case, the waiting list would reach 13.6m (95% CI: 12.4m to 15.6m) by Autumn 2022, if 75% of missed referrals returned and only 90% of pre pandemic capacity could be achieved. Under this scenario, the proportion of patients waiting under 18 weeks would reduce from 67.6% in August 2021 to 42.2% (37.4% to 46.2%) with the number waiting over 52 weeks reaching 1.6m (0.8m to 3.1m) by Summer 2023. At this time, 29.0% (21.3% to 36.8%) of patients would be leaving the waiting list before treatment. Waiting lists would remain pressured under even the most optimistic of scenarios considered, with 18-week performance struggling to maintain 60% (against the 92% constitutional target).\n\nConclusionsThis study reveals the long-term challenge for the NHS in recovering elective waiting lists as well as potential implications for patient outcomes and experience.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.12.21267573", + "rel_abs": "A post-hoc analysis of the phase 2 data was performed for the SARS-COV-2 subunit protein vaccine MVC-COV1901. Anti-spike IgG, neutralization assays with live virus and pseudovirus were used to demonstrate age-dependent vaccine-induced antibody response to the vaccine. Results showed that an association exists between age and immune responses to the vaccine, providing further support for the need of booster shots, especially for the older age groups.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Nicholas C Howlett", - "author_inst": "Modelling and Analytics (BNSSG CCG), National Health Service" + "author_name": "Chia En Lien", + "author_inst": "Medigen Vaccine Biologics Corporation, Taipei, Taiwan" }, { - "author_name": "Richard M Wood", - "author_inst": "Modelling and Analytics (BNSSG CCG), National Health Service" + "author_name": "Yi-Jiun Lin", + "author_inst": "Medigen Vaccine Biologics Corporation, Taipei, Taiwan" + }, + { + "author_name": "Yi-Ling Lin", + "author_inst": "Institute of Biomedical Sciences and Biomedical Translation Research Centre, Academia Sinica, Taipei, Taiwan" + }, + { + "author_name": "I-Chen Tai", + "author_inst": "Medigen Vaccine Biologics Corporation, Taipei, Taiwan" + }, + { + "author_name": "Charles Chen", + "author_inst": "Medigen Vaccine Biologics Corporation, Taipei, Taiwan" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.10.21267574", @@ -458549,93 +456913,69 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.13.472352", - "rel_title": "CHARM: COVID-19 Health Action Response for Marines - association of antigen-specific interferon-gamma and IL2 responses with asymptomatic and symptomatic infections after a positive qPCR SARS-CoV-2 test", + "rel_doi": "10.1101/2021.12.13.472159", + "rel_title": "Mucosal and systemic responses to SARS-CoV-2 vaccination in infection naive and experienced individuals", "rel_date": "2021-12-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.13.472352", - "rel_abs": "SARS-CoV-2 T cell responses are associated with COVID-19 recovery, and Class I- and Class II-restricted epitopes have been identified in the spike (S), nucleocapsid (N) and membrane (M) proteins and others. This prospective COVID-19 Health Action Response for Marines (CHARM) study enabled assessment of T cell responses in symptomatic and asymptomatic SARS-CoV-2 infected participants.\n\nAt enrollment all participants were negative by qPCR; follow-up occurred biweekly and then bimonthly for the next 6 weeks. Study participants who tested positive by qPCR SARS-CoV-2 test were asked to enroll in an immune response sub-study. FluoroSpot interferon-gamma (IFN-{gamma}) and IL2 responses following qPCR-confirmed infection at enrollment (day 0), day 7 and 14 and more than 28 days later were measured using pools of 17mer peptides covering S, N, and M proteins, or CD4+CD8 peptide pools containing predicted epitopes from multiple SARS-CoV-2 antigens.\n\nAmong 124 asymptomatic and 105 symptomatic participants, SARS-CoV-2 infection generated IFN-{gamma} responses to the S, N and M proteins that persisted longer in asymptomatic cases. IFN-{gamma} responses were significantly (p=0.001) more frequent to the N pool (51.4%) than the M pool (18.9%) among asymptomatic subjects; however, the difference was not statistically significant (p=0.06) for symptomatic subjects (N pool: 44.4%; M pool: 25.9%). In asymptomatic participants IFN-{gamma} responders to the CD4+CD8 pool responded more frequently to the S pool (55.6%) and N pool (57.1%), than the M pool (7.1%), but symptomatic participants, IFN-{gamma} responses were more frequent to the S pool (75.0%) than N pool (33.3%) and M pool (33.3%). The frequencies of IFN-{gamma} responses to the S and N+M pools peaked 7 days after the positive qPCR test among asymptomatic (S pool: 22.2%; N+M pool: 28.7%) and symptomatic (S pool: 15.3%; N+M pool 21.9%) participants and dropped by >28 days. Magnitudes of post-infection IFN-{gamma} and IL2 responses to the N+M pool were significantly correlated with IFN-{gamma} and IL2 responses to the N and M pools.\n\nThese data further support the central role of Th1-biased cell mediated immunity IFN-{gamma} and IL2 responses, particularly to the N protein, in controlling COVID-19 symptoms, and justify T cell-based COVID-19 vaccines that include the N and S proteins.", - "rel_num_authors": 19, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.13.472159", + "rel_abs": "With much of the world infected with or vaccinated against SARS-CoV-2, understanding the immune responses to the SARS-CoV-2 spike (S) protein in different situations is crucial to controlling the pandemic. We studied the clinical, systemic, mucosal, and cellular responses to two doses of SARS-CoV-2 mRNA vaccines in 62 individuals with and without prior SARS-CoV-2 exposure that were divided into three groups based on serostatus and/or degree of symptoms: Antibody negative, Asymptomatic, and Symptomatic. In the previously SARS-CoV-2-infected (SARS2-infected) Asymptomatic and Symptomatic groups, symptoms related to a recall response were elicited after the first vaccination. Anti-S trimer IgA and IgG levels peaked after 1st vaccination in the SARS2-infected groups, and were higher that the in the SARS2-naive group in the plasma and nasal samples at all time points. Neutralizing antibodies titers were also higher against the WA-1 and B.1.617.2 (Delta) variants of SARS-CoV-2 in the SARS2-infected compared to SARS2-naive vaccinees. After the first vaccination, differences in cellular immunity were not evident between groups, but the AIM+ CD4+ cell response correlated with durability of humoral immunity against the SARS-CoV-2 S protein. In those SARS2-infected, the number of vaccinations needed for protection, the durability, and need for boosters are unknown. However, the lingering differences between the SARS2-infected and SARS2-naive up to 10 months post-vaccination could explain the decreased reinfection rates in the SARS2-infected vaccinees recently reported and suggests that additional strategies (such as boosting of the SARS2-naive vaccinees) are needed to narrow the differences observed between these groups.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Martha Sedegah", - "author_inst": "Naval Medical Research Center" - }, - { - "author_name": "Chad Porter", - "author_inst": "Naval Medical Research Center" - }, - { - "author_name": "Michael R. Hollingdale", - "author_inst": "Naval Medical Research Center" - }, - { - "author_name": "Harini Ganeshan", - "author_inst": "Naval Medical Research Center" - }, - { - "author_name": "Jun Huang", - "author_inst": "Naval Medical Research Center" - }, - { - "author_name": "Carl W. Goforth", - "author_inst": "Naval Medical Research Center" - }, - { - "author_name": "Maria Belmonte", - "author_inst": "Naval Medical Research Center" + "author_name": "Mohammad M. Sajadi", + "author_inst": "Institute of Human Virology at University of Maryland School of Medicine" }, { - "author_name": "Arnel Belmonte", - "author_inst": "Naval Medical Research Center" + "author_name": "Amber Myers", + "author_inst": "La Jolla Institute For Immunology (LJI)" }, { - "author_name": "Dawn L. Weir", - "author_inst": "Naval Medical Research Center" + "author_name": "James Logue", + "author_inst": "University of Maryland School of Medicine" }, { - "author_name": "Rhonda A. Lizewski", - "author_inst": "NAMRU-6" + "author_name": "Saman Saadat", + "author_inst": "Institute of Human Virology at University of Maryland School of Medicine" }, { - "author_name": "Stephen E. Lizewski", - "author_inst": "NAMRU-6" + "author_name": "Narjes Shokatpour", + "author_inst": "University of Maryland School of Medicine" }, { - "author_name": "Stuart C. Sealfon", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "James Quinn", + "author_inst": "La Jolla Institute For Immunology (LJI)" }, { - "author_name": "Vihasi Jani", - "author_inst": "Naval Medical Research Center" + "author_name": "Michelle Newman", + "author_inst": "University of Maryland School of Medicine" }, { - "author_name": "Ying Cheng", - "author_inst": "Naval Medical Research Center" + "author_name": "Meagan Deming", + "author_inst": "University of Maryland School of Medicine" }, { - "author_name": "Sandra Inoue", - "author_inst": "Naval Medical Research Center" + "author_name": "Zahra Rikhtegaran Tehrani", + "author_inst": "Institute of Human Virology at University of Maryland School of Medicine" }, { - "author_name": "Rachel Velasco", - "author_inst": "Naval Medical Research Center" + "author_name": "Maryam Karimi", + "author_inst": "Institute of Human Virology at University of Maryland School of Medicine" }, { - "author_name": "Eileen Villasante", - "author_inst": "Naval Medical Research Center" + "author_name": "Rahim Abbasi", + "author_inst": "Institute of Human Virology at University of Maryland School of Medicine" }, { - "author_name": "Peifang Sun", - "author_inst": "Naval Medical Research Center" + "author_name": "Shane Crotty", + "author_inst": "La Jolla Institute For Immunology (LJI)" }, { - "author_name": "Andrew Letizia", - "author_inst": "Naval Medical Research Center" + "author_name": "Anthony D. Harris", + "author_inst": "University of Maryland School of Medicine" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nd", "type": "new results", "category": "immunology" }, @@ -460287,67 +458627,43 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.12.12.21267646", - "rel_title": "Plasma neutralization properties of the SARS-CoV-2 Omicron variant", + "rel_doi": "10.1101/2021.12.13.472413", + "rel_title": "Inactivation of SARS-CoV-2 and influenza A virus by spraying hypochlorous acid solution and hydrogen peroxide solution in the form of Dry Fog", "rel_date": "2021-12-13", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.12.21267646", - "rel_abs": "BACKGROUNDThe Omicron SARS-CoV-2 variant has spread internationally and is responsible for rapidly increasing case numbers. The emergence of divergent variants in the context of a heterogeneous and evolving neutralizing antibody response in host populations might compromise protection afforded by vaccines or prior infection.\n\nMETHODSWe measured neutralizing antibody titers in 169 longitudinally collected plasma samples using pseudotypes bearing the Wuhan-hu-1 or the Omicron variant or a laboratory-designed neutralization-resistant SARS-CoV-2 spike (PMS20). Plasmas were obtained from convalescents who did or did not subsequently receive an mRNA vaccine, or naive individuals who received 3-doses of mRNA or 1-dose Ad26 vaccines. Samples were collected approximately 1, 5-6 and 12 months after initial vaccination or infection.\n\nRESULTSLike PMS20, the Omicron spike protein was substantially resistant to neutralization compared to Wuhan-hu-1. In convalescent plasma the median deficit in neutralizing activity against PMS20 or Omicron was 30- to 60-fold. Plasmas from recipients of 2 mRNA vaccine doses were 30- to 180- fold less potent against PMS20 and Omicron than Wuhan-hu-1. Notably, previously infected or two-mRNA dose vaccinated individuals who received additional mRNA vaccine dose(s) had 38 to 154-fold and 35 to 214-fold increases in neutralizing activity against Omicron and PMS20 respectively.\n\nCONCLUSIONSOmicron exhibits similar distribution of sequence changes and neutralization resistance as does a laboratory-designed neutralization-resistant spike protein, suggesting natural evolutionary pressure to evade the human antibody response. Currently available mRNA vaccine boosters, that may promote antibody affinity maturation, significantly ameliorate SARS-CoV-2 neutralizing antibody titers.", - "rel_num_authors": 12, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.13.472413", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), is transmitted by droplet and contact infection. SARS-CoV-2 that adheres to environmental surfaces remains infectious for several days. We herein attempted to inactivate SARS-CoV-2 and influenza A virus adhering to an environmental surface by spraying aerosolized hypochlorous acid solution and hydrogen peroxide solution in the form of Dry Fog (fog that does not wet objects even if touched). SARS-CoV-2 and influenza virus were dried on plastic plates and placed into a test chamber for inactivation by the Dry Fog spraying of disinfectants. The results obtained showed that Dry Fog spraying inactivated SARS-CoV-2 and influenza A virus in time- and exposed disinfectant amount-dependent manners. SARS-CoV-2 was more resistant to the virucidal effects of aerosolized hypochlorous acid solution and hydrogen peroxide solution than influenza A virus; therefore, higher concentrations of spray solutions were required to inactivate SARS-CoV-2 than influenza A virus. The present results provide important information for the development of a strategy that inactivates SARS-CoV-2 and influenza A virus on environmental surfaces by spatial spraying.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Fabian Schmidt", - "author_inst": "The Rockefeller University" - }, - { - "author_name": "Frauke Muecksch", - "author_inst": "The Rockefeller University" - }, - { - "author_name": "Yiska Weisblum", - "author_inst": "The Rockefeller University" - }, - { - "author_name": "Justin Da Silva", - "author_inst": "The Rockefeller University" - }, - { - "author_name": "Eva Bednarski", - "author_inst": "The Rockefeller University" + "author_name": "Masahiro Urushidani", + "author_inst": "H. Ikeuchi & Co., Ltd." }, { - "author_name": "Alice Cho", - "author_inst": "The Rockefeller University" - }, - { - "author_name": "Zijun Wang", - "author_inst": "The Rockefeller University" + "author_name": "Akira Kawayoshi", + "author_inst": "H. Ikeuchi & Co., Ltd." }, { - "author_name": "Christian Gaebler", - "author_inst": "The Rockefeller University" - }, - { - "author_name": "Marina Caskey", - "author_inst": "The Rockefeller University" + "author_name": "Tomohiro Kotaki", + "author_inst": "Osaka University: Osaka Daigaku" }, { - "author_name": "Michel Nussenzweig", - "author_inst": "The Rockefeller University" + "author_name": "Keiichi Saeki", + "author_inst": "Kobe University Faculty of Agriculture Graduate School of Agricultural Science: Kobe Daigaku Daigakuin Nogaku Kenkyuka Nogakubu" }, { - "author_name": "Theodora Hatziioannou", - "author_inst": "The Rockefeller University" + "author_name": "Yasuko Mori", + "author_inst": "Kobe University Graduate School of Medicine School of Medicine: Kobe Daigaku Daigakuin Igakukei Kenkyuka Igakubu" }, { - "author_name": "Paul Bieniasz", - "author_inst": "The Rockefeller University" + "author_name": "Masanori Kameoka", + "author_inst": "Kobe University Graduate School of Health Sciences" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2021.12.12.472286", @@ -462585,39 +460901,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.08.21267466", - "rel_title": "Aerosol emission rates from playing wind instruments -- Implications for COVID-19 transmission during music performance", + "rel_doi": "10.1101/2021.12.10.21267408", + "rel_title": "Adolescent vaccination with BNT162b2 (Comirnaty, Pfizer-BioNTech) vaccine and effectiveness of the first dose against COVID-19: national test-negative case-control study, England", "rel_date": "2021-12-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.08.21267466", - "rel_abs": "BackgroundThe pandemic of COVID-19 led to exceeding restrictions especially in public life and music business. Airborne transmission of SARS-CoV-2 demands for risk assessment also in wind playing situations. Previous studies focused on short-range transmission, whereas long-range transmission has not been assessed so far.\n\nMethods and findingsWe measured resulting aerosol concentrations in a hermetically closed cabin of 20 m3 in an operating theatre from 20 minutes standardized wind instrument playing (19 flute, 11 oboe, 1 clarinet, 1 trumpet players). Based on the data, we calculated total aerosol emission rates showing uniform distribution for both instrument groups (flute, oboe). Aerosol emission from wind instruments playing ranged from 7 {+/-} 327 particles/second (P/s) up to 2583 {+/-} 236 P/s, average rate {+/-} standard deviation. The analysis of the aerosol particle size distribution showed that about 70 - 80% of emitted particles had a size [≤] 0.4 {micro}m and thus being alveolar. Masking the bell with a surgical mask did not reduce aerosol emission. Aerosol emission rates were higher from wind instruments playing than from speaking and breathing. Differences between instrumental groups could not be found, but high interindividual variance as expressed by uniform distribution of aerosol emission rates.\n\nConclusionsOur findings indicate that aerosol emission depends on physiological factors and playing techniques rather than on the type of instrument, in contrast to some previous studies. Based on our results, we present risk calculations for long-range transmission of COVID-19 for three typical woodwind playing situations.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.10.21267408", + "rel_abs": "Adolescents in the UK were recommended to have their first dose of mRNA vaccine during a period of high community transmission due to the highly transmissible Delta variant, followed by a second dose at an extended interval of 8-12 weeks. We used national SARS-CoV-2 testing, vaccination and hospitalisation data to estimate vaccine effectiveness (VE) using a test-negative case-control design, against PCR-confirmed symptomatic COVID-19 in England. BNT162b2 vaccination in 12-15-year-olds and 16-17-year-olds was associated with lower VE against symptomatic COVID-19 caused by Omicron compared to Delta. Data shows a rapid increase in VE against symptomatic COVID-19 after the second dose for both Delta and Omicron, although this declines to 23% against Omicron after 70+ days. Very high protection was achieved for Delta against hospitalisation after one dose. Our data highlight the importance of the second vaccine dose for protection against symptomatic COVID-19 and raise important questions about the objectives of an adolescent immunisation programme. If prevention of infection is the primary aim, then regular COVID-19 vaccine boosters will be required.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Carl Firle", - "author_inst": "Park-Klinik Sophie Charlotte" + "author_name": "Annabel A Powell", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Anke Steinmetz", - "author_inst": "Physical and Rehabilitation Medicine, Clinic of Trauma, Reconstructive Surgery and Rehabilitation Medicine, University Medicine Greifswald, Greifswald, Germany" + "author_name": "Freja Kirsebom", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Oliver Stier", - "author_inst": "Siemens AG, Technology, 13623 Berlin, Germany" + "author_name": "Julia Stowe", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Dirk Stengel", - "author_inst": "Center for Clinical Research, BG Klinikum Unfallkrankenhaus Berlin gGmbH, Berlin, Germany and BG Kliniken, Hospital Group of the Statutory Accident Insurance, " + "author_name": "Kelsey McOwat", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Axel Ekkernkamp", - "author_inst": "Physical and Rehabilitation Medicine, Clinic of Trauma, Reconstructive Surgery and Rehabilitation Medicine, Uni. Med. Greifswald, Germany and Dep. of Trauma and" + "author_name": "Vanessa Saliba", + "author_inst": "UK Health Security Agency" + }, + { + "author_name": "Mary E Ramsay", + "author_inst": "UK Health Security Agency" + }, + { + "author_name": "Jamie Lopez Bernal", + "author_inst": "UK Health Security Agency" + }, + { + "author_name": "Nick Andrews", + "author_inst": "UK Health Security Agency" + }, + { + "author_name": "Shamez N Ladhani", + "author_inst": "UK Health Security Agency" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.12.10.21267338", @@ -464319,95 +462651,75 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.12.08.21267421", - "rel_title": "Vaccine hesitancy for COVID-19 explored in a phenomic study of 259 socio-cognitive-behavioural measures in the UK-REACH study of 12,431 UK healthcare workers", + "rel_doi": "10.1101/2021.12.08.471707", + "rel_title": "Delta breakthrough infections elicit potent, broad and durable neutralizing antibody responses", "rel_date": "2021-12-09", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.08.21267421", - "rel_abs": "BackgroundVaccination is key to successful prevention of COVID-19 particularly nosocomial acquired infection in health care workers (HCWs). Vaccine hesitancy is common in the population and in HCWs, and like COVID-19 itself, hesitancy is more frequent in ethnic minority groups. UK-REACH (United Kingdom Research study into Ethnicity and COVID-19 outcomes) is a large-scale study of COVID-19 in UK HCWs from diverse ethnic backgrounds, which includes measures of vaccine hesitancy. The present study explores predictors of vaccine hesitancy using a phenomic approach, considering several hundred questionnaire-based measures.\n\nMethodsUK-REACH includes a questionnaire study encompassing 12,431 HCWs who were recruited from December 2020 to March 2021 and completed a lengthy online questionnaire (785 raw items; 392 derived measures; 260 final measures). Ethnicity was classified using the Office for National Statistics five (ONS5) and eighteen (ONS18) categories. Missing data were handled by multiple imputation. Variable selection used the islasso package in R, which provides standard errors so that results from imputations could be combined using Rubins rules. The data were modelled using path analysis, so that predictors, and predictors of predictors could be assessed. Significance testing used the Bayesian approach of Kass and Raftery, a very strong Bayes Factor of 150, N=12,431, and a Bonferroni correction giving a criterion of p<4.02 x 10-8 for the main regression, and p<3.11 x 10-10 for variables in the path analysis.\n\nResultsAt the first step of the phenomic analysis, six variables were direct predictors of greater vaccine hesitancy: Lower pro-vaccination attitudes; no flu vaccination in 2019-20; pregnancy; higher COVID-19 conspiracy beliefs; younger age; and lower optimism the roll-out of population vaccination. Overall 44 lower variables in total were direct or indirect predictors of hesitancy, with the remaining 215 variables in the phenomic analysis not independently predicting vaccine hesitancy. Key variables for predicting hesitancy were belief in conspiracy theories of COVID-19 infection, and a low belief in vaccines in general. Conspiracy beliefs had two main sets of influences:\n\nO_LIHigher Fatalism, which was influenced a) by high external and chance locus of control and higher need for closure, which in turn were associated with neuroticism, conscientiousness, extraversion and agreeableness; and b) by religion being important in everyday life, and being Muslim.\nC_LIO_LIreceiving information via social media, not having higher education, and perceiving greater risks to self, the latter being influenced by higher concerns about spreading COVID, greater exposure to COVID-19, and financial concerns.\nC_LI\n\nThere were indirect effects of ethnicity, mediated by religion. Religion was more important for Pakistani and African HCWs, and less important for White and Chinese groups. Lower age had a direct effect on hesitancy, and age and female sex also had several indirect effects on hesitancy.\n\nConclusionsThe phenomic approach, coupled with a path analysis revealed a complex network of social, cognitive, and behavioural influences on SARS-Cov-2 vaccine hesitancy from 44 measures, 6 direct and 38 indirect, with the remaining 215 measures not having direct or indirect effects on hesitancy. It is likely that issues of trust underpin many associations with hesitancy. Understanding such a network of influences may help in tailoring interventions to address vaccine concerns and facilitate uptake in more hesistant groups.\n\nFundingUKMRI-MRC and NIHR", - "rel_num_authors": 19, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.08.471707", + "rel_abs": "The SARS-CoV-2 Delta variant is currently responsible for most infections worldwide, including among fully vaccinated individuals. Although these latter infections are associated with milder COVID-19 disease relative to unvaccinated subjects, the specificity and durability of antibody responses elicited by Delta breakthrough cases remain unknown. Here, we demonstrate that breakthrough infections induce serum binding and neutralizing antibody responses that are markedly more potent, durable and resilient to spike mutations observed in variants of concern than those observed in subjects who were infected only or received only two doses of COVID-19 vaccine. However, wee show that Delta breakthrough cases, subjects who were vaccinated after SARS-CoV-2 infection and individuals vaccinated three times (without infection) have serum neutralizing activity of comparable magnitude and breadth indicate that multiple types of exposure or increased number of exposures to SARS-CoV-2 antigen(s) enhance spike-specific antibody responses. Neutralization of the genetically divergent SARS-CoV, however, was moderate with all four cohorts examined, except after four exposures to the SARS-CoV-2 spike, underscoring the importance of developing vaccines eliciting broad sarbecovirus immunity for pandemic preparedness.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Chris McManus", - "author_inst": "University College London" - }, - { - "author_name": "Woolf Woolf", - "author_inst": "University College London" - }, - { - "author_name": "Christopher A Martin", - "author_inst": "University of Leicester; University Hospitals of Leicester NHS Trust" - }, - { - "author_name": "Laura B Nellums", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Anna L Guyatt", - "author_inst": "University of Leicester" - }, - { - "author_name": "Carl Melbourne", - "author_inst": "University of Leicester" + "author_name": "Alexandra C Walls", + "author_inst": "University of Washington" }, { - "author_name": "Luke Bryant", - "author_inst": "University of Leicester" + "author_name": "Kaitlin R Sprouse", + "author_inst": "University of Washington" }, { - "author_name": "Amit Gupta", - "author_inst": "Oxford University Hospitals NHS Foundation Trust" + "author_name": "Anshu Joshi", + "author_inst": "University of Washington" }, { - "author_name": "Catherine John", - "author_inst": "University of Leicester" + "author_name": "John E Bowen", + "author_inst": "University of Washington" }, { - "author_name": "Martin D Tobin", - "author_inst": "University of Leicester" + "author_name": "Nicholas Franko", + "author_inst": "University of Washington" }, { - "author_name": "Sue Carr", - "author_inst": "General Medical Council; University Hospitals Leicester NHS Trust" + "author_name": "Mary-Jane Navarro", + "author_inst": "University of Washington" }, { - "author_name": "Sandra Simpson", - "author_inst": "Nottinghamshire Healthcare NHS Foundation Trust" + "author_name": "Cameron Stewart", + "author_inst": "University of Washington" }, { - "author_name": "Bindu Gregary", - "author_inst": "Royal Preston Hospital" + "author_name": "Matthew McCallum", + "author_inst": "University of Washington" }, { - "author_name": "Avinash Aujayeb", - "author_inst": "Northumbria Specialist Emergency Care Hospital." + "author_name": "Erin A Goecker", + "author_inst": "University of Washington" }, { - "author_name": "Stephen Zingwe", - "author_inst": "Berkshire Healthcare NHS Foundation Trust." + "author_name": "Emily J Degli-Angeli", + "author_inst": "University of Washington" }, { - "author_name": "Rubina Reza", - "author_inst": "Derbyshire Healthcare NHS Foundation Trust" + "author_name": "Jenni Logue", + "author_inst": "University of Washington" }, { - "author_name": "Laura J Gray", - "author_inst": "University of Leicester" + "author_name": "Alex Greninger", + "author_inst": "University of Washington" }, { - "author_name": "Kamlesh Khunti", - "author_inst": "University of Leicester" + "author_name": "Helen Chu", + "author_inst": "University of Washington" }, { - "author_name": "Manish Pareek", - "author_inst": "University of Leicester; University Hospitals of Leicester NHS Trust" + "author_name": "David Veesler", + "author_inst": "University of Washington" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.12.07.471590", @@ -465901,91 +464213,59 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.12.07.471539", - "rel_title": "No evidence of fetal defects or anti-syncytin-1 antibody induction following COVID-19 mRNA vaccination", + "rel_doi": "10.1101/2021.12.06.471483", + "rel_title": "Intranasal immunization with a vaccinia virus vaccine vector expressing pre-fusion stabilized SARS-CoV-2 spike fully protected mice against lethal challenge with the heavily mutated mouse-adapted SARS2-N501YMA30 strain of SARS-CoV-2", "rel_date": "2021-12-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.07.471539", - "rel_abs": "The impact of coronavirus disease 2019 (COVID-19) mRNA vaccination on pregnancy and fertility has become a major topic of public interest. We investigated two of the most widely propagated claims to determine 1) whether COVID-19 mRNA vaccination of mice during early pregnancy is associated with an increased incidence of birth defects or growth abnormalities, and 2) whether COVID-19 mRNA-vaccinated human volunteers exhibit elevated levels of antibodies to the human placental protein syncytin-1. Using a mouse model, we found that intramuscular COVID-19 mRNA vaccination during early pregnancy at gestational age E7.5 did not lead to differences in fetal size by crown-rump length or weight at term, nor did we observe any gross birth defects. In contrast, injection of the TLR3 agonist and double-stranded RNA mimic polyinosinic-polycytidylic acid, or poly(I:C), impacted growth in utero leading to reduced fetal size. No overt maternal illness following either vaccination or poly(I:C) exposure was observed. We also found that term fetuses from vaccinated murine pregnancies exhibit high circulating levels of anti-Spike and anti-RBD antibodies to SARS-CoV-2 consistent with maternal antibody status, indicating transplacental transfer. Finally, we did not detect increased levels of circulating anti-syncytin-1 antibodies in a cohort of COVID-19 vaccinated adults compared to unvaccinated adults by ELISA. Our findings contradict popular claims associating COVID-19 mRNA vaccination with infertility and adverse neonatal outcomes.", - "rel_num_authors": 18, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.06.471483", + "rel_abs": "The Omicron SARS-CoV-2 variant has been designated a variant of concern because its spike protein is heavily mutated. In particular, Omicron spike is mutated at 5 positions (K417, N440, E484, Q493 and N501) that have been associated with escape from neutralizing antibodies induced by either infection with or immunization against the early Washington strain of SARS-CoV-2. The mouse-adapted strain of SARS-CoV-2, SARS2-N501YMA30, contains a spike that is also heavily mutated, with mutations at 4 of the 5 positions in Omicron spike associated with neutralizing antibody escape (K417, E484, Q493 and N501). In this manuscript we show that intranasal immunization with a pre-fusion stabilized Washington strain spike, expressed from a highly attenuated, replication-competent vaccinia virus construct, NYVAC-KC, fully protected mice against disease and death from SARS2-N501YMA30. Similarly, immunization by scarification on the skin fully protected against death, but not from mild disease. This data demonstrates that Washington strain spike, when expressed from a highly attenuated, replication-competent poxvirus, administered without parenteral injection can fully protect against the heavily mutated mouse-adapted SARS2-N501YMA30.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Alice Lu-Culligan", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Alexandra Tabachnikova", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Maria Tokuyama", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Hannah J Lee", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Carolina Lucas", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Valter Silva Monteiro", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "M. Catherine Muenker", - "author_inst": "Yale University" - }, - { - "author_name": "Subhasis Mohanty", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Jiefang Huang", - "author_inst": "Yale University School of Medicine" + "author_name": "Karen V Kibler", + "author_inst": "Arizona State University" }, { - "author_name": "Insoo Kang", - "author_inst": "Yale University School of Medicine" + "author_name": "Mateusz Szczerba", + "author_inst": "Arizona State University" }, { - "author_name": "Charles Dela Cruz", - "author_inst": "Yale University School of Medicine" + "author_name": "Douglas F. Lake", + "author_inst": "Arizona State University" }, { - "author_name": "Shelli Farhadian", - "author_inst": "Yale University School of Medicine" + "author_name": "Alexa J Roeder", + "author_inst": "Arizona State University" }, { - "author_name": "Melissa Campbell", - "author_inst": "Yale University School of Medicine" + "author_name": "Masmudur Rahman", + "author_inst": "Arizona State University" }, { - "author_name": "Inci Yildirim", - "author_inst": "Yale University School of Medicine" + "author_name": "Brenda G Hogue", + "author_inst": "Arizona State University" }, { - "author_name": "Albert Shaw", - "author_inst": "Yale University School of Medicine" + "author_name": "Lok Yin Roy Wong", + "author_inst": "University of Iowa" }, { - "author_name": "Albert Ko", - "author_inst": "Yale University" + "author_name": "Stanley Perlman", + "author_inst": "University of Iowa" }, { - "author_name": "Saad Omer", - "author_inst": "Yale University" + "author_name": "Yize Li", + "author_inst": "Arizona State University" }, { - "author_name": "Akiko Iwasaki", - "author_inst": "Yale University School of Medicine" + "author_name": "Bertram L Jacobs", + "author_inst": "Arizona State University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.12.06.471215", @@ -468023,27 +466303,23 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2021.12.04.471200", - "rel_title": "Omicron: A heavily mutated SARS-CoV-2 variant exhibits stronger binding to ACE2 and potently escape approved COVID-19 therapeutic antibodies", + "rel_doi": "10.1101/2021.12.04.471246", + "rel_title": "The High Transmission of SARS-CoV-2 Omicron (B.1.1.529) Variant is Not Only Due to Its hACE2 binding: A Free Energy of Perturbation Study", "rel_date": "2021-12-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.04.471200", - "rel_abs": "The new SARS-CoV-2 variant of concern \"Omicron\" was recently (Nov. 24th. 2021) spotted in South Africa and already spread around the world due to its enhanced transmissibility. The variant became conspicuous as it harbors more than thirty mutations in the spike protein with 15 mutations in the RBD region alone, potentially dampening the potency of therapeutic antibodies and enhancing the ACE2 binding. More worrying, Omicron infections have been reported in individuals who have received vaccines jabs in South Africa and Hong Kong. Here, we investigated the binding strength of Omicron with ACE2 and seven monoclonal antibodies that are either approved by FDA for COVID-19 therapy or undergoing phase III clinical trials. Computational mutagenesis and binding free energies could confirm that Omicron Spike binds ACE2 stronger than prototype SARS-CoV-2. Notably, three substitutions, i.e., T478K, Q493K, and Q498R, significantly contribute to the binding energies and doubled electrostatic potential of the RBDOmic-ACE2 complex. Instead of E484K substitution that helped neutralization escape of Beta, Gamma, and Mu variants, Omicron harbors E484A substitution. Together, T478K, Q493K, Q498R, and E484A substitutions contribute to a significant drop in the electrostatic potential energies between RBDOmic-mAbs, particularly in Etesevimab, Bamlanivimab, and CT-p59. CDR diversification could help regain the neutralization strength of these antibodies; however, we could not conduct this analysis to this end. Conclusively, our findings suggest that Omicron binds ACE2 with greater affinity, enhancing its infectivity and transmissibility. Mutations in the Spike are prudently devised by the virus that enhances the receptor binding and weakens the mAbs binding to escape the immune response.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.04.471246", + "rel_abs": "The mutations in the spike protein of SARS-CoV-2 Omicron variant (B.1.1.529 lineage) gave rise to questions, but the data on the mechanism of action at the molecular level is limited. In this study, we present the Free energy of perturbation (FEP) data about the RBD-hACE2 binding of this new variant.\n\nWe identified two groups of mutations located close to the most contributing substitutions Q498R and Q493R, which altered significantly the RBD-hACE2 interactions. The Q498R, Y505H and G496S mutations, in addition to N501Y, highly increased the binding to hACE2. They enhanced the binding by 98, 14 and 13 folds, respectively, which transforms the S1-RBD to a picomolar binder. However, in contrast to the case in mice the Q493R/K mutations, in a combination with K417N and T478K, dramatically reduced the S1 RBD binding by over 100 folds. The N440K, G446S and T478K substitutions had lesser contribution. Thus, the total effect of these nine mutations located on the interaction surface of RBD-hACE2 turns out to be similar to that observed in the Alpha variant. In a special circumstances it could be further altered by the E484A and S477N mutations and even lower binding capacity is likely to be detected. Finally, we provide a structural basis of the observed changes in the interactions.\n\nThese data may explain only partially the observed in South Africa extremely high Omicron spread and is in support to the hypothesis for multiple mechanisms of actions involved in the transmission.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC=\"FIGDIR/small/471246v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (64K):\norg.highwire.dtl.DTLVardef@144d901org.highwire.dtl.DTLVardef@10310e7org.highwire.dtl.DTLVardef@4ac7dborg.highwire.dtl.DTLVardef@1870231_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Hyun Goo Woo", - "author_inst": "Ajou University" - }, - { - "author_name": "Masaud Shah", - "author_inst": "Department of Physiology, Ajou University School of Medicine, Suwon, Republic of Korea" + "author_name": "Filip Fratev", + "author_inst": "Micar Innovation (Micar21)" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", - "category": "genomics" + "category": "biochemistry" }, { "rel_doi": "10.1101/2021.12.05.471290", @@ -469649,33 +467925,85 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.12.05.21267319", - "rel_title": "Beyond well-mixed: a simple probabilistic model of airborne disease transmission in indoor spaces", + "rel_doi": "10.1101/2021.11.29.21267000", + "rel_title": "A One-Step open RT-qPCR for SARS-CoV-2 detection", "rel_date": "2021-12-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.05.21267319", - "rel_abs": "We develop a simple model for assessing risk of airborne disease transmission that accounts for non-uniform mixing in indoor spaces and is compatible with existing epidemiological models. A database containing 174 high-resolution simulations of airflow in classrooms, lecture halls, and buses is generated and used to quantify the spatial distribution of expiratory droplet nuclei for a wide range of ventilation rates, exposure times, and room configurations. Imperfect mixing due to obstructions, buoyancy, and turbulent dispersion results in concentration fields with significant variance. The spatial non-uniformity is found to be accurately described by a shifted lognormal distribution. A well-mixed mass balance model is used to predict the mean, and the standard deviation is parameterized based on ventilation rate and room geometry. When employed in a dose-response function risk model, infection probability can be estimated considering spatial heterogeneity that contributes to both short- and long-range transmission.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.29.21267000", + "rel_abs": "The COVID-19 pandemic has resulted in millions of deaths globally, and while several diagnostic systems were proposed, real-time reverse transcription polymerase chain reaction (RT-PCR) remains the gold standard. However, diagnostic reagents, including enzymes used in RT-PCR, are subject to centralized production models and intellectual property restrictions, which present a challenge for less developed countries. With the aim of generating a standardized One-Step open RT-qPCR protocol to detect SARS-CoV-2 RNA in clinical samples, we purified and tested recombinant enzymes and a non-proprietary buffer. The protocol utilized M-MLV RT and Taq DNA pol enzymes to perform a Taqman probe-based assay. Synthetic RNA samples were used to validate the One-Step RT-qPCR components, and the kit showed comparable sensitivity to approved commercial kits. The One-Step RT-qPCR was then tested on clinical samples and demonstrated similar performance to commercial kits in terms of positive and negative calls. This study represents a proof of concept for an open approach to developing diagnostic kits for viral infections and diseases, which could provide a cost-effective and accessible solution for less developed countries.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Sijian Tan", - "author_inst": "University of Michigan" + "author_name": "Ariel Cerda", + "author_inst": "ANID - Millennium Science Initiative Program - Millennium Institute for Integrative Biology (iBio)" }, { - "author_name": "Zhihang Zhang", - "author_inst": "University of Michigan" + "author_name": "Maira Rivera", + "author_inst": "ANID - Millennium Science Initiative Program - Millennium Institute for Integrative Biology (iBio)" }, { - "author_name": "Kevin J. Maki", - "author_inst": "University of Michigan" + "author_name": "Grace Armijo", + "author_inst": "ANID - Millennium Science Initiative Program - Millennium Institute for Integrative Biology (iBio)" }, { - "author_name": "Krzysztof J. Fidkowski", - "author_inst": "University of Michigan" + "author_name": "Catalina Ibarra", + "author_inst": "ANID - Millennium Science Initiative Program - Millennium Institute for Integrative Biology (iBio)" }, { - "author_name": "Jesse Capecelatro", - "author_inst": "University of Michigan" + "author_name": "Javiera Reyes", + "author_inst": "ANID - Millennium Science Initiative Program - Millennium Institute for Integrative Biology (iBio)" + }, + { + "author_name": "Paula Blazquez-Sanchez", + "author_inst": "ANID - Millennium Science Initiative Program - Millennium Institute for Integrative Biology (iBio)" + }, + { + "author_name": "Javiera Aviles", + "author_inst": "ANID - Millennium Science Initiative Program - Millennium Institute for Integrative Biology (iBio)" + }, + { + "author_name": "Anibal Arce", + "author_inst": "ANID - Millennium Science Initiative Program - Millennium Institute for Integrative Biology (iBio)" + }, + { + "author_name": "Aldo Seguel", + "author_inst": "ANID - Millennium Science Initiative Program - Millennium Institute for Integrative Biology (iBio)" + }, + { + "author_name": "Alexander J Brown", + "author_inst": "Department of Biomedical Research, National Jewish Health, Denver, CO, USA" + }, + { + "author_name": "Yesseny Vasquez", + "author_inst": "Escuela de Ciencias Medicas. Facultad de Medicina. Universidad de Santiago de Chile. USACH, Santiago, Chile." + }, + { + "author_name": "Marcelo Cortez-San Martin", + "author_inst": "Departamento de Biologia, Facultad de Quimica y Biologia, Universidad de Santiago de Chile, USACH, Santiago, Chile." + }, + { + "author_name": "Francisco Cubillos", + "author_inst": "ANID - Millennium Science Initiative Program - Millennium Institute for Integrative Biology (iBio)" + }, + { + "author_name": "Patricia Garcia", + "author_inst": "Departamento de Laboratorios Clinicos. Escuela de Medicina. Facultad de Medicina. Pontificia Universidad Catoolica de Chile, Santiago, Chile" + }, + { + "author_name": "Marcela Ferres", + "author_inst": "Departamento de Laboratorios Clinicos. Escuela de Medicina. Facultad de Medicina. Pontificia Universidad Catolica de Chile, Santiago, Chile" + }, + { + "author_name": "Cesar A. Ramirez-Sarmiento", + "author_inst": "Pontificia Universidad Catolica de Chile; ANID - Millennium Science Initiative Program - Millennium Institute for Integrative Biology (iBio)" + }, + { + "author_name": "Fernan Federici", + "author_inst": "Pontificia Universidad Catolica de Chile; ANID - Millennium Science Initiative Program - Millennium Institute for Integrative Biology (iBio)" + }, + { + "author_name": "Rodrigo Gutierrez", + "author_inst": "Pontificia Universidad Catolica de Chile; ANID - Millennium Science Initiative Program - Millennium Institute for Integrative Biology (iBio)" } ], "version": "1", @@ -471543,183 +469871,87 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.02.21267198", - "rel_title": "Ad26.COV2.S or BNT162b2 Boosting of BNT162b2 Vaccinated Individuals", + "rel_doi": "10.1101/2021.12.03.21267036", + "rel_title": "Mucosal memory T cells in breastmilk are modulated by SARS-CoV-2 mRNA vaccination", "rel_date": "2021-12-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.02.21267198", - "rel_abs": "The rapid spread of the highly mutated SARS-CoV-2 Omicron variant has raised substantial concerns about the protective efficacy of currently available vaccines. We assessed Omicron-specific humoral and cellular immune responses in 65 individuals who were vaccinated with two immunizations of BNT162b2 and were boosted after at least 6 months with either Ad26.COV2.S (Johnson & Johnson; N=41) or BNT162b2 (Pfizer; N=24) (Table S1).\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@41c8baorg.highwire.dtl.DTLVardef@e14f5forg.highwire.dtl.DTLVardef@21ea87org.highwire.dtl.DTLVardef@ac4522org.highwire.dtl.DTLVardef@1eed52b_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable S1.C_FLOATNO O_TABLECAPTIONCharacteristics of the study population\n\nC_TABLECAPTION C_TBL", - "rel_num_authors": 41, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.03.21267036", + "rel_abs": "Human breastmilk is rich in T cells; however, their specificity and function are largely unknown. We compared the phenotype, diversity, and antigen specificity of T cells in the breastmilk and peripheral blood of lactating individuals who received SARS-CoV-2 mRNA vaccination. Relative to blood, breastmilk contained higher frequencies of T effector and central memory populations that expressed mucosal-homing markers. T cell receptor (TCR) sequence overlap was limited between blood and breastmilk. Overabundan t breastmilk clones were observed in all individuals, were diverse, and contained CDR3 sequences with known epitope specificity including to SARS-CoV-2 Spike. Spike-specific TCRs were more frequent in breastmilk compared to blood and expanded in breastmilk following a third mRNA vaccine dose. Our observations indicate that the lactating breast contains a distinct T cell population that can be modulated by maternal vaccination with potential implications for infant passive protection.\n\nOne-Sentence SummaryThe breastmilk T cell repertoire is distinct and enriched for SARS-CoV-2 Spike-specificity after maternal mRNA vaccination.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "C. Sabrina Tan", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Ai-ris Collier", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Jinyan Liu", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Jingyou Yu", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Abishek Chandrashekar", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Katherine McMahan", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Huahua Wan", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Xuan He", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Catherine Jacob-Dolan", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Daniel Sellers", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "John Ventura", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Yannic Bartsch", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" - }, - { - "author_name": "Blake Hauser", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" - }, - { - "author_name": "Jennifer Munt", - "author_inst": "University of North Carolina" - }, - { - "author_name": "Melissa Mattocks", - "author_inst": "University of North Carolina" - }, - { - "author_name": "Kathryn Stephenson", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Samuel Vidal", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Kate Jaegle", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Marjorie Rowe", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Rachel Hemod", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Lorriane Bermudez Rivera", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Tochi Anioke", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Julia Barrett", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Benjamin Chung", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Sarah Gardner", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Blair Armistead", + "author_inst": "Seattle Children's Research Institute" }, { - "author_name": "Makda Gebre", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Yonghou Jiang", + "author_inst": "Seattle Children's Research Institute" }, { - "author_name": "Nicole Hachmann", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Marc Carlson", + "author_inst": "Seattle Children's Research Institute" }, { - "author_name": "Michelle Lifton", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Emily S Ford", + "author_inst": "FHCRC" }, { - "author_name": "Jessica Miller", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Saumya Jani", + "author_inst": "University of Washington" }, { - "author_name": "Felix Nampanya", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "John Houck", + "author_inst": "Seattle Children's Research Institute" }, { - "author_name": "Olivia Powers", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Xia Wu", + "author_inst": "University of Washington" }, { - "author_name": "Michaela Sciacca", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Lichen Jing", + "author_inst": "University of Washington" }, { - "author_name": "Mazuba Siamatu", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Tiffany Pecor", + "author_inst": "Seattle Children's Research Institute" }, { - "author_name": "Nehalee Surve", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Alisa Kachikis", + "author_inst": "University of Washington" }, { - "author_name": "Lisa Tostanoski", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Winnie Yeung", + "author_inst": "Seattle Children's Research Institute" }, { - "author_name": "Haley VanWyk", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Tina Nguyen", + "author_inst": "Seattle Children's Research Institute" }, { - "author_name": "Cindy Wu", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Nana Minkah", + "author_inst": "Seattle Children's Research Institute" }, { - "author_name": "Ralph S. Baric", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Sasha E Larsen", + "author_inst": "Seattle Children's Research Institute" }, { - "author_name": "Aaron Schmidt", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Rhea N Coler", + "author_inst": "University of Washington" }, { - "author_name": "Galit Alter", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "David M Koelle", + "author_inst": "University of Washington" }, { - "author_name": "Dan Barouch", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Whitney E Harrington", + "author_inst": "University of Washington" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2021.12.03.21267281", @@ -473389,61 +471621,65 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.12.02.21266765", - "rel_title": "The impact of the COVID-19 pandemic on children with medical complexity", + "rel_doi": "10.1101/2021.12.02.21266778", + "rel_title": "Disruptions in Care: Consequences of the COVID-19 Pandemic in a Children's Hospital", "rel_date": "2021-12-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.02.21266765", - "rel_abs": "BackgroundDescriptions of the COVID-19 pandemics indirect consequences on children are emerging. We aimed to describe the impacts of the pandemic on children with medical complexity (CMC) and their families.\n\nMethodsA one-time survey of Canadian paediatricians using the Canadian Paediatric Surveillance Program (CPSP) was conducted in Spring 2021.\n\nResultsA total of 784 paediatricians responded to the survey, with 70% (n=540) providing care to CMC. Sixty-seven (12.4%) reported an adverse health outcome due to a COVID-19 pandemic-related disruption in healthcare delivery. Disruption of the supply of medication and equipment was reported by 11.9% of respondents (n=64). Respondents reported an interruption in family caregiving (47.5%, n=252) and homecare delivery (40.8%, n=218). Almost 47% of respondents (n=253) observed a benefit to CMC due to COVID-19 related changes in healthcare delivery, including increased availability of virtual care and reduction in respiratory illness. Some (14.4%) reported that CMC were excluded from in-person learning when their peers without medical complexity were not.\n\nConclusionCanadian paediatricians reported that CMC experienced adverse health outcomes during the COVID-19 pandemic, including disruptions to family caregiving and community supports. These results highlight the need for healthcare, community and education policymakers to collaborate with families to optimize their health.\n\n\"What This Study Adds\"O_LIChildren with medical complexity experienced adverse health outcomes related to the direct and indirect effects of the COVID-19 pandemic.\nC_LIO_LIThe COVID-19 pandemic has interrupted family caregiving, homecare support, access to education, and key supports for CMC and their families.\nC_LIO_LICanadian paediatricians observed benefits associated with structural changes relating to the COVID-19 pandemic, including the expansion of virtual care and the reduced incidence of respiratory illness\nC_LI", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.02.21266778", + "rel_abs": "BackgroundPublic health restrictions are an essential strategy to prevent the spread of COVID-19; however, unintended consequences of these interventions may have led to significant delays, deferrals and disruptions in medical care. This study explores clinical cases where the care of children was perceived to have been negatively impacted as a result of public health measures and changes in healthcare delivery and access due to the COVID-19 pandemic.\n\nMethodsThis study used a qualitative multiple case study design with descriptive thematic analysis of clinician-reported consequences of the COVID-19 pandemic on care provided at a childrens hospital. A quantitative analysis of overall hospital activity data during the study period was performed.\n\nResultsThe COVID-19 pandemic has resulted in significant change to hospital activity at our tertiary care hospital, including an initial reduction in Emergency Department attendance by 38% and an increase in ambulatory virtual care from 4% before COVID-19, to 67% in August, 2020. Two hundred and twelve clinicians reported a total of 116 unique cases. Themes including (1) timeliness of care, (2) disruption of patient-centered care, (3) new pressures in the provision of safe and efficient care and (4) inequity in the experience of the COVID-19 pandemic emerged, each impacting patients, their families and healthcare providers.\n\nConclusionBeing aware of the breadth of the impact of the COVID-19 pandemic across all of the identified themes is important to enable the delivery of timely, safe, high-quality, family-centred pediatric care moving forward.\n\nWhats newCOVID-19 disrupted typical paediatric care delivery.\n\nThis study demonstrates the breadth of its impact on the delivery of timely, safe, equitable and patient and family centered care, highlighting considerations for paediatric providers as we move forward.", + "rel_num_authors": 13, "rel_authors": [ { "author_name": "Catherine Diskin", "author_inst": "The Hospital for Sick Children" }, { - "author_name": "Francine Buchanan", + "author_name": "Julia Orkin", "author_inst": "The Hospital for Sick Children" }, { - "author_name": "Eyal Cohen", - "author_inst": "The Hospital for Sick Children" + "author_name": "Blossom Dharmaraj", + "author_inst": "Hospital for Sick Children" }, { - "author_name": "Tammie Dewan", - "author_inst": "Alberta 'Children's Hospital, University of Calgary, Calgary" + "author_name": "Tanvi Agarwal", + "author_inst": "Hospital for Sick Children" + }, + { + "author_name": "Arpita Parmar", + "author_inst": "The Hospital for Sick Children" }, { - "author_name": "Tessa Diaczun", - "author_inst": "BCChildren's Hospital" + "author_name": "Kelly Mc Naughton", + "author_inst": "The Hospital for Sick Children" }, { - "author_name": "Michelle Gordon", - "author_inst": "Orillia Soldiers Memorial Hospital" + "author_name": "Eyal Cohen", + "author_inst": "The Hospital for Sick Children" }, { - "author_name": "Esther Lee", - "author_inst": "BCChildrens Hospital" + "author_name": "Alia Sunderji", + "author_inst": "The Hospital for Sick Children" }, { - "author_name": "Charlotte Moore Hepburn", + "author_name": "David Faraoni", "author_inst": "The Hospital for Sick Children" }, { - "author_name": "Nathalie Major", - "author_inst": "Children's Hospital of Eastern Ontario" + "author_name": "Annie Fecteau", + "author_inst": "The Hospital for Sick Children" }, { - "author_name": "Julia Orkin", + "author_name": "Jason Fischer", "author_inst": "The Hospital for Sick Children" }, { - "author_name": "Hema Patel", - "author_inst": "Montreal Children's Hospital" + "author_name": "Sanjay Mahant", + "author_inst": "The Hospital for SickChildren" }, { - "author_name": "Peter Gill", - "author_inst": "Hospital for Sick Children" + "author_name": "Jeremy Friedman", + "author_inst": "The Hospital for Sick Children" } ], "version": "1", @@ -475243,39 +473479,23 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2021.11.29.21267025", - "rel_title": "Inexpensive and colorimetric RNA detection by E. coli cell-free protein synthesis platform at room temperature", + "rel_doi": "10.1101/2021.11.30.21267086", + "rel_title": "Rapid Clinical Screening and Staging for COVID-19 Severe Outcome - A Hospitalization Study in New York City", "rel_date": "2021-12-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.29.21267025", - "rel_abs": "We report colorimetric detection of SARS-CoV-2 viral RNA by an in vitro transcription/translation assay with crude E. coli extracts at room temperature, with the aid of body heat. Clinically-relevant concentrations of viral RNA (ca. 600 copies/test) were detected from synthetic RNA samples. The activation of cell-free gene expression was achieved by toehold-switch-mediated riboregulatory elements that are specific to viral RNA sequences. The colorimetric output was generated by the -complementation of {beta}-galactosidase {omega}-fragment (LacZ{omega}) with cell-free expressed LacZ, using an X-gal analogue as a substrate. The estimated cost of single reaction is <{euro}1/test, which may facilitate diagnostic kit accessibility in developing countries.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.30.21267086", + "rel_abs": "BackgroundWe aimed to evaluate the risk factors for Coronavirus disease 2019 (COVID-19) related severe outcome in New York State (NYS) and proposed a method that could be used to inform future work to develop clinical algorithms and predict resource needs for COVID-19 patients.\n\nMethodsWe analyzed COVID-19 related hospital encounter and hospitalization in NYS from April 1st to November 17th, 2020, using Statewide Planning and Research Cooperative System (SPARCS) hospital discharge dataset. Logistic regression was performed to evaluate the risk factors for COVID-19 related in-hospital death using demographic variables, symptom, rapid clinical examination, and medical history of chronic co-morbid conditions. Receiver operating characteristic (ROC) curve was calculated, and cut-off points for predictors were selected to stage the risk of COVID-19 related fatal outcome.\n\nFindingsLogistic regression analysis showed age was the greatest risk factor for COVID-19 related fatal outcome, which by itself achieved the diagnostic accuracy of 0.78 represented by the area under the ROC curve. By adding other demographic variables, dyspnea or hypoxemia and multiple chronic co-morbid conditions, the diagnostic accuracy was improved to 0.85. We selected cut-off points for predictors and provided a general recommendation to categorize the levels of risk for COVID-19 related fatal outcome.\n\nInterpretationWe assessed risk factors associated with in-hospital COVID-19 mortality and identified cut-off points that might be used to categorize the level of risk. Further studies are warranted to evaluate laboratory tests and develop laboratory biomarkers to improve the diagnostic accuracy for early intervention.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Michela Notarangelo", - "author_inst": "University of Trento" - }, - { - "author_name": "Alessandro Quattrone", - "author_inst": "University of Trento" - }, - { - "author_name": "Massimo Pizzato", - "author_inst": "University of Trento" - }, - { - "author_name": "Sheref S. Mansy", - "author_inst": "University of Alberta" - }, - { - "author_name": "O. Duhan Toparlak", - "author_inst": "University of Trento" + "author_name": "Chaorui C Huang", + "author_inst": "New York City Department of Health and Mental Hygiene" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.02.21267185", @@ -476885,83 +475105,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.11.30.21250895", - "rel_title": "Coping with COVID-19 Stressors: Adverse and Protective Factors Responding to Emotions in a Chinese Sample", + "rel_doi": "10.1101/2021.11.29.21266847", + "rel_title": "Population level impact of a pulse oximetry remote monitoring programme on mortality and healthcare utilisation in the people with covid-19 in England: a national analysis using a stepped wedge design", "rel_date": "2021-11-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.30.21250895", - "rel_abs": "BackgroundThe potential roles of affective responses to environmental stressors in individuals physical and mental health are complex and multi-faceted. This study, then, explores Chinese citizens emotional responses to COVID-19-related stressors and influence factors which may boost or buffer such effects.\n\nMethodsFrom late March to early June (2020), a cross-sectional study was conducted using an anonymous online questionnaire included demographic characteristics, COVID-19-related stressors related to individuals daily functioning, and the self-assessed impact of protective and adverse internal factors on emotions.\n\nResults1,662 questionnaires were received from residents in 32 Chinese provinces classified by prevalence level according to COVID-19 infections. Among the 17 positive and negative emotional responses, agglomerative hierarchical clustering revealed four subclassifications: (1) stress relations; (2) missing someone relations; (3) individual relations; and (4) social relations. Additionally, heightened regional prevalence levels positively corresponded to intensity of stress relations. Lowest intensity of social relations was found in the areas surrounding Wuhan and coastal areas. Specially, economic- and work-related stressors as well as negative self-perceptions (e.g., suppression, emotionally unstable, self-denial) implicated in negative emotions. While positive emotions were tied to demographic characteristics (e.g., high education, young age and male) and protective traits (e.g., creativity, sympathy, social responsibility), and inversely linked to relationships- and pandemic-related stressors, etc.\n\nConclusionAssociations were clearly noted among Chinese residents emotions to specific stressors during pandemic. Providing appropriate psychological resources/supports during future or extended public health crises may help offset the cognitive burden of individuals striving to regain an adequate level of normalcy and emotional well-being.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.29.21266847", + "rel_abs": "ObjectivesTo identify the population level impact of a national pulse oximetry remote monitoring programme for covid-19 (COVID Oximetry @home; CO@h) in England on mortality and health service use.\n\nDesignRetrospective cohort study using a stepped wedge pre- and post-implementation design.\n\nSettingAll Clinical Commissioning Groups (CCGs) in England implementing a local CO@h programme.\n\nParticipants217,650 people with a positive covid-19 polymerase chain reaction test result and symptomatic, from 1st October 2020 to 3rd May 2021, aged [≥]65 years or identified as clinically extremely vulnerable. Care home residents were excluded.\n\nInterventionsA pre-intervention period before implementation of the CO@h programme in each CCG was compared to a post-intervention period after implementation.\n\nMain outcome measuresFive outcome measures within 28 days of a positive covid-19 test: i) death from any cause; ii) any A&E attendance; iii) any emergency hospital admission; iv) critical care admission; and v) total length of hospital stay.\n\nResultsImplementation of the programme was not associated with mortality or length of hospital stay. Implementation was associated with increased health service utilisation with a 12% increase in the odds of A&E attendance (95% CI: 6%-18%) and emergency hospital admission (95% CI: 5%-20%) and a 24% increase in the odds of critical care admission in those admitted (95% CI: 5%-47%). In a secondary analysis of CO@h sites with at least 10% or 20% of eligible people enrolled, there was no significant association with any outcome measure. However, uptake of the programme was low, with enrolment data received for only 5,527 (2.5%) of the eligible population.\n\nConclusionsAt a population level, there was no association with mortality following implementation of the CO@h programme, and small increases in health service utilisation were observed. Low enrolment of eligible people may have diluted the effects of the programme at a population level.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Rui Xu", - "author_inst": "Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China" - }, - { - "author_name": "Xinfeng Zhang", - "author_inst": "Information Department, Beijing University of Technology, Beijing 100124, China" - }, - { - "author_name": "Danni Liu", - "author_inst": "Information Department, Beijing University of Technology, Beijing 100124, China" - }, - { - "author_name": "Qiang Li", - "author_inst": "Comprehensive Logistic Support Division, China Southern Airlines Company Limited, Guangzhou 510406, China" - }, - { - "author_name": "Yanping Wang", - "author_inst": "Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China" - }, - { - "author_name": "Rong Jiao", - "author_inst": "The First Clinical College, Hainan Medical University, Haikou 570100, China" - }, - { - "author_name": "Ximei Gong", - "author_inst": "Ophthalmologic Hospital, China Academy of Chinese Medical Sciences, Beijing 100040, China" + "author_name": "Thomas Beaney", + "author_inst": "Imperial College London" }, { - "author_name": "Xueyan Hou", - "author_inst": "Shenyang Medical College, Shenyang 110034, China" + "author_name": "Jonathan Clarke", + "author_inst": "Imperial College London" }, { - "author_name": "Tao Xu", - "author_inst": "Air Force Healthcare Center for Special Services Hangzhou, Hangzhou 310007, China" + "author_name": "Ahmed Alboksmaty", + "author_inst": "Imperial College London" }, { - "author_name": "Xuemei Qing", - "author_inst": "Guanganmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China" + "author_name": "Kelsey Flott", + "author_inst": "Imperial College London" }, { - "author_name": "Kangxing Song", - "author_inst": "Department of Cardiology, the First Medical Center, Chinese PLA General Hospital, Beijing 100853, China" + "author_name": "Aidan Fowler", + "author_inst": "NHS England and Improvement" }, { - "author_name": "Voyko Kavcic", - "author_inst": "Institute of Gerontology, Wayne State University, Detroit, MI, 48202, USA" + "author_name": "Jonathan R Benger", + "author_inst": "NHS Digital" }, { - "author_name": "Shiyan Yan", - "author_inst": "School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing 100029, China" + "author_name": "Paul Aylin", + "author_inst": "Imperial College London" }, { - "author_name": "Ruolei Gu", - "author_inst": "CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China" + "author_name": "Sarah Elkin", + "author_inst": "Imperial College London" }, { - "author_name": "Terry Stratton", - "author_inst": "Department of Behavioral Science, College of Medicine, University of Kentucky, KY 40536-0086, USA" + "author_name": "Ana Luisa Neves", + "author_inst": "Imperial College London" }, { - "author_name": "Yang Jiang", - "author_inst": "Department of Behavioral Science, College of Medicine, University of Kentucky, KY 40536-0086, USA" + "author_name": "Ara Darzi", + "author_inst": "Imperial College London" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "health systems and quality improvement" }, { "rel_doi": "10.1101/2021.11.29.21267041", @@ -478863,43 +477059,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.11.28.21264509", - "rel_title": "Estimating the transmissibility of SARS-CoV-2 during periods of high, low and zero case incidence", + "rel_doi": "10.1101/2021.11.29.21266986", + "rel_title": "Modelling the effect of the interaction between vaccination and non-pharmaceutical measures on COVID-19 incidence", "rel_date": "2021-11-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.28.21264509", - "rel_abs": "Against a backdrop of widespread global transmission, a number of countries have successfully brought large outbreaks of COVID-19 under control and maintained near-elimination status. A key element of epidemic response is the tracking of disease transmissibility in near real-time. During major outbreaks, the reproduction rate can be estimated from a time-series of case, hospitalisation or death counts. In low or zero incidence settings, knowing the potential for the virus to spread is a response priority. Absence of case data means that this potential cannot be estimated directly.\n\nWe present a semi-mechanistic modelling framework that draws on time-series of both behavioural data and case data (when disease activity is present) to estimate the transmissibility of SARS-CoV-2 from periods of high to low - or zero - case incidence, with a coherent transition in interpretation across the changing epidemiological situations. Of note, during periods of epidemic activity, our analysis recovers the effective reproduction number, while during periods of low - or zero - case incidence, it provides an estimate of transmission risk. This enables tracking and planning of progress towards the control of large outbreaks, maintenance of virus suppression, and monitoring the risk posed by re-introduction of the virus.\n\nWe demonstrate the value of our methods by reporting on their use throughout 2020 in Australia, where they have become a central component of the national COVID-19 response.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.29.21266986", + "rel_abs": "Since December 2019, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly from Wuhan (China) across the globe, affecting more than 200 countries by mid-2021, with over 190 M reported cases and around 4 M fatalities. During the first year of the pandemic, affected countries implemented a variety of non-pharmaceutical interventions to control virus transmission. In December 2020, countries started administering several authorised vaccines under a limited supply scenario. In this context, the aim of this study was to develop a SEIR-type continuous-time deterministic disease model, to determine the impact of interaction between different vaccination scenarios and levels of protection measures on disease incidence. For this, the model incorporates (i) a protection measure including low (self-protection), medium (mobility limitation), high (closure of indoor facilities) and very high (lockdown) protection levels, (ii) quarantine for confirmed cases, and (iii) vaccination rate and efficacy of four type of vaccines (Pfizer, Moderna, Astra Zeneca or Janssen). The model was verified and evaluated using the response timeline and vaccination strategies and rates in the Basque Country (N. Spain). Once the model performance was validated, different initial phase (when 30% of the population is vaccinated) vaccination scenarios were simulated, including (i) a realistic vaccine limited supply scenario, and (ii) four potential full vaccine supply scenarios where a unique vaccine type is administered. Some differences in disease incidence were found between vaccination scenarios for low and medium-level protection measures. However, regardless of the administered vaccine, a high-level protection scenario is the most effective to control the virus transmission and disease mortality in the studied initial phase of vaccination. The results obtained here may vary in further studies since there may be some unpredictable factors/covariates. With this in mind, the model here could be easily applied to other regions or countries, modifying the strategies implemented and initial conditions.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Nick Golding", - "author_inst": "Curtin University and Telethon Kids Institute" - }, - { - "author_name": "David J Price", - "author_inst": "The Peter Doherty Institute for Infection and Immunity" - }, - { - "author_name": "Gerry Ryan", - "author_inst": "Curtin University and Telethon Kids Institute" - }, - { - "author_name": "Jodie McVernon", - "author_inst": "The Peter Doherty Institute for Infection and Immunity" - }, - { - "author_name": "James M McCaw", - "author_inst": "School of Mathematics and Statistics, The University of Melbourne" + "author_name": "Atsegine Canga", + "author_inst": "University of the Basque Country" }, { - "author_name": "Freya M Shearer", - "author_inst": "Melbourne School of Population and Global Health, The University of Melbourne" + "author_name": "Gorka Bidegain", + "author_inst": "University of the Basque Country" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.11.25.21266875", @@ -480597,59 +478777,119 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.11.24.469813", - "rel_title": "Dual Effects of NV-CoV-2 Biomimetic Polymer: An Antiviral regimen against COVID-19", + "rel_doi": "10.1101/2021.11.24.469860", + "rel_title": "Nanopore ReCappable Sequencing maps SARS-CoV-2 5' capping sites and provides new insights into the structure of sgRNAs", "rel_date": "2021-11-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.24.469813", - "rel_abs": "Remdesivir (RDV) is the only antiviral drug so far approved for COVID-19 therapy by the FDA. However its efficacy is limited in vivo due to its low stability in presence of plasma. This paper compared the stability of RDV encapsulated with our platform technology based polymer NV-387 (NV-CoV-2), in presence of plasma in vitro and in vivo. Furthermore, a non- clinical pharmacology studies of NV-CoV-2 (Polymer) and NV-CoV-2-R (Polymer encapsulated Remdesivir) in both NL-63 infected and uninfected rats were done. In an in vitro cell culture model experiment, antiviral activity of NV-CoV-2 and NV-CoV-2-R are also compared with RDV.\n\nThe results are (i) NV-CoV-2 polymer encapsulation protects RDV from plasma- mediated catabolism in vitro and in vivo, too. (ii) Body weight measurements of the normal (uninfected) rats after administration of the test materials (NV-CoV-2, and NV-CoV-2-R) show no toxic effects on them. (iii) NL-63 infected rats body weights and their survival length were like uninfected rats after treatment with NV-CoV-2 and NV-CoV-2-R, and the efficacy as an antiviral regimen were found in the order as below: NV-CoV-2-R > NV-CoV-2 > RDV.\n\nIn brief, our platform technology based NV-387-encapsulated-RDV (NV-CoV-2-R) drug has a dual effect on coronaviruses. First, NV-CoV-2 itself as an antiviral regimen. Secondly, RDV is protected from plasma-mediated degradation in transit, rendering altogether the safest and an efficient regimen against COVID-19.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.24.469860", + "rel_abs": "The SARS-CoV-2 virus has a complex transcriptome characterised by multiple, nested sub genomic RNAs used to express structural and accessory proteins. Long-read sequencing technologies such as nanopore direct RNA sequencing can recover full-length transcripts, greatly simplifying the assembly of structurally complex RNAs. However, these techniques do not detect the 5' cap, thus preventing reliable identification and quantification of full-length, coding transcript models. Here we used Nanopore ReCappable Sequencing (NRCeq), a new technique that can identify capped full-length RNAs, to assemble a complete annotation of SARS-CoV-2 sgRNAs and annotate the location of capping sites across the viral genome. We obtained robust estimates of sgRNA expression across cell lines and viral isolates and identified novel canonical and non-canonical sgRNAs, including one that uses a previously un-annotated leader-to-body junction site. The data generated in this work constitute a useful resource for the scientific community and provide important insights into the mechanisms that regulate the transcription of SARS-CoV-2 sgRNAs.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Ashok Chakraborty", - "author_inst": "Allexcel, Inc" + "author_name": "Camilla Ugolini", + "author_inst": "Italian Institute of Technology" }, { - "author_name": "Anil Diwan", - "author_inst": "Allexcel, Shelton" + "author_name": "Logan Mulroney", + "author_inst": "Italian Institute of Technology" }, { - "author_name": "Vijetha Chiniga", - "author_inst": "Allexcel, Shelton, CT" + "author_name": "Adrien Leger", + "author_inst": "Oxford Nanopore Technologies" }, { - "author_name": "Vinod Arora", - "author_inst": "Allexcel, Inc, CT" + "author_name": "Matteo Castelli", + "author_inst": "Vita-Salute San Raffaele University" }, { - "author_name": "Preetam Holkar", - "author_inst": "Allexcel, Shelton, CT" + "author_name": "Elena Criscuolo", + "author_inst": "Vita-Salute San Raffaele University" }, { - "author_name": "Yogesh Thakur", - "author_inst": "Allexcel, Inc, Shelton, CT" + "author_name": "Maia Kavanagh Williamson", + "author_inst": "University of Bristol" }, { - "author_name": "Jay Tatake", - "author_inst": "Allexcel, Inc, Shelton, CT" + "author_name": "Andrew D Davidson", + "author_inst": "University of Bristol" }, { - "author_name": "Randall Barton", - "author_inst": "Nanoviricides, Inc., Shelton, Inc." + "author_name": "Abdulaziz Almuqrin", + "author_inst": "University of Bristol" }, { - "author_name": "Neelam Holkar", - "author_inst": "Allexcel, Inc, Shelton, CT" + "author_name": "Roberto Giambruno", + "author_inst": "Istituto Italiano di Tecnologia" }, { - "author_name": "Bethany Pond", - "author_inst": "Allexcel, Inc, Shelton, CT" + "author_name": "Miten Jain", + "author_inst": "University of California Santa Cruz" + }, + { + "author_name": "Gianmaria Frig\u00e8", + "author_inst": "Istituto Europeo di Oncologia" + }, + { + "author_name": "Hugh Olsen", + "author_inst": "University of California Santa Cruz" + }, + { + "author_name": "George Tzertzinis", + "author_inst": "New England Biolabs" + }, + { + "author_name": "Ira Schildkraut", + "author_inst": "New England Biolabs" + }, + { + "author_name": "Madalee F Wulf", + "author_inst": "New England Biolabs" + }, + { + "author_name": "Ivan R. Corr\u00eaa Jr.", + "author_inst": "New England Biolabs" + }, + { + "author_name": "Laurence Ettwiller", + "author_inst": "New England Biolabs Inc" + }, + { + "author_name": "Nicola Clementi", + "author_inst": "Vita-Salute San Raffaele University" + }, + { + "author_name": "Massimo Clementi", + "author_inst": "Vita-Salute San Raffaele University" + }, + { + "author_name": "Nicasio Mancini", + "author_inst": "Universit\u00e0 Vita-Salute San Raffaele" + }, + { + "author_name": "Ewan Birney", + "author_inst": "European Bioinformatics Institute" + }, + { + "author_name": "Mark Akeson", + "author_inst": "University of California Santa Cruz" + }, + { + "author_name": "Francesco Nicassio", + "author_inst": "Istituto Italiano di Tecnologia" + }, + { + "author_name": "David A Matthews", + "author_inst": "University of Bristol" + }, + { + "author_name": "Tommaso Leonardi", + "author_inst": "Italian Institute of Technology" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "new results", - "category": "pharmacology and toxicology" + "category": "genomics" }, { "rel_doi": "10.1101/2021.11.24.21266812", @@ -482483,113 +480723,93 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.22.21266673", - "rel_title": "Neutralization of SARS-CoV-2 variants by rVSV-\u0394G-spike-elicited human sera", + "rel_doi": "10.1101/2021.11.22.21266711", + "rel_title": "Germany's low SARS-CoV-2 seroprevalence confirms effective containment in 2020: Results of the nationwide RKI-SOEP study", "rel_date": "2021-11-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.22.21266673", - "rel_abs": "The emergence of rapidly spreading variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a major challenge to the ability of vaccines and therapeutic antibodies to provide immunity. These variants contain mutations at specific amino acids that might impede vaccine efficacy. BriLife(R) (rVSV-{Delta}G-spike) is a newly developed SARS-CoV-2 vaccine candidate currently in Phase II clinical trials. It is based on a replication competent vesicular stomatitis virus (VSV) platform. rVSV-{Delta}G-spike contains several spontaneously-acquired spike mutations that correspond to SARS-CoV-2 variants mutations. We show that human sera from BriLife(R) vaccinees preserve comparable neutralization titers towards alpha, gamma and delta variants, and show less than 3-fold reduction in neutralization capacity of beta and omicron compared to the original virus. Taken together, we show that human sera from BriLife(R) vaccinees overall maintain neutralizing antibody response against all tested variants. We suggest that BriLife(R) acquired mutations may prove advantageous against future SARS-CoV-2 VOCs.", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.22.21266711", + "rel_abs": "Pre-vaccine SARS-CoV-2 seroprevalence data from Germany are scarce outside hotspots, and socioeconomic disparities remained largely unexplored. The nationwide RKI-SOEP study with 15,122 adult participants investigated seroprevalence and testing in a supplementary wave of the Socio-Economic-Panel conducted predominantly in October-November 2020. Self-collected oral-nasal swabs were PCR-positive in 0.4% and Euroimmun anti-SARS-CoV-2-S1-IgG ELISA from dry capillary blood in 1.3% (95% CI 0.9-1.7%, population-weighted, corrected for sensitivity=0.811, specificity=0.997). Seroprevalence was 1.7% (95% CI 1.2-2.3%) when additionally adjusting for antibody decay. Overall infection prevalence including self-reports was 2.1%. We estimate 45% (95% CI 21-60%) undetected cases and analyses suggest lower detection in socioeconomically deprived districts. Prior SARS-CoV-2 testing was reported by 18% from the lower educational group compared to 25% and 26% from the medium and high educational group (p<0.0001). Symptom-triggered test frequency was similar across educational groups. However, routine testing was more common in low-educated adults, whereas travel-related testing and testing after contact with an infected person was more common in highly educated groups. In conclusion, pre-vaccine SARS-CoV-2-seroprevalence in Germany was very low. Notified cases appear to capture more than half of infections but may underestimate infections in lower socioeconomic groups. These data confirm the successful containment strategy of Germany until winter 2020.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Yfat Yahalom-Ronen", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Noam Erez", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Morly Fisher", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Hadas Tamir", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Boaz Politi", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Hagit Achdout", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Hannelore Neuhauser", + "author_inst": "Robert Koch Institute, Berlin, Germany" }, { - "author_name": "Sharon Melamed", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Angelika Schaffrath Rosario", + "author_inst": "Robert Koch Institute, Berlin, Germany" }, { - "author_name": "Itai Glinert", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Hans Butschalowsky", + "author_inst": "Robert Koch Institute, Berlin, Germany" }, { - "author_name": "Shay Weiss", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Sebastian Haller", + "author_inst": "Robert Koch Institute, Berlin, Germany" }, { - "author_name": "Inbar Cohen-Gihon", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Jens Hoebel", + "author_inst": "Robert Koch Institute, Berlin, Germany" }, { - "author_name": "Ofir Israely", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Janine Michel", + "author_inst": "Robert Koch Institute, Berlin, Germany" }, { - "author_name": "Marina Izak", - "author_inst": "MDA" + "author_name": "Andreas Nitsche", + "author_inst": "Robert Koch Institute, Berlin, Germany" }, { - "author_name": "Michal Mandelboim", - "author_inst": "Sheba Medical Center" + "author_name": "Christina Poethko-Mueller", + "author_inst": "Robert Koch Institute, Berlin, Germany" }, { - "author_name": "Yoseph Caraco", - "author_inst": "Hadassah Medical Center" + "author_name": "Franziska Pruetz", + "author_inst": "Robert Koch Institute, Berlin, Germany" }, { - "author_name": "Noa Madar-Balakirski", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Martin Schlaud", + "author_inst": "Robert Koch Institute, Berlin, Germany" }, { - "author_name": "Adva Mechaly", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Hans W. Steinhauer", + "author_inst": "Socio-Economic Panel, German Institute for Economic Research, Berlin, Germany" }, { - "author_name": "Eilat Shinar", - "author_inst": "MDA" + "author_name": "Hendrik Wilking", + "author_inst": "Robert Koch Institute, Berlin, Germany" }, { - "author_name": "Ran Zichel", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Lothar H. Wieler", + "author_inst": "Robert Koch Institute, Berlin, Germany" }, { - "author_name": "Daniel Cohen", - "author_inst": "Tel Aviv University" + "author_name": "Lars Schaade", + "author_inst": "Robert Koch Institute, Berlin, Germany" }, { - "author_name": "Adi Beth-Din", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Stefan Liebig", + "author_inst": "Socio-Economic Panel, German Institute for Economic Research, Berlin, Germany and SOEP & Department of Political and Social Sciences, Free University, Berlin, G" }, { - "author_name": "Anat Zvi", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Antje Goesswald", + "author_inst": "Robert Koch Institute, Berlin, Germany" }, { - "author_name": "Hadar Marcus", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Markus M. Grabka", + "author_inst": "Socio-Economic Panel, German Institute for Economic Research, Berlin, Germany" }, { - "author_name": "Tomer Israely", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Sabine Zinn", + "author_inst": "Socio-Economic Panel, German Institute for Economic Research, Berlin, Germany and SOEP & Department of Social Sciences, Humboldt University, Berlin, Germany" }, { - "author_name": "Nir Paran", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Thomas Ziese", + "author_inst": "Robert Koch Institute, Berlin, Germany" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -484281,57 +482501,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.24.469537", - "rel_title": "Neurotoxic Amyloidogenic Peptides Identified in the Proteome of SARS-COV2: Potential Implications for Neurological Symptoms in COVID-19", + "rel_doi": "10.1101/2021.11.22.469552", + "rel_title": "Stabilization of the SARS-CoV-2 Receptor Binding Domain by Protein Core Redesign and Deep Mutational Scanning", "rel_date": "2021-11-24", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.24.469537", - "rel_abs": "COVID-19 is primarily known as a respiratory disease caused by the virus SARS-CoV-2. However, neurological symptoms such as memory loss, sensory confusion, cognitive and psychiatric issues, severe headaches, and even stroke are reported in as many as 30% of cases and can persist even after the infection is over (so-called long COVID). These neurological symptoms are thought to be caused by brain inflammation, triggered by the virus infecting the central nervous system of COVID-19 patients, however we still dont fully understand the mechanisms for these symptoms. The neurological effects of COVID-19 share many similarities to neurodegenerative diseases such as Alzheimers and Parkinsons in which the presence of cytotoxic protein-based amyloid aggregates is a common etiological feature. Following the hypothesis that some neurological symptoms of COVID-19 may also follow an amyloid etiology we performed a bioinformatic scan of the SARS-CoV-2 proteome, detecting peptide fragments that were predicted to be highly amyloidogenic. We selected two of these peptides and discovered that they do rapidly self-assemble into amyloid. Furthermore, these amyloid assemblies were shown to be highly toxic to a neuronal cell line. We introduce and support the idea that cytotoxic amyloid aggregates of SARS-CoV-2 proteins are causing some of the neurological symptoms commonly found in COVID-19 and contributing to long COVID, especially those symptoms which are novel to long COVID in contrast to other post-viral syndromes.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.22.469552", + "rel_abs": "Stabilizing antigenic proteins as vaccine immunogens or diagnostic reagents is a stringent case of protein engineering and design as the exterior surface must maintain recognition by receptor(s) and antigen--specific antibodies at multiple distinct epitopes. This is a challenge, as stability-enhancing mutations must be focused on the protein core, whereas successful computational stabilization algorithms typically select mutations at solvent-facing positions. In this study we report the stabilization of SARS-CoV-2 Wuhan Hu-1 Spike receptor binding domain (S RBD) using a combination of deep mutational scanning and computational design, including the FuncLib algorithm. Our most successful design encodes I358F, Y365W, T430I, and I513L RBD mutations, maintains recognition by the receptor ACE2 and a panel of different anti-RBD monoclonal antibodies, is between 1-2{degrees}C more thermally stable than the original RBD using a thermal shift assay, and is less proteolytically sensitive to chymotrypsin and thermolysin than the original RBD. Our approach could be applied to the computational stabilization of a wide range of proteins without requiring detailed knowledge of active sites or binding epitopes, particularly powerful for cases when there are multiple or unknown binding sites.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Saba Islam", - "author_inst": "La Trobe University" - }, - { - "author_name": "Mirren Charnley", - "author_inst": "Swinburne University of Technology" - }, - { - "author_name": "Guneet Bindra", - "author_inst": "La Trobe University" - }, - { - "author_name": "Julian Ratcliffe", - "author_inst": "La Trobe University Bioimaging Platform" - }, - { - "author_name": "Jiangtao Zhou", - "author_inst": "ETH Zurich" + "author_name": "Alison C Leonard", + "author_inst": "University of Colorado, Boulder" }, { - "author_name": "Raffaele Mezzenga", - "author_inst": "ETH Zurich" + "author_name": "Jonathan Weinstein", + "author_inst": "Weizmann Institute of Science" }, { - "author_name": "Mark D Hulett", - "author_inst": "La Trobe University" + "author_name": "Paul J Steiner", + "author_inst": "University of Colorado, Boulder" }, { - "author_name": "Kyunghoon Han", - "author_inst": "University of Luxembourg" + "author_name": "Annette Erbse", + "author_inst": "University of Colorado, Boulder" }, { - "author_name": "Joshua T Berryman", - "author_inst": "University of Luxembourg" + "author_name": "Sarel J Fleishman", + "author_inst": "Weizmann Institute of Science" }, { - "author_name": "Nicholas P Reynolds", - "author_inst": "La Trobe University" + "author_name": "Timothy A Whitehead", + "author_inst": "University of Colorado, Boulder" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", "category": "biochemistry" }, @@ -486139,41 +484343,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.11.19.21266593", - "rel_title": "COVID-19 Vaccine Rollouts and the Reproduction of Urban Spatial Inequality: Disparities Within Large U.S. Cities in March and April 2021 by Racial/Ethnic and Socioeconomic Composition", + "rel_doi": "10.1101/2021.11.17.21266479", + "rel_title": "Healthcare workers benefit from second dose of COVID-19 mRNA vaccine: Effects of partial and full vaccination on sick leave duration and symptoms", "rel_date": "2021-11-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.19.21266593", - "rel_abs": "Rollouts of COVID-19 vaccines in the U.S. were opportunities to redress disparities that surfaced during the pandemic. Initial eligibility criteria, however, neglected geographic, racial/ethnic, and socioeconomic considerations. Marginalized populations may have faced barriers to then-scarce vaccines, reinforcing disparities. Inequalities may have subsided as eligibility expanded. Using spatial modeling, we investigate how strongly local vaccination levels were associated with socioeconomic and racial/ethnic composition as authorities first extended vaccine eligibility to all adults. We harmonize administrative, demographic, and geospatial data across postal codes in eight large U.S. cities over three weeks in Spring 2021. We find that, although vaccines were free regardless of health insurance coverage, local vaccination levels in March and April were negatively associated with poverty, enrollment in means-tested public health insurance (e.g., Medicaid), and the uninsured population. By April, vaccination levels in Black and Hispanic communities were only beginning to reach those of Asian and White communities in March. Increases in vaccination were smaller in socioeconomically disadvantaged Black and Hispanic communities than in more affluent, Asian, and White communities. Our findings suggest vaccine rollouts contributed to cumulative disadvantage. Populations that were left most vulnerable to COVID-19 benefited least from early expansions in vaccine availability in large U.S. cities.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.17.21266479", + "rel_abs": "ImportanceIn addition to morbidity and mortality of individuals, COVID-19 can affect staffing among organizations. It is important to determine whether vaccination can mitigate this burden. Objective: This study examined the association between COVID-19 vaccination status and time until return to work among 952 healthcare workers (HCW) who tested positive for COVID-19.\n\nDesignData were collected prospectively between December 2020 and July 2021. HCW who tested positive for COVID-19 completed an initial interview and were followed until they returned to work.\n\nSettingAn academic campus in Southern California consisting of two large hospitals and multiple outpatient clinics and other facilities.\n\nParticipantsClinical and nonclinical HCW who tested positive for COVID-19 during the study period (N=952, mean age=39.2 years, 69% female, 45% Hispanic, 14% white, 14% Asian/Pacific Islander, 5% African American, and 21% other race/ethnicity).\n\nExposureCOVID-19 vaccination status (unvaccinated, partially vaccinated, or fully vaccinated)\n\nMain Outcome MeasuresDays until return to work, presenting symptom\n\nResultsReturn-to-work time for fully vaccinated HCWs (mean=10.9 days) was significantly shorter than that of partially vaccinated HCWs (15.5 days), which in turn was significantly shorter than that of unvaccinated HCWs (18.0 days). Fully vaccinated HCWs also showed milder symptom profiles compared to partially vaccinated and unvaccinated HCWs.\n\nConclusions and RelevanceCOVID-19 vaccination has the potential to prevent long absences from work and the adverse financial, staffing, and managerial consequences of these long absences.\n\nKEY POINTSO_ST_ABSQuestionC_ST_ABSDo healthcare workers (HCW) who are vaccinated against COVID-19 return to work sooner and experience milder symptoms compared with unvaccinated HCW?\n\nFindingsAmong 952 healthcare workers who tested positive for COVID-19 between December 2020 and July 2021, return-to-work time for fully vaccinated HCWs (mean=10.9 days) was significantly shorter than that of partially vaccinated HCWs (15.5 days), which in turn was significantly shorter than that of unvaccinated HCWs (18.0 days). Fully vaccinated HCWs also showed milder symptom profiles compared to partially vaccinated and unvaccinated HCWs.\n\nMeaningCOVID-19 vaccination has the potential to prevent long absences from work and the adverse financial, staffing, and managerial consequences of these long absences.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Nicholas V DiRago", - "author_inst": "University of California, Los Angeles" - }, - { - "author_name": "Meiying Li", + "author_name": "Earl M Strum", "author_inst": "University of Southern California" }, { - "author_name": "Thalia Tom", + "author_name": "Yolee Casagrande", "author_inst": "University of Southern California" }, { - "author_name": "Will Schupmann", - "author_inst": "University of California, Los Angeles" - }, - { - "author_name": "Yvonne Carrillo", - "author_inst": "University of California, Los Angeles" - }, - { - "author_name": "Colleen M. Carey", - "author_inst": "Cornell University" + "author_name": "Kim I Newton", + "author_inst": "University of Southern California" }, { - "author_name": "S. Michael Gaddis", - "author_inst": "University of California, Los Angeles" + "author_name": "Jennifer B Unger", + "author_inst": "University of Southern California" } ], "version": "1", @@ -487773,93 +485965,93 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.17.21266297", - "rel_title": "SARS-CoV-2 testing in the community: Testing positive samples with the TaqMan SARS-CoV-2 Mutation Panel to find variants in real-time", + "rel_doi": "10.1101/2021.11.17.21266459", + "rel_title": "Healthcare workers' SARS-CoV-2 infection rates during the second wave of the pandemic: prospective cohort study", "rel_date": "2021-11-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.17.21266297", - "rel_abs": "Genome sequencing is a powerful tool for identifying SARS-CoV-2 variant lineages, however there can be limitations due to sequence drop-out when used to identify specific key mutations. Recently, Thermo Fisher Scientific have developed genotyping assays to help bridge the gap between testing capacity and sequencing capability to generate real-time genotyping results based on specific variants. Over a 6-week period during the months of April and May 2021, we set out to assess the Thermo Fisher TaqMan Mutation Panel Genotyping Assay, initially for three mutations of concern and then an additional two mutations of concern, against SARS-CoV-2 positive clinical samples and the corresponding COG-UK sequencing data. We demonstrate that genotyping is a powerful in-depth technique for identifying specific mutations, an excellent complement to genome sequencing and has real clinical health value potential allowing laboratories to report and action variants of concern much quicker.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.17.21266459", + "rel_abs": "ObjectivesTo assess if healthcare workers during the second wave of the coronavirus disease 2019 (COVID-19) pandemic had increased severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection rates following close contact with patients, co-workers and persons outside work with COVID-19.\n\nMethodsA prospective cohort study of 5985 healthcare workers from Denmark were followed November 2020 to April 2021 and provided day-by-day information on COVID-19 contacts. SARS-CoV-2 infection was defined by the first positive polymerase chain reaction (PCR) test ever.\n\nResults159 positive and 35 996 negative PCR tests were recorded during 514 165 person-days. The SARS-CoV-2 infection rate following close contact with COVID-19 patients 3-7 days earlier was 153.7 per 100,000 person-days corresponding with an incidence rate ratio (IRR) of 3.17 (40 cases, 95% CI 2.15 - 4.66) compared with no close contact. IRRs following close contact with co-workers and persons outside work with COVID-19 were 2.54 (10 cases, 95% CI 1.30 - 4.96) and 17.79 (35 cases, 95% CI 12.05 - 26.28). The estimates for close contact with COVID-19 patients, co-workers or persons outside work were mutually adjusted.\n\nConclusionsDespite strong focus on preventive measures during the second wave of the pandemic, healthcare workers were still at increased risk of SARS-CoV-2 infection when in close contact with patients with COVID-19. Among all health care workers, the numbers affected due to close patient contact were comparable to the numbers affected following COVID-19 contact outside work.", "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Fiona Ashford", - "author_inst": "University of Birmingham" + "author_name": "Anne Mette Wurtz", + "author_inst": "Department of Public Health, Work, Environment and Health, Danish Ramazzini Centre, Aarhus University" }, { - "author_name": "Angus Best", - "author_inst": "University of Birmingham" + "author_name": "Martin B. Kinnerup", + "author_inst": "Department of Occupational Medicine, Danish Ramazzini Centre, Aarhus University Hospital" }, { - "author_name": "Steven Dunn", - "author_inst": "University of Birmingham" + "author_name": "Kirsten Pugdal", + "author_inst": "Department of Occupational Medicine, Danish Ramazzini Centre, Aarhus University Hospital" }, { - "author_name": "Zahra Ahmed", - "author_inst": "University of Birmingham" + "author_name": "Vivi Schlunssen", + "author_inst": "Department of Public Health, Work, Environment and Health, Danish Ramazzini Centre, Aarhus University" }, { - "author_name": "Henna Siddiqui", - "author_inst": "University of Birmingham" + "author_name": "Jesper Medom Vestergaard", + "author_inst": "Department of Occupational Medicine, Danish Ramazzini Centre, Aarhus University Hospital" }, { - "author_name": "Jordan Melville", - "author_inst": "University of Birmingham" + "author_name": "Kent Nielsen", + "author_inst": "); Department of Occupational Medicine, Danish Ramazzini Centre, Goedstrup Hospital" }, { - "author_name": "Samuel Wilkinson", - "author_inst": "University of Birmingham" + "author_name": "Christine Cramer", + "author_inst": "Department of Occupational Medicine, Danish Ramazzini Centre, Aarhus University Hospital" }, { - "author_name": "Jeremy Mirza", - "author_inst": "University of Birmingham" + "author_name": "Jens Peter Bonde", + "author_inst": "Department of Occupational and Environmental Medicine, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Copenhagen" }, { - "author_name": "Nicola Cumley", - "author_inst": "University of Birmingham" + "author_name": "Karin Biering", + "author_inst": "Department of Occupational Medicine, Danish Ramazzini Centre, Goedstrup Hospital" }, { - "author_name": "Joanna Stockton", - "author_inst": "University of Birmingham" + "author_name": "Ole Carstensen", + "author_inst": "Department of Occupational Medicine, Danish Ramazzini Centre, Goedstrup Hospital" }, { - "author_name": "Jack Ferguson", - "author_inst": "University of Birmingham" + "author_name": "Karoline Kaergaard Hansen", + "author_inst": "Department of Occupational Medicine, Danish Ramazzini Centre, Aarhus University Hospital" }, { - "author_name": "Lucy Wheatley", - "author_inst": "University of Birmingham" + "author_name": "Annett Dalboege", + "author_inst": "Department of Occupational Medicine, Danish Ramazzini Centre, Aarhus University Hospital" }, { - "author_name": "Elizabeth Ratcliffe", - "author_inst": "University Hospital Birmingham" + "author_name": "Esben Meulengracht Flachs", + "author_inst": "Department of Occupational and Environmental Medicine, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Copenhagen" }, { - "author_name": "Anna Casey", - "author_inst": "University Hospital Birmingham" + "author_name": "Mette Lausten Hansen", + "author_inst": "Department of Occupational Medicine, Danish Ramazzini Centre, Aarhus University Hospital" }, { - "author_name": "- The COVID-19 Genomics UK (COG-UK) Consortium5", - "author_inst": "-" + "author_name": "Ane Marie Thulstrup", + "author_inst": "Department of Occupational Medicine, Danish Ramazzini Centre, Aarhus University Hospital" }, { - "author_name": "Joshua Quick", - "author_inst": "University of Birmingham" + "author_name": "Else Toft Wurtz", + "author_inst": "Department of Occupational Medicine, Danish Ramazzini Centre, Aarhus University Hospital" }, { - "author_name": "Alex Richter", - "author_inst": "University of Birmingham" + "author_name": "Mona Kjaersgaard", + "author_inst": "Department of Clinical Microbiology, Aarhus University Hospital" }, { - "author_name": "Nicholas James Loman", - "author_inst": "University of Birmingham" + "author_name": "Mette Wulf Christensen", + "author_inst": "Department of Occupational Medicine, Danish Ramazzini Centre, Aarhus University Hospital" }, { - "author_name": "Alan McNally", - "author_inst": "University of Birmingham" + "author_name": "Henrik A. Kolstad", + "author_inst": "Department of Occupational Medicine, Danish Ramazzini Centre, Aarhus University Hospital" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -489463,35 +487655,31 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.11.18.469078", - "rel_title": "Metformin Suppresses SARS-CoV-2 in Cell Culture", - "rel_date": "2021-11-19", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.18.469078", - "rel_abs": "Comorbidities such as diabetes worsen COVID-19 severity and recovery. Metformin, a first-line medication for type 2 diabetes, has antiviral properties and certain studies have also indicated its prognostic potential in COVID-19. Here, we report that metformin significantly inhibits SARS-CoV-2 growth in cell culture models. First, a steady increase in AMPK phosphorylation was detected as infection progressed, suggesting its important role during viral infection. Activation of AMPK in Calu3 and Caco2 cell lines using metformin revealed that metformin suppresses SARS-CoV-2 infectious titers up to 99%, in both naive as well as infected cells. TCID50 values from dose-variation studies in infected cells were found to be 0.8 and 3.5 mM in Calu3 and Caco2 cells, respectively. Role of AMPK in metformins antiviral suppression was further confirmed using other pharmacological compounds, AICAR and Compound C. Collectively, our study demonstrates that metformin is effective in limiting the replication of SARS-CoV-2 in cell culture and thus possibly could offer double benefits s diabetic COVID-19 patients by lowering both blood glucose levels and viral load.", - "rel_num_authors": 4, + "rel_doi": "10.1101/2021.11.17.21263608", + "rel_title": "Reduced Incidence of Long-COVID Symptoms Related to Administration of COVID-19 Vaccines Both Before COVID-19 Diagnosis and Up to 12 Weeks After", + "rel_date": "2021-11-18", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.17.21263608", + "rel_abs": "Both clinical trials and studies leveraging real-world data have repeatedly confirmed the three COVID-19 vaccines authorized for use by the Food and Drug Administration are safe and effective at preventing infection, hospitalization, and death due to COVID-19 and a recent observational study of self-reported symptoms provides support that vaccination may also reduce the probability of developing long-COVID. As part of a federated research study with the COVID-19 Patient Recovery Alliance, Arcadia.io performed a retrospective analysis of the medical history of 240,648 COVID-19-infected persons to identity factors influencing the development and progression of long-COVID. This analysis revealed that patients who received at least one dose of any of the three COVID vaccines prior to their diagnosis with COVID-19 were 7-10 times less likely to report two or more long-COVID symptoms compared to unvaccinated patients. Furthermore, unvaccinated patients who received their first COVID-19 vaccination within four weeks of SARS-CoV-2 infection were 4-6 times less likely to report multiple long-COVID symptoms, and those who received their first dose 4-8 weeks after diagnosis were 3 times less likely to report multiple long-COVID symptoms compared to those who remained unvaccinated. This relationship supports the hypothesis that COVID-19 vaccination is protective against long-COVID and that effect persists even if vaccination occurs up to 12 weeks after COVID-19 diagnosis. A critical objective of this study was hypothesis generation, and the authors intend to perform further studies to substantiate the findings and encourage other researchers to as well.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Haripriya Parthasarathy", - "author_inst": "Centre for Cellular and Molecular Biology" - }, - { - "author_name": "Dixit Tandel", - "author_inst": "Centre for Cellular and Molecular Biology, Academy of Scientific and Innovative Research" + "author_name": "Michael A Simon", + "author_inst": "Arcadia" }, { - "author_name": "Abdul Hamid Siddiqui", - "author_inst": "CSIR-Centre for Cellular and Molecular Biology" + "author_name": "Ryan Luginbuhl", + "author_inst": "The MITRE Corporation" }, { - "author_name": "Krishnan Harinivas Harshan", - "author_inst": "Centre for Cellular and Molecular Biology" + "author_name": "Richard Parker", + "author_inst": "Arcadia" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.11.14.21266334", @@ -491173,51 +489361,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.11.16.21265186", - "rel_title": "Experience with open schools and preschools in periods of high community transmission of COVID-19 in Norway during the academic year of 2020/2021.", + "rel_doi": "10.1101/2021.11.16.21266324", + "rel_title": "COVID-19 in Elderly Patients with Acute Kidney Injury", "rel_date": "2021-11-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.16.21265186", - "rel_abs": "BackgroundSchools and preschools have largely remained open in Norway throughout the pandemic, with flexible mitigation measures in place. This contrasts with many other high-income countries that closed schools for long periods of time. Here we describe cases and outbreaks of COVID-19 in schools and preschools during the academic year 2020/2021, to evaluate the strategy of keeping these open with infection prevention control measures in place.\n\nMethodsIn this descriptive study, the Norwegian Institute of Public Health initiated systematic surveillance for COVID-19 cases and outbreaks in schools and preschools in October 2020. Data was compiled from the national outbreak alert system VESUV, municipality websites, and media scanning combined with the national emergency preparedness register Beredt C-19. An outbreak was defined as [≥] 2 cases among pupils or staff within 14 days at the same educational setting. Settings were categorized as preschool (1-5-years), primary school (6-12-years), lower secondary school (13-15-years) and upper secondary school (16-18-years). We reported the incidence rate among preschool and school-aged pupils and gave a descriptive overview of outbreaks and included cases per educational setting.\n\nResultsDuring the whole academic year, a total of 1203 outbreaks in preschools and school settings were identified, out of a total of 8311 preschools and schools nationwide. The incidence of COVID-19 in preschool- and school-aged children and the rates of outbreaks in these settings largely followed the community trend. Most of the outbreaks occurred in primary schools (40%) and preschools (25%). Outbreaks across all settings were mostly small (median 3 cases, range 2 to 72), however, 40 outbreaks (3% of total) included 20 or more cases. The larger outbreaks were predominantly seen in primary schools (43%).\n\nConclusionsWe observed few large outbreaks in open schools and preschools in Norway during the academic year of 2020/2021, also when the Alpha variant was predominant. This illustrates that it is possible to keep schools and preschools open even during periods of high community transmission of COVID-19. Adherence to targeted IPC measures adaptable to the local situation has been essential to keep educational settings open, and thus reduce the total burden on children and adolescents.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.16.21266324", + "rel_abs": "ObjectiveCoronavirus disease 2019 (Covid 19) started in China in December 2019 and spread all over the world, is more progressive in patients who are elderly and with chronic diseases. Especially kidney involvement affects the survival of patients. In this study, we analyzed Covid 19 patients who developed acute kidney injury treated in our unit, retrospectively.\n\nMatherialsThe clinical and laboratory data of 610 patients who hospitalized due to Covid 19 pandemic between 01.06.2020 and 30.06.2021 in the intensive care and other clinics of our hospital evaluated from the records, retrospectively. One hundred-fourty patients diagnosed with AKI according to the criteria of KDIGO (Kidney Disease Global Outcomes). The patients divided into two groups as KDIGO stage 1 and 2, 3.\n\nResultsThe median age in both groups was 70 (35-92) and 73 (35-90) years. Approximately seventy percent of them were over 65 years old. Almost all of the patients had hypertension. Most of the patients were using angiotensin converting enzyme inhibitors (ACE inh) or angiotensin receptor blockers (ARB) (84%). AKI was present at the time of admission (61.9%) in the KDIGO 1 group and at the time of hospitalization (64.3%) in the KDIGO 2, 3 group. The mortality rate was higher in stage 2-3 AKI patients (35.7%). Ferritin and fibrinogen levels were high in the KDIGO 2, 3 group, while lymphocyte levels were low.\n\nConclusionAKI can be seen at the time of admission and during treatment in patients who are hospitalized and treated due to Covid 19. Covid 19 is more mortal in patients with advanced AKI.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Sara Stebbings", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Yavuz AYAR", + "author_inst": "Bursa City Hospital" }, { - "author_name": "Torill Alise Rotevatn", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Olgun Deniz", + "author_inst": "University of Health Sciences, Bursa Faculty of Medicine, Department of Geriatrics, Bursa, Turkey" }, { - "author_name": "Vilde Bergstad Larsen", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Baris Doner", + "author_inst": "University of Health Sciences, Cam and Sakura City Hospital, Istanbul, Turkey" }, { - "author_name": "P\u00e5l Sur\u00e9n", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Isa Kilic", + "author_inst": "University of Health Sciences, Bursa Faculty of Medicine, Department of Intensive Care, Anesthesia and Reanimation, Bursa, Turkey" }, { - "author_name": "Petter Elstr\u00f8m", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Canan Demir", + "author_inst": "University of Health Sciences, Bursa Faculty of Medicine, Department of Clinical Microbiology and Infection Diseases, Bursa, Turkey" }, { - "author_name": "Margrethe Greve-Isdahl", - "author_inst": "Norwegian Institute of Public Health" - }, - { - "author_name": "Tone Bjordal Johansen", - "author_inst": "Norwegian Institute of Public Health" - }, - { - "author_name": "Elisabeth Astrup", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Abdulkadir Sahin", + "author_inst": "University of Health Sciences, Bursa Faculty of Medicine, Department of Internal Medicine, Bursa, Turkey" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "nephrology" }, { "rel_doi": "10.1101/2021.11.15.21265526", @@ -493323,67 +491503,83 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.12.21266291", - "rel_title": "Neurodevelopmental outcomes of infants secondary to in utero exposure to maternal SARS-CoV-2 infection: A national prospective study in Kuwait", + "rel_doi": "10.1101/2021.11.11.21266212", + "rel_title": "Aortic stenosis post-COVID-19: A mathematical model on waiting lists and mortality", "rel_date": "2021-11-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.12.21266291", - "rel_abs": "BackgroundAn increasing proportion of women are being infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during pregnancy. Intrauterine viral infections induce an increase in the levels of proinflammatory cytokines, which inhibit the proliferation of neuronal precursor cells and stimulate oligodendrocyte cell death, leading to abnormal neurodevelopment. Whether a maternal cytokine storm can affect neonatal brain development is unclear. The objective of the present study is to assess neurodevelopmental outcomes in neonates born to mothers with SARS-CoV-2 infections during pregnancy.\n\nMethodsIn this prospective cohort study, the neurodevelopment status of infants (N=298) born to women with SARS-CoV-2 infections during pregnancy was assessed at 10-12 months post discharge using the Ages and Stages Questionnaire, 3rd edition (ASQ-3). The ASQ-3 scores were classified into developmental delays (cutoff score: [≤]2 standard deviations (SDs) below the population mean) and no delay (score >2 SDs above the population mean).\n\nResultsApproximately 10% of infants born to mothers with SARS-CoV-2 infections during pregnancy showed developmental delays. Two of 298 infants tested positive for SARS-CoV-2, and both had normal ASQ-3 scores. The majority of the pregnant women had SARS-CoV-2 infection during their third trimester. The risk of developmental delays among infants was higher in those whose mothers had SARS-CoV-2 infections during the first (P=0.039) and second trimesters (P=0.001) than in those whose mothers had SARS-CoV-2 infections during the third trimester. Infants born at <31 weeks gestation were more prone to developmental delays than those born at >31 weeks gestation (10% versus 0.8%; P=0.002).\n\nConclusionThe findings of the study highlight the need for long term neurodevelopmental assessment of infants born to mothers with SARS-CoV-2 infection.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.11.21266212", + "rel_abs": "ObjectivesTo provide estimates for how different treatment pathways for the management of severe aortic stenosis (AS) may affect NHS England waiting list duration and associated mortality.\n\nDesignWe constructed a mathematical model of the excess waiting list and found the closed-form analytic solution to that model. From published data, we calculated estimates for how the following strategies may affect the time to clear the backlog of patients waiting for treatment and the associated waiting list mortality.\n\nInterventions1) increasing the capacity for the treatment of severe AS, 2) converting proportions of cases from surgery to transcatheter aortic valve implantation, and 3) a combination of these two.\n\nResultsIn a capacitated system, clearing the backlog by returning to pre-COVID-19 capacity is not possible. A conversion rate of 50% would clear the backlog within 666 (95% CI, 533-848) days with 1419 (95% CI, 597-2189) deaths whilst waiting during this time. A 20% capacity increase would require 535 (95% CI, 434-666) days, with an associated mortality of 1172 (95% CI, 466-1859). A combination of converting 40% cases and increasing capacity by 20% would clear the backlog within a year (343 (95% CI, 281-410) days) with 784 (95% CI, 292-1324) deaths whilst awaiting treatment.\n\nConclusionA strategy change to the management of severe AS is required to reduce the NHS backlog and waiting list deaths during the post-COVID-19 recovery period. However, plausible adaptations will still incur a substantial wait and many hundreds dying without treatment.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Mariam Ayed", - "author_inst": "Ministry of Health" + "author_name": "Christian P Stickels", + "author_inst": "Department of Mathematical Sciences, University of Liverpool, UK" }, { - "author_name": "Alia Embaireeg", - "author_inst": "Neonatal Department, Farwaniya Hospital, Kuwait." + "author_name": "Ramesh Nadarajah", + "author_inst": "Leeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, UK" }, { - "author_name": "Mais Kartam", - "author_inst": "Paediatric Department, Farwaniya Hospital, Kuwait." + "author_name": "Chris P Gale", + "author_inst": "Leeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, UK" }, { - "author_name": "Kiran More", - "author_inst": "Division of Neonatology, Sidra Medicine, Doha, Qatar. Weill Cornell Medicine, Doha, Qatar" + "author_name": "Houyuan Jiang", + "author_inst": "Judge Business School, University of Cambridge, UK" }, { - "author_name": "Mafaza Alqallaf", - "author_inst": "Paediatric Department, Adan Hospital, Kuwait." + "author_name": "Kieran J Sharkey", + "author_inst": "Department of Mathematical Sciences, University of Liverpool, UK" }, { - "author_name": "Abdullah AlNafisi", - "author_inst": "Paediatric Department, Sabah Hospital, Kuwait." + "author_name": "Ben Gibbison", + "author_inst": "Cardiac Anaesthesia and Intensive Care, Bristol Medical School, University of Bristol, UK" }, { - "author_name": "Zainab Alsaffar", - "author_inst": "Paediatric Department, Farwaniya Hospital, Kuwait." + "author_name": "Nick Holliman", + "author_inst": "School of Computing, Newcastle University, UK" }, { - "author_name": "Zainab Bahzad", - "author_inst": "Paediatric Department, Adan Hospital, Kuwait." + "author_name": "Sara Lombardo", + "author_inst": "Mathematical Sciences, Loughborough University, UK" }, { - "author_name": "Yasmeen Buhamad", - "author_inst": "Paediatric Department, Farwaniya Hospital, Kuwait." + "author_name": "Lars Schewe", + "author_inst": "School of Mathematics, University of Edinburgh, UK" }, { - "author_name": "Haneen Alsayegh", - "author_inst": "Paediatric Department, Amiri Hospital, Kuwait." + "author_name": "Matteo Sommacal", + "author_inst": "Department of Mathematics, Physics and Electrical Engineering, Northumbria University, UK" }, { - "author_name": "Wadha AFouzan", - "author_inst": "Department of Microbiology, Faculty of Medicine, Kuwait University, Jabriya, Kuwait" + "author_name": "Louise Sun", + "author_inst": "Division of Cardiac Anaesthesiology, University of Ottawa Heart Institute, Canada" }, { - "author_name": "Hessa Alkandari", - "author_inst": "Pediatric Department, Farwaniya Hospital, Kuwait." + "author_name": "Jonathan Weir-McCall", + "author_inst": "Department of Radiology, University of Cambridge, UK" + }, + { + "author_name": "Katherine Cheema", + "author_inst": "British Heart Foundation, UK" + }, + { + "author_name": "James H F Rudd", + "author_inst": "Division of Cardiovascular Medicine, University of Cambridge, UK" + }, + { + "author_name": "Mamas A. Mamas", + "author_inst": "Keele Cardiovascular Research Group, Keele University, UK" + }, + { + "author_name": "Feryal Erhun", + "author_inst": "Judge Business School, University of Cambridge, UK" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2021.11.12.21266292", @@ -495077,25 +493273,209 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.11.08.21265055", - "rel_title": "A Mathematical Model for Stability Analysis of Covid like Epidemic/Endemic/Pandemic", + "rel_doi": "10.1101/2021.11.11.21266107", + "rel_title": "Swiss public health measures associated with reduced SARS-CoV-2 transmission using genome data", "rel_date": "2021-11-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.08.21265055", - "rel_abs": "The transmission and spread of infectious disease like Covid-19 occurs through horizontal and vertical mode. The causative pathogens for such kind of disease may be bacterium, protozoa, virus or toxin. The infectious diseases like AIDS, SARS, MARS, Polio Plague, Bubonic Plague and Covid-19 have destroyed the social and economic structure of world population. The world scientific community adopts different mechanisms to model and analyse the population dynamics of infectious disease outbreaks. Mathematical Modelling is the most effective tool to take the informed decision about the containment, control and eradication of the pandemic. The main focus of Government and public health authorities is to design the strategy in destabilising the spread and impact of the infections. A series of models-SIR, SEIR, SEIRD, SEAIHCRD, SAUQAR has been under study to combat the Covid-19 since its inception. An effort has been made to design the model based on reproduction number, endemic equilibrium and disease-free equilibrium to curtail the impact of Covid-19 through stability analysis methods-Hurwitz stability criteria, Lyapunov Method and Linear Stability Analysis.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.11.21266107", + "rel_abs": "Genome sequences from evolving infectious pathogens allow quantification of case introductions and local transmission dynamics. We sequenced 11,357 SARS-CoV-2 genomes from Switzerland in 2020 - the 6th largest effort globally. Using a representative subset of these data, we estimated viral introductions to Switzerland and their persistence over the course of 2020. We contrast these estimates with simple null models representing the absence of certain public health measures. We show that Switzerlands border closures de-coupled case introductions from incidence in neighboring countries. Under a simple model, we estimate an 86 - 98% reduction in introductions during Switzerlands strictest border closures. Furthermore, the Swiss 2020 partial lockdown roughly halved the time for sampled introductions to die out. Finally, we quantified local transmission dynamics once introductions into Switzerland occurred, using a novel phylodynamic model. We find that transmission slowed 35 - 63% upon outbreak detection in summer 2020, but not in fall. This finding may indicate successful contact tracing over summer before overburdening in fall. The study highlights the added value of genome sequencing data for understanding transmission dynamics.\n\nOne Sentence SummaryPhylogenetic and phylodynamic methods quantify the drop in case introductions and local transmission with implementation of public health measures.", + "rel_num_authors": 48, "rel_authors": [ { - "author_name": "Sanjeev Kumar", - "author_inst": "Lovely Professional University" + "author_name": "Sarah A. Nadeau", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" + }, + { + "author_name": "Timothy G. Vaughan", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" + }, + { + "author_name": "Christiane Beckmann", + "author_inst": "Viollier AG; Allschwil, Switzerland" + }, + { + "author_name": "Ivan Topolsky", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" + }, + { + "author_name": "Chaoran Chen", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" + }, + { + "author_name": "Emma Hodcroft", + "author_inst": "Institute for Social and Preventive Medicine, University of Bern; Bern, Switzerland" + }, + { + "author_name": "Tobias Schaer", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" + }, + { + "author_name": "Ina Nissen", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" + }, + { + "author_name": "Natascha Santacroce", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" + }, + { + "author_name": "Elodie Burcklen", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" + }, + { + "author_name": "Pedro Ferreira", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" + }, + { + "author_name": "Kim Philipp Jablonski", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" + }, + { + "author_name": "Susana Posada-Cespedes", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" + }, + { + "author_name": "Vincenzo Capece", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" + }, + { + "author_name": "Sophie Seidel", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" + }, + { + "author_name": "Noemi Santamaria de Souza", + "author_inst": "Department of Biology, ETH Zurich; Zurich, Switzerland" + }, + { + "author_name": "Julia M. Martinez-Gomez", + "author_inst": "Department of Dermatology, University Hospital Zurich, University of Zurich; Zurich, Switzerland" + }, + { + "author_name": "Phil Cheng", + "author_inst": "Department of Dermatology, University Hospital Zurich, University of Zurich; Zurich, Switzerland" + }, + { + "author_name": "Philipp P. Bosshard", + "author_inst": "Department of Dermatology, University Hospital Zurich, University of Zurich; Zurich, Switzerland" + }, + { + "author_name": "Mitchell P. Levesque", + "author_inst": "Department of Dermatology, University Hospital Zurich, University of Zurich; Zurich, Switzerland" + }, + { + "author_name": "Verena Kufner", + "author_inst": "Institute of Medical Virology, University of Zurich; Zurich, Switzerland" + }, + { + "author_name": "Stefan Schmutz", + "author_inst": "Institute of Medical Virology, University of Zurich; Zurich, Switzerland" + }, + { + "author_name": "Maryam Zaheri", + "author_inst": "Institute of Medical Virology, University of Zurich; Zurich, Switzerland" + }, + { + "author_name": "Michael Huber", + "author_inst": "Institute of Medical Virology, University of Zurich; Zurich, Switzerland" + }, + { + "author_name": "Alexandra Trkola", + "author_inst": "Institute of Medical Virology, University of Zurich; Zurich, Switzerland" + }, + { + "author_name": "Samuel Cordey", + "author_inst": "Laboratory of Virology, Division of Infectious Diseases and Division of Laboratory Medicine, University Hospitals of Geneva and Faculty of Medicine, University " + }, + { + "author_name": "Florian Laubscher", + "author_inst": "Laboratory of Virology, Division of Infectious Diseases and Division of Laboratory Medicine, University Hospitals of Geneva and Faculty of Medicine, University " + }, + { + "author_name": "Ana Rita Goncalves", + "author_inst": "Swiss National Reference Centre for Influenza, University Hospitals of Geneva; Geneva, Switzerland" + }, + { + "author_name": "Sebastien Aeby", + "author_inst": "Institute of Microbiology, University Hospital Centre and University of Lausanne; Lausanne, Switzerland" + }, + { + "author_name": "Trestan Pillonel", + "author_inst": "Institute of Microbiology, University Hospital Centre and University of Lausanne; Lausanne, Switzerland" + }, + { + "author_name": "Damien Jacot", + "author_inst": "Institute of Microbiology, University Hospital Centre and University of Lausanne; Lausanne, Switzerland" }, { - "author_name": "Amit Kumar Awasthi", - "author_inst": "Lovely Professional University Punjab India" + "author_name": "Claire Bertelli", + "author_inst": "Institute of Microbiology, University Hospital Centre and University of Lausanne; Lausanne, Switzerland" + }, + { + "author_name": "Gilbert Greub", + "author_inst": "Institute of Microbiology, University Hospital Centre and University of Lausanne; Lausanne, Switzerland" + }, + { + "author_name": "Karoline Leuzinger", + "author_inst": "Division of Clinical Virology, University Hospital Basel and Department of Biomedicine, University of Basel; Basel, Switzerland" + }, + { + "author_name": "Madlen Stange", + "author_inst": "Department of Biomedicine, University of Basel and Division of Clinical Bacteriology and Mycology, University Hospital Basel; Basel, Switzerland" + }, + { + "author_name": "Alfredo Mari", + "author_inst": "Department of Biomedicine, University of Basel and Division of Clinical Bacteriology and Mycology, University Hospital Basel; Basel, Switzerland" + }, + { + "author_name": "Tim Roloff", + "author_inst": "Department of Biomedicine, University of Basel and Division of Clinical Bacteriology and Mycology, University Hospital Basel; Basel, Switzerland" + }, + { + "author_name": "Helena Seth-Smith", + "author_inst": "Department of Biomedicine, University of Basel and Division of Clinical Bacteriology and Mycology, University Hospital Basel; Basel, Switzerland" + }, + { + "author_name": "Hans H. Hirsch", + "author_inst": "Division of Clinical Virology, University Hospital Basel and Department of Biomedicine, University of Basel; Basel, Switzerland" + }, + { + "author_name": "Adrian Egli", + "author_inst": "Department of Biomedicine, University of Basel and Division of Clinical Bacteriology and Mycology, University Hospital Basel; Basel, Switzerland" + }, + { + "author_name": "Maurice Redondo", + "author_inst": "Viollier AG; Allschwil, Switzerland" + }, + { + "author_name": "Olivier Kobel", + "author_inst": "Viollier AG; Allschwil, Switzerland" + }, + { + "author_name": "Christoph Noppen", + "author_inst": "Viollier AG; Allschwil, Switzerland" + }, + { + "author_name": "Louis du Plessis", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" + }, + { + "author_name": "Niko Beerenwinkel", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" + }, + { + "author_name": "Richard A. Neher", + "author_inst": "Biozentrum, University of Basel; Basel, Switzerland" + }, + { + "author_name": "Christian Beisel", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" + }, + { + "author_name": "Tanja Stadler", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich; Basel, Switzerland" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -496967,69 +495347,41 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2021.11.08.21266047", - "rel_title": "COVID-19 vaccinations: perceptions and behaviours in people with primary ciliary dyskinesia", + "rel_doi": "10.1101/2021.11.10.21266084", + "rel_title": "Genomic landscape of SARS-CoV-2 pandemic in Brazil suggests an external P.1 variant origin", "rel_date": "2021-11-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.08.21266047", - "rel_abs": "Primary ciliary dyskinesia (PCD) is a rare genetic disease that causes recurrent respiratory infections. People with PCD may be at high risk of severe COVID-19 and vaccination against SARS-CoV-2 is therefore important. We studied vaccination willingness, speed of vaccination uptake, side effects, and changes in social contact behavior after vaccination in people with PCD. We used data from COVID-PCD, an international participatory cohort study. A questionnaire was e-mailed to participants in May 2021 that asked about COVID-19 vaccinations. 423 participants from 31 countries replied (median age: 30 years; 261 (62%) female). Vaccination uptake and willingness was high with 273 of 287 adults (96%) being vaccinated or willing to be in June 2021; only 4% were hesitant. The most common reasons for hesitancy were fear of side effects (reported by 88%). Mild side effects were common but no participant reported severe side effects. Half of participants changed their social contact behaviour after vaccination by seeing friends and family more often. The high vaccination willingness in the study population might reflect the extraordinary effort taken by PCD support groups to inform people about COVID-19 vaccination. Clear and specific public information and involvement of representatives is important for high vaccine uptake.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.10.21266084", + "rel_abs": "Brazil was the epicenter of worldwide pandemics at the peak of its second wave. The genomic/proteomic perspective of the COVID-19 pandemic in Brazil can bring new light to understand the global pandemics behavior. In this study, we track SARS-CoV-2 molecular information in Brazil using real-time bioinformatics and data science strategies to provide a comparative and evolutive panorama of the lineages in the country. SWeeP vectors represented the Brazilian and worldwide genomic/proteomic data from GISAID between 02/2020 - 08/2021. Clusters were analyzed and compared with PANGO lineages. Hierarchical clustering provided phylogenetic and evolutionary analysis of the lineages, and we tracked the P.1 (Gamma) variant origin. The genomic diversity based on Chaos estimation allowed us to compare richness and coverage among Brazilian states and other representative countries. We found that epidemics in Brazil occurred in two distinct moments, with different genetic profiles. The P.1 lineages emerged in the second wave, which was more aggressive. We could not trace the origin of P.1 from the variants present in Brazil in 2020. Instead, we found evidence pointing to its external source and a possible recombinant event that may relate P.1 to the B.1.1.28 variant subset. We discussed the potential application of the pipeline for emerging variants detection and the stability of the PANGO terminology over time. The diversity analysis showed that the low coverage and unbalanced sequencing among states in Brazil could have allowed the silenty entry and dissemination of P.1 and other dangerous variants. This comparative and evolutionary analysis may help to understand the development and the consequences of the entry of variants of concern (VOC).", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Eva Sophie Lunde Pedersen", - "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland" - }, - { - "author_name": "Maria Christina Mallet", - "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland" - }, - { - "author_name": "Yin Ting Lam", - "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland" - }, - { - "author_name": "Sara Bellu", - "author_inst": "Associazione italiana Discinesia Ciliare Primaria Sindrome di Kartagener Onlus, Italy" - }, - { - "author_name": "Isabelle Cizeau", - "author_inst": "Association ADCP, Saint-Etienne, France" - }, - { - "author_name": "Fiona Copeland", - "author_inst": "PCD support UK, London, UK" - }, - { - "author_name": "Trini Lopez Fernandez", - "author_inst": "Asociacion Espanola de Pacientes con Discinesia Ciliar Primaria, Spain" - }, - { - "author_name": "Michele Manion", - "author_inst": "PCD Foundation, United States" + "author_name": "Camila Pereira Perico", + "author_inst": "Graduate Program in Bioinformatics, Federal University of Parana, Curtiba, Parana, Brazil" }, { - "author_name": "Amanda Harris", - "author_inst": "Primary Ciliary Dyskinesia Centre, NIHR Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK" + "author_name": "Camilla Reginatto De Pierri", + "author_inst": "Department of Biochemistry and Molecular Biology, Federal University of Parana, Curtiba, Parana, Brazil" }, { - "author_name": "Jane S Lucas", - "author_inst": "Primary Ciliary Dyskinesia Centre, NIHR Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK; University of Southam" + "author_name": "Giuseppe Pasqualato Neto", + "author_inst": "Graduate Program in Bioinformatics, Federal University of Parana, Curtiba, Parana, Brazil" }, { - "author_name": "Francesca Santamaria", - "author_inst": "Department of Translational Medical Sciences, Federico II University, Naples, Italy" + "author_name": "Danrley Rafael Fernandes", + "author_inst": "Graduate Program in Bioinformatics, Federal University of Parana, Curtiba, Parana, Brazil" }, { - "author_name": "- COVID-PCD patient advisory group", - "author_inst": "" + "author_name": "Fabio de Oliveira Pedrosa", + "author_inst": "Department of Biochemistry and Molecular Biology, Federal University of Parana, Curtiba, Parana, Brazil" }, { - "author_name": "Myrofora Goutaki", - "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Division of Paediatric Respiratory Medicine and Allergology, Department of P" + "author_name": "Emanuel Maltempi de Souza", + "author_inst": "Department of Biochemistry and Molecular Biology, Federal University of Parana, Curtiba, Parana, Brazil" }, { - "author_name": "Claudia E. Kuehni", - "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Division of Paediatric Respiratory Medicine and Allergology, Department of P" + "author_name": "Roberto Tadeu Raittz", + "author_inst": "Graduate Program in Bioinformatics, Federal University of Parana, Curtiba, Parana, Brazil" } ], "version": "1", @@ -498636,43 +496988,23 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.05.21265998", - "rel_title": "The preparedness and response to COVID-19 in a quaternary Intensive Care Unit in Australia: perspectives and insights from frontline critical care clinicians", + "rel_doi": "10.1101/2021.11.08.467715", + "rel_title": "SARS-CoV-2 triggered excessive inflammation and abnormal energy metabolism in gut microbiota", "rel_date": "2021-11-09", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.05.21265998", - "rel_abs": "ObjectivesThis study was conducted to explore the perspectives and opinions of Intensive Care Unit (ICU) nurses and doctors at a COVID-19 designated pandemic hospital concerning the preparedness and response to COVID-19 and to consolidate the lessons learnt for crisis/disaster management in the future.\n\nDesignA qualitative study using in-depth interviews (IDIs) and focus group discussions (FGDs). Purposeful sampling was conducted to identify participants. A semi-structured guide was utilised to facilitate in-depth interviews with individual participants. Two focus group discussions were conducted, one with the ICU doctors and another with the ICU nurses. Thematic analysis identified themes and subthemes informing about the level of preparedness, response measures, processes, and factors that were either facilitators or those that triggered challenges.\n\nSettingICU in a quaternary referral centre affiliated to a university teaching COVID-19 designated pandemic hospital, in Adelaide, South Australia.\n\nParticipantsThe participants included eight ICU doctors and eight ICU nurses for the in-depth interviews. Another sixteen clinicians participated in focus group discussions.\n\nResultsThe study identified six themes relevant to preparedness for, and responses to, COVID-19. The themes included: (1) Staff competence and planning, (2) Information transfer and communication, (3) Education and skills for the safe use of PPE, (4) Team dynamics and clinical practice, (5) leadership, and (6) Managing End-of life situations and expectations of caregivers.\n\nConclusionFindings highlight that preparedness and response to the COVID-19 crisis were proportionate to the situations gravity. More enablers than barriers were identified. However, opportunities for improvement were recognised in the domains of planning, logistics, self-sufficiency with equipment, operational and strategic oversight, communication, and managing end-of-life care.\n\nARTICLE SUMMARYO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LIThis is the first study that provided insights about clinicians perspectives and viewpoints to preparing and responding to COVID-19 in Australia.\nC_LIO_LIThe study used qualitative methodological framework allowing participants to provide in-depth accounts of processes and enabling factors and barriers.\nC_LIO_LIOur study provides information on issues that needs to be addressed from a critical care viewpoint and interventions that were effective and efficient\nC_LIO_LIThis is a single-center study in a developed country where experience is vastly different from other centers with higher demand and fewer resources\nC_LIO_LIWe acknowledge the potential for selection bias because of the qualitative design\nC_LI", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.08.467715", + "rel_abs": "Specific roles of gut microbes in COVID-19 progression are critical. However, the circumstantial mechanism remains elusive. In this study, shotgun metagenomic or metatranscriptomic sequencing were performed on fecal samples collected from 13 COVID-19 patients and controls. We analyzed the structure of gut microbiota, identified the characteristic bacteria and selected biomarkers. Further, GO, KEGG and eggNOG annotation were employed to correlate the taxon alteration and corresponding functions. The gut microbiota of COVID-19 patients was characterized by the enrichment of opportunistic pathogens and depletion of commensals. The abundance of Bacteroides spp. displayed an inverse relationship to COVID-19 severity, whereas Actinomyces oris, Escherichia coli, and Gemmiger formicilis were positively correlated with disease severity. The genes encoding oxidoreductase were significantly enriched in SARS-CoV-2 infection. KEGG annotation indicated that the expression of ABC transporter was up regulated, while the synthesis pathway of butyrate was aberrantly reduced. Furthermore, increased metabolism of lipopolysaccharide, polyketide sugar, sphingolipids and neutral amino acids was found. These results suggested the gut microbiome of COVID-19 patients was correlated with disease severity and in a state of excessive inflammatory response. Healthy gut microbiota may enhance antiviral defenses via butyrate metabolism, whereas the accumulation of opportunistic and inflammatory bacteria may exacerbate the disease progression.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "KRISHNASWAMY SUNDARARAJAN", - "author_inst": "Royal Adelaide Hospital" - }, - { - "author_name": "Peng Bi", - "author_inst": "The University of Adelaide" - }, - { - "author_name": "Adriana Milazzo", - "author_inst": "The University of Adelaide" - }, - { - "author_name": "Alexis Poole", - "author_inst": "The University of Adelaide" - }, - { - "author_name": "Benjamin Reddi", - "author_inst": "Royal Adelaide Hospital and The University of Adelaide" - }, - { - "author_name": "Afzal Mahmood", - "author_inst": "The University of Adelaide" + "author_name": "Tuoyu Zhou", + "author_inst": "Lanzhou university" } ], "version": "1", "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.11.09.21266122", @@ -500526,39 +498858,51 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.11.04.467291", - "rel_title": "Stable Cell Clones Harboring Self-Replicating SARS-CoV-2 RNAs for Drug Screen", + "rel_doi": "10.1101/2021.11.06.467547", + "rel_title": "Accelerated decline of genome heterogeneity in the SARS-CoV-2 coronavirus", "rel_date": "2021-11-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.04.467291", - "rel_abs": "The development of antivirals against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been hampered by the lack of efficient cell-based replication systems that are amenable to high-throughput screens in biosafety level 2 laboratories. Here we report that stable cell clones harboring autonomously replicating SARS-CoV-2 RNAs without S, M, E genes can be efficiently derived from the baby hamster kidney (BHK-21) cell line when a pair of mutations were introduced into the non-structural protein 1 (Nsp1) of SARS-CoV-2 to ameliorate cellular toxicity associated with virus replication. In a proof-of-concept experiment we screened a 273-compound library using replicon cells and identified three compounds as novel inhibitors of SARS-CoV-2 replication. Altogether, this work establishes a robust, cell-based system for genetic and functional analyses of SARS-CoV-2 replication and for the development of antiviral drugs.\n\nIMPORTANCESARS-CoV-2 replicon systems that have been reported up to date were unsuccessful in deriving stable cell lines harboring non-cytopathic replicons. The transient expression of viral sgmRNA or a reporter gene makes it impractical for industry-scale screening of large compound libraries using these systems. Here, for the first time, we derived stable cell clones harboring the SARS-CoV-2 replicon. These clones may now be conveniently cultured in a standard BSL-2 laboratory for high throughput screen of compound libraries. This achievement represents a ground-breaking discovery that will greatly accelerate the pace of developing treatments for COVID-19.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.06.467547", + "rel_abs": "During the spread of the COVID-19 pandemic, the SARS-CoV-2 coronavirus underwent mutation and recombination events that altered its genome compositional structure, thus providing an unprecedented opportunity to search for adaptive evolutionary trends in real-time. The mutation rate in coronavirus is known to be lower than expected for neutral evolution, thus suggesting a role for natural selection. We summarize the compositional heterogeneity of each viral genome by computing its Sequence Compositional Complexity (SCC). To study the full range of SCC diversity, random samples of high-quality coronavirus genomes covering pandemic time span were analyzed. We then search for evolutionary trends that could inform on the adaptive process of the virus to its human host by computing the phylogenetic ridge regression of SCC against time (i.e., the collection date of each viral isolate). In early samples, we find no statistical support for any trend in SCC, although the viral genome appears to evolve faster than Brownian Motion (BM) expectation. However, in samples taken after the emergence of high fitness variants, and despite the brief time span elapsed, a driven decreasing trend for SCC, and an increasing one for its absolute evolutionary rate, are detected, pointing to a role for selection in the evolution of SCC in coronavirus genomes. We conclude that the higher fitness of variant genomes leads to adaptive trends of SCC over pandemic time in the coronavirus.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Shufeng Liu", - "author_inst": "US FDA" + "author_name": "Jose L. Oliver", + "author_inst": "Universidad de Granada" }, { - "author_name": "Chao-Kai Chou", - "author_inst": "US FDA" + "author_name": "Pedro Bernaola-Galvan", + "author_inst": "Universidad de Malaga" }, { - "author_name": "Wells W Wu", - "author_inst": "US FDA" + "author_name": "Francisco Perfectti", + "author_inst": "Universidad de Granada" }, { - "author_name": "Binquan Luan", - "author_inst": "IBM Thomas J. Watson Research" + "author_name": "Cristina Gomez-Martin", + "author_inst": "University of Granada" }, { - "author_name": "Tony T Wang", - "author_inst": "U.S. Food and Drug Administration" + "author_name": "Silvia Castiglione", + "author_inst": "Dipartimento di Scienze della Terra, dell Ambiente e delle Risorse, Universita di Napoli Federico II, 80126, Napoli, Italy" + }, + { + "author_name": "Pasquale Raia", + "author_inst": "Dipartimento di Scienze della Terra, dell Ambiente e delle Risorse, Universita di Napoli Federico II, 80126, Napoli, Italy" + }, + { + "author_name": "Miguel Verdu", + "author_inst": "Institute of Integrative Systems Biology (I2Sysbio), University of Valencia and Consejo Superior de Investigaciones Cientificas (CSIC), 46980, Valencia, Spain" + }, + { + "author_name": "Andres Moya", + "author_inst": "Universitat de Valencia" } ], "version": "1", - "license": "cc0", + "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "genomics" }, { "rel_doi": "10.1101/2021.11.03.21265533", @@ -502324,115 +500668,43 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2021.11.05.467458", - "rel_title": "Single cell RNA-seq uncovers the nuclear decoy lincRNA PIRAT as a regulator of systemic monocyte immunity during COVID-19", + "rel_doi": "10.1101/2021.11.04.467378", + "rel_title": "A high-throughput, automated, cell-free expression and screening platform for antibody discovery", "rel_date": "2021-11-05", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.05.467458", - "rel_abs": "The systemic immune response to viral infection is shaped by master transcription factors such as NF{kappa}B or PU.1. Although long non-coding RNAs (lncRNAs) have been suggested as important regulators of transcription factor activity, their contributions to the systemic immunopathologies observed during SARS-CoV-2 infection have remained unknown. Here, we employed a targeted single-cell RNA-seq approach to reveal lncRNAs differentially expressed in blood leukocytes during severe COVID-19. Our results uncover the lncRNA PIRAT as a major PU.1 feedback-regulator in monocytes, governing the production of the alarmins S100A8/A9 - key drivers of COVID-19 pathogenesis. Knockout and transgene expression, combined with chromatin-occupancy profiling characterized PIRAT as a nuclear decoy RNA, diverting the PU.1 transcription factor from alarmin promoters to dead-end pseudogenes in naive monocytes. NF{kappa}B-dependent PIRAT down-regulation during COVID-19 consequently releases a transcriptional brake, fueling alarmin production. Our results suggest a major role of nuclear noncoding RNA circuits in systemic antiviral responses to SARS-CoV-2 in humans.", - "rel_num_authors": 24, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.04.467378", + "rel_abs": "Antibody discovery is bottlenecked by the individual expression and evaluation of antigen-specific hits. Here, we address this gap by developing an automated workflow combining cell-free DNA template generation, protein synthesis, and high-throughput binding measurements of antibody fragments in a process that takes hours rather than weeks. We apply this workflow to 119 published SARS-CoV-2 neutralizing antibodies and demonstrate rapid identification of the most potent antibody candidates.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Marina Aznaourova", - "author_inst": "Philipps University Marburg" - }, - { - "author_name": "Nils Schmerer", - "author_inst": "Philipps University Marburg" - }, - { - "author_name": "Harshavardhan Janga", - "author_inst": "Philipps University Marburg" - }, - { - "author_name": "Zhenhua Zhang", - "author_inst": "Helmholtz-Centre for Infection Research (HZI)" - }, - { - "author_name": "Kim Pauck", - "author_inst": "Philipps University Marburg" - }, - { - "author_name": "Judith Hoppe", - "author_inst": "Freie Universitaet Berlin" - }, - { - "author_name": "Sarah M Volkers", - "author_inst": "Charite Universitaetsmedizin Berlin" - }, - { - "author_name": "Daniel Wendisch", - "author_inst": "Charite Universitaetsmedizin Berlin" - }, - { - "author_name": "Philipp Georg", - "author_inst": "Charite Universitaetsmedizin Berlin" - }, - { - "author_name": "Margrit Guendisch", - "author_inst": "Philipps University Marburg" - }, - { - "author_name": "Elisabeth Mack", - "author_inst": "Philipps University Marburg" - }, - { - "author_name": "Chrysanthi Skevaki", - "author_inst": "Philipps University Marburg" - }, - { - "author_name": "Christian Keller", - "author_inst": "Philipps University Marburg" - }, - { - "author_name": "Christian Bauer", - "author_inst": "Philipps University Marburg" - }, - { - "author_name": "Wilhelm Bertrams", - "author_inst": "Philipps University Marburg" - }, - { - "author_name": "Andrea Nist", - "author_inst": "Philipps University Marburg" - }, - { - "author_name": "Thorsten Stiewe", - "author_inst": "Philipps University Marburg" - }, - { - "author_name": "Achim D Gruber", - "author_inst": "Freie Universitaet Berlin" - }, - { - "author_name": "Clemens Ruppert", - "author_inst": "Universities of Giessen and Marburg Lung Center" + "author_name": "Andrew C Hunt", + "author_inst": "Northwestern University" }, { - "author_name": "Yang Li", - "author_inst": "Radboud University Nijmegen Medical Centre" + "author_name": "Bastian Vogeli", + "author_inst": "Northwestern University" }, { - "author_name": "Holger Garn", - "author_inst": "Philipps University Marburg" + "author_name": "Weston K. Kightlinger", + "author_inst": "Northwestern University" }, { - "author_name": "Leif E Sander", - "author_inst": "Charite Universitaetsmedizin Berlin" + "author_name": "Danielle J. Yoesep", + "author_inst": "Northwestern University" }, { - "author_name": "Bernd Schmeck", - "author_inst": "Philipps University Marburg" + "author_name": "Antje Kruger", + "author_inst": "Northwestern University" }, { - "author_name": "Leon N Schulte", - "author_inst": "Philipps University Marburg" + "author_name": "Michael C. Jewett", + "author_inst": "Northwestern University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "new results", - "category": "immunology" + "category": "synthetic biology" }, { "rel_doi": "10.1101/2021.11.04.21265937", @@ -503962,115 +502234,271 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.11.03.21265478", - "rel_title": "Waning of the Humoral Response to SARS-CoV-2 in Pregnancy is Variant-Dependent", + "rel_doi": "10.1101/2021.11.03.21265685", + "rel_title": "Hypothyroidism does not lead to worse prognosis in COVID-19: findings from the Brazilian COVID-19 registry", "rel_date": "2021-11-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.03.21265478", - "rel_abs": "ImportanceThe SARS-CoV-2 alpha variant posed increased risk for COVID-19 complications in pregnant women. However, its impact on the maternal humoral response and placental IgG transport remains unclear.\n\nObjectiveTo characterize the maternal humoral waning and neonate immunity acquired during the 3rd COVID-19 wave in Israel, dominated by the Alpha variant, as compared to earlier Wildtype infections and humoral response to vaccination across gestation.\n\nDesignMaternal and fetal blood serum were collected at delivery since April 2020 from parturients. Sera IgG and IgM titers were measured using the Milliplex MAP SARS-CoV-2 Antigen Panel supplemented with additional HA-coupled microspheres.\n\nSettingA nationwide multicenter cohort study on SARS-CoV-2 infections and vaccination during pregnancy.\n\nParticipantsExpectant women presenting for delivery were recruited at 8 medical centers across Israel and assigned to 3 primary groups: SARS-CoV-2 positive (n = 157) and fully vaccinated during pregnancy (n = 125), and unvaccinated noninfected controls matched to the infected group by BMI, maternal age, comorbidities and gestational age (n = 212). Eligibility criteria included pregnant women without active COVID-19 disease, age [≥]18 years and willingness to provide informed consent.\n\nMain Outcome(s) and Measure(s)Pregnant womens humoral response is dependent on the SARS-CoV-2 strain.\n\nResultsThe humoral response to infection as detected at birth, showed a gradual and significant decline as the interval between infection/vaccination and delivery increased. Significantly faster decay of antibody titers was found for infections occurring during the 3rd wave compared to earlier infections/vaccination. Cord blood IgG antigens levels correlated with maternal IgG. However, cord IgG-HA variance significantly differed in SARS-CoV2 infections as compared to the other groups. No sexual dimorphism in IgG transfer was observed. Lastly, high fetal IgM response to SARS-CoV-2 was detected in 17 neonates, all showing elevated IgM to N suggesting exposure to SARS-Cov-2 antigens.\n\nConclusions and RelevanceInfections occurring during the 3rd wave induced a faster decline in humoral response when compared to Wildtype infections or mRNA BNT162b2 vaccination during pregnancy, consistent with a shift in disease etiology and severity induced by the Alpha variant. Vaccination policies in previously infected pregnant women should consider the timing of exposure along pregnancy as well as the risk of infection to specific variants of concern.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat is the difference in the maternal-fetal humoral response between Alpha variant and SARS-CoV-2 Wildtype infections?\n\nFindingsIn this nationwide multicenter study including 494 pregnant women, the maternal humoral response to Alpha variant infection was weaker and shorter when compared to Wildtype infections. Placental transport compensated for the maternal waning of immunity. Fetal sex did not affect humoral response.\n\nMeaningVaccination policies should be adjusted to account for the timing of infection and the SARS-CoV-2 variant.", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.03.21265685", + "rel_abs": "BackgroundIt is not clear whether previous thyroid diseases influence the course and outcomes of COVID-19. The study aims to compare clinical characteristics and outcomes of COVID-19 patients with and without hypothyroidism.\n\nMethodsThe study is a part of a multicentric cohort of patients with confirmed COVID-19 diagnosis, including data collected from 37 hospitals. Matching for age, sex, number of comorbidities and hospital was performed to select the patients without hypothyroidism for the paired analysis.\n\nResultsFrom 7,762 COVID-19 patients, 526 had previously diagnosed hypothyroidism (50%) and 526 were selected as matched controls. The median age was 70 (interquartile range 59.0-80.0) years-old and 68.3% were females. The prevalence of underlying comorbidities were similar between groups, except for coronary and chronic kidney diseases, that had a higher prevalence in the hypothyroidism group (9.7% vs. 5.7%, p=0.015 and 9.9% vs. 4.8%, p=0.001, respectively). At hospital presentation, patients with hypothyroidism had a lower frequency of respiratory rate > 24 breaths per minute (36.1% vs 42.0%; p=0.050) and need of mechanical ventilation (4.0% vs 7.4%; p=0.016). D-dimer levels were slightly lower in hypothyroid patients (2.3 times higher than the reference value vs 2.9 times higher; p=0.037). In-hospital management was similar between groups, but hospital length-of-stay (8 vs 9 days; p=0.029) and mechanical ventilation requirement (25.4% vs. 33.1%; p=0.006) were lower for patients with hypothyroidism. There was a trend of lower in-hospital mortality in patients with hypothyroidism (22.1% vs. 27.0%; p=0.062).\n\nConclusionIn this large Brazilian COVID-19 Registry, patients with hypothyroidism had a lower requirement of mechanical ventilation, and showed a trend of lower in-hospital mortality. Therefore, hypothyroidism does not seem to be associated with a worse prognosis, and should not be considered among the comorbidities that indicate a risk factor for COVID-19 severity.", + "rel_num_authors": 63, "rel_authors": [ { - "author_name": "Romina Plitman Mayo", - "author_inst": "Department of Biological Regulation, The Weizmann Institute of Science, Rehovot, Israel" + "author_name": "Daniella Nunes Pereira", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Tal Raz", - "author_inst": "Koret School of Veterinary Medicine, The Robert H. Smith Faculty of Agriculture, Food & Environment, The Hebrew University of Jerusalem, Rehovot, Israel" + "author_name": "Leticia Ferreira Gontijo Silveira", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Bar Ben David", - "author_inst": "Department of Biological Regulation, The Weizmann Institute of Science, Rehovot, Israel" + "author_name": "Milena Maria Moreira Guimaraes", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Gila Meir", - "author_inst": "Department of Biological Regulation, The Weizmann Institute of Science, Rehovot, Israel" + "author_name": "Carisi Anne Polanczyk", + "author_inst": "Universidade Federal do Rio Grande do Sul. Coordinator of the Institute for Health Technology Assessment (IATS/CNPq)" }, { - "author_name": "Haim Barr", - "author_inst": "The Nancy and Stephen Grand Israel National Center for Personalized Medicine (G-INCPM), Weizmann Institute of Science, Rehovot, Israel" + "author_name": "Aline Gabrielle Sousa Nunes", + "author_inst": "Hospital Unimed-BH" }, { - "author_name": "Leonardo solmesky", - "author_inst": "The Nancy and Stephen Grand Israel National Center for Personalized Medicine (G-INCPM), Weizmann Institute of Science, Rehovot, Israel" + "author_name": "Andre Soares de Moura Costa", + "author_inst": "Hospitais da Rede Mater Dei, Belo Horizonte, Brasil." }, { - "author_name": "Rony Chen", - "author_inst": "Helen Schneider Hospital for Women, Rabin Medical Center, Petach Tikva; affiliated to Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel" + "author_name": "Barbara Lopes Farace", + "author_inst": "Hospital Risoleta Tolentino Neves" }, { - "author_name": "Ana Idelson", - "author_inst": "Helen Schneider Hospital for Women, Rabin Medical Center, Petach Tikva; affiliated to Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel" + "author_name": "Christiane Correa Rodrigues Cimini", + "author_inst": "Hospital Santa Rosalia" }, { - "author_name": "Lucilla Zorzetti", - "author_inst": "The Hillel Yaffe Medical Center, Hadera, Israel; affiliated to the Bruce Rappaport Faculty of Medicine, Technion- Israel Institute of Technology, Haifa, Israel" + "author_name": "Cintia Alcantara de Carvalho", + "author_inst": "Hospital Joao XXIII." }, { - "author_name": "Rinat Gabbay-Benziv", - "author_inst": "The Hillel Yaffe Medical Center, Hadera, Israel; affiliated to the Bruce Rappaport Faculty of Medicine, Technion- Israel Institute of Technology, Haifa, Israel" + "author_name": "Daniela Ponce", + "author_inst": "Hospital das Clinicas da Faculdade de Medicina de Botucatu" }, { - "author_name": "Yuval Yaffe Moshkovich", - "author_inst": "The Hillel Yaffe Medical Center, Hadera, Israel; affiliated to the Bruce Rappaport Faculty of Medicine, Technion- Israel Institute of Technology, Haifa, Israel" + "author_name": "Eliane Wurdig Roesch", + "author_inst": "Hospital de Clinicas de Porto Alegre" }, { - "author_name": "Tal Biron-Shental", - "author_inst": "Department of Obstetrics and Gynecology, Meir Medical Center, Kfar Saba, Israel; affiliated to Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israe" + "author_name": "Euler Roberto Fernandes Manenti", + "author_inst": "Hospital Mae de Deus" }, { - "author_name": "Gil Shechter-Maor", - "author_inst": "Department of Obstetrics and Gynecology, Meir Medical Center, Kfar Saba, Israel; affiliated to Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israe" + "author_name": "Fernanda Barbosa Lucas", + "author_inst": "Hospital Santo Antonio" }, { - "author_name": "Hen Yitzhak Sela", - "author_inst": "Department of Obstetrics and Gynecology, Shaare Zedek Medical Center; affiliated to the Faculty of Medicine, Hebrew University of Jerusalem, Israel" + "author_name": "Fernanda d'Athayde Rodrigues", + "author_inst": "Hospital de Clinicas de Porto Alegre" }, { - "author_name": "Itamar Glick", - "author_inst": "Department of Obstetrics and Gynecology, Shaare Zedek Medical Center; affiliated to the Faculty of Medicine, Hebrew University of Jerusalem, Israel" + "author_name": "Fernando Anschau", + "author_inst": "Grupo Hospitalar Conceicao. Professor of the Graduation Program on Evaluation and Production of Technologies for the Brazilian National Health System, Hospital " }, { - "author_name": "Hedi Benyamini Raischer", - "author_inst": "Department of Obstetrics and Gynecology, Emek Medical Center, Afula, Israel; affiliated to the Bruce Rappaport Faculty of Medicine, Technion- Israel Institute o" + "author_name": "Fernando Graca Aranha", + "author_inst": "Hospital SOS Cardio" }, { - "author_name": "Raed Salim", - "author_inst": "Department of Obstetrics and Gynecology, Emek Medical Center, Afula, Israel; affiliated to the Bruce Rappaport Faculty of Medicine, Technion- Israel Institute o" + "author_name": "Frederico Bartolazzi", + "author_inst": "Hospital Santo Antonio" }, { - "author_name": "Yariv Yogev", - "author_inst": "Lis Hospital for Women, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; affiliated to Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel" + "author_name": "Giovanna Grunewald Vietta", + "author_inst": "Hospital SOS Cardio" }, { - "author_name": "Ofer Beharier", - "author_inst": "Department of Obstetrics and Gynecology, Hadassah-Hebrew University Medical Center, Jerusalem, Israel" + "author_name": "Guilherme Fagundes Nascimento", + "author_inst": "Hospital Unimed BH" }, { - "author_name": "Debra Goldman-Wohl", - "author_inst": "Department of Obstetrics and Gynecology, Hadassah-Hebrew University Medical Center, Jerusalem, Israel" + "author_name": "Helena Duani", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Ariel Many", - "author_inst": "Lis Hospital for Women, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; affiliated to Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel" + "author_name": "Heloisa Reniers Vianna", + "author_inst": "Hospital Universitario Ciencias Medicas" }, { - "author_name": "Michal Kovo", - "author_inst": "Department of Obstetrics and Gynecology, Wolfson Medical Center, Holon; affiliated to Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel" + "author_name": "Henrique Cerqueira Guimaraes", + "author_inst": "Hospital Risoleta Tolentino Neves" }, { - "author_name": "Simcha Yagel", - "author_inst": "Department of Obstetrics and Gynecology, Hadassah-Hebrew University Medical Center, Jerusalem, Israel" + "author_name": "Jamille Hemetrio Salles Martins Costa", + "author_inst": "Hospital Marcio Cunha" }, { - "author_name": "Michal Neeman", - "author_inst": "Department of Biological Regulation, The Weizmann Institute of Science, Rehovot, Israel" + "author_name": "Joanna d'Arc Lyra Batista", + "author_inst": "University of Fronteira Sul" + }, + { + "author_name": "Joice Coutinho de Alvarenga", + "author_inst": "Hospital Joao XXIII" + }, + { + "author_name": "Jose Miguel Chatkin", + "author_inst": "Faculdade de Medicina, Universidade Catolica do Rio Grande do Sul" + }, + { + "author_name": "Julia Drumond Parreiras de Morais", + "author_inst": "Hospital Universitario Ciencias Medicas" + }, + { + "author_name": "Juliana Machado-Rugolo", + "author_inst": "Hospital das Clinicas da Faculdade de Medicina de Botucatu" + }, + { + "author_name": "Karen Brasil Ruschel", + "author_inst": "Hospital Mae de Deus, Hospital Universitario de Canoas, Universidade Federal do Rio Grande do Sul e Instituto de Avaliacao de Tecnologia em Saude" + }, + { + "author_name": "Lilian Santos Pinheiro", + "author_inst": "Universidade Federal dos Vales do Jequitinhonha e Mucuri" + }, + { + "author_name": "Luanna Silva Monteiro Menezes", + "author_inst": "Hospital Luxemburgo" + }, + { + "author_name": "Luciana Siuves Ferreira Couto", + "author_inst": "Hospital Luxemburgo" + }, + { + "author_name": "Luciane Kopittke", + "author_inst": "Hospital Nossa Senhora da Conceicao" + }, + { + "author_name": "Luis Cesar de Castro", + "author_inst": "Hospital Bruno Born" + }, + { + "author_name": "Luiz Antonio Nasi", + "author_inst": "Hospital Moinhos de Vento" + }, + { + "author_name": "Maderson Alvares de Souza Cabral", + "author_inst": "Universidade Federal de Minas Gerais" + }, + { + "author_name": "Maiara Anschau Floriani", + "author_inst": "Hospital Moinhos de Vento" + }, + { + "author_name": "Maira Dias Souza", + "author_inst": "Hospital Metropolitano Odilon Behrens" + }, + { + "author_name": "Marcelo Carneiro", + "author_inst": "Hospital Santa Cruz" + }, + { + "author_name": "Maria Aparecida Camargos Bicalho", + "author_inst": "Hospital Julia Kubitschek" + }, + { + "author_name": "Mariana Frizzo de Godoy", + "author_inst": "Hospital Sao Lucas PUCRS" + }, + { + "author_name": "Matheus Carvalho Alves Nogueira", + "author_inst": "Hospitais da Rede Mater Dei" + }, + { + "author_name": "Milton Henriques Guimaraes Junior", + "author_inst": "Hospital Marcio Cunha" + }, + { + "author_name": "Natalia da Cunha Severino Sampaio", + "author_inst": "Hospital Eduardo de Menezes" + }, + { + "author_name": "Neimy Ramos de Oliveira", + "author_inst": "Hospital Eduardo de Menezes" + }, + { + "author_name": "Pedro Ledic Assaf", + "author_inst": "Hospital Metropolitano Doutor Celio de Castro" + }, + { + "author_name": "Renan Goulart Finger", + "author_inst": "Hospital Regional do Oeste" + }, + { + "author_name": "Roberta Xavier Campos", + "author_inst": "Hospital Julia Kubitschek" + }, + { + "author_name": "Rochele Mosmann Menezes", + "author_inst": "Hospital Santa Cruz" + }, + { + "author_name": "Saionara Cristina Francisco", + "author_inst": "Hospital Metropolitano Doutor Celio de Castro" + }, + { + "author_name": "Samuel Penchel Alvarenga", + "author_inst": "Hospital Sao Joao de Deus" + }, + { + "author_name": "Silvana Mangeon Mereilles Guimaraes", + "author_inst": "Hospital Semper" + }, + { + "author_name": "Silvia Ferreira Araujo", + "author_inst": "Hospital Semper" + }, + { + "author_name": "Talita Fischer Oliveira", + "author_inst": "Hospital Metropolitano Odilon Behrens" + }, + { + "author_name": "Thulio Henrique Oliveira Diniz", + "author_inst": "Hospital Sao Joao de Deus" + }, + { + "author_name": "Yuri Carlotto Ramires", + "author_inst": "Hospital Bruno Born" + }, + { + "author_name": "Evelin Paola de Almeida Cenci", + "author_inst": "Hospital Universitario Canoas" + }, + { + "author_name": "Thainara Conceicao de Oliveira", + "author_inst": "Hospital Universitario Canoas" + }, + { + "author_name": "Alexandre Vargas Schwarzbold", + "author_inst": "Hospital Universitario de Santa Maria" + }, + { + "author_name": "Patricia Klarmann Ziegelmann", + "author_inst": "Hospital Tacchini" + }, + { + "author_name": "Roberta Pozza", + "author_inst": "Hospital Tacchini" + }, + { + "author_name": "Magda Carvalho Pires", + "author_inst": "Associate Professor and Statistician, Department of Statistics, Universidade Federal de Minas Gerais" + }, + { + "author_name": "Milena Soriano Marcolino", + "author_inst": "Associate Professor and Internal Medicine Physician. Department of Internal Medicine, Medical School; and Telehealth Center, University Hospital, Universidade F" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "obstetrics and gynecology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.11.02.466951", @@ -506380,75 +504808,47 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2021.10.31.21265718", - "rel_title": "Serological Response to BNT162b2 and ChAdOx1 nCoV-19 Vaccines in Patients with Inflammatory Bowel Disease on Biologic Therapies; A Multi-Center Prospective Study", + "rel_doi": "10.1101/2021.10.31.21265676", + "rel_title": "Underlying factors that influence the acceptance of COVID-19 vaccine in a country with a high vaccination rate", "rel_date": "2021-11-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.31.21265718", - "rel_abs": "IntroductionImmunogenicity of SARS-CoV-2 vaccines in patients with inflammatory bowel disease (IBD) on biologics are not well studied. The goal of this study is to measure serological response to BNT162b2 and ChAdOx1 nCoV-19 vaccines in patients with IBD receiving different biologic therapies.\n\nMethodWe performed a multi-center prospective study between August 1st, 2021, and September 15th, 2021. We measured seropositivity of SARS-CoV2 antibodies, SARS-CoV-2 IgG and neutralizing antibody concentrations, in patients with IBD receiving biologic therapies between 4-10 weeks after second dose or 3-6 weeks after first dose of vaccination with BNT162b2 or ChAdOx1 nCoV-19 vaccines.\n\nResultsThere were 126 patients enrolled (mean age, 31 years; 60% male; 71% Crohns disease, 29% ulcerative colitis). 92 patients were vaccinated with BNT162b2 vaccine (73%) and 34 patients with ChAdOx1 nCoV-19 vaccine (27%). The proportion of patients who achieved positive anti-SARS-CoV-2 IgG antibody levels after receiving 2 doses of the vaccine in patients treated with infliximab and adalimumab were 44 out of 59 patients (74.5%) and 13 out of 16 patients (81.2%), respectively. Whereas the proportion of patients who achieved positive anti-SARS-CoV-2 IgG antibody levels after receiving two doses of the vaccine in patients treated with ustekinumab and vedolizumab were 100% and 92.8%, respectively. In patients receiving infliximab and adalimumab, the proportion of patients who had positive anti-SARS-CoV-2 neutralizing antibody levels after two-dose vaccination was 40 out of 59 patients (67.7%) and 14 out 16 patients (87.5%), respectively. Whereas the proportions of patients who had positive anti-SARS-CoV-2 neutralizing antibody levels were 12 out of 13 patients (92.3%) and 13 out of 14 patients (92.8%) in patients receiving ustekinumab and vedolizumab.\n\nConclusionThe majority of patients with IBD on infliximab, adalimumab, and vedolizumab seroconverted after two doses of SARS-CoV-2 vaccination. All patients on ustekinumab seroconverted after two doses of SARS-CoV-2 vaccine. BNT162b2 and ChAdOx1 nCoV-19 SARS-CoV-2 are both likely to be effective after two doses in patients with IBD on biologics. A follow up larger studies are needed to evaluate if decay of antibodies occurs over time.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.31.21265676", + "rel_abs": "Control of the COVID-19 pandemic largely depends on the effectiveness of the vaccination. Several factors including vaccine hesitancy can affect the vaccination process. Understanding the factors that underlie the willingness to accept vaccination brings pivotal information to control the pandemic. We analyzed the association between the willingness level to accept the COVID-19 vaccine, and vaccine determinants amidst the Chilean vaccination process. Individual-level survey data was collected from nationally representative samples of 744 respondents, and multivariate regression models used to estimate the association between outcome and explanatory variables. We found that trust in the COVID-19 vaccine, scientists, and medical professionals increased the willingness to: accept the vaccine, a booster dose, annual vaccination, and children vaccination. Our results are critical to understand the acceptance of COVID-19 vaccines in the context of a country with one of the worlds highest vaccination rates. We provide information for decision-making, policy design and communication of vaccination programs.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Mohammad Shehab", - "author_inst": "Mubarak Hospital" - }, - { - "author_name": "Fatema Alrashed", - "author_inst": "Kuwait University" - }, - { - "author_name": "Ahmad Alfadhli", - "author_inst": "Mubarak Hospital" - }, - { - "author_name": "Khazna Alotaibi", - "author_inst": "Mubarak Hospital" - }, - { - "author_name": "Abdullah Alsahli", - "author_inst": "Mubarak Hospital" - }, - { - "author_name": "Hussain Mohammad", - "author_inst": "Mubarak Alkaber" - }, - { - "author_name": "Preethi Cherian", - "author_inst": "Department of Biochemistry and Molecular Biology, Dasman Diabetes Institute (DDI), Dasman, Kuwait" - }, - { - "author_name": "Irina Alkhairi", - "author_inst": "Department of Biochemistry and Molecular Biology, Dasman Diabetes Institute (DDI), Dasman, Kuwait" + "author_name": "Daniela Toro-Ascuy", + "author_inst": "Universidad Autonoma de Chile" }, { - "author_name": "Thangavel Alphonse Thanaraj", - "author_inst": "Department of Genetics and Bioinformatics, Dasman Diabetes Institute (DDI), Dasman, Kuwait" + "author_name": "Nicolas Cifuentes-Munoz", + "author_inst": "Universidad Autonoma de Chile" }, { - "author_name": "Arshad Channanath", - "author_inst": "Department of Genetics and Bioinformatics, Dasman Diabetes Institute (DDI), Dasman, Kuwait" + "author_name": "Andrea Avaria", + "author_inst": "Universidad Autonoma de Chile" }, { - "author_name": "Hamad Ali", - "author_inst": "Department of Medical Laboratory Sciences, Faculty of Allied Health Sciences, Health Sciences Center (HSC), Kuwait University, Jabriya, Kuwait" + "author_name": "Camila Pereira-Montecinos", + "author_inst": "Universidad Autonoma de Chile" }, { - "author_name": "Mohamed Abu-farha", - "author_inst": "Dasman Diabetes Institute" + "author_name": "Gilena Cruzat", + "author_inst": "Universidad Autonoma de Chile" }, { - "author_name": "Jehad Abubaker", - "author_inst": "Dasman Diabetes Institute" + "author_name": "Francisco Zorondo-Rodriguez", + "author_inst": "Universidad de Santiago de Chile" }, { - "author_name": "Fahd Al-Mulla", - "author_inst": "Dasman Diabetes Institute" + "author_name": "Loreto F Fuenzalida", + "author_inst": "Universidad Autonoma de Chile" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "gastroenterology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.11.01.21265653", @@ -508046,55 +506446,55 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.10.28.21265601", - "rel_title": "Factors associated with acceptance of a digital contact tracing application for COVID-19 in the Japanese working-age population", - "rel_date": "2021-10-30", + "rel_doi": "10.1101/2021.10.28.21265598", + "rel_title": "Personalized survival probabilities for SARS-CoV-2 positive patients by explainable machine learning", + "rel_date": "2021-10-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.28.21265601", - "rel_abs": "ObjectiveThis study aimed to determine factors associated with acceptance of a Digital Contact Tracing (DCT) app for Coronavirus Disease 2019 (COVID-19) in the Japanese working-age population.\n\nMethodsA cross-sectional study was performed for 27,036 full-time workers registered with an internet survey company during December 2020 in Japan.\n\nResultsThe rate of downloading the DCT app was 25.1%. The DCT app was more likely to be accepted by people with married status, university graduation or above, higher income, and occupations involving desk work. Fear of COVID-19 transmission, wearing a mask, using hand disinfection, willingness to be vaccinated against COVID-19, and presence of an acquaintance infected with COVID-19 were also associated with a greater likelihood of adopting the app.\n\nConclusionsThe present findings have important implications for widespread adoption of DCT apps in working-age populations in Japan and elsewhere.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.28.21265598", + "rel_abs": "Interpretable risk assessment of SARS-CoV-2 positive patients can aid clinicians to implement precision medicine. Here we trained a machine learning model to predict mortality within 12 weeks of a first positive SARS-CoV-2 test. By leveraging data on 33,928 confirmed SARS-CoV-2 cases in eastern Denmark, we considered 2,723 variables extracted from electronic health records (EHR) including demographics, diagnoses, medications, laboratory test results and vital parameters. A discrete-time framework for survival modelling enabled us to predict personalized survival curves and explain individual risk factors. Performances of weighted concordance index 0.95 and precision-recall area under the curve 0.71 were measured on the test set. Age, sex, number of medications, previous hospitalizations and lymphocyte counts were identified as top mortality risk factors. Our explainable survival model developed on EHR data also revealed temporal dynamics of the 22 selected risk factors. Upon further validation, this model may allow direct reporting of personalized survival probabilities in routine care.", "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Tomohiro Ishimaru", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Adrian G. Zucco", + "author_inst": "PERSIMUNE Center of Excellence, Rigshospitalet, Copenhagen, Denmark" }, { - "author_name": "Koki Ibayashi", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Rudi Agius", + "author_inst": "Department of Hematology, Rigshospitalet, Copenhagen, Denmark" }, { - "author_name": "Masako Nagata", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Rebecka Svanberg", + "author_inst": "Department of Hematology, Rigshospitalet, Copenhagen, Denmark" }, { - "author_name": "Seiichiro Tateishi", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Kasper S. Moestrup", + "author_inst": "PERSIMUNE Center of Excellence, Rigshospitalet, Copenhagen, Denmark" }, { - "author_name": "Ayako Hino", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Ramtin Z. Marandi", + "author_inst": "PERSIMUNE Center of Excellence, Rigshospitalet, Copenhagen, Denmark" }, { - "author_name": "Mayumi Tsuji", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Cameron Ross MacPherson", + "author_inst": "PERSIMUNE Center of Excellence, Rigshospitalet, Copenhagen, Denmark" }, { - "author_name": "Hajime Ando", - "author_inst": "Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health" + "author_name": "Jens Lundgren", + "author_inst": "PERSIMUNE Center of Excellence, Rigshospitalet, Copenhagen, Denmark" }, { - "author_name": "Keiji Muramatsu", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Sisse R. Ostrowski", + "author_inst": "Department of Clinical Immunology, Rigshospitalet, Copenhagen, Denmark" }, { - "author_name": "Yoshihisa Fujino", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Carsten U. Niemann", + "author_inst": "Department of Hematology, Rigshospitalet, Copenhagen, Denmark" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "health informatics" }, { "rel_doi": "10.1101/2021.10.28.21265499", @@ -509864,43 +508264,123 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2021.10.27.21265522", - "rel_title": "Impact of non-pharmacological interventions on COVID-19 boosting vaccine prioritization and vaccine-induced herd immunity: a population-stratified modelling study", + "rel_doi": "10.1101/2021.10.26.21265497", + "rel_title": "Implementation and extended evaluation of the Euroimmun Anti-SARS-CoV-2 IgG assay and its contribution to the United Kingdom's COVID-19 public health response", "rel_date": "2021-10-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.27.21265522", - "rel_abs": "BackgroundWhile the COVID-19 pandemic seemed far from the end, the booster vaccine project was proposed to further reduce the transmission risk and infections. However, handful studies have focused on questions that with limited vaccine capacity ether boosting high-risk workers first or prioritizing susceptible normal individuals is optimal, and vaccinating how many people can lead us to the goal of herd immunity. In this study we aimed to explore the conclusions of such two problems with consideration of non-pharmacological interventions including mandatory quarantine for international entrants, keeping social distance and wearing masks.\n\nMethodsBy implementing the corresponding proportion of individuals who remain infectious after four lengths of quarantine strategies to the novel population-stratified model, we quantified the impact of such measures on optimizing vaccine prioritization between high-risk workers and normal populations. Furthermore, by setting the hypothetical COVID-19 transmission severity (reproduction number, R0) to the level of the most contagious COVID-19 variant (B.1.617.2, delta variant, R0 = 5.0), we separately estimated the threshold vaccine coverage of five countries (China, United States, India, South Africa and Brazil) to reach herd immunity, with and without the consideration of interventions including wearings masks and keeping social distance. At last, the sensitive analysis of essential parameter settings was performed to examine the robustness of conclusions.\n\nResultsFor Chinese scenarios considered with moderate hypothetical transmission rate (R0 = 1.15-1.8), prioritizing high-risk workers the booster dose reached lower cumulative infections and deaths if at least 7-days of quarantine for international travelers is maintained, and the required screening time to remain such vaccinating strategy as optimal increased from 7-days to 21-days with the transmission severity. Although simply maintaining at least 7-days quarantine can lead to over 69.12% reduction in total infections, the improvement of longer quarantine strategies was becoming minimum and the least one was 2.28% between the 21 and the 28-days of quarantine. Besides, without the vaccination program, the impact of such measures on transmission control dropped significantly when R0 exceeded 1.5 and reached its minimal level when R0 equal to 2.5. On the other hand, when we combat the delta variant, the threshold vaccine coverage of total population to reach herd immunity lay within 74%-89% (corresponding to the vaccine efficiency from 70% to 50%), and such range decreased to 71%-84% if interventions including wearing mask and keeping social distance were implemented. Furthermore, Results of other countries with 85% vaccine efficiency were estimated at 79%, 91%, 94% and 96% for South Africa, Brazil, India and United States respectively.\n\nConclusionsNon-pharmacological interventions can substantially affect booster vaccination prioritization and the threshold condition to reach herd immunity. To combat the delta variant, restrictions need to be integrated with mass vaccination so that can reduce the transmission to the minimum level, and the 21-days might be the suggested maximum quarantine duration according to the cost-effectiveness. Besides, by implementing interventions, the requirement to reach herd immunity can be lower in all countries. Lastly, the following surveillance after vaccination can help ensure the real-time proportion of vaccinated individuals with sufficient protection.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.26.21265497", + "rel_abs": "1.In March 2020, the Rare and Imported Pathogens Laboratory at Public Health England, Porton Down, was tasked by the Department of Health and Social Care with setting up a national surveillance laboratory facility to study SARS-CoV-2 antibody responses and population-level sero-surveillance in response to the growing SARS-CoV-2 outbreak. In the following 12 months, the laboratory tested more than 160,000 samples, facilitating a wide range of research and informing PHE, DHSC and UK government policy. Here we describe the implementation and use of the Euroimmun anti-SARS-CoV-2 IgG assay and provide an extended evaluation of its performance. We present a markedly improved sensitivity of 91.39% ([≥]14 days 92.74%, [≥]21 days 93.59%) compared to our small-scale early study, and a specificity of 98.56%. In addition, we detail extended characteristics of the Euroimmun assay: intra- and inter-assay precision, correlation to neutralisation and assay linearity.", + "rel_num_authors": 26, "rel_authors": [ { - "author_name": "Zhiyao Li", - "author_inst": "Department of Health Statistics and Epidemiology, School of Public Health, Collaborative Innovation Center of Reverse Microbial Etiology, Shanxi Medical Univers" + "author_name": "Ashley David Otter", + "author_inst": "Diagnostics and Genomics, National Infection Service, Public Health England, Porton, SP4 0JG" }, { - "author_name": "Jiale Wang", - "author_inst": "Department of Health Statistics and Epidemiology, School of Public Health, Collaborative Innovation Center of Reverse Microbial Etiology, Shanxi Medical Univers" + "author_name": "Abbie Bown", + "author_inst": "Diagnostics and Genomics, National Infection Service, Public Health England, Porton, SP4 0JG" }, { - "author_name": "Boran Yang", - "author_inst": "Department of Health Statistics and Epidemiology, School of Public Health, Collaborative Innovation Center of Reverse Microbial Etiology, Shanxi Medical Univers" + "author_name": "Silvia D'Arcangelo", + "author_inst": "Diagnostics and Genomics, National Infection Service, Public Health England, Porton, SP4 0JG" }, { - "author_name": "Wenjing Li", - "author_inst": "Department of Occupational Health, School of Public Health, Shanxi Medical University, Taiyuan, China" + "author_name": "Daniel Bailey", + "author_inst": "Diagnostics and Genomics, National Infection Service, Public Health England, Porton, SP4 0JG" }, { - "author_name": "Jianguo Xu", - "author_inst": "State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Diseas" + "author_name": "Amanda Semper", + "author_inst": "Rare and Imported Pathogens Laboratory, Public Health England, Porton, SP4 0JG" }, { - "author_name": "Tong Wang", - "author_inst": "Department of Health Statistics and Epidemiology, School of Public Health, Collaborative Innovation Center of Reverse Microbial Etiology, Shanxi Medical Univers" + "author_name": "Jacqueline Hewson", + "author_inst": "SARS-CoV-2 serosurveillance laboratory, National Infection Service, Public Health England, Porton, SP4 0JG" + }, + { + "author_name": "Matthew Catton", + "author_inst": "Diagnostics and Genomics, National Infection Service, Public Health England, Porton, SP4 0JG" + }, + { + "author_name": "Prem Perumal", + "author_inst": "Diagnostics and Genomics, National Infection Service, Public Health England, Porton, SP4 0JG" + }, + { + "author_name": "Angela Sweed", + "author_inst": "Diagnostics and Genomics, National Infection Service, Public Health England, Porton, SP4 0JG" + }, + { + "author_name": "Jessica Jones", + "author_inst": "Rare and Imported Pathogens Laboratory, Public Health England, Porton, SP4 0JG" + }, + { + "author_name": "Heli Harvala", + "author_inst": "NHS Blood and Transfusion, Microbiology Services, Colindale, UK" + }, + { + "author_name": "Abigail Lamikanra", + "author_inst": "NHS Blood and Transfusion, Microbiology Services, Colindale, UK" + }, + { + "author_name": "Maria Zambon", + "author_inst": "Public Health England, Colindale, NW9 5EQ" + }, + { + "author_name": "Nick Andrews", + "author_inst": "Public Health England, Colindale, NW9 5EQ" + }, + { + "author_name": "Heather Whitaker", + "author_inst": "Public Health England, Colindale, NW9 5EQ" + }, + { + "author_name": "Ezra Linley", + "author_inst": "Seroepidemiology Unit, Public Health England, Manchester, M13 9WZ" + }, + { + "author_name": "Alexander J Mentzer", + "author_inst": "Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK" + }, + { + "author_name": "Donal Skelly", + "author_inst": "Oxford University Hospitals NHS Foundation Trust, Oxford, UK" + }, + { + "author_name": "Julian Knight", + "author_inst": "Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK" + }, + { + "author_name": "Paul Klenerman", + "author_inst": "Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford, UK" + }, + { + "author_name": "- PHE Porton Euroimmun testing group", + "author_inst": "-" + }, + { + "author_name": "Gayatri Amirthalingam", + "author_inst": "Public Health England, Colindale, NW9 5EQ" + }, + { + "author_name": "Stephen Taylor", + "author_inst": "Pathogen Immunology, Public Health England, Porton, SP4 0JG" + }, + { + "author_name": "Cathy Rowe", + "author_inst": "National Infection Service, Public Health England, Porton, SP4 0JG" + }, + { + "author_name": "Richard Vipond", + "author_inst": "Diagnostics and Genomics, National Infection Service, Public Health England, Porton, SP4 0JG" + }, + { + "author_name": "Tim Brooks", + "author_inst": "Rare and Imported Pathogens Laboratory, Public Health England, Porton, SP4 0JG" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.10.27.21265574", @@ -511618,87 +510098,67 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.10.24.465080", - "rel_title": "Targeting the chemokine receptor CXCR4 with histamine analogue to reduce inflammation in juvenile arthritis: a proof of concept for COVID-19 therapeutic approach", + "rel_doi": "10.1101/2021.10.25.465646", + "rel_title": "Structure, receptor recognition and antigenicity of the human coronavirus CCoV-HuPn-2018 spike glycoprotein", "rel_date": "2021-10-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.24.465080", - "rel_abs": "Among immune cells, activated monocytes play a detrimental role in chronic and viral-induced inflammatory pathologies. The uncontrolled activation of monocytes and the subsequent excessive production of inflammatory factors damage bone-cartilage joints in Juvenile Idiopathic Arthritis (JIA), a childhood rheumatoid arthritis (RA) disease. Inflammatory monocytes also exert a critical role in the cytokine storm induced by SARS-CoV2 infection in severe COVID-19 patients. The moderate beneficial effect of current therapies and clinical trials highlights the need of alternative strategies targeting monocytes to treat RA and COVID-19 pathologies. Here, we show that targeting CXCR4 with small amino compound such as the histamine analogue clobenpropit (CB) inhibits spontaneous and induced-production of a set of key inflammatory cytokines by monocytes isolated from blood and synovial fluids of JIA patients. Moreover, daily intraperitoneal CB treatment of arthritic mice results in significant decrease in circulating inflammatory cytokine levels, immune cell infiltrates, joints erosion, and bone resorption leading to reduction of disease progression. Finally, we provide the prime evidence that the exposure of whole blood from hospitalized COVID-19 patients to CB significantly reduces levels of key cytokine-storm-associated factors including TNF-, IL-6 and IL-1{beta}. These overall data show that targeting CXCR4 with CB-like molecules may represent a promising therapeutic option for chronic and viral-induced inflammatory diseases.", - "rel_num_authors": 17, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.25.465646", + "rel_abs": "The recent isolation of CCoV-HuPn-2018 from a child respiratory swab indicates that more coronaviruses are spilling over to humans than previously appreciated. Here, we determined cryo-electron microscopy structures of the CCoV-HuPn-2018 spike glycoprotein trimer in two distinct conformational states and identified that it binds canine, feline and porcine aminopeptidase N (APN encoded by ANPEP) orthologs which serve as entry receptors. Introduction of an oligosaccharide at position N739 of human APN renders cells susceptible to CCoV-HuPn-2018 spike-mediated entry, suggesting that single nucleotide polymorphisms could account for the detection of this virus in some individuals. Human polyclonal plasma antibodies elicited by HCoV-229E infection and a porcine coronavirus monoclonal antibody inhibit CCoV-HuPn-2018 S-mediated entry, indicating elicitation of cross-neutralizing activity among -coronaviruses. These data provide a blueprint of the CCoV-HuPn-2018 infection machinery, unveil the viral entry receptor and pave the way for vaccine and therapeutic development targeting this zoonotic pathogen.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Nassima Bekaddour", - "author_inst": "CNRS UMR-8601, CICB, 45 rue des Saints-Peres, 75006 Paris, France; Team Chemistry & Biology, Modeling & Immunology for Therapy, CBMIT, Paris, France; Universit&" - }, - { - "author_name": "Nikaia Smith", - "author_inst": "Translational Immunology Lab, Institut Pasteur, Paris, France" - }, - { - "author_name": "Benoit Beitz", - "author_inst": "BIOASTER, Lyon, France" - }, - { - "author_name": "Alba Llibre", - "author_inst": "Translational Immunology Lab, Institut Pasteur, Paris, France" - }, - { - "author_name": "Tom Dott", - "author_inst": "BIOASTER, Lyon, France" - }, - { - "author_name": "Anne Baudry", - "author_inst": "Universite de Paris, Paris, France; INSERM UMR-S1124, Team Stem Cells, Signaling and Prions, Paris, France" + "author_name": "M. Alejandra Tortorici", + "author_inst": "University of Washington" }, { - "author_name": "Anne-Sophie Korganow", - "author_inst": "INSERM UMR S1109, Faculte de Medecine, FHU OMICARE, FMTS, Universite de Strasbourg, Strasbourg, France; Department of Clinical Immunology and Internal Medicine," + "author_name": "Alexandra C Walls", + "author_inst": "University of Washington" }, { - "author_name": "S\u00e9bastien Nisole", - "author_inst": "IRIM, Universit\u00e9 de Montpellier, CNRS UMR 9004, Montpellier, France" + "author_name": "Anshu Joshi", + "author_inst": "University of Washington" }, { - "author_name": "Richard Mouy", - "author_inst": "Paediatric Haematology-Immunology and Rheumatology Department, RAISE Reference centre for rare diseases, Hopital Universitaire Necker, Assistance Publique-Hopit" + "author_name": "Young-Jun Park", + "author_inst": "University of Washington" }, { - "author_name": "Sylvain Breton", - "author_inst": "Paediatric Haematology-Immunology and Rheumatology Department, RAISE Reference centre for rare diseases, Hopital Universitaire Necker, Paris, France; Paediatric" + "author_name": "Rachel T Eguia", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "Brigitte Bader-Meunier", - "author_inst": "Universite de Paris, Paris, France; Hopital Universitaire Necker, Assistance Publique-Hopitaux de Paris, Paris, France; Imagine Institute, Paris, France; INSERM" + "author_name": "Terry Stevens-Ayers", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "Darragh Duffy", - "author_inst": "Translational Immunology Lab, Institut Pasteur, Paris, France" + "author_name": "Michael J Boeckh", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "Benjamin Terrier", - "author_inst": "Department of Internal Medicine, National Referral Center for Rare Systemic Autoimmune Diseases, Assistance Publique H\u00f4pitaux de Paris-Centre (APHP-CUP), U" + "author_name": "Amalio Talenti", + "author_inst": "Vir Biotechnology" }, { - "author_name": "Benoit Schneider", - "author_inst": "Universit\u00e9 de Paris, Paris, France; INSERM UMR-S1124, Team Stem Cells, Signaling and Prions, Paris, France" + "author_name": "Antonio Lanzavecchia", + "author_inst": "Vir Biotechnology" }, { - "author_name": "Pierre Quartier", - "author_inst": "Universite de Paris, Paris, France; Hopital Universitaire Necker, Assistance Publique-Hopitaux de Paris, Paris, France; Imagine Institute, Paris, France; INSERM" + "author_name": "Davide Corti", + "author_inst": "Humabs Biomed SA" }, { - "author_name": "Mathieu Rodero", - "author_inst": "CNRS UMR-8601, CICB, 45 rue des Saints-Peres, 75006 Paris, France; Team Chemistry & Biology, Modeling & Immunology for Therapy, CBMIT, Paris, France; Universit&" + "author_name": "Jesse D Bloom", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "Jean-Philippe Herbeuval", - "author_inst": "CNRS UMR-8601, CICB, 45 rue des Saints-Peres, 75006 Paris, France; Team Chemistry & Biology, Modeling & Immunology for Therapy, CBMIT, Paris, France; Universit&" + "author_name": "David Veesler", + "author_inst": "University of Washington" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.10.25.465714", @@ -513540,91 +512000,95 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.25.21265456", - "rel_title": "Trends in social exposure to SARS-Cov-2 in France. Evidence from the national socio-epidemiological cohort - EPICOV", + "rel_doi": "10.1101/2021.10.26.465865", + "rel_title": "Excessive inflammatory and metabolic responses to acute SARS-CoV-2 infection are associated with a distinct gut microbiota composition", "rel_date": "2021-10-26", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.25.21265456", - "rel_abs": "BackgroundWe aimed to study whether social patterns of exposure to SARS-CoV-2 infection changed in France throughout the year 2020, in light to the easing of social contact restrictions.\n\nMethodsA population-based cohort of individuals aged 15 years or over was randomly selected from the national tax register to collect socio-economic data, migration history, and living conditions in May and November 2020. Home self-sampling on dried blood was proposed to a 10% random subsample in May and to all in November. A positive anti-SARS-CoV-2 ELISA IgG result against the virus spike protein (ELISA-S) was the primary outcome. The design, including sampling and post-stratification weights, was taken into account in univariate and multivariate analyses.\n\nResultsOf the 134,391 participants in May, 107,759 completed the second questionnaire in November, and respectively 12,114 and 63,524 were tested. The national ELISA-S seroprevalence was 4.5% [95%CI: 4.0%-5.1%] in May and 6.2% [5.9%-6.6%] in November. It increased markedly in 18-24-year-old population from 4.8% to 10.0%, and among second-generation immigrants from outside Europe from 5.9% to 14.4%. This group remained strongly associated with seropositivity in November, after controlling for any contextual or individual variables, with an adjusted OR of 2.1 [1.7-2.7], compared to the majority population. In both periods, seroprevalence remained higher in healthcare professions than in other occupations.\n\nConclusionThe risk of Covid-19 infection increased among young people and second-generation migrants between the first and second epidemic waves, in a context of less strict social restrictions, which seems to have reinforced territorialized socialization among peers.", - "rel_num_authors": 18, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.26.465865", + "rel_abs": "Protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and associated clinical sequelae requires well-coordinated metabolic and immune responses that limit viral spread and promote recovery of damaged systems. In order to understand potential mechanisms and interactions that influence coronavirus disease 2019 (COVID-19) outcomes, we performed a multi-omics analysis on hospitalised COVID-19 patients and compared those with the most severe outcome (i.e. death) to those with severe non-fatal disease, or mild/moderate disease, that recovered. A distinct subset of 8 cytokines and 140 metabolites in sera identified those with a fatal outcome to infection. In addition, elevated levels of multiple pathobionts and lower levels of protective or anti-inflammatory microbes were observed in the faecal microbiome of those with the poorest clinical outcomes. Weighted gene correlation network analysis (WGCNA) identified modules that associated severity-associated cytokines with tryptophan metabolism, coagulation-linked fibrinopeptides, and bile acids with multiple pathobionts. In contrast, less severe clinical outcomes associated with clusters of anti-inflammatory microbes such as Bifidobacterium or Ruminococcus, short chain fatty acids (SCFAs) and IL-17A. Our study uncovered distinct mechanistic modules that link host and microbiome processes with fatal outcomes to SARS-CoV-2 infection. These features may be useful to identify at risk individuals, but also highlight a role for the microbiome in modifying hyperinflammatory responses to SARS-CoV-2 and other infectious agents.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Josiane WARSZAWSKI", - "author_inst": "INSERM CESP U1018, Universit\u00e9 Paris-Saclay,Service de sant\u00e9 publique, AP-HP" + "author_name": "Werner C. Albrich", + "author_inst": "Division of Infectious Diseases & Hospital Epidemiology, Cantonal Hospital St. Gallen, Rorschacherstrasse 95, 9007 St. Gallen, Switzerland" }, { - "author_name": "Laurence Meyer", - "author_inst": "Inserm U1018 - UMRS 1018, Facult\u00e9 de M\u00e9decine Paris-Sud - AP-HP, Epidemiology and Public Health Service" + "author_name": "Tarini Shankar Ghosh", + "author_inst": "School of Microbiology, APC Microbiome Ireland, University College Cork, National University of Ireland, Cork, Ireland" }, { - "author_name": "Jeanna-Eve Franck", - "author_inst": "Iris Institut de Recherche Interdisciplinaire sur les enjeux sociaux, Inserm, Aubervilliers, France" + "author_name": "Sinead Ahearn-Ford", + "author_inst": "APC Microbiome Ireland, University College Cork, National University of Ireland, Cork, Ireland" }, { - "author_name": "Delphine Rahib", - "author_inst": "Sant\u00e9 Publique France, Saint-Maurice France" + "author_name": "Flora Mikaeloff", + "author_inst": "The Systems Virology Lab, Division of Clinical Microbiology, Department of Laboratory Medicine, Karolinska Institute, ANA Futura, Campus Flemingsberg, Stockholm" }, { - "author_name": "Nathalie Lydie", - "author_inst": "Sant\u00e9 Publique France, Saint-Maurice France" + "author_name": "Nonhlanhla Lunjani", + "author_inst": "Department of Dermatology, University of Cape Town, Cape Town, South Africa; APC Microbiome Ireland, University College Cork, National University of Ireland, Co" }, { - "author_name": "Anne Gosselin", - "author_inst": "French Institute for Demographic Studies (INED), French Collaborative Institute on Migrations/CNRS, Aubervilliers, France" + "author_name": "Brian Forde", + "author_inst": "School of Microbiology, APC Microbiome Ireland, University College Cork, National University of Ireland, Cork, Ireland" }, { - "author_name": "Emilie Counil", - "author_inst": "French Institute for Demographic Studies (INED)" + "author_name": "Noemie Suh", + "author_inst": "Division of Intensive Care, Geneva University Hospitals and the University of Geneva Faculty of Medicine, 1211 Geneva, Switzerland" }, { - "author_name": "Robin Kreling", - "author_inst": "INSERM CESP U1018, Universit\u00e9 Paris-Saclay, Le Kremlin-Bic\u00eatre, France" + "author_name": "Gian-Reto Kleger", + "author_inst": "Division of Intensive Care, Cantonal Hospital St. Gallen, Rorschacherstrasse 95, 9007 St. Gallen, Switzerland" }, { - "author_name": "Sophie Novelli", - "author_inst": "INSERM CESP U1018, Universit\u00e9 Paris-Saclay, Le Kremlin-Bic\u00eatre, France" + "author_name": "Urs Pietsch", + "author_inst": "Department of Anesthesia, Intensive Care, Emergency and Pain Medicine, Cantonal Hospital St. Gallen, Rorschacherstrasse 95, 9007 St. Gallen, Switzerland" }, { - "author_name": "Remy Slama", - "author_inst": "Institut th\u00e9matique de Sant\u00e9 Publique, INSERM, Paris France ; Inserm, CNRS, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, I" + "author_name": "Manuel Frischknecht", + "author_inst": "Division of Infectious Diseases & Hospital Epidemiology, Cantonal Hospital St. Gallen, Rorschacherstrasse 95, 9007 St. Gallen, Switzerland" }, { - "author_name": "Philippe Raynaud", - "author_inst": "DREES - Direction de la Recherche, des Etudes, \u00e9valuation et statistiques, Paris, France" + "author_name": "Christian Garzoni", + "author_inst": "Clinic of Internal Medicine and Infectious Diseases, Clinica Luganese Moncucco, Lugano, Switzerland; Department of Infectious Diseases, Bern University Hospital" }, { - "author_name": "Guillaume Bagein", - "author_inst": "DREES - Direction de la Recherche, des Etudes, \u00e9valuation et statistiques, Paris, France" + "author_name": "Rossella Forlenza", + "author_inst": "Fondazione Epatocentro Ticino, Via Soldino 5, 6900 Lugano, Switzerland" }, { - "author_name": "Vianney Costemalle", - "author_inst": "DREES - Direction de la Recherche, des Etudes, \u00e9valuation et statistiques, Paris, France" + "author_name": "Mary Horgan", + "author_inst": "Department of Medicine, University College Cork, National University of Ireland, Cork, Ireland; Department of Infectious Diseases, Cork University Hospital, Cor" }, { - "author_name": "Patrick Sillard", - "author_inst": "Institut National de la statistique et des \u00e9tudes \u00e9conomiques, Montrouge, France" + "author_name": "Corinna Sadlier", + "author_inst": "Department of Medicine, University College Cork, National University of Ireland, Cork, Ireland; Department of Infectious Diseases, Cork University Hospital, Cor" }, { - "author_name": "Toscane Fourie", - "author_inst": "Unit\u00e9 des Virus Emergents, UVE, Aix Marseille Univ, INSERM 1207, IRD 190 FR" + "author_name": "Tommaso Rochat Negro", + "author_inst": "Division of Intensive Care, Geneva University Hospitals and the University of Geneva Faculty of Medicine, 1211 Geneva, Switzerland" }, { - "author_name": "Xavier de Lamballerie", - "author_inst": "Unit\u00e9 des Virus Emergents, UVE, Aix Marseille Univ, INSERM 1207, IRD 190 FR" + "author_name": "Jerome Pugin", + "author_inst": "Division of Intensive Care, Geneva University Hospitals and the University of Geneva Faculty of Medicine, 1211 Geneva, Switzerland" }, { - "author_name": "Nathalie Bajos", - "author_inst": "Iris Institut de Recherche Interdisciplinaire sur les enjeux sociaux, Inserm, Aubervilliers, France; Ecole des Hautes Etudes en Sciences Sociales, Paris, France" + "author_name": "Hannah Wozniak", + "author_inst": "Division of Intensive Care, Geneva University Hospitals and the University of Geneva Faculty of Medicine, 1211 Geneva, Switzerland" }, { - "author_name": "- EpiCov Study Group", - "author_inst": "-" + "author_name": "Andreas Cerny", + "author_inst": "Fondazione Epatocentro Ticino, Via Soldino 5, 6900 Lugano, Switzerland" + }, + { + "author_name": "Ujjwal Neogi", + "author_inst": "The Systems Virology Lab, Division of Clinical Microbiology, Department of Laboratory Medicine, Karolinska Institute, ANA Futura, Campus Flemingsberg, Stockholm" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.10.18.21264530", @@ -515642,79 +514106,75 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2021.10.22.465481", - "rel_title": "Inactivation of SARS Coronavirus 2 and COVID-19 patient samples for contemporary immunology and metabolomics studies", + "rel_doi": "10.1101/2021.10.22.465294", + "rel_title": "Characterization of raloxifene as potential pharmacological agent against SARS-CoV-2 and its variants", "rel_date": "2021-10-24", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.22.465481", - "rel_abs": "In late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged from Wuhan, China spurring the Coronavirus Disease-19 (COVID-19) pandemic that has resulted in over 219 million confirmed cases and nearly 4.6 million deaths worldwide. Intensive research efforts ensued to constrain SARS-CoV-2 and reduce COVID-19 disease burden. Due to the severity of this disease, the US Centers for Disease Control and Prevention (CDC) and World Health Organization (WHO) recommend that manipulation of active viral cultures of SARS-CoV-2 and respiratory secretions from COVID-19 patients be performed in biosafety level 3 (BSL3) containment laboratories. Therefore, it is imperative to develop viral inactivation procedures that permit samples to be transferred and manipulated at lower containment levels (i.e., BSL2), and maintain the fidelity of downstream assays to expedite the development of medical countermeasures (MCMs). We demonstrate optimal conditions for complete viral inactivation following fixation of infected cells with paraformaldehyde solution or other commonly-used branded reagents for flow cytometry, UVC inactivation in sera and respiratory secretions for protein and antibody detection assays, heat inactivation following cDNA amplification of single-cell emulsions for droplet-based single-cell mRNA sequencing applications, and extraction with an organic solvent for metabolomic studies. Thus, we provide a suite of protocols for viral inactivation of SARS-CoV-2 and COVID-19 patient samples for downstream contemporary immunology assays that facilitate sample transfer to BSL2, providing a conceptual framework for rapid initiation of high-fidelity research as the COVID-19 pandemic continues.", - "rel_num_authors": 15, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.22.465294", + "rel_abs": "The new coronavirus that emerged, called SARS-CoV-2, is the causative agent of the COVID-19 pandemic. The identification of potential drug candidates that can rapidly enter clinical trials for the prevention and treatment of COVID-19 is an urgent need, despite the recent introduction of several new vaccines for the prevention and protection of this infectious disease, which in many cases becomes severe. Drug repurposing (DR), a process for studying existing pharmaceutical products for new therapeutic indications, represents one of the most effective potential strategies employed to increase the success rate in the development of new drug therapies. We identified raloxifene, a known Selective Estrogen Receptor Modulator (SERM), as a potential pharmacological agent for the treatment of COVID-19 patients. Following a virtual screening campaign on the most relevant viral protein targets, in this work we report the results of the first pharmacological characterization of raloxifene in relevant cellular models of COVID-19 infection. The results obtained on all the most common viral variants originating in Europe, United Kingdom, Brazil, South Africa and India, currently in circulation, are also reported, confirming the efficacy of raloxifene and, consequently, the relevance of the proposed approach.\n\nTaken together, all the information gathered supports the clinical development of raloxifene and confirms that the drug can be proposed as a viable new option to fight the pandemic in at least some patient populations. The results obtained so far have paved the way for a first clinical study to test the safety and efficacy of raloxifene, just concluded in patients with mild to moderate COVID-19.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Devon J. Eddins", - "author_inst": "Emory University" + "author_name": "Daniela Iaconis", + "author_inst": "Domp\u00e9 farmaceutici spa" }, { - "author_name": "Leda C. Bassit", - "author_inst": "Emory University" + "author_name": "Carmine Talarico", + "author_inst": "Domp\u00e9 farmaceutici spa" }, { - "author_name": "Joshua Chandler", - "author_inst": "Emory University" + "author_name": "Candida Manelfi", + "author_inst": "Domp\u00e9 farmaceutici spa" }, { - "author_name": "Natalie S. Haddad", - "author_inst": "Emory University" + "author_name": "Maria Candida Cesta", + "author_inst": "Domp\u00e9 farmaceutici s.p.a" }, { - "author_name": "Kathryn Musall", - "author_inst": "Emory University" + "author_name": "Mara Zippoli", + "author_inst": "Domp\u00e9 farmaceutici spa" }, { - "author_name": "Junkai Yang", - "author_inst": "Emory University" - }, - { - "author_name": "Astrid Kosters", - "author_inst": "Emory University" + "author_name": "Francesca Caccuri", + "author_inst": "University of Brescia: Universita degli Studi di Brescia" }, { - "author_name": "Brian S. Dobosh", - "author_inst": "Emory University" + "author_name": "Giulia Matusali", + "author_inst": "Lazzaro Spallanzani National Institute for Infectious Diseases, IRCCS" }, { - "author_name": "Mindy R. Hernandez", - "author_inst": "Emory University" + "author_name": "Licia Bordi", + "author_inst": "Lazzaro Spallanzani National Institute for Infectious Diseases, IRCCS" }, { - "author_name": "Richard P. Ramonell", - "author_inst": "Emory University" + "author_name": "Laura Scorzolini", + "author_inst": "Lazzaro Spallanzani National Institute for Infectious Diseases, IRCCS" }, { - "author_name": "Rabindra M. Tirouvanziam", - "author_inst": "Emory University" + "author_name": "Enrico M Bucci", + "author_inst": "Temple University" }, { - "author_name": "Frances Eun-Hyung Lee", - "author_inst": "Emory University" + "author_name": "Arnaldo Caruso", + "author_inst": "University of Brescia; Universita degli Studi di Brescia" }, { - "author_name": "Keivan Zandi", - "author_inst": "Emory University" + "author_name": "Emanuele Nicastri", + "author_inst": "Lazzaro Spallanzani National Institute for Infectious Diseases, IRCCS" }, { - "author_name": "Raymond F. Schinazi", - "author_inst": "Emory University" + "author_name": "Marcello Allegretti", + "author_inst": "Domp\u00e9 farmaceutici spa" }, { - "author_name": "Eliver Ghosn", - "author_inst": "Emory University" + "author_name": "Andrea Rosario Beccari", + "author_inst": "Domp\u00e9 farmaceutici spa" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "pharmacology and toxicology" }, { "rel_doi": "10.1101/2021.10.22.465476", @@ -517728,18 +516188,67 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2021.10.14.21264933", - "rel_title": "Differential features of the fifth wave of COVID-19 associated with vaccination and the Delta variant in a reference hospital in Catalonia, Spain", + "rel_doi": "10.1101/2021.10.20.21265115", + "rel_title": "Dysregulation of circulating protease activity in Covid-19-associated superinfection", "rel_date": "2021-10-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.14.21264933", - "rel_abs": "Since the beginning of the COVID-19 pandemic, Spain has suffered five waves of infection, the latter being related to the expansion of the Delta variant and with a high incidence. A vaccination campaign began in December 2020 and by the end of the fifth wave 77.3% of people had been fully vaccinated. Understanding the impact of these new characteristics on COVID-19 is essential for public health strategies. Our objective was to ascertain any differences in the characteristics and outcomes of hospitalized patients during that period compared to previous waves. We found that patients in the fifth wave were considerably younger than before and the mortality rate fell from 22.5 to 2.0%. Admissions to the Intensive Care Unit decreased from 10 to 2%. Patients in the fifth wave had fewer comorbidities, and the age of the patients who died was higher than those who survived. Our results show a marked improvement in patient outcomes in the fifth wave, suggesting success of the vaccination campaign despite the explosion in cases due to the Delta variant.", - "rel_num_authors": 0, - "rel_authors": null, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.20.21265115", + "rel_abs": "Infection by SARS-CoV-2 and subsequent COVID-19 can cause viral sepsis and septic shock. Several complications have been observed in patients admitted to the intensive care unit (ICU) with COVID-19, one of those being bacterial superinfection. Based on prior evidence that dysregulated systemwide proteolysis is associated with death in bacterial septic shock, we investigated whether protease activity and proteolysis could be elevated in COVID-19-induced sepsis with bacterial superinfection. In particular, we sought to assess the possible implications on the regulation of protein systems, such as for instance the proteins and enzymes involved in the clotting cascade.\n\nBlood samples collected at multiple time points during the ICU stay of four COVID-19 patients were analyzed to quantify: a) the circulating proteome and peptidome by mass spectrometry; b) plasma enzymatic activity of trypsin-like substrates and five clotting factors (plasmin, thrombin, factor VII, factor IX, factor X) by a fluorogenic assay.\n\nOf the four patients, one was diagnosed with bacterial superinfection on day 7 after beginning of the study and later died. The other three patients all survived (ICU length-of-stay 11.25{+/-}6.55 days, hospital stay of 15.25{+/-}7.18 days). Spikes in protease activity (factor VII, trypsin-like activity) were detected on day 7 for the patient who died. Corresponding increases in the total intensity of peptides derived by hydrolysis of plasma proteins, especially of fibrinogen degradation products, and a general reduction of coagulation proteins, were measured as well. A downregulation of endogenous enzymatic inhibitors, in particular trypsin inhibitors, characterized the non-surviving patient throughout her ICU stay. Enzymatic activity was stable in the patients who survived.\n\nOur study highlights the potential of multiomics approaches, combined with quantitative analysis of enzymatic activity, to i) shed light on proteolysis as a possible pathological mechanism in sepsis and septic shock, including COVID-19-induced sepsis; ii) provide additional insight into malfunctioning protease-mediated systems, such as the coagulation cascade; and iii) describe the progression of COVID-19 with bacterial superinfection.", + "rel_num_authors": 12, + "rel_authors": [ + { + "author_name": "Fernando dos Santos", + "author_inst": "Department of Anesthesiology, School of Medicine, University of California, San Diego, La Jolla, CA, U.S.A" + }, + { + "author_name": "Joyce B Li", + "author_inst": "Department of Bioengineering, University of California, San Diego, La Jolla, CA, U.S.A." + }, + { + "author_name": "Nathalia Juocys", + "author_inst": "Heart Institute, Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo (InCor-FMUSP), Sao Paulo, Brazil" + }, + { + "author_name": "Rafi Mazor", + "author_inst": "Department of Anesthesiology, School of Medicine, University of California, San Diego, La Jolla, CA, U.S.A." + }, + { + "author_name": "Laura Beretta", + "author_inst": "Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, U.S.A." + }, + { + "author_name": "Nicole G Coufal", + "author_inst": "Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, U.S.A." + }, + { + "author_name": "Michael TY Lam", + "author_inst": "Department of Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, U.S.A." + }, + { + "author_name": "Maze F Odish", + "author_inst": "Department of Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, U.S.A." + }, + { + "author_name": "Maria C Irigoyen", + "author_inst": "Instituto do Coracao, Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo (InCor-FMUSP), Sao Paulo, Brazil" + }, + { + "author_name": "Anthony J O Donoghue", + "author_inst": "4Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, U.S.A." + }, + { + "author_name": "Federico Aletti", + "author_inst": "Institute of Science and Technology, Universidade Federal de Sao Paulo" + }, + { + "author_name": "Erik B Kistler", + "author_inst": "Department of Anesthesiology, School of Medicine, University of California, San Diego, La Jolla, CA, U.S.A." + } + ], "version": "1", "license": "", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2021.10.20.21265149", @@ -519721,187 +518230,23 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.10.20.465121", - "rel_title": "Post-entry, spike-dependent replication advantage of B.1.1.7 and B.1.617.2 over B.1 SARS-CoV-2 in an ACE2-deficient human lung cell line", + "rel_doi": "10.1101/2021.10.16.21265096", + "rel_title": "SARS-COV-2 \u03b4 variant drives the pandemic in India and Europe via two subvariants", "rel_date": "2021-10-20", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.20.465121", - "rel_abs": "Epidemiological data demonstrate that SARS-CoV-2 variants of concern (VOC) B.1.1.7 and B.1.617.2 are more transmissible and infections are associated with a higher mortality than non-VOC virus infections. Phenotypic properties underlying their enhanced spread in the human population remain unknown. B.1.1.7 virus isolates displayed inferior or equivalent spread in most cell lines and primary cells compared to an ancestral B.1 SARS-CoV-2, and were outcompeted by the latter. Lower infectivity and delayed entry kinetics of B.1.1.7 viruses were accompanied by inefficient proteolytic processing of spike. B.1.1.7 viruses failed to escape from neutralizing antibodies, but slightly dampened induction of innate immunity. The bronchial cell line NCI-H1299 supported 24- and 595-fold increased growth of B.1.1.7 and B.1.617.2 viruses, respectively, in the absence of detectable ACE2 expression and in a spike-determined fashion. Superior spread in NCI-H1299 cells suggests that VOCs employ a distinct set of cellular cofactors that may be unavailable in standard cell lines.", - "rel_num_authors": 42, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.16.21265096", + "rel_abs": "SARS-COV-2 evolution generates different variants and drives the pandemic. As the current main driver, {delta} variant bears little resemblance to the other three variants of concern, raising the question what features future variants of concern may possess. To address this important question, I compared different variant genomes and specifically analyzed {delta} genomes in the GISAID database for potential clues. The analysis revealed that {delta} genomes identified in India by April 2021 form four different groups (referred to as {delta}1, {delta}2, {delta}3 and {delta}4) with signature spike, nucleocapsid and NSP3 substitutions defining each group. Since May 2021, {delta}1 has gradually overtaken all other subvariants and become the dominant pandemic driver, whereas {delta}2 has played a less prominent role and the remaining two ({delta}3 and {delta}4) are insignificant. This group composition and variant transition are also apparent across Europe. In the United Kingdom, {delta}1 has quickly become predominant and is the sole pandemic driver underlying the current wave of COVID-19 cases. Alarmingly, {delta}1 subvariant has evolved further in the country and yielded a sublineage encoding spike V36F, A222V and V1264L. These substitutions may make the sublineage more virulent than {delta}1 itself. In the rest of Europe, {delta}1 is also the main pandemic driver, but {delta}2 still plays a role. In many European countries, there is a {delta}1 sublineage encoding spike T29A, T250I and Q613H. This sublineage originated from Morocco and has been a key pandemic driver there. Therefore, {delta} variant drives the pandemic in India and across Europe mainly through {delta}1 and {delta}2, with the former acquiring additional substitutions and yielding sublineages with the potential to drive the pandemic further. These results suggest a continuously branching model by which {delta} variant evolves and generates more virulent subvariants.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Daniela Niemeyer", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Simon Schroeder", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Kirstin Friedmann", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Friderike Weege", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Jakob Trimpert", - "author_inst": "Freie Universitaet Berlin" - }, - { - "author_name": "Anja Richter", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Saskia Stenzel", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Jenny Jansen", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Jackson Emanuel", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Julia Kazmierski", - "author_inst": "Charite Universitaetsmedizin Berlin" - }, - { - "author_name": "Fabian Pott", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Lara M. Jeworowski", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Ruth Olmer", - "author_inst": "Hannover Medical School" - }, - { - "author_name": "Mark-Christian Jaboreck", - "author_inst": "Hannover Medical School" - }, - { - "author_name": "Beate Tenner", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Jan Papies", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Julian Heinze", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Felix Walper", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Marie L. Schmidt", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Nicolas Heinemann", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Elisabeth Moencke-Buchner", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Talitha Veith", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Morris Baumgardt", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Karen Hoffmann", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Marek Widera", - "author_inst": "University Hospital, Goethe University Frankfurt am Main" - }, - { - "author_name": "Tran Thi Nhu Thao", - "author_inst": "Institute of Virology and Immunology, Bern and Mittelhaeusern, Switzerland" - }, - { - "author_name": "Anita Balazs", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Jessica Schulze", - "author_inst": "Robert Koch Institute" - }, - { - "author_name": "Christin Mache", - "author_inst": "Robert Koch Institute" - }, - { - "author_name": "Markus Morkel", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Sandra Ciesek", - "author_inst": "Goethe University Frankfurt" - }, - { - "author_name": "Leif G. Hanitsch", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Marcus Mall", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Andreas C. Hocke", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Volker Thiel", - "author_inst": "Institute for Virology and Immunology" - }, - { - "author_name": "Klaus Osterrieder", - "author_inst": "Freie Universitaet Berlin" - }, - { - "author_name": "Thorsten Wolff", - "author_inst": "Robert Koch Institute" - }, - { - "author_name": "Ulrich Martin", - "author_inst": "Hannover Medical School" - }, - { - "author_name": "Victor M Corman", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Marcel A Mueller", - "author_inst": "Charite Universitaetsmedizin Berlin" - }, - { - "author_name": "Christine Goffinet", - "author_inst": "Charite - Universitaetsmedizin Berlin" - }, - { - "author_name": "Christian Drosten", - "author_inst": "Charite Universitaetsmedizin" + "author_name": "Xiang-Jiao Yang", + "author_inst": "McGill University" } ], "version": "1", - "license": "cc_by_nd", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.10.18.21265057", @@ -521622,81 +519967,49 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2021.10.14.21264873", - "rel_title": "A high content microscopy-based platform for detecting antibodies to the nucleocapsid, spike and membrane proteins of SARS-CoV-2", + "rel_doi": "10.1101/2021.10.15.21265066", + "rel_title": "A Thermostable Cas12b from Brevibacillus Leverages One-pot Detection of SARS-CoV-2 Variants of Concern", "rel_date": "2021-10-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.14.21264873", - "rel_abs": "The strong humoral immune response produced against the SARS-CoV-2 nucleocapsid (N) and spike (S) proteins has underpinned serological testing but the prevalence of antibody responses to other SARS-CoV-2 proteins, which may be of use as further serological markers, is still unclear. Cell-based serological screening platforms can fulfil a crucial niche in the identification of antibodies which recognise more complex folded epitopes or those incorporating post-translation modifications which may be undetectable by other methods used to investigate the antigenicity of the SARS-CoV-2 proteome. Here, we employed automated high content immunofluorescence microscopy (AHCIM) to assess the viability of such an approach as a method capable of assaying humoral immune responses against full length SARS-CoV-2 proteins in their native cellular state. We first demonstrate that AHCIM provides high sensitivity and specificity in the detection of SARS-CoV-2 N and S IgG. Assessing the prevalence of antibody responses to the SARS-CoV-2 structural membrane protein (M), we further find that 85% of COVID-19 patients within our sample set developed detectable M IgG responses (M sensitivity 85%, N sensitivity 93%, combined N + M sensitivity 95%). The identification of M as a serological marker of high prevalence may be of value in detecting additional COVID-19 cases during the era of mass SARS-CoV-2 vaccinations, where serological screening for SARS CoV-2 infections in vaccinated individuals is dependent on detection of antibodies against N. These findings highlight the advantages of using cell-based systems as serological screening platforms and raise the possibility of using M as a widespread serological marker alongside N and S.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.15.21265066", + "rel_abs": "Current SARS-CoV-2 detection platforms lack the ability to differentiate among variants of concern (VOCs) in an efficient manner. CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) has the potential to transform diagnostics due to its programmability. However, many of the CRISPR-based detection methods are reliant on either a multi-step process involving amplification or elaborate guide RNA designs. A complete one-pot detection reaction using alternative Cas effector endonucleases has been proposed to overcome these challenges. Yet, current approaches using Alicyclobacillus acidiphilus Cas12b (AapCas12b) are limited by its thermal instability at optimum reverse transcription loop-mediated isothermal amplification (RT-LAMP) reaction temperatures. Herein, we demonstrate that a novel Cas12b from Brevibacillus sp. SYP-B805 (referred to as BrCas12b) has robust trans-cleavage activity at ideal RT-LAMP conditions. A competitive profiling study of BrCas12b against Cas12b homologs from other bacteria genera underscores the potential of BrCas12b in the development of new diagnostics. As a proof-of-concept, we incorporated BrCas12b into an RT-LAMP-mediated one-pot reaction system, coined CRISPR-SPADE (CRISPR Single Pot Assay for Detecting Emerging VOCs) to enable rapid, differential detection of SARS-CoV-2 VOCs, including Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), and Delta (B.1.617.2) in 205 clinical samples. Notably, a BrCas12b detection signal was observed within 1-3 minutes of amplification, achieving an overall 98.1% specificity, 91.2% accuracy, and 88.1% sensitivity within 30 minutes. Significantly, for samples with high viral load (Ct value [≤] 30), 100% accuracy and sensitivity were attained. To facilitate dissemination and global implementation of the assay, we combined the lyophilized one-pot reagents with a portable multiplexing device capable of interpreting fluorescence signals at a fraction of the cost of a qPCR system. With relaxed design requirements, one-pot detection, and simple instrumentation, this assay has the capability to advance future diagnostics.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Daniel M. Williams", - "author_inst": "School of Bioscience, University of Sheffield, Western Bank, Sheffield S102TN" - }, - { - "author_name": "Hayley Hornsby", - "author_inst": "Department of Infection, Immunity and Cardiovascular Disease The Medical School Beech Hill Road Sheffield S10 2RX" - }, - { - "author_name": "Ola M. Shehata", - "author_inst": "School of Bioscience, University of Sheffield, Western Bank, Sheffield S102TN" - }, - { - "author_name": "Rebecca Brown", - "author_inst": "Department of Infection, Immunity and Cardiovascular Disease The Medical School Beech Hill Road Sheffield S10 2RX" - }, - { - "author_name": "Domen Zafred", - "author_inst": "Department of Infection, Immunity and Cardiovascular Disease The Medical School Beech Hill Road Sheffield S10 2RX" - }, - { - "author_name": "Amber S.M. Shun-Shion", - "author_inst": "School of Bioscience, University of Sheffield, Western Bank, Sheffield S102TN" - }, - { - "author_name": "Anthony J. Hodder", - "author_inst": "School of Bioscience, University of Sheffield, Western Bank, Sheffield S102TN" - }, - { - "author_name": "Deepa Bliss", - "author_inst": "School of Bioscience, University of Sheffield, Western Bank, Sheffield S102TN" - }, - { - "author_name": "Andrew Metcalfe", - "author_inst": "School of Bioscience, University of Sheffield, Western Bank, Sheffield S102TN" + "author_name": "Long T. Nguyen", + "author_inst": "University of Florida" }, { - "author_name": "James Edgar", - "author_inst": "Department of Pathology, University of Cambridge, Tennis Court Road CB2 1QP" + "author_name": "Nicolas C. Macaluso", + "author_inst": "University of Florida" }, { - "author_name": "David E. Gordon", - "author_inst": "Whitehead Building, Atlanta, GA, USA Department of Pathology Emory University" + "author_name": "Brianna L.M. Pizzano", + "author_inst": "University of Florida" }, { - "author_name": "Jon R. Sayers", - "author_inst": "Department of Infection, Immunity and Cardiovascular Disease The Medical School Beech Hill Road Sheffield S10 2RX" + "author_name": "Melanie N. Cash", + "author_inst": "University of Florida" }, { - "author_name": "Martin J. Nicklin", - "author_inst": "Department of Infection, Immunity and Cardiovascular Disease The Medical School Beech Hill Road Sheffield S10 2RX" + "author_name": "Jan Spacek", + "author_inst": "Sparsek s.r.o." }, { - "author_name": "Paul J. Collini", - "author_inst": "Department of Infection, Immunity and Cardiovascular Disease The Medical School Beech Hill Road Sheffield S10 2RX" + "author_name": "Jan Karasek", + "author_inst": "SCIERING s.r.o." }, { - "author_name": "Steve Brown", - "author_inst": "School of Bioscience, University of Sheffield, Western Bank, Sheffield S102TN" + "author_name": "Rhoel R. Dinglasan", + "author_inst": "University of Florida" }, { - "author_name": "Thushan I. de Silva", - "author_inst": "Dept. of Infection, Immunity and Cardiovascular Diseases University of Sheffield Medical School Beech Hill Road Sheffield S10 2RX" + "author_name": "Marco Salemi", + "author_inst": "University of Florida" }, { - "author_name": "Andrew A. Peden", - "author_inst": "School of Bioscience, University of Sheffield, Western Bank, Sheffield S102TN" + "author_name": "Piyush K. Jain", + "author_inst": "University of Florida" } ], "version": "1", @@ -523180,125 +521493,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.17.21265121", - "rel_title": "Reduced seroconversion in children compared to adults with mild COVID-19", + "rel_doi": "10.1101/2021.10.16.21265067", + "rel_title": "The usefulness of antigen testing in predicting contagiousness in COVID-19", "rel_date": "2021-10-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.17.21265121", - "rel_abs": "ImportanceThe immune response in children with SARS-CoV-2 infection is not well understood.\n\nObjectiveTo compare seroconversion in children and adults with non-hospitalized (mild) SARS-CoV-2 infection and to understand the factors that influence this.\n\nDesignParticipants were part of a household cohort study of SARS-CoV-2 infection. Weekly nasopharyngeal/throat swabs and blood samples were collected during the acute and convalescent period following PCR diagnosis for analysis.\n\nSettingParticipants were recruited at the Royal Childrens Hospital, Melbourne, Australia between May and October 2020.\n\nParticipantsThose who had a SARS-CoV-2 PCR-positive nasal/throat swab.\n\nMain outcomes and measuresSARS-CoV-2 antibody and cellular responses in children and adults. Seroconversion was defined by seropositivity in all three serological assays.\n\nResultsAmong 108 SARS-CoV-2 PCR-positive participants, 57 were children (median age: 4, IQR 2-10) and 51 were adults (median age: 37, IQR 34-45). Using three established serological assays, a lower proportion of children seroconverted compared with adults [20/54 (37.0%) vs 32/42 (76.2%); (p<0.001)]. This was not related to viral load, which was similar in children and adults [mean Ct 28.58 (SD: 6.83) vs 24.14 (SD: 8.47)]. Age and sex also did not influence seroconversion or the magnitude of antibody response within children or adults. Notably, in adults (but not children) symptomatic adults had three-fold higher antibody levels than asymptomatic adults (median 227.5 IU/mL, IQR 133.7-521.6 vs median 75.3 IU/mL, IQR 36.9-113.6). Evidence of cellular immunity was observed in adults who seroconverted but not in children who seroconverted.\n\nConclusion and RelevanceIn this non-hospitalized cohort with mild COVID-19, children were less likely to seroconvert than adults despite similar viral loads. This has implications for future protection following COVID-19 infection in children and for interpretation of serosurveys that involve children. Further research to understand why children are less likely to seroconvert and develop symptoms following SARS-CoV-2 infection, and comparison with vaccine responses may be of clinical and scientific importance.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSWhat proportion of children with non-hospitalized (mild) SARS-CoV-2 infection seroconvert compared to adults?\n\nFindingsIn this cohort study conducted in 2020, we found the proportion of children who seroconverted to SARS-CoV-2 was half that in adults despite similar viral load.\n\nMeaningSerology is a less reliable marker of prior SARS-CoV-2 infection in children. SARS-CoV-2-infected children who do not seroconvert may be susceptible to reinfection. Our findings support strategies to protect children against COVID-19 including vaccination.", - "rel_num_authors": 27, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.16.21265067", + "rel_abs": "Increasing the diagnostic capacity of COVID-19 (SARS-CoV-2 infection) is required to improve case detection, reduce COVID-19 expansion, and boost the world economy. Rapid antigen detection tests are cheaper and easier to implement, but their diagnostic performance has been questioned compared to RT-PCR. Here, we evaluate the performance of the Standard Q COVID-19 antigen test for diagnosing SARS-CoV-2 infection and predicting contagiousness compared to RT-PCR and viral culture, respectively. The antigen test was 100.0% specific but only 40.9% sensitive for diagnosing infection compared to RT-PCR. Interestingly, SARS-CoV-2 contagiousness is highly unlikely with a negative antigen test since it exhibited a negative predictive value of 99.9% than viral culture. Furthermore, a cycle threshold (Ct) value of 18.1 in RT-PCR was shown to be the one that best predicts contagiousness (AUC 97.6%). Thus, screening people with antigen testing is a good approach to prevent SARS-CoV-2 contagion and allow returning to daily activities.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Zheng Quan Toh", - "author_inst": "Murdoch Children's Research Institute" - }, - { - "author_name": "Jeremy Anderson", - "author_inst": "Murdoch Children's Research Institute" - }, - { - "author_name": "Nadia Mazarakis", - "author_inst": "Murdoch Children's Research Institute" - }, - { - "author_name": "Melanie Neeland", - "author_inst": "Murdoch Children's Research Institute" - }, - { - "author_name": "Rachel A Higgins", - "author_inst": "Murdoch Children's Research Institute" - }, - { - "author_name": "Karin Rautenbacher", - "author_inst": "Royal Childrens Hospital" - }, - { - "author_name": "Kate Dohle", - "author_inst": "Murdoch Children's Research Institute" - }, - { - "author_name": "Jill Nguyen", - "author_inst": "Murdoch Children's Research Institute" - }, - { - "author_name": "Isabelle Overmars", - "author_inst": "Murdoch Children's Research Institute" - }, - { - "author_name": "Celeste Donato", - "author_inst": "Murdoch Children's Research Institute" - }, - { - "author_name": "Sohinee Sarkar", - "author_inst": "Murdoch Children's Research Institute" - }, - { - "author_name": "Vanessa Clifford", - "author_inst": "Royal Childrens Hospital" - }, - { - "author_name": "Andrew Daley", - "author_inst": "Royal Childrens Hospital" - }, - { - "author_name": "Suellen Nicholson", - "author_inst": "VIDRL" - }, - { - "author_name": "Francesca L Mordant", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Kanta Subbarao", - "author_inst": "University of Melbourne" - }, - { - "author_name": "David Burgner", - "author_inst": "Murdoch Children's Research Institute" - }, - { - "author_name": "Nigel Curtis", - "author_inst": "Murdoch Children's Research Institute" - }, - { - "author_name": "Julie E Bines", - "author_inst": "Murdoch Children's Research Institute" - }, - { - "author_name": "Sarah McNab", - "author_inst": "Royal Childrens Hospital" - }, - { - "author_name": "Andrew C Steer", - "author_inst": "Murdoch Children's Research Institute" - }, - { - "author_name": "Kim Mulholland", - "author_inst": "Murdoch Children's Research Institute" - }, - { - "author_name": "Shidan Tosif", - "author_inst": "Murdoch Children's Research Institute" + "author_name": "Tulio J. Lopera", + "author_inst": "University of Antioquia" }, { - "author_name": "Nigel W Crawford", - "author_inst": "Murdoch Children's Research Institute" + "author_name": "Francisco J. Diaz", + "author_inst": "Universidad de Antioquia" }, { - "author_name": "Daniel G Pellicci", - "author_inst": "Murdoch Children's Research Institute" + "author_name": "Juan C. Alzate-Angel", + "author_inst": "Universidad de Antioquia" }, { - "author_name": "Lien Anh Ha Do", - "author_inst": "Murdoch Children's Research Institute" + "author_name": "Maria Teresa Rugeles", + "author_inst": "Universidad de Antioquia" }, { - "author_name": "Paul Licciardi", - "author_inst": "Murdoch Children's Research Institute" + "author_name": "Wbeimar Aguilar-Jimenez", + "author_inst": "Universidad de Antioquia" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -525273,47 +523498,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.11.21264849", - "rel_title": "Effect of SARS-CoV-2 vaccination on symptoms from post-acute COVID syndrome: results from the national VAXILONG survey", + "rel_doi": "10.1101/2021.10.11.21261865", + "rel_title": "Antimicrobial consumption in pediatric intensive care units during the first year of COVID-19 pandemic", "rel_date": "2021-10-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.11.21264849", - "rel_abs": "IntroductionFew data are available concerning the effect of SARS-CoV-2 vaccination on the persistent symptoms associated with COVID-19, also called long-COVID or post-acute COVID-19 syndrome (PACS).\n\nPatients and methodsWe conducted a nationwide online survey among adult patients with PACS as defined by symptoms persisting over 4 weeks following a confirmed or probable COVID-19, without any identified alternative diagnosis. Information concerning PACS symptoms, vaccine type and scheme and its effect on PACS symptoms were studied.\n\nResultsSix hundred and twenty surveys were completed and 567 satisfied the inclusion criteria and were analyzed. Respondents were 83.4% of women of median age 44 (IQR 25-75: 37-50). Initial infection was proven in 365 patients (64%) and 5.1% had been hospitalized to receive oxygen. 396 patients had received at least one injection of SARS-CoV-2 vaccine at the time of the survey, after a median of 357 [198-431] days following the initially-reported SARS-CoV-2 infection. Among the 380 patients who reported persistent symptoms at the time of SARS-CoV-2 vaccination, 201 (52.8%) reported variation of symptoms following the injection, without difference based on the type of vaccine used. After a complete vaccination scheme, 93.3% (28/30) of initially seronegative patients reported a positive anti-SARS-CoV-2 IgG.\n\n170 PACS patients had not been vaccinated. The most common reasons for postponing SARS-CoV-2 vaccine were a fear of worsening PACS symptoms (55.9%) and the idea that vaccination was contraindicated because of PACS (15.6%).\n\nConclusionOur study suggests that SARS-CoV-2 vaccination is well tolerated in the majority of PACS patients and has good immunogenicity. Disseminating these reassuring data might prove crucial to increase vaccine coverage in patients with PACS.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.11.21261865", + "rel_abs": "IntroductionThe absence of standardized treatment for critical children admitted in pediatric intensive care units (PICUs) with COVID could lead to an increase in antimicrobial consumption, as indirect effect.\n\nAimTo describe trends of antimicrobial consumption in two PICUs before and during the COVID pandemic year.\n\nMethodsWe did a retrospective study in children admitted in two PICUs of Rio de Janeiro city, between March 2019 and March 2021. The first year represented the pre-pandemic period and the last one the pandemic period. Trends of antimicrobial consumption were measured by days of therapy (DOT/1000 patient-days) and analyzed by linear regression for antibiotics, antivirals and antifungals\n\nResultsNumber of patients-days in the PICU 1 was 3495 in the pre-pandemic period and 3600 in the pandemic period. The overall DOT/1000 PD of antibiotics, antivirals and antifungal was 15,308.1, 942.8 and 1,691.1, respectively in the pre-pandemic period and 13,481.5, 1,335.4 and 1,243.7, respectively in pandemic period. It was verified trend of reduction of antibiotic and antifungals and increase in antivirals consumption. Number of patients-days in the PICU 2 was 5029 in the pre-pandemic period and 4557 in the pandemic period and the overall DOT/1000 PD of antibiotics, antivirals and antifungal was 16,668.5, 1,385 and 1,966.7, respectively in the pre-pandemic period and 10,896.5, 830.7 and 677.3 in pandemic period. It was verified trend of reduction of antibiotic, antivirals and antifungals consumption.\n\nConclusionTrends of antimicrobial consumption reduction were verified for antibiotics and antifungals in two PICUs and reduction for antiviral in one of them", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Marc SCHERLINGER", - "author_inst": "Rheumatology department, Strasbourg University Hospital" - }, - { - "author_name": "Luc Pijnenburg", - "author_inst": "Rheumatology department, Strasbourg University Hospital" + "author_name": "Monique Faitanin Moura", + "author_inst": "Universidade Federal Fluminense" }, { - "author_name": "Emmanuel Chatelus", - "author_inst": "Rheumatology department, Strasbourg University Hospital" + "author_name": "Maria Eduarda de Oliveira Pires", + "author_inst": "Universidade Federal Fluminense" }, { - "author_name": "Laurent Arnaud", - "author_inst": "Rheumatology department, Strasbourg University Hospital" + "author_name": "Rafael da Rocha Quijada Santos", + "author_inst": "UNiversidade Federal Fluminense" }, { - "author_name": "Jacques-Eric Gottenberg", - "author_inst": "Rheumatology department, Strasbourg University Hospital" + "author_name": "Cristiane Henriques Teixeira", + "author_inst": "Prontobaby Group" }, { - "author_name": "Jean Sibilia", - "author_inst": "Rheumatology department, Strasbourg University Hospital" + "author_name": "Cristina Vieira Souza", + "author_inst": "Prontobaby Group" }, { - "author_name": "Renaud Felten", - "author_inst": "Rheumatology department, Strasbourg University Hospital" + "author_name": "Andre Ricardo Araujo da Silva", + "author_inst": "Federal Fluminense University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "pediatrics" }, { "rel_doi": "10.1101/2021.10.11.21264709", @@ -527103,39 +525324,87 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.10.12.21264877", - "rel_title": "Effects of Side-Effect Risk Framing Strategies on COVID-19 Vaccine Intentions in the United States and the United Kingdom: A Randomized Controlled Trial", + "rel_doi": "10.1101/2021.10.13.464307", + "rel_title": "A monoclonal antibody that neutralizes SARS-CoV-2 variants, SARS-CoV, and other sarbecoviruses", "rel_date": "2021-10-14", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.12.21264877", - "rel_abs": "Fear over side-effects is one of the main drivers of COVID-19 vaccine hesitancy. We conducted a pre-registered randomized controlled trial among 8998 individuals to examine the effects of different ways of framing and presenting vaccine side-effects on individuals willingness to get vaccinated. We found that adding a descriptive risk label (\"very low risk\") next to the numerical side-effect and providing a comparison to motor vehicle mortality increased participants willingness to take the COVID-19 vaccine by 3.0 percentage points (p = 0.003) and 2.4 percentage points (p = 0.049), respectively. These effects were independent and additive and combining both framing strategies increased willingness to receive the vaccine by 6.1 percentage points (p < 0.001). Mechanistically, we find evidence that these framing effects operate by increasing individuals perceptions of how safe the vaccine is. Our results reveal that low-cost side-effect framing strategies can meaningfully affect vaccine intentions at a population level.", - "rel_num_authors": 5, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.13.464307", + "rel_abs": "The repeated emergence of highly pathogenic human coronaviruses as well as their evolving variants highlight the need to develop potent and broad-spectrum antiviral therapeutics and vaccines. By screening monoclonal antibodies (mAbs) isolated from COVID-19-convalescent patients, we found one mAb, 2-36, with cross-neutralizing activity against SARS-CoV. We solved the cryo-EM structure of 2-36 in complex with SARS-CoV-2 or SARS-CoV spike, revealing a highly conserved epitope in the receptor-binding domain (RBD). Antibody 2-36 neutralized not only all current circulating SARS-CoV-2 variants and SARS-COV, but also a panel of bat and pangolin sarbecoviruses that can use human angiotensin-converting enzyme 2 (ACE2) as a receptor. We selected 2-36-escape viruses in vitro and confirmed that K378T in SARS-CoV-2 RBD led to viral resistance. Taken together, 2-36 represents a strategic reserve drug candidate for the prevention and treatment of possible diseases caused by pre-emergent SARS-related coronaviruses. Its epitope defines a promising target for the development of a pan-sarbecovirus vaccine.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Nikkil Sudharsanan", - "author_inst": "Technical University of Munich" + "author_name": "Pengfei Wang", + "author_inst": "Fudan University" }, { - "author_name": "Caterina Favaretti", - "author_inst": "Heidelberg Institute of Global Health" + "author_name": "Ryan G Casner", + "author_inst": "Department of Biochemistry and Molecular Biophysics, Columbia University" }, { - "author_name": "Violetta Hachaturyan", - "author_inst": "Heidelberg Institute of Global Health" + "author_name": "Manoj S Nair", + "author_inst": "Columbia University" }, { - "author_name": "Till Baernighausen", - "author_inst": "Heidelberg Institute of Global Health" + "author_name": "Jian Yu", + "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons" }, { - "author_name": "Alain Vandormael", - "author_inst": "Heidelberg Institute of Global Health" + "author_name": "Yicheng Guo", + "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons" + }, + { + "author_name": "Maple Wang", + "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons" + }, + { + "author_name": "Jasper F.W. Chan", + "author_inst": "University of Hong Kong" + }, + { + "author_name": "Gabriele Cerutti", + "author_inst": "Columbia University" + }, + { + "author_name": "Sho Iketani", + "author_inst": "Columbia University Irving Medical Center" + }, + { + "author_name": "Lihong Liu", + "author_inst": "Columbia University Irving Medical Center" + }, + { + "author_name": "Zizhang Sheng", + "author_inst": "Columbia University" + }, + { + "author_name": "Zhiwei Chen", + "author_inst": "The University of Hong Kong" + }, + { + "author_name": "Kwok-Yung Yuen", + "author_inst": "The University of Hong Kong" + }, + { + "author_name": "Peter D Kwong", + "author_inst": "National Institutes of Health" + }, + { + "author_name": "Yaoxing Huang", + "author_inst": "Columbia University" + }, + { + "author_name": "Lawrence Shapiro", + "author_inst": "Columbia University" + }, + { + "author_name": "David D Ho", + "author_inst": "Columbia University Irving Medical Center" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2021.10.13.21264975", @@ -528909,59 +527178,47 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2021.10.11.21263897", - "rel_title": "Baricitinib plus Standard of Care for Hospitalised Adults with COVID-19 on Invasive Mechanical Ventilation or Extracorporeal Membrane Oxygenation: Results of a Randomized, Placebo-Controlled Trial.", + "rel_doi": "10.1101/2021.10.08.21264719", + "rel_title": "Trans Sodium Crocetinate (TSC) to Improve Oxygenation in COVID-19", "rel_date": "2021-10-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.11.21263897", - "rel_abs": "BackgroundThe oral, selective Janus kinase (JAK)1/JAK2 inhibitor baricitinib demonstrated efficacy in hospitalised adults with COVID-19. This study evaluates the efficacy and safety of baricitinib in critically ill adults with COVID-19 requiring invasive mechanical ventilation (IMV) or extracorporeal membrane oxygenation (ECMO).\n\nMethodsCOV-BARRIER was a global, phase 3, randomised, double-blind, placebo-controlled trial in patients with confirmed SARS-CoV-2 infection (ClinicalTrials.gov NCT04421027). This addendum trial added a critically ill cohort not included in the main COV-BARRIER trial. Participants on baseline IMV/ECMO were randomly assigned 1:1 to baricitinib 4-mg (n=51) or placebo (n=50) for up to 14 days in combination with standard of care (SOC). Prespecified endpoints included all-cause mortality through days 28 and 60, and number of ventilator-free days, duration of hospitalisation, and time to recovery through day 28. Efficacy and safety analyses included the intent-to-treat and safety populations, respectively.\n\nFindingsSOC included baseline systemic corticosteroid use in 86% of participants. Treatment with baricitinib significantly reduced 28-day all-cause mortality compared to placebo (39{middle dot}2% vs 58{middle dot}0%; hazard ratio [HR]=0{middle dot}54 [95%CI 0{middle dot}31-0{middle dot}96]; p=0{middle dot}030). One additional death was prevented for every six baricitinib-treated participants. Significant reduction in 60-day mortality was also observed (45{middle dot}1% vs 62{middle dot}0%; HR=0{middle dot}56 [95%CI 0{middle dot}33-0{middle dot}97]; p=0{middle dot}027).\n\nBaricitinib-treated participants showed numerically more ventilator-free days (8.1 vs 5.5 days, p=0.21) and spent over 2 days less in the hospital than placebo-treated participants (23{middle dot}7 vs 26{middle dot}1 days, p=0{middle dot}050). The rates of infections, blood clots, and adverse cardiovascular events were similar between treatment arms.\n\nInterpretationIn critically ill patients with COVID-19 already receiving IMV/ECMO, treatment with baricitinib as compared to placebo (in combination with SOC, including corticosteroids) showed mortality HR of 0{middle dot}56, corresponding to a 44% relative reduction at 60 days. This is consistent with the mortality reduction observed in less severely ill hospitalised primary COV-BARRIER study population.\n\nFundingEli Lilly and Company.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe evaluated current and prior studies assessing the efficacy and safety of interventions in patients requiring invasive mechanical ventilation (IMV) and searched current PubMed using the terms \"COVID-19\", \"SARS-CoV-2\", \"treatment\", \"critical illness\", \"invasive mechanical ventilation\", \"baricitinib\", and \"JAK inhibitor\" for articles in English, published until December 1, 2020, regardless of article type. We also reviewed the NIH and IDSA COVID-19 guidelines and reviewed similar terms on clinicaltrials.gov. When the critical illness addendum study to COV-BARRIER study was designed, there was only one open-label study of dexamethasone showing mortality benefit in hospitalised patients with COVID-19 requiring IMV. Small studies of interleukin-6 inhibitors had shown no effect and larger trials were underway. Guidelines recommended use of dexamethasone with or without remdesivir and recommended against the use of interleukin-6 inhibitors, except in a clinical trial. Overall, there were no reported double-blind, placebo-controlled phase 3 trials which included corticosteroids as part of SOC investigating the efficacy and safety of novel treatments in the NIAID-OS 7 population. Baricitinibs mechanism of action as a JAK1 and JAK2 inhibitor was identified as a potential intervention for the treatment of COVID-19 given its known anti-cytokine properties and potential antiviral mechanism for targeting host proteins mediating viral endocytosis Data from the NIAID sponsored ACTT-2 trial showed that baricitinib when added to remdesivir improved time to recovery and other outcomes including mortality compared to placebo plus remdesivir. A numerically larger proportion of participants who received baricitinib plus remdesivir showed an improvement in ordinal scale compared to those who received placebo plus remdesivir at day 15 in participants requiring IMV (NIAID-OS score of 7) at baseline. We designed COV-BARRIER, a phase 3, global, double-blind, randomised, placebo-controlled trial, to evaluate the efficacy and safety of baricitinib in combination with SOC (including corticosteroids) for the treatment of hospitalised adults with COVID-19 who did not require mechanical ventilation (i.e., NIAID-OS 4-6). A significant reduction in mortality was found after 28 days between baricitinib and placebo (HR 0{middle dot}57, corresponding to a 43% relative reduction, p=0{middle dot}0018); one additional death was prevented per 20 baricitinib-treated participants. In the more severely ill NIAID-OS 6 subgroup, one additional death was prevented per nine baricitinib-treated participants (HR 0{middle dot}52, corresponding to a 48% relative reduction, p=0{middle dot}0065). We therefore implemented an addendum to the COV-BARRIER trial to evaluate the benefit/risk of baricitinib in the critically ill NIAID-OS 7 population and considered the sample size of 100 participants sufficient for this trial.\n\nAdded value of this studyThis was the first phase 3 study to evaluate baricitinib in addition to the current standard of care (SOC), including antivirals, anticoagulants, and corticosteroids, in patients who were receiving IMV or extracorporeal membrane oxygenation at enrolment. This was a multinational, randomised, double-blind, placebo-controlled trial in regions with high COVID-19 hospitalisation rates. Treatment with baricitinib reduced 28-day all-cause mortality compared to placebo (HR 0{middle dot}54, 95% CI 0{middle dot}31-0{middle dot}96; nominal p=0{middle dot}030), corresponding to a 46% relative reduction, and significantly reduced 60-day all-cause mortality (HR 0{middle dot}56, 95% CI 0{middle dot}33-0{middle dot}97; p=0{middle dot}027); overall, one additional death was prevented per six baricitinib-treated participants. Numerical improvements in endpoints such as number of ventilator-free days, duration of hospitalisation, and time to recovery were demonstrated. The frequency of serious adverse events, serious infections, and venous thromboembolic events was similar between baricitinib and placebo, respectively.\n\nThe COV-BARRIER study overall trial results plus these COV-BARRIER addendum study data in mechanically ventilated and ECMO patients provide important information in context of other large, phase 3 randomised trials in participants with invasive mechanical ventilation at baseline. The RECOVERY study reported mortality of 29{middle dot}3% following treatment with dexamethasone compared to 41{middle dot}4% for usual care (rate ratio of 0{middle dot}64, corresponding to a 36% relative reduction) and 49% mortality in participants who received tocilizumab compared to 51% for usual care (rate ratio of 0.93, corresponding to a 7% relative reduction). The ACTT-2 study reported 28-day mortality of 23{middle dot}1% and 22{middle dot}6% in the baricitinib plus remdesivir and placebo plus remdesivir groups, respectively, in this critically ill patient population; however, the primary outcome of this trial was time to recovery, so was not powered to detect a change in mortality.\n\nImplications of all the available evidenceIn this phase 3 addendum trial, baricitinib given in addition to SOC (which predominantly included corticosteroids) had a significant effect on mortality reduction by 28 days in critically ill patients, an effect which was maintained by 60 days. These data were comparable with those seen in the COV-BARRIER primary study population of hospitalised patients, but which excluded patients who required IMV or extracorporeal membrane oxygenation at enrolment. These findings suggest that baricitinib has synergistic effects to other SOC treatment modalities including remdesivir and dexamethasone. Based on the available evidence, baricitinib is a novel treatment option to decrease mortality in hospitalised, critically ill patients with COVID-19 even when started late in the disease process after steroids, mechanical ventilation, and ECMO have already been implemented.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.08.21264719", + "rel_abs": "BackgroundTrans Sodium Crocetinate (TSC) is a bipolar synthetic carotenoid under development as a drug to enhance oxygenation to hypoxic tissue in addition to standard of care. TSC acts via a novel mechanism of action, improving the diffusivity of oxygen in blood plasma. Thus, it is based on physical-chemical principles, unlike most drugs which are based on biochemistry-based mechanisms. We explored the use of escalating doses and multiple daily dosing of TSC as a potential therapeutic for patients suffering from hypoxemia due to SARS-CoV-2 infection.\n\nMethodsIndividuals [≥]18 years who were hospitalized with confirmed SARS-CoV-2 infection and hypoxemia, defined as SpO2 < 94% on room air or requiring supplemental oxygen, WHO ordinal scale 3 through 7 (exclusive of Extra Corporeal Membrane Oxygenation [ECMO]) were enrolled in cohorts of six subjects, each of whom received the same dose (0.25, 0.5, 1.0, or 1.5 mg/kg) of TSC via intravenous bolus every 6 hours in addition to standard of care (SOC).\n\nThis report describes the safety and efficacy results from the lead-in phase of the study and the population pharmacokinetics (PK) analyses. Safety was assessed as the number of serious adverse events and dose-limiting toxicities (DLTs) observed with each dose. Several efficacy parameters were examined in the lead-in phase and descriptive statistics of efficacy parameters are provided. No formal statistical analyses were performed. The population PK analyses were based on previous analyses and examination of the concentration profiles, and two-compartment linear pharmacokinetic models were evaluated and validated. Covariates, including body size, age, sex, organ function, and dose level, were evaluated for inclusion into the model.\n\nResultsTSC was well tolerated. There were no treatment emergent adverse events (TEAEs) reported. There were 2 serious adverse events (SAEs) reported during the study, neither were considered treatment-related. A total of 24 (96%) subjects survived. One subject (4.0%) died during the study as a result of an SAE (respiratory failure), and that event was determined to be due to COVID-19 complications and not related to study drug.\n\nThere was an observed reduction in the time to improvement in WHO Ordinal Scale with increasing dose. The median time to 1-point reduction in subjects receiving 0.25 mg/kg was 11.5 days versus 7.5 days in the 1.5 mg/kg treatment cohort. The overall range across all doses was 1 day to 28 days. A total of 36.0% of subjects had a 1-point improvement in WHO Ordinal Scale to Day 7. The 1.5 mg/kg dose resulted in observed superior outcomes for multiple secondary clinical outcomes: time to 1-point WHO Ordinal Score improvement through Day 29/discharge, 1-point improvement by Day 7, days to return to room air, and hospital length of stay.\n\nThe PK results showed that the two-compartment model fit the data well. Clearance decreased with increasing dose level and there was no evidence that clearance was affected by covariates other than dose level.\n\nConclusionsThese findings suggest that TSC administration every 6 hours at doses up to 1.5 mg/kg for up to 15 days is safe and well tolerated with predictable pharmacokinetics and demonstrated an observed clinical benefit in the treatment of COVID-19-related hypoxemia.\n\n(ClinicalTrials.gov number, NCT04573322)", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "E. Wesley Ely", - "author_inst": "Critical Illness, Brain Dysfunction, and Survivorship (CIBS) Center, Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine at Vande" + "author_name": "Adrian Streinu-Cercel", + "author_inst": "National Institute of Infectious Diseases. Bucharest, Romania" }, { - "author_name": "Athimalaipet V. Ramanan", - "author_inst": "Bristol Royal Hospital for Children; Translational Health Sciences, University of Bristol" - }, - { - "author_name": "Cynthia E. Kartman", - "author_inst": "Eli Lilly and Company" - }, - { - "author_name": "Stephanie de Bono", - "author_inst": "Eli Lilly and Company" - }, - { - "author_name": "Ran Liao", - "author_inst": "Eli Lilly and Company" + "author_name": "Oana Sandulescu", + "author_inst": "National Institute for Infectious Diseases. Bucharest, Romania" }, { - "author_name": "Maria Lucia B. Piruzeli", - "author_inst": "Eli Lilly and Company" + "author_name": "Victor Daniel Miron", + "author_inst": "National Institute for Infectious Diseases. Bucharest, Romania" }, { - "author_name": "Jason D. Goldman", - "author_inst": "Swedish Medical Center, Providence St. Joseph Health, and University of Washington" + "author_name": "Alina-Alexandra Oana", + "author_inst": "National Institute for Infectious Diseases. Bucharest, Romania" }, { - "author_name": "Jose Francisco Kerr Saraiva", - "author_inst": "Instituto de Pesquisa Clinica de Campinas (IPECC)" + "author_name": "Maria Magdalena Motoi", + "author_inst": "National Institute for Infectious Diseases. Bucharest, Romania" }, { - "author_name": "Sujatro Chakladar", - "author_inst": "Eli Lilly and Company" + "author_name": "Christopher D. Galloway", + "author_inst": "Diffusion Pharmaceuticals" }, { - "author_name": "Vincent C. Marconi", - "author_inst": "Emory University School of Medicine, Rollins School of Public Health, Emory Vaccine Center" + "author_name": "Adrian Streinu-Cercel", + "author_inst": "National Institute for Infectious Diseases. Bucharest, Romania" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2021.10.09.21264794", @@ -530834,55 +529091,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.06.21264651", - "rel_title": "Clinical Benefits and Budget Impact of Lenzilumab plus Standard of Care Compared with Standard of Care Alone for the Treatment of Hospitalized Patients with COVID-19 in the United States from the Hospital Perspective", - "rel_date": "2021-10-10", + "rel_doi": "10.1101/2021.10.08.21264741", + "rel_title": "Estimate of the rate of unreported COVID-19 cases during the first outbreak in Rio de Janeiro", + "rel_date": "2021-10-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.06.21264651", - "rel_abs": "AimsThe study estimated the clinical benefits and budget impact of lenzilumab plus standard of care (SOC) compared with SOC alone in the treatment of hospitalized COVID-19 patients from the United States hospital perspective.\n\nMaterials and MethodsAn economic model was developed to estimate the clinical benefits and costs for an average newly hospitalized COVID-19 patient, with a 28-day time horizon for the index hospitalization. Clinical outcomes from the LIVE-AIR trial included failure to achieve survival without ventilation (SWOV), mortality, time to recovery, intensive care unit (ICU) admission, and invasive mechanical ventilation (IMV) use. Base case costs included drug acquisition and administration for lenzilumab and hospital resource costs based on the level of care required. The inclusion of 1-year rehospitalization costs was examined in a scenario analysis.\n\nResultsIn the base case and all scenarios, treatment with lenzilumab plus SOC improved all specified clinical outcomes over SOC alone. Adding lenzilumab to SOC was also estimated to result in cost savings of $3,190 per patient in a population aged <85 years with CRP <150 mg/L and receiving remdesivir (base case). Per-patient cost savings were also estimated in the following scenarios: 1) aged <85 years with CRP <150 mg/L, with or without remdesivir ($1,858); 2) Black and African American patients with CRP <150 mg/L ($13,154); and 3) Black and African American patients from the full population ($2,763). In the full mITT population, a budget impact of $4,952 was estimated. When adding rehospitalization costs to the index hospitalization, a total per-patient cost savings of $5,154 was estimated.\n\nConclusionsThe results highlight the clinical benefits for SWOV, ventilator use, time to recovery, mortality, time in ICU, and time on IMV, in addition to a favorable budget impact from the United States hospital perspective associated with adding lenzilumab to SOC for patients with COVID-19 pneumonia.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.08.21264741", + "rel_abs": "In this work we fit an epidemiological model SEIAQR (Susceptible - Exposed - Infectious - Asymptomatic - Quarantined - Removed) to the data of the first COVID-19 outbreak in Rio de Janeiro, Brazil. Particular emphasis is given to the unreported rate, that is, the proportion of infected individuals that is not detected by the health system. The evaluation of the parameters of the model is based on a combination of error-weighted least squares method and appropriate B-splines. The structural and practical identifiability is analyzed to support the feasibility and robustness of the parameters estimation. We use the bootstrap method to quantify the uncertainty of the estimates. For the outbreak of March-July 2020 in Rio de Janeiro, we estimate about 90% of unreported cases, with a 95% confidence interval (85%, 93%).", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Adrian Kilcoyne", - "author_inst": "Humanigen Inc" - }, - { - "author_name": "Edward Jordan", - "author_inst": "Humanigen Inc" + "author_name": "Maria Soledad ARONNA", + "author_inst": "FGV - EMAp" }, { - "author_name": "Allen Zhou", - "author_inst": "EVERSANA" - }, - { - "author_name": "Kimberly A. Thomas", - "author_inst": "EVERSANA" - }, - { - "author_name": "Alicia N. Pepper", - "author_inst": "EVERSANA" - }, - { - "author_name": "Dale Chappell", - "author_inst": "Humanigen Inc" - }, - { - "author_name": "Miyuru Amarapala", - "author_inst": "Humanigen Inc" - }, - { - "author_name": "Avery Hughes", - "author_inst": "EVERSANA" + "author_name": "Roberto Guglielmi", + "author_inst": "University of Waterloo" }, { - "author_name": "Melissa Thompson", - "author_inst": "EVERSANA" + "author_name": "Lucas Machado Moschen", + "author_inst": "FGV - EMAp" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.10.07.21264419", @@ -532556,109 +530789,197 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2021.10.07.21264599", - "rel_title": "Characterizing the effective reproduction number during the COVID-19 epidemic: Insights from Qatar experience", + "rel_doi": "10.1101/2021.10.06.21264641", + "rel_title": "Comparative transmissibility of SARS-CoV-2 variants Delta and Alpha in New England, USA", "rel_date": "2021-10-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.07.21264599", - "rel_abs": "BackgroundThe effective reproduction number, Rt, is a tool to track and understand epidemic dynamics. This investigation of Rt estimations was conducted to guide the national COVID-19 response in Qatar, from the onset of the epidemic until August 18, 2021.\n\nMethodsReal-time \"empirical\" [Formula] was estimated using five methods, including the Robert Koch Institute, Cislaghi, Systrom-Bettencourt and Ribeiro, Wallinga and Teunis, and Cori et al. methods. R was also estimated using a transmission dynamics model [Formula]. Uncertainty and sensitivity analyses were conducted. Agreements between different Rt estimates were assessed by calculating correlation coefficients.\n\nResults[Formula] captured the evolution of the epidemic through three waves, public health response landmarks, effects of major social events, transient fluctuations coinciding with significant clusters of infection, and introduction and expansion of the B.1.1.7 variant. The various estimation methods produced consistent and overall comparable [Formula] estimates with generally large correlation coefficients. The Wallinga and Teunis method was the fastest at detecting changes in epidemic dynamics. [Formula] estimates were consistent whether using time series of symptomatic PCR-confirmed cases, all PCR-confirmed cases, acute-care hospital admissions, or ICU-care hospital admissions, to proxy trends in true infection incidence. [Formula] correlated strongly with [Formula] and provided an average [Formula].\n\nConclusionsRt estimations were robust and generated consistent results regardless of the data source or the method of estimation. Findings affirmed an influential role for Rt estimations in guiding national responses to the COVID-19 pandemic, even in resource-limited settings.", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.06.21264641", + "rel_abs": "The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant quickly rose to dominance in mid-2021, displacing other variants, including Alpha. Studies using data from the United Kingdom and India estimated that Delta was 40-80% more transmissible than Alpha, allowing Delta to become the globally dominant variant. However, it was unclear if the ostensible difference in relative transmissibility was due mostly to innate properties of Deltas infectiousness or differences in the study populations. To investigate, we formed a partnership with SARS-CoV-2 genomic surveillance programs from all six New England US states. By comparing logistic growth rates, we found that Delta emerged 37-163% faster than Alpha in early 2021 (37% Massachusetts, 75% New Hampshire, 95% Maine, 98% Rhode Island, 151% Connecticut, and 163% Vermont). We next computed variant-specific effective reproductive numbers and estimated that Delta was 58-120% more transmissible than Alpha across New England (58% New Hampshire, 68% Massachusetts, 76% Connecticut, 85% Rhode Island, 98% Maine, and 120% Vermont). Finally, using RT-PCR data, we estimated that Delta infections generate on average [~]6 times more viral RNA copies per mL than Alpha infections. Overall, our evidence indicates that Deltas enhanced transmissibility could be attributed to its innate ability to increase infectiousness, but its epidemiological dynamics may vary depending on the underlying immunity and behavior of distinct populations.", + "rel_num_authors": 45, "rel_authors": [ { - "author_name": "Raghid Bsat", - "author_inst": "Qatar University" + "author_name": "Rebecca Earnest", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA" }, { - "author_name": "Hiam Chemaitelly", - "author_inst": "Weill Cornell Medicine-Qatar" + "author_name": "Rockib Uddin", + "author_inst": "Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA 02114, USA" }, { - "author_name": "Peter Coyle", - "author_inst": "Hamad Medical Corporation" + "author_name": "Nicholas Matluk", + "author_inst": "Maine Center for Disease Control and Prevention, Augusta, ME 04333; Health and Environmental Testing Laboratory, 221 State Street, Augusta, Maine 04033" }, { - "author_name": "Patrick Tang", - "author_inst": "Sidra Medicine" + "author_name": "Nicholas Renzette", + "author_inst": "The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA" }, { - "author_name": "Mohammad Rubayet Hasan", - "author_inst": "Sidra Medicine" + "author_name": "Katherine J. Siddle", + "author_inst": "Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA" }, { - "author_name": "Zaina Al Kanaani", - "author_inst": "Hamad Medical Corporation" + "author_name": "Christine Loreth", + "author_inst": "Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA" }, { - "author_name": "Einas Al Kuwari", - "author_inst": "Hamad Medical Corporation" + "author_name": "Gordon Adams", + "author_inst": "Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA" }, { - "author_name": "Adeel A Butt", - "author_inst": "Hamad Medical Corporation" + "author_name": "Christopher Tomkins-Tinch", + "author_inst": "Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA" }, { - "author_name": "Andrew Jeremijenko", - "author_inst": "Hamad Medical Corporation" + "author_name": "Mary E. Petrone", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA" }, { - "author_name": "Anvar Hassan Kaleeckal", - "author_inst": "Hamad Medical Corporation" + "author_name": "Jessica E. Rothman", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA" }, { - "author_name": "Ali Nizar Latif", - "author_inst": "Hamad Medical Corporation" + "author_name": "Mallery I. Breban", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA" }, { - "author_name": "Riyazuddin Mohammad Shaik", - "author_inst": "Hamad Medical Corporation" + "author_name": "Robert Tobias Koch", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA" }, { - "author_name": "Gheyath A Nasrallah", - "author_inst": "Qatar University" + "author_name": "Kendall Billig", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA" }, { - "author_name": "Fatiha Benslimane", - "author_inst": "Qatar University" + "author_name": "Joseph R. Fauver", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA" }, { - "author_name": "Hebah A. Al Khatib", - "author_inst": "Qatar University" + "author_name": "Chantal B.F. Vogels", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA" }, { - "author_name": "HADI M. YASSINE", - "author_inst": "Qatar University" + "author_name": "Sarah Turbett", + "author_inst": "Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA 02114, USA" }, { - "author_name": "Mohamed Ghaith Al Kuwari", - "author_inst": "Primary Health Care Corporation" + "author_name": "Kaya Bilguvar", + "author_inst": "Yale Center for Genome Analysis, Yale University, New Haven, CT, 06510, USA; Departments of Neurosurgery and Genetics, Yale School of Medicine, New Haven, CT 06" }, { - "author_name": "Hamad Eid Al Romaihi", - "author_inst": "Ministry of Public Health" + "author_name": "Bony De Kumar", + "author_inst": "Yale Center for Genome Analysis, Yale University, New Haven, CT, 06510, USA" }, { - "author_name": "Mohamed H. Al-Thani", - "author_inst": "Ministry of Public Health" + "author_name": "Marie L. Landry", + "author_inst": "Departments of Laboratory Medicine and Medicine, Yale University School of Medicine, New Haven, CT 06510, USA" }, { - "author_name": "Abdullatif Al Khal", - "author_inst": "Hamad Medical Corporation" + "author_name": "David R. Peaper", + "author_inst": "Departments of Laboratory Medicine and Medicine, Yale University School of Medicine, New Haven, CT 06510, USA" }, { - "author_name": "Roberto Bertollini", - "author_inst": "Ministry of Public Health" + "author_name": "Kevin Kelly", + "author_inst": "The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA" }, { - "author_name": "Laith J Abu-Raddad", - "author_inst": "Weill Cornell Medicine-Qatar" + "author_name": "Greg Omerza", + "author_inst": "The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA" }, { - "author_name": "Houssein H. Ayoub", - "author_inst": "Qatar University" + "author_name": "Heather Grieser", + "author_inst": "Maine Center for Disease Control and Prevention, Augusta, ME 04333; Health and Environmental Testing Laboratory, 221 State Street, Augusta, Maine 04033" + }, + { + "author_name": "Sim Meak", + "author_inst": "Maine Center for Disease Control and Prevention, Augusta, ME 04333; Health and Environmental Testing Laboratory, 221 State Street, Augusta, Maine 04033" + }, + { + "author_name": "John Martha", + "author_inst": "Maine Center for Disease Control and Prevention, Augusta, ME 04333; Health and Environmental Testing Laboratory, 221 State Street, Augusta, Maine 04033" + }, + { + "author_name": "Hannah H. Dewey", + "author_inst": "The Jackson Laboratory, Bar Harbor, ME 04609, USA" + }, + { + "author_name": "Susan Kales", + "author_inst": "The Jackson Laboratory, Bar Harbor, ME 04609, USA" + }, + { + "author_name": "Daniel Berenzy", + "author_inst": "The Jackson Laboratory, Bar Harbor, ME 04609, USA" + }, + { + "author_name": "Kristin Carpenter-Azevedo", + "author_inst": "Rhode Island Department of Health, Providence, RI 02904" + }, + { + "author_name": "Ewa King", + "author_inst": "Rhode Island Department of Health, Providence, RI 02904" + }, + { + "author_name": "Richard C. Huard", + "author_inst": "Rhode Island Department of Health, Providence, RI 02904" + }, + { + "author_name": "Sandra C. Smole", + "author_inst": "Massachusetts Department of Public Health, Boston MA, 02130, USA" + }, + { + "author_name": "Catherine M. Brown", + "author_inst": "Massachusetts Department of Public Health, Boston MA, 02130, USA" + }, + { + "author_name": "Timelia Fink", + "author_inst": "Massachusetts Department of Public Health, Boston MA, 02130, USA" + }, + { + "author_name": "Andrew S. Lang", + "author_inst": "Massachusetts Department of Public Health, Boston MA, 02130, USA" + }, + { + "author_name": "Glen R. Gallagher", + "author_inst": "Massachusetts Department of Public Health, Boston MA, 02130, USA" + }, + { + "author_name": "Pardis C. Sabeti", + "author_inst": "Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA" + }, + { + "author_name": "Stacey Gabriel", + "author_inst": "Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA" + }, + { + "author_name": "Bronwyn L. MacInnis", + "author_inst": "Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA" + }, + { + "author_name": "- New England Variant Investigation Team", + "author_inst": "" + }, + { + "author_name": "Ryan Tewhey", + "author_inst": "The Jackson Laboratory, Bar Harbor, ME 04609, USA; Graduate School of Biomedical Sciences, Tufts University School of Medicine, Boston, MA 02111, USA" + }, + { + "author_name": "Mark D. Adams", + "author_inst": "The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA" + }, + { + "author_name": "Daniel J. Park", + "author_inst": "Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA" + }, + { + "author_name": "Jacob E. Lemieux", + "author_inst": "Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA 02114, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA" + }, + { + "author_name": "Nathan D. Grubaugh", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA; Department of Ecology and Evolutionary Biology, Yale U" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -534750,29 +533071,73 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.10.04.21263345", - "rel_title": "Characterizing the spatiotemporal heterogeneity of the COVID-19 vaccination landscape", + "rel_doi": "10.1101/2021.10.06.21264632", + "rel_title": "Time trends in social contacts before and during the COVID-19 pandemic: the CONNECT study", "rel_date": "2021-10-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.04.21263345", - "rel_abs": "It is critical that we maximize vaccination coverage across the United States so that SARS-CoV-2 transmission can be suppressed, and we can sustain the recent reopening of the nation. Maximizing vaccination requires that we track vaccination patterns to measure the progress of the vaccination campaign and target locations that may be undervaccinated. To improve efforts to track and characterize COVID-19 vaccination progress in the United States, we integrate CDC and state-provided vaccination data, identifying and rectifying discrepancies between these data sources. We find that COVID-19 vaccination coverage in the US exhibits significant spatial heterogeneity at the county level and statistically identify spatial clusters of undervaccination, all with foci in the southern US. Vaccination progress at the county level is also variable; many counties stalled in vaccination into June 2021 and few recovered by July, with transmission of the Delta variant rapidly rising. Using a comparison with a mechanistic growth model fitted to our integrated data, we classify vaccination dynamics across time at the county scale. Our findings underline the importance of curating accurate, fine-scale vaccination data and the continued need for widespread vaccination in the US, especially in the wake of the highly transmissible Delta variant.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.06.21264632", + "rel_abs": "BackgroundSince the beginning of the COVID-19 pandemic, many countries, including Canada, have adopted unprecedented physical distancing measures such as closure of schools and non-essential businesses, and restrictions on gatherings and household visits. We described time trends in social contacts for the pre-pandemic and pandemic periods in Quebec, Canada.\n\nMethodsCONNECT is a population-based study of social contacts conducted shortly before (2018/2019) and during the COVID-19 pandemic (April 2020 - February 2021), using the same methodology for both periods. We recruited participants by random-digit-dialing and collected data by self-administered web-based questionnaires. Questionnaires documented socio-demographic characteristics and social contacts for two assigned days. A contact was defined as a two-way conversation at a distance [≤]2 meters or as a physical contact, irrespective of masking. We used weighted generalized linear models with a Poisson distribution and robust variance (taking possible overdispersion into account) to compare the mean number of social contacts over time by characteristics.\n\nResultsA total of 1291 and 5516 Quebecers completed the study before and during the pandemic, respectively. Contacts significantly decreased from a mean of 8 contacts/day prior to the pandemic to 3 contacts/day during the spring 2020 lockdown. Contacts remained lower than the pre-COVID period thereafter (lowest=3 contacts/day during the Christmas 2020/2021 holidays, highest=5 in September 2020). Contacts at work, during leisure activities/other locations, and at home with visitors showed the greatest decreases since the beginning of the pandemic. All sociodemographic subgroups showed significant decreases of contacts since the beginning of the pandemic. The mixing matrices illustrated the impact of public health measures (e.g. school closure, gathering restrictions) with fewer contacts between children/teenagers and fewer contacts outside of the three main diagonals of contacts between same-age partners/siblings and between children and their parents.\n\nConclusionPhysical distancing measures in Quebec significantly decreased social contacts, which most likely mitigated the spread of COVID-19.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Andrew Tiu", - "author_inst": "Georgetown University" + "author_name": "Melanie Drolet", + "author_inst": "Centre de recherche du CHU de Quebec-Universite Laval, Canada" }, { - "author_name": "Zachary Susswein", - "author_inst": "Georgetown University" + "author_name": "Aurelie Godbout", + "author_inst": "Laval University, Canada" }, { - "author_name": "Alexes Merritt", - "author_inst": "Georgetown University" + "author_name": "Myrto Mondor", + "author_inst": "Centre de recherche du CHU de Quebec-Universite Laval, Canada" }, { - "author_name": "Shweta Bansal", - "author_inst": "Georgetown University" + "author_name": "Lea Drolet-Roy", + "author_inst": "Centre de recherche du CHU de Quebec-Universite Laval, Canada" + }, + { + "author_name": "Guillaume Beraud", + "author_inst": "Centre Hospitalier Universitaire de Poitiers, France" + }, + { + "author_name": "Philippe Lemieux-Mellouki", + "author_inst": "Laval University, Canada" + }, + { + "author_name": "Alexandre Bureau", + "author_inst": "Laval University, Canada" + }, + { + "author_name": "Eric Demers", + "author_inst": "Centre de recherche du CHU de Quebec-Universite Laval, Canada" + }, + { + "author_name": "Mare-Claude Boily", + "author_inst": "Imperial College London, UK" + }, + { + "author_name": "Chantal Sauvageau", + "author_inst": "Institut national de sante publique du Quebec" + }, + { + "author_name": "Gaston De Serres", + "author_inst": "Institut national de sante publique du Quebec, Canada" + }, + { + "author_name": "Niel Hens", + "author_inst": "Hasselt University and University of Antwerp" + }, + { + "author_name": "Philippe Beutels", + "author_inst": "University of Antwerp, Belgium" + }, + { + "author_name": "Benoit Dervaux", + "author_inst": "Univ Lille, Inserm, CHU Lille, Institut Pasteur U1167-RID-AGE, France" + }, + { + "author_name": "Marc Brisson", + "author_inst": "Laval University" } ], "version": "1", @@ -537156,51 +535521,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.04.21264521", - "rel_title": "Clinical utility of Elecsys Anti-SARS-CoV-2 S assay in COVID-19 vaccination: An exploratory analysis of the mRNA-1273 phase 1 trial", - "rel_date": "2021-10-05", + "rel_doi": "10.1101/2021.10.01.21264447", + "rel_title": "The paradox of the COVID-19 pandemic: the impact on patient demand in Japanese hospitals", + "rel_date": "2021-10-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.04.21264521", - "rel_abs": "BackgroundThe ability to quantify an immune response after vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential. This study assessed the clinical utility of the quantitative Roche Elecsys(R) Anti-SARS-CoV-2 S assay (ACOV2S) using samples from the 2019-nCoV vaccine (mRNA-1273) phase 1 trial (NCT04283461).\n\nMethodsSamples from 30 healthy participants, aged 18-55 years, who received two injections with mRNA-1273 at a dose of 25 g (n=15) or 100 g (n=15), were collected at Days 1 (first vaccination), 15, 29 (second vaccination), 43 and 57. ACOV2S results (shown in U/mL - equivalent to BAU/mL per the first WHO international standard) were compared with results from ELISAs specific to antibodies against the Spike protein (S-2P) and the receptor binding domain (RBD) as well as neutralization tests including nanoluciferase (nLUC80), live-virus (PRNT80), and a pseudovirus neutralizing antibody assay (PsVNA50).\n\nResultsRBD-specific antibodies were already detectable by ACOV2S at the first time point of assessment (d15 after first vaccination), with seroconversion before in all but 2 participants (25 g dose group); all had seroconverted by Day 29. Across all post-baseline visits, geometric mean concentration of antibody levels were 3.27-7.48-fold higher in the 100 g compared with the 25 g dose group. ACOV2S measurements were highly correlated with those from RBD ELISA (Pearsons r=0.938; p<0.0001) and S-2P ELISA (r=0.918; p<0.0001). For both ELISAs, heterogeneous baseline results and smaller increases in antibody levels following the second vs first vaccination compared with ACOV2S were observed. ACOV2S showed absence of any baseline noise indicating high specificity detecting vaccine-induced antibody response. Moderate-strong correlations were observed between ACOV2S and neutralization tests (nLUC80 r=0.933; PsVNA50, r=0.771; PRNT80, r=0.672; all p[≤]0.0001).\n\nConclusionThe Elecsys Anti-SARS-CoV-2 S assay (ACOV2S) can be regarded as a highly valuable method to assess and quantify the presence of RBD-directed antibodies against SARS-CoV-2 following vaccination, and may indicate the presence of neutralizing antibodies. As a fully automated and standardized method, ACOV2S could qualify as the method of choice for consistent quantification of vaccine-induced humoral response.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.01.21264447", + "rel_abs": "Analyzing data from a large, nationally distributed group of Japanese hospitals, we found a dramatic decline in both inpatient and outpatient volumes over the three waves of the COVID- 19 pandemic in Japan from February-December 2020. We identified three key reasons for this fall in patient demand. First, COVID-19-related hygiene measures and behavioral changes significantly reduced non-COVID-19 infectious diseases. Second, consultations relating to chronic diseases fell sharply. Third, certain medical investigations and interventions were postponed or cancelled. Despite the drop in hospital attendances and admissions, COVID-19 is said to have brought the Japanese health care system to the brink of collapse. In this context, we explore longstanding systematic issues, finding that Japans abundant supply of beds and current payment system may have introduced a perverse incentive to overprovide services, creating a mismatch between patient needs and the supply of health care resources. Poor coordination among health care providers and the highly decentralized governance of the health care system have also contributed to the crisis. In order to ensure the long-term sustainability of the Japanese health care system beyond COVID-19, it is essential to promote specialization and differentiation of medical functions among hospitals, to strengthen governance, and to introduce appropriate payment reform.\n\nO_TEXTBOXHighlights{blacksquare} Patient volumes in Japanese hospitals fell sharply due to the COVID-19 pandemic.\n{blacksquare}Behavioral changes and appointment cancellations contributed to the decline.\n{blacksquare}Japans health system reached breaking point due to longstanding systematic issues.\n{blacksquare}There is a mismatch between patient needs and the supply of health care resources.\n{blacksquare}Payment reform and stronger governance are needed to future-proof the health system.\n\n\nC_TEXTBOX", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Simon Jochum", - "author_inst": "Roche Diagnostics GmbH" - }, - { - "author_name": "Imke Kirste", - "author_inst": "Roche Diagnostics Operations" - }, - { - "author_name": "Sayuri Hortsch", - "author_inst": "Roche Diagnostics GmbH" - }, - { - "author_name": "Veit Peter Grunert", - "author_inst": "Roche Diagnostics GmbH" - }, - { - "author_name": "Holly Legault", - "author_inst": "Moderna Inc." - }, - { - "author_name": "Udo Eichenlaub", - "author_inst": "Roche Diagnostics GmbH" - }, - { - "author_name": "Basel Kashlan", - "author_inst": "PPD Inc." + "author_name": "Masako Ii", + "author_inst": "Hitotsubashi University" }, { - "author_name": "Rolando Pajon", - "author_inst": "Moderna Inc." + "author_name": "Sachiko Watanabe", + "author_inst": "Global Health Consulting Japan" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "health policy" }, { "rel_doi": "10.1101/2021.10.02.21264210", @@ -538754,79 +537095,75 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.10.01.21264371", - "rel_title": "COVID-19 Neutralizing Antibody Surveillance Testing for Fully Vaccinated Individuals During Delta Variant Spread", + "rel_doi": "10.1101/2021.10.02.21264468", + "rel_title": "SARS-CoV-2 Seroprevalence among Healthcare Workers", "rel_date": "2021-10-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.01.21264371", - "rel_abs": "We recently performed 568 rapid neutralizing antibody (NAb) tests on 164 fully vaccinated individuals who received either Moderna or Pfizer COVID-19 vaccine regimens over 7 weeks. The NAb levels against the wild type (WA1/2020), Delta, and Kappa variants were measured and compared. Depending on each individuals medical condition and vaccination status, the NAb levels for most of the fully vaccinated people decreased within 2-6 months, while a small number of individuals either generated non-detectable amount of NAbs after full vaccination (e.g., immunocompromised), or had high NAb levels lasting beyond 6 months. Since the NAb levels vary significantly among different individuals and decrease over time, the deployment of a low-cost rapid test to monitor NAb levels against both the wild type and emerging variants among fully vaccinated individuals can play a very crucial role to control the current pandemic. Our study provides an example of using such a rapid NAb test to fill this currently unmet medical need.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.02.21264468", + "rel_abs": "BackgroundMonitoring COVID-19 infection risk among health care workers (HCWs) is a public health priority. We examined the seroprevalence of SARS-CoV-2 among HCWs following the fall infection surge in Minnesota, and before and after COVID-19 vaccination. Additionally, we assessed demographic and occupational risk factors for SARS-CoV-2 infection.\n\nMethodsWe conducted two rounds of seroprevalence testing among a cohort of HCWs: samples in round 1 were collected from 11/22/20 - 02/21/21 and in round 2 from 12/18/20 - 02/15/21. Demographic and occupational exposures assessed with logistic regression were age, sex, healthcare role and setting, and number of children in the household. The primary outcome was SARS-CoV-2 IgG seropositivity. A secondary outcome, SARS-CoV-2 infection, included both seropositivity and self-reported SARS-CoV-2 test positivity.\n\nResultsIn total, 459 HCWs were tested. 43/454 (9.47%) had a seropositive sample 1 and 75/423 (17.7%) had a seropositive sample 2. By time of sample 2 collection, 54% of participants had received at least one vaccine dose and seroprevalence was 13% among unvaccinated individuals. Relative to physicians, the odds of SARS-CoV-2 infection in other roles were increased (Nurse Practitioner: OR[95%CI] 1.93[0.57,6.53], Physicians Assistant: 1.69[0.38,7.52], Nurse: 2.33[0.94,5.78], Paramedic/EMTs: 3.86[0.78,19.0], other: 1.68[0.58,4.85]). The workplace setting was associated with SARS-CoV-2 infection (p=0.04). SARS-CoV-2 seroprevalence among HCWs reporting duties in the ICU vs. those working in an ambulatory clinic was elevated: OR[95%CI] 2.17[1.01,4.68].\n\nConclusionsSARS-CoV-2 seroprevalence in HCW increased during our study period which was consistent with community infection rates. HCW role and setting -- particularly working in the ICU -- is associated with higher risk for SARS-CoV-2 infection.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Jing Pan", - "author_inst": "ANP Technologies, Inc." - }, - { - "author_name": "Zhigang Li", - "author_inst": "ANP Technologies, Inc." + "author_name": "Talia D Wiggen", + "author_inst": "Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN" }, { - "author_name": "Lin Wang", - "author_inst": "ANP Technologies, Inc." + "author_name": "Bruno Bohn", + "author_inst": "Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN" }, { - "author_name": "Joshua Szymanski", - "author_inst": "ANP Technologies, Inc." + "author_name": "Angela K Ulrich", + "author_inst": "Center for Infectious Disease Research and Policy, University of Minnesota, Minneapolis, MN" }, { - "author_name": "Maria Romano", - "author_inst": "ANP Technologies, Inc." + "author_name": "Steven D Stovitz", + "author_inst": "Department of Family Medicine and Community Health, Medical School, University of Minnesota, Minneapolis, MN" }, { - "author_name": "Dylan Yin", - "author_inst": "ANP Technologies, Inc." + "author_name": "Ali J Strickland", + "author_inst": "Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN" }, { - "author_name": "Allen Wang", - "author_inst": "ANP Technologies, Inc." + "author_name": "Brianna Mae Naumchik", + "author_inst": "Department of Pediatrics, Medical School, University of California San Diego, San Diego, CA" }, { - "author_name": "Thomas Small", - "author_inst": "ANP Technologies, Inc." + "author_name": "Sara Walsh", + "author_inst": "NORC at the University of Chicago, Health Sciences, Chicago, IL" }, { - "author_name": "Zhiying Zou", - "author_inst": "ANP Technologies, Inc." + "author_name": "Stephen Smith", + "author_inst": "NORC at the University of Chicago, Health Sciences, Chicago, IL" }, { - "author_name": "Jing Li", - "author_inst": "ANP Technologies, Inc." + "author_name": "Brett Baumgartner", + "author_inst": "Quansys Biosciences, Logan, UT" }, { - "author_name": "Greg Witham", - "author_inst": "ANP Technologies, Inc." + "author_name": "Susan Kline", + "author_inst": "Division of Infectious Diseases and International Medicine, Medical School, University of Minnesota, Minneapolis, MN" }, { - "author_name": "Li Wang", - "author_inst": "ANP Technologies, Inc." + "author_name": "Stephanie Yendell", + "author_inst": "Minnesota Department of Health, St. Paul, MN" }, { - "author_name": "Yubei Zhang", - "author_inst": "ANP Technologies, Inc." + "author_name": "Craig Hedberg", + "author_inst": "Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN" }, { - "author_name": "Kai Qi", - "author_inst": "ANP Technologies, Inc." + "author_name": "Timothy J Beebe", + "author_inst": "Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, MN" }, { - "author_name": "Ray Yin", - "author_inst": "ANP Technologies, Inc." + "author_name": "Ryan T Demmer", + "author_inst": "Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN & Department of Epidemiology, Mailman School of" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.10.01.21264412", @@ -540488,67 +538825,71 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2021.09.30.21264273", - "rel_title": "Predicting the unpredictable: how dynamic COVID-19 policies and restrictions challenge model forecasts", + "rel_doi": "10.1101/2021.09.29.21264314", + "rel_title": "Telemedicine and molecular Sars-CoV-2 early detection to face the COVID-19 pandemic", "rel_date": "2021-10-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.30.21264273", - "rel_abs": "IntroductionTo retrospectively assess the accuracy of a mathematical modelling study that projected the rate of COVID-19 diagnoses for 72 locations worldwide in 2021, and to identify predictors of model accuracy.\n\nMethodsBetween June and August 2020, an agent-based model was used to project rates of COVID-19 infection incidence and cases diagnosed as positive from 15 September to 31 October 2020 for 72 geographic settings. Five scenarios were modelled: a baseline scenario where no future changes were made to existing restrictions, and four scenarios representing small or moderate changes in restrictions at two intervals. Post hoc, upper and lower bounds for number of diagnosed Covid-19 cases were compared with actual data collected during the prediction window. A regression analysis with 17 covariates was performed to determine correlates of accurate projections.\n\nResultsThe actual data fell within the lower and upper bounds in 27 settings and out of bounds in 45 settings. The only statistically significant predictor of actual data within the predicted bounds was correct assumptions about future policy changes (OR = 15.04; 95%CI 2.20-208.70; p=0.016).\n\nConclusionsFor this study, the accuracy of COVID-19 model projections was dependent on whether assumptions about future policies are correct. Frequent changes in restrictions implemented by governments, which the modelling team was not always able to predict, in part explains why the majority of model projections were inaccurate compared with actual outcomes and supports revision of projections when policies are changed as well as the importance of policy experts collaborating on modelling projects.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.29.21264314", + "rel_abs": "The COVID-19 pandemic brought a series of challenges to the academic community. Social distancing measures imposed the interruption of face-to-face activities besides the implementation of remote work and online classes. For safe and gradual return, the monitoring of individuals, quick detection of infection, contact tracing, and isolation of those infected became essential. In this sense, we developed strategies to face the pandemic at the Federal University of Lavras (UFLA) - Brazil. A Telemedicine Program (TeleCovid) and the assemblage of a laboratory for SARS-CoV-2 molecular diagnosis (LabCovid) were essential measures for monitoring, preventing, and controlling outbreaks at the university. TeleCovid works with a team of students who guide and answer questions regarding COVID-19 and, when necessary, make the referral for online consultation with medical professionals. In the suspicion of SARS-CoV-2 infection, the doctor refers the patient for testing at LabCovid. LabCovid performs the sample collection using nasal swabs, followed by processing samples by the RT-qPCR method. We have placed all positive patients in isolation and tested their contacts. This approach meant that positive cases were identified early, thus avoiding outbreaks in different environments in face-to-face activities.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Farah Houdroge", - "author_inst": "Burnet Institute" + "author_name": "Jose Cherem", + "author_inst": "Federal University of Lavras" }, { - "author_name": "Anna Palmer", - "author_inst": "Burnet Institute" + "author_name": "Victor Satler Pylro", + "author_inst": "Federal University of Lavras" }, { - "author_name": "Dominic Delport", - "author_inst": "Burnet Institute" + "author_name": "Katia Poles", + "author_inst": "Federal University of Lavras" }, { - "author_name": "Tom Walsh", - "author_inst": "Burnet Institute" + "author_name": "Richardson Costa Carvalho", + "author_inst": "Unilavras" }, { - "author_name": "Sherrie L Kelly", - "author_inst": "Burnet Institute" + "author_name": "Ewerton Carvalho Sr.", + "author_inst": "Federal University of Lavras" }, { - "author_name": "Samuel W Hainsworth", - "author_inst": "Burnet Institute" + "author_name": "Juliana Anacleto dos Santos", + "author_inst": "Federal University of Lavras" }, { - "author_name": "Romesh G Abeysuriya", - "author_inst": "Burnet Institute" + "author_name": "Ingrid Marciano Alvarenga", + "author_inst": "Federal University of Lavras" }, { - "author_name": "Robyn M Stuart", - "author_inst": "University of Copenhagen" + "author_name": "Denise Alvarenga Rocha", + "author_inst": "Federal University of Lavras" }, { - "author_name": "Cliff C Kerr", - "author_inst": "Bill & Melinda Gates Foundation, University of Sydney" + "author_name": "Karla Silva Teixeira Souza", + "author_inst": "Federal University of Lavras" }, { - "author_name": "Paul Coplan", - "author_inst": "Johnson and Johnson" + "author_name": "Joseane Camilla Castro", + "author_inst": "Federal University of Lavras" }, { - "author_name": "David P Wilson", - "author_inst": "Burnet Institute, Monash University, Bill & Melinda Gates Foundation" + "author_name": "Mariana Almeida Torquete", + "author_inst": "Federal University of Lavras" }, { - "author_name": "Nick Scott", - "author_inst": "Burnet Institute" + "author_name": "Sidney de Almeida Ferreira", + "author_inst": "Federal University of Lavras" + }, + { + "author_name": "Joziana MP Barcante", + "author_inst": "Federal University of Lavras" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.10.01.21264382", @@ -542742,29 +541083,97 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.27.21264194", - "rel_title": "SARS-Cov-2 Infection versus Vaccine-Induced Immunity among Veterans", + "rel_doi": "10.1101/2021.09.27.21264013", + "rel_title": "Persistence of robust humoral immune response in COVID-19 convalescent individuals over 12 months after infection", "rel_date": "2021-09-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.27.21264194", - "rel_abs": "BackgroundWith over 40 million cases of SARS-CoV-2 infection reported in the US and discussion of both vaccine mandates as well as boosters ongoing, we aim to examine protection conferred by previous infection compared with vaccination so that citizens and policy makers can make informed decisions.\n\nObjectivesTo compare mRNA COVID-19 vaccine-induced immunity against immunity induced by previous infection with SARS-CoV-2 between June and August 2021 when the Delta variant became dominant in the US.\n\nWe conducted a retrospective observational study comparing two groups whose incident vaccination or infection occurred within the first two months of 2021: (1) SARS-CoV-2-naive individuals who received a full mRNA vaccination - 2 doses of either Pfizer or Moderna vaccine, (2) newly infected individuals who were subdivided into those have not been vaccinated and those have been vaccinated after their infection. Matched multivariable Cox proportional hazards model was applied. We evaluated laboratory (RT-PCR) confirmed SARS-CoV-2 infection during follow-up, COVID-related hospitalization, and deaths.\n\nSettingVeterans Health Administration (VHA).\n\nMain outcomesPositive SARS-CoV-2 PCR test, COVID-related hospitalization, and deaths. Protection was estimated from hazard ratios with 95% confidence intervals (CI).\n\nResultsA total of 9,539 patients with SARS-CoV-2 infection during the first two months of 2021 were matched to 14,458 and 23,105 patients fully vaccinated with Moderna and Pfizer mRNA vaccines, during the same two months. 3,917 (41%) of patients with SARS-CoV-2 infection were subsequently vaccinated. We plan to study this group separately. Consequently, protections were estimated among those with infection but were not subsequently vaccinated and those vaccinated with a mRNA vaccine. Among seniors, Moderna and Pfizer mRNA vaccines offered stronger protection against infection, lowering the risk by an additional 66% [HR: 0.34 (95% CI, 0.14-0.78)] and 68% [HR: 0.32 (95% CI, 0.14-0.70)]; stronger protection against hospitalization, lowering the risk by an additional 61% [HR: 0.34 (95% CI, 0.14-0.78)] and 45% [HR: 0.34 (95% CI, 0.14-0.78)]; and stronger protection against deaths lowering the risk by an additional 95% [HR: 0.05 (95% CI, 0.004-0.62)] and 99% [HR: 0.01 (95% CI, 0.001-0.44)]. Among young adults (age < 65), the protections offered by vaccines were statistically equivalent to that provided by previous infection, especially in terms of absolute incidence rate.\n\nConclusionsAmong the elderly (age 65 or older), two-dose mRNA vaccines provided stronger protection against infection, hospitalization, and death, compared to natural immunity. Among young adults (age < 65), the protections offered between natural immunity and vaccine-induced immunity were similar.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.27.21264013", + "rel_abs": "SARS-CoV-2 infection elicits varying degrees of protective immunity conferred by neutralizing antibodies (nAbs). Here we report the persistence of nAb responses over 12 months after infection despite its decreasing trend noticed from 6 months. The study included sera from 358 individuals who had been infected with SARS-CoV-2 between January and May 2020. Samples were collected at 6 and 12 months after onset. The titers of IgG to the viral nucleocapsid protein (NP) and receptor-binding domain of the spike protein (RBD) were measured by CLEIA. The nAb titer was determined using lentivirus-based pseudovirus or authentic virus. Antibody titers of NP-IgG, RBD-IgG, and nAbs were higher in severe and moderate cases than in mild cases at 12 months after onset. While the nAb levels were likely to confer adequate protection against wild-type viral infection, the neutralization activity to recently circulating variants in some of the mild cases ([~]30%) was undermined, implying the susceptibility of reinfection to the variants of concerns (VOCs). COVID-19 convalescent individuals have robust humoral immunity even at 12 months after infection albeit that the medical history and background of patients could affect the function and dynamics of antibody response to the VOCs.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Yinong Young-Xu", - "author_inst": "White River Junction Veterans Affairs Medical Center, White River Junction, VT" + "author_name": "Kei Miyakawa", + "author_inst": "Yokohama City University Graduate School of Medicine" }, { - "author_name": "Jeremy Smith", - "author_inst": "VA Medical Center White River Junction Vermont" + "author_name": "Sousuke Kubo", + "author_inst": "Yokohama City University Graduate School of Medicine" }, { - "author_name": "Caroline Korves", - "author_inst": "White River Junction Veterans Affairs Medical Center, White River Junction, VT" + "author_name": "Sundararaj Stanleyraj Jeremiah", + "author_inst": "Yokohama City University Graduate School of Medicine" + }, + { + "author_name": "Hirofumi Go", + "author_inst": "Yokohama City University Graduate School of Medicine" + }, + { + "author_name": "Yutaro Yamaoka", + "author_inst": "Kanto Chemical Co, Inc." + }, + { + "author_name": "Norihisa Ohtake", + "author_inst": "Tosoh Corporation" + }, + { + "author_name": "Hideaki Kato", + "author_inst": "Yokohama City University Hospital" + }, + { + "author_name": "Satoshi Ikeda", + "author_inst": "Kanagawa Cardiovascular and Respiratory Center" + }, + { + "author_name": "Takahiro Mihara", + "author_inst": "Yokohama City University Graduate School of Data Science" + }, + { + "author_name": "Ikuro Matsuba", + "author_inst": "Matsuba Medical Clinic" + }, + { + "author_name": "Naoko Sanno", + "author_inst": "Shinagawa Strings Clinic" + }, + { + "author_name": "Masaaki Miyakawa", + "author_inst": "Miyakawa Internal Medicine and Pediatrics Clinic" + }, + { + "author_name": "Masaharu Shinkai", + "author_inst": "Tokyo-Shinagawa Hospital" + }, + { + "author_name": "Tomoyuki Miyazaki", + "author_inst": "Yokohama City University Graduate School of Medicine" + }, + { + "author_name": "Takashi Ogura", + "author_inst": "Kanagawa Cardiovascular and Respiratory Center" + }, + { + "author_name": "Shuichi Ito", + "author_inst": "Yokohama City University Graduate School of Medicine" + }, + { + "author_name": "Takeshi Kaneko", + "author_inst": "Yokohama City University Graduate School of Medicine" + }, + { + "author_name": "Kouji Yamamoto", + "author_inst": "Yokohama City University Graduate School of Medicine" + }, + { + "author_name": "Atsushi Goto", + "author_inst": "Yokohama City University Graduate School of Data Science" + }, + { + "author_name": "Akihide Ryo", + "author_inst": "Yokohama City University Graduate School of Medicine" } ], "version": "1", - "license": "cc0", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -544816,79 +543225,47 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.09.27.21264166", - "rel_title": "Prevalence and duration of detectable SARS-CoV-2 nucleocapsid antibody in staff and residents of long-term care facilities over the first year of the pandemic (VIVALDI study): prospective cohort study", - "rel_date": "2021-09-29", + "rel_doi": "10.1101/2021.09.27.21264005", + "rel_title": "\"The vaccination is positive; I don't think it's the panacea\": A qualitative study on COVID-19 vaccine attitudes among ethnically diverse healthcare workers in the United Kingdom", + "rel_date": "2021-09-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.27.21264166", - "rel_abs": "BackgroundLong Term Care Facilities (LTCF) have reported high SARS-CoV-2 infection rates and related mortality, but the proportion infected amongst survivors and duration of the antibody response to natural infection is unknown. We determined the prevalence and stability of nucleocapsid antibodies - the standard assay for detection of prior infection - in staff and residents from 201 LTCFs.\n\nMethodsProspective cohort study of residents aged >65 years and staff of LTCFs in England (11 June 2020-7 May 2021). Serial blood samples were tested for IgG antibodies against SARS-CoV-2 nucleocapsid protein. Prevalence and cumulative incidence of antibody-positivity were weighted to the LTCF population. Cumulative incidence of sero-reversion was estimated from Kaplan-Meier curves.\n\nResults9488 samples were included, 8636 (91%) of which could be individually-linked to 1434 residents or 3288 staff members. The cumulative incidence of nucleocapsid seropositivity was 35% (95% CI: 30-40%) in residents and 26% (95% CI: 23-30%) in staff over 11 months. The incidence rate of loss of antibodies (sero-reversion) was 2{middle dot}1 per 1000 person-days at risk, and median time to reversion was around 8 months.\n\nInterpretationAt least one-quarter of staff and one-third of surviving residents were infected during the first two pandemic waves. Nucleocapsid-specific antibodies often become undetectable within the first year following infection which is likely to lead to marked underestimation of the true proportion of those with prior infection. Since natural infection may act to boost vaccine responses, better assays to identify natural infection should be developed.\n\nFundingUK Government Department of Health and Social Care.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSA search was conducted of Ovid MEDLINE and MedRxiv on 21 July 2021 to identify studies conducted in long term care facilities (LTCF) that described seroprevalence using the terms \"COVID-19\" or \"SARS-CoV-2\" and \"nursing home\" or \"care home\" or \"residential\" or \"long term care facility\" and \"antibody\" or \"serology\" without date or language restrictions. One meta-analysis was identified, published before the introduction of vaccination, that included 2 studies with a sample size of 291 which estimated seroprevalence as 59% in LTCF residents. There were 28 seroprevalence surveys of naturally-acquired SARS-CoV-2 antibodies in LTCFs; 16 were conducted in response to outbreaks and 12 conducted in care homes without known outbreaks. 16 studies included more than 1 LTCF and all were conducted in Autumn 2020 after the first wave of infection but prior to subsequent peaks. Seroprevalence studies conducted following a LTCF outbreak were biased towards positivity as the included population was known to have been previously infected. In the 12 studies that were conducted outside of known outbreaks, seroprevalence varied significantly according to local prevalence of infection. The largest of these was a cross-sectional study conducted in 9,000 residents and 10,000 staff from 362 LTCFs in Madrid, which estimated seroprevalence in staff as 31{middle dot}5% and 55{middle dot}4% in residents. However, as this study was performed in one city, it may not be generalisable to the whole of Spain and sequential sampling was not performed. Of the 28 studies, 9 undertook longitudinal sampling for a maximum of four months although three of these reported from the same cohort of LTCFs in London. None of the studies reported on antibody waning amongst the whole resident population.\n\nAdded value of this studyWe estimated the proportion of care home staff and residents with evidence of SARS-CoV-2 natural infection using data from over 3,000 staff and 1,500 residents in 201 geographically dispersed LTCFs in England. Population selection was independent of outbreak history and the sample is therefore more reflective of the population who reside and work in LTCFs. Our estimates of the proportion of residents with prior natural infection are substantially higher than estimates based on population-wide PCR testing, due to limited testing coverage at the start of the pandemic. 1361 individuals had at least one positive antibody test and participants were followed for up to 11 months, which allowed modelling of the time to loss of antibody in over 600 individuals in whom the date of primary infection could be reliably estimated. This is the longest reported serological follow up in a population of LTCF residents, a group who are known to be most at risk of severe outcomes following infection with SARS-CoV-2 and provides important evidence on the duration that nucleocapsid antibodies remained detectable over the first and second waves of the pandemic.\n\nImplications of all available researchA substantial proportion of the LTCF population will have some level of natural immunity to infection as a result of past infection. Immunological studies have highlighted greater antibody responses to vaccination in seropositive individuals, so vaccine efficacy in this population may be affected by this large pool of individuals who have survived past infection. In addition, although the presence of nucleocapsid-specific antibodies is generally considered as the standard marker for prior infection, we find that antibody waning is such that up to 50% of people will lose detectable antibody responses within eight months. Individual prior natural infection history is critical to assess the impact of factors such as vaccine response or protection against re-infection. These findings may have implications for duration of immunity following natural infection and indicate that alternative assays for prior infection should be developed.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.27.21264005", + "rel_abs": "BackgroundGlobally, healthcare workers (HCWs) are prioritised for receiving vaccinations against the coronavirus disease-2019 (COVID-19). Previous research has shown disparities in COVID-19 vaccination uptake among HCWs based on ethnicity, job role, sex, age, and deprivation. However, vaccine attitudes underpinning these variations are yet to be fully explored.\n\nMethodsWe conducted a qualitative study with 164 HCWs from different ethnicities, sexes, job roles, migration statuses, and regions in the United Kingdom (UK). Interviews and focus groups were conducted using Microsoft Teams or telephone, and recorded with participants permission. Recordings were transcribed and thematically analysed following an inductive approach.\n\nFindingsWe conducted an in-depth analysis of 53 randomly selected transcripts (involving 82 participants) to generate rapid evidence. Four different vaccine attitudes were identified: Active Acceptance, Passive Acceptance, Passive Decline, and Active Decline. Factors influencing vaccine acceptance include: knowledge of vaccine; risk perception; positive attitude towards other vaccines; social influences; and considerations about the future. Correspondingly, barriers to vaccine acceptance were identified as, low trust in the vaccine and historical (mis)trust, inadequate communication, and inequities in delivery and access. Opinion on mandatory vaccination was divided.\n\nInterpretationOur data show that vaccine attitudes are diverse and elements of hesitancy may remain even after vaccine acceptance. This has implications for the sustainability of the vaccine programme, particularly as new components (e.g. boosters) are being added. Based on our findings we recommend trust-building, designing inclusive and accessible information, and addressing structural inequities for improving vaccine uptake among HCWs.\n\nFundingUKRI-MRC and NIHR.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Maria Krutikov", - "author_inst": "University College London" - }, - { - "author_name": "Tom Palmer", - "author_inst": "University College London" - }, - { - "author_name": "Gokhan Tut", - "author_inst": "University of Birmingham, Medical School" - }, - { - "author_name": "Christopher Fuller", - "author_inst": "University College London" - }, - { - "author_name": "Borscha Azmi", - "author_inst": "University College London" - }, - { - "author_name": "Rebecca Giddings", - "author_inst": "University College London" - }, - { - "author_name": "Madhumita Shrotri", - "author_inst": "University College London" - }, - { - "author_name": "Nayandeep Kaur", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Panagiota Sylla", - "author_inst": "University of Birmingham" + "author_name": "Mayuri Gogoi", + "author_inst": "Department of Respiratory Sciences, University of Leicester" }, { - "author_name": "Tara Lancaster", - "author_inst": "University of Birmingham" + "author_name": "Fatimah Wobi", + "author_inst": "Department of Respiratory Sciences, University of Leicester" }, { - "author_name": "Aidan Irwin-Singer", - "author_inst": "Department of Health & Social Care" + "author_name": "Irtiza Qureshi", + "author_inst": "Division of Epidemiology and Public Health, School of Medicine, University of Nottingham, Nottingham, UK" }, { - "author_name": "Andrew Hayward", - "author_inst": "UCL" + "author_name": "Amani Al-Oraibi", + "author_inst": "Division of Epidemiology and Public Health, School of Medicine, University of Nottingham, Nottingham, UK" }, { - "author_name": "Paul Moss", - "author_inst": "University of Birmingham" + "author_name": "Osama Hassan", + "author_inst": "Division of Epidemiology and Public Health, School of Medicine, University of Nottingham, Nottingham, UK" }, { - "author_name": "Andrew Copas", - "author_inst": "University College London" + "author_name": "Laura B Nellums", + "author_inst": "Division of Epidemiology and Public Health, School of Medicine, University of Nottingham, Nottingham, UK" }, { - "author_name": "Laura Shallcross", - "author_inst": "UCL" + "author_name": "Manish Pareek", + "author_inst": "Department of Respiratory Sciences, University of Leicester, UK; Department of Infection and HIV Medicine, University Hospitals of Leicester NHS Trust, , Leices" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.09.27.21264044", @@ -546390,47 +544767,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.26.21264135", - "rel_title": "Descriptive characteristics of continuous oximetry measurement in moderate to severe COVID-19 patients", + "rel_doi": "10.1101/2021.09.25.21264115", + "rel_title": "pIVW: A novel Mendelian Randomization Method Accounting for Weak Instruments and Horizontal Pleiotropy with Applications to the COVID-19 Outcomes", "rel_date": "2021-09-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.26.21264135", - "rel_abs": "Non-invasive oxygen saturation (SpO2) is a central vital sign that supports the management of COVID-19 patients. However, reports on SpO2 characteristics are scarce and none has analysed high resolution continuous SpO2 in COVID-19. We provide the first analysis of high resolution SpO2 across the spectrum of COVID-19 disease severity and respiratory support. A total of 367 COVID-19 patients recordings, comprising 27K hours of continuous SpO2 data, could be retrieved from patients hospitalized at the Rambam Health Care Campus. Using oximetry digital biomarkers (OBM), we quantified SpO2 characteristics and showed that the percentage of time under 93% oxygen saturation threshold is the best single OBM discriminating between critical and non-critical patients. OBMs traditionally used in the field of sleep medicine research, were informative for assessing the patients response to respiratory support. In addition, periodicity and hypoxic burden biomarkers were affected up to several hours before the initiation of the mechanical ventilation. Characteristics from high resolution SpO2 signal may enable to anticipate clinically relevant events, monitoring of treatment response and may be indicative of future deterioration.x", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.25.21264115", + "rel_abs": "SO_SCPLOWUMMARYC_SCPLOWMendelian randomization (MR) utilizes genetic variants as instrumental variables (IVs) to estimate the causal effect of an exposure variable on an outcome of interest even in the presence of unmeasured confounders. However, the popular inverse-variance weighted (IVW) estimator could be biased in the presence of weak IVs, a common challenge in MR studies. In this article, we develop a novel penalized inverse-variance weighted (pIVW) estimator, which adjusts the original IVW estimator to account for the weak IV issue by using a penalization approach to prevent the denominator of the pIVW estimator from being close to zero. Moreover, we adjust the variance estimation of the pIVW estimator to account for the presence of balanced horizontal pleiotropy. We show that the recently proposed debiased IVW (dIVW) estimator is a special case of our proposed pIVW estimator. We further prove that the pIVW estimator has smaller bias and variance than the dIVW estimator under some regularity conditions. We also conduct extensive simulation studies to demonstrate the performance of the proposed pIVW estimator. Furthermore, we apply the pIVW estimator to estimate the causal effects of five obesity-related exposures on three coronavirus disease 2019 (COVID-19) outcomes. Notably, we find that hypertensive disease is associated with an increased risk of hospitalized COVID-19; and peripheral vascular disease and higher body mass index are associated with increased risks of COVID-19 infection, hospitalized COVID-19 and critically ill COVID-19.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Jonathan Aryeh Sobel", - "author_inst": "Faculty of Biomedical Engineering, Technion, Israel Institute of Technology, Haifa, Israel" - }, - { - "author_name": "Jeremy Levy", - "author_inst": "Faculty of Biomedical Engineering, Technion, Israel Institute of Technology, Haifa, Israel" - }, - { - "author_name": "Ronit Almog", - "author_inst": "Rambam Health Care Campus, Haifa, Israel" - }, - { - "author_name": "Anat Reiner Benaim", - "author_inst": "School of Public Health, Faculty of Health Sciences, Ben Gurion University of the Negev, Be'er Sheva, Israel" + "author_name": "Siqi Xu", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Asaf Miller", - "author_inst": "Rambam Health Care Campus, Haifa, Israel" + "author_name": "Peng Wang", + "author_inst": "Huazhong University of Science and Technology" }, { - "author_name": "Danny Eytan", - "author_inst": "Rambam Health Care Campus, Haifa, Israel" + "author_name": "Wing Kam Fung", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Joachim A Behar", - "author_inst": "Faculty of Biomedical Engineering, Technion, Israel Institute of Technology, Haifa, Israel" + "author_name": "Zhonghua Liu", + "author_inst": "The University of Hong Kong" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.09.25.21264082", @@ -548540,37 +546905,25 @@ "category": "rheumatology" }, { - "rel_doi": "10.1101/2021.09.23.21264048", - "rel_title": "Effectiveness of COVID-19 vaccines against SARS-CoV-2 variants of concern: a systematic review and meta-analysis", + "rel_doi": "10.1101/2021.09.23.21264017", + "rel_title": "Assessing the impact of temperature and humidity exposures during early infection stages on case-fatality of COVID-19: a modelling study in Europe", "rel_date": "2021-09-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.23.21264048", - "rel_abs": "BackgroundIt was urgent and necessary to synthesize the evidence for vaccine effectiveness (VE) against SARS-CoV-2 variants of concern (VOC). We conducted a systematic review and meta-analysis to provide a comprehensive overview of the effectiveness profile of COVID-19 vaccines against VOC.\n\nMethodsPublished and preprinted randomized controlled trials (RCTs), cohort studies, and case-control studies that evaluated the VE against VOC (Alpha, Beta, Gamma, or Delta) were searched until 31 August 2021. Pooled estimates and 95% confidence intervals (CIs) were calculated using random-effects meta-analysis. VE was defined as (1- estimate).\n\nResultsSeven RCTs (51,169 participants), 10 cohort studies (14,385,909 participants) and 16 case-control studies (734,607 cases) were included. Eight COVID-19 vaccines (mRNA-1273, BNT162b2, ChAdOx1, Ad26.COV2.S, NVX-CoV2373, BBV152, CoronaVac, and BBIBP-CorV) were included in this analysis. Full vaccination was effective against Alpha, Beta/Gamma, and Delta variants, with VE of 88.3% (95% CI, 82.4-92.2), 70.7% (95% CI, 59.9-78.5), and 71.6% (95% CI, 64.1-77.4), respectively. But partial vaccination was less effective, with VE of 59.0% (95% CI, 51.3-65.5), 49.3% (95% CI, 33.0-61.6), and 52.6% (95% CI, 43.3-60.4), respectively. mRNA vaccines seemed to have higher VE against VOC over others, significant interactions (pinteraction < 0.10) were observed between VE and vaccine type (mRNA vaccines vs. non-mRNA vaccines).\n\nConclusionsFull vaccination of COVID-19 vaccines is highly effective against Alpha variant, and moderate effective against Beta/Gamma and Delta variants. Partial vaccination has less VE against VOC. mRNA vaccines seem to have higher VE against Alpha, Beta/Gamma, and Delta variants over others.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.23.21264017", + "rel_abs": "BackgroundAlthough associations between key weather indicators (i.e. temperature and humidity) and COVID-19 mortality has been reported, the relationship between these exposures among different timing in early infection stages (from virus exposure up to a few days after symptom onset) and the probability of death after infection (also called case fatality rate, CFR) has yet to be determined.\n\nMethodsWe estimated the instantaneous CFR of eight European countries using Bayesian inference in conjunction with stochastic transmission models, taking account of delays in reporting the number of newly confirmed cases and deaths. The exposure-lag-response associations between fatality rate and weather conditions to which patients were exposed at different timing were obtained using distributed lag nonlinear models coupled with mixed-effect models.\n\nResultsOur results showed that the Odds Ratio (OR) of death is negatively associated with the temperature, with two maxima (OR=1.29 (95% CI: 1.23, 1.35) at -0.1{degrees}C; OR=1.12 (95% CI: 1.08, 1.16) at 0.1{degrees}C) occurred at the time of virus exposure and after symptom onset. Two minima (OR=0.81 (95% CI: 0.71, 0.92) at 23.2{degrees}C; OR=0.71 (95% CI: 0.63, 0.80) at 21.7{degrees}C) also occurred at these two distinct periods correspondingly. Low humidity (below 50%) during the early stages and high humidity (approximately 89%) after symptom onset were related to the lower fatality.\n\nConclusionEnvironmental conditions may affect not only the initial viral load when exposure to viruses but also individuals immunity response around symptom onset. Warmer temperatures and higher humidity after symptom onset were related to the lower fatality.\n\nHighlightsO_LITemperature and humidity conditions that patients were exposed to during their early infection stages were associated with COVID-19 case fatality rate.\nC_LIO_LIWarmer temperatures (> 20{degrees}C) at infection time or after symptom onset, but not during the incubation period, were associated with lower death risk. Low relative humidity (< 50%) during the early stages and high relative humidity (> 85%) after symptom onset were related to higher death risk.\nC_LIO_LICreating optimal indoor conditions for cases who are under quarantine/isolation may reduce their risk of death.\nC_LI", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Baoqi Zeng", - "author_inst": "Department of Science and Education, Peking University Binhai Hospital, Tianjin, China" - }, - { - "author_name": "Le Gao", - "author_inst": "Department of Pharmacology and Pharmacy, The University of Hong Kong, Hong Kong, China" - }, - { - "author_name": "Qingxin Zhou", - "author_inst": "Tianjin Centers for Disease Control and Prevention, Tianjin, China" - }, - { - "author_name": "Kai Yu", - "author_inst": "Department of Science and Education, Peking University Binhai Hospital, Tianjin, China" + "author_name": "Jingbo Liang", + "author_inst": "Department of Biomedical Sciences, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong" }, { - "author_name": "Feng Sun", - "author_inst": "Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China" + "author_name": "Hsiang-Yu Yuan", + "author_inst": "Department of Biomedical Sciences, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -550218,71 +548571,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.23.21258047", - "rel_title": "Tracking the temporal variation of COVID-19 surges through wastewater-based epidemiology during the peak of the pandemic: a six-month long study in Charlotte, North Carolina", + "rel_doi": "10.1101/2021.09.23.461536", + "rel_title": "High-throughput super-resolution analysis of influenza virus pleomorphism reveals insights into viral spatial organization", "rel_date": "2021-09-24", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.23.21258047", - "rel_abs": "The global spread of SARS-CoV-2 has continued to be a serious concern after WHO declared the virus the causative agent of the coronavirus disease 2019 (COVID-19) a global pandemic. Monitoring of wastewater is a useful tool for assessing community prevalence given that fecal shedding of SARS-CoV-2 occurs in high concentrations by infected individuals, regardless of whether they are asymptomatic or symptomatic. Using tools that are part of the wastewater-based epidemiology (WBE) approach, combined with molecular analyses, wastewater monitoring becomes a key piece of information used to assess trends and quantify the scale and dynamics of COVID-19 infection in a specific community, municipality, or area of service. This study investigates a six-month long SARS-CoV-2 RNA quantification in influent wastewater from four municipal wastewater treatment plants (WWTP) serving the Charlotte region of North Carolina (NC) using both RT-qPCR and RT-ddPCR platforms. Influent wastewater was analyzed for the nucleocapsid (N) genes N1 and N2. Both RT-qPCR and RT-ddPCR performed well for detection and quantification of SARS-CoV-2 using the N1 target, while for the N2 target RT-ddPCR was more sensitive. SARS-CoV-2 concentration ranged from 103 to105 copies/L for all four plants. Both RT-qPCR and RT-ddPCR showed a significant moderate to a strong positive correlation between SARS-CoV-2 concentrations and the 7-day rolling average of clinically reported COVID-19 cases using a lag that ranged from 7 to 12 days. A major finding of this study is that despite small differences, both RT-qPCR and RT-ddPCR performed well for tracking the SARS-CoV-2 virus across WWTP of a range of sizes and metropolitan service functions.", - "rel_num_authors": 13, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.23.461536", + "rel_abs": "Many viruses form highly pleomorphic particles; in influenza, these particles range from spheres of ~ 100 nm in diameter to filaments of several microns in length. Virion structure is of interest, not only in the context of virus assembly, but also because pleomorphic variations may correlate with infectivity and pathogenicity. We have used fluorescence super-resolution microscopy combined with a rapid automated analysis pipeline to image many thousands of individual influenza virions, gaining information on their size, morphology and the distribution of membrane-embedded and internal proteins. We observed broad phenotypic variability in filament size, and Fourier transform analysis of super resolution images demonstrated no generalized common spatial frequency patterning of HA or NA on the virion surface, suggesting a model of virus particle assembly where the release of progeny filaments from cells occurs in a stochastic way. Finally, we showed that in long filaments, viral RNP complexes are located preferentially within Archetti bodies, suggesting that these structures may play a role in virus transmission. Our approach therefore offers exciting new insights into influenza virus morphology and represents a powerful technique that is easily extendable to the study of pleomorphism in other pathogenic viruses.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Visva Bharati Barua", - "author_inst": "UNC Charlotte" - }, - { - "author_name": "Md Ariful Islam Juel", - "author_inst": "UNC Charlotte" - }, - { - "author_name": "A. Denene Blackwood", - "author_inst": "UNC-IMS" - }, - { - "author_name": "Thomas Clerkin", - "author_inst": "UNC-IMS" - }, - { - "author_name": "Mark Ciesielski", - "author_inst": "UNC-IMS" - }, - { - "author_name": "Adeola Julian Sorinolu", - "author_inst": "UNC Charlotte" - }, - { - "author_name": "David A. Holcomb", - "author_inst": "UNC Chapel Hill" - }, - { - "author_name": "Isaiah Young", - "author_inst": "UNC Charlotte" + "author_name": "Andrew McMahon", + "author_inst": "University of Oxford" }, { - "author_name": "Gina Kimble", - "author_inst": "Charlotte Water" + "author_name": "Rebecca Andrews", + "author_inst": "University of Warwick" }, { - "author_name": "Shannon Sypolt", - "author_inst": "Charlotte Water" + "author_name": "Sohail V Ghani", + "author_inst": "University of Warwick" }, { - "author_name": "Lawrence S. Engel", - "author_inst": "UNC Chapel Hill" + "author_name": "Thorben Cordes", + "author_inst": "Ludwig Maximilians University Munich" }, { - "author_name": "Rachel T. Noble", - "author_inst": "UNC-IMS" + "author_name": "Achillefs N Kapanidis", + "author_inst": "University of Oxford" }, { - "author_name": "Mariya Munir", - "author_inst": "University Of North Carolina Charlotte" + "author_name": "Nicole C Robb", + "author_inst": "University of Warwick" } ], "version": "1", - "license": "cc_by_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_no", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2021.09.23.461605", @@ -551912,103 +550237,47 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.09.17.21263624", - "rel_title": "Covid-19 in the Phase 3 Trial of mRNA-1273 During the Delta-variant Surge", + "rel_doi": "10.1101/2021.09.19.21263788", + "rel_title": "Cardiovascular Risk Factors and Outcomes in COVID-19: Hospital-Based Prospective Study in India", "rel_date": "2021-09-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.17.21263624", - "rel_abs": "BackgroundFollowing emergency use authorization in December 2020, the Coronavirus Efficacy (COVE) trial was amended to an open-label phase, where participants were unblinded and those randomized to placebo were offered vaccination. Emergence of the delta variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been associated with increased incidences of coronavirus disease 2019 (Covid-19) among unvaccinated and vaccinated persons. This exploratory analysis evaluated the incidence and genetic sequences of Covid-19 cases in the ongoing COVE trial during the open-label phase, with a focus on July-August 2021, when delta-variants surged in the US.\n\nMethodsCovid-19 cases were identified in participants initially randomized to mRNA-1273 (vaccinated from July-December 2020) and those initially randomized to the placebo (vaccinated December 2020-April 2021) who received at least one dose and were SARS-CoV-2-negative at baseline in the modified-intent-to-treat population were analyzed. Included were Covid-19 cases occurring after 26-Mar-2021 with positive RT-PCR results in nasopharyngeal samples (central lab test) and reported Covid-19 symptoms. Genetic sequencing of Covid-19 cases was also performed.\n\nResultsThere were 14,746 participants in the earlier mRNA-1273 (mRNA-1273e) group and 11,431 in the later placebo-mRNA1273 (mRNA-1273p) group. Covid-19 cases increased from the start of the open-label phase to July-August 2021. During July and August, 162 Covid-19 cases occurred in the mRNA-1273e group and 88 in the mRNA-1273p group. Of the cases sequenced, 144/149 [97%]) in the mRNA-1273 and 86/88 (99%) in the mRNA-1273p groups were attributed to delta. The incidence rate of Covid-19 was lower for the mRNA-1273p (49.0/1000 person-years) versus mRNA-1273e (77.1/1000 person-years) group [36.4% (95% CI 17.1%-51.5%) reduction]. There were fewer severe Covid-19 cases in the mRNA-1273p (6; 6.2/1000 person-years) than mRNA-1273e (13; 3.3/1000 person-years) [46.0% (95% CI -52.4%-83.2%) reduction]. Three Covid-19 related hospitalizations occurred with two resulting deaths in the mRNA-1273e group.\n\nConclusionIncidence rates of Covid-19 and severe Covid-19 were lower during the months when delta was the dominant variant (July/August 2021) among COVE participants vaccinated more recently. Analysis of COVID-19 cases from the open-label phase of the COVE study is ongoing.", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.19.21263788", + "rel_abs": "Background & ObjectivesPresence of cardiovascular (CV) risk factors enhance adverse outcomes in COVID-19. To determine association of risk factors with clinical outcomes in India we performed a study.\n\nMethodsSuccessive virologically confirmed patients of COVID-19 at a government hospital were recruited at admission and in-hospital outcome and other details obtained. The cohort was classified according to age, sex, hypertension, diabetes and tobacco use. To compare intergroup outcomes we performed univariate and multivariate logistic regression.\n\nResultsFrom March-September 2020 we recruited 4645 (men 3386, women 1259) out of 5103 COVID-19 patients (91.0%). Mean age was 46{+/-}18y, hypertension was in 17.8%, diabetes in 16.6% and tobacco-use in 29.5%. Duration of hospital stay was 6.8{+/-}3.7 days, supplemental oxygen was in 18.4%, non-invasive ventilation in 7.1%, mechanical ventilation in 3.6% and 7.3% died. Unadjusted and age-sex adjusted odds ratio and 95% confidence intervals, respectively were, age [≥]50y (4.16, 3.22-5.37 and 4.15,3.21-5.35), men (1.88,1.41-2.51 and 1.26,0.91-1.48); hypertension (2.22,1.74-2.83 and 1.32,1.02-1.70), diabetes (1.88,1.46-2.43 and 1.16,0.89-1.52) and tobacco (1.29,1.02-1.63 and 1.28,1.00-1.63). Need for invasive ventilation was greater in age >50y (3.06,2.18-4.28 and 3.06,2.18-4.29) and diabetes (1.64,1.14-2.35 and 1.12,0.77-1.62). Non-invasive ventilation was more in age [≥]50y (2.27,1.80-2.86 and 2.26,1.79-2.85) and hypertension (1.82,1.41-2.35 and 1.29,0.99-1.69). Multivariate adjustment for presenting factors attenuated the significance.\n\nConclusionCardiovascular risk factors-age, male sex, hypertension, diabetes and tobacco-are associated with greater risk of death and adverse outcomes in COVID-19 patients in India.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Lindsey R Baden", - "author_inst": "Brigham and Womens Hospital" - }, - { - "author_name": "Hana M ElSahly", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Brandon Essink", - "author_inst": "Meridian Clinical Research" - }, - { - "author_name": "Dean Follman", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Kathleen M Neuzil", - "author_inst": "University of Maryland" - }, - { - "author_name": "Allison August", - "author_inst": "Moderna Inc." - }, - { - "author_name": "Heather Clouting", - "author_inst": "Moderna, Inc." - }, - { - "author_name": "Gabrielle Fortier", - "author_inst": "Moderna, Inc." - }, - { - "author_name": "Weiping Deng", - "author_inst": "Moderna Inc." - }, - { - "author_name": "Shu Han", - "author_inst": "Moderna Inc." - }, - { - "author_name": "Xiaoping Zhao", - "author_inst": "Moderna Inc." - }, - { - "author_name": "Brett Leav", - "author_inst": "Moderna Inc." - }, - { - "author_name": "Carla Talarico", - "author_inst": "Moderna Inc." - }, - { - "author_name": "Bethany Girard", - "author_inst": "Moderna Inc." - }, - { - "author_name": "Yamuna Paila", - "author_inst": "Moderna Inc." + "author_name": "Arvind K Sharma", + "author_inst": "RUHS College of Medical Sciences, Jaipur, India" }, { - "author_name": "Joanne E Tomassini", - "author_inst": "Moderna Inc." + "author_name": "Vaseem Naheed Baig", + "author_inst": "RUHS College of Medical Sciences, Jaipur, India" }, { - "author_name": "Florian Schodel", - "author_inst": "Moderna Inc." + "author_name": "Sonali Sharma", + "author_inst": "RUHS College of Medical Sciences, Jaipur, India" }, { - "author_name": "Rolando Pajon", - "author_inst": "Moderna Inc." + "author_name": "Gaurav Dalela", + "author_inst": "RUHS College of Medical sciences, Jaipur, India" }, { - "author_name": "Honghong Zhou", - "author_inst": "Moderna Inc." + "author_name": "Raja Babu Panwar", + "author_inst": "Rajasthan University of Health Sciences, Jaipur, India" }, { - "author_name": "Rituparna Das", - "author_inst": "Moderna Inc." + "author_name": "Vishwa Mohan Katoch", + "author_inst": "ICMR-NASI Chair, Rajasthan University of Health Sciences, Jaipur, India" }, { - "author_name": "Jacqueline Miller", - "author_inst": "Moderna Inc." + "author_name": "Rajeev Gupta", + "author_inst": "Eternal Heart Care Centre & Research Institute, Jaipur, India" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2021.09.18.21263773", @@ -553858,103 +552127,59 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.09.16.21263684", - "rel_title": "The removal of airborne SARS-CoV-2 and other microbial bioaerosols by air filtration on COVID-19 surge units", + "rel_doi": "10.1101/2021.09.20.21263837", + "rel_title": "Social relationships and activities following elimination of SARS-CoV-2: a qualitative cross-sectional study", "rel_date": "2021-09-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.16.21263684", - "rel_abs": "BackgroundThe COVID-19 pandemic has overwhelmed the respiratory isolation capacity in hospitals; many wards lacking high-frequency air changes have been repurposed for managing patients infected with SARS-CoV-2 requiring either standard or intensive care. Hospital-acquired COVID-19 is a recognised problem amongst both patients and staff, with growing evidence for the relevance of airborne transmission. This study examined the effect of air filtration and ultra-violet (UV) light sterilisation on detectable airborne SARS-CoV-2 and other microbial bioaerosols.\n\nMethodsWe conducted a crossover study of portable air filtration and sterilisation devices in a repurposed surge COVID ward and surge ICU. National Institute for Occupational Safety and Health (NIOSH) cyclonic aerosol samplers and PCR assays were used to detect the presence of airborne SARS-CoV-2 and other microbial bioaerosol with and without air/UV filtration.\n\nResultsAirborne SARS-CoV-2 was detected in the ward on all five days before activation of air/UV filtration, but on none of the five days when the air/UV filter was operational; SARS-CoV-2 was again detected on four out of five days when the filter was off. Airborne SARS-CoV-2 was infrequently detected in the ICU. Filtration significantly reduced the burden of other microbial bioaerosols in both the ward (48 pathogens detected before filtration, two after, p=0.05) and the ICU (45 pathogens detected before filtration, five after p=0.05).\n\nConclusionsThese data demonstrate the feasibility of removing SARS-CoV-2 from the air of repurposed surge wards and suggest that air filtration devices may help reduce the risk of hospital-acquired SARS-CoV-2.\n\nFundingWellcome Trust, MRC, NIHR", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.20.21263837", + "rel_abs": "ObjectivesTo investigate how successfully SARS-CoV-2 elimination strategies fulfil their promise of allowing a return to a normal social life, and to identify obstacles and challenges that may inhibit the realisation of this goal.\n\nDesignQualitative cross-sectional survey.\n\nSettingNew Zealand community cohort.\n\nParticipants1040 respondents entered the study (18-90 years, M = 48.18.11, SD = 15.52, 76% women). 966 completed the questions relevant to this article. Participants were recruited via online advertisement campaigns designed to maximise variation in the sample as far as practicably possible.\n\nMain outcome measuresThematic analysis of participants narratives.\n\nResultsA majority of participants reported that the elimination of SARS-CoV-2 had allowed their life to go back to being more or less the same as before the pandemic. A small number indicated the pandemic had inspired them to become more social following elimination. Nevertheless, a sizeable minority of respondents reported being less social, even many months after SARS-CoV-2 had been eliminated. This was often because of fears that the virus might be circulating undetected, or because the March-May 2020 lockdown had led to changes in relationships and personal habits that were not easily reversed. Becoming less social was associated with having an underlying health condition that heightened ones vulnerability to COVID-19 (p = 0.00005) and older age (p = 0.007).\n\nConclusionsElimination strategies can successfully allow the public to return to a pre-pandemic normal - or reinvent and improve their social lives should they wish. However, such outcomes are not inevitable. Re-establishing social connections after elimination can sometimes be a challenging process, with which people may need support. Plans for providing such support should be an integral part of elimination strategies.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Andrew Conway Morris", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Katherine Sharrocks", - "author_inst": "Cambridge University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Rachel Bousfield", - "author_inst": "Cambridge University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Leanne Kermack", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Mailis Maes", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Ellen Higginson", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Sally Forrest", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Joannna Pereira-Dias", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Claire Cormie", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Timothy Old", - "author_inst": "Cambridge University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Sophie Brooks", - "author_inst": "Cambridge University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Islam Hamed", - "author_inst": "Cambridge University Hospitals NHS Foundation Trust" + "author_name": "Nicholas J Long", + "author_inst": "London School of Economics and Political Science" }, { - "author_name": "Alicia Koenig", - "author_inst": "Cambridge University Hospitals NHS Foundation Trust" + "author_name": "Nayantara Sheoran Appleton", + "author_inst": "Victoria University of Wellington" }, { - "author_name": "Andrew Turner", - "author_inst": "Cambridge University Hospitals NHS Foundation Trust" + "author_name": "Sharyn Graham Davies", + "author_inst": "Monash University & Auckland University of Technology" }, { - "author_name": "Paul White", - "author_inst": "Cambridge University Hospitals NHS Foundation Trust" + "author_name": "Antje Deckert", + "author_inst": "Auckland University of Technology" }, { - "author_name": "R. Andres Floto", - "author_inst": "University of Cambridge" + "author_name": "Edmond Fehoko", + "author_inst": "University of Auckland" }, { - "author_name": "Gordon Dougan", - "author_inst": "University of Cambridge" + "author_name": "Eleanor Holroyd", + "author_inst": "Auckland University of Technology" }, { - "author_name": "Effrossyni Gkrania-Klotsas", - "author_inst": "Cambridge University Hospitals NHS Foundation trust" + "author_name": "Nelly Martin-Anatias", + "author_inst": "Auckland University of Technology" }, { - "author_name": "Theodore Gouliouris", - "author_inst": "Cambridge University Hospitals NHS Foundation Trust" + "author_name": "Rogena Sterling", + "author_inst": "University of Waikato" }, { - "author_name": "Stephen Baker", - "author_inst": "University of Cambridge" + "author_name": "Susanna Trnka", + "author_inst": "University of Auckland" }, { - "author_name": "Vilas Navapurkar", - "author_inst": "Cambridge University Hospitals" + "author_name": "Laumua Tunufa'i", + "author_inst": "Auckland University of Technology" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "health policy" }, { "rel_doi": "10.1101/2021.09.16.21263576", @@ -555385,39 +553610,47 @@ "category": "pharmacology and therapeutics" }, { - "rel_doi": "10.1101/2021.09.17.21263619", - "rel_title": "COVID-19 vaccination rates among health care workers by immigrant background. A nation-wide registry study from Norway.", + "rel_doi": "10.1101/2021.09.17.21263726", + "rel_title": "Single-Dose SARS-CoV-2 Vaccination With BNT162b2 and AZD1222 Induce Disparate Th1 Responses and IgA Production", "rel_date": "2021-09-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.17.21263619", - "rel_abs": "BackgroundStudies have suggested that some minority groups tend to have lower vaccination rates than the overall population. This study aims to examine COVID-19 vaccination rates among health care workers (HCWs) in Norway, according to immigrant background.\n\nMethodsWe used individual-level, nation-wide registry data from Norway to identify all HCWs employed full-time at 1 December 2020. We examined the relationship between country of birth and COVID-19 vaccination from December 2020 to August 2021, both crude and adjusted for e.g. age, sex, municipality of residence, and detailed occupation codes in logistic regression models.\n\nResultsAmong all HCWs in Norway, immigrants had a 9 percentage point lower vaccination rate (85%) than HCWs without an immigrant background (94%) at 31 August 2021. The overall vaccination rate varied by country of birth, with immigrants born in Russia (71%), Serbia (72%), Lithuania (72%), Romania (75%), Poland (76%), Eritrea (77%), and Somalia (78%) having the lowest crude vaccination rates. When we adjusted for demographics and detailed occupational codes, immigrant groups that more often worked as health care assistants, such as immigrants from Eritrea and Somalia, increased their vaccination rates.\n\nConclusionSubstantial differences in vaccination rates among immigrant groups employed in the health care sector in Norway indicate that measures to improve vaccine uptake should focus specific immigrant groups rather than all immigrants together. Lower vaccination rates in some immigrant groups appears to be largely driven by the occupational composition, suggesting that some of the differences in vaccine rates can be attributed to variation in vaccine access.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.17.21263726", + "rel_abs": "While vaccination programs against SARS-CoV-2 are globally ongoing, disparate strategies for the deployment of spike antigen show varying effectiveness. In order to explore this phenomenon, we sought to compare the early immune responses against AZD1222 and BNT162b2. SARS-CoV-2 seronegative participants received a single dose of either vaccine and were analyzed for immune cell, effector T cell and antibody dynamics. AZD1222 induced transient leukopenia and major changes among innate and adaptive subpopulations. Both vaccines induced spike protein specific effector T cells which were dominated by Th1 responses following AZD1222 vaccination. A significant reduction of anti-inflammatory T cells upon re-stimulation was also restricted to AZD1222 vaccinees. While IgM and IgG were the dominant isotypes elicited by AZD1222, BNT162b2 led to a significant production of IgG and IgA. Our results suggest that the strategy for spike antigen delivery impacts on how and to what extent immune priming against the main SARS-CoV-2 antigen proceeds.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Kristian Bandlien Kraft", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Michael M\u00fcller", + "author_inst": "Core Facility for Cell Sorting and Cell Analysis, Rostock University Medical Center, Rostock, Germany" }, { - "author_name": "Ingeborg Hess Elgersma", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Johann Volzke", + "author_inst": "Core Facility for Cell Sorting and Cell Analysis, Rostock University Medical Center, Rostock, Germany" }, { - "author_name": "Trude Marie Lyngstad", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Behnam Subin", + "author_inst": "Department of Cardiology, Rostock University Medical Center, Germany" }, { - "author_name": "Petter Elstrom", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Silke M\u00fcller", + "author_inst": "Institute of Pharmacology and Toxicology, Rostock University Medical Center, Rostock, Germany" }, { - "author_name": "Kjetil Elias Telle", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Martina Sombetzki", + "author_inst": "Division of Tropical Medicine and Infectious Diseases, Center of Internal Medicine II, Rostock University Medical Center, Rostock, Germany" + }, + { + "author_name": "Emil Christian Reisinger", + "author_inst": "Division of Tropical Medicine and Infectious Diseases, Center of Internal Medicine II, Rostock University Medical Center, Rostock, Germany" + }, + { + "author_name": "Brigitte M\u00fcller-Hilke", + "author_inst": "University Medical Center" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.09.17.21263723", @@ -556979,49 +555212,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.15.21263633", - "rel_title": "Self-reported and physiological reactions to the third BNT162b2 mRNA COVID-19 (booster) vaccine dose", + "rel_doi": "10.1101/2021.09.07.21263229", + "rel_title": "Quantitative measurement of infectious virus in SARS-CoV-2 Alpha, Delta and Epsilon variants reveals higher infectivity (viral titer:RNA ratio) in clinical samples containing the Delta and Epsilon variants.", "rel_date": "2021-09-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.15.21263633", - "rel_abs": "BackgroundThe rapid rise in hospitalizations associated with the Delta-driven COVID-19 resurgence, and the imminent risk of hospital overcrowding, led the Israeli government to initialize a national third (booster) COVID-19 vaccination campaign in early August 2021, offering the BNT162b2 mRNA vaccine to individuals who received their second dose over five months ago. However, the safety of the third (booster) dose has not been fully established yet.\n\nObjectiveEvaluate the short-term, self-reported and physiological reactions to the third BNT162b2 mRNA COVID-19 (booster) vaccine dose.\n\nDesignA prospective observational study, in which participants are equipped with a smartwatch and fill in a daily questionnaire via a dedicated mobile application for a period of 21 days, starting seven days before the vaccination.\n\nSettingAn Israel-wide third (booster) vaccination campaign.\n\nParticipantsA group of 1,609 (18+ years of age) recipients of at least one dose of the BNT162b2 vaccine between December 20, 2020, and September 15, 2021, out of a larger cohort of 2,912 prospective study participants. 1,344 of the participants were recipients of the third vaccine dose.\n\nMeasurementsDaily self-reported questionnaires regarding local and systemic reactions, mood level, stress level, sport duration, and sleep quality. Heart rate, heart rate variability and blood oxygen saturation level were continuously measured by Garmin Vivosmart 4 smartwatches.\n\nResultsThe extent of systemic reactions reported following the third (booster) dose administration is similar to that reported following the second dose (p-value=0.305) and considerably greater than that reported following the first dose (p-value<0.001). Our analyses of self-reported well-being indicators as well as the objective heart rate and heart rate variability measures recorded by the smartwatches further support this finding. Focusing on the third dose, reactions were more apparent in younger participants (p-value<0.01), in women (p-value<0.001), and in participants with no underlying medical conditions (p-value<0.001). Nevertheless, reported reactions and changes in physiological measures returned to their baseline levels within three days from inoculation with the third dose.\n\nLimitationsParticipants may not adequately represent the vaccinated population in Israel and elsewhere.\n\nConclusionOur work further supports the safety of a third COVID-19 BNT162b2 mRNA (booster) vaccine dose from both a subjective and an objective perspective, particularly in individuals 65+ years of age and those with underlying medical conditions.\n\nPrimary funding sourceEuropean Research Council (ERC) project #949850", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.07.21263229", + "rel_abs": "BackgroundNovel SARS-CoV-2 Variants of Concern (VoC) pose a challenge to controlling the COVID-19 pandemic. Previous studies indicate that clinical samples collected from individuals infected with the Delta variant may contain higher levels of RNA than previous variants, but the relationship between viral RNA and infectious virus for individual variants is unknown.\n\nMethodsWe measured infectious viral titer (using a micro-focus forming assay) as well as total and subgenomic viral RNA levels (using RT-PCR) in a set of 165 clinical samples containing SARS-CoV-2 Alpha, Delta and Epsilon variants that were processed within two days of collection from the patient.\n\nResultsWe observed a high degree of variation in the relationship between viral titers and RNA levels. Despite the variability we observed for individual samples the overall infectivity differed among the three variants. Both Delta and Epsilon had significantly higher infectivity than Alpha, as measured by the number of infectious units per quantity of viral E gene RNA (6 and 4 times as much, p=0.0002 and 0.009 respectively) or subgenomic E RNA (11 and 7 times as much, p<0.0001 and 0.006 respectively).\n\nConclusionIn addition to higher viral RNA levels reported for the Delta variant, the infectivity (amount of replication competent virus per viral genome copy) may also be increased compared to Alpha. Measuring the relationship between live virus and viral RNA is an important step in assessing the infectivity of novel SARS-CoV-2 variants. An increase in the infectivity of the Delta variant may further explain increased spread and suggests a need for increased measures to prevent viral transmission.\n\nSIGNIFICANCE STATEMENTCurrent and future SARS-CoV-2 variants threaten our ability to control the COVID-19 pandemic. Variants with increased transmission, higher viral loads, or greater immune evasion are of particular concern. Viral loads are currently measured by the amount of viral RNA in a clinical sample rather than the amount of infectious virus. We measured both RNA and infectious virus levels directly in a set of 165 clinical specimens from Alpha, Epsilon or Delta variants. Our data shows that Delta is more infectious compared to Alpha, with [~] six times as much infectious virus for the same amount of RNA. This increase in infectivity suggests increased measures (vaccination, masking, distancing, ventilation) are needed to control Delta compared to Alpha.", "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Merav Mofaz", - "author_inst": "Tel Aviv University" + "author_name": "Hannah W Despres", + "author_inst": "University of Vermont" }, { - "author_name": "Matan Yechezkel", - "author_inst": "Tel Aviv university" + "author_name": "Margaret G Mills", + "author_inst": "University of Washington" }, { - "author_name": "Grace Guan", - "author_inst": "Stanford University" + "author_name": "David J Shirley", + "author_inst": "Faraday, Inc." }, { - "author_name": "Margaret L. Brandeau", - "author_inst": "Stanford University" + "author_name": "Madaline M Schmidt", + "author_inst": "University of Vermont" }, { - "author_name": "Tal Patalon", - "author_inst": "Kahn Sagol Maccabi (KSM) Research & Innovation Center, Maccabi Healthcare Services" + "author_name": "Meei-Li Huang", + "author_inst": "University of Washington" }, { - "author_name": "Sivan Gazit", - "author_inst": "Kahn Sagol Maccabi (KSM) Research & Innovation Center, Maccabi Healthcare Services" + "author_name": "Keith R. Jerome", + "author_inst": "University of Washington" }, { - "author_name": "Dan Yamin", - "author_inst": "Tel Aviv University" + "author_name": "Alex L. Greninger", + "author_inst": "University of Washington" }, { - "author_name": "Erez Shmueli", - "author_inst": "Tel-Aviv University" + "author_name": "Emily A Bruce", + "author_inst": "University of Vermont" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -559321,71 +557554,87 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.09.17.460782", - "rel_title": "The nuts and bolts of SARS-CoV-2 Spike Receptor Binding Domain heterologous expression", + "rel_doi": "10.1101/2021.09.16.460724", + "rel_title": "ZRC3308 monoclonal antibody cocktail shows protective efficacy in Syrian hamsters against SARS-CoV-2 infection", "rel_date": "2021-09-17", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.17.460782", - "rel_abs": "COVID-19 is a highly infectious disease caused by a newly emerged coronavirus (SARS-CoV-2) that has rapidly progressed into a pandemic. This unprecedent emergency has stressed the significance of developing effective therapeutics to fight current and future outbreaks. The receptor-binding domain (RBD) of the SARS-CoV-2 surface Spike protein is the main target for vaccines and represents a helpful \"tool\" to produce neutralizing antibodies or diagnostic kits. In this work, we provide a detailed characterization of the native RBD produced in three major model systems: Escherichia coli, insect and HEK-293 cells. Circular dichroism, gel filtration chromatography and thermal denaturation experiments indicated that recombinant SARS-CoV-2 RBD proteins are stable and correctly folded. In addition, their functionality and receptor-binding ability were further evaluated through ELISA, flow cytometry assays and bio-layer interferometry.", - "rel_num_authors": 13, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.16.460724", + "rel_abs": "We have developed a monoclonal antibody (mAb) cocktail (ZRC-3308) comprising of ZRC3308-A7 and ZRC3308-B10 in the ratio 1:1 for COVID-19 treatment. The mAbs were designed to have reduced immune effector functions and increased circulation half-life. mAbs showed good binding affinities to non-competing epitopes on RBD of SARS-CoV-2 spike protein and were found neutralizing SARS-CoV-2 variants B.1, B.1.1.7, B.1.351, B.1.617.2 and B.1.617.2 AY.1 in vitro. The mAb cocktail demonstrated effective prophylactic and therapeutic activity against SARS-CoV-2 infection in Syrian hamsters. The antibody cocktail appears to be a promising candidate for the prophylactic use and for therapy in early COVID-19 cases which have not progressed to severe disease.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Mariano Maffei", - "author_inst": "Evvivax biotech" + "author_name": "Pragya Yadav", + "author_inst": "ICMR_National Institute of Virology" }, { - "author_name": "Linda C Montemiglio", - "author_inst": "Institute of Molecular Biology and Pathology (IBPM), National Research Council, Rome, Italy" + "author_name": "Sanjeev Kumar Mendiratta", + "author_inst": "Zydus Research Centre, Cadila Healthcare Limited" }, { - "author_name": "Grazia Vitagliano", - "author_inst": "Takis biotech" + "author_name": "Sreelekshmy Mohandas", + "author_inst": "ICMR-National Institute of Virology, Pune" }, { - "author_name": "Luigi Fedele", - "author_inst": "Takis biotech" + "author_name": "Arun K Singh", + "author_inst": "Zydus Research Centre, Cadila Healthcare Limited" }, { - "author_name": "Shaila Sellathurai", - "author_inst": "Takis biotech" + "author_name": "Priya Abraham", + "author_inst": "ICMR-National Institute of Virology, Pune" }, { - "author_name": "Federica Bucci", - "author_inst": "Takis biotech" + "author_name": "Anita Shete", + "author_inst": "ICMR-National Institute of Virology, Pune" }, { - "author_name": "Mirco Compagnone", - "author_inst": "Neomatrix biotech" + "author_name": "Sanjay Bandhyopadhyay", + "author_inst": "Zydus Research Centre, Cadila Healthcare Limited" }, { - "author_name": "Valerio Chiarini", - "author_inst": "Takis biotech" + "author_name": "Sanjay Kumar", + "author_inst": "Command Hospital, Armed Forces Medical College, Pune" }, { - "author_name": "Cecile Exertier", - "author_inst": "Department of Biochemical Sciences A. Rossi Fanelli University of Rome, Sapienza, Rome, Italy" + "author_name": "Aashini Parikh", + "author_inst": "Zydus Research Centre, Cadila Healthcare Limited" }, { - "author_name": "Alessia Muzi", - "author_inst": "Takis biotech" + "author_name": "Pankaj Kalita", + "author_inst": "Zydus Research Centre, Cadila Healthcare Limited" }, { - "author_name": "Giuseppe Roscilli", - "author_inst": "Takis biotech & Evvivax biotech" + "author_name": "Vibhuti Sharma", + "author_inst": "Zydus Research Centre, Cadila Healthcare Limited" }, { - "author_name": "Beatrice Vallone", - "author_inst": "Department of Biochemical Sciences A. Rossi Fanelli University of Rome, Sapienza, Rome, Italy" + "author_name": "Hardik Pandya", + "author_inst": "Zydus Research Centre, Cadila Healthcare Limited" }, { - "author_name": "Emanuele Marra", - "author_inst": "Takis biotech & Evvivax biotech" + "author_name": "Chirag G Patel", + "author_inst": "Zydus Research Centre, Cadila Healthcare Limited" + }, + { + "author_name": "Mihir Patel", + "author_inst": "Zydus Research Centre, Cadila Healthcare Limited" + }, + { + "author_name": "Swagat Soni", + "author_inst": "Zydus Research Centre, Cadila Healthcare Limited" + }, + { + "author_name": "Suresh Giri", + "author_inst": "Zydus Research Centre, Cadila Healthcare Limited" + }, + { + "author_name": "Mukul Jain", + "author_inst": "Zydus Research Centre, Cadila Healthcare Limited" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "biochemistry" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.09.13.21263487", @@ -561343,115 +559592,75 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.09.10.21262527", - "rel_title": "Antibody kinetics to SARS-CoV-2 at 13.5 months, by disease severity", + "rel_doi": "10.1101/2021.09.10.21263333", + "rel_title": "Children and adults with mild COVID-19 symptoms develop memory T cell immunity to SARS-CoV-2", "rel_date": "2021-09-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.10.21262527", - "rel_abs": "BackgroundUnderstanding humoral responses and seroprevalence in SARS-CoV-2 infection is essential for guiding vaccination strategies in both infected and uninfected individuals.\n\nMethodsWe determine the kinetics of IgM against the nucleocapsid (N) and IgG against the spike (S) and N proteins of SARS-CoV-2 in a cohort of 860 health professionals (healthy and infected) in northern Barcelona. We model the kinetics of IgG and IgM at nine time points over 13.5 months from infection, using non-linear mixed models by sex and clinical disease severity.\n\nResultsOf the 781 participants who were followed up, 478 (61.2%) became infected with SARS-CoV-2. Significant differences were found for the three antibodies by disease severity and sex. At day 270 after diagnosis, median IgM(N) levels were already below the positivity threshold in patients with asymptomatic and mild-moderate disease, while IgG(N, S) levels remained positive to days 360 and 270, respectively. Kinetic modelling showed a general rise in both IgM(N) and IgG(N) levels up to day 30, followed by a decay whose rate depended on disease severity. IgG(S) levels increased at day 15 and remained relatively constant over time.\n\nConclusionsWe describe kinetic models of IgM(N) and IgG(N, S) SARS-CoV-2 antibodies at 13.5 months from infection and disease spectrum. Our analyses delineate differences in the kinetics of IgM and IgG over a year and differences in the levels of IgM and IgG as early as 15 days from symptoms onset in severe cases. These results can inform public health policies around vaccination criteria.\n\nFunded by the regional Ministry of Health of the Generalitat de Catalunya (Call COVID19-PoC SLT16_04; NCT04885478)", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.10.21263333", + "rel_abs": "BackgroundSevere acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has led to considerable morbidity/mortality worldwide, but most infections, especially among children, have a mild course. However, it remains largely unknown whether infected children develop cellular immune memory.\n\nMethodsTo determine whether a memory T cell response is being developed as an indicator for long-term immune protection, we performed a longitudinal assessment of the SARS-CoV-2-specific T cell response by IFN-{gamma} ELISPOT and activation marker expression analyses of peripheral blood samples from children and adults with mild-to-moderate COVID-19.\n\nResultsUpon stimulation of PBMCs with heat-inactivated SARS-CoV-2 or overlapping peptides of spike (S-SARS-CoV-2) and nucleocapsid proteins, we found S-SARS-CoV-2-specific IFN-{gamma} T cell responses in most infected children (83%) and all adults (100%) that were absent in unexposed controls. Frequencies of SARS-CoV-2-specific T cells were higher in infected adults, especially in those with moderate symptoms, compared to infected children. The S-SARS-CoV-2 IFN-{gamma} T cell response correlated with S1-SARS-CoV-2-specific serum IgM, IgG, and IgA antibody concentrations. Predominantly, effector memory CD4+ T cells of a Th1 phenotype were activated upon exposure to SARS-CoV-2 antigens, which persisted for 4-8 weeks after symptom onset. We detected very low frequencies of SARS-CoV-2-reactive CD8+ T cells in these individuals.\n\nConclusionsOur data indicate that an antigen-specific memory CD4+ T cell response is induced in children and adults with mild SARS-CoV-2 infection. T cell immunity induced after mild COVID-19 could contribute to protection against re-infection.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Concepcion Violan", - "author_inst": "Unitat de Suport a la Recerca Metropolitana Nord, Institut Universitari d'Investigacio en Atencio Primaria Jordi Gol (IDIAP Jordi Gol), Mataro, Spain." - }, - { - "author_name": "Pere Toran", - "author_inst": "Unitat de Suport a la Recerca Metropolitana Nord, Institut Universitari d'Investigacio en Atencio Primaria Jordi Gol (IDIAP Jordi Gol), Mataro, Spain." - }, - { - "author_name": "Bibiana Quirant", - "author_inst": "Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain." - }, - { - "author_name": "Noemi Lamonja-Vicente", - "author_inst": "Unitat de Suport a la Recerca Metropolitana Nord, Institut Universitari d'Investigacio en Atencio Primaria Jordi Gol (IDIAP Jordi Gol), Mataro, Spain." - }, - { - "author_name": "Lucia A Carrasco-Ribelles", - "author_inst": "Institut Universitari d'Investigacio en Atencio Primaria Jordi Gol (IDIAP Jordi Gol), Barcelona, Spain." - }, - { - "author_name": "Carla Chacon", - "author_inst": "Institut Universitari d'Investigacio en Atencio Primaria Jordi Gol (IDIAP Jordi Gol), Barcelona, Spain." - }, - { - "author_name": "Josep Maria Manresa-Dominguez", - "author_inst": "Institut Universitari d'Investigacio en Atencio Primaria Jordi Gol (IDIAP Jordi Gol), Barcelona, Spain." - }, - { - "author_name": "Francesc Ramos-Roure", - "author_inst": "Unitat de Suport a la Recerca Metropolitana Nord, Institut Universitari d'Investigacio en Atencio Primaria Jordi Gol (IDIAP Jordi Gol), Mataro, Spain." - }, - { - "author_name": "Albert Roso-Llorach", - "author_inst": "Institut Universitari d'Investigacio en Atencio Primaria Jordi Gol (IDIAP Jordi Gol), Barcelona, Spain." - }, - { - "author_name": "Aleix Pujol", - "author_inst": "Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain." - }, - { - "author_name": "Dan Ouchi", - "author_inst": "Institut Universitari d'Investigacio en Atencio Primaria Jordi Gol (IDIAP Jordi Gol), Barcelona, Spain." + "author_name": "Patricia Kaaijk", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" }, { - "author_name": "Monica Monteagudo", - "author_inst": "Institut Universitari d'Investigacio en Atencio Primaria Jordi Gol (IDIAP Jordi Gol), Barcelona, Spain." + "author_name": "Veronica Olivo Pimentel", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" }, { - "author_name": "Pilar Montero", - "author_inst": "Unitat de Suport a la Recerca Metropolitana Nord, Institut Universitari d'Investigacio en Atencio Primaria Jordi Gol (IDIAP Jordi Gol), Mataro, Spain." + "author_name": "Maarten E. Emmelot", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" }, { - "author_name": "Rosa Garcia-Sierra", - "author_inst": "Unitat de Suport a la Recerca Metropolitana Nord, Institut Universitari d'Investigacio en Atencio Primaria Jordi Gol (IDIAP Jordi Gol), Mataro, Spain." + "author_name": "Martien Poelen", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" }, { - "author_name": "Fernando Armestar", - "author_inst": "Universitat Autonoma de Barcelona, Cerdanyola del Valles, Spain." + "author_name": "Alper Cevirgel", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" }, { - "author_name": "Rosalia Dacosta-Aguayo", - "author_inst": "Unitat de Suport a la Recerca Metropolitana Nord, Institut Universitari d'Investigacio en Atencio Primaria Jordi Gol (IDIAP Jordi Gol), Mataro, Spain." + "author_name": "Rutger M. Schepp", + "author_inst": "National Institute for Public Health and The Environment (RIVM)" }, { - "author_name": "Maria Dolade", - "author_inst": "Clinical and Biochemical Analysis Division. Laboratori clinic Metropolitana Nord (LCMN). Hospital Universitari Germans Trias i Pujol, Badalona, Spain." + "author_name": "Gerco den Hartog", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" }, { - "author_name": "Nuria Prat", - "author_inst": "Direccio d'Atencio Primaria Metropolitana Nord Institut Catala de Salut." + "author_name": "Daphne F.M. Reukers", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" }, { - "author_name": "Josep Maria Bonet", - "author_inst": "Direccio d'Atencio Primaria Metropolitana Nord Institut Catala de Salut." + "author_name": "Lisa Beckers", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" }, { - "author_name": "Bonaventura Clotet", - "author_inst": "Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain." + "author_name": "Josine van Beek", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" }, { - "author_name": "Ignacio Blanco", - "author_inst": "Hospital Universitari Germans Trias i Pujol, Badalona, Spain; Gerencia Territorial Metropolitana Nord, Institut Catala de la Salut, Barcelona, Spain." + "author_name": "Cecile A.C.M. van Els", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" }, { - "author_name": "Julia G Prado", - "author_inst": "Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain." + "author_name": "Adam Meijer", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" }, { - "author_name": "Eva Maria Martinez-Caceres", - "author_inst": "Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain." + "author_name": "Nynke Y. Rots", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" }, { - "author_name": "- ProHEpiC-19 Investigators", - "author_inst": "" + "author_name": "Jelle de Wit", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.09.10.21263072", @@ -563105,79 +561314,67 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.09.21263139", - "rel_title": "SARS-CoV-2 serology across scales: a framework for unbiased seroprevalence estimation incorporating antibody kinetics and epidemic recency", + "rel_doi": "10.1101/2021.09.10.21263410", + "rel_title": "Analytical performances of the COVISTIX and Panbio antigen rapid tests for SARS-CoV-2 detection in an unselected population (all commers)", "rel_date": "2021-09-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.09.21263139", - "rel_abs": "Serosurveys are a key resource for measuring SARS-CoV-2 cumulative incidence. A growing body of evidence suggests that asymptomatic and mild infections (together making up over 95% of all infections) are associated with lower antibody titers than severe infections. Antibody levels also peak a few weeks after infection and decay gradually. We developed a statistical approach to produce adjusted estimates of seroprevalence from raw serosurvey results that account for these sources of spectrum bias. We incorporate data on antibody responses on multiple assays from a post-infection longitudinal cohort, along with epidemic time series to account for the timing of a serosurvey relative to how recently individuals may have been infected. We applied this method to produce adjusted seroprevalence estimates from five large-scale SARS-CoV-2 serosurveys across different settings and study designs. We identify substantial differences between reported and adjusted estimates of over two-fold in the results of some surveys, and provide a tool for practitioners to generate adjusted estimates with pre-set or custom parameter values. While unprecedented efforts have been launched to generate SARS-CoV-2 seroprevalence estimates over this past year, interpretation of results from these studies requires properly accounting for both population-level epidemiologic context and individual-level immune dynamics.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.10.21263410", + "rel_abs": "ImportanceA steady increase in acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases worldwide is causing some regions of the world to withstand a third or even fourth wave of contagion. Swift detection of SARS-CoV-2 infection is paramount for the containment of cases, prevention of sustained contagion; and most importantly, for the reduction of mortality.\n\nObjectiveTo evaluate the performance and validity of the COVISTIX rapid antigen test, for the detection of SARS-CoV-2 in an unselected population and compare it to Panbio rapid antigen test and RT-PCR.\n\nDesignThis is comparative effectiveness study; samples were collected at two point-of-care facilities in Mexico City between May and August 2021.\n\nParticipantsRecruited individuals were probable COVID-19 cases, either symptomatic or asymptomatic persons that were at risk of infection due to close contact to SARS-CoV-2 positive cases.\n\nDiagnostic interventionRT-PCR was used as gold standard for detection of SARS-CoV-2 in nasal and nasopharyngeal swabs, study subjects were tested in parallel either with the COVISTIX or with Panbio rapid antigen test.\n\nMain outcomeDiagnostic performance of the COVISTIX assay is adequate in all commers since its accuracy parameters were not affected in samples collected after 7 days of symptom onset, and it detected almost 65% of samples with a Ct-value between 30 and 34.\n\nResultsFor the population tested with COVISTIX (n=783), specificity and sensitivity of the was 96.0% (CI95% 94.0-98.0) and 81% (CI95% 76.0-85.0), as for the Panbio (n=2202) population, was 99.0% (CI95%: 0.99-1.00) and 62% (CI%: 58.0-64.0%), respectively.\n\nConclusions and relevanceThe COVISTIX rapid antigen test shows a high performance in all comers, thus, this test is also adequate for testing patients who have passed the peak of viral shedding or for asymptomatic patients.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Saki Takahashi", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Michael J Peluso", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Jill Hakim", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Keirstinne Turcios", - "author_inst": "University of California, San Francisco" + "author_name": "Francisco Garcia-Cardenas", + "author_inst": "Instituto Nacional de Medicina Genomica, Mexico City, Mexico" }, { - "author_name": "Owen Janson", - "author_inst": "University of California, San Francisco" + "author_name": "Alba Franco", + "author_inst": "Instituto Nacional de Medicina Genomica, Mexico City, Mexico" }, { - "author_name": "Isobel Routledge", - "author_inst": "University of California, San Francisco" + "author_name": "Ricardo Cortes", + "author_inst": "Instituto Nacional de Medicina Genomica, Mexico City, Mexico" }, { - "author_name": "Michael Paul Busch", - "author_inst": "VITALANT RESEARCH INSTITUTE" + "author_name": "Jenny Bertin", + "author_inst": "Centro Citibanamex COVID, Mexico City, Mexico" }, { - "author_name": "Rebecca Hoh", - "author_inst": "University of California, San Francisco" + "author_name": "Rafael Valdez", + "author_inst": "Centro Citibanamex COVID, Mexico City, Mexico" }, { - "author_name": "Viva Tai", - "author_inst": "University of California, San Francisco" + "author_name": "Fernando Penaloza", + "author_inst": "Instituto Nacional de Medicina Genomica, Mexico City, Mexico" }, { - "author_name": "J. Daniel Kelly", - "author_inst": "University of California, San Francisco" + "author_name": "Emmanuel Frias-Jimenez", + "author_inst": "Instituto Nacional de Medicina Genomica, Mexico City, Mexico" }, { - "author_name": "Jeffrey N. Martin", - "author_inst": "University of California, San Francisco" + "author_name": "Alberto Cedro-Tanda", + "author_inst": "Instituto Nacional de Medicina Genomica, Mexico City, Mexico" }, { - "author_name": "Steven G Deeks", - "author_inst": "University of California, San Francisco" + "author_name": "Alfredo Mendoza-Vargas", + "author_inst": "Instituto Nacional de Medicina Genomica, Mexico City, Mexico" }, { - "author_name": "Timothy J. Henrich", - "author_inst": "University of California, San Francisco" + "author_name": "Juan P Reyes-Grajeda", + "author_inst": "Instituto Nacional de Medicina Genomica, Mexico City, Mexico" }, { - "author_name": "Bryan Greenhouse", - "author_inst": "University of California, San Francisco" + "author_name": "Alfredo Hidalgo-Miranda", + "author_inst": "Instituto Nacional de Medicina Genomica, Mexico City, Mexico" }, { - "author_name": "Isabel Rodriguez-Barraquer", - "author_inst": "University of California, San Francisco" + "author_name": "Luis A Herrera", + "author_inst": "Instituto Nacional de Medicina Genomica, Mexico City, Mexico" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.09.07.21262725", @@ -565275,69 +563472,61 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.09.09.21263331", - "rel_title": "Second wave of the Covid-19 pandemic in Delhi, India: high seroprevalence not a deterrent?", + "rel_doi": "10.1101/2021.09.09.21263026", + "rel_title": "The clinically extremely vulnerable to COVID: Identification and changes in health care while self-isolating (shielding) during the coronavirus pandemic", "rel_date": "2021-09-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.09.21263331", - "rel_abs": "BackgroundWe report the findings of a large follow-up community-based serosurvey and correlating it with the COVID-19 test-positivity rate and the case load observed during the peak of the second wave of the Covid-19 pandemic in Delhi, India.\n\nMethodsIndividuals of age [≥]5 years were recruited from 274 wards of the state (population [~] 19.6 million) during January 11 to January 22 2021. A total of 100 participants each were included from all the wards for a net sample size of [~]28,000. A multi-stage sampling technique was applied for selection of participants for the household serosurvey. Anti SARS CoV-2 IgG antibodies were detected by using the VITROS assay (90% Sn, 100% Sp).\n\nResultsAntibody positivity was observed in 14,298 (50.76%) of the 28,169 samples. The age, sex and district population weighted seroprevalence of the IgG SARS-CoV-2 was 50.52% (95% C.I. 49.94-51.10) and after adjustment for assay characteristics was 56.13% (95% C.I. 55.49-56.77). On adjusted analysis, participants aged [≥]50 years, of female gender, housewives, having ever lived in containment zones, urban slum dwellers, and diabetes or hypertensive patients had significantly higher odds of SARS-CoV-2 antibody positivity.\n\nThe peak infection rate and the test positivity rate since October 2020 were initially observed in mid-November 2020 with a subsequent steep declining trend, followed by a period of persistently low case burden lasting until the first week of March 2021. This was followed by a steady increase followed by an exponential surge in infections from April 2021 onwards culminating in the second wave of the pandemic.\n\nConclusionsThe presence of infection induced immunity from SARS-CoV-2 even in more than one in two people can be ineffective in protecting the population.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.09.21263026", + "rel_abs": "BackgroundIn March 2020, the government of Scotland identified people deemed clinically extremely vulnerable to COVID due to their pre-existing health conditions. These people were advised to strictly self-isolate (shield) at the start of the pandemic, except for necessary healthcare. We examined who was identified as clinically extremely vulnerable, how their healthcare changed during isolation, and whether this process exacerbated healthcare inequalities.\n\nMethodsWe linked those on the shielding register in NHS Grampian, a health authority in Scotland, to healthcare records from 2015-2020. We described the source of identification, demographics, and clinical history of the cohort. We measured changes in out-patient, in-patient, and emergency healthcare during isolation in the shielding population and compared to the general non-shielding population.\n\nResultsThe register included 16,092 people (3% of the population), clinically vulnerable primarily due to a respiratory disease, immunosuppression, or cancer. Among them, 42% were not identified by national healthcare record screening but added ad hoc, with these additions including more children and fewer economically-deprived.\n\nDuring isolation, all forms of healthcare use decreased (25%-46%), with larger decreases in scheduled care than in emergency care. However, people shielding had better maintained scheduled care compared to the non-shielding general population: out-patient visits decreased 35% vs 49%; in-patient visits decreased 46% vs 81%. Notably, there was substantial variation in whose scheduled care was maintained during isolation: younger people and those with cancer had significantly higher visit rates, but there was no difference between sexes or socioeconomic levels.\n\nConclusionsHealthcare changed dramatically for the clinically extremely vulnerable population during the pandemic. The increased reliance on emergency care while isolating indicates that continuity of care for existing conditions was not optimal. However, compared to the general population, there was success in maintaining scheduled care, particularly in young people and those with cancer. We suggest that integrating demographic and primary care data would improve identification of the clinically vulnerable and could aid prioritising their care.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Nandini Sharma", - "author_inst": "Department of Community Medicine, Maulana Azad Medical College, New Delhi" - }, - { - "author_name": "Pragya Sharma", - "author_inst": "Department of Community Medicine, Maulana Azad Medical College, New Delhi" - }, - { - "author_name": "Saurav Basu", - "author_inst": "Department of Community Medicine, Maulana Azad Medical College, New Delhi" + "author_name": "Jessica Erin Butler", + "author_inst": "University of Aberdeen" }, { - "author_name": "Ritika Bakshi", - "author_inst": "Department of Community Medicine, Maulana Azad Medical College, New Delhi" + "author_name": "Mintu Nath", + "author_inst": "University of Aberdeen" }, { - "author_name": "Ekta Gupta", - "author_inst": "Department of Virology, Institute of Liver and Biliary Sciences, New Delhi" + "author_name": "Dimitra Blana", + "author_inst": "University of Aberdeen" }, { - "author_name": "Reshu Agarwal", - "author_inst": "Department of Virology, Institute of Liver and Biliary Sciences, New Delhi" + "author_name": "William P Ball", + "author_inst": "University of Aberdeen" }, { - "author_name": "Kumar Dushyant", - "author_inst": "Department of Community Medicine, Maulana Azad Medical College, New Delhi" + "author_name": "Nicola Beech", + "author_inst": "NHS Grampian" }, { - "author_name": "Nutan Mundeja", - "author_inst": "Directorate General of Health Services, Government of National Capital Territory, Delhi" + "author_name": "Corri Black", + "author_inst": "NHS Grampian and University of Aberdeen" }, { - "author_name": "Zeasaly Marak", - "author_inst": "Directorate General of Health Services, Government of National Capital Territory, Delhi" + "author_name": "Graham Osler", + "author_inst": "NHS Grampian" }, { - "author_name": "Sanjay Singh", - "author_inst": "Directorate General of Health Services, Government of National Capital Territory, Delhi" + "author_name": "Sebastien Peytrignet", + "author_inst": "Health Foundation" }, { - "author_name": "Gautam Singh", - "author_inst": "Directorate General of Health Services, Government of National Capital Territory, Delhi" + "author_name": "Katie Wilde", + "author_inst": "University of Aberdeen" }, { - "author_name": "Ruchir Rustagi", - "author_inst": "Directorate of Family Welfare, Government of National Capital Territory, Delhi" + "author_name": "Artur Wozniak", + "author_inst": "University of Aberdeen" }, { - "author_name": "S K Sarin", - "author_inst": "Institute of Liver and Biliary Sciences, New Delhi" + "author_name": "Simon Sawhney", + "author_inst": "NHS Grampian and University of Aberdeen" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -567001,29 +565190,29 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.09.11.459886", - "rel_title": "Adaptive convergent evolution of genome proofreading in SARS-CoV2: insights into the Eigen's paradox", + "rel_doi": "10.1101/2021.09.11.459844", + "rel_title": "Rapid and parallel adaptive mutations in spike S1 drive clade success in SARS-CoV-2", "rel_date": "2021-09-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.11.459886", - "rel_abs": "Evolutionary history of coronaviruses holds the key to understand mutational behavior and prepare for possible future outbreaks. By performing comparative genome analysis of nidovirales that contain the family of coronaviruses, we traced the origin of proofreading, surprisingly to the eukaryotic antiviral component ZNFX1. This common recent ancestor contributes two zinc finger (ZnF) motifs that are unique to viral exonuclease, segregating them from DNA proof-readers. Phylogenetic analyses indicate that following acquisition, genomes of coronaviruses retained and further fine-tuned proofreading exonuclease, whereas related families harbor substitution of key residues in ZnF1 motif concomitant to a reduction in their genome sizes. Structural modelling followed by simulation suggests the role of ZnF in RNA binding. Key ZnF residues strongly coevolve with replicase, and the helicase involved in duplex RNA unwinding. Hence, fidelity of replication in coronaviruses is a result of convergent evolution, that enables maintenance of genome stability akin to cellular proofreading systems.", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.11.459844", + "rel_abs": "Given the importance of variant SARS-CoV-2 viruses with altered receptor-binding or antigenic phenotypes, we sought to quantify the degree to which adaptive evolution is driving accumulation of mutations in the SARS-CoV-2 genome. Here we assessed adaptive evolution across genes in the SARS-CoV-2 genome by correlating clade growth with mutation accumulation as well as by comparing rates of nonsynonymous to synonymous divergence, clustering of mutations across the SARS-CoV-2 phylogeny and degree of convergent evolution of individual mutations. We find that spike S1 is the focus of adaptive evolution, but also identify positively-selected mutations in other genes that are sculpting the evolutionary trajectory of SARS-CoV-2. Adaptive changes in S1 accumulated rapidly, resulting in a remarkably high ratio of nonsynonymous to synonymous divergence that is 2.5X greater than that observed in HA1 at the beginning of the 2009 H1N1 pandemic.", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Vivek T Natarajan", - "author_inst": "CSIR-IGIB" + "author_name": "Kathryn Kistler", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "Keerthic Aswin", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology" + "author_name": "John Huddleston", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "Srinivasan Ramachandran", - "author_inst": "Institute of Genomics and Integrative Biology" + "author_name": "Trevor Bedford", + "author_inst": "Fred Hutchinson Cancer Research Center, University of Washington" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "evolutionary biology" }, @@ -568987,29 +567176,101 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2021.09.07.21263207", - "rel_title": "metaCOVID: An R-Shiny application for living meta-analyses of COVID-19 trials", + "rel_doi": "10.1101/2021.09.02.21262979", + "rel_title": "Exponential growth, high prevalence of SARS-CoV-2 and vaccine effectiveness associated with Delta variant in England during May to July 2021", "rel_date": "2021-09-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.07.21263207", - "rel_abs": "\"Living\" evidence synthesis is of primary interest for decision-makers to overcome the COVID-19 pandemic. The COVID-NMA provides open-access living meta-analyses assessing different therapeutic and preventive interventions. Data are posted on a platform (https://covid-nma.com/) and analyses are updated every week. However, guideline developers and other stakeholders also need to investigate the data and perform their own analyses. This requires resources, time, statistical expertise, and software knowledge. To assist them, we created the \"metaCOVID\" application which, based on automation processes, facilitates the fast exploration of the data and the conduct of analyses tailored to end-users needs. metaCOVID has been created in R and is freely available as an R-Shiny application. The application conducts living meta-analyses for every outcome. Several options are available for subgroup and sensitivity analyses. The results are presented in downloadable forest plots. metaCOVID is freely available from https://covid-nma.com/metacovid/ and the source code from https://github.com/TEvrenoglou/metaCovid.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.02.21262979", + "rel_abs": "BackgroundThe prevalence of SARS-CoV-2 infection continues to drive rates of illness and hospitalisations despite high levels of vaccination, with the proportion of cases caused by the Delta lineage increasing in many populations. As vaccination programs roll out globally and social distancing is relaxed, future SARS-CoV-2 trends are uncertain.\n\nMethodsWe analysed prevalence trends and their drivers using reverse transcription-polymerase chain reaction (RT-PCR) swab-positivity data from round 12 (between 20 May and 7 June 2021) and round 13 (between 24 June and 12 July 2021) of the REal-time Assessment of Community Transmission-1 (REACT-1) study, with swabs sent to non-overlapping random samples of the population ages 5 years and over in England.\n\nResultsWe observed sustained exponential growth with an average doubling time in round 13 of 25 days (lower Credible Interval of 15 days) and an increase in average prevalence from 0.15% (0.12%, 0.18%) in round 12 to 0.63% (0.57%, 0.18%) in round 13. The rapid growth across and within rounds appears to have been driven by complete replacement of Alpha variant by Delta, and by the high prevalence in younger less-vaccinated age groups, with a nine-fold increase between rounds 12 and 13 among those aged 13 to 17 years. Prevalence among those who reported being unvaccinated was three-fold higher than those who reported being fully vaccinated. However, in round 13, 44% of infections occurred in fully vaccinated individuals, reflecting imperfect vaccine effectiveness against infection despite high overall levels of vaccination. Using self-reported vaccination status, we estimated adjusted vaccine effectiveness against infection in round 13 of 49% (22%, 67%) among participants aged 18 to 64 years, which rose to 58% (33%, 73%) when considering only strong positives (Cycle threshold [Ct] values < 27); also, we estimated adjusted vaccine effectiveness against symptomatic infection of 59% (23%, 78%), with any one of three common COVID-19 symptoms reported in the month prior to swabbing. Sex (round 13 only), ethnicity, household size and local levels of deprivation jointly contributed to the risk of higher prevalence of swab-positivity.\n\nDiscussionFrom end May to beginning July 2021 in England, where there has been a highly successful vaccination campaign with high vaccine uptake, infections were increasing exponentially driven by the Delta variant and high infection prevalence among younger, unvaccinated individuals despite double vaccination continuing to effectively reduce transmission. Although slower growth or declining prevalence may be observed during the summer in the northern hemisphere, increased mixing during the autumn in the presence of the Delta variant may lead to renewed growth, even at high levels of vaccination.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Theodoros Evrenoglou", - "author_inst": "Universite de Paris" + "author_name": "Paul Elliott", + "author_inst": "Imperial College London School of Public Health" }, { - "author_name": "Isabelle Boutron", - "author_inst": "Universite de Paris" + "author_name": "David J Haw", + "author_inst": "Imperial College London" }, { - "author_name": "Anna Chaimani", - "author_inst": "Universite de Paris" + "author_name": "Haowei Wang", + "author_inst": "Imperial College London" + }, + { + "author_name": "Oliver Eales", + "author_inst": "Imperial College London" + }, + { + "author_name": "Caroline E Walters", + "author_inst": "Imperial College London" + }, + { + "author_name": "Kylie E. C. Ainslie", + "author_inst": "Imperial College London" + }, + { + "author_name": "Christina J Atchison", + "author_inst": "Imperial College London" + }, + { + "author_name": "Claudio Fronterre", + "author_inst": "Lancaster University" + }, + { + "author_name": "Peter Diggle", + "author_inst": "Lancaster University" + }, + { + "author_name": "Andrew J Page", + "author_inst": "Quadram Institute" + }, + { + "author_name": "Alex Trotter", + "author_inst": "Quadram Institute Bioscience" + }, + { + "author_name": "Sophie J Prosolek", + "author_inst": "Quadram Institute" + }, + { + "author_name": "- The COVID-19 Genomics UK (COG-UK) consortium", + "author_inst": "The COVID-19 Genomics UK (COG-UK) consortium" + }, + { + "author_name": "Deborah Ashby", + "author_inst": "Imperial College London" + }, + { + "author_name": "Christl Donnelly", + "author_inst": "University of Oxford" + }, + { + "author_name": "Wendy Barclay", + "author_inst": "Imperial College London" + }, + { + "author_name": "Graham P Taylor", + "author_inst": "Imperial College London" + }, + { + "author_name": "Graham Cooke", + "author_inst": "Imperial College" + }, + { + "author_name": "Helen Ward", + "author_inst": "Imperial College London" + }, + { + "author_name": "Ara Darzi", + "author_inst": "Imperial College London" + }, + { + "author_name": "Steven Riley", + "author_inst": "Dept Inf Dis Epi, Imperial College" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -571049,99 +569310,59 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2021.09.08.459485", - "rel_title": "SARS-CoV-2 mRNA vaccination elicits robust and persistent T follicular helper cell response in humans", + "rel_doi": "10.1101/2021.09.08.459428", + "rel_title": "Cigarette smoke preferentially induces full length ACE2 exposure in primary human airway cells but does not alter susceptibility to SARS-CoV-2 infection", "rel_date": "2021-09-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.08.459485", - "rel_abs": "SARS-CoV-2 mRNA vaccines induce robust anti-spike (S) antibody and CD4+ T cell responses. It is not yet clear whether vaccine-induced follicular helper CD4+ T (TFH) cell responses contribute to this outstanding immunogenicity. Using fine needle aspiration of draining axillary lymph nodes from individuals who received the BNT162b2 mRNA vaccine, we show that frequency of TFH correlates with that of S-binding germinal center B cells. Mining of the responding TFH T cell receptor repertoire revealed a strikingly immunodominant HLADPB1* 04-restricted response to S167-180 in individuals with this allele, which is among the most common HLA alleles in humans. Paired blood and lymph node specimens show that while circulating S-specific TFH cells peak one week after the second immunization, S-specific TFH persist at nearly constant frequencies for at least six months. Collectively, our results underscore the key role that robust TFH cell responses play in establishing long-term immunity by this efficacious human vaccine.", - "rel_num_authors": 20, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.08.459428", + "rel_abs": "Cigarette smoking has multiple serious negative health consequences. However, the epidemiological relationship between cigarette smoking and SARS-CoV-2 infection is controversial; and the interaction between cigarette smoking, airway expression of the ACE2 receptor and the susceptibility of airway cells to infection is unclear. We exposed differentiated air-liquid interface cultures derived from primary human airway stem cells to cigarette smoke extract (CSE) and infected them with SARS-CoV-2. We found that CSE increased expression of full-length ACE2 (flACE2) but did not alter the expression of a Type I-interferon sensitive truncated ACE2 that lacks the capacity to bind SARS-CoV-2 or a panel of interferon-sensitive genes. Importantly, exposure to CSE did not increase viral infectivity despite the increase in flACE2. Our data are consistent with epidemiological data suggesting current smokers are not at excess risk of SARS-CoV-2 infection. This does not detract from public health messaging emphasising the excess risk of severe COVID-19 associated with smoking-related cardiopulmonary disease.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Philip A Mudd", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Jackson S Turner", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Wooseob Kim", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Elizaveta Kalaidina", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Jan Petersen", - "author_inst": "Monash University" - }, - { - "author_name": "Aaron J Schmitz", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Tingting Lei", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Alem Haile", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Thi H.O Nguyen", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Louise C Rowntree", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Elisa Rosati", - "author_inst": "Christian-Albrecht University of Kiel" + "author_name": "Wenrui Guo", + "author_inst": "Department of Medicine, University of Cambridge" }, { - "author_name": "Michael K Klebert", - "author_inst": "Washington University School of Medicine" + "author_name": "Brian Ortmann", + "author_inst": "CITIID, University of Cambridge" }, { - "author_name": "Teresa Suessen", - "author_inst": "Washington University School of Medicine" + "author_name": "Thomas Crozier", + "author_inst": "CITIID, University of Cambridge" }, { - "author_name": "William D Middleton", - "author_inst": "Washington University School of Medicine" + "author_name": "Edward JD Greenwood", + "author_inst": "University of Cambridge" }, { - "author_name": "- the SJTRC Study Team", - "author_inst": "" + "author_name": "Daniel Kottmann", + "author_inst": "Department of Medicine, University of Cambridge" }, { - "author_name": "Sharlene A Teefey", - "author_inst": "Washington University School of Medicine" + "author_name": "Ravindra Mahadeva", + "author_inst": "Cambridge University Hospital NHS Foundation Trust" }, { - "author_name": "Rachel M Presti", - "author_inst": "Washington University School of Medicine" + "author_name": "James A Nathan", + "author_inst": "University of Cambridge" }, { - "author_name": "Katherine Kedzierska", - "author_inst": "University of Melbourne" + "author_name": "Paul J Lehner", + "author_inst": "CITIID, University of Cambridge" }, { - "author_name": "Jamie Rossjohn", - "author_inst": "Monash University" + "author_name": "Frank McCaughan", + "author_inst": "University of Cambridge" }, { - "author_name": "Ali Ellebedy", - "author_inst": "Washington University School of Medicine" + "author_name": "Linsey Porter", + "author_inst": "Department of Medicine, University of Cambridge" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.09.08.459480", @@ -572871,21 +571092,69 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2021.09.02.21262861", - "rel_title": "Covid spirals: a phase diagram representation of COVID-19 effective reproduction number Rt", + "rel_doi": "10.1101/2021.09.03.21263061", + "rel_title": "Secondary transmission of SARS-CoV-2 in educational settings in Northern Italy from September 2020 to April 2021: a population-based study", "rel_date": "2021-09-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.02.21262861", - "rel_abs": "In this paper, we propose a phase diagram representation of COVID-19 effective reproduction number Rt. Specifically, we express Rt as a function of the estimated infected individuals. This function plots a particular clockwise spiral that allows to easily compare the evolution of the number of new infected individuals at different dates and, possibly, provide some hints on the future progression of the infection.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.03.21263061", + "rel_abs": "BackgroundWe aimed to quantify the risk of transmission of SARS-CoV-2 in the school setting by type of school, characteristics of the index case and calendar period in the Reggio Emilia province (RE), Italy. The secondary aim was to estimate the promptness of contact tracing.\n\nMethodsA population-based analysis of surveillance data of all COVID-19 cases occurring in RE, Italy, from September 1, 2020, to April 4th, 2021, for which a school contact and/or exposure was suspected. Indicator of the delay in contact tracing was computed as the time elapsed since positivity of the index case and the date on which the swab for classmates was scheduled (or most were scheduled).\n\nResultsOverall, 30,184 and 13,608 contacts among classmates and teachers/staff, respectively, were identified and received recommendation for testing; 43,214 (98.7%) performed the test. Secondary transmission occurred in about 40% of the investigated classes, and the overall secondary case attack rate was 4%, slightly higher when the index case was a teacher, but with almost no differences by type of school and stable during the study period. Promptness of contact tracing increased during the study period, reducing the time from index case identification and testing of contacts from 7 to 3 days, as well the ability to identify possible source of infection in the index case.\n\nConclusionsDespite the spread of the Alpha variant during the study period in RE, the secondary case attack rate remained stable from school reopening in September 2020 until the beginning of April 2021.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Raffaele Pesenti", - "author_inst": "University Ca' Foscari, Venezia" + "author_name": "Olivera Djuric", + "author_inst": "Azienda USL-IRCCS di Reggio Emilia, Italy" }, { - "author_name": "Kenneth W Pesenti", - "author_inst": "University of Trieste" + "author_name": "Elisabetta Larosa", + "author_inst": "Azienda USL-IRCCS di Reggio Emilia, Italy" + }, + { + "author_name": "Mariateresa Cassinadri", + "author_inst": "Azienda USL-IRCCS di Reggio Emilia, Italy" + }, + { + "author_name": "Silvia Cilloni", + "author_inst": "Azienda USL-IRCCS di Reggio Emilia, Italy" + }, + { + "author_name": "Eufemia Bisaccia", + "author_inst": "Azienda USL-IRCCS di Reggio Emilia, Italy" + }, + { + "author_name": "Davide Pepe", + "author_inst": "Azienda USL-IRCCS di Reggio Emilia, Italy" + }, + { + "author_name": "Massimo Vicentini", + "author_inst": "Azienda USL-IRCCS di Reggio Emilia, Italy" + }, + { + "author_name": "Francesco Venturelli", + "author_inst": "Azienda USL-IRCCS di Reggio Emilia, Italy" + }, + { + "author_name": "Laura Bonvicini", + "author_inst": "Azienda USL-IRCCS di Reggio Emilia, Italy" + }, + { + "author_name": "Paolo Giorgi Rossi", + "author_inst": "Azienda USL-IRCCS di Reggio Emilia, Italy" + }, + { + "author_name": "Patrizio Pezzotti", + "author_inst": "Department of Infectious Diseases, Istituto Superiore di Sanita, Rome, Italy." + }, + { + "author_name": "Alberto Mateo Urdiales", + "author_inst": "Department of Infectious Diseases, Istituto Superiore di Sanita, Rome, Italy." + }, + { + "author_name": "Emanuela Bedeschi", + "author_inst": "Azienda USL-IRCCS di Reggio Emila, Italy" + }, + { + "author_name": "- Reggio Emilia Covid-19 Working Group", + "author_inst": "" } ], "version": "1", @@ -574333,75 +572602,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.09.01.21262985", - "rel_title": "Elevation of Neurodegenerative Serum Biomarkers among Hospitalized COVID-19 Patients", + "rel_doi": "10.1101/2021.09.01.21262952", + "rel_title": "Ideology, policy decision-making and environmental impact in the face of the Coronavirus pandemic in the US", "rel_date": "2021-09-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.01.21262985", - "rel_abs": "INTRODUCTIONOlder adults hospitalized with COVID-19 are susceptible to neurological complications, particularly encephalopathy, which may reflect age-related neurodegenerative processes.\n\nMETHODSSerum total tau, ptau-181, GFAP, NFL, UCHL1, and amyloid-beta(A{beta}-40,42) were measured in hospitalized COVID-19 patients without a history of dementia, and compared among patients with or without encephalopathy, in-hospital death versus survival, and discharge home versus other dispositions using multivariable Cox proportional hazards regression analyses.\n\nRESULTSAmong 251 patients, admission serum ptau-181 and UCHL1 were significantly elevated in patients with encephalopathy (both P<0.05) and total tau, GFAP, and NFL were significantly lower in those discharged home(all P<0.05). These markers correlated significantly with severity of COVID illness. NFL, GFAP and UCH-L1 were significantly higher in hospitalized COVID patients than in non-COVID controls with mild cognitive impairment or Alzheimers disease(AD).\n\nDISCUSSIONAge-related neurodegenerative biomarkers were elevated to levels observed in AD and associated with encephalopathy and worse outcomes among hospitalized COVID-19 patients.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.01.21262952", + "rel_abs": "Covid-19 pandemic was a challenge for the health systems of many countries. It altered peoples way of life and shocked the world economy. In the United States, political ideology has clashed with the fight against the pandemic. President Trumps denial prevailed despite the warnings from the WHO and scientists who alerted of the seriousness of the situation. Despite this, some state governments did not remain passive in the absence of federal government measures, and passed laws restricting mobility (lockdowns). Consequently, the political polarity was accentuated. On the one hand, the defenders of more severe public health measures and, on the other, the advocates of individual rights and freedom above any other consideration. In this study, we analyze whether political partisanship and the political ideology has influenced the way Covid-19 was handled at the outbreak. Specifically, we analyze by using a Diff-in-Diff model, whether the ideology of each state, measure at three levels, affected the decrease in the NO2 levels observed after the pandemic outbreak in the US. We distinguish three alternative post-Covid periods and results show that the State ideology has a robust negative impact on the NO2 levels. There is an important difference between Democratic and Republican states, not just in the scope and following-up of the mobility and activity restrictions, but also in the speed they implemented them.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Jennifer A. Frontera", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Allal Boutajangout", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Arjun Masurkar", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Rebecca A Betensky", - "author_inst": "New York University School of Global Public Health" - }, - { - "author_name": "Yulin Ge", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Alok Vedvyas", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Ludovic Debure", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Andre Moreira", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Ariane Lewis", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Joshua Huang", - "author_inst": "NYU Langone Health" + "author_name": "Juan Prieto-Rodriguez", + "author_inst": "University of Oviedo (Spain)" }, { - "author_name": "Sujata Thawani", - "author_inst": "NYU Grossman School of Medicine" + "author_name": "Rafael Salas", + "author_inst": "Universidad Complutense de Madrid" }, { - "author_name": "Laura Balcer", - "author_inst": "NYU Grossman School of Medicine" + "author_name": "Douglas Noonan", + "author_inst": "IUPUI" }, { - "author_name": "Steven Galetta", - "author_inst": "NYU Grossman School of Medicine" + "author_name": "Francisco Tomas Cabeza-Martinez", + "author_inst": "Universidad de Oviedo" }, { - "author_name": "Thomas Wisniewski", - "author_inst": "NYU Grossman School of Medicine" + "author_name": "Javier Ramos-Gutierrez", + "author_inst": "Universidad Complutense de Madrid" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "health policy" }, { "rel_doi": "10.1101/2021.09.03.458854", @@ -576131,133 +574364,189 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.08.30.21262465", - "rel_title": "Covid-19 Vaccine Effectiveness in Healthcare Personnel in six Israeli Hospitals (CoVEHPI)", + "rel_doi": "10.1101/2021.08.30.21262701", + "rel_title": "Longitudinal analysis of SARS-CoV-2 vaccine breakthrough infections reveal limited infectious virus shedding and restricted tissue distribution", "rel_date": "2021-09-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.30.21262465", - "rel_abs": "BackgroundMethodologically rigorous studies on Covid-19 vaccine effectiveness (VE) in preventing SARS-CoV-2 infection are critically needed to inform national and global policy on Covid-19 vaccine use. In Israel, healthcare personnel (HCP) were initially prioritized for Covid-19 vaccination, creating an ideal setting to evaluate real-world VE in a closely monitored population.\n\nMethodsWe conducted a prospective study among HCP in 6 hospitals to estimate the effectiveness of the BNT162b2 mRNA Covid-19 vaccine in preventing SARS-CoV-2 infection. Participants filled out weekly symptom questionnaires, provided weekly nasal specimens, and three serology samples - at enrollment, 30 days and 90 days. We estimated VE against PCR-confirmed SARS-CoV-2 infection using the Cox Proportional Hazards model and against a combined PCR/serology endpoint using Fishers exact test.\n\nFindingsOf the 1,567 HCP enrolled between December 27, 2020 and February 15, 2021, 1,250 previously uninfected participants were included in the primary analysis; 998 (79.8%) were vaccinated with their first dose prior to or at enrollment, all with Pfizer BNT162b2 mRNA vaccine. There were four PCR-positive events among vaccinated participants, and nine among unvaccinated participants. Adjusted two-dose VE against any PCR- confirmed infection was 94.5% (95% CI: 82.6%-98.2%); adjusted two-dose VE against a combined endpoint of PCR and seroconversion for a 60-day follow-up period was 94.5% (95% CI: 63.0%-99.0%). Five PCR-positive samples from study participants were sequenced; all were alpha variant.\n\nInterpretationOur prospective VE study of HCP in Israel with rigorous weekly surveillance found very high VE for two doses of Pfizer BNT162b2 mRNA vaccine against SARS-CoV-2 during a period of predominant alpha variant circulation.\n\nFundingClalit Health Services", - "rel_num_authors": 29, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.30.21262701", + "rel_abs": "The global effort to vaccinate people against SARS-CoV-2 in the midst of an ongoing pandemic has raised questions about the nature of vaccine breakthrough infections and the potential for vaccinated individuals to transmit the virus. These questions have become even more urgent as new variants of concern with enhanced transmissibility, such as Delta, continue to emerge. To shed light on how vaccine breakthrough infections compare with infections in immunologically naive individuals, we examined viral dynamics and infectious virus shedding through daily longitudinal sampling in a small cohort of adults infected with SARS-CoV-2 at varying stages of vaccination. The durations of both infectious virus shedding and symptoms were significantly reduced in vaccinated individuals compared with unvaccinated individuals. We also observed that breakthrough infections are associated with strong tissue compartmentalization and are only detectable in saliva in some cases. These data indicate that vaccination shortens the duration of time of high transmission potential, minimizes symptom duration, and may restrict tissue dissemination.", + "rel_num_authors": 43, "rel_authors": [ { - "author_name": "Mark A. Katz", - "author_inst": "Clalit Research Institute, Innovation Division, Clalit Health Services; School of Public Health, Faculty of Health Sciences, Ben Gurion University of the Negev;" + "author_name": "Ruian Ke", + "author_inst": "Los Alamos National Laboratory" }, { - "author_name": "Efrat Bron Harlev", - "author_inst": "Schneider Children's Medical Center of Israel" + "author_name": "Pamela Martinez", + "author_inst": "UIUC" }, { - "author_name": "Bibiana Chazan", - "author_inst": "Infectious Diseases and Infection Control Unit, Ha'Emek Medical Center; Rappaport Faculty of Medicine, Technion" + "author_name": "Rebecca Lee Smith", + "author_inst": "University of Illinois at Urbana-Champaign" }, { - "author_name": "Michal Chowers", - "author_inst": "Infectious Diseases, Meir Medical Center; Sackler School of Medicine, Tel Aviv University" + "author_name": "Laura Gibson", + "author_inst": "UMass" }, { - "author_name": "David Greenberg", - "author_inst": "Pediatric Infectious Disease Unit the Pediatric Division, Soroka University Medical Center; Faculty of Health Sciences, Ben Gurion University of the Negev" + "author_name": "Chad Achenbach", + "author_inst": "Northwestern" }, { - "author_name": "Alon Peretz", - "author_inst": "Occupational Medicine Clinic, Rabin Medical Center" + "author_name": "Sally McFall", + "author_inst": "Northwestern" }, { - "author_name": "Sagi Tshori", - "author_inst": "Research Authority, Kaplan Medical Center; The Faculty of Medicine, Hebrew University of Jerusalem" + "author_name": "Chao Qi", + "author_inst": "Northwestern University Feinberg School of Medicine" }, { - "author_name": "Joseph Levy", - "author_inst": "Clalit Research Institute, Innovation Division, Clalit Health Services" + "author_name": "Joshua Jacob", + "author_inst": "Northwestern" }, { - "author_name": "Mili Yacobi", - "author_inst": "Clalit Research Institute, Innovation Division, Clalit Health Services" + "author_name": "Etienne Dembele", + "author_inst": "Northwestern" }, { - "author_name": "Avital Hirsch", - "author_inst": "Clalit Research Institute, Innovation Division, Clalit Health Services" + "author_name": "Camille Bundy", + "author_inst": "Northwestern" }, { - "author_name": "Doron Amichay", - "author_inst": "Clalit Central Laboratory, Clalit Health Services; Faculty of Health Sciences, Ben Gurion University of the Negev" + "author_name": "Lacy M Simons", + "author_inst": "Northwestern University" }, { - "author_name": "Ronit Weinberger", - "author_inst": "Clalit Central Laboratory, Clalit Health Services" + "author_name": "Egon A Ozer", + "author_inst": "Northwestern University" }, { - "author_name": "Anat Ben Dor", - "author_inst": "Clalit Central Laboratory, Clalit Health Services" + "author_name": "Judd F. Hultquist", + "author_inst": "Northwestern University Feinberg School of Medicine" }, { - "author_name": "Elena Keren Taraday", - "author_inst": "Clalit Central Laboratory, Clalit Health Services" + "author_name": "Ramon Lorenzo-Redondo", + "author_inst": "Northwestern University" }, { - "author_name": "Dana Reznik", - "author_inst": "Schneider Children's Medical Center of Israel" + "author_name": "Anita Opdycke", + "author_inst": "Northwestern" }, { - "author_name": "Chen Barazani Chayat", - "author_inst": "Multidisciplinary laboratory, Schneider Children's Medical Center of Israel" + "author_name": "Claudia Hawkins", + "author_inst": "Northwestern" }, { - "author_name": "Dana Sagas", - "author_inst": "Clinical Microbiology Laboratory, Ha'Emek Medical Center" + "author_name": "Robert Murphy", + "author_inst": "Northwestern" }, { - "author_name": "Haim Ben Zvi", - "author_inst": "Microbiology Department, Rabin Medical Center" + "author_name": "Agha Mirza", + "author_inst": "JHMI" }, { - "author_name": "Rita Berdinstein", - "author_inst": "Microbiology Department, Kaplan Medical Center; The Faculty of Medicine, Hebrew University of Jerusalem" + "author_name": "Madison Conte", + "author_inst": "JHMI" }, { - "author_name": "Gloria Rashid", - "author_inst": "Department of Clinical Laboratories, Meir Medical Center" + "author_name": "Nicholas Gallagher", + "author_inst": "JHMI" }, { - "author_name": "Yonat Shemer Avni", - "author_inst": "Virology, Soroka University Medical Center" + "author_name": "Chun Huai Luo", + "author_inst": "JHMI" }, { - "author_name": "Michal Mandelboim", - "author_inst": "Central Virology Laboratory, Chaim Sheba Medical Center, Ministry of Health; Department of Epidemiology and Preventive Medicine, Sackler Faculty of Medicine, Sc" + "author_name": "Junko Jarrett", + "author_inst": "Johns Hopkins Hospital" }, { - "author_name": "Neta Zuckerman", - "author_inst": "Central Virology Laboratory, Chaim Sheba Medical Center, Ministry of Health" + "author_name": "Abigail Conte", + "author_inst": "JHMI" }, { - "author_name": "Nir Rainy", - "author_inst": "Laboratory Division, Shamir Medical Center" + "author_name": "Ruifeng Zhou", + "author_inst": "JHU" }, { - "author_name": "Amichay Akriv", - "author_inst": "Clalit Research Institute, Innovation Division, Clalit Health Services" + "author_name": "Mireille Farjo", + "author_inst": "UIUC" }, { - "author_name": "Noa Dagan", - "author_inst": "Clalit Research Institute, Innovation Division, Clalit Health Services; Software and Information Systems Engineering, Ben Gurion University; Department of Biome" + "author_name": "Gloria Rendon", + "author_inst": "UIUC" }, { - "author_name": "Eldad Kepten", - "author_inst": "Clalit Research Institute, Innovation Division, Clalit Health Services" + "author_name": "Christopher J. Fields", + "author_inst": "University of Illinois at Urbana Champaign" }, { - "author_name": "Noam Barda", - "author_inst": "Clalit Research Institute, Innovation Division, Clalit Health Services; Software and Information Systems Engineering, Ben Gurion University; Department of Biome" + "author_name": "Leyi Wang", + "author_inst": "UIUC" + }, + { + "author_name": "Richard Fredrickson", + "author_inst": "UIUC" }, { - "author_name": "Ran D. Balicer", - "author_inst": "Clalit Research Institute, Innovation Division, Clalit Health Services; School of Public Health, Faculty of Health Sciences, Ben Gurion University of the Negev" + "author_name": "Melinda Baughman", + "author_inst": "UIUC" + }, + { + "author_name": "Karen Chiu", + "author_inst": "UIUC" + }, + { + "author_name": "Hannah Choi", + "author_inst": "UIUC" + }, + { + "author_name": "Kevin Scardina", + "author_inst": "UIUC" + }, + { + "author_name": "Alyssa Owens", + "author_inst": "UMass" + }, + { + "author_name": "John Broach", + "author_inst": "UMass" + }, + { + "author_name": "Bruce Barton", + "author_inst": "UMass" + }, + { + "author_name": "Peter Lazar", + "author_inst": "UMass" + }, + { + "author_name": "Matthew L Robinson", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "Heba Mostafa", + "author_inst": "JHMI" + }, + { + "author_name": "Yukari C Manabe", + "author_inst": "Johns Hopkins University School of Medicine" + }, + { + "author_name": "Andrew Pekosz", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" + }, + { + "author_name": "David McManus", + "author_inst": "UMass" + }, + { + "author_name": "Christopher B Brooke", + "author_inst": "University of Illinois at Urbana-Champaign" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -578145,79 +576434,43 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.08.30.458222", - "rel_title": "Apropos of Universal Epitope Discovery for COVID-19 Vaccines: A Framework for Targeted Phage Display-Based Delivery and Integration of New Evaluation Tools", + "rel_doi": "10.1101/2021.08.25.21262601", + "rel_title": "The resurgence risk of COVID-19 in the presence of immunity waning and ADE effect: a mathematical modelling study", "rel_date": "2021-08-31", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.30.458222", - "rel_abs": "Targeted bacteriophage (phage) particles are potentially attractive yet inexpensive platforms for immunization. Herein, we describe targeted phage capsid display of an immunogenically relevant epitope of the SARS-CoV-2 Spike protein that is empirically conserved, likely due to the high mutational cost among all variants identified to date. This observation may herald an approach to developing vaccine candidates for broad-spectrum, towards universal, protection against multiple emergent variants of coronavirus that cause COVID-19.", - "rel_num_authors": 15, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.25.21262601", + "rel_abs": "Since the end of 2020, the mass vaccination has been actively promoted and seemed to be effective to bring the COVID-19 pandemic under control. However, the fact of immunity waning and the possible existence of antibody-dependent enhancement (ADE) make the situation uncertain. We developed a dynamic model of COVID-19 incorporating vaccination and immunity waning, which was calibrated by using the data of accumulative vaccine doses administered and the COVID-19 epidemic in 2020 in mainland China. We explored how long the current vaccination program can prevent China in a low risk of resurgence, and how ADE affects the long-term trajectory of COVID-19 epidemics. The prediction suggests that the vaccination coverage with at least one dose reach 95.87%, and with two-doses reach 77.92% on August 31, 2021. However, even with the mass vaccination, randomly introducing infected cases in the post-vaccination period can result in large outbreaks quickly in the presence of immunity waning, particularly for SARS-CoV-2 variants with higher transmission ability. The results showed that with the current vaccination program and a proportion of 50% population wearing masks, mainland China can be protected in a low risk of resurgence till 2023/01/18. However, ADE effect and higher transmission ability for variants would significantly shorten the protective period for more than 1 year. Furthermore, intermittent outbreaks can occur while the peak values of the subsequential outbreaks are decreasing, meaning that subsequential outbreaks boosted the immunity in the population level, which further indicating that catching-up vaccination program can help to mitigate the possible outbreaks, even avoid the outbreaks. The findings reveal that integrated effects of multiple factors, including immunity waning, ADE, relaxed interventions, and higher transmission ability of variants, make the control of COVID-19 much more difficult. We should get ready for a long struggle with COVID-19, and should not totally rely on COVID-19 vaccine.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Christopher Markosian", - "author_inst": "Rutgers University" - }, - { - "author_name": "Daniela I. Staquicini", - "author_inst": "Rutgers University" - }, - { - "author_name": "Prashant Dogra", - "author_inst": "Houston Methodist Research Institute" - }, - { - "author_name": "Esteban Dodero-Rojas", - "author_inst": "Rice University" - }, - { - "author_name": "Fenny H. F. Tang", - "author_inst": "Rutgers University" - }, - { - "author_name": "Tracey L. Smith", - "author_inst": "Rutgers University" - }, - { - "author_name": "Vin\u00edcius G. Contessoto", - "author_inst": "Rice University" - }, - { - "author_name": "Steven K. Libutti", - "author_inst": "Rutgers University" - }, - { - "author_name": "Zhihui Wang", - "author_inst": "Houston Methodist Research Institute" - }, - { - "author_name": "Vittorio Cristini", - "author_inst": "Houston Methodist Research Institute" + "author_name": "Weike Zhou", + "author_inst": "Shaanxi Normal University" }, { - "author_name": "Paul C. Whitford", - "author_inst": "Northeastern University" + "author_name": "Biao Tang", + "author_inst": "Xi'an Jiaotong University" }, { - "author_name": "Stephen K. Burley", - "author_inst": "Rutgers University" + "author_name": "Yao Bai", + "author_inst": "Xi'an Center for Disease Prevention and Control" }, { - "author_name": "Jos\u00e9 N. Onuchic", - "author_inst": "Rice University" + "author_name": "Yiming Shao", + "author_inst": "Chinese Center for Disease Control and Prevention" }, { - "author_name": "Renata Pasqualini", - "author_inst": "Rutgers University" + "author_name": "Yanni Xiao", + "author_inst": "Xi'an Jiaotong University" }, { - "author_name": "Wadih Arap", - "author_inst": "Rutgers University" + "author_name": "Sanyi Tang", + "author_inst": "Shaanxi Normal University" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.08.24.21262245", @@ -580235,43 +578488,135 @@ "category": "gastroenterology" }, { - "rel_doi": "10.1101/2021.08.23.21262293", - "rel_title": "Predictive factors of response to 3rd dose of COVID-19 mRNA vaccine in kidney transplant recipients", + "rel_doi": "10.1101/2021.08.28.458047", + "rel_title": "The pigtail macaque (Macaca nemestrina) model of COVID-19 reproduces diverse clinical outcomes and reveals new and complex signatures of disease", "rel_date": "2021-08-30", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.23.21262293", - "rel_abs": "Only a minority of kidney transplant recipients (KTRs) develop protective neutralizing titers of anti-receptor binding domain of spike protein (RBD) IgG after two doses of mRNA COVID-19 vaccine. Administration of a third dose of mRNA vaccine to KTRs with sub-optimal response increase anti-RBD IgG titers but with high inter-individual variability. Patients with the higher response rate to the third dose of vaccine can be identified by the presence of low anti-RBD IgG titers and spike-specific CD4+ T cells in their circulation 14 days after the second dose.", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.28.458047", + "rel_abs": "The novel coronavirus SARS-CoV-2, the causative agent of COVID-19 disease, has killed over four million people worldwide as of July 2021 with infections rising again due to the emergence of highly transmissible variants. Animal models that faithfully recapitulate human disease are critical for assessing SARS-CoV-2 viral and immune dynamics, for understanding mechanisms of disease, and for testing vaccines and therapeutics. Pigtail macaques (PTM, Macaca nemestrina) demonstrate a rapid and severe disease course when infected with simian immunodeficiency virus (SIV), including the development of severe cardiovascular symptoms that are pertinent to COVID-19 manifestations in humans. We thus proposed this species may likewise exhibit severe COVID-19 disease upon infection with SARS-CoV-2. Here, we extensively studied a cohort of SARS-CoV-2-infected PTM euthanized either 6- or 21-days after respiratory viral challenge. We show that PTM demonstrate largely mild-to-moderate COVID-19 disease. Pulmonary infiltrates were dominated by T cells, including CD4+ T cells that upregulate CD8 and express cytotoxic molecules, as well as virus-targeting T cells that were predominantly CD4+. We also noted increases in inflammatory and coagulation markers in blood, pulmonary pathologic lesions, and the development of neutralizing antibodies. Together, our data demonstrate that SARS-CoV-2 infection of PTM recapitulates important features of COVID-19 and reveals new immune and viral dynamics and thus may serve as a useful animal model for studying pathogenesis and testing vaccines and therapeutics.", + "rel_num_authors": 29, "rel_authors": [ { - "author_name": "Xavier Charmetant", - "author_inst": "INSERM CIRI U1111, Lyon" + "author_name": "Alexandra Melton", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" }, { - "author_name": "Maxime ESPI", - "author_inst": "INSERM CIRI U1111, Lyon" + "author_name": "Lara A Doyle-Meyers", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" }, { - "author_name": "Thomas Barba", - "author_inst": "INSERM CIRI U1111, Lyon" + "author_name": "Robert V Blair", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" }, { - "author_name": "Anne Ovize", - "author_inst": "Eurofins Biomnis" + "author_name": "Cecily Midkiff", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" }, { - "author_name": "Emmanuel Morelon", - "author_inst": "INSERM CIRI U1111, Lyon; Hospices Civils de Lyon, Edouard Herriot Hospital, Department of Transplantation, Nephrology and Clinical Immunology, Lyon, France; Cla" + "author_name": "Hunter J Melton", + "author_inst": "Florida State University, Department of Statistics, Tallahassee, Florida" }, { - "author_name": "Olivier Thaunat", - "author_inst": "INSERM CIRI U1111, Lyon; Hospices Civils de Lyon, Edouard Herriot Hospital, Department of Transplantation, Nephrology and Clinical Immunology, Lyon, France; Cla" + "author_name": "Kasi Russell-Lodrigue", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" + }, + { + "author_name": "Pyone P Aye", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" + }, + { + "author_name": "Faith Schiro", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" + }, + { + "author_name": "Marissa Fahlberg", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" + }, + { + "author_name": "Dawn Szeltner", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" + }, + { + "author_name": "Skye Spencer", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" + }, + { + "author_name": "Brandon J Beddingfield", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" + }, + { + "author_name": "Kelly Goff", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" + }, + { + "author_name": "Nadia Golden", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" + }, + { + "author_name": "Toni Penney", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" + }, + { + "author_name": "Breanna Picou", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" + }, + { + "author_name": "Krystle Hensley", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" + }, + { + "author_name": "Kristin E Chandler", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" + }, + { + "author_name": "Jessica A Plante", + "author_inst": "World Reference Center for Emerging Viruses and Arboviruses, Institute for Human Infections and Immunity, University of Texas Medical Branch, Galveston, Texas" + }, + { + "author_name": "Kenneth S Plante", + "author_inst": "World Reference Center for Emerging Viruses and Arboviruses, Institute for Human Infections and Immunity, University of Texas Medical Branch, Galveston, Texas" + }, + { + "author_name": "Scott C Weaver", + "author_inst": "World Reference Center for Emerging Viruses and Arboviruses, Institute for Human Infections and Immunity, University of Texas Medical Branch, Galveston, Texas" + }, + { + "author_name": "Chad J Roy", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" + }, + { + "author_name": "James A Hoxie", + "author_inst": "Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania" + }, + { + "author_name": "Hongmei Gao", + "author_inst": "Duke University Medical Center, Duke Human Vaccine Institute, Durham, North Carolina" + }, + { + "author_name": "David C Montefiori", + "author_inst": "Duke University Medical Center, Duke Human Vaccine Institute, Durham, North Carolina" + }, + { + "author_name": "Joseph L Mankowski", + "author_inst": "Department of Molecular and Comparative Pathobiology, Johns Hopkins School of Medicine, Baltimore, Maryland" + }, + { + "author_name": "Rudolf P Bohm", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" + }, + { + "author_name": "Jay Rappaport", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" + }, + { + "author_name": "Nicholas J Maness", + "author_inst": "Tulane National Primate Research Center, Covington, Louisiana" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "transplantation" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.08.20.21261687", @@ -581941,25 +580286,37 @@ "category": "gastroenterology" }, { - "rel_doi": "10.1101/2021.08.26.21262655", - "rel_title": "Racial discrimination and covid-19 vaccine uptake: is mistrust of the health service behind vaccine refusal?", + "rel_doi": "10.1101/2021.08.25.21262586", + "rel_title": "Willingness and influential factors of parents to vaccinate their children against the COVID-19: a systematic review and meta-analysis", "rel_date": "2021-08-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.26.21262655", - "rel_abs": "ObjectiveTo examine whether racial/ethnic discrimination predicts future COVID-19 vaccine refusal, and whether this association is explained by trust in government and the health system.\n\nDesignLongitudinal observational study of racial/ethnic discrimination occurring since the start of the first lockdown (measured in July 2020) and later COVID-19 vaccine status.\n\nSettingUK (England, Scotland, Wales, and Northern Ireland)\n\nParticipants633 adults belonging to ethnic minority groups who took part in the UCL COVID-19 Social Study.\n\nMain outcome measureCOVID-19 vaccine refusal (vs accepted/waiting/had at least one dose) between 23 December 2020 and 14 June 2021.\n\nResultsNearly one in ten (6.7%) who had refused a COVID-19 vaccine had experienced racial/ethnic discrimination in a medical setting since the start of the pandemic and had experienced twice as many incidents of racial/ethnic discrimination than those who had accepted the vaccine. Structural equation modelling results indicated a nearly 4-fold (odds ratio [OR] = 3.9, 95% confidence interval [CI] = 1.4 to 10.9) total effect of racial/ethnic discrimination on refusing the vaccine was which was mediated by low trust in the health system to handle the pandemic (OR = 2.5, 95% CI = 1.1 to 5.4). Analyses adjusted for a range of demographic and COVID-19 related factors.\n\nConclusionsFindings underscore the importance of addressing racial/ethnic discrimination and the role the National Health Service in regaining trust from ethnic minority groups to increase COVID-19 vaccine uptake amongst ethnic minority adults.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.25.21262586", + "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19) vaccine uptake among children will be critical in limiting the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the disease. Parents are key decision-makers for whether their children will receive a COVID-19 vaccine.\n\nObjectiveTo estimate parents willingness to vaccinate their children against the COVID-19, and to investigate the predictors for their decision.\n\nMethodsWe followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines for this systematic review and meta-analysis. We searched Scopus, Web of Science, Medline, PubMed, ProQuest, and CINAHL from inception to August 11, 2021. The review protocol was registered with PROSPERO (CRD42021273125). We applied a random effect model to estimate pooled effects since the heterogeneity was very high. We used subgroup analysis and meta-regression analysis to explore sources of heterogeneity.\n\nResultsWe found 17 studies including 45,783 parents. The overall proportion of parents that intend to vaccinate their children against the COVID-19 was 56.8% (95% confidence interval: 51.8-61.8%). Parents willingness ranged from 29% to 72.7%. Studies quality, sample size, data collection time, and the continent that studies were conducted did not affect the results. The main predictors of parents intention to vaccinate their children against COVID-19 were male gender, older age of parents and children, higher socio-economic status, white race, positive attitudes toward vaccination, higher levels of knowledge, and higher levels of perceived threat from the COVID-19, worry, fear, and anxiety.\n\nConclusionsParents willingness to vaccinate their children against the COVID-19 is moderate and several factors affect this decision. Understanding parental COVID-19 vaccine hesitancy does help policy makers to change the stereotypes and establish broad community COVID-19 vaccination. Identification of the factors that affect parents willingness to vaccinate their children against COVID-19 will provide opportunities to enhance parents trust in the COVID-19 vaccines and optimize childrens uptake of a COVID-19 vaccine.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Elise Paul", - "author_inst": "University College London" + "author_name": "Petros Galanis", + "author_inst": "National and Kapodistrian University of Athens" }, { - "author_name": "Daisy Fancourt", - "author_inst": "University College London" + "author_name": "Irene Vraka", + "author_inst": "P & A Kyriakou Children's Hospital" }, { - "author_name": "Mohammad Razai", - "author_inst": "St George's University" + "author_name": "Olga Siskou", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Olympia Konstantakopoulou", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Aglaia Katsiroumpa", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Daphne Kaitelidou", + "author_inst": "National and Kapodistrian University of Athens" } ], "version": "1", @@ -584147,79 +582504,23 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.08.24.21262475", - "rel_title": "Evaluation of commercial anti-SARS-CoV-2 antibody assays and comparison of standardized titers in vaccinated healthcare workers.", + "rel_doi": "10.1101/2021.08.24.21262517", + "rel_title": "Infection inhibiting effect of RT-PCR testing-isolation in COVID-19 - a case study of Hiroshima and Fukuoka in Japan -", "rel_date": "2021-08-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.24.21262475", - "rel_abs": "With the availability of vaccines, commercial assays detecting anti-SARS-CoV-2 antibodies (Ab) evolved towards quantitative assays directed to the spike glycoprotein or its receptor binding domain (RBD). The main objective of the present study was to compare the Ab titers obtained with quantitative commercial binding Ab assays, after 1 dose (convalescent individuals) or 2 doses (naive individuals) of vaccine, in healthcare workers (HCW).\n\nAntibody titers were measured in 255 sera (from 150 HCW) with 5 quantitative immunoassays (Abbott RBD IgG II quant, bioMerieux RBD IgG, DiaSorin Trimeric spike IgG, Siemens Healthineers RBD IgG, Wantai RBD IgG). One qualitative total antibody anti RBD detection assay (Wantai) was used to detect previous infection before vaccination. The results are presented in binding Ab units (BAU)/mL after application, when possible, of a conversion factor provided by the manufacturers and established from a World Health Organization (WHO) internal standard.\n\nThere was a 100% seroconversion with all assays evaluated after two doses of vaccine. With assays allowing BAU/ml correction, Ab titers were correlated (Pearson correlation coefficient, {rho}, range: 0.85-0.94). The titer differences varied by a mean of 10.6% between Siemens and bioMerieux assays to 60.9% between Abbott and DiaSorin assays. These results underline the importance of BAU conversion for the comparison of Ab titer obtained with the different quantitative assays. However, significant differences persist, notably, between kits detecting Ab against the different antigens.\n\nA true standardization of the assays would be to include the International Standard in the calibration of each assays to express the results in IU/mL.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.24.21262517", + "rel_abs": "A simple method of estimating the effect of reverse transcription polymerase chain reaction (RT-PCR) testing-isolation on the restraint of infection of COVID-19 is proposed. The effect is expressed as the ratio{chi} of the reproductive number to that in the case that no isolation measure would be taken. The method was applied in the case of the third infection wave (from December, 2020 to February, 2021) of Hiroshima and Fukuoka in Japan. The ratio{chi} was estimated to be 0.78 to 0.84 and 0.86 to 0.9 in Hiroshima and Fukuoka, respectively. It is also shown that the reduction of{chi} by 0.07 would have reduced at least 50% of total infected patients during the third infection wave in Fukuoka.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Kahina Saker", - "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C" - }, - { - "author_name": "Vanessa Escuret", - "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C" - }, - { - "author_name": "Virginie Pitiot", - "author_inst": "Occupational Health and Medicine Department, Hospices Civils de Lyon, Lyon, France" - }, - { - "author_name": "Amelie Massardier-Pilonchery", - "author_inst": "Occupational Health and Medicine Department, Hospices Civils de Lyon, Lyon, France" - }, - { - "author_name": "Stephane Paul", - "author_inst": "Laboratory of Immunology and Immunomonitoring, CIC 1408 INSERM, GIMAP EA3064, University Hospital of Saint-Etienne, F-42055, Saint-Etienne cedex 2, France" - }, - { - "author_name": "Bouchra Mokdad", - "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C" - }, - { - "author_name": "Carole Langlois-Jacques", - "author_inst": "CNRS, UMR 5558, University of Lyon, Laboratoire de Biometrie et Biologie Evolutive, Equipe Biostatistique-Sante, F-69100, Villeurbanne, France" - }, - { - "author_name": "Muriel Rabilloud", - "author_inst": "CNRS, UMR 5558, University of Lyon, Laboratoire de Biometrie et Biologie Evolutive, Equipe Biostatistique-Sante, F-69100, Villeurbanne, France" - }, - { - "author_name": "David Goncalves", - "author_inst": "Immunology Department, Lyon Sud Hospital, Hospices Civils de Lyon, F69495, Pierre-Benite cedex, France" - }, - { - "author_name": "Nicole Fabien", - "author_inst": "Immunology Department, Lyon Sud Hospital, Hospices Civils de Lyon, F69495, Pierre-Benite cedex, France" - }, - { - "author_name": "Nicolas Guibert", - "author_inst": "Occupational Health and Medicine Department, Hospices Civils de Lyon, Lyon, France" - }, - { - "author_name": "Jean-Baptiste Fassier", - "author_inst": "Occupational Health and Medicine Department, Hospices Civils de Lyon, Lyon, France" - }, - { - "author_name": "Antonin Bal", - "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C" - }, - { - "author_name": "Sophie Trouillet-Assant", - "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C" - }, - { - "author_name": "Mary-Anne Trabaud", - "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C" + "author_name": "Kazuo Maki", + "author_inst": "MediEco R&D Corporation" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.08.23.21262477", @@ -586265,67 +584566,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.08.18.21261804", - "rel_title": "SARS-CoV-2 susceptibility and ACE2 gene variations within diverse ethnic backgrounds", + "rel_doi": "10.1101/2021.08.23.21262162", + "rel_title": "Evaluation of the relationship between quantitative PCR results and cell culturing of SARS2-CoV with respect to symptoms onset and Viral load - a systematic review", "rel_date": "2021-08-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.18.21261804", - "rel_abs": "BackgroundHost genetics play a major role in COVID-19 susceptibility and severity. Here, we analyse an ethnically diverse cohort of National Health Service (NHS) patients in the United Kingdom (UK) to assess the association between variants in the ACE2 locus and COVID-19 risk.\n\nMethodsWe analysed whole-genome sequencing (WGS) data of 6,274 participants who were tested for SARS-CoV-2 from the UKs 100,000 Genomes Project (100KGP) for the presence of ACE2 coding variants and expression quantitative trait loci (eQTLs).\n\nFindingsWe identified a splice site variant (rs2285666) associated with increased ACE2 expression with an overrepresentation in SARS-CoV-2 positive patients relative to 100KGP controls (p = .015), and in hospitalised European patients relative to outpatients in intra-ethnic comparisons (p = .029). We also compared the prevalence of 288 eQTLs, of which 23 were enriched in SARS-CoV-2 positive patients. The eQTL rs12006793 had the largest effect size (d = 0.91), which decreases ACE2 expression and is more prevalent in controls, thus potentially reducing risk of COVID-19. We identified three novel nonsynonymous variants predicted to alter ACE2 function, and showed that three variants (p.K26R, p.H378R, p.Y515N) alter receptor affinity for the viral Spike (S) protein. Variants p.K26R and p.N720D are more prevalent in the European population (p < .001), but Y497H is less prevalent compared to East Asians (p = .020).\n\nInterpretationOur results demonstrate that the spectrum of genetic variants in ACE2 may inform risk stratification of COVID-19 patients and could partially explain the differences in disease susceptibility and severity among different ethnic groups.\n\nFundingThe 100KGP is funded by the National Institute for Health Research and NHS England. Funding was also obtained from Stanford University, Palo Alto.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.23.21262162", + "rel_abs": "BackgroundViral culture is currently the most accurate method to demonstrate viability and infectivity of Severe acute respiratory syndrome Coronavirus (SARS-2 CoV). Routine clinical diagnosis, however, is mostly performed by PCR - based assays that do not discriminate between infectious and non-virus. Herein, we aimed to determine the correlation between positive viral cultures and either PCR positivity, the Cycle Threshold (Ct) or the number of viral copies.\n\nMethodsA systematic electronic literature search was performed and studies that reported both viral SARS-CoV-2 culture and PCR-based assays were included. A separate search for samples from blood, urine, stool, breast milk and tears were performed. To convert Ct values reported in the reviewed studies were to viral genomic copies, calibration experiments with four different reaction performed, using quantified RNA molecules.\n\nResultsA total 540 articles were reviewed, and 38 studies were included in this review. Out of 276 positive-culture of non-severe patients, 272 (98.55%) were negative ten days after symptoms onset, while PCR assays remained positive for up to 67 days. In severely ill or immunocompromised patients positive-culture was obtained up to 32 days and out of 168 cultures, 31 (18.45%) stayed positive after day 10. In non-severe patients, in Ct value greater than 30 only 10.8% were still culture-positive while in Ct >35 it was nearly universally negative. The minimal calculated number of viral genome copies in culture-positive sample was 2.5 x 103 copies / mL. These findings were similar in immunocompromised patients. Recovering positive culture from non-respiratory samples was sporadically obtained in stool or urine samples. Conversion of Ct values to viral genome copies showed variability between different PCR assays and highlighted the need to standardize reports to correctly compare results obtained in different laboratories.\n\nConclusionDuring the pandemic phase, non-severe COVID-19 patients who are recovering and are not immuno-suppressed, can be regarded as non-infectious, within 10 days from symptom onset, or with Ct value greater than 35 (or a calculated viral load lower than 1.2x103 copies / mL). These findings have important implications for recovering patients and asymptomatic patients, with respect to isolation criteria. The conversion of Cq values to viral genome copies described herein may be useful in future work, enabling a more standardized comparison between results reported in different studies from different laboratories.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Nirmal Vadgama", - "author_inst": "Stanford University" - }, - { - "author_name": "Alexander Kreymerman", - "author_inst": "Harvard University" - }, - { - "author_name": "Jackie Campbell", - "author_inst": "University of Northampton" + "author_name": "gilad rozenberg", + "author_inst": "rambam health care campus haifa" }, { - "author_name": "Olga Shamardina", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Christiane Brugger", - "author_inst": "Brown University" - }, - { - "author_name": "- Genomics England Research Consortium", - "author_inst": "" - }, - { - "author_name": "Richard T. Lee", - "author_inst": "Harvard University" - }, - { - "author_name": "Christopher J. Penkett", - "author_inst": "University of Cambridge" + "author_name": "Oran Erster", + "author_inst": "sheba Medical Center, Tel Hashomer, Ramat-Gan, Israel." }, { - "author_name": "Casey A. Gifford", - "author_inst": "Stanford University" + "author_name": "Itai Ghersin", + "author_inst": "rambam health care campus, haifa, israel" }, { - "author_name": "Mark Mercola", - "author_inst": "Stanford University" + "author_name": "Michal Mandelboim", + "author_inst": "Sheba Medical Center, Tel Hashomer, Ramat-Gan, Israel" }, { - "author_name": "Jamal Nasir", - "author_inst": "University of Northampton" + "author_name": "Ami neuberger", + "author_inst": "rambam health care campus, haifa, israel" }, { - "author_name": "Ioannis Karakikes", - "author_inst": "Stanford University" + "author_name": "Eli Schwartz", + "author_inst": "Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel." } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.08.19.21262139", @@ -588078,83 +586355,35 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2021.08.19.21262231", - "rel_title": "Symptoms and SARS-CoV-2 positivity in the general population in the UK", + "rel_doi": "10.1101/2021.08.17.21262193", + "rel_title": "Dynamics of the Third wave, modelling COVID-19 pandemic with an outlook towards India", "rel_date": "2021-08-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.19.21262231", - "rel_abs": "BackgroundSeveral community-based studies have assessed the ability of different symptoms to identify COVID-19 infections, but few have compared symptoms over time (reflecting SARS-CoV-2 variants) and by vaccination status.\n\nMethodsUsing data and samples collected by the COVID-19 Infection Survey at regular visits to representative households across the UK, we compared symptoms in new PCR-positives and comparator test-negative controls.\n\nResultsFrom 26/4/2020-7/8/2021, 27,869 SARS-CoV-2 PCR-positive episodes occurred in 27,692 participants (median 42 years (IQR 22-58)); 13,427 (48%) self-reported symptoms (\"symptomatic positive episodes\"). The comparator group comprised 3,806,692 test-negative visits (457,215 participants); 130,612 (3%) self-reported symptoms (\"symptomatic negative visit\"). Reporting of any symptoms in positive episodes varied over calendar time, reflecting changes in prevalence of variants, incidental changes (e.g. seasonal pathogens, schools re-opening) and vaccination roll-out. There was a small increase in sore throat reporting in symptomatic positive episodes and negative visits from April-2021. After May-2021 when Delta emerged there were substantial increases in headache and fever in positives, but not in negatives. Although specific symptom reporting in symptomatic positive episodes vs. negative visits varied by age, sex, and ethnicity, only small improvements in symptom-based infection detection were obtained; e.g. adding fatigue/weakness or all eight symptoms to the classic four symptoms (cough, fever, loss of taste/smell) increased sensitivity from 74% to 81% to 90% but tests per positive from 4.6 to 5.3 to 8.7.\n\nConclusionsWhilst SARS-CoV-2-associated symptoms vary by variant, vaccination status and demographics, differences are modest and do not warrant large-scale changes to targeted testing approaches given resource implications.\n\nSummaryWithin the COVID-19 Infection Survey, recruiting representative households across the UK general population, SARS-CoV-2-associated symptoms varied by viral variant, vaccination status and demographics. However, differences are modest and do not currently warrant large-scale changes to targeted testing approaches.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.17.21262193", + "rel_abs": "Since 2020, the COVID-19 pandemic has devastated human civilization throughout the earth. The pandemic is returning in different waves because of constant changes in the genetic components of the virus. Had we been able to predict the nature and timing of these waves earlier, numerous lives could, in essence, have been saved. It is evident that the situation has spiraled out of control in several countries for want of proper preventive measures. In this article, we described a comprehensive mathematical approach to understand the nature of the pandemic waves. Also, we determined the probable timing of the third wave that will help the concerned government(s) to take the necessary steps to better prepare for the unforeseen situation.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Karina-Doris Vihta", - "author_inst": "University of Oxford" - }, - { - "author_name": "Koen B. Pouwels", - "author_inst": "University of Oxford" - }, - { - "author_name": "Tim Peto", - "author_inst": "University of Oxford" - }, - { - "author_name": "Emma Pritchard", - "author_inst": "University of Oxford" - }, - { - "author_name": "David W. Eyre", - "author_inst": "University of Oxford" - }, - { - "author_name": "Thomas House", - "author_inst": "University of Manchester" - }, - { - "author_name": "Owen Gethings", - "author_inst": "Office for National Statistics" - }, - { - "author_name": "Ruth Studley", - "author_inst": "Office for National Statistics" - }, - { - "author_name": "Emma Rourke", - "author_inst": "Office for National Statistics" - }, - { - "author_name": "Duncan Cook", - "author_inst": "Office for National Statistics" - }, - { - "author_name": "Ian Diamond", - "author_inst": "Office for National Statistics" - }, - { - "author_name": "Derrick Crook", - "author_inst": "University of Oxford" - }, - { - "author_name": "Philippa C. Matthews", - "author_inst": "University of Oxford" + "author_name": "Ayanava Basak", + "author_inst": "Department of Mathematics, Jadavpur University, Kolkata 700032, India" }, { - "author_name": "Nicole Stoesser", - "author_inst": "University of Oxford" + "author_name": "Sayanur Rahaman", + "author_inst": "Biozentrum, University of Basel, 4056 Basel, Switzerland" }, { - "author_name": "Ann Sarah Walker", - "author_inst": "University of Oxford" + "author_name": "Abhishek Guha", + "author_inst": "Department of Neurology, University of Alabama at Birmingham, Birmingham, AL 35294, USA" }, { - "author_name": "- COVID-19 Infection Survey team", - "author_inst": "" + "author_name": "Tanmay Sanyal", + "author_inst": "Department of Zoology, Krishnagar Government College, Krishnagar 741101, India" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.08.16.21262150", @@ -590016,199 +588245,51 @@ "category": "pathology" }, { - "rel_doi": "10.1101/2021.08.23.457229", - "rel_title": "mRNA Vaccination Induces Durable Immune Memory to SARS-CoV-2 with Continued Evolution to Variants of Concern", + "rel_doi": "10.1101/2021.08.22.457295", + "rel_title": "Intra-host SARS-CoV-2 evolution in the gut of mucosally-infected Chlorocebus aethiops (African green monkeys)", "rel_date": "2021-08-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.23.457229", - "rel_abs": "SARS-CoV-2 mRNA vaccines have shown remarkable efficacy, especially in preventing severe illness and hospitalization. However, the emergence of several variants of concern and reports of declining antibody levels have raised uncertainty about the durability of immune memory following vaccination. In this study, we longitudinally profiled both antibody and cellular immune responses in SARS-CoV-2 naive and recovered individuals from pre-vaccine baseline to 6 months post-mRNA vaccination. Antibody and neutralizing titers decayed from peak levels but remained detectable in all subjects at 6 months post-vaccination. Functional memory B cell responses, including those specific for the receptor binding domain (RBD) of the Alpha (B.1.1.7), Beta (B.1.351), and Delta (B.1.617.2) variants, were also efficiently generated by mRNA vaccination and continued to increase in frequency between 3 and 6 months post-vaccination. Notably, most memory B cells induced by mRNA vaccines were capable of cross-binding variants of concern, and B cell receptor sequencing revealed significantly more hypermutation in these RBD variant-binding clones compared to clones that exclusively bound wild-type RBD. Moreover, the percent of variant cross-binding memory B cells was higher in vaccinees than individuals who recovered from mild COVID-19. mRNA vaccination also generated antigen-specific CD8+ T cells and durable memory CD4+ T cells in most individuals, with early CD4+ T cell responses correlating with humoral immunity at later timepoints. These findings demonstrate robust, multi-component humoral and cellular immune memory to SARS-CoV-2 and current variants of concern for at least 6 months after mRNA vaccination. Finally, we observed that boosting of pre-existing immunity with mRNA vaccination in SARS-CoV-2 recovered individuals primarily increased antibody responses in the short-term without significantly altering antibody decay rates or long-term B and T cell memory. Together, this study provides insights into the generation and evolution of vaccine-induced immunity to SARS-CoV-2, including variants of concern, and has implications for future booster strategies.\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=146 HEIGHT=200 SRC=\"FIGDIR/small/457229v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (32K):\norg.highwire.dtl.DTLVardef@16c64b1org.highwire.dtl.DTLVardef@146ca3aorg.highwire.dtl.DTLVardef@86b7edorg.highwire.dtl.DTLVardef@956879_HPS_FORMAT_FIGEXP M_FIG C_FIG", - "rel_num_authors": 45, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.22.457295", + "rel_abs": "In recent months, several SARS-CoV-2 variants have emerged that enhance transmissibility and escape host humoral immunity. Hence, the tracking of viral evolutionary trajectories is clearly of great importance. Little is known about SARS-CoV-2 evolution in nonhuman primate models used to test vaccines and therapies and to model human disease. Viral RNA was sequenced from rectal swabs from Chlorocebus aethiops (African green monkeys) after experimental respiratory SARS-CoV-2 infection. Two distinct patterns of viral evolution were identified that were shared between all collected samples. First, mutations in the furin cleavage site that were initially present in the virus as a consequence of VeroE6 cell culture adaptation were subsequently lost in virus recovered in rectal swabs, confirming the necessity of this motif for viral infection in vivo. Three amino acid changes were also identified; ORF 1a S2103F, and spike D215G and H655Y, that were detected in rectal swabs from all sampled animals. These findings are demonstrative of intra-host SARS-CoV-2 evolution unique to this nonhuman primate species and may identify a host-adapted variant of SARS-CoV-2 that would be useful in future development of primate disease models.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Rishi R Goel", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Mark M Painter", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Sokratis A Apostolidis", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Divij Mathew", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Wenzhao Meng", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Aaron M Rosenfeld", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Kendall A Lundgreen", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Arnold Reynaldi", - "author_inst": "University of New South Wales" - }, - { - "author_name": "David S Khoury", - "author_inst": "University of New South Wales" - }, - { - "author_name": "Ajinkya Pattekar", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Sigrid Gouma", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Leticia Kuri-Cervantes", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Philip Hicks", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Sarah Dysinger", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Amanda Hicks", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Harsh Sharma", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Sarah Herring", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Scott Korte", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Amy E Baxter", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Derek A Oldridge", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Josephine R Giles", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Madison E Weirick", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Christopher M McAllister", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Moses Awofolaju", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Nicole Tanenbaum", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Elizabeth M Drapeau", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Jeanette Dougherty", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Sherea Long", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Jacob T Hamilton", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Maura McLaughlin", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Justine C Williams", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Sharon Adamski", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "- The UPenn COVID Processing Unit", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Oliva Kuthuru", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Ian Frank", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Michael R Betts", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Alba Grifoni", - "author_inst": "La Jolla Institute for Immunology" - }, - { - "author_name": "Daniela Weiskopf", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Lori A Rowe", + "author_inst": "Tulane National Primate Research Center" }, { - "author_name": "Alessandro Sette", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Brandon J Beddingfield", + "author_inst": "Tulane National Primate Research Center" }, { - "author_name": "Scott E Hensley", - "author_inst": "University of Pennsylvania" + "author_name": "Kelly Goff", + "author_inst": "Tulane National Primate Research Center" }, { - "author_name": "Miles P Davenport", - "author_inst": "University of New South Wales" + "author_name": "Stephanie Z Killeen", + "author_inst": "Tulane National Primate Research Center" }, { - "author_name": "Paul Bates", - "author_inst": "University of Pennsylvania" + "author_name": "Nicole R Chirichella", + "author_inst": "Tulane National Primate Research Center" }, { - "author_name": "Eline T Luning Prak", - "author_inst": "University of Pennsylvania" + "author_name": "Alexandra Melton", + "author_inst": "Tulane National Primate Research Center" }, { - "author_name": "Allison R Greenplate", - "author_inst": "University of Pennsylvania" + "author_name": "CHAD J ROY", + "author_inst": "Tulane University School of Medicine" }, { - "author_name": "E. John Wherry", - "author_inst": "University of Pennsylvania" + "author_name": "Nicholas J Maness", + "author_inst": "Tulane National Primate Research Center" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.08.23.457408", @@ -591918,71 +589999,63 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.08.19.21262314", - "rel_title": "Inhaled nitric oxide use in COVID19-induced hypoxemic respiratory failure.", - "rel_date": "2021-08-21", + "rel_doi": "10.1101/2021.08.15.21262077", + "rel_title": "Infection with the SARS-CoV-2 Delta Variant is Associated with Higher Infectious Virus Loads Compared to the Alpha Variant in both Unvaccinated and Vaccinated Individuals", + "rel_date": "2021-08-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.19.21262314", - "rel_abs": "IntroductionNitric Oxide (NO) is an endogenous vasodilator that is synthesized by the vascular endothelium. Due to its vasodilatory effect and short half-life, the use of NO as an exogenous inhaled medication (iNO) to target the pulmonary vasculature, in conditions with increased pulmonary vascular resistance, has been studied.\n\nThe use of iNO in patients with ARDS secondary to COVID-19 has therapeutic importance in improving oxygenation. It also has potential anti-viral, anti-inflammatory, and anti-thrombotic properties.\n\nHerein, we want to share our experience of use of iNO in hypoxemic respiratory failure secondary to COVID 19 pneumonia. We hypothesized that iNO may be beneficial at preventing intubation, decreasing invasive mechanical ventilation duration, and consequently improve outcomes including hospital mortality.\n\nMethodsThis is a descriptive hypothesis generating study of patients admitted for COVID-19 pneumonia who received iNO for hypoxemic respiratory failure, at a single tertiary care center. We collected information on patient demographics, co-morbidities, iNO treatment, need for intubation, arterial blood gas analysis, laboratory values, hospital length of stay, and mortality. Patients were divided into two groups based on the timing of iNO administration: group 1 - \"pre-intubation\" (i.e. iNO started at least 1 day prior to endotracheal intubation, if any) and group 2 - \"post-intubation\" (i.e. iNO started on the same day as or after endotracheal intubation and mechanical ventilation).\n\nResultA total of 45 (group 1, n=26 [57.8%] vs group2, n=19 [42.2%]) COVID 19 patients who had iNO use. The mean time from hospital admission to iNO administration(days) in group 1 was 2.1 ({+/-}1.8) vs 4.2 ({+/-}5.9) in group 2. The mean hospital length of stay from the beginning of iNO treatment until discharge or death was 18.3 vs 26.2 days, with 8 deaths (30.8%) vs 9 deaths (47.4%) in group 1 vs group 2, respectively.\n\nDiscussionOur study is unable to demonstrate comparably outcomes benefit of iNO. Although there was a trend towards decreased need for invasive mechanical ventilation in group 1[Only 11 (42.3%) patients were intubated out of 26 who received iNO early after hospital admission (2.3 days)], no statistical significance could be achieved because of small sample size.\n\nOur study demonstrated that iNO administration pre-intubation did not appear harmful and appears to be safe, complementary to HFNC, signalling the domain where systematic investigation is required to confirm or not the potential for iNO to improve patient outcomes in the management of COVID 19-induced hypoxemic respiratory failure.\n\nConclusionThis study showcases the potential benefit of early pre-intubation use of iNO in COVID patients with hypoxemic respiratory failure. This study could conclusively form the basis for a prospective trial and could have a tremendous impact in improving patient outcomes.\n\nHighlightsO_LIInhaled nitric oxide can be used in the treatment COVID 19 induced hypoxemic respiratory failure.\nC_LIO_LIInhaled nitric oxide use can lower the burden on overwhelmed medical system.\nC_LIO_LIInhaled nitric oxide use may lower the need for intubation and subsequent invasive mechanical ventilation.\nC_LI", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.15.21262077", + "rel_abs": "BackgroundThe emerging SARS-CoV-2 variant of concern (VOC) B.1.6.17.2 (Delta) quickly displaced the B.1.1.7 (Alpha) and is associated with increases in COVID-19 cases nationally. The Delta variant has been associated with greater transmissibility and higher viral RNA loads in both unvaccinated and fully vaccinated individuals. Data is lacking regarding the infectious virus load in Delta infected individuals and how that compares to individuals infected with other SARS-CoV-2 lineages.\n\nMethodsWhole genome sequencing of 2,785 clinical isolates was used to characterize the prevalence of SARS-CoV-2 lineages circulating in the National Capital Region between January and July 2021. Clinical chart reviews were performed for the Delta, Alpha, and B.1.2 (a control predominant lineage prior to both VOCs) variants to evaluate disease severity and outcome and Cycle threshold values (Cts) were compared. The presence of infectious virus was determined using Vero-TMPRSS2 cells and anti-SARS-CoV-2 IgG levels were determined from upper respiratory specimen. An analysis of infection in unvaccinated and fully vaccinated populations was performed.\n\nResultsThe Delta variant displaced the Alpha variant to constitute 88.2% of the circulating lineages in the National Capital Region by July, 2021. The Delta variant associated with increased breakthrough infections in fully vaccinated individuals that were mostly symptomatic when compared to the Alpha breakthrough infections, though it is important to note there was a significantly longer period of time between vaccination and infection with Delta infections. The recovery of infectious virus on cell culture was significantly higher with the Delta variant compared to Alpha in both vaccinated and unvaccinated groups. The impact of vaccination on reducing the recovery of infectious virus from clinical samples was only observed with Alpha variant infections but was strongly associated with low localized SARS-CoV-2 IgG for both variants. A comparison of Ct values showed a significant decrease in the Delta compared to Alpha with no significant differences between unvaccinated and vaccinated groups.\n\nConclusionsOur data indicate that the Delta variant is associated with increased infectious virus loads when compared to the Alpha variant and decreased upper respiratory antiviral IgG levels. Measures to reduce transmission in addition to increasing vaccinations rates have to be implemented to reduce Delta variant spread.\n\nFundingNIH/NIAID Center of Excellence in Influenza Research and Surveillance contract HHS N2772201400007C, Johns Hopkins University, Maryland department of health, Centers for Disease Control and Prevention contract 75D30121C11061.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Abhishek R. Giri", - "author_inst": "Mayo Clinic, Jacksonville, Florida" - }, - { - "author_name": "Siva Naga S. Yarrarapu", - "author_inst": "Mayo Clinic, Jacksonville, Florida." - }, - { - "author_name": "Nirmaljot Kaur", - "author_inst": "Mayo Clinic, Jacksonville, Florida" + "author_name": "Chun Huai Luo", + "author_inst": "Johns Hopkins School of Medicine" }, { - "author_name": "Alexander P. Hochwald", - "author_inst": "Mayo Clinic, Jacksonville, Florida." + "author_name": "C. Paul Morris", + "author_inst": "Johns Hopkins School of Medicine" }, { - "author_name": "Julia Crook", - "author_inst": "Mayo Clinic, Jacksonville, Florida." + "author_name": "Jaiprasath Sachithanandham", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" }, { - "author_name": "Scott Helgeson", - "author_inst": "Mayo Clinic, Jacksonville, Florida." + "author_name": "Adannaya Amadi", + "author_inst": "Johns Hopkins School of Medicine" }, { - "author_name": "Michael F. Harrison", - "author_inst": "Mayo Clinic, Jacksonville, Florida" + "author_name": "David Gaston", + "author_inst": "Johns Hopkins School of Medicine" }, { - "author_name": "Neal Patel", - "author_inst": "Mayo Clinic, Jacksonville, Florida." + "author_name": "Maggie Li", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" }, { - "author_name": "Pramod K. Guru", - "author_inst": "Mayo Clinic, Jacksonville, Florida." + "author_name": "Nicholas J Swanson", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" }, { - "author_name": "Philip Lowman", - "author_inst": "Mayo Clinic, Jacksonville, Florida." + "author_name": "Matthew Schwartz", + "author_inst": "Johns Hopkins School of Medicine" }, { - "author_name": "Pablo Moreno-Franco", - "author_inst": "Mayo Clinic, Jacksonville, Florida" + "author_name": "Eili Y Klein", + "author_inst": "Johns Hopkins School of Medicine" }, { - "author_name": "Augustine Lee", - "author_inst": "Mayo Clinic, Jacksonville, Florida." + "author_name": "Andrew Pekosz", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" }, { - "author_name": "Devang K. Sanghavi", - "author_inst": "Mayo Clinic, Jacksonville, Florida" + "author_name": "Heba H Mostafa", + "author_inst": "Johns Hopkins School of Medicine" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.08.14.21262042", @@ -593684,143 +591757,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.13.21261889", - "rel_title": "Robust SARS-CoV-2-specific and heterologous immune responses after natural infection in elderly residents of Long-Term Care Facilities", + "rel_doi": "10.1101/2021.08.13.21261939", + "rel_title": "EXCESS DEATHS FROM ALL CAUSES AND BY COVID-19 IN BRAZIL IN 2020", "rel_date": "2021-08-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.13.21261889", - "rel_abs": "Long term care facilities (LTCF) provide residential and/or nursing care support for frail and elderly people and many have suffered from a high prevalence of SARS-CoV-2 infection. Although mortality rates have been high in LTCF residents there is little information regarding the features of SARS-CoV-2-specific immunity after infection in this setting or how this may influence immunity to other infections. We studied humoral and cellular immunity against SARS-CoV-2 in 152 LTCF staff and 124 residents over a prospective 4-month period shortly after the first wave of infection and related viral serostatus to heterologous immunity to other respiratory viruses and systemic inflammatory markers. LTCF residents developed high levels of antibodies against spike protein and RBD domain which were stable over 4 months of follow up. Nucleocapsid-specific responses were also elevated in elderly donors but showed waning across all populations. Antibodies showed stable and equivalent levels of functional inhibition against spike-ACE2 binding in all age groups with comparable activity against viral variants of concern. SARS-CoV-2 seropositive donors showed high levels of antibodies to other beta-coronaviruses but serostatus did not impact humoral immunity to influenza or RSV. SARS-CoV-2-specific cellular responses were equivalent across the life course but virus-specific populations showed elevated levels of activation in older donors. LTCF residents who are survivors of SARS-CoV-2 infection thus show robust and stable immunity which does not impact responses to other seasonal viruses. These findings augur well for relative protection of LTCF residents to re-infection. Furthermore, they underlie the potent influence of previous infection on the immune response to Covid-19 vaccine which may prove to be an important determinant of future vaccine strategy.\n\nOne sentence summeryCare home residents show waning of nucleocapsid specific antibodies and enhanced expression of activation markers on SARS-CoV-2 specific cells", - "rel_num_authors": 31, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.13.21261939", + "rel_abs": "ObjectiveTo estimate the 2020 all-cause and COVID-19 excess mortality according to sex, age, race/color, and state, and to compare mortality rates by selected causes with that of the five previous years in Brazil.\n\nMethodsData from the Mortality Information System were used. Expected deaths for 2020 were estimated from 2015 to 2019 data using a negative binomial log-linear model.\n\nResultsExcess deaths in Brazil in 2020 amounted to 13.7%, and the ratio of excess deaths to COVID-19 deaths was 0.90. Reductions in deaths from cardiovascular diseases (CVD), respiratory diseases, and external causes, and an increase in ill-defined causes were all noted. Excess deaths were also found to be heterogeneous, being higher in the Northern, Center-Western, and Northeastern states. In some states, the number of COVID-19 deaths was lower than that of excess deaths, whereas the opposite occurred in others. Moreover, excess deaths were higher in men, in those aged 20 to 59, and in black, yellow, or indigenous individuals. Meanwhile, excess mortality was lower in women, individuals aged 80 years or older, and in whites. Additionally, deaths among those aged 0 to 19 were 7.2% lower than expected, with reduction in mortality from respiratory diseases and external causes. There was also a drop in mortality due to external causes in men and in those aged 20 to 39 years. Furthermore, reductions in deaths from CVD and neoplasms were noted in some states and groups.\n\nConclusionThere is evidence of underreporting of COVID-19 deaths and of the possible impact of restrictive measures in the reduction of deaths from external causes and respiratory diseases. The impacts of COVID-19 on mortality were heterogeneous among the states and groups, revealing that regional, demographic, socioeconomic, and racial differences expose individuals in distinct ways to the risk of death from both COVID-19 and other causes.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Gokhan Tut", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Tara Lancaster", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Megan S Butler", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Panagiota Sylla", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Eliska Spalkova", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "David Bone", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Nayandeep Kaur", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Christopher Bentley", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Umayr Amin", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Azar T Jadir", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Samuel Hulme", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Morenike Ayodele", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Alexander C Dowell", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Hayden Pearce", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Sandra Margielewska-Davies", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Kriti Verma", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Samantha Nicol", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Jusnara Begum", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Elizabeth Jinks", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Elif Tut", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Rachel Bruton", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" + "author_name": "Alcione Miranda dos Santos", + "author_inst": "Federal University of Maranhao. Postgraduate Program in Public Health." }, { - "author_name": "Maria Krutikov", - "author_inst": "UCL Institute of Health Informatics, London, UK" + "author_name": "Bruno Feres de Souza", + "author_inst": "Federal University of Maranhao. Computer Engineering Deparment" }, { - "author_name": "Madhumita Shrotri", - "author_inst": "UCL Institute of Health Informatics, London, UK" + "author_name": "Carolina Abreu de Carvalho", + "author_inst": "Federal University of Maranhao. Postgraduate Program in Public Health." }, { - "author_name": "Rebecca Giddings", - "author_inst": "UCL Institute of Health Informatics, London, UK" + "author_name": "Marcos Adriano Garcia Campos", + "author_inst": "Federal University of Maranhao. Postgraduate Program in Public Health." }, { - "author_name": "Borscha Azmi", - "author_inst": "UCL Institute of Health Informatics, London, UK" + "author_name": "Bruno Luciano Carneiro Alves de Oliveira", + "author_inst": "Federal University of Maranhao. Postgraduate Program in Public Health." }, { - "author_name": "Chris Fuller", - "author_inst": "UCL Institute of Health Informatics, London, UK" + "author_name": "Eduardo Moraes Diniz", + "author_inst": "Federal University of Maranhao. Physics Department." }, { - "author_name": "Aidan Irwin-Singer", - "author_inst": "Department of Health and Social Care, London, UK" + "author_name": "Maria dos Remedios Freitas Carvalho Branco", + "author_inst": "Federal University of Maranhao. Postgraduate Program in Public Health." }, { - "author_name": "Andrew Hayward", - "author_inst": "Health Data Research UK" + "author_name": "Rejane Christine de Sousa Queiroz", + "author_inst": "Federal University of Maranhao. Postgraduate Program in Public Health." }, { - "author_name": "Andrew Copas", - "author_inst": "UCL Institute for Global Health, London, UK" + "author_name": "Vitoria Abreu de Carvalho", + "author_inst": "Federal University of Maranhao" }, { - "author_name": "Laura Shallcross", - "author_inst": "UCL Institute of Health Informatics, London, UK" + "author_name": "Waleska Regina Machado Araujo", + "author_inst": "Sao Paulo University. Preventive Medicine Department." }, { - "author_name": "Paul Moss", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" + "author_name": "Antonio Augusto Moura da Silva", + "author_inst": "Federal University of Maranhao. Postgraduate Program in Public Health." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.08.13.21262039", @@ -595378,65 +593371,41 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.08.16.21262044", - "rel_title": "Rapid initiation of nasal saline irrigation: hospitalizations in COVID-19 patients randomized to alkalinization or povidone-iodine compared to a national dataset", + "rel_doi": "10.1101/2021.08.13.21262021", + "rel_title": "Immunogenicity and safety of inactivated whole virion Coronavirus vaccine with CpG (VLA2001) in healthy adults aged 18 to 55: a randomised phase 1 /2 clinical trial", "rel_date": "2021-08-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.16.21262044", - "rel_abs": "ImportanceSARS-CoV-2 enters the nasopharynx to replicate; nasal irrigation soon after diagnosis could reduce viral load and inhibit furin cleavage necessary for cell entry, thereby reducing morbidity and mortality.\n\nObjectiveTo determine whether initiating nasal irrigation after COVID-19 diagnosis reduces hospitalizations and death in high-risk outpatients, and whether irrigant composition impacts severity.\n\nDesignUnblinded randomized clinical trial of two nasal irrigation protocols in older outpatients PCR positive for SARS-CoV-2, with an observational arm using laboratory-confirmed cases in the CDC COVID-19 Case Surveillance dataset.\n\nSettingSingle-lab community testing facility associated with the emergency department (ED) in Augusta, GA.\n\nParticipantsA consecutive sample of high-risk adults were enrolled within 24 hours of a positive COVID-19 test between September 24 and December 21 of 2020. Patients aged 55 and older were remotely consented. Among 826 screened, 321 of 694 eligible patients were unable to be reached, 294 refused participation, and 79 participants were enrolled.\n\nInterventionsParticipants were randomly assigned adding 2.5 mL povidone-iodine 10% or 2.5 mL sodium bicarbonate to 240 mL of isotonic nasal irrigation twice daily for 14 days.\n\nMain Outcomes and MeasuresThe primary outcome was hospitalization or death from COVID-19 within 28 days of enrollment by daily self-report confirmed with phone calls and hospital records, compared to the CDC Surveillance Dataset covering the same time. Secondary outcomes compared symptom resolution by irrigant additive.\n\nResultsSeventy-nine high-risk participants were enrolled (mean [SD] age, 64 [8] years; 36 [46%] women; 71% Non-Hispanic White), with mean BMI 30.3. Analyzed by intention-to-treat, by day 28, COVID-19 symptoms resulted in one ED visit and no hospitalizations in 42 irrigating with alkalinization, one hospitalization of 37 in the povidone-iodine group, (1.27%) and no deaths. Of nearly three million CDC cases, 9.47% were known to be hospitalized, with an additional 1.5% mortality in those without hospitalization data. The total risk of hospitalization or death (11%) was 8.57 times that of enrolled patients (SE=2.74; P=.006). 62 completed daily surveys (78%), averaging 1.8 irrigations/day. Eleven had irrigation complaints, and four discontinued. There were no significant differences by additive.\n\nConclusionSARS-CoV-2+ participants initiating nasal irrigation were over 8 times less likely to be hospitalized than the national rate.\n\nTrial RegistrationClinicalTrial.gov Identifier: NCT04559035\n\nAuthor ApprovalAll authors have filled out ICMJE and approved submission.\n\nConflict of Interest StatementMaterials were provided by Neilmed Inc. and Rhinosystems Inc. The study was supported by funding from the Bernard and Anne Gray Donor Advised Fund Community Foundation for Greater Atlanta, Neilmed Inc., and Rhinosystems. No authors have conflict of interest.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSAfter testing positive for COVID-19, will rapidly initiating nasal irrigation reduce the risk of morbidity and mortality compared to a national dataset?\n\nFindingsA consecutive sample of 79 high-risk adults (mean age 64, BMI 30.3) were randomized to initiate one of two nasal irrigation protocols within 24 hours of a positive COVID-19 test. Compared to a CDC COVID-19 National Dataset observational arm, 1.27% of participants initiating twice daily nasal irrigation were hospitalized or died, compared to 11%, a significant difference.\n\nMeaningIn high-risk outpatients testing positive for SARS-CoV-2 who initiated nasal irrigation rapidly after diagnosis, risk of hospitalization or death was eight times lower than national rates reported by the CDC.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.13.21262021", + "rel_abs": "BackgroundWe assessed the safety, tolerability and immunogenicity of VLA2001 is a whole-virion inactivated SARS-CoV-2 vaccine adsorbed to alum with a toll-like receptor 9 agonist adjuvant in healthy volunteers aged 18-55.\n\nMethodsThe first 15 participants were enrolled, in groups of 5, to receive two doses, separated by 21 days, of one of three dose concentrations, administered intramuscularly. 138 further participants were randomised 1:1:1 to receive the same 3 dose concentrations, in a double blinded manner. Primary outcomes were solicited adverse reactions 7 days after each vaccination and neutralising antibody geometric mean titres (GMT) against SARS-CoV-2, 2 weeks after the second vaccination (day 36), measured by live microneutralisation assay against wild-type virus (MNA50). Secondary outcomes included unsolicited adverse events, and humoral and cellular responses at day 36, measured by IgG ELISA against Spike protein and interferon-{gamma} secreting T-cells by ELISpot stimulated with multiple SARS-CoV-2 antigens. (ClinicalTrials.gov NCT04671017, ISRCTN 82411169)\n\nFindingsBetween December 16, 2020 and January 21, 2021, 153 participants were enrolled and randomised evenly between the dose groups. The rates of solicited reactions were similar after the first and second doses and between the three dose groups. The most frequent local reactions were tenderness (58{middle dot}2%) and pain (41{middle dot}8%) and systemic reactions were headache (46%) and fatigue (39{middle dot}2%).\n\nIn the high dose group, two weeks following the second dose, the geometric mean titres were 530.4 (95% CI: 421{middle dot}49, 667{middle dot}52) for neutralizing antibodies and 2147{middle dot}9 (95% CI: 1705{middle dot}98, 2704{middle dot}22) for S-binding antibodies. There was a dose dependent response with 90{middle dot}0% (95% CI:78{middle dot}0%.,97{middle dot}0%) seroconversion (4-fold rise) at day 36 in the high dose group, which was significantly higher than rates in both the medium (73.5%; 95% CI: 59%,85%), CIs) and low dose (51%; 95%CI: 37%,65%) rate, CIs) groups (both p < 0.001). Antigen-specific interferon-{gamma} T-cells reactive against the S, M and N proteins were observed in 76, 36 and 49% of high dose recipients, respectively.\n\nInterpretationVLA2001-201 was well tolerated and produced both humoral and cellular immune responses, with a clear dose-response effect.\n\nFundingThis study was funded by the Department of Health and Social Care, UK\n\nThe funder had no role in the study design, implementation or analysis.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Amy L. Baxter", - "author_inst": "Augusta University" - }, - { - "author_name": "Kyle R. Schwartz", - "author_inst": "Edinburgh Napier University" - }, - { - "author_name": "Ryan W. Johnson", - "author_inst": "MedicalCollege of Georgia, Augusta University" - }, - { - "author_name": "Taylor Giller", - "author_inst": "Medical College of Georgia, Augusta University" - }, - { - "author_name": "Kevin M. Swartout", - "author_inst": "Georgia State University" - }, - { - "author_name": "Arni Rao", - "author_inst": "Medical College of Gerogia" - }, - { - "author_name": "Ann M Kuchinski", - "author_inst": "Augusta University" + "author_name": "Rajeka Lazarus", + "author_inst": "University Hospitals Bristol and Weston NHS Trust" }, { - "author_name": "Robert W Gibson", - "author_inst": "Augusta University" + "author_name": "Christian Taucher", + "author_inst": "Valneva Austria GMBH" }, { - "author_name": "Houlton Boomer", - "author_inst": "Augusta University, Augusta GA" + "author_name": "Christopher Duncan", + "author_inst": "Department of Infection and Tropical Medicine, Newcastle upon Tyne Hospitals NHS Foundation Trust; Translational and Clinical Research Institute, Immunity and I" }, { - "author_name": "Erica Cherian", - "author_inst": "Medical College of Georgia, Augusta University" + "author_name": "Saul Faust", + "author_inst": "NIHR Southampton Clinical Research Facility and NIHR Southampton Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust; and Faculty o" }, { - "author_name": "Matthew Lyon", - "author_inst": "Augusta University" + "author_name": "Christopher A Green", + "author_inst": "University Hospitals Birmingham NHS Foundation Trust" }, { - "author_name": "Richard B Schwartz", - "author_inst": "Augusta University" + "author_name": "Adam Finn", + "author_inst": "Schools of Population Health Sciences and Cellular and Molecular Medicine, University of Bristol, Bristol UK" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -597136,35 +595105,103 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2021.08.11.21261712", - "rel_title": "Mental Health Utilization in Children in the time of COVID-19", + "rel_doi": "10.1101/2021.08.12.21261913", + "rel_title": "What has changed in the experiences of people with mental health problems during the COVID-19 pandemic? Findings from follow-up interviews using a coproduced, participatory qualitative approach", "rel_date": "2021-08-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.11.21261712", - "rel_abs": "BackgroundIn early 2020, coronavirus disease 2019 (COVID-19) was declared a public health emergency and a combination of lockdown and social distancing measures were put in place across the globe. Many children, adolescents and adults have experienced adverse mental health effects related to the pandemic and its impact on daily life, although the long-term impact on individuals and health systems is not well understood.\n\nMethodsThis cross-sectional study was based on data from 2018-2021 collected via medical records from our hospital. Admissions were transformed into time-series data, and models were generated to analyze changes in admission rates for mental health emergencies in 2020 and 2021 compared to previous years.\n\nResultsOf 1906 inpatient encounters among 1543 unique patients seen by the Child and Adolescent Psychiatry Consultation-Liaison service, there was a decrease in overall admissions beginning in March 2020, coinciding with statewide lock down due to the COVID-19 pandemic. In April 2020, admissions were reduced 36% compared to average admissions from 2018-2019. By 2021, overall admissions were significantly higher than for the previous three years. Similarly, the count of suicide attempts was significantly higher in 2021 compared to previous years. The rate of patients admitted to inpatient facilities upon discharge was significantly higher during the COVID-19 pandemic period.\n\nConclusionAdmissions for mental health emergencies fluctuated during the period associated with the COVID-19 pandemic across an array of diagnoses. Increases in admissions and severity of mental health emergencies during COVID-19 may reflect a detrimental impact of the pandemic on the mental health of children, as well as unmet needs during this time.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.12.21261913", + "rel_abs": "PurposeWe sought to understand how the experiences of people in the UK with pre-existing mental health conditions had developed during the course of the COVID-19 pandemic.\n\nMethodsIn September-October 2020 we interviewed adults with mental health conditions pre-dating the pandemic, whom we had previously interviewed three months earlier. Participants had been recruited through online advertising and voluntary sector community organisations. Interviews were conducted by telephone or video-conference by researchers with lived experience of mental health difficulties, and explored changes over time in peoples experience of the pandemic.\n\nResultsWe interviewed 44 people, achieving diversity of demographic characteristics and a range of mental health conditions and service use among our sample. Three overarching themes were derived from interviews. The first theme \"Spectrum of adaptation\": to difficulties in access to, or the quality of, statutory mental health services, through developing new personal coping strategies or identifying alternative sources of support. The second theme is \"Accumulating pressures\": from pandemic-related anxieties and sustained disruption to social contact and support, and to mental health treatment. The third theme \"Feeling overlooked\": A sense of people with pre-existing mental health conditions being overlooked during the pandemic by policy-makers at all levels. The latter was compounded for people from ethnic minority communities or with physical health problems.\n\nConclusionOur study highlights the need to support marginalised groups who are at risk of increased inequalities, and to maintain crucial mental and physical healthcare and social care for people with existing mental health conditions, notwithstanding challenges of the pandemic.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Leah Coates", - "author_inst": "OHSU-PSU School of Public Health, Portland, OR" + "author_name": "Prisha Shah", + "author_inst": "Division of Psychiatry, University College London. UK" }, { - "author_name": "Rebecca Marshall", - "author_inst": "Department of Psychiatry, School of Medicine, Portland, OR" + "author_name": "Jackie Hardy", + "author_inst": "Division of Psychiatry, University College London. UK" }, { - "author_name": "Kyle Johnson", - "author_inst": "Department of Psychiatry, School of Medicine, Portland, OR" + "author_name": "Mary Birken", + "author_inst": "Division of Psychiatry, University College London. UK" + }, + { + "author_name": "Una Foye", + "author_inst": "Institute of Psychiatry, Psychology and Neuroscience, Kings College London. UK" + }, + { + "author_name": "Rachel Rowan Olive", + "author_inst": "Division of Psychiatry, University College London. UK" + }, + { + "author_name": "Patrick Nyikavaranda", + "author_inst": "Division of Psychiatry, University College London. UK" + }, + { + "author_name": "Ceri Dare", + "author_inst": "Division of Psychiatry, University College London. UK" + }, + { + "author_name": "Theodora Stefanidou", + "author_inst": "Division of Psychiatry, University College London. UK" }, { - "author_name": "Byron Alexander Foster", - "author_inst": "Department of Pediatrics, School of Medicine, Portland, OR" + "author_name": "Merle Schlief", + "author_inst": "Division of Psychiatry, University College London. UK" + }, + { + "author_name": "Eiluned Pearce", + "author_inst": "Division of Psychiatry, University College London. UK" + }, + { + "author_name": "Natasha Lyons", + "author_inst": "Division of Psychiatry, University College London. UK" + }, + { + "author_name": "Karen Machin", + "author_inst": "Division of Psychiatry, University College London. UK" + }, + { + "author_name": "Tamar Jeynes", + "author_inst": "Division of Psychiatry, University College London. UK" + }, + { + "author_name": "Beverley Chipp", + "author_inst": "Division of Psychiatry, University College London. UK" + }, + { + "author_name": "Anjie Chhapia", + "author_inst": "Division of Psychiatry, University College London. UK" + }, + { + "author_name": "Nick Barber", + "author_inst": "Division of Psychiatry, University College London. UK" + }, + { + "author_name": "Steven Gillard", + "author_inst": "Centre for Mental Health Research, City, University of London. UK" + }, + { + "author_name": "Alexandra Pitman", + "author_inst": "Division of Psychiatry, University College London. UK" + }, + { + "author_name": "Alan Simpson", + "author_inst": "Institute of Psychiatry, Psychology and Neuroscience, Kings College London. UK" + }, + { + "author_name": "Sonia Johnson", + "author_inst": "Division of Psychiatry, University College London. UK" + }, + { + "author_name": "Brynmor Lloyd-Evans", + "author_inst": "Division of Psychiatry, University College London. UK" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2021.08.11.21261946", @@ -598958,69 +596995,77 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2021.08.13.21262006", - "rel_title": "Altered increase in STAT1 expression and phosphorylation in severe COVID-19", + "rel_doi": "10.1101/2021.08.13.21261992", + "rel_title": "Another step toward final call on Remdesivir efficacy as a treatment for hospitalized COVID-19 patients: a multicenter open-label trial", "rel_date": "2021-08-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.13.21262006", - "rel_abs": "The interferon pathway represents a key antiviral defense mechanism and is being considered as a therapeutic target in COVID-19. Both, substitution of interferon and blocking interferon signaling through JAK STAT inhibition to limit cytokine storms have been proposed. However, little is known so far about possible abnormalities in STAT signaling in immune cells during SARS-CoV-2 infection. In the current study, we investigated downstream targets of interferon signaling, including STAT1, pSTAT1 and 2 and IRF1, 7 and 9 by flow cytometry in 30 patients with COVID-19, 17 with mild and 13 with severe infection. We report an upregulation of STAT1 and IRF9 in mild and severe COVID-19 cases, which correlated with the IFN-signature assessed by Siglec-1 (CD169) expression on peripheral monocytes. Most interestingly, Siglec-1 and STAT1 in CD14+ monocytes and plasmablasts showed lower expression among severe COVID-19 cases compared to mild cases. Contrary to the baseline whole protein STAT1 expression, the phosphorylation of STAT1 was enhanced in severe COVID-19 cases, indicating a dysbalanced JAK STAT signaling that fails to induce transcription of interferon stimulated response elements (ISRE). This abnormality persisted after IFN- and IFN-{gamma} stimulation of PBMCs from patients with severe COVID-19. The data suggest impaired STAT1 transcriptional upregulation among severely infected patients which may represent a potential predictive biomarker and may allow stratification of patients for certain interferon-pathway targeted treatments.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.13.21261992", + "rel_abs": "IntroductionAfter emerging the global pandemic of SARS-CoV2 some preliminary studies demonstrated the efficacy of antiviral treatments. But shortly thereafter, inconsistencies in the results of further clinical trials raised doubts on the efficacy of these agents. In this study, we aimed to evaluate the effect of Remdesivir on hospitalized COVID-19 patients outcomes.\n\nMaterial and methodsThis study was an open-label, single-armed, clinical trial on hospitalized patients diagnosed with COVID-19 who had progressive respiratory symptoms despite receiving standard care. All patients received Remdesivir and their characteristics, outcomes, time of treatment initiation, and respiratory support stages during hospitalization were registered and followed up for 14 days.\n\nResults145 patients with the mean age of 52.89 {+/-} 1.12 years enrolled in this study, 38 (26.2%) died at the end of 14 days period. The mean time interval from the onset of the symptoms to antiviral treatment was 10.63{+/-}0.56 days. Thirty deceased patients (78.9%) were men, showing 2.8 times higher mortality chance compared to women (ORadj=2.77; 95%CI=1.08-7.09). The type of respiratory support on the first day of treatment initiation showed a significantly lower mortality chance in patients receiving O2 only than those who needed non-invasive and/or mechanical ventilation (ORadj=3.91; 95%CI=1.64-9.32). The start time (early vs late administration) and duration (less or more than 7 days) of antiviral treatment had no statistically significant association with mortality or ventilation escalation among the patients (p-value > 0.05).\n\nConclusionIn this study, we showed that Remdesivir probably is not effective on the outcome of hospitalized COVID-19 patients.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Hectot Rincon-Arevalo", - "author_inst": "Charite Berlin" + "author_name": "Hamed Hosseini", + "author_inst": "Center for Research and Training in Skin Disease and Leprosy, Tehran University of Medical Sciences." }, { - "author_name": "Arman Aue", - "author_inst": "Charite Berlin" + "author_name": "Anahita Sadeghi", + "author_inst": "Department of Internal Medicine, Tehran University of Medical Sciences, Tehran, Iran." }, { - "author_name": "Jacob Ritter", - "author_inst": "Charite Berlin" + "author_name": "Payam Tabarsi", + "author_inst": "Department of Infectious Disease, Shahid Beheshti University of Medical Sciences, Tehran, Iran." }, { - "author_name": "Franziska Szelinski", - "author_inst": "Charite Berlin" + "author_name": "Azin Etemadimanesh", + "author_inst": "Department of Pathology, Tehran University of Medical Sciences, Tehran, Iran." }, { - "author_name": "Dmytro Khadzhynov", - "author_inst": "Charite Berlin" + "author_name": "Ilad Alavi Darazam", + "author_inst": "Department of Infectious Disease, Shahid Beheshti University of Medical Sciences, Tehran, Iran." }, { - "author_name": "Daniel Zickler", - "author_inst": "Charite Berlin" + "author_name": "Nasser Aghdami", + "author_inst": "Department of Infectious Disease, Tehran University of Medical Science, Tehran, Iran." }, { - "author_name": "Ana-Luisa Stefanski", - "author_inst": "Charite Berlin" + "author_name": "Saeed Kalantari", + "author_inst": "Antimicrobial Resistance Research Center, Iran University of Medical Sciences, Tehran, Iran" }, { - "author_name": "Andreia C Lino", - "author_inst": "DRFZ" + "author_name": "Mehrdad Hasibi", + "author_inst": "Department of Infectious Disease, Tehran University of Medical Science, Tehran, Iran." }, { - "author_name": "Sixten Koerper", - "author_inst": "Institute for Clinical Transfusion Medicine and Immunogenetics Ulm" + "author_name": "Azar Hadadi", + "author_inst": "Department of Infectious Disease, Tehran University of Medical Science, Tehran, Iran." }, { - "author_name": "Kai-Uwe Eckardt", - "author_inst": "Charite Berlin" + "author_name": "Farhang Babamahmoodi", + "author_inst": "Antimicrobial Resistance Research Center, Communicable Diseases Institute, Mazandaran University of Medical Sciences, Sari, Iran" }, { - "author_name": "Hubert Schrezenmeier", - "author_inst": "Institute for Clinical Transfusion Medicine and Immunogenetics Ulm" + "author_name": "Mansooreh Momen-Heravi", + "author_inst": "Department of infectious diseases, faculty of medicine, Kashan university of medical sciences, Kashan, Iran." }, { - "author_name": "Thomas Doerner", - "author_inst": "Charite Berlin" + "author_name": "Ahmad Hormati", + "author_inst": "Gastroenterology and Hepatology Disease Research Center, Oom university of medical sciences, Iran. -Gastrointestinal and Liver Diseases Research Center, Iran un" }, { - "author_name": "Eva Schrezenmeier", - "author_inst": "Charite Berlin" + "author_name": "Yunes Panahi", + "author_inst": "Pharmacotherapy Department, Faculty of Pharmacy, Baqiyatallah University of Medical Sciences, Tehran, Iran" + }, + { + "author_name": "Rozita Khodashahi", + "author_inst": "Department of Infectious disease and tropical medicine, Faculty of Medicine, Mashhad university of medical sciences, Mashhad, Iran." + }, + { + "author_name": "Mohammadreza Salehi", + "author_inst": "Department of Infectious Disease, Tehran University of Medical Science, Tehran, Iran." } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -601176,151 +599221,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.10.21261849", - "rel_title": "SARS-CoV-2 Seroprevalence and Drug Use in Trauma Patients from Six Sites in the United States", + "rel_doi": "10.1101/2021.08.10.21261856", + "rel_title": "Using a physical model and aggregate data from Israel to estimate the current (July 2021 ) efficacy of the Pfizer-BioNTech vaccine", "rel_date": "2021-08-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.10.21261849", - "rel_abs": "In comparison to the general patient population, trauma patients show higher level detections of bloodborne infectious diseases, such as Hepatitis and Human Immunodeficiency Virus. In comparison to bloodborne pathogens, the prevalence of respiratory infections such as SARS-CoV-2 and how that relates with other variables, such as drug usage and trauma type, is currently unknown in trauma populations. Here, we evaluated SARS-CoV-2 seropositivity and antibody isotype profile in 2,542 trauma patients from six Level-1 trauma centers between April and October of 2020 during the first wave of the COVID-19 pandemic. We found that the seroprevalence in trauma victims 18-44 years old (9.79%, 95% confidence interval/CI: 8.33 11.47) was much higher in comparison to older patients (45-69 years old: 6.03%, 4.59-5.88; 70+ years old: 4.33%, 2.54 - 7.20). Black/African American (9.54%, 7.77 - 11.65) and Hispanic/Latino patients (14.95%, 11.80 - 18.75) also had higher seroprevalence in comparison, respectively, to White (5.72%, 4.62 7.05) and Non-Latino patients (6.55%, 5.57 - 7.69). More than half (55.54%) of those tested for drug toxicology had at least one drug present in their system. Those that tested positive for narcotics or sedatives had a significant negative correlation with seropositivity, while those on anti-depressants trended positive. These findings represent an important consideration for both the patients and first responders that treat trauma patients facing potential risk of respiratory infectious diseases like SARS-CoV-2.", - "rel_num_authors": 33, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.10.21261856", + "rel_abs": "From the end of June 2021, the state of Israel, where 60% of the population is vaccinated with an mRNA BNT162b2 vaccine, has an increase in the daily morbidity. This increase may be a result of different events: a temporal decline of the vaccines efficacy; Lower efficacy of the vaccine against the current Delta ((B.1.617.2) variant (which is now the dominant strain in Israel); A result of lack of social restrictions, a highly contagious variant, or any combination of the above. We found, by using a novel spatial-dynamic model and recent aggregate data from Israel, that this new surge of cases is partiality due to a decline in the shielding of those who were vaccinated about six months ago. Also, we found a decrease in the vaccines efficacy against severe morbidity for the early elderly population compared to the rest of the vaccinated population. These results, which are consistent with recent studies, emphasize the high ability of the model in evaluating the time- and age- dependent efficacy of the vaccine for different age groups and enables to predict the spread of the pandemic as a function of such efficacy.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Tran B Ngo", - "author_inst": "Section on Immuno-Engineering. National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda MD 20894" - }, - { - "author_name": "Maria Karkanitsa", - "author_inst": "Section on Immuno-Engineering. National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda MD 20894" - }, - { - "author_name": "Kenneth M Adusei", - "author_inst": "Section on Immuno-Engineering. National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda MD 20894" - }, - { - "author_name": "Lindsey A Graham", - "author_inst": "Dunlap and Associates, Inc., Stamford CT 06906" - }, - { - "author_name": "Emily E Ricotta", - "author_inst": "Epidemiology and Population Studies Unit, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda MD 20894" - }, - { - "author_name": "Jenna R Darrah", - "author_inst": "Dunlap and Associates, Inc., Stamford CT 06906" - }, - { - "author_name": "Richard D Blomberg", - "author_inst": "Dunlap and Associates, Inc., Stamford CT 06906" - }, - { - "author_name": "Jacquelyn Spathies", - "author_inst": "Bioengineering and Physical Sciences Shared Resource, National Institute for Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda MD 2" - }, - { - "author_name": "Kyle J Pauly", - "author_inst": "Bioengineering and Physical Sciences Shared Resource, National Institute for Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda MD 2" - }, - { - "author_name": "Carleen Klumpp-Thomas", - "author_inst": "National Center for Advancing Translational Sciences, National Institutes of Health, Rockville MD 20852" - }, - { - "author_name": "Jameson Travers", - "author_inst": "National Center for Advancing Translational Sciences, National Institutes of Health, Rockville MD 20852" - }, - { - "author_name": "Jennifer Mehalko", - "author_inst": "Protein Expression Laboratory, Frederick National Laboratory for Cancer Research, Frederick MD 21702" - }, - { - "author_name": "Matthew Drew", - "author_inst": "Protein Expression Laboratory, Frederick National Laboratory for Cancer Research, Frederick MD 21702" - }, - { - "author_name": "Matthew D Hall", - "author_inst": "National Center for Advancing Translational Sciences, National Institutes of Health, Rockville MD 20852" - }, - { - "author_name": "Matthew J Memoli", - "author_inst": "Clinical Studies Unit, Laboratory of Infectious Diseases, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Bethesda MD 208" - }, - { - "author_name": "Dominic Esposito", - "author_inst": "Protein Expression Laboratory, Frederick National Laboratory for Cancer Research, Frederick MD 21702" - }, - { - "author_name": "Rosemary A Kozar", - "author_inst": "Shock Trauma Center, University of Maryland School of Medicine, Baltimore MD 21201" - }, - { - "author_name": "Christopher Griggs", - "author_inst": "Department of Emergency Medicine, Atrium Healths Carolinas Medical Center, Charlotte NC 28203" - }, - { - "author_name": "Kyle W Cunningham", - "author_inst": "Division of Acute Care Surgery, Atrium Healths Carolinas Medical Center, Charlotte NC 28203" - }, - { - "author_name": "Carl I Schulman", - "author_inst": "University of Miami Miller School of Medicine, Miami FL 33136" - }, - { - "author_name": "Marie Crandall", - "author_inst": "Department of Surgery, University of Florida College of Medicine, Jacksonville FL 33209" - }, - { - "author_name": "Mark Neavyn", - "author_inst": "Maine Medical Center, Department of Emergency Medicine, Tufts University School of Medicine, Portland ME 04102" - }, - { - "author_name": "Jon D Dorfman", - "author_inst": "Department of Surgery, Division of Trauma and Surgical Critical Care, UMass Memorial Medical Center, University of Massachusetts Medical School, Worcester MA 01" - }, - { - "author_name": "Jeffrey T Lai", - "author_inst": "Division of Medical Toxicology, Department of Emergency Medicine, University of Massachusetts Medical School, Worcester MA 01655" - }, - { - "author_name": "Jennifer M Whitehill", - "author_inst": "Department of Health Promotion and Policy, University of Massachusetts Amherst, Amherst MA 01003" - }, - { - "author_name": "Kavita M Babu", - "author_inst": "Division of Medical Toxicology, Department of Emergency Medicine, University of Massachusetts Medical School, Worcester MA 01655" - }, - { - "author_name": "Nicholas M Mohr", - "author_inst": "Department of Emergency Medicine, Anesthesia Critical Care, and Epidemiology, University of Iowa Health Care, Iowa City IA 52242" - }, - { - "author_name": "Jon Van Heukelom", - "author_inst": "Department of Emergency Medicine, University of Iowa Health Care, Iowa City IA 52242" - }, - { - "author_name": "James C Fell", - "author_inst": "NORC at the University of Chicago, Bethesda, MD 20814" - }, - { - "author_name": "Whit Rooke", - "author_inst": "KIYATEC, Inc., Greenville SC 29605" - }, - { - "author_name": "Heather Kalish", - "author_inst": "Bioengineering and Physical Sciences Shared Resource, National Institute for Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda MD 2" - }, - { - "author_name": "F. Dennis Thomas", - "author_inst": "Dunlap and Associates, Inc., Stamford CT 06906" + "author_name": "Hilla De-Leon", + "author_inst": "ECT*" }, { - "author_name": "Kaitlyn Sadtler", - "author_inst": "Section on Immuno-Engineering. National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda MD 20894" + "author_name": "Francesco Pederiva", + "author_inst": "INFN-TiFPA" } ], "version": "1", - "license": "cc0", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.08.10.21261847", @@ -603141,65 +601062,81 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.08.09.21261778", - "rel_title": "Genomic analysis of SARS-CoV-2 variants of concern identified from the ChAdOx1 nCoV-19 immunized patients from Southwest part of Bangladesh", + "rel_doi": "10.1101/2021.08.09.21261789", + "rel_title": "A multidimensional cross-sectional analysis of COVID-19 seroprevalence among a police officer cohort: The PoliCOV-19 study", "rel_date": "2021-08-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.09.21261778", - "rel_abs": "IntroductionBangladesh introduced ChAdOx1 nCoV-19 since February, 2021 and in six months, only a small population (3.5%) received their first dose of vaccination like other low-income countries. The remaining populations are struggling with increased rate of infection due to beta and delta variants. Although this uncontrolled COVID-19 pandemic did not leave even the immunized group because of immune escaping capacity of those new variants.\n\nMethodsA total of 4718 nasopharygeal samples were collected from 1st March until 15th April, 2021, of which, 834 (18%) were SARS-CoV-2 positive. Randomly generated 135 positive cases were selected for telephone interview and 108 were available and provided consent. The prevalence of SARS-CoV-2 variants and disease severity among both immunized and unimmunized group was measured. A total of 63 spike protein sequence and 14 whole genome sequences were performed from both groups and phylogenetic reconstruction and mutation analysis were compared.\n\nResultsA total of 40 respondents (37%, N=108) received single-dose and 2 (2%) received both doses of ChAdOx1 nCoV-19 vaccine which significantly reduce dry cough, loss of appetite and difficulties in breathing compared to none. There was no significant difference in hospitalization, duration of hospitalization or reduction of other symptoms like running nose, muscle pain, shortness of breathing or generalized weakness between immunized and unimmunized group. Spike protein sequence assumed 21 (87.5%) B.1.351, one B.1.526 and two 20B variants in immunized group compared to 27 (69%) B.1.351, 5 (13%) B.1.1.7, 4 (10%) 20B, 2 B.1.526 and one B.1.427 variant in unimmunized group. Those variants were further confirmed by 14 whole genome sequence analysis. Complete genome analysis included seven B.1.351 Beta V2, three B.1.1.7 Alpha V1, one B.1.526 Eta and rest three 20B variant.\n\nConclusionSingle dose of ChAdOx1 couldnt prevent the new infection or disease severity by the COVID-19 variants of concern, B.1.351, in Bangladesh.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.09.21261789", + "rel_abs": "OBJECTIVETo determine the seroprevalence of SARS-CoV-2 antibodies in employees of the Cantonal Police Bern, Switzerland; to investigate individual and work-related factors associated with seropositivity; and to assess the neutralizing capacity of the antibodies of seropositive study participants.\n\nDESIGNCross-sectional analysis of a cohort study.\n\nSETTINGWearing face masks was made mandatory for employees of the police during working hours at the rise of the second wave of the pandemic in mid-October 2020. Protests and police fieldwork provided a high exposure environment for SARS-CoV-2 infections. The investigation was performed prior to initiation of a vaccine programme. Study participants were invited for serological testing of SARS-CoV-2 and to complete questionnaires on sociodemographic, work and health-related questions.\n\nPARTICIPANTS978 police personnel working in four different geographic districts, representing 35% of the entire staff, participated from February to March 2021.\n\nMAIN OUTCOME MEASURESSeroprevalence of anti-SARS-CoV-2 antibodies in February to March 2021, geographic and work-related risk factors for seropositivity, and serum neutralization titres towards the wild-type SARS-CoV-2 spike protein (expressing D614G) and the alpha and beta variants.\n\nRESULTSSeroprevalence was 12.9% (126 of 978 employees). It varied by geographic region within the canton; ranged from 9% to 13% in three regions, including the city; and was 22% in Bernese Seeland/Jura. Working in the latter region was associated with higher odds for seropositivity (odds ratio 2.38, 95% confidence interval 1.28 to 4.44, P=0.006). Job roles with mainly office activity were associated with a lower risk of seropositivity (0.33, 0.14 to 0.77, P=0.010). Most seropositive employees (67.5%) reported having had coronavirus disease 2019 (COVID-19) 3 months or longer prior to serological testing, and the proportion of agreement between positive nasopharyngeal test results and seroconversion was 95% to 97%. Among reported symptoms, new loss of smell or taste was the best discriminator for seropositivity (odds ratio 52.4, 30.9 to 89.0, P<0.001). Compliance with mask wearing during working hours was 100%, and 45% of all seropositive versus 5% of all seronegative participants (P<0.001) reported having had contact with a proven COVID-19 case living in the same household. The level of serum antibody titres correlated well with neutralization capacity. Antibodies derived from natural SARS-CoV-2 infection effectively neutralized the SARS-CoV-2 spike protein (expressing D614G), but were less effective against the alpha and beta variants. A regression model demonstrated that anti-spike antibodies had higher odds for neutralization than did anti-nucleocapsid protein antibodies.\n\nCONCLUSIONSSeroprevalence in the pre-vaccinated police cohort was similar to that reported in the general population living in the same region. The high compliance with mask wearing and the low proportion of seroconversion after contact with a presumed or proven COVID-19 case during working hours imply that personal protective equipment is effective and that household contacts are the leading transmission venues. The level of serum antibody titres, in particular that of anti-spike antibodies, correlated well with neutralization capacity. Low antibody titres were not effective against the alpha and beta variants.\n\nSUMMARY BOXESO_ST_ABSWHAT IS ALREADY KNOWN ON THIS TOPICC_ST_ABSO_LIThe seroprevalence of anti-SARS-CoV-2 antibodies in the general population shows variations, depending on the geographic location of investigated study participants.\nC_LIO_LISocial distancing by avoiding crowds and maintaining a distance of 6 feet from others when in public are recommended. These recommendations are not realistic for security personnel and employees of a police department.\nC_LIO_LIPreventive strategies for individuals in a health care setting are warranted and effective to reduce potential exposures. The effect of preventive strategies on individuals working for the police force has not been investigated.\nC_LI\n\nWHAT THIS STUDY ADDSO_LIThe study suggests that the overall seroprevalence of anti-SARS-CoV-2 antibodies among police officers is not higher than that in the general population, despite presumed higher exposure (e.g., public protests).\nC_LIO_LICompliance with use of personal protective equipment among police officers was very high. The study results suggested that household contacts, rather than exposure during working hours, is the main source for viral transmission.\nC_LIO_LIAnti-SARS-CoV-2 antibodies derived from natural infection demonstrated good neutralization capacity towards strains that epidemiologically likely caused the infection, but moderate to poor neutralization capacity towards the alpha and beta variant.\nC_LI", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Hassan M. Al-Emran", - "author_inst": "JUST" + "author_name": "Parham Sendi", + "author_inst": "Institute for Infectious Diseases, University of Bern, Bern, Switzerland" }, { - "author_name": "Md. Shazid Hasan", - "author_inst": "JUST" + "author_name": "Rossella Baldan", + "author_inst": "Institute for Infectious Diseases, University of Bern, Bern, Switzerland" }, { - "author_name": "Md. Ali Ahsan Setu", - "author_inst": "JUST" + "author_name": "Marc Thierstein", + "author_inst": "Division Operations, Cantonal Police Bern, Bern, Switzerland" }, { - "author_name": "Md. Shaminur Rahman", - "author_inst": "JUST" + "author_name": "Nadja Widmer", + "author_inst": "Interregional Blood Transfusion Swiss Red Cross, Bern, Switzerland." }, { - "author_name": "ASM Rubayet Ul Alam", - "author_inst": "JUST" + "author_name": "Peter Gowland", + "author_inst": "Interregional Blood Transfusion Swiss Red Cross, Bern, Switzerland." }, { - "author_name": "Shovon Lal Sarkar", - "author_inst": "JUST" + "author_name": "Brigitta Gahl", + "author_inst": "CTU Bern, University of Bern, Bern, Switzerland" }, { - "author_name": "Md. Tanvir Islam", - "author_inst": "JUST" + "author_name": "Annina Elisabeth Buechi", + "author_inst": "Department of Emergency Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland" }, { - "author_name": "Mir Raihanul Islam", - "author_inst": "JUST" + "author_name": "Dominik Guentensperger", + "author_inst": "CTU Bern, University of Bern, Bern, Switzerland" }, { - "author_name": "Mohammad Mahfuzur Rahman", - "author_inst": "JUST" + "author_name": "Manon Wider", + "author_inst": "Institute for Infectious Diseases, University of Bern, Bern, Switzerland" }, { - "author_name": "M. Anwar Islam", - "author_inst": "JUST" + "author_name": "Manuel Raphael Blum", + "author_inst": "Department of General Internal Medicine, Inselspital, Bern University Hospital, Uand Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzer" }, { - "author_name": "Iqbal Kabir Jahid", - "author_inst": "JUST" + "author_name": "Caroline Tinguely", + "author_inst": "Interregional Blood Transfusion Swiss Red Cross, Bern, Switzerland" }, { - "author_name": "M. Anwar Hossain", - "author_inst": "JUST" + "author_name": "Cedric Maillat", + "author_inst": "Hopital du Jura bernois SA, Saint-Imier, Switzerland." + }, + { + "author_name": "Elitza S. Theel", + "author_inst": "Division of Infectious Disease, Mayo Clinic, Rochester, MN, USA." + }, + { + "author_name": "Elie Berbari", + "author_inst": "Division of Infectious Disease, Mayo Clinic, Rochester, MN, USA." + }, + { + "author_name": "Ronald Dijkman", + "author_inst": "Institute for Infectious Diseases, University of Bern, Bern, Switzerland." + }, + { + "author_name": "Christoph Niederhauser", + "author_inst": "Interregional Blood Transfusion Swiss Red Cross, Bern, and Institute for Infectious Diseases, University of Bern, Bern, Switzerland." } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -604991,39 +602928,103 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.08.09.454215", - "rel_title": "Fully Human Antibody Immunoglobulin from Transchromosomic Bovines is Potent Against SARS-CoV-2 Variant Pseudoviruses", + "rel_doi": "10.1101/2021.08.07.455523", + "rel_title": "Broad neutralizing nanobody against SARS-CoV-2 engineered from pre-designed synthetic library", "rel_date": "2021-08-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.09.454215", - "rel_abs": "SAB-185 is a fully human polyclonal anti-SARS-CoV-2 immunoglobulin produced from the plasma of transchromosomic bovines that are hyperimmunized with recombinant SARS-CoV-2 Wuhan-Hu-1 Spike protein. SAB-185 is being evaluated for efficacy in aphase 3 clinical trial. The World Health Organization (WHO) has identified multiple Variants-of-Concern and Variants-of-Interest (VOC/VOI) that have mutations in their Spike protein that appear to increase transmissibility and/or reduce the effectiveness of therapeutics and vaccines, among other parameters of concern. SAB-185 was evaluated using lentiviral-based pseudovirus assays performed in a BSL2 environment that incorporates stable or transient cell lines that express human angiotensin converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2). The results indicate that SAB-185 retained neutralization potency against multiple SARS-CoV-2 pseudovirus variants, including the Delta, Kappa, Lambda and Omicron variants, that have or are supplanting other VOC/VOI in many countries and regions around the world.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.07.455523", + "rel_abs": "SARS-CoV-2 infection is initiated with Spike glycoprotein binding to the receptor of human angiotensin converting enzyme 2 via its receptor binding domain. Blocking this interaction is considered as an effective approach to inhibit virus infection. Here we report the discovery of a neutralizing nanobody, VHH60, directly produced from a humanized synthetic nanobody library. VHH60 competes with human ACE2 to bind the receptor binding domain of the Spike protein with a KD of 2.56 nM, inhibits infections of both live SARS-CoV-2 and pseudotyped viruses harboring wildtype, escape mutations and prevailing variants at nanomolar level. VHH60 also suppresses SARS-CoV-2 infection and propagation 50-fold better and protects mice from death two times longer than that of control group after live virus inoculation on mice. VHH60 therefore is a powerful synthetic nanobody with a promising profile for disease control against COVID19.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Thomas Luke", - "author_inst": "SAB Biotherapeutics.com" + "author_name": "Qianyun Liu", + "author_inst": "State Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, 430072, Hubei, China" }, { - "author_name": "Hua Wu", - "author_inst": "SAB Biotherapeutics, Inc. 2301 E 60th N, Sioux Falls, SD 57104." + "author_name": "Chenguang Cai", + "author_inst": "Bioduro-sundia LLC., Wuxi 214174, Jiangsu, China." }, { - "author_name": "Kristi A Egland", - "author_inst": "SAB Biotherapeutics, Inc. 2301 E 60th N, Sioux Falls, SD 57104." + "author_name": "Yanyan Huang", + "author_inst": "Bioduro-sundia LLC., Wuxi 214174, Jiangsu, China." }, { - "author_name": "Eddie J Sullivan", - "author_inst": "SAB Biotherapeutics, Inc. 2301 E 60th N, Sioux Falls, SD 57104." + "author_name": "Li Zhou", + "author_inst": "State Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, 430072, Hubei, China" + }, + { + "author_name": "Yanbin Guan", + "author_inst": "Bioduro-sundia LLC., Wuxi 214174, Jiangsu, China." }, { - "author_name": "Christoph L Bausch", - "author_inst": "SAB Biotherapeutics, Inc. 2301 E 60th N, Sioux Falls, SD 57104." + "author_name": "Shiying Fu", + "author_inst": "Bioduro-sundia LLC., Wuxi 214174, Jiangsu, China." + }, + { + "author_name": "Youyou Lin", + "author_inst": "Bioduro-sundia LLC., Wuxi 214174, Jiangsu, China." + }, + { + "author_name": "Ting Yang", + "author_inst": "Bioduro-sundia LLC., Wuxi 214174, Jiangsu, China." + }, + { + "author_name": "Xiaohua Liang", + "author_inst": "Bioduro-sundia LLC., Wuxi 214174, Jiangsu, China." + }, + { + "author_name": "Nanyan Wang", + "author_inst": "Bioduro-sundia LLC., Wuxi 214174, Jiangsu, China." + }, + { + "author_name": "Fengzhi Zhang", + "author_inst": "Bioduro-sundia LLC., Wuxi 214174, Jiangsu, China." + }, + { + "author_name": "Qi Sun", + "author_inst": "Bioduro-sundia LLC., Wuxi 214174, Jiangsu, China." + }, + { + "author_name": "Ying Bai", + "author_inst": "Bioduro-sundia LLC., Wuxi 214174, Jiangsu, China." + }, + { + "author_name": "Yu Chen", + "author_inst": "Bioduro-sundia LLC., Wuxi 214174, Jiangsu, China." + }, + { + "author_name": "Huan Yan", + "author_inst": "Wuhan University" + }, + { + "author_name": "Zhen Zhang", + "author_inst": "State Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, 430072, Hubei, China" + }, + { + "author_name": "Ke Lan", + "author_inst": "State Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, 430072, Hubei, China" + }, + { + "author_name": "Yu Chen", + "author_inst": "State Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, 430072, Hubei, China" + }, + { + "author_name": "Xiang Li", + "author_inst": "Bioduro-sundia LLC., Wuxi 214174, Jiangsu, China." + }, + { + "author_name": "Shin-Chen Hou", + "author_inst": "Bioduro-sundia LLC., Wuxi 214174, Jiangsu, China." + }, + { + "author_name": "Yi Xiong", + "author_inst": "Bioduro-sundia LLC., Wuxi 214174, Jiangsu, China." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.08.09.455656", @@ -607061,91 +605062,63 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.08.06.21261419", - "rel_title": "Occupational risk of SARS-CoV-2 infection and reinfection during the second pandemic surge: a cohort study.", - "rel_date": "2021-08-08", + "rel_doi": "10.1101/2021.08.04.21261609", + "rel_title": "Diagnostic Efficacy of Rapid Antigen Testing for SARS-CoV-2: The COVid-19 AntiGen (COVAG) study", + "rel_date": "2021-08-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.06.21261419", - "rel_abs": "ObjectivesThis cohort study including essential workers, assessed the{square}risk and incidence of SARS-CoV-2{square}infection during the second surge of COVID-19 according to baseline serostatus and occupational sector.\n\nMethodsEssential workers were selected from a seroprevalence survey cohort in Geneva, Switzerland and were linked to a state centralized registry compiling SARS-CoV-2 infections. Primary outcome was the number of virologically-confirmed infections from serological assessment (between May and September 2020) to January 25, 2021, according to baseline antibody status and stratified by three pre-defined occupational groups (occupations requiring sustained physical proximity, involving brief regular contact or others). Secondary outcomes included the incidence of infection.\n\nResults10457 essential workers were included (occupations requiring sustained physical proximity accounted for 3057 individuals, those involving regular brief contact, 3645, and 3755 workers were classified under \"Other essential occupations\"). After a follow-up period of over 27 weeks, 5 (0.6%) seropositive and 830 (8.5%) seronegative individuals had a positive SARS-CoV-2 test, with an incidence rate of 0.2 (95% CI 0.1 to 0.6) and 3.2 (95% CI 2.9 to 3.4) cases per person-week, respectively. Incidences were similar across occupational groups. Seropositive essential workers had a 93% reduction in the hazard (HR of 0.07, 95% CI 0.03 to 0.17) of having a positive test during follow-up with no significant between-occupational group difference.\n\nConclusionsA ten-fold reduction in the hazard of being virologically tested positive was observed among anti-SARS-CoV-2 seropositive essential workers regardless of their sector of occupation, confirming the seroprotective effect of a previous SARS-CoV2 exposure at least six months after infection.\n\nKey messagesO_ST_ABSWhat is already known about this subject?C_ST_ABSRisk of SARS-CoV-2 reinfection is low in the general population and among healthcare workers.\n\nWhat are the new findings?A ten-fold reduction of risk of being virologically tested positive reinfection is observed among anti-SARS-CoV-2 seropositive essential workers of different activity sectors, regardless of their occupation-related risk of exposure.\n\nHow might this impact on policy or clinical practice in the foreseeable future?Vaccination could be delayed in individuals with previous history of SARS-CoV-2 infection with serologic confirmation, regardless of their occupational exposure. These observations need to be confirmed for new SARS-CoV-2 variants.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.04.21261609", + "rel_abs": "BackgroundWidely available rapid testing is pivotal to the fight against COVID-19. Real-time reverse transcription-polymerase chain reaction (rRT-PCR) remains the gold standard. We compared two frequently used commercial rapid diagnostic tests (RDTs) for SARS-CoV-2-antigens, the SD Biosensor SARS-CoV-2 Rapid Antigen Test (Roche Diagnostics) and the Panbio COVID-19 Ag Rapid Test (Abbott Diagnostics), against rRT-PCR for SARS-CoV-2 detection.\n\nMethodsWe compared the tests in 2215 all-comers at a diagnostic centre between February 1 and March 31, 2021. rRT-PCR-positive samples were examined for SARS-CoV-2 variants.\n\nFindings338 participants (15%) were rRT-PCR-positive for SARS-CoV-2. The sensitivities of Roche-RDT and Abbott-RDT were 60.4% and 56.8% (P<0{middle dot}0001) and specificities 99.7% and 99.8% (P=0{middle dot}076), respectively. Sensitivity inversely correlated with rRT-PCR-derived Ct values. Unadjusted, the RDTs had higher sensitivities in individuals referred by treating physicians and health departments than those tested for other reasons, in persons without comorbidities compared to those with comorbidities, in individuals with symptoms suggesting COVID-19, and in the absence of SARS-CoV-2 variants compared to Alpha variant carriers. The associations of sensitivity with clinical symptoms and the SARS-CoV-2 genotype were robust against adjustment for Ct values. Assuming that 10 000 symptomatic individuals are tested, 500 of which are truly positive, the RDTs would generate 38 false-positive and 124 false-negative results. Assuming that 10 000 asymptomatic individuals are tested, including 50 true positives, 18 false-positives and 34 false-negatives would be generated.\n\nInterpretationThe sensitivities of the two RDTs are unsatisfactory. This calls into question whether their widespread use is effective in the ongoing SARS-CoV-2 pandemic.\n\nFundingSYNLAB Holding Deutschland GmbH\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSSmall studies and a meta-analysis from the Cochrance collaboration indicate vastly different diagnostic efficacies of commercial rapid diagnostic tests (RDTs) for SARS-CoV-2 antigen. The impact of SARS-CoV-2 variants has not been known.\n\nAdded value of this studyThis is one of the largest real-world studies of the diagnostic efficacy of two widely recommended RDTs SARS-CoV-2 antigen in comparison to rRT-PCR. The sensitivities of the two RDTs are unsatisfactory, mainly in asymptomatic persons. Presence of the SARS-CoV-2 Alpha Variant decreased both tests sensitivities significantly.\n\nImplications of all the available evidencePolicy and health care providers should account for substantial limitations of RDTs for SARS-CoV-2 particular in asymptomatic persons. Research into alternative approaches to the screening for SARS-CoV-2 should be intensified.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Antonio Leidi", - "author_inst": "Division of General Internal Medicine, Geneva University Hospitals, Geneva, Switzerland" + "author_name": "Christoph Wertenauer", + "author_inst": "Synlab Holding Deutschland GmbH" }, { - "author_name": "Amandine Berner", - "author_inst": "Division of General Internal Medicine, Geneva University Hospitals, Geneva, Switzerland" + "author_name": "Geovana Brenner-Michael", + "author_inst": "SYNLAB Holding Deutschland GmbH, Gubener Strasse 39, 86156 Augsburg, Germany" }, { - "author_name": "Dumont Roxane", - "author_inst": "Division and Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland" - }, - { - "author_name": "Richard Dubos", - "author_inst": "Division and Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland" - }, - { - "author_name": "Flora Koegler", - "author_inst": "Division of General Internal Medicine, Geneva University Hospitals, Geneva, Switzerland" - }, - { - "author_name": "Giovanni Piumatti", - "author_inst": "Institute of Public Health, Faculty of BioMedical Sciences, Universita della Svizzera Italiana, Lugano, Switzerland" - }, - { - "author_name": "Nicolas Vuilleumier", - "author_inst": "Division of Laboratory Medicine, Geneva University Hospitals, Geneva, Switzerland" - }, - { - "author_name": "Laurent Kaiser", - "author_inst": "Geneva Center for Emerging Viral Diseases, Geneva University Hospitals, Geneva, Switzerland" - }, - { - "author_name": "Jean-Francois Balavoine", - "author_inst": "Department of Medicine, Faculty of Medicine, University of Geneva, Switzerland" - }, - { - "author_name": "Didier Trono", - "author_inst": "School of Life Sciences, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland" + "author_name": "Alexander Dressel", + "author_inst": "Dr. Dressel Consulting, Am Exerzierplatz 23, 68167 Mannheim" }, { - "author_name": "Didier Pittet", - "author_inst": "Infection Control Program and World Health Organization Collaborating Center on Patient Safety, Geneva University Hospitals and Faculty of Medicine, Geneva, Swi" + "author_name": "Caroline Pfeifer", + "author_inst": "SYNLAB Holding Deutschland GmbH, Gubener Strasse 39, 86156 Augsburg, Germany" }, { - "author_name": "Francois Chappuis", - "author_inst": "Division and Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland" + "author_name": "Ulrike Hauser", + "author_inst": "SYNLAB Medical Care Center Augsburg GmbH, Gubener Strasse 39, 86156 Augsburg, Germany" }, { - "author_name": "Omar Kherad", - "author_inst": "Division of Internal Medicine, Hopital de la Tour and Faculty of Medicine, Geneva, Switzerland" + "author_name": "Eberhard Wieland", + "author_inst": "SYNLAB Medical Care Center Leinfelden-Echterdingen GmbH, Nikolaus-Otto- Strasse 6, 70771 Leinfelden-Echterdingen / Germany" }, { - "author_name": "Delphine Courvoisier", - "author_inst": "General Directorate of Health, Geneva, Switzerland" + "author_name": "Christian Mayer", + "author_inst": "SYNLAB Holding Deutschland GmbH, Gubener Strasse 39, 86156 Augsburg, Germany" }, { - "author_name": "Andrew S Azman", - "author_inst": "Division and Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland & Department of Epidemiology, Johns Hopkins Bloomberg School " + "author_name": "Caren Mutschmann", + "author_inst": "SGS Analytics Germany GmbH, Turmstrasse 21, 10559 Berlin, Germany" }, { - "author_name": "Maria-Eugenia Zaballa", - "author_inst": "Division and Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland" + "author_name": "Martin Roskos", + "author_inst": "SYNLAB Holding Deutschland GmbH, Gubener Strasse 39, 86156 Augsburg, Germany" }, { - "author_name": "Idris Guessous", - "author_inst": "Division and Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland" + "author_name": "Hans-Joerg Wertenauer", + "author_inst": "Hausaerzte am Schillerplatz, Hauptstrasse 5, 70563 Stuttgart-Vaihingen, Germany" }, { - "author_name": "Silvia Stringhini", - "author_inst": "Division and Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland" + "author_name": "Winfried Maerz", + "author_inst": "Medical Clinic V, Medical Faculty Mannheim, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.08.05.21261627", @@ -608899,155 +606872,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.04.21260420", - "rel_title": "Helmet noninvasive ventilation for COVID-19 patients (Helmet-COVID): study protocol for a multicenter randomized controlled trial", + "rel_doi": "10.1101/2021.08.03.21260966", + "rel_title": "Development and performance evaluation of a low-cost in-house rRT-PCR assay in Ecuador for the detection of SARS-CoV-2", "rel_date": "2021-08-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.04.21260420", - "rel_abs": "IntroductionNoninvasive ventilation delivered by helmet is has been used for respiratory support of patients with acute hypoxemic respiratory failure due to COVID-19 pneumonia. The aim of this study is to compare helmet noninvasive ventilation with usual care versus usual care alone to reduce the mortality.\n\nMethods and analysisThis is a multicenter, pragmatic, parallel, randomized controlled trial that compares helmet noninvasive ventilation with usual care to usual care alone in 1:1 ratio. A total of 320 patients will be enrolled in this study. The primary outcome is 28-day all-cause mortality. The primary outcome will be compared between the two study groups in the intention-to-treat and per-protocol cohorts. An interim analysis will be conducted for both safety and effectiveness.\n\nEthics and disseminationApprovals are obtained from the Institutional Review Boards (IRBs) of each participating institution. Our findings will be published in peer-review journals and presented at relevant conferences and meetings.\n\nTrial registration numberNCT04477668 registered on July 20, 2020\n\nArticle SummaryO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LIThis trial compares helmet NIV to usual care for respiratory support of patients with acute hypoxemic respiratory failure due to COVID-19 pneumonia.\nC_LIO_LIThe trial is a multi-center, pragmatic, parallel randomized controlled trial.\nC_LIO_LIThe main limitation is the unblinded design due to the nature of the intervention.\nC_LI", - "rel_num_authors": 34, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.03.21260966", + "rel_abs": "AntecedentsEcuador has had the greatest fatality rate from Coronavirus (COVID-19) in South America during the SARS-CoV-2 pandemic. To control the pandemic, it is necessary to test as much population as possible to prevent the spread of the SARS-CoV-2 infection. For the Ecuadorian population, accessing a PCR test is challenging, since commercial screening kits tend to be expensive. Objective: the objective of this study was to develop an in-house duplex rRT-PCR protocol for the detection of SARS-CoV-2 that contributes to the screening while keeping quality and low testing costs. Results: An in-house duplex rRT-PCR protocol based on the viral envelope (E) gene target of SARS-CoV-2 and a human ribonuclease P gene (RP) as an internal control is reported. The protocol was optimized to obtain primers E with an efficiency of up to 94.45% and detection of 100% of SARS-CoV-2 up to 15 copies per uL. The clinical performance was determined by a sensibility of 93.8% and specificity of 98.3%. Conclusion: we developed, standardized, and validated a low-cost, sensitive in-house duplex rRT-PCR assay that may be utilized in low-income countries.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Yaseen Arabi", - "author_inst": "Intensive Care Department, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" - }, - { - "author_name": "Haytham Tlayjeh", - "author_inst": "Intensive Care Department, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" - }, - { - "author_name": "Sara Aldekhyl", - "author_inst": "Intensive Care Department, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" - }, - { - "author_name": "Hasan Al-Dorzi", - "author_inst": "Intensive Care Department, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" + "author_name": "Marco Salinas", + "author_inst": "Central University of Ecuador" }, { - "author_name": "Sheryl Ann Abdukahil", - "author_inst": "Intensive Care Department, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" + "author_name": "Diana Aguirre", + "author_inst": "Central University of Ecuador" }, { - "author_name": "Mohammad Khulaif Al Harbi", - "author_inst": "Department of Anesthesia, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" + "author_name": "David De la Torre", + "author_inst": "Central University of Ecuador" }, { - "author_name": "Husain Al Haji", - "author_inst": "Respiratory Services Department, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" + "author_name": "Jorge P\u00e9rez-Galarza", + "author_inst": "Central University of Ecuador" }, { - "author_name": "Mohammed Al Mutairi", - "author_inst": "Respiratory Services Department, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" + "author_name": "Ronny Pibaque", + "author_inst": "Central University of Ecuador" }, { - "author_name": "Omar Al Zumai", - "author_inst": "Respiratory Services Department, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" + "author_name": "Paul Beltran", + "author_inst": "Central University of Ecuador" }, { - "author_name": "Eman Al Qasim", - "author_inst": "Intensive Care Department, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" + "author_name": "Tatiana Veloz", + "author_inst": "Central University of Ecuador" }, { - "author_name": "Wedyan Al Wehaibi", - "author_inst": "Intensive Care Department, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" - }, - { - "author_name": "Saad Al Qahtani", - "author_inst": "Intensive Care Department, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" - }, - { - "author_name": "Fahad Al-Hameed", - "author_inst": "Intensive Care Department, Ministry of National Guard Health Affairs, Jeddah, Saudi Arabia" - }, - { - "author_name": "Jamal Chalabi", - "author_inst": "Intensive Care Department, Ministry of National Guard Health Affairs, Al Ahsa, Saudi Arabia" - }, - { - "author_name": "Mohammed Alshahrani", - "author_inst": "King Fahd Hospital of the University, Al Khobar" - }, - { - "author_name": "Abdulrahman Alharthy", - "author_inst": "King Saud Medical City" - }, - { - "author_name": "Ahmed Mady", - "author_inst": "King Saud Medical City" - }, - { - "author_name": "Abdulhadi Bin Eshaq", - "author_inst": "King Khalid Hospital, Najran" - }, - { - "author_name": "Ali Al Bshabshe", - "author_inst": "Aseer Central Hospital" - }, - { - "author_name": "Zohair Al Aseri", - "author_inst": "King Saud Medical City" - }, - { - "author_name": "Zainab Al Duhailib", - "author_inst": "King Faisal Specialist Hospital and Research Center, Riyadh" - }, - { - "author_name": "Ayman Kharaba", - "author_inst": "King Fahad Hospital Madinah" - }, - { - "author_name": "Rakan Alqahtani", - "author_inst": "King Khalid University Hospital" - }, - { - "author_name": "Adnan Al Ghamdi", - "author_inst": "Prince Sultan Military Medical City" - }, - { - "author_name": "Ali Altalag", - "author_inst": "Prince Sultan Military Medical City" - }, - { - "author_name": "Khalid Alghamdi", - "author_inst": "King Faisal Specialist Hospital and Research Center, Jeddah" - }, - { - "author_name": "Mohammed Almaani", - "author_inst": "King Fahad Medical City, Riyadh" - }, - { - "author_name": "Haifa Algethamy", - "author_inst": "King Abdulaziz University Hospital, Jeddah" - }, - { - "author_name": "Ahmad Al Aqeily", - "author_inst": "Respiratory Services Department, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" - }, - { - "author_name": "Faisal Al Baseet", - "author_inst": "Respiratory Services Department, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" - }, - { - "author_name": "Hashem Al Samannoudi", - "author_inst": "Respiratory Services Department, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" - }, - { - "author_name": "Mohammed Al Obaidi", - "author_inst": "Respiratory Services Department, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" - }, - { - "author_name": "Yassin Ismaiel", - "author_inst": "Respiratory Services Department, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" - }, - { - "author_name": "Abdulrahman Al-Fares", - "author_inst": "Al Amiri Hospital, Kuwait" + "author_name": "Lucy Balde\u00f3n", + "author_inst": "Central University of Ecuador" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.08.06.455424", @@ -610645,39 +608514,619 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.04.21261595", - "rel_title": "Structural racism and COVID-19 response: Higher risk of exposure drives disparate COVID-19 deaths among Black and Hispanic/Latinx residents of Illinois, USA", + "rel_doi": "10.1101/2021.08.03.21261548", + "rel_title": "Mitigation of SARS-CoV-2 Transmission at a Large Public University", "rel_date": "2021-08-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.04.21261595", - "rel_abs": "BACKGROUNDStructural racism has driven and continues to drive policies that create the social, economic, and community factors resulting in residential segregation, lack of access to adequate healthcare, and lack of employment opportunities that would allow economic mobility. This results in overall poorer population health for minoritized people. In 2020, Black and Hispanic/Latinx communities throughout the United States, including the state of Illinois, experienced disproportionately high rates of COVID-19 cases and deaths. Public health officials in Illinois implemented targeted programs at state and local levels to increase intervention access and reduce disparities.\n\nMETHODSTo quantify how disparities in COVID outcomes evolved through the epidemic, data on SARS-CoV-2 diagnostic tests, COVID-19 cases, and COVID-19 deaths were obtained from the Illinois National Electronic Disease Surveillance System for the period from March 1 to December 31, 2020. Relative risks of COVID-19 cases and deaths were calculated for Black and Hispanic/Latinx vs. White residents, stratified by age group and epidemic interval. Deaths attributable to racial/ethnic disparities in incidence and case fatality were estimated with counterfactual simulations.\n\nRESULTSDisparities in case and death rates became less drastic after May 2020, but did not disappear, and were more pronounced at younger ages. From March to May of 2020, the risk of a COVID-19 case for Black and Hispanic/Latinx populations was more than twice that of Whites across all age groups. The relative risk of COVID-19 death reached above 10 for Black and Hispanic/Latinx individuals under 50 years of age compared to age-matched Whites in the early epidemic. In all Illinois counties, relative risk of a COVID-19 case was the same or significantly increased for minoritized populations compared to the White population. 79.3% and 86.7% of disparities in deaths among Black and Hispanic/Latinx populations, respectively, were attributable to differences in age-adjusted incidence compared to White populations rather than differences in case fatality ratios.\n\nCONCLUSIONSRacial and ethnic disparities in the COVID-19 pandemic are products of society, not biology. Considering age and geography in addition to race/ethnicity can help to identify the structural factors driving poorer outcomes for certain groups. Studies and policies aimed at reducing inequalities in disease exposure will reduce disparities in mortality more than those focused on drivers of case fatality.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.03.21261548", + "rel_abs": "In the Fall of 2020, many universities saw extensive transmission of SARS-CoV-2 among their populations, threatening the health of students, faculty and staff, the viability of in-person instruction, and the health of surrounding communities.1, 2 Here we report that a multimodal \"SHIELD: Target, Test, and Tell\" program mitigated the spread of SARS-CoV-2 at a large public university, prevented community transmission, and allowed continuation of in-person classes amidst the pandemic. The program combines epidemiological modelling and surveillance (Target); fast and frequent testing using a novel and FDA Emergency Use Authorized low-cost and scalable saliva-based RT-qPCR assay for SARS-CoV-2 that bypasses RNA extraction, called covidSHIELD (Test); and digital tools that communicate test results, notify of potential exposures, and promote compliance with public health mandates (Tell). These elements were combined with masks, social distancing, and robust education efforts. In Fall 2020, we performed more than 1,000,000 covidSHIELD tests while keeping classrooms, laboratories, and many other university activities open. Generally, our case positivity rates remained less than 0.5%, we prevented transmission from our students to our faculty and staff, and data indicate that we had no spread in our classrooms or research laboratories. During this fall semester, we had zero COVID-19-related hospitalizations or deaths amongst our university community. We also prevented transmission from our university community to the surrounding Champaign County community. Our experience demonstrates that multimodal transmission mitigation programs can enable university communities to achieve such outcomes until widespread vaccination against COVID-19 is achieved, and provides a roadmap for how future pandemics can be addressed.", + "rel_num_authors": 150, "rel_authors": [ { - "author_name": "Tobias M Holden", - "author_inst": "Northwestern University Feinberg School of Medicine, Chicago IL" + "author_name": "Diana Rose E Ranoa", + "author_inst": "University of Illinois at Urbana-Champaign" }, { - "author_name": "Melissa A Simon", - "author_inst": "Department of Obstetrics and Gynecology, Northwestern University, Chicago IL" + "author_name": "Robin L Holland", + "author_inst": "University of Illinois at Urbana-Champaign" }, { - "author_name": "Damon T Arnold", - "author_inst": "Blue Cross Blue Shield of Illinois, Chicago IL" + "author_name": "Fadi G Alnaji", + "author_inst": "University of Illinois at Urbana-Champaign" }, { - "author_name": "Veronica Halloway", - "author_inst": "Illinois Department of Public Health, Springfield IL" + "author_name": "Kelsie J Green", + "author_inst": "University of Illinois at Urbana-Champaign" }, { - "author_name": "Jaline Gerardin", - "author_inst": "Department of Preventive Medicine and Institute for Global Health, Northwestern University, Chicago IL" + "author_name": "Leyi Wang", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Richard L Fredrickson", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Tong Wang", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "George N Wong", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Johnny Uelmen", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Sergei Maslov", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Ahmed Elbanna", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Zachary J Weiner", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Alexei V Tkachenko", + "author_inst": "Brookhaven National Laboratory" + }, + { + "author_name": "Hantao Zhang", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Zhiru Liu", + "author_inst": "Stanford University" + }, + { + "author_name": "Sanjay J Patel", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "John M Paul", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Nickolas P Vance", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Joseph G Gulick", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Sandeep P Satheesan", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Isaac J Galvan", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Andrew Miller", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Joseph Grohens", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Todd J Nelson", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Mary P Stevens", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "P. Mark Hennessy", + "author_inst": "Inabyte" + }, + { + "author_name": "Robert C Parker", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Edward Santos", + "author_inst": "OSF Healthcare" + }, + { + "author_name": "Charles Brackett", + "author_inst": "OSF Healthcare" + }, + { + "author_name": "Julie D Steinman", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Melvin R Fenner Jr.", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Kristin Dohrer", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Kraig Wagenecht", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Michael DeLorenzo", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Laura Wilhelm-Barr", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Brian R Brauer", + "author_inst": "Illinois Fire Service Institute" + }, + { + "author_name": "Catherine Best-Popescu", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Gary Durack", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Nathan Wetter", + "author_inst": "Tekmill" + }, + { + "author_name": "David M Kranz", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Jessica Breitbarth", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Charlie Simpson", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Julie A Pryde", + "author_inst": "Champaign-Urbana Public Health District" + }, + { + "author_name": "Robin N Kaler", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Chris Harris", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Allison C Vance", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Jodi L Silotto", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Mark Johnson", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Enrique Valera", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Patricia K Anton", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Lowa Mwilambwe", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Stephen B Bryan", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Deborah S Stone", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Danita B Young", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Wanda E Ward", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "John Lantz", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "John A Vozenilek", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Rashid Bashir", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Jeffrey S Moore", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Mayank Garg", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Julian C Cooper", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Gillian Snyder", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Michelle H Lore", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Dustin L Yocum", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Neal J Cohen", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Jan E Novakofski", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Melanie J Loots", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Randy L Ballard", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Mark Band", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Kayla M Banks", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Joseph D Barnes", + "author_inst": "University of Illinois Health" + }, + { + "author_name": "Iuliana Bentea", + "author_inst": "University of Illinois at Chicago" + }, + { + "author_name": "Jessica Black", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Jeremy Busch", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Hannah Christensen", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Abigail Conte", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" + }, + { + "author_name": "Madison Conte", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "Michael Curry", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Jennifer Eardley", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "April Edwards", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Therese Eggett", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Judes Fleurimont", + "author_inst": "University of Illinois Health" + }, + { + "author_name": "Delaney Foster", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Bruce W Fouke", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Nicholas Gallagher", + "author_inst": "Johns Hopkins University School of Medicine" + }, + { + "author_name": "Nicole Gastala", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" + }, + { + "author_name": "Scott A Genung", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Declan Glueck", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Brittani Gray", + "author_inst": "University of Illinois Health" + }, + { + "author_name": "Andrew Greta", + "author_inst": "University of Illinois System Office" + }, + { + "author_name": "Robert M Healy", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Ashley Hetrick", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Arianna A Holterman", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Nahed Ismail", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Ian Jasenof", + "author_inst": "University of Illinois Health" + }, + { + "author_name": "Patrick Kelly", + "author_inst": "University of Wisconsin-Madison, Madison" + }, + { + "author_name": "Aaron Kielbasa", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Teresa Kiesel", + "author_inst": "University of Wisconsin-Madison, Madison" + }, + { + "author_name": "Lorenzo M Kindle", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Rhonda L Lipking", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Yukari C Manabe", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" + }, + { + "author_name": "Jade ? Mayes", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Reubin McGuffin", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Kenton G McHenry", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Agha Mirza", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "Jada Moseley", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Heba H Mostafa", + "author_inst": "Johns Hopkins University School of Medicine" + }, + { + "author_name": "Melody Mumford", + "author_inst": "University of Illinois Health" + }, + { + "author_name": "Kathleen Munoz", + "author_inst": "University of Illinois Health" + }, + { + "author_name": "Arika D Murray", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Moira Nolan", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Nil A Parikh", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Andrew Pekosz", + "author_inst": "Johns Hopkins Bloomberg School of Public Health; Johns Hopkins School of Medicine" + }, + { + "author_name": "Janna Pflugmacher", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Janise M Phillips", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Collin Pitts", + "author_inst": "University of Wisconsin-Madison, Madison" + }, + { + "author_name": "Mark C Potter", + "author_inst": "University of Illinois at Chicago" + }, + { + "author_name": "James Quisenberry", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Janelle Rear", + "author_inst": "University of Illinois System" + }, + { + "author_name": "Matthew L Robinson", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "Edith Rosillo", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Leslie N Rye", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "MaryEllen Sherwood", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Anna Simon", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Jamie M Singson", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Carly Skadden", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Tina H Skelton", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Charlie Smith", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Mary Stech", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Ryan Thomas", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Matthew A Tomaszewski", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Erika A Tyburski", + "author_inst": "Emory University School of Medicine, Children?s Healthcare of Atlanta, and Georgia Institute of Technology" + }, + { + "author_name": "Scott Vanwingerden", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Evette Vlach", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Ronald S Watkins", + "author_inst": "University of Illinois System Office" + }, + { + "author_name": "Karriem Watson", + "author_inst": "University of Illinois Health" + }, + { + "author_name": "Karen C White", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Timothy L Killeen", + "author_inst": "University of Illinois System" + }, + { + "author_name": "Robert J Jones", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Andreas C Cangellaris", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Susan A Martinis", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Awais Vaid", + "author_inst": "Champaign-Urbana Public Health District" + }, + { + "author_name": "Christopher B Brooke", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Joseph T Walsh", + "author_inst": "University of Illinois System" + }, + { + "author_name": "William C Sullivan", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Rebecca L Smith", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Nigel D Goldenfeld", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Timothy M Fan", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Paul J Hergenrother", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" + }, + { + "author_name": "Martin D Burke", + "author_inst": "University of Illinois at Urbana-Champaign; Tekmill" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.08.04.21261538", @@ -612327,33 +610776,33 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.08.04.454929", - "rel_title": "Analysis of 329,942 SARS-CoV-2 records retrieved from GISAID database", + "rel_doi": "10.1101/2021.08.03.455003", + "rel_title": "Llamanade: an open-source computational pipeline for robust nanobody humanization", "rel_date": "2021-08-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.04.454929", - "rel_abs": "BackgroundThe 31st of December 2019 was when the World Health Organization received a report about an outbreak of pneumonia of unknown etiology in the Chinese city of Wuhan. The outbreak was the result of the novel virus labeled as SARS-CoV-2, which spread to about 220 countries and caused approximately 3,311,780 deaths, infecting more than 159,319,384 people by May 12th, of 2021. The virus caused a worldwide pandemic leading to panic, quarantines, and lockdowns - although none of its predecessors from the coronavirus family have ever achieved such a scale. The key to understanding the global success of SARS-CoV-2 is hidden in its genome.\n\nMaterials and MethodsWe retrieved data for 329,942 SARS-CoV-2 records uploaded to the GISAID database from the beginning of the pandemic until the 8th of January 2021. To process the data, a Python variant detection script was developed, using pairwise2 from the BioPython library. Pandas, Matplotlib, and Seaborn, were applied to visualize the data. Genomic coordinates were obtained from the UCSC Genome Browser (https://genome.ucsc.edu/). Sequence alignments were performed for every gene separately. Genomes less than 26,000 nucleotides long were excluded from the research. Clustering was performed using HDBScan.\n\nResultsHere, we addressed the genetic variability of SARS-CoV-2 using 329,942 worldwide samples. The analysis yielded 155 genome variations (SNPs and deletions) in more than 0.3% of the sequences. Nine common SNPs were present in more than 20% of the samples. Clustering results suggested that a proportion of people (2.46%) were infected with a distinct subtype of the B.1.1.7 variant. The subtype may be characterized by four to six additional mutations, with four being a more frequent option (G28881A, G28882A, and G28883[C] in the N gene, A23403G in S, A28095T in ORF8, G25437T in ORF3a). Two clusters were formed by mutations in the samples uploaded predominantly by Denmark and Australia, which may indicate the emergence of \"Danish\" and \"Australian\" variants. Five clusters were linked to increased/decreased age, shifted gender ratio, or both. According to a correlation coefficient matrix, 69 mutations correlate with at least one other mutation (correlation coefficient greater than 0.7). We also addressed the completeness of the GISAID database, where between 77% and 93% of the fields were either left blank or filled incorrectly. Metadata mining analysis has led to a hypothesis about gender inequality in medical care in certain countries. Finally, we found ORF6 and E as the most conserved genes (96.15% and 94.66% of the sequences totally match the reference, respectively), making them potential targets for vaccines and treatment. Our results indicate areas of the SARS-CoV-2 genome that researchers can focus on for further structural and functional analysis.", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.03.455003", + "rel_abs": "Nanobodies (Nbs) have recently emerged as a promising class of antibody fragments for biomedical and therapeutic applications. Despite having marked physicochemical properties, Nbs are derived from camelids and may require \"humanization\" to improve translational potentials for clinical trials. Here we have systematically analyzed the sequence and structural properties of Nbs based on NGS (next-generation sequencing) databases and high-resolution structures. Our analysis reveals substantial framework diversities and underscores the key differences between Nbs and human Immunoglobulin G (IgG) antibodies. We identified conserved residues that may contribute to enhanced solubility, structural stability, and antigen-binding, providing insights into Nb humanization. Based on big data analysis, we developed \"Llamanade, a user-friendly, open-source to facilitate rational humanization of Nbs. Using Nb sequence as input, Llamanade provides information on the sequence features, model structures, and optimizes solutions to humanize Nbs. The full analysis for a given Nb takes less than a minute on a local computer. To demonstrate the robustness of this tool, we applied it to successfully humanize a cohort of structurally diverse and highly potent SARS-CoV-2 neutralizing Nbs. Llamanade is freely available and will be easily accessible on a web server to support the development of a rapidly expanding repertoire of therapeutic Nbs into safe and effective trials.\n\nAuthor SummaryCamelid Nbs are characterized by small size, excellent pharmacological properties and high flexibility in bioengineering for therapeutic development. However, Nbs are \"xeno\" antibodies, which require \"humanization\" to improve their translational potential. Currently, there is a lack of systematic investigation of Nbs to rationally guide humanization. No dedicated software has been developed for this purpose. Here, we report the development of Llamanade, an open-source computational pipeline and the first dedicated software to facilitate rational humanization of Nbs.\n\nTo subjectively evaluate Llamanade, we used it to humanize a cohort of structurally diverse and ultrapotent antiviral Nbs against SARS-CoV-2. Robust humanization by Llamanade significantly improved the humanness level of Nbs to closely resemble fully human IgGs. Importantly, these highly humanized antiviral Nbs remained excellent solubility and comparably high bioactivities to the non-humanized Nb precursors. We envision that Llamanade will help advance Nb research into therapeutic development.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Maria Zelenova", - "author_inst": "Mental Health Research Center" + "author_name": "Zhe Sang", + "author_inst": "University of Pittsburgh, Department of Computational and Systems Biology" }, { - "author_name": "Anna Ivanova", - "author_inst": "Quantori, LLC" + "author_name": "Yufei Xiang", + "author_inst": "University of Pittsburgh, Department of Cell Biology" }, { - "author_name": "Semyon Semyonov", - "author_inst": "Quantori, LLC" + "author_name": "Ivet Bahar", + "author_inst": "University of Pittsburgh, Department of Computational and Systems Biology" }, { - "author_name": "Yuriy Gankin", - "author_inst": "Quantori, LLC" + "author_name": "Yi Shi", + "author_inst": "University of Pittsburgh, Department of Cell Biology" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "new results", "category": "bioinformatics" }, @@ -614437,47 +612886,79 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.07.31.454592", - "rel_title": "SARS-CoV-2 fears green: the chlorophyll catabolite Pheophorbide a is a potent antiviral", - "rel_date": "2021-08-02", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.31.454592", - "rel_abs": "SARS-CoV-2 pandemic is having devastating consequences worldwide. Although vaccination advances at good pace, effectiveness against emerging variants is unpredictable. The virus has displayed a remarkable resistance to treatments and no drugs have been proved fully effective against Covid-19. Thus, despite the international efforts, there is still an urgent need for new potent and safe antivirals against SARS-CoV-2. Here we exploited the enormous potential of plant metabolism using the bryophyte Marchantia polymorpha and identified a potent SARS-CoV-2 antiviral, following a bioactivity-guided fractionation and mass-spectrometry approach. We found that the chlorophyll derivative Pheophorbide a (PheoA), a porphyrin compound similar to animal Protoporphyrin IX, has an extraordinary antiviral activity against SARS-CoV-2 preventing infection of cultured monkey and human cells, without noticeable cytotoxicity. We also show that PheoA prevents coronavirus entry into the cells by directly targeting the viral particle. Besides SARS-CoV-2, PheoA also displayed a broad-spectrum antiviral activity against (+) strand RNA viral pathogens such as HCV, West Nile, and other coronaviruses, but not against (-) strand RNA viruses, such as VSV. Our results indicate that PheoA displays a remarkable potency and a satisfactory therapeutic index, which together with its previous use in photoactivable cancer therapy in humans, suggest that it may be considered as a potential candidate for antiviral therapy against SARS-CoV-2.", - "rel_num_authors": 7, + "rel_doi": "10.1101/2021.07.30.21261351", + "rel_title": "KNOWLEDGE AND RISK PERCEPTION OF NIGERIANS TOWARDS THE CORONAVIRUS DISEASE (COVID-19)", + "rel_date": "2021-08-01", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.30.21261351", + "rel_abs": "ABSTARCTO_ST_ABSBackgroundC_ST_ABSThe Coronavirus Disease 2019 (COVID-19) is far from over, although appreciable progress has been made to limit the devastating effects of the pandemic across the globe. Adequate knowledge and risk perception is a critical assessment that is required to ensure proper preventive measures. This study assessed these among Nigerians.\n\nMethodsThe study was a cross-sectional assessment of 776 consenting Nigerian adults that were distributed across the 6 geo-political zones and the Federal Capital Territory. Online pre-tested, semi-structured questionnaire were used to obtain the socio-demographic data and assessed the knowledge and risk perception of the participants to COVID-19. The knowledge of COVID-19 was assessed based on the number of accurate responses given in comparison to average scores. Chi-square analysis was computed to analysis the association between socio-demographic characteristics and knowledge of COVID-19 and risk perception. Data analysis was done using SPSS version 21, the level of significance was set at value p<0.05 at 95% confidence interval.\n\nResultsMajority of the participants were male 451 (58.1%), there was a good knowledge of COVID-19 among 90.3% of respondents with 57% having positive risk perception. There was a statistically significant relationship between good knowledge and positive risk perception of COVID-19 (p < 0.001). Annual income (p =0.012) and the perception that \"vaccines are good\" significantly predict positive risk perception of COVID-19 among the respondents.\n\nConclusionA good knowledge of COVID-19 and vaccination against the virus were the two most important factors that determined risk perception among the population. This may be because of the widespread advocacy, and it portends a good omen at combating COVID-19 menace.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Guillermo H Jimenez-Aleman", - "author_inst": "National Centre for Biotechnology (CNB-CSIC)" + "author_name": "Bolaji Felicia Udomah", + "author_inst": "University of Osun Teaching Hospital, Osogbo, Osun State, Nigeria" }, { - "author_name": "Victoria Castro", - "author_inst": "National Centre for Biotechnology (CNB-CSIC)" + "author_name": "Uriel Oludare Ashaolu", + "author_inst": "Obafemi Awolowo University Teaching Hospital Complex, Ile-Ife, Osun State, Nigeria" }, { - "author_name": "Addis Longdaitsbehere", - "author_inst": "National Centre for Biotechnology (CNB-CSIC)" + "author_name": "Charles Oluwatemitope Olomofe", + "author_inst": "Abt Associates" }, { - "author_name": "Marta Gutierrez-Rodriguez", - "author_inst": "Medicinal Chemistry Institute (IQM-CSIC)" + "author_name": "Olufunke Folasade Dada", + "author_inst": "Obafemi Awolowolo University Teaching Hospital Complex, Ile-Ife, Osun State, Nigeria" }, { - "author_name": "Urtzi Garaigorta", - "author_inst": "National Centre for Biotechnology (CNB-CSIC)" + "author_name": "Victor Kehinde Soyemi", + "author_inst": "Medical Affairs, Pharma R&D, GlaxoSmithKline Pharmaceutical, Nigeria" }, { - "author_name": "Pablo Gastaminza", - "author_inst": "National Centre for Biotechnology (CNB-CSIC)" + "author_name": "Yetunde Bolatito Aremu-Kasumu", + "author_inst": "Federal Medical Center, Gusau, Zamfara State, Nigeria" + }, + { + "author_name": "Chikezie John Ochieze", + "author_inst": "DeTar Healthcare Systems, Victoria, Texas, United States" + }, + { + "author_name": "Olusola Ayodele Adeyemi", + "author_inst": "Bafrow Medical Center, The Republic of the Gambia" + }, + { + "author_name": "Adeyinka Olabisi Owolabi", + "author_inst": "William Harvey Hospital, Willesborough, Ashford, Kent, United Kingdom" }, { - "author_name": "Roberto Solano", - "author_inst": "National Centre for Biotechnology (CNB-CSIC)" + "author_name": "Martin Chukwudum Igbokwe", + "author_inst": "Zenith Medical and Kidney Center, Kudu, Abuja, Nigeria" + }, + { + "author_name": "Emmanuel Eziashi Ajumuka", + "author_inst": "Ahmadu Bello University Teaching Hospital, Zaria, Kaduna State, Nigeria" + }, + { + "author_name": "Kehinde Williams Ologunde", + "author_inst": "Federal Medical Center, Gusau, Zamfara State, Nigeria" + }, + { + "author_name": "Gbenga Omotade Popoola", + "author_inst": "Department of Psychiatry, Federal Teaching Hospital, Ido-Ekiti, Ekiti State Nigeria" + }, + { + "author_name": "Olumuyiwa Elijah Ariyo", + "author_inst": "Federal Teaching Hospital, Ido-Ekiti" + }, + { + "author_name": "Olaniyi Bamidele Fayemi", + "author_inst": "Federal Teaching Hospital, Ido-Ekiti, Ekiti State, Nigeria" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "molecular biology" + "license": "cc_by_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.07.30.21261383", @@ -616543,21 +615024,77 @@ "category": "emergency medicine" }, { - "rel_doi": "10.1101/2021.07.24.21260660", - "rel_title": "Individual Preparedness for Distant Wildfires and the Delta Variant in the United States: A Survey of 2,250 US Residents", + "rel_doi": "10.1101/2021.07.28.21261272", + "rel_title": "Monitoring COVID-19 spread in Prague local neighborhoods based on the presence of SARS-CoV-2 RNA in wastewater collected throughout the sewer network", "rel_date": "2021-07-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.24.21260660", - "rel_abs": "BackgroundCOVID-19 virus travels in the air and collects indoors through tiny particles from exhaled breath, and remains a growing concern globally especially since case studies of vaccine breakthrough infections are being reported. Last years wildfires resulted in the worst air quality on record in the Western US due to toxic wildfire smoke (PM 2.5 pollution) traveling from distant wildfires and this year can potentially be even worse due to extremely dry conditions. Aerosol precautions such as high-filtration (Hi-Fi) masks and HEPA air purifiers are useful to effectively reduce inhalation of most of these toxic aerosols. Whereas the lack of fit or filtration in a mask or use of an air purifier of insufficient size (capacity) for the room can inadvertently render these precautions ineffective. Here we investigate the publics concerns about wildfires and the COVID-19 variants (e.g. delta), their use of aerosol precautions, and whether these are being done in an effective manner.\n\nMethodsWe conducted a national survey of 2,250 US residents in order to understand public concerns about airborne threats and their usage of airborne (aerosol) precautions.\n\nResultsWe find over 66% of US residents surveyed are worried about inhaling COVID-19 and its variants, and 52% are worried about toxic wildfire particles in the air. In the mountain and pacific regions the latter rises to 73%. Only a quarter are using masks with higher filtration and high level of fit (or Hi-Fi masks e.g. N95 or similar such as elastomeric N95 or KF94). Two-thirds are still using loose-fitting cloth or surgical masks. Just over 40% of respondents report using air purifiers at home, and of this group only 40% use it in their bedroom where they sleep. Of those using air purifiers, the majority said they chose the size of their air purifier based on \"most popular\" models, \"recommendations,\" or \"reviews.\" However, of those using air purifiers only 42% reported doing a calculation (or using a calculator) to estimate the right size of air purifier needed for the room they are using it in. Notably, a much higher percentage of people (than average) reported use of Hi-Fi masks and home air purifiers in certain occupations such as doctors, healthcare, first responders, public safety, engineering, military, and construction.\n\nConclusionNational survey data suggests most US residents are worried about wildfire smoke and Covid variants (e.g. delta variant) but a majority are not prepared for it. Preparation with aerosol precautions will also be useful for future pandemics and national biodefense.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.28.21261272", + "rel_abs": "Many reports have documented that the presence of SARS-CoV-2 RNA in the influents of municipal wastewater treatment plants (WWTP) correlates with the actual epidemic situation in a given city. However, few data have been reported thus far on measurements upstream of WWTPs, i.e. throughout the sewer network. In this study, the monitoring of the presence of SARS-CoV-2 RNA in Prague wastewater was carried out at selected locations of the Prague sewer network from August 2020 through May 2021. Various locations such as residential areas of various sizes, hospitals, city center areas, student dormitories, transportation hubs (airport, bus terminal), and commercial areas were monitored together with four of the main Prague sewers. The presence of SARS-CoV-2 RNA was determined by reverse transcription - multiplex quantitative polymerase chain reaction (RT-mqPCR) after the precipitation of nucleic acids with PEG8000 and RNA isolation with TRIzol Reagent. The number of copies of the gene encoding SARS-CoV-2 nucleocapsid (N1) per liter of wastewater was compared with the number of officially registered COVID-19 cases in Prague. Although the data obtained by sampling wastewater from the major Prague sewers were more consistent than those obtained from the small sewers, the correlation between wastewater-based and clinical-testing data was also good for the residential areas with more than 1 000 registered inhabitants. It was shown that monitoring SARS-CoV-2 RNA in wastewater sampled from small sewers could identify isolated occurrences of COVID-19-positive cases in local neighborhoods. This can be very valuable while tracking COVID-19 hotspots within large cities.\n\nHighlightsO_LISARS-CoV-2 RNA presence was measured at 24 locations in the Prague sewer network\nC_LIO_LIResidential areas (100-13 000 inhab.), transport hubs, hospitals etc. were included\nC_LIO_LIConsistent wastewater monitoring by RT-mqPCR took place from August 2020 - May 2021\nC_LIO_LIThe sampling of major Prague sewers correlated well with clinical-based data\nC_LIO_LIGrab samples can identify COVID-19 hotspots in local neighborhoods\nC_LI\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC=\"FIGDIR/small/21261272v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (25K):\norg.highwire.dtl.DTLVardef@1f6e54forg.highwire.dtl.DTLVardef@48e72borg.highwire.dtl.DTLVardef@40cdbdorg.highwire.dtl.DTLVardef@833fbb_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Devabhaktuni Srikrishna", - "author_inst": "Patient Knowhow, Inc." + "author_name": "Kamila Zdenkova", + "author_inst": "Department of Biochemistry and Microbiology, University of Chemistry and Technology Prague" + }, + { + "author_name": "Jana Bartackova", + "author_inst": "Department of Water Technology and Environmental Engineering, University of Chemistry and Technology Prague" + }, + { + "author_name": "Eliska Cermakova", + "author_inst": "Department of Biochemistry and Microbiology, University of Chemistry and Technology Prague" + }, + { + "author_name": "Katerina Demnerova", + "author_inst": "Department of Water Technology and Environmental Engineering, University of Chemistry and Technology Prague" + }, + { + "author_name": "Alzbeta Dostalkova", + "author_inst": "Department of Biotechnology , University of Chemistry and Technology Prague" + }, + { + "author_name": "Vaclav Janda", + "author_inst": "Department of Biochemistry and Microbiology, University of Chemistry and Technology Prague" + }, + { + "author_name": "Zuzana Novakova", + "author_inst": "Prazske vodovody a kanalizace, a.s." + }, + { + "author_name": "Michaela Rumlova", + "author_inst": "Department of Biotechnology , University of Chemistry and Technology Prague" + }, + { + "author_name": "Jana Rihova Ambrozova", + "author_inst": "Department of Biochemistry and Microbiology, University of Chemistry and Technology Prague" + }, + { + "author_name": "Klara Skodakova", + "author_inst": "Department of Biochemistry and Microbiology, University of Chemistry and Technology Prague" + }, + { + "author_name": "Iva Swierczkova", + "author_inst": "Military Health Institute, Military Medical Agency" + }, + { + "author_name": "Petr Sykora", + "author_inst": "Prazske vodovody a kanalizace, a.s." + }, + { + "author_name": "Dana Vejmelkova", + "author_inst": "Department of Water Technology and Environmental Engineering, University of Chemistry and Technology Prague" + }, + { + "author_name": "Jiri Wanner", + "author_inst": "Department of Water Technology and Environmental Engineering, University of Chemistry and Technology Prague" + }, + { + "author_name": "Jan Bartacek", + "author_inst": "Department of Water Technology and Environmental Engineering, University of Chemistry and Technology Prague" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -618325,67 +616862,111 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.07.28.21260990", - "rel_title": "A highly sensitive and specific SARS-CoV-2 spike- and nucleoprotein-based fluorescent multiplex immunoassay (FMIA) to measure IgG, IgA and IgM class antibodies", + "rel_doi": "10.1101/2021.07.28.21261086", + "rel_title": "Effect of vaccination and of prior infection on infectiousness of vaccine breakthrough infections and reinfections", "rel_date": "2021-07-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.28.21260990", - "rel_abs": "BackgroundValidation and standardization of accurate serological assays are crucial for the surveillance of the coronavirus disease 2019 (COVID-19) pandemic and population immunity.\n\nMethodsWe describe the analytical and clinical performance of an in-house fluorescent multiplex immunoassay (FMIA) for simultaneous quantification of antibodies against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleoprotein and spike glycoprotein. Furthermore, we calibrated IgG-FMIA against World Health Organisation (WHO) International Standard and compared FMIA results to an in-house enzyme immunoassay (EIA) and a microneutralisation test (MNT). We also compared the MNT results of two laboratories.\n\nResultsIgG-FMIA displayed 100% specificity and sensitivity for samples collected 13-150 days post-onset of symptoms (DPO). For IgA- and IgM-FMIA 100% specificity and sensitivity were obtained for a shorter time window (13-36 and 13-28 DPO for IgA- and IgM-FMIA, respectively). FMIA and EIA results displayed moderate to strong correlation, but FMIA was overall more specific and sensitive. IgG-FMIA identified 100% of samples with neutralising antibodies (NAbs). Anti-spike IgG concentrations correlated strongly ({rho}=0.77-0.84, P<2.2x10-16) with NAb titers. The NAb titers of the two laboratories displayed a very strong correlation ({rho}=0.95, P<2.2x10-16).\n\nDiscussionOur results indicate good correlation and concordance of antibody concentrations measured with different types of in-house SARS-CoV-2 antibody assays. Calibration against WHO international standard did not, however, improve the comparability of FMIA and EIA results.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.28.21261086", + "rel_abs": "SARS-CoV-2 breakthrough infections in vaccinated individuals and in those who had a prior infection have been observed globally, but the transmission potential of these infections is unknown. The RT-qPCR cycle threshold (Ct) value is inversely correlated with viral load and culturable virus. Here, we investigated differences in RT-qPCR Ct values across Qatars national cohorts of primary infections, reinfections, BNT162b2 (Pfizer-BioNTech) breakthrough infections, and mRNA-1273 (Moderna) breakthrough infections. Through matched-cohort analyses of the randomly diagnosed infections, the mean Ct value was higher in all cohorts of breakthrough infections compared to the cohort of primary infections in unvaccinated individuals. The Ct value was 1.3 (95% CI: 0.9-1.8) cycles higher for BNT162b2 breakthrough infections, 3.2 (95% CI: 1.8-4.5) cycles higher for mRNA-1273 breakthrough infections, and 4.0 (95% CI: 3.4-4.6) cycles higher for reinfections in unvaccinated individuals. Assuming a linear relationship between viral load and infectiousness, these differences imply that breakthrough infections are at least 50% less infectious than primary infections in unvaccinated individuals. Public health benefits of vaccination may have been underestimated, as COVID-19 vaccines not only protect against acquisition of infection, but also appear to protect against transmission of infection.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Anna Solastie", - "author_inst": "Department of Health Security, Expert Microbiology Unit, Finnish Institute for Health and Welfare, Helsinki, Finland" + "author_name": "Laith J Abu-Raddad", + "author_inst": "Weill Cornell Medicine-Qatar" }, { - "author_name": "Camilla Virta", - "author_inst": "Department of Health Security, Expert Microbiology Unit, Finnish Institute for Health and Welfare, Helsinki, Finland" + "author_name": "Hiam Chemaitelly", + "author_inst": "Weill Cornell Medicine-Qatar" }, { - "author_name": "Anu Haveri", - "author_inst": "Department of Health Security, Expert Microbiology Unit, Finnish Institute for Health and Welfare, Helsinki, Finland" + "author_name": "Houssein H. Ayoub", + "author_inst": "Qatar University" }, { - "author_name": "Nina Ekstr\u00f6m", - "author_inst": "Department of Health Security, Expert Microbiology Unit, Finnish Institute for Health and Welfare, Helsinki, Finland" + "author_name": "Patrick Tang", + "author_inst": "Sidra Medicine" }, { - "author_name": "Anu Kantele", - "author_inst": "Meilahti Infectious Diseases and Vaccination Research Center, MeiVac, Department of Infectious Diseases, Helsinki University Hospital and University of Helsinki" + "author_name": "Peter Coyle", + "author_inst": "Hamad Medical Corporation" }, { - "author_name": "Simo Miettinen", - "author_inst": "Department of Virology, University of Helsinki" + "author_name": "Mohammad Rubayet Hasan", + "author_inst": "Sidra Medicine" }, { - "author_name": "Johanna Lempainen", - "author_inst": "Department of Pediatrics, University of Turku and Turku University Hospital and Immunogenetics Laboratory, Institute of Biomedicine, University of Turku, Turku," + "author_name": "HADI M. YASSINE", + "author_inst": "Qatar University" }, { - "author_name": "Pinja Jalkanen", - "author_inst": "Infection and Immunity, Institute of Biomedicine, University of Turku, Turku, Finland" + "author_name": "Fatiha Benslimane", + "author_inst": "Qatar University" }, { - "author_name": "Laura Kakkola", - "author_inst": "Infection and Immunity, Institute of Biomedicine, University of Turku, Turku, Finland" + "author_name": "Hebah A. Al Khatib", + "author_inst": "Qatar University" }, { - "author_name": "Timothee Dub", - "author_inst": "Department of Health Security, Infectious Disease Control and Vaccinations Unit, Finnish Institute for Health and Welfare, Helsinki, Finland" + "author_name": "Zaina Al Kanaani", + "author_inst": "Hamad Medical Corporation" }, { - "author_name": "Ilkka Julkunen", - "author_inst": "Infection and Immunity, Institute of Biomedicine, University of Turku, Turku, Finland; Clinical Microbiology, Turku University Hospital, Turku, Finland" + "author_name": "Einas Al Kuwari", + "author_inst": "Hamad Medical Corporation" }, { - "author_name": "Merit Melin", - "author_inst": "Department of Health Security, Expert Microbiology Unit, Finnish Institute for Health and Welfare, Helsinki, Finland" + "author_name": "Andrew Jeremijenko", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Anvar Hassan Kaleeckal", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Ali Nizar Latif", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Riyazuddin Mohammad Shaik", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Hanan F. Abdul Rahim", + "author_inst": "Qatar University" + }, + { + "author_name": "Gheyath Nasrallah", + "author_inst": "Qatar University" + }, + { + "author_name": "Mohamed Ghaith Al Kuwari", + "author_inst": "Primary Health Care Corporation" + }, + { + "author_name": "Adeel A Butt", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Hamad Eid Al Romaihi", + "author_inst": "Ministry of Public Health" + }, + { + "author_name": "Abdullatif Al Khal", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Mohamed H. Al-Thani", + "author_inst": "Ministry of Public Health" + }, + { + "author_name": "Roberto Bertollini", + "author_inst": "Ministry of Public Health" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.07.27.21261221", @@ -620019,127 +618600,71 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.07.29.454333", - "rel_title": "Antibody Evolution after SARS-CoV-2 mRNA Vaccination", + "rel_doi": "10.1101/2021.07.29.454326", + "rel_title": "SARS-CoV-2 exposure in wild white-tailed deer (Odocoileus virginianus)", "rel_date": "2021-07-29", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.29.454333", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection produces B-cell responses that continue to evolve for at least one year. During that time, memory B cells express increasingly broad and potent antibodies that are resistant to mutations found in variants of concern1. As a result, vaccination of coronavirus disease 2019 (COVID-19) convalescent individuals with currently available mRNA vaccines produces high levels of plasma neutralizing activity against all variants tested1, 2. Here, we examine memory B cell evolution 5 months after vaccination with either Moderna (mRNA-1273) or Pfizer- BioNTech (BNT162b2) mRNA vaccines in a cohort of SARS-CoV-2 naive individuals. Between prime and boost, memory B cells produce antibodies that evolve increased neutralizing activity, but there is no further increase in potency or breadth thereafter. Instead, memory B cells that emerge 5 months after vaccination of naive individuals express antibodies that are similar to those that dominate the initial response. While individual memory antibodies selected over time by natural infection have greater potency and breadth than antibodies elicited by vaccination, the overall neutralizing potency of plasma is greater following vaccination. These results suggest that boosting vaccinated individuals with currently available mRNA vaccines will increase plasma neutralizing activity but may not produce antibodies with breadth equivalent to those obtained by vaccinating convalescent individuals.", - "rel_num_authors": 27, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.29.454326", + "rel_abs": "Widespread human SARS-CoV-2 infections combined with human-wildlife interactions create the potential for reverse zoonosis from humans to wildlife. We targeted white-tailed deer (Odocoileus virginianus) for serosurveillance based on evidence these deer have ACE2 receptors with high affinity for SARS-CoV-2, are permissive to infection, exhibit sustained viral shedding, can transmit to conspecifics, and can be abundant near urban centers. We evaluated 624 pre- and post-pandemic serum samples from wild deer from four U.S. states for SARS-CoV-2 exposure. Antibodies were detected in 152 samples (40%) from 2021 using a surrogate virus neutralization test. A subset of samples was tested using a SARS-CoV-2 virus neutralization test with high concordance between tests. These data suggest white-tailed deer in the populations assessed have been exposed to SARS-CoV-2.\n\nOne-Sentence SummaryAntibodies to SARS-CoV-2 were detected in 40% of wild white-tailed deer sampled from four U.S. states in 2021.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Alice Cho", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Frauke Muecksch", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Dennis Schaefer-Babajew", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Zijun Wang", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Shlomo Finkin", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Christian Gaebler", - "author_inst": "The Rockefeller University" - }, - { - "author_name": "Victor Ramos", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Melissa Cipolla", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Pilar Mendoza", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Marianna Agudelo", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Eva Bednarski", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Justin DaSilva", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Irina Shimeliovich", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Juan Dizon", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Mridushi Daga", - "author_inst": "Rockefeller University" + "author_name": "Jeffrey C Chandler", + "author_inst": "USDA APHIS WS National Wildlife Research Center" }, { - "author_name": "Katrina Millard", - "author_inst": "Rockefeller University" + "author_name": "Sarah N Bevins", + "author_inst": "USDA APHIS WS National Wildlife Research Center" }, { - "author_name": "Martina Turroja", - "author_inst": "Rockefeller University" + "author_name": "Jeremy W Ellis", + "author_inst": "USDA APHIS WS National Wildlife Research Center" }, { - "author_name": "Fabian Schmidt", - "author_inst": "Rockefeller University" + "author_name": "Timothy J Linder", + "author_inst": "USDA APHIS WS National Wildlife Disease Program" }, { - "author_name": "Fengwen Zhang", - "author_inst": "Rockefeller University" + "author_name": "Rachel M Tell", + "author_inst": "USDA APHIS VS National Veterinary Services Laboratories" }, { - "author_name": "Tarek Ben Tanfous", - "author_inst": "Rockefeller University" + "author_name": "Melinda Jenkins-Moore", + "author_inst": "USDA APHIS VS National Veterinary Services Laboratories" }, { - "author_name": "Mila Jankovic", - "author_inst": "Rockefeller University" + "author_name": "J Jeffrey Root", + "author_inst": "USDA APHIS WS National Wildlife Research Center" }, { - "author_name": "Thiago Oliveira", - "author_inst": "Rockefeller University" + "author_name": "Julianna B Lenoch", + "author_inst": "USDA APHIS WS National Wildlife Disease Program" }, { - "author_name": "Anna Gazumyan", - "author_inst": "Rockefeller University" + "author_name": "Suelee Robbe-Austerman", + "author_inst": "USDA APHIS VS National Veterinary Services Laboratories" }, { - "author_name": "Marina Caskey", - "author_inst": "The Rockefeller University" + "author_name": "Thomas J DeLiberto", + "author_inst": "USDA APHIS WS National Wildlife Research Center" }, { - "author_name": "Paul D Bieniasz", - "author_inst": "The Rockefeller University" + "author_name": "Thomas Gidlewski", + "author_inst": "USDA APHIS WS National Wildlife Disease Program" }, { - "author_name": "Theodora Hatziioannou", - "author_inst": "Rockefeller University" + "author_name": "Mia Kim Torchetti", + "author_inst": "USDA APHIS VS National Veterinary Services Laboratories" }, { - "author_name": "Michel C. Nussenzweig", - "author_inst": "Rockefeller University" + "author_name": "Susan A Shriner", + "author_inst": "USDA APHIS WS National Wildlife Research Center" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc0", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.07.25.21260838", @@ -622217,47 +620742,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.07.26.453874", - "rel_title": "Understanding SARS-CoV-2 budding through molecular dynamics simulations of M and E protein complexes", + "rel_doi": "10.1101/2021.07.27.453834", + "rel_title": "Site-specific recognition of SARS-CoV-2 nsp1 protein with a tailored titanium dioxide nanoparticle", "rel_date": "2021-07-27", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.26.453874", - "rel_abs": "SARS-CoV-2 and other coronaviruses pose major threats to global health, yet computational efforts to understand them have largely overlooked the process of budding, a key part of the coronavirus life cycle. When expressed together, coronavirus M and E proteins are sufficient to facilitate budding into the ER-Golgi intermediate compartment (ERGIC). To help elucidate budding, we ran atomistic molecular dynamics (MD) simulations using the Feig laboratorys refined structural models of the SARS-CoV-2 M protein dimer and E protein pentamer. Our MD simulations consisted of M protein dimers and E protein pentamers in patches of membrane. By examining where these proteins induced membrane curvature in silico, we obtained insights around how the budding process may occur. Multiple M protein dimers acted together to induce global membrane curvature through protein-lipid interactions while E protein pentamers kept the membrane planar. These results could eventually help guide development of antiviral therapeutics which inhibit coronavirus budding.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.27.453834", + "rel_abs": "The ongoing world-wide Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) pandemic shows the need for new sensing and therapeutic means against the CoV viruses. The SARS-CoV-2 nsp1 protein is important, both for replication and pathogenesis, making it an attractive target for intervention. In recent years nanoparticles have been shown to interact with peptides, ranging in size from single amino acids up to proteins. These nanoparticles can be tailor-made with specific functions and properties including bioavailability. To the best of our knowledge, in this study we show for the first time that a tailored titanium oxide nanoparticle interacts specifically with a unique site of the full-length SARS-CoV-2 nsp1 protein. This can be developed potentially into a tool for selective control of viral protein functions.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Logan Thrasher Collins", - "author_inst": "Conduit Computing; Washington University in St. Louis" - }, - { - "author_name": "Tamer Elkholy", - "author_inst": "Conduit Computing; Zapata Computing" + "author_name": "Peter Agback", + "author_inst": "Swedish University of Agricultural Sciences" }, { - "author_name": "Shafat Mubin", - "author_inst": "Conduit Computing; Valdosta State University" + "author_name": "Tatiana Agback", + "author_inst": "Swedish University of Agricultural Sciences: Sveriges lantbruksuniversitet" }, { - "author_name": "David Hill", - "author_inst": "Conduit Computing; Xeviosoft" + "author_name": "Francisco Dominguez", + "author_inst": "The University of Alabama at Birmingham" }, { - "author_name": "Ricky Williams", - "author_inst": "Conduit Computing; Harvard University" + "author_name": "Elena I Frolova", + "author_inst": "University of Alabama at Birmingham" }, { - "author_name": "Kayode Ezike", - "author_inst": "Conduit Computing; Attune" + "author_name": "Gulaim Seisenbaeva", + "author_inst": "Swedish University of Agricultural Sciences" }, { - "author_name": "Ankush Singhal", - "author_inst": "Conduit Computing; Leiden University" + "author_name": "Vadim Kessler", + "author_inst": "Swedish University of Agricultural Sciences" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "biophysics" + "category": "molecular biology" }, { "rel_doi": "10.1101/2021.07.27.453843", @@ -624231,83 +622752,83 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.19.21260777", - "rel_title": "Characterization of SARS-CoV-2 Genetic Material in Wastewater", + "rel_doi": "10.1101/2021.07.22.21258785", + "rel_title": "Proton pump inhibitor use is not associated with severe COVID-19 related outcomes: A propensity score weighted analysis of a national veteran cohort", "rel_date": "2021-07-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.19.21260777", - "rel_abs": "SARS-CoV-2 genetic material has been detected in raw wastewater around the world throughout the COVID-19 pandemic and has served as a useful tool for monitoring community levels of SARS-CoV-2 infections. SARS-CoV-2 genetic material is highly detectable in a patients feces and the household wastewater for several days before and after a positive COVID-19 qPCR test from throat or sputum samples. Here, we characterize genetic material collected from raw wastewater samples and determine recovery efficiency during a concentration process. We find that pasteurization of raw wastewater samples did not reduce SARS-CoV-2 signal if RNA is extracted immediately after pasteurization. On the contrary, we find that signal decreased by approximately half when RNA was extracted 24-36 hours post-pasteurization and [~]90% when freeze-thawed prior to concentration. As a matrix control, we use an engineered enveloped RNA virus. Surprisingly, after concentration, the recovery of SARS-CoV-2 signal is consistently higher than the recovery of the control virus leading us to question the nature of the SARS-CoV-2 genetic material detected in wastewater. We see no significant difference in signal after different 24-hour temperature changes; however, treatment with detergent decreases signal [~]100-fold. Furthermore, the density of the samples is comparable to enveloped retrovirus particles, yet, interestingly, when raw wastewater samples were used to inoculate cells, no cytopathic effects were seen indicating that wastewater samples do not contain infectious SARS-CoV-2. Together, this suggests that wastewater contains fully intact enveloped particles.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.22.21258785", + "rel_abs": "Background and AimsLow pH deactivates most pathogens, including coronaviruses. Proton pump inhibitors (PPIs) are potent gastric acid suppressing medications. Whether PPI use vs non-use is associated with severe Coronavirus disease-2019 (COVID-19) outcomes remains uncertain. We aimed to compare severe COVID-19 outcomes between current outpatient PPI users and non-users.\n\nMethodsWe conducted a retrospective propensity score-weighted analysis of a national cohort of US veterans with established care who tested positive for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) through January 9, 2021, and who had 60 days of follow-up. The positive test date was the index date. Current outpatient PPI use up to and including the index date (primary exposure) was compared to non-use, defined as no PPI prescription fill in the 365 days prior to the index date. The primary outcome was a composite of use of mechanical ventilation or death within 60 days. Weighted logistic regression models evaluated severe COVID-19 outcomes between current PPI users vs non-users.\n\nResultsOf 97,674 Veterans with SARS-CoV-2 testing, 14,958 tested positive (6262 [41.9%] current PPI users, 8696 [58.1%] non-users) and comprised the analytic cohort. After weighting, all covariates were well-balanced. In the weighted cohort, there was no difference in the primary composite outcome (8.2% vs 8.0%; OR 1.03, 95% CI 0.91-1.16), secondary composite outcome, nor individual component outcomes between current PPI users and non-users. There was no significant interaction between age and PPI use on outcomes.\n\nConclusionAmong patients with SARS-CoV-2 infection, current PPI use vs non-use is not associated with severe COVID-19 outcomes.", "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Carolyn A Robinson", - "author_inst": "University of Missouri" + "author_name": "Shailja C. Shah", + "author_inst": "Veterans Affairs San Diego Healthcare System" }, { - "author_name": "Hsin-yeh Hsieh", - "author_inst": "University of Missouri" + "author_name": "Alese Halvorson", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Shu Yu Hsu", - "author_inst": "University of Missouri-Columbia" + "author_name": "Brandon McBay", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Yang Wang", - "author_inst": "University of Missouri-Columbia" + "author_name": "Chad Dorn", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Braxton Salcedo", - "author_inst": "University of Missouri" + "author_name": "Otis Wilson", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Jessica Klutts", - "author_inst": "Missouri Department of Natural Resources" + "author_name": "Sony Tuteja", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Sally Zemmer", - "author_inst": "Missouri Department of Natural Resources" + "author_name": "Kyong-Mi Chang", + "author_inst": "Cpl Michael J. Crescenz VAMC & University of Pennsylvania" }, { - "author_name": "Anthony Belenchia", - "author_inst": "Missouri Department of Health and Senior Services" + "author_name": "Ayako Suzuki", + "author_inst": "Duke University" }, { - "author_name": "Melissa Reynolds", - "author_inst": "Missouri Department of Health and Senior Services" + "author_name": "Christine Hunt", + "author_inst": "Duke University and Durham VA Medical Center" }, { - "author_name": "Elizabeth Semkiw", - "author_inst": "Missouri Department of Health and Senior Services" + "author_name": "Richard Hauger", + "author_inst": "University of California, San Diego" }, { - "author_name": "Trevor Foley", - "author_inst": "Missouri Department of Corrections" + "author_name": "Kelly Cho", + "author_inst": "VA Boston Healthcare System" }, { - "author_name": "Xiu-feng Wan", - "author_inst": "University of Missouri" + "author_name": "Edward Siew", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Chris Wieberg", - "author_inst": "Missouri Department of Natural Resources" + "author_name": "Michael Matheny", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Jeff Wenzel", - "author_inst": "Missouri Department of Health and Senior Services" + "author_name": "Adriana Hung", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Chung-Ho Lin", - "author_inst": "University of Missouri" + "author_name": "Robert Greevy", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Marc C Johnson", - "author_inst": "University of Missouri" + "author_name": "Christianne Roumie", + "author_inst": "Vanderbilt University Medical Center" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "gastroenterology" }, { "rel_doi": "10.1101/2021.07.22.21260878", @@ -626217,55 +624738,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.19.21260794", - "rel_title": "Comparative profiles of SARS-CoV-2 Spike-specific milk antibodies elicited by COVID-19 vaccines currently authorized in the USA", + "rel_doi": "10.1101/2021.07.20.21260842", + "rel_title": "Change in age distribution of COVID-19 deaths with the introduction of COVID-19 vaccination", "rel_date": "2021-07-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.19.21260794", - "rel_abs": "Numerous COVID-19 vaccines are authorized globally. To date, [~]71% of doses are comprised of the Pfizer/BioNTech vaccine, and [~]17% the Moderna/NIH vaccine, both of which are mRNA-based. The chimpanzee Ad-based Oxford/AstraZeneca (AZ) vaccine comprises [~]9%, while the Johnson & Johnson/Janssen (J&J) human adenovirus (Ad26) vaccine ranks 4th at [~]2% [1]. No COVID-19 vaccines are yet available for children 0-4. One method to protect this population may be passive immunization via antibodies (Abs) provided in the milk of a lactating vaccinated person. Our early work [2] and other reports [3-5] have demonstrated that unlike the post-SARS-CoV-2 infection milk Ab profile, which is rich in specific secretory (s)IgA, the vaccine response is highly IgG-dominant. In this report, we present a comparative assessment of the milk Ab response elicited by Pfizer, Moderna, J&J, and AZ vaccines. This analysis revealed 86% -100% of mRNA vaccine recipient milk exhibited Spike-specific IgG endpoint titers, which were 12 - 28-fold higher than those measured for Ad vaccine recipient milk. Ad-based vaccines elicited Spike-specific milk IgG in only 33%-38% of recipients. Specific IgA was measured in 52%-71% of mRNA vaccine recipient milk and 17%-23% of Ad vaccine recipient milk. J&J recipient milk exhibited significantly lower IgA than Moderna recipients, and AZ recipients exhibited significantly lower IgA titers than Moderna and Pfizer. <50% of milk of any group exhibited specific secretory Ab, with Moderna recipient IgA titers measuring significantly higher than AZ. Moderna appeared to most frequently elicit >2-fold increases in specific secretory Ab titer relative to pre-vaccine sample. These data indicate that current Ad-based COVID-19 vaccines poorly elicit Spike-specific Ab in milk compared to mRNA-based vaccines and that mRNA vaccines are preferred for immunizing the lactating population. This study highlights the need to design vaccines better aimed at eliciting an optimal milk Ab response.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.20.21260842", + "rel_abs": "BackgroundMost countries initially deployed COVID-19 vaccines preferentially in elderly populations. Population-level vaccine effectiveness may be heralded by an increase in the proportion of deaths among non-elderly populations that were less covered by vaccination programs.\n\nMethodsWe collected data from 40 countries on age-stratified COVID-19 deaths during the vaccination period (1/14/2021-5/31/2021) and two control periods (entire pre-vaccination period and excluding the first wave). We meta-analyzed the proportion of deaths in different age groups in vaccination versus control periods in countries with low vaccination rates; (2) countries with age-independent vaccination policies; and (3) countries with standard age-dependent vaccination policies.\n\nFindingsCountries that prioritized vaccination among older people saw an increasing share of deaths among 0-69 year old people in the vaccination versus the two control periods (summary prevalence ratio 1{middle dot}32 [95 CI% 1{middle dot}24-1{middle dot}41] and 1{middle dot}35 [95 CI% 1{middle dot}26-1{middle dot}44)]. No such change was seen on average in countries with age-independent vaccination policies (1{middle dot}05 [95 CI% 0{middle dot}78-1{middle dot}41 and 0{middle dot}97 [95 CI% 0{middle dot}95-1{middle dot}00], respectively) and limited vaccination (0{middle dot}93 [95 CI% 0{middle dot}85-1{middle dot}01] and 0{middle dot}95 [95 CI% 0{middle dot}87-1{middle dot}03], respectively). Prevalence ratios were associated with the difference of vaccination rates in elderly versus non-elderly people. No significant changes occurred in the share of deaths in age 0-49 among all 0-69 deaths in the vaccination versus pre-vaccination periods.\n\nInterpretationThe substantial shift in the age distribution of COVID-19 deaths in countries that rapidly implemented vaccination predominantly among elderly may herald the population level-effectiveness of COVID-19 vaccination and a favorable evolution of the pandemic towards endemicity with fewer elderly deaths.\n\nFundingThis study received no specific funding.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Xiaoqi Yang", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Alisa Fox", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Roberta Pastorino", + "author_inst": "Fondazione Policlinico Universitario A. Gemelli IRCCS" }, { - "author_name": "Claire DeCarlo", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Angelo Maria Pezzullo", + "author_inst": "Universit\u00e0 Cattolica del Sacro Cuore" }, { - "author_name": "Caroline Norris", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Leonardo Villani", + "author_inst": "Universit\u00e0 Cattolica del Sacro Cuore" }, { - "author_name": "Samantha Griffin", - "author_inst": "Imperial College London" + "author_name": "Francesco Andrea Causio", + "author_inst": "Universit\u00e0 Cattolica del Sacro Cuore" }, { - "author_name": "Sophie Wedekind", - "author_inst": "Imperial College London" + "author_name": "Cathrine Axfors", + "author_inst": "Stanford University" }, { - "author_name": "James M Flanagan", - "author_inst": "Imperial College London" + "author_name": "Despina G. Contopoulos-Ioannidis", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Rebecca L Powell", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Stefania Boccia", + "author_inst": "Universit\u00e0 Cattolica del Sacro Cuore" }, { - "author_name": "Natalie Shenker", - "author_inst": "Imperial College London" + "author_name": "John P.A. Ioannidis", + "author_inst": "Stanford University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.07.19.21260721", @@ -629107,39 +627624,39 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2021.07.23.453524", - "rel_title": "US Dog Importations during the COVID-19 Pandemic: Do we have an erupting problem?", + "rel_doi": "10.1101/2021.07.23.453488", + "rel_title": "TMPRSS2 promotes SARS-CoV-2 evasion from NCOA7-mediated restriction", "rel_date": "2021-07-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.23.453524", - "rel_abs": "Dog importation data from 2018-2020 were evaluated to ascertain whether the dog importation patterns in the United States changed during the COVID-19 pandemic, specifically with regard to denial of entry. Dog denial of entry reports from January 1, 2018, to December 31, 2020, stored within the Centers for Disease Control and Prevention (CDC) Quarantine Activity Reporting System, were reviewed. Basic descriptive statistics were used to analyze the data. Reason for denial, country of origin, and month of importation were all examined to determine which countries of origin resulted in the largest number of denials, and whether there was a seasonal change in importations during the COVID-19 pandemic (2020), compared to previous years (2018 and 2019). During 2020, CDC denied entry to 458 dogs. This represents a 52% increase in dogs denied entry compared to the averages in 2018 and 2019. Dogs were primarily denied entry for falsified rabies vaccination certificates (56%). Three countries exported 74% of all dogs denied entry into the United States, suggesting that targeted interventions may be needed for certain countries. Increased attempts to import inadequately vaccinated dogs from countries with canine rabies in 2020 may have been due to the increased demand for domestic pets during the COVID-19 pandemic. Educational messaging should highlight the risk of rabies and the importance of making informed pet purchases from foreign entities to protect pet owners, their families, and the public.", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.23.453488", + "rel_abs": "Interferons play a critical role in regulating host immune responses to SARS-CoV-2, but the interferon (IFN)-stimulated gene (ISG) effectors that inhibit SARS-CoV-2 are not well characterized. The IFN-inducible short isoform of human nuclear receptor coactivator 7 (NCOA7) inhibits endocytic virus entry, interacts with the vacuolar ATPase, and promotes endo-lysosomal vesicle acidification and lysosomal protease activity. Here, we used ectopic expression and gene knockout to demonstrate that NCOA7 inhibits infection by SARS-CoV-2 as well as by lentivirus particles pseudotyped with SARS-CoV-2 Spike in lung epithelial cells. Infection with the highly pathogenic, SARS-CoV-1 and MERS-CoV, or seasonal, HCoV-229E and HCoV-NL63, coronavirus Spike-pseudotyped viruses was also inhibited by NCOA7. Importantly, either overexpression of TMPRSS2, which promotes plasma membrane fusion versus endosomal fusion of SARS-CoV-2, or removal of Spikes polybasic furin cleavage site rendered SARS-CoV-2 less sensitive to NCOA7 restriction. Collectively, our data indicate that furin cleavage sensitizes SARS-CoV-2 Spike to the antiviral consequences of endosomal acidification by NCOA7, and suggest that the acquisition of furin cleavage may have favoured the co-option of cell surface TMPRSS proteases as a strategy to evade the suppressive effects of IFN-induced endo-lysosomal dysregulation on virus infection.", "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Emily G Pieracci", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Caroline Goujon", + "author_inst": "Montpellier University: Universite de Montpellier" }, { - "author_name": "Cara Williams", - "author_inst": "CDC: Centers for Disease Control and Prevention" + "author_name": "David Matthews", + "author_inst": "University of Bristol" }, { - "author_name": "Ryan M Wallace", - "author_inst": "CDC: Centers for Disease Control and Prevention" + "author_name": "Andrew Davidson", + "author_inst": "University of Bristol" }, { - "author_name": "Cheryl Kalapura", - "author_inst": "CDC: Centers for Disease Control and Prevention" + "author_name": "Suzannah Rihn", + "author_inst": "University of Glasgow" }, { - "author_name": "Clive M Brown", - "author_inst": "CDC: Centers for Disease Control and Prevention" + "author_name": "Massimo Palmarini", + "author_inst": "University of Glasgow" } ], "version": "1", - "license": "cc0", + "license": "cc_by", "type": "new results", - "category": "scientific communication and education" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.07.20.21260558", @@ -631113,81 +629630,65 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2021.07.19.21260445", - "rel_title": "Single-dose mRNA vaccine effectiveness against SARS-CoV-2 in healthcare workers extending 16 weeks post-vaccination: a test-negative design from Quebec, Canada", + "rel_doi": "10.1101/2021.07.19.21260726", + "rel_title": "SARS-CoV-2 Genomic Surveillance Reveals Little Spread Between a Large University Campus and the Surrounding Community", "rel_date": "2021-07-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.19.21260445", - "rel_abs": "IntroductionIn Canada, first and second doses of mRNA vaccines against SARS-CoV-2 were uniquely spaced 16 weeks apart, but the duration of single-dose protection remains uncertain. We estimated one- and two-dose mRNA vaccine effectiveness (VE) among healthcare workers (HCWs) in Quebec, Canada including protection against varying outcome severity, variants of concern (VOC), and the stability of single-dose protection out to 16 weeks post-vaccination.\n\nMethodsA test-negative design compared vaccination among SARS-CoV-2 test-positive and weekly-matched (10:1), randomly-sampled, test-negative HCWs using linked surveillance and immunization databases. Vaccine status was defined by one dose [≥]14 days or two doses [≥]7 days before illness onset or specimen collection. Adjusted VE was estimated by conditional logistic regression.\n\nResultsPrimary analysis included 5,316 cases and 53,160 controls. Single-dose VE was 70% (95%CI: 68-73) against SARS-CoV-2 infection, 73% (95%CI: 71-75) against COVID-19 illness and 97% (95%CI: 92-99) against associated hospitalization. Two-dose VE was 86% (95%CI: 81-90) and 93% (95%CI: 89-95), respectively, with no associated hospitalizations. VE was higher for non-VOC than VOC (73% Alpha) among single-dose (77%, 95%CI: 73-81 versus 63%, 95%CI: 57-67) but not two-dose recipients (87%, 95%CI: 57-96 versus 94%, 95%CI: 89-96). Across 16 weeks, no decline in single-dose VE was observed with appropriate stratification based upon prioritized vaccination determined by higher versus lower likelihood of direct patient contact.\n\nConclusionOne mRNA vaccine dose provided substantial and sustained protection to HCWs extending at least four months post-vaccination. In circumstances of vaccine shortage, delaying the second dose may be a pertinent public health strategy to consider.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.19.21260726", + "rel_abs": "COVID-19 has had high incidence at institutions of higher education (IHE) in the United States, but the transmission dynamics in these settings are not well understood. It remains unclear to what extent IHE-associated outbreaks have contributed to transmission in nearby communities. We implemented high-density prospective genomic surveillance to investigate these dynamics at the University of Michigan-Ann Arbor and the surrounding community during the Fall 2020 semester (August 16th -November 24th). We sequenced complete SARS-CoV-2 genomes from 1659 individuals, including 468 students, representing 20% of cases in students and 25% of total confirmed cases in Washtenaw County over the study interval. Phylogenetic analysis identified over 200 introductions into the student population, most of which were not related to other student cases. There were two prolonged transmission clusters among students that spanned across multiple on-campus residences. However, there were very few genetic descendants of student clusters among non-students during a subsequent November wave of infections in the community. We conclude that outbreaks at the University of Michigan did not significantly contribute to the rise in Washtenaw County COVID-19 incidence during November 2020. These results provide valuable insights into the distinct transmission dynamics of SARS-CoV-2 among IHE populations and surrounding communities.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Sara Carazo", - "author_inst": "Centre de Recherche CHU de Quebec - Universite Laval" - }, - { - "author_name": "Denis Talbot", - "author_inst": "Universite Laval" - }, - { - "author_name": "Nicole Boulianne", - "author_inst": "INSPQ" - }, - { - "author_name": "Marc Brisson", - "author_inst": "Universite Laval" - }, - { - "author_name": "Rodica Gilca", - "author_inst": "INSPQ" + "author_name": "Andrew L. Valesano", + "author_inst": "University of Michigan" }, { - "author_name": "Genevieve Deceuninck", - "author_inst": "Centre de recherche CHU de Quebec - Universite Laval" + "author_name": "William J. Fitzsimmons", + "author_inst": "University of Michigan" }, { - "author_name": "Nicholas Brousseau", - "author_inst": "INSPQ" + "author_name": "Christopher N. Blair", + "author_inst": "University of Michigan" }, { - "author_name": "Melanie Drolet", - "author_inst": "Centre de Recherche CHU de Quebec - Universite Laval" + "author_name": "Robert J. Woods", + "author_inst": "University of Michigan" }, { - "author_name": "Manale Ouakki", - "author_inst": "INSPQ" + "author_name": "Julie Gilbert", + "author_inst": "University of Michigan" }, { - "author_name": "Chantal Sauvageau", - "author_inst": "INSPQ" + "author_name": "Dawn Rudnik", + "author_inst": "University of Michigan" }, { - "author_name": "Sapha Barkati", - "author_inst": "McGill University" + "author_name": "Lindsey Mortenson", + "author_inst": "University of Michigan" }, { - "author_name": "Elise Fortin", - "author_inst": "INSPQ" + "author_name": "Thomas S. Friedrich", + "author_inst": "University of Wisconsin Madison" }, { - "author_name": "Alex Carignan", - "author_inst": "Universite de Sherbrook" + "author_name": "David O'Connor", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Philippe De Wals", - "author_inst": "INSPQ" + "author_name": "Joshua G Petrie", + "author_inst": "University of Michigan School of Public Health" }, { - "author_name": "Danuta M Skowronski", - "author_inst": "BC Centre for Disease Control" + "author_name": "Emily Toth Martin", + "author_inst": "University of Michigan-Ann Arbor" }, { - "author_name": "Gaston De Serres", - "author_inst": "INSPQ" + "author_name": "Adam S. Lauring", + "author_inst": "University of Michigan" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -633275,39 +631776,127 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2021.07.22.453345", - "rel_title": "ADAR mediated A-to-I RNA editing affects SARS-CoV-2 characteristics and fuels its evolution", + "rel_doi": "10.1101/2021.07.21.453232", + "rel_title": "Structure insights, thermodynamic profiles, dsDNA melting activity, and liquid-liquid phase separation of the SARS-CoV-2 nucleocapsid N-terminal domain binding to DNA", "rel_date": "2021-07-22", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.22.453345", - "rel_abs": "Upon SARS-CoV-2 infection, viral intermediates activate the Type I interferon (IFN) response through MDA5-mediated sensing and accordingly induce ADAR1 p150 expression, which might lead to A-to-I RNA editing of SARS-CoV-2. Here, we developed an RNA virus-specific editing identification pipeline, surveyed 7622 RNA-seq data from diverse types of samples infected with SARS-CoV-2, and constructed an atlas of A-to-I RNA editing sites in SARS-CoV-2. We found that A-to-I editing was dynamically regulated, and on average, approximately 91 editing events were deposited at viral dsRNA intermediates per sample. Moreover, editing hotspots were observed, including recoding sites in the spike gene that affect viral infectivity and antigenicity. Finally, we provided evidence that RNA editing accelerated SARS-CoV-2 evolution in humans. Collectively, our data suggest that SARS-CoV-2 hijacks components of the host antiviral machinery to edit its genome and fuel its evolution.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.21.453232", + "rel_abs": "The SARS-CoV-2 nucleocapsid protein (N) is a multifunctional promiscuous nucleic acid-binding protein, which plays a major role in nucleocapsid assembly and discontinuous RNA transcription, facilitating the template switch of transcriptional regulatory sequences (TRS). Here, we dissect the structural features of the N protein N-terminal domain (N-NTD), either with or without the SR-rich motif (SR), upon binding to single and double-stranded TRS DNA, as well as their activities for dsTRS melting and TRS-induced liquid-liquid phase separation (LLPS). Our study gives insights on specificity for N-NTD/N-NTD-SR interaction with TRS, including an unfavorable energetic contribution to binding along with hydrogen bonds between the triple-thymidine (TTT) motif in the dsTRS and {beta}-sheet II due to the defined position and orientation of the DNA duplex, a well-defined pattern ({Delta}H > 0 and {Delta}S > 0 for ssTRS, and {Delta}H < 0 and {Delta}S < 0 for dsTRS) for the thermodynamic profile of binding, and a preference for TRS in the formation of liquid condensates when compared to a non-specific sequence. Moreover, our results on DNA binding may serve as a starting point for the design of inhibitors, including aptamers, against N, a possible therapeutic target essential for the virus infectivity.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Yulong Song", - "author_inst": "SYSU" + "author_name": "Icaro Putinhon Caruso", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Vitor S. Almeida", + "author_inst": "Federal University of Rio de Janeiro" }, { - "author_name": "Xiuju He", - "author_inst": "SYSU" + "author_name": "Mariana J. Amaral", + "author_inst": "Federal University of Rio de Janeiro" }, { - "author_name": "Wenbing Yang", - "author_inst": "SYSU" + "author_name": "Guilherme C. Andrade", + "author_inst": "Federal University of Rio de Janeiro" }, { - "author_name": "Tian Tang", - "author_inst": "SYSU" + "author_name": "Gabriela R. Araujo", + "author_inst": "Federal University of Rio de Janeiro" }, { - "author_name": "Rui Zhang", - "author_inst": "SYSU" + "author_name": "Talita S. Araujo", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Jessica M. Azevedo", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Glauce M. Barbosa", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Leonardo Bartkevihi", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Peter R. Bezerra", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Katia Maria dos Santos Cabral", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Isabella O. Louren\u00e7o", + "author_inst": "Sao Paulo States University" + }, + { + "author_name": "Clara L. F. Malizia-Motta", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Aline L. Marques", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Nathane C. Mebus-Antunes", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Thais Cristtina Neves-Martins", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Jessica M de S\u00e1", + "author_inst": "Sao Paulo States University" + }, + { + "author_name": "Karoline Sanches", + "author_inst": "Sao Paulo States University" + }, + { + "author_name": "Marcos Caique Santana-Silva", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Ariana A. Vasconcelos", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Marcius S. Almeida", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Gisele C. Amorim", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Cristiane D. Anobom", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Andrea T. Da Poian", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Francisco Gomes-Neto", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Anderson S. Pinheiro", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Fabio C. L. Almeida", + "author_inst": "Federal University of Rio de Janeiro" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "biophysics" }, { "rel_doi": "10.1101/2021.07.22.453287", @@ -634873,123 +633462,67 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.07.20.453162", - "rel_title": "PRE-CLINICAL IMMUNE RESPONSE AND SAFETY EVALUATION OF THE PROTEIN SUBUNIT VACCINE NANOCOVAX FOR COVID-19", + "rel_doi": "10.1101/2021.07.20.453146", + "rel_title": "SARS-CoV-2 Restructures the Host Chromatin Architecture", "rel_date": "2021-07-21", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.20.453162", - "rel_abs": "The Coronavirus disease-2019 (COVID-19) pandemic caused by the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), has become a dire global health concern. The development of vaccines with high immunogenicity and safety is crucial for control of the global COVID-19 pandemic and prevention of further illness and fatalities. Here, we report development of SARS-CoV-2 vaccine candidate, Nanocovax, based on recombinant protein production of the extracellular (soluble) portion of the S protein of SARS-CoV-2. The results showed that Nanocovax induced high levels of S protein-specific IgG, as well neutralizing antibody in three animal models including Balb/C mice, Syrian hamsters, and non-human primate (Macaca leonina). In addition, the viral challenge study using the hamster model showed that Nanocovax protected the upper respiratory tract from SARS-CoV-2 infection. No adverse effects were induced by Nanocovax in swiss mice (Musmusculus var. Albino), Rats (Rattus norvegicus), and New Zealand rabbits. These pre-clinical results indicated that Nanocovax is safe and effective.", - "rel_num_authors": 26, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.20.453146", + "rel_abs": "SARS-CoV-2 has made >190-million infections worldwide, thus it is pivotal to understand the viral impacts on host cells. Many viruses can significantly alter host chromatin1, but such roles of SARS-CoV-2 are largely unknown. Here, we characterized the three-dimensional (3D) genome architecture and epigenome landscapes in human cells after SARS-CoV-2 infection, revealing remarkable restructuring of host chromatin architecture. High-resolution Hi-C 3.0 uncovered widespread A compartmental weakening and A-B mixing, together with a global reduction of intra-TAD chromatin contacts. The cohesin complex, a central organizer of the 3D genome, was significantly depleted from intra-TAD regions, supporting that SARS-CoV-2 disrupts cohesin loop extrusion. Calibrated ChIP-Seq verified chromatin restructuring by SARS-CoV-2 that is particularly manifested by a pervasive reduction of euchromatin modifications. Built on the rewired 3D genome/epigenome maps, a modified activity-by-contact model2 highlights the transcriptional weakening of antiviral interferon response genes or virus sensors (e.g., DDX58) incurred by SARS-CoV-2. In contrast, pro-inflammatory genes (e.g. IL-6) high in severe infections were uniquely regulated by augmented H3K4me3 at their promoters. These findings illustrate how SARS-CoV-2 rewires host chromatin architecture to confer immunological gene deregulation, laying a foundation to characterize the long-term epigenomic impacts of this virus.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Thi Nhu Mai Tran", - "author_inst": "Nanogen Biopharmaceuticals JSc." - }, - { - "author_name": "Bruce May", - "author_inst": "Nanogen Biopharmaceuticals JSc." - }, - { - "author_name": "Thuan Trong Ung", - "author_inst": "Nanogen pharmmaceutical Biotechnology JSC" - }, - { - "author_name": "Mai Khoi Nguyen", - "author_inst": "Nanogen Biopharmaceuticals JSc." - }, - { - "author_name": "Thuy Trang Nguyen", - "author_inst": "Nanogen Biopharmaceuticals JSc." - }, - { - "author_name": "Van Long Dinh", - "author_inst": "Nanogen Biopharmaceuticals JSc." - }, - { - "author_name": "The Vinh Tran", - "author_inst": "Nanogen Biopharmaceuticals JSc." - }, - { - "author_name": "Hiep Khong", - "author_inst": "Nanogen Biopharmaceuticals JSc." - }, - { - "author_name": "Thanh Truc Nguyen", - "author_inst": "Nanogen Biopharmaceuticals JSc." - }, - { - "author_name": "Hoang Quoc Huy Hua", - "author_inst": "Nanogen Biopharmaceuticals JSc." - }, - { - "author_name": "Viet Anh Nguyen", - "author_inst": "Nanogen Biopharmaceuticals JSc." - }, - { - "author_name": "Tan Phat Ha", - "author_inst": "Nanogen Biopharmaceuticals JSc." - }, - { - "author_name": "Dang Luu Phan", - "author_inst": "Nanogen Biopharmaceuticals JSc." - }, - { - "author_name": "Truong An Nguyen", - "author_inst": "Nanogen Biopharmaceuticals JSc." - }, - { - "author_name": "Thi Ngoc Bui", - "author_inst": "Nanogen Biopharmaceuticals JSc." + "author_name": "Ruoyu Wang", + "author_inst": "University of Texas Health Science Center Houston" }, { - "author_name": "Tieu My Tu", - "author_inst": "Nanogen Biopharmaceuticals JSc." + "author_name": "Joo-Hyung Lee", + "author_inst": "University of Texas Health Science Center Houston" }, { - "author_name": "Thi Theo Nguyen", - "author_inst": "Nanogen Biopharmaceuticals JSc." + "author_name": "Feng Xiong", + "author_inst": "University of Texas Health Science Center Houston" }, { - "author_name": "Thuy Hang Le", - "author_inst": "Nanogen Biopharmaceuticals JSc." + "author_name": "Jieun Kim", + "author_inst": "University of Texas Health Science Center Houston" }, { - "author_name": "Thi Lan Dong", - "author_inst": "Nanogen Biopharmaceuticals JSc." + "author_name": "Lana Al Hasani", + "author_inst": "University of Texas Health Science Center Houston" }, { - "author_name": "Trong Hieu Huynh", - "author_inst": "Nanogen Biopharmaceuticals JSc." + "author_name": "Xiaoyi Yuan", + "author_inst": "University of Texas Health Science Center Houston" }, { - "author_name": "Cong Thao Truong", - "author_inst": "Nanogen Biopharmaceuticals JSc." + "author_name": "Pooja Shivshankar", + "author_inst": "University of Texas Health Science Center Houston" }, { - "author_name": "Lim Nie", - "author_inst": "Nanogen Biopharmaceuticals JSc." + "author_name": "Joanna Krakowiak", + "author_inst": "University of Texas Health Science Center Houston" }, { - "author_name": "Minh Ngoc Cao", - "author_inst": "Nanogen Biopharmaceuticals JSc." + "author_name": "Chuangye Qi", + "author_inst": "University of Texas Health Science Center Houston" }, { - "author_name": "Duy Khanh Nguyen", - "author_inst": "Nanogen Biopharmaceuticals JSc." + "author_name": "Yangyu Wang", + "author_inst": "University of Texas Health Science Center Houston" }, { - "author_name": "Thanh Hung Trinh", - "author_inst": "Vietnam Ministry of Science and technonoly" + "author_name": "Holger K Eltzschig", + "author_inst": "University of Texas Health Science Center Houston" }, { - "author_name": "Minh Si Do", - "author_inst": "Nanogen Biopharmaceuticals JSc." + "author_name": "Wenbo Li", + "author_inst": "University of Texas Health Science Center Houston" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2021.07.20.453118", @@ -636767,35 +635300,91 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.15.21260583", - "rel_title": "Scaling SARS-CoV-2 Wastewater Concentrations to Population Estimates of Infection", + "rel_doi": "10.1101/2021.07.15.21260590", + "rel_title": "Development and validation of a clinical risk score to predict SARS-CoV-2 infection in emergency department patients: The CCEDRRN COVID-19 Infection Score (CCIS)", "rel_date": "2021-07-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.15.21260583", - "rel_abs": "Monitoring the progression of SARS-CoV-2 outbreaks requires accurate estimates of infection rates. Estimation methods based on observed cases are biased due to changes in testing over time. Here we report an approach based upon scaling daily concentrations of SARS-CoV-2 RNA in wastewater to infections that produces representative estimates due to the consistent population contribution of fecal material to the sewage collection system.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.15.21260590", + "rel_abs": "ObjectivesTo develop and validate a clinical risk score that can accurately quantify an emergency department patients probability of SARS-CoV-2 infection without the need for laboratory testing\n\nDesignCohort study of participants in the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN) registry. Regression models were fitted to predict a positive SARS-CoV-2 test result using clinical and demographic predictors, as well as an indicator of local SARS-CoV-2 incidence.\n\nSetting32 emergency departments in eight Canadian provinces\n\nParticipants27,665 consecutively-enrolled patients who were tested for SARS-CoV-2 in participating emergency departments between March 1-October 30,2020\n\nMain outcome measuresPositive SARS-CoV-2 nucleic acid test result within 14 days of an index emergency department encounter for suspected COVID-19 disease\n\nResultsWe derived a 10-item CCEDRRN COVID-19 Infection Score using data from 21,743 patients. This score included variables from history and physical examination, and an indicator of local disease incidence. The score had a c-statistic of 0.838 with excellent calibration. We externally validated the rule in 5,295 patients. The score maintained excellent discrimination and calibration, and had superior performance compared to another previously published risk score. Score cutoffs were identified that can rule-in or rule-out SARS-CoV-2 infection without the need for nucleic acid testing with 97.4 % sensitivity (95% CI 96.4-98..3) and 95.9% specificity (95% CI 95.5-96.0).\n\nConclusionsThe CCEDRRN COVID-19 Infection Score uses clinical characteristics and publicly available indicators of disease incidence to quantify a patients probability of SARS-CoV-2 infection. The score can identify patients at sufficiently high risk of SARS-CoV-2 infection to warrant isolation and empiric therapy prior to test confirmation, while also identifying patients at sufficiently low risk of infection that they may not need testing.\n\nTrial registrationCCEDRRN is registered at clinicaltrials.gov (NCT04702945).\n\nFundingThe network is funded by the Canadian Institutes of Health Research (447679), BC Academic Health Science Network Society, BioTalent Canada, Genome BC (COV024; VAC007), Ontario Ministry of Colleges and Universities (C-655-2129), the Saskatchewan Health Research Foundation (5357) and the Fondation CHU de Quebec (Octroi #4007). These organizations are not-for-profit, and had no role in study conduct, analysis, or manuscript preparation.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Edward H Kaplan", - "author_inst": "Yale University" + "author_name": "Andrew D. McRae", + "author_inst": "University of Calgary" }, { - "author_name": "Alessandro Zulli", - "author_inst": "Yale University" + "author_name": "Corinne M. Hohl", + "author_inst": "University of British Columbia" }, { - "author_name": "Marcela Sanchez", - "author_inst": "Yale University" + "author_name": "Rhonda J. Rosychuk", + "author_inst": "University of Alberta" }, { - "author_name": "Jordan Peccia", - "author_inst": "Yale University" + "author_name": "Shabnam Vatanpour", + "author_inst": "University of Calgary" + }, + { + "author_name": "Gelareh Ghaderi", + "author_inst": "University of British Columbia" + }, + { + "author_name": "Patrick M. Archambault", + "author_inst": "Universite Laval" + }, + { + "author_name": "Steven C. Brooks", + "author_inst": "Queen's University" + }, + { + "author_name": "Ivy Cheng", + "author_inst": "University of Toronto" + }, + { + "author_name": "Philip Davis", + "author_inst": "University of Saskatchewan" + }, + { + "author_name": "Jake Hayward", + "author_inst": "University of Alberta" + }, + { + "author_name": "Eddy S. Lang", + "author_inst": "University of Calgary" + }, + { + "author_name": "Robert Ohle", + "author_inst": "Northern Ontario School of Medicine" + }, + { + "author_name": "Brian H. Rowe", + "author_inst": "University of Alberta" + }, + { + "author_name": "Michelle Welsford", + "author_inst": "McMaster University" + }, + { + "author_name": "Krishan Yadav", + "author_inst": "University of Ottawa" + }, + { + "author_name": "Laurie J. Morrison", + "author_inst": "Unity Health Toronto" + }, + { + "author_name": "Jeffrey J. Perry", + "author_inst": "University of Ottawa" + }, + { + "author_name": "- Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN)", + "author_inst": "" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "emergency medicine" }, { "rel_doi": "10.1101/2021.07.15.21260543", @@ -638761,41 +637350,41 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.07.17.452804", - "rel_title": "ACE2 binding is an ancestral and evolvable trait of sarbecoviruses", + "rel_doi": "10.1101/2021.07.16.452571", + "rel_title": "Molecular evolution and structural analyses of the spike glycoprotein from Brazilian SARS-CoV-2 genomes: the impact of the fixation of selected mutations", "rel_date": "2021-07-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.17.452804", - "rel_abs": "Two different sarbecoviruses have caused major human outbreaks in the last two decades1,2. Both these sarbecoviruses, SARS-CoV-1 and SARS-CoV-2, engage ACE2 via the spike receptor-binding domain (RBD)2-6. However, binding to ACE2 orthologs from humans, bats, and other species has been observed only sporadically among the broader diversity of bat sarbecoviruses7-11. Here, we use high-throughput assays12 to trace the evolutionary history of ACE2 binding across a diverse range of sarbecoviruses and ACE2 orthologs. We find that ACE2 binding is an ancestral trait of sarbecovirus RBDs that has subsequently been lost in some clades. Furthermore, we demonstrate for the first time that bat sarbecoviruses from outside Asia can bind ACE2. In addition, ACE2 binding is highly evolvable: for many sarbecovirus RBDs there are single amino-acid mutations that enable binding to new ACE2 orthologs. However, the effects of individual mutations can differ markedly between viruses, as illustrated by the N501Y mutation which enhances human ACE2 binding affinity within several SARS-CoV-2 variants of concern12 but severely dampens it for SARS-CoV-1. Our results point to the deep ancestral origin and evolutionary plasticity of ACE2 binding, broadening consideration of the range of sarbecoviruses with spillover potential.", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.16.452571", + "rel_abs": "The COVID-19 pandemic caused by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has reached by July 2021 almost 200 million cases and more than 4 million deaths worldwide since its beginning in late 2019, leading to enhanced concern in the scientific community and the general population. One of the most important pieces of this host-pathogen interaction is the spike protein, which binds to the human Angiotensin-converting enzyme 2 (hACE2) cell receptor, mediates the membrane fusion and is the major target of neutralizing antibodies against SARS-CoV-2. The multiple amino acid substitutions observed in this region, specially in the Receptor Binding Domain (RBD), mainly after almost one year of its emergence (late 2020), have enhanced the hACE2 binding affinity and led to several modifications in the mechanisms of SARS-CoV-2 pathogenesis, improving the viral fitness and/or promoting immune evasion, with potential impact in the vaccine development. In this way, the present work aimed to evaluate the effect of positively selected mutations fixed in the Brazilian SARS-CoV-2 lineages and to check for mutational evidence of coevolution. Additionally, we evaluated the impact of selected mutations identified in some of the VOC and VOI lineages (C.37, B.1.1.7, P.1, and P.2) of Brazilian samples on the structural stability of the spike protein, as well as their possible association with more aggressive infection profiles by estimating the binding affinity in the RBD-hACE2 complex. We identified 48 sites under selective pressure in Brazilian spike sequences, 17 of them with the strongest evidence by the HyPhy tests, including VOC related mutation sites 138, 142, 222, 262, 484, 681, and 845, among others. The coevolutionary analysis identified a number of 28 coevolving sites that were found not to be conditionally independent, such as the couple E484K - N501Y from P.1 and B.1.351 lineages. Finally, the molecular dynamics and free energy estimates showed the structural stabilizing effect and the higher impact of E484K for the improvement of the binding affinity between the spike RBD and the hACE2 in P.1 and P.2 lineages, as well as the stabilizing and destabilizing effects for the positively selected sites.", "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Tyler N Starr", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Patricia A. G. Ferrareze", + "author_inst": "Universidade Federal de Ciencias da Saude de Porto Alegre (UFCSPA)" }, { - "author_name": "Samantha K Zepeda", - "author_inst": "University of Washington" + "author_name": "Ricardo Zimerman", + "author_inst": "Irmandade Santa Casa de Misericordia" }, { - "author_name": "Alexandra C Walls", - "author_inst": "University of Washington" + "author_name": "Vinicius Bonetti Franceschi", + "author_inst": "Universidade Federal do Rio Grande do Sul" }, { - "author_name": "Allison J Greaney", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Gabriel Dickin Caldana", + "author_inst": "Universidade Federal de Ciencias da Saude de Porto Alegre" }, { - "author_name": "David Veesler", - "author_inst": "University of Washington" + "author_name": "Paulo Netz", + "author_inst": "Universidade Federal do Rio Grande do Sul" }, { - "author_name": "Jesse D Bloom", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Claudia Elizabeth Thompson", + "author_inst": "Universidade Federal de Ciencias da Saude de Porto Alegre" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "new results", "category": "evolutionary biology" }, @@ -640555,39 +639144,283 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.12.21260263", - "rel_title": "Performance of antigenic detection of SARS-CoV-2 in nasopharyngeal samples", + "rel_doi": "10.1101/2021.07.12.21259660", + "rel_title": "An Open Repository of Real-Time COVID-19 Indicators", "rel_date": "2021-07-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.12.21260263", - "rel_abs": "ObjectivesSARS-CoV-2 virus detection on nasopharyngeal specimens to infected individuals has become a challenge for the COVID-19 pandemic outbreak. We aim at comparing the performance of antigenic detection of SARS-CoV-2 in nasopharyngeal samples via an immunochromatographic method to molecular detection via qRT-PCR.\n\nMaterials and Methods47 nasopharyngeal exudates were collected from suspicious COVID-19 cases. The samples were performed both via the qualitative immuno-chromatographic method for S protein detection in the SARS-CoV-2 structure, using fluorescent labelled anti-protein S antibodies and via qRT-PCR test for the qualitative detection of the screening gene E and the specific ORF1ab region of the RNA-SARS-CoV-2.\n\nResultsThere was a fair correlation between the positive antigen tests and the positive PCR assays measured through threshold cycle ORF1ab region (Ct orf). A better correlation was obtained between the antigen test results and the Ct orf when including patients with Ct orf below 25.\n\nConclusionsUsing antigen tests as screening tests is useful on symptomatic persons during the viral replication period, therefore during the contagious period. A positive test shows a high predictive value for infection, while a negative antigen test result via immuno-chromatography must be confirmed by a qRT-PCR test.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.12.21259660", + "rel_abs": "The COVID-19 pandemic presented enormous data challenges in the United States. Policy makers, epidemiological modelers, and health researchers all require up-to-date data on the pandemic and relevant public behavior, ideally at fine spatial and temporal resolution. The COVIDcast API is our attempt to fill this need: operational since April 2020, it provides open access to both traditional public health surveillance signals (cases, deaths, and hospitalizations) and many auxiliary indicators of COVID-19 activity, such as signals extracted from de-identified medical claims data, massive online surveys, cell phone mobility data, and internet search trends. These are available at a fine geographic resolution (mostly at the county level) and are updated daily. The COVIDcast API also tracks all revisions to historical data, allowing modelers to account for the frequent revisions and backfill that are common for many public health data sources. All of the data is available in a common format through the API and accompanying R and Python software packages. This paper describes the data sources and signals, and provides examples demonstrating that the auxiliary signals in the COVIDcast API present information relevant to tracking COVID activity, augmenting traditional public health reporting and empowering research and decision-making.", + "rel_num_authors": 66, "rel_authors": [ { - "author_name": "Catalina Lunca", - "author_inst": "Department of Preventive Medicine and Interdisciplinarity, Faculty of Medicine, University of Medicine and Pharmacy \"Grigore T. Popa\" , Iasi" + "author_name": "Alex Reinhart", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Logan Brooks", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Maria Jahja", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Aaron Rumack", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Jingjing Tang", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Sumit Agrawal", + "author_inst": "Google.org Fellows, Google LLC" + }, + { + "author_name": "Wael Al Saeed", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Taylor Arnold", + "author_inst": "University of Richmond" + }, + { + "author_name": "Amartya Basu", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Jacob Bien", + "author_inst": "University of Southern California" + }, + { + "author_name": "\u00c1ngel A Cabrera", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Andrew Chin", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Eu Jing Chua", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Brian Clark", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Sarah Colquhoun", + "author_inst": "Google.org Fellows, Google LLC" + }, + { + "author_name": "Nat DeFries", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "David C. Farrow", + "author_inst": "Google.org Fellows, Google LLC" + }, + { + "author_name": "Jodi Forlizzi", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Jed Grabman", + "author_inst": "Google.org Fellows, Google LLC" + }, + { + "author_name": "Samuel Gratzl", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Alden Green", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "George Haff", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Robin Han", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Kate Harwood", + "author_inst": "Google.org Fellows, Google LLC" + }, + { + "author_name": "Addison J Hu", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Raphael Hyde", + "author_inst": "Google.org Fellows, Google LLC" + }, + { + "author_name": "Sangwon Hyun", + "author_inst": "University of Southern California" + }, + { + "author_name": "Ananya Joshi", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Jimi Kim", + "author_inst": "University of Texas at Dallas" + }, + { + "author_name": "Andrew Kuznetsov", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Wichada La Motte-Kerr", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Yeon Jin Lee", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Kenneth Lee", + "author_inst": "University of California Davis" + }, + { + "author_name": "Zachary C Lipton", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Michael X Liu", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Lester Mackey", + "author_inst": "Microsoft Research New England" + }, + { + "author_name": "Kathryn Mazaitis", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Daniel J McDonald", + "author_inst": "University of British Columbia" + }, + { + "author_name": "Phillip McGuinness", + "author_inst": "Google.org Fellows, Google LLC" + }, + { + "author_name": "Balasubramanian Narasimhan", + "author_inst": "Stanford University" + }, + { + "author_name": "Michael P. O'Brien", + "author_inst": "Google.org Fellows, Google LLC" + }, + { + "author_name": "Natalia L Oliveira", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Pratik Patil", + "author_inst": "Carnegie Mellon University" }, { - "author_name": "Cristian Cojocaru", - "author_inst": "Medical III Department, Faculty of Medicine, University of Medicine and Pharmacy \"Grigore T. Popa\" Iasi" + "author_name": "Adam Perer", + "author_inst": "Carnegie Mellon University" }, { - "author_name": "Irina Luciana Gurzu", - "author_inst": "Department of Preventive Medicine and Interdisciplinarity, Faculty of Medicine, University of Medicine and Pharmacy \"Grigore T. Popa\" , Iasi" + "author_name": "Collin A Politsch", + "author_inst": "Carnegie Mellon University" }, { - "author_name": "Florin Dumitru Petrariu", - "author_inst": "Department of Preventive Medicine and Interdisciplinarity, Faculty of Medicine, University of Medicine and Pharmacy \"Grigore T. Popa\", Iasi" + "author_name": "Samyak Rajanala", + "author_inst": "Stanford University" }, { - "author_name": "Elena Cojocaru", - "author_inst": "Morpho-Functional Sciences II Department, Faculty of Medicine, University of Medicine and Pharmacy \"Grigore T. Popa\", Iasi" + "author_name": "Dawn Rucker", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Chris Scott", + "author_inst": "Google.org Fellows, Google LLC" + }, + { + "author_name": "Nigam Shah", + "author_inst": "Stanford University" + }, + { + "author_name": "Vishnu Shankar", + "author_inst": "Stanford University" + }, + { + "author_name": "James Sharpnack", + "author_inst": "University of California Davis" + }, + { + "author_name": "Dmitry Shemetov", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Noah Simon", + "author_inst": "University of Washington" + }, + { + "author_name": "Benjamin Y. Smith", + "author_inst": "Google.org Fellows, Google LLC" + }, + { + "author_name": "Vishakha Srivastava", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Shuyi Tan", + "author_inst": "University of British Columbia" + }, + { + "author_name": "Robert Tibshirani", + "author_inst": "Stanford University" + }, + { + "author_name": "Elena Tuzhilina", + "author_inst": "Stanford University" + }, + { + "author_name": "Ana Karina Van Nortwick", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Val\u00e9rie Ventura", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Larry Wasserman", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Benjamin Weaver", + "author_inst": "Google.org Fellows, Google LLC" + }, + { + "author_name": "Jeremy C Weiss", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Kristin Williams", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Roni Rosenfeld", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Ryan J Tibshirani", + "author_inst": "Carnegie Mellon University" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.07.11.21260318", @@ -642161,23 +640994,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.15.452549", - "rel_title": "Visualizing Amino Acid Substitutions in a Physicochemical Vector Space", + "rel_doi": "10.1101/2021.07.14.21260549", + "rel_title": "Influenza infection, Acute myocardial Infarction, Flu Shot during COVID-19 Pandemic in US population. A Review of Literature.", "rel_date": "2021-07-16", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.15.452549", - "rel_abs": "A three-dimensional representation of the twenty proteinogenic amino acids in a physicochemical space is presented. Vectors corresponding to amino acid substitutions are classified based on whether they are accessible via a single-nucleotide mutation. It is shown that the standard genetic code establishes a \"choice architecture\" that permits nearly independent tuning of the properties related with size and those related with hydrophobicity. This work sheds light on the non-arbitrary benefits of evolvability that may have shaped the development standard genetic code to increase the probability that adaptive point mutations will be generated. Illustrations of the usefulness of visualizing amino acid substitutions in a 3D physicochemical space are shown using recent datasets collected regarding the SARS-CoV-2 receptor binding domain. First, the substitutions most responsible for antibody escape are almost always inaccessible via single nucleotide mutation, and change multiple properties concurrently. Second, it is shown that assays of ACE2 binding by sarbecovirus variants, including the viruses responsible for SARS and COVID-19, are more easily understood when plotted with this method. The results of this research can extend our understanding of certain hereditary disorders caused by point mutations, as well as guide the development of rational protein and vaccine design.", - "rel_num_authors": 1, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.14.21260549", + "rel_abs": "Influenza is a major cause of hospitalization in all age groups but can cause more severe infections in specific high-risk population. Novel Corona Virus Disease 2019 (COVID-19) pandemic and Influenza virus infection cause similar illness and coexist. Cardiovascular complications due to influenza are important causes of morbidity and mortality in the US, especially in the elderly population (aged more than 65 years). Acute Myocardial Infarction (AMI) is the most serious among the cardiovascular causes of mortality following the attack of influenza, mainly in patients with various co-morbidities like pre-existing coronary artery disease (CAD), diabetes mellitus (DM), hypertension (HTN), and heart failure (HF). We have reviewed the association between influenza virus infection and AMI and extrapolated the beneficial effects of influenza vaccine in preventing AMI and its grave consequences. We have also highlighted about the importance of flu shot during the COVID-19 pandemic.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Louis R Nemzer", - "author_inst": "Nova Southeastern University" + "author_name": "Nischit Baral", + "author_inst": "Michigan State University College of Human Medicine" + }, + { + "author_name": "Niranjan Nayak", + "author_inst": "Manipal College of Medical Sciences" } ], "version": "1", - "license": "cc_by_nd", - "type": "new results", - "category": "bioinformatics" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2021.07.12.21260345", @@ -644114,87 +642951,99 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.07.12.21260357", - "rel_title": "Contamination of personal protective equipment during COVID-19 autopsies", - "rel_date": "2021-07-15", + "rel_doi": "10.1101/2021.07.12.21260119", + "rel_title": "The QuantuMDx Q-POC SARS-CoV-2 RT-PCR assay for rapid detection of COVID-19 at point-of-care: preliminary evaluation of a novel technology", + "rel_date": "2021-07-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.12.21260357", - "rel_abs": "Confronted with an emerging infectious disease, the medical community faced relevant concerns regarding the performance of autopsies of COVID-19 deceased at the beginning of the pandemic. This attitude has changed, and autopsies are now recognized as indispensable tools for elucidating COVID-19; despite this, the true risk of infection for autopsy staff is still debated. To elucidate the rate of SARS-CoV-2 contamination in personal protective equipment (PPE), swabs were taken at nine locations of the PPE of one physician and an assistant each from 11 full autopsies performed at four different centers. Further samples were obtained for three minimally invasive autopsies (MIA) conducted at a fifth center. Lung/bronchus swabs of the deceased served as positive controls. SARS-CoV-2 RNA was detected by RT-qPCR. In 9/11 full autopsies PPE samples were tested RNA positive with PCR, in total 21% of all PPE samples taken. The main contaminated parts of the PPE were the gloves (64% positive), the aprons (50% positive), and the upper sides of shoes (36% positive) while for example the fronts of safety goggles were only positive in 4.5% of the samples and all face masks were negative. In MIA, viral RNA was observed in one sample from a glove, but not in other swabs. Infectious virus isolation in cell culture was performed in RNA positive swabs from full autopsies. Of all RNA positive PPE samples, 21% of the glove samples were positive for infectious virus taken in 3/11 full autopsies. In conclusion, in >80% of autopsies, PPE was contaminated with viral RNA. In >25% of autopsies, PPE was found to be even contaminated with infectious virus, signifying a potential risk of infection among autopsy staff. Adequate PPE and hygiene measures, including appropriate waste deposition, are therefore mandatory to enable safe work environment.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.12.21260119", + "rel_abs": "BackgroundAccurate, affordable, and rapid point-of-care (PoC) diagnostics are critical to the global control and management of the COVID-19 pandemic. The current standard for accurate diagnosis of SARS-CoV-2 is laboratory-based reverse transcription polymerase chain reaction (RT-PCR). Here, we report a preliminary prospective performance evaluation of the QuantuMDx Q-POC SARS CoV-2 RT-PCR assay.\n\nMethodsBetween November 2020 and March 2021, we obtained 49 longitudinal nose and throat swabs from 29 individuals hospitalised with RT-PCR confirmed COVID-19 at St Georges NHS Foundation Trust, London (UK). In addition, we obtained 101 mid nasal swabs from healthy volunteers in June 2021. We then used these samples to evaluate the Q-POC SARS-CoV-2 RT-PCR assay. The primary analysis was to compare the sensitivity and specificity of the Q-POC test against a reference laboratory-based RT-PCR assay.\n\nResultsThe overall sensitivity of the Q-POC test compared with the reference test was 96.88% (83.78%-99.92% CI) for a cycle threshold (Ct) cut-off value for the reference test of 35 and 80.00% (64.35% to 90.95% CI) without altering the reference tests Ct cut-off value of 40.\n\nConclusionsThe Q-POC test is a sensitive, specific and rapid point-of-care test for SARS-CoV-2 at a reference Ct cut-off value of 35. The Q-POC test provides an accurate and affordable option for RT-PCR at point-of-care without the need for sample pre-processing and laboratory handling. The Q-POC test would enable rapid diagnosis and clinical triage in acute care and other settings.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Johanna M Brandner", - "author_inst": "Business Division of Safety, Security and Compliance, University Medical Center Hamburg-Eppendorf, Hamburg, Germany/Department of Dermatology and Venerology, Un" + "author_name": "Jessica Caffry", + "author_inst": "QuantuMDx" }, { - "author_name": "Peter Boor", - "author_inst": "Institute of Pathology, Rheinisch Westfaelische Technische Hochschule, Aachen University Hospital, Aachen, Germany" + "author_name": "Matthew Selby", + "author_inst": "QuantuMDx" }, { - "author_name": "Lukas S Borcherding", - "author_inst": "General Pathology and Molecular Diagnostics, Medical Faculty, University Augsburg, Germany" + "author_name": "Katie Barr", + "author_inst": "QuantuMDx" }, { - "author_name": "Carolin Edler", - "author_inst": "Department of Legal Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany/DEFEAT PANDEMICS working group" + "author_name": "George Morgan", + "author_inst": "QuantuMDx" }, { - "author_name": "Sven Gerber", - "author_inst": "Business Division of Safety, Security and Compliance, University Medical Center Hamburg-Eppendorf, Hamburg, Germany/DEFEAT PANDEMICS working group" + "author_name": "David McGurk", + "author_inst": "QuantuMDx" }, { - "author_name": "Axel Heinemann", - "author_inst": "Department of Legal Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany/DEFEAT PANDEMICS working group" + "author_name": "Philip Scully", + "author_inst": "QuantuMDx" }, { - "author_name": "Julia Hilsenbeck", - "author_inst": "Institute of Pathology, University Hospital Carl Gustav Carus Dresden, Technical University of Dresden, Dresden, Germany/DEFEAT PANDEMICS working group" + "author_name": "Catherine Park", + "author_inst": "QuantuMDx" }, { - "author_name": "Atsuko Kasajima", - "author_inst": "Institute of Pathology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany" + "author_name": "Anna-Maria Caridis", + "author_inst": "QuantuMDx" }, { - "author_name": "Larissa Lohner", - "author_inst": "Department of Legal Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany/DEFEAT PANDEMICS working group" + "author_name": "Emily Southworth", + "author_inst": "QuantuMDx" }, { - "author_name": "Bruno M\u00e4rkl", - "author_inst": "General Pathology and Molecular Diagnostics, Medical Faculty, University Augsburg, Germany/DEFEAT PANDEMICS working group" + "author_name": "Jack Morrison", + "author_inst": "QuantuMDx" }, { - "author_name": "Jessica Pablik", - "author_inst": "Institute of Pathology, University Hospital Carl Gustav Carus Dresden, Technical University of Dresden, Dresden, Germany/DEFEAT PANDEMICS working group" + "author_name": "David J Clark", + "author_inst": "St George's University of London" }, { - "author_name": "Ann Sophie Schr\u00f6der", - "author_inst": "Department of Legal Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany/DEFEAT PANDEMICS working group" + "author_name": "Nicholas M Eckersley", + "author_inst": "St George's University of London" }, { - "author_name": "Linna Sommer", - "author_inst": "Institute of Pathology, University Hospital Carl Gustav Carus Dresden, Technical University of Dresden, Dresden, Germany/DEFEAT PANDEMICS working group" + "author_name": "Elisabetta Groppelli", + "author_inst": "St George's University of London" }, { - "author_name": "Julia Slotta-Huspenina", - "author_inst": "Institute of Pathology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany/DEFEAT PANDEMICS working group" + "author_name": "Daniela E Kirwan", + "author_inst": "St George's University of London" }, { - "author_name": "Jan-Peter Sperhake", - "author_inst": "Department of Legal Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany/DEFEAT PANDEMICS working group" + "author_name": "Irene Monahan", + "author_inst": "St George's University of London" }, { - "author_name": "Saskia von Stillfried", - "author_inst": "Institute of Pathology, Rheinisch Westfaelische Technische Hochschule, Aachen University Hospital, Aachen, Germany/DEFEAT PANDEMICS working group" + "author_name": "Yolanda Augustin", + "author_inst": "St George's Uninversity of London" }, { - "author_name": "Sebastian Dintner", - "author_inst": "General Pathology and Molecular Diagnostics, Medical Faculty, University Augsburg, Germany" + "author_name": "Colin Toombs", + "author_inst": "QuantuMDx" + }, + { + "author_name": "Tim Planche", + "author_inst": "St George's University of London" + }, + { + "author_name": "Henry M Staines", + "author_inst": "St George's University of London" + }, + { + "author_name": "Sanjeev Krishna", + "author_inst": "St George's University of London" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "pathology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.07.10.21260293", @@ -645824,41 +644673,157 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.09.21260262", - "rel_title": "Time-to-event assessment for the discovery of the proper prognostic value of clinical biomarkers optimized for COVID-19", + "rel_doi": "10.1101/2021.07.09.21260266", + "rel_title": "Highly versatile antibody binding assay for the detection of SARS-CoV-2 infection", "rel_date": "2021-07-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.09.21260262", - "rel_abs": "In the early days of the pandemic, clinical biomarkers for COVID -19 have been investigated to predict patient mortality. A decision tree has been proposed previously comprising three variables, i.e., lactic dehydrogenase (LDH), high-sensitivity C-reactive protein (CRP), and lymphocyte percentage, with more than 90% accuracy in a public cohort. In this work, we highlighted the importance of the cohort made publicly available and complemented the findings by incorporating further evaluation. Results confirmed poor short-term prognosis to abnormal levels of some laboratorial indicators, such as LDH, CRP, lymphocytes, interleukin-6, and procalcitonin. In addition, our findings provide insights into COVID-19 research, such as key levels of fibrin degradation products, which are directly associated with the Dimerized plasmin fragment D and could indicate active coagulation and thrombosis. Still, we highlight here the prognostic value of interleukin-6, a cytokine that induces inflammatory response and may serve as a predictive biomarker.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.09.21260266", + "rel_abs": "Monitoring the burden and spread of infection with the new coronavirus SARS-CoV-2, whether within small communities or in large geographical settings, is of paramount importance for public health purposes. Serology, which detects the host antibody response to the infection, is the most appropriate tool for this task, since virus-derived markers are most reliably detected during the acute phase of infection. Here we show that our ELISA protocol, which is based on antibody binding to the Receptor Binding Domain (RBD) of the S1 subunit of the viral Spike protein expressed as a novel fusion protein, detects antibody responses to SARS-CoV-2 infection and COVID-19 vaccination.\n\nWe also show that our ELISA is accurate and versatile. It compares favorably with commercial assays widely used in clinical practice to determine exposure to SARS-CoV-2. Moreover, our protocol accommodates use of various blood- and non-blood-derived biospecimens, such as breast milk, as well as dried blood obtained with microsampling cartridges that are appropriate for remote collection. As a result, our RBD-based ELISA protocols are well suited for seroepidemiology and other large-scale studies requiring parsimonious sample collection outside of healthcare settings.", + "rel_num_authors": 35, "rel_authors": [ { - "author_name": "Jose Raniery Ferreira Jr.", - "author_inst": "Hilab" + "author_name": "Pratik Datta", + "author_inst": "Public Health Research Institute, New Jersey Medical School, Newark, New Jersey, USA" + }, + { + "author_name": "Rahul Ukey", + "author_inst": "Public Health Research Institute, New Jersey Medical School, Newark, New Jersey, USA" + }, + { + "author_name": "Natalie Bruiners", + "author_inst": "Public Health Research Institute, New Jersey Medical School, Newark, New Jersey, USA" + }, + { + "author_name": "William Honnen", + "author_inst": "Public Health Research Institute, New Jersey Medical School, Newark, New Jersey, USA" }, { - "author_name": "Victor Henrique Alves Ribeiro", - "author_inst": "Hilab" + "author_name": "Mary O Caryannopoulos", + "author_inst": "Department of Pathology, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA" }, { - "author_name": "Marcelo Cossetin", - "author_inst": "Hilab" + "author_name": "Charles Reichman", + "author_inst": "Public Health Research Institute, New Jersey Medical School, Newark, New Jersey, USA" }, { - "author_name": "Marcus Vinicius Mazega Figueredo", - "author_inst": "Hilab" + "author_name": "Alok K Choudhary", + "author_inst": "Public Health Research Institute, New Jersey Medical School, Newark, New Jersey, USA" }, { - "author_name": "Carolina Queiroz Cardoso", - "author_inst": "Hilab" + "author_name": "Alberta Onyuka", + "author_inst": "Global Tuberculosis Institute, New Jersey Medical School, Newark, New Jersey, USA" }, { - "author_name": "Bernardo Montesanti Almeida", - "author_inst": "Hilab" + "author_name": "Deborah Handler", + "author_inst": "Global Tuberculosis Institute, New Jersey Medical School, Newark, New Jersey, USA" + }, + { + "author_name": "Valentina Guerrini", + "author_inst": "Public Health Research Institute, New Jersey Medical School, Newark, New Jersey, USA" + }, + { + "author_name": "Pankaj Mishra", + "author_inst": "Public Health Research Institute, New Jersey Medical School, Newark, New Jersey, USA" + }, + { + "author_name": "Hannah K Dewald", + "author_inst": "Department of Medicine, Rutgers New Jersey Medical School, Newark, New Jersey, USA" + }, + { + "author_name": "Alfred Lardizabal", + "author_inst": "Global Tuberculosis Institute, New Jersey Medical School, Newark, New Jersey, USA" + }, + { + "author_name": "Leeba Lederer", + "author_inst": "Bikur Cholim of Lakewood, Lakewood, New Jersey, USA" + }, + { + "author_name": "Aliza L Leiser", + "author_inst": "Rutgers University, New Brunswick, New Jersey, USA" + }, + { + "author_name": "Sabiha Hussain", + "author_inst": "Department of medicine, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA" + }, + { + "author_name": "Sugeet K Jagpal", + "author_inst": "Department of medicine, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA" + }, + { + "author_name": "Jared Radbel", + "author_inst": "Department of medicine, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA" + }, + { + "author_name": "Tanaya Bhowmick", + "author_inst": "Department of medicine, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA" + }, + { + "author_name": "Daniel B Horton", + "author_inst": "Department of pediatrics, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA" + }, + { + "author_name": "Emily S Barrett", + "author_inst": "Environmental and Occupational Health Sciences Institute, Department of Biostatistics and Epidemiology, Rutgers University, Piscataway, New Jersey, USA" + }, + { + "author_name": "Yingda L Xie", + "author_inst": "Department of medicine, Division of infectious diseases, Rutgers New Jersey Medical School, Newark, NJ" + }, + { + "author_name": "Patricia Fitzgerald-Bocarsly", + "author_inst": "Department of medicine, Rutgers New Jersey Medical School, Newark, NJ" + }, + { + "author_name": "Stanley H Weiss", + "author_inst": "Department of medicine, Rutgers New Jersey Medical School, Newark, NJ" + }, + { + "author_name": "Melissa Woortman", + "author_inst": "Department of Biochemistry and Microbiology, School of Environmental and Biological Sciences, Rutgers University, New Brunswick, NJ" + }, + { + "author_name": "Heta Parmar", + "author_inst": "Division of infectious diseases, Rutgers New Jersey Medical School, Newark, NJ" + }, + { + "author_name": "Jason Roy", + "author_inst": "Department of Biostatistics and Epidemiology, Rutgers University, Piscataway, New Jersey, USA" + }, + { + "author_name": "Maria Gloria Dominguez-Bello", + "author_inst": "Department of Biochemistry and Microbiology, School of Environmental and Biological Sciences, Rutgers University, New Brunswick, NJ" + }, + { + "author_name": "Martin Blaser", + "author_inst": "Center for Advanced Biotechnology and Medicine,Rutgers University, Piscataway, New Jersey, USA" + }, + { + "author_name": "Jeffrey L Carson", + "author_inst": "Rutgers Institute for Translational Medicine & Science, New Brunswick, New Jersey, USA" + }, + { + "author_name": "Reynold A Panettieri", + "author_inst": "Rutgers Institute for Translational Medicine & Science, New Brunswick, New Jersey, USA" + }, + { + "author_name": "Steven K Libutti", + "author_inst": "Cancer Institute of New Jersey, Rutgers University, New Brunswick, USA" + }, + { + "author_name": "Henry F Raymond", + "author_inst": "School of Public Health, Rutgers University, Piscataway, New Jersey, USA" + }, + { + "author_name": "Abraham Pinter", + "author_inst": "Public Health Research Institute, New Jersey Medical School, Newark, New Jersey, USA" + }, + { + "author_name": "Maria Laura Gennaro", + "author_inst": "Public Health Research Institute, New Jersey Medical School, Newark, New Jersey, USA" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -647654,51 +646619,107 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.07.12.452021", - "rel_title": "Drug-free nasal spray as a barrier against SARS-CoV-2 infection: safety and efficacy in human nasal airway epithelia", - "rel_date": "2021-07-12", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.12.452021", - "rel_abs": "BackgroundFor SARS-CoV-2 and other respiratory viruses, the nasal epithelium is a key portal for infection. Therefore, the nose is an important target of prophylactic and therapeutic interventions against these viruses. We developed a nasal spray (AM-301, a medical device marketed as Bentrio) to protect against infection by SARS-CoV-2 and potentially other viruses.\n\nAims of the studyTo test the safety and efficacy of AM-301 against SARS-CoV-2 infection.\n\nMethodsAM-301 was tested on an in vitro 3D model of primary human nasal airway epithelium. Safety was assessed in assays for tight junction integrity, cytotoxicity and cilia beating frequency. Efficacy against SARS-CoV-2 infection was evaluated in prophylaxis and infection mitigation assays.\n\nResultsAM-301 did not have any detrimental effect on the nasal epithelium. Prophylactic treatment with AM-301 reduced viral titer significantly vs. controls over 4 days, reaching a maximum reduction of 99%. When treatment with AM-301 was started 24 or 30 h after infection, epithelia that received the formulation had a 12- or 14-fold lower titer than controls.\n\nConclusionAM-301 was found to be safe in vitro, and it significantly decelerated viral titer growth in experimental models of prophylaxis and mitigation. Its physical (non-pharmaceutical) mechanism of action, safety and efficacy pave the way for further investigation of its possible use against a broad spectrum of viruses, allergens and pollutants.", - "rel_num_authors": 8, + "rel_doi": "10.1101/2021.07.09.21260287", + "rel_title": "Markers of immune activation and inflammation in individuals with post-acute sequelae of SARS-CoV-2 infection", + "rel_date": "2021-07-11", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.09.21260287", + "rel_abs": "BACKGROUNDThe biological processes associated with post-acute sequelae of SARS-CoV-2 infection (PASC) are unknown.\n\nMETHODSWe measured soluble markers of inflammation in a SARS-CoV-2 recovery cohort at early (<90 days) and late (>90 days) timepoints. We defined PASC as the presence of one or more COVID-19-attributed symptoms beyond 90 days. We compared fold-changes in marker values between those with and without PASC using mixed effects models with terms for PASC and early and late recovery time periods.\n\nRESULTSDuring early recovery, those who went on to develop PASC generally had higher levels of cytokine biomarkers including TNF-alpha (1.14-fold higher mean ratio, 95%CI 1.01-1.28, p=0.028) and IP-10 (1.28-fold higher mean ratio, 95%CI 1.01-1.62, p=0.038). Among those with PASC, there was a trend toward higher IL-6 levels during early recovery (1.28-fold higher mean ratio, 95%CI 0.98- 1.70, p=0.07) which became more pronounced in late recovery (1.44-fold higher mean ratio, 95%CI: 1.11-1.86, p<0.001). These differences were more pronounced among those with a greater number of PASC symptoms.\n\nCONCLUSIONSPersistent immune activation may be associated with ongoing symptoms following COVID-19. Further characterization of these processes might identify therapeutic targets for those experiencing PASC.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Fabio Fais", - "author_inst": "Auris Medical AG / Altamira Medica AG" + "author_name": "Michael J Peluso", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Reda Juskeviciene", - "author_inst": "Auris Medical AG / Altamira Medica AG" + "author_name": "Scott Lu", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Veronica Francardo", - "author_inst": "Auris Medical AG / Altamira Medica AG" + "author_name": "Alex F. Tang", + "author_inst": "University of California, San Francisco" }, { - "author_name": "St\u00e9phanie Mateos", - "author_inst": "Texcell SA" + "author_name": "Matthew S Durstenfeld", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Samuel Constant", - "author_inst": "Epithelix Sarl" + "author_name": "Hsi-en Ho", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Massimo Borelli", - "author_inst": "Life Sciences and Technologies Department, School of PhD Programmes, Magna Graecia University" + "author_name": "Sarah A. Goldberg", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Carrie A. Forman", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Ilja P. Hohenfeld", - "author_inst": "Auris Medical AG / Altamira Medica AG" + "author_name": "Sadie E. Munter", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Thomas Meyer", - "author_inst": "Auris Medical AG / Altamira Medica AG" + "author_name": "Rebecca Hoh", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Viva Tai", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Ahmed Chenna", + "author_inst": "Monogram Biosciences Inc.," + }, + { + "author_name": "Brandon C. Yee", + "author_inst": "Monogram Biosciences Inc.," + }, + { + "author_name": "John W. Winslow", + "author_inst": "Monogram Biosciences Inc.," + }, + { + "author_name": "Christos J. Petropoulos", + "author_inst": "Monogram Biosciences Inc." + }, + { + "author_name": "Bryan Greenhouse", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Peter W. Hunt", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Priscilla Y. Hsue", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Jeffrey N. Martin", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "J. Daniel Kelly", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "David V. Glidden", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Steven G Deeks", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Timothy J. Henrich", + "author_inst": "University of California, San Francisco" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "pharmacology and toxicology" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.07.11.451855", @@ -649284,95 +648305,67 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.07.21259699", - "rel_title": "Decoding Clinical Biomarker Space of COVID-19: Exploring Matrix Factorization-based Feature Selection Methods", - "rel_date": "2021-07-09", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.07.21259699", - "rel_abs": "One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 patients that are predictive of poor prognosis and morbidity. Our approach consists of two interconnected schemes: Feature Selection and Prognosis Classification. The former is based on different Matrix Factorization (MF)-based methods, and the latter is performed using Random Forest algorithm. Our model reveals that Arterial Blood Gas (ABG) O2 Saturation and C-Reactive Protein (CRP) are the most important clinical biomarkers determining the poor prognosis in these patients. Our approach paves the path of building quantitative and optimized clinical management systems for COVID-19 and similar diseases.", - "rel_num_authors": 19, + "rel_doi": "10.1101/2021.07.07.451463", + "rel_title": "SARS-CoV-2 Neurotropism and Single Cell Responses in Brain Organoids Containing Innately Developing Microglia", + "rel_date": "2021-07-08", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.07.451463", + "rel_abs": "Neuropsychiatric manifestations are common in both the acute and post-acute phase of SARS-CoV-2 infection, but the mechanisms of these effects are unknown. In a newly established brain organoid model with innately developing microglia, we demonstrate that SARS-CoV-2 infection causes an extensive cell death and loss of post-synaptic termini. Despite limited neurotropism and a decelerating viral replication, we observe a threefold increase in microglial engulfment of postsynaptic termini after SARS-CoV-2 exposure. We define the microglial responses to SARS-CoV-2 infection by single cell transcriptomic profiling and observe an upregulation of interferon-responsive genes as well as genes promoting migration and synaptic stripping. To a large extent, SARS-CoV-2 exposed microglia display a transcriptomic profile previously observed in neurodegenerative disorders characterized by early a synapse loss and an increased incident risk after a Covid-19 infection. Our results reveal that brain organoids infected with SARS-CoV-2 display disruption in circuit integrity via microglia-mediated synapse elimination and identifies a potential novel mechanism contributing to cognitive impairments in patients recovering from Covid-19.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Farshad Saberi-Movahed", - "author_inst": "North Carolina State University" - }, - { - "author_name": "Mahyar Mohammadifard", - "author_inst": "Birjand University of Medical Sciences" + "author_name": "Samudyata", + "author_inst": "Department of Physiology and Pharmacology, Karolinska Institute, Stockholm, Sweden" }, { - "author_name": "Adel Mehrpooya", - "author_inst": "Queensland University of Technology" + "author_name": "Ana Osorio Oliveira", + "author_inst": "Department of Physiology and Pharmacology, Karolinska Institute, Stockholm, Sweden" }, { - "author_name": "Mohammad Rezaei-Ravari", - "author_inst": "University of Kerman" + "author_name": "Susmita Malwade", + "author_inst": "Department of Physiology and Pharmacology, Karolinska Institute, Stockholm, Sweden" }, { - "author_name": "Kamal Berahmand", - "author_inst": "Queensland University of Technology" - }, - { - "author_name": "Mehrdad Rostami", - "author_inst": "Oulu University" - }, - { - "author_name": "Saeed Karami", - "author_inst": "Institute for Advanced Studies in Basic Sciences" - }, - { - "author_name": "Mohammad Najafzadeh", - "author_inst": "Graduate University of Advanced Technology" - }, - { - "author_name": "Davood Hajinezhad", - "author_inst": "SAS Institute Inc" - }, - { - "author_name": "Mina Jamshidi", - "author_inst": "Graduate University of Advanced Technology" - }, - { - "author_name": "Farshid Abedi", - "author_inst": "Birjand University of Medical Sciences" + "author_name": "Nuno Rufino de Sousa", + "author_inst": "Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden." }, { - "author_name": "Mahtab Mohammadifard", - "author_inst": "Birjand University of Medical Sciences" + "author_name": "Sravan K Goparaju", + "author_inst": "Department of Physiology and Pharmacology, Karolinska Institute, Stockholm, Sweden" }, { - "author_name": "Elnaz Farbod", - "author_inst": "City University of New York" + "author_name": "Funda Orhan", + "author_inst": "Department of Physiology and Pharmacology, Karolinska Institute, Stockholm, Sweden" }, { - "author_name": "Farinaz Safavi", - "author_inst": "National Institute of Health" + "author_name": "Laura Steponaviciute", + "author_inst": "Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden." }, { - "author_name": "Mohammadreza Dorvash", - "author_inst": "Monash University" + "author_name": "Martin Schalling", + "author_inst": "Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden" }, { - "author_name": "Mahdi Eftekhari", - "author_inst": "University of Kerman" + "author_name": "Steven D Sheridan", + "author_inst": "Center for Genomic Medicine and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA" }, { - "author_name": "Shahrzad Vahedi", - "author_inst": "Independent Researcher" + "author_name": "Roy H Perlis", + "author_inst": "Center for Genomic Medicine and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA" }, { - "author_name": "Farid Saberi-Movahed", - "author_inst": "Graduate University of Advanced Technology" + "author_name": "Antonio Gigliotti Rothfuchs", + "author_inst": "Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden." }, { - "author_name": "Iman Tavassoly", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Carl Sellgren-Majkowitz", + "author_inst": "Department of Physiology and Pharmacology, Karolinska Institute, Stockholm, Sweden" } ], "version": "1", - "license": "cc_by_nc", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "neuroscience" }, { "rel_doi": "10.1101/2021.07.06.21260112", @@ -651218,43 +650211,39 @@ "category": "neurology" }, { - "rel_doi": "10.1101/2021.07.06.21259051", - "rel_title": "Demonstrating an approach for evaluating synthetic geospatial and temporal epidemiologic data utility: Results from analyzing >1.8 million SARS-CoV-2 tests in the United States National COVID Cohort Collaborative (N3C)", + "rel_doi": "10.1101/2021.07.06.21260099", + "rel_title": "Following the science? Views from scientists on government advisory boards during the COVID-19 pandemic: a qualitative interview study in five European countries", "rel_date": "2021-07-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.06.21259051", - "rel_abs": "ObjectiveTo evaluate whether synthetic data derived from a national COVID-19 data set could be used for geospatial and temporal epidemic analyses.\n\nMaterials and MethodsUsing an original data set (n=1,854,968 SARS-CoV-2 tests) and its synthetic derivative, we compared key indicators of COVID-19 community spread through analysis of aggregate and zip-code level epidemic curves, patient characteristics and outcomes, distribution of tests by zip code, and indicator counts stratified by month and zip code. Similarity between the data was statistically and qualitatively evaluated.\n\nResultsIn general, synthetic data closely matched original data for epidemic curves, patient characteristics, and outcomes. Synthetic data suppressed labels of zip codes with few total tests (mean=2.9{+/-}2.4; max=16 tests; 66% reduction of unique zip codes). Epidemic curves and monthly indicator counts were similar between synthetic and original data in a random sample of the most tested (top 1%; n=171) and for all unsuppressed zip codes (n=5,819), respectively. In small sample sizes, synthetic data utility was notably decreased.\n\nDiscussionAnalyses on the population-level and of densely-tested zip codes (which contained most of the data) were similar between original and synthetically-derived data sets. Analyses of sparsely-tested populations were less similar and had more data suppression.\n\nConclusionIn general, synthetic data were successfully used to analyze geospatial and temporal trends. Analyses using small sample sizes or populations were limited, in part due to purposeful data label suppression -an attribute disclosure countermeasure. Users should consider data fitness for use in these cases.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.06.21260099", + "rel_abs": "ObjectivesTo explore the views and experiences of scientists working on government advisory boards during the COVID-19 pandemic, with the aim to learn lessons for future pandemic management and preparedness.\n\nDesignExplorative qualitative interview study.\n\nParticipantsTwenty one scientists with an official government advisory role during the COVID-19 pandemic in Belgium, the Netherlands, UK, Sweden or Germany.\n\nMethodsOnline video or telephone semi-structured interviews took place between December 2020 and April 2021. They were audio recorded and transcribed, and analyzed using a combination of inductive and deductive thematic analysis techniques.\n\nResultsScientists found working on the advisory boards during the COVID-19 pandemic to be a rewarding experience. However, they identified numerous challenges including learning to work in an interdisciplinary way, ensuring that evidence is understood and taken on board by governments, and dealing with media and public reactions. Scientists found themselves taking on new roles, the boundaries of which were not clearly defined. Consequently, they received substantial media attention and were often perceived and treated as a public figure.\n\nConclusionsScientists working on advisory boards in European countries faced similar challenges, highlighting key lessons to be learnt. Future pandemic preparedness efforts should focus on building interdisciplinary collaboration within advisory boards; ensuring transparency in how boards operate; defining and protecting boundaries of the scientific advisor role; and supporting scientists to inform the public in the fight against disinformation, whilst dealing with potential hostile reactions.\n\nO_TEXTBOXWhat is already known on this topicO_LITo tackle the COVID-19 pandemic, governments have established various types of scientific advisory boards to provide evidence and recommendations to policy makers.\nC_LIO_LIWith science becoming a focal point of this pandemic, scientific advisors also found themselves in the public eye.\nC_LIO_LIAs more attention is being paid to analysing what we can do to be better prepared for the next pandemic, the views of key actors, i.e. government scientific advisors, is still largely missing.\nC_LI\n\nWhat this study addsO_LIThe government scientific advisors working during the COVID-19 pandemic faced a number of challenges such as working in an interdisciplinary way with their peers on scientific boards, establishing a working relationship with government allowing evidence to be taken on board, and dealing with media and public reactions.\nC_LIO_LIIt is crucial that we take on board key lessons shared by scientific advisors, which calls for building interdisciplinary collaboration within advisory boards; ensuring transparency in both how boards operate and clear boundaries of scientists-government relationship; and supporting scientists in their role of informing the public.\nC_LI\n\nC_TEXTBOX", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Jason A Thomas", - "author_inst": "University of Washington" - }, - { - "author_name": "Randi E Foraker", - "author_inst": "Division of General Medical Sciences, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA; Institute for Informatics, School of Medicine," + "author_name": "Elien Colman", + "author_inst": "Department of Family Medicine and Population Health, University of Antwerp, 2610 Wilrijk, Belgium" }, { - "author_name": "Noa Zamstein", - "author_inst": "MDClone Ltd., Beer Sheva, Israel" + "author_name": "Marta Wanat", + "author_inst": "Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG" }, { - "author_name": "Philip RO Payne", - "author_inst": "Division of General Medical Sciences, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA; Institute for Informatics, School of Medicine," + "author_name": "Herman Goosens", + "author_inst": "Laboratory of Medical Microbiology, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium" }, { - "author_name": "Adam B Wilcox", - "author_inst": "Department of Biomedical Informatics & Medical Education, University of Washington, Seattle, WA, USA; UW Medicine, Seattle, WA, USA" + "author_name": "Sarah Tonkin-Crine", + "author_inst": "Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG" }, { - "author_name": "- N3C Consortium", - "author_inst": "" + "author_name": "Sibyl Anthierens", + "author_inst": "Department of Family Medicine and Population Health, University of Antwerp, 2610 Wilrijk, Belgium" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "health policy" }, { "rel_doi": "10.1101/2021.07.06.21259473", @@ -653244,49 +652233,69 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.01.21259852", - "rel_title": "Efficacy of remdesivir-containing therapy in hospitalized COVID-19 patients: a prospective clinical experience", + "rel_doi": "10.1101/2021.07.03.21259949", + "rel_title": "Preserved C-reactive protein responses to blood stream infections following tocilizumab treatment for COVID-19", "rel_date": "2021-07-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.01.21259852", - "rel_abs": "Objectivesremdesivir is currently approved for the treatment of COVID-19. The recommendation for using remdesivir in COVID-19 was based on the in vitro and in vivo activity of this drug against SARS-CoV-2.\n\nMethodsthis was a prospective, observational study conducted on a large population of patients hospitalized for COVID-19. The primary endpoint of the study was to evaluate the impact of remdesivir-containing therapy on 30-day mortality; secondary endpoint was the impact of remdesivir-containing therapy on the need of high flow oxygen therapy (HFNC) or non-invasive ventilation (NIV) or mechanical ventilation. Data were analyzed after propensity score matching.\n\nResults407 patients with SARS-CoV-2 pneumonia were consecutively enrolled. Out of these, 294 (72.2%) and 113 (27.8%) were respectively treated or not with remdesivir. Overall, 61 (14.9%) patients were treated during hospitalization with non-invasive or mechanical ventilation, while a 30-day mortality was observed in 21 (5.2%) patients with a global in-hospital mortality of 11%. Cox regression analysis, after propensity score matching, showed that therapies, including remdesivir-containing therapy, were not statistically associated with 30-day survival or mortality, while need of HFNC/NIV (HR 17.921, CI95% 0.954-336.73, p=0.044) and mechanical ventilation (HR 3.9, CI95% 5.36-16.2, p=0.003) resulted independently associated with 30-day mortality. Finally, therapies including or not remdesivir were not independently associated with a lower or higher risk of HFNC/NIV or mechanical ventilation.\n\nConclusionsthis real-life experience about the remdesivir use in hospitalized patients with COVID-19 was not associated with significant increase in rates of survival or reduced use of HFNC/NIV or mechanical ventilation, compared to patients treated with other therapies not including remdesivir.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.03.21259949", + "rel_abs": "C-reactive protein (CRP) levels are elevated following bacterial infections but may be attenuated by the IL-6-receptor antagonist tocilizumab. In hospitalised COVID-19 patients, tocilizumab induced a transient (<21 day) fall in CRP but retained CRP responses to nosocomial blood stream infections, and therefore its utility in guiding antibiotic prescribing.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Alessandro Russo", - "author_inst": "Infectious Diseases Division, Department of Medicine, University of Udine, Udine, Italy" + "author_name": "Emmanuel Q Wey", + "author_inst": "Royal Free London NHS Trust" + }, + { + "author_name": "Clare Bristow", + "author_inst": "Royal Free London NHS Trust" }, { - "author_name": "Erica Binetti", - "author_inst": "Sapienza University of Rome" + "author_name": "Aarti Nandani", + "author_inst": "Royal Free London NHS Trust" }, { - "author_name": "Cristian Borrazzo", - "author_inst": "Sapienza University of Rome" + "author_name": "Bryan O'Farrell", + "author_inst": "Royal Free London NHS Trust" }, { - "author_name": "Elio Gentilini Cacciola", - "author_inst": "Sapienza University of Rome" + "author_name": "Jay Pang", + "author_inst": "Royal Free London NHS Trust" }, { - "author_name": "Luigi Battistini", - "author_inst": "Sapienza University of Rome" + "author_name": "Marisa Lanzman", + "author_inst": "Royal Free London NHS Trust" }, { - "author_name": "Giancarlo Ceccarelli", - "author_inst": "University of Rome La Sapienza" + "author_name": "Shuang Yang", + "author_inst": "Royal Free London NHS Trust" }, { - "author_name": "Claudio M Mastroianni", - "author_inst": "Sapienza University" + "author_name": "Soo Ho", + "author_inst": "Royal Free London NHS Trust" }, { - "author_name": "Gabriella d'Ettorre", - "author_inst": "\"Sapienza\" University, Rome, Italy" + "author_name": "Damien Mack", + "author_inst": "Royal Free London NHS Trust" + }, + { + "author_name": "Michael Spiro", + "author_inst": "University College London" + }, + { + "author_name": "Indran Balakrishnan", + "author_inst": "Royal Free London NHS Trust" + }, + { + "author_name": "Sanjay Bhagani", + "author_inst": "Royal Free London NHS Trust" + }, + { + "author_name": "Gabriele Pollara", + "author_inst": "University College London" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -654982,47 +653991,23 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.07.06.21259955", - "rel_title": "Vaccination and COVID-19 dynamics in hemodialysis patients: a population-based study in France.", + "rel_doi": "10.1101/2021.07.06.21260077", + "rel_title": "On the effectiveness of COVID-19 restrictions and lockdowns: Pan metron ariston", "rel_date": "2021-07-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.06.21259955", - "rel_abs": "ImportanceMaintenance hemodialysis (MHD) patients have a high mortality risk after COVID-19 and an altered humoral response to vaccines, but vaccine clinical efficacy remains unknown in this population.\n\nObjectiveTo estimate the association between vaccination and COVID-19 hospitalization rate in MHD patients\n\nDesignUsing Bayesian multivariable spatiotemporal models, we estimated the expected number of SARS-CoV-2 severe infections (infections with hospital admission) in MHD patients from simultaneous cases in the general population.\n\nSettingFrench population-based retrospective analysis in MHD and non-dialysis patients.\n\nParticipantsModels were fitted from 3620 hospitalizations of MHD patients and 457,160 hospitalizations in the general population.\n\nExposureSevere SARS-CoV-2 infections in the general population and vaccine exposure.\n\nMain Outcome and MeasureWeekly incidence of severe infections in MHD patients.\n\nResultsDuring the first epidemic wave, incidence of severe infections in MHD patients was approximately proportional to incidence in the general population. However, our model overestimated incidence during the second wave, suggesting an effect of prevention measures during the 2nd wave. A second model (based on data up to the end of the 2nd wave) estimated that the risk in MHD patients decreased between waves 1 and 2, with incidence rate ratio (IRR) = 0.70 (95% CI: 0.64, 0.76). Moreover, while this model correctly estimated the reported MHD cases up to the end of the 2nd wave, predictions overestimated the expected number of cases from the beginning of the vaccination campaign. Using vaccination coverages as additional predictors permitted to correctly fit the weekly reported number of cases, with IRR in MHD patients of 0.41 (95% CI: 0.28, 0.58) for vaccine exposure in MHD patients and 0.50 (95% CI: 0.40, 0.61) per 10% increase in vaccination coverage in the same-age general population.\n\nConclusions and RelevanceOur findings suggest that both individual and herd immunity due to vaccination may yield a protective effect against severe forms of COVID-19 in MHD patients.\n\nQuestionWhether vaccination against SARS-CoV-2 limits hospitalization rates in hemodialysis patients is still unknown.\n\nFindingsBy modeling the dynamics of 3620 hospital admissions for SARS-CoV-2 infections among hemodialysis patients, as a proportion of 457,160 cases reported in the French general population from March 2020 to April 2021, we identified vaccination coverage in both hemodialysis patients and the general population as independently associated with protection of hemodialysis patients against severe infection.\n\nMeaningVaccination against SARS-CoV-2 is associated with reduced hospitalization rate in hemodialysis patients.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.06.21260077", + "rel_abs": "I examine the dynamics of confirmed case (and death) growth rates conditional on different levels of severity in implemented NPIs, the mobility of citizens and other non restrictive policies. To account for the endogeneity of many of these variables, and the possibility of correlated latent (unobservable) country characteristics, I estimate a four structural model of the evolution of case growth rates, death growth rates, average changes in mobility and the determination of the severity of NPIs. There are strongly decreasing returns to the stringency of NPIs, especially for extreme lockdowns, as no significant improvement in the main outcome measures is found beyond NPIs corresponding to a Stringency Index range of 51-60 for cases and 41-50 for deaths. A non-restrictive policy of extensive and open testing has half of the impact on pandemic dynamics as the optimal NPIs, with none of the associated social and economic costs resulting from the latter. Decreases in mobility were found to increase, rather than decrease case growth rates, consistent with arguments that within-household transmission-resulting from spending more time at residences due to mobility restrictions-may outweigh the benefits of reduced community transmission. Vaccinations led to a fall in case and death growth rates, however the effect size must be re-evaluated when more data becomes available. Governments conditioned policy choice on recent pandemic dynamics, and were found to de-escalate the associated stringency of implemented NPIs more cautiously than in their escalation, i.e., policy mixes exhibited significant hysteresis. Finally, at least 90% of the maximum effectiveness of NPIs can be achieved by policies with an average Stringency index of 31-40, without restricting internal movement or imposing stay at home measures, and only recommending (not enforcing) closures on workplaces and schools, accompanied by public informational campaigns. Consequently, the positive effects on case and death growth rates of voluntary behavioral changes in response to beliefs about the severity of the pandemic, generally trumped those arising from mandatory behavioral restrictions. The exception being more stringent mandatory restrictions on gatherings and international movement, which were found to be effective. The findings suggest that further work should be directed at re-evaluating the effectiveness of NPIs, particularly towards empirically determining the optimal policy mix and associated stringency of individual NPIs.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "khalil el karoui", - "author_inst": "henri mondor hospital" - }, - { - "author_name": "maryvonne hourmant", - "author_inst": "CHU nantes" - }, - { - "author_name": "carole ayav", - "author_inst": "CHRU Nancy" - }, - { - "author_name": "francois glowacki", - "author_inst": "CHRU Lille" - }, - { - "author_name": "cecile couchoud", - "author_inst": "Agence de la biomedecine, France" - }, - { - "author_name": "nathanael lapidus", - "author_inst": "Institut Pierre Louis d'Epidemiologie, Paris" - }, - { - "author_name": "- REIN registry", - "author_inst": "" + "author_name": "Leonidas Spiliopoulos", + "author_inst": "Max Planck Institute for Human Development" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "nephrology" + "category": "health policy" }, { "rel_doi": "10.1101/2021.07.05.21260050", @@ -657060,49 +656045,29 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.07.03.21259881", - "rel_title": "Modeling the COVID-19 Vaccination Dynamics in the United States: An Estimation of Coverage Velocity and Carrying Capacity Based on Socio-demographic Vulnerability Indices in California", + "rel_doi": "10.1101/2021.07.01.21259851", + "rel_title": "Informing University COVID-19 Decisions Using Simple Compartmental Models", "rel_date": "2021-07-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.03.21259881", - "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19) disparities among vulnerable populations are of paramount concern that extend to vaccine administration. With recent uptick in infection rates, dominance of the delta variant, and proposal of a third booster shot, understanding the population-level vaccine coverage dynamics and underlying sociodemographic factors is critical for achieving equity in public health outcomes. This study aimed to characterize the scope of vaccine inequity in California counties through modeling the trends of vaccination using the Social Vulnerability Index (SVI).\n\nMethodsOverall SVI, its four themes, and 9228 data points of daily vaccination numbers from December 15, 2020, to May 23, 2021, across all 58 California counties were used to model the growth velocity and anticipated maximum proportion of population vaccinated, defined as having received at least one dose of vaccine.\n\nResultsBased on the overall SVI, the vaccination coverage velocity was lower in counties in the high vulnerability category (v=0.0346, 95% CI: 0.0334, 0.0358) compared to moderate (v=0.0396, 95% CI: 0.0385, 0.0408) and low (v=0.0414, 95% CI: 0.0403, 0.0425) vulnerability categories. SVI Theme 3 (minority status and language) yielded the largest disparity in coverage velocity between low and high-vulnerable counties (v=0.0423 versus v=0.035, P<0.001). Based on the current trajectory, while counties in low-vulnerability category of overall SVI are estimated to achieve a higher proportion of vaccinated individuals, our models yielded a higher asymptotic maximum for highly vulnerable counties of Theme 3 (K=0.544, 95% CI: 0.527, 0.561) compared to low-vulnerability counterparts (K=0.441, 95% CI: 0.432, 0.450). The largest disparity in asymptotic proportion vaccinated between the low and high-vulnerability categories was observed in Theme 2 describing the household composition and disability (K=0.602, 95% CI: 0.592, 0.612; versus K=0.425, 95% CI: 0.413, 0.436). Overall, the large initial disparities in vaccination rates by SVI status attenuated over time, particularly based on Theme 3 status which yielded a large decrease in cumulative vaccination rate ratio of low to high-vulnerability categories from 1.42 to 0.95 (P=0.002).\n\nConclusionsThis study provides insight into the problem of COVID-19 vaccine disparity across California which can help promote equity during the current pandemic and guide the allocation of future vaccines such as COVID-19 booster shots.\n\nKey MessagesO_LIThe Social Vulnerability Index (SVI) and its four themes along with the daily proportion of vaccinated individuals across the 58 California counties were used to model, overall and by theme, the growth velocity and anticipated maximum proportion of population vaccinated.\nC_LIO_LIOverall, high vulnerability counties in California had a lower vaccine coverage velocity compared to low and moderate vulnerability counties.\nC_LIO_LIThe largest disparity in coverage velocity between low and high vulnerability counties was observed based on the SVI Theme 3 status (minority status & language).\nC_LIO_LIBased on the current trajectory, highly vulnerable counties based on SVI Theme 3 are expected to eventually achieve a higher proportion of vaccinated individuals compared to low vulnerable counterparts.\nC_LIO_LIUnderstanding the vaccine coverage dynamics and underlying sociodemographic factors is critical for achieving equity in public health outcomes during disease outbreaks and catastrophes.\nC_LI", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.01.21259851", + "rel_abs": "Tracking the COVID-19 pandemic has been a major challenge for policy makers. Although, several efforts are ongoing for accurate forecasting of cases, deaths, and hospitalization at various resolutions, few have been attempted for college campuses despite their potential to become COVID-19 hot-spots. In this paper, we present a real-time effort towards weekly forecasting of campus-level cases during the fall semester for four universities in Virginia, United States. We discuss the challenges related to data curation. A causal model is employed for forecasting with one free time-varying parameter, calibrated against case data. The model is then run forward in time to obtain multiple forecasts. We retrospectively evaluate the performance and, while forecast quality suffers during the campus reopening phase, the model makes reasonable forecasts as the fall semester progresses. We provide sensitivity analysis for the several model parameters. In addition, the forecasts are provided weekly to various state and local agencies.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Alexander Bruckhaus", - "author_inst": "Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, 2025 Zonal A" - }, - { - "author_name": "Aidin Abedi", - "author_inst": "Department of Neurosurgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA" - }, - { - "author_name": "Sana Salehi", - "author_inst": "Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, 2025 Zonal A" - }, - { - "author_name": "Trevor A Pickering", - "author_inst": "Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA" - }, - { - "author_name": "Yujia Zhang", - "author_inst": "Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, 2025 Zonal A" - }, - { - "author_name": "Aubrey Martinez", - "author_inst": "Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, 2025 Zonal A" + "author_name": "Benjamin Hurt", + "author_inst": "University of Virginia" }, { - "author_name": "Matthew Lai", - "author_inst": "Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, 2025 Zonal A" + "author_name": "Aniruddha Adiga", + "author_inst": "University of Virginia" }, { - "author_name": "Rachael Garner", - "author_inst": "Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, 2025 Zonal A" + "author_name": "Madhav Marathe", + "author_inst": "University of Virginia" }, { - "author_name": "Dominique Duncan", - "author_inst": "Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, 2025 Zonal A" + "author_name": "Christopher Barrett", + "author_inst": "University of Virginia" } ], "version": "1", @@ -658698,55 +657663,55 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.07.02.21259900", - "rel_title": "Children's emotional wellbeing during spring 2020 COVID-19 restrictions: a qualitative study with parents of young children in England", + "rel_doi": "10.1101/2021.07.04.21255203", + "rel_title": "Vaccination willingness for COVID-19 among health care workers in Switzerland", "rel_date": "2021-07-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.02.21259900", - "rel_abs": "BackgroundDuring COVID-19 restrictions in England in spring 2020, early years settings for young children were closed to all but a small percentage of families, social contact was limited and play areas in parks were closed. Concerns were raised about the impact of these restrictions on young childrens emotional wellbeing. The aim of this study was to explore parents perceptions of young childrens emotional wellbeing during these COVID-19 restrictions.\n\nMethodsWe interviewed 20 parents of children 3-4 years due to begin school in England in September 2020. Interviews were conducted via telephone (n=18) and video call (n=2), audio-recorded and transcribed verbatim. Interviews focused on childcare arrangements, childrens behaviour and transition to school. A sample of transcripts were coded line-by-line to create a coding framework, which was subsequently applied to the remaining transcripts. Coded data were then analysed using a nurture lens to develop themes and further understanding.\n\nResultsParticipants were predominantly mothers (n=16), White British (n=10), and educated to degree level (n=13), with half the sample living in the highest deprivation quintile in England (n=10). Five were single parents. Three themes developed from nurturing concepts were identified: creating age-appropriate explanations; understanding childrens behaviour; concerns about school transition. Parents recognised their childrens emotional wellbeing was impacted but attempted to support their young children whilst looking ahead to their transition to primary school.\n\nConclusionsThis study is one of the first to examine in-depth the impact of COVID-19 restrictions on young childrens emotional wellbeing. The longer-term impacts are not yet understood. Although young children may be unable to understand in detail what the virus is, they undoubtedly experience the disruption it brings to their lives. The wellbeing of families and children needs to be nurtured as they recover from the effects of the pandemic to allow them to thrive.\n\nKey messagesCOVID-19 restrictions are predicted to have a negative impact on young children.\n\nWe interviewed parents of children in England due to begin primary school to understand their experiences of COVID-19 restrictions.\n\nNurture concepts helped us understand the challenges families faced.\n\nKey themes identified were: creating age-appropriate explanations; understanding childrens behaviour; and concerns about school transition.\n\nWe suggest a nurturing approach to recovery to best support children and their families.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.04.21255203", + "rel_abs": "Aims of the studyVaccination is regarded as the most promising response to the COVID-19 pandemic. We assessed opinions towards COVID-19 vaccination, willingness to be vaccinated, and reasons for vaccination hesitancy among health care workers (HCWs).\n\nMethodsWe conducted a cross-sectional, web-based survey among 3,793 HCWs in December 2020 in the Canton of Solothurn, Switzerland, before the start of the national COVID-19 vaccination campaign.\n\nResultsMedian age was 43 years (interquartile range [IQR] 31-53), 2,841 were female (74.9%). 1,511 HCWs (39.8%) reported willingness to accept vaccination, while 1,114 (29.4%) were unsure, and 1,168 (30.8%) would decline vaccination. Among medical doctors, 76.1% were willing, while only 27.8% of nurses expressed willingness. Among 1,168 HCWs who would decline vaccination, 1,073 (91.9%) expressed concerns about vaccine safety and side effects. The willingness of HCWs to be vaccinated was associated with older age (adjusted odds ratio [aOR] 1.97, 95%Cl 1.71-2.27) and having been vaccinated for influenza this year (aOR 2.70, 95%Cl 2.20-3.31). HCWs who reported a lack of confidence in government were less likely to be willing to be vaccinated (aOR 0.58, 95%Cl 0.40-0.84), and women were less willing to be vaccinated than men (OR 0.33 (0.28-0.38).\n\nConclusionLess than half of HCWs reported willingness to be vaccinated before the campaign start, but proportions varied greatly depending on the profession and workplace. Strategies with clear and objective messages that particularly address the concerns of HCWs are needed if their willingness to be vaccinated is to be increased.", "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Stephanie Chambers", - "author_inst": "University of Glasgow" + "author_name": "Kathrin Zuercher", + "author_inst": "Institue of Social and Preventive, University of Bern, Bern, Switzerland" }, { - "author_name": "Joanna Clarke", - "author_inst": "University of Birmingham" + "author_name": "Catrina Mugglin", + "author_inst": "Institue of Social and Preventive, University of Bern, Bern, Switzerland" }, { - "author_name": "Ruth Kipping", - "author_inst": "University of Bristol" + "author_name": "Matthias Egger", + "author_inst": "Institue of Social and Preventive, University of Bern, Bern, Switzerland" }, { - "author_name": "Rebecca Langford", - "author_inst": "University of Bristol" + "author_name": "Sandro Mueller", + "author_inst": "Amt fuer soziale Sicherheit, Kanton Solothurn" }, { - "author_name": "Rachel Brophy", - "author_inst": "University of Bristol" + "author_name": "Michael Fluri", + "author_inst": "Hausarztpraxis Weissenstein, Langendorf, Kanton Solothurn, Schweiz" }, { - "author_name": "Kimberly J Hannam", - "author_inst": "University of Bristol" + "author_name": "Laurence Bolick", + "author_inst": "Department of Internal Medicine, Infectious Diseases and Hospital Epidemiology, Cantonal Hospital Olten, Switzerland" }, { - "author_name": "Kate Willis", - "author_inst": "University of Bristol" + "author_name": "Rein Jan Piso", + "author_inst": "Department of Internal Medicine, Infectious Diseases and Hospital Epidemiology, Cantonal Hospital Olten, Switzerland" }, { - "author_name": "Hilary Taylor", - "author_inst": "University of Bristol" + "author_name": "Matthias Hoffmann", + "author_inst": "Department of Internal Medicine, Infectious Diseases and Hospital Epidemiology, Cantonal Hospital Olten, Switzerland" }, { - "author_name": "Sharon Simpson", - "author_inst": "University of Glasgow" + "author_name": "Lukas Fenner", + "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; and Gesundheitsamt, Kanton Solothurn, Switzerland" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.07.06.21259749", @@ -660308,47 +659273,103 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2021.07.03.21259958", - "rel_title": "The risk of severe COVID-19 and mortality from COVID-19 in people living with HIV compared to individuals without HIV - a systematic review and meta-analysis of 1 268 676 individuals.", + "rel_doi": "10.1101/2021.07.02.21259897", + "rel_title": "Anti-spike antibody response to natural SARS-CoV-2 infection in the general population", "rel_date": "2021-07-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.03.21259958", - "rel_abs": "BackgroundThere is conflicting evidence about the risk of mortality and severe disease due to COVID-19 in people living with HIV (PLHIV).\n\nObjectivesTo compare mortality, hospitalization, and the need for intensive care services due to COVID-19 between PLHIV and individuals without HIV based on data from the existing literature.\n\nMethodsA comprehensive search in PubMed, Cochrane Library, Scopus, China Academic Journals Full Text Database, the Database of Abstracts of Reviews of Effectiveness (DARE) and and the medRXIV and bioRxiv databases of preprints was carried out. Each data source was searched from 1 January 2020 to 20th of February 2021. Eligible studies were case control, cross-sectional and cohort studies where participants had confirmed COVID-19. From each study, data on numbers of PLHIV and individuals without HIV for each outcome were extracted. Study quality was assessed using the MethodologicAl STandard for Epidemiological Research (MASTER) scale. Data synthesis used a bias adjusted model and predefined age and geographical subgroups were analysed.\n\nResultsOf a total of 2757 records identified, 11 studies, from 4 countries, the United Kingdom, Spain, the United States of America and South Africa, were included. The total participants assessed for the outcomes in this meta-analysis were 1 268 676 of which 13 886 were PLHIV. Overall, the estimated effect of HIV on mortality suggested some worsening (OR 1.3, 95% CI: 0.9 - 2.0, I2 = 78.6%) with very weak evidence against the model hypothesis at this sample size. However, in individuals aged <60 years, the estimated effect on mortality suggested more worsening in PLHIV (OR 2.7, 95% CI: 1.1 - 6.5, I2 = 95.7%) with strong evidence against the model hypothesis at this sample size. HIV was also associated with an estimated effect on hospitalization for COVID-19 that suggested worsening (OR 1.6, 95% CI: 1.3-2.1, I2 = 96.0%) also with strong evidence against the model hypothesis at this sample size. A secondary analysis of the included studies suggested no difference, by HIV status, in the prevalence of pre-existing conditions.\n\nConclusionPeople living with HIV have higher risk of death and hospitalisation from COVID-19, compared to individuals without HIV. A secondary analysis suggests this is not due to associated comorbid conditions. The difference in mortality is exaggerated in those younger than 60 years of age.\n\nRegistrationPROSPERO: CRD42020221311 (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=221311)\n\nEvidence before this studyFindings from existing studies have shown conflicting evidence concerning the risk of severe COVID-19 and death from COVID-19 in people living with HIV (PLHIV) compared to people without HIV. Evidence from three existing systematic reviews suggests that the risk of severe COVID-19 and death from COVID-19 in PLHIV may be similar to that in individuals without HIV. However, findings from three large cohort studies and one meta-analysis of four studies suggest that the risk of death from COVID-19 in PLHIV may be higher than that in individuals without HIV. One of the large cohort studies, which is also included in the previous meta-analysis, consisted of individuals with unknown COVID-19 status, and therefore there is still debate concerning the risk of severe COVID-19 outcomes in PLHIV.\n\nAdded value of this studyIn this meta-analysis of 11 studies with 1 268 676 individuals with confirmed COVID-19, we found a stronger difference in mortality by HIV status for those individuals below the age of 60 years, and over this age, HIV had an attenuated effect on mortality, suggesting that age-related mortality overshadows PLHIV related mortality. Further, PLHIV had increased odds of being hospitalized and needing intensive cares services, probably related to increased COVID-19 severity in PLHIV. A secondary analysis of the included studies suggested no difference in the prevalence of pre-existing conditions.\n\nImplications of all the available evidenceOur findings suggest that PLHIV are at higher risk than the general population and should be prioritized for vaccine coverage and monitoring if diagnosed with COVID-19. This is especially important for countries in Sub-Saharan Africa that have a high burden of HIV in the younger populations who are more vulnerable.\n\nStrengthsThis study was carried out rigorously following the PRISMA guidelines for systematic reviews and meta-analyses. We used a comprehensive search strategy across most of the main citation databases to ensure that no relevant studies were missed. We included studies where participants had confirmed COVID-19 only and we synthesized the findings from studies using a bias adjustment model that took into consideration the quality of included studies.\n\nLimitationsAll studies included in this review are observational studies and conclusions about causality require cautious interpretation. Due to a lack of data from included studies, we were not able to analyse the effect of being on treatment for HIV, and HIV control variables such as viral load and CD4 counts on COVID-19 hospitalization, intensive care services and mortality. Lastly most of the included studies had small samples overall or for PLHIV and this may affect the effect estimates in this analysis. Future research is therefore indicated to confirm these findings.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.02.21259897", + "rel_abs": "We estimated the duration and determinants of antibody response after SARS-CoV-2 infection in the general population using representative data from 7,256 United Kingdom COVID-19 infection survey participants who had positive swab SARS-CoV-2 PCR tests from 26-April-2020 to 14-June-2021. A latent class model classified 24% of participants as non-responders not developing anti-spike antibodies. These seronegative non-responders were older, had higher SARS-CoV-2 cycle threshold values during infection (i.e. lower viral burden), and less frequently reported any symptoms. Among those who seroconverted, using Bayesian linear mixed models, the estimated anti-spike IgG peak level was 7.3-fold higher than the level previously associated with 50% protection against reinfection, with higher peak levels in older participants and those of non-white ethnicity. The estimated anti-spike IgG half-life was 184 days, being longer in females and those of white ethnicity. We estimated antibody levels associated with protection against reinfection likely last 1.5-2 years on average, with levels associated with protection from severe infection present for several years. These estimates could inform planning for vaccination booster strategies.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Lovemore Mapahla", - "author_inst": "1.\tDivision of Epidemiology and Biostatistics, Department of Global Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South A" + "author_name": "Jia Wei", + "author_inst": "University of Oxford" }, { - "author_name": "Asmaa Abdelmaksoud", - "author_inst": "Department of Population Medicine, College of medicine, QU Health, Qatar University, Doha, Qatar" + "author_name": "Philippa C Matthews", + "author_inst": "University of Oxford" }, { - "author_name": "Rida Arif", - "author_inst": "Department of Population Medicine, College of medicine, QU Health, Qatar University, Doha, Qatar" + "author_name": "Nicole Stoesser", + "author_inst": "University of Oxford" }, { - "author_name": "Nazmul Islam", - "author_inst": "Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar" + "author_name": "Thomas Maddox", + "author_inst": "Office for National Statistics" }, { - "author_name": "Albert Chinhenzva", - "author_inst": "Division of Epidemiology and Biostatistics, Department of Global Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Afri" + "author_name": "Luke Lorenzi", + "author_inst": "Office for National Statistics" }, { - "author_name": "Suhail A. R. Doi", - "author_inst": "Department of Population Medicine, College of medicine, QU Health, Qatar University, Doha, Qatar" + "author_name": "Ruth Studley", + "author_inst": "Office for National Statistics" }, { - "author_name": "Tawanda Chivese", - "author_inst": "Qatar University" + "author_name": "John I Bell", + "author_inst": "University of Oxford" + }, + { + "author_name": "John N Newton", + "author_inst": "Public Health England" + }, + { + "author_name": "Jeremy Farrar", + "author_inst": "Wellcome Trust" + }, + { + "author_name": "Ian Diamond", + "author_inst": "Office for National Statistics" + }, + { + "author_name": "Emma Rourke", + "author_inst": "Office for National Statistics" + }, + { + "author_name": "Alison Howarth", + "author_inst": "University of Oxford" + }, + { + "author_name": "Brian D Marsden", + "author_inst": "University of Oxford" + }, + { + "author_name": "Sarah Hoosdally", + "author_inst": "University of Oxford" + }, + { + "author_name": "E Yvonne Jones", + "author_inst": "University of Oxford" + }, + { + "author_name": "David I Stuart", + "author_inst": "University of Oxford" + }, + { + "author_name": "Derrick W Crook", + "author_inst": "NIHR Oxford Biomedical Research Centre" + }, + { + "author_name": "Tim E.A. Peto", + "author_inst": "University of Oxford" + }, + { + "author_name": "Koen B. Pouwels", + "author_inst": "University of Oxford" + }, + { + "author_name": "A. Sarah Walker", + "author_inst": "University of Oxford" + }, + { + "author_name": "David W Eyre", + "author_inst": "University of Oxford" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "hiv aids" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.07.03.21259959", @@ -662026,41 +661047,45 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2021.06.29.21259609", - "rel_title": "Neuropsychiatric disorders as risk factors and consequences of COVID-19: A Mendelian randomization study", + "rel_doi": "10.1101/2021.06.29.21259579", + "rel_title": "BNT162b2 mRNA Vaccine Effectiveness Given Confirmed Exposure; Analysis of Household Members of COVID-19 Patients", "rel_date": "2021-07-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.29.21259609", - "rel_abs": "BackgroundMore than 180 million cases of COVID-19 have been reported worldwide. It has been proposed that neuropsychiatric disorders may be risk factors and/or consequences of COVID-19 infection. However, observational studies could be affected by confounding bias.\n\nMethodsWe performed bi-directional two-sample Mendelian randomization (MR) analysis to evaluate causal relationships between liability to COVID-19 (and severe/critical infection) and a wide range of neuropsychiatric disorders or traits. We employed GWAS summary statistics from the COVID-19 Host Genetics Initiative. A variety of MR methods including those accounting for horizontal pleiotropy were employed.\n\nResultsOverall, we observed evidence that liability to COVID-19 or severe infection may be causally associated with higher risks of post-traumatic stress disorder (PTSD), bipolar disorder (BD) (especially BD II), schizophrenia (SCZ), attention deficit hyperactivity disorder (ADHD) and suicidal thought (ST) when compared to the general population. On the other hand, liability to a few psychiatric traits/disorders, for example ADHD, alcohol and opioid use disorders may be causally associated with higher risks of COVID-19 infection or severe disease. In genetic correlation analysis, cannabis use disorder, ADHD, and anxiety showed significant and positive genetic correlation with critical or hospitalized infection. All the above findings passed multiple testing correction at a false discovery rate (FDR)<0.05. For pneumonia, in general we observed a different pattern of causal associations. We observed bi-directional positive associations with depression- and anxiety-related phenotypes.\n\nConclusionsIn summary, this study provides evidence for tentative bi-directional causal associations between liability to COVID-19 (and severe infection) and a number of neuropsychiatric disorders. Further replications and prospective studies are required to verify the findings.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.29.21259579", + "rel_abs": "ImportanceWhile the mRNA BNT162b2 vaccine effectivness was demonstrated in general population, the question of effectiveness given confirmed exposure has yet been answered, though it has policy implications, as the need for self-quarantine when exposed and protective measures for vaccinated in high-risk areas.\n\nObjectiveAssessing the BNT162b2 vaccine effectiveness in preventing SARS-CoV-2 infection given high-risk exposure, through analysis of household members of confirmed cases.\n\nDesignRetrospective cohort study. Data of household members of confirmed SARS-CoV-2 cases between 20/12/2020 and 17/03/2021 were collected.\n\nSettingNationally centralized database of Maccabi Healthcare Services (MHS), the second largest Healthcare Maintenance Organization in Israel.\n\nParticipants2.5 million MHS members were considered, of which we included only households with two adult members, given possible lower transmission and susceptibility among children. Households with no prior confirmed infections and a confirmed index case during the study period were included.\n\nExposureParticipants were classified into three vaccination groups in time of the index case (the confirmed exposure)-Unvaccinated; Fully Vaccinated(7 or more days post second dose) and a reference control group of Recently Vaccinated Once(0-7 days from the first dose, presumably still unprotected).\n\nMain Outcomes and MeasuresAssessing the probability of an additional SARS-CoV-2 infection in the household occurring within 10 days of an index case, calculated separately for the three vaccination groups. Main outcome was vaccine effectiveness given confirmed exposure. High testing rates among household members enabled us to estimate with a high degree of confidence effectiveness against asymptomatic SARS-CoV-2 infection as well.\n\nResultsA total of 173,569 households were included, out of which 6,351 households had an index infection (mean [SD] age, 58.9 [13.5] years; 50% were women). Vaccine effectiveness of Fully Vaccinated compared to Unvaccinated participants was 80.0% [95% CI, 73.0-85.1] and 82.0% [95% CI, 75.5-86.7] compared to those Recently Vaccinated Once.\n\nConclusion and RelevanceThe BNT162b2 vaccine is effective in a high-risk, real life, exposure scenario, but the protection rates afforded in these settings are lower than those previously described. Household members of COVID-19 patients and any individual with a confirmed exposure to COVID-19 are still at a considerable risk of being infected even if fully vaccinated.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Yong XIANG", - "author_inst": "Chinese University of Hong Kong" + "author_name": "Sivan Gazit", + "author_inst": "KSM Research and Innovation Center, Maccabi Healthcare Services" }, { - "author_name": "Jinghong QIU", - "author_inst": "Chinese University of Hong Kong" + "author_name": "Barak Mizrahi", + "author_inst": "KI Research Institute" }, { - "author_name": "Ruoyu ZHANG", - "author_inst": "Chinese University of Hong Kong" + "author_name": "Nir Kalkstein", + "author_inst": "KI Research Institute" }, { - "author_name": "Carlos Kwan-Long CHAU", - "author_inst": "Chinese University of Hong Kong" + "author_name": "Ami Neuberger", + "author_inst": "Infectious Diseases Institute, Rambam Health Care Campus" }, { - "author_name": "Shitao RAO", - "author_inst": "Chinese University of Hong Kong" + "author_name": "Asaf Peretz", + "author_inst": "Internal Medicine COVID-19 Ward, Samson Assuta Ashdod University Hospital" }, { - "author_name": "Hon-Cheong SO", - "author_inst": "Chinese University of Hong Kong" + "author_name": "Miri Mizrahi-Reuveni", + "author_inst": "Health Division, Maccabi Healthcare Services" + }, + { + "author_name": "Tal Patalon", + "author_inst": "KSM Research & Innovation Center, Maccabi Healthcare Services" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -664052,135 +663077,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.27.21259196", - "rel_title": "An immune-protein signature combining TRAIL, IP-10 and CRP for accurate prediction of severe COVID-19 outcome", + "rel_doi": "10.1101/2021.06.25.21259556", + "rel_title": "Use of the Elimination Strategy in Response to the COVID-19 Pandemic: Health and Economic Impacts for New Zealand Relative to Other OECD Countries", "rel_date": "2021-07-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.27.21259196", - "rel_abs": "BACKGROUNDAccurately identifying COVID-19 patients at-risk to deteriorate remains challenging. Tools integrating host-protein expression have proven useful in determining infection etiology and hold potential for prognosticating disease severity.\n\nMETHODSAdults with COVID-19 were recruited at medical centers in Israel, Germany, and the United States. Severe outcome was defined as intensive care unit admission, non-invasive or invasive ventilation, or death. Tumor necrosis factor related apoptosis inducing ligand (TRAIL) and interferon gamma inducible protein-10 (IP-10; also known as CXCL10) and C-reactive protein (CRP) were measured using an analyzer providing values within 15 minutes. A signature indicating the likelihood of severe outcome was derived generating a score (0-100). Patients were assigned to 4 score bins.\n\nRESULTSBetween March and November 2020, 518 COVID-19 patients were enrolled, of whom 394 were eligible, 29% meeting a severe outcome. The signatures area under the receiver operating characteristic curve (AUC) was 0.86 (95% confidence interval: 0.81-0.91). Performance was not confounded by age, sex, or comorbidities and superior to IL-6 (AUC 0.77; p = 0.033) and CRP (AUC 0.78; p < 0.001). Likelihood of severe outcome increased significantly (p < 0.001) with higher scores. The signature differentiated patients who further deteriorated after meeting a severe outcome from those who improved (p = 0.004) and projected 14-day survival probabilities (p < 0.001).\n\nCONCLUSIONThe derived immune-protein signature combined with a rapid measurement platform is an accurate predictive tool for early detection of COVID-19 patients at-risk for severe outcome, facilitating timely care escalation and de-escalation and appropriate resource allocation.\n\nFUNDINGMeMed funded the study", - "rel_num_authors": 29, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.25.21259556", + "rel_abs": "BackgroundIn response to the COVID-19 pandemic, some countries in the Asia-Pacific Region used very intensive control measures, and one of these, New Zealand (NZ), adopted a clear \"elimination strategy\". We therefore aimed to compare key health and economic outcomes of NZ relative to OECD countries as of mid-June 2021.\n\nMethodsThis analysis compared health outcomes (cumulative death rates from COVID-19 and \"excess death\" rates) and economic measures (quarterly GDP and unemployment levels) across OECD countries.\n\nResultsNZ had the lowest cumulative COVID-19 death rate in the OECD at 242 times lower than the 38-OECD-country average: 5{middle dot}2 vs 1256 per million population. When considering \"excess deaths\", NZ had the largest negative value in the OECD, equivalent to around 2000 fewer deaths than expected. When considering the average GDP change over the five quarters of 2020 to 2021-Q1, NZ was the sixth best performer (at 0{middle dot}5% vs -0{middle dot}3% for the OECD average). The increase in unemployment in NZ was also less than the OECD average (1{middle dot}1 percentage points to a peak of 5{middle dot}2%, vs 3{middle dot}3 points to 8{middle dot}6%, respectively).\n\nConclusionsNew Zealands elimination strategy response to COVID-19 produced the best mortality protection outcomes in the OECD. In economic terms it also performed better than the OECD average in terms of adverse impacts on GDP and employment. Nevertheless, a fuller accounting of the benefits and costs needs to be done once the population is vaccinated and longer-term health and economic outcomes are considered.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Niv Samuel Mastboim", - "author_inst": "MeMed" - }, - { - "author_name": "Alon Angel", - "author_inst": "MeMed" - }, - { - "author_name": "Oded Shaham", - "author_inst": "MeMed" - }, - { - "author_name": "Tahel Ilan Ber", - "author_inst": "MeMed" - }, - { - "author_name": "Roy Navon", - "author_inst": "MeMed" - }, - { - "author_name": "Einav Simon", - "author_inst": "MeMed" - }, - { - "author_name": "Michal Rosenberg", - "author_inst": "MeMed" - }, - { - "author_name": "Yael Israeli", - "author_inst": "MeMed" - }, - { - "author_name": "Mary Hainrichson", - "author_inst": "MeMed" - }, - { - "author_name": "Noa Avni", - "author_inst": "MeMed" - }, - { - "author_name": "Eran Reiner", - "author_inst": "MeMed" - }, - { - "author_name": "Paul Feigin", - "author_inst": "Technion-Israel Institute of Technology" - }, - { - "author_name": "Kfir Oved", - "author_inst": "MeMed, Canopy Immuno-therapeutics" - }, - { - "author_name": "Boaz Tadmor", - "author_inst": "Rabin Medical Center" - }, - { - "author_name": "Pierre Singer", - "author_inst": "Rabin Medical Center" - }, - { - "author_name": "Ilya Kagan", - "author_inst": "Rabin Medical Center" - }, - { - "author_name": "Shaul Lev", - "author_inst": "Rabin Medical Center" - }, - { - "author_name": "Dror Diker", - "author_inst": "Rabin Medical Center" - }, - { - "author_name": "Amir Jarjoui", - "author_inst": "Shaare Zedek Medical Center, Hebrew University School of Medicine" - }, - { - "author_name": "Ramzi Kurd", - "author_inst": "Shaare Zedek Medical Center, Hebrew University School of Medicine" - }, - { - "author_name": "Eli Ben-Chetrit", - "author_inst": "Shaare Zedek Medical Center, Hebrew University School of Medicine" - }, - { - "author_name": "Guy Danziger", - "author_inst": "Saarland University Hospital" - }, - { - "author_name": "Cihan Papan", - "author_inst": "Saarland University Hospital" - }, - { - "author_name": "Sergey Motov", - "author_inst": "Maimonides Medical Center" - }, - { - "author_name": "Maanit Shapira", - "author_inst": "Technion-Israel Institute of Technology, Hillel Yaffe Medical Center" + "author_name": "Nick Wilson", + "author_inst": "University of Otago, Wellington" }, { - "author_name": "Michal Stein", - "author_inst": "Technion-Israel Institute of Technology, Hillel Yaffe Medical Center" + "author_name": "Leah Grout", + "author_inst": "University of Otago Wellington" }, { - "author_name": "Adi Klein", - "author_inst": "Technion-Israel Institute of Technology, Hillel Yaffe Medical Center" + "author_name": "Jennifer A Summers", + "author_inst": "Otago University, New Zealand" }, { - "author_name": "Tanya Michelle Gottlieb", - "author_inst": "MeMed" + "author_name": "Nhung Nghiem", + "author_inst": "University of Otago" }, { - "author_name": "Eran Eden", - "author_inst": "MeMed" + "author_name": "Michael G Baker", + "author_inst": "University of Otago Wellington" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "emergency medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.06.28.21259384", @@ -666442,37 +665371,21 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2021.06.28.21258847", - "rel_title": "Side Effects and Perceptions Following Sinopharm COVID-19 Vaccination", + "rel_doi": "10.1101/2021.06.28.21256779", + "rel_title": "Community-Based Phenotypic Study of Safety, Tolerability, Reactogenicity and Immunogenicity of Emergency-Use-Authorized Vaccines Against COVID-19 and Viral Shedding Potential of Post-Vaccination Infections: Protocol for a prospective study", "rel_date": "2021-07-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.28.21258847", - "rel_abs": "BackgroundVaccines are one of the best interventions developed for eradicating COVID-19, the rapid creation of vaccinations was increased the risk of vaccine safety problems. The aim of this study to provide evidence on Sinopharm COVID-19 vaccine side effects which is approved by the United Arab Emirates (UAE).\n\nMethodsA cross-sectional survey study was conducted between January and April 2021 to collect data on the effects of COVID-19 vaccine among individuals in the UAE. Demographic data, chronic conditions, side effects of the 1st and 2nd dose toward the vaccination, and the response of unwilling taking COVID-19 vaccine were reported.\n\nResultsThe most common side effects of post 1st dose vaccination among participants ([≤]49 years old vs >49 years) were normal injection site pain 42.2%, fatigue 12.2%, and headache 9.6%, while pain at the vaccination site 32.6%, fatigue16.3%, lethargy13.7%, headache10%, and tenderness 10% were the most side effects of the post 2nd dose of vaccination in both groups. All the side effects in both doses were more prevalent among the participants [≤] 49-year-old group.\n\nAmong two groups (females vs males), the study revealed the increase in the number of females that suffered from the vaccine side effects compared with males in both doses. The most prevalence adverse reactions of first dose in (females vs males) were fatigue (15.8% vs 3.75%), lethargy (12.6% vs 1.25%), headache (10.5% vs 7.5%), while in 2nd dose were fatigue (20% vs 7.5%), sever injection site pain (10.5% vs 2.5%). The most common reason of not willing to take the COVID-19 vaccine among the participants were the vaccines are not effective, and the participants were not authorized to take vaccine.\n\nConclusionThe 1st and 2nd dose post-vaccination side effects were mild, predictable, and there were no hospitalization cases, this data will help to reduce the vaccine hesitancy.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.28.21256779", + "rel_abs": "1The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to a global pandemic that disrupted and impacted lives in unprecedented ways. Within less than a year after the beginning of the COVID-19 pandemic, vaccines developed by several research teams were emergency-use authorized and made their way to distribution sites across the US and other countries. COVID-19 vaccines were tested in clinical trials with thousands of participants before authorization, and were administered to over a billion people across the globe in the following 6 months. Post-authorization safety monitoring was performed using pre-existing systems (such as the World Health Organizations platform VigiBase or US Vaccine Adverse Event Reporting System, VAERS) and newly developed post-vaccination health checkers (such as V-safe in the US). Vaccinated individuals were also posting their experiences on multiple social media groups created on Facebook, Reddit, Telegram and other platforms, but the groups were often removed as \"proliferating false claims\". These forms of reporting are susceptible to biases and misclassifications and do not reach all vaccinated individuals, raising questions about risks of exacerbating health inequalities as well as security and privacy vulnerabilities.\n\nThe objective of this paper is to present the protocol for a community-based participatory research approach enabling long-term monitoring of health effects, strengthening community participation via transparent messaging and support, and addressing challenges of transitioning to a new normal.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Balsam Qubais", - "author_inst": "University of Sharjah" - }, - { - "author_name": "Rula Al-Shahrabi", - "author_inst": "University of Sharjah" - }, - { - "author_name": "Shaikha Salah Alhaj", - "author_inst": "University of Sharjah" - }, - { - "author_name": "Zainab Mansour Alkokhardi", - "author_inst": "University of Sharjah" - }, - { - "author_name": "Ahmed Omar Adrees", - "author_inst": "University of Sharjah" + "author_name": "Irene S Gabashvili", + "author_inst": "Aurametrix" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -668176,35 +667089,43 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.06.30.450490", - "rel_title": "The SARS-CoV-2 host cell membrane fusion protein TMPRSS2 is a tumor suppressor and its downregulation correlates with increased antitumor immunity and immunotherapy response in lung adenocarcinoma", + "rel_doi": "10.1101/2021.06.30.450614", + "rel_title": "Exploitation of the Secretory Pathway by SARS-CoV-2 Envelope", "rel_date": "2021-06-30", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.30.450490", - "rel_abs": "BackgroundTMPRSS2 is a host cell membrane fusion protein for SARS-CoV-2 invading human host cells. It also has an association with cancer, particularly prostate cancer. However, its association with lung cancer remains insufficiently explored. Thus, an in-depth investigation into the association between TMPRSS2 and lung cancer is significant, considering that lung cancer is the leading cause of cancer death and that the lungs are the primary organ SARS-CoV-2 attacks.\n\nMethodsUsing five lung adenocarcinoma (LUAD) genomics datasets, we explored associations between TMPRSS2 expression and immune signatures, cancer-associated pathways, tumor progression phenotypes, and clinical prognosis in LUAD by the bioinformatics approach. Furthermore, we validated the findings from the bioinformatics analysis by performing in vitro experiments with the human LUAD cell line A549 and in vivo experiments with mouse tumor models. We also validated our findings in LUAD patients from Jiangsu Cancer Hospital, China.\n\nResultsTMPRSS2 expression levels were negatively correlated with the enrichment levels of CD8+ T and NK cells and immune cytolytic activity in LUAD, which represent antitumor immune signatures. Meanwhile, TMPRSS2 expression levels were negatively correlated with the enrichment levels of CD4+ regulatory T cells and myeloid-derived suppressor cells and PD-L1 expression levels in LUAD, which represent antitumor immunosuppressive signatures. However, TMPRSS2 expression levels showed a significant positive correlation with the ratios of immune-stimulatory/immune-inhibitory signatures (CD8+ T cells/PD-L1) in LUAD. It indicated that TMPRSS2 levels had a stronger negative correlation with immune-inhibitory signatures than with immune-stimulatory signatures. TMPRSS2 downregulation correlated with elevated activities of many oncogenic pathways in LUAD, including cell cycle, mismatch repair, p53, and extracellular matrix (ECM) signaling. TMPRSS2 downregulation correlated with increased proliferation, stemness, genomic instability, tumor advancement, and worse survival in LUAD. In vitro and in vivo experiments validated the association of TMPRSS2 deficiency with increased tumor cell proliferation and invasion and antitumor immunity in LUAD. Moreover, in vivo experiments demonstrated that TMPRSS2-knockdown tumors were more sensitive to BMS-1, an inhibitor of PD-1/PD-L1.\n\nConclusionsTMPRSS2 is a tumor suppressor, while its downregulation is a positive biomarker of immunotherapy in LUAD. Our data provide a connection between lung cancer and pneumonia caused by SARS-CoV-2 infection.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.30.450614", + "rel_abs": "The {beta}-coronavirus SARS-CoV-2 is the causative agent of the global Covid-19 pandemic. Coronaviral Envelope (E) proteins are pentameric viroporins that play essential roles in assembly, release and pathogenesis. We developed an inert tagging strategy for SARS-CoV-2 E and find that it localises to the Golgi and to lysosomes. We identify sequences in E, conserved across Coronaviridae, responsible for ER-to-Golgi export, and relate this activity to interaction with COP-II via SEC24. Using proximity biotinylation, we identify host-cell factors that interact with E and identify an ARFRP1/AP-1 dependent pathway allowing Golgi-to-lysosome trafficking of E. We identify sequences in E that bind AP-1, are conserved across {beta}-coronaviruses and allow E to be trafficked from Golgi to lysosomes. We show that E acts to deacidify lysosomes and by developing a trans-complementation assay, we show that both lysosomal trafficking of E and its viroporin activity are necessary for efficient viral replication and release.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Zhixian Liu", - "author_inst": "Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University" + "author_name": "Guy J Pearson", + "author_inst": "King's College London and the Francis Crick Institute" }, { - "author_name": "Zhilan Zhang", - "author_inst": "China Pharmaceutical University" + "author_name": "Harriet Mears", + "author_inst": "The Francis Crick Institute" }, { - "author_name": "Qiushi Feng", - "author_inst": "China Pharmaceutical University" + "author_name": "Malgorzata Broncel", + "author_inst": "Francis Crick Institute" }, { - "author_name": "Xiaosheng Wang", - "author_inst": "China Pharmaceutical University" + "author_name": "Ambrosius P Snijders", + "author_inst": "The Francis Crick Institute" + }, + { + "author_name": "David LV Bauer", + "author_inst": "The Francis Crick Institute" + }, + { + "author_name": "Jeremy G Carlton", + "author_inst": "King's College London" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "new results", - "category": "immunology" + "category": "cell biology" }, { "rel_doi": "10.1101/2021.06.30.450617", @@ -670370,87 +669291,51 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2021.06.23.21259327", - "rel_title": "Reduced neutralisation of the Delta (B.1.617.2) SARS-CoV-2 variant of concern following vaccination", + "rel_doi": "10.1101/2021.06.23.21259292", + "rel_title": "Short-term Outcomes in Children Recovered from Multisystem Inflammatory Syndrome associated with SARS-CoV-2 infection", "rel_date": "2021-06-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.23.21259327", - "rel_abs": "Vaccines are proving to be highly effective in controlling hospitalisation and deaths associated with SARS-CoV-2 infection but the emergence of viral variants with novel antigenic profiles threatens to diminish their efficacy. Assessment of the ability of sera from vaccine recipients to neutralise SARS-CoV-2 variants will inform the success of strategies for minimising COVID19 cases and the design of effective antigenic formulations. Here, we examine the sensitivity of variants of concern (VOCs) representative of the B.1.617.1 and B.1.617.2 (first associated with infections in India) and B.1.351 (first associated with infection in South Africa) lineages of SARS-CoV-2 to neutralisation by sera from individuals vaccinated with the BNT162b2 (Pfizer/BioNTech) and ChAdOx1 (Oxford/AstraZeneca) vaccines. Across all vaccinated individuals, the spike glycoproteins from B.1.617.1 and B.1.617.2 conferred reductions in neutralisation of 4.31 and 5.11-fold respectively. The reduction seen with the B.1.617.2 lineage approached that conferred by the glycoprotein from B.1.351 (South African) variant (6.29-fold reduction) that is known to be associated with reduced vaccine efficacy. Neutralising antibody titres elicited by vaccination with two doses of BNT162b2 were significantly higher than those elicited by vaccination with two doses of ChAdOx1. Fold decreases in the magnitude of neutralisation titre following two doses of BNT162b2, conferred reductions in titre of 7.77, 11.30 and 9.56-fold respectively to B.1.617.1, B.1.617.2 and B.1.351 pseudoviruses, the reduction in neutralisation of the delta variant B.1.617.2 surpassing that of B.1.351. Fold changes in those vaccinated with two doses of ChAdOx1 were 0.69, 4.01 and 1.48 respectively. The accumulation of mutations in these VOCs, and others, demonstrate the quantifiable risk of antigenic drift and subsequent reduction in vaccine efficacy. Accordingly, booster vaccines based on updated variants are likely to be required over time to prevent productive infection. This study also suggests that two dose regimes of vaccine are required for maximal BNT162b2 and ChAdOx1-induced immunity.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.23.21259292", + "rel_abs": "BackgroundMulti System Inflammatory Syndrome in children (MIS-C) associated with COVID-19 is a recently recognised potentially life-threatening entity. There is limited data on post MIS-C sequelae.\n\nMethods21 children fulfilling the WHO criteria for MIS-C were included in our study. Data was collected at baseline and at 12-16 weeks post discharge to look for any persistent sequelae mainly relating to the lungs or heart including coronary arteries\n\nResultsFever was the most common presentation, found in 18 (85.7%) patients. All had marked hyper-inflammatory state. Low ejection fraction (EF) was found in 10 (47.6%), but none had any coronary artery abnormality. All received corticosteroids, while 7 (33.3%) children required additional treatment with intravenous Immunoglobulins. 20 children improved while 1 left against medical advice. At discharge, 3 children had impaired left ventricular function. At median 15 weeks follow-up, no persistent complications were found. EF had returned to normal and no coronary artery abnormalities were found during repeat echocardiography. Chest radiographs showed no fibrosis and all biochemical parameters had normalized.\n\nConclusionThe children with MIS-C are extremely sick during the acute stage. Timely and adequate management led to full recovery without any sequelae at a median follow-up of 15 weeks.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Chris Davis", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Nicola Logan", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Grace Tyson", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Richard Orton", - "author_inst": "University of Glasgow" - }, - { - "author_name": "William Harvey", - "author_inst": "University of Glasgow" - }, - { - "author_name": "John Haughney", - "author_inst": "Queen Elizabeth University Hospital" - }, - { - "author_name": "Jon Perkins", - "author_inst": "Queen Elizabeth University Hospital" - }, - { - "author_name": "- The COVID-19 Genomics UK (COG-UK) Consortium", - "author_inst": "" - }, - { - "author_name": "Thomas Peacock", - "author_inst": "Imperial College London" - }, - { - "author_name": "Wendy S Barclay", - "author_inst": "Imperial College London" + "author_name": "Sibabratta Patnaik", + "author_inst": "Kalinga Institute of Medical Sciences, Bhubaneswar" }, { - "author_name": "Peter Cherepanov", - "author_inst": "The Francis Crick Institute" + "author_name": "Mukesh Kumar Jain", + "author_inst": "Kalinga Institute of Medical Sciences, Bhubaneswar" }, { - "author_name": "Massimo Palmarini", - "author_inst": "University of Glasgow" + "author_name": "Sakir Ahmed", + "author_inst": "Kalinga Institute of Medical Sciences" }, { - "author_name": "Pablo R Murcia", - "author_inst": "University of Glasgow" + "author_name": "Arun Kumar Dash", + "author_inst": "Kalinga Institute of Medical Sciences, Bhubaneswar" }, { - "author_name": "Arvind H Patel", - "author_inst": "University of Glasgow" + "author_name": "Ram Kumar P", + "author_inst": "Kalinga Institute of Medical Sciences, Bhubaneswar" }, { - "author_name": "David L Robertson", - "author_inst": "University of Glasgow" + "author_name": "Bandya Sahoo", + "author_inst": "Kalinga Institute of Medical Sciences, Bhubaneswar" }, { - "author_name": "Emma C Thomson", - "author_inst": "University of Glasgow" + "author_name": "Reshmi Mishra", + "author_inst": "Kalinga Institute of Medical Sciences, Bhubaneswar" }, { - "author_name": "Brian James Willett", - "author_inst": "University of Glasgow" + "author_name": "Manas Ranjan Behera", + "author_inst": "Kalinga Institute of Medical Sciences, Bhubaneswar" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "pediatrics" }, { "rel_doi": "10.1101/2021.06.24.21259087", @@ -672972,299 +671857,63 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.06.24.21259374", - "rel_title": "A proteomic survival predictor for COVID-19 patients in intensive care", + "rel_doi": "10.1101/2021.06.24.21259463", + "rel_title": "COVID-19 infection and subsequent psychiatric morbidity, sleep problems and fatigue: analysis of an English primary care cohort of 226,521 positive patients", "rel_date": "2021-06-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.24.21259374", - "rel_abs": "Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Comprehensively capturing the host physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index and APACHE II score were poor predictors of survival. Plasma proteomics instead identified 14 proteins that showed concentration trajectories different between survivors and non-survivors. A proteomic predictor trained on single samples obtained at the first time point at maximum treatment level (i.e. WHO grade 7) and weeks before the outcome, achieved accurate classification of survivors in an exploratory (AUROC 0.81) as well as in the independent validation cohort (AUROC of 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that predictors derived from plasma protein levels have the potential to substantially outperform current prognostic markers in intensive care.\n\nTrial registrationGerman Clinical Trials Register DRKS00021688", - "rel_num_authors": 70, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.24.21259463", + "rel_abs": "ObjectivesThe primary hypothesis was that the risk of incident or repeat psychiatric illness, fatigue and sleep problems increased following COVID-19 infection. The analysis plan was pre-registered (https://osf.io/n2k34/).\n\nDesignMatched cohorts were assembled using a UK primary care registry (the CPRD-Aurum database). Patients were followed-up for up to 10 months, from 1st February 2020 to 9th December 2020.\n\nSettingPrimary care database of 11,923,499 adults ([≥]16 years).\n\nParticipantsFrom 232,780 adults with a positive COVID-19 test (after excluding those with <2 years historical data or <1 week follow-up), 86,922 without prior mental illness, 19,020 with anxiety or depression, 1,036 with psychosis, 4,152 with fatigue and 4,539 with sleep problems were matched to up to four controls based on gender, general practice and year of birth. A negative control used patients who tested negative for COVID-19 and patients negative for COVID with an influenza diagnosis.\n\nMain Outcomes and MeasuresCox proportional hazard models estimated the association between a COVID-19 positive test and subsequent psychiatric morbidity (depression, anxiety, psychosis, or self-harm), sleep problems, fatigue or psychotropic prescribing. Models adjusted for comorbidities, ethnicity, smoking and BMI.\n\nResultsAfter adjusting for observed confounders, there was an association between testing positive for COVID-19 and almost all markers of psychiatric morbidity, fatigue and sleep problems. The adjusted hazard ratio (aHR) for incident psychiatric morbidity was 1.75 (95% CI 1.56-1.96). However, there was a similar risk of incident psychiatric morbidity for those with a negative COVID-19 test (aHR 1.57, 95% CI 1.51-1.63) and a larger increase associated with influenza (aHR 2.97, 95% CI 1.36-6.48).\n\nConclusionsThere is consistent evidence that COVID-19 infection elevates risk of fatigue and sleep problems, however the results from the negative control analysis suggests that residual confounding may be responsible for at least some of the association between COVID-19 and psychiatric morbidity.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Vadim Demichev", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Pinkus Tober-Lau", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Tatiana Nazarenko", - "author_inst": "University College London" - }, - { - "author_name": "Simran Kaur Aulakh", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Harry Whitwell", - "author_inst": "Imperial College London" - }, - { - "author_name": "Oliver Lemke", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Annika Roehl", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Anja Freiwald", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Mirja Mittermaier", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Lukasz Szyrwiel", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Daniela Ludwig", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Clara Correia-Melo", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Lena Lippert", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Elisa T. Helbig", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Paula Stubbemann", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Nadine Olk", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Charlotte Thibeault", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Nana-Maria Gruening", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Oleg Blyuss", - "author_inst": "Lobachevsky University," - }, - { - "author_name": "Spyros Vernardis", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Matthew White", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Christoph B. Messner", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Michael Joannidis", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "Thomas Sonnweber", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "Sebastian J. Klein", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "Alex Pizzini", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "Yvonne Wohlfarter", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "Sabina Sahanic", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "Richard Hilbe", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "Benedikt Schaefer", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "Sonja Wagner", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "Felix Machleidt", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Carmen Garcia", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Christoph Ruwwe-Gloesenkamp", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Tilman Lingscheid", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Laure Bosquillon de Jarcy", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Miriam Stegemann", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Moritz Pfeiffer", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Linda Juergens", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Sophy Denker", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Daniel Zickler", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Claudia Spies", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Andreas Edel", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Nils B. Mueller", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Philipp Enghard", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Aleksej Zelezniak", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Rosa Bellmann-Weiler", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "Guenter Weiss", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "Archie Campbell", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Caroline Hayward", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "David J. Porteous", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Riccardo E. Marioni", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Alexander Uhrig", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" - }, - { - "author_name": "Heinz Zoller", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "Judith Loeffler-Ragg", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "Markus A. Keller", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "Ivan Tancevski", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "John F. Timms", - "author_inst": "University College London" - }, - { - "author_name": "Alexey Zaikin", - "author_inst": "University College London" - }, - { - "author_name": "Stefan Hippenstiel", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + "author_name": "Kathryn M Abel", + "author_inst": "University of Manchester" }, { - "author_name": "Michael Ramharter", - "author_inst": "Bernhard Nocht Institute for Tropical Medicine" + "author_name": "Matthew J Carr", + "author_inst": "University of Manchester" }, { - "author_name": "Holger Mueller-Redetzky", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + "author_name": "Darren M Ashcroft", + "author_inst": "University of Manchester" }, { - "author_name": "Martin Witzenrath", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + "author_name": "Trudie Chalder", + "author_inst": "King's College London" }, { - "author_name": "Norbert Suttorp", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + "author_name": "Carolyn A Chew-Graham", + "author_inst": "University of Keele" }, { - "author_name": "Kathryn Lilley", - "author_inst": "The University of Cambridge" + "author_name": "Holly F Hope", + "author_inst": "University of Manchester" }, { - "author_name": "Michael Muelleder", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + "author_name": "Navneet Kapur", + "author_inst": "University of Manchester" }, { - "author_name": "Leif Erik Sander", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + "author_name": "Sally McManus", + "author_inst": "National Centre for Social Research" }, { - "author_name": "- PA-COVID- Study group", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + "author_name": "Sarah F Steeg", + "author_inst": "University of Manchester" }, { - "author_name": "Florian Kurth", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + "author_name": "Roger T Webb", + "author_inst": "University of Manchester" }, { - "author_name": "Markus Ralser", - "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + "author_name": "Matthias Pierce", + "author_inst": "University of Manchester" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.06.24.21259444", @@ -674850,65 +673499,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.23.21259045", - "rel_title": "Use of HFNC in COVID-19 patients in non-ICU setting: Experience from a tertiary referral centre of north India and a systematic review of literature", + "rel_doi": "10.1101/2021.06.24.21257174", + "rel_title": "Viral detection and identification in 20 minutes by rapid single-particle fluorescence in-situ hybridization of viral RNA", "rel_date": "2021-06-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.23.21259045", - "rel_abs": "IntroductionThe rapid surge of cases and insufficient numbers of intensive care unit (ICU) beds have forced hospitals to utilise their general wards for administration of non-invasive respiratory support including HFNC(High Flow Nasal Cannula) in severe COVID-19. However, there is a dearth of data on the success of such advanced levels of care outside the ICU setting. Therefore, we conducted an observational study at our centre, and systematically reviewed the literature, to assess the success of HFNC in managing severe COVID-19 cases outside the ICU.\n\nMethodsA retrospective cohort study was conducted in a tertiary referral centre where records of all adult COVID-19 patients ([≥]18 years) requiring HFNC support were between September and December 2020 were analysed. HFNC support was adjusted to target SpO2 [≥]90% and respiratory rate [≤]30 per min. The clinical, demographic, laboratory, and treatment details of these patients were retrieved from the medical records and entered in pre-designed proforma. Outcome parameters included duration of oxygen during hospital stay, duration of HFNC therapy, length of hospital stay and death or discharge. HFNC success was denoted when a patient did not require escalation of therapy to NIV or invasive mechanical ventilation, or shifting to the ICU, and was eventually discharged from the hospital without oxygen therapy; otherwise, the outcome was denoted as HFNC failure. Systematic review was also performed on the available literature on the experience with HFNC in COVID-19 patients outside of ICU settings using the MEDLINE, Web of Science and Embase databases. Statistical analyses were performed with the use of STATA software, version 12, OpenMeta[Analyst], and visualization of the risk of bias plot using robvis.\n\nResultsThirty-one patients receiving HFNC in the ward setting, had a median age of 62 (50 - 69) years including 24 (77%) males. Twenty-one (68%) patients successfully tolerated HFNC and were subsequently discharged from the wards, while 10 (32%) patients had to be shifted to ICU for non-invasive or invasive ventilation, implying HFNC failure. Patients with HFNC failure had higher median D-dimer values at baseline (2.2 mcg/ml vs 0.6 mcg/ml, p=0.001) and lower initial SpO2 on room air at admission (70% vs 80%, p=0.026) as compared to those in whom HFNC was successful .A cut-off value of 1.7 mg/L carried a high specificity (90.5%) and moderate sensitivity (80%) for the occurrence of HFNC failure. Radiographic severity scoring as per the BRIXIA score was comparable in both the groups(11 vs 10.5 out of 18, p=0.78). After screening 98 articles, total of seven studies were included for synthesis in the systematic review with a total of 820 patients, with mean age of the studies ranging from 44 to 83 years and including 62% males. After excluding 2 studies from the analysis, the pooled rates of HFNC failure were 36.3% (95% CI 31.1% - 41.5%) with no significant heterogeneity (I2 =0%, p=0.55).\n\nConclusionsOur study demonstrated successful outcomes with use of HFNC in an outside of ICU setting among two-thirds of patients with severe COVID-19 pneumonia. Lower room air SpO2 and higher D-dimer levels at presentation were associated with failure of HFNC therapy leading to ICU transfer for endotracheal intubation or death. Also, the results from the systematic review demonstrated similar rates of successful outcomes concluding that HFNC is a viable option with failure rates similar to those of ICU settings in such patients.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.24.21257174", + "rel_abs": "The increasing risk from viral outbreaks such as the ongoing COVID-19 pandemic exacerbates the need for rapid, affordable and sensitive methods for virus detection, identification and quantification; however, existing methods for detecting virus particles in biological samples usually depend on multistep protocols that take considerable time to yield a result. Here, we introduce a rapid fluorescence in situ hybridization (FISH) protocol capable of detecting influenza virus, avian infectious bronchitis virus and SARS-CoV-2 specifically and quantitatively in approximately 20 minutes, in both virus cultures and combined throat and nasal swabs without previous purification. This fast and facile workflow is applicable to a wide range of enveloped viruses and can be adapted both as a lab technique and a future diagnostic tool.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Anivita Aggarwal", - "author_inst": "All India Institute of Medical Sciences, New Delhi , India" - }, - { - "author_name": "Umang Arora", - "author_inst": "All India Institute of Medical Sciences , New Delhi, India" - }, - { - "author_name": "Ankit Mittal", - "author_inst": "All India Institute of Medical Sciences , New Delhi, India" - }, - { - "author_name": "Arunima Aggarwal", - "author_inst": "University College of Medical Sciences, New Delhi, India" - }, - { - "author_name": "Komal Singh", - "author_inst": "All India Institute of Medical Sciences , New Delhi, India" - }, - { - "author_name": "Animesh Ray", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" - }, - { - "author_name": "Manish Soneja", - "author_inst": "All India Institute of Medical Sciences , New Delhi, India" - }, - { - "author_name": "Pankaj Jorwal", - "author_inst": "All India Institute of Medical Sciences , New Delhi, India" - }, - { - "author_name": "Neeraj Nischal", - "author_inst": "All India Institute of Medical Sciences , New Delhi, India" - }, - { - "author_name": "Akhil Singh", - "author_inst": "All India Institute of Medical Sciences , New Delhi, India" + "author_name": "Christof Hepp", + "author_inst": "University of Oxford" }, { - "author_name": "Puneet Khanna", - "author_inst": "All India Institute of Medical Sciences , New Delhi, India" + "author_name": "Nicolas Shiaelis", + "author_inst": "University of Oxford" }, { - "author_name": "Naveet Wig", - "author_inst": "All India Institute of Medical Sciences , New Delhi, India" + "author_name": "Nicole C Robb", + "author_inst": "University of Warwick" }, { - "author_name": "Anjan Trikha", - "author_inst": "All India Institute of Medical Sciences , New Delhi, India" + "author_name": "Achillefs N Kapanidis", + "author_inst": "University of Oxford" } ], "version": "1", @@ -676632,63 +675245,75 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.06.24.449252", - "rel_title": "Lipid and nucleocapsid N-protein accumulation in COVID-19 patient lung and infected cells", + "rel_doi": "10.1101/2021.06.23.449282", + "rel_title": "Structure, activity and inhibition of human TMPRSS2, a protease implicated in SARS-CoV-2 activation", "rel_date": "2021-06-24", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.24.449252", - "rel_abs": "The pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global outbreak and prompted an enormous research effort. Still, the subcellular localization of the corona virus in lungs of COVID-19 patients is not well understood. Here, the localization of the SARS-CoV-2 proteins is studied in postmortem lung material of COVID-19 patients and in SARS- CoV-2 infected Vero cells, processed identically. Correlative light and electron microscopy on semi- thick cryo-sections, demonstrated induction of electron-lucent, lipid filled compartments after SARS- CoV-2 infection in both lung and cell cultures. In lung tissue, the non-structural protein 4 and the stable nucleocapsid N-protein, were detected on these novel lipid filled compartments. The induction of such lipid filled compartments and the localization of the viral proteins in lung of patients with fatal COVID-19, may explain the extensive inflammatory response and provide a new hallmark for SARS- Cov-2 infection at the final, fatal stage of infection.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.23.449282", + "rel_abs": "Transmembrane protease, serine 2 (TMPRSS2) has been identified as key host cell factor for viral entry and pathogenesis of SARS-coronavirus-2 (SARS-CoV-2). Specifically, TMPRSS2 proteolytically processes the SARS-CoV-2 Spike (S) Protein, enabling virus-host membrane fusion and infection of the lungs. We present here an efficient recombinant production strategy for enzymatically active TMPRSS2 ectodomain enabling enzymatic characterization, and the 1.95 [A] X-ray crystal structure. To stabilize the enzyme for co-crystallization, we pre-treated TMPRSS2 with the synthetic protease inhibitor nafamosat to form a stable but slowly reversible (15 hour half-life) phenylguanidino acyl-enzyme complex. Our study provides a structural basis for the potent but non-specific inhibition by nafamostat and identifies distinguishing features of the TMPRSS2 substrate binding pocket that will guide future generations of inhibitors to improve selectivity. TMPRSS2 cleaved recombinant SARS-CoV-2 S protein ectodomain at the canonical S1/S2 cleavage site and at least two additional minor sites previously uncharacterized. We established enzymatic activity and inhibition assays that enabled ranking of clinical protease inhibitors with half-maximal inhibitory concentrations ranging from 1.7 nM to 120 M and determination of inhibitor mechanisms of action. These results provide a body of data and reagents to support future drug development efforts to selectively inhibit TMPRSS2 and other type 2 transmembrane serine proteases involved in viral glycoprotein processing, in order to combat current and future viral threats.\n\nSUMMARY PARAGRAPHViruses hijack the biochemical activity of host proteins for viral invasion and replication. Transmembrane protease, serine-2 (TMPRSS2) is a surface-expressed protease implicated in the activation of influenza A, influenza B, and coronaviruses, including SARS-CoV-2, to drive efficient infection of the lungs1-5. TMPRSS2 is an attractive target for antiviral therapies, as inhibiting its proteolytic activity blocks efficient viral entry5,6. However, a structural and biochemical understanding of the protease has remained elusive and no selective inhibitors are available. We engineered on-demand activatable TMPRSS2 ectodomain and determined the 1.95 [A] X-ray crystal structure of the stabilized acyl-enzyme after treatment with nafamostat, a protease inhibitor under investigation as a COVID-19 therapeutic. The structure reveals unique features of the TMPRSS2 substrate recognition pocket and domain architecture, and explains the potent, but nonselective inhibition by nafamostat. TMPRSS2 efficiently cleaved the SARS-CoV-2 S protein at the canonical S1/S2 site as well as two minor sites previously uncharacterized. We further established a robust enzymatic assay system and characterized inhibition by two additional clinical protease inhibitors under study for COVID-19, camostat and bromhexine. Our results provide a body of data and reagents to enable ongoing drug development efforts to selectively inhibit TMPRSS2 and other TTSPs involved in viral glycoprotein processing, in order to combat current and future viral threats.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Anita Grootemaat", - "author_inst": "Amsterdam UMC" + "author_name": "Bryan J Fraser", + "author_inst": "University of British Columbia" }, { - "author_name": "Sanne van der Niet", - "author_inst": "Amsterdam UMC" + "author_name": "Serap Beldar", + "author_inst": "University of Toronto" }, { - "author_name": "Edwin R. Scholl", - "author_inst": "Amsterdam UMC" + "author_name": "Almagul Seitova", + "author_inst": "University of Toronto" }, { - "author_name": "Eva Roos", - "author_inst": "Amsterdam UMC" + "author_name": "Ashley Hutchinson", + "author_inst": "University of Toronto" }, { - "author_name": "Bernadette Schurink", - "author_inst": "Amsterdam UMC" + "author_name": "Dhiraj Mannar", + "author_inst": "University of British Columbia" }, { - "author_name": "Marianna Bugiani", - "author_inst": "Amsterdam UMC" + "author_name": "Yanjun Li", + "author_inst": "University of Toronto" }, { - "author_name": "Sara E. Miller", - "author_inst": "Duke Medical Center" + "author_name": "Daniel Kwon", + "author_inst": "British Columbia Cancer Research Institute" }, { - "author_name": "Per W Larsen", - "author_inst": "Amsterdam UMC" + "author_name": "Ruiyan Tan", + "author_inst": "British Columbia Cancer Research Institute" }, { - "author_name": "Jeannette Pankras", - "author_inst": "Amsterdam UMC" + "author_name": "Ryan P Wilson", + "author_inst": "British Columbia Cancer Research Institute" }, { - "author_name": "Eric E Reits", - "author_inst": "Amsterdam UMC" + "author_name": "Karoline Leopold", + "author_inst": "University of British Columbia" }, { - "author_name": "Nicole N van der Wel", - "author_inst": "Amsterdam UMC" + "author_name": "Sriram Subramaniam", + "author_inst": "University of British Columbia" + }, + { + "author_name": "Levon Halabelian", + "author_inst": "University of Toronto" + }, + { + "author_name": "Cheryl H Arrowsmith", + "author_inst": "University of Toronto" + }, + { + "author_name": "Francois Benard", + "author_inst": "University of British Columbia" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2021.06.23.449627", @@ -678334,43 +676959,47 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2021.06.17.21259071", - "rel_title": "Safe in my heart: resting heart rate variability longitudinally predicts emotion regulation, worry and sense of safeness during COVID-19 lockdown", + "rel_doi": "10.1101/2021.06.21.21259241", + "rel_title": "First identification of SARS-CoV-2 Lambda (C.37) variant in Southern Brazil", "rel_date": "2021-06-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.17.21259071", - "rel_abs": "Due to its ability to reflect the capacity to engage in context-appropriate responses, tonic heart rate variability (HRV) is considered a putative biomarker of stress resilience. However, most studies are cross-sectional, precluding causal inferences. The high levels of uncertainty and fear at a global level that characterize the COVID-19 pandemic offer a unique opportunity to investigate the longitudinal role of HRV in stress resilience. The present study examined whether HRV, measured about 2 years earlier (Time 0), could predict emotion regulation strategies and daily affect in healthy adults during the May 2020 lockdown (Time 1). Moreover, we evaluated the association between HRV measures, emotion regulation strategies, subjective perception of COVID-19 risk, and self-reported depressive symptoms at Time 1. Higher tonic HRV at Time 0 resulted a significant predictor of a stronger engagement in more functional emotion regulation strategies, as well as of higher daily feelings of safeness and reduced daily worry at Time 1. Moreover, depressive symptoms negatively correlated with HRV and positively correlated with the subjective perception of COVID-19 risk at Time 1. Current data support the view that HRV might be not only a marker but also a precursor of resilience under stressful times.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.21.21259241", + "rel_abs": "In June 15, 2021, the lineage Lambda (C.37) of SARS-CoV-2 was considered a variant of interest (VOI) by the World Health Organization. This lineage has high prevalence in some South America countries but it was described only occasionally in Brazil. Here we describe the first report of the SARS-CoV-2 Lambda variant in Southern Brazil. The sequence described in this paper presented all the eight C.37 defining lineage mutations (ORF1a gene: {Delta}3675-3677; Spike gene: {Delta}246-252, G75V, T76I, L452Q, F490S, D614G, and T859N) in addition to other 19 mutations. Considering that this VOI has been associated with high rates of transmissibility, the possible spread in the Southern Brazilian community is a matter of concern.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Elena Makovac", - "author_inst": "King's College London" + "author_name": "Priscila Lamb Wink", + "author_inst": "Hospital de Clinicas de Porto Alegre" }, { - "author_name": "Luca Carnevali", - "author_inst": "Stress Physiology Lab, Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy" + "author_name": "Fabiana Caroline Zempulski Volpato", + "author_inst": "Hospital de Clinicas de Porto Alegre" }, { - "author_name": "Sonia Hernandez-Medina", - "author_inst": "King's College London" + "author_name": "Francielle Liz Monteiro", + "author_inst": "Hospital de Clinicas de Porto Alegre" }, { - "author_name": "Andrea Sgoifo", - "author_inst": "University of Parma" + "author_name": "Julia Biz Willig", + "author_inst": "Hospital de Clinicas de Porto Alegre" }, { - "author_name": "Nicola Petrocchi", - "author_inst": "Department of Economics and Social Sciences, John Cabot University, Rome, Italy" + "author_name": "Alexandre P. Zavascki", + "author_inst": "Hospital de Clinicas de Porto Alegre" }, { - "author_name": "Cristina Ottaviani", - "author_inst": "Department of Psychology, Sapienza University of Rome, Rome, Italy" + "author_name": "Afonso Luis Barth", + "author_inst": "Hospital de Clinicas de Porto Alegre" + }, + { + "author_name": "Andreza Francisco Martins", + "author_inst": "Hospital de Clinicas de Porto Alegre" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.06.23.449583", @@ -679704,21 +678333,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.06.19.21258779", - "rel_title": "A physically plausible incidence rate for compartmental epidemiological models", + "rel_doi": "10.1101/2021.06.14.21258882", + "rel_title": "Inequalities in initiation of COVID19 vaccination by age and population group in Israel- December 2020-April 2021", "rel_date": "2021-06-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.19.21258779", - "rel_abs": "Motivated by the recent trajectory of SARS-Cov-2 new infection incidences in Germany and other European countries, this note reconsiders the need to use a non-linear incidence rate function in deterministic compartmental models for current SARS-Cov-2 epidemic modelling. Employing a homogenous contact model, it derives such function systematically using stochastic arguments. The presented result, which is relevant to modelling of proliferation of arbitrary infectious diseases, integrates well with previous analyses, in particular closes an analytical \"gap\" mentioned in London and Yorke (1973) and complements the stability related work on incidence rate functions of the form {beta}IpSq seen for example in Liu, Hethcote and Levin (1987).", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.14.21258882", + "rel_abs": "BackgroundIn Israel, COVID19 vaccination coverage varies widely by population group and age. Despite the vaccine being locally and freely available in the entire country. Comparing crude coverage between localities and population groups is misleading because of differing age structures in different population groups. In order to describe inequalities in COVID19 vaccine initiation we determined differences in age-specific dose 1 vaccine coverage between the main population groups in Israel, and characterised the influence of age on vaccine coverage within each of these groups.\n\nMethodsWe obtained daily doses administered by municipality and age from the Ministry of Health, and demographic data from the Central Bureau of Statistics. We determined whether the relative proportion of people vaccinated in each age group (15-19, 20-29, 30-39, 40-49, 50-59, 60+) changed by population group (General Jewish, Ultra-Orthodox and Arab) using ANOVA and quantified association between age, population group and vaccine coverage using binomial regression.\n\nResults8,507,723 individuals in 268 localities were included. Compared with the General Jewish population, vaccine coverage was lower among the Arab and Ultra-Orthodox populations and lowest in the Ultra-Orthodox population in all age groups. Gaps between population groups differed according to age group (p<0.001). In all populations, coverage decreased with decreasing age (p<0.001). The Ultra-orthodox population was the least vaccinated in all age groups relatively to those aged 60 and over\n\nConclusionsIn all age groups, the Ultra-Orthodox population had the lowest vaccine coverage. The younger the age group, the more Ultra-Orthodox Jews are diverging from their age peers in terms of initiating COVID19 vaccination. These findings suggest generational differences in terms of vaccination behaviour in this group. Qualitative studies understanding the causes behind this divergence can inform tailored vaccination strategies.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Thomas Pitschel", - "author_inst": "Goethe University Frankfurt" + "author_name": "Yanay Gorelik", + "author_inst": "Bar-Ilan University Faculty of Medicine" + }, + { + "author_name": "Michael Edelstein", + "author_inst": "Bar Ilan University Faculty of Medicine" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -681418,59 +680051,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.15.21258879", - "rel_title": "Recovery from Covid-19 critical illness: a secondary analysis of the ISARIC4C CCP-UK cohort study and the RECOVER trial", + "rel_doi": "10.1101/2021.06.18.21259137", + "rel_title": "Comparative performance of between-population allocation strategies for SARS-CoV-2 vaccines.", "rel_date": "2021-06-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.15.21258879", - "rel_abs": "BackgroundWe aimed to compare the prevalence and severity of fatigue in survivors of Covid-19 versus non-Covid-19 critical illness, and to explore potential associations between baseline characteristics and worse recovery.\n\nMethodsWe conducted a secondary analysis of two prospectively collected datasets. The population included was 92 patients who received invasive mechanical ventilation (IMV) with Covid-19, and 240 patients who received IMV with non-Covid-19 illness before the pandemic. Follow-up data was collected post-hospital discharge using self-reported questionnaires. The main outcome measures were self-reported fatigue severity and the prevalence of severe fatigue (severity >7/10) 3 and 12-months post-hospital discharge.\n\nResultsCovid-19 IMV-patients were significantly younger with less prior comorbidity, and more males, than pre-pandemic IMV-patients. At 3-months, the prevalence (38.9% [7/18] vs. 27.1% [51/188]) and severity (median 5.5/10 vs. 5.0/10) of fatigue was similar between the Covid-19 and pre-pandemic populations respectively. At 6-months, the prevalence (10.3% [3/29] vs. 32.5% [54/166]) and severity (median 2.0/10 vs. 5.7/10) of fatigue was less in the Covid-19 cohort. In the Covid-19 population, women under 50 experienced more severe fatigue, breathlessness, and worse overall health state compared to other Covid-19 IMV-patients. There were no significant sex differences in long-term outcomes in the pre-pandemic population. In the total sample of IMV-patients included (i.e. all Covid-19 and pre-pandemic patients), having Covid-19 was significantly associated with less severe fatigue (severity <7/10) after adjusting for age, sex, and prior comorbidity (adjusted OR 0.35 (95%CI 0.15-0.76, p=0.01).\n\nConclusionFatigue may be less severe after Covid-19 than after other critical illness.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.18.21259137", + "rel_abs": "2Vaccine allocation decisions during emerging pandemics have proven to be challenging due to competing ethical, practical, and political considerations. Complicating decision making, policy makers need to consider vaccine allocation strategies that balance needs both within and between populations. Due to limited vaccine stockpiles, vaccine doses should be allocated in locations where their impact will be maximized. Using a susceptible-exposed-infectious-recovered (SEIR) model we examine optimal vaccine allocation decisions across two populations considering the impact of population size, underlying immunity, continuous vaccine roll-out, heterogeneous population risk structure, and differences in disease transmissibility. We find that in the context of an emerging pathogen where many epidemiologic characteristics might not be known, equal vaccine allocation between populations performs optimally in most scenarios. In the specific case considering heterogeneous population risk structure, first targeting individuals at higher risk of transmission or death due to infection leads to equal resource allocation across populations.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Ellen E Pauley", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Thomas M Drake", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "David Griffith", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Nazir I Lone", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Ewen M Harrison", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "J Kenneth Baillie", - "author_inst": "Roslin Institute, University of Edinburgh" + "author_name": "Keya Joshi", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Janet T Scott", - "author_inst": "MRC-University of Glasgow Center for Virus research" + "author_name": "Eva Rumpler", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Timothy S Walsh", - "author_inst": "University of Edinburgh" + "author_name": "Lee Kennedy-Shaffer", + "author_inst": "Vassar College" }, { - "author_name": "Malcolm G Semple", - "author_inst": "University of Liverpool" + "author_name": "Rafia Bosan", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Annemarie B Docherty", - "author_inst": "University of Edinburgh" + "author_name": "Marc Lipsitch", + "author_inst": "Harvard T.H. Chan School of Public Health" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.06.15.21258529", @@ -683603,59 +682216,127 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.06.19.449092", - "rel_title": "Mapping the host protein interactome of non-coding regions in SARS-CoV-2 genome", + "rel_doi": "10.1101/2021.06.18.446355", + "rel_title": "Discovery of SARS-CoV-2 Mpro Peptide Inhibitors from Modelling Substrate and Ligand Binding", "rel_date": "2021-06-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.19.449092", - "rel_abs": "A deep understanding of SARS-CoV-2-host interactions is crucial to the development of effective therapeutics. The role of non-coding regions of viral RNA (ncrRNAs) has not been scrutinized. We developed a method using MS2 affinity purification coupled with liquid chromatography-mass spectrometry (MAMS) to systematically map the interactome of SARS-CoV-2 ncrRNA in different human cell lines. Integration of the results defined the core and cell-type-specific ncrRNA-host protein interactomes. The majority of ncrRNA-binding proteins were involved in RNA biogenesis, protein translation, viral infection, and stress response. The 5' UTR interactome is enriched with proteins in the snRNP family and is a target for the regulation of viral replication and transcription. The 3' UTR interactome is enriched with proteins involved in the cytoplasmic RNP granule (stress granule) and translation regulation. We show that the ORF10 is likely to be a part of 3' UTR. Intriguingly, the interactions between negative-sense ncrRNAs and host proteins, such as translation initiation factors and antiviral factors, suggest a pathological role of negative-sense ncrRNAs. Moreover, the cell-type-specific interactions between ncrRNAs and mitochondria may explain the differences of cell lines in viral susceptibility. Our study unveils a comprehensive landscape of the functional SARS-CoV-2 ncrRNA-host protein interactome, providing a new perspective on virus-host interactions and the design of future therapeutics.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.18.446355", + "rel_abs": "The main protease (Mpro) of SARS-CoV-2 is central to its viral lifecycle and is a promising drug target, but little is known concerning structural aspects of how it binds to its 11 natural cleavage sites. We used biophysical and crystallographic data and an array of classical molecular mechanics and quantum mechanical techniques, including automated docking, molecular dynamics (MD) simulations, linear-scaling DFT, QM/MM, and interactive MD in virtual reality, to investigate the molecular features underlying recognition of the natural Mpro substrates. Analyses of the subsite interactions of modelled 11-residue cleavage site peptides, ligands from high-throughput crystallography, and designed covalently binding inhibitors were performed. Modelling studies reveal remarkable conservation of hydrogen bonding patterns of the natural Mpro substrates, particularly on the N-terminal side of the scissile bond. They highlight the critical role of interactions beyond the immediate active site in recognition and catalysis, in particular at the P2/S2 sites. The binding modes of the natural substrates, together with extensive interaction analyses of inhibitor and fragment binding to Mpro, reveal new opportunities for inhibition. Building on our initial Mpro-substrate models, computational mutagenesis scanning was employed to design peptides with improved affinity and which inhibit Mpro competitively. The combined results provide new insight useful for the development of Mpro inhibitors.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Liuyiqi Jiang", - "author_inst": "Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China; Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Scienc" + "author_name": "H. T. Henry Chan", + "author_inst": "University of Oxford" }, { - "author_name": "Mu Xiao", - "author_inst": "Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China; Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Scienc" + "author_name": "Marc A. Moesser", + "author_inst": "University of Oxford" }, { - "author_name": "Qing-Qing Liao", - "author_inst": "Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China." + "author_name": "Rebecca K. Walters", + "author_inst": "University of Bristol" }, { - "author_name": "Luqian Zheng", - "author_inst": "Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China." + "author_name": "Tika R. Malla", + "author_inst": "University of Oxford" }, { - "author_name": "Chunyan Li", - "author_inst": "Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China." + "author_name": "Rebecca M. Twidale", + "author_inst": "University of Bristol" }, { - "author_name": "Yuemei Liu", - "author_inst": "Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China; Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Scienc" + "author_name": "Tobias John", + "author_inst": "University of Oxford" }, { - "author_name": "Bing Yang", - "author_inst": "Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China." + "author_name": "Helen M. Deeks", + "author_inst": "University of Bristol" }, { - "author_name": "Aiming Ren", - "author_inst": "Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China." + "author_name": "Tristan Johnston-Wood", + "author_inst": "University of Oxford" }, { - "author_name": "Chao Jiang", - "author_inst": "Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China; Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Scienc" + "author_name": "Victor Mikhailov", + "author_inst": "University of Oxford" }, { - "author_name": "Xin-Hua Feng", - "author_inst": "Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China; Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Scienc" + "author_name": "Richard B. Sessions", + "author_inst": "University of Bristol" + }, + { + "author_name": "William Dawson", + "author_inst": "RIKEN R-CCS" + }, + { + "author_name": "Eidarus Salah", + "author_inst": "University of Oxford" + }, + { + "author_name": "Petra Lukacik", + "author_inst": "Diamond Light Source Ltd" + }, + { + "author_name": "Claire Strain-Damerell", + "author_inst": "Diamond Light Source Ltd" + }, + { + "author_name": "David Owen", + "author_inst": "Diamond Light Source Ltd" + }, + { + "author_name": "Takahito Nakajima", + "author_inst": "RIKEN R-CCS" + }, + { + "author_name": "Katarzyna Swiderek", + "author_inst": "Universitat Jaume I" + }, + { + "author_name": "Alessio Lodola", + "author_inst": "University of Parma" + }, + { + "author_name": "Vicent Moliner", + "author_inst": "Universitat Jaume I" + }, + { + "author_name": "David R. Glowacki", + "author_inst": "University of Bristol" + }, + { + "author_name": "Martin A. Walsh", + "author_inst": "Diamond Light Source Ltd" + }, + { + "author_name": "Christopher J. Schofield", + "author_inst": "University of Oxford" + }, + { + "author_name": "Luigi Genovese", + "author_inst": "University of Grenoble" + }, + { + "author_name": "Deborah Shoemark", + "author_inst": "University of Bristol" + }, + { + "author_name": "Adrian J. Mulholland", + "author_inst": "University of Bristol" + }, + { + "author_name": "Fernanda Duarte", + "author_inst": "University of Oxford" + }, + { + "author_name": "Garrett M. Morris", + "author_inst": "University of Oxford" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "new results", - "category": "genomics" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.06.17.448816", @@ -685389,69 +684070,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.16.21258817", - "rel_title": "Mass mask-wearing notably reduces COVID-19 transmission", + "rel_doi": "10.1101/2021.06.16.21258989", + "rel_title": "Massive social protests amid the pandemic in selected Colombian cities: Did they increase COVID-19 cases?", "rel_date": "2021-06-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.16.21258817", - "rel_abs": "Mask-wearing has been a controversial measure to control the COVID-19 pandemic. While masks are known to substantially reduce disease transmission in healthcare settings [1-3], studies in community settings report inconsistent results [4-6].\n\nInvestigating the inconsistency within epidemiological studies, we find that a commonly used proxy, government mask mandates, does not correlate with large increases in mask-wearing in our window of analysis. We thus analyse the effect of mask-wearing on transmission instead, drawing on several datasets covering 92 regions on 6 continents, including the largest survey of individual-level wearing behaviour (n=20 million) [7]. Using a hierarchical Bayesian model, we estimate the effect of both mask-wearing and mask-mandates on transmission by linking wearing levels (or mandates) to reported cases in each region, adjusting for mobility and non-pharmaceutical interventions.\n\nWe assess the robustness of our results in 123 experiments spanning 22 sensitivity analyses. Across these analyses, we find that an entire population wearing masks in public leads to a median reduction in the reproduction number R of 25.8%, with 95% of the medians between 22.2% and 30.9%. In our window of analysis, the median reduction in R associated with the wearing level observed in each region was 20.4% [2.0%, 23.3%]1. We do not find evidence that mandating mask-wearing reduces transmission. Our results suggest that mask-wearing is strongly affected by factors other than mandates.\n\nWe establish the effectiveness of mass mask-wearing, and highlight that wearing data, not mandate data, are necessary to infer this effect.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.16.21258989", + "rel_abs": "BackgroundSince April 28, 2021, in Colombia there are social protests with numerous demonstrations in various cities. The aim of this study was to assess the effect of social protests on the number and trend of the confirmed COVID-19 cases in some selected Colombian cities where social protests had more intensity.\n\nMethodsWe performed and interrupted time-series analysis (ITSA) and Autoregressive Integrated Moving Average (ARIMA) models, based on the confirmed COVID-19 cases in Colombia, between March 1 and May 15, 2021, for Bogota, Cali, Barranquilla, Medellin, and Bucaramanga. The ITSA models estimated the effect of social demonstrations on the number and trend of cases for each city by using Newey-West standard errors. ARIMA models assessed the overall pattern of the series and effect of the intervention. We considered May 2, 2021, as the intervention date for the analysis, five days after social demonstrations started in the country.\n\nFindingsDuring the study period the number of cases by city was 1,014,815 for Bogota, 192,320 for Cali, 175,269 for Barranquilla, 311,904 for Medellin, and 62,512 for Bucaramanga. Heterogeneous results were found among cities. Only for the cities of Cali and Barranquilla statistically significant changes in trend of the number of cases were obtained after the intervention: positive in the first city, negative in the second one. None ARIMA models show evidence of abrupt changes in the trend of the series for any city and intervention effect was only significant for Bucaramanga.\n\nInterpretationSocial protests had a heterogeneous effect on the number and trend of COVID-19 cases. Different effects might be related to the epidemiologic moment of the pandemic and the characteristics of the social protests. Assessing the effect of social protests within a pandemic is complex and there are several methodological limitations. Further analyses are required with longer time-series data.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Gavin Leech", - "author_inst": "Department of Computer Science, University of Bristol" - }, - { - "author_name": "Charlie Rogers-Smith", - "author_inst": "External collaborator to OATML Group, University of Oxford" - }, - { - "author_name": "Jonas Benjamin Sandbrink", - "author_inst": "Future of Humanity Institute, University of Oxford, UK" - }, - { - "author_name": "Benedict Snodin", - "author_inst": "Future of Humanity Institute, University of Oxford" - }, - { - "author_name": "Robert Zinkov", - "author_inst": "Department of Computer Science, University of Oxford" - }, - { - "author_name": "Benjamin Rader", - "author_inst": "Computational Epidemiology Lab, Boston Children's Hospital" - }, - { - "author_name": "John S. Brownstein", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Yarin Gal", - "author_inst": "Oxford Applied and Theoretical Machine Learning (OATML) Group, Department of Computer Science, University of Oxford" - }, - { - "author_name": "Samir Bhatt", - "author_inst": "Department of Public Health, University of Copenhagen" - }, - { - "author_name": "Mrinank Sharma", - "author_inst": "Future of Humanity Institute, University of Oxford" + "author_name": "Jose Moreno-Montoya", + "author_inst": "Fundacion SantaFe de Bogota" }, { - "author_name": "S\u00f6ren Mindermann", - "author_inst": "Oxford Applied and Theoretical Machine Learning (OATML) Group, Department of Computer Science, University of Oxford" - }, - { - "author_name": "Jan Markus Brauner", - "author_inst": "Oxford Applied and Theoretical Machine Learning (OATML) Group, Department of Computer Science, University of Oxford" + "author_name": "Laura A Rodriguez Villamizar", + "author_inst": "Universidad Industrial de Santander" }, { - "author_name": "Laurence Aitchison", - "author_inst": "Department of Computer Science, University of Bristol" + "author_name": "Alvaro Javier Idrovo", + "author_inst": "Universidad Industrial de Santander" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -687767,27 +686408,91 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.06.15.21258880", - "rel_title": "Serological prevalence of SARS-CoV-2 antibody among children and young age (between age 2-17 years) group in India: An interim result from a large multi-centric population-based seroepidemiological study", + "rel_doi": "10.1101/2021.06.12.21258811", + "rel_title": "Evaluation of saliva molecular point of care for detection of SARS-CoV-2 in ambulatory care", "rel_date": "2021-06-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.15.21258880", - "rel_abs": "BackgroundConcern has been raised in India regarding the probable third wave of COVID-19 where children and young age group is thought to get affected the most. There is a lack of serological prevalence data in this age group. We have some interim data from our research for WHO unity protocol, which might help policymakers and the research community to answer such questions based on evidence. Hence, we conducted a study to compare the COVID -19 sero-positivity rate between children and adults\n\nMethods/MaterialsThis is part of an ongoing large multi-centric population-based sero-epidemiological study. The study is being conducted in five selected states with a proposed total sample size of 10,000. We have data of 4,500 participants at the time of midterm analysis from four states of India. Total serum antibody against SARS-CoV-2 virus was assessed qualitatively by using a standard ELISA kit. Here we are reporting the interim data of serological prevalence among children aged between 2 to 17 years along with a comparison with [≥]18-year old participants.\n\nResultsThe data collection period was from 15th March 2021 to 10th June 2021. Total available data was of 4,509 participants out of which <18 years were 700 and [≥]18 years was 3,809. The site-wise number of available data among the 2-17 year age group were 92, 189, 165, 146 and 108 for the site of Delhi urban resettlement colony, Delhi rural (Villages in Faridabad district under Delhi NCR), Bhubaneswar rural, Gorakhpur rural and Agartala rural area respectively. The seroprevalence was 55.7% in the <18 years age group and 63.5% in the [≥] 18 year age group. There was no statistically significant difference in prevalence between adult and children.\n\nConclusionSARS-CoV-2 sero-positivity rate among children was high and were comparable to the adult population. Hence, it is unlikely that any future third wave by prevailing COVID-19 variant would disproportionately affect children two years or older.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.12.21258811", + "rel_abs": "BackgroundRapid identification of SARS-Cov-2 infected individuals is a cornerstone in strategies for the control of virus spread. The sensitivity of SARS-CoV-2 RNA detection by RT-PCR is similar in saliva and nasopharyngeal swab. Rapid molecular point-of-care tests in saliva could facilitate, broaden and speed up the diagnosis.\n\nObjectives and methodsWe conducted a prospective study in two community COVID-19 screening centers to evaluate the performances of a CE-marked RT-LAMP assay (EasyCoV) specifically designed for the detection of SARS-CoV2 RNA from fresh saliva samples, compared to nasopharyngeal RT-PCR (reference test), to saliva RT-PCR and to nasopharyngeal antigen testing.\n\nResultsOverall, 117 of the 1718 participants (7%) were tested positive with nasopharyngeal RT-PCR. Compared to nasopharyngeal RT-PCR, the sensitivity and specificity of the RT-LAMP assay in saliva were 34% (95%CI: 26-44) and 97% (95%CI: 96-98) respectively. The performance was similar in symptomatic and asymptomatic participants. The Ct values of nasopharyngeal RT-PCR were significantly lower in the 40 true positive subjects with saliva RT-LAMP (Ct 25.9) than in the 48 false negative subjects with saliva RT-LAMP (Ct 28.4) (p=0.028). Considering six alternate criteria for reference test, including saliva RT-PCR and nasopharyngeal antigen, the sensitivity of saliva RT-LAMP ranged between 27 and 44%.\n\nConclusionIn the ambulatory setting, the detection of SARS-CoV-2 from crude saliva samples with the RT-LAMP assay had a lower sensitivity than nasopharyngeal RT-PCR, saliva RT-PCR and nasopharyngeal antigen testing.\n\nRegistration numberNCT04578509\n\nFunding SourcesFrench Ministry of Health and the Assistance Publique-Hopitaux de Paris Foundation.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Puneet Misra", - "author_inst": "AIIMS, New Delhi" + "author_name": "Jerome Le Goff", + "author_inst": "Universite de Paris" }, { - "author_name": "- WHO Unity Seroprevalence study team of AIIMS", - "author_inst": "" + "author_name": "Solen Kerneis", + "author_inst": "Universite de Paris, INSERM, IAME, F-75018 Paris, France" + }, + { + "author_name": "Caroline Elie", + "author_inst": "Clinical Research Unit / Clinical Investigation Center, APHP, Necker-Enfants malades Hospital, F-75015 Paris, France" + }, + { + "author_name": "Severine Mercier Delarue", + "author_inst": "Virologie, AP-HP, Hopital Saint Louis, F-75010 Paris, France" + }, + { + "author_name": "Nabil Gastli", + "author_inst": "Plateforme Covid IDF, AP-HP.Centre, F-75014 Paris, France" + }, + { + "author_name": "Laure Choupeaux", + "author_inst": "Clinical Research Unit / Clinical Investigation Center, APHP, Necker-Enfants malades Hospital, F-75015 Paris, France" + }, + { + "author_name": "Jacques Fourgeaud", + "author_inst": "Virologie, AP-HP, Hopital Necker-Enfants Malades, F-75015 Paris, France" + }, + { + "author_name": "Marie-Laure Alby", + "author_inst": "Centre de depistage COVISAN 13 14 15, Communaute professionnelle de territoire de sante, F-75014, Paris, France" + }, + { + "author_name": "Pierre Quentin", + "author_inst": "Centre de depistage COVISAN 13 14 15, Communaute professionnelle de territoire de sante, F-75014, Paris, France" + }, + { + "author_name": "Juliette Pavie", + "author_inst": "Immuno-Infectiologie, AP-HP, Hotel Dieu, F-75004 Paris, France" + }, + { + "author_name": "Paricia Brazille", + "author_inst": "Immuno-Infectiologie, AP-HP, Hotel Dieu, F-75004 Paris, France" + }, + { + "author_name": "Marie-Laure Nere", + "author_inst": "Laboratoire de Virologie, Hopital Saint-Louis, AP-HP" + }, + { + "author_name": "Audrey Gabassi", + "author_inst": "Virologie, AP-HP, Hopital Saint Louis, F-75010 Paris, France" + }, + { + "author_name": "Marine Minier", + "author_inst": "Virologie, AP-HP, Hopital Saint Louis, F-75010 Paris, France" + }, + { + "author_name": "Chrystel Leroy", + "author_inst": "Plateforme Covid IDF, AP-HP.Centre, F-75014 Paris, France" + }, + { + "author_name": "Beatrice Parfait", + "author_inst": "Centre de Ressources Biologiques - site Cochin, AP-HP, Federation des CRB/PRB d'AP-HP. Centre-Universite de Paris, Hopital Cochin, F-75014 Paris, France" + }, + { + "author_name": "Jean-Marc Treluyer", + "author_inst": "Clinical Research Unit / Clinical Investigation Center, APHP, Necker-Enfants malades Hospital, F-75015 Paris, France" + }, + { + "author_name": "Constance Delaugerre", + "author_inst": "Universite de Paris, INSERM, U944, F-75010 Paris, France" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.06.15.448611", @@ -689656,37 +688361,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.12.21258831", - "rel_title": "Efficacy and safety of hydroxychloroquine as pre-and post-exposure prophylaxis and treatment of COVID-19. Systematic review and meta-analysis of blinded, placebo-controlled, randomized clinical trials", + "rel_doi": "10.1101/2021.06.13.21258851", + "rel_title": "VAERS data reveals no increased risk of neuroautoimmune adverse events from COVID-19 vaccines", "rel_date": "2021-06-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.12.21258831", - "rel_abs": "BACKGROUNDHydroxychloroquine (HCQ) is an anti-malarial and immunomodulatory drug considered a potential candidate for drug repurposing in COVID-19 due to their in vitro antiviral activity against SARS-CoV-2. Despite the potential antiviral effects and anti-inflammatory profile, the results based on clinical studies are contradictory and the quality of the decision-making process from meta-analyses summarizing the available evidence selecting studies with different designs and unblinded trials is limited. The aim of this study was to synthesize the best evidence on the efficacy and safety of HCQ as pre-and post-exposure prophylaxis and treatment of non-hospitalized and hospitalized patients with COVID-19.\n\nMETHODSSearches for studies were performed in PubMed, Web of Science, Embase, Lilacs, the website ClinicalTrials.gov and the preprint server medRxiv from January 1, 2020 to May 17, 2021. The following elements were used to define eligibility criteria: (1) Population, individuals at high-risk of exposure to SARS-CoV-2 (pre-exposure), individuals who had close contact with a positive or probable case of COVID-19 (post-exposure), non-hospitalized patients with COVID-19 and hospitalized patients with COVID-19; (2) Intervention, HCQ; (3) Comparison, placebo; (4) Outcomes: incidence of SARS-CoV-2 infection, need for hospitalization, length of hospital stay, need for invasive mechanical ventilation (MV), death, and adverse events; and (5) Study type, blinded, placebo-controlled, randomized clinical trials (RCTs). Risk of bias was judged according to the Cochrane guidelines for RCTs. Treatment effects were reported as relative risk (RR) for dichotomous variables and mean difference (MD) for continuous variables with 95% confidence intervals (CI). We used either a fixed or random-effects model to pool the results of individual studies depending on the presence of heterogeneity. The GRADE system was used to evaluate the strength of evidence between use of HCQ and the outcomes of interest.\n\nRESULTSFourteen blinded, placebo-controlled RCTs were included in the meta-analysis. Four trials used HCQ as a prophylactic medication pre-exposure to COVID-19, two as a prophylactic medication post-exposure to COVID-19, three as treatment for non-hospitalized patients, and five as treatment for hospitalized patients with COVID-19. We found no decreased risk of SARS-CoV-2 infection among individuals receiving HCQ as pre-exposure (RR = 0.90; 95% CI 0.46 to 1.77) or post-exposure (RR = 0.96; 95% CI 0.72 to 1.29) prophylaxis to prevent COVID-19. There is no decreased risk of hospitalization for outpatients with SARS-CoV-2 infection (RR = 0.64; 95% CI 0.33 to 1.23) and no decreased risk of MV (RR = 0.81; 95% CI 0.49 to 1.34) and death (RR = 1.05; 95% CI 0.62 to 1.78) among hospitalized patients with COVID-19 receiving HCQ. The certainty of the results on the lack of clinical benefit for HCQ was rated as moderate. Moreover, our results demonstrated an increased risk for any adverse events and gastrointestinal symptoms among those using HCQ.\n\nCONCLUSIONAvailable evidence based on the results of blinded, placebo-controlled RCTs showed no clinical benefits of HCQ as pre-and post-exposure prophylaxis and treatment of non-hospitalized and hospitalized patients with COVID-19.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.13.21258851", + "rel_abs": "Neuroautoimmune disorders, such as multiple sclerosis and Guillain-Barre syndrome, have been documented in relation to various vaccines in the past. This paper uses passive reporting information from the CDC/FDAs VAERS system to analyse whether neuroautoimmune presentations are reported at a relatively higher or lower rate, vis-a-vis other adverse effects, for COVID-19 vaccines than for other vaccines. Through computing the reporting odds ratios for a range of symptoms and comparator vaccines, a clear indication in favour of the safety of COVID-19 vaccines emerges, with reports of neuroautoimmune adverse events in relation to other adverse events being over 70% less likely for COVID-19 than for comparator vaccines (ROR : 0.292, p < 0.0001). In comparison with other vaccines given as part of routine care in adulthood, COVID-19 vaccines have the lowest reporting odds ratio of neuroautoimmune adverse effects (median ROR: 0.246).", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Paulo Ricardo Martins-Filho", - "author_inst": "Investigative Pathology Laboratory, Federal University of Sergipe, Aracaju, Sergipe, Brazil." - }, - { - "author_name": "Lis Campos Ferreira", - "author_inst": "Department of Medicine, Tiradentes University, Aracaju, Sergipe, Brazil." - }, - { - "author_name": "Luana Heimfarth", - "author_inst": "Laboratory of Neuroscience and Pharmacological Assays, Department of Physiology, Federal University of Sergipe, Sao Cristovao, Sergipe, Brazil" - }, - { - "author_name": "Adriano Antunes de Souza Araujo", - "author_inst": "Laboratory of Pharmaceutical Assays and Toxicity, Department of Pharmacy, Federal University of Sergipe, Sao Cristovao, Sergipe, Brazil" - }, - { - "author_name": "Lucindo Jose Quintans-Junior", - "author_inst": "Laboratory of Neuroscience and Pharmacological Assays, Department of Physiology, Federal University of Sergipe, Sao Cristovao, Sergipe, Brazil." + "author_name": "Chris von Csefalvay", + "author_inst": "Starschema" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -690783,35 +689472,171 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2021.06.12.21258774", - "rel_title": "Impact of long-term care facility size on preparedness and adherence to infection prevention and control guidance for the mitigation of COVID-19", + "rel_doi": "10.1101/2021.06.14.21258569", + "rel_title": "Subcutaneous REGEN-COV Antibody Combination in Early SARS-CoV-2 Infection", "rel_date": "2021-06-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.12.21258774", - "rel_abs": "AimTo evaluate the preparedness and adherence of Brazilian long-term care facilities (LTCFs) to the World Health Organization (WHO) infection prevention and control (IPC) guidance and examine the association of LTCF size with adherence to recommendations.\n\nMethodsWe conducted a cross-sectional study of LTCF managers for 12 consecutive weeks from May 5, 2020. We developed and pre-tested a 46-item questionnaire based on WHO IPC guidance that included multiple-choice and dichotomous questions as well as an open-ended question on the main difficulties encountered by the facility in tackling the pandemic. Using a global adherence score based on the adoption of 20 recommendations, we classified preparedness as (1) excellent for LTCFs following [≥]14 recommendations, (2) good for those following 10-13 recommendations, and (3) poor for those following <10 recommendations. LTCF size was established as small, medium, and large according to a 2-step cluster analysis of the number of residents as a continuous variable. We used descriptive statistics and chi-square tests at a 5% significance level.\n\nResultsOf 362 facilities included in the study, 308 (85.1%) adhered to 14 or more recommendations; 3 were classified as poorly adherent. Regarding LTCF size, we found a lower adherence to screening visitors for COVID-19 signs and symptoms (p=0.037) and to isolating patients until they have 2 negative laboratory tests (p=0.032) in larger facilities than in medium and small facilities.\n\nConclusionsPreparedness for mitigating COVID-19 in Brazilian LTCFs was considered excellent for most of the proposed recommendations, regardless of LTCF size. Difficulties and problems with infrastructure and/or resident care were much less commonly reported than those related to maintenance of a sufficient stock of materials, workforce management, and financial distress.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.14.21258569", + "rel_abs": "ImportanceEasy-to-administer antiviral treatments may be used to prevent progression from asymptomatic infection to COVID-19 and to reduce viral carriage.\n\nObjectiveEvaluate the efficacy and safety of subcutaneous casirivimab and imdevimab antibody combination (REGEN-COV) to prevent progression from early asymptomatic SARS-CoV-2 infection to COVID-19.\n\nDesignRandomized, double-blind, placebo-controlled, phase 3 study that enrolled asymptomatic close contacts living with a SARS-CoV-2-infected household member (index case). Participants who were SARS-CoV-2 RT-qPCR-positive at baseline were included in the analysis reported here.\n\nSettingMulticenter trial conducted at 112 sites in the United States, Romania, and Moldova.\n\nParticipantsAsymptomatic individuals [≥]12 years of age were eligible if identified within 96 hours of collection of the index cases positive SARS-CoV-2 test sample.\n\nInterventionsA total of 314 asymptomatic, SARS-CoV-2 RT-qPCR-positive individuals living with an infected household contact were randomized 1:1 to receive a single dose of subcutaneous REGEN-COV 1200mg (n=158) or placebo (n=156).\n\nMain Outcome(s) and Measure(s)The primary endpoint was the proportion of participants who developed symptomatic COVID-19 during the 28-day efficacy assessment period. The key secondary efficacy endpoints were the number of weeks of symptomatic SARS-CoV-2 infection and the number of weeks of high viral load (>4 log10 copies/mL). Safety was assessed in all treated participants.\n\nResultsSubcutaneous REGEN-COV 1200mg significantly prevented progression from asymptomatic to symptomatic disease compared with placebo (31.5% relative risk reduction; 29/100 [29.0%] vs 44/104 [42.3%], respectively; P=.0380). REGEN-COV reduced the overall population burden of high-viral load weeks (39.7% reduction vs placebo; 48 vs 82 total weeks; P=.0010) and of symptomatic weeks (45.3% reduction vs placebo; 89.6 vs 170.3 total weeks; P=.0273), the latter corresponding to an approximately 5.6-day reduction in symptom duration per symptomatic participant. Six placebo-treated participants had a COVID-19-related hospitalization or ER visit versus none for those receiving REGEN-COV. The proportion of participants receiving placebo who had [≥]1 treatment-emergent adverse events was 48.1% compared with 33.5% for those receiving REGEN-COV, including events related (39.7% vs 25.8%, respectively) or not related (16.0% vs 11.0%, respectively) to COVID-19.\n\nConclusions and RelevanceSubcutaneous REGEN-COV 1200mg prevented progression from asymptomatic SARS-CoV-2 infection to COVID-19, reduced the duration of high viral load and symptoms, and was well tolerated.\n\nTrial RegistrationClinicalTrials.gov Identifier, NCT04452318\n\nKEY POINTSO_ST_ABSQuestionC_ST_ABSCan treatment with the anti-SARS-CoV-2 antibody combination REGEN-COV prevent COVID-19 and reduce viral load when given to recently exposed and asymptomatic individuals?\n\nFindingsIn this randomized, double-blind, phase 3 trial, subcutaneously administered REGEN-COV 1200 mg significantly reduced progression of asymptomatic SARS-CoV-2 infection to symptomatic infection (ie, COVID-19) by 31.5% compared with placebo. REGEN-COV also reduced the overall population burden of high viral load weeks (39.7% reduction vs placebo; 48 vs 82 total weeks; P=.0010).\n\nMeaningIn the current pandemic, utilization of subcutaneous REGEN-COV prevents progression of early asymptomatic infection to COVID-19 and reduces viral carriage.", + "rel_num_authors": 38, "rel_authors": [ { - "author_name": "Patrick Alexander Wachholz", - "author_inst": "Botucatu Medical School, Sao Paulo State University (UNESP)" + "author_name": "Meagan P O'Brien", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Eduardo Forleo-Neto", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Neena Sarkar", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Flonza Isa", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Peijie Hou", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Kuo-Chen Chan", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Bret J Musser", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Katharine J Bar", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Ruanne V Barnabas", + "author_inst": "University of Washington; Fred Hutchinson Cancer Research Center" + }, + { + "author_name": "Dan H Barouch", + "author_inst": "Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard Medical School" + }, + { + "author_name": "Myron S Cohen", + "author_inst": "Institute for Global Health and Infectious Diseases, University of North Carolina" + }, + { + "author_name": "Christopher B Hurt", + "author_inst": "Institute for Global Health and Infectious Diseases, University of North Carolina" + }, + { + "author_name": "Dale R Burwen", + "author_inst": "National Institute of Allergy and Infectious Diseases, National Institutes of Health" + }, + { + "author_name": "Mary A Marovich", + "author_inst": "National Institute of Allergy and Infectious Diseases, National Institutes of Health" + }, + { + "author_name": "Elizabeth R Brown", + "author_inst": "Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center" + }, + { + "author_name": "Ingeborg Heirman", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "John D Davis", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Kenneth C Turner", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Divya Ramesh", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Adnan Mahmood", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Andrea T Hooper", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Jennifer D Hamilton", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Yunji Kim", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Lisa A Purcell", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Alina Baum", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Christos A Kyratsous", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "James Krainson", + "author_inst": "Clinical Trials of Florida, LLC" + }, + { + "author_name": "Richard Perez-Perez", + "author_inst": "Medical Research of Westchester" + }, + { + "author_name": "Rizwana Mohseni", + "author_inst": "Catalina Research Institute, LLC" + }, + { + "author_name": "Bari Kowal", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "A Thomas DiCioccio", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Neil Stahl", + "author_inst": "Regeneron Pharmaceuticals, Inc." }, { - "author_name": "Ruth Caldeira de Melo", - "author_inst": "School of Arts, Sciences and Humanities, Universidade de Sao Paulo (USP)" + "author_name": "Leah Lipsich", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Ned Braunstein", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Gary Herman", + "author_inst": "Regeneron Pharmaceuticals, Inc." }, { - "author_name": "Alessandro Ferrari Jacinto", - "author_inst": "Division of Geriatrics and Gerontology, Escola Paulista de Medicina, Universidade Federal de Sao Paulo (UNIFESP)" + "author_name": "George D Yancopoulos", + "author_inst": "Regeneron Pharmaceuticals, Inc." }, { - "author_name": "Paulo Jose Fortes Villas Boas", - "author_inst": "Botucatu Medical School, Sao Paulo State University (UNESP)" + "author_name": "David M Weinreich", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "- Covid-19 Phase 3 Prevention Trial Team", + "author_inst": "" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "geriatric medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.06.11.21258564", @@ -692537,51 +691362,95 @@ "category": "systems biology" }, { - "rel_doi": "10.1101/2021.06.12.448175", - "rel_title": "Glycolytic inhibitor 2-Deoxy-D-glucose attenuates SARS-CoV-2 multiplication in host cells and weakens the infective potential of progeny virions", + "rel_doi": "10.1101/2021.06.09.21258556", + "rel_title": "Safety, Immunogenicity, and Efficacy of a COVID-19 Vaccine (NVX-CoV2373) Co-administered With Seasonal Influenza Vaccines", "rel_date": "2021-06-13", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.12.448175", - "rel_abs": "The COVID-19 pandemic is an ongoing public health emergency of international concern. While a lot of efforts are being invested in vaccinating the population, there is also an emergent requirement to find potential therapeutics to effectively counter this fast mutating SARS-CoV-2 virus-induced pathogenicity. Virus-infected host cells switch their metabolism to a more glycolytic phenotype. This switch induced by the virus is needed for faster production of ATP and higher levels of anabolic intermediates, required for new virion synthesis and packaging. In this study, we used 2-Deoxy-D-glucose (2-DG) to target and inhibit the metabolic reprogramming induced by SARS-CoV-2 infection. Our results showed that virus infection induces glucose influx and glycolysis resulting in selective high accumulation of the fluorescent glucose/2-DG analogue, 2-NBDG in these cells. Subsequently, 2-DG inhibits glycolysis in infected cells thereby reducing the virus multiplication and alleviates the cells from virus induced cytopathic effect (CPE) and cell death. Herein, we demonstrate that the crucial Nglycosites (N331 and N343) of RBD in spike protein of progeny virions produced from 2-DG treated cells were found unglycosylated and defective with compromised infectivity potential. In line with earlier reported observations, our study also showed that 2-DG mediated metabolic inhibiton can attenuate SARS-COV-2 multiplication. In addition, mechanistic study revealed that the inhibition of SARS-COV-2 multiplication is attributed to 2-DG induced un-glycosylation of spike protein. Our findings strengthen the notion that 2-DG effectively inhibits SARS-CoV-2 multiplication. Therefore, based on its previous human trials in different types of Cancer and Herpes patients, it could be a potential molecule to study in COVID-19 patients.", - "rel_num_authors": 8, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.09.21258556", + "rel_abs": "BackgroundThe safety and immunogenicity profile of COVID-19 vaccines when administered concomitantly with seasonal influenza vaccines has not yet been reported.\n\nMethodsA sub-study on influenza vaccine co-administration was conducted as part of the phase 3 randomized trial of the safety and efficacy of NVX-CoV2373. The first [~]400 participants meeting main study entry criteria and with no contraindications to influenza vaccination were invited to join the sub-study. After randomization in a 1:1 ratio to receive NVX-CoV2373 (n=217) or placebo (n=214), sub-study participants received an age-appropriate, licensed, open-label influenza vaccine with dose 1 of NVX-CoV2373. Reactogenicity was evaluated via electronic diary for 7 days post-vaccination in addition to monitoring for unsolicited adverse events (AEs), medically-attended AEs (MAAEs), and serious AEs (SAEs). Influenza haemagglutination inhibition and SARS-CoV-2 anti-spike IgG assays were performed. Vaccine efficacy against PCR-confirmed, symptomatic COVID-19 was assessed. Comparisons were made between sub-study and main study participants.\n\nFindingsSub-study participants were younger, more racially diverse, and had fewer comorbid conditions than main study participants. Reactogenicity events more common in the co-administration group included tenderness (70.1% vs 57.6%) or pain (39.7% vs 29.3%) at injection site, fatigue (27.7% vs 19.4%), and muscle pain (28.3% vs 21.4%). Rates of unsolicited AEs, MAAEs, and SAEs were low and balanced between the two groups. Co-administration resulted in no change to influenza vaccine immune response, while a reduction in antibody responses to the NVX-CoV2373 vaccine was noted. Vaccine efficacy in the sub-study was 87.5% (95% CI: -0.2, 98.4) while efficacy in the main study was 89.8% (95% CI: 79.7, 95.5).\n\nInterpretationThis is the first study to demonstrate the safety, immunogenicity, and efficacy profile of a COVID-19 vaccine when co-administered with seasonal influenza vaccines. The results suggest concomitant vaccination may be a viable immunisation strategy.\n\nFundingThis study was funded by Novavax, Inc.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for research articles published from December 2019 until 1 April 2021 with no language restrictions for the terms \"SARS-CoV-2\", \"COVID-19\", \"vaccine\", \"co-administration\", and \"immunogenicity\". There were no peer-reviewed publications describing the simultaneous use of any SARS-CoV-2 vaccine and another vaccine. Several vaccine manufacturers had recent publications on phase 3 trials results (Pfizer/BioNTech, Moderna, AstraZeneca, Janssen, and the Gamaleya Research Institute of Epidemiology and Microbiology). Neither these publications nor their clinical trials protocols (when publicly available) described co-administration and they often had trial criteria specifically excluding those with recent or planned vaccination with any licenced vaccine near or at the time of any study injection.\n\nAdded value of this studyImmune interference and safety are always a concern when two vaccines are administered at the same time. This is the first study to demonstrate the safety and immunogenicity profile and clinical vaccine efficacy of a COVID-19 vaccine when co-administered with a seasonal influenza vaccine.\n\nImplications of all the available evidenceThis study provides much needed information to help guide national immunisation policy decision making on the critical issue of concomitant use of COVID-19 vaccines with influenza vaccines.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Anant Narayan Bhatt", - "author_inst": "Institute of Nuclear Medicine & Allied Sciences, Delhi, India." + "author_name": "Paul Heath", + "author_inst": "St Georges, University of London" }, { - "author_name": "Abhishek Kumar", - "author_inst": "Institute of Nuclear Medicine & Allied Sciences, Delhi, India." + "author_name": "Seth Toback", + "author_inst": "Novavax" }, { - "author_name": "Yogesh Rai", - "author_inst": "Institute of Nuclear Medicine & Allied Sciences, Delhi, India." + "author_name": "Eva Galiza", + "author_inst": "St. George's, University of London" }, { - "author_name": "Neeraj Kumari", - "author_inst": "Institute of Nuclear Medicine & Allied Sciences, Delhi, India." + "author_name": "Catherine Cosgrove", + "author_inst": "St Georges University of London" }, { - "author_name": "Dhiviya Vedagiri", - "author_inst": "CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India 500007" + "author_name": "James Galloway", + "author_inst": "Kings College London" }, { - "author_name": "Krishnan H. Harshan", - "author_inst": "CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India 500007" + "author_name": "Anna L. Goodman", + "author_inst": "Guy's and St Thomas' NHS Foundation Trust" }, { - "author_name": "Vijayakumar Chinnadurai", - "author_inst": "Institute of Nuclear Medicine & Allied Sciences, Delhi, India." + "author_name": "Pauline A. Swift", + "author_inst": "Epsom and St. Helier University Hospitals NHS Trust" }, { - "author_name": "Sudhir Chandna", - "author_inst": "Institute of Nuclear Medicine & Allied Sciences, Delhi, India." + "author_name": "Sankarasubramanian Rajaram", + "author_inst": "Seqirus" + }, + { + "author_name": "Alison Graves-Jones", + "author_inst": "Seqirus" + }, + { + "author_name": "Jonathan Edelman", + "author_inst": "Seqirus" + }, + { + "author_name": "Fiona Burns", + "author_inst": "University College London, and Royal Free London NHS Foundation Trust" + }, + { + "author_name": "Angela M. Minassian", + "author_inst": "University of Oxford, and Oxford Health NHS Foundation Trust" + }, + { + "author_name": "Iksung Cho", + "author_inst": "Novavax" + }, + { + "author_name": "Lakshmi Kumar", + "author_inst": "Novavax" + }, + { + "author_name": "Joyce S. Plested", + "author_inst": "Novavax" + }, + { + "author_name": "E. Joy Rivers", + "author_inst": "Novavax" + }, + { + "author_name": "Andreana Robertson", + "author_inst": "Novavax" + }, + { + "author_name": "Filip Dubovsky", + "author_inst": "Novavax" + }, + { + "author_name": "Greg Glenn", + "author_inst": "Novavax" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "cell biology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2021.06.08.21258533", @@ -694227,105 +693096,57 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.06.10.447982", - "rel_title": "High-affinity, neutralizing antibodies to SARS-CoV-2 can be made in the absence of T follicular helper cells", + "rel_doi": "10.1101/2021.06.11.447942", + "rel_title": "Anti-SARS-CoV-2 hyperimmune immunoglobulin provides potent and robust neutralization capacity and antibody-dependent cellular cytotoxicity and phagocytosis induction through N and S proteins", "rel_date": "2021-06-11", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.10.447982", - "rel_abs": "T follicular helper (Tfh) cells are the conventional drivers of protective, germinal center (GC)-based antiviral antibody responses. However, loss of Tfh cells and GCs has been observed in patients with severe COVID-19. As T cell-B cell interactions and immunoglobulin class switching still occur in these patients, non-canonical pathways of antibody production may be operative during SARS-CoV-2 infection. We found that both Tfh-dependent and -independent antibodies were induced against SARS-CoV-2 as well as influenza A virus. Tfh-independent responses were mediated by a population we call lymph node (LN)-Th1 cells, which remain in the LN and interact with B cells outside of GCs to promote high-affinity but broad-spectrum antibodies. Strikingly, antibodies generated in the presence and absence of Tfh cells displayed similar neutralization potency against homologous SARS-CoV-2 as well as the B.1.351 variant of concern. These data support a new paradigm for the induction of B cell responses during viral infection that enables effective, neutralizing antibody production to complement traditional GCs and even compensate for GCs damaged by viral inflammation.\n\nOne-Sentence SummaryComplementary pathways of antibody production mediate neutralizing responses to SARS-CoV-2.", - "rel_num_authors": 23, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.11.447942", + "rel_abs": "BackgroundAlthough progressive COVID-19 vaccinations provide a significant reduction of infection rate in the short-to mid-term, effective COVID-19 treatments will continue to be an urgent need.\n\nMethodsWe have functionally characterized the anti-SARS-CoV-2 hyperimmune immunoglobulin (hIG) prepared from human COVID-19 convalescent plasma. SARS-CoV-2 virus neutralization was evaluated by four different methodologies (plaque reduction, virus induced cytotoxicity, TCID50 reduction and immunofluorimetry-based methodology) performed at four different laboratories and using four geographically different SARS-CoV-2 isolates (one each from USA and Italy; two from Spain). Two of the isolates contained the D614G mutation. Neutralization capacity against the original Wuhan SARS-CoV-2 straom and variants (D614G mutant, B.1.1.7, P.1 and B.1.351 variants) was evaluated using a pseudovirus platform expressing the corresponding spike (S) protein. The capacity to induce antibody-dependent cellular cytotoxicity (ADCC) and antibody-dependent cellular phagocytosis (ADCP) was also evaluated.\n\nResultsAll the SARS-CoV-2 isolates tested were effectively neutralized by hIG solutions. This was confirmed by all four methodologies showing potent neutralization capacity. Wild-type SARS-CoV-2 and variants were effectively neutralized as demonstrated using the pseudovirus platform. The hIG solutions had the capacity to induce ADCC and ADCP against SARS-CoV-2 N and S proteins but not the E protein. Under our experimental conditions, very low concentrations (25-100 {micro}g IgG/mL) were required to induce both effects. Besides the S protein, we observed a clear and potent effect triggered by antibodies in the hIG solutions against the SARS-CoV-2 N protein.\n\nConclusionsThese results show that, beyond neutralization, other IgG Fc-dependent pathways may play a role in the protection from and/or resolution of SARS-CoV-2 infection when using hIG COVID-19 products. This could be especially relevant for the treatment of more neutralization resistant SARS-CoV-2 variants of concern.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Jennifer S. Chen", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Ryan D. Chow", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Eric Song", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Tianyang Mao", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Benjamin Israelow", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Kathy Kamath", - "author_inst": "Serimmune, Inc." - }, - { - "author_name": "Joel Bozekowski", - "author_inst": "Serimmune, Inc." - }, - { - "author_name": "Winston A. Haynes", - "author_inst": "Serimmune, Inc." - }, - { - "author_name": "Renata B. Filler", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Bridget L. Menasche", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Jin Wei", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Mia Madel Alfajaro", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Wenzhi Song", - "author_inst": "Yale University School of Medicine" + "author_name": "Jos\u00e9-Mar\u00eda D\u00edez", + "author_inst": "Grifols" }, { - "author_name": "Lei Peng", - "author_inst": "Yale University School of Medicine" + "author_name": "Carolina Romero", + "author_inst": "Grifols" }, { - "author_name": "Lauren Carter", - "author_inst": "University of Washington" + "author_name": "Mar\u00eda Cruz", + "author_inst": "Grifols" }, { - "author_name": "Jason S. Weinstein", - "author_inst": "Rutgers New Jersey Medical School" + "author_name": "Peter Vandeberg", + "author_inst": "Grifols" }, { - "author_name": "Uthaman Gowthaman", - "author_inst": "University of Massachusetts Medical School" + "author_name": "W. Keither Merritt", + "author_inst": "Grifols" }, { - "author_name": "Sidi Chen", - "author_inst": "Yale University School of Medicine" + "author_name": "Edwards Pradenas", + "author_inst": "IrsiCaixa AIDS Research Institute" }, { - "author_name": "Joe Craft", - "author_inst": "Yale University School of Medicine" + "author_name": "Benjamin Trinit\u00e9", + "author_inst": "IrsiCaixa AIDS Research Institute" }, { - "author_name": "John C. Shon", - "author_inst": "Serimmune, Inc." + "author_name": "Juli\u00e1 Blanco", + "author_inst": "IrsiCaixa AIDS Research Institute" }, { - "author_name": "Akiko Iwasaki", - "author_inst": "Yale University School of Medicine" + "author_name": "Bonaventura Clotet", + "author_inst": "IrsiCaixa AIDS Research Institute" }, { - "author_name": "Craig B. Wilen", - "author_inst": "Yale University School of Medicine" + "author_name": "Todd Willis", + "author_inst": "Grifols" }, { - "author_name": "Stephanie C. Eisenbarth", - "author_inst": "Yale University School of Medicine" + "author_name": "Rodrigo Gajardo", + "author_inst": "Grifols" } ], "version": "1", @@ -696253,49 +695074,53 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2021.06.08.21258563", - "rel_title": "High throughput sequencing based detection of SARS-CoV-2 prevailing in wastewater of Pune, West India", + "rel_doi": "10.1101/2021.06.07.21257958", + "rel_title": "COVID-19 infections in day care centres in Germany: Social and organizational determinants of infections in children and staff in the second and third wave of the pandemic", "rel_date": "2021-06-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.08.21258563", - "rel_abs": "Given a large number of SARS-CoV-2 infected individuals, clinical detection has proved challenging. The wastewater-based epidemiological paradigm would cover the clinically escaped asymptomatic individuals owing to the faecal shedding of the virus. We hypothesised using wastewater as a valuable resource for analysing SARS-CoV-2 mutations circulating in the wastewater of Pune region (Maharashtra; India), one of the most affected during the covid-19 pandemic. We conducted a case study in open wastewater drains from December 2020-March 2021 to assess the presence of SARS-CoV-2 nucleic acid and further detect mutations using ARTIC protocol of MinION sequencing. The analysis revealed 108 mutations across six samples categorised into 40 types of mutations. We report the occurrence of mutations associated with B.1.617 lineage in March-2021 samples, simultaneously also reported as a Variant of Concern (VoC) responsible for the rapid increase in infections. The study also revealed four mutations; S:N801, S:C480R, NSP14:C279F and NSP3:L550del not currently reported from wastewater or clinical data in India but reported in the world. Further, a novel mutation NSP13:G206F mapping to NSP13 region was observed from wastewater. Notably, S:P1140del mutation was observed in December 2020 samples while it was reported in February 2021 from clinical data, indicating the instrumentality of wastewater data in early detection. This is the first study in India to conclude that wastewater-based epidemiology to identify mutations associated with SARS-CoV-2 virus from wastewater as an early warning indicator system.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.07.21257958", + "rel_abs": "BackgroundDuring the SARS-CoV-2 pandemic, German early childhood education and care (ECEC) centres organised childrens attendance variably (i.e., reduced opening hours, emergency support for few children only or full close-down). Further, protection and hygiene measures like fixed children/staff groups, ventilation and surface disinfection were introduced among ECEC centres. To inform or modify public health measures in ECEC, we investigate the occurrence of SARS-CoV-2 infections among children and staff of ECEC centres in light of social determinants (socioeconomic status of the children) and recommended structural and hygiene measures. We focus on the question if the relevant factors differ between the 2nd (when no variant of concern (VOC) circulated) and the 3rd wave (when VOC B.1.1.7 (Alpha) predominated).\n\nMethodsBased on panel data from a weekly online survey of ECEC centre managers (calendar week 36/2020 to 22/2021, ongoing) including approx. 8500 centres, we estimate the number of SARS-CoV-2 infections in children and staff using random-effect-within-between (REWB) panel models for count data in the 2nd and 3rd wave.\n\nResultsCentres with a high proportion of children with low socioeconomic status (SES) have a higher risk of infections in staff and children. Strict contact restrictions between groups like fixed group assignments among children and fixed staff assignments to groups prevent infections. Both effects tend to be stronger in the 3rd wave.\n\nContributionECEC centres with a large proportion of children from a low SES background and lack of using fixed child/staff cohorts experience higher COVID-19 rates. Centres should be supported in maintaining recommended measures over the long run. Preventive measures such as vaccination of staff should be prioritised in centres with large proportions of low SES children.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Tanmay Dharmadhikari", - "author_inst": "CSIR - National Chemical Laboratory" + "author_name": "Franz Neuberger", + "author_inst": "German Youth Institute" }, { - "author_name": "Vinay Rajput", - "author_inst": "CSIR - National Chemical Laboratory" + "author_name": "Mariana Grgic", + "author_inst": "German Youth Institute" }, { - "author_name": "Rakeshkumar Yadav", - "author_inst": "CSIR - National Chemical Laboratory" + "author_name": "Svenja Diefenbacher", + "author_inst": "German Youth Institute" }, { - "author_name": "Radhika Boargaonkar", - "author_inst": "Ecosan Services Foundation" + "author_name": "Florian Spensberger", + "author_inst": "German Youth Institute" }, { - "author_name": "Dayanand Panse", - "author_inst": "Ecosan Services Foundation" + "author_name": "Ann-Sophie Lehfeld", + "author_inst": "Robert Koch-Institut" }, { - "author_name": "Sanjay Kamble", - "author_inst": "CSIR - National Chemical Laboratory" + "author_name": "Udo Buchholz", + "author_inst": "Robert Koch-Institut" }, { - "author_name": "Syed Dastager", - "author_inst": "CSIR - National Chemical Laboratory" + "author_name": "Walter Haas", + "author_inst": "Robert Koch-Institut" }, { - "author_name": "mahesh dharne", - "author_inst": "NATIONAL CHEMICAL LABORATORY" + "author_name": "Bernhard Kalicki", + "author_inst": "German Youth Institute" + }, + { + "author_name": "Susanne Kuger", + "author_inst": "German Youth Institute" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -698291,31 +697116,63 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.06.08.447365", - "rel_title": "Country-wide genomic surveillance of SARS-CoV-2 strains", + "rel_doi": "10.1101/2021.06.08.445535", + "rel_title": "SARS-CoV-2 B.1.617 Indian variants: are electrostatic potential changes responsible for a higher transmission rate?", "rel_date": "2021-06-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.08.447365", - "rel_abs": "Genomic surveillance has enabled the identification of several SARS-CoV-2 variants, allowing the formulation of appropriate public health policies. However, surveillance could be made more effective. We have determined that the time taken from strain collection to genome submission for over 1.7 million SARS-CoV-2 strains available at GISAID. We find that strain-wise, time lag in this process ranges from one day to over a year. Country-wise, the UK has taken a median of 16 days (for 417,287 genomes), India took 57 days (for 15,614 genomes), whereas Qatar spent 289 days (for 2298 genomes). We strongly emphasize that along with increasing the number of genomes of COVID-19 positive cases sequenced, their accelerated submission to GISAID should also be strongly encouraged and facilitated. This will enable researchers across the globe to track the spreading of variants in a timely manner; analyse their biology, epidemiology, and re-emerging infections; and define effective public health policies.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.08.445535", + "rel_abs": "Lineage B.1.617+, also known as G/452R.V3, is a recently described SARS-CoV-2 variant under investigation (VUI) firstly identified in October 2020 in India. As of May 2021, three sublineages labelled as B.1.617.1, B.1.617.2 and B.1.617.3 have been already identified, and their potential impact on the current pandemic is being studied. This variant has 13 amino acid changes, three in its spike protein, which are currently of particular concern: E484Q, L452R and P681R. Here we report a major effect of the mutations characterizing this lineage, represented by a marked alteration of the surface electrostatic potential (EP) of the Receptor Binding Domain (RBD) of the spike protein. Enhanced RBD-EP is particularly noticeable in the B.1.617.2 sublineage, which shows multiple replacements of neutral or negatively-charged amino acids with positively-charged amino acids. We here hypothesize that this EP change can favor the interaction between the B.1.617+RBD and the negatively-charged ACE2 thus conferring a potential increase in the virus transmission.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Kishan Kalia", - "author_inst": "Institute of Bioinformatics and Applied Biotechnology (IBAB), Bengaluru" + "author_name": "Stefano Pascarella", + "author_inst": "Universita di Roma La Sapienza" }, { - "author_name": "Gayatri Saberwal", - "author_inst": "Institute of Bioinformatics and Applied Biotechnology (IBAB), Bengaluru" + "author_name": "Massimo Ciccozzi", + "author_inst": "Campus Biomedical University of Rome" }, { - "author_name": "Gaurav Sharma", - "author_inst": "Institute of Bioinformatics and Applied Biotechnology (IBAB), Bengaluru" + "author_name": "Davide Zella", + "author_inst": "Institute of Human Virology- UNiversity of Maryland, Baltimore" + }, + { + "author_name": "Martina Bianchi", + "author_inst": "Universita di Roma la Sapienza" + }, + { + "author_name": "Francesca Benedetti", + "author_inst": "Institute of Human Virology" + }, + { + "author_name": "Francesco Broccolo", + "author_inst": "Universita Bicocca di Milano" + }, + { + "author_name": "Roberto Cauda", + "author_inst": "Universita Cattolica del Sacro Cuore, Rome, Italy" + }, + { + "author_name": "Arnaldo Caruso", + "author_inst": "Universita di Brescia" + }, + { + "author_name": "Silvia Angeletti", + "author_inst": "Policlinico Universitario Campus Biomedico, Rome, Italy" + }, + { + "author_name": "Marta Giovanetti", + "author_inst": "Fundacao Oswaldo Cruz" + }, + { + "author_name": "Antonio Cassone", + "author_inst": "University of Siena" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", - "category": "microbiology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.06.09.447527", @@ -700217,131 +699074,71 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.06.04.21258333", - "rel_title": "Introduction and transmission of SARS-CoV-2 B.1.1.7 in Denmark", + "rel_doi": "10.1101/2021.06.03.21258001", + "rel_title": "A Systematic Review and Meta-Analysis of the Mental Health Symptoms during the Covid-19 Pandemic in Southeast Asia", "rel_date": "2021-06-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.04.21258333", - "rel_abs": "In early 2021, the SARS-CoV-2 lineage B.1.1.7 became dominant across large parts of the world. In Denmark, comprehensive and real-time test, contact-tracing, and sequencing efforts were applied to sustain epidemic control. Here, we use these data to investigate the transmissibility, introduction, and onward transmission of B.1.1.7 in Denmark. In a period with stable restrictions, we estimated an increased B.1.1.7 transmissibility of 58% (95% CI: [56%,60%]) relative to other lineages. Epidemiological and phylogenetic analyses revealed that 37% of B.1.1.7 cases were related to the initial introduction in November 2020. Continuous introductions contributed substantially to case numbers, highlighting the benefit of balanced travel restrictions and self-isolation procedures coupled with comprehensive surveillance efforts, to sustain epidemic control in the face of emerging variants.", - "rel_num_authors": 28, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.03.21258001", + "rel_abs": "AimsThe Covid-19 pandemic has had a substantial impact on the mental health of the general public and high-risk groups worldwide. Due to its proximity and close links to China, Southeast Asia was one of the first regions to be affected by the outbreak. The aim of this systematic review was to evaluate the prevalence of anxiety, depression and insomnia in the general adult population and healthcare workers (HCWs) in Southeast Asia during the course of the first year of the pandemic.\n\nMethodsSeveral literature databases were systemically searched for articles published up to February 2021 and two reviewers independently evaluated all relevant studies using pre-determined criteria. The prevalence rates of mental health symptoms were calculated using a random-effect meta-analysis model.\n\nResultsIn total, 32 samples from 25 studies with 20,352 participants were included. Anxiety was assessed in all 25 studies and depression in 15 studies with pooled prevalence rates of 22% and 16% respectively. Only two studies assessed insomnia, which was estimated at 19%. The prevalence of anxiety and depression was similar amongst frontline HCWs (18%), general HCWs (17%), and students (20%) whilst being noticeably higher in the general population (27%).\n\nConclusionsThis is the first systematic review to investigate the mental health impact of the Covid-19 pandemic in Southeast Asia. A considerable proportion of the general population and HCWs reported mild to moderate symptoms of anxiety and depression; the pooled prevalence rater, however, remain significantly lower than those reported in other areas such as China and Europe.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Thomas Yssing Michaelsen", - "author_inst": "Department of Chemistry and Bioscience, Aalborg University; Aalborg, Denmark." - }, - { - "author_name": "Marc Bennedbaek", - "author_inst": "Centre of Excellence for Health, Immunity and Infection (CHIP), Department of Infectious Diseases, Rigshospitalet, University of Copenhagen; Copenhagen, Denmark" - }, - { - "author_name": "Lasse Engbo Christiansen", - "author_inst": "Department of Applied Mathematics and Computer Science, Technical University of Denmark; Lyngby, Denmark." - }, - { - "author_name": "Mia Sarah Fischer Jorgensen", - "author_inst": "Infectious Disease Epidemiology & Prevention, Statens Serum Institut; Copenhagen, Denmark." - }, - { - "author_name": "Camilla Holten Moller", - "author_inst": "Infectious Disease Preparedness, Statens Serum Institut; Copenhagen, Denmark." - }, - { - "author_name": "Emil Aarre Sorensen", - "author_inst": "Department of Chemistry and Bioscience, Aalborg University; Aalborg, Denmark." - }, - { - "author_name": "Simon Knutsson", - "author_inst": "Department of Chemistry and Bioscience, Aalborg University; Aalborg, Denmark." - }, - { - "author_name": "Jakob Brandt", - "author_inst": "Department of Chemistry and Bioscience, Aalborg University; Aalborg, Denmark." - }, - { - "author_name": "Thomas Bygh Nymann Jensen", - "author_inst": "Department of Chemistry and Bioscience, Aalborg University; Aalborg, Denmark." - }, - { - "author_name": "Clarisse Chiche-Lapierre", - "author_inst": "Department of Chemistry and Bioscience, Aalborg University; Aalborg, Denmark." - }, - { - "author_name": "Emilio Fuster Collados", - "author_inst": "Department of Chemistry and Bioscience, Aalborg University; Aalborg, Denmark." - }, - { - "author_name": "Trine Sorensen", - "author_inst": "Department of Chemistry and Bioscience, Aalborg University; Aalborg, Denmark." - }, - { - "author_name": "Celine Petersen", - "author_inst": "Department of Chemistry and Bioscience, Aalborg University; Aalborg, Denmark." - }, - { - "author_name": "Vang Le-Quy", - "author_inst": "Unit for Research Data Services (CLAAUDIA), Aalborg University; Aalborg, Denmark." - }, - { - "author_name": "Mantas Sereika", - "author_inst": "Department of Chemistry and Bioscience, Aalborg University; Aalborg, Denmark." - }, - { - "author_name": "Frederik Teilfeldt Hansen", - "author_inst": "Department of Chemistry and Bioscience, Aalborg University; Aalborg, Denmark." + "author_name": "Sofia Pappa", + "author_inst": "Division of Brain Sciences, Imperial College London, London" }, { - "author_name": "Morten Rasmussen", - "author_inst": "Department of Virus & Microbiological Special Diagnostics, Statens Serum Institut; Copenhagen, Denmark." + "author_name": "Jiyao Chen", + "author_inst": "Oregon State University" }, { - "author_name": "Jannik Fonager", - "author_inst": "Department of Virus & Microbiological Special Diagnostics, Statens Serum Institut; Copenhagen, Denmark." + "author_name": "Joshua Barnett", + "author_inst": "West London NHS Trust, London, United Kingdom" }, { - "author_name": "Soren Michael Karst", - "author_inst": "Department of Virus & Microbiological Special Diagnostics, Statens Serum Institut; Copenhagen, Denmark." + "author_name": "Anabel Chang", + "author_inst": "Department of Chemistry and Biochemistry, University of Oregon" }, { - "author_name": "Rasmus Lykke Marvig", - "author_inst": "Center for Genomic Medicine, Rigshospitalet; Copenhagen, Denmark" + "author_name": "Rebecca Kechen Dong", + "author_inst": "Business School, University of South Australia" }, { - "author_name": "Marc Stegger", - "author_inst": "Department of Bacteria, Parasites and Fungi, Statens Serum Institut; Copenhagen, Denmark" + "author_name": "Wen Xu", + "author_inst": "Nottingham University Business School China, University of Nottingham Ningbo China" }, { - "author_name": "Raphael Sieber", - "author_inst": "Department of Bacteria, Parasites and Fungi, Statens Serum Institut; Copenhagen, Denmark" + "author_name": "Allen Yin", + "author_inst": "School of Humanities, Southeast University, Nanjing, China" }, { - "author_name": "Robert Leo Skov", - "author_inst": "Infectious Disease Preparedness, Statens Serum Institut; Copenhagen, Denmark." + "author_name": "Bryan Z Chen", + "author_inst": "Crescent Valley High School, Corvallis" }, { - "author_name": "Rebecca Legarth", - "author_inst": "Infectious Disease Epidemiology & Prevention, Statens Serum Institut; Copenhagen, Denmark." + "author_name": "Andrew Delios", + "author_inst": "University of Adelaide, Australia" }, { - "author_name": "Tyra Grove Krause", - "author_inst": "Infectious Disease Preparedness, Statens Serum Institut; Copenhagen, Denmark." + "author_name": "Richard Z Chen", + "author_inst": "Crescent Valley High School" }, { - "author_name": "Anders Fomsgaard", - "author_inst": "Department of Virus & Microbiological Special Diagnostics, Statens Serum Institut; Copenhagen, Denmark." + "author_name": "Saylor Miller", + "author_inst": "College of Business, Oregon State University" }, { - "author_name": "- Danish Covid-19 Genome Consortium", - "author_inst": "" + "author_name": "Xue Wan", + "author_inst": "School of Economics and Management, Tongji University, Shanghai, China" }, { - "author_name": "Mads Albertsen", - "author_inst": "Department of Chemistry and Bioscience, Aalborg University; Aalborg, Denmark." + "author_name": "Stephen X. Zhang", + "author_inst": "University of Adelaide" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2021.06.05.21258407", @@ -701915,37 +700712,33 @@ "category": "hiv aids" }, { - "rel_doi": "10.1101/2021.06.03.21258315", - "rel_title": "Individual-based modeling of COVID-19 transmission in college communities", + "rel_doi": "10.1101/2021.06.03.21258330", + "rel_title": "Temporal association of reduced serum vitamin D with COVID-19 infection: A single-institution case-control and historical cohort study", "rel_date": "2021-06-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.03.21258315", - "rel_abs": "The ongoing COVID-19 pandemic has created major public health and socio-economic challenges across the United States. Among them are challenges to the educational system where college administrators are struggling with the questions of how to reopen in-person activities while prioritizing student safety. To help address this challenge, we developed a flexible computational framework to model the spread and control of COVID-19 on a residential college campus. The modeling framework accounts for heterogeneity in social interactions, activities, disease progression, and control interventions. The relative contribution of classroom, dorm, and social activities to disease transmission was explored. We observed that the dorm has the highest contribution to disease transmission followed by classroom and social activities. Without vaccination, frequent (weekly) random testing coupled with risk reduction measures (e.g. facial mask,) in classroom, dorm, and social activities is the most effective control strategy to mitigate the spread of COVID-19 on college campuses. Moreover, since random screening testing allows for the successful and early detection of both asymptomatic and symptomatic individuals, it successfully reduces the transmission rate such that the maximum quarantine capacity is far lower than expected to further reduce the economic burden caused from quarantine. With vaccination, herd immunity is estimated to be achievable by 50% to 80% immunity coverage. In the absence of herd immunity, simulations indicate that it is optimal to keep some level of transmission risk reduction measures in classroom, dorm, and social activities, while testing at a lower frequency. Though our quantitative results are likely provisional on our model assumptions, extensive sensitivity analysis confirms the robustness of their qualitative nature.\n\nHighlightsO_LIIndividual-based model for college communities with structured students interactions.\nC_LIO_LIWe evaluated COVID-19 control measures needed for in-person college reopening.\nC_LIO_LIWithout vaccination, high testing frequency is paramount for outbreak control.\nC_LIO_LIWith high vaccination coverage, some NPIs are still needed for outbreak control.\nC_LIO_LIGeneral access website tool was developed for the public to explore simulations.\nC_LI\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC=\"FIGDIR/small/21258315v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (42K):\norg.highwire.dtl.DTLVardef@4abed3org.highwire.dtl.DTLVardef@13639e0org.highwire.dtl.DTLVardef@111de45org.highwire.dtl.DTLVardef@1788a9_HPS_FORMAT_FIGEXP M_FIG Graphic Abstract\n\nC_FIG", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.03.21258330", + "rel_abs": "ObjectivesVitamin D supplementation has been proposed for the prevention and treatment of COVID-19, but the relationship between the two is inconclusive: Reduced serum vitamin D may predispose to COVID-19, but it may also be a secondary consequence of infection. The objective of this study was to assess the temporal association between serum vitamin D levels and COVID-19.\n\nDesignA single-institution case-control study and a historical cohort study\n\nSettingUniversity of California San Diego (UCSD) Health System in San Diego, California\n\nParticipantsPatients testing positive for COVID-19 from January 1, 2020 to September 30, 2020 with serum 25-hydroxy-vitamin D (25(OH)D) measured within 180 days of diagnosis. Patients were separated based on whether 25(OH)D was measured before (n=107; \"pre-diagnosis\") or after (n=203; \"post-diagnosis\") COVID-19 diagnosis. Subjects with 25(OH)D assessments prior to COVID-19 diagnosis were evaluated using a case-control study design, while subjects with 25(OH)D measured after COVID-19 diagnosis were analyzed with a historical cohort study design.\n\nPrimary and Secondary Outcome MeasuresIn the pre-diagnosis study, a conditional logistic regression was performed using COVID-19 infection status as the binary dependent variable. In the post-diagnosis study, an ordinary least squares regression was performed using serum 25(OH)D levels as the continuous dependent variable.\n\nResultsSerum 25(OH)D levels were not associated with the odds of subsequently testing positive for COVID-19 (OR 1.00, 95% CI: 0.98 to 1.02, p = 0.982). However, COVID-19 positive individuals had serum 25(OH)D measurements that were lower by 2.70 ng/mL (95% CI: -5.19 to -0.20, p = 0.034) compared to controls.\n\nConclusionsIn our study population, serum 25(OH)D levels were not associated with risk of testing positive for COVID-19 but were reduced in subjects after being diagnosed with COVID-19 infection. These results raise the possibility that reduced serum 25(OH)D may be a consequence and not a cause of COVID-19 infection.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Qimin Huang", - "author_inst": "Case Western Reserve University" - }, - { - "author_name": "Martial Ndeffo-Mbah", - "author_inst": "Texas A&M University" + "author_name": "Diviya Gupta", + "author_inst": "UCSD" }, { - "author_name": "Anirban Mondal", - "author_inst": "Case Western Reserve University" + "author_name": "Sahit Menon", + "author_inst": "UCSD" }, { - "author_name": "Sara Lee", - "author_inst": "Case Western Reserve University" + "author_name": "Michael H Criqui", + "author_inst": "UCSD" }, { - "author_name": "David Gurarie", - "author_inst": "Case Western Reserve University" + "author_name": "Bryan K Sun", + "author_inst": "UCSD" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -703633,51 +702426,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.03.21257996", - "rel_title": "Relation of vaccination with severity, oxygen requirement and outcome of COVID-19 infection in Chattogram, Bangladesh", + "rel_doi": "10.1101/2021.06.03.447023", + "rel_title": "Immunological profiling of COVID-19 patients with pulmonary sequelae", "rel_date": "2021-06-04", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.03.21257996", - "rel_abs": "IntroductionPeoples all around the world are waiting for vaccination against COVID -19 infection. In Bangladesh, Astra-Zeneca (AZ) vaccine was provided, but patients had infections of SARS-COV-2 even after vaccination. We focused on observing the severity, oxygen requirement and outcome of the COVID-19 infected patients who took the first dose or completed the immunization regimen.\n\nMethodsThis is an observational study done among 174 COVID-19 patients from three COVID-19 dedicated hospitals of Chattogram, Bangladesh, who took AZ vaccines 1st dose or completed the schedule. All patients were Real-Time Reverse Transcription Polymerase Chain Reaction (rRT-PCR) positive for COVID-19. Patients were enrolled after receiving written informed consent. Suspected cases or unwilling patients were excluded from the study. Ethical approval was granted by the CMOSH-ERB. SPSS-20 was used to analyze the information gathered.\n\nResultsAmong 174 vaccinated patients, 55(31.61%) completed the vaccination schedule, and 119(68.39%) took their 1st dose of the COVID-19 vaccine. Gender distributions revealed 67(38.5%) female and 107(61.5%) male got the vaccine, and 55 patients completed the full two doses, and 119 patients took the 1st dose. Most of the patients were 40 years and above. In the completed vaccination group, 33(60.0%) out of 55 in and in the first dose vaccinated group, 75(63.0%) out of 119 had a mild COVID-19, and severe and critical cases were found very minimum. Among the patients who have completed the vaccination, 32(58.2%) needed no oxygen, and who was given the first dose, 78(65%) needed no oxygen. No death occurred who completed the vaccine, and 3(2.5%) patients died who took 1st dose of the vaccine.\n\nConclusionVaccine provided in Bangladesh to the people so far seems safe and effective. Severe and critical COVID-19 is low, and the need for oxygen to admitted patients is less, and the death rate is minimal.", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.03.447023", + "rel_abs": "Cellular immunity may be involved in organ damage and rehabilitation in patients with coronavirus disease 2019 (COVID-19). We aimed to delineate immunological features of COVID-19 patients with pulmonary sequelae (PS) one year after discharge. 50 COVID-19 survivors were recruited and classified according to radiological characteristics: 24 patients with PS and 26 patients without PS. Phenotypic and functional characteristics of immune cells were evaluated by multiparametric flow cytometry. Patients with PS had an increased proportion of natural killer (NK) cells and lower percentage of B cells compared to patients without PS. Phenotypic and functional features of T cells in patients with PS were predominated by the accumulation of CD4+ T cells secreting IL-17A, short-lived effector-like CD8+ T cells (CD27-CD62L-) and senescent T cells with excessive secretion of granzyme-B/perforin/IFN-{gamma}. NK cells were characterized by the excessive secretion of granzyme-B and perforin and the downregulation of NKP30 and NKP46; highly activated NKT and {gamma}{delta} T cells exhibited NKP30 and TIM-3 upregulation and NKB1 downregulation in patients with PS. However, immunosuppressive cells were comparable between the two groups. The interrelation of immune cells in COVID-19 was intrinsically identified, whereby T cells secreting IL-2, IL-4 and IL-17A were enriched among CD28+ and CD57-cells and cells secreting perforin/granzyme-B/IFN-{gamma}/TNF- expressed markers of terminal differentiation. CD57+NK cells, CD4+perforin+ T cells and CD8+CD27+CD62L+ T cells were identified as the independent predictors for residual lesions. Overall, our findings unveil the profound imbalance of immune landscape that may correlate with organ damage and rehabilitation in COVID-19.\n\nIMPORTANCEA considerable proportion of COVID-19 survivors have residual lung lesions, such as ground glass opacity and fiber streak shadow. To determine the relationship between host immunity and residual lung lesions, we performed an extensive analysis of immune responses in convalescent patients with COVID-19 one year after discharge. We found significant differences in immunological characteristics between patients with pulmonary sequelae and patients without pulmonary sequelae one year after discharge. Our study highlights the profound imbalance of immune landscape in the COVID-19 patients with pulmonary sequelae, characterized by the robust activation of cytotoxic T cells, NK cells and {gamma}{delta} T cells as well as the deficiencies of immunosuppressive cells. Importantly, CD57+NK cells, CD4+perforin+ T cells and CD8+CD27+CD62L+ T cells were identified as the independent predictors for residual lesions.", "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Shuva Das", - "author_inst": "Chittagong Medical College" + "author_name": "Jianghua Wu", + "author_inst": "Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Nadia Islam Tumpa", - "author_inst": "Chittagong Medical College" + "author_name": "Lu Tang", + "author_inst": "Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Ayesha Ahmed Khan", - "author_inst": "Chittagong Medical College" + "author_name": "Yanling Ma", + "author_inst": "Department of Respiratory and Critical Care Medicine,Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Md Minhazul Hoque", - "author_inst": "250 Bedded Chattogram General Hospital" + "author_name": "Yu Li", + "author_inst": "Department of Respiratory and Critical Care Medicine,Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Md Ehsanul Hoque", - "author_inst": "National Institute of Laboratory Medicine and Referral Centre" + "author_name": "Dong-Mei Zhang", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Safatuj Jahan", - "author_inst": "CMOSHMC" + "author_name": "Qian Li", + "author_inst": "Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Kazi Farhad Ahmed", - "author_inst": "CMOSHMC" + "author_name": "Heng Mei", + "author_inst": "Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Rajat Sanker Roy Biswas", - "author_inst": "CMOSHMC" + "author_name": "Yu Hu", + "author_inst": "Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" } ], "version": "1", - "license": "cc_by_nc", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.06.03.446942", @@ -705375,247 +704168,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.01.21257987", - "rel_title": "Prevention and Attenuation of COVID-19 by BNT162b2 and mRNA-1273 Vaccines", + "rel_doi": "10.1101/2021.05.31.21258062", + "rel_title": "Job stress and loneliness among remote workers", "rel_date": "2021-06-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.01.21257987", - "rel_abs": "BACKGROUNDInformation is limited on messenger RNA (mRNA) BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) COVID-19 vaccine effectiveness (VE) in preventing SARS-CoV-2 infection or attenuating disease when administered in real-world conditions.\n\nMETHODSProspective cohorts of 3,975 healthcare personnel, first responders, and other essential and frontline workers completed weekly SARS-CoV-2 testing during December 14 2020--April 10 2021. Self-collected mid-turbinate nasal swabs were tested by qualitative and quantitative reverse-transcription-polymerase-chain-reaction (RT-PCR). VE was calculated as 100%x(1-hazard ratio); adjusted VE was calculated using vaccination propensity weights and adjustments for site, occupation, and local virus circulation.\n\nRESULTSSARS-CoV-2 was detected in 204 (5.1%) participants; 16 were partially ([≥]14 days post-dose-1 to 13 days after dose-2) or fully ([≥]14 days post-dose-2) vaccinated, and 156 were unvaccinated; 32 with indeterminate status (<14 days after dose-1) were excluded. Adjusted mRNA VE of full vaccination was 91% (95% confidence interval [CI]=76%-97%) against symptomatic or asymptomatic SARS-CoV-2 infection; VE of partial vaccination was 81% (95% CI=64%-90%). Among partially or fully vaccinated participants with SARS-CoV-2 infection, mean viral RNA load (Log10 copies/mL) was 40% lower (95% CI=16%-57%), the risk of self-reported febrile COVID-19 was 58% lower (Risk Ratio=0.42, 95% CI=0.18-0.98), and 2.3 fewer days (95% CI=0.8-3.7) were spent sick in bed compared to unvaccinated infected participants.\n\nCONCLUSIONSAuthorized mRNA vaccines were highly effective among working-age adults in preventing SARS-CoV-2 infections when administered in real-world conditions and attenuated viral RNA load, febrile symptoms, and illness duration among those with breakthrough infection despite vaccination.", - "rel_num_authors": 57, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.31.21258062", + "rel_abs": "BackgroundTo prevent the spread of coronavirus disease 2019 (COVID-19), physical distancing and isolation are crucial strategies in society. However, this response to the pandemic promotes loneliness. Previous studies have reported an increase in loneliness since the outbreak of COVID-19, but there is little evidence on the relationship between job stress and loneliness among remote workers.\n\nAimsTo assess the relationship between job stress and loneliness among remote workers.\n\nMethodsThis study is a part of nation-wide cross-sectional online survey evaluating the impact of the COVID-19 pandemic in Japan. A total of 27,036 full-time workers completed the self-administrated questionnaire in December 2020. We extracted data on 4,052 desk workers who indicated that they were doing remote work. Loneliness was assessed using a single question and job stress was measured using the Job Content Questionnaire. Multiple logistic regression was performed.\n\nResultsFrequency of remote work was moderately associated with loneliness (adjusted odds ratio [AOR] = 1.60, 95% confidence interval [CI]: 1.04-2.46, P = 0.033). Participants who reported of having a low level of co-worker or supervisor support had greater odds of feeling lonely than those who were highly supported (co-worker support: AOR = 4.06, 95% CI: 2.82-5.84, P <0.001; supervisor support: AOR = 2.49, 95% CI: 1.79-3.47, P <0.001).\n\nConclusionsCo-worker support and supervisor support were strongly associated with loneliness, whereas frequency of remote work was moderately associated with feeling lonely. Support from co-workers and supervisors may be crucial factors to prevent loneliness caused by remote work.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Mark G Thompson", - "author_inst": "CDC" - }, - { - "author_name": "Jefferey L Burgess", - "author_inst": "Mel and Enid Zuckerman College of Public Health, University of Arizona" - }, - { - "author_name": "Allison Naleway", - "author_inst": "Kaiser Permanente Northwest Center of Health Research" - }, - { - "author_name": "Harmony Tyner", - "author_inst": "St. Luke's" - }, - { - "author_name": "Sarang K Yoon", - "author_inst": "University of Utah" - }, - { - "author_name": "Jennifer Meece", - "author_inst": "Marshfield Clinic" - }, - { - "author_name": "Lauren E.W. Olsho", - "author_inst": "Abt Associates" - }, - { - "author_name": "Alberto Caban-Martinez", - "author_inst": "University of Miami, Miller School of Medicine" - }, - { - "author_name": "Ashley L Fowlkes", - "author_inst": "CDC" - }, - { - "author_name": "Karen Lutrick", - "author_inst": "Mel and Enid Zuckerman College of Public Health, University of Arizona" - }, - { - "author_name": "Holly C Groom", - "author_inst": "Kaiser Permanente Northwest Center of Health Research" - }, - { - "author_name": "Kayan Dunnigan", - "author_inst": "Baylor Scott White Health" - }, - { - "author_name": "Marilyn J Odean", - "author_inst": "Whiteside Institute for Clinical Research, St. Luke's" - }, - { - "author_name": "Kurt Hegmann", - "author_inst": "University of Utah" - }, - { - "author_name": "Elisha Stefanski", - "author_inst": "Marshfield Clinic" - }, - { - "author_name": "Laura J Edwards", - "author_inst": "Abt Associates" - }, - { - "author_name": "Natasha Schaefer-Solle", - "author_inst": "Leonard M Miller School of Medicine, University of Miami" - }, - { - "author_name": "Lauren Grant", - "author_inst": "CDC" - }, - { - "author_name": "Katherine Ellingson", - "author_inst": "Mel and Enid Zuckerman College of Public Health, University of Arizona" - }, - { - "author_name": "Jennifer L Kuntz", - "author_inst": "Kaiser Permanente Northwest Center of Health Research" - }, - { - "author_name": "Tnelda Zunie", - "author_inst": "Baylor Scott & White Health" - }, - { - "author_name": "Matthew S Thiese", - "author_inst": "University of Utah" - }, - { - "author_name": "Lynn Ivacic", - "author_inst": "Marshfield Clinic" - }, - { - "author_name": "Meredith G Wesley", - "author_inst": "Abt Associates" - }, - { - "author_name": "Julie Mayo Lamberte", - "author_inst": "CDC" - }, - { - "author_name": "Xiaxiao Sun", - "author_inst": "Mel and Enid Zuckerman College of Public Health, University of Arizona" - }, - { - "author_name": "Michael E Smith", - "author_inst": "Baylor Scott & White Health" - }, - { - "author_name": "Andrew L Phillips", - "author_inst": "University of Utah" - }, - { - "author_name": "Kimberly D Groover", - "author_inst": "Abt Associates" - }, - { - "author_name": "Young M Yoo", - "author_inst": "CDC" - }, - { - "author_name": "Joe K Gerald", - "author_inst": "Mel and Enid Zuckerman College of Public Health, University of Arizona" - }, - { - "author_name": "Rachel T Brown", - "author_inst": "University of Utah" - }, - { - "author_name": "Meghan K Herring", - "author_inst": "Abt Associates" - }, - { - "author_name": "Gregory Joseph", - "author_inst": "CDC" - }, - { - "author_name": "Shawn Beitel", - "author_inst": "Mel and Enid Zuckerman College of Public Health, University of Arizona" - }, - { - "author_name": "Tyler C Morrill", - "author_inst": "Abt Associates" - }, - { - "author_name": "Josephine Mak", - "author_inst": "CDC" - }, - { - "author_name": "Patrick Rivers", - "author_inst": "Mel and Enid Zuckerman College of Public Health, University of Arizona" - }, - { - "author_name": "Brandon P Poe", - "author_inst": "Abt Associates" - }, - { - "author_name": "Brian Lynch", - "author_inst": "CDC" - }, - { - "author_name": "Ying Tao Zhou", - "author_inst": "CDC" - }, - { - "author_name": "Jing Zhang", - "author_inst": "CDC" - }, - { - "author_name": "Anna Kelleher", - "author_inst": "CDC" - }, - { - "author_name": "Yan Li", - "author_inst": "CDC" - }, - { - "author_name": "Monica E. Dickerson", - "author_inst": "CDC" - }, - { - "author_name": "Erika Hanson", - "author_inst": "Wisconsin State Lab of Hygiene" - }, - { - "author_name": "Kyley Guenther", - "author_inst": "Wisconsin State Lab of Hygiene" - }, - { - "author_name": "Suxiang Tong", - "author_inst": "CDC" - }, - { - "author_name": "Allen Bateman", - "author_inst": "Wisconsin State Lab of Hygiene" + "author_name": "Fuyu Miyake", + "author_inst": "University of Occupational and Environmental Health, Japan" }, { - "author_name": "Erik Reisdorf", - "author_inst": "Wisconsin State Lab of Hygiene" + "author_name": "Chimed-Ochir Odgerel", + "author_inst": "University of Occupational and Environmental Health, Japan" }, { - "author_name": "John R Barnes", - "author_inst": "CDC" + "author_name": "Ayako Hino", + "author_inst": "University of Occupational and Environmental Health, Japan" }, { - "author_name": "Eduardo Azziz-Baumgartner", - "author_inst": "CDC" + "author_name": "Kazunori Ikegami", + "author_inst": "University of Occupational and Environmental Health, Japan" }, { - "author_name": "Danielle R Hunt", - "author_inst": "Abt Associates" + "author_name": "Tomohisa Nagata", + "author_inst": "University of Occupational and Environmental Health, Japan" }, { - "author_name": "Melissa L Arvay", - "author_inst": "CDC" + "author_name": "Seiichiro Tateishi", + "author_inst": "University of Occupational and Environmental Health, Japan" }, { - "author_name": "Preeta Kutty", - "author_inst": "CDC" + "author_name": "Mayumi Tsuji", + "author_inst": "University of Occupational and Environmental Health, Japan" }, { - "author_name": "Alicia M Fry", - "author_inst": "CDC" + "author_name": "Shinya Matsuda", + "author_inst": "University of Occupational and Environmental Health, Japan" }, { - "author_name": "Manjusha Gaglani", - "author_inst": "Baylor Scott & White Health" + "author_name": "Tomohiro Ishimaru", + "author_inst": "University of Occupational and Environmental Health, Japan" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2021.06.01.21258172", @@ -707577,27 +706178,47 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2021.05.26.21257598", - "rel_title": "The Impact of COVID-19 Lockdowns on Mental Health Patient Populations: Evidence from Medical Claims Data", + "rel_doi": "10.1101/2021.06.02.21258209", + "rel_title": "CorCast: A Distributed Architecture for Bayesian Epidemic Nowcasting and its Application to District-Level SARS-CoV-2 Infection Numbers in Germany", "rel_date": "2021-06-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.26.21257598", - "rel_abs": "BackgroundSocial distancing policies were enacted during March 2020 to limit the spread of COVID-19. Lockdowns and movement restrictions increased the potential of negative impact on population mental health, in which depression and anxiety symptoms were frequently reported by different population groups during COVID-19 lockdown. However, the causal relationship of mitigation policies on national-wide mental health resource usage is lacking.\n\nObjectiveThis study investigates the effect of COVID-19 mitigation measures on mental health across the United States, on county and state levels. It examines the effect on mental health facility usage and the prevalence of mental illnesses on the total population, different age and gender groups, and patients of selected mental health diagnoses.\n\nMethodsWe used large-scale medical claims data for mental health patients dated from September 1, 2019 to December 31, 2020, with publicly available state- and county-specific COVID-19 cases from first case in January to December 31, 2020, and used publicly available lockdown dates for states and counties. We designed a difference-in-differences (DID) model, which infers the causal effect of a policy intervention by comparing pre-policy and post-policy periods in different regions. We mainly focused on two types of social distancing policies, stay-at-home and school closure orders.\n\nResultsBased on common pre-treatment trend assumption of regions, we find that lockdown has significantly and causally increased the usage of mental health in regions with lockdowns in comparison to regions without. In regions with lockdown orders the resource usage increased by 18% compared to 1% decline in regions without a lockdown. Also, female populations have been exposed to a larger lockdown effect on their mental health with 24% increase in regions with lockdowns compared to 3% increase in regions without. While male mental health patients decreased by 5% in regions without lockdowns. Patients diagnosed with panic disorders and reaction to severe stress both were significantly exposed to a significant large effect of lockdowns. Also, life management difficulty patients doubled in regions with stay-at-home orders but increased less with school closures. Contrarily, attention-deficit hyperactivity patients declined in regions without stay-at-home orders. Patients older than 80 used mental health resources less in regions with lockdowns. Adults between (21 - 40) years old were exposed to the greatest lockdown effect with increase between 20% to 30% in regions with lockdown.\n\nConclusionAlthough non-pharmaceutical intervention policies were effective in containing the spread of COVID-19, our results show that mitigation policies led to population-wide increase in mental health patients. Our results suggest the need for greater mental health treatment resources in the face of lockdown policies.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.02.21258209", + "rel_abs": "Timely information on current infection numbers during an epidemic is of crucial importance for decision makers in politics, medicine, and businesses. As information about local infection risk can guide public policy as well as individual behavior, such as the wearing of personal protective equipment or voluntary social distancing, statistical models providing such insights should be transparent and reproducible as well as accurate. Fulfilling these requirements is drastically complicated by the large amounts of data generated during exponential growth of infection numbers, and by the complexity of common inference pipelines. Here, we present CorCast - a stable and scalable distributed architecture for the reproducible estimation of nowcasts suitable for pandemic scenarios - and its application to the inference of district-level SARS-CoV-2 infection numbers in Germany.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Ibtihal Ferwana", - "author_inst": "University of Illinois Urbana Champaign" + "author_name": "Anna-Katharina Hildebrandt", + "author_inst": "MONDATA GmbH" }, { - "author_name": "Lav R. Varshney", - "author_inst": "University of Illinois Urbana-Champaign" + "author_name": "Konstantin Bob", + "author_inst": "Johannes Gutenberg University" + }, + { + "author_name": "David Teschner", + "author_inst": "Johannes Gutenberg University" + }, + { + "author_name": "Thomas Kemmer", + "author_inst": "Johannes Gutenberg University" + }, + { + "author_name": "Jennifer Leclaire", + "author_inst": "Johannes Gutenberg University" + }, + { + "author_name": "Bertil Schmidt", + "author_inst": "Johannes Gutenberg University" + }, + { + "author_name": "Andreas Hildebrandt", + "author_inst": "Johannes Gutenberg University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "health informatics" }, { "rel_doi": "10.1101/2021.05.29.21258010", @@ -709367,27 +707988,51 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.29.21258041", - "rel_title": "Forecasting COVID-19 Number of Cases by Implementing ARIMA and SARIMA with Grid Search in the United States", + "rel_doi": "10.1101/2021.05.31.21258018", + "rel_title": "Mechanistic modeling of SARS-CoV-2 immune memory, variants, and vaccines", "rel_date": "2021-06-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.29.21258041", - "rel_abs": "COVID-19 has surged in the United States since January 2020. Since then, social distancing and lockdown have helped many people to avoid infectious diseases. However, this did not help the upswing of the number of cases after the lockdown was finished. Modeling the infectious disease can help the health care providers and governors to plan ahead for obtain the needed resources. In this manner, precise short-term determining of the number of cases can be imperative to the healthcare system. Many models have been used since the pandemic has started. In this paper we will compare couple of time series models like Simple Moving Average, Exponentially Weighted Moving Average, Holt-Winters Double Exponential Smoothing Additive, ARIMA, and SARIMA. Two models that have been used to predict the number of cases are ARIMA and SARIMA. A grid search has been implemented to select the best combination of the parameters for both models. Results show that in the case of modeling, the Holt-Winters Double Exponential model outperforms Exponentially Weighted Moving Average and Simple Moving Average while forecasting ARIMA outperforms SARIMA.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.31.21258018", + "rel_abs": "The functional relationship between neutralizing antibodies (NAbs) and protection against SARS-CoV-2 infection and disease remains unclear. We jointly estimated protection against infection and disease progression following natural infection and vaccination from meta-study data. We find that NAbs are strongly correlated with prevention of infection and that any history of NAbs will stimulate immune memory to moderate disease progression. We also find that natural infection provides stronger protection than vaccination for the same level of NAbs, noting that infection itself, unlike vaccination, carries risk of morbidity and mortality, and that our most potent vaccines induce much higher NAb levels than natural infection. These results suggest that while sterilizing immunity may decay, we expect protection against severe disease to be robust over time and in the face of immune-evading variants.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Saina Abolmaali", - "author_inst": "Auburn University" + "author_name": "Jamie A Cohen", + "author_inst": "Institute for Disease Modeling" + }, + { + "author_name": "Robyn Margaret Stuart", + "author_inst": "University of Copenhagen" + }, + { + "author_name": "Katherine Rosenfeld", + "author_inst": "Institute for Disease Modeling" + }, + { + "author_name": "Hil Lyons", + "author_inst": "Institute for Disease Modeling" + }, + { + "author_name": "Michael White", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Cliff Kerr", + "author_inst": "Institute for Disease Modeling" + }, + { + "author_name": "Daniel J Klein", + "author_inst": "Institute for Disease Modeling" }, { - "author_name": "Samira Shirzaei", - "author_inst": "Auburn university" + "author_name": "Michael Famulare", + "author_inst": "Institute for Disease Modeling" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.05.28.21258008", @@ -710785,71 +709430,35 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.28.21257989", - "rel_title": "UV-A and UV-B Can Neutralize SARS-CoV-2 Infectivity", + "rel_doi": "10.1101/2021.05.28.21258012", + "rel_title": "Observational Study on 255 Mechanically Ventilated Covid Patients at the Beginning of the USA Pandemic", "rel_date": "2021-05-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.28.21257989", - "rel_abs": "We performed an in-depth analysis of the virucidal effect of discrete wavelengths: UV-C (278 nm), UV-B (308 nm), UV-A (366 nm) and violet (405 nm) on SARS-CoV-2. By using a highly infectious titer of SARS-CoV-2 we observed that the violet light-dose resulting in a 2-log viral inactivation is only 10-4 times less efficient than UV-C light. Moreover, by qPCR and fluorescence in situ hybridization (FISH) approach we verified that the viral titer typically found in the sputum of COVID-19 patients can be completely inactivated by the long UV-wavelengths corresponding to UV-A and UV-B solar irradiation. The comparison of the UV action spectrum on SARS-CoV-2 to previous results obtained on other pathogens suggests that RNA viruses might be particularly sensitive to long UV wavelengths. Our data extend previous results showing that SARS-CoV-2 is highly susceptible to UV light and offer an explanation to the reduced incidence of SARS-CoV-2 infection seen in the summer season.\n\nSYNOPSISUV-A, UV-B and violet wavelengths kill SARS-CoV-2, supporting the sterilizing effects of the solar pump on human pathogens and the explanation of the seasonality of the COVID-19 pandemic.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.28.21258012", + "rel_abs": "IntroductionThis observational study looked at 255 COVID19 patients who required invasive mechanical ventilation (IMV) during the first two months of the US pandemic. Through comprehensive, longitudinal evaluation and new consideration of all the data, we were able to better describe and understand factors affecting outcome after intubation.\n\nMethodsAll vital signs, laboratory values, and medication administrations (time, date, dose, and route) were collected and organized. Further, each patients prior medical records, including PBM data and available ECG, were reviewed by a physician. These data were incorporated into time-series database for statistical analysis.\n\nResultsBy discharge or Day 90, 78.2% of the cohort expired. The most common pre-existing conditions were hypertension, (63.5%), diabetes (59.2%) and obesity (50.4%). Age correlated with death. Comorbidities and clinical status on presentation were not predictive of outcome. Admission markers of inflammation were universally elevated (>96%). The cohorts weight range was nearly 7-fold. Causal modeling establishes that weight-adjusted HCQ and AZM therapy improves survival by over 100%. QTc prolongation did not correlate with cumulative HCQ dose or HCQ serum levels.\n\nDiscussionThis detailed approach gives us better understanding of risk factors, prognostic indicators, and outcomes of Covid patients needing IMV. Few variables were related to outcome. By considering more factors and using new methods, we found that when increased doses of co-administered HCQ and AZM were associated with >100% increase in survival. Comparison of absolute with weight-adjusted cumulative doses proves administration [≥]80 mg/kg of HCQ with > 1 gm AZM increases survival in IMV-requiring Covid patients by over 100%. According to our data, HCQ is not associated with prolongation. Studies, which reported QTc prolongation secondary to HCQ, need to be re-evaluated more stringently and with controls.\n\nThe weight ranges of Covid patient cohorts are substantially greater than those of most antibiotic RCTs. Future clinical trials need to consider the weight variance of hospitalized Covid patients and need to study therapeutics more thoughtfully.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Mara Biasin", - "author_inst": "Dipartimento di Scienze Biomediche e Cliniche L. Sacco, University of Milan, Italy" - }, - { - "author_name": "Sergio Strizzi", - "author_inst": "Dipartimento di Scienze Biomediche e Cliniche L. Sacco, University of Milan, Italy" - }, - { - "author_name": "Andrea Bianco", - "author_inst": "Istituto Nazionale di Astrofisica (INAF), Osservatorio Astronomico di Brera, Milano/Merate, Italy" - }, - { - "author_name": "Alberto Macchi", - "author_inst": "Istituto Nazionale di AstroFisica (INAF), Osservatorio Astronomico di Brera, Milano/Merate, Italy" - }, - { - "author_name": "Olga Utyro", - "author_inst": "Department of Biomedical and Clinical Sciences L. Sacco, University of Milan, Milan, Italy." - }, - { - "author_name": "Giovanni Pareschi", - "author_inst": "Italian National Institute for Astrophysics (INAF), Brera Astronomical Observatory, Milano/ Merate, Italy" - }, - { - "author_name": "Alessia Loffreda", - "author_inst": "Experimental Imaging Center, IRCCS Ospedale San Raffaele, Milan, Italy" + "author_name": "Leon G Smith", + "author_inst": "Smith Center For Infectious Diseases and Urban Health" }, { - "author_name": "Adalberto Cavalleri", - "author_inst": "Epidemiology and Prevention Unit, IRCCS Foundation, Istituto Nazionale dei Tumori, Milan, Italy" - }, - { - "author_name": "Manuela Lualdi", - "author_inst": "Department of Imaging Diagnostic and Radioterapy, IRCCS Foundation, Istituto Nazionale dei Tumori, Milan, Italy" - }, - { - "author_name": "Daria Trabattoni", - "author_inst": "Department of Biomedical and Clinical Sciences L. Sacco, University of Milan, Milan, Italy" - }, - { - "author_name": "Carlo Tacchetti", - "author_inst": "Experimental Imaging Center, IRCCS Ospedale San Raffaele, Milan, Italy" + "author_name": "Nicolas Mendoza", + "author_inst": "Smith Center For Infectious Diseases and Urban Health" }, { - "author_name": "Davide Mazza", - "author_inst": "Experimental Imaging Center, IRCCS Ospedale San Raffaele, Milan, Italy." + "author_name": "Stephen Smith", + "author_inst": "Smith Center For Infectious Diseases and Urban Health" }, { - "author_name": "Mario Salvatore Clerici", - "author_inst": "Department of Pathophysiology and Transplantation, University of Milano and Fondazione Don Gnocchi" + "author_name": "David P Dobesh", + "author_inst": "Saint Barnabas Medical Center" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pharmacology and therapeutics" }, { "rel_doi": "10.1101/2021.05.28.21257993", @@ -712382,85 +710991,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.26.21257548", - "rel_title": "Clinical Evaluation of In House Produced 3D Printed Nasopharyngeal Swabs for COVID-19 Testing", + "rel_doi": "10.1101/2021.05.26.21257798", + "rel_title": "MALDI-ToF Protein Profiling as Potential Rapid Diagnostic Platform for COVID-19", "rel_date": "2021-05-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.26.21257548", - "rel_abs": "3D printed alternatives to standard flocked swabs were rapidly developed to provide a response to the unprecedented and sudden need for an exponentially growing amounts of diagnostic tools to fight the pandemics of COVID-19. In light of the anticipated shortage, an hospital-based 3D printing platform was implemented in our institution for the production of swabs for nasopharyngeal and oropharyngeal sampling based on the freely available open-sourced design made available to the community by University of South Floridas Health Radiology and Northwell Health System teams as replacement for locally used commercial swabs. Validation of our 3D printed swabs was performed by a head-to-head diagnostic accuracy study of the 3D printed \"Northwell model\" with the cobas PCR Media swabs sample kit. We observed an excellent concordance (total agreement 96.8%, Kappa 0.936) in results obtained with the 3D printed and flocked swabs indicating that the in-house 3D printed swab can be used reliably in a context of shortage of flocked swabs. To our knowledge, this is the first study to report on autonomous hospital-based production and clinical validation of 3D printed swabs.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.26.21257798", + "rel_abs": "More than a year after the COVID-19 pandemic has been declared, the need still exists for accurate, rapid, inexpensive and non-invasive diagnostic methods that yield high specificity and sensitivity towards the current and newly emerging SARS-CoV-2 strains. Several studies have since established saliva as a more amenable specimen type for early detection of SARS-CoV-2 as compared to nasopharyngeal swabs. Considering the limitations and high demand for COVID-19 testing, we employed MALDI-ToF mass spectrometry for the analysis of 60 gargle samples from human donors and compared the spectra with their COVID-19 status. Several standards including isolated human serum immunoglobulins and controls such as pre-COVID-19 saliva and heat inactivated SARS-CoV-2 virus were simultaneously analyzed to provide a relative view of the saliva and viral proteome as they would appear in this works methodology. Five potential biomarker peaks were established that demonstrated high concordance with COVID-19 positive individuals. Overall, the agreement of these results with RT-qPCR testing on NP swabs was no less than 90% for the studied cohort, which consisted of young and largely asymptomatic student athletes. From a clinical standpoint, the results from this pilot study are promising and suggest that MALDI-ToF can be used to develop a relatively rapid and inexpensive COVID-19 assay.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Simon Grandjean Lapierre", - "author_inst": "Universit\u00e9 de Montr\u00e9al" - }, - { - "author_name": "Stephane Bedwani", - "author_inst": "CRCHUM" - }, - { - "author_name": "Fran\u00e7ois Deblois", - "author_inst": "CRCHUM" - }, - { - "author_name": "Audray Fortin", - "author_inst": "CRCHUM" - }, - { - "author_name": "Natalia Zamorano Cuervo", - "author_inst": "Universit\u00e9 de Montr\u00e9al" - }, - { - "author_name": "Karim Zerouali", - "author_inst": "CRCHUM" - }, - { - "author_name": "Elise Caron", - "author_inst": "CRCHUM" - }, - { - "author_name": "Philippe Morency Potvin", - "author_inst": "CRCHUM" - }, - { - "author_name": "Simon Gagnon", - "author_inst": "Centre hospitalier de l'Universit\u00e9 de Montr\u00e9al" - }, - { - "author_name": "Nakome Nguissan", - "author_inst": "Centre hospitalier de l'Universit\u00e9 de Montr\u00e9al" - }, - { - "author_name": "Pascale Arlotto", - "author_inst": "Centre hospitalier de l'Universit\u00e9 de Montr\u00e9al" + "author_name": "Prajkta Chivte", + "author_inst": "Northern Illinois University" }, { - "author_name": "Isabelle Hardy", - "author_inst": "Hopital Notre-Dame CHUM" + "author_name": "Zane LaCasse", + "author_inst": "Northern Illinois University" }, { - "author_name": "Catherine-Audrey Boutin", - "author_inst": "CRCHUM" + "author_name": "Ventaka Devesh Reddy Seethi", + "author_inst": "Northern Illinois University" }, { - "author_name": "Cecile Tremblay", - "author_inst": "CRCHUM" + "author_name": "Pratool Bharti", + "author_inst": "Northern Illinois University" }, { - "author_name": "Francois Coutlee", - "author_inst": "Centre Hospitalier de l'Universit\u00e9 de Montr\u00e9al (CHUM)" + "author_name": "Joshua Bland", + "author_inst": "University of Illinois at Chicago" }, { - "author_name": "Jacques de Guise", - "author_inst": "CRCHUM" + "author_name": "Shrihari S. Kadkol", + "author_inst": "University of Illinois at Chicago" }, { - "author_name": "Nathalie Grandvaux", - "author_inst": "CRCHUM" + "author_name": "Elizabeth R. Gaillard", + "author_inst": "Northern Illinois University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -714184,53 +712753,37 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2021.05.28.446009", - "rel_title": "Combination of a Sindbis-SARS-CoV-2 spike vaccine and \u03b1OX40 antibody elicits protective immunity against SARS-CoV-2 induced disease and potentiates long-term SARS-CoV-2-specific humoral and T-cell immunity", + "rel_doi": "10.1101/2021.05.27.445991", + "rel_title": "Metformin Suppresses Monocyte Immunometabolic Activation by SARS-CoV-2 and Spike Protein Subunit 1", "rel_date": "2021-05-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.28.446009", - "rel_abs": "The COVID-19 pandemic caused by the coronavirus SARS-CoV-2 is a major global public threat. Currently, a worldwide effort has been mounted to generate billions of effective SARS-CoV-2 vaccine doses to immunize the worlds population at record speeds. However, there is still demand for alternative effective vaccines that rapidly confer long-term protection and rely upon cost-effective, easily scaled-up manufacturing. Here, we present a Sindbis alphavirus vector (SV), transiently expressing the SARS-CoV-2 spike protein (SV.Spike), combined with the OX40 immunostimulatory antibody (OX40) as a novel, highly effective vaccine approach. We show that SV.Spike plus OX40 elicits long-lasting neutralizing antibodies and a vigorous T-cell response in mice. Protein binding, immunohistochemical and cellular infection assays all show that vaccinated mice sera inhibits spike functions. Immunophenotyping, RNA Seq transcriptome profiles and metabolic analysis indicate a reprogramming of T-cells in vaccinated mice. Activated T-cells were found to mobilize to lung tissue. Most importantly, SV.Spike plus OX40 provided robust immune protection against infection with authentic coronavirus in transgenic mice expressing the human ACE2 receptor (hACE2-Tg). Finally, our immunization strategy induced strong effector memory response, potentiating protective immunity against re-exposure to SARS-CoV-2 spike protein. Our results show the potential of a new Sindbis virus-based vaccine platform to counteract waning immune response that can be used as a new candidate to combat SARS-CoV-2. Given the strong T-cell responses elicited, our vaccine is likely to be effective against variants that are proving challenging, as well as, serve as a platform to develop a broader spectrum pancoronavirus vaccine. Similarly, the vaccine approach is likely to be applicable to other pathogens.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.27.445991", + "rel_abs": "A hallmark of COVID-19 is a hyperinflammatory state that is associated with severity. Various anti-inflammatory therapeutics have shown mixed efficacy in treating COVID-19, and the mechanisms by which hyperinflammation occurs are not well understood. Previous research indicated that monocytes, a key innate immune cell, undergo metabolic reprogramming and produce inflammatory cytokines when stimulated with SARS-CoV-2. We hypothesized that binding by the viral spike protein mediates this effect, and that drugs which regulate immunometabolism could inhibit the inflammatory response in monocytes. Monocytes stimulated with recombinant SARS-CoV-2 spike protein subunit 1 showed a dose-dependent increase in glycolytic metabolism that was associated with production of pro-inflammatory cytokines including interleukin-6 and tumor necrosis factor-. This response was dependent on hypoxia-inducible factor-1, as chetomin inhibited glycolysis and cytokine production. Inhibition of glycolytic metabolism by 2-deoxyglucose (2-DG) or glucose deprivation also inhibited the glycolytic response, and 2-DG strongly suppressed cytokine production. Glucose-deprived monocytes rescued cytokine production by upregulating oxidative phosphorylation, an effect which was not present in 2-DG-treated monocytes due to the known effect of 2-DG on suppressing mitochondrial metabolism. Finally, pre-treatment of monocytes with metformin strongly suppressed spike protein-mediated cytokine production in monocytes, and abrogated glycolytic and mitochondrial metabolism. Likewise, metformin pre-treatment blocked cytokine induction by SARS-CoV-2 strain WA1/2020 in direct infection experiments in monocytes. In summary, the SARS-CoV-2 spike protein induces a pro-inflammatory immunometabolic response in monocytes that can be suppressed by metformin, and metformin likewise suppresses inflammatory responses to live SARS-CoV-2. This has potential implications for the treatment of hyperinflammation during COVID-19.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Antonella Scaglione", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Silvana Opp", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Alicia Hurtado", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Christine Pampeno", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Ziyan Lin", - "author_inst": "NYU Grossman School of Medicine" + "author_name": "Theodore J. Cory", + "author_inst": "University of Tennessee Health Science Center" }, { - "author_name": "Maria Gaby Noval", - "author_inst": "NYU Grossman School of Medicine" + "author_name": "Russell S. Emmons", + "author_inst": "University of Memphis" }, { - "author_name": "Sara Thannickal", - "author_inst": "NYU Grossman School of Medicine" + "author_name": "Johnathan R. Yarbro", + "author_inst": "University of Tennessee Health Science Center" }, { - "author_name": "Kenneth Stapleford", - "author_inst": "NYU Grossman School of Medicine" + "author_name": "Kierstin L. Davis", + "author_inst": "University of Memphis" }, { - "author_name": "Daniel Meruelo", - "author_inst": "NYU Grossman School of Medicine" + "author_name": "Brandt D. Pence", + "author_inst": "University of Memphis" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "new results", "category": "immunology" }, @@ -715641,95 +714194,111 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.05.24.21257425", - "rel_title": "The Humoral Response to the BNT162b2 Vaccine in Hemodialysis Patients", + "rel_doi": "10.1101/2021.05.25.21257803", + "rel_title": "SELP Asp603Asn and severe thrombosis in COVID-19 males: implication for anti P-selectin monoclonal antibodies treatment", "rel_date": "2021-05-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.24.21257425", - "rel_abs": "ImportanceHemodialysis patients have an exceptionally high mortality from COVID-19 and this patient population often has a poor response to vaccinations. Randomized controlled trials for COVID-19 vaccines included few patients with kidney disease, therefore vaccine immunogenicity is uncertain in this population.\n\nObjectiveEvaluate the SARS-CoV-2 antibody response in chronic hemodialysis patients following one versus two doses of BNT162b2 COVID-19 vaccination compared to health care worker controls and convalescent serum.\n\nDesignProspective observational cohort study.\n\nSettingSingle centre study in Toronto, Ontario, Canada.\n\nParticipants142 in-centre hemodialysis patients and 35 health care worker controls.\n\nExposureBNT162b2 (Pfizer-BioNTech) COVID-19 vaccine.\n\nMain Outcomes and MeasuresSARS-CoV-2 IgG antibodies to the spike protein (anti-spike), receptor binding domain (anti-RBD), and nucleocapsid protein (anti-NP) were measured in 66 hemodialysis patients receiving one vaccine dose following a public health policy change, 76 patients receiving two vaccine doses, and 35 health care workers receiving two vaccine doses.\n\nResultsDetectable anti-NP suggestive of natural SARS-CoV-2 infection was detected in 15/142 (11%) of patients at baseline while only three patients had prior RT-PCR confirmed COVID-19. Two additional patients contracted COVID-19 after receiving two doses of vaccine. In patients receiving a single BNT162b2 dose, seroconversion occurred in 53/66 (80%) for anti-spike and 35/66 (55%) for anti-RBD by 28 days post dose, but only 15/66 (23%) and 4/66 (6%), respectively attained a robust response as defined by reaching the median level of anti-spike and anti-RBD in convalescent serum from COVID-19 survivors. In patients receiving two doses of BNT162b2 vaccine, seroconversion occurred in 69/72 (96%) for anti-spike and 63/72 (88%) for anti-RBD by 2 weeks following the second dose while 52/72 (72%) and 43/76 (41%) reached the median convalescent serum level of anti-spike and anti-RBD, respectively. In contrast, 35/35 (100%) of health care workers exceeded the median level of anti-spike and anti-RBD found in convalescent serum 2-4 weeks after the second dose.\n\nConclusions and RelevanceThis study confirms poor immunogenicity 28 days following a single dose of BNT162b2 vaccine in the hemodialysis population, supporting adherence to recommended vaccination schedules, and avoiding delay of the second dose in these at-risk individuals.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat is the serologic response to the BNT162b2 COVID-19 vaccine in hemodialysis patients?\n\nFindingsIn this prospective observational study, humoral response was compared in 66 hemodialysis patients sampled 28 days after receipt of one dose of vaccine to 76 patients who received two doses of vaccine sampled 14 days after the second dose. Among those receiving one dose, 6% had anti-RBD response above the median level of convalescent serum versus 41% who received two doses.\n\nMeaningGiven that hemodialysis patients exhibit a poor humoral response to a single dose of BNT162b2 vaccine, the second dose should not be delayed.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.25.21257803", + "rel_abs": "Thromboembolism is a frequent cause of severity and mortality in COVID-19. However, the etiology of this phenomenon is not well understood. A cohort of 1,186 subjects, from the GEN-COVID consortium, infected by SARS-CoV-2 with different severity were stratified by sex and adjusted by age. Then, common coding variants from whole exome sequencing were mined by LASSO logistic regression. The homozygosity of the cell adhesion molecule P-selectin gene (SELP) rs6127 (c.1807G>A; p.Asp603Asn) which increases platelet activation is found to be associated with severity in the male subcohort of 513 subjects (Odds Ratio= 2.27, 95% Confidence Interval 1.54-3.36). As the SELP gene is downregulated by testosterone, the odd ratio is increased in males older than 50 (OR 2.42, 95% CI 1.53-3.82). Asn/Asn homozygotes have increased D-dimers values especially when associated with poly Q[≥]23 in the androgen receptor (AR) gene (OR 3.26, 95% CI 1.41-7.52). These results provide a rationale for the repurposing of antibodies against P-selectin as adjuvant therapy in rs6127 male homozygotes especially if older than 50 or with impaired AR gene.\n\nKey points{circ} The functional polymorphism rs6127 (p.Asp603Asn) in the testosterone-regulated SELP gene associates with COVID-19 severity and thrombosis.\n{circ}Conditions with decreased testosterone (old males), or decreased testosterone efficacy (AR gene polyQ [≥] 23) strengthen the association.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Kevin Yau", - "author_inst": "Sunnybrook Health Sciences Centre" + "author_name": "Chiara Fallerini", + "author_inst": "Medical Genetics, University of Siena, Italy; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" }, { - "author_name": "Kento T Abe", - "author_inst": "Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital; Sinai Health System" + "author_name": "Sergio Daga", + "author_inst": "Medical Genetics, University of Siena, Italy; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" }, { - "author_name": "David MJ Naimark", - "author_inst": "Sunnybrook Health Sciences Centre" + "author_name": "Elisa Benetti", + "author_inst": "Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" }, { - "author_name": "Matthew J Oliver", - "author_inst": "Sunnybrook Health Sciences Centre" + "author_name": "Nicola Picchiotti", + "author_inst": "Department of Mathematics, University of Pavia, Pavia, Italy; University of Siena, DIISM-SAILAB, Siena, Italy" }, { - "author_name": "Jeffrey Perl", - "author_inst": "Unity Health Toronto" + "author_name": "Kristina Zguro", + "author_inst": "Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" }, { - "author_name": "Jerome A Leis", - "author_inst": "Sunnybrook Health Sciences Centre" + "author_name": "Francesca Catapano", + "author_inst": "Medical Genetics, University of Siena, Italy; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" }, { - "author_name": "Shelly Bolotin", - "author_inst": "Public Health Ontario" + "author_name": "Virginia Baroni", + "author_inst": "Medical Genetics, University of Siena, Italy; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" }, { - "author_name": "Vanessa Tran", - "author_inst": "Ontario Public Health Laboratory" + "author_name": "Simone Lanini", + "author_inst": "National Institute for the Infectious Diseases \"L. Spallanzani,\" Rome, Italy." }, { - "author_name": "Sarah Mullin", - "author_inst": "Sunnybrook Health Sciences Centre" + "author_name": "Alessandro Bucalossi", + "author_inst": "Stem Cell Transplant and Cellular Therapy Unit, University Hospital, Siena, Italy" }, { - "author_name": "Ellen Shadowitz", - "author_inst": "Sunnybrook Health Sciences Centre" + "author_name": "Giuseppe Marotta", + "author_inst": "Stem Cell Transplant and Cellular Therapy Unit, University Hospital, Siena, Italy" }, { - "author_name": "Julie Garnham-Takaoka", - "author_inst": "Unity Health Toronto" + "author_name": "Margherita Baldassarri", + "author_inst": "Medical Genetics, University of Siena, Italy; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" }, { - "author_name": "Keelia Quinn De Launay", - "author_inst": "Unity Health Toronto" + "author_name": "Francesca Fava", + "author_inst": "Medical Genetics, University of Siena, Italy; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy; Genetica" }, { - "author_name": "Alyson Takaoka Takaoka", - "author_inst": "Unity Health Toronto" + "author_name": "Giada Beligni", + "author_inst": "Medical Genetics, University of Siena, Italy; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" }, { - "author_name": "Sharon E Straus", - "author_inst": "Unity Health Toronto" + "author_name": "Laura Di Sarno", + "author_inst": "Medical Genetics, University of Siena, Italy; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" }, { - "author_name": "Allison J McGeer", - "author_inst": "Sinai Health System" + "author_name": "Diana Alaverdian", + "author_inst": "Medical Genetics, University of Siena, Italy; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" }, { - "author_name": "Christopher T Chan", - "author_inst": "University Health Network" + "author_name": "Maria Palmieri", + "author_inst": "Medical Genetics, University of Siena, Italy; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" }, { - "author_name": "Karen Colwill", - "author_inst": "Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital; Sinai Health System" + "author_name": "Susanna Croci", + "author_inst": "Medical Genetics, University of Siena, Italy; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" }, { - "author_name": "Anne-Claude Gingras", - "author_inst": "Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital; Sinai Health System" + "author_name": "Andrea M. Isidori", + "author_inst": "Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy" }, { - "author_name": "Michelle A Hladunewich", - "author_inst": "Sunnybrook Health Sciences Centre" + "author_name": "Simone Furini", + "author_inst": "Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" + }, + { + "author_name": "Elisa Frullanti", + "author_inst": "Medical Genetics, University of Siena, Italy; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" + }, + { + "author_name": "GEN-COVID Multicenter Study", + "author_inst": "Medical Genetics, University of Siena, Italy" + }, + { + "author_name": "Alessandra Renieri", + "author_inst": "Medical Genetics, University of Siena, Italy; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy; 7)\tGenet" + }, + { + "author_name": "Francesca Mari", + "author_inst": "Medical Genetics, University of Siena, Italy; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy; Genetica" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "nephrology" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2021.05.25.21257811", @@ -717851,63 +716420,63 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.21.21257600", - "rel_title": "Infection control, occupational and public health measures including mRNA-based vaccination against SARS-CoV-2 infections to protect healthcare workers from variants of concern: a 14-month observational study using surveillance data", + "rel_doi": "10.1101/2021.05.23.445114", + "rel_title": "ABO blood group is involved in the quality of the specific immune response", "rel_date": "2021-05-25", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.21.21257600", - "rel_abs": "BackgroundWe evaluated measures to protect healthcare workers (HCWs) in Vancouver, Canada, where variants of concern (VOC) went from <1% in February 2021 to >92% in mid-May. Canada has amongst the longest periods between vaccine doses worldwide, despite Vancouver having the highest P.1 variant rate outside Brazil.\n\nMethodsWith surveillance data since the pandemic began, we tracked laboratory-confirmed SARS-CoV-2 infections, positivity rates, and vaccine uptake in all 25,558 HCWs in Vancouver Coastal Health, by occupation and subsector, and compared to the general population. We employed Cox regression modelling adjusted for age and calendar-time to calculate vaccine effectiveness (VE) against SARS-CoV-2 in fully vaccinated ([≥] 7 days post-second dose), partially vaccinated (14 days post vaccine) and unvaccinated HCWs; we also compared with unvaccinated community members of the same age-range.\n\nFindingsOnly 3.3% of our HCWs became infected, mirroring community rates, with peak positivity of 9.1%, compared to 11.8% in the community. As vaccine coverage increased, SARS-CoV-2 infections declined significantly in HCWs, despite a surge with predominantly VOC; unvaccinated HCWs had an infection rate of 1.3/10,000 person-days compared to 0.89 for HCWs post first dose, and 0.30 for fully vaccinated HCWs. VE compared to unvaccinated HCWs was 37.2% (95% CI: 16.6-52.7%) 14 days post-first dose, 79.2% (CI: 64.6-87.8%) 7 days post-second dose; one dose provided significant protection against infection until at least day 42. Compared with community infection rates, VE after one dose was 54.7% (CI: 44.8-62.9%); and 84.8% (CI: 75.2-90.7%) when fully vaccinated.\n\nInterpretationPredominantly droplet-contact precautions, with N95s required for aerosol generating medical procedures and available as needed according to point-of-care risk assessment, has been a highly effective approach to preventing occupational infection in HCWs, with one dose of mRNA vaccination further reducing infection risk despite VOC and transmissibility concerns. Delaying second doses to allow more widespread vaccination against severe disease, with strict public health, occupational health and infection control measures, has been effective in protecting the healthcare workforce.", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.23.445114", + "rel_abs": "Since December 2019, the coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread throughout the world. To eradicate it, it is crucial to acquire a strong and long-lasting anti-SARS-CoV-2 immunity, by either natural infection or vaccination. We collected blood samples 12-305 days after positive polymerase chain reactions (PCRs) from 35 recovered individuals infected by SARS-CoV-2. Peripheral blood mononuclear cells were stimulated with SARS-CoV-2-derived peptide pools, such as the Spike (S), Nucleocapsid (N), and Membrane (M) proteins, and we quantified anti-S immunoglobulins in plasma. After 10 months post-infection, we observed a sustained SARS-CoV-2-specific CD4+ T-cell response directed against M-protein, but responses against S- or N-proteins were lost over time. Besides, we demonstrated that A-group individuals presented significantly higher frequencies of specific CD4+ T-cell responses against Pep-M than O-group individuals. The A-group subjects also needed longer to clear the virus and they lost cellular immune responses over time, compared to the O-group individuals, who showed a persistent specific immune response against SARS-CoV-2. Therefore, the S-specific immune response was lost over time, and individual factors determine the sustainability of the bodys defences, which must be considered in the future design of vaccines to achieve continuous anti-SARS-CoV-2 immunity.\n\nSummaryThis work describes that cellular responses against SARS-CoV-2 M-protein can be detected after 10 months but were lost against S- and N-proteins. Moreover, the individual factors; ABO-group and age influence the sustainability of the specific humoral and cellular immunity against SARS-CoV-2.", "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Annalee Yassi", - "author_inst": "The University of British Columbia" + "author_name": "Sergio Gil-Manso", + "author_inst": "Laboratory of Immune-Regulation, Gregorio Maranon Health Research Institute (IiSGM), Gregorio Maranon University General Hospital, Madrid, Spain" }, { - "author_name": "Jennifer M. Grant", - "author_inst": "Vancouver Coastal Health (VCH)" + "author_name": "Iria Miguens Blanco", + "author_inst": "Department of Emergency, Gregorio Maranon University General Hospital, Madrid, Spain" }, { - "author_name": "Karen Lockhart", - "author_inst": "The University of British Columbia" + "author_name": "Bruce Motyka", + "author_inst": "Depts. of Pediatrics, Alberta Transplant Institute and Canadian Donation and Transplantation Research Program; University of Alberta, Edmonton, Alberta, Canada" }, { - "author_name": "Stephen Barker", - "author_inst": "The University of British Columbia" + "author_name": "Anne Halpin", + "author_inst": "Depts. of Pediatrics, Alberta Transplant Institute and Canadian Donation and Transplantation Research Program; University of Alberta, Edmonton, Alberta, Canada" }, { - "author_name": "Stacy Sprague", - "author_inst": "Vancouver Coastal Health (VCH)" + "author_name": "Rocio Lopez-Estaban", + "author_inst": "Laboratory of Immune-Regulation, Gregorio Maranon Health Research Institute (IiSGM), Gregorio Maranon University General Hospital, Madrid, Spain" }, { - "author_name": "Arnold I. Okpani", - "author_inst": "The University of British Columbia" + "author_name": "Veronica Astrid Perez-Fernandez", + "author_inst": "Laboratory of Immune-Regulation, Gregorio Maranon Health Research Institute (IiSGM), Gregorio Maranon University General Hospital, Madrid, Spain" }, { - "author_name": "Titus Wong", - "author_inst": "Vancouver Coastal Health (VCH)" + "author_name": "Diego Carbonell-Munoz", + "author_inst": "Department of Hematology, Gregorio Maranon University General Hospital, Madrid, Spain" }, { - "author_name": "Patricia Daly", - "author_inst": "Vancouver Coastal Health (VCH)" + "author_name": "Luis Andres Lopez-Fernandez", + "author_inst": "Service of Pharmacy, Gregorio Maranon Health Research Institute (IiSGM), Gregorio Maranon University General Hospital, Spanish Clinical Research Network (SCReN)" }, { - "author_name": "William Henderson", - "author_inst": "Vancouver Coastal Health (VCH)" + "author_name": "Lori J west", + "author_inst": "Medical Microbiology & Immunology, Surgery, and Laboratory Medicine & Pathology; University of Alberta, Edmonton, Alberta, Canada" }, { - "author_name": "Stan Lubin", - "author_inst": "Vancouver Coastal Health (VCH)" + "author_name": "Rafael Correa-Rocha", + "author_inst": "Laboratory of Immune-Regulation, Gregorio Maranon Health Research Institute (IiSGM), Gregorio Maranon University General Hospital, Madrid, Spain" }, { - "author_name": "Chad Kim Sing", - "author_inst": "Vancouver Coastal Health (VCH)" + "author_name": "Marjorie Pion", + "author_inst": "Laboratory of Immune-Regulation, Gregorio Maranon Health Research Institute (IiSGM), Gregorio Maranon University General Hospital, Madrid, Spain" } ], "version": "1", "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.05.24.21257465", @@ -719601,63 +718170,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.05.24.445313", - "rel_title": "Identification of site-specific evolutionary trajectories shared across human betacoronaviruses", + "rel_doi": "10.1101/2021.05.23.21257669", + "rel_title": "Exploiting Molecular Basis of Age and Gender Differences in Outcomes of SARS-CoV-2 Infections.", "rel_date": "2021-05-25", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.24.445313", - "rel_abs": "Comparing the evolution of distantly related viruses can provide insights into common adaptive processes related to shared ecological niches. Phylogenetic approaches, coupled with other molecular evolution tools, can help identify mutations informative on adaptation, whilst the structural contextualization of these to functional sites of proteins may help gain insight into their biological properties. Two zoonotic betacoronaviruses capable of sustained human-to-human transmission have caused pandemics in recent times (SARS-CoV-1 and SARS-CoV-2), whilst a third virus (MERS-CoV) is responsible for sporadic outbreaks linked to animal infections. Moreover, two other betacoronaviruses have circulated endemically in humans for decades (HKU1 and OC43). To search for evidence of adaptive convergence between established and emerging betacoronaviruses capable of sustained human-to-human transmission (HKU1, OC43, SARS-CoV-1 and SARS-CoV-2), we developed a methodological pipeline to classify shared non-synonymous mutations as putatively denoting homoplasy (repeated mutations that do not share direct common ancestry) or stepwise evolution (sequential mutations leading towards a novel genotype). In parallel, we look for evidence of positive selection, and draw upon protein structure data to identify potential biological implications. We find 30 mutations, with four of these [codon sites 18121 (nsp14/residue 28), 21623 (spike/21), 21635 (spike/25) and 23948 (spike/796); SARS-CoV-2 genome numbering] displaying evolution under positive selection and proximity to functional protein regions. Our findings shed light on potential mechanisms underlying betacoronavirus adaptation to the human host and pinpoint common mutational pathways that may occur during establishment of human endemicity.", - "rel_num_authors": 11, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.23.21257669", + "rel_abs": "MotivationSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (coronavirus disease, 2019; COVID-19) is associated with adverse outcomes in patients. It has been observed that lethality seems to be related to the age of patients. Moreover, it has been demonstrated that ageing causes some modifications at a molecular level.\n\nObjectiveThe study aims to shed out light on a possible link between the increased COVID-19 lethality and the molecular changes that occur in elderly people.\n\nMethodsWe considered public datasets on ageing-related genes and their expression at tissue level. We selected interactors that are known to be related to ageing process. Then, we performed a network-based analysis to identify interactors significantly related to both SARS-CoV-2 and ageing. Finally, we investigated changes on the expression level of coding genes at tissue, gender and age level.\n\nResultsWe observed a significant intersection between some SARS-CoV-2 interactors and ageing-related genes suggesting that those genes are particularly affected by COVID-19 infection. Our analysis evidenced that virus infection particularly affects ageing molecular mechanisms centred around proteins EEF2, NPM1, HMGA1, HMGA2, APEX1, CHEK1, PRKDC, and GPX4. We found that HMGA1, and NPM1 have a different expression in lung of males, while HMGA1, APEX1, CHEK1, EEF2, and NPM1 present changes in expression in males due to aging effects.\n\nConclusionOur study generated a mechanistic framework to explaining the correlation between COVID-19 incidence in elderly patients and molecular mechanisms of ageing. This will provide testable hypotheses for future investigation and pharmacological solutions tailored on specific age ranges.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Marina Escalera-Zamudio", - "author_inst": "University of Oxford" - }, - { - "author_name": "Sergei L Kosakovsky Pond", - "author_inst": "Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA 19122, USA" - }, - { - "author_name": "Natalia Martinez de la Vina", - "author_inst": "Department of Zoology, University of Oxford, Parks Rd Oxford, OX1 3PS, UK" - }, - { - "author_name": "Bernardo Gutierrez", - "author_inst": "Department of Zoology, University of Oxford, Parks Rd Oxford, OX1 3PS, UK" - }, - { - "author_name": "Rhys P. D. Inward", - "author_inst": "Department of Biology, University of Oxford, Oxford, OX1 3PS, UK" - }, - { - "author_name": "Julien Theze", - "author_inst": "Universite Clermont Auvergne, INRAE, VetAgro Sup, UMR EPIA, Saint-Genes-Champanelle, France" - }, - { - "author_name": "Lucy van Dorp", - "author_inst": "UCL Genetics Institute" - }, - { - "author_name": "Hugo G Castelan", - "author_inst": "CONACYT" + "author_name": "Daniele Mercatelli", + "author_inst": "University of Bologna" }, { - "author_name": "Thomas A Bowden", - "author_inst": "Division of Structural Biology, Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK" + "author_name": "Elisabetta Pedace", + "author_inst": "Soverato Hospital" }, { - "author_name": "Oliver G Pybus", - "author_inst": "Department of Zoology, University of Oxford, Parks Rd Oxford, OX1 3PS, UK" + "author_name": "Federico Manuel Giorgi", + "author_inst": "University of Bologna" }, { - "author_name": "Ruben J.G. Hulswit", - "author_inst": "Division of Structural Biology, Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK" + "author_name": "Pietro Hiram Guzzi", + "author_inst": "University of Catanzaro" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "evolutionary biology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2021.05.25.445601", @@ -721355,63 +719896,51 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.21.21257634", - "rel_title": "Combining serological assays and official statistics to describe the trajectory of the COVID-19 pandemic: results from the EPICOVID19-RS study in Rio Grande do Sul (Southern Brazil)", + "rel_doi": "10.1101/2021.05.21.21257613", + "rel_title": "Perceptions of and obstacles to SARS-CoV-2 vaccination among adults in Lebanon: a cross-sectional online survey", "rel_date": "2021-05-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.21.21257634", - "rel_abs": "BackgroundThe EPICOVID19-RS study conducted 10 population-based surveys in Rio Grande do Sul (Southern Brazil), starting early in the epidemic. The sensitivity of the rapid point-of-care test used in the first eight surveys has been shown to decrease over time after some phases of the study were concluded. The 9th survey used both the rapid test and an enzyme-linked immunosorbent assay (ELISA) test, which has a higher and stable sensitivity.\n\nMethodsWe provide a theoretical justification for a correction procedure of the rapid test estimates, assess its performance in a simulated dataset and apply it to empirical data from the EPICOVID19-RS study. COVID-19 deaths from official statistics were used as an indicator of the temporal distribution of the epidemic, under the assumption that fatality is constant over time. Both the indicator and results from the 9th survey were used to calibrate the temporal decay function of the rapid tests sensitivity from a previous validation study, which was used to estimate the true sensitivity in each survey and adjust the rapid test estimates accordingly.\n\nResultsSimulations corroborated the procedure is valid. Corrected seroprevalence estimates were substantially larger than uncorrected estimates, which were substantially smaller than respective estimates from confirmed cases and therefore clearly underestimate the true infection prevalence.\n\nConclusionCorrecting biased estimates requires a combination of data and modelling assumptions. This work illustrates the practical utility of analytical procedures, but also the critical need for good quality, populationally-representative data for tracking the progress of the epidemic and substantiate both projection models and policy making.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.21.21257613", + "rel_abs": "The COVID-19 pandemic is an additional burden on Lebanons stressed population, fragmented healthcare system, and political, economic, and refugee crises. Understanding the populations intentions to vaccinate, and perceptions of and obstacles to SARS-CoV-2 vaccination, can inform Lebanons vaccination efforts. We performed a cross-sectional study from 29 Jan 2021 to 11 Mar 2021 using an online questionnaire in Arabic via convenience \"snowball\" sampling to assess the perceptions of adults residing in Lebanon. 1,185 adults participated in the survey. % [95% CI: 43.2%-49.0%] of survey participants intended to take the SARS-CoV-2 vaccine when available to them, 19.0% [16.8%-21.4%] indicated that they would not, and 34.0% [31.3%-36.8%] were unsure. The most common reasons for hesitancy were concerns about safety, limited testing, side effects, and efficacy. Vaccine hesitancy appears to be high in Lebanon. Disseminating clear, consistent, evidence-based safety and efficacy information on vaccines may help reduce vaccine hesitancy, especially among the large proportion of adults who appear to be unsure about (rather than opposed to) vaccination.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Fernando Pires Hartwig", - "author_inst": "Federal University of Pelotas" + "author_name": "Nadeem E Abou-Arraj", + "author_inst": "School of Public Health, University of California, Berkeley, CA, USA; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA" }, { - "author_name": "Lu\u00eds Paulo Vidaletti", - "author_inst": "Federal University of Pelotas" + "author_name": "Diana Maddah", + "author_inst": "School of Health Sciences, Modern University for Business and Science, Lebanon" }, { - "author_name": "Alu\u00edsio JD Barros", - "author_inst": "Federal University of Pelotas" + "author_name": "Vanessa Buhamdan", + "author_inst": "School of Health Sciences, Modern University for Business and Science, Lebanon" }, { - "author_name": "Gabriel D Victora", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Ana MB Menezes", - "author_inst": "Federal University of Pelotas" - }, - { - "author_name": "Marilia A Mesenburg", - "author_inst": "Federal University of Health Sciences of Porto Alegre" + "author_name": "Roua Abbas", + "author_inst": "School of Health Sciences, Modern University for Business and Science, Lebanon" }, { - "author_name": "Bernardo L Horta", - "author_inst": "Federal University of Pelotas" - }, - { - "author_name": "Mari\u00e2ngela F Silveira", - "author_inst": "Federal University of Pelotas" + "author_name": "Nadine K. Jawad", + "author_inst": "Stanford University School of Medicine, Stanford, CA, USA" }, { - "author_name": "Cesar G Victora", - "author_inst": "Federal University of Pelotas" + "author_name": "Fatima Karaki", + "author_inst": "Refugee and Asylum seeker Health Initiative (RAHI), Department of Medicine, University of California San Francisco, CA, USA" }, { - "author_name": "Pedro C Hallal", - "author_inst": "Federal University of Pelotas" + "author_name": "Nael H. Alami", + "author_inst": "Modern University for Business and Science, Lebanon" }, { - "author_name": "Claudio J Struchiner", - "author_inst": "Getulio Vargas Foundation" + "author_name": "Pascal Geldsetzer", + "author_inst": "Division of Primary Care and Population Health, Department of Medicine, Stanford University, Stanford, CA, USA; Heidelberg Institute of Global Health, Heidelber" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.05.20.21257542", @@ -723409,125 +721938,45 @@ "category": "hematology" }, { - "rel_doi": "10.1101/2021.05.20.21257393", - "rel_title": "Release of infectious virus and cytokines in nasopharyngeal swabs from individuals infected with non-B.1.1.7 or B.1.1.7 SARS-CoV-2 variants.", + "rel_doi": "10.1101/2021.05.20.21255825", + "rel_title": "SARS-CoV-2 vaccination with CoronaVac: seroconversion rate in healthcare workers after 40 days", "rel_date": "2021-05-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.20.21257393", - "rel_abs": "The mechanisms that allowed for the SARS-CoV-2 B.1.1.7 variant to rapidly outcompete pre-existing variants in many countries remain poorly characterized. Here, we analyzed viral release, anti-SARS-CoV-2 antibodies and cytokine production in a retrospective series of 427 RT-qPCR+ nasopharyngeal swabs collected in COVID-19 patients harbouring either non-B.1.1.7 or B.1.17 variants. We utilized a novel rapid assay, based on S-Fuse-T reporter cells, to quantify infectious SARS-CoV-2. With both non-B.1.1.7 and B.1.1.7 variants, viral titers were highly variable, ranging from 0 to >106 infectious units, and correlated with viral RNA levels. Lateral flow antigenic rapid diagnostic tests (RDTs) were positive in 96% of the samples harbouring infectious virus. About 67 % of individuals carried detectable infectious virus within the first two days after onset of symptoms. This proportion decreased overtime, and viable virus was detected up to 14 days. Samples containing anti-SARS-CoV-2 IgG or IgA did not generally harbour infectious virus. The proportion of individuals displaying viable virus or being RDT-positive was not higher with B.1.1.7 than with non-B.1.1.7 variants. Ct values were slightly but not significantly lower with B.1.1.7. The variant was characterized by a fast decrease of infectivity overtime and a marked release of 17 cytokines (including IFN-{beta}, IP-10, IL-10 and TRAIL). Our results highlight differences between non-B.1.1.7 and B.1.1.7 variants. B.1.1.7 is associated with modified viral decays and cytokine profiles at the nasopharyngeal mucosae during symptomatic infection.", - "rel_num_authors": 27, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.20.21255825", + "rel_abs": "BackgroundThis study aimed to calculate the seroconversion rate of the CoronaVac vaccine in healthcare workers (HCWs) after immunization.\n\nMethodsSerum samples from 133 HCWs from Southern Brazil were collected one day before (Day 0) and +10, +20, +40, + 60, +110 days after administering the vaccines first dose. Immunoglobulin G (IgG) was quantified using immunoassays for anti-N-protein (nucleocapsid) antibodies (Abbott, Sligo, Ireland) and for anti-S1 (spike) protein antibodies (Euroimmun, Lubeck, Germany).\n\nResultsSeroconversion by day 40 occurred in 129 (97%) HCWs for the S1 protein, and in 69 (51.87%) HCWs for the N protein. An absence of IgG antibodies (by both methodologies), occurred in two (1.5%) HCWs undergoing semiannual rituximab administration, and also in another two (1.5%) HCWs with no apparent reason.\n\nConclusionThis study showed that CoronaVac has a high seroconversion rate when evaluated in an HCW population.\n\nFundingThis work was supported by the PROPLAN/Federal University of Parana, Curitiba-Parana, Brazil; FINEP, Funder of Studies and Projects, Ministry of Science, Technology and Innovation, Brazil Institutional Network, Project: Laboratories for Diagnostic Tests for COVID-19 (0494/20).", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Blandine Monel", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Delphine Planas", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Ludivine Grzelak", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Nikaia Smith", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Nicolas Robillard", - "author_inst": "AP-HP" - }, - { - "author_name": "Isabelle Staropoli", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Pedro Goncalves", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Francoise Porrot", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Florence Guivel-Benhassine", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Nathalie Demory", - "author_inst": "AP-HP" - }, - { - "author_name": "Julien Rodary", - "author_inst": "AP-HP" - }, - { - "author_name": "Julien Puech", - "author_inst": "AP-HP" - }, - { - "author_name": "Victor Euzen", - "author_inst": "AP-HP" - }, - { - "author_name": "Laurent Belec", - "author_inst": "AP-HP" - }, - { - "author_name": "Galdric Orvoen", - "author_inst": "AP-HP" - }, - { - "author_name": "Lea Nunes", - "author_inst": "AP-HP" - }, - { - "author_name": "Veronique Moulin", - "author_inst": "AP-HP" - }, - { - "author_name": "Jacques Fourgeaud", - "author_inst": "AP-HP" - }, - { - "author_name": "Maxime Wack", - "author_inst": "AP-HP" - }, - { - "author_name": "Sandrine Imbeaud", - "author_inst": "INSERM" - }, - { - "author_name": "Pascal Campagne", - "author_inst": "Institut Pasteur" + "author_name": "Lucas Bochnia-Bueno", + "author_inst": "Universidade Federal do Parana" }, { - "author_name": "Darragh Duffy", - "author_inst": "Institut Pasteur" + "author_name": "Sergio Monteiro De Almeida", + "author_inst": "Universidade Federal do Parana" }, { - "author_name": "James Di Santo", - "author_inst": "Institut Pasteur" + "author_name": "Sonia Mara Raboni", + "author_inst": "Universidade Federal do Parana" }, { - "author_name": "Timothee Bruel", - "author_inst": "Institut Pasteur" + "author_name": "Douglas Adamoski", + "author_inst": "Universidade Federal do Parana" }, { - "author_name": "Helene Pere", - "author_inst": "AP-HP" + "author_name": "Ludmilla Louise Moreira Amadeu", + "author_inst": "Universidade Federal do Parana" }, { - "author_name": "David Veyer", - "author_inst": "AP-HP" + "author_name": "Suzana Carstensen", + "author_inst": "Universidade Federal do Parana" }, { - "author_name": "Olivier Schwartz", - "author_inst": "Institut Pasteur" + "author_name": "Meri Bordignon Nogueira", + "author_inst": "Universidade Federal do Parana" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -725323,131 +723772,47 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2021.05.20.445060", - "rel_title": "Generation of potent cellular and humoral immunity against SARS-CoV-2 antigens via conjugation to a polymeric glyco-adjuvant", + "rel_doi": "10.1101/2021.05.21.445156", + "rel_title": "ESCA pipeline: Easy-to-use SARS-CoV-2 genome Assembler", "rel_date": "2021-05-21", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.20.445060", - "rel_abs": "The SARS-CoV-2 virus has caused an unprecedented global crisis, and curtailing its spread requires an effective vaccine which elicits a diverse and robust immune response. We have previously shown that vaccines made of a polymeric glyco-adjuvant conjugated to an antigen were effective in triggering such a response in other disease models and hypothesized that the technology could be adapted to create an effective vaccine against SARS-CoV-2. The core of the vaccine platform is the copolymer p(Man-TLR7), composed of monomers with pendant mannose or a toll-like receptor 7 (TLR7) agonist. Thus, p(Man-TLR7) is designed to target relevant antigen-presenting cells (APCs) via mannose-binding receptors and then activate TLR7 upon endocytosis. The p(Man-TLR7) construct is amenable to conjugation to protein antigens such as the Spike protein of SARS-CoV-2, yielding Spike-p(Man-TLR7). Here, we demonstrate Spike-p(Man-TLR7) vaccination elicits robust antigen-specific cellular and humoral responses in mice. In adult and elderly wild-type mice, vaccination with Spike-p(Man-TLR7) generates high and long-lasting titers of anti-Spike IgGs, with neutralizing titers exceeding levels in convalescent human serum. Interestingly, adsorbing Spike-p(Man-TLR7) to the depot-forming adjuvant alum, amplified the broadly neutralizing humoral responses to levels matching those in mice vaccinated with formulations based off of clinically-approved adjuvants. Additionally, we observed an increase in germinal center B cells, antigen-specific antibody secreting cells, activated T follicular helper cells, and polyfunctional Th1-cytokine producing CD4+ and CD8+ T cells. We conclude that Spike-p(Man-TLR7) is an attractive, next-generation subunit vaccine candidate, capable of inducing durable and robust antibody and T cell responses.", - "rel_num_authors": 28, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.21.445156", + "rel_abs": "Early sequencing and quick analysis of SARS-CoV-2 genome are contributing to understand the dynamics of COVID19 epidemics and to countermeasures design at global level. Amplicon-based NGS methods are widely used to sequence the SARS-CoV-2 genome and to identify novel variants that are emerging in rapid succession, harboring multiple deletions and amino acid changing mutations. To facilitate the analysis of NGS sequencing data obtained from amplicon-based sequencing methods, here we propose an easy-to-use SARS-CoV-2 genome Assembler: the ESCA pipeline. Results showed that ESCA can perform high quality genome assembly from IonTor-rent and Illumina raw data, and help the user in easily correct low-coverage regions. Moreover, ESCA includes the possibility to compare assembled genomes of multi sample runs through an easy table format.\n\nScript and manuals are available on GitHub: https://github.com/cesaregruber/ESCA", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Laura T. Gray", - "author_inst": "University of Chicago" - }, - { - "author_name": "Michal M. Raczy", - "author_inst": "University of Chicago" - }, - { - "author_name": "Priscilla S. Briquez", - "author_inst": "University of Chicago" - }, - { - "author_name": "Tiffany M. Marchell", - "author_inst": "University of Chicago" - }, - { - "author_name": "Aaron T. Alpar", - "author_inst": "University of Chicago" - }, - { - "author_name": "Rachel P. Wallace", - "author_inst": "University of Chicago" - }, - { - "author_name": "Lisa R. Volpatti", - "author_inst": "University of Chicago" - }, - { - "author_name": "Maria Stella Sasso", - "author_inst": "University of Chicago" - }, - { - "author_name": "Shijie Cao", - "author_inst": "University of Chicago" - }, - { - "author_name": "Mindy Nguyen", - "author_inst": "University of Chicago" - }, - { - "author_name": "Aslan Mansurov", - "author_inst": "University of Chicago" - }, - { - "author_name": "Erica Budina", - "author_inst": "University of Chicago" - }, - { - "author_name": "Elyse A. Watkins", - "author_inst": "University of Chicago" - }, - { - "author_name": "Ani Solanki", - "author_inst": "University of Chicago" - }, - { - "author_name": "Nikolaos Mitrousis", - "author_inst": "University of Chicago" - }, - { - "author_name": "Joseph W. Reda", - "author_inst": "University of Chicago" - }, - { - "author_name": "Shann S. Yu", - "author_inst": "University of Chicago" - }, - { - "author_name": "Andrew C Tremain", - "author_inst": "University of Chicago" - }, - { - "author_name": "Ruyi Wang", - "author_inst": "University of Chicago" - }, - { - "author_name": "Vlad Nicolaescu", - "author_inst": "University of Chicago" - }, - { - "author_name": "Kevin Furlong", - "author_inst": "University of Chicago" - }, - { - "author_name": "Steve Dvorkin", - "author_inst": "University of Chicago" + "author_name": "Martina Rueca", + "author_inst": "National Institute for Infectious Diseases (INMI) \"L. Spallanzani\" IRCCS, via Portuense 292, Rome, Italy" }, { - "author_name": "Balaji Manicassamy", - "author_inst": "University of Iowa" + "author_name": "Emanuela Giombini", + "author_inst": "National Institute for Infectious Diseases (INMI) \"L. Spallanzani\" IRCCS, via Portuense 292, Rome, Italy" }, { - "author_name": "Glenn Randall", - "author_inst": "University of Chicago" + "author_name": "Francesco Messina", + "author_inst": "National Institute for Infectious Diseases (INMI) \"L. Spallanzani\" IRCCS, via Portuense 292, Rome, Italy" }, { - "author_name": "D. Scott Wilson", - "author_inst": "Johns Hopkins School of Medicine" + "author_name": "Barbara Bartolini", + "author_inst": "National Institute for Infectious Diseases (INMI) \"L. Spallanzani\" IRCCS, via Portuense 292, Rome, Italy" }, { - "author_name": "Marcin Kwissa", - "author_inst": "University of Chicago" + "author_name": "Antonino Di Caro", + "author_inst": "National Institute for Infectious Diseases (INMI) \"L. Spallanzani\" IRCCS, via Portuense 292, Rome, Italy" }, { - "author_name": "Melody A. Swartz", - "author_inst": "University of Chicago" + "author_name": "Maria R. Capobianchi", + "author_inst": "National Institute for Infectious Diseases (INMI) \"L. Spallanzani\" IRCCS, via Portuense 292, Rome, Italy" }, { - "author_name": "Jeffrey A. Hubbell", - "author_inst": "University of Chicago" + "author_name": "Cesare E.M. Gruber", + "author_inst": "National Institute for Infectious Diseases (INMI) \"L. Spallanzani\" IRCCS, via Portuense 292, Rome, Italy" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "bioengineering" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.05.21.445152", @@ -727321,55 +725686,47 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2021.05.19.21257455", - "rel_title": "A COVID-19 Community Vulnerability Index to drive precision policy in the US", + "rel_doi": "10.1101/2021.05.20.444935", + "rel_title": "Fluorescence signatures of SARS CoV-2 spike S1 proteins and an human ACE-2: excitation-emission maps and fluorescence lifetimes", "rel_date": "2021-05-20", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.19.21257455", - "rel_abs": "BackgroundIn April 2020 we released the US COVID-19 Community Vulnerability Index (CCVI) to bring to life vulnerability to health, economic, and social impact of COVID-19 at the state, county, and census tract level. Here we describe the methodology, how vulnerability is distributed across the U.S., and assess the impact on vulnerable communities over the first year of the pandemic.\n\nMethodsThe index combines 40 indicators into seven themes, drawing on both public and proprietary data. We associate timeseries of COVID-19 cases, deaths, test site access, and rental arrears with vulnerability.\n\nResultsAlthough overall COVID-19 vulnerability is concentrated in the South, the seven underlying themes show substantial spatial variability. As of May 13, 2021, the top-third of vulnerable counties have seen 21% more cases and 47% more deaths than the bottom-third of vulnerable counties, despite receiving 27% fewer tests (adjusted for population). Individual vulnerability themes vary over time in their relationship with mortality as the virus swept across the country. Over 20% of households in the top vulnerability tercile have fallen behind on rent. Poorer test site access for rural vulnerable populations early in the pandemic has since been alleviated.\n\nConclusionThe CCVI captures greater risk of health and economic impact. It has enjoyed widespread use in response planning, and we share lessons learned about developing a data-driven tool in the midst of a fast-moving pandemic. The CCVI and an interactive data explorer are available at precisionforcovid.org/ccvi.\n\nO_TEXTBOXWhat is already known on this topicO_LIVarious communities across the United States will experience the adverse effects of public health crises to different degrees of severity.\nC_LIO_LIComposite indicators, such as the CDC Social Vulnerability Index, have proven to be valuable to policymakers by turning complex data sets into easily digestible and actionable information. However, the indicators within the Social Vulnerability Index do not fully contextualize the negative impacts spurred by the current pandemic.\nC_LI\n\nWhat this study addsO_LIThe U.S. COVID-19 Community Vulnerability Index captures vulnerabilities spanning health, social, and economic dimensions that have been felt by every community in the US differently.\nC_LIO_LIVulnerable populations have experienced more cases and deaths, higher unemployment, and a lack of access to critical support such as testing sites.\nC_LIO_LIPrecision policies targeting vulnerable populations need to be designed and enacted to decrease the gap in negative consequences experienced in this and future pandemics, and the COVID-19 Community Vulnerability Index is a tool to highlight where and why these inequities occur.\nC_LI\n\nC_TEXTBOX", - "rel_num_authors": 9, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.20.444935", + "rel_abs": "SignificanceFast and reliable detection of infectious SARS-CoV-2 virus loads is an important issue. Fluorescence spectroscopy is a sensitive tool to do so in clean environments. This presumes a comprehensive knowledge of fluorescence data.\n\nAimThis work aims at providing fully featured information on wavelength and time-dependent data of the fluorescence of the SARS-CoV-2 spike protein S1 subunit, its receptor binding domain (RBD) and the human angiotensinconverting enzyme 2 (hACE2), especially with respect to possible optical detection schemes.\n\nApproachSpectrally resolved excitation-emission maps of the involved proteins and measurements of fluorescence lifetimes were recorded for excitations from 220 to 295 nm. The fluorescence decay times were extracted by using a bi-exponential kinetic approach. The binding process in the SARS-CoV-2 RBD was likewise examined for spectroscopic changes.\n\nResultsDistinct spectral features for each protein are pointed out in relevant spectra extracted from the excitation emission maps. We also identify minor spectroscopic changes under the binding process. The decay times in the bi-exponential model are found to be (2.0{+/-} 0.1) ns and (8.0 {+/-}1.0) ns.\n\nConclusionsSpecific material data serve as important background information for the design of optical detection and testing methods for SARS-CoV-2 loaded media.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Peter Smittenaar", - "author_inst": "Surgo Ventures" - }, - { - "author_name": "Nicholas Stewart", - "author_inst": "Surgo Ventures" - }, - { - "author_name": "Staci Sutermaster", - "author_inst": "Surgo Ventures" + "author_name": "Jonas Grzesiak", + "author_inst": "German Aerospace Center (DLR)" }, { - "author_name": "Lindsay Coome", - "author_inst": "Surgo Ventures" + "author_name": "Lea Fellner", + "author_inst": "German Aerospace Center (DLR)" }, { - "author_name": "Aaron Dibner-Dunlap", - "author_inst": "Surgo Ventures" + "author_name": "Karin Gr\u00fcnewald", + "author_inst": "German Aerospace Center (DLR)" }, { - "author_name": "Mokshada Jain", - "author_inst": "Surgo Ventures" + "author_name": "Christoph K\u00f6lbl", + "author_inst": "German Aerospace Center (DLR)" }, { - "author_name": "Yael Caplan", - "author_inst": "Surgo Ventures" + "author_name": "Arne Walter", + "author_inst": "German Aerospace Center (DLR)" }, { - "author_name": "Christine Campigotto", - "author_inst": "Surgo Ventures" + "author_name": "Reinhold Horlacher", + "author_inst": "Trenzyme GmbH" }, { - "author_name": "Sema K. Sgaier", - "author_inst": "Surgo Ventures; Department of Global Health and Population, Harvard T.H. Chan School of Public Health; Department of Global Health, University of Washington" + "author_name": "Frank Duschek", + "author_inst": "German Aerospace Center (DLR)" } ], "version": "1", - "license": "cc_by_nc", - "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "license": "cc_by", + "type": "new results", + "category": "biophysics" }, { "rel_doi": "10.1101/2021.05.14.21257058", @@ -728967,29 +727324,61 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.15.21257264", - "rel_title": "A novel deterministic epidemic model considering mass vaccination and lockdown against Covid-19 spread in Israel: Numerical study", + "rel_doi": "10.1101/2021.05.13.21257143", + "rel_title": "Non-differential risk of SARS-CoV-2 infection for members of polling stations on Catalan parliament voting day.", "rel_date": "2021-05-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.15.21257264", - "rel_abs": "Why public health intervention by the Israeli government against coronavirus disease 2019 spread has been successful while the majority of other countries are still coping with it? To give a quantitative answer, a simple numerical epidemic model is prepared to simulate the entire trend of various infection-related variables considering the 1st and 2nd vaccination campaigns against the alpha variant and simultaneous lockdown. This model is an extension of our previously published deterministic physical model, i.e. Apparent Time Lag Model, which aims at predicting an entire trend of variables in a single epidemic. The time series data of both vaccine dose ratio and lockdown period are employed in the model. Predictions have been compared with observed data in terms of daily new cases, isolated people, infections at large and effective reproductive number, and, further, the model is verified. Moreover, parameter survey calculations for several scenarios have clarified the synergy effects of vaccination and lockdown. In particular, the key element of Israels success has been suggested to lie in a high-dose vaccination rate that prevents the onset of a rebound in daily new cases on the rescission of the lockdown.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.13.21257143", + "rel_abs": "We aimed to assess the risk of SARS-CoV-2 infection for polling station members during the Catalan elections in February 2021. We compared the incidence 14 days after the elections between a cohort of polling station members (N= 18,304) and a control cohort paired by age, sex and place of residence. A total of 37 COVID-19 cases (0.2%) were confirmed in the members of the polling stations and 43 (0.23%) in the control group (p-value 0.576). Our study suggests that there was no greater risk of infection for the members of the polling stations.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Motoaki Utamura", - "author_inst": "Utamura professional engineer office" + "author_name": "Manuel Medina-Peralta", + "author_inst": "Sistemes Informaci\u00f3 dels Serveis Atenci\u00f3 Prim\u00e0ria, Institut Catal\u00e0 de la Salut" }, { - "author_name": "Makoto Koizumi", - "author_inst": "individual" + "author_name": "Luis Garcia-Eroles", + "author_inst": "\u00c0rea de Sistemes d'Informaci\u00f3, Servei Catal\u00e0 de la Salut" }, { - "author_name": "Seiichi Kirikami", - "author_inst": "Individual" + "author_name": "Eduardo Hermosilla", + "author_inst": "IDIAP Jordi Gol" + }, + { + "author_name": "Antonio Fuentes", + "author_inst": "\u00c0rea de Sistemes d'Informaci\u00f3, Servei Catal\u00e0 de la Salut" + }, + { + "author_name": "Leonardo M\u00e9ndez-Boo", + "author_inst": "Sistemes Informaci\u00f3 dels Serveis Atenci\u00f3 Prim\u00e0ria, Institut Catal\u00e0 de la Salut" + }, + { + "author_name": "Francesc Fina", + "author_inst": "Sistemes Informaci\u00f3 dels Serveis Atenci\u00f3 Prim\u00e0ria, Institut Catal\u00e0 de la Salut" + }, + { + "author_name": "Mireia F\u00e0bregas", + "author_inst": "Sistemes Informaci\u00f3 dels Serveis Atenci\u00f3 Prim\u00e0ria, Institut Catal\u00e0 de la Salut" + }, + { + "author_name": "Ermengol Coma", + "author_inst": "Sistemes Informaci\u00f3 dels Serveis Atenci\u00f3 Prim\u00e0ria, Institut Catal\u00e0 de la Salut" + }, + { + "author_name": "Yolanda Lejardi", + "author_inst": "Direcci\u00f3 Assistencial Atenci\u00f3 Prim\u00e0ria, Institut Catal\u00e0 de la Salut" + }, + { + "author_name": "Marc Ramentol", + "author_inst": "Generalitat de Catalunya" + }, + { + "author_name": "Ismael Pe\u00f1a-L\u00f3pez", + "author_inst": "Generalitat de Catalunya" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -732213,39 +730602,43 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2021.05.16.21257299", - "rel_title": "Indian Interventional trials for COVID-19 drugs: Insights and Learnings", + "rel_doi": "10.1101/2021.05.16.21256907", + "rel_title": "SPEEDS: A Portable Serological Testing Platform for Rapid Electrochemical Detection of SARS-CoV-2 Antibodies", "rel_date": "2021-05-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.16.21257299", - "rel_abs": "Since the COVID-19 pandemic began, India has substantially contributed to drug development and clinical research. Task Force on Repurposing of Drugs (TFORD) for COVID19 has tried to look at the overall position of India in terms of interventional clinical trials and highlight learnings which can prepare us to fight future pandemics in a better way. Trials registered on CTRI from March 2020 to December 2020 were considered for this purpose. From a total 409 trials registered, 108 focused on modern drugs. From 108 trials studied, 92 were randomized trials, 34 trials were sponsored by Indian Pharmaceutical industry, 23 were self-sponsored and 20 were sponsored by Research institutes and hospitals. Only 83 trials studied the repurposed drugs. An unfortunate revelation was that out of 108 trials, 79 showed as not yet recruiting. This highlights the urgent need for Government, Research institutions and Indian Pharmaceutical industries to break down silos and work together towards this common cause.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.16.21256907", + "rel_abs": "The COVID-19 pandemic has resulted in a worldwide health crisis. Rapid diagnosis, new therapeutics and effective vaccines will all be required to stop the spread of COVID-19. Quantitative evaluation of serum antibody levels against the SARS-CoV-2 virus provides a means of monitoring a patients immune response to a natural viral infection or vaccination, as well as evidence of a prior infection. In this paper, a portable and low-cost electrochemical immunosensor is developed for the rapid and accurate quantification of SARS-CoV-2 serum antibodies. The immunosensor is capable of quantifying the concentrations of immunoglobulin G (IgG) and immunoglobulin M (IgM) antibodies against the SARS-CoV-2 spike protein in human serum. For IgG and IgM, it provides measurements in the range of 10.1 ng/mL - 60 {micro}g/mL and 1.64 ng/mL - 50 {micro}g/mL, respectively, and both antibodies can be assayed in 13 min. We also developed device stabilization and storage strategies to achieve stable performance of the immunosensor within 24-week storage at room temperature. We evaluated the performance of the immunosensor using COVID-19 patient serum samples collected at different time points after symptom onset. The rapid and sensitive detection of IgG and IgM provided by our immunosensor fulfills the need of rapid COVID-19 serology testing for both point-of-care diagnosis and population immunity screening.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Arati Nikhil Ranade", - "author_inst": "Venture Center" + "author_name": "Ran Peng", + "author_inst": "University of Toronto" }, { - "author_name": "Kirtee Wani", - "author_inst": "Venture Center" + "author_name": "Yueyue Pan", + "author_inst": "University of Toronto" }, { - "author_name": "Premnath Venugopalan", - "author_inst": "CSIR-National Chemical Laboratory" + "author_name": "Zhijie Li", + "author_inst": "University of Toronto" }, { - "author_name": "Chitra Lele", - "author_inst": "ActuReal Services and Consulting" + "author_name": "Zhen Qin", + "author_inst": "University of Toronto" }, { - "author_name": "Smita Sandeep Kale", - "author_inst": "Venture Center" + "author_name": "James M. Rini", + "author_inst": "University of Toronto" + }, + { + "author_name": "Xinyu Liu", + "author_inst": "University of Toronto" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.05.18.21257267", @@ -734303,35 +732696,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.11.21257055", - "rel_title": "COVID-19 Patients Analysis using Superheat Map and Bayesian Network to identify Comorbidities Correlations under Different Scenarios.", + "rel_doi": "10.1101/2021.05.11.21256774", + "rel_title": "Psychosocial and Behavioral Responses and SARS-CoV-2 Transmission Prevention Behaviors while Working during the COVID-19 Pandemic", "rel_date": "2021-05-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.11.21257055", - "rel_abs": "BackgroundGiven the exposure risk of comorbidities in Mexican society, the new pandemic involves the highest risk for the population in the history.\n\nObjectiveThis article presents an analysis of the COVID-19 risk from Mexicos regions.\n\nMethodThe study period runs from April 12 to June 29, 2020 (220,667 patients). The method has a nature applied and according to its level of deepening in the object of study it is framed in a descriptive and explanatory analysis type. The data used here has a quantitative and semi-quantitative characteristic because they are the result of a questionnaire instrument made up of 34 fields and the virus test. The instrument is of a deliberate type. According to the manipulation of the variables, this research is a secondary type of practices, and it has a factual inference from an inductive method because it is emphasizing the concomitant variations for each region of the country.\n\nResultsRegion 1 and Region 4 have a higher percentage of hospitalized patients, while Region 2 has a minimum of them. The average age of non-hospitalized patients is around 40 years old, while the hospitalized patients age it is close to 55 years. The most sensitive comorbidities in hospitalized patients are three principal: obesity, diabetes mellitus and hypertension. The patients whose needed the mechanical respirator were in ranged from 7.45% to 10.79%.\n\nConclusionsThere is a higher risk of lose their lives in the Region 1 and Region 4 territories than in the Region 2, this information was dictated by the statistical analysis..", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.11.21256774", + "rel_abs": "BackgroundThe impact of coronavirus disease-2019 (COVID-19) on psychosocial and behavioral responses of the non-healthcare workforce is unknown. This study investigated these outcomes in this population during the pandemic while also evaluating transmission prevention behavior implementation at the workplace.\n\nMethodsWe deployed the baseline questionnaire of a prospective online survey from November 2020-February 2021 to U.S.-based employees. The survey included questions on psychosocial and behavioral responses in addition to transmission prevention behaviors (e.g., mask wear). Select questions asked employees to report perceptions and behaviors before and during the COVID-19 pandemic. Data were analyzed descriptively and stratified by work from home (WFH) percentage.\n\nResultsIn total, 3,607 employees completed the survey from eight companies. Most participants (70.0%) averaged [≥]90% of their time WFH during the pandemic. Employees reported increases in stress (54.0%), anxiety (57.4%), fatigue (51.6%), and feeling unsafe (50.4%) from before to during the pandemic, while feeling a lack of companionship (60.5%) and isolation from others (69.3%). Productivity was perceived to decrease, and non-work screen time and alcohol consumption to increase, for 43.0%, 50.7%, and 25.1% of employees, respectively, from before to during the pandemic. Adverse changes were worse among those with lower WFH percentages. Most employees reported wearing a mask (98.2%), washing hands regularly (95.7%), and physically distancing (93.6%) when at workplace.\n\nConclusionResults suggested worsened psychosocial and behavioral outcomes from before to during the COVID-19 pandemic and higher transmission prevention behavior implementation among non-healthcare employees. Observations provide novel insight into how the COVID-19 pandemic has impacted non-healthcare employees.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Oralia Nolasco-Jauregui Sr.", - "author_inst": "Biostatistics Department of Tecana American University" + "author_name": "Araliya M Senerat", + "author_inst": "Well Living Lab" }, { - "author_name": "Luis Alberto Quezada-Tellez Sr.", - "author_inst": "Universidad Iberoamericana" + "author_name": "Zachary Pope", + "author_inst": "Well Living Lab; Department of Physiology and Biomedical Engineering, Mayo Clinic" }, { - "author_name": "Erika E Rodriguez-Torres Sr.", - "author_inst": "Universidad Autonoma del Estado de Hidalgo" + "author_name": "Sarah Rydell", + "author_inst": "Division of Epidemiology & Community Health, University of Minnesota" }, { - "author_name": "Guillermo Fernandez-Anaya Sr.", - "author_inst": "Universidad Iberoamericana" + "author_name": "Aidan Mullan", + "author_inst": "Department of Quantitative Health Sciences, Mayo Clinic" + }, + { + "author_name": "Veronique Roger", + "author_inst": "Department of Cardiovascular Diseases Medicine, Mayo Clinic College of Medicine; Epidemiology and Community Health Branch National Heart, Lung and Blood Institu" + }, + { + "author_name": "Mark Pereira", + "author_inst": "Division of Epidemiology & Community Health, University of Minnesota" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.05.15.21256976", @@ -736221,18 +734622,99 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.14.444026", - "rel_title": "CovidExpress: an interactive portal for intuitive investigation on SARS-CoV-2 related transcriptomes", + "rel_doi": "10.1101/2021.05.16.444004", + "rel_title": "Potent neutralization of SARS-CoV-2 variants of concern by an antibody with a unique genetic signature and structural mode of spike recognition", "rel_date": "2021-05-16", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.14.444026", - "rel_abs": "Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in humans could cause coronavirus disease 2019 (COVID-19). Since its first discovery in Dec 2019, SARS-CoV-2 has become a global pandemic and caused 3.3 million direct/indirect deaths (2021 May). Amongst the scientific communitys response to COVID-19, data sharing has emerged as an essential aspect of the combat against SARS-CoV-2. Despite the ever-growing studies about SARS-CoV-2 and COVID-19, to date, only a few databases were curated to enable access to gene expression data. Furthermore, these databases curated only a small set of data and do not provide easy access for investigators without computational skills to perform analyses. To fill this gap and advance open-access to the growing gene expression data on this deadly virus, we collected about 1,500 human bulk RNA-seq datasets from publicly available resources, developed a database and visualization tool, named CovidExpress (https://stjudecab.github.io/covidexpress). This open access database will allow research investigators to examine the gene expression in various tissues, cell lines, and their response to SARS-CoV-2 under different experimental conditions, accelerating the understanding of the etiology of this disease to inform the drug and vaccine development. Our integrative analysis of this big dataset highlights a set of commonly regulated genes in SARS-CoV-2 infected lung and Rhinovirus infected nasal tissues, including OASL that were under-studied in COVID-19 related reports. Our results also suggested a potential FURIN positive feedback loop that might explain the evolutional advantage of SARS-CoV-2.", - "rel_num_authors": 0, - "rel_authors": null, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.16.444004", + "rel_abs": "The emergence of novel SARS-CoV-2 lineages that are more transmissible and resistant to currently approved antibody therapies poses a considerable challenge to the clinical treatment of COVID-19. Therefore, the need for ongoing discovery efforts to identify broadly reactive monoclonal antibodies to SARS-CoV-2 is of utmost importance. Here, we report a panel of SARS-CoV-2 antibodies isolated using the LIBRA-seq technology from an individual who recovered from COVID-19. Of these antibodies, 54042-4 showed potent neutralization against authentic SARS-CoV-2 viruses, including variants of concern (VOCs). A cryo-EM structure of 54042-4 in complex with the SARS-CoV-2 spike revealed an epitope composed of residues that are highly conserved in currently circulating SARS-CoV-2 lineages. Further, 54042-4 possesses unique genetic and structural characteristics that distinguish it from other potently neutralizing SARS-CoV-2 antibodies. Together, these findings motivate 54042-4 as a lead candidate for clinical development to counteract current and future SARS-CoV-2 VOCs.", + "rel_num_authors": 20, + "rel_authors": [ + { + "author_name": "Kevin J Kramer", + "author_inst": "Vanderbilt University" + }, + { + "author_name": "Nicole V Johnson", + "author_inst": "The University of Texas at Austin" + }, + { + "author_name": "Andrea R Shiakolas", + "author_inst": "Vanderbilt University" + }, + { + "author_name": "Naveenchandra Suryadevara", + "author_inst": "Vanderbilt University Vaccine Center" + }, + { + "author_name": "Sivakumar Periasamy", + "author_inst": "University of Texas Medical Branch at Galveston" + }, + { + "author_name": "Nagarajan Raju", + "author_inst": "Vanderbilt University Vaccine Center" + }, + { + "author_name": "Jazmean K Williams", + "author_inst": "Integral Molecular" + }, + { + "author_name": "Daniel Wrapp", + "author_inst": "University of Texas at Austin" + }, + { + "author_name": "Seth J Zost", + "author_inst": "Vanderbilt University Vaccine Center" + }, + { + "author_name": "Clinton M Holt", + "author_inst": "Vanderbilt University" + }, + { + "author_name": "Ching-Lin Hsieh", + "author_inst": "University of Texas at Austin" + }, + { + "author_name": "Rachel E Sutton", + "author_inst": "Vanderbilt University Vaccine Center" + }, + { + "author_name": "Ariana Paulo", + "author_inst": "Vanderbilt Vaccine Center" + }, + { + "author_name": "Edgar Davidson", + "author_inst": "Integral Molecular" + }, + { + "author_name": "Benjamin J Doranz", + "author_inst": "Integral Molecular" + }, + { + "author_name": "James E. Crowe", + "author_inst": "Vanderbilt University Medical Center" + }, + { + "author_name": "Alexander Bukreyev", + "author_inst": "University of Texas Medical Branch at Galveston" + }, + { + "author_name": "Robert H Carnahan Jr.", + "author_inst": "Vanderbilt University Medical Center" + }, + { + "author_name": "Jason S McLellan", + "author_inst": "The University of Texas at Austin" + }, + { + "author_name": "Ivelin S Georgiev", + "author_inst": "Vanderbilt University Medical Center" + } + ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "bioinformatics" + "category": "immunology" }, { "rel_doi": "10.1101/2021.05.13.444010", @@ -738398,55 +736880,59 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2021.05.13.443955", - "rel_title": "Tyrosine Kinase Inhibitor Family of Drugs as Prospective Targeted Therapy for COVID-19 Based on In Silico And 3D-Human Vascular Lung Model Studies", + "rel_doi": "10.1101/2021.05.14.21256900", + "rel_title": "Efficacy and Safety of Polyherbal formulation as an add-on to the standard of care in mild to moderate COVID-19: A randomized, double-blind, placebo-controlled trial", "rel_date": "2021-05-14", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.13.443955", - "rel_abs": "COVID-19 pandemic has ravaged the world and vaccines have been rapidly developed as preventive measures. But there is no target-based therapy which can be used if infection sets in. Remdesiver and dexamethasone were not designed to combat COVID-19 but are used clinically till better targeted therapies are available. Given this situation target based therapies that intervene in the disease pathway are urgently needed.\n\nSince COVID-19 genesis is driven by uncontrolled inflammation/thrombosis and protein kinases are critical in mounting this response, we explored if available tyrosine kinase inhibitors (TKIs) can be used as intervention. We profiled four TKIs namely; Lapatinib, Dasatinib, Pazopanib and Sitravatinib which inhibit tyrosine kinases but are completely distinct in their chemical structures.\n\nWe demonstrate using in silico and an in vitro 3D-human vascular lung model which profiles anti-inflammatory and anti-thrombogenic properties that all four TKIs are active in varying degrees. Our findings that chemically different TKIs which share kinase inhibition as the common mechanism of action are active, strongly indicates that its a tyrosine kinase target-based activity and not off-target arbitrary effect. We propose that TKIs, approved for human use and widely available, can be rapidly deployed as specific target-based therapy for COVID-19.", - "rel_num_authors": 9, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.14.21256900", + "rel_abs": "ObjectiveTo assess the efficacy and safety of polyherbal formulation (designated as IP) in comparison to placebo as add on to the standard of care (SoC) among patients with mild to moderate novel corona virus disease 2019 (COVID-19)\n\nMethodsLaboratory proved patients of mild to moderate COVID-19 disease were randomized to either placebo or IP as an add-on to SoC. Using quantitative reverse transcription-polymerase chain reaction (qRTPCR), we assessed the effect on viral load (VL). Change in immunological parameters such as blood lymphocyte subset, serum immunoglobulin was determined. The clinical improvement was assessed using a numerical rating scale (NRS) and WHO ordinal scale. Patients were followed for 30 days after randomization.\n\nResultsIn total, 72 patients were randomized to either placebo (n=33) and IP (n=39). Fifty-two patients (n=21 in placebo and n=31 in IP arm) had qRT-PCR on day 0 and day 4. There was significant reduction in VL in IP arm (from 662081 copies/mL on day 0 to 48963 copies/mL on day 4; p=0.002)) but not in the placebo arm (from 385670 copies/mL on day 0 to 66845 copies/mL on day 4, p=0.106). Change in the NRS score and WHO ordinal scale score was significant in both treatment arms. However, the difference between the two groups was statistically significant in favour of drug group. The increase in Th1 response was significant in the IP arm (p=0.023) but not in the placebo arm (p=0.098), thus implying immunomodulatory activity in the drug. No safety concerns were observed in any of the trial participants.\n\nConclusionThis study finds that polyherbal formulation reduces viral load and contributes to immunomodulation and improvement in clinical conditions when used as add-on to the standard care in patients with mild to moderate COVID-19 without any side effects. These findings need to be further confirmed in a large, prospective, randomized study.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Shalini Saxena", - "author_inst": "INDRAS Pvt. Ltd" + "author_name": "Suresh Balkrishna Patankar", + "author_inst": "AMAI Charitable Trust, Pune, India" }, { - "author_name": "Kranti Meher", - "author_inst": "Reagene Innovations Pvt Ltd" + "author_name": "Hrishikesh Rangnekar", + "author_inst": "Quest Clinical Services, Pune" }, { - "author_name": "Madhuri Rotella", - "author_inst": "Reagene Innovations Pvt Ltd" + "author_name": "Kalpana Joshi", + "author_inst": "Dept. of Biotechnology, Sinhagad College of Engineering, Pune" }, { - "author_name": "Subhramanyam Vangala", - "author_inst": "Reagene Innovations Pvt Ltd" + "author_name": "Kishor Suryawanshi", + "author_inst": "YCM Hospital, Pune" }, { - "author_name": "Satish Chandran", - "author_inst": "Reagene Innovations Pvt Ltd" + "author_name": "Pravin Soni", + "author_inst": "YCM Hospital, Pune" }, { - "author_name": "Nikhil Malhotra", - "author_inst": "TechMahindra Ltd" + "author_name": "Anupama Gorde", + "author_inst": "Sinhgad Institute of Medical Sciences, Pune" }, { - "author_name": "Ratnakar Palakodeti", - "author_inst": "TechMahindra Ltd" + "author_name": "Tejas Shah", + "author_inst": "KRSNNA Diagnostics Pvt. Ltd." }, { - "author_name": "Sreedhara Voleti", - "author_inst": "Indras Private Ltd" + "author_name": "Sagar Patankar", + "author_inst": "AMAI Charitable Trust, Pune" }, { - "author_name": "Uday Saxena", - "author_inst": "Reagene Innovations Pvt Ltd" + "author_name": "Diwakar Jha", + "author_inst": "SHRIPAD Medisearch Pvt. Ltd" + }, + { + "author_name": "Rajesh Raje", + "author_inst": "AMAI Charitable Trust,Pune" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "pharmacology and toxicology" + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.05.13.21256639", @@ -741084,47 +739570,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.11.21256147", - "rel_title": "Significant and sustained decrease in non-SARS-CoV-2 respiratory viral infections during COVID-19 public health interventions.", + "rel_doi": "10.1101/2021.05.12.21256975", + "rel_title": "Inferring the COVID-19 IFR with a simple Bayesian evidence synthesis of seroprevalence study data and imprecise mortality data", "rel_date": "2021-05-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.11.21256147", - "rel_abs": "Public health interventions to decrease the spread of SARS-CoV-2 were largely implemented in the United States during spring 2020. This study evaluates the additional effects of these interventions on non-SARS-CoV-2 respiratory viral infections from a single healthcare system in the San Francisco Bay Area. The results of a respiratory pathogen multiplex polymerase chain reaction panel intended for inpatient admissions were analyzed by month between 2019 and 2020. We found major decreases in the proportion and diversity of non-SARS-CoV-2 respiratory viral illnesses in all months following masking and shelter-in-place ordinances. These findings suggest real-world effectiveness of nonpharmaceutical interventions on droplet-transmitted respiratory infections.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.12.21256975", + "rel_abs": "Estimating the COVID-19 infection fatality rate (IFR) has proven to be particularly challenging -and rather controversial- due to the fact that both the data on deaths and the data on the number of individuals infected are subject to many different biases. We consider a Bayesian evidence synthesis approach which, while simple enough for researchers to understand and use, accounts for many important sources of uncertainty inherent in both the seroprevalence and mortality data. With the understanding that the results of ones evidence synthesis analysis may be largely driven by which studies are included and which are excluded, we conduct two separate parallel analyses based on two lists of eligible studies obtained from two different research teams. The results from both analyses are rather similar. With the first analysis, we estimate the COVID-19 IFR to be 0.31% (95% credible interval of (0.16%, 0.53%)) for a typical community-dwelling population where 9% of the population is aged over 65 years and where the gross-domestic product at purchasing-power parity (GDP at PPP) per capita is $17.8k (the approximate worldwide average). With the second analysis, we obtain 0.32% (95% credible interval of (0.19%, 0.47%)). Our results suggest that, as one might expect, lower IFRs are associated with younger populations (and may also be associated with wealthier populations). For a typical community-dwelling population with the age and wealth of the United States we obtain IFR estimates of 0.43% and 0.41%; and with the age and wealth of the European Union, we obtain IFR estimates of 0.67% and 0.51%. O_QDAbove all, whats needed is humility in the face of an intricately evolving body of evidence. The pandemic could well drift or shift into something that defies our best efforts to model and characterize it.\n\nSiddhartha Mukherjee, The New Yorker\n\nFebruary 22, 2021\n\nC_QD", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Jeffrey D. Whitman", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Phong Pham", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Caryn Bern", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Elaine M. Dekker", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Barbara L. Haller", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Vivek Jain", - "author_inst": "University of California, San Francisco" + "author_name": "Harlan Campbell", + "author_inst": "University of British Columbia" }, { - "author_name": "Lisa G. Winston", - "author_inst": "University of California, San Francisco" + "author_name": "Paul Gustafson", + "author_inst": "University of British Columbia" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.05.06.21256738", @@ -742806,91 +741272,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.10.21256644", - "rel_title": "Reinfection by the SARS-CoV-2 P.1 variant in blood donors in Manaus, Brazil", + "rel_doi": "10.1101/2021.05.10.21256999", + "rel_title": "Who should get vaccinated first? An effective network information-driven priority vaccination strategy", "rel_date": "2021-05-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.10.21256644", - "rel_abs": "BackgroundThe city of Manaus, north Brazil, was stricken by a second epidemic wave of SARS-CoV-2 despite high seroprevalence estimates, coinciding with the emergence of the Gamma (P.1) variant. Reinfections were postulated as a partial explanation for the second surge. However, accurate calculation of reinfection rates is difficult when stringent criteria as two time-separated RT-PCR tests and/or genome sequencing are required. To estimate the proportion of reinfections caused by the Gamma variant during the second wave in Manaus and the protection conferred by previous infection, we analyzed a cohort of repeat blood donors to identify anti-SARS-CoV-2 antibody boosting as a means to infer reinfection.\n\nMethodsWe tested serial blood samples from unvaccinated repeat blood donors in Manaus for the presence of anti-SARS-CoV-2 IgG antibody. Donors were required to have three or more donations and at least one donation during each epidemic wave. Donors were tested with two assays that display waning in early convalescence, enabling the detection of reinfection-induced boosting. The serial samples were used to divide donors into six groups defined based on the inferred sequence of infection and reinfection with non-Gamma and Gamma variants.\n\nResultsFrom 3,655 repeat blood donors, 238 met all inclusion criteria, and 223 had enough residual sample volume to perform both serological assays. Using a strict serological definition of reinfection, we found 13.6% (95% CI 7.0% - 24.5%) of all presumed Gamma infections that were observed in 2021 were reinfections. If we also include cases of probable or possible reinfections, these percentages increase respectively to 22.7% (95% CI 14.3% - 34.2%) and 39.3% (95% CI 29.5% - 50.0%). Previous infection conferred a protection against reinfection of 85.3% (95% CI 71.3% - 92.7%), decreasing to respectively 72.5% (95% CI 54.7% - 83.6%) and 39.5% (95% CI 14.1% - 57.8%) if probable and possible reinfections are included.\n\nConclusionsReinfection due to Gamma is common and may play a significant role in epidemics where Gamma is prevalent, highlighting the continued threat variants of concern pose even to settings previously hit by substantial epidemics.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.10.21256999", + "rel_abs": "Approval of emergency use of the Novel Coronavirus Disease 2019 (COVID-19) vaccines in many countries has brought hope to ending the COVID-19 pandemic sooner. Considering the limited vaccine supply in the early stage of COVID-19 vaccination programs in most countries, a highly relevant question to ask is: who should get vaccinated first? In this article we propose a network information-driven vaccination strategy where a small number of people in a network (population) are categorized, according to a few key network properties, into priority groups. Using a network-based SEIR model for simulating the pandemic progression, the network information-driven vaccination strategy is compared with a random vaccination strategy. Results for both large-scale synthesized networks and real social networks have demonstrated that the network information-driven vaccination strategy can significantly reduce the cumulative number of infected individuals and lead to a more rapid containment of the pandemic. The results provide insight for policymakers in designing an effective early-stage vaccination plan.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Carlos A. Prete Jr.", - "author_inst": "Department of Electronic Systems Engineering, University of Sao Paulo" - }, - { - "author_name": "Lewis F Buss", - "author_inst": "Departamento de Molestias Infecciosas e Parasitarias and Instituto de Medicina Tropical da Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil" - }, - { - "author_name": "Renata Buccheri", - "author_inst": "Vitalant Research Institute, San Francisco CA, USA" - }, - { - "author_name": "Claudia M. M. Abrahim", - "author_inst": "Fundacao Hospitalar de Hematologia e Hemoterapia do Amazonas, Manaus, Brazil" - }, - { - "author_name": "Tassila Salomon", - "author_inst": "Fundacao Hemominas and Falculdade de Ciencias Medicas de Minas Gerais, Brazil" - }, - { - "author_name": "Myuki A. E. Crispim", - "author_inst": "Fundacao Hospitalar de Hematologia e Hemoterapia do Amazonas, Manaus, Brazil." - }, - { - "author_name": "Marcio K. Oikawa", - "author_inst": "Center of Mathematics, Computing and Cognition, Universidade Federal do ABC, Brazil" - }, - { - "author_name": "Eduard Grebe", - "author_inst": "Vitalant Research Institute; University of California San Francisco, San Fracisco CA, USA; SACEMA, Stellenbosch University, Stellenbosch, South Africa" - }, - { - "author_name": "Allyson G. da Costa", - "author_inst": "Fundacao Hospitalar de Hematologia e Hemoterapia do Amazonas, Manaus, Brazil." - }, - { - "author_name": "Nelson A. Fraiji", - "author_inst": "Fundacao Hospitalar de hematologia e Hemoterapia do Amazonas - HEMOAM" - }, - { - "author_name": "Maria do P. S. S. Carvalho", - "author_inst": "Fundacao Hospitalar de hematologia e Hemoterapia do Amazonas - HEMOAM" - }, - { - "author_name": "Charles Whittaker", - "author_inst": "Imperial College, London" - }, - { - "author_name": "Neal Alexander", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Nuno R. Faria", - "author_inst": "Department of Infectious Disease Epidemiology, Imperial College London, UK; Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, " - }, - { - "author_name": "Christopher Dye", - "author_inst": "Department of Zoology, University of Oxford, UK" + "author_name": "Dong Liu", + "author_inst": "City University of Hong Kong" }, { - "author_name": "Vitor H. Nascimento", - "author_inst": "Department of Electronic Systems Engineering, University of Sao Paulo, Brazil" + "author_name": "Chi K. Tse", + "author_inst": "City University of Hong Kong" }, { - "author_name": "Michael Paul Busch", - "author_inst": "Vitalant Research Institute; University of California San Francisco, San Francisco CA, USA" + "author_name": "Rosa Ho Man Chan", + "author_inst": "City University of Hong Kong" }, { - "author_name": "Ester C. Sabino", - "author_inst": "Instituto de Medicina Tropical, University of Sao Paulo, Brazil" + "author_name": "Choujun Zhan", + "author_inst": "South China Normal University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "health policy" }, { "rel_doi": "10.1101/2021.05.11.21257016", @@ -744932,123 +743342,51 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.10.21256920", - "rel_title": "Comparison of Mental Health Symptoms prior to and during COVID-19: Evidence from a Living Systematic Review and Meta-analysis", + "rel_doi": "10.1101/2021.05.11.21257027", + "rel_title": "COVID-19 Pandemic and Prevalence of Self-care Practices among the Future Physicians: A Bangladesh Study", "rel_date": "2021-05-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.10.21256920", - "rel_abs": "ObjectivesThe rapid pace, high volume, and limited quality of mental health evidence that has been generated during COVID-19 poses a barrier to understanding mental health outcomes. We sought to summarize results from studies that compared mental health outcomes during COVID-19 to outcomes assessed prior to COVID-19 in the same cohort in the general population and in other groups for which data have been reported.\n\nDesignLiving systematic review.\n\nData SourcesMEDLINE (Ovid), PsycINFO (Ovid), CINAHL (EBSCO), EMBASE (Ovid), Web of Science Core Collection: Citation Indexes, China National Knowledge Infrastructure, Wanfang, medRxiv (preprints), and Open Science Framework Preprints (preprint server aggregator).\n\nEligibility criteria for selecting studiesFor this report, we included studies that compared general mental health, anxiety symptoms, or depression symptoms, assessed January 1, 2020 or later, to the same outcomes collected between January 1, 2018 and December 31, 2019. Any population was eligible. We required [≥] 90% of participants pre-COVID-19 and during COVID-19 to be the same or the use of statistical methods to address missing data. For population groups with continuous outcomes for at least two studies in an outcome domain, we conducted restricted maximum-likelihood random-effects meta-analyses. Worse COVID-19 mental health outcomes are reported as positive. Risk of bias of included studies was assessed using an adapted version of the Joanna Briggs Institute Checklist for Prevalence Studies.\n\nResultsAs of April 11, 2022, we had reviewed 94,411 unique titles and abstracts and identified 137 unique eligible studies with data from 134 cohorts. Almost all studies were from high-income (105, 77%) or upper-middle income (28, 20%) countries. Among adult general population studies, we did not find changes in general mental health (standardized mean difference of change [SMDchange = 0.11, 95% CI -0.00 to 0.22) or anxiety symptoms (SMDchange = 0.05, 95% CI -0.04 to 0.13), but depression symptoms worsened minimally (SMDchange = 0.12, 95% CI 0.01 to 0.24). Among women or females, mental health symptoms worsened by minimal to small amounts in general mental health (SMDchange = 0.22, 95% CI 0.08 to 0.35), anxiety symptoms (SMDchange = 0.20, 95% CI 0.12 to 0.29), and depression symptoms (SMDchange = 0.22, 95% CI 0.05 to 0.40). Of 27 other analyses across outcome domains, among subgroups other than women or females, 5 analyses suggested minimal or small amounts of symptom worsening, and 2 suggested minimal or small symptom improvements. No other subgroup experienced statistically significant changes across outcome domains. In the 3 studies with data from March to April 2020 and later in 2020, symptoms either were unchanged from pre-COVID-19 at both time points or increased initially then returned to pre-COVID-19 levels. Heterogeneity measured by the I2 statistic was high (e.g., > 80%) for most analyses, and there was concerning risk of bias in most studies.\n\nConclusionsHigh risk of bias in many studies and substantial heterogeneity suggest that point estimates should be interpreted cautiously. Nonetheless, there was general consistency across analyses in that most symptom change estimates were close to zero and not statistically significant, and changes that were identified were of minimal to small magnitudes. There were, however, small negative changes for women or females in all domains. It is possible that gaps in data have not allowed identification of changes in some vulnerable groups. Continued updating is needed as evidence accrues.\n\nFunding: Canadian Institutes of Health Research (CMS-171703; MS1-173070; GA4-177758; WI2-179944); McGill Interdisciplinary Initiative in Infection and Immunity Emergency COVID-19 Research Fund (R2-42).\n\nRegistration: PROSPERO (CRD42020179703); registered on April 17, 2020.", - "rel_num_authors": 26, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.11.21257027", + "rel_abs": "BackgroundSince December 2019, the novel coronavirus, SARS-CoV-2, has garnered global attention due to its rapid transmission, which has infected more than twenty nine million people worldwide. World is facing enormous stress and anxiety as there is no effective medicine or vaccine to treat or prevent COVID-19 till date. Experts are recommending self-care like social distancing, respiratory etiquette, hand washing, using face mask to prevent corona virus infection.\n\nMaterials and methodsThis descriptive cross-sectional study was designed to assess the prevalence of self-care practice among the undergraduate medical students (4th year) of 14 medical colleges of Bangladesh during COVID-19 pandemic. A structured questionnaire survey linked in the google form was used as study instrument and was distributed among study population through email, messenger, whatsapp and other social media during the month of October 2020. Total 916 students were participated in the study.\n\nResults79.8% of students reported self-care practice in study period. 44.98% of students went outside once in a week. 90.5%, 70.96% and 52.62% of respondents always used face mask, followed 20 seconds hand washing principle and maintained social distancing. Face masks (97.8%), sanitizers (76.7%) and gloves (71.9%) are most common items purchased as protective mesures. Most of the students (76.9%) follow their hobbies as a coping strategy to overcome phychological stress, while 6% of students took professional help.\n\nConclusionSuboptimal practice of self-care was found among the undergraduate medical students of Bangladesh.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Ying Sun", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" - }, - { - "author_name": "Yin Wu", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" - }, - { - "author_name": "Suiqiong Fan", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" - }, - { - "author_name": "Tiffany Dal Santo", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" - }, - { - "author_name": "Letong Li", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" - }, - { - "author_name": "Xiaowen Jiang", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" - }, - { - "author_name": "Kexin Li", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" - }, - { - "author_name": "Yutong Wang", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" - }, - { - "author_name": "Amina Tasleem", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" - }, - { - "author_name": "Ankur Krishnan", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" - }, - { - "author_name": "Chen He", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" - }, - { - "author_name": "Olivia Bonardi", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" - }, - { - "author_name": "Jill T. Boruff", - "author_inst": "Schulich Library of Physical Sciences, Life Sciences, and Engineering, McGill University, Montreal, Quebec, Canada" - }, - { - "author_name": "Danielle B. Rice", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" - }, - { - "author_name": "Sarah Markham", - "author_inst": "Department of Biostatistics and Health Informatics, King's College London, London, UK" - }, - { - "author_name": "Brooke Levis", - "author_inst": "Centre for Prognosis Research, School of Medicine, Keele University, Staffordshire, UK" - }, - { - "author_name": "Marleine Azar", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" - }, - { - "author_name": "Ian Thombs-Vite", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" - }, - { - "author_name": "Dipika Neupane", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" + "author_name": "Fatema Johora", + "author_inst": "Army Medical College Bogura" }, { - "author_name": "Branka Agic", - "author_inst": "Centre for Addiction and Mental Health, Toronto, Ontario, Canada" + "author_name": "Asma Akter Abbasy", + "author_inst": "Brahmanbaria Medical College" }, { - "author_name": "Christine Fahim", - "author_inst": "Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, Ontario, Canada" + "author_name": "Fatiha Tasmin Jeenia", + "author_inst": "Chattagram International Medical College" }, { - "author_name": "Michael S. Martin", - "author_inst": "School of Epidemiology and Public Health, University of Ottawa; Ontario, Canada" + "author_name": "Mithun Chandra Bhowmik", + "author_inst": "Rangpur Medical College" }, { - "author_name": "Sanjeev Sockalingam", - "author_inst": "Centre for Addiction and Mental Health, Toronto, Ontario, Canada" + "author_name": "Mohsena Aktar", + "author_inst": "Cumilla Medical College" }, { - "author_name": "Gustavo Turecki", - "author_inst": "Department of Psychiatry, McGill University, Montreal, Quebec, Canada" + "author_name": "Nargis Akhter Choudhury", + "author_inst": "Sheikh Hasina Medical College, Habiganj" }, { - "author_name": "Andrea Benedetti", - "author_inst": "Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada" + "author_name": "Priyanka Moitra", + "author_inst": "Colonel Malek Medical College, Manikganj" }, { - "author_name": "Brett D. Thombs", - "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada" + "author_name": "Jannatul Ferdoush", + "author_inst": "BGC Trust Medical College, Chattogram" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.05.11.21256479", @@ -747730,49 +746068,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.04.21255575", - "rel_title": "A Targeted Geospatial Approach to COVID-19 Vaccine Delivery: Findings from the Johns Hopkins Hospital Emergency Department", + "rel_doi": "10.1101/2021.05.08.21256831", + "rel_title": "Social and racial/ethnic differences in parental willingness to vaccinate children against COVID-19 in Montreal, Canada", "rel_date": "2021-05-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.04.21255575", - "rel_abs": "While COVID-19 vaccines have been shown to significantly decrease morbidity and mortality, there is still much debate about optimal strategies of vaccine rollout. We tested identity-unlinked stored remnant blood specimens of patients at least 18 years presenting to the Johns Hopkins Hospital emergency department (ED) between May to November 2020 for IgG to SARS-CoV-2. Data on SARS-CoV-2 RT PCR were available for patients who were tested due to suspected infection. SARS-CoV-2 infections was defined as either a positive IgG and/or RT-PCR. SARS-CoV-2 infection clustering by zipcode was analyzed by spatial analysis using the Bernoulli model (SaTScan software, Version 9.7). Median age of the 7,461 unique patients visiting the ED was 47 years and 50.8% were female; overall, 740 (9.9%) unique patients had evidence of SARS-CoV-2 infection. Prevalence of infection in ED patients by ZIP code ranged from 4.1% to 22.3%. The observed number of cases in ZIP code C was nearly double the expected (observed/expected ratio = 1.99; 95% CI: 1.62, 2.42). These data suggest a targeted geospatial approach to COVID vaccination should be considered to maximize vaccine rollout efficiency and include high-risk populations that may otherwise be subjected to delays, or missed.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.08.21256831", + "rel_abs": "BackgroundThe success of current and prospective COVID-19 vaccine campaigns for children and adolescents will in part depend on the willingness of parents to accept vaccination. This study examined social determinants of parental COVID-19 vaccine acceptance and uptake for children and adolescents.\n\nMethodsWe used cross-sectional data from an ongoing COVID-19 cohort study in Montreal, Canada and included all parents of 2 to 18-year-olds who completed an online questionnaire between May 18 and June 26, 2021 (n=809). We calculated child age-adjusted prevalence estimates of vaccine acceptance by parental education, race/ethnicity, birthplace, household income, and neighbourhood, and used multinomial logistic regression to estimate adjusted prevalence differences (aPD) and ratios (aPR). Social determinants of vaccine uptake were estimated for the vaccine-eligible sample of 12 to 18 year-olds (n=306).\n\nResultsIntention to vaccinate children against COVID-19 was high, with only 12.4% of parents unlikely to have their child vaccinated. Parents with younger children were less likely to accept vaccination, as were those from lower-income households, racialized groups, and those born outside Canada. The percent of parents whose child was vaccinated or very likely to be vaccinated was 18.4 percentage points lower among those with annual household incomes <$100,000 vs. [≥]$150,000 (95% CI: 10.1 to 26.7). Racialized parents reported greater unwillingness to vaccinate compared to White parents (aPD=10.3; 95% CI: 1.5, 19.1). Vaccine-eligible adolescents from the most deprived neighbourhood were half as likely to be vaccinated compared to those from the least deprived neighbourhood (aPR = 0.48; 95% CI: 0.18 to 0.77).\n\nInterpretationThis study identified marked social inequalities in COVID-19 vaccine acceptance and uptake for children and adolescents. Efforts are needed to reach disadvantaged and marginalized populations with tailored strategies that promote informed decision making and facilitate access to vaccination.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Sunil S Solomon", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Yu-Hsiang Hsieh", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Richard E Rothman", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Oliver Laeyendecker", - "author_inst": "Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health" + "author_name": "Britt McKinnon", + "author_inst": "University of Montreal" }, { - "author_name": "Shruti H Mehta", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Caroline Quach Thanh", + "author_inst": "University of Montreal" }, { - "author_name": "Mark Anderson", - "author_inst": "Abbott Laboratories" + "author_name": "Eve Dube", + "author_inst": "Laval University" }, { - "author_name": "Gavin Cloherty", - "author_inst": "Abbott Laboratories" + "author_name": "Cat Tuong Nguyen", + "author_inst": "Montreal regional department of public health" }, { - "author_name": "Thomas C Quinn", - "author_inst": "Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health" + "author_name": "Kate Zinszer", + "author_inst": "University of Montreal" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -749956,43 +748282,75 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.05.05.21254694", - "rel_title": "Impact of National and Regional Lockdowns on Growth of COVID-19 Cases in COVID-Hotspot City of Pune in Western India: A Real-World Data Analysis", + "rel_doi": "10.1101/2021.05.06.21256733", + "rel_title": "RT-qPCR-based tests for SARS-CoV-2 detection in pooled saliva samples for massive population screening to monitor epidemics.", "rel_date": "2021-05-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.05.21254694", - "rel_abs": "BackgroundReal-world data assessing the impact of lockdowns on COVID-19 cases remain limited from resource-limited settings. We examined growth of incident confirmed COVID-19 cases before, during and after lockdowns in Pune, a city in western India with 3.1 million population that reported the largest COVID-19 burden at the peak of the pandemic.\n\nMethodsUsing anonymized individual-level data captured by Punes public health surveillance program between February 1st and September 15th 2020, we assessed weekly incident COVID-19 cases, infection rates, and epidemic curves by lockdown status (overall and by sex, age, and population density) and modelled the natural epidemic using the 9-compartmental model INDSCI-SIM. Effect of lockdown on incident cases was assessed using multilevel Poisson regression. We used geospatial mapping to characterize regional spread.\n\nFindingsOf 241,629 persons tested for SARS-CoV-2, the COVID-19 disease rate was 267.0 (95% CI 265.3 - 268.8) per 1000 persons. Epidemic curves and geospatial mapping showed delayed peak of the cases by approximately 8 weeks during the lockdowns as compared to modelled natural epidemic. Compared to a subsequent unlocking period, incident COVID-19 cases 43% lower (IRR 0.57, 95% CI 0.53 - 0.62) during Indias nationwide lockdown and 22% (IRR 0.78, 95% CI 0.73 - 0.84) during Punes regional lockdown and was uniform across age groups and population densities.\n\nConclusionLockdowns slowed the growth of COVID-19 cases in population dense, urban region in India. Additional analysis from rural and semi-rural regions of India and other resource-limited settings are needed.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.06.21256733", + "rel_abs": "Swab, quantitative, reverse transcription polymerase chain reaction (RT-qPCR) tests remain the gold standard of diagnostics of SARS-CoV-2 infections. However, these tests are costly and time-consuming, and swabbing limits their throughput. We developed a 3-gene, seminested RT-qPCR test with SYBR green-based detection, optimized for testing pooled saliva samples for high-throughput diagnostics of epidemic-affected populations. The proposed two-tier approach depends on decentralized self-collection of saliva samples, pooling, 1st-tier testing with the mentioned highly sensitive screening test and subsequent 2nd-tier testing of individual samples from positive pools with the in vitro diagnostic (IVD) test. The screening test was able to detect 5 copies of the viral genome in 10 {micro}l of isolated RNA with 50% probability and 18.8 copies with 95% probability and reached Ct values that were highly linearly RNA concentration-dependent. In the side-by-side comparison (testing artificial pooled samples), the screening test attained slightly better results than the commercially available IVD-certified RT-qPCR diagnostic test (100% specificity and 89.8% sensitivity vs. 100% and 73.5%, respectively). Testing of 1475 individual clinical samples pooled in 374 pools of 4 revealed 0.8% false positive pools and no false negative pools. In weekly prophylactic testing of 113 people within 6 months, a two-tier testing approach enabled the detection of 18 infected individuals, including several asymptomatic individuals, with a fraction of the costs of individual RT-PCR testing.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Vidya Mave", - "author_inst": "Byramjee-Jeejeebhoy Government Medical College-Johns Hopkins University Clinical Research Site, Pune" + "author_name": "Michal Rozanski", + "author_inst": "Institute of Medical Biology PAS, Lodz, Poland" }, { - "author_name": "Arsh Shaikh", - "author_inst": "Indian Institute of Science Education and Research, Pune, India" + "author_name": "Aurelia Walczak-Drzewiecka", + "author_inst": "Institute of Medical Biology PAS, Lodz, Poland" }, { - "author_name": "Joy Merwin Monteiro", - "author_inst": "Indian Institute of Science Education and Research, Pune, India" + "author_name": "Jolanta Witaszewska", + "author_inst": "Proteon Pharmaceuticals S.A., Lodz, Poland" }, { - "author_name": "Prasad Bogam", - "author_inst": "Johns Hopkins India, Pune, India" + "author_name": "Ewelina Wojcik", + "author_inst": "Proteon Pharmaceuticals S.A., Lodz, Poland" }, { - "author_name": "Bhalchandra S Pujari", - "author_inst": "Savitribai Phule Pune University, Pune, India" + "author_name": "Arkadiusz Guzinski", + "author_inst": "Proteon Pharmaceuticals S.A., Lodz, Poland" }, { - "author_name": "Nikhil Gupte", - "author_inst": "Johns Hopkins India, Pune, India" + "author_name": "Bogumil Zimon", + "author_inst": "Proteon Pharmaceuticals S.A., Lodz, Poland" + }, + { + "author_name": "Rafal Matusiak", + "author_inst": "Proteon Pharmaceuticals S.A., Lodz, Poland" + }, + { + "author_name": "Joanna Kazimierczak", + "author_inst": "Proteon Pharmaceuticals S.A., Lodz, Poland" + }, + { + "author_name": "Maciej Borowiec", + "author_inst": "Medical University of Lodz, Lodz, Poland" + }, + { + "author_name": "Katarzyna Kania", + "author_inst": "Institute of Medical Biology PAS, Lodz, Poland" + }, + { + "author_name": "Edyta Paradowska", + "author_inst": "Institute of Medical Biology PAS, Lodz, Poland" + }, + { + "author_name": "Jakub Pawelczyk", + "author_inst": "Institute of Medical Biology PAS, Lodz, Poland" + }, + { + "author_name": "Jaroslaw Dziadek", + "author_inst": "Institute of Medical Biology PAS, Lodz, Poland" + }, + { + "author_name": "Jaroslaw Dastych", + "author_inst": "Proteon Pharmaceuticals S.A., Lodz, Poland; Institute of Medical Biology PAS, Lodz, Poland" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.05.05.21256668", @@ -752110,31 +750468,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.04.21256623", - "rel_title": "Vaccination strategies when vaccines are scarce: On conflicts between reducing the burden and avoiding the evolution of escape mutants", + "rel_doi": "10.1101/2021.05.04.21256636", + "rel_title": "Identification of risk and protective human leukocyte antigens in COVID-19 using genotyping and structural modeling", "rel_date": "2021-05-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.04.21256623", - "rel_abs": "When vaccine supply is limited but population immunisation urgent, the allocation of the available doses needs to be carefully considered. One aspect of dose allocation is the time interval between the primer and the booster injections in two-dose vaccines. By stretching this interval, more individuals can be vaccinated with the first dose more quickly. Even if the level of immunity of these half-vaccinated individuals is lower than that of those who have received both shots, delaying the second injection can be beneficial in reducing case numbers, provided a single dose is sufficiently effective. On the other hand, there has been concern that intermediate levels of immunity in partially vaccinated individuals may favour the evolution of vaccine escape mutants. In that case, a large fraction of half-vaccinated individuals would pose a risk - but only if they encounter the virus. This raises the question whether there is a conflict between reducing the burden and the risk of vaccine escape evolution or not. We develop a minimal model to assess the population-level effects of the timing of the booster dose. We set up an SIR-type model, in which more and more individuals become vaccinated with a two-dose vaccine over the course of a pandemic. As expected, there is no trade-off when vaccine escape evolves at equal probabilities in unvaccinated and half-vaccinated patients. If vaccine escape evolves more easily in half-vaccinated patients, the presence or absence of a trade-off depends on the reductions in susceptibility and transmissibility elicited by the primer dose.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.04.21256636", + "rel_abs": "COVID-19 is caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). The severity of COVID-19 is highly variable and related to known (e.g., age, obesity, immune deficiency) and unknown risk factors. Since innate and adaptive immune responses are elicited in COVID-19 patients, we genotyped 94 Florida patients with confirmed COVID-19 and 89 healthy controls. We identified an HLA gene, HLA-DPA1, in which specific alleles were associated with the risk of SARS-CoV-2 positivity and COVID-19 disease. HLA-DPA1*01:03 was associated with reduced incidence of SARS-CoV-2 positivity, whereas HLA-DPA1*03:01 was associated with increased risk of SARS-CoV-2 positivity. These data suggest a model in which COVID-19 severity is influenced by immunodominant peptides derived from SARS-CoV-2 preferentially presented by specific HLA-DP molecules to either protective (for asymptomatic COVID-19) or pathogenic T cells (in severe COVID-19). Although this study is limited to comparing SARS-CoV-2 positive and negative subjects, these data suggest that HLA typing of COVID-19 patients stratified for disease severity may be informative for identifying biomarkers and disease mechanisms in high-risk individuals.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "F\u00e9lix Geoffroy", - "author_inst": "Max Planck Institute for Evolutionary Biology" + "author_name": "Yiran Shen", + "author_inst": "University of Florida" }, { - "author_name": "Arne Traulsen", - "author_inst": "Max Planck Institute for Evolutionary Biology" + "author_name": "David Ostrov", + "author_inst": "University of Florida" }, { - "author_name": "Hildegard Uecker", - "author_inst": "Max Planck Institute for Evolutionary Biology" + "author_name": "Santosh Rananaware", + "author_inst": "University of Florida" + }, + { + "author_name": "Piyush K Jain", + "author_inst": "University of Florida" + }, + { + "author_name": "Cuong Nguyen", + "author_inst": "University of Florida" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2021.05.04.21256655", @@ -754220,35 +752586,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.05.07.443053", - "rel_title": "A hybrid PDE-ABM model for viral dynamics with application to SARS-CoV-2 and influenza", + "rel_doi": "10.1101/2021.05.01.442286", + "rel_title": "Phylodynamic insights on the early spread of the COVID-19 pandemic and the efficacy of intervention measures", "rel_date": "2021-05-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.07.443053", - "rel_abs": "We propose a hybrid partial differential equation - agent-based (PDE-ABM) model to describe the spatio-temporal viral dynamics in a cell population. The virus concentration is considered as a continuous variable and virus movement is modelled by diffusion, while changes in the states of cells (i.e. healthy, infected, dead) are represented by a stochastic agent-based model. The two subsystems are intertwined: the probability of an agent getting infected in the ABM depends on the local viral concentration, and the source term of viral production in the PDE is determined by the cells that are infected.\n\nWe develop a computational tool that allows us to study the hybrid system and the generated spatial patterns in detail. We systematically compare the outputs with a classical ODE system of viral dynamics, and find that the ODE model is a good approximation only if the diffusion coefficient is large.\n\nWe demonstrate that the model is able to predict SARS-CoV-2 infection dynamics, and replicate the output of in vitro experiments. Applying the model to influenza as well, we can gain insight into why the outcomes of these two infections are different.", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.01.442286", + "rel_abs": "We performed phylodynamic analyses of all available SARS-CoV-2 genomes from the early phase of the COVID-19 pandemic--combined with a novel dataset on contemporary global air-travel volume--to assess the efficacy of public-health measures on viral geographic spread. Globally, viral dispersal rates are significantly correlated with air-travel volume, and widespread international air-travel bans imposed against China by early February coincide with a significant reduction in geographic viral spread. In North America, the efficacy of this travel ban was temporary, possibly due to the lack of both containment measures against other infected regions and domestic mitigation measures. By contrast, in China, domestic mitigation measures were correlated with a long-term reduction in viral spread, despite repeated international introductions. Our study supports a role for both targeted international containment and domestic mitigation measures as critical components of a more comprehensive public-health strategy to mitigate future outbreaks caused by the emergence of novel SARS-CoV-2 variants.\n\nOne sentence summaryPhylodynamic analyses reveal that variation in rates of early geographic spread of COVID-19 are correlated with intervention measures.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Sadegh Marzban", - "author_inst": "Bolyai Institute, University of Szeged, H-6720 Szeged, Hungary." + "author_name": "Jiansi Gao", + "author_inst": "University of California, Davis" }, { - "author_name": "Renji Han", - "author_inst": "Bolyai Institute, University of Szeged, H-6720 Szeged, Hungary." + "author_name": "Michael R. May", + "author_inst": "University of California Berkeley, University of California Davis" }, { - "author_name": "N\u00f3ra Juh\u00e1sz", - "author_inst": "Bolyai Institute, University of Szeged, H-6720 Szeged, Hungary." + "author_name": "Bruce Rannala", + "author_inst": "University of California Davis" }, { - "author_name": "Gergely R\u00f6st", - "author_inst": "Bolyai Institute, University of Szeged, H-6720 Szeged, Hungary." + "author_name": "Brian R. Moore", + "author_inst": "University of California, Davis" } ], "version": "1", "license": "", "type": "new results", - "category": "systems biology" + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2021.05.01.21256182", @@ -756314,18 +754680,31 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2021.05.05.442742", - "rel_title": "Sequencing SARS-CoV-2 in a malaria research laboratory in Mali, West Africa: the road to sequencing the first SARS-CoV-2 genome in Mali", + "rel_doi": "10.1101/2021.05.03.21256565", + "rel_title": "A Call For Better Methodological Quality Of Reviews On Using Artificial Intelligence For COVID-19 Detection In Medical Imaging - An Umbrella Systematic Review", "rel_date": "2021-05-05", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.05.442742", - "rel_abs": "Next generation sequencing (NGS) has become a necessary tool for genomic epidemiology. Even though the utility of genomics in human health has been proved, the genomic surveillance has never been so important until the COVID 19 pandemic. This has been evidenced with the detection of new variants of SARS-CoV-2 in the United Kingdom, South Africa and Brazil recently using genomic surveillance. Until recently, Malian scientists did not have access to any local NGS platform and samples had to be shipped abroad for sequencing. Here, we report on how we adapted a laboratory setup for Plasmodium research to generate the first complete SARS-CoV-2 genome locally. Total RNA underwent a library preparation using an Illumina TruSeq stranded RNA kit. A metagenomics sequencing was performed on an Illumina MiSeq platform following by bioinformatic analyses on a local server in Mali. We recovered a full genome of SARS-CoV-2 of 29 kb with an average depth coverage of 200x. We have demonstrated our capability of generating a high quality genome with limited resources and highlight the need to develop genomics capacity locally to solve health problems. We discuss challenges related to access to reagents during a pandemic period and propose some home-made solutions.", - "rel_num_authors": 0, - "rel_authors": null, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.03.21256565", + "rel_abs": "ObjectiveIn this umbrella systematic review, we screen existing reviews on using artificial intelligence (AI) techniques to diagnose COVID-19 in patients of any age and sex (both hospitalised and ambulatory) using medical images and assess their methodological quality.\n\nMethodsWe searched seven databases (MEDLINE, EMBASE, Web of Science, Scopus, dblp, Cochrane Library, IEEE Xplore) and two preprint services (arXiv, OSF Preprints) up to September 1, 2020. Eligible studies were identified as reviews or surveys where any metric of classification of detection of COVID-19 using AI was provided. Two independent reviewers did all steps of identification of records (titles and abstracts screening, full texts assessment, essential data extraction, and quality assessment). Any discrepancies were resolved by discussion. We qualitatively analyse methodological credibility of the reviews using AMSTAR 2 and evaluate reporting using PRISMA-DTA tools, leaving quantitative analysis for further publications.\n\nResultsWe included 22 reviews out of 725 records covering 165 primary studies. This review covers 416,254 participants in total, including 50,022 diagnosed with COVID-19. The methodological quality of all eligible studies was rated as critically low. 91% of papers had significant flaws in reporting quality. More than half of the reviews did not comment on the results of previously published reviews at all. Almost three fourth of the studies included less than 10% of available studies.\n\nDiscussionIn this umbrella review, we focus on the descriptive summary of included papers. Much wasting time and resources could be avoided if referring to previous reviews and following methodological guidelines. Due to the low credibility of evidence and flawed reporting, any recommendation about automated COVID-19 clinical diagnosis from medical images using AI at this point cannot be provided.\n\nFundingPO was supported by NIH grant AI116794 (the funding body had no role in the design, in any stage of the review, or in writing the manuscript); PJ and DS did not receive any funding.\n\nRegistrationThe protocol of this review was registered on the OSF platform [1].", + "rel_num_authors": 3, + "rel_authors": [ + { + "author_name": "Pawe\u0142 Jemio\u0142o", + "author_inst": "AGH University of Science and Technology" + }, + { + "author_name": "Dawid Storman", + "author_inst": "Jagiellonian University Medical College" + }, + { + "author_name": "Patryk Orzechowski", + "author_inst": "University of Pennsylvania" + } + ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "genomics" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.05.05.442782", @@ -758259,45 +756638,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.03.21256545", - "rel_title": "Roles of generation-interval distributions in shaping relative epidemic strength, speed, and control of new SARS-CoV-2 variants", + "rel_doi": "10.1101/2021.05.03.21256542", + "rel_title": "Analysis and visualization of epidemics on the timescale of burden: derivation and application of Epidemic Resistance Lines (ERLs) to COVID-19 outbreaks in the US", "rel_date": "2021-05-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.03.21256545", - "rel_abs": "Inferring the relative strength (i.e., the ratio of reproduction numbers, [R]var/[R]wt) and relative speed (i.e., the difference between growth rates, rvar -rwt) of new SARS-CoV-2 variants compared to their wild types is critical to predicting and controlling the course of the current pandemic. Multiple studies have estimated the relative strength of new variants from the observed relative speed, but they typically neglect the possibility that the new variants have different generation intervals (i.e., time between infection and transmission), which determines the relationship between relative strength and speed. Notably, the increasingly predominant B.1.1.7 variant may have a longer infectious period (and therefore, a longer generation interval) than prior dominant lineages. Here, we explore how differences in generation intervals between a new variant and the wild type affect the relationship between relative strength and speed. We use simulations to show how neglecting these differences can lead to biases in estimates of relative strength in practice and to illustrate how such biases can be assessed. Finally, we discuss implications for control: if new variants have longer generation intervals then speed-like interventions such as contact tracing become more effective, whereas strength-like interventions such as social distancing become less effective.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.03.21256542", + "rel_abs": "The 2020 COVID-19 pandemic produced thousands of well-quantified epidemics in counties, states, and countries around the world. Comparing the dynamics and outcomes of these nested epidemics could improve our understanding of the efficacy of non-pharmaceutical interventions (NPIs) and help managers with risk assessment across multiple geographic levels. However, cross-outbreak comparisons are challenging due to their variable dates of introduction of the SARS-CoV-2 virus, rates of transmission, case detection rates, and asynchronous and diverse management interventions.\n\nHere, we present a graphical method for comparing ongoing COVID-19 epidemics by using disease burden as a natural timescale for comparison. Trajectories of growth rates of cases over the timescale of lagged deaths per-capita produces coherent visual comparisons of epidemics that are otherwise incoherent and asynchronous in the timescale of calendar dates or incomparable using non-stationary measures of burden such as cases. Applied to US COVID-19 outbreaks at the county and state level, this approach reveals lockdowns reducing transmission at fewer deaths per-capita early in the epidemic, reopenings causing resurgent summer epidemics, and peaks that while separated in time and place actually occur at points of similar per-capita deaths.\n\nOur method uses early and minimally mitigated epidemics, like that in NYC in March-April 2020 and Sweden in later 2020, to define what we call \"epidemic resistance lines\" (ERLs) or hypothesized upper bounds of epidemic speed and burden. ERLs from less-mitigated epidemics allow benchmarking of resurgent summer epidemics in the US. In particular, the unmitigated NYC epidemic resistance line appears to bound the growth rates of 3,000 US counties and funnel growth rates across counties to their peaks where growth rates equal zero in the fall and winter of 2020. Corroboration of upper-bounds on epidemic trajectories allowed early predictions of mortality burden for unmitigated COVID-19 epidemics in these populations, predictions that were more accurate for counties in states without mask-wearing mandates. We discuss how this method could be used for future epidemics, including seasonal epidemics caused by influenza or ongoing epidemics caused by new SARS-CoV-2 variants.\n\nPress SummaryWhy, despite no statewide mask-wearing mandates or other restrictions like restaurant closures, did South Dakotas COVID-19 epidemic peak not in January, when seasonal forcing wanes, but in early November? Why are we not seeing a resurgent epidemic in Florida or Texas, where non-pharmaceutical interventions have been relaxed for months? How can we compare the current outbreak in India with other countries epidemics to contextualize the speed of the Indian outbreak and estimate the potential loss of life?\n\nWe have developed a new method of visualizing epidemics in progress that can help to compare distinct COVID-19 outbreaks to understand, in specific cases like South Dakota, why they peaked when they did. The \"when\" in this case does not refer to prediction of a calendar date, but rather a point in the accumulation of deaths in a given locale due to the disease in question. The method presented in this paper therefore essentially uses population-based burden of disease as a timescale for measuring epidemics. Just as the age of a car can be measured in years or miles, the age of a COVID-19 epidemic can be measured in days or deaths per-capita. Plotting growth rates of cases as a function of per-capita deaths 11 days later produces a real-time visual comparison of epidemics that are otherwise asynchronous in time.\n\nThis approach permits both direct comparison across local outbreaks that may be disparate in time and/or place, as well as benchmarking of any outbreak against known exemplars of archetypal response strategies, such as New York Citys unmitigated urban outbreak in Spring 2020 and Swedens uncontained summer 2020 epidemic. Whether comparing the speed of resurgent outbreaks following relaxation in US states like Florida or the peak mortality burden in fall outbreaks across thousands of US counties with and without statewide mask-wearing mandates, this method offers a simple, intuitive tool for real-time monitoring and prediction capability connecting epidemic speed, burden, and management interventions. While our findings point to compelling epidemiological hypotheses for peaks in less-regulated states, future work is needed to confirm and extend our results predicting mortality burden at the peak of confirmed cases in the ongoing and evolving COVID-19 pandemic.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Sang Woo Park", - "author_inst": "Princeton University" - }, - { - "author_name": "Benjamin M. Bolker", - "author_inst": "McMaster University" - }, - { - "author_name": "Sebastian Funk", - "author_inst": "London School of Hygiene & Tropical Medicine" - }, - { - "author_name": "C. Jessica E. Metcalf", - "author_inst": "Princeton University" + "author_name": "Alex D. Washburne", + "author_inst": "Selva Analytics, LLC" }, { - "author_name": "Joshua S. Weitz", - "author_inst": "Georgia Institute of Technology" + "author_name": "Justin D Silverman", + "author_inst": "Pennsylvania State University" }, { - "author_name": "Bryan T. Grenfell", - "author_inst": "Princeton University" + "author_name": "Jose Lourenco", + "author_inst": "Oxford University" }, { - "author_name": "Jonathan Dushoff", - "author_inst": "McMaster University" + "author_name": "Nathaniel Hupert", + "author_inst": "Weill Cornell Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -759891,12 +758258,12 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.03.21256416", - "rel_title": "Non-neutralizing secretory IgA and T cells targeting SARS-CoV-2 spike protein are transferred to the breastmilk upon BNT162b2 vaccination", + "rel_doi": "10.1101/2021.05.04.21256323", + "rel_title": "Clinical evaluation of BD Veritor\u2122 SARS-CoV-2 and Flu A+B Assay for point-of-care (POC) System", "rel_date": "2021-05-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.03.21256416", - "rel_abs": "In view of data scarcity to guide decision-making in breastfeeding women, we evaluated how mRNA vaccines impact immune response of lactating health care workers (HCW) and the effector profile of breast milk transferred immune protection. We show that upon BNT162b2 vaccination, immune transfer via milk to suckling infants occurs through secretory IgA (SIgA) and T cells. Functionally, spike-SIgA was non-neutralizing and its titers were unaffected by vaccine boosting, indicating that spike-SIgA is produced in a T-cell independent manner by mammary gland. Even though their milk was devoid of neutralizing antibodies, we found that lactating women had higher frequencies of RBD-reactive circulating memory B cells and more RBD-IgG antibodies, when compared to controls. Nonetheless, blood neutralization titers in lactating and non-lactating HCW were similar. Further studies are required to determine transferred antibodies and spike-T cells complete functional profile and whether they can mediate protection in the suckling infant.\n\nHighlightsO_LIMilk and blood responses to BNT162b2 vaccine are initially isotype discordant\nC_LIO_LIImmune transfer via milk to suckling infants occurs by spike-reactive SIgA and T cells\nC_LIO_LISpike-reactive SIgA in the breastmilk is non-neutralizing and T-cell independent\nC_LIO_LILactating vs non-lactating HCW had distinct cellular responses, despite similar NT50\nC_LI", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.04.21256323", + "rel_abs": "Differential diagnosis of COVID-19 and/or influenza (flu) at point of care is critical for efficient patient management and treatment for either of these diseases. Clinical performance of the BD Veritor System for Rapid Detection of SARS-CoV-2 & FluA+B (\"Veritor SARS-CoV-2/Flu\") triplex assay was characterized. The performance for SARS-CoV-2 detection was determined using two hundred and ninety-eight (298) specimens from patients reporting COVID-19 symptoms within 7 days from symptom onset (DSO) in comparison with Lyra(R) SARS-CoV-2 RT-PCR Assay (\"Lyra SARS-CoV-2\"). The Veritor SARS-CoV-2/Flu Assay met the FDA EUA acceptance criterion with 95% overall agreement for SARS-CoV-2 test when compared to Lyra SARS-CoV-2. The performance for Flu A and Flu B detection was determined using 75 influenza-positive and 40 influenza-negative retrospective specimens in comparison with the previously FDA cleared BD Veritor System for Rapid Detection of Flu A+B (\"Veritor Flu\"). The Veritor SARS-CoV-2/Flu also demonstrated 100% agreement with the Veritor Flu.", "rel_num_authors": 0, "rel_authors": null, "version": "1", @@ -761342,41 +759709,97 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.05.02.442052", - "rel_title": "Preliminary Immunogenicity of a Pan-COVID-19 T Cell Vaccine in HLA-A*02:01 Mice", + "rel_doi": "10.1101/2021.05.02.442326", + "rel_title": "Convergent antibody responses to the SARS-CoV-2 spike protein in convalescent and vaccinated individuals", "rel_date": "2021-05-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.02.442052", - "rel_abs": "New strains of SARS-CoV-2 have emerged, including B.1.351 and P.1, that demonstrate increased transmissibility and the potential of rendering current SARS-CoV-2 vaccines less effective. A concern is that existing SARS-CoV-2 spike subunit vaccines produce neutralizing antibodies to three dimensional spike epitopes that are subject to change during viral drift. Here we provide an initial report on the hypothesis that adaptive T cell based immunity may provide a path for a pan-COVID-19 vaccine that is resilient to viral drift. T cell based adaptive immunity can be based on short peptide sequences selected from the viral proteome that are less subject to drift, and can utilize multiple such epitopes to provide redundancy in the event of drift. We find that SARS-CoV-2 peptides contained in a mRNA-LNP T cell vaccine for SARS-CoV-2 are immunogenic in mice transgenic for the human HLA-A*02:01 gene. We plan to test the efficacy of this vaccine with SARS-CoV-2 B.1.351 challenge trials with HLA-A*02:01 mice.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.02.442326", + "rel_abs": "Unrelated individuals can produce genetically similar clones of antibodies, known as public clonotypes, which have been seen in responses to different infectious diseases as well as healthy individuals. Here we identify 37 public clonotypes in memory B cells from convalescent survivors of SARS-CoV-2 infection or in plasmablasts from an individual after vaccination with mRNA-encoded spike protein. We identified 29 public clonotypes, including clones recognizing the receptor-binding domain (RBD) in the spike protein S1 subunit (including a neutralizing, ACE2-blocking clone that protects in vivo), and others recognizing non-RBD epitopes that bound the heptad repeat 1 region of the S2 domain. Germline-revertant forms of some public clonotypes bound efficiently to spike protein, suggesting these common germline-encoded antibodies are preconfigured for avid recognition. Identification of large numbers of public clonotypes provides insight into the molecular basis of efficacy of SARS-CoV-2 vaccines and sheds light on the immune pressures driving the selection of common viral escape mutants.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Brandon Carter", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Elaine C. Chen", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Jinjin Chen", - "author_inst": "Tufts University" + "author_name": "Pavlo Gilchuk", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Clarety Kaseke", - "author_inst": "Ragon Institute of MGH, MIT and Harvard" + "author_name": "Seth J. Zost", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Alexander Dimitrakakis", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Naveenchandra Suryadevara", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Gaurav D. Gaiha", - "author_inst": "Ragon Institute of MGH, MIT and Harvard" + "author_name": "Emma S. Winkler", + "author_inst": "Washington University in St. Louis" }, { - "author_name": "Qiaobing Xu", - "author_inst": "Tufts University" + "author_name": "Carly R. Cabel", + "author_inst": "University of Arizona College of Medicine" }, { - "author_name": "David K. Gifford", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Elad Binshtein", + "author_inst": "Vanderbilt University" + }, + { + "author_name": "Rachel E. Sutton", + "author_inst": "Vanderbilt University Medical Center" + }, + { + "author_name": "Jessica L. Rodriguez", + "author_inst": "Vanderbilt University Medical Center" + }, + { + "author_name": "Samuel Day", + "author_inst": "Vanderbilt University Medical Center" + }, + { + "author_name": "Luke Myers", + "author_inst": "Vanderbilt University Medical Center" + }, + { + "author_name": "Andrew Trivette", + "author_inst": "Vanderbilt University Medical Center" + }, + { + "author_name": "Jazmean K. Williams", + "author_inst": "Integral Molecular" + }, + { + "author_name": "Edgar Davidson", + "author_inst": "Integral Molecular" + }, + { + "author_name": "Shuaizhi Li", + "author_inst": "University of Arizona College of Medicine" + }, + { + "author_name": "Benjamin J. Doranz", + "author_inst": "Integral Molecular" + }, + { + "author_name": "Samuel K. Campos", + "author_inst": "University of Arizona College of Medicine" + }, + { + "author_name": "Robert H. Carnahan", + "author_inst": "Vanderbilt University Medical Center" + }, + { + "author_name": "Curtis A. Thorne", + "author_inst": "University of Arizona College of Medicine" + }, + { + "author_name": "Michael S. Diamond", + "author_inst": "Washington University School of Medicine" + }, + { + "author_name": "James E. Crowe Jr.", + "author_inst": "Vanderbilt University Medical Center" } ], "version": "1", @@ -763232,39 +761655,55 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2021.04.28.21256263", - "rel_title": "Reduced Pediatric Urgent Asthma Utilization and Exacerbations During the COVID-19 Pandemic", - "rel_date": "2021-05-01", + "rel_doi": "10.1101/2021.04.29.21256256", + "rel_title": "COVID-19 vaccine hesitancy among persons living in homeless shelters in France.", + "rel_date": "2021-04-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.28.21256263", - "rel_abs": "Background and ObjectivesThe COVID-19 pandemic has had a profound impact on healthcare access and utilization, which could have important implications for children with chronic diseases, including asthma. We sought to evaluate changes in healthcare utilization and outcomes in children with asthma during the COVID-19 pandemic.\n\nMethodsWe used electronic health records data to evaluate healthcare use and asthma outcomes in 3,959 children and adolescents, 5-17 years of age, with a prior diagnosis of asthma who had a history of well child visits and encounters within the healthcare system. We assessed all-cause healthcare encounters and asthma exacerbations in the 12-months preceding the start of the COVID-19 pandemic (March 1, 2019 - February 29, 2020) and the first 12-months of the pandemic (March 1, 2020 - February 28, 2021).\n\nResultsAll-cause healthcare encounters decreased significantly during the pandemic compared to the preceding year, including well child visits (48.1% during the pandemic vs. 66.6% in the prior year; p < 0.01), emergency department visits (9.7% vs. 21.0%; p < 0.01), and inpatient admissions (1.6% vs. 2.5%; p < 0.01), though there was over a 100-fold increase in telehealth encounters. Asthma exacerbations that required treatment with systemic steroids also decreased (127 vs. 504 exacerbations; p < 0.01). Race/ethnicity was not associated with changes in healthcare utilization or asthma outcomes.\n\nConclusionThe COVID-19 pandemic corresponded to dramatic shifts in healthcare utilization, including increased telehealth use and improved outcomes among children with asthma. Social distancing measures may have also reduced asthma trigger exposure.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.29.21256256", + "rel_abs": "COVID-19 vaccine hesitancy is frequent and can constitute a barrier to the dissemination of vaccines once they are available. Unequal access to vaccines may also contribute to socioeconomic inequalities with regard to COVID-19. We studied vaccine hesitancy among persons living in homeless shelters in France between May and June 2020 (n=235). Overall, 40.9% of study participants reported vaccine hesitancy, which is comparable to general population trends in France. In multivariate regression models, factors associated with vaccine hesitancy are: being a woman (OR=2.55; 95% CI 1.40-4.74), living with a partner (OR=2.48, 95% CI 1.17-5.41), no legal residence in France (OR=0.51, 95% CI 0.27-0.92), and health literacy (OR=0.38, 95% CI 0.21, 0.68). Our results suggest that trends in vaccine hesitancy and associated factors are similar among homeless persons as in the general population. Dissemination of information on vaccine risks and benefits needs to be adapted to persons who experience severe disadvantage.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Jillian H Hurst", - "author_inst": "Duke University School of Medicine" + "author_name": "Cecile Longchamps", + "author_inst": "INSERM" }, { - "author_name": "Congwen Zhao", - "author_inst": "Duke University School of Medicine" + "author_name": "Simon Ducarroz", + "author_inst": "INSERM" }, { - "author_name": "Nicholas S. Fitzpatrick", - "author_inst": "Duke University School of Medicine" + "author_name": "Lisa Crouzet", + "author_inst": "Universite Lyon" }, { - "author_name": "Benjamin A. Goldstein", - "author_inst": "Duke University School of Medicine" + "author_name": "Nicolas Vignier", + "author_inst": "INSERM" }, { - "author_name": "Jason E. Lang", - "author_inst": "Duke University School of Medicine" + "author_name": "Lionel Pourtau", + "author_inst": "Habitat et Humanisme" + }, + { + "author_name": "Cecile Allaire", + "author_inst": "Sante Publique France" + }, + { + "author_name": "Anne-Claire Colleville", + "author_inst": "Sante Publique France" + }, + { + "author_name": "Tarik El Aarbaoui", + "author_inst": "INSERM" + }, + { + "author_name": "Maria Melchior", + "author_inst": "INSERM" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.04.28.21256146", @@ -764828,47 +763267,31 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.04.30.441968", - "rel_title": "Influenza viral particles harboring the SARS-CoV-2 spike RBD as a combination respiratory disease vaccine", + "rel_doi": "10.1101/2021.04.29.442061", + "rel_title": "Decitabine Reactivation of FoxM1-Dependent Endothelial Regeneration and Vascular Repair for Potential Treatment of Elderly ARDS and COVID-19 Patients", "rel_date": "2021-04-30", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.30.441968", - "rel_abs": "Vaccines targeting SARS-CoV-2 have gained emergency FDA approval, however the breadth against emerging variants and the longevity of protection remains unknown. Post-immunization boosting may be required, perhaps on an annual basis if the virus becomes an endemic pathogen. Seasonal influenza virus vaccines are already developed every year, an undertaking made possible by a robust global vaccine production and distribution infrastructure. To create a seasonal combination vaccine targeting influenza viruses and SARS-CoV-2 that is also amenable to frequent reformulation, we have developed a recombinant influenza A virus (IAV) genetic platform that \"reprograms\" the virus to package an immunogenic domain of the SARS-CoV-2 spike (S) protein onto IAV particles. Vaccination with this combination vaccine elicits neutralizing antibodies and provides protection from lethal challenge with both pathogens. This technology may allow for leveraging of established influenza vaccine infrastructure to generate a cost-effective and scalable seasonal vaccine solution for both influenza and coronaviruses.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.29.442061", + "rel_abs": "Aging is a major risk factor of high incidence and increased mortality of acute respiratory distress syndrome (ARDS) and COVID-19. We repot that aging impairs the intrinsic FoxM1-dependent endothelial regeneration and vascular repair program and causes persistent lung injury and high mortality following sepsis. Therapeutic gene transduction of FOXM1 in vascular endothelium or treatment with FDA-approved drug Decitabine was sufficient to reactivate FoxM1-dependent lung endothelial regeneration in aged mice, reverse aging-impaired resolution of inflammatory injury, and promote survival. In COVID-19 lung autopsy samples, FOXM1 expression was not induced in vascular endothelial cells of elderly patients in contrast to mid-age patients. Thus, Decitabine reactivation of FoxM1-dependent vascular repair represents a potential effective therapy for elderly COVID-19 and non-COVID-19 ARDS patients.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Ryan R Chaparian", - "author_inst": "Duke University" - }, - { - "author_name": "Alfred T Harding", - "author_inst": "MIT" - }, - { - "author_name": "Kristina Riebe", - "author_inst": "Duke University" - }, - { - "author_name": "Amelia Karlsson", - "author_inst": "Duke University" - }, - { - "author_name": "Gregory D Sempowski", - "author_inst": "Duke University" + "author_name": "Gokhan Mutlu", + "author_inst": "University of Chicago" }, { - "author_name": "Nicholas S Heaton", - "author_inst": "Duke University" + "author_name": "Yun Fang", + "author_inst": "University of Chicago" }, { - "author_name": "Brook E Heaton", - "author_inst": "Duke University" + "author_name": "David Wu", + "author_inst": "University of Chicago" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2021.04.28.21255760", @@ -766814,39 +765237,47 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.04.24.21256044", - "rel_title": "SARS-CoV-2 virus transfers to skin through contact with contaminated solids", + "rel_doi": "10.1101/2021.04.25.21255923", + "rel_title": "Evolving Phenotypes of non-hospitalized Patients that Indicate Long Covid", "rel_date": "2021-04-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.24.21256044", - "rel_abs": "Transfer of SARS-CoV-2 from solids to fingers is one step in infection via contaminated solids, and the possibility of infection from this route has driven calls for increased frequency of handwashing during the COVID-19 pandemic. To analyze this route of infection, we measured the percentage of SARS-CoV-2 that was transferred from a solid to an artificial finger. A droplet of SARS-CoV-2 suspension (1 {micro}L) was placed on a solid, and then artificial skin was briefly pressed against the solid with a light force (3 N). Transfer from a variety of solids was detected, and transfer from the non-porous solids, glass, stainless steel, and Teflon, was substantial (13-16 %) when the droplet was still wet. Transfer still occurred after the droplet evaporated, but it was smaller. We found a lower level of transfer from porous solids but did not find a significant effect of solid wettability for non-porous solids.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.25.21255923", + "rel_abs": "For some SARS-CoV-2 survivors, recovery from the acute phase of the infection has been grueling with lingering effects. Many of the symptoms characterized as the post-acute sequelae of COVID-19 (PASC) could have multiple causes or are similarly seen in non-COVID patients. Accurate identification of phenotypes will be important to guide future research and help the healthcare system focus its efforts and resources on adequately controlled age- and gender-specific sequelae of a COVID-19 infection. In this retrospective electronic health records (EHR) cohort study, we applied a computational framework for knowledge discovery from clinical data, MLHO, to identify phenotypes that positively associate with a past positive reverse transcription-polymerase chain reaction (RT-PCR) test for COVID-19. We evaluated the post-test phenotypes in two temporal windows at 3-6 and 6-9 months after the test and by age and gender. Data from longitudinal diagnosis records stored in EHRs from Mass General Brigham in the Boston metropolitan area was used for the analyses. Statistical analyses were performed on data from March 2020 to June 2021. Study participants included over 96 thousand patients who had tested positive or negative for COVID-19 and were not hospitalized. We identified 33 phenotypes among different age/gender cohorts or time windows that were positively associated with past SARS-CoV-2 infection. All identified phenotypes were newly recorded in patients medical records two months or longer after a COVID-19 RT-PCR test in non-hospitalized patients regardless of the test result. Among these phenotypes, a new diagnosis record for anosmia and dysgeusia (OR: 2.60, 95% CI [1.94 - 3.46]), alopecia (OR: 3.09, 95% CI [2.53 - 3.76]), chest pain (OR: 1.27, 95% CI [1.09 - 1.48]), chronic fatigue syndrome (OR 2.60, 95% CI [1.22-2.10]), shortness of breath (OR 1.41, 95% CI [1.22 - 1.64]), pneumonia (OR 1.66, 95% CI [1.28 - 2.16]), and type 2 diabetes mellitus (OR 1.41, 95% CI [1.22 - 1.64]) are some of the most significant indicators of a past COVID-19 infection. Additionally, more new phenotypes were found with increased confidence among the cohorts who were younger than 65. Our approach avoids a flood of false positive discoveries while offering a more robust probabilistic approach compared to the standard linear phenome-wide association study (PheWAS). The findings of this study confirm many of the post-COVID symptoms and suggest that a variety of new diagnoses, including new diabetes mellitus and neurological disorder diagnoses, are more common among those with a history of COVID-19 than those without the infection. Additionally, more than 63 percent of PASC phenotypes were observed in patients under 65 years of age, pointing out the importance of vaccination to minimize the risk of debilitating post-acute sequelae of COVID-19 among younger adults.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Saeed Behzadinasab", - "author_inst": "Dept. of Chemical Engineering and Center for Soft Matter and Biological Physics, Virginia Tech, VA, 24061, USA" + "author_name": "Hossein Estiri", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Alex W.H. Chin", - "author_inst": "School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China" + "author_name": "Zachary Strasser", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Mohsen Hosseini", - "author_inst": "Dept. of Chemical Engineering and Center for Soft Matter and Biological Physics, Virginia Tech, VA, 24061, USA" + "author_name": "Gabriel Brat", + "author_inst": "Harvard Medical School" }, { - "author_name": "Leo L.M. Poon", - "author_inst": "School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China." + "author_name": "Yevgeniy Semenov", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "- The Consortium for Characterization of COVID-19 by EHR (4CE)", + "author_inst": "" + }, + { + "author_name": "Chirag Patel", + "author_inst": "Harvard Medical School" }, { - "author_name": "William A. Ducker", - "author_inst": "Dept. of Chemical Engineering and Center for Soft Matter and Biological Physics, Virginia Tech, VA, 24061, USA" + "author_name": "Shawn Murphy", + "author_inst": "Massachusetts General Hospital" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "health informatics" }, { "rel_doi": "10.1101/2021.04.26.21255732", @@ -768768,27 +767199,43 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2021.04.19.21255731", - "rel_title": "ASSESSING VACCINATION STRATEGIES FOR THE COVID-19 EPIDEMIC IN MINAS GERAIS (BRAZIL)", + "rel_doi": "10.1101/2021.04.19.21255736", + "rel_title": "Have news reports on suicide and attempted suicide during the COVID-19 pandemic adhered to guidance on safer reporting? A UK-wide content analysis study", "rel_date": "2021-04-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.19.21255731", - "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWIn this work we analyze the effectiveness of vaccination strategies for the COVID-19 epidemic in the Brazilian state of Minas Gerais. Firstly we study the effectiveness of general vaccination in the decreasing of the number of infected individuals using a traditional non structured SEIR model. Secondly we consider an age-structured SEIR model with 3 age groups (youngster, adult and elderly) and we analyze the current strategy in the Brazilian state of Minas Gerais, of focusing the vaccination on the elderly group. We conclude by showing this strategy to be mistaken and that a vaccination focusing on the age group of the adults would be much more efficient in decreasing the total number of infected individuals.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.19.21255736", + "rel_abs": "Associations between sensational news coverage of suicide and subsequent increases in suicidal behaviour in the general population have been well documented. Amidst growing concern over the impact of the COVID-19 pandemic on suicide rates, it is especially important that news coverage of suicidal behaviour adheres to recommended standards for the responsible reporting of suicide. Using a set of dimensions based on international media guidelines, we analysed the quality and content of all UK news reports of possible COVID-19 related suicides and suicide attempts in the first four months of the pandemic (N=285 reports of 78 individual incidents published in print and online newspapers between 16th March and 12th July 2020). The majority of news reports made an explicit link between suicidal behaviour and the COVID-19 pandemic in the headline (187/285, 65.5%), and portrayed this association as strong and direct (n=196/272, 72.1%), mostly based on statements by family, friends or acquaintances of the deceased (171/285, 60%). The impact of the pandemic on suicidal behaviour was most often attributed to feelings of isolation (78/285, 27.4%), poor mental health (42, 14.7%) and sense of entrapment (41, 14.4%) as a result of government-imposed restrictions. Although rarely of poor overall quality, reporting was biased towards young people, frontline staff and relatively unusual suicides (including those involving a celebrity, murder-suicide and violent methods) Also, to varying degrees, reports failed to meet recommended standards; for example, 41.1% (117/285) did not signpost readers to sources of support, a quarter (69, 24.2%) included examples of sensational language and a third provided over-simplistic explanations for the suicidal behavior (93, 32.6%). While news reporting has improved compared to earlier coverage of suicide in the UK, it is essential that careful attention is paid to the quality and content of reports, especially as longer-term consequences of the COVID-19 pandemic develop.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "MARCELO DOMINGOS MARCHESIN", - "author_inst": "FEDERAL UNIVERSITY OF MINAS GERAIS" + "author_name": "Lisa Marzano", + "author_inst": "Middlesex University" }, { - "author_name": "MEHRAN SABETI", - "author_inst": "FEDERAL UNVIVERSITY OF VICOSA" + "author_name": "Monica Hawley", + "author_inst": "Samaritans" + }, + { + "author_name": "Lorna Fraser", + "author_inst": "Samaritans" + }, + { + "author_name": "Eva Harris-Skillman", + "author_inst": "University of Oxford" + }, + { + "author_name": "Yasmine Lainez", + "author_inst": "Middlesex University" + }, + { + "author_name": "Keith Hawton", + "author_inst": "University of Oxford" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.04.19.21255709", @@ -770361,59 +768808,79 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2021.04.20.21255787", - "rel_title": "Implementation of Rapid and Frequent SARS-CoV2 Antigen Testing and Response in Congregate Homeless Shelters", + "rel_doi": "10.1101/2021.04.25.21255890", + "rel_title": "Stimulation of vascular organoids with SARS-CoV-2 antigens increases endothelial permeability and regulates vasculopathy", "rel_date": "2021-04-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.20.21255787", - "rel_abs": "BackgroundPeople experiencing homelessness who live in congregate shelters are at high risk of SARS-CoV2 transmission and severe COVID-19. Current screening and response protocols using rRT-PCR in homeless shelters are expensive, require specialized staff and have delays in returning results and implementing responses.\n\nMethodsWe piloted a program to offer frequent, rapid antigen-based tests (BinaxNOW) to residents and staff of congregate-living shelters in San Francisco, California, from January 15th to February 19th, 2021. We used the Reach-Effectiveness-Adoption-Implementation-Maintenance (RE-AIM) framework to evaluate the implementation.\n\nResultsO_ST_ABSReachC_ST_ABSWe offered testing at ten of twelve eligible shelters. Shelter residents and staff had variable participation across shelters; approximately half of eligible individuals tested at least once; few tested consistently during the study.\n\nEffectiveness2.2% of participants tested positive. We identified three outbreaks, but none exceeded 5 cases. All BinaxNOW-positive participants were isolated or left the shelters.\n\nAdoptionWe offered testing to all eligible participants within weeks of the projects initiation.\n\nImplementationAdaptations made to increase reach and improve consistency were promptly implemented.\n\nMaintenanceSan Francisco Department of Public Health expanded and maintained testing with minimal support after the end of the pilot.\n\nConclusionRapid and frequent antigen testing for SARS-CoV2 in homeless shelters is a viable alternative to rRT-PCR testing that can lead to immediate isolation of infectious individuals. Using the RE-AIM framework, we evaluated and adapted interventions to enable the expansion and maintenance of protocols.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.25.21255890", + "rel_abs": "ObjectiveThrombotic complications and vasculopathy have been extensively associated with severe COVID-19 infection, however the mechanisms by which endotheliitis is induced remain poorly understood. Here we investigate vascular permeability in the context of SARS-CoV-2-mediated endotheliitis in patient samples and a vascular organoid model.\n\nMethods and ResultsWe report the presence of the Spike glycoprotein in pericytes associated with pericyte activation and increased endothelial permeability in post-mortem COVID-19 lung autopsies. A pronounced decrease in the expression of the adhesion molecule VE-cadherin is observed in patients with thrombotic complications. Interestingly, fibrin-rich thrombi did not contain platelets, did not colocalize with tissue factor and have heterogenous levels of Von Willebrand factor, suggesting a biomarker-guided therapy might be required to target thrombosis in severe patients. Using a 3D vascular organoid model, we observe that ACE2 is primarily expressed in pericytes adjacent to vascular networks, consistent with patient data, indicating a preferential uptake of the S glycoprotein by these cells. Exposure of vascular organoids to SARS-CoV-2 or its antigens, recombinant trimeric Spike glycoprotein and Nucleocapsid protein, reduced endothelial cell and pericyte viability as well as CD144 expression with no additive effect upon endothelial activation via IL-1{beta}.\n\nConclusionsOur data suggest that pericyte uptake of SARS-CoV-2 or Spike glycoprotein contributes to vasculopathy by altering endothelial permeability increasing the risk of thrombotic complications.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Andres Aranda-Diaz", - "author_inst": "University of California, San Francisco" + "author_name": "Abdullah O Khan", + "author_inst": "University of Birmingham" }, { - "author_name": "Elizabeth Imbert", - "author_inst": "University of California, San Francisco" + "author_name": "Jasmeet S Reyat", + "author_inst": "University of Birmingham" }, { - "author_name": "Sarah Strieff", - "author_inst": "San Francisco Department of Public Health" + "author_name": "Joshua H Bourne", + "author_inst": "University of Birmingham" }, { - "author_name": "Dave Graham-Squire", - "author_inst": "University of California, San Francisco" + "author_name": "Martina Colicchia", + "author_inst": "University of Birmingham" }, { - "author_name": "Jennifer Evans", - "author_inst": "University of California, San Francisco" + "author_name": "Maddy L Newby", + "author_inst": "University of Southampton" }, { - "author_name": "Jamie Moore", - "author_inst": "San Francisco Department of Public Health" + "author_name": "Joel D Allen", + "author_inst": "University of Southampton" }, { - "author_name": "Willi McFarland", - "author_inst": "San Francisco Department of Public Health" + "author_name": "Max Crispin", + "author_inst": "University of Birmingham" }, { - "author_name": "Jonathan Fuchs", - "author_inst": "San Francisco Department of Public Health" + "author_name": "Esther Youd", + "author_inst": "University of Glasgow" }, { - "author_name": "Margaret Handley", - "author_inst": "University of California, San Francisco" + "author_name": "Paul G Murray", + "author_inst": "University of Birmingham" }, { - "author_name": "Margot B Kushel", - "author_inst": "University of California, San Francisco/Benioff Homelessness and Housing Initiative" + "author_name": "Graham S Taylor", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Zania Stamataki", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Alex G Richter", + "author_inst": "University of Birminghan" + }, + { + "author_name": "Adam F Cunningham", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Matthew Pugh", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Julie Rayes", + "author_inst": "University of Birmingham" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health systems and quality improvement" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.04.24.21256054", @@ -772159,71 +770626,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.23.21255846", - "rel_title": "Transmission of SARS-CoV-2 within households: a prospective cohort study in the Netherlands and Belgium - Interim results", + "rel_doi": "10.1101/2021.04.23.21255959", + "rel_title": "Increased Interregional Travel to Shopping Malls and Restaurants in Response to Differential COVID-19 Restrictions in the Greater Toronto Area", "rel_date": "2021-04-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.23.21255846", - "rel_abs": "BackgroundHousehold transmission studies are useful to obtain granular data on SARS-CoV-2 transmission dynamics and to gain insight into the main determinants. In this interim report we investigated secondary attack rates (SAR) by household and subject characteristics in the Netherlands and Belgium.\n\nMethodsHouseholds with a real-time reverse transcription polymerase chain reaction (RT-PCR) confirmed SARS-CoV-2 index case were enrolled <48 hours following report of the positive test result. Daily symptom follow-up, standardized nose-throat sampling at enrollment and at new-onset acute respiratory illness (ARI) and paired dried blood spots (DBS) were collected from each participant. Children 0-2 years of age were additionally requested to collect a stool sample 7 days after enrollment and at new-onset of ARI. Swabs and stool samples were tested by RT-PCR for virus detection and DBS by multiplex protein microarray for detection of SARS-CoV-2 antibodies. The SAR was calculated 1) per-household as the proportion of households with [≥]1 secondary SARS-CoV-2 case and 2) per-person as the probability of infection in household members at risk. We explored differences in SARs by household and subject characteristics.\n\nResultsThis analysis includes 117 households that completed follow-up between April-December 2020. Among 382 subjects, 74 secondary infections were detected, of which 13 (17.6%) were asymptomatic and 20 (27.0%) infections were detected by seroconversion only. Of cases detected by RT-PCR, 50 (67.6%) were found at enrollment. The household SAR was 44.4% (95%-CI: 35.4-53.9%) and was higher for index cases meeting the ARI case definition (52.3%; 95%-CI 41.4-62.9%) compared to mildly symptomatic (22.2%; 95%-CI: 9.4-42.7%) and asymptomatic index cases (0.0%; 95%-CI: 0.0-80.2%). The per-person SAR was 27.9% (95%-CI: 22.7-33.8%). Transmission was lowest from child to parent (9.1%; 95%-CI: 2.4-25.5%) and highest from parent to child (28.1%; 95%-CI: 19.7-38.4%) and in children 6-12 years (34.2%; 95%-CI: 20.1-51.4%). Among 141 subjects with RT-PCR confirmed SARS-CoV-2 infections, seroconversion was detected in 111 (78.7%).\n\nConclusionWe found a high household SAR, with the large majority of transmissions detected early after identification of the index case. Our findings confirm differential SAR by symptom status of the index. In almost a quarter of RT-PCR positive cases, no antibodies were detected. Other factors influencing transmission will be further explored as more data accumulate.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.23.21255959", + "rel_abs": "BackgroundIn the fall of 2020, the government of Ontario, Canada adopted a 5-tier, regional framework of public health measures for the COVID-19 pandemic. During the second wave of COVID-19 in Ontario, the urban core of the Greater Toronto Area (Toronto and Peel) were the first regions in the province to enter the highest restriction tier (\"lockdown\") on November 23, 2020, which closed restaurants to in-person dining and limited non-essential businesses, including shopping malls, to curbside pickup. The peripheral regions of the Greater Toronto Area (York, Durham, Halton) would not enter lockdown until later the following month. In this analysis, we examine whether the implementation of differentially timed restrictions in a highly interconnected metropolitan area led to increased interregional travel, potentially driving further transmission of SARS-CoV-2.\n\nMethodsWe used anonymized smartphone data to estimate the number of visits by residents of regions in the urban core to shopping malls and restaurants in peripheral regions in the week before compared to the week after the November 23 lockdown.\n\nResultsResidents of Toronto and Peel took fewer trips to shopping malls and restaurants in the week following lockdown. This was entirely driven by reductions in visits within the locked down regions themselves, as there was a significant increase in trips to shopping malls in peripheral regions by these residents in the same period (Toronto: +40.7%, Peel: +65.5%). Visits to restaurants in peripheral regions also increased slightly (Toronto: +6.3%, Peel: +11.8%).\n\nDiscussionHeterogeneous restrictions may undermine lockdowns in the urban core as well as driving residents from zones of higher transmission to zones of lower transmission. These concerns are likely generalizable to other major metropolitan areas, which often comprise interconnected but administratively independent regions.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Marieke LA de Hoog", - "author_inst": "UMC Utrecht" - }, - { - "author_name": "Janneke DM Verberk", - "author_inst": "University Medical Center Utrecht" - }, - { - "author_name": "Ilse Westerhof", - "author_inst": "University Medical Center Utrecht" - }, - { - "author_name": "Sam van Goethem", - "author_inst": "University of Antwerp" - }, - { - "author_name": "Christine Lammens", - "author_inst": "University of Antwerp" + "author_name": "Jean-Paul R. Soucy", + "author_inst": "Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada" }, { - "author_name": "Greet Ieven", - "author_inst": "University of Antwerp" + "author_name": "Amir Ghasemi", + "author_inst": "Communications Research Centre Canada, Ottawa, Canada" }, { - "author_name": "Erwin de Bruin", - "author_inst": "Erasmus Medical Centre" + "author_name": "Shelby L. Sturrock", + "author_inst": "Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada" }, { - "author_name": "Julia Bielicki", - "author_inst": "University of Basel" + "author_name": "Isha Berry", + "author_inst": "Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada" }, { - "author_name": "Samuel Coenen", - "author_inst": "University of Antwerp" + "author_name": "Sarah A. Buchan", + "author_inst": "Public Health Ontario, Toronto, Canada" }, { - "author_name": "Janko van Beek", - "author_inst": "Erasmus Medical Center" + "author_name": "Derek R. MacFadden", + "author_inst": "Ottawa Hospital Research Institute, Ottawa, Canada" }, { - "author_name": "Marc JM Bonten", - "author_inst": "University Medical Center Utrecht" + "author_name": "Nick Daneman", + "author_inst": "Sunnybrook Hospital, Toronto, Canada" }, { - "author_name": "Herman Goossens", - "author_inst": "University of Antwerp" + "author_name": "Nicholas Gibb", + "author_inst": "Public Health Agency of Canada, Ottawa, Canada" }, { - "author_name": "Patricia CJL Bruijning-Verhagen", - "author_inst": "University Medical Center Utrecht" + "author_name": "Kevin A. Brown", + "author_inst": "Public Health Ontario, Toronto, Canada" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.04.23.21255995", @@ -773789,25 +772240,77 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2021.04.22.21255946", - "rel_title": "RELIABILITY METHODS FOR ANALYZING COVID-19 PANDEMIC SPREADING BEHAVIOR, LOCKDOWN IMPACT AND INFECTIOUSNESS", + "rel_doi": "10.1101/2021.04.23.21255515", + "rel_title": "Transmission characteristics of SARS-CoV-2 variants of concern: Rapid Scoping Review", "rel_date": "2021-04-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.22.21255946", - "rel_abs": "In 2021, the COVID-19 pandemic continues to challenge the globalized world. Restrictions on the public life and lockdowns of different characteristics define the life in many countries. This paper focuses on the first year of the COVID-19 pandemic (01-28-2020 to 01-15-2021). As a transfer of methods used in reliability engineering for analyzing occurrence of infection, Weibull distribution models are used to evaluate the spreading behavior of COVID-19.\n\nKey issues of this study are the differences of spreading behavior in first and second pandemic phase and the various impacts of lockdown measures with different characteristics (hard, light). Therefore, the occurrence of infection in normed time periods with and without lockdown measures are analyzed in detail on the example of Germany representing the spreading behavior in Europe. Additional information in comparison to classical infection analyzes models like SIR model is generated by the application of Weibull distribution models with easy interpretable parameters and the dynamic development of COVID-19 is outlined.\n\nIn a further step, the occurrence of infection of COVID-19 is put into the context of other common infectious diseases in Germany like Influenza or Norovirus to evaluate the infectiousness. Differences in spreading behavior of COVID-19 in comparison to these well-known infectious diseases are underlined for different pandemic phases.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.23.21255515", + "rel_abs": "BackgroundAs of March 2021, three SARS-CoV-2 variants of concern (VOC) have been identified (B.1.1.7, B.1.351 and P.1) and been detected in over 111 countries. Despite their widespread circulation, little is known about their transmission characteristics. There is a need to understand current evidence on VOCs before practice and policy decisions can be made. This study aimed to map the evidence related to the transmission characteristics of three VOCs.\n\nMethodsA rapid scoping review approach was used. Seven databases were searched on February 21, 2021 for terms related to VOCs, transmission, public health and health systems. A grey literature search was conducted on February 26, 2021. Title/abstracts were screened independently by one reviewer, while full texts were screened in duplicate. Data were extracted using a standardized form which was co-developed with infectious disease experts. A second data extractor verified the results. Studies were included if they reported on at least one of the VOCs and transmissibility. Animal studies and modeling studies were excluded. The final report was reviewed by content experts.\n\nResultsOf the 1796 articles and 67 grey literature sources retrieved, 16 papers and 7 grey sources were included. Included studies used a wide range of designs and methods. The majority (n=20) reported on B.1.1.7. Risk of transmission, reported in 15 studies, was 45-71% higher for B.1.1.7 compared to non-VOCs, while R0 was 75-78% higher and the reported Rt ranged from 1.1-2.8. There was insufficient evidence on the transmission risk of B.1.35.1 and P.1. Twelve studies discussed the mechanism of transmission of VOCs. Evidence suggests an increase in viral load among VOCs based on cycle threshold values, and possible immune evasion due to increased ACE2 binding capacity of VOCs. However, findings should be interpreted with caution due to the variability in study designs and methods.\n\nConclusionVOCs appear to be more transmissible than non-VOCs, however the mechanism of transmission is unclear. With majority of studies focusing on the B.1.1.7 VOC, more research is needed to build upon these preliminary findings. It is recommended that decision-makers continue to monitor VOCs and emerging evidence on this topic to inform public health policy.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Stefan Bracke", - "author_inst": "University of Wuppertal" + "author_name": "Janet A Curran", + "author_inst": "Dalhousie University" }, { - "author_name": "Alicia Puls", - "author_inst": "University of Wuppertal" + "author_name": "Justine Dol", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Leah Boulos", + "author_inst": "Maritime SPOR SUPPORT Unit (MSSU)" + }, + { + "author_name": "Mari Somerville", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Jason LeBlanc", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Lisa Barrett", + "author_inst": "Nova Scotia Health Authority (NSHA)" + }, + { + "author_name": "Jeannette Comeau", + "author_inst": "IWK Health Centre" + }, + { + "author_name": "Bearach Reynolds", + "author_inst": "Evidence Synthesis Ireland (ESI)" + }, + { + "author_name": "Holly McCulloch", + "author_inst": "IWK Health Centre" + }, + { + "author_name": "Marilyn MacDonald", + "author_inst": "JBI Centre of Excellence, School of Nursing, Dalhousie University" + }, + { + "author_name": "Danielle Shin", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Allyson Gallant", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Helen Wong", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Daniel Crowther", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Ziwa Yu", + "author_inst": "Dalhousie University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -775247,51 +773750,75 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.04.20.440722", - "rel_title": "Mild and severe SARS-CoV-2 infection induces respiratory and intestinal microbiome changes in the K18-hACE2 transgenic mouse model", + "rel_doi": "10.1101/2021.04.20.21255480", + "rel_title": "Multiplex SARS-CoV-2 Genotyping PCR for Population-Level Variant Screening and Epidemiologic Surveillance", "rel_date": "2021-04-23", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.20.440722", - "rel_abs": "Transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in millions of deaths and declining economies around the world. K18-hACE2 mice develop disease resembling severe SARS-CoV-2 infection in a virus dose-dependent manner. The relationship between SARS-CoV-2 and the intestinal or respiratory microbiome is not fully understood. In this context, we characterized the cecal and lung microbiome of SARS-CoV-2 challenged K18-hACE2 transgenic mice in the presence or absence of treatment with the Mpro inhibitor GC376. Cecum microbiome showed decreased Shannon and Inv Simpson diversity index correlating with SARS-CoV-2 infection dosage and a difference of Bray-Curtis dissimilarity distances among control and infected mice. Bacterial phyla such as Firmicutes, particularly Lachnospiraceae and Oscillospiraceae, were significantly less abundant while Verrucomicrobiota, particularly the family Akkermansiaceae, were increasingly more prevalent during peak infection in mice challenged with a high virus dose. In contrast to the cecal microbiome, the lung microbiome showed similar microbial diversity among the control, low and high challenge virus groups, independent of antiviral treatment. Bacterial phyla in the lungs such as Bacteroidota decreased while Firmicutes and Proteobacteria were significantly enriched in mice challenged with a high dose of SARS-CoV-2. In summary, we identified changes in the cecal and lung microbiome of K18-hACE2 mice with severe clinical signs of SARS-CoV-2 infection.\n\nIMPORTANCEThe COVID-19 pandemic has resulted in millions of deaths. The hosts respiratory and intestinal microbiome can affect directly or indirectly the immune system during viral infections. We characterized the cecal and lung microbiome in a relevant mouse model challenged with a low and high dose of SARS-CoV-2 in the presence or absence of an antiviral Mpro inhibitor, GC376. Decreased microbial diversity and taxonomic abundances of the phyla Firmicutes, particularly Lachnospiraceae, correlating with infection dosage was observed in the cecum. In addition, microbes within the family Akkermansiaceae were increasingly more prevalent during peak infection, which is observed in other viral infections. The lung microbiome showed similar microbial diversity to the control, independent of antiviral treatment. Decreased Bacteroidota and increased Firmicutes and Proteobacteria were observed in the lungs in a virus dose-dependent manner. These studies add to a better understanding of the complexities associated with the intestinal microbiome during respiratory infections.", - "rel_num_authors": 8, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.20.21255480", + "rel_abs": "BackgroundEmergence of SARS-CoV-2 variants with concerning phenotypic mutations is of public health interest. Genomic surveillance is an important tool for pandemic response, but many laboratories do not have the resources to support population-level sequencing. We hypothesized that a spike genotyping nucleic acid amplification test (NAAT) could facilitate high-throughput variant surveillance.\n\nMethodsWe designed and analytically validated a one-step multiplex allele-specific reverse transcriptase polymerase chain reaction (RT-qPCR) to detect three non-synonymous spike protein mutations (L452R, E484K, N501Y). Assay specificity was validated with next-generation whole-genome sequencing. We then screened a large cohort of SARS-CoV-2 positive specimens from our San Francisco Bay Area population.\n\nResultsBetween December 1, 2020 and March 1, 2021, we screened 4,049 unique infections by genotyping RT-qPCR, with an assay failure rate of 2.8%. We detected 1,567 L452R mutations (38.7%), 34 N501Y mutations (0.84%), 22 E484K mutations (0.54%), and 3 (0.07%) E484K+N501Y mutations. The assay had near-perfect (98-100%) concordance with whole-genome sequencing in a validation subset of 229 specimens, and detected B.1.1.7, B.1.351, B.1.427, B.1.429, B.1.526, and P.2 variants, among others. The assay revealed rapid emergence of L452R in our population, with a prevalence of 24.8% in December 2020 that increased to 62.5% in March 2021.\n\nConclusionsWe developed and clinically implemented a genotyping RT-qPCR to conduct high-throughput SARS-CoV-2 variant screening. This approach can be adapted for emerging mutations and immediately implemented in laboratories already performing NAAT worldwide using existing equipment, personnel, and extracted nucleic acid.\n\nSummary / Key PointsEmergence of SARS-CoV-2 variants with concerning phenotypes is of public health interest. We developed a multiplex genotyping RT-qPCR to rapidly detect L452R, E484K, and N501Y with high sequencing concordance. This high-throughput alternative to resource-intensive sequencing enabled surveillance of L452R emergence.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Brittany A Seibert", - "author_inst": "University of Georgia" + "author_name": "Hannah Wang", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Joaquin Caceres", - "author_inst": "University of Georgia" + "author_name": "Jacob Miller", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Stivalis Cardenas-Garcia", - "author_inst": "University of Georgia" + "author_name": "Michelle Verghese", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Silvia Carnaccini", - "author_inst": "University of Georgia" + "author_name": "Mamdouh Sibai", + "author_inst": "Stanford Healthcare" }, { - "author_name": "Ginger Geiger", - "author_inst": "University of Georgia" + "author_name": "Daniel Solis", + "author_inst": "Stanford Medicine" }, { - "author_name": "Daniela Raj\u00e3o", - "author_inst": "University of Georgia" + "author_name": "Kenji O Mfuh", + "author_inst": "Stanford Health Care" }, { - "author_name": "Elizabeth A Ottesen", - "author_inst": "University of Georgia" + "author_name": "Becky Jiang", + "author_inst": "Stanford Health Care" }, { - "author_name": "Daniel R. Perez", - "author_inst": "University of Georgia" + "author_name": "Naomi Iwai", + "author_inst": "Stanford Health Care" + }, + { + "author_name": "Marilyn Mar", + "author_inst": "Stanford Health Care" + }, + { + "author_name": "ChunHong Huang", + "author_inst": "Stanford University School of Medicine" + }, + { + "author_name": "Fumiko Yamamoto", + "author_inst": "Stanford University School of Medicine" + }, + { + "author_name": "Malaya K. Sahoo", + "author_inst": "Stanford University School of Medicine" + }, + { + "author_name": "James Zehnder", + "author_inst": "Stanford University School of Medicine" + }, + { + "author_name": "Benjamin A. Pinsky", + "author_inst": "Stanford University School of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2021.04.22.21255952", @@ -777141,45 +775668,77 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.04.19.21255725", - "rel_title": "No evidence of significant cross-reactivity between the dengue virus (DENV) and SARS-CoV-2 IgG antibodies", + "rel_doi": "10.1101/2021.04.19.21255720", + "rel_title": "SARS-CoV-2 natural antibody response persists up to 12 months in a nationwide study from the Faroe Islands", "rel_date": "2021-04-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.19.21255725", - "rel_abs": "BackgroundSeveral studies reported serological cross-reaction between DENV and SARS-CoV-2 IgG antibodies using rapid point of care (POC) assays. Limited data are available about cross-reactivity when testing is done using advanced chemiluminescence immunoassay (CLIA) and ELISA assays.\n\nObjectiveThis study aims to investigate potential serological cross-reactivity between SARS-CoV-2-IgG and DENV-IgG using CLIA and ELISA assays.\n\nStudy-designA total of 90 DENV-IgG-ELISA positive and 90 negative pre-pandemic sera were tested for anti-SARS-CoV-2-IgG using the automated CL-900i CLIA assay. Furthermore, a total of 91 SARS-CoV-2-IgG-CLIA positive and 91 negative post-pandemic sera were tested for anti-DENV-IgG using the Novalis ELISA assay.\n\nResultsThe DENV-IgG positive sera had 5 positives and 85 negatives for SARS-CoV-2-IgG. The DENV-IgG negative sera also had 5 positives and 85 negatives for SARS-CoV-2-IgG. No statistically significant difference in specificity between the DENV-IgG positive and DENV-IgG negative sera was found (p-value=1.00). The SARS-CoV-2-IgG positive sera had 43 positives, 47 negatives, and 1 equivocal for DENV-IgG. The SARS-CoV-2-IgG negative sera had 50 positives, 40 negatives, and 1 equivocal for DENV-IgG. No statistically significant difference in the proportion that is DENV-IgG positive between the SARS-CoV-2-IgG positive and SARS-CoV-2-IgG negative sera (p-value=0.58).\n\nConclusionsNo evidence for cross-reactivity between the DENV and SARS-CoV-2 IgG antibodies was found.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.19.21255720", + "rel_abs": "Only a few studies have assessed the long-term duration of the humoral immune response against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).\n\nIn this nationwide longitudinal study from the Faroe Islands with close to full participation of all individuals on the Islands with PCR confirmed COVID-19 during the two waves of infections in the spring and autumn 2020 (n=172 & n=233), samples were drawn at three longitudinal time points (3, 7 and 12 months and 1, 3 and 7 months after disease onset, respectively).\n\nSerum was analyzed with a direct quantitative IgG antibody binding ELISA to detect anti-SARS-CoV-2 spike RBD antibodies and a commercially available qualitative sandwich RBD ELISA kit measuring total antibody binding.\n\nThe seropositive rate in the convalescent individuals was above 95 % at all sampling time points for both assays. There was an overall decline in IgG titers over time in both waves (p < 0.001). Pairwise comparison showed that IgG declined significantly from the first sample until approximately 7 months in both waves (p < 0.001). After that, the antibody level still declined significantly (p < 0.001), but decelerated with an altered slope remaining fairly stable from 7 months to 12 months after infection. Interestingly, the IgG titers followed a U-shaped curve with higher antibody levels among the oldest (67+) and the youngest (0- 17) age groups compared to intermediate groups (p < 0.001).\n\nOur results indicate that COVID-19 convalescent individuals are likely to be protected from reinfection at least 12 months after symptom onset and maybe even longer. We believe our results can add to the understanding of natural immunity and the expected durability of SARS-CoV-2 vaccine immune responses.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Farah M. Shurrab", - "author_inst": "Qatar University" + "author_name": "Maria Skaalum Petersen", + "author_inst": "Department of Occupational Medicine and Public Health, the Faroese Hospital System, Torshavn, Faroe Islands, Centre of Health Science, University of the Faroe I" }, { - "author_name": "Fathima Humaira", - "author_inst": "Qatar University" + "author_name": "Cecilie Bo Hansen", + "author_inst": "Department of Clinical Immunology, Rigshospitalet, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark" }, { - "author_name": "Enas S. Al-Absi", - "author_inst": "Qatar University" + "author_name": "Marnar Fridheim Kristiansen", + "author_inst": "Centre of Health Science, University of the Faroe Islands, Torshavn, Faroe Islands, COVID-19 task force, Ministry of Health, Faroe Islands" }, { - "author_name": "Duaa W. Al-Sadeq", - "author_inst": "Qatar University" + "author_name": "Jogvan Pall Fjallsbak", + "author_inst": "Faroese Food and Veterinary Authority, Torshavn, Faroe Islands" }, { - "author_name": "Hamda Qotba", - "author_inst": "Primary Health Care Centers, Qatar" + "author_name": "Solrun Larsen", + "author_inst": "Faroese Food and Veterinary Authority, Torshavn, Faroe Islands" }, { - "author_name": "Hadi M. Yassine", - "author_inst": "Qatar University" + "author_name": "Johanna Ljosa Hansen", + "author_inst": "Faroese Food and Veterinary Authority, Torshavn, Faroe Islands" }, { - "author_name": "Laith J Abu-Raddad", - "author_inst": "Weill Cornell Medicine-Qatar" + "author_name": "Ida Jarlhelt", + "author_inst": "Department of Clinical Immunology, Rigshospitalet, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark" }, { - "author_name": "Gheyath K. Nasrallah", - "author_inst": "Qatar University" + "author_name": "Laura Perez Alos", + "author_inst": "Department of Clinical Immunology, Rigshospitalet, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark" + }, + { + "author_name": "Bjarni a Steig", + "author_inst": "COVID 19 task force, Ministry of Health, Faroe Islands, Medical Department, National Hospital of the Faroe Islands, Torshavn, Faroe Islands" + }, + { + "author_name": "Debes Hammershaimb Christiansen", + "author_inst": "Faroese Food and Veterinary Authority, Torshavn, Faroe Islands" + }, + { + "author_name": "Lars Fodgaard Moller", + "author_inst": "Chief Medical Officer, Torshavn, Faroe Islands" + }, + { + "author_name": "Marin Strom", + "author_inst": "Centre of Health Science, University of the Faroe Islands, Torshavn, Faroe Islands, Department of Epidemiology Research, Statens Serum Institut, Copenhagen S, D" + }, + { + "author_name": "Gudrid Andorsdottir", + "author_inst": "The Genetic Biobank, Torshavn, Faroe Islands" + }, + { + "author_name": "Shahin Gaini", + "author_inst": "Medical Department, National Hospital of the Faroe Islands, Torshavn, Faroe Islands, Department of Infectious Diseases, Odense University Hospital, Odense, Denm" + }, + { + "author_name": "Pal Weihe", + "author_inst": "Department of Occupational Medicine and Public Health, the Faroese Hospital System, Torshavn, Faroe Islands, Centre of Health Science, University of the Faroe I" + }, + { + "author_name": "Peter Garred", + "author_inst": "Department of Clinical Immunology, Rigshospitalet, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark" } ], "version": "1", @@ -779110,41 +777669,89 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.20.21254636", - "rel_title": "Effectiveness of the BNT162b2 vaccine in preventing COVID-19 in the working age population - first results from a cohort study in Southern Sweden", + "rel_doi": "10.1101/2021.04.20.21255677", + "rel_title": "Discrete immune response signature to SARS-CoV-2 mRNA vaccination versus infection", "rel_date": "2021-04-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.20.21254636", - "rel_abs": "BackgroundVaccine effectiveness against COVID-19 needs to be assessed in diverse real-world population settings.\n\nMethodsA cohort study of 805 741 residents in Sk[a]ne county, Southern Sweden, aged 18-64 years, of whom 26 587 received at least one dose of the BNT162b2 vaccine. Incidence rates of COVID-19 were estimated in sex- and age-adjusted analysis and stratified in two-week periods with substantial community spread of the disease.\n\nResultsThe estimated vaccine effectiveness in preventing infection [≥]7 days after second dose was 86% (95% CI 72-94%) but only 42% (95% CI 14-63%) [≥]14 days after a single dose. No difference in vaccine effectiveness was observed between females and males. Having a prior positive test was associated with 91% (95% CI 85 to 94%) effectiveness against new infection among the unvaccinated.\n\nConclusionA satisfactory effectiveness of BNT162b2 after the second dose was suggested, but with possibly substantially lower effect before the second dose.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.20.21255677", + "rel_abs": "SARS-CoV-2 infection and vaccination elicit potent immune responses. Our study presents a comprehensive multimodal single-cell dataset of peripheral blood of patients with acute COVID-19 and of healthy volunteers before and after receiving the SARS-CoV-2 mRNA vaccine and booster. We compared host immune responses to the virus and vaccine using transcriptional profiling, coupled with B/T cell receptor repertoire reconstruction. COVID-19 patients displayed an enhanced interferon signature and cytotoxic gene upregulation, absent in vaccine recipients. These findings were validated in an independent dataset. Analysis of B and T cell repertoires revealed that, while the majority of clonal lymphocytes in COVID-19 patients were effector cells, clonal expansion was more evident among circulating memory cells in vaccine recipients. Furthermore, while clonal {beta} T cell responses were observed in both COVID-19 patients and vaccine recipients, dramatic expansion of clonal {gamma}{delta}T cells was found only in infected individuals. Our dataset enables comparative analyses of immune responses to infection versus vaccination, including clonal B and T cell responses. Integrating our data with publicly available datasets allowed us to validate our findings in larger cohorts. To our knowledge, this is the first dataset to include comprehensive profiling of longitudinal samples from healthy volunteers pre/post SARS-CoV-2 vaccine and booster.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Jonas Bjork", - "author_inst": "Division of Occupational and Environmental Medicine, Lund University, Lund, Sweden" + "author_name": "Ellie N Ivanova", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Malin Inghammar", - "author_inst": "Department of Clinical Sciences Lund, Section for Infection Medicine, Skane University Hospital, Lund University, Lund, Sweden" + "author_name": "Joseph C Devlin", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Mahnaz Moghaddassi", - "author_inst": "Social Medicine and Global Health, Department of Clinical Sciences Malmo, Lund University, Malmo, Sweden" + "author_name": "Terild B Buus", + "author_inst": "University of Copenhagen" }, { - "author_name": "Magnus Rasmussen", - "author_inst": "Department of Clinical Sciences Lund, Section for Infection Medicine, Skane University Hospital, Lund University, Lund, Sweden" + "author_name": "Akiko Koide", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Ulf Malmqvist", - "author_inst": "Clinical Studies Sweden, Forum South, Skane University Hospital, Lund, Sweden" + "author_name": "Amber Cornelius", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Fredrik Kahn", - "author_inst": "Department of Clinical Sciences Lund, Section for Infection Medicine, Skane University Hospital, Lund University, Lund, Sweden" + "author_name": "Marie I Samanovic", + "author_inst": "NYU Grossman School of Medicine" + }, + { + "author_name": "Alberto Herrera", + "author_inst": "NYU Grossman School of Medicine" + }, + { + "author_name": "Eleni P Mimitou", + "author_inst": "NY Genome Center" + }, + { + "author_name": "Chenzhen Zhang", + "author_inst": "NYU Grossman School of Medicine" + }, + { + "author_name": "Ludovic Desvignes", + "author_inst": "NYU Grossman School of Medicine" + }, + { + "author_name": "Niels Odum", + "author_inst": "University of Copenhagen" + }, + { + "author_name": "Peter Smibert", + "author_inst": "NY Genome Center" + }, + { + "author_name": "Robert Ulrich", + "author_inst": "NYU Grossman School of Medicine" + }, + { + "author_name": "Mark J Mulligan", + "author_inst": "NYU Grossman School of Medicine" + }, + { + "author_name": "Shohei Koide", + "author_inst": "NYU Grossman School of Medicine" + }, + { + "author_name": "Kelly V Ruggles", + "author_inst": "NYU Grossman School of Medicine" + }, + { + "author_name": "Ramin S Herati", + "author_inst": "NYU Grossman School of Medicine" + }, + { + "author_name": "Sergei B Koralov", + "author_inst": "NYU School of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -780864,37 +779471,25 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2021.04.15.21255556", - "rel_title": "Contracting COVID-19: A Longitudinal Investigation of the Impact of Beliefs and Knowledge", + "rel_doi": "10.1101/2021.04.20.21255781", + "rel_title": "Demographics of COVID19 vaccine hesitancy during the second wave of COVID-19 pandemic: A cross-sectional web-based survey in Saudi Arabia", "rel_date": "2021-04-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.15.21255556", - "rel_abs": "Recent work has found that an individuals beliefs and personal characteristics can impact perceptions of and responses to the COVID-19 pandemic. Certain individuals--such as those who are politically conservative, endorse conspiracy theories, or who believe the threat of COVID-19 to be exaggerated--are less likely to engage in such preventative behaviors as social distancing. The current research aims to address whether these individual difference variables not only affect peoples subjective and behavioral reactions to the pandemic, but also whether they actually impact individuals likelihood of contracting COVID-19. In the early months of the pandemic, U.S. participants responded to a variety of individual difference measures as well as questions specific to COVID-19 and the pandemic itself. Four months later, 2,120 of these participants responded with whether they had contracted COVID-19. Nearly all of our included individual difference measures significantly predicted whether a person reported believing they had contracted COVID-19 as well as whether they had actually tested positive for the virus in this four-month period. Additional analyses revealed that all of these relationships were primarily mediated by whether participants held accurate knowledge about COVID-19. These findings offer useful insights for developing more effective interventions aimed at slowing the spread of both COVID-19 and future diseases. Moreover, some findings offer critical tests of the validity of such theoretical frameworks as those concerning conspiratorial ideation and disgust sensitivity within a real-world context.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.20.21255781", + "rel_abs": "BackgroundThe Coronavirus disease 2019 (COVID-19) pandemic is considered a major global public health threat affecting across the life course and socioeconomic aspects of life. Globally acceptance to an effective vaccine is the most anticipated resolution. This study aims to evaluate intent to be vaccinated among public in Saudi Arabia during the second wave of COVID-19 pandemic.\n\nMethodsA cross-sectional web-based study was designed in Saudi Arabia. Study participants (N=658) were recruited through snowball sampling. SurveyMonkey platform was used to record the response. Cross-tabulation were performed by participants intention to vaccinate against COVID-19 virus with sociodemographic characteristics and respondents risk perception towards COVID-19, trust in the healthcare system, and their history of vaccine hesitancy behavior. Multivariable logistic regression analysis was performed to compute the predictors of vaccination intention among the study participants.\n\nResults658 participants were completed the survey (females = 47.4%). Of the 658 participants 351 (53.3%) have shown intent to be vaccinated. 519 (78.8%) of the participants were reported to be at high risk of COVID-19, and 307 (46.6%) were reported to trust the healthcare system in the country. The multivariable analysis shows respondents with a high-risk perception (OR: 2.27, 95% CI: 1.49-3.48); higher trust in the healthcare system (OR: 3.24, 95% CI: 2.32-4.61) was found to be the significant factor affecting the decision in acceptance of the COVID-19 vaccine in Saudi Arabia.\n\nConclusionParticipants reported high knowledge towards COVID-19 virus, and vaccine developments. About half (46.6%) of the study participant reported refusal/hesitancy towards the vaccine during the second wave of the pandemic in Saudi Arabia. The study highlighted that higher risk perception and higher trust in the healthcare system were found to be the main reasons for participants intentions behind the vaccination.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Courtney A Moore", - "author_inst": "The Ohio State University" - }, - { - "author_name": "Benjamin C Ruisch", - "author_inst": "Leiden University" - }, - { - "author_name": "Javier A Granados Samayoa", - "author_inst": "The Ohio State University" - }, - { - "author_name": "Shelby T Boggs", - "author_inst": "The Ohio State University" + "author_name": "Mohammed Abdulrahman Almohaithef", + "author_inst": "Department of Public Health, College of Health Sciences, Saudi Electronic University, Riyadh, Saudi Arabia" }, { - "author_name": "Jesse T Ladanyi", - "author_inst": "The Ohio State University" + "author_name": "Bijaya Kumar Padhi", + "author_inst": "Department of Community Medicine & School of Public Health, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India" }, { - "author_name": "Russell H Fazio", - "author_inst": "The Ohio State University" + "author_name": "Soukaina Abdulmajed Ennaceur", + "author_inst": "Department of Public Health, College of Health Sciences, Saudi Electronic University, Jeddah, Kingdom of Saudi Arabia" } ], "version": "1", @@ -782550,31 +781145,95 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2021.04.16.21255630", - "rel_title": "CovidEnvelope: A Fast Automated Approach to Diagnose COVID-19 from Cough Signals", + "rel_doi": "10.1101/2021.04.17.21255518", + "rel_title": "Skin imprints to provide noninvasive metabolic profiling of COVID-19 patients", "rel_date": "2021-04-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.16.21255630", - "rel_abs": "The COVID-19 pandemic has a devastating impact on the health and well-being of global population. Cough audio signals classification showed potential as a screening approach for diagnosing people, infected with COVID-19. Recent approaches need costly deep learning algorithms or sophisticated methods to extract informative features from cough audio signals. In this paper, we propose a low-cost envelope approach, called CovidEnvelope, which can classify COVID-19 positive and negative cases from raw data by avoiding above disadvantages. This automated approach can pre-process cough audio signals by filter-out back-ground noises, generate an envelope around the audio signal, and finally provide outcomes by computing area enclosed by the envelope. It has been seen that reliable datasets are also important for achieving high performance. Our approach proves that human verbal confirmation is not a reliable source of information. Finally, the approach reaches highest sensitivity, specificity, accuracy, and AUC of 0.92, 0.87, 0.89, and 0.89 respectively. The automatic approach only takes 1.8 to 3.9 minutes to compute these performances. Overall, this approach is fast and sensitive to diagnose the people living with COVID-19, regardless of having COVID-19 related symptoms or not, and thus have vast applicability in human well-being by designing HCI devices incorporating this approach.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.17.21255518", + "rel_abs": "As the current COVID-19 pandemic progresses, more symptoms and signals related to how the disease manifests in the human body arise in the literature. Skin lesions and coagulopathies may be confounding factors on routine care and patient management. We analyzed the metabolic and lipidic profile of the skin from COVID-19 patients using imprints in silica plates as a non-invasive alternative, in order to better understand the biochemical disturbances caused by SARS-CoV-2 in the skin. One hundred and one patients (64 COVID-19 positive patients and 37 control patients) were enrolled in this cross-sectional study from April 2020 to June 2020 during the first wave of COVID-19 in Sao Paulo, Brazil. Fourteen biomarkers were identified related to COVID-19 infection (7 increased and 7 decreased in COVID-19 patients). Remarkably, oleamide has shown promising performance, providing 79.0% of sensitivity on a receiver operating characteristic curve model. Species related to coagulation and immune system maintenance such as phosphatidylserines were decreased in COVID-19 patients; on the other hand, cytokine storm and immunomodulation may be affected by molecules increased in the COVID-19 group, particularly primary fatty acid amides and N-acylethanolamines, which are part of the endocannabinoid system. Our results show that skin imprints may be a useful, noninvasive strategy for COVID-19 screening, by electing a pool of biomarkers with diagnostic potential.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Md Zakir Hossain", - "author_inst": "The Australian National University" + "author_name": "Jeany Delafiori", + "author_inst": "Innovare Biomarkers Laboratory, School of Pharmaceutical Sciences, University of Campinas, Campinas, Brazil" }, { - "author_name": "Md. Bashir Uddin", - "author_inst": "Khulna University of Engineering & Technology" + "author_name": "Rinaldo Focaccia Siciliano", + "author_inst": "Clinical Division of Infectious and Parasitic Diseases, University of S\u00e3o Paulo Medical School, Brazil; Instituto do Coracao (InCor), Hospital das Clinicas HCFM" }, { - "author_name": "Khandaker Asif Ahmed", - "author_inst": "The Commonwealth Science and Industrial Research Organization" + "author_name": "Arthur Noin de Oliveira", + "author_inst": "Innovare Biomarkers Laboratory, School of Pharmaceutical Sciences, University of Campinas, Campinas, Brazil" + }, + { + "author_name": "Jos\u00e9 Carlos Nicolau", + "author_inst": "Instituto do Coracao (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de S\u00e3o Paulo, S\u00e3o Paulo, Brazil" + }, + { + "author_name": "Geovana Manzan Sales", + "author_inst": "Innovare Biomarkers Laboratory, School of Pharmaceutical Sciences, University of Campinas, Campinas, Brazil" + }, + { + "author_name": "Talia Falc\u00e3o Dal\u00e7\u00f3quio", + "author_inst": "Instituto do Coracao (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de S\u00e3o Paulo, S\u00e3o Paulo, Brazil Brazil" + }, + { + "author_name": "Estela Natacha Brandt Busanello", + "author_inst": "Innovare Biomarkers Laboratory, School of Pharmaceutical Sciences, University of Campinas, Campinas, Brazil" + }, + { + "author_name": "Adriana Eguti", + "author_inst": "Sumar\u00e9 State Hospital, Sumar\u00e9, Brazil" + }, + { + "author_name": "Diogo Noin de Oliveira", + "author_inst": "Innovare Biomarkers Laboratory, School of Pharmaceutical Sciences, University of Campinas, Campinas, Brazil" + }, + { + "author_name": "Adriadne Justi Bertolin", + "author_inst": "Instituto do Coracao (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de S\u00e3o Paulo, S\u00e3o Paulo, Brazil" + }, + { + "author_name": "Luiz Augusto dos Santos", + "author_inst": "Paul\u00ednia Municipal Hospital, Paul\u00ednia, Brazil" + }, + { + "author_name": "Roc\u00edo Salsoso", + "author_inst": "Instituto do Coracao (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de S\u00e3o Paulo, S\u00e3o Paulo, Brazil" + }, + { + "author_name": "Fabiana G Marcondes-Braga", + "author_inst": "Instituto do Coracao (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de S\u00e3o Paulo, S\u00e3o Paulo, Brazil" + }, + { + "author_name": "Nelson Dur\u00e1n", + "author_inst": "Laboratory of Urogenital Carcinogenesis and Immunotherapy, University of Campinas, Campinas, Brazil" + }, + { + "author_name": "Maur\u00edcio Wesley Perroud Jr.", + "author_inst": "Sumar\u00e9 State Hospital, Sumar\u00e9, Brazil" + }, + { + "author_name": "Ester Cerdeira Sabino", + "author_inst": "Institute of Tropical Medicine, University of S\u00e3o Paulo, S\u00e3o Paulo, Brazil" + }, + { + "author_name": "Leonardo Oliveira Reis", + "author_inst": "UroScience Laboratory, University of Campinas, Campinas, Brazil" + }, + { + "author_name": "Wagner Jos\u00e9 F\u00e1varo", + "author_inst": "Laboratory of Urogenital Carcinogenesis and Immunotherapy, University of Campinas, Campinas, Brazil" + }, + { + "author_name": "Rodrigo Ramos Catharino", + "author_inst": "Innovare Biomarkers Laboratory, School of Pharmaceutical Sciences, University of Campinas, Campinas, Brazil" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.04.14.21255512", @@ -784784,89 +783443,81 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.12.21255324", - "rel_title": "Sero-monitoring of health care workers reveals complex relationships between common coronavirus antibodies and SARS-CoV-2 severity", + "rel_doi": "10.1101/2021.04.12.21255284", + "rel_title": "Differential Performance of CoronaCHEK SARS-CoV-2 Lateral Flow Antibody Assay by Geographic Origin of Samples", "rel_date": "2021-04-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.12.21255324", - "rel_abs": "Recent common coronavirus (CCV) infections are associated with reduced COVID-19 severity upon SARS-CoV-2 infection, however the immunological mechanisms involved are unknown. We completed serological assays using samples collected from health care workers to identify antibody types associated with SARS-CoV-2 protection and COVID-19 severity. Rare SARS-CoV-2 cross-reactive antibodies elicited by past CCV infections were not associated with protection; however, the duration of symptoms following SARS-CoV-2 infections was significantly reduced in individuals with higher common betacoronavirus ({beta}CoV) antibody titers. Since antibody titers decline over time after CCV infections, individuals in our cohort with higher {beta}CoV antibody titers were more likely recently infected with common {beta}CoVs compared to individuals with lower antibody titers. Therefore, our data suggest that recent {beta}CoV infections potentially limit the severity of SARS-CoV-2 infections through mechanisms that do not involve cross-reactive antibodies. Our data are consistent with the emerging hypothesis that cellular immune responses elicited by recent common {beta}CoV infections transiently reduce disease severity following SARS-CoV-2 infections.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.12.21255284", + "rel_abs": "BackgroundWe assessed the performance of CoronaCHEK lateral flow assay on samples from Uganda and Baltimore to determine the impact of geographic origin on assay performance.\n\nMethodsSerum samples from SARS-CoV-2 PCR+ individuals (Uganda: 78 samples from 78 individuals and Baltimore: 266 samples from 38 individuals) and from pre-pandemic individuals (Uganda 1077 and Baltimore 532) were evaluated. Prevalence ratios (PR) were calculated to identify factors associated with a false-positive test.\n\nResultsAfter first positive PCR in Ugandan samples the sensitivity was: 45% (95% CI 24,68) at 0-7 days; 79% (95%CI 64,91) 8-14 days; and 76% (95%CI 50,93) >15 days. In samples from Baltimore, sensitivity was: 39% (95% CI 30, 49) 0-7 days; 86% (95% CI 79,92) 8-14 days; and 100% (95% CI 89,100) 15 days post positive PCR. The specificity of 96.5% (95% CI 97.5,95.2) in Ugandan samples was significantly lower than samples from Baltimore 99.3% (95% CI 98.1,99.8), p<0.01. In Ugandan samples, individuals with a false positive result were more likely to be male (PR 2.04, 95% CI 1.03,3.69) or individuals who had a fever more than a month prior to sample acquisition (PR 2.87, 95% CI 1.12,7.35).\n\nConclusionsSensitivity of the CoronaCHEK was similar in samples from Uganda and Baltimore. The specificity was significantly lower in Ugandan samples than in Baltimore samples. False positive results in Ugandan samples appear to correlate with a recent history of a febrile illness, potentially indicative of a cross-reactive immune response in individuals from East Africa.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Sigrid Gouma", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Madison E. Weirick", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Marcus J. Bolton", - "author_inst": "University of Pennsylvania" + "author_name": "Owen R Baker", + "author_inst": "NIAID" }, { - "author_name": "Claudia P. Arevalo", - "author_inst": "University of Pennsylvania" + "author_name": "M. Kate Grabowski", + "author_inst": "Johns Hopkins University School of Medicine," }, { - "author_name": "Eileen C. Goodwin", - "author_inst": "University of Pennsylvania" + "author_name": "Ronald M Galiwango", + "author_inst": "Rakai Health Sciences Program" }, { - "author_name": "Elizabeth M. Anderson", - "author_inst": "University of Pennsylvania" + "author_name": "Aminah Nalumansi", + "author_inst": "Uganda Virus Research Institute" }, { - "author_name": "Christopher M. McAllister", - "author_inst": "University of Pennsylvania" + "author_name": "Jennifer Serwanga", + "author_inst": "MRC/UVRI Uganda Research Unit on AIDS" }, { - "author_name": "Shannon R. Christensen", - "author_inst": "University of Pennsylvania" + "author_name": "William Clarke", + "author_inst": "Johns Hopkins University School of Medicine" }, { - "author_name": "Debora Dunbar", - "author_inst": "University of Pennsylvania" + "author_name": "Yu-Hsiang Hsieh", + "author_inst": "Johns Hopkins University School of Medicine" }, { - "author_name": "Danielle Fiore", - "author_inst": "University of Pennsylvania" + "author_name": "Richard Eric Rothman", + "author_inst": "Johns Hopkins Hospital" }, { - "author_name": "Amanda Brock", - "author_inst": "University of Pennsylvania" + "author_name": "Reinaldo E Fernandez", + "author_inst": "JHU" }, { - "author_name": "JoEllen Weaver", - "author_inst": "University of Pennsylvania" + "author_name": "David M. Serwadda", + "author_inst": "Makerere University School of Public Health" }, { - "author_name": "John Millar", - "author_inst": "University of Pennsylvania" + "author_name": "Joseph Kagaayi", + "author_inst": "Rakai Health Sciences Program" }, { - "author_name": "Stephanie DerOhannessian", - "author_inst": "University of Pennsylvania" + "author_name": "Tom Lutalo", + "author_inst": "RHSP" }, { - "author_name": "Ian Frank", - "author_inst": "University of Pennsylvania" + "author_name": "Steven J. Reynolds", + "author_inst": "NIAID and JHU" }, { - "author_name": "Daniel J. Rader", - "author_inst": "University of Pennsylvania" + "author_name": "Pontiano Kaleebu", + "author_inst": "Medical Research Council/Uganda Virus Research Institute" }, { - "author_name": "E. John Wherry", - "author_inst": "University of Pennsylvania" + "author_name": "Thomas C. Quinn", + "author_inst": "NIAID and JHU" }, { - "author_name": "Scott E. Hensley", - "author_inst": "University of Pennsylvania" + "author_name": "Oliver Laeyendecker", + "author_inst": "NIAID" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -786646,41 +785297,77 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.04.13.21255320", - "rel_title": "Assessing the impact of SARS-CoV-2 prevention measures in schools by means of agent-based simulations calibrated to cluster tracing data", + "rel_doi": "10.1101/2021.04.12.21255349", + "rel_title": "The multi-dimensional challenges of controlling SARS-CoV-2 transmission in indoor spaces: Insights from the linkage of a microscopic pedestrian simulation and virus transmission models", "rel_date": "2021-04-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.13.21255320", - "rel_abs": "How to safely maintain open schools during a pandemic is still controversial. We aim to identify those measures that effectively control the spread of SARS-CoV-2 in Austrian schools. By control we mean that each source case infects less than one other person on average. We use Austrian data on 616 clusters involving 2,822 student-cases and 676 teacher-cases to calibrate an agent-based epidemiological model in terms of cluster size and transmission risk depending on age and clinical presentation. Considering a situation in which the B1.617.2 (delta) virus strain is dominant and parts of the population are vaccinated, we quantify the impact of non-pharmaceutical intervention measures (NPIs) such as room ventilation, reduction of class size, wearing of masks during lessons, vaccinations, and school entry testing by SARS-CoV2-antigen tests. In the tracing data we find that 40% of all clusters involved no more than two cases, and 3% of the clusters only had more than 20 cases. The younger the students, the more likely we found asymptomatic cases and teachers as the source case of the in-school transmissions. Based on this data, the model shows that different school types require different combinations of NPIs to achieve control of the infection spreading: If 80% of teachers and 50% of students are vaccinated, in primary schools, it is necessary to combine at least two of the above NPIs. In secondary schools, where contact networks of students and teachers become increasingly large and dense, a combination of at least three NPIs is needed. A sensitivity analysis indicated that poorly executed mitigation measures might increase the cluster size by a factor of more than 17 for primary schools and even higher increases are to be expected for the other school types. Our results suggest that school-type-specific combinations of NPIs together with vaccinations are necessary to allow for a controlled opening of schools under sustained community transmission of the SARS-CoV-2 delta variant. However, large clusters might still occur on an infrequent, however, regular basis.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.12.21255349", + "rel_abs": "SARS-CoV-2 transmission in indoor spaces, where most infection events occur, depends on the types and duration of human interactions, among others. Understanding how these human behaviours interface with virus characteristics to drive pathogen transmission and dictate the outcomes of non-pharmaceutical interventions is important for the informed and safe use of indoor spaces. To better understand these complex interactions, we developed the Pedestrian Dynamics - Virus Spread model (PeDViS): an individual-based model that combines pedestrian behaviour models with virus spread models that incorporate direct and indirect transmission routes. We explored the relationships between virus exposure and the duration, distance, respiratory behaviour, and environment in which interactions between infected and uninfected individuals took place, and compared this to benchmark at risk interactions (1.5 metres for 15 minutes). When considering aerosol transmission, individuals adhering to distancing measures may be at risk due to build-up of airborne virus in the environment when infected individuals spend prolonged time indoors. In our restaurant case, guests seated at tables near infected individuals were at limited risk of infection but could, particularly in poorly ventilated places, experience risks that surpass that of benchmark interactions. Combining interventions that target different transmission routes can aid in accumulating impact, for instance by combining ventilation with face masks. The impact of such combined interventions depends on the relative importance of transmission routes, which is hard to disentangle and highly context dependent. This uncertainty should be considered when assessing transmission risks upon different types of human interactions in indoor spaces. We illustrated the multi-dimensionality of indoor SARS-CoV-2 transmission that emerges from the interplay of human behaviour and the spread of respiratory viruses. A modelling strategy that incorporates this in risk assessments can help inform policy makers and citizens on the safe use of indoor spaces with varying inter-human interactions.\n\nSUMMARYWith most infections happening indoors, indoor spaces played an important role in the spread and control of SARS-CoV-2. Indoor transmission and the impact of interventions targeted at these spaces are hard to predict due to the interplay of diverse inter-human interactions, host factors, virus characterisitics, and the local environment. Mathematical models can help disentangle such complex processes. Here, we introduce a model that simulates viral spread in indoor spaces by combining models on detailed human movements and interactions with models that simulate the spread and uptake of viruses through direct and indirect transmission routes. We use a restaurant-setting as a case-study and illustrate that, while common distancing measures hold for infection prevention during relatively short interactions, transmission may occur over longer distances if infected individuals spend more time in a space, particularly if poorly ventilated. The effects of intervention measures are tightly coupled to the transmission route they target and the relative importance of this route in a specific scenario. Uncertainty around the latter should be considered when assessing transmission risks. The model can be adapted to different settings, interventions, levels of population immune protection, and to other virus variants and respiratory pathogens. It can help guide decision making on effective mitigation of virus transmission in indoor spaces.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Jana Lasser", - "author_inst": "Medical University Vienna, Spitalgasse 23, 1090 Vienna, Austria and Complexity Science Hub Vienna, Josefst\\\"adterstrasse 39, 1080 Vienna, Austria" + "author_name": "Busra Atamer Balkan", + "author_inst": "Wageningen University and Research" }, { - "author_name": "Johannes Sorger", - "author_inst": "Complexity Science Hub Vienna, Josefstaedterstrasse 39, 1080 Vienna, Austria" + "author_name": "You Chang", + "author_inst": "Wageningen University and Research" }, { - "author_name": "Lukas Richter", - "author_inst": "Oesterreichische Agentur fuer Gesundheit und Ernaehrungssicherheit GmbH, Spargelfeldstrasse 191, 1220 Vienna, Austria" + "author_name": "Martijn Sparnaaij", + "author_inst": "Delft University of Technology" }, { - "author_name": "Stefan Thurner", - "author_inst": "Complexity Science Hub Vienna, Josefstaedterstrasse 39, 1080 Vienna, Austria and Medical University Vienna, Spitalgasse 23, 1090 Vienna, Austria and Santa Fe In" + "author_name": "Berend Wouda", + "author_inst": "Delft University of Technology" }, { - "author_name": "Daniela Schmid", - "author_inst": "Oesterreichische Agentur fuer Gesundheit und Ernaehrungssicherheit GmbH, Spargelfeldstrasse 191, 1220 Vienna, Austria" + "author_name": "Doris Boschma", + "author_inst": "Delft University of Technology" }, { - "author_name": "Peter Klimek", - "author_inst": "Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria" + "author_name": "Yangfan Liu", + "author_inst": "Wageningen University and Research" + }, + { + "author_name": "Yufei Yuan", + "author_inst": "Delft University of Technology" + }, + { + "author_name": "Winnie Daamen", + "author_inst": "Delft University of Technology" + }, + { + "author_name": "Mart C.M. de Jong", + "author_inst": "Wageningen University and Research" + }, + { + "author_name": "Colin Teberg", + "author_inst": "Steady State Scientific Computing" + }, + { + "author_name": "Kevin Schachtschneider", + "author_inst": "Steady State Scientific Computing" + }, + { + "author_name": "Reina S Sikkema", + "author_inst": "Erasmus Medical Center" + }, + { + "author_name": "Linda van Veen", + "author_inst": "Delft University of Technology" + }, + { + "author_name": "Dorine Duives", + "author_inst": "Delft University of Technology" + }, + { + "author_name": "Quirine ten Bosch", + "author_inst": "Wageningen University and Research" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -788352,71 +787039,79 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.12.21255299", - "rel_title": "Clinical validation of point-of-care SARS-COV-2 BD Veritor antigen test by a single throat swab for rapid COVID-19 status on hospital patients predominantly without overt COVID symptoms", - "rel_date": "2021-04-17", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.12.21255299", - "rel_abs": "BACKGROUNDFast identification of severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) infected individuals is a strategically vital task to ensure correct management and quarantine. Rapid antigen test could be a supplement to the standard-of-care Nucleic Acid Amplification Test (NAAT). The aim of this study was to determine the accuracy of the BD Veritor SARS-CoV-2 antigen test as a screening instrument in a hospital setting.\n\nMETHODSA cohort of prospective samples were collected from hospital staff and patients at the Emergency, Infectious Diseases and Pediatrics and Adolescent Medicine departments at Hvidovre Hospital. All samples were collected using oropharyngeal swabs, and BD Veritor Antigen test results were paired with routine NAAT test results. Sensitivity, specificity, positive and negative predictive values of the antigen test were calculated using NAAT as reference.\n\nRESULTSOverall, 809 samples from 674 individuals were included (average age 45 years, range 0-98 years). Among all samples, 8% were SARS-CoV-2 positive by NAAT testing and 5.3% by BD Veritor. The sensitivity of the antigen test was 63.1% and specificity 99.7%. The positive predictive value was 95.3%. False-positive rate was 4%. The cycle threshold value was significantly higher among individuals with false negative antigen tests compared to true positives.\n\nCONCLUSIONThe sensitivity, specificity and positive predictive values show that the BD Veritor antigen test from oropharyngeal collected specimens performs well. Antigen testing may be a supplement, but not substitute, to NAAT testing as the primary diagnostic modality in hospital settings where fast turnaround test results may assist in decisions regarding isolation and quarantine.", - "rel_num_authors": 13, + "rel_doi": "10.1101/2021.04.16.440124", + "rel_title": "SARS-CoV-2 proteins bind heme and hemoglobin", + "rel_date": "2021-04-16", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.16.440124", + "rel_abs": "The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome virus 2 (SARS-CoV-2), has led to a global crisis that included collapsing healthcare systems and shut-down communities, producing considerable economic burden. Despite the number of effective vaccines quickly implemented, the emergence of new variants is a primary concern. The scientific community undertook a rapid response to better study this new virus. However, critical questions about viral protein-protein interactions and mechanisms of its physiopathology are still unclear. Although severe COVID-19 was associated with hematological dysfunctions, scarce experimental data were produced about iron dysmetabolism and the viral proteins possible interaction with hemoglobin (Hb) chains. This work demonstrates the binding of SARS-CoV-2 proteins to hemin and Hb using a multimethodological approach. In silico analysis indicated binding motifs between a cavity in the viral nucleoprotein and hemoglobins porphyrin coordination region. Different hemin binding capacities of mock and SARS-CoV-2-infected culture extracts were noticed using gel electrophoresis and TMB staining. Hemin-binding proteins were isolated from SARS-CoV-2-infected cells by affinity chromatography and identified by shotgun proteomics, indicating that structural (nucleoprotein, spike, and membrane protein) and non-structural (Nsp3 and Nsp7) viral proteins interact with hemin. In vitro analyses of virus adsorption to host cells and viral replication studies in Vero cells demonstrated inhibitory activities - at different levels - by hemin, protoporphyrin IX (PpIX) Hb. Strikingly, free Hb at 1M suppressed viral replication (99 %), and its interaction with SARS-CoV-2 was localized to the RBD region of the Spike protein. The findings showed clear evidence of new avenues to disrupt viral replication and understand virus physiopathology that warrants further investigation.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Jesper Bonde", - "author_inst": "Molecular Pathology Laboratory, Dept. Pathology, Copenhagen University Hospital, Amager and Hvidovre Hospital, Copenhagen, Denmark" + "author_name": "Salvatore Giovanni De-Simone", + "author_inst": "FIOCRUZ" }, { - "author_name": "Ditte M Ejegod", - "author_inst": "Molecular Pathology Laboratory, Dept. Pathology, Copenhagen University Hospital, Amager and Hvidovre Hospital, Copenhagen, Denmark" + "author_name": "Guilherme Curty Lechuga", + "author_inst": "Fiocruz" }, { - "author_name": "Helle Pedersen", - "author_inst": "Molecular Pathology Laboratory, Dept. Pathology, Copenhagen University Hospital, Amager and Hvidovre Hospital, Copenhagen, Denmark" + "author_name": "Franklin Souza-Silva", + "author_inst": "FIOCRUZ" }, { - "author_name": "Birgitte Smith", - "author_inst": "Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital, Amager and Hvidovre Hospital, Copenhagen, Denmark" + "author_name": "Carolina de Queiroz Sacramento", + "author_inst": "FIOCRUZ" }, { - "author_name": "Dina Cortes", - "author_inst": "Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital, Amager and Hvidovre Hospital, Copenhagen, Denmark" + "author_name": "Monique Ramos de Oliveira Trugilho", + "author_inst": "FIOCRUZ" }, { - "author_name": "Caecilie Leding", - "author_inst": "Department of Infectious Diseases, Copenhagen University Hospital, Amager and Hvidovre Hospital, Copenhagen, Denmark" + "author_name": "Richard Hemmi Valente", + "author_inst": "FIOCRUZ" }, { - "author_name": "Thorbjoern Thomsen", - "author_inst": "Department of Clinical Research, Copenhagen University Hospital, Amager and Hvidovre Hospital, Copenhagen, Denmark" + "author_name": "Paloma Napole\u00e3o-P\u00eago", + "author_inst": "FIOCRUZ" }, { - "author_name": "Thomas Benfield", - "author_inst": "Department of Infectious Diseases, Copenhagen University Hospital, Amager and Hvidovre Hospital, Copenhagen, Denmark" + "author_name": "Suelen da SIlva Gomes Dias", + "author_inst": "FIOCRUZ" }, { - "author_name": "Uffe V Schnieder", - "author_inst": "Department of Clinical Microbiology, Copenhagen University Hospital, Amager and Hvidovre Hospital, Copenhagen, Denmark" + "author_name": "Natalia Fintelman-Rodrigues", + "author_inst": "FIOCRUZ" }, { - "author_name": "Jens Tingleff", - "author_inst": "Department of Emergency Medicine, Copenhagen University Hospital, Amager and Hvidovre Hospital, Copenhagen, Denmark" + "author_name": "Jairo Ramos Temerozzo", + "author_inst": "FIOCRUZ" }, { - "author_name": "Marc Arbyn", - "author_inst": "Unit of Cancer Epidemiology, Belgian Cancer Centre, Sciensano, Brussels, Belgium" + "author_name": "Nicolas Carels", + "author_inst": "FIOCRUZ" }, { - "author_name": "Gorm Lisby", - "author_inst": "Department of Clinical Microbiology, Copenhagen University Hospital, Amager and Hvidovre Hospital, Copenhagen, Denmark" + "author_name": "Carlos Roberto Alves", + "author_inst": "FIOCRUZ" }, { - "author_name": "Ove Andersen", - "author_inst": "Department of Clinical Research, Copenhagen University Hospital, Amager and Hvidovre Hospital, Copenhagen, Denmark" + "author_name": "Mirian Claudia de Souza Pereira", + "author_inst": "FIOCRUZ" + }, + { + "author_name": "David William Provance-Jr", + "author_inst": "FIOCRUZ" + }, + { + "author_name": "Thiago M De-Simone", + "author_inst": "FIOCRUZ" } ], "version": "1", "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "type": "new results", + "category": "biochemistry" }, { "rel_doi": "10.1101/2021.04.13.21255139", @@ -790130,83 +788825,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.08.21255100", - "rel_title": "REACT-1 round 10 report: Level prevalence of SARS-CoV-2 swab-positivity in England during third national lockdown in March 2021", + "rel_doi": "10.1101/2021.04.10.21255244", + "rel_title": "Modeling COVID-19 in Iran using Particle Swarm Optimization algorithm", "rel_date": "2021-04-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.08.21255100", - "rel_abs": "BackgroundIn England, hospitalisations and deaths due to SARS-CoV-2 have been falling consistently since January 2021 during the third national lockdown of the COVID-19 pandemic. The first significant relaxation of that lockdown occurred on 8 March when schools reopened.\n\nMethodsThe REal-time Assessment of Community Transmission-1 (REACT-1) study augments routine surveillance data for England by measuring swab-positivity for SARS-CoV-2 in the community. The current round, round 10, collected swabs from 11 to 30 March 2021 and is compared here to round 9, in which swabs were collected from 4 to 23 February 2021.\n\nResultsDuring round 10, we estimated an R number of 1.00 (95% confidence interval 0.81, 1.21). Between rounds 9 and 10 we estimated national prevalence has dropped by [~]60% from 0.49% (0.44%, 0.55%) in February to 0.20% (0.17%, 0.23%) in March. There were substantial falls in weighted regional prevalence: in South East from 0.36% (0.29%, 0.44%) in round 9 to 0.07% (0.04%, 0.12%) in round 10; London from 0.60% (0.48%, 0.76%) to 0.16% (0.10%, 0.26%); East of England from 0.47% (0.36%, 0.60%) to 0.15% (0.10%, 0.24%); East Midlands from 0.59% (0.45%, 0.77%) to 0.19% (0.13%, 0.28%); and North West from 0.69% (0.54%, 0.88%) to 0.31% (0.21%, 0.45%). Areas of apparent higher prevalence remain in parts of the North West, and Yorkshire and The Humber. The highest prevalence in March was found among school-aged children 5 to 12 years at 0.41% (0.27%, 0.62%), compared with the lowest in those aged 65 to 74 and 75 and over at 0.09% (0.05%, 0.16%). The close approximation between prevalence of infections and deaths (suitably lagged) is diverging, suggesting that infections may have resulted in fewer hospitalisations and deaths since the start of widespread vaccination.\n\nConclusionWe report a sharp decline in prevalence of infections between February and March 2021. We did not observe an increase in the prevalence of SARS-CoV-2 following the reopening of schools in England, although the decline of prevalence appears to have stopped. Future rounds of REACT-1 will be able to measure the rate of growth or decline from this current plateau and hence help assess the effectiveness of the vaccination roll-out on transmission of the virus as well as the potential size of any third wave during the ensuing months.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.10.21255244", + "rel_abs": "BackgroundThe first confirmed cases of COVID-19 in Iran were reported on February 19, 2020. The coronavirus expanded rapidly in all Iranian provinces and three waves of COVID-19 cases have been observed since the pandemic took effect and the fourth wave of Covid-19 cases will likely be observed soon. This study aimed to model the spread of COVID-19 in Iran and to estimate the epidemic parameters and to predict the short-term future trend of COVID-19 in Iran.\n\nMethodsWe proposed a modified SEIR epidemic spreading model and we used data from February 20, 2020, to April 9, 2021, on the number of cases reported by Iranian governments to fit the proposed model on the reported data. Particle Swarm Optimization (PSO) algorithm was employed to estimate the parameters of the proposed model and the numerical simulation results were obtained by Runge-Kutta method. The estimated parameters were employed to calculate the effective reproduction number and to predict the short-term future trends of COVID-19 cases.\n\nResultsThe results indicated that the effective reproduction number has increased during Nowruz (Persian New Year) and it was estimated to be 1.28. Considering only two exposed cases as the initial cases in the model, the cumulative number of exposed cases was estimated to be 15,252,372 individuals since the beginning of the outbreak. The prediction of the short-term future trends of COVID-19 cases with different scenarios showed that another peak of the pandemic cases occurs in the next weeks. By immediate lockdown implementation the number of active infected cases was estimated to be 397,585.\n\nConclusionDifferent scenarios of short-term prediction of the future trends of COVID-19 cases indicated that immediate strict social distancing policies need to be implemented to prevent a tremendous burden of the fourth major wave of COVID-19 infections on the health care system of Iran.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Steven Riley", - "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" - }, - { - "author_name": "Oliver Eales", - "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" - }, - { - "author_name": "David Haw", - "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" - }, - { - "author_name": "Caroline E. Walters", - "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" - }, - { - "author_name": "Haowei Wang", - "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" - }, - { - "author_name": "Kylie E. C. Ainslie", - "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" - }, - { - "author_name": "Christina Atchinson", - "author_inst": "School of Public Health, Imperial College London, UK" - }, - { - "author_name": "Claudio Fronterre", - "author_inst": "CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK" - }, - { - "author_name": "Peter J. Diggle", - "author_inst": "CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK" - }, - { - "author_name": "Deborah Ashby", - "author_inst": "School of Public Health, Imperial College London, UK" - }, - { - "author_name": "Christl A Donnelly", - "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" - }, - { - "author_name": "Graham Cooke", - "author_inst": "Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic" - }, - { - "author_name": "Wendy Barclay", - "author_inst": "Department of Infectious Disease, Imperial College London, UK" - }, - { - "author_name": "Helen Ward", - "author_inst": "School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear" - }, - { - "author_name": "Ara Darzi", - "author_inst": "Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a" + "author_name": "Ebrahim Sahafizadeh", + "author_inst": "Persian Gulf University" }, { - "author_name": "Paul Elliott", - "author_inst": "School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear" + "author_name": "MohammadAli Khajeian", + "author_inst": "Persian Gulf University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.04.08.21255118", @@ -791844,59 +790483,171 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.04.11.21255274", - "rel_title": "A Systematic Review and Meta-Analysis on Mental Illness Symptoms in Spain in the COVID-19 Crisis", + "rel_doi": "10.1101/2021.04.14.439284", + "rel_title": "Cryptic SARS-CoV2-spike-with-sugar interactions revealed by 'universal' saturation transfer analysis", "rel_date": "2021-04-14", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.11.21255274", - "rel_abs": "ObjectiveThis paper systematically reviews and assesses the prevalence of anxiety, depression, and insomnia symptoms in the general population, frontline healthcare workers (HCWs), and adult students in Spain during the COVID-19 crisis.\n\nData sourcesArticles in PubMed, Embase, Web of Science, PsycINFO, and medRxiv from March 2020 to February 6, 2021.\n\nResultsThe pooled prevalence of anxiety symptoms in 23 studies comprising a total sample of 85,560 was 20% (95% CI: 15% - 25%, I2 = 99.9%), that of depression symptoms in 23 articles with a total sample comprising of 86,469 individuals was 23% (95% CI: 18% - 28%, I2 = 99.8%), and that of insomnia symptoms in 4 articles with a total sample of 915 were 52% (95% CI: 42-64%, I2 = 88.9%). The overall prevalence of mental illness symptoms in frontline HCWs, general population, and students in Spain are 42%, 19%, and 50%, respectively.\n\nDiscussionThe accumulative evidence from the meta-analysis reveals that adults in Spain suffered higher prevalence rates of mental illness symptoms during the COVID-19 crisis with a significantly higher rate relative to other countries such as China. Our synthesis reveals high heterogeneity, varying prevalence rates and a relative lack of studies in frontline and general HCWs in Spain, calling future research and interventions to pay attention to those gaps to help inform evidence-based mental health policymaking and practice in Spain during the continuing COVID-19 crisis. The high prevalence rates call for preventative and prioritization measures of the mental illness symptoms during the Covid-19 pandemic.", - "rel_num_authors": 10, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.14.439284", + "rel_abs": "Many host pathogen interactions such as human viruses (including non-SARS-coronaviruses) rely on attachment to host cell-surface glycans. There are conflicting reports about whether the Spike protein of SARS-CoV-2 binds to sialic acid commonly found on host cell-surface N-linked glycans. In the absence of a biochemical assay, the ability to analyze the binding of glycans to heavily- modified proteins and resolve this issue is limited. Classical Saturation Transfer Difference (STD) NMR can be confounded by overlapping sugar resonances that compound with known experimental constraints. Here we present universal saturation transfer analysis (uSTA), an NMR method that builds on existing approaches to provide a general and automated workflow for studying protein-ligand interactions. uSTA reveals that B-origin-lineage-SARS-CoV-2 spike trimer binds sialoside sugars in an end on manner and modelling guided by uSTA localises binding to the spike N-terminal domain (NTD). The sialylated-polylactosamine motif is found on tetraantennary human N-linked-glycoproteins in deeper lung and may have played a role in zoonosis. Provocatively, sialic acid binding is abolished by mutations in some subsequent SARS- CoV-2 variants-of-concern. A very high resolution cryo-EM structure confirms the NTD location and end on mode; it rationalises the effect of NTD mutations and the structure-activity relationship of sialic acid analogues. uSTA is demonstrated to be a robust, rapid and quantitative tool for analysis of binding, even in the most demanding systems.\n\nExtended AbstractThe surface proteins found on both pathogens and host cells mediate entry (and exit) and influence disease progression and transmission. Both types can bear host-generated post- translational modifications such as glycosylation that are essential for function but can confound biophysical methods used for dissecting key interactions. Several human viruses (including non- SARS-coronaviruses) attach to host cell-surface N-linked glycans that include forms of sialic acid (sialosides). There remains, however, conflicting evidence as to if or how SARS-associated coronaviruses might use such a mechanism. Here, we demonstrate quantitative extension of saturation transfer protein NMR methods to a complete mathematical model of the magnetization transfer caused by interactions between protein and ligand. The method couples objective resonance-identification via a deconvolution algorithm with Bloch-McConnell analysis to enable a structural, kinetic and thermodynamic analysis of ligand binding beyond previously-perceived limits of exchange rates, concentration or system. Using an automated and openly available workflow this universal saturation transfer analysis (uSTA) can be readily-applied in a range of even heavily-modified systems in a general manner to now obtain quantitative binding interaction parameters (KD, kEx). uSTA proved critical in mapping direct interactions between natural sialoside sugar ligands and relevant virus-surface attachment glycoproteins - SARS-CoV-2-spike and influenza-H1N1-haemagglutinin variants - by quantitating ligand signal in spectral regions otherwise occluded by resonances from mobile protein glycans (that also include sialosides). In B- origin-lineage-SARS-CoV-2 spike trimer end on-binding to sialoside sugars was revealed contrasting with extended surface-binding for heparin sugar ligands; uSTA-derived constraints used in structural modelling suggested sialoside-glycan binding sites in a beta-sheet-rich region of spike N-terminal domain (NTD). Consistent with this, uSTA-glycan binding was minimally- perturbed by antibodies that neutralize the ACE2-binding domain (RBD) but strongly disrupted in spike from the B1.1.7/alpha and B1.351/beta variants-of-concern, which possess hotspot mutations in the NTD. Sialoside binding in B-origin-lineage-NTD was unequivocally pinpointed by cryo-EM to a site that is created from residues that are notably deleted in variants (e.g. H69,V70,Y145 in alpha). An analysis of beneficial genetic variances in cohorts of patients from early 2020 suggests a model in which this site in the NTD of B-origin-lineage-SARS-CoV-2 (but not in alpha/beta-variants) may have exploited a specific sialylated-polylactosamine motif found on tetraantennary human N-linked-glycoproteins in deeper lung. Together these confirm a novel binding mode mediated by the unusual NTD of SARS-CoV-2 and suggest how it may drive virulence and/or zoonosis via modulation of glycan attachment. Since cell-surface glycans are widely relevant to biology and pathology, uSTA can now provide ready, quantitative, widespread analysis of complex, host-derived and post-translationally modified proteins with putative ligands relevant to disease even in previously confounding complex systems.", + "rel_num_authors": 38, "rel_authors": [ { - "author_name": "Richard Z Chen", - "author_inst": "Crescent Valley High School" + "author_name": "Charles J. Buchanan", + "author_inst": "Department of Chemistry, University of Oxford, Oxford, OX1 3TA" }, { - "author_name": "Stephen X. Zhang", - "author_inst": "University of Adelaide" + "author_name": "Ben Gaunt", + "author_inst": "The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK." }, { - "author_name": "Wen Xu", - "author_inst": "University of Nottingham Ningbo China" + "author_name": "Peter J. Harrison", + "author_inst": "Division of Structural Biology, University of Oxford, The Wellcome Centre for Human Genetics, Headington, Oxford, OX3 7BN, UK." }, { - "author_name": "Allen Yin", - "author_inst": "School of Humanities, Southeast University" + "author_name": "Yun Yang", + "author_inst": "University of Oxford" }, { - "author_name": "Rebecca Kechen Dong", - "author_inst": "Business School, University of South Australia," + "author_name": "Jiwei Liu", + "author_inst": "Rosalind Franklin Institute" }, { - "author_name": "Bryan Z Chen", - "author_inst": "Crescent Valley High School" + "author_name": "Aziz Khan", + "author_inst": "Department of Chemistry, University of Oxford, Oxford, OX1 3TA" }, { - "author_name": "Andrew Delios", - "author_inst": "University of Adelaide" + "author_name": "Andrew M. Giltrap", + "author_inst": "The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK." }, { - "author_name": "Roger S McIntyre", - "author_inst": "Department of Psychiatry, University of Toronto" + "author_name": "Audrey Le Bas", + "author_inst": "Division of Structural Biology, University of Oxford, The Wellcome Centre for Human Genetics, Headington, Oxford, OX3 7BN, UK." }, { - "author_name": "Saylor Miller", - "author_inst": "College of Business, Oregon State University" + "author_name": "Philip N. Ward", + "author_inst": "Division of Structural Biology, University of Oxford, The Wellcome Centre for Human Genetics, Headington, Oxford, OX3 7BN, UK." }, { - "author_name": "Xue Wan", - "author_inst": "School of Economics and Management, Tongji University" + "author_name": "Kapil Gupta", + "author_inst": "University of Bristol" + }, + { + "author_name": "Maud Dumoux", + "author_inst": "The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK." + }, + { + "author_name": "Sergio Daga", + "author_inst": "Medical Genetics, University of Siena, Siena, Italy" + }, + { + "author_name": "Nicola Picchiotti", + "author_inst": "Department of Information Engineering and Mathematics, University of Siena, Italy" + }, + { + "author_name": "Margherita Baldassarri", + "author_inst": "Medical Genetics, University of Siena, Siena, Italy" + }, + { + "author_name": "Elisa Benetti", + "author_inst": "Department of Medical Biotechnologies, University of Siena, Siena, Italy" + }, + { + "author_name": "Chiara Fallerini", + "author_inst": "Medical Genetics, University of Siena, Siena, Italy" + }, + { + "author_name": "Francesca Fava", + "author_inst": "Medical Genetics, University of Siena, Siena, Italy" + }, + { + "author_name": "Annarita Giliberti", + "author_inst": "Medical Genetics, University of Siena, Siena, Italy" + }, + { + "author_name": "Panagiotis I. Koukos", + "author_inst": "Bijvoet Centre for Biomolecular Research, Faculty of Science, Utrecht University, Netherlands" + }, + { + "author_name": "Abirami Lakshminarayanan", + "author_inst": "Department of Chemistry, University of Oxford, Oxford, OX1 3TA" + }, + { + "author_name": "Xiaochao Xue", + "author_inst": "Department of Chemistry, University of Oxford, Oxford, OX1 3TA" + }, + { + "author_name": "Georgios Papadakis", + "author_inst": "Department of Chemistry, University of Oxford, Oxford, OX1 3TA" + }, + { + "author_name": "Lachlan P. Deimel", + "author_inst": "Sir William Dunn School of Pathology, South Parks Road, Oxford, UK." + }, + { + "author_name": "Virginia Casablancas-Antras", + "author_inst": "Department of Chemistry, University of Oxford, Oxford, OX1 3TA" + }, + { + "author_name": "Timothy D.W. Claridge", + "author_inst": "Department of Chemistry, University of Oxford, Oxford, OX1 3TA" + }, + { + "author_name": "Alexandre M.J.J. Bonvin", + "author_inst": "Bijvoet Centre for Biomolecular Research, Faculty of Science, Utrecht University, Netherlands" + }, + { + "author_name": "Quentin J. Sattentau", + "author_inst": "Sir William Dunn School of Pathology, South Parks Road, Oxford, UK." + }, + { + "author_name": "Simone Furini", + "author_inst": "Department of Medical Biotechnologies, University of Siena, Siena, Italy" + }, + { + "author_name": "Marco Gori", + "author_inst": "Department of Information Engineering and Mathematics, University of Siena, Italy" + }, + { + "author_name": "Jiangdong Huo", + "author_inst": "The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK." + }, + { + "author_name": "Raymond J. Owens", + "author_inst": "The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK." + }, + { + "author_name": "Christian Schaffitzel", + "author_inst": "University of Bristol" + }, + { + "author_name": "Imre Berger", + "author_inst": "University of Bristol" + }, + { + "author_name": "Alessandra Renieri", + "author_inst": "Medical Genetics, University of Siena, Siena, Italy" + }, + { + "author_name": "- GEN-COVID Multicenter Study", + "author_inst": "-" + }, + { + "author_name": "James H. Naismith", + "author_inst": "The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK." + }, + { + "author_name": "Andrew Baldwin", + "author_inst": "Department of Chemistry, University of Oxford, Oxford, OX1 3TA" + }, + { + "author_name": "Benjamin G. Davis", + "author_inst": "The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK." } ], "version": "1", - "license": "cc_by_nc", - "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "license": "cc_by", + "type": "new results", + "category": "biophysics" }, { "rel_doi": "10.1101/2021.04.13.439641", @@ -793534,29 +792285,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.10.21255240", - "rel_title": "Increased serum thromboxane A2 and prostacyclin but lower complement C3 and C4 levels in COVID-19: associations with chest CT-scan anomalies and lowered peripheral oxygen saturation.", + "rel_doi": "10.1101/2021.04.09.21255200", + "rel_title": "Do post-COVID-19 patients need a second dose of vaccine?", "rel_date": "2021-04-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.10.21255240", - "rel_abs": "BackgroundCOVID-19 patients suffer from hypercoagulation and activated immune-inflammatory pathways. This study was performed to assay serum complement C3 and C4, and thromboxane A2 (TxA2) and prostacyclin (PGI2) in association with chest CT scan anomalies (CCTAs) and peripheral oxygen saturation (SpO2)\n\nMethodsSerum levels of C3, C4, TxA2, and PGI2 were measured by ELISA and albumin, calcium, and magnesium by spectrophotometric method in 60 COVID-19 patients and 30 controls.\n\nResultsC3 and C4 are significantly decreased and TxA2 and PGI2 significantly increased in COVID-19 patients as compared with controls. Neural networks showed that a combination of C3, albumin, and TxA2 yielded a predictive accuracy of 100% in detecting COVID-19 patients. SpO2 was significantly decreased in COVID-19 patients and was inversely associated with TxA2 and PGI2, and positively with C3, C4, albumin, and calcium. CCTAs were accompanied by lower SpO2 and albumin, and increased PGI2 levels. Patients with positive IgG results show significantly higher SpO2, TxA2, PGI2, and C4 levels than IgG negative patients.\n\nConclusionHypoalbuminemia, which is strongly associated with lung lesions and lowered peripheral oxygen saturation, is characterized by increased TxA2, suggesting that interactions between immune-inflammatory pathways and platelet hyperactivity participate in the pathophysiology of COVID-19 and consequently may play a role in enhanced risk of hypercoagulability and venous thromboembolism. These mechanisms are aggravated by lowered calcium and magnesium levels.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.09.21255200", + "rel_abs": "Vaccination forms a key part of public health strategies to control the spread of SARS-CoV-2 globally. In the UK, two vaccines (BNT162b2-mRNA produced by Pfizer, and ChAdOx-1-S produced by Oxford-AstraZeneca) have been licensed to date, and their administration is prioritised according to individual risk. This study forms part of a longitudinal assessment of participants SARS-CoV-2-specific antibody levels before and after vaccination. Our results confirm that there is little quantitative difference in the antibody titres achieved by the two vaccines. Our results also suggest that individuals who have previously been infected with SARS-CoV-2 achieve markedly higher antibody titres than those who are immunologically naive. This finding is useful to inform vaccine prioritisation strategies in the future: individuals with no history of SARS-CoV-2 infection should be prioritised for a second vaccine inoculation.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Hussein K Al-Hakeim", - "author_inst": "University of Kufa" + "author_name": "Jorg Taubel", + "author_inst": "Richmond Pharmacology Ltd" + }, + { + "author_name": "Christopher S Spencer", + "author_inst": "Richmond Research Institute" }, { - "author_name": "Shaymaa Al-Hamami", - "author_inst": "Altoosi University College, Najaf, Iraq" + "author_name": "Anne Freier", + "author_inst": "Richmond Research Institute" }, { - "author_name": "Michael Maes", - "author_inst": "Chulalongkorn University" + "author_name": "Dorothee Camilleri", + "author_inst": "Richmond Pharmacology Ltd" + }, + { + "author_name": "Ibon Garitaonandia", + "author_inst": "Richmond Research Institute" + }, + { + "author_name": "Ulrike Lorch", + "author_inst": "Richmond Pharmacology Ltd" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -795460,65 +794223,57 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.04.08.21255005", - "rel_title": "The emergence of SARS-CoV-2 variant(s) and its impact on the prevalence of COVID-19 cases in Nabatieh region, Lebanon", + "rel_doi": "10.1101/2021.04.08.21255119", + "rel_title": "ddPCR Reveals SARS-CoV-2 Variants in Florida Wastewater", "rel_date": "2021-04-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.08.21255005", - "rel_abs": "BackgroundAn outbreak of an unknown respiratory illness caused by a novel corona-virus, SARS-CoV-2, emerged in the city of Wuhan in Hubei province, China, in December 2019 and was referred to as coronavirus disease-2019 (COVID-19). Soon after, it was declared as a global pandemic by the World Health Organization (WHO) in March 2020. SARS-CoV-2 mainly infects the respiratory tract with different outcomes ranging from asymptomatic infection to severe critical illness leading to death. Different SARS-CoV-2 variants are emerging of which three have raised concerns worldwide due to their high transmissibility among populations.\n\nObjectiveTo study the prevalence of COVID-19 in the region of Nabatieh - South Lebanon during the past year and assess the presence of SARS-CoV-2 variants and their effect on the spread of infection during times of lock-down. Methods: In our study, 37,474 nasopharyngeal swab samples were collected and analyzed for the detection of SARS-CoV-2 virus in suspected patients attending a tertiary health care center in South Lebanon during the period between March 16, 2020 and February 21, 2021.\n\nResultsResults demonstrated a variation in the prevalence rates ranging from less than 1% during full lockdown of the country to 8.4% upon easing lockdown restrictions and reaching 27.5% after the holidays and 2021 New Year celebrations. Interestingly, a new variant(s) appeared starting January 2021 with a significant positive association between the prevalence of positive tests and the percentage of the variant(s).\n\nConclusionOur results indicate that the lockdown implemented by the Lebanese officials presented an effective intervention to contain COVID-19 spread. Our study also showed that lifting lockdown measures during the holidays, which allowed indoor crowded gatherings to occur, caused a surge in COVID-19 cases and rise in the mortality rates nationwide. More importantly, we confirmed the presence of a highly transmissible SARS-CoV-2 variant(s) circulating in the Lebanese community, at least since January 2021 onwards.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.08.21255119", + "rel_abs": "Wastewater was screened for the presence of functionally significant mutations in SARS-CoV-2 associated with emerging variants of concern (VOC) by ddPCR, and results accorded with sequencing of clinical samples from the same region. We propose that PCR-based screening of wastewater can provide a powerful tool for rapid and inexpensive screening of large population segments for VOC-associated mutations and can hone complementary sampling and sequencing of direct (human) test material to track emerging VOC.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Fatima Y Noureddine", - "author_inst": "Sheikh Ragheb Harb University Hospital" - }, - { - "author_name": "Mohamed Chakkour", - "author_inst": "American University of Beirut" - }, - { - "author_name": "Ali El Roz", - "author_inst": "Lebanese University" + "author_name": "Eben Gering", + "author_inst": "Nova Southeastern University" }, { - "author_name": "Jana Reda", - "author_inst": "Sheikh Ragheb Harb University Hospital" + "author_name": "Jacob Colbert", + "author_inst": "Nova Southeastern University" }, { - "author_name": "Reem Al Sahily", - "author_inst": "Sheikh Ragheb Harb University Hospital" + "author_name": "Sarah Schmedes", + "author_inst": "Bureau of Public Health Laboratories, Florida Department of Health" }, { - "author_name": "Ali Assi", - "author_inst": "Sheikh Ragheb Harb University Hospital" + "author_name": "George Duncan", + "author_inst": "Nova Southeastern University" }, { - "author_name": "Mohamed Joma", - "author_inst": "Sheikh Ragheb Harb University Hospital" + "author_name": "Jose Victor Lopez", + "author_inst": "Nova Southeastern University" }, { - "author_name": "Hassan Salami", - "author_inst": "Sheikh Ragheb Harb University Hospital" + "author_name": "Jessy Motes", + "author_inst": "Bureau of Public Health Laboratories, Florida Department of Health" }, { - "author_name": "Sadek J Hashem", - "author_inst": "Sheikh Ragheb Harb University Hospital" + "author_name": "James Weiss", + "author_inst": "Bureau of Public Health Laboratories, Florida Department of Health" }, { - "author_name": "Batoul Harb", - "author_inst": "Sheikh Ragheb Harb University Hospital" + "author_name": "Taj Azarian", + "author_inst": "Bureau of Public Health Laboratories, Florida Department of Health. Burnett School of Biomedical Sciences, University of Central Florida" }, { - "author_name": "Ali Salami", - "author_inst": "Lebanese University" + "author_name": "Omer Tekin", + "author_inst": "Bureau of Public Health Laboratories, Florida Department of Health" }, { - "author_name": "Ghassan Ghssein", - "author_inst": "Lebanese University" + "author_name": "Jason Blanton", + "author_inst": "Bureau of Public Health Laboratories, Florida Department of Health" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -797218,87 +795973,63 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2021.04.10.439288", - "rel_title": "ADAM17 inhibition prevents neutrophilia and lung injury in a mouse model of Covid-19", + "rel_doi": "10.1101/2021.04.10.439279", + "rel_title": "Ultrastructural insight into SARS-CoV-2 attachment, entry and budding in human airway epithelium", "rel_date": "2021-04-11", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.10.439288", - "rel_abs": "Severe coronavirus disease 2019 (Covid-19) is characterized by lung injury, cytokine storm and increased neutrophil-to-lymphocyte ratio (NLR). Current therapies focus on reducing viral replication and inflammatory responses, but no specific treatment exists to prevent the development of severe Covid-19 in infected individuals. Angiotensin-converting enzyme-2 ACE-2) is the receptor for SARS-CoV-2, the virus causing Covid-19, but it is also critical for maintaining the correct functionality of lung epithelium and endothelium. Coronaviruses induce activation of a disintegrin and metalloprotease 17 (ADAM17) and shedding of ACE-2 from the cell surface resulting in exacerbated inflammatory responses. Thus, we hypothesized that ADAM17 inhibition ameliorates Covid-19-related lung inflammation. We employed a pre-clinical mouse model using intra-tracheal instillation of a combination of polyinosinic:polycytidylic acid (poly-I:C) and the receptor-binding domain of the SARS-CoV-2 spike protein (RBD-S) to mimic lung damage associated with Covid-19. Histological analysis of inflamed mice confirmed the expected signs of lung injury including edema, fibrosis, vascular congestion and leukocyte infiltration. Moreover, inflamed mice also showed an increased NLR as observed in critically ill Covid-19 patients. Administration of the ADAM17 inhibitors apratastat and TMI-1 significantly improved lung histology and prevented leukocyte infiltration. Reduced leukocyte recruitment could be explained by reduced production of pro-inflammatory cytokines and lower levels of the endothelial adhesion molecules ICAM-1 and VCAM-1. Additionally, the NLR was significantly reduced by ADAM17 inhibition. Thus, we propose inhibition of ADAM17 as a novel promising treatment strategy in SARS-CoV-2-infected individuals to prevent the progression towards severe Covid-19.", - "rel_num_authors": 17, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.10.439279", + "rel_abs": "Ultrastructural studies of SARS-CoV-2 infected cells are crucial to better understand the mechanisms of viral entry and budding within host cells. Many studies are limited by the lack of access to appropriate cellular models. As the airway epithelium is the primary site of infection it is essential to study SARS-CoV-2 infection of these cells. Here, we examined human airway epithelium, grown as highly differentiated air-liquid interface cultures and infected with three different isolates of SARS-CoV-2 including the B.1.1.7 variant (Variant of Concern 202012/01) by transmission electron microscopy and tomography. For all isolates, the virus infected ciliated but not goblet epithelial cells. Two key SARS-CoV-2 entry molecules, ACE2 and TMPRSS2, were found to be localised to the plasma membrane including microvilli but excluded from cilia. Consistent with these observations, extracellular virions were frequently seen associated with microvilli and the apical plasma membrane but rarely with ciliary membranes. Profiles indicative of viral fusion at the apical plasma membrane demonstrate that the plasma membrane is one site of entry where direct fusion releasing the nucleoprotein-encapsidated genome occurs. Intact intracellular virions were found within ciliated cells in compartments with a single membrane bearing S glycoprotein. Profiles strongly suggesting viral budding from the membrane was observed in these compartments and this may explain how virions gain their S glycoprotein containing envelope.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Nathaniel L. Lartey", - "author_inst": "Cinvestav-IPN, Department of Molecular Biomedicine" - }, - { - "author_name": "Salvador Valle-Reyes", - "author_inst": "Cinvestav-IPN, Department of Molecular Biomedicine" - }, - { - "author_name": "Hilda Vargas-Robles", - "author_inst": "Cinvestav-IPN, Department of Molecular Biomedicine" - }, - { - "author_name": "Karina E. Jim\u00e9nez-Camacho", - "author_inst": "Cinvestav-IPN, Department of Molecular Biomedicine" - }, - { - "author_name": "Idaira M. Guerrero-Fonseca", - "author_inst": "Cinvestav-IPN, Department of Molecular Biomedicine" - }, - { - "author_name": "Ram\u00f3n Castellanos-Mart\u00ednez", - "author_inst": "Cinvestav-IPN, Department of Molecular Biomedicine" - }, - { - "author_name": "Armando Montoya-Garc\u00eda", - "author_inst": "Cinvestav-IPN, Department of Molecular Biomedicine" + "author_name": "Andreia L Pinto", + "author_inst": "Royal Brompton Hospital" }, { - "author_name": "Julio Garc\u00eda-Cordero", - "author_inst": "Cinvestav-IPN, Department of Molecular Biomedicine" + "author_name": "Ranjit K Rai", + "author_inst": "Royal Brompton Hospital" }, { - "author_name": "Leticia Cedillo-Barr\u00f3n", - "author_inst": "Cinvestav-IPN, Department of Molecular Biomedicine" + "author_name": "Jonathan C Brown", + "author_inst": "Imperial College London" }, { - "author_name": "Porfirio Nava", - "author_inst": "Cinvestav-IPN, Department of Physiology, Biophysics and Neurosciences" + "author_name": "Paul Griffin", + "author_inst": "Royal Brompton Hospital" }, { - "author_name": "Jessica G. Filisola-Villase\u0148or", - "author_inst": "Cinvestav-IPN, Department of Biochemistry" + "author_name": "James R Edgar", + "author_inst": "University of Cambridge" }, { - "author_name": "Daniela Roa-Vel\u00e1zquez", - "author_inst": "Cinvestav-IPN, Department of Biochemistry" + "author_name": "Anand Shah", + "author_inst": "Royal Brompton Hospital" }, { - "author_name": "Dan I. Zavala-Vargas", - "author_inst": "Cinvestav-IPN, Department of Biochemistry" + "author_name": "Aran Singanayagam", + "author_inst": "Imperial College London" }, { - "author_name": "Edgar Morales-R\u00edos", - "author_inst": "Cinvestav-IPN, Department of Biochemistry" + "author_name": "Claire Hogg", + "author_inst": "Royal Brompton Hospital" }, { - "author_name": "Citlaltepetl Salinas-Lara", - "author_inst": "Instituto Nacional de Neurolog\u00eda" + "author_name": "Wendy S Barclay", + "author_inst": "Imperial College London" }, { - "author_name": "Eduardo Vadillo", - "author_inst": "Oncology Research Unit, Hospital de Oncolog\u00eda, Centro M\u00e9dico Nacional Siglo XXI" + "author_name": "Clare E Futter", + "author_inst": "University College London" }, { - "author_name": "Michael Schnoor", - "author_inst": "Cinvestav del IPN, Department of Molecular Biomedicine" + "author_name": "Thomas Burgoyne", + "author_inst": "University College London" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "pathology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.04.09.439260", @@ -799048,39 +797779,47 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.04.07.438871", - "rel_title": "Machine Learning Identifies Ponatinib as a Potent Inhibitor of SARS-CoV2-induced Cytokine Storm", + "rel_doi": "10.1101/2021.04.06.21254997", + "rel_title": "Machine Learning based COVID-19 Diagnosis from Blood Tests with Robustness to Domain Shifts", "rel_date": "2021-04-09", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.07.438871", - "rel_abs": "Although 15-20% of COVID-19 patients experience hyper-inflammation induced by massive cytokine production, cellular triggers of this process and strategies to target them remain poorly understood. Here, we show that the N-terminal domain (NTD) of the spike protein from the SARS-CoV-2 and emerging variants B1.1.7 and B.1.351 substantially induces multiple inflammatory molecules in human monocytes and PBMCs. Further, we identified several protein kinases, including JAK1, EPHA7, IRAK1, MAPK12, and MAP3K8, as essential downstream mediators of NTD-induced cytokine release. Additionally, we found that the FDA-approved, multi-kinase inhibitor Ponatinib is a potent inhibitor of the NTD-mediated cytokine storm. Taken together, we propose that agents targeting multiple kinases required for the SARS-CoV-2-mediated cytokine storm, such as Ponatinib, may represent an attractive therapeutic option for treating moderate to severe COVID-19.", - "rel_num_authors": 5, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.06.21254997", + "rel_abs": "We investigate machine learning models that identify COVID-19 positive patients and estimate the mortality risk based on routinely acquired blood tests in a hospital setting. However, during pandemics or new outbreaks, disease and testing characteristics change, thus we face domain shifts. Domain shifts can be caused, e.g., by changes in the disease prevalence (spreading or tested population), by refined RT-PCR testing procedures (taking samples, laboratory), or by virus mutations. Therefore, machine learning models for diagnosing COVID-19 or other diseases may not be reliable and degrade in performance over time. To countermand this effect, we propose methods that first identify domain shifts and then reverse their negative effects on the model performance. Frequent re-training and reassessment, as well as stronger weighting of more recent samples, keeps model performance and credibility at a high level over time. Our diagnosis models are constructed and tested on large-scale data sets, steadily adapt to observed domain shifts, and maintain high ROC AUC values along pandemics.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Marina Chan", - "author_inst": "Fred Hutchinson Cancer Research Institute" + "author_name": "Theresa Roland", + "author_inst": "ELLIS Unit Linz, LIT AI Lab, Institute for Machine Learning, Johannes Kepler University Linz, Austria" }, { - "author_name": "Siddharth Vijay", - "author_inst": "Fred Hutchinson Cancer Research Institute" + "author_name": "Carl Boeck", + "author_inst": "Department of Anesthesiology and Critical Care Medicine, Kepler University Hospital GmbH, Johannes Kepler University Linz, Austria" }, { - "author_name": "M. Juliana McElrath", - "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA" + "author_name": "Thomas Tschoellitsch", + "author_inst": "Department of Anesthesiology and Critical Care Medicine, Kepler University Hospital GmbH, Johannes Kepler University Linz, Austria" }, { - "author_name": "Eric C Holland", - "author_inst": "Fred Hutchinson Cancer Research Center, Seattle, WA, USA" + "author_name": "Alexander Maletzky", + "author_inst": "RISC Software GmbH, Hagenberg i.M., Austria" + }, + { + "author_name": "Sepp Hochreiter", + "author_inst": "ELLIS Unit Linz, LIT AI Lab, Institute for Machine Learning, Johannes Kepler University Linz, Austria" + }, + { + "author_name": "Jens Meier", + "author_inst": "Department of Anesthesiology and Critical Care Medicine, Kepler University Hospital GmbH, Johannes Kepler University Linz, Austria" }, { - "author_name": "Taranjit S Gujral", - "author_inst": "Fred Hutchinson Cancer Research Institute" + "author_name": "Guenter Klambauer", + "author_inst": "ELLIS Unit Linz, LIT AI Lab, Institute for Machine Learning, Johannes Kepler University Linz, Austria" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "systems biology" + "type": "PUBLISHAHEADOFPRINT", + "category": "health informatics" }, { "rel_doi": "10.1101/2021.04.05.21254834", @@ -800690,57 +799429,49 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.04.07.438820", - "rel_title": "Comparable environmental stability and disinfection profiles of the currently circulating SARS-CoV-2 variants of concern B.1.1.7 and B.1.351", + "rel_doi": "10.1101/2021.04.06.438731", + "rel_title": "Functional evaluation of proteolytic activation for the SARS-CoV-2 variant B.1.1.7: role of the P681H mutation", "rel_date": "2021-04-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.07.438820", - "rel_abs": "The emergence of novel SARS-CoV-2 B.1.1.7 and B.1.351 variants of concern with increased transmission dynamics has raised questions regarding stability and disinfection of these viruses. In this study, we analyzed surface stability and disinfection of the currently circulating SARS-CoV-2 variants B.1.1.7 and B.1.351 compared to the wildtype. Treatment with heat, soap and ethanol revealed similar inactivation profiles indicative of a comparable susceptibility towards disinfection. Furthermore, we observed comparable surface stability on steel, silver, copper and face masks. Overall, our data support the application of currently recommended hygiene concepts to minimize the risk of B.1.1.7 and B.1.351 transmission.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.06.438731", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the agent causing the COVID-19 pandemic. SARS-CoV-2 B.1.1.7 (Alpha), a WHO variant of concern (VOC) first identified in the UK in late 2020, contains several mutations including P681H in the spike S1/S2 cleavage site, which is predicted to increase cleavage by furin, potentially impacting the viral cell entry. Here, we studied the role of the P681H mutation in B.1.1.7 cell entry. We performed assays using fluorogenic peptides mimicking the Wuhan-Hu-1 and B.1.1.7 S1/S2 sequence and observed no significant difference in furin cleavage. Functional assays using pseudoparticles harboring SARS-CoV-2 spikes and cell-to-cell fusion assays demonstrated no differences between Wuhan-Hu-1, B.1.1.7 or a P681H point mutant. Likewise, we observed no differences in viral growth between USA-WA1/2020 and a B.1.1.7 isolate in cell culture. Our findings suggest that while the B.1.1.7 P681H mutation may slightly increase S1/S2 cleavage this does not significantly impact viral entry or cell-cell spread.\n\nHighlightsO_LISARS-CoV-2 B.1.1.7 VOC has a P681H mutation in the spike that is predicted to enhance viral infection\nC_LIO_LIP681H does not significantly impact furin cleavage, viral entry or cell-cell spread\nC_LIO_LIOther mutations in the SARS-CoV-2 B.1.1.7 VOC may account for increased infection rates\nC_LI\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC=\"FIGDIR/small/438731v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (33K):\norg.highwire.dtl.DTLVardef@c148d7org.highwire.dtl.DTLVardef@1954eeeorg.highwire.dtl.DTLVardef@171130dorg.highwire.dtl.DTLVardef@99bd45_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Toni Luise Meister", - "author_inst": "Department for Molecular & Medical Virology, Ruhr University Bochum, 44801 Bochum Germany" - }, - { - "author_name": "Jil Fortmann", - "author_inst": "Materials Discovery and Interfaces, Ruhr University Bochum, 44801 Bochum Germany" - }, - { - "author_name": "Daniel Todt", - "author_inst": "Ruhr University Bochum" + "author_name": "Bailey Lubinski", + "author_inst": "Cornell Univ" }, { - "author_name": "Natalie Heinen", - "author_inst": "Department for Molecular & Medical Virology, Ruhr University Bochum, 44801 Bochum Germany" + "author_name": "Maureen HV Fernandes", + "author_inst": "Cornell Univ" }, { - "author_name": "Alfred Ludwig", - "author_inst": "Materials Discovery and Interfaces, Ruhr University Bochum, 44801 Bochum Germany" + "author_name": "Laura Frazier", + "author_inst": "Cornell Univ" }, { - "author_name": "Yannick Brueggemann", - "author_inst": "Department for Molecular & Medical Virology, Ruhr University Bochum, 44801 Bochum Germany" + "author_name": "Tiffany Tang", + "author_inst": "Cornell Univ" }, { - "author_name": "Carina Elsner", - "author_inst": "Institute for Virology, University Hospital of Essen, University of Duisburg-Essen, 45147 Essen, Germany." + "author_name": "Susan Daniel", + "author_inst": "Cornell University" }, { - "author_name": "Ulf Dittmer", - "author_inst": "Institute for Virology, University Hospital of Essen, University of Duisburg-Essen, 45147 Essen, Germany." + "author_name": "Diego Diel", + "author_inst": "Cornell University College of Veterinary Medicine" }, { - "author_name": "Stephanie Pfaender", - "author_inst": "Department for Molecular & Medical Virology, Ruhr University Bochum, 44801 Bochum Germany" + "author_name": "Javier A. Jaimes", + "author_inst": "Cornell University" }, { - "author_name": "Eike Steinmann", - "author_inst": "Department for Molecular & Medical Virology, Ruhr University Bochum, 44801 Bochum Germany" + "author_name": "Gary Whittaker", + "author_inst": "Cornell Univ" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "new results", "category": "microbiology" }, @@ -803272,21 +802003,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.04.02.21254821", - "rel_title": "Modelling, Simulations and Analysis ofthe First and Second COVID-19 Epidemics in Beijing", + "rel_doi": "10.1101/2021.04.01.21254802", + "rel_title": "Mean time to infection by small diffusing droplets containing SARS-CoV-2 during close social contacts", "rel_date": "2021-04-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.02.21254821", - "rel_abs": "To date, over 130 million people on infected with COVID-19. It causes more 2.8 millions deaths. This paper introduces a symptomatic-asymptomatic-recoverer-dead differential equation model (SARDDE). It gives the conditions of the asymptotical stability on the disease-free equilibrium of SARDDE. It proposes the necessary conditions of disease spreading for the SARDDE. Based on the reported data of the first and the second COVID-19 epidemics in Beijing and simulations, it determines the parameters of SARDDE, respectively. Numerical simulations of SARDDE describe well the outcomes of current symptomatic and asymptomatic individuals, recovered symptomatic and asymptomatic individuals, and died individuals, respectively. The numerical simulations suggest that both symptomatic and asymptomatic individuals cause lesser asymptomatic spread than symptomatic spread; blocking rate of about 90% cannot prevent the spread of the COVID19 epidemic in Beijing; the strict prevention and control strategies implemented by Beijing government is not only very effective but also completely necessary. The numerical simulations suggest also that using the data from the beginning to the day after about two weeks at the turning point can estimate well or approximately the following outcomes of the two COVID-19 academics, respectively. It is expected that the research can provide better understanding, explaining, and dominating for epidemic spreads, prevention and control measures.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.01.21254802", + "rel_abs": "Airborne viruses such as SARS-CoV-2 are partly spreading through aerosols containing viral particles. Inhalation of infectious airborne particles can lead to infection, a route that can even be more predominant compared with droplet or contact transmission. To study the transmission between a susceptible and an infected person, we estimate the distribution of arrival times of small diffusing aerosol particles to the inhaled region located below the nose until the number of particles reaches a critical threshold. Our results suggest that although contamination by continuous respiration can take around 90 minutes at a distance of one meter, it is reduced to a few minutes when coughing or sneezing. Interestingly, there is not much differences between outdoors and indoors when the air is still. When a window is open inside an office, the infection time is reduced. Finally, wearing a mask leads to a delay in the time to infection. To conclude, diffusion analysis provides several key time scale of viral airborne transmission.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Lequan Min", - "author_inst": "University of Science and Technology Beijing" + "author_name": "Ulrich Dobramysl", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Christian Sieben", + "author_inst": "EPFL" + }, + { + "author_name": "David holcman", + "author_inst": "ENS" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -804994,61 +803733,93 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.01.21254813", - "rel_title": "Prospective analytical performance evaluation of the QuickNavi\u2122-COVID19 Ag for asymptomatic individuals", + "rel_doi": "10.1101/2021.04.01.21254767", + "rel_title": "Neutrophil-mediated Oxidative Stress and Albumin Structural Damage Predict COVID-19-associated Mortality", "rel_date": "2021-04-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.01.21254813", - "rel_abs": "IntroductionAntigen testing may help screen for and detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in asymptomatic individuals. However, limited data regarding the diagnostic performance of antigen tests for this group are available.\n\nMethodsWe used clinical samples to prospectively evaluate the analytical and clinical performance of the antigen test QuickNavi-COVID19 Ag. This study was conducted at a PCR center between October 7, 2020 and January 9, 2021. Two nasopharyngeal samples per patient were obtained with flocked swabs; one was used for the antigen test, and the other for real-time reverse transcription PCR (RT-PCR). The diagnostic performance of the antigen test was compared between asymptomatic and symptomatic patients, and the RT-PCR results were used as a reference.\n\nResultsAmong the 1,934 collected samples, SARS-CoV-2 was detected by real-time RT-PCR in 188 (9.7%); 76 (40.4%) of these samples were from asymptomatic individuals. Over half of the total samples (1,073; 55.5%) were obtained from asymptomatic volunteers. The sensitivity of the antigen test was significantly lower for asymptomatic group than for symptomatic patients (67.1% vs 89.3%, p < 0.001). The specificity was 100% for both groups, and no false positives were observed among all 1,934 samples. The median Ct value for the asymptomatic group was significantly higher than that of the symptomatic group (24 vs 20, p < 0.001).\n\nConclusionsThe QuickNavi-COVID19 Ag showed a lower sensitivity for asymptomatic group than for symptomatic patients. However, its specificity was consistently high, and no false positives were found in this study.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.01.21254767", + "rel_abs": "Human serum albumin (HSA) is the frontline antioxidant protein in blood with established anti-inflammatory and anticoagulation functions. Here we report that COVID-19-induced oxidative stress inflicts structural damages to HSA and is linked with mortality outcome in critically ill patients. We recruited 25 patients who were followed up for a median of 12.5 days (1-35 days), among them 14 had died. Analyzing blood samples from patients and healthy individuals (n=10), we provide evidence that neutrophils are major sources of oxidative stress in blood and that hydrogen peroxide is highly accumulated in plasmas of non-survivors. We then analyzed electron paramagnetic resonance (EPR) spectra of spin labelled fatty acids (SLFA) bound with HSA in whole blood of control, survivor, and non-survivor subjects (n=10-11). Non-survivors HSA showed dramatically reduced protein packing order parameter, faster SLFA correlational rotational time, and greater S/W ratio (strong-binding/weak-binding sites within HSA), all reflecting remarkably fluid protein microenvironments. Stratified at the means, Kaplan-Meier survival analysis indicated that lower values of S/W ratio and accumulated H2O2 in plasma significantly predicted in-hospital mortality (S/W<0.16, 80% (9/12) vs. S/W>0.16, 20% (2/10), p=0.008; plasma [H2O2]>7.1 M, 83.3% (5/6) vs. 16.7% (1/6), p=0.049). When we combined these two parameters as the ratio ((S/W)/[H2O2]) to derive a risk score, the resultant risk score lower than the mean (< 0.0253) predicted mortality with 100% accuracy (100% (6/6) vs. 0% (0/6), logrank{chi} 2 = 12.01, p = 5x10-4). The derived parameters may provide a surrogate marker to assess new candidates for COVID-19 treatments targeting HSA replacements.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Yoshihiko Kiyasu", - "author_inst": "University of Tsukuba Hospital" + "author_name": "Mohamed A Badawy", + "author_inst": "Research Department, Children Cancer Hospital Egypt 57357, Cairo, Egypt" }, { - "author_name": "Yuto Takeuchi", - "author_inst": "University of Tsukuba Hospital" + "author_name": "Basma A Yasseen", + "author_inst": "Research Department, Children Cancer Hospital Egypt 57357, Cairo, Egypt" }, { - "author_name": "Yusaku Akashi", - "author_inst": "Tsukuba Medical Center Hospital" + "author_name": "Riem M El-Messiery", + "author_inst": "Infectious Disease Unit, Internal Medicine Department, Faculty of Medicine, Cairo University, Cairo, Egypt" }, { - "author_name": "Daisuke Kato", - "author_inst": "Denka Co., Ltd" + "author_name": "Engy A Abdel-Rahman", + "author_inst": "Research Department, Children Cancer Hospital Egypt 57357, Cairo, Egypt" }, { - "author_name": "Miwa Kuwahara", - "author_inst": "Denka Co., Ltd" + "author_name": "Aya A Elkhodiry", + "author_inst": "Research Department, Children Cancer Hospital Egypt 57357, Cairo, Egypt" }, { - "author_name": "Shino Muramatsu", - "author_inst": "Denka Co., Ltd." + "author_name": "Azza G Kamel", + "author_inst": "Research Department, Children Cancer Hospital Egypt 57357, Cairo, Egypt" }, { - "author_name": "Shigeyuki Notake", - "author_inst": "Tsukuba Medical Center Hospital" + "author_name": "Asmaa M. Shedra", + "author_inst": "Research Department, Children Cancer Hospital Egypt 57357, Cairo, Egypt" }, { - "author_name": "Atsuo Ueda", - "author_inst": "Tsukuba Medical Center Hospital" + "author_name": "Rehab Hamdy", + "author_inst": "Research Department, Children Cancer Hospital Egypt 57357, Cairo, Egypt" }, { - "author_name": "Koji Nakamura", - "author_inst": "Tsukuba Medical Center Hospital" + "author_name": "Mona Zidan", + "author_inst": "Research Department, Children Cancer Hospital Egypt 57357, Cairo, Egypt" }, { - "author_name": "Hiroichi Ishikawa", - "author_inst": "Tsukuba Medical Center Hospital" + "author_name": "Diaa Al-Raawi", + "author_inst": "Research Department, Children Cancer Hospital Egypt 57357, Cairo, Egypt" }, { - "author_name": "Hiromichi Suzuki", - "author_inst": "University of Tsukuba Hospital" + "author_name": "Mahmoud Hammad", + "author_inst": "Pediatric Oncology Department, National Cancer Institute, Cairo University and Children Cancer Hospital 57357, Cairo, Egypt" + }, + { + "author_name": "Nahla Elsharkawy", + "author_inst": "Clinical pathology department, National Cancer Institute, Cairo University and Children Cancer Hospital 57357, Cairo, Egypt" + }, + { + "author_name": "Mohamed El Ansary", + "author_inst": "Department of Intensive Care, Faculty of Medicine, Cairo University, Cairo, Egypt" + }, + { + "author_name": "Ahmed Al-Halfawy", + "author_inst": "Department of Pulmonary Medicine, Faculty of Medicine, Cairo University, Cairo, Egypt" + }, + { + "author_name": "Alaa Elhadad", + "author_inst": "Pediatric Oncology Department, National Cancer Institute, Cairo University and Children Cancer Hospital 57357, Cairo, Egypt" + }, + { + "author_name": "Ashraf Hatem", + "author_inst": "Department of Chest Diseases, Faculty of Medicine, Cairo University, Cairo, Egypt" + }, + { + "author_name": "Sherif Abouelnaga", + "author_inst": "Pediatric Oncology Department, National Cancer Institute, Cairo University and Children Cancer Hospital 57357, Cairo, Egypt" + }, + { + "author_name": "Laura L. Dugan", + "author_inst": "Division of Geriatric Medicine, Department of Medicine, Vanderbilt University Medical Center; and VA Tennessee Valley Geriatric Research, Education and Clinical" + }, + { + "author_name": "Sameh S Ali", + "author_inst": "Research Department, Children Cancer Hospital Egypt 57357, Cairo, Egypt" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -806664,107 +805435,115 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.04.05.438352", - "rel_title": "A new SARS-CoV-2 lineage that shares mutations with known Variants of Concern is rejected by automated sequence repository quality control", + "rel_doi": "10.1101/2021.04.05.438479", + "rel_title": "SARS-CoV-2 Vaccines Elicit Durable Immune Responses in Infant Rhesus Macaques", "rel_date": "2021-04-06", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.05.438352", - "rel_abs": "We report a SARS-CoV-2 lineage that shares N501Y, P681H, and other mutations with known variants of concern, such as B.1.1.7. This lineage, which we refer to as B.1.x (COG-UK sometimes references similar samples as B.1.324.1), is present in at least 20 states across the USA and in at least six countries. However, a large deletion causes the sequence to be automatically rejected from repositories, suggesting that the frequency of this new lineage is underestimated using public data. Recent dynamics based on 339 samples obtained in Santa Cruz County, CA, USA suggest that B.1.x may be increasing in frequency at a rate similar to that of B.1.1.7 in Southern California. At present the functional differences between this variant B.1.x and other circulating SARS-CoV-2 variants are unknown, and further studies on secondary attack rates, viral loads, immune evasion and/or disease severity are needed to determine if it poses a public health concern. Nonetheless, given what is known from well-studied circulating variants of concern, it seems unlikely that the lineage could pose larger concerns for human health than many already globally distributed lineages. Our work highlights a need for rapid turnaround time from sequence generation to submission and improved sequence quality control that removes submission bias. We identify promising paths toward this goal.", - "rel_num_authors": 22, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.05.438479", + "rel_abs": "Early life SARS-CoV-2 vaccination has the potential to provide lifelong protection and achieve herd immunity. To evaluate SARS-CoV-2 infant vaccination, we immunized two groups of 8 infant rhesus macaques (RMs) at weeks 0 and 4 with stabilized prefusion SARS-CoV-2 S-2P spike (S) protein, either encoded by mRNA encapsulated in lipid nanoparticles (mRNA-LNP) or mixed with 3M-052-SE, a TLR7/8 agonist in a squalene emulsion (Protein+3M-052-SE). Neither vaccine induced adverse effects. High magnitude S-binding IgG and neutralizing infectious dose 50 (ID50) >103 were elicited by both vaccines. S-specific T cell responses were dominated by IL-17, IFN-{gamma}, or TNF-. Antibody and cellular responses were stable through week 22. The S-2P mRNA-LNP and Protein-3M-052-SE vaccines are promising pediatric SARS-CoV-2 vaccine candidates to achieve durable protective immunity.\n\nOne-Sentence SummarySARS-CoV-2 vaccines are well-tolerated and highly immunogenic in infant rhesus macaques", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Bryan Thornlow", - "author_inst": "University of California, Santa Cruz" + "author_name": "Carolina Garrido Garrado", + "author_inst": "Duke University" }, { - "author_name": "Angie S Hinrichs", - "author_inst": "University of California, Santa Cruz" + "author_name": "Alan D Curtis", + "author_inst": "University of North Carolina" }, { - "author_name": "Miten Jain", - "author_inst": "University of California, Santa Cruz" + "author_name": "Maria Dennis", + "author_inst": "Duke University" }, { - "author_name": "Namrita Dhillon", - "author_inst": "University of California, Santa Cruz" + "author_name": "Sachi H Pathak", + "author_inst": "University of North Carolina" }, { - "author_name": "Scott La", - "author_inst": "University of California, Santa Cruz" + "author_name": "Hongmei Gao", + "author_inst": "Duke University" }, { - "author_name": "Joshua D Kapp", - "author_inst": "University of California, Santa Cruz" + "author_name": "David Montefiori", + "author_inst": "Duke University" }, { - "author_name": "Ikenna Anigbogu", - "author_inst": "University of California, Santa Cruz" + "author_name": "Mark Tomai", + "author_inst": "3M Corporate Research Materials Laboratory" }, { - "author_name": "Molly Cassatt-Johnstone", - "author_inst": "University of California, Santa Cruz" + "author_name": "Christopher B Fox", + "author_inst": "Infectious Disease Research Institute" }, { - "author_name": "Jakob Mcbroome", - "author_inst": "University of California, Santa Cruz" + "author_name": "Pamela A Kozlowski", + "author_inst": "Louisiana State University Health Sciences Center" }, { - "author_name": "Maximilian Haeussler", - "author_inst": "University of California, Santa Cruz" + "author_name": "Trevor Scobey", + "author_inst": "University of North Carolina" }, { - "author_name": "Yatish Turakhia", - "author_inst": "University of California, Santa Cruz" + "author_name": "Jennifer E Munt", + "author_inst": "University of North Carolina" }, { - "author_name": "Terren Chang", - "author_inst": "University of California, Santa Cruz" + "author_name": "Michael L Mallory", + "author_inst": "University of North Carolina" }, { - "author_name": "Hugh E Olsen", - "author_inst": "University of California, Santa Cruz" + "author_name": "Pooja T Saha", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Jeremy Sanford", - "author_inst": "University of California, Santa Cruz" + "author_name": "Michael G Hudgens", + "author_inst": "UNC Chapel Hill" }, { - "author_name": "Michael Stone", - "author_inst": "University of California, Santa Cruz" + "author_name": "Lisa C Lindesmith", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Olena Vaske", - "author_inst": "University of California, Santa Cruz" + "author_name": "Ralph S. Baric", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Isabel Bjork", - "author_inst": "University of California, Santa Cruz" + "author_name": "Olubukola M Abiona", + "author_inst": "NIH, Vaccine Research Institute" }, { - "author_name": "Mark Akeson", - "author_inst": "University of California, Santa Cruz" + "author_name": "Kizzmekia S Corbett", + "author_inst": "NIH, Vaccine Research Institute" }, { - "author_name": "Beth Shapiro", - "author_inst": "University of California, Santa Cruz" + "author_name": "Darin Edwards", + "author_inst": "Moderna, Inc." }, { - "author_name": "David Haussler", - "author_inst": "University of California, Santa Cruz" + "author_name": "Andrea Carfi", + "author_inst": "Moderna, Inc" }, { - "author_name": "A. Marm Kilpatrick", - "author_inst": "University of California, Santa Cruz" + "author_name": "Genevieve Fouda", + "author_inst": "Duke University" }, { - "author_name": "Russ Corbett-Detig", - "author_inst": "University of California, Santa Cruz" + "author_name": "Koen K. A. Van Rompay", + "author_inst": "University of California, Davis" + }, + { + "author_name": "Kristina De Paris", + "author_inst": "UNC Chapel Hill" + }, + { + "author_name": "Sallie R Permar", + "author_inst": "Cornell Weill Medical College" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "new results", - "category": "genomics" + "category": "immunology" }, { "rel_doi": "10.1101/2021.04.05.438465", @@ -808602,31 +807381,47 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.04.06.438675", - "rel_title": "Unique protein features of SARS-CoV-2 relative to other Sarbecoviruses", + "rel_doi": "10.1101/2021.04.05.438547", + "rel_title": "Murine monoclonal antibodies against RBD of SARS-CoV-2 neutralize authentic wild type SARS-CoV-2 as well as B.1.1.7 and B.1.351 viruses and protect in vivo in a mouse model in a neutralization dependent manner", "rel_date": "2021-04-06", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.06.438675", - "rel_abs": "Defining the unique properties of SARS-CoV-2 protein sequences, has potential to explain the range of Coronavirus Disease 2019 (COVID-19) severity. To achieve this we compared proteins encoded by all Sarbecoviruses using profile Hidden Markov Model similarities to identify protein features unique to SARS-CoV-2. Consistent with previous reports, a small set of bat and pangolin-derived Sarbecoviruses show the greatest similarity to SARS-CoV-2 but unlikely to be the direct source of SARS-CoV-2. Three proteins (nsp3, spike and orf9) showed differing regions between the bat Sarbecoviruses and SARS-CoV-2 and indicate virus protein features that might have evolved to support human infection and/or transmission. Spike analysis identified all regions of the protein that have tolerated change and revealed that the current SARS-CoV-2 variants of concern (VOCs) have sampled only a fraction (~31%) of the possible spike domain changes which have occurred historically in Sarbecovirus evolution. This result emphasises the evolvability of these coronaviruses and potential for further change in virus replication and transmission properties over the coming years.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.05.438547", + "rel_abs": "After first emerging in December 2019 in China, severe acute respiratory syndrome 2 (SARS-CoV-2) has since caused a pandemic leading to millions of infections and deaths worldwide. Vaccines have been developed and authorized but supply of these vaccines is currently limited. With new variants of the virus now emerging and spreading globally, it is essential to develop therapeutics that are broadly protective and bind conserved epitopes in the receptor binding domain (RBD) or the whole spike of SARS-CoV-2. In this study, we have generated mouse monoclonal antibodies (mAbs) against different epitopes on the RBD and assessed binding and neutralization against authentic SARS-CoV-2. We have demonstrated that antibodies with neutralizing activity, but not non-neutralizing antibodies, lower viral titers in the lungs when administered in a prophylactic setting in vivo in a mouse challenge model. In addition, most of the mAbs cross-neutralize the B.1.351 as well as the B.1.1.7 variants in vitro.\n\nImportanceCrossneutralization of SARS-CoV-2 variants by RBD-targeting antibodies is still not well understood and very little is known about the potential protective effect of non-neutralizing antibodies in vivo. Using a panel of mouse monoclonal antibodies, we investigate both of these aspects.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Matthew Cotten", - "author_inst": "MRC/UVRI & LSHTM Uganda Research Unit, Entebbe, Uganda" + "author_name": "Fatima Amanat", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "David L. Robertson", - "author_inst": "MRC-University of Glasgow Centre for Virus Research, Glasgow, UK" + "author_name": "Shirin Strohmeier", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "My V.T. Phan", - "author_inst": "MRC/UVRI & LSHTM Uganda Research Unit, Entebbe, Uganda" + "author_name": "Wen-Hsin Lee", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Sandhya Bangaru", + "author_inst": "Scripps" + }, + { + "author_name": "Andrew B Ward", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Lynda Coughlan", + "author_inst": "University of Maryland" + }, + { + "author_name": "Florian Krammer", + "author_inst": "Icahn School of Medicine at Mount Sinai" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "evolutionary biology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.04.06.438634", @@ -810544,69 +809339,69 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.04.03.438330", - "rel_title": "Driving potent neutralization of a SARS-CoV-2 Variant of Concern with a heterotypic boost", + "rel_doi": "10.1101/2021.04.02.437747", + "rel_title": "XAV-19, a novel swine glyco-humanized polyclonal antibody against SARS-CoV-2 spike, efficiently neutralizes B.1.1.7 British and B.1.351 South-African variants.", "rel_date": "2021-04-05", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.03.438330", - "rel_abs": "The emergence of SARS-CoV-2 Variants of Concern (VOCs) with mutations in key neutralizing antibody epitopes threatens to undermine vaccines developed against the pandemic founder variant (Wu-Hu-1). Widespread vaccine rollout and continued transmission are creating a population that has antibody responses of varying potency to Wu-Hu-1. Against this background, it is critical to assess the outcomes of subsequent immunization with variant antigens. It is not yet known whether heterotypic vaccine boosts would be compromised by original antigenic sin, where pre-existing responses to a prior variant dampen responses to a new one, or whether the primed memory B cell repertoire would bridge the gap between Wu-Hu-1 and VOCs. Here, we show that a single adjuvanted dose of receptor binding domain (RBD) protein from VOC 501Y.V2 (B.1.351) drives an extremely potent neutralizing antibody response capable of cross-neutralizing both Wu-Hu-1 and 501Y.V2 in rhesus macaques previously immunized with Wu-Hu-1 spike protein. Passive immunization with plasma sampled following this boost protected K18-hACE2 mice from lethal challenge with a 501Y.V2 clinical isolate, whereas only partial protection was afforded by plasma sampled after two Wu-Hu-1 spike immunizations.", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.02.437747", + "rel_abs": "Amino acid substitutions and deletions in Spike protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants can reduce the effectiveness of monoclonal antibodies (mAbs). In contrast, heterologous polyclonal antibodies raised against S protein, through the recognition of multiple target epitopes, have the potential to maintain neutralization capacities. XAV-19 is a swine glyco-humanized polyclonal neutralizing antibody raised against the receptor binding domain (RBD) of the Wuhan-Hu-1 Spike protein of SARS-CoV-2. XAV-19 target epitopes were found distributed all over the RBD and particularly cover the receptor binding motives (RBM), in direct contact sites with the Angiotensin Converting Enzyme-2 (ACE-2). Therefore, in Spike/ACE2 interaction assays, XAV-19 showed potent neutralization capacities of the original Wuhan Spike and of the United Kingdom (Alpha/B.1.1.7) and South African (Beta/B.1.351) variants. These results were confirmed by cytopathogenic assays using Vero E6 and live virus variants including the Brazil (Gamma/P.1) and the Indian (Delta/B.1.617.2) variants. In a selective pressure study with the Beta strain on Vero E6 cells conducted over 1 month, no mutation was associated with addition of increasing doses XAV-19. The potential to reduce viral load in lungs was confirmed in a human ACE2 transduced mouse model. XAV-19 is currently evaluated in patients hospitalized for COVID-19-induced moderate pneumonia in a phase 2a-2b (NCT04453384) where safety was already demonstrated and in an ongoing 2/3 trial (NCT04928430) to evaluate the efficacy and safety of XAV-19 in patients with moderate-to-severe COVID-19. Owing to its polyclonal nature and its glyco-humanization, XAV-19 may provide a novel safe and effective therapeutic tool to mitigate the severity of coronavirus disease 2019 (Covid-19) including the different variants of concern identified so far.", "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Daniel J Sheward", - "author_inst": "Karolinska Institutet" + "author_name": "Bernard Vanhove", + "author_inst": "Xenothera" }, { - "author_name": "Marco Mandolesi", - "author_inst": "Karolinska Institutet" + "author_name": "Ray So", + "author_inst": "HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, P.R. China" }, { - "author_name": "Egon Urgard", - "author_inst": "Karolinska Institutet" + "author_name": "Benjamin Gaborit", + "author_inst": "CHU Nantes, Department of Infectious Disease, Clinical Investigation, Nantes, France" }, { - "author_name": "Changil Kim", - "author_inst": "Karolinska Institutet" + "author_name": "Gwenaelle Evanno", + "author_inst": "Xenothera" }, { - "author_name": "Leo Hanke", - "author_inst": "Karolinska Institutet" + "author_name": "Guillaume Lafrogne", + "author_inst": "Xenothera" }, { - "author_name": "Laura Perez Vidakovics", - "author_inst": "Karolinska Institutet" + "author_name": "Edwige Mevel", + "author_inst": "Xenothera" }, { - "author_name": "Alec Pankow", - "author_inst": "Karolinska Institutet" + "author_name": "Carine Ciron", + "author_inst": "Xenothera" }, { - "author_name": "Natalie L Smith", - "author_inst": "Karolinska Institutet" + "author_name": "Pierre-Joseph Royer", + "author_inst": "Xenothera" }, { - "author_name": "Xaquin Castro Dopico", - "author_inst": "Karolinska Institutet" + "author_name": "Elsa Lheriteau", + "author_inst": "Xenothera" }, { - "author_name": "Gerald M McInerney", - "author_inst": "Karolinska Institutet" + "author_name": "Francois Raffi", + "author_inst": "CHU Nantes, Department of Infectious Disease, Clinical Investigation, Nantes, France" }, { - "author_name": "Jonathan M Coquet", - "author_inst": "Karolinska Institutet" + "author_name": "Roberto Bruzzone", + "author_inst": "HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, P.R. China" }, { - "author_name": "Gunilla Karlsson Hedestam", - "author_inst": "Karolinska Institutet" + "author_name": "Chris Ka Pun Mok", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Ben Murrell", - "author_inst": "Karolinska Institutet" + "author_name": "Odile Duvaux", + "author_inst": "Xenothera" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "new results", "category": "immunology" }, @@ -812474,59 +811269,47 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.04.02.437736", - "rel_title": "A high-throughput fluorescence polarization assay to discover inhibitors of arenavirus and coronavirus exoribonucleases", + "rel_doi": "10.1101/2021.04.02.438186", + "rel_title": "SARS-CoV-2 B.1.1.7 infection of Syrian hamster does not cause more severe disease and is protected by naturally acquired immunity", "rel_date": "2021-04-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.02.437736", - "rel_abs": "Viral exoribonucleases are uncommon in the world of RNA viruses. To date, this activity has been identified only in the Arenaviridae and the Coronaviridae families. These exoribonucleases play important but different roles in both families: for mammarenaviruses the exoribonuclease is involved in the suppression of the host immune response whereas for coronaviruses, exoribonuclease is both involved in a proofreading mechanism ensuring the genetic stability of viral genomes and participating to evasion of the host innate immunity. Because of their key roles, they constitute attractive targets for drug development. Here we present a high-throughput assay using fluorescence polarization to assess the viral exoribonuclease activity and its inhibition. We validate the assay using three different viral enzymes from SARS-CoV-2, lymphocytic choriomeningitis and Machupo viruses. The method is sensitive, robust, amenable to miniaturization (384 well plates) and allowed us to validate the proof-of-concept of the assay by screening a small focused compounds library (23 metal chelators). We also determined the IC50 of one inhibitor common to the three viruses.\n\nHighlightsO_LIArenaviridae and Coronaviridae viral families share an exoribonuclease activity of common evolutionary origin\nC_LIO_LIArenaviridae and Coronaviridae exoribonuclease is an attractive target for drug development\nC_LIO_LIWe present a high-throughput assay in 384 well-plates for the screening of inhibitors using fluorescence polarization\nC_LIO_LIWe validated the assay by screening of a focused library of 23 metal chelators against SARS-CoV-2, Lymphocytic Choriomeningitis virus and Machupo virus exoribonucleases\nC_LIO_LIWe determined the IC50 by fluorescence polarization of one inhibitor common to the three viruses.\nC_LI", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.02.438186", + "rel_abs": "Epidemiological studies have revealed the emergence of multiple SARS-CoV-2 variants of concern (VOC), including the lineage B.1.1.7 that is rapidly replacing old variants. The B.1.1.7 variant has been linked to increased morbidity rates, transmissibility, and potentially mortality (1). To assess viral fitness in vivo and to address whether the B.1.1.7 variant is capable of immune escape, we conducted infection and re-infection studies in naive and convalescent Syrian hamsters (>10 months old). Hamsters infected by either a B.1.1.7 variant or a B.1 (G614) variant exhibited comparable viral loads and pathology. Convalescent hamsters that were previously infected by the original D614 variant were protected from disease following B.1.1.7 challenge with no observable clinical signs or lung pathology. Altogether, our study did not find that the B.1.1.7 variant significantly differs from the B.1 variant in pathogenicity in hamsters and that natural infection-induced immunity confers protection against a secondary challenge by the B1.1.7 variant.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Sergio Guillermo Hernandez Tapia", - "author_inst": "AMU" - }, - { - "author_name": "Mikael Feracci", - "author_inst": "AMU" - }, - { - "author_name": "Carolina Trajano De Jesus", - "author_inst": "AMU" - }, - { - "author_name": "Priscilla El-Kazzi", - "author_inst": "AMU" + "author_name": "Ivette A Nunez", + "author_inst": "US FDA" }, { - "author_name": "Rafik Kaci", - "author_inst": "AMU" + "author_name": "Christopher Z Lien", + "author_inst": "US FDA" }, { - "author_name": "Laura Garlatti", - "author_inst": "AMU" + "author_name": "Prabhuanand Selvaraj", + "author_inst": "US FDA" }, { - "author_name": "Etienne Decroly", - "author_inst": "CNRS" + "author_name": "Charles B Stauft", + "author_inst": "US FDA" }, { - "author_name": "Bruno Canard", - "author_inst": "CNRS" + "author_name": "Shufeng Liu", + "author_inst": "US FDA" }, { - "author_name": "Francois Ferron", - "author_inst": "CNRS" + "author_name": "Matthew Starost", + "author_inst": "NIH" }, { - "author_name": "Karine Alvarez", - "author_inst": "CNRS" + "author_name": "Tony Wang", + "author_inst": "U.S. Food and Drug Administration" } ], "version": "1", - "license": "cc_no", + "license": "cc0", "type": "new results", - "category": "biochemistry" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.04.02.438155", @@ -814564,43 +813347,107 @@ "category": "gastroenterology" }, { - "rel_doi": "10.1101/2021.03.30.21254661", - "rel_title": "Why did the children stop coming? Reasons for paediatric emergency department attendance decrease during the first wave of the COVID-19 pandemic in the United Kingdom: A qualitative study", + "rel_doi": "10.1101/2021.03.30.21254632", + "rel_title": "Coping with COVID-19 Pandemic: A Population-Based Study in Bangladesh", "rel_date": "2021-03-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.30.21254661", - "rel_abs": "UK Lockdown measures introduced in March 2020 aimed to mitigate the spread of Covid-19. Although seeking healthcare was still permitted within restrictions, paediatric emergency department attendances reduced dramatically and led to concern over risks caused by delayed presentation. Our aim was to gain insight into healthcare decisions faced by parents during the first wave of the Covid-19 pandemic and to understand if use of urgent healthcare, self-care, and information needs differed during lockdown as well as how parents perceived risks of Covid-19.\n\nWe undertook qualitative telephone interviews with a purposive sample of parents living in the North East of England recruited through online advertising. We used a semi-structured topic guide to explore past and current healthcare use, perceptions of risk and the impact of the pandemic on healthcare decisions. Interviews were transcribed and analysed using Thematic Analysis.\n\nThree major themes were identified which concerned (i) how parents made sense of risks posed to, and by their children, (ii) understanding information regarding health services and (iii) attempting to make the right decision. These themes contribute to the understanding of the initial impact of Covid-19 and associated restrictions on parental decisions about urgent healthcare for children. These findings are important to consider when planning for potential future public health emergencies but also in the wider context of encouraging appropriate use of urgent healthcare.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.30.21254632", + "rel_abs": "This study aims to investigate coping strategies used by Bangladeshi citizens during the COVID-19 pandemic.\n\nDesignProspective, cross-sectional survey of adults (N=2001) living in Bangladesh.\n\nMethodsParticipants were interviewed for socio-demographic data and completed the Bengali translated Brief-COPE Inventory. Statistical data analysis was conducted using SPSS (Version 20).\n\nResultsParticipants (N=2001), aged 18 to 86 years, were recruited from eight administrative divisions within Bangladesh (mean age 31.85{+/-}14.2 years). Male to female participant ratio was 53.4% (n=1074) to 46.6% (n=927). Higher scores were reported for approach coping styles (29.83{+/-}8.9), with lower scores reported for avoidant coping styles (20.83 {+/-} 6.05). Humor coping scores were reported at 2.68{+/-}1.3 and religion coping scores at 5.64{+/-}1.8. Both men and women showed similar coping styles. Multivariate analysis found a significant relationship between male gender and both humor and avoidant coping (p <.01). Male gender was found to be inversely related to both religion and approach coping (p <.01). Marital status and education were significantly related to all coping style domains (p<.01). Occupation was significantly related to approach coping (p <.01). Rural and urban locations differed significantly in participant coping styles (p <.01). Factor analysis revealed two cluster groups (Factor 1 and 2) comprised of unique combinations from all coping style domains.\n\nConclusionParticipants in this study coped with the COVID-19 pandemic by utilizing a combination of coping strategies. Factor 1 revealed both avoidant and approach coping strategies and Factor 2 revealed a combination of humor and avoidant coping strategies. Overall, a higher utilization of approach coping strategies was reported, which has previously been associated with better physical and mental health outcomes. Religion was found to be a coping strategy for all participants. Future research may focus on understanding resilience in vulnerable populations, including people with disability or with migrant or refugee status in Bangladesh.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Matthew Breckons", - "author_inst": "Newcastle University" + "author_name": "K M Amran Hossain", + "author_inst": "Bangladesh Health Professions Institute" }, { - "author_name": "Sophie J Thorne", - "author_inst": "Newcastle University" + "author_name": "Karen Saunders", + "author_inst": "University of Kent" }, { - "author_name": "Rebecca Walsh", - "author_inst": "Newcastle University" + "author_name": "Mohamed Sakel", + "author_inst": "East Kent Hospitals University NHS Foundation Trust" }, { - "author_name": "Sunil S Bhopal", - "author_inst": "Newcastle University" + "author_name": "Lori Maria Walton", + "author_inst": "University of Scranton" }, { - "author_name": "Stephen Owens", - "author_inst": "Newcastle University" + "author_name": "Veena Raigangar", + "author_inst": "University of Sharjah" }, { - "author_name": "Judith Rankin", - "author_inst": "Newcastle University" + "author_name": "Zakir Uddin", + "author_inst": "McMaster University" + }, + { + "author_name": "Mohammad Anwar Hossain", + "author_inst": "Centre for the Rehabilitation of the Paralysed (CRP)" + }, + { + "author_name": "Asma Islam", + "author_inst": "Bangladesh Health Professions Institute (BHPI)" + }, + { + "author_name": "Faruq Ahmed", + "author_inst": "Centre for the Rehabilitation of the Paralysed (CRP)" + }, + { + "author_name": "Rafey Faruqui", + "author_inst": "University of Kent" + }, + { + "author_name": "Tamanna Tasnim", + "author_inst": "Bangladesh Health Professions Institute (BHPI)" + }, + { + "author_name": "Shohag Rana", + "author_inst": "Bangladesh Health Professions Institute (BHPI)" + }, + { + "author_name": "Shafin Rubayet", + "author_inst": "Centre for the Rehabilitation of the Paralysed (CRP)" + }, + { + "author_name": "Md. Shahoriar Ahmed", + "author_inst": "Centre for the Rehabilitation of the Paralysed (CRP)" + }, + { + "author_name": "Md. Obaidul Haque", + "author_inst": "Bangladesh Health Professions Institute (BHPI)" + }, + { + "author_name": "Md. Feroz Kabir", + "author_inst": "Jashore University of Science and Technology" + }, + { + "author_name": "Md. Sohrab Hossain", + "author_inst": "Bangladesh Health Professions Institute (BHPI)" + }, + { + "author_name": "Iqbal Kabir Jahid", + "author_inst": "JASHORE UNIVERSITY" + }, + { + "author_name": "Mst. Hosneara Yeasmin", + "author_inst": "Centre for the Rehabilitation of the Paralysed (CRP)" + }, + { + "author_name": "Sonjit Kumar Chakrovorty", + "author_inst": "Jashore University of Science and Technology" + }, + { + "author_name": "Md. Shahadat Hossain", + "author_inst": "Jahangirnagar University" + }, + { + "author_name": "Joty Paul", + "author_inst": "Centre for the Rehabilitation of the Paralysed (CRP)" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.03.28.21254496", @@ -816030,111 +814877,75 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2021.03.30.437769", - "rel_title": "A protective broadly cross-reactive human antibody defines a conserved site of vulnerability on beta-coronavirus spikes", + "rel_doi": "10.1101/2021.03.30.437771", + "rel_title": "Arrayed multicycle drug screens identify broadly acting chemical inhibitors for repurposing against SARS CoV 2", "rel_date": "2021-03-31", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.30.437769", - "rel_abs": "Broadly neutralizing antibodies (bnAbs) to coronaviruses (CoVs) are valuable in their own right as prophylactic and therapeutic reagents to treat diverse CoVs and, importantly, as templates for rational pan-CoV vaccine design. We recently described a bnAb, CC40.8, from a coronavirus disease 2019 (COVID-19)-convalescent donor that exhibits broad reactivity with human beta-coronaviruses ({beta}-CoVs). Here, we showed that CC40.8 targets the conserved S2 stem-helix region of the coronavirus spike fusion machinery. We determined a crystal structure of CC40.8 Fab with a SARS-CoV-2 S2 stem-peptide at 1.6 [A] resolution and found that the peptide adopted a mainly helical structure. Conserved residues in {beta}-CoVs interacted with CC40.8 antibody, thereby providing a molecular basis for its broad reactivity. CC40.8 exhibited in vivo protective efficacy against SARS-CoV-2 challenge in two animal models. In both models, CC40.8-treated animals exhibited less weight loss and reduced lung viral titers compared to controls. Furthermore, we noted CC40.8-like bnAbs are relatively rare in human COVID-19 infection and therefore their elicitation may require rational structure-based vaccine design strategies. Overall, our study describes a target on {beta}-CoV spike proteins for protective antibodies that may facilitate the development of pan-{beta}-CoV vaccines.\n\nSUMMARYA human mAb isolated from a COVID-19 donor defines a protective cross-neutralizing epitope for pan-{beta}-CoV vaccine design strategies", - "rel_num_authors": 23, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.30.437771", + "rel_abs": "Coronaviruses (CoVs) circulate in humans and animals, and expand their host range by zoonotic and anthroponotic transmissions. Endemic human CoVs, such as 229E and OC43 cause limited respiratory disease, and elicit short term anti-viral immunity favoring recurrent infections. Yet, severe acute respir-atory syndrome (SARS)-CoV-2 spreads across the globe with unprecedented impact on societies and economics. The world lacks broadly effective and affordable anti-viral agents to fight the pandemic and reduce the death toll. Here, we developed an image-based multicycle replication assay for focus for-mation of -coronavirus hCoV-229E-eGFP infected cells for screening with a chemical library of 5440 compounds arrayed in 384 well format. The library contained about 39% clinically used compounds, 26% in phase I, II or III clinical trials, and 34% in preclinical development. Hits were counter-selected against toxicity, and challenged with hCoV-OC43 and SARS-CoV-2 in tissue culture and human bronchial and nasal epithelial explant cultures from healthy donors. Fifty three compounds inhibited hCoV-229E-GFP, 39 of which at 50% effective concentrations (EC50) < 2M, and were at least 2-fold separated from toxicity. Thirty nine of the 53 compounds inhibited the replication of hCoV-OC43, while SARS-CoV-2 was inhibited by 11 compounds in at least two of four tested cell lines. Six of the 11 compounds are FDA-approved, one of which is used in mouth wash formulations, and five are systemic and orally available. Here, we demonstrate that methylene blue (MB) and mycophenolic acid (MPA), two broadly available low cost compounds, strongly inhibited shedding of infectious SARS-CoV-2 at the apical side of the cultures, in either pre- or post-exposure regimens, with somewhat weaker effects on viral RNA release indicated by RT-qPCR measurements. Our study illustrates the power of full cycle screens in repurposing clinical compounds against SARS-CoV-2. Importantly, both MB and MPA reportedly act as immunosuppressants, making them interesting candidates to counteract the cytokine storms affecting COVID-19 patients.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Panpan Zhou", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." - }, - { - "author_name": "Meng Yuan", - "author_inst": "Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA." - }, - { - "author_name": "Ge Song", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." - }, - { - "author_name": "Nathan Beutler", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." - }, - { - "author_name": "Namir Shaabani", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." - }, - { - "author_name": "Deli Huang", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." - }, - { - "author_name": "Wan-ting He", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." - }, - { - "author_name": "Xueyong Zhu", - "author_inst": "Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA." - }, - { - "author_name": "Sean Callaghan", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." - }, - { - "author_name": "Peter Yong", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." + "author_name": "Luca P Murer", + "author_inst": "University of Zurich" }, { - "author_name": "Fabio Anzanello", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." + "author_name": "Romain Volle", + "author_inst": "University of Zurich" }, { - "author_name": "Linghang Peng", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." + "author_name": "Vardan Andriasyan", + "author_inst": "University of Zurich" }, { - "author_name": "James Ricketts", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." + "author_name": "Nicole Meili", + "author_inst": "University of Zurich" }, { - "author_name": "Mara Parren", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." + "author_name": "Liliane Yang", + "author_inst": "University of Zurich" }, { - "author_name": "Elijah Garcia", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." + "author_name": "Daniela Sequeira", + "author_inst": "University of Zurich" }, { - "author_name": "Stephen A. Rawlings", - "author_inst": "Division of Infectious Diseases, Department of Medicine, University of California, San Diego, La Jolla, CA 92037, USA." + "author_name": "Alfonso Gomez-Gonzalez", + "author_inst": "University of Zurich" }, { - "author_name": "Davey M. Smith", - "author_inst": "Division of Infectious Diseases, Department of Medicine, University of California, San Diego, La Jolla, CA 92037, USA." + "author_name": "Anthony Petkidis", + "author_inst": "University of Zurich" }, { - "author_name": "David Nemazee", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." + "author_name": "Dominik Olszewski", + "author_inst": "University of Zurich" }, { - "author_name": "John R. Teijaro", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." + "author_name": "Michael Bauer", + "author_inst": "University of Zurich" }, { - "author_name": "Thomas Rogers", - "author_inst": "Division of Infectious Diseases, Department of Medicine, University of California, San Diego, La Jolla, CA 92037, USA." + "author_name": "Maarit Suomalainen", + "author_inst": "University of Zurich" }, { - "author_name": "Ian A. Wilson", - "author_inst": "Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA." + "author_name": "Fabien Kuttler", + "author_inst": "Ecole polytechnique federale de Lausanne" }, { - "author_name": "Dennis R. Burton", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." + "author_name": "Gerardo Turcatti", + "author_inst": "Ecole polytechnique federale de Lausanne" }, { - "author_name": "Raiees Andrabi", - "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA." + "author_name": "Urs F Greber", + "author_inst": "University of Zurich" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.03.29.21254590", @@ -817920,83 +816731,47 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2021.03.22.21254077", - "rel_title": "IL-6 and D-Dimer at Admission Predicts Cardiac Injury and Early Mortality during SARS-CoV-2 Infection", + "rel_doi": "10.1101/2021.03.27.21252266", + "rel_title": "A rapid, cost efficient and simple method to identify current SARS-CoV-2 variants of concern by Sanger sequencing part of the spike protein gene", "rel_date": "2021-03-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.22.21254077", - "rel_abs": "BACKGROUNDWe recently described mortality of cardiac injury in COVID-19 patients. Admission activation of immune, thrombotic biomarkers and their ability to predict cardiacinjury and mortality patterns in COVID-19 is unknown.\n\nMETHODSThis retrospective cohort study included 170 COVID-19 patients with cardiac injury at admission to Tongji Hospital in Wuhan from January 29-March 8, 2020. Temporal evolution of inflammatory cytokines, coagulation markers, clinical, treatment and mortality were analyzed.\n\nRESULTSOf 170 patients, 60 (35.3%) died early (<21d) and 61 (35.9%) died after prolonged stay. Admission lab work that correlated with early death were elevate levels of interleukin 6 (IL-6) (p<0.0001), Tumor Necrosis Factor-a (TNF-a) (p=0.0025), and C-reactive protein (CRP) (p<0.0001). We observed the trajectory of biomarker changes after admission, and determined that early mortality had a rapidly increasing D-dimer, gradually decreasing platelet and lymphocyte counts. Multivariate and simple linear regression models showed that death risk was determined by immune and thrombotic pathway activation. Increasing cTnI levels were associated with those of increasing IL-6 (p=0.03) and D-dimer (p=0.0021). Exploratory analyses suggested that patients that received heparin has lower early mortality compared to those who did not (p =0.07), despite similar risk profile.\n\nCONCLUSIONSIn COVID-19 patients with cardiac injury, admission IL-6 and D-dimer predicted subsequent elevation of cTnI and early death, highlighting the need for early inflammatory cytokine-based risk stratification in patients with cardiac injury.\n\nCondensed AbstractCOVID-19 with cardiac injury is associated with worse survival. Admission activation of immune, thrombotic biomarkers and their ability to predict cardiac injury and mortality patterns in COVID-19 is unknown. This study proved that cardiac injury in these patients is closely related to the activation of immunological and thrombotic pathways and can be predicted by admission biomarkers of these pathways. This study supports the strategy of biomarker-guided, point-of-care therapy that warrants further studies in a randomized manner to develop anti-immune and anti-thrombotic treatment regimens in severe COVID-19 patients with cardiac injury.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.27.21252266", + "rel_abs": "In 2020, the novel coronavirus, SARS-CoV-2, caused a pandemic, which is still raging at the time of writing this. Many countries have set up high throughput RT-qPCR based diagnostics for people with COVID-19 symptoms and for the wider population. In addition, with the use of whole genome sequencing (WGS) new lineages of SARS-CoV-2 have been identified that have been associated with increased transmissibility or altered vaccine efficacy, so-called Variants of Concern (VoC). WGS is generally too labor intensive and expensive to be applied to all positive samples from the diagnostic tests, and often has a turnaround time too long to enable VoC focused contact tracing. Here, we propose to use Sanger sequencing for the detection of common variants of concern and key mutations in early 2021, using a single set of the recognized ARTIC Network primers. The proposed setup relies entirely on materials and methods already in use in diagnostic RT-qPCR labs and on existing infrastructure from companies that have specialized in cheap and rapid turnaround Sanger sequencing. In addition, we provide an automated mutation calling software (https://github.com/kblin/covid-spike-classification). We have validated the setup on 195 SARS-CoV-2 positive samples, and we were able to profile >85% of RT-qPCR positive samples, where the last 15% largely stem from samples with low viral count. At approximately 4{euro} per sample in material cost, with minimal hands-on time, little data handling, and a turnaround time of less than 30 hours, the setup is simple enough to be implemented in any SARS-CoV-2 RT-qPCR diagnostic lab. Our protocol provides results that can be used to focus contact-tracing efforts and it is cheap enough for the tracking and surveillance of all positive samples for emerging variants such as B.1.1.7, B.1.351 and P.1 as of January 2021.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Daoyuan Si", - "author_inst": "China-Japan Union Hospital of Jilin University" - }, - { - "author_name": "Beibei Du", - "author_inst": "China-Japan Union Hospital of Jilin University" - }, - { - "author_name": "Bo Yang", - "author_inst": "Tongji Hospital" + "author_name": "Tue Sparholt Joergensen", + "author_inst": "Technical University of Denmark, The Novo Nordisk Foundation Center for Biosustainability, 2800 Kgs Lyngby, Denmark" }, { - "author_name": "Lina Jin", - "author_inst": "School of Public Health, Jilin University" + "author_name": "Kai Blin", + "author_inst": "Technical University of Denmark, The Novo Nordisk Foundation Center for Biosustainability, 2800 Kgs Lyngby, Denmark" }, { - "author_name": "Lujia Ni", - "author_inst": "China-Japan Union Hospital of Jilin University" + "author_name": "Franziska Kuntke", + "author_inst": "Technical University of Denmark, Department of Health Technology, Centre for Diagnostics, 2800 Kgs. Lyngby" }, { - "author_name": "Qian Zhang", - "author_inst": "China-Japan Union Hospital of Jilin University" + "author_name": "Henrik K. Salling", + "author_inst": "Novo Nordisk A/S, Dept. 609.04 Virology, Hagedornsvej 1, 2820 Gentofte, Denmark" }, { - "author_name": "Zhongfan Zhang", - "author_inst": "China-Japan Union Hospital of Jilin University" - }, - { - "author_name": "Mohammed Ali Azam", - "author_inst": "The Hull Family Laboratory, PMCC, University Health Network" - }, - { - "author_name": "Patrick F.H Lai", - "author_inst": "The Hull Family Laboratory, PMCC, University Health Network" - }, - { - "author_name": "Stephane Masse", - "author_inst": "The Hull Family Laboratory, PMCC, University Health Network" - }, - { - "author_name": "Huan Sun", - "author_inst": "China-Japan Union Hospital of Jilin University" - }, - { - "author_name": "Xingtong Wang", - "author_inst": "The First Hospital of Jilin University" - }, - { - "author_name": "Slava Epelman", - "author_inst": "Peter Munk Cardiac Centre, University Health Network, Toronto, Canada; The Ted Rogers Centre for Heart Research, Toronto, Canada" - }, - { - "author_name": "Patrick R Lawler", - "author_inst": "Peter Munk Cardiac Centre, University Health Network, Toronto, Canada; The Ted Rogers Centre for Heart Research, Toronto, Canada; Interdepartmental Division of " + "author_name": "Thomas Yssing Michaelsen", + "author_inst": "Aalborg University, Department of Chemistry and Bioscience, 9220 Aalborg, Denmark" }, { - "author_name": "Ping Yang", - "author_inst": "China-Japan Union Hospital of Jilin University" + "author_name": "Mads Albertsen", + "author_inst": "Aalborg University, Department of Chemistry and Bioscience, 9220 Aalborg, Denmark" }, { - "author_name": "Kumaraswamy Nanthakumar", - "author_inst": "The Hull Family Laboratory, PMCC, University Health Network" + "author_name": "Helene Larsen", + "author_inst": "Technical University of Denmark, Department of Health Technology, Centre for Diagnostics, 2800 Kgs. Lyngby" } ], "version": "1", "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "cardiovascular medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.03.27.21254480", @@ -819758,33 +818533,33 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.03.27.21254107", - "rel_title": "Detection of SARS-CoV-2 N501Y mutation by RT-PCR to identify the UK and the South African strains in the population of South Indian state of Telangana", + "rel_doi": "10.1101/2021.03.26.21254421", + "rel_title": "Estimating COVID-19 cases and deaths prevented by non-pharmaceutical interventions in 2020-2021, and the impact of individual actions: a retrospective model-based analysis", "rel_date": "2021-03-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.27.21254107", - "rel_abs": "ObjectiveTo detect N501Y mutation of the SARS-CoV-2 spike protein by RT-PCR to distinguish (B.1.1.7) UK and (501Y.V2) South African strains from others in the population of Telangana and to determine its clinical implications.\n\nMethodsA primer-probe mix that specifically detects the mutated N501Y strain by real time RT-PCR was designed. 93 samples that were reported positive for COVID-19 by our laboratory in the month of February 2021 were tested using our own primer-probe mix for the presence of N501Y by RT-PCR. The results of RT-PCR were validated by Sanger sequencing in representative samples. Sanger sequencing of other defining spike mutations of B.1.1.7 (del 69-70, del 144, N501Y, A570D, D614G, P681H, T716I, S982A and D1118H) and 501Y.V2 (K417N, E484K, N501Y and D614G) was also investigated.\n\nFindingsOut of 93 COVID-19 positive samples, 12 samples are detected positive for N501Y by RT-PCR. Sanger sequencing of these 12 samples further confirmed the presence of N501Y and other mutations that are characteristic of UK strain (B.1.1.7). The South African strain (501Y.V2) is not detected in any of our samples in this study. But, the E484K mutation that is characteristic of 501Y.V2 is detected in one N501Y negative sample.\n\nConclusionStrain-specific RT-PCR for N501Y was developed and validated with Sanger sequencing. Such strategy facilitates quick surveillance for more transmissible and more vaccine resistant strains.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.26.21254421", + "rel_abs": "Simulation models from the early COVID-19 pandemic highlighted the urgency of applying non-pharmaceutical interventions (NPIs), but had limited empirical data. Here we use data from 2020-2021 to retrospectively model the impact of NPIs in Ontario, Canada. Our model represents age groups and census divisions in Ontario, and is parameterised with epidemiological, testing, demographic, travel, and mobility data. The model captures how individuals adopt NPIs in response to reported cases. We compare a scenario representing NPIs introduced within Ontario (closures of workplaces/schools, reopening of schools/workplaces with NPIs in place, individual-level NPI adherence) to counterfactual scenarios wherein alternative strategies (e.g. no closures, reliance on individual NPI adherence) are adopted to ascertain the extent to which NPIs reduced cases and deaths. Combined school/workplace closure and individual NPI adoption reduced the number of deaths in the best-case scenario for the case fatality rate (CFR) from 178548 [CI: 171845, 185298] to 3190 [CI: 3095, 3290] in the Spring 2020 wave. In the Fall 2020/Winter 2021 wave, the introduction of NPIs in workplaces/schools reduced the number of deaths from 20183 [CI: 19296, 21057] to 4102 [CI: 4075, 4131]. Deaths were several times higher in the worst-case CFR scenario. Each additional 9-16 (resp. 285-578) individuals who adopted NPIs in the first wave prevented one additional infection (resp., death). Our results show that the adoption of NPIs prevented a public health catastrophe. A less comprehensive approach, employing only closures or individual-level NPI adherence, would have resulted in a large number of cases and deaths.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Safaa Muneer Ahmed", - "author_inst": "Tenet Diagnostics" + "author_name": "Kathyrn Fair", + "author_inst": "University of Guelph" }, { - "author_name": "Smita Rao Juvvadi", - "author_inst": "Tenet Diagnostics" + "author_name": "Vadim Karatayev", + "author_inst": "University of Guelph" }, { - "author_name": "Rakesh Kalapala", - "author_inst": "Asian Institute of Gastroenterology" + "author_name": "Madhur Anand", + "author_inst": "University of Guelph" }, { - "author_name": "Jagadeesh Babu Sreemanthula", - "author_inst": "Tenet Diagnostics" + "author_name": "Chris Bauch", + "author_inst": "University of Waterloo" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -821564,101 +820339,69 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.20.21253896", - "rel_title": "Challenges in defining Long COVID: Striking differences across literature, Electronic Health Records, and patient-reported information", + "rel_doi": "10.1101/2021.03.22.21254006", + "rel_title": "Localised community circulation of SARS-CoV-2 viruses with an increased accumulation of single nucleotide polymorphisms that adversely affect the sensitivity of real-time reverse transcription assays targeting Nucleocapsid protein.", "rel_date": "2021-03-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.20.21253896", - "rel_abs": "Since late 2019, the novel coronavirus SARS-CoV-2 has introduced a wide array of health challenges globally. In addition to a complex acute presentation that can affect multiple organ systems, increasing evidence points to long-term sequelae being common and impactful. The worldwide scientific community is forging ahead to characterize a wide range of outcomes associated with SARS-CoV-2 infection; however the underlying assumptions in these studies have varied so widely that the resulting data are difficult to compareFormal definitions are needed in order to design robust and consistent studies of Long COVID that consistently capture variation in long-term outcomes. Even the condition itself goes by three terms, most widely \"Long COVID\", but also \"COVID-19 syndrome (PACS)\" or, \"post-acute sequelae of SARS-CoV-2 infection (PASC)\". In the present study, we investigate the definitions used in the literature published to date and compare them against data available from electronic health records and patient-reported information collected via surveys. Long COVID holds the potential to produce a second public health crisis on the heels of the pandemic itself. Proactive efforts to identify the characteristics of this heterogeneous condition are imperative for a rigorous scientific effort to investigate and mitigate this threat.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.22.21254006", + "rel_abs": "Currently the primary method for confirming acute SARS-CoV-2 infection is through the use of molecular assays that target highly conserved regions within the viral genome. Many, if not most of the diagnostic targets currently in use were produced early in the pandemic, using genomes sequenced and shared in early 2020. As viral diversity increases, mutations may arise in diagnostic target sites that have an impact on the performance of diagnostic tests. Here, we report on a local outbreak of SARS-CoV-2 which had gained an additional mutation at position 28890 of the nucleocapsid protein, on a background of pre-existing mutations at positions 28881, 28882, 28883 in one of the main circulating viral lineages in Wales at that time. The impact of this additional mutation had a statistically significant impact on the Ct value reported for the N gene target designed by the Chinese CDC and used in a number of commercial diagnostic products. Further investigation identified that, in viral genomes sequenced from Wales over the summer of 2020, the N gene had a higher rate of mutations in diagnostic target sites than other targets, with 115 issues identified affecting over 10% of all cases sequenced between February and the end of August 2020. In comparison an issue was identified for ORFab, the next most affected target, in less than 1.4% of cases over the same time period. This work emphasises the potential impact that mutations in diagnostic target sites can have on tracking local outbreaks, as well as demonstrating the value of genomics as a routine tool for identifying and explaining potential diagnostic primer issues as part of a laboratory quality management system. This work also indicates that with increasing genomic sequencing data availability, there is a need to re-evaluate the diagnostic targets that are in use for SARS-CoV-2 testing, to better target regions that are now demonstrated to be of lower variability.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Halie M. Rando", - "author_inst": "Center for Health AI, University of Colorado School of Medicine, Aurora, CO, USA; Department of Biochemistry and Molecular Genetics, University of Colorado Scho" - }, - { - "author_name": "Tellen D. Bennett", - "author_inst": "Section of Informatics and Data Science, Department of Pediatrics, University of Colorado School of Medicine, University of Colorado, Aurora, CO, USA" - }, - { - "author_name": "James Brian Byrd", - "author_inst": "The University of Michigan at Ann Arbor, Ann Arbor, MI, USA" - }, - { - "author_name": "Carolyn Bramante", - "author_inst": "University of Minnesota, Minneapolis, MN, USA" - }, - { - "author_name": "Tiffany J. Callahan", - "author_inst": "Computational Bioscience, University of Colorado Anschutz Medical Campus, Boulder, CO, USA" - }, - { - "author_name": "Christopher G. Chute", - "author_inst": "Schools of Medicine, Public Health, and Nursing, Johns Hopkins University, Baltimore, MD, USA" - }, - { - "author_name": "Hannah Davis", - "author_inst": "Patient-Led Research for COVID-19" - }, - { - "author_name": "Rachel Deer", - "author_inst": "The University of Texas Medical Branch at Galveston" - }, - { - "author_name": "Joel Gagnier", - "author_inst": "The University of Michigan at Ann Arbor, Ann Arbor, MI, USA" + "author_name": "Catherine Moore", + "author_inst": "Public Health Wales NHS Trust" }, { - "author_name": "Farrukh M Koraishy", - "author_inst": "Stony Brook University, Stony Brook, NY, USA" + "author_name": "Louise Davies", + "author_inst": "Public Health Wales NHS Trust" }, { - "author_name": "Feifan Liu", - "author_inst": "University of Massachusetts Medical School Worcester, Worcester, MA, USA" + "author_name": "Rhianydd Rees", + "author_inst": "Public Health Wales NHS Trust" }, { - "author_name": "Julie A. McMurry", - "author_inst": "University of Colorado Denver I Anschutz Medical Campus, Aurora, CO, USA" + "author_name": "Laura Gifford", + "author_inst": "Public Health Wales NHS Trust" }, { - "author_name": "Richard A. Moffitt", - "author_inst": "Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA" + "author_name": "Heather Lewis", + "author_inst": "Public Health Wales NHS Trust" }, { - "author_name": "Emily R. Pfaff", - "author_inst": "Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA" + "author_name": "Amy Plimmer", + "author_inst": "Public Health Wales NHS Trust" }, { - "author_name": "Justin T. Reese", - "author_inst": "Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA" + "author_name": "Andrew Mack", + "author_inst": "Cardiff University" }, { - "author_name": "Rose Relevo", - "author_inst": "Oregon Health & Science University, Portland, OR, USA" + "author_name": "Nicole Pacchiarini", + "author_inst": "Public Health Wales NHS Trust" }, { - "author_name": "Peter N. Robinson", - "author_inst": "The Jackson Laboratory For Genomic Medicine, Farmington, CT, USA; Institute for Systems Genomics, University of Connecticut, Farmington, CT, USA." + "author_name": "Joel Alexander Southgate", + "author_inst": "Cardiff University" }, { - "author_name": "Joel H. Saltz", - "author_inst": "Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA" + "author_name": "- The COVID-19 Genomics UK (COG-UK) consortium", + "author_inst": "" }, { - "author_name": "Anthony Solomonides", - "author_inst": "Research Institute, NorthShore University HealthSystem, Evanston, IL, USA" + "author_name": "Matthew J Bull", + "author_inst": "Public Health Wales NHS Trust" }, { - "author_name": "Anupam Sule", - "author_inst": "Saint Joseph Mercy Health System, Ypsilanti, MI, USA" + "author_name": "Joanne Watkins", + "author_inst": "Public Health Wales NHS Trust" }, { - "author_name": "Umit Topaloglu", - "author_inst": "School of Medicine, Wake Forest University, Winston Salem, NC, USA" + "author_name": "Sally Corden", + "author_inst": "Public Health Wales NHS Trust" }, { - "author_name": "Melissa A. Haendel", - "author_inst": "University of Colorado Denver I Anschutz Medical Campus, Aurora, CO, USA" + "author_name": "Thomas Richard Connor", + "author_inst": "Cardiff University" } ], "version": "1", @@ -823590,69 +822333,93 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.25.21254296", - "rel_title": "A SIMPLE, HOME-THERAPY ALGORYTHM TO PREVENT HOSPITALIZATION OF COVID-19 PATIENTS: A RETROSPECTIVE OBSERVATIONAL MATCHED-COHORT STUDY", + "rel_doi": "10.1101/2021.03.24.21253807", + "rel_title": "Impact of the COVID-19 Pandemic on Antimicrobial Resistance (AMR) Surveillance, Prevention and Control: A Global Survey", "rel_date": "2021-03-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.25.21254296", - "rel_abs": "BackgroundEffective simple, home-treatment algorithms implemented on the basis of a pathophysiologic and pharmacologic rationale to accelerate recovery and prevent hospitalization of patients with early coronavirus disease 2019 (COVID-19) would have major implications for patients and health care providers.\n\nMethodsThis academic, matched-cohort study compared outcomes of 90 consecutive consenting patients with mild COVID-19 treated at home by their family physicians from October 2020 to January 2021 according to the proposed recommendation algorithm with those of 90 age-, sex-, and comorbidities-matched patients who received other therapeutic regimens. Primary outcome was time to resolution of major symptoms. Secondary outcomes included prevention of hospitalization. Analyses were by intention-to-treat.\n\nFindingsAll patients achieved complete remission. The median [IQR] time to resolution of major symptoms was 18 [14-23] days in the recommended schedule cohort and 14 [7-30] days in the matched control cohort (p=0{middle dot}033). Minor symptoms persisted in a lower percentage of patients in the recommended than in the control cohort (23{middle dot}3% versus 73{middle dot}3%, respectively, p<0{middle dot}0001) and for a shorter period (p=0{middle dot}0107). Two patients in the recommended cohort were hospitalized compared to 13 (14{middle dot}4%) controls (Log-rank test, p=0{middle dot}0038). Prevention algorithm abated the days and cumulative costs of hospitalization by >90% (from 481 to 44 days and from 296 to 28 thousand Euros, respectively. 1{middle dot}2 patients had to be treated to save one hospitalization event.\n\nInterpretationImplementation of an early, home-treatment algorithm failed to accelerate recovery from major symptoms of COVID-19, but almost blunted the risk of hospitalization and related treatment costs.\n\nRO_SCPLOWESEARCHC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWINC_SCPLOW CO_SCPLOWONTEXTC_SCPLOWO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed and the Cochrane Library for peer-reviewed articles published in any language up to March 19, 2021, using the search terms (\"2019-nCoV\" or \"SARS-CoV-2\" or \"COVID-19\") and (\"early\" or \"outpatient\" or \"treatment\" or \"home\"). Our search did not identify any randomised clinical trials or observational studies that assessed the effectiveness of treatment regimens targeting early mild symptoms of COVID-19 in the outpatient setting.\n\nAdded value of this studyIn this fully academic, observational matched-cohort study, we found that early home-treatment of 90 consecutive patients with mild COVID-19 by their family physicians according to the proposed recommendation algorithm, designed on the basis of a pathophysiologic and pharmacologic rationale, significantly reduced the risk of hospitalisation compared to 90 age-, sex-, and comorbidities-matched patients who received other therapeutic regimens. Days of hospitalization and related treatment costs were reduced by more than 90%. Just 1.2 patients needed to be treated to save one hospitalization event. The recommended schedule cohort required a few more days to achieve resolution of major symptoms, including fever, dyspnea, musculoskeletal pain, headache and cough compared to the control cohort. Symptoms, such as anosmia and ageusia/dysgeusia, persisted less commonly and for a shorter period in the recommendation than in the control cohort.\n\nImplications of the available evidenceThe finding that the implementation of the proposed simple treatment algorithm during the initial, mild phase of COVID-19 has the potential to prevent disease progression, eventually limiting the need of hospital admission may have major implications for patients and health care providers. Indeed, preventing hospitalisations due to worsening of COVID-19 will not only save lives, but will also contribute to remarkably reduce treatment costs and to reshape health care systems that are overburdened because of the pandemic effects.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.24.21253807", + "rel_abs": "SynopsisO_ST_ABSObjectivesC_ST_ABSThe COVID-19 pandemic has had a substantial impact on health systems. The WHO Antimicrobial Resistance (AMR) Collaborating Centres Network conducted a survey to assess the effects of COVID-19 on AMR surveillance, prevention and control.\n\nMethodsFrom October-December 2020, WHO Global Antimicrobial Resistance and Use Surveillance System (GLASS) national focal points completed a questionnaire including Likert-scales and open-ended questions. Data were descriptively analysed, income/regional differences were assessed, and free-text questions were thematically analysed.\n\nResultsSeventy-three countries across income levels participated. During the COVID-19 pandemic, 67% reported limited ability to work with AMR partnerships; decreases in funding were frequently reported by low- and middle-income countries (LMICs; p<0.01). Reduced availability of nursing, medical and public health staff for AMR was reported by 71%, 69% and 64%, respectively, whereas 67% reported stable cleaning staff availability. The majority (58%) reported reduced reagents/consumables, particularly LMICs (p<0.01). Decreased numbers of cultures, elective procedures, chronically ill admissions and outpatients and increased intensive care unit admissions reported could bias AMR data. Reported overall infection prevention and control (IPC) improvement could decrease AMR rates, whereas increases in selected inappropriate IPC practices and antibiotic prescribing could increase rates. Most did not yet have complete data on changing AMR rates due to COVID-19.\n\nConclusionsThis was the first survey to explore the global impact of COVID-19 on AMR among GLASS countries. Responses revealed universal patterns but also captured country variability. Although focus is understandably on COVID-19, gains in detecting and controlling AMR, a global health priority, cannot afford to be lost.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Fredy Suter", - "author_inst": "Azienda Socio-Sanitaria Territoriale (ASST) Papa Giovanni XXIII, Bergamo, Italy" + "author_name": "Sara Tomczyk", + "author_inst": "Robert Koch Institute, WHO Collaborating Center for Emerging Infections and Biological Threats, Berlin, Germany" }, { - "author_name": "Elena Consolaro", - "author_inst": "ATS Insubria, Varese, Italy" + "author_name": "Angelina Taylor", + "author_inst": "Robert Koch Institute, WHO Collaborating Center for Emerging Infections and Biological Threats, Berlin, Germany" }, { - "author_name": "Stefania Pedroni", - "author_inst": "ATS Insubria, Varese, Italy" + "author_name": "Allison Brown", + "author_inst": "Centers for Disease Control and Prevention, WHO Collaborating Centre for International Monitoring of Bacterial Resistance to Antimicrobial Agents, Atlanta, Geor" }, { - "author_name": "Chiara Moroni", - "author_inst": "ATS Insubria, Varese, Italy" + "author_name": "Marlieke de Kraker", + "author_inst": "Geneva University Hospitals and Faculty of Medicine, WHO Collaborating Centre on Patient Safety, Geneva, Switzerland" }, { - "author_name": "Elena Pasto", - "author_inst": "ATS Insubria, Varese, Italy" + "author_name": "Tim Eckmanns", + "author_inst": "Robert Koch Institute, WHO Collaborating Center for Emerging Infections and Biological Threats, Berlin, Germany" }, { - "author_name": "Maria Vittoria Paganini", - "author_inst": "ATS Insubria, Varese, Italy" + "author_name": "Aiman El-Saed", + "author_inst": "King Abdulaziz Medical City, WHO Collaborating Centre for Infection Prevention and Control and Anti-Microbial, Riyadh, Saudi" }, { - "author_name": "Grazia Prevettoni", - "author_inst": "Ospedale Circolo di Busto Arsizio, Varese, Italy" + "author_name": "Majid Alshamrani", + "author_inst": "King Abdulaziz Medical City, WHO Collaborating Centre for Infection Prevention and Control and Anti-Microbial, Riyadh, Saudi" }, { - "author_name": "Umberto Cantarelli", - "author_inst": "ASL Teramo, Teramo, Italy" + "author_name": "Rene Hendriksen", + "author_inst": "Technical University of Denmark, National Food Institute, WHO Collaborating Centre for Antimicrobial Resistance in Foodborne Pathogens and Genomics, Kongens Lyn" }, { - "author_name": "Nadia Rubis", - "author_inst": "Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Bergamo, Italy" + "author_name": "Megan Jacob", + "author_inst": "College of Veterinary Medicine, North Carolina State University, WHO Collaborating Centre for Global One Health and Antimicrobial Resistance Initiatives, Raleig" }, { - "author_name": "Norberto Perico", - "author_inst": "Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Bergamo, Italy" + "author_name": "Sonja Lofmark", + "author_inst": "Public Health Agency of Sweden, WHO Collaborating Centre for Antimicrobial Resistance Containment, Stockholm, Sweden" }, { - "author_name": "Annalisa Perna", - "author_inst": "Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Bergamo, Italy" + "author_name": "Olga Perovic", + "author_inst": "National Institute for Communicable Diseases and School of Pathology at University of Witwatersrand, WHO Collaborating Centre for Antimicrobial Resistance, Joha" }, { - "author_name": "Tobia Peracchi", - "author_inst": "Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Bergamo, Italy" + "author_name": "Nandini Shetty", + "author_inst": "National Infection Service Laboratories, Public Health England, WHO Collaborating Centre for Reference & Research on Antimicrobial Resistance and Healthcare Ass" }, { - "author_name": "Piero Ruggenenti", - "author_inst": "Azienda Socio-Sanitaria Territoriale (ASST) Papa Giovanni XXIII, Bergamo, Italy" + "author_name": "Dawn Sievert", + "author_inst": "Centers for Disease Control and Prevention, WHO Collaborating Centre for International Monitoring of Bacterial Resistance to Antimicrobial Agents, Atlanta, Geor" }, { - "author_name": "Giuseppe Remuzzi", - "author_inst": "Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Bergamo, Italy" + "author_name": "Rachel Smith", + "author_inst": "Centers for Disease Control and Prevention, WHO Collaborating Centre for International Monitoring of Bacterial Resistance to Antimicrobial Agents, Atlanta, Geor" + }, + { + "author_name": "John Stelling", + "author_inst": "Brigham and Women?s Hospital, WHO Collaborating Centre for Surveillance of Antimicrobial Resistance, Boston, Massachusetts, United States of America" + }, + { + "author_name": "Siddhartha Thakur", + "author_inst": "College of Veterinary Medicine, North Carolina State University, WHO Collaborating Centre for Global One Health and Antimicrobial Resistance Initiatives, Raleig" + }, + { + "author_name": "Barbara Tornimbene", + "author_inst": "Surveillance, Prevention and Control Department, World Health Organization, Geneva, Switzerland" + }, + { + "author_name": "Ann Christin Vietor", + "author_inst": "Robert Koch Institute, WHO Collaborating Center for Emerging Infections and Biological Threats, Berlin, Germany" + }, + { + "author_name": "Sergey Eremin", + "author_inst": "Surveillance, Prevention and Control Department, World Health Organization, Geneva, Switzerland" + }, + { + "author_name": "- WHO AMR Surveillance and Quality Assessment Collaborating Centre Network", + "author_inst": "" } ], "version": "1", @@ -825080,171 +823847,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.03.23.21253487", - "rel_title": "Impaired antibacterial immune signaling and changes in the lung microbiome precede secondary bacterial pneumonia in COVID-19", + "rel_doi": "10.1101/2021.03.25.21254288", + "rel_title": "Virtual peer role-play during COVID-19 pandemic for teaching medical students how to break bad news", "rel_date": "2021-03-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.23.21253487", - "rel_abs": "Secondary bacterial infections, including ventilator-associated pneumonia (VAP), lead to worse clinical outcomes and increased mortality following viral respiratory infections including in patients with coronavirus disease 2019 (COVID-19). Using a combination of tracheal aspirate bulk and single-cell RNA sequencing we assessed lower respiratory tract immune responses and microbiome dynamics in 23 COVID-19 patients, 10 of whom developed VAP, and eight critically ill uninfected controls. At a median of three days (range: 2-4 days) before VAP onset we observed a transcriptional signature of bacterial infection. At a median of 15 days prior to VAP onset (range: 8-38 days), we observed a striking impairment in immune signaling in COVID-19 patients who developed VAP. Longitudinal metatranscriptomic analysis revealed disruption of lung microbiome community composition in patients with VAP, providing a connection between dysregulated immune signaling and outgrowth of opportunistic pathogens. These findings suggest that COVID-19 patients who develop VAP have impaired antibacterial immune defense detectable weeks before secondary infection onset.", - "rel_num_authors": 38, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.25.21254288", + "rel_abs": "In order to cope with the SARS-CoV-2 pandemic and meet with the educational needs of medical students, we have evaluated the virtual peer role-plays (VPRP), an innovative approach to teach breaking bad news communication skills to medical students. Three scenarios of relational simulation were successively proposed to 237 medical students divided in 10 groups, each supervised by two teachers. Pre- and post-VPRP questionnaires were submitted to evaluate students satisfaction. The response rate of the pre- and post-VPRP questionnaires were 89% and 52% respectively. Two-thirds of the students had never participated in a peer role-play session. Most students had low level of confidence in breaking bad news communication and were motivated to participate to the VPRP session. Students satisfaction on VPRP session regarding quality (realism, organization), interest, perceived benefits was very positive. In conclusion, VPRP are feasible, of low cost (no material is required), applicable to other healthcare students and is relevant to the growth of teleconsultation.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Alexandra Tsitsiklis", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Beth Shoshana Zha", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Ashley Byrne", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Catherine Devoe", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Elze Rackaityte", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Sophia Levan", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Sara Sunshine", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Eran Mick", - "author_inst": "University of California, San Francisco, Chan Zuckerberg Biohub" - }, - { - "author_name": "Rajani Ghale", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Christina Love", - "author_inst": "University of California San Francisco" - }, - { - "author_name": "Alexander J Tarashansky", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Angela Pisco", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Jack Albright", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Alejandra Jauregui", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Aartik Sarma", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Norma Neff", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Paula Hayakawa Serpa", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Thomas J. Deiss", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Amy Kistler", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Sidney Carrillo", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "K. Mark Ansel", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Aleksandra Leligdowicz", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Stephanie Christenson", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Norman Jones", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Bing Wu", - "author_inst": "Genentech" - }, - { - "author_name": "Spyros Darmanis", - "author_inst": "Genentech" - }, - { - "author_name": "Michael M Matthay", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Susan V Lynch", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Joseph L. DeRisi", - "author_inst": "UCSF, Chan Zuckerberg Biohub" - }, - { - "author_name": "- COMET Consortium", - "author_inst": "" + "author_name": "Jebrane Bouaoud", + "author_inst": "Cancer Research Center of Lyon" }, { - "author_name": "Carolyn M. Hendrickson", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Kristen N. Kangelaris", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Matthew F. Krummel", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Prescott G. Woodruff", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "David J. Earle", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Oren Rosenberg", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Carolyn S. Calfee", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Charles R. Langelier", - "author_inst": "University of California, San Francisco" + "author_name": "Pierre Saintigny", + "author_inst": "Cancer Researh Center of Lyon, Department ofTranslational Medicine" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "medical education" }, { "rel_doi": "10.1101/2021.03.23.21254207", @@ -826710,53 +825333,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.24.21254271", - "rel_title": "COVID-19 RT-PCR diagnostic assay sensitivity and SARS-CoV-2 transmission: A missing link?", + "rel_doi": "10.1101/2021.03.26.21254383", + "rel_title": "Increased angiotensin-converting enzyme 2, sRAGE and immune activation, but lowered calcium and magnesium in COVID-19: association with chest CT abnormalities and lowered peripheral oxygen saturation.", "rel_date": "2021-03-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.24.21254271", - "rel_abs": "BackgroundThe sensitivity of commercially available RT-PCR assays varies over 10,000 fold, ranging from 10 to 20,000 viral copies/ml. The reporting of high Ct value results has been under scrutiny, as the clinical significance of these values is not yet completely understood. The early detection of infected individuals (high Ct results) in the pre-symptomatic phase of the disease using highly sensitive RT-PCR methods has been argued as a strategy to prevent transmission, while on the contrary, the reporting of high Ct has been criticized as false-positive results causing unnecessary testing and having several negative implications. The purpose of this study was to verify the presence of SARS-CoV-2 genomes in samples with a wide range of RT-PCR Ct values including samples with high Ct (37 to 42) using next-generation sequencing (NGS).\n\nMethodsThe study evaluated a total of 547 previously positive samples tested with the PerkinElmer(R) New Coronavirus Nucleic Acid Detection RT-PCR kit. The samples included in this study ranged from Ct values of 17-42, with 44 samples having a Ct > 37. Of the 547 samples, 149 were sequenced using PerkinElmer NEXTFLEX Variant-Seq SARS-CoV2 assay on NovaSeq 6000, and 398 samples were sequenced using Illumina SARS-CoV-2 respiratory viral panel kits using the NextSeq 500/550 system.\n\nResultsBetween the two clinical laboratories, a total of [~]1.95 million samples were tested using the FDA-EUA PerkinElmer(R) New Coronavirus RT-PCR assay. Of the 1.95 million samples, [~]1.72 million were negative, [~]250,000 positive, and [~]16,500 in the range of 37-42. Of the 547 samples sequenced, the percentage of sequencing reads that aligned to the SARS-CoV-2 Wuhan-hu-1 reference genome (NC_045512.2) ranged from 25.5% to 99.69%. All samples sequenced showed high sequence specificity to the SARS-CoV-2 virus. Low Ct samples showed complete uniform coverage across the entire 29kb SAR-CoV-2 genome. The average coverage in samples with high Ct (>37) was found to be 55.5% (range 16.1-99.2%). However, as sample Ct increased, a gradual decrease in coverage uniformity was observed for few samples.\n\nConclusionThis study demonstrates for the first time that the viral RNA is present in the high Ct value range of 37-42 and the sequence is unique to SARS-CoV-2 confirmed using two separate sequencing assays. This confirms that the detected Ct values are reflective of the presence of the SARS-CoV-2 virus and they are not an artifact or contamination. In light of the recent work highlighting the majority of transmission being pre-symptomatic/ asymptomatic, and high Ct results being observed at both the early and late phases of infection warrants further investigation into the clinical utility of high Ct results to curtail the spread of the virus.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.26.21254383", + "rel_abs": "BackgroundThe characterization of new biomarkers of COVID-19 is extremely important. Few studies measured the soluble receptor for advanced glycation end product (sRAGE), angiotensin-converting enzyme 2 (ACE2), calcium and magnesium in COVID-19.\n\nAimsTo measure sRAGE, ACE2, interleukin (IL) -6, IL-10, CRP, calcium, magnesium, and albumin in COVID-19 patients in association with peripheral oxygen saturation (SpO2) and chest CT scan abnormalities (CCTA) including ground glass opacities.\n\nMethodsThis study measured sRAGE, ACE2, IL-6, IL-10, CRP using ELISA techniques, and calcium, magnesium, and albumin using a spectrophotometric method in 60 COVID-19 patients and 30 healthy controls.\n\nResultsCOVID-19 is characterized by significantly increased IL-6, CRP, IL-10, sRAGE, ACE2, and lowered levels of SpO2, albumin, magnesium and calcium. Neural networks showed that a combination of calcium, IL-6, CRP, and sRAGE yielded an accuracy of 100% in detecting COVID-19 patients with calcium being the most important predictor followed by IL-6, and CRP. COVID-19 patients with CCTAs showed lower SpO2 and albumin levels than those without CCTAs. SpO2 was significantly and inversely correlated with IL-6, IL-10, CRP, sRAGE, and ACE2, and positively with albumin, magnesium and calcium. Patients with positive IgG results showed a significant elevation in the serum level of IL-6, sRAGE, and ACE2 compared to the negatively IgG patient subgroup.\n\nConclusionThe results show that immune-inflammatory and RAGE pathway biomarkers may be used as external validating criterion for the diagnosis COVID-19. Those pathways coupled with lowered SpO2, calcium and magnesium are drug targets that may help to reduce the consequences of COVID-19.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Nikhil Shri Sahajpal", - "author_inst": "Augusta University" - }, - { - "author_name": "Ephrem Chin Lip Hon", - "author_inst": "PerkinElmer Inc." - }, - { - "author_name": "Stephanie Dallaire", - "author_inst": "PerkinElmer Inc." - }, - { - "author_name": "Colin Williams", - "author_inst": "Augusta University" - }, - { - "author_name": "Sudha Ananth", - "author_inst": "Augusta University" - }, - { - "author_name": "Ashis K Mondal", - "author_inst": "Augusta University" + "author_name": "Hussein Al-Hakeim", + "author_inst": "University of Kufa" }, { - "author_name": "Amyn M Rojiani", - "author_inst": "Augusta University" + "author_name": "Hawraa Al-Jassas", + "author_inst": "University of Kufa" }, { - "author_name": "Madhuri Hegde", - "author_inst": "PerkinElmer Inc." + "author_name": "Gerwyn Morris", + "author_inst": "Deakin University" }, { - "author_name": "Ravindra Kolhe", - "author_inst": "Augusta University" + "author_name": "Michael Maes", + "author_inst": "Chulalongkorn University; Deakin University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -828832,18 +827435,63 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2021.03.22.21251380", - "rel_title": "The Role of Testing Availability on Intentions to Isolate during the COVID-19 Pandemic - A Randomized Trial", + "rel_doi": "10.1101/2021.03.25.436907", + "rel_title": "A robust SARS-CoV-2 replication model in primary human epithelial cells at the air liquid interface to assess antiviral agents", "rel_date": "2021-03-25", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.22.21251380", - "rel_abs": "BackgroundLittle information exists on how COVID-19 testing availability influences intentions to engage in risky behavior. Understanding the behavioral effects of testing availability may provide insight into the role of adequate testing on controlling viral transmission.\n\nObjectiveTo evaluate the impact of testing availability on behavioral intention to self-isolate in a simulated scenario with participants who have been clinically diagnosed with COVID-19.\n\nMethodsA total of 1400 participants were recruited from Amazon Mechanical Turk (MTurk) through a national, online, opt-in survey. Participants were randomized to one of three hypothetical scenarios. Each scenario asked participants to imagine having symptoms consistent with COVID-19 along with a clinical diagnosis from their physician. However, scenarios differed in their testing result: testing unavailable, positive test, or negative test. The primary outcome was intention to engage in high-risk COVID-19 behaviors, measured using an 11-item mean score (range 1-7) that was pre-registered prior to data collection. The randomized survey was conducted between July 23rd to July 29th, 2020.\n\nResultsOut of 1194 respondents (41.6% male, 58.4% female) with a median age of 38.5 years, participants who had no testing available in their clinical scenario showed significantly greater intentions to engage in behavior facilitating COVID-19 transmission compared to those who received a positive confirmatory test result scenario (difference (SE): 0.14 (0.06), P=0.016), equating to an 11.1% increase in mean score risky behavior intentions. Intention to engage in behaviors that can spread COVID-19 were also positively associated with male gender, poor health status, and Republican party affiliation.\n\nConclusionTesting availability appears to play an independent role in influencing behaviors facilitating COVID-19 transmission. Such findings shed light on the possible negative externalities of testing unavailability.\n\nTrial RegistrationEffect of Availability of COVID-19 Testing on Choice to Isolate and Socially Distance, NCT04459520, https://clinicaltrials.gov/ct2/show/NCT04459520", - "rel_num_authors": 0, - "rel_authors": null, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.25.436907", + "rel_abs": "There are, besides remdesivir, no approved antivirals for the treatment of SARS-CoV-2 infections. To aid in the search for antivirals against this virus, we explored the use of human tracheal airway epithelial cells (HtAEC) and human small airway epithelial cells (HsAEC) grown at the air/liquid interface (ALI). These cultures were infected at the apical side with one of two different SARS-CoV-2 isolates. Each virus was shown to replicate to high titers for extended periods of time (at least 8 days) and, in particular an isolate with the D614G in the spike (S) protein did so more efficiently at 35{degrees}C than 37{degrees}C. The effect of a selected panel of reference drugs that were added to the culture medium at the basolateral side of the system was explored. Remdesivir, GS-441524 (the parent nucleoside of remdesivir), EIDD-1931 (the parent nucleoside of molnupiravir) and IFN ({beta}1 and {lambda}1) all resulted in dose-dependent inhibition of viral RNA and infectious virus titers collected at the apical side. However, AT-511 (the free base form of AT-527 currently in clinical testing) failed to inhibit viral replication in these in vitro primary cell models. Together, these results provide a reference for further studies aimed at selecting SARS-CoV-2 inhibitors for further preclinical and clinical development.", + "rel_num_authors": 11, + "rel_authors": [ + { + "author_name": "Thuc Nguyen Dan Do", + "author_inst": "Rega Institute - KU Leuven" + }, + { + "author_name": "Kim Donckers", + "author_inst": "Rega Institute - KU Leuven" + }, + { + "author_name": "Laura Vangeel", + "author_inst": "Rega Institute" + }, + { + "author_name": "Arnab K. Chatterjee", + "author_inst": "California Institute for Biochemical Research" + }, + { + "author_name": "Philippe A. Gallay", + "author_inst": "California Institute for Biochemical Research" + }, + { + "author_name": "Michael D. Bobardt", + "author_inst": "California Institute for Biochemical Research" + }, + { + "author_name": "John P. Bilello", + "author_inst": "Gilead Sciences" + }, + { + "author_name": "Tomas Cihlar", + "author_inst": "Gilead Sciences" + }, + { + "author_name": "Steven De Jonghe", + "author_inst": "Rega Institute - KU Leuven" + }, + { + "author_name": "Johan Neyts", + "author_inst": "Rega Institute" + }, + { + "author_name": "Dirk Jochmans", + "author_inst": "REGA Institute - KULeuven" + } + ], "version": "1", "license": "", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2021.03.25.436930", @@ -830417,65 +829065,89 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.21.21253158", - "rel_title": "P1 variant and amino acid mutations at Spike gene identified using Sanger protocol", + "rel_doi": "10.1101/2021.03.18.21253862", + "rel_title": "Self-reported smell and taste recovery in COVID-19 patients: a one-year prospective study", "rel_date": "2021-03-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.21.21253158", - "rel_abs": "SARS-CoV-2 variants, along with vaccination, mark the second year of the pandemic. The spike region is a focal point in COVID-19 pathogenesis, with different amino acid changes potentially modulating vaccine response and some being part of variant signatures. NGS is the standard tool to sequence the virus but limitations of different sources hinders expansion of genomic surveillance in many places. To improve surveillance capability we developed a Sanger based sequencing protocol to obtain coverage of most (>95%) spike gene. Eleven nasopharyngeal swabs collections had RNA extracted for real time PCR diagnosis and leftover RNA had up to 3785 bp sequenced at an ABI3500 using dye termination chemistry of nested PCR products of two reactions of one-step RT-PCR. P1 amino acid mutations signatures were present in 18% (2/11), with 82% (9/11) with three or more additional amino acid changes (GISAID CoVsurver list). Most sequences (86%, 6/7) from 2021 have the E484K, whereas the mutation was not present in samples collected in 2020 (0/4, p=0.015).The swiftness that favorable mutations to the virus may prevail and their potential impact in vaccines and other current interventions need broader surveillance and more public health attention.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.18.21253862", + "rel_abs": "PurposeThe aim of the present study was to estimate the one-year prevalence and recovery rate of self-reported chemosensory dysfunction in a series of subjects with previous mild-to-moderate symptomatic COVID-19.\n\nMethodsProspective study based on the SNOT-22 (item sense of smell or taste) and additional outcomes.\n\nResults268/315 patients (85.1%) completing the survey at baseline also completed the follow-up interview. The 12-months prevalence of self-reported COVID-19 associated chemosensory dysfunction was 21.3% (95% CI: 16.5-26.7%). Of the 187 patients who complained of COVID-19 associated chemosensory dysfunction at baseline, 130 (69.5%; 95% CI 62.4-76.0%) reported complete resolution of smell or taste impairment, 41 (21.9%) reported a decrease in the severity, and 16 (8.6%) reported the symptom was unchanged or worse one year after onset. The risk of persistence was higher for patients reporting a baseline SNOT-22 score > o = 4 (OR=3.32; 95% CI: 1.32-8.36) as well as for those requiring > o = 22 days for a negative swab (OR=2.18; 95% CI: 1.12-4.27).\n\nConclusionA substantial proportion of patients with previous mild-to-moderate symptomatic COVID-19 characterized by new onset of chemosensory dysfunction still complained on altered sense of smell or taste one-year after the onset.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Gabriela Bastos Cabral", - "author_inst": "Adolfo Lutz Institute" + "author_name": "Paolo Boscolo-Rizzo", + "author_inst": "University of Trieste" }, { - "author_name": "Cintia Mayumi Ahagon", - "author_inst": "Adolfo Lutz Institute" + "author_name": "Francesco Guida", + "author_inst": "University of Trieste" }, { - "author_name": "Giselle Ibette Silva Lopez-Lopes", - "author_inst": "Adolfo Lutz Institute" + "author_name": "Jerry Polesel", + "author_inst": "Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano" }, { - "author_name": "Igor Mohamed Hussein", - "author_inst": "Adolfo Lutz Institute" + "author_name": "Alberto Vito Marcuzzo", + "author_inst": "University of Trieste" }, { - "author_name": "Paula Morena Guimaraes", - "author_inst": "Adolfo Lutz Institute" + "author_name": "Paolo Antonucci", + "author_inst": "University of Trieste" }, { - "author_name": "Audrey Cilli", - "author_inst": "Adolfo Lutz Institute" + "author_name": "Vincenzo Capriotti", + "author_inst": "Papa Giovanni XXIII General Hospital, Bergamo" }, { - "author_name": "Valeria Oliveira Silva", - "author_inst": "Adolfo Lutz Institute" + "author_name": "Erica Sacchet", + "author_inst": "University of Trieste" }, { - "author_name": "Maria do Carmo ST Timenetsky", - "author_inst": "Adolfo Lutz Institute" + "author_name": "Fiordaliso Cragnolini", + "author_inst": "University of Trieste" }, { - "author_name": "Ivy de Jesus Alves", - "author_inst": "Adolfo Lutz Institute" + "author_name": "Andrea D'Alessandro", + "author_inst": "University of Trieste" }, { - "author_name": "Andrea GC Bombonatte", - "author_inst": "Adolfo Lutz Institute" + "author_name": "Enrico Zanelli", + "author_inst": "University of Trieste" }, { - "author_name": "Fabiana C Pereira dos Santos", - "author_inst": "Adolfo Lutz Institute" + "author_name": "Riccardo Marzolino", + "author_inst": "University of Trieste" }, { - "author_name": "Luis Fernando de Macedo Brigido", - "author_inst": "Instituto Adolfo Lutz" + "author_name": "Chiara Lazzarin", + "author_inst": "University of Trieste" + }, + { + "author_name": "Margherita Tofanelli", + "author_inst": "University of Trieste" + }, + { + "author_name": "Nicoletta Gardenal", + "author_inst": "University of Trieste" + }, + { + "author_name": "Daniele Borsetto", + "author_inst": "Cambridge University Hospital" + }, + { + "author_name": "Claire Hopkins", + "author_inst": "Guy's and St Thomas' Hospital, London" + }, + { + "author_name": "Luigi Angelo Vaira", + "author_inst": "University of Sassari" + }, + { + "author_name": "Giancarlo Tirelli", + "author_inst": "University of Trieste" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -831985,105 +830657,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.14.21253039", - "rel_title": "Past SARS-CoV-2 infection elicits a strong immune response after a single vaccine dose", + "rel_doi": "10.1101/2021.03.22.21254131", + "rel_title": "The Impact of Vaccination to Control COVID-19 Burden in the United States: A Simulation Modeling Approach", "rel_date": "2021-03-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.14.21253039", - "rel_abs": "We hypothesized that in individuals with previous SARS-CoV-2 infection, the first vaccine dose would work as a booster, eliciting a faster and more intense immune response. We herein describe antibody responses to the first and second doses of Gam-COVID-Vac (SPUTNIK V) vaccine in health personnel of Tucuman, Argentina, with previous COVID-19 and compared it with uninfected personnel. Individuals with anti-SARS-CoV-2 titers at baseline showed significantly higher responses to the first dose than people with no prior history of disease (p <0.0001), with titers higher to those registered after the second dose in the control group, representing a clear secondary antibody response. This suggests that a single dose of SPUTNIK V for people with previous SARS-CoV-2 infection could contribute to a better use of available doses.\n\nOne-Sentence SummaryFirst vaccine dose in subjects with prior COVID19 elicits a higher antibody response than two doses in uninfected individuals", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.22.21254131", + "rel_abs": "IntroductionVaccination programs aim to control the COVID-19 pandemic. However, the relative impacts of vaccine coverage, effectiveness, and capacity in the context of nonpharmaceutical interventions such as mask use and physical distancing on the spread of SARS-CoV-2 are unclear. Our objective was to examine the impact of vaccination on the control of SARS-CoV-2 using our previously developed agent-based simulation model.\n\nMethodsWe applied our agent-based model to replicate COVID-19-related events in 1) Dane County, Wisconsin; 2) Milwaukee metropolitan area, Wisconsin; 3) New York City (NYC). We evaluated the impact of vaccination considering the proportion of the population vaccinated, probability that a vaccinated individual gains immunity, vaccination capacity, and adherence to nonpharmaceutical interventions. The primary outcomes were the number of confirmed COVID-19 cases and the timing of pandemic control, defined as the date after which only a small number of new cases occur. We also estimated the number of cases without vaccination.\n\nResultsThe timing of pandemic control depends highly on vaccination coverage, effectiveness, and adherence to nonpharmaceutical interventions. In Dane County and Milwaukee, if 50% of the population is vaccinated with a daily vaccination capacity of 0.1% of the population, vaccine effectiveness of 90%, and the adherence to nonpharmaceutical interventions is 85%, controlled spread could be achieved by July 2021 and August 2021, respectively versus in March 2022 in both regions without vaccine. If adherence to nonpharmaceutical interventions increases to 70%, controlled spread could be achieved by May 2021 and April 2021 in Dane County and Milwaukee, respectively.\n\nDiscussionIn controlling the spread of SARS-CoV-2, the impact of vaccination varies widely depending not only on effectiveness and coverage, but also concurrent adherence to nonpharmaceutical interventions. The effect of SARS-CoV-2 variants was not considered.\n\nPrimary Funding SourceNational Institute of Allergy and Infectious Diseases", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Rossana Elena Chahla", - "author_inst": "Tucuman Public Healthcare Administration (SIPROSA)" - }, - { - "author_name": "Rodrigo Hernan Tomas-Grau", - "author_inst": "Institute of Applied Molecular and Cellular Medicine. IMMCA (UNT-CONICET-SIPROSA). Tucuman Argentina" - }, - { - "author_name": "Silvia Ines Cazorla", - "author_inst": "Reference Center for Lactobacilli. CERELA (CONICET). Tucuman, Argentina" - }, - { - "author_name": "Diego Ploper", - "author_inst": "Institute of Applied Molecular and Cellular Medicine. IMMCA (UNT-CONICET-SIPROSA). Tucuman Argentina" - }, - { - "author_name": "Esteban Vera Pingitore", - "author_inst": "Institute of Applied Molecular and Cellular Medicine. IMMCA (UNT-CONICET-SIPROSA). Tucuman Argentina" - }, - { - "author_name": "Monica Aguilar Lopez", - "author_inst": "Nestor Kirchner Hospital, Central Public Health laboratory (LSP) (SIPROSA). Tucuman, Argentina." - }, - { - "author_name": "Patricia Aznar VII", - "author_inst": "Nestor Kirchner Hospital, Central Public Health laboratory (LSP) (SIPROSA). Tucuman, Argentina." - }, - { - "author_name": "Maria Elena Alcorta", - "author_inst": "Nestor Kirchner Hospital, Central Public Health laboratory (LSP) (SIPROSA). Tucuman, Argentina." - }, - { - "author_name": "Eva Maria del Mar Velez", - "author_inst": "Faculty of Biochemistry, Chemistry and Pharmacy, National University of Tucuman. Tucuman." - }, - { - "author_name": "Agustin Stagnetto", - "author_inst": "Institute of Applied Molecular and Cellular Medicine. IMMCA (UNT-CONICET-SIPROSA). Tucuman Argentina" - }, - { - "author_name": "Cesar Luis Avila", - "author_inst": "Institute of Applied Molecular and Cellular Medicine. IMMCA (UNT-CONICET-SIPROSA). Tucuman Argentina" - }, - { - "author_name": "Carolina Maldonado Galdeano", - "author_inst": "Reference Center for Lactobacilli. CERELA (CONICET). Tucuman, Argentina" - }, - { - "author_name": "Sergio Benjamin Socias", - "author_inst": "Institute of Applied Molecular and Cellular Medicine. IMMCA (UNT-CONICET-SIPROSA). Tucuman Argentina" - }, - { - "author_name": "Dar Heinze", - "author_inst": "Section of Gastroenterology, Department of Medicine, Center for Regenerative Medicine (CReM), Boston University School of Medicine, Boston, USA" - }, - { - "author_name": "Silvia Adriana Navarro", - "author_inst": "Institute of Applied Molecular and Cellular Medicine. IMMCA (UNT-CONICET-SIPROSA). Tucuman Argentina" - }, - { - "author_name": "Conrado Llapur", - "author_inst": "Nestor Kirchner Hospital, Central Public Health laboratory (LSP) (SIPROSA). Tucuman, Argentina." - }, - { - "author_name": "Dardo Costas", - "author_inst": "Nestor Kirchner Hospital, Central Public Health laboratory (LSP) (SIPROSA). Tucuman, Argentina." + "author_name": "Oguzhan Alagoz", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Isolina Flores", - "author_inst": "Nestor Kirchner Hospital, Central Public Health laboratory (LSP) (SIPROSA). Tucuman, Argentina." + "author_name": "Ajay Sethi", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Gabriela Apfelbaum", - "author_inst": "School of Medicine. Universidad Nacional de Tucuman. Tucuman. Argentina" + "author_name": "Brian Patterson", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Raul Mostoslavsky", - "author_inst": "The Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, USA" + "author_name": "Matthew Churpek", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Gustavo Mostoslavsky", - "author_inst": "Section of Gastroenterology, Department of Medicine, Center for Regenerative Medicine (CReM), Boston University School of Medicine, Boston, USA" + "author_name": "Ghalib Alhanaee", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Gabriela del Valle Perdigon", - "author_inst": "Reference Center for Lactobacilli. CERELA (CONICET). Tucuman, Argentina" + "author_name": "Elizabeth Scaria", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Rosana Chehin", - "author_inst": "Institute of Applied Molecular and Cellular Medicine. IMMCA (UNT-CONICET-SIPROSA). Tucuman ArgentinaCONICET" + "author_name": "Nasia Safdar", + "author_inst": "University of Wisconsin-Madison" } ], "version": "1", @@ -833991,79 +832599,95 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.20.21253819", - "rel_title": "Seroprevalence of anti-SARS-CoV-2 IgG antibody among health care workers of anaesthesia departments from various hospital settings in India", - "rel_date": "2021-03-24", + "rel_doi": "10.1101/2021.03.18.21252686", + "rel_title": "Addressing disruptions in childhood routine immunisation services during the COVID-19 pandemic: perspectives and lessons learned from Liberia, Nepal, and Senegal", + "rel_date": "2021-03-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.20.21253819", - "rel_abs": "BackgroundHealth care workers (HCWs) are the most susceptible group to get COVID-19 infection and this group always need special attention as they are the key human resource to contain this pandemic.\n\nObjectiveTo track down the seroprevalence among a particular group of HCWs working in the anaesthesia department in hospital settings.\n\nStudy designTwo rounds of serosurvey were done to track the dynamicity among the 128 and 164 HCWs participants in the first round and second round, respectively. 5 mL of blood was collected and anti-SARS-CoV-2 IgG antibody was tested in Abbott Architect i1000SR.\n\nResultsThe seroprevalence found in the first and second round was 12.5% and 38.4%, respectively. A significant number (n=61, 77.21%) of seropositivity came from the asymptomatic HCWs group as found in both the survey. There was no significant association among different age, gender and RT-PCR tested groups.\n\nConclusionRoutine diagnosis of COVID-19 should be referred among HCWs to identify and act upon unrecognized SARS-CoV-2 infection.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.18.21252686", + "rel_abs": "The COVID-19 pandemic has inflicted multifaceted disruptions to routine immunisation from global to local levels, affecting every aspect of vaccine supply, access, and demand. Since March 2020, country programmes have implemented a range of strategies to either continue vaccination services during COVID-19 measures like lockdown and/or resume services when risks of SARS-CoV-2 transmission could be appropriately mitigated. Through the Exemplars in Global Health partnership in Liberia, Nepal, and Senegal, we conducted interviews with immunisation programme managers and ministry of health leadership to better understand how they have addressed the myriad vaccination challenges posed by the ongoing pandemic. From establishing alternative modes of service delivery to combatting vaccine distrust and rumours via risk communication campaigns, many routine immunisation programmes have demonstrated how to adapt, resume, and/or maintain vital vaccination efforts during the COVID-19 crisis. Yet millions of children remain un- or under-vaccinated worldwide, and the same programmes striving to implement catch-up services for missed doses and postponed mass campaigns will also soon be tasked with COVID-19 vaccine deployment. As laid bare by the current pandemic, the worlds gains against vaccine-preventable diseases are fragile: enshrined by a delicate global ecosystem of logistics, supply, and procurement, the success of routine immunisation ultimately rests upon dedicated programme staff, the resources and support available to them, and then the trust in and demand for vaccines by their recipients. Our collective lessons learned during COVID-19 offer insights in programme adaptation and resilience that, if prioritised, could strengthen equitable, sustainable vaccine delivery for all populations.\n\nSummary boxO_LIKey message 1: As the COVID-19 pandemic affected routine immunisation services worldwide, country programmes have used a range of mitigation strategies to maintain vaccine delivery and/or resume interrupted programming. Interviews with immunisation programme managers and Ministry of Health staff provided key perspectives and lessons learned on how countries have approached routine immunisation services during the COVID-19 crisis.\nC_LIO_LIKey message 2: Key themes for mitigating COVID-19s effects on routine immunisation included prioritising continued services with strengthened infection prevention control; identifying alternative locations and approaches to providing vaccine services (e.g., conducting door-to-door vaccination if facility-based services were not possible); engaging in effective communications and mobilisation activities, especially to offset misinformation about COVID-19 and vaccines; setting up systems and strategies for reaching children who missed doses amid periods of disruption; and conducting catch-up campaigns as soon as SARS-CoV-2 transmission risks could be minimised.\nC_LIO_LIKey message 3: The ways in which COVID-19 has affected routine immunisation services have varied over time and across settings, underscoring the importance of contextually-tailored mitigation efforts and adaptation given evolving challenges amid an ongoing pandemic. As countries prepare and initiate roll-out COVID-19 vaccines, it will be vital to avoid one-size-fits-all implementation strategies and support the continuance of routine immunisation services through this next phase of COVID-19 response.\nC_LI", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Debaprasad Parai", - "author_inst": "ICMR - Regional Medical Research Centre, Bhubaneswar, India" + "author_name": "Sameer M Dixit", + "author_inst": "Center for Molecular Dynamics Nepal (CMDN), Kathmandu, Nepal" }, { - "author_name": "Hari Ram Choudhary", - "author_inst": "ICMR - Regional Medical Research Centre, Bhubaneswar, India" + "author_name": "Moussa Sarr", + "author_inst": "Institut de Recherche en Sante de Surveillance Epidemiologique et de Formations (IRESSEF), Dakar, Senegal" }, { - "author_name": "Girish Chandra Dash", - "author_inst": "ICMR - Regional Medical Research Centre, Bhubaneswar, India" + "author_name": "Daouda M Gueye", + "author_inst": "Institut de Recherche en Sante de Surveillance Epidemiologique et de Formations (IRESSEF), Dakar, Senegal" }, { - "author_name": "Annalisha Peter", - "author_inst": "ICMR - Regional Medical Research Centre, Bhubaneswar, India" + "author_name": "Kyle Muther", + "author_inst": "Last Mile Health, Monrovia, Liberia" }, { - "author_name": "Dipika Saket", - "author_inst": "Department of Microbiology, ICMR-Regional Medical Research Centre (Dept. of Health Research, Ministry of Health & Family Welfare, Govt. of India), Chandrasekhar" + "author_name": "T Ruston Yarnko", + "author_inst": "Last Mile Health, Monrovia, Liberia" }, { - "author_name": "Ritesh Roy", - "author_inst": "Indian Society of Anaesthesia, Bhubaneswar City Branch, Odisha, India" + "author_name": "Robert A Bednarczyk", + "author_inst": "Rollins School of Public Health, Emory University, Atlanta, Georgia, United States" }, { - "author_name": "Gaurav Agarwal", - "author_inst": "Indian Society of Anaesthesia, Bhubaneswar City Branch, Odisha, India" + "author_name": "Adolphus T Clarke", + "author_inst": "Expanded Programme on Immunisation, Ministry of Health, Monrovia, Liberia" }, { - "author_name": "Saroj Sahoo", - "author_inst": "Indian Society of Anaesthesia, Bhubaneswar City Branch, Odisha, India" + "author_name": "Aliou Diallo", + "author_inst": "Expanded Programme on Immunisation Unit, World Health Organization Country Office, Dakar, Senegal" }, { - "author_name": "Usha Kiran Rout", - "author_inst": "ICMR - Regional Medical Research Centre, Bhubaneswar, India" + "author_name": "Bonheur Dounebaine", + "author_inst": "Rollins School of Public Health, Emory University, Atlanta, Georgia, United States" }, { - "author_name": "Rashmi Ranjan Nanda", - "author_inst": "ICMR - Regional Medical Research Centre, Bhubaneswar, India" + "author_name": "Anna Ellis", + "author_inst": "Rollins School of Public Health, Emory University, Atlanta, Georgia, United States" }, { - "author_name": "Jaya Singh Kshatri", - "author_inst": "ICMR - Regional Medical Research Centre, Bhubaneswar, India" + "author_name": "Nancy Fullman", + "author_inst": "Gates Ventures, Kirkland, Washington, United States" }, { - "author_name": "Srikanta Kanungo", - "author_inst": "ICMR - Regional Medical Research Centre, Bhubaneswar, India" + "author_name": "Nathaniel Gerthe", + "author_inst": "Gates Ventures, Kirkland, Washington, United States" }, { - "author_name": "Subrata Kumar Palo", - "author_inst": "ICMR - Regional Medical Research Centre, Bhubaneswar, India" + "author_name": "Jhalak S Guatam", + "author_inst": "Child Health and Immunization Section, Family Welfare Division, Department of Health Services, Ministry of Health and Population, Kathmandu, Nepal" }, { - "author_name": "Sanghamitra Pati", - "author_inst": "ICMR - Regional Medical Research Centre, Bhubaneswar, India" + "author_name": "Kyra Hester", + "author_inst": "Rollins School of Public Health, Emory University, Atlanta, Georgia, United States" }, { - "author_name": "Dr. Debdutta Bhattacharya", - "author_inst": "ICMR - Regional Medical Research Centre, Bhubaneswar" + "author_name": "Gloria Ikilezi", + "author_inst": "Gates Ventures, Kirkland, Washington, United States" + }, + { + "author_name": "Souleymane Mboup", + "author_inst": "Institut de Recherche en Sante de Surveillance Epidemiologique et de Formations (IRESSEF), Dakar, Senegal" + }, + { + "author_name": "Rajesh Man Rajbhandari", + "author_inst": "Center for Molecular Dynamics Nepal (CMDN), Kathmandu, Nepal" + }, + { + "author_name": "David E Phillips", + "author_inst": "Gates Ventures, Kirkland, Washington, United States" + }, + { + "author_name": "Matthew C Freeman", + "author_inst": "Rollins School of Public Health, Emory University, Atlanta, Georgia, United States" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.03.21.21254047", @@ -836121,51 +834745,23 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.19.21253969", - "rel_title": "Primary care clinical management following self-harm during the first wave of COVID-19 in the UK", + "rel_doi": "10.1101/2021.03.21.21254050", + "rel_title": "Emotional responses toward COVID-19: A longitudinal assessment of age differences", "rel_date": "2021-03-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.19.21253969", - "rel_abs": "BackgroundA substantial reduction in GP-recorded self-harm occurred during the first wave of COVID-19 but effects on primary care management of self-harm are unknown.\n\nAimTo examine the impact of COVID-19 on clinical management within three months of an episode of self-harm.\n\nDesign and settingProspective cohort study using data from the UK Clinical Practice Research Datalink.\n\nMethodWe compared cohorts of patients with an index self-harm episode recorded during a pre-pandemic period (10th March-10th June, 2010-2019) versus the COVID-19 first-wave period (10th March-10th June 2020). Patients were followed up for three months to capture psychotropic medication prescribing, GP/practice nurse consultation and referral to mental health services.\n\nResults48,739 episodes of self-harm were recorded during the pre-pandemic period and 4,238 during the first-wave COVID-19 period. Similar proportions were prescribed psychotropic medication within 3 months in the pre-pandemic (54.0%) and COVID-19 first-wave (54.9%) cohorts. Likelihood of having at least one GP/practice nurse consultation was broadly similar (83.2% vs. 80.3% in the COVID-19 cohort). The proportion of patients referred to mental health services in the COVID-19 cohort (3.4%) was around half of that in the pre-pandemic cohort (6.5%).\n\nConclusionDespite the challenges experienced by primary healthcare teams during the initial COVID-19 wave, prescribing and consultation patterns following self-harm were broadly similar to pre-pandemic levels. However, the reduced likelihood of referral to mental health services warrants attention. Accessible outpatient and community services for people who have self-harmed are required as the COVID-19 crisis recedes and the population faces new challenges to mental health.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.21.21254050", + "rel_abs": "The current study investigates the relation between age and emotional responses and coping strategies at two moments during the spread of COVID-19 in Poland, namely the first peak (March-May 2020) and the second pick (October-December 2020). A sample of 414 individuals between the ages of 18 and 81 were asked to rate the intensity of the shock, sadness, anger, and fear they experienced due to COVID-19 and respond to items from the Brief Cope questionnaire. The present findings demonstrate that anger was consistently less intense among older adults than younger ones. Emotion-focused coping strategies were more commonly used by younger adults than middle-aged or older ones at the first peak of the outbreak; however, this trend had reversed during the second peak of the pandemic, as the older age groups demonstrated a far greater increase in the use of this form of coping. Results indicate a greater ability to use emotional regulation among older adults than younger ones, as the former are less likely to react to a crisis through anger and more able to adapt coping mechanisms to a dynamic environment.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Sarah Steeg", - "author_inst": "University of Manchester" - }, - { - "author_name": "Matthew J Carr", - "author_inst": "University of Manchester" - }, - { - "author_name": "Laszlo Trefan", - "author_inst": "University of Manchester" - }, - { - "author_name": "Darren M Ashcroft", - "author_inst": "University of Manchester" - }, - { - "author_name": "Nav Kapur", - "author_inst": "University of Manchester" - }, - { - "author_name": "Emma Nielsen", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Brian McMillan", - "author_inst": "University of Manchester" - }, - { - "author_name": "Roger Webb", - "author_inst": "University of Manchester" + "author_name": "Marta Malesza", + "author_inst": "University of Economics and Human Sciences in Warsaw" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "primary care research" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2021.03.19.21253425", @@ -838027,135 +836623,39 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.03.20.436259", - "rel_title": "Acriflavine, a clinically aproved drug, inhibits SARS-CoV-2 and other betacoronaviruses", - "rel_date": "2021-03-21", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.20.436259", - "rel_abs": "SO_SCPLOWUMMARYC_SCPLOWThe COVID-19 pandemic caused by SARS-CoV-2 has been socially and economically devastating. Despite an unprecedented research effort, effective therapeutics are still missing to limit severe disease and mortality. Using high-throughput screening, we identified acriflavine as a potent papain-like protease (PLpro) inhibitor. NMR titrations and a co-crystal structure confirm that acriflavine blocks the PLpro catalytic pocket in an unexpected binding mode. We show that the drug inhibits viral replication at nanomolar concentration in cellular models, in vivo in mice and ex vivo in human airway epithelia, with broad range activity against SARS-CoV-2 and other betacoronaviruses. Considering that acriflavine is an inexpensive drug approved in some countries, it may be immediately tested in clinical trials and play an important role during the current pandemic and future outbreaks.", - "rel_num_authors": 29, + "rel_doi": "10.1101/2021.03.19.21253949", + "rel_title": "Cancer services during the COVID-19 pandemic: systematic review of patients' and caregivers' experiences", + "rel_date": "2021-03-20", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.19.21253949", + "rel_abs": "BackgroundCancer patients have faced intersecting crises in the face of COVID-19 pandemic. This review aimed to examine patients and caregivers experiences of accessing cancer services during the COVID-19 pandemic and perceived impact of the pandemic on their psychological wellbeing.\n\nMethodsA protocol-led (CRD42020214906) systematic review was conducted by searching six databases including EMBASE, MEDLINE and CINAHL for articles published in English-language between 1/2020-12/2020. Data were extracted using a pilot-tested, structured data extraction form. Thematic synthesis of data was undertaken and reported as per the PRISMA guideline.\n\nResultsA total of 1110 articles were screened of which 19 studies met the inclusion criteria. Studies originated from 10 different countries including the US, UK, India and China. Several themes were identified which were categorised into seven categories. Postponement and delays in cancer screening and treatment, drug shortages and inadequate nursing care were commonly experienced by patients. Hospital closures, resource constraints, national lockdowns and patient reluctance to use health services because of infection worries contributed to the delay. Financial and social distress, isolation; and spiritual distress due to the uncertainty of rites as well as fulfilment of last wishes were also commonly reported. Caregivers felt anxious about infecting cancer patients with COVID-19.\n\nConclusionsPatients and caregivers experienced extensive impact of COVID-19 on cancer screening, treatment and care, and their own psychological wellbeing. Patient and caregiver views and preferences should be incorporated in ensuring resilient cancer services that can minimise the impact of ongoing and future pandemic on cancer care and mitigate patient fears.\n\nProtocol RegistrationPublished protocol registered with Centre for Review and Dissemination CRD42020214906 (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=214906)", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Valeria Napolitano", - "author_inst": "Helmholtz Zentrum Munchen, Ingolstadter Landstrasse 1, 85764 Neuherberg, Germany" - }, - { - "author_name": "Agnieszka Dabrowska", - "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7a, 30-387 Krakow, Poland; Microbiology Departmen" - }, - { - "author_name": "Kenji Schorpp", - "author_inst": "Helmholtz Zentrum Munchen, Ingolstadter Landstrasse 1, 85764 Neuherberg, Germany" - }, - { - "author_name": "Andre Mourao", - "author_inst": "Helmholtz Zentrum Munchen, Ingolstadter Landstrasse 1, 85764 Neuherberg, Germany" - }, - { - "author_name": "Emilia Barreto-Duran", - "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7a, 30-387 Krakow, Poland." - }, - { - "author_name": "Malgorzata Benedyk", - "author_inst": "Microbiology Department, Faculty of Biochemistry, Biophysics and Biotechnology, Jagiellonian University, Gronostajowa 7, 30-387 Krakow, Poland." - }, - { - "author_name": "Pawel Botwina", - "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7a, 30-387 Krakow, Poland; Microbiology Departmen" - }, - { - "author_name": "Stefanie Brandner", - "author_inst": "Helmholtz Zentrum Munchen, Ingolstadter Landstrasse 1, 85764 Neuherberg, Germany" - }, - { - "author_name": "Mark Bostock", - "author_inst": "Helmholtz Zentrum Munchen, Ingolstadter Landstrasse 1, 85764 Neuherberg, Germany; Bavarian NMR Center, Department of Chemistry, Technical University of Munich, " - }, - { - "author_name": "Yuliya Chykunova", - "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7a, 30-387 Krakow, Poland." - }, - { - "author_name": "Anna Czarna", - "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7a, 30-387 Krakow, Poland." - }, - { - "author_name": "Grzegorz Dubin", - "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7a, 30-387 Krakow, Poland." - }, - { - "author_name": "Tony Frohlich", - "author_inst": "Helmholtz Zentrum Munchen, Ingolstadter Landstrasse 1, 85764 Neuherberg, Germany" - }, - { - "author_name": "Michael Hoelscher", - "author_inst": "Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Leopoldstrasse 5, 80802 Munich, Germany; German Center for Infection Res" - }, - { - "author_name": "Malwina Jedrysik", - "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7a, 30-387 Krakow, Poland." - }, - { - "author_name": "Alex Matsuda", - "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7a, 30-387 Krakow, Poland." - }, - { - "author_name": "Katarzyna Owczarek", - "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7a, 30-387 Krakow, Poland." - }, - { - "author_name": "Magdalena Pachota", - "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7a, 30-387 Krakow, Poland; Microbiology Departmen" - }, - { - "author_name": "Oliver Plettenburg", - "author_inst": "Helmholtz Zentrum Munchen, Ingolstadter Landstrasse 1, 85764 Neuherberg, Germany" - }, - { - "author_name": "Jan Potempa", - "author_inst": "Microbiology Department, Faculty of Biochemistry, Biophysics and Biotechnology, Jagiellonian University, Gronostajowa 7, 30-387 Krakow, Poland." - }, - { - "author_name": "Ina Rothenaigner", - "author_inst": "Helmholtz Zentrum Munchen, Ingolstadter Landstrasse 1, 85764 Neuherberg, Germany" - }, - { - "author_name": "Florian Schlauderer", - "author_inst": "Helmholtz Zentrum Munchen, Ingolstadter Landstrasse 1, 85764 Neuherberg, Germany" - }, - { - "author_name": "Artur Szczepanski", - "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7a, 30-387 Krakow, Poland; Microbiology Departmen" - }, - { - "author_name": "Kristin Greve-Isdahl Mohn", - "author_inst": "Haukeland University Hospital, Bergen, Norway" - }, - { - "author_name": "Bjorn Blomberg", - "author_inst": "Haukeland University Hospital, Bergen, Norway" + "author_name": "Symran Dhada", + "author_inst": "University of Birmingham" }, { - "author_name": "Michael Sattler", - "author_inst": "Helmholtz Zentrum Munchen, Ingolstadter Landstrasse 1, 85764 Neuherberg, Germany; Bavarian NMR Center, Department of Chemistry, Technical University of Munich, " + "author_name": "Derek Stewart", + "author_inst": "Qatar University" }, { - "author_name": "Kamyar Hadian", - "author_inst": "Helmholtz Zentrum Munchen, Ingolstadter Landstrasse 1, 85764 Neuherberg, Germany" + "author_name": "Ejaz Cheema", + "author_inst": "University of Birmingham" }, { - "author_name": "Grzegorz Maria Popowicz", - "author_inst": "Helmholtz Zentrum Munchen, Ingolstadter Landstrasse 1, 85764 Neuherberg, Germany; Bavarian NMR Center, Department of Chemistry, Technical University of Munich, " + "author_name": "Muhammed Abdul Hadi", + "author_inst": "University of Birmingham" }, { - "author_name": "Krzysztof Pyrc", - "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7a, 30-387 Krakow, Poland." + "author_name": "Vibhu Paudyal", + "author_inst": "University of Birmingham" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nc", + "type": "PUBLISHAHEADOFPRINT", + "category": "oncology" }, { "rel_doi": "10.1101/2021.03.19.21253962", @@ -840297,75 +838797,347 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.16.21252988", - "rel_title": "Targeted Hybridization Capture of SARS-CoV-2 and Metagenomics Enables Genetic Variant Discovery and Nasal Microbiome Insights", + "rel_doi": "10.1101/2021.03.19.21253986", + "rel_title": "Collaborative Cohort of Cohorts for COVID-19 Research (C4R) Study: Study Design", "rel_date": "2021-03-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.16.21252988", - "rel_abs": "The emergence of novel SARS-CoV-2 genetic variants that may alter viral fitness highlights the urgency of widespread next-generation sequencing (NGS) surveillance. To profile genetic variants, we developed and clinically validated a hybridization capture SARS-CoV-2 NGS assay, integrating novel methods for panel design using dsDNA biotin-labeled probes, and built accompanying software. The positive and negative percent agreement were defined in comparison to an orthogonal RT-PCR assay (PPA and NPA: both 96.7%). The limit of detection was established to be 800 copies/ml with an average fold-enrichment of 46,791x. We identified novel 107 mutations, including 24 in the functionally-important spike protein. Further, we profiled the full nasopharyngeal microbiome using metagenomics and found overrepresentation of 7 taxa and macrolide resistance in SARS-CoV-2-positive patients. This hybrid capture NGS assay, coupled with optimized software, is a powerful approach to detect and comprehensively map SARS-CoV-2 genetic variants for tracking viral evolution and guiding vaccine updates.\n\nTEASERThis is the first target hybridization capture-based NGS assay to detect SARS-CoV-2 genetic variants for tracking viral evolution.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.19.21253986", + "rel_abs": "The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults at risk for coronavirus disease 2019 (COVID-19) comprising 14 established United States (US) prospective cohort studies. For decades, C4R cohorts have collected extensive data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R will link this pre-COVID phenotyping to information on SARS-CoV-2 infection and acute and post-acute COVID-related illness. C4R is largely population-based, has an age range of 18-108 years, and broadly reflects the racial, ethnic, socioeconomic, and geographic diversity of the US. C4R is ascertaining severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and COVID-19 illness using standardized questionnaires, ascertainment of COVID-related hospitalizations and deaths, and a SARS-CoV-2 serosurvey via dried blood spots. Master protocols leverage existing robust retention rates for telephone and in-person examinations, and high-quality events surveillance. Extensive pre-pandemic data minimize referral, survival, and recall bias. Data are being harmonized with research-quality phenotyping unmatched by clinical and survey-based studies; these will be pooled and shared widely to expedite collaboration and scientific findings. This unique resource will allow evaluation of risk and resilience factors for COVID-19 severity and outcomes, including post-acute sequelae, and assessment of the social and behavioral impact of the pandemic on long-term trajectories of health and aging.", + "rel_num_authors": 82, "rel_authors": [ { - "author_name": "Dorottya Nagy-Szakal", - "author_inst": "Biotia, Inc., SUNY Downstate Health Sciences University, The Department Cell Biology/College of Medicine" + "author_name": "Elizabeth C Oelsner", + "author_inst": "Columbia University Irving Medical Center" }, { - "author_name": "Mara Couto-Rodriguez", - "author_inst": "Biotia, Inc." + "author_name": "Norinna Bai Allen", + "author_inst": "Northwestern University" }, { - "author_name": "Heather L. Wells", - "author_inst": "Biotia, Inc." + "author_name": "Tauqueer Ali", + "author_inst": "University of Oklahoma Health Sciences Center" }, { - "author_name": "Joseph E. Barrows", - "author_inst": "Biotia, Inc." + "author_name": "Pramod Anugu", + "author_inst": "University of Mississippi Medical Center" }, { - "author_name": "Marilyne Debieu", - "author_inst": "Biotia, Inc." + "author_name": "Howard Andrews", + "author_inst": "Columbia University" }, { - "author_name": "Kristin D. Butcher", - "author_inst": "Twist Bioscience" + "author_name": "Alyssa Asaro", + "author_inst": "University of Colorado Anschutz Medical Campus" }, { - "author_name": "Siyuan Chen", - "author_inst": "Twist Bioscience" + "author_name": "Pallavi P Balte", + "author_inst": "Columbia University" + }, + { + "author_name": "R Graham Barr", + "author_inst": "Columbia University" }, { - "author_name": "Agnes T. Berki", - "author_inst": "Caldwell University, The School of Natural Sciences, College of Natural, Behavioral and Health Sciences" + "author_name": "Alain Bertoni", + "author_inst": "Wake Forest School of Medicine" }, { - "author_name": "Courteny N. Hager", - "author_inst": "Biotia, Inc." + "author_name": "Jessica Bon", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Robert J. Boorstein", - "author_inst": "Lenco Diagnostic Laboratories, Inc." + "author_name": "Rebekah Boyle", + "author_inst": "University of Vermont" }, { - "author_name": "Mariah K. Taylor", - "author_inst": "The University of Tennessee Health Science Center" + "author_name": "Arunee A Chang", + "author_inst": "University of California San Francisco" }, { - "author_name": "Colleen B. Jonsson", - "author_inst": "The University of Tennessee Health Science Center" + "author_name": "Grace Chen", + "author_inst": "National Jewish Health" }, { - "author_name": "Christopher E. Mason", - "author_inst": "Biotia, Inc., Tri-Institutional Computational Biology & Medicine Program, The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Bio" + "author_name": "Shelley A Cole", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Josef Coresh", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Elaine Cornell", + "author_inst": "University of Vermont" + }, + { + "author_name": "Adolfo Correa", + "author_inst": "University of Mississippi Medical Center" + }, + { + "author_name": "David Couper", + "author_inst": "University of North Carolina" + }, + { + "author_name": "Mary Cushman", + "author_inst": "University of Vermont" + }, + { + "author_name": "Ryan T Demmer", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Mitchell S Elkind", + "author_inst": "Columbia University" + }, + { + "author_name": "Aaron R Folsom", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Amanda M Fretts", + "author_inst": "University of Washington" + }, + { + "author_name": "Kelley Pettee Gabriel", + "author_inst": "University of Alabama at Birmingham" + }, + { + "author_name": "Linda Gallo", + "author_inst": "San Diego State University" + }, + { + "author_name": "Jose Gutierrez Contreras", + "author_inst": "Columbia University" + }, + { + "author_name": "Meilan K Han", + "author_inst": "University of Michigan" + }, + { + "author_name": "Joel M Henderson", + "author_inst": "Boston University" + }, + { + "author_name": "Virginia J Howard", + "author_inst": "University of Alabama at Birmingham" + }, + { + "author_name": "Carmen R Isasi", + "author_inst": "Albert Einstein College of Medicine" + }, + { + "author_name": "David R Jacobs Jr.", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Suzanne E Judd", + "author_inst": "University of Alabama at Birmingham" + }, + { + "author_name": "Debora Kamin Mukaz", + "author_inst": "University of Vermont" + }, + { + "author_name": "Alka M Kanaya", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Namratha R Kandula", + "author_inst": "Northwestern University" + }, + { + "author_name": "Robert C Kaplan", + "author_inst": "Albert Einstein College of Medicine" + }, + { + "author_name": "Akshaya Krishnaswamy", + "author_inst": "Columbia University" + }, + { + "author_name": "Gregory L Kinney", + "author_inst": "University of Colorado Anschutz Medical Campus" + }, + { + "author_name": "Anna Kucharska-Newton", + "author_inst": "University of North Carolina" + }, + { + "author_name": "Joyce S Lee", + "author_inst": "University of Colorado Anschutz Medical Campus" + }, + { + "author_name": "Cora E Lewis", + "author_inst": "University of Alabama at Birmingham" + }, + { + "author_name": "Deborah A Levine", + "author_inst": "University of Michigan" + }, + { + "author_name": "Emily B Levitan", + "author_inst": "University of Alabama at Birmingham" + }, + { + "author_name": "Bruce Levy", + "author_inst": "Brigham and Women's Hospital" + }, + { + "author_name": "Barry Make", + "author_inst": "National Jewish Health" + }, + { + "author_name": "Kimberly Malloy", + "author_inst": "University of Oklahoma Health Sciences Center" + }, + { + "author_name": "Jennifer J Manly", + "author_inst": "Columbia University Irving Medical Center" + }, + { + "author_name": "Katie A Meyer", + "author_inst": "University of North Carolina" + }, + { + "author_name": "Yuan-I Min", + "author_inst": "University of Mississippi Medical Center" + }, + { + "author_name": "Matthew Moll", + "author_inst": "Brigham and Women's Hospital" + }, + { + "author_name": "Wendy C Moore", + "author_inst": "Wake Forest School of Medicine" + }, + { + "author_name": "Dave Mauger", + "author_inst": "Pennsylvania State University" }, { - "author_name": "Niamh B. O'Hara", - "author_inst": "Biotia, Inc., Jacobs Technion-Cornell Institute, Cornell Tech" + "author_name": "Victor E Ortega", + "author_inst": "Wake Forest School of Medicine" + }, + { + "author_name": "Priya Palta", + "author_inst": "Columbia University" + }, + { + "author_name": "Monica M Parker", + "author_inst": "New York State Department of Health" + }, + { + "author_name": "Wanda Phipatanakul", + "author_inst": "Boston Childrens Hospital" + }, + { + "author_name": "Wendy Post", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Bruce M Psaty", + "author_inst": "University of Washington" + }, + { + "author_name": "Elizabeth A Regan", + "author_inst": "National Jewish Health" + }, + { + "author_name": "Kimberly Ring", + "author_inst": "University of North Carolina" + }, + { + "author_name": "Veronique L Roger", + "author_inst": "Division of Intramural Research, National Heart Lung and Blood Institute of the National Institutes of Health" + }, + { + "author_name": "Jerome I Rotter", + "author_inst": "The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center" + }, + { + "author_name": "Tatjana Rundek", + "author_inst": "University of Miami" + }, + { + "author_name": "Ralph L Sacco", + "author_inst": "University of Miami" + }, + { + "author_name": "Michael Schembri", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "David A Schwartz", + "author_inst": "University of Colorado Anschutz Medical Campus" + }, + { + "author_name": "Sudha Seshadri", + "author_inst": "UT Health San Antonio" + }, + { + "author_name": "James M Shikany", + "author_inst": "University of Alabama at Birmingham" + }, + { + "author_name": "Mario Sims", + "author_inst": "University of Mississippi Medical Center" + }, + { + "author_name": "Karen D Hinckley Stukovsky", + "author_inst": "University of Washington" + }, + { + "author_name": "Gregory A Talavera", + "author_inst": "San Diego State University" + }, + { + "author_name": "Russell P Tracy", + "author_inst": "University of Vermont" + }, + { + "author_name": "Jason G Umans", + "author_inst": "Georgetown University" + }, + { + "author_name": "Ramachandran S Vasan", + "author_inst": "Boston University" + }, + { + "author_name": "Karol Watson", + "author_inst": "UCLA" + }, + { + "author_name": "Sally E Wenzel", + "author_inst": "University of Pittsburgh" + }, + { + "author_name": "Karen Winters", + "author_inst": "University of Mississippi Medical Center" + }, + { + "author_name": "Prescott G Woodruff", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Vanessa Xanthakis", + "author_inst": "Boston University" + }, + { + "author_name": "Ying Zhang", + "author_inst": "University of Oklahoma Health Sciences Center" + }, + { + "author_name": "Yiyi Zhang", + "author_inst": "Columbia University" + }, + { + "author_name": "- The C4R Investigators", + "author_inst": "" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.03.19.21253974", @@ -841867,37 +840639,49 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.17.21250449", - "rel_title": "The effect of in-person primary and secondary school instruction on county-level SARS-CoV-2 spread in Indiana", + "rel_doi": "10.1101/2021.03.16.21253743", + "rel_title": "\"This is about the coolest thing I've ever seen is that you just showed right up.\" COVID-19 testing and vaccine acceptability among homeless-experienced adults: Qualitative data from two samples", "rel_date": "2021-03-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.17.21250449", - "rel_abs": "BackgroundTo determine the county-level effect of in-person primary and secondary school reopening on daily cases of SARS-CoV-2 in Indiana.\n\nMethodsThis is a county-level population-based study using a panel data regression analysis of the proportion of in-person learning to evaluate an association with community-wide daily new SARS-CoV-2 cases. The study period was July 12-October 6, 2020. We included 73 out of 92 (79.3%) Indiana counties in the analysis, accounting for 85.7% of school corporations and 90.6% of student enrollement statewide. The primary exposure was the proportion of students returning to in-person instruction. The primary outcome was the daily new SARS-CoV-2 cases per 100,000 residents at the county level.\n\nResultsThere is a statistically significant relationship between the proportion of students attending K-12 schools in-person and the county level daily cases of SARS-CoV-2 28 days later. For all ages, the coefficient of interest ({beta}) is estimated at 3.36 (95% CI: 1.91--4.81; p < 0.001). This coefficient represents the effect of a change the proportion of students attending in-person on new daily cases 28 days later. For example, a 10 percentage point increase in K-12 students attending school in-person is associated with a daily increase in SARS-CoV-2 cases in the county equal to 0.336 cases/100,000 residents of all ages.\n\nConclusionIn-person primary and secondary school is associated with a statistically significant but proportionally small increase in the spread of SARS-CoV-2 cases.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.16.21253743", + "rel_abs": "BackgroundHomeless-experienced populations are at increased risk of exposure to SARS CoV-2 due to their living environments and face increased risk of severe COVID-19 disease due to underlying health conditions. Little is known about COVID-19 testing and vaccination acceptability among homeless-experienced populations.\n\nObjectiveTo understand the facilitators and barriers to COVID-19 testing and vaccine acceptability among homeless-experienced adults.\n\nDesignWe conducted in-depth interviews with participants from July-October 2020. We purposively recruited participants from 1) a longitudinal cohort of homeless-experienced older adults in Oakland, CA (n=37) and 2) a convenience sample of people (n=57) during a mobile outreach COVID-19 testing event in San Francisco.\n\nParticipantsAdults with current or past experience of homelessness.\n\nApproachWe asked participants about their experiences with and attitudes towards COVID-19 testing and their perceptions of COVID-19 vaccinations. We used participant observation techniques to document the interactions between testing teams and those approached for testing. We audio-recorded, transcribed and content analyzed all interviews and identified major themes and subthemes.\n\nKey ResultsParticipants found incentivized COVID-19 testing administered in unsheltered settings and supported by community health outreach workers (CHOWs) to be acceptable. The majority of participants expressed positive inclination toward vaccine acceptability, citing a desire to return to routine life and civic responsibility. Those who expressed hesitancy cited a desire to see trial data, concerns that vaccines included infectious materials, and mistrust of the government.\n\nConclusionsParticipants expressed positive evaluations of the incentivized, mobile COVID-19 testing supported by CHOWs in unsheltered settings. The majority of participants expressed positive inclination toward vaccination. Vaccine hesitancy concerns must be addressed when designing vaccine delivery strategies that overcome access challenges. Based on the successful implementation of COVID-19 testing, we recommend mobile delivery of vaccines using trusted CHOWs to address concerns and facilitate wider access to and uptake of the COVID vaccine.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Gabriel T Bosslet", - "author_inst": "Indiana University" + "author_name": "Kelly R Knight", + "author_inst": "Department of Humanities and Social Sciences, University of California, San Francisco; UCSF Center for Vulnerable Populations at Zuckerberg San Francisco Genera" }, { - "author_name": "Jeong Joon Jang", - "author_inst": "Indiana University" + "author_name": "Michael R Duke", + "author_inst": "UCSF Center for Vulnerable Populations at Zuckerberg San Francisco General Hospital and Trauma Center; UCSF Benioff Homelessness and Housing Initiative" }, { - "author_name": "Rebekah Roll", - "author_inst": "Indiana University" + "author_name": "Caitlin A Carey", + "author_inst": "UCSF Center for Vulnerable Populations at Zuckerberg San Francisco General Hospital and Trauma Center; UCSF Benioff Homelessness and Housing Initiative" }, { - "author_name": "Mark Sperling", - "author_inst": "Indiana University Northwest" + "author_name": "Graham Pruss", + "author_inst": "UCSF Center for Vulnerable Populations at Zuckerberg San Francisco General Hospital and Trauma Center; UCSF Benioff Homelessness and Housing Initiative" }, { - "author_name": "Babar Khan", - "author_inst": "Indiana University" + "author_name": "Cheyenne M Garcia", + "author_inst": "UCSF Center for Vulnerable Populations at Zuckerberg San Francisco General Hospital and Trauma Center; UCSF Benioff Homelessness and Housing Initiative" + }, + { + "author_name": "Marguerita Lightfoot", + "author_inst": "UCSF Center for Vulnerable Populations at Zuckerberg San Francisco General Hospital and Trauma Center; UCSF Benioff Homelessness and Housing Initiative; Divisio" + }, + { + "author_name": "Elizabeth Imbert", + "author_inst": "Division of HIV, ID and Global Medicine, Department of Medicine, University of California, San Francisco at Zuckerberg San Francisco General Hospital and Trauma" + }, + { + "author_name": "Margot B Kushel", + "author_inst": "UCSF Center for Vulnerable Populations at Zuckerberg San Francisco General Hospital and Trauma Center; UCSF Benioff Homelessness and Housing Initiative" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -843737,41 +842521,129 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.15.21253589", - "rel_title": "A bibliometric analysis of COVID-19 research in Africa", + "rel_doi": "10.1101/2021.03.15.21253653", + "rel_title": "Epidemiological and clinical insights from SARS-CoV-2 RT-PCR cycle amplification values", "rel_date": "2021-03-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.15.21253589", - "rel_abs": "BackgroundThe ongoing COVID-19 pandemic has led to an unprecedented global research effort to build a body of knowledge that can inform mitigation strategies. We carried out a bibliometric analysis to describe the COVID-19 research output in Africa.\n\nMethodsWe searched for articles published between 1st December 2019 and 3rd January 2021 from various databases including PubMed, African Journals Online, MedRxiv, BioRxiv, Collabovid, the World Health Organisation global research database and Google for grey literature. Editorial type publications and papers reporting original research done in Africa and were included. Data analysis was done using Microsoft Excel.\n\nResultsA total of 1296 articles were retrieved. 46.6% were primary research articles, 48.6% were editorials type articles while 4.6% were secondary research articles. 20.3% articles used the entire continent of Africa as their study setting while South Africa (15.4%) was the most common country focused setting. 90.3% of the articles had at least one African researcher as author, 78.5% had an African researcher as first author, while 63.5% had an African researcher as last author. The University of Cape Town tops the list with the greatest number of first and last authors. Over 13% of the articles were published in MedRxiv and of the studies that declared funding, the Wellcome Trust was the top funding body. The most common research topics include \"country preparedness and response\" (24.9%) and \"the direct and indirect health impacts of the pandemic\" (21.6%). However, only 1.0% of articles focus on therapeutics and vaccines.\n\nConclusionsThis study sheds light on the contribution of African researchers to COVID-19 research in Africa and highlights Africas existing capacity to carry out research that addresses local problems. However, the uneven distribution of research productivity amongst African countries emphasizes the need for increased investment where needed.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.15.21253653", + "rel_abs": "The SARS-CoV-2 pandemic has led to an unprecedented daily use of molecular RT-PCR tests. These tests are interpreted qualitatively for diagnosis, and the relevance of the test result intensity, i.e. the number of amplification cycles (Ct), is debated because of strong potential biases. We analyze a national database of tests performed on more than 2 million individuals between January and November 2020. Although we find Ct values to vary depending on the testing laboratory or the assay used, we detect strong significant trends with patient age, number of days after symptoms onset, or the state of the epidemic (the temporal reproduction number) at the time of the test. These results suggest that Ct values can be used to improve short-term predictions for epidemic surveillance.", + "rel_num_authors": 28, "rel_authors": [ { - "author_name": "Fatuma Hassan Guleid", - "author_inst": "KEMRI-WELLCOME TRUST" + "author_name": "Samuel Alizon", + "author_inst": "MIVEGEC, CNRS, IRD, University of Montpellier" }, { - "author_name": "Robinson Oyando", - "author_inst": "KEMRI-Wellcome Trust Research Programme" + "author_name": "Christian Selinger", + "author_inst": "MIVEGEC, CNRS, IRD, University of Montpellier" }, { - "author_name": "Evelyn Kabia", - "author_inst": "KEMRI-Wellcome Trust Research Programme" + "author_name": "Mircea T Sofonea", + "author_inst": "MIVEGEC, CNRS, IRD, University of Montpellier" }, { - "author_name": "Audrey Mumbi", - "author_inst": "KEMRI-Wellcome Trust Research Programme" + "author_name": "Stephanie Haim-Boukobza", + "author_inst": "Laboratoire CERBA, Saint-Ouen-L'Aumone, France" }, { - "author_name": "Samuel Akech", - "author_inst": "KEMRI-Wellcome Trust Research Programme" + "author_name": "Jean-Marc Giannoli", + "author_inst": "BIOGROUP, Scientific Direction, France" }, { - "author_name": "Edwine Barasa", - "author_inst": "KEMRI-Wellcome Trust Research Programme" + "author_name": "Laetitia Ninove", + "author_inst": "Unite des Virus emergents (UVE: Aix-Marseille Univ-IRD 190-Inserm 1207-IHU Mediterranee Infection), Marseille, France" + }, + { + "author_name": "Sylvie Pillet", + "author_inst": "Laboratoire des agents infectieux et d'hygiene, CHU de Saint-Etienne, France" + }, + { + "author_name": "Thibault Vincent", + "author_inst": "Laboratoire de Virologie, CHU Rennes, France" + }, + { + "author_name": "Alexis de Rougemont", + "author_inst": "Laboratory of Virology, University Hospital of Dijon, F-21000, Dijon, France" + }, + { + "author_name": "Camille Tumiotto", + "author_inst": "Univ. Bordeaux, CNRS-UMR 5234, CHU Bordeaux, Virology Department, F-33000, Bordeaux, France" + }, + { + "author_name": "Morgane Solis", + "author_inst": "CHU de Strasbourg, Laboratoire de Virologie, Strasbourg, France / Universite de Strasbourg, INSERM, IRM UMR_S 1109, Strasbourg, France" + }, + { + "author_name": "Robin Stephan", + "author_inst": "Laboratoire de Microbiologie, CHU Nimes, France" + }, + { + "author_name": "Celine Bressollette-Bodin", + "author_inst": "Nantes Universite, CHU Nantes, Inserm, Centre de Recherche en Transplantation et Immunologie, UMR 1064, ITUN ; CHU Nantes, Service de Virologie ; CHU Nantes, C" + }, + { + "author_name": "Maud Salmona", + "author_inst": "Laboratoire de Virologie, Hopital Saint Louis, APHP, INSERM U976, equipe INSIGHT, Universite de Paris, France" + }, + { + "author_name": "Anne-Sophie L'Honneur", + "author_inst": "Assistance Publique-Hopitaux de Paris, Hopital Cochin, Service de Virologie, France" + }, + { + "author_name": "Sylvie Behillil", + "author_inst": "National Reference Center for Respiratory Viruses, Molecular Genetics of RNA Viruses, UMR 3569 CNRS, University of Paris, Institut Pasteur, Paris, France." + }, + { + "author_name": "Caroline Lefeuvre", + "author_inst": "Departement des Agents Infectieux, Laboratoire de Virologie, CHU d'Angers, Angers, France et Laboratoire HIFIH, UPRES EA 3859, Universite d'Angers, Angers, Fra" + }, + { + "author_name": "Julia Dina", + "author_inst": "Normandie Univ, UNICAEN, UNIROUEN, GRAM 2.0, 14000 Caen, France, Caen University Hospital, Department of Virology, F 14000 Caen, France" + }, + { + "author_name": "Sebastien Hantz", + "author_inst": "CHU Limoges, Laboratoire de Bacteriologie-Virologie-Hygiene, F-87000 Limoges, France et Univ. Limoges, RESINFIT, U 1092, F-87000 Limoges, France" + }, + { + "author_name": "Cedric Hartard", + "author_inst": "Laboratoire de Virologie, CHRU de Nancy Brabois, Vandoeuvre-les-Nancy, France ; Universite de Lorraine, CNRS, LCPME, F-54000, Nancy, France" + }, + { + "author_name": "David Veyer", + "author_inst": "Laboratoire de Virologie, Service de Microbiologie, hopital europeen Georges Pompidou, Assistance Publique-Hopitaux de Paris et Unite de Genomique Fonctionnelle" + }, + { + "author_name": "HeloIse M Delagreverie", + "author_inst": "AP-HP, Hopital Avicenne, Laboratoire de microbiologie clinique, Bobigny, France" + }, + { + "author_name": "Slim Fourati", + "author_inst": "Henri Mondor Hospital, virology department, France" + }, + { + "author_name": "Benoit Visseaux", + "author_inst": "Universite de Paris, Inserm, UMR 1137 IAME et Laboratoire de Virologie, Hopital Bichat Claude Bernard, AP-HP, Paris, France" + }, + { + "author_name": "Cecile Henquell", + "author_inst": "Service de Virologie medicale, 3IHP, CHU Clermont-Ferrand, France" + }, + { + "author_name": "Bruno Lina", + "author_inst": "CNR des virus des infections respiratoires (dont la Grippe), Institut des Agents Infectieux, Hopital de la Croix Rousse, HCL, Lyon, France" + }, + { + "author_name": "Vincent Foulougne", + "author_inst": "Laboratoire de Virologie, CHU de Montpellier, France" + }, + { + "author_name": "Sonia Burrel", + "author_inst": "Sorbonne Universite, INSERM U1136, Institut Pierre Louis d'Epidemiologie et de Sante Publique (IPLESP), AP-HP, Hopital Pitie-Salpetriere, Service de Virologie, " } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -845447,79 +844319,99 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.14.21253564", - "rel_title": "Show us the Data: Global COVID-19 Wastewater Monitoring Efforts, Equity, and Gaps", + "rel_doi": "10.1101/2021.03.17.435802", + "rel_title": "Characterisation of a novel ACE2-based therapeutic with enhanced rather than reduced activity against SARS-CoV2 variants", "rel_date": "2021-03-17", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.14.21253564", - "rel_abs": "A year since the declaration of the global coronavirus disease 2019 (COVID-19) pandemic there were over 110 million cases and 2.5 million deaths. Learning from methods to track community spread of other viruses such as poliovirus, environmental virologists and those in the wastewater based epidemiology (WBE) field quickly adapted their existing methods to detect SARS-CoV-2 RNA in wastewater. Unlike COVID-19 case and mortality data, there was not a global dashboard to track wastewater monitoring of SARS-CoV-2 RNA worldwide. This study provides a one year review of the \"COVIDPoops19\" global dashboard of universities, sites, and countries monitoring SARS-CoV-2 RNA in wastewater. Methods to assemble the dashboard combined standard literature review, direct submissions, and daily, social media keyword searches. Over 200 universities, 1,000 sites, and 55 countries with 59 dashboards monitor wastewater for SARS-CoV-2 RNA. However, monitoring is primarily in high-income countries (65%) with less access to this valuable tool in low and middle income countries (35%). Data are not widely shared publicly or accessible to researchers to further inform public health actions, perform meta-analysis, better coordinate, and determine equitable distribution of monitoring sites. For WBE to be used to its full potential during COVID-19 and beyond, show us the data.", - "rel_num_authors": 15, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.17.435802", + "rel_abs": "The human angiotensin-converting enzyme 2 acts as the host cell receptor for SARS-CoV-2 and the other members of the Coronaviridae family SARS-CoV-1 and HCoV-NL63. Here we report the biophysical properties of the SARS-CoV-2 spike variants D614G, B.1.1.7 and B.1.351 with affinities to the ACE2 receptor and infectivity capacity, revealing weaknesses in the developed neutralising antibody approaches. Furthermore, we report a pre-clinical characterisation package for a soluble receptor decoy engineered to be catalytically inactive and immunologically inert, with broad neutralisation capacity, that represents an attractive therapeutic alternative in light of the mutational landscape of COVID-19. This construct efficiently neutralised four SARS-CoV-2 variants of concern. The decoy also displays antibody-like biophysical properties and manufacturability, strengthening its suitability as a first-line treatment option in prophylaxis or therapeutic regimens for COVID-19 and related viral infections.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Colleen C Naughton", - "author_inst": "University of California Merced" + "author_name": "Mathieu Ferrari", + "author_inst": "Autolus Ltd" }, { - "author_name": "Fernando A Roman Jr.", - "author_inst": "University of California Merced" + "author_name": "Leila Mekkaoui", + "author_inst": "Autolus Ltd" }, { - "author_name": "Ana Grace F. Alvarado", - "author_inst": "University of California Merced" + "author_name": "F. Tudor Ilca", + "author_inst": "Autolus Ltd" }, { - "author_name": "Arianna Q. Tariqi", - "author_inst": "University of California Merced" + "author_name": "Zulaikha Akbar", + "author_inst": "Autolus Ltd" }, { - "author_name": "Matthew A. Deeming", - "author_inst": "University of California Merced" + "author_name": "Reyisa Bughda", + "author_inst": "Autolus Ltd" }, { - "author_name": "Kyle Bibby", - "author_inst": "University of Notre Dame" + "author_name": "Katarina Lamb", + "author_inst": "Autolus Ltd" }, { - "author_name": "Aaron Bivins", - "author_inst": "Ohio State University" + "author_name": "Katarzyna Ward", + "author_inst": "Autolus Ltd" }, { - "author_name": "Joan B. Rose", - "author_inst": "Michigan State University" + "author_name": "Farhaan Parekh", + "author_inst": "Autolus Ltd" }, { - "author_name": "Gertjan Medema", - "author_inst": "KWR Water Research Institute" + "author_name": "Rajeev Karattil", + "author_inst": "Autolus Ltd" }, { - "author_name": "Warish Ahmed", - "author_inst": "CSIRO" + "author_name": "Christopher Allen", + "author_inst": "Autolus Ltd" }, { - "author_name": "Panagis Katsivelis", - "author_inst": "Venthic Technologies" + "author_name": "Philip Wu", + "author_inst": "Autolus Ltd" }, { - "author_name": "Vajra Allan", - "author_inst": "PATH" + "author_name": "Vania Baldan", + "author_inst": "Autolus Ltd" }, { - "author_name": "Ryan Sinclair", - "author_inst": "Loma Linda University" + "author_name": "Giada Mattiuzzo", + "author_inst": "National Institute for Biological Standards and Control" }, { - "author_name": "Yihan Zhang", - "author_inst": "University of California Davis" + "author_name": "Emma M Bentley", + "author_inst": "National Institute for Biological Standards and Control" }, { - "author_name": "Maureen N. Kinyua", - "author_inst": "University of California Davis" + "author_name": "Yasuhiro Takeuchi", + "author_inst": "University College London" + }, + { + "author_name": "James Sillibourne", + "author_inst": "Autolus Ltd" + }, + { + "author_name": "Preeta Datta", + "author_inst": "Autolus Ltd" + }, + { + "author_name": "Alexander Kinna", + "author_inst": "Autolus Ltd" + }, + { + "author_name": "Martin Pule", + "author_inst": "Autolus Ltd" + }, + { + "author_name": "Shimobi Onuoha", + "author_inst": "Autolus Ltd" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by_nd", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.03.16.435705", @@ -847705,35 +846597,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.12.435186", - "rel_title": "SARS-CoV-2 Nsp8 N-terminal domain dimerizes and harbors autonomously folded elements", + "rel_doi": "10.1101/2021.03.13.21253522", + "rel_title": "SYSTEMATIC OBSERVATION OF COVID-19 MITIGATION (SOCOM): ASSESSING FACE COVERING AND DISTANCING IN SCHOOLS", "rel_date": "2021-03-15", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.12.435186", - "rel_abs": "The SARS-CoV-2 Nsp8 protein is a critical component of the RNA replicase, as its N-terminal domain (NTD) anchors Nsp12, the RNA, and Nsp13. Whereas its C-terminal domain (CTD) structure is well resolved, there is an open debate regarding the conformation adopted by the NTD as it is predicted as disordered but found in a variety of complex-dependent conformations or missing from many other structures. Using NMR spectroscopy, we show that the SARS CoV-2 Nsp8 NTD features both well folded secondary structure and disordered segments. Our results suggest that while part of this domain corresponding to two long -helices forms autonomously, the folding of other segments would require interaction with other replicase components. When isolated, the -helix population progressively declines towards the C-termini, and dynamics measurements indicate that the Nsp8 NTD behaves as a dimer under our conditions.", - "rel_num_authors": 4, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.13.21253522", + "rel_abs": "IntroductionDuring the COVID-19 pandemic, some K-12 schools resumed in-person classes with varying degrees of mitigation plans in the fall of 2020. Physical distancing and face coverings can minimize SARS-CoV-2 spread, the virus that causes COVID-19. However, no research has focused on mitigation strategy adherence during school days. Thus, we sought to develop a systematic observation protocol to capture COVID-19 mitigation strategy adherence in school environments: The Systematic Observation of COVID-19 Mitigation (SOCOM).\n\nMethodsWe extended previously validated and internationally used tools to develop the SOCOM training and implementation protocol to assess physical distancing and face covering behaviors. SOCOM was tested in diverse indoor and outdoor settings (classrooms, lunchrooms, physical education [PE], and recess) among diverse schools (elementary, secondary, and special needs).\n\nResultsFor the unique metrics of physical-distancing and face-covering behaviors, areas with more activity and a maximum of 10-15 students were ideal for accurately capturing data. Overall proportion of agreement was high for physical distancing (90.9%), face covering (88.6%), activity type (89.2%), and physical activity level (87.9%). Agreement was lowest during active recess, PE, and observation areas with [≥]20 students.\n\nConclusionsMillions of children throughout the US are likely to return to school in the months ahead despite the current surge of COVID-19 cases. SOCOM is a relatively inexpensive tool that can be implemented by schools to determine mitigation strategy adherence and assess changes to protocols to help students return to school safely and slow the spread of COVID-19 and can be used for research purposes.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Miguel \u00c1 Trevi\u00f1o", - "author_inst": "\"Rocasolano\" Institute for Physical Chemistry" + "author_name": "Ricky Camplain", + "author_inst": "Center for Health Equity Research, Northern Arizona University, Flagstaff, AZ" }, { - "author_name": "David Pantoja-Uceda", - "author_inst": "\"Rocasolano\" Institute for Physical Chemistry" + "author_name": "Nanette V. Lopez", + "author_inst": "Department of Health Sciences, Northern Arizona University, Flagstaff, AZ" }, { - "author_name": "Douglas Vinson Laurents", - "author_inst": "\"Rocasolano\" Institute for Physical Chemistry" + "author_name": "Dan M. Cooper", + "author_inst": "University of California at Irvine" }, { - "author_name": "Miguel Mompe\u00e1n", - "author_inst": "\"Rocasolano\" Institute for Physical Chemistry" + "author_name": "Thomas McKenzie", + "author_inst": "SDSU" + }, + { + "author_name": "Kai Zheng", + "author_inst": "University of California at Irvine" + }, + { + "author_name": "Shlomit Radom-Aizik", + "author_inst": "University of California at Irvine" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "biophysics" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2021.03.11.21253404", @@ -850043,29 +848943,25 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.03.12.21253496", - "rel_title": "Multi-resolution characterization of the COVID-19 pandemic: A unified framework and open-source tool", + "rel_doi": "10.1101/2021.03.13.21253515", + "rel_title": "COVID-19 Risk Factors and Mortality among Native Americans", "rel_date": "2021-03-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.12.21253496", - "rel_abs": "Amidst the continuing spread of COVID-19, real-time data analysis and visualization remain critical to track the pandemics impact and inform policy making. Multiple metrics have been considered to evaluate the spread, infection, and mortality of infectious diseases. For example, numbers of new cases and deaths provide measures of absolute impact within a given population and time frame, while the effective reproduction rate provides a measure of the rate of spread. It is critical to evaluate multiple metrics concurrently, as they provide complementary insights into the impact and current state of the pandemic. We describe a unified framework for estimating and quantifying the uncertainty in the smoothed daily effective reproduction number, case rate, and death rate in a region using log-linear models. We apply this framework to characterize COVID-19 impact at multiple geographic resolutions, including by US county and state as well as by country, demonstrating the variation across resolutions and the need for harmonized efforts to control the pandemic. We provide an open-source online dashboard for real-time analysis and visualization of multiple key metrics, which are critical to evaluate the impact of COVID-19 and make informed policy decisions.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.13.21253515", + "rel_abs": "BACKGROUNDAcademic research on the disproportionate impact of COVID-19 among Native Americans has largely been restricted to particular indigenous groups or reservations.\n\nOBJECTIVEWe estimate COVID-19 mortality for Native Americans relative to other racial/ethnic groups and explore how state-level mortality is associated with known risk factors. METHODS: We use the Standard Mortality Ratio (SMR), adjusted for age, to estimate COVID-19 mortality by racial/ethnic groups for the U.S. and 16 selected states that account for three-quarters of the Native American population. The prevalence of risk factors is derived from the American Community Survey and the Behavioral Risk Factor Surveillance System.\n\nRESULTSThe SMR for Native Americans greatly exceeds those for Black and Latino populations and varies enormously across states. There is a strong positive correlation across states between the share of Native Americans living on a reservation and the SMR. The SMR for Native Americans is highly correlated with the income-poverty ratio, the prevalence of multigenerational families, and health insurance (excluding the Indian Health Service). Risk factors associated with socioeconomic status and co-morbidities are generally more prevalent for Native Americans living on homelands, a proxy for reservation status, than for those living elsewhere.\n\nCONCLUSIONSMost risk factors for COVID-19 are disproportionately high among Native Americans. Reservation life appears to increase the risk of COVID-19 mortality.\n\nCONTRIBUTIONWe assemble and analyze a broader set of COVID-19-related risk factors for Native Americans than previous studies, a critical step toward understanding the exceptionally high COVID-19 death rates in this population.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Andy Shi", - "author_inst": "Department of Biostatistics, Harvard TH Chan School of Public Health" - }, - { - "author_name": "Sheila M. Gaynor", - "author_inst": "Department of Biostatistics, Harvard TH Chan School of Public Health" + "author_name": "Katherine Leggat-Barr", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Corbin Quick", - "author_inst": "Department of Biostatistics, Harvard TH Chan School of Public Health" + "author_name": "Fumiya Uchikoshi", + "author_inst": "Princeton University" }, { - "author_name": "Xihong Lin", - "author_inst": "Department of Biostatistics, Harvard TH Chan School of Public Health; Department of Statistics, Harvard University" + "author_name": "Noreen Goldman", + "author_inst": "Princeton University" } ], "version": "1", @@ -852041,81 +850937,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.09.21253147", - "rel_title": "Higher viral load drives infrequent SARS-CoV-2 transmission between asymptomatic residence hall roommates", + "rel_doi": "10.1101/2021.03.09.21253222", + "rel_title": "Global association of obesity and COVID-19 death rates", "rel_date": "2021-03-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.09.21253147", - "rel_abs": "In 2019-2020, the COVID-19 pandemic spread to over 200 countries in less than six months. To understand the basis of this aggressive spread, it is essential to determine the transmission rate and define the factors that increase the risk of transmission. One complication is the large fraction of asymptomatic cases, particularly in young populations: these individuals have viral loads indistinguishable from symptomatic people and do transmit the SARS-CoV-2 virus, but they often go undetected. As university students living in residence halls commonly share a small living space with roommates, some schools established regular, high density testing programs to mitigate on-campus spread. In this study, we analyzed longitudinal testing data of residence hall students at the University of Colorado Boulder. We observed that students in single rooms were infected at a lower rate than students in multiple occupancy rooms. However, this was not due to high rates of transmission between roommates, which only occurred approximately 20% of the time. Since these cases were usually asymptomatic at the time of diagnosis, this provides further evidence for asymptomatic transmission. Notably, individuals who likely transmitted to their roommates had an average viral load [~]6.5 times higher than individuals who did not. Although students were moved to separate isolation rooms after diagnosis, there was no difference in time to isolation between these cases with or without transmission. This analysis argues that inter-roommate transmission occurs in a minority of cases in university residence halls and provides strong correlative evidence that viral load can be proportional to the probability of transmission.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.09.21253222", + "rel_abs": "ImportanceCOVID-19 was responsible for an enormous global death toll with large variation among countries.\n\nObjectiveTo examine the possible impact of obesity on COVID-19 death rates.\n\nDesignMeasure associations between obesity rates in 2016 and COVID-19 deaths/million population through 2/25/2021, across countries.\n\nSettingGlobal\n\nParticipants167 countries for which obesity and death data were available, grouped by population size, with multiples of 10 countries in each of 8 groups plus a group including all 57 countries with obesity rates <15%.\n\nOutcome and measuresUsing Excel, COVID-19 deaths/million were regressed on the obesity rate for each country, based on obesity being a key factor in COVID hospitalizations and deaths. Using the least squares formula for the best fit for each model, R2, components of the formula, and the percentage of world population represented, were recorded for each group.\n\nResultsObesity rates ranged from 2.1% to 37.9% and death rates ranged from 0.4/million to 1,892/million for groups representing up to 91% of global population. Results for the 8 population groups had R2 from 0.30 to 0.90 with slopes of the fitted line ranging from 27.9-51.0. Countries with obesity rates <15% had consistently low death rates ([≤]233/million), R2 of 0.003 and slope of the line=1.01.\n\nConclusionsFor most countries about one-third of the difference in COVID death rates was due to obesity while in countries with obesity <15%, consistently low death rates were not associated with obesity. Reduced obesity rates could potentially have lowered the COVID death toll.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Kristen K Bjorkman", - "author_inst": "University of Colorado Boulder" - }, - { - "author_name": "Tassa K Saldi", - "author_inst": "University of Colorado Boulder" - }, - { - "author_name": "Erika Lasda", - "author_inst": "University of Colorado Boulder" - }, - { - "author_name": "Leisha Conners Bauer", - "author_inst": "University of Colorado Boulder" - }, - { - "author_name": "Jennifer Kovarik", - "author_inst": "University of Colorado Boulder" - }, - { - "author_name": "Patrick K Gonzales", - "author_inst": "University of Colorado Boulder" - }, - { - "author_name": "Morgan R Fink", - "author_inst": "University of Colorado Boulder" - }, - { - "author_name": "Kimngang L Tat", - "author_inst": "University of Colorado Boulder" - }, - { - "author_name": "Cole R Hager", - "author_inst": "University of Colorado Boulder" - }, - { - "author_name": "Jack C Davis", - "author_inst": "University of Colorado Boulder" - }, - { - "author_name": "Christopher D Ozeroff", - "author_inst": "University of Colorado Boulder" - }, - { - "author_name": "Gloria R Brisson", - "author_inst": "University of Colorado Boulder" - }, - { - "author_name": "Daniel B Larremore", - "author_inst": "University of Colorado Boulder" - }, - { - "author_name": "Leslie A Leinwand", - "author_inst": "University of Colorado Boulder" - }, - { - "author_name": "Matthew B McQueen", - "author_inst": "University of Colorado Boulder" - }, - { - "author_name": "Roy Parker", - "author_inst": "University of Colorado Boulder" + "author_name": "Mary L Adams", + "author_inst": "On Target Health Data LLC" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -853847,61 +852683,101 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2021.03.10.21253282", - "rel_title": "Impact of close interpersonal contact on COVID-19 incidence: evidence from one year of mobile device data", + "rel_doi": "10.1101/2021.03.10.21253173", + "rel_title": "High household transmission of SARS-CoV-2 in the United States: living density, viral load, and disproportionate impact on communities of color", "rel_date": "2021-03-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.10.21253282", - "rel_abs": "Close contact between people is the primary route for transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). We sought to quantify interpersonal contact at the population-level by using anonymized mobile device geolocation data. We computed the frequency of contact (within six feet) between people in Connecticut during February 2020 - January 2021. Then we aggregated counts of contact events by area of residence to obtain an estimate of the total intensity of interpersonal contact experienced by residents of each town for each day. When incorporated into a susceptible-exposed-infective-removed (SEIR) model of COVID-19 transmission, the contact rate accurately predicted COVID-19 cases in Connecticut towns during the timespan. The pattern of contact rate in Connecticut explains the large initial wave of infections during March-April, the subsequent drop in cases during June-August, local outbreaks during August-September, broad statewide resurgence during September-December, and decline in January 2021. Contact rate data can help guide public health messaging campaigns to encourage social distancing and in the allocation of testing resources to detect or prevent emerging local outbreaks more quickly than traditional case investigation.\n\nOne sentence summaryClose interpersonal contact measured using mobile device location data explains dynamics of COVID-19 transmission in Connecticut during the first year of the pandemic.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.10.21253173", + "rel_abs": "BackgroundFew prospective studies of SARS-CoV-2 transmission within households have been reported from the United States, where COVID-19 cases are the highest in the world and the pandemic has had disproportionate impact on communities of color.\n\nMethods and FindingsThis is a prospective observational study. Between April-October 2020, the UNC CO-HOST study enrolled 102 COVID-positive persons and 213 of their household members across the Piedmont region of North Carolina, including 45% who identified as Hispanic/Latinx or non-white. Households were enrolled a median of 6 days from onset of symptoms in the index case. Secondary cases within the household were detected either by PCR of a nasopharyngeal (NP) swab on study day 1 and weekly nasal swabs (days 7, 14, 21) thereafter, or based on seroconversion by day 28. After excluding household contacts exposed at the same time as the index case, the secondary attack rate (SAR) among susceptible household contacts was 60% (106/176, 95% CI 53%-67%). The majority of secondary cases were already infected at study enrollment (73/106), while 33 were observed during study follow-up. Despite the potential for continuous exposure and sequential transmission over time, 93% (84/90, 95% CI 86%-97%) of PCR-positive secondary cases were detected within 14 days of symptom onset in the index case, while 83% were detected within 10 days. Index cases with high NP viral load (>10^6 viral copies/ul) at enrollment were more likely to transmit virus to household contacts during the study (OR 4.9, 95% CI 1.3-18 p=0.02). Furthermore, NP viral load was correlated within families (ICC=0.44, 95% CI 0.26-0.60), meaning persons in the same household were more likely to have similar viral loads, suggesting an inoculum effect. High household living density was associated with a higher risk of secondary household transmission (OR 5.8, 95% CI 1.3-55) for households with >3 persons occupying <6 rooms (SAR=91%, 95% CI 71-98%). Index cases who self-identified as Hispanic/Latinx or non-white were more likely to experience a high living density and transmit virus to a household member, translating into an SAR in minority households of 70%, versus 52% in white households (p=0.05).\n\nConclusionsSARS-CoV-2 transmits early and often among household members. Risk for spread and subsequent disease is elevated in high-inoculum households with limited living space. Very high infection rates due to household crowding likely contribute to the increased incidence of SARS-CoV-2 infection and morbidity observed among racial and ethnic minorities in the US. Quarantine for 14 days from symptom onset of the first case in the household is appropriate to prevent onward transmission from the household. Ultimately, primary prevention through equitable distribution of effective vaccines is of paramount importance.\n\nAUTHORS SUMMARYO_ST_ABSWhy was this study done?C_ST_ABSO_LIUnderstanding the secondary attack rate and the timing of transmission of SARS-CoV-2 within households is important to determine the role of household transmission in the larger pandemic and to guide public health policies about quarantine.\nC_LIO_LIProspective studies looking at the determinants of household transmission are sparse, particularly studies including substantial racial and ethnic minorities in the United States and studies with adequate follow-up to detect sequential transmission events.\nC_LIO_LIIdentifying individuals at high risk of transmitting and acquiring SARS-CoV-2 will inform strategies for reducing transmission in the household, or reducing disease in those exposed.\nC_LI\n\nWhat did the researchers do and find?O_LIBetween April-November 2020, the UNC CO-HOST study enrolled 102 households across the Piedmont region of North Carolina, including 45% with an index case who identified as racial or ethnic minorities.\nC_LIO_LIOverall secondary attack rate was 60% with two-thirds of cases already infected at study enrollment.\nC_LIO_LIDespite the potential for sequential transmission in the household, the majority of secondary cases were detected within 10 days of symptom onset of the index case.\nC_LIO_LIViral loads were correlated within families, suggesting an inoculum effect.\nC_LIO_LIHigh viral load in the index case was associated with a greater likelihood of household transmission.\nC_LIO_LISpouses/partners of the COVID-positive index case and household members with obesity were at higher risk of becoming infected.\nC_LIO_LIHigh household living density contributed to an increased risk of household transmission.\nC_LIO_LIRacial/ethnic minorities had an increased risk of acquiring SARS-CoV-2 in their households in comparison to members of the majority (white) racial group.\nC_LI\n\nWhat do these findings mean?O_LIHousehold transmission often occurs quickly after a household member is infected.\nC_LIO_LIHigh viral load increases the risk of transmission.\nC_LIO_LIHigh viral load cases cluster within households - suggesting high viral inoculum in the index case may put the whole household at risk for more severe disease.\nC_LIO_LIIncreased household density may promote transmission within racial and ethnic minority households.\nC_LIO_LIEarly at-home point-of-care testing, and ultimately vaccination, is necessary to effectively decrease household transmission.\nC_LI", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Forrest W. Crawford", - "author_inst": "Yale School of Public Health" + "author_name": "Carla Cerami", + "author_inst": "MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine" }, { - "author_name": "Sydney A. Jones", - "author_inst": "Epidemic Intelligence Service, Centers for Disease Control & Prevention" + "author_name": "Tyler Rapp", + "author_inst": "Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA" }, { - "author_name": "Matthew Cartter", - "author_inst": "Infectious Diseases Section, Connecticut Department of Public Health" + "author_name": "Feng-Chang Lin", + "author_inst": "Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC USA" }, { - "author_name": "Samantha G. Dean", - "author_inst": "Yale School of Public Health" + "author_name": "Kathleen Tompkins", + "author_inst": "Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA" }, { - "author_name": "Joshua L. Warren", - "author_inst": "Yale School of Public Health" + "author_name": "Christopher Basham", + "author_inst": "Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA" }, { - "author_name": "Zehang Li", - "author_inst": "Department of Statistics, University of California, Santa Cruz" + "author_name": "Meredith Smith Muller", + "author_inst": "Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA" }, { - "author_name": "Jacqueline Barbieri", - "author_inst": "Whitespace Solutions Ltd." + "author_name": "Maureen Whittelsey", + "author_inst": "Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA" }, { - "author_name": "Jared Campbell", - "author_inst": "Whitespace Solutions, Ltd" + "author_name": "Haoming Zhang", + "author_inst": "Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC USA" }, { - "author_name": "Patrick Kenney", - "author_inst": "Whitespace Solutions, Ltd" + "author_name": "Srijana Bhattarai Chhetri", + "author_inst": "Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA" }, { - "author_name": "Thomas Valleau", - "author_inst": "Whitespace Solutions Ltd" + "author_name": "Judy Smith", + "author_inst": "Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA" }, { - "author_name": "Olga W. Morozova", - "author_inst": "SUNY Stony Brook" + "author_name": "Christy Litel", + "author_inst": "Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA" + }, + { + "author_name": "Kelly Lin", + "author_inst": "Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA" + }, + { + "author_name": "Mehal Churiwal", + "author_inst": "Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA" + }, + { + "author_name": "Salman Khan", + "author_inst": "Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, NC USA" + }, + { + "author_name": "Faith Claman", + "author_inst": "Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA" + }, + { + "author_name": "Rebecca Rubinstein", + "author_inst": "Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA" + }, + { + "author_name": "Katie Mollan", + "author_inst": "Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC USA" + }, + { + "author_name": "David Wohl", + "author_inst": "Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA" + }, + { + "author_name": "Lakshmanane Premkumar", + "author_inst": "University of North Carolina School of Medicine" + }, + { + "author_name": "Jonathan J. Juliano", + "author_inst": "Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA" + }, + { + "author_name": "Jessica T Lin", + "author_inst": "Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -855377,57 +854253,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.11.21251938", - "rel_title": "Natural spring water gargle and direct RT-PCR for the diagnosis of COVID-19 (COVID-SPRING study)", + "rel_doi": "10.1101/2021.03.11.21253375", + "rel_title": "Using translational in vitro-in vivo modeling to improve drug repurposing outcomes for inhaled COVID-19 therapeutics", "rel_date": "2021-03-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.11.21251938", - "rel_abs": "We prospectively compared natural spring water gargle to combined oro-nasopharyngeal swab (ONPS) for the diagnosis of coronavirus disease 2019 (COVID-19) in paired clinical specimens (1005 ONPS and 1005 gargles) collected from 987 unique early symptomatic as well as asymptomatic individuals from the community. Using a direct RT-PCR method with the Allplex 2019-nCoV Assay (Seegene), the clinical sensitivity of the gargle was 95.3% (95% confidence interval [CI], 90.2 to 98.3%) and was similar to the sensitivity of the ONPS (93.8%; 95% CI, 88.2 to 97.3%), despite significantly lower viral RNA concentration in gargles, as reflected by higher cycle threshold values. No single specimen type detected all COVID-19 cases. SARS-CoV-2 RNA was stable in gargles at room temperature for at least 7 days. The simplicity of this sampling method coupled with the accessibility of spring water are clear advantages in a pandemic situation where testing frequency, turnaround time and shortage of consumables and trained staff are critical elements.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.11.21253375", + "rel_abs": "The ongoing COVID-19 pandemic has created an urgent need for antiviral treatments that can be deployed rapidly. Drug repurposing represents a promising means of achieving this objective, but repurposing efforts are often unsuccessful. A common hurdle to effective drug repurposing is a failure to achieve a sufficient therapeutic window in the new indication. A clear example is the use of ivermectin in COVID-19, where the approved dose (administered orally) fails to achieve therapeutic concentrations in the lungs. Our proposed solution to the problem of ineffective drug repurposing for COVID-19 antivirals is two-fold: to broaden the therapeutic window by reformulating therapeutics for the pulmonary route, and to select drug repurposing candidates based on their model-predicted therapeutic index for inhalation. In this article, we propose a two-stage model-driven screening and validation process for selecting inhaled antiviral drug repurposing candidates. While we have applied this approach in the specific context of COVID-19, this in vitro-in vivo translational methodology is also broadly applicable to repurposing drugs for diseases of the lower respiratory tract.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Jeannot Dumaresq", - "author_inst": "CISSS de Chaudi\u00e8re-Appalaches" - }, - { - "author_name": "Fran\u00e7ois Coutl\u00e9e", - "author_inst": "Centre Hospitalier de l'Universit\u00e9 de Montr\u00e9al" - }, - { - "author_name": "P. Dufresne", - "author_inst": "Institut national de sant\u00e9 publique du Qu\u00e9bec, Laboratoire de sant\u00e9 publique du Qu\u00e9bec, Sainte-Anne-de-Bellevue" - }, - { - "author_name": "Jean Longtin", - "author_inst": "Centre hospitalier universitaire (CHU) de Qu\u00e9bec" - }, - { - "author_name": "Judith Fafard", - "author_inst": "Laboratoire de Sant\u00e9 Publique du Qu\u00e9bec, Institut national de sant\u00e9 publique du Qu\u00e9bec" - }, - { - "author_name": "Julie Bestman-Smith", - "author_inst": "Centre hospitalier universitaire (CHU) de Qu\u00e9bec" - }, - { - "author_name": "Marco Andres Bergevin", - "author_inst": "H\u00f4pital Cit\u00e9 de la Sant\u00e9" - }, - { - "author_name": "\u00c9milie Valli\u00e8res", - "author_inst": "CHU Sainte-Justine" + "author_name": "Madison Stoddard", + "author_inst": "Fractal Therapeutics, Inc." }, { - "author_name": "Marc Desforges", - "author_inst": "CHU Ste-Justine" + "author_name": "Lin Yuan", + "author_inst": "Fractal Therapeutics, Inc." }, { - "author_name": "Annie-Claude Labb\u00e9", - "author_inst": "H\u00f4pital Maisonneuve-Rosemont" + "author_name": "Arijit Chakravarty", + "author_inst": "Fractal Therapeutics, Inc." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -856930,107 +855778,131 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2021.03.08.21253148", - "rel_title": "Spike vs nucleocapsid SARS-CoV-2 antigen detection: application in nasopharyngeal swab specimens", + "rel_doi": "10.1101/2021.03.11.434928", + "rel_title": "A tandem-repeat dimeric RBD protein-based COVID-19 vaccine ZF2001 protects mice and nonhuman primates", "rel_date": "2021-03-11", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.08.21253148", - "rel_abs": "Public health experts emphasize the need for quick, point-of-care SARS-CoV-2 detection as an effective strategy for controlling virus spread. To this end, many \"antigen\" detection devices were developed and commercialized. These devices are mostly based on detecting SARS-CoV-2s nucleocapsid protein. Recently, alerts issued by both the FDA and the CDC raised concerns regarding the devices tendency to exhibit false positive results. In this work we developed a novel alternative spike-based antigen assay, comprised of four high-affinity, specific monoclonal antibodies, directed against different epitopes on the spikes S1 subunit. The assays performance was evaluated for COVID-19 detection from nasopharyngeal swabs, compared to an in-house nucleocapsid-based assay, composed of antibodies directed against the nucleocapsid. Detection of COVID-19 was carried out in a cohort of 284 qRT-PCR positive and negative nasopharyngeal swab samples. The time resolved fluorescence (TRF) ELISA spike-assay displayed very high specificity (99%) accompanied with a somewhat lower sensitivity (66% for Ct<25), compared to the nucleocapsid ELISA assay which was more sensitive (85% for Ct<25) while less specific (87% specificity). Despite being out-performed by qRT-PCR, we suggest that there is room for such tests in the clinical setting, as cheap and rapid pre-screening tools. Our results further suggest that when applying antigen detection, one must consider its intended application (sensitivity vs specificity), taking into consideration that the nucleocapsid might not be the optimal target. In this regard, we propose that a combination of both antigens might contribute to the validity of the results.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC=\"FIGDIR/small/21253148v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (24K):\norg.highwire.dtl.DTLVardef@2cdc04org.highwire.dtl.DTLVardef@12090daorg.highwire.dtl.DTLVardef@10603dforg.highwire.dtl.DTLVardef@1e84cfa_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphic abstractSchematic representation of sample collection and analysis. The figure was created using BioRender.com", - "rel_num_authors": 22, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.11.434928", + "rel_abs": "A safe, efficacious and deployable vaccine is urgently needed to control COVID-19 pandemic. We report here the preclinical development of a COVID-19 vaccine candidate, ZF2001, which contains tandem-repeat dimeric receptor-binding domain (RBD) protein with alum-based adjuvant. We assessed vaccine immunogenicity and efficacy in both mice and non-human primates (NHPs). ZF2001 induced high levels of RBD-binding and SARS-CoV-2 neutralizing antibody in both mice and NHPs, and also elicited balanced TH1/TH2 cellular responses in NHPs. Two doses of ZF2001 protected Ad-hACE2-transduced mice against SARS-CoV-2 infection, as detected by reduced viral RNA and relieved lung injuries. In NHPs, vaccination of either 25 g or 50 g ZF2001 prevented infection with SARS-CoV-2 in lung, trachea and bronchi, with milder lung lesions. No evidence of disease enhancement is observed in both models. ZF2001 is being evaluated in the ongoing international multi-center Phase 3 trials (NCT04646590) and has been approved for emergency use in Uzbekistan.", + "rel_num_authors": 28, "rel_authors": [ { - "author_name": "Moria Barlev-Gross", - "author_inst": "IIBR" + "author_name": "Yaling An", + "author_inst": "Savaid Medical School, University of Chinese Academy of Sciences, Beijing, 101408, China" }, { - "author_name": "Shay Weiss", - "author_inst": "IIBR" + "author_name": "Shihua Li", + "author_inst": "CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China" }, { - "author_name": "Amir Ben-Shmuel", - "author_inst": "IIBR" + "author_name": "Xiyue Jin", + "author_inst": "School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China" }, { - "author_name": "Assa Sittner", - "author_inst": "IIBR" + "author_name": "Jian-Bao Han", + "author_inst": "Key Laboratory of Tropical Translational Medicine of Ministry of Education, School of Tropical Medicine and Laboratory Medicine, The First Affiliated Hospital, " }, { - "author_name": "Keren Eden", - "author_inst": "IIBR" + "author_name": "Kun Xu", + "author_inst": "Key Laboratory of Tropical Translational Medicine of Ministry of Education, School of Tropical Medicine and Laboratory Medicine, The First Affiliated Hospital, " }, { - "author_name": "Noam Mazuz", - "author_inst": "IIBR" + "author_name": "Senyu Xu", + "author_inst": "Research Network of Immunity and Health (RNIH), Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China" }, { - "author_name": "Itai Glinert", - "author_inst": "IIBR" + "author_name": "Yuxuan Han", + "author_inst": "Savaid Medical School, University of Chinese Academy of Sciences, Beijing, 101408, China" }, { - "author_name": "Elad Bar-David", - "author_inst": "IIBR" + "author_name": "Chuanyu Liu", + "author_inst": "Laboratory of Animal Infectious Diseases, College of Animal Sciences and Veterinary Medicine, Guangxi University, Nanning, China" }, { - "author_name": "Reut Puni", - "author_inst": "IIBR" + "author_name": "Tianyi Zheng", + "author_inst": "Key Laboratory of Tropical Translational Medicine of Ministry of Education, School of Tropical Medicine and Laboratory Medicine, The First Affiliated Hospital, " }, { - "author_name": "Sharon Amit", - "author_inst": "Clinical Microbiology, Sheba Medical Centre, Ramat-Gan, Israel" + "author_name": "Mei Liu", + "author_inst": "CAS Key Laboratory of Microbial Physiological and Metabolic Engineering, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China" }, { - "author_name": "Or Kriger", - "author_inst": "Clinical Microbiology, Sheba Medical Centre, Ramat-Gan, Israel" + "author_name": "Mi Yang", + "author_inst": "CAS Key Laboratory of Microbial Physiological and Metabolic Engineering, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China" }, { - "author_name": "Ofir Schuster", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Tian-zhang Song", + "author_inst": "Key Laboratory of Animal Models and Human Disease Mechanism of the Chinese Academy of Sciences, Kunming Institute of Zoology, Chinese Academic of Sciences, Kunm" }, { - "author_name": "Ron Alcalay", - "author_inst": "IIBR" + "author_name": "Baoying Huang", + "author_inst": "NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206" }, { - "author_name": "Efi Makdasi", - "author_inst": "IIBR" + "author_name": "Li Zhao", + "author_inst": "NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206" }, { - "author_name": "Eyal Epstein", - "author_inst": "IIBR" + "author_name": "Wen Wang", + "author_inst": "NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206" }, { - "author_name": "Tal Noy-Porat", - "author_inst": "IIBR" + "author_name": "Ruhan A", + "author_inst": "NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206" }, { - "author_name": "Ronit Rosenfeld", - "author_inst": "IIBR" + "author_name": "Yingjie Cheng", + "author_inst": "Anhui Zhifei Longcom Biopharmaceutical Co. Ltd, Anhui 230088, China" }, { - "author_name": "Hagit Achdout", - "author_inst": "IIBR" + "author_name": "Changwei Wu", + "author_inst": "Anhui Zhifei Longcom Biopharmaceutical Co. Ltd, Anhui 230088, China" }, { - "author_name": "Ohad Mazor", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Enqi Huang", + "author_inst": "Anhui Zhifei Longcom Biopharmaceutical Co. Ltd, Anhui 230088, China" }, { - "author_name": "Tomer Israely", - "author_inst": "IIBR" + "author_name": "Shilong Yang", + "author_inst": "Anhui Zhifei Longcom Biopharmaceutical Co. Ltd, Anhui 230088, China" }, { - "author_name": "Haim Levy", - "author_inst": "IIBR" + "author_name": "Gary Wang", + "author_inst": "CAS Key Laboratory of Molecular Virology & Immunology, Institut Pasteur of Shanghai, Chinese Academy of Sciences, Shanghai 200031, China; Department of Microbio" }, { - "author_name": "Adva Mechaly", - "author_inst": "IIBR" + "author_name": "Yuhai Bi", + "author_inst": "CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China" + }, + { + "author_name": "Changwen Ke", + "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China" + }, + { + "author_name": "Wenjie Tan", + "author_inst": "NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206" + }, + { + "author_name": "Jinghua Yan", + "author_inst": "CAS Key Laboratory of Microbial Physiological and Metabolic Engineering, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China" + }, + { + "author_name": "Yong-Tang Zheng", + "author_inst": "Kunming National High-Level Biosafety Research Center for Non-human Primates, Center for Biosafety Mega-Science, Kunming Institute of Zoology, Chinese Academy o" + }, + { + "author_name": "Lianpan Dai", + "author_inst": "CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China; Savaid Medical Schoo" + }, + { + "author_name": "George F. Gao", + "author_inst": "CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China" } ], "version": "1", - "license": "cc_by_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.03.11.434841", @@ -858955,51 +857827,75 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.08.21252905", - "rel_title": "Population-based estimates of post-acute sequelae of SARS-CoV-2 infection (PASC) prevalence and characteristics: A cross-sectional study", + "rel_doi": "10.1101/2021.03.09.21253184", + "rel_title": "Increased mortality among individuals hospitalised with COVID-19 during the second wave in South Africa", "rel_date": "2021-03-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.08.21252905", - "rel_abs": "ImportanceEmerging evidence suggests many people have persistent symptoms after acute COVID-19 illness.\n\nObjectiveTo estimate the prevalence and correlates of persistent COVID-19 symptoms 30 and 60 days post onset using a population-based sample.\n\nDesign & SettingThe Michigan COVID-19 Recovery Surveillance Study is a population-based cross-sectional survey of a probability sample of adults with confirmed COVID-19 in the Michigan Disease Surveillance System (MDSS). Respondents completed a survey online or via telephone in English, Spanish, or Arabic between June - December 2020.\n\nParticipantsLiving non-institutionalized adults (aged 18+) in MDSS with COVID-19 onset through mid-April 2020 were eligible for selection (n=28,000). Among 2,000 adults selected, 629 completed the survey. We excluded 79 cases during data collection due to ineligibility, 6 asymptomatic cases, 7 proxy reports, and 24 cases missing outcome data, resulting in a sample size of 593. The sample was predominantly female (56.1%), aged 45 and older (68.2%), and Non-Hispanic White (46.3%) or Black (34.8%).\n\nExposuresDemographic (age, sex, race/ethnicity, and annual household income) and clinical factors (smoking status, body mass index, diagnosed comorbidities, and illness severity).\n\nMain outcomes and MeasuresWe defined post-acute sequelae of SARS-CoV-2 infection (PASC) as persistent symptoms 30+ days (30-day COVID-19) or 60+ days (60-day COVID-19) post COVID-19 onset.\n\nResults30- and 60-day COVID-19 were highly prevalent (52.5% and 35.0%), even among respondents reporting mild symptoms (29.2% and 24.5%) and non-hospitalized respondents (43.7% and 26.9%, respectively). Low income was statistically significantly associated with 30-day COVID-19 in adjusted models. Respondents reporting very severe (vs. mild) symptoms had 2.25 times higher prevalence of 30-day COVID-19 (Adjusted Prevalence Ratio [aPR] 2.25, 95% CI 1.46-3.46) and 1.71 times higher prevalence of 60-day COVID-19 (aPR 1.71, 95% 1.02-2.88). Hospitalized (vs. non-hospitalized) respondents had about 40% higher prevalence of both 30-day (aPR 1.37, 95% CI 1.12-1.69) and 60-day COVID-19 (aPR 1.40, 95% CI 1.02-1.93).\n\nConclusions and RelevancePASC is highly prevalent among cases with severe initial symptoms, and, to a lesser extent, cases with mild and moderate symptoms.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.09.21253184", + "rel_abs": "IntroductionSouth Africa experienced its first wave of COVID-19 peaking in mid-July 2020 and a larger second wave peaking in January 2021, in which the SARS-CoV-2 501Y.V2 lineage predominated. We aimed to compare in-hospital mortality and other patient characteristics between the first and second waves of COVID-19.\n\nMethodsWe analysed data from the DATCOV national active surveillance system for COVID-19 hospitalisations. We defined four wave periods using incidence risk for hospitalisation, pre-wave 1, wave 1, pre-wave 2 and wave 2. We compared the characteristics of hospitalised COVID-19 cases in wave 1 and wave 2, and risk factors for in-hospital mortality accounting for wave period using multivariable logistic regression.\n\nResultsPeak rates of COVID-19 cases, admissions and in-hospital deaths in the second wave exceeded the rates in the first wave (138.1 versus 240.1; 16.7 versus 28.9; and 3.3 versus 7.1 respectively per 100,000 persons). The weekly average incidence risk increase in hospitalisation was 22% in wave 1 and 28% in wave 2 [ratio of growth rate in wave two compared to wave one: 1.04, 95% CI 1.04-1.05]. On multivariable analysis, after adjusting for weekly COVID-19 hospital admissions, there was a 20% increased risk of in-hospital mortality in the second wave (adjusted OR 1.2, 95% CI 1.2-1.3). In-hospital case fatality-risk (CFR) increased in weeks of peak hospital occupancy, from 17.9% in weeks of low occupancy (<3,500 admissions) to 29.6% in weeks of very high occupancy (>12,500 admissions) (adjusted OR 1.5, 95% CI 1.4-1.5).\n\nCompared to the first wave, individuals hospitalised in the second wave, were more likely to be older, 40-64 years [OR 1.1, 95% CI 1.0-1.1] and [≥]65 years [OR 1.1, 95% CI 1.1-1.1] compared to <40 years; and admitted in the public sector [OR 2.2, 95% CI 1.7-2.8]; and less likely to have comorbidities [OR 0.5, 95% CI 0.5-0.5].\n\nConclusionsIn South Africa, the second wave was associated with higher incidence and more rapid increase in hospitalisations, and increased in-hospital mortality. While some of this is explained by increasing pressure on the health system, a residual increase in mortality of hospitalised patients beyond this, could be related to the new lineage 501Y.V2.\n\nRESEARCH IN CONTEXT O_TEXTBOXEvidence before this studyMost countries have reported higher numbers of COVID-19 cases in the second wave but lower case-fatality risk (CFR), in part due to new therapeutic interventions, increased testing and better prepared health systems. South Africa experienced its second wave which peaked in January 2021, in which the variant of concern, SARS-CoV-2 501Y.V2 predominated. New variants have been shown to be more transmissible and in the United Kingdom, to be associated with increased hospitalisation and mortality rates in people infected with variant B.1.1.7 compared to infection with non-B.1.1.7 viruses. There are currently limited data on the severity of lineage 501Y.V2.\n\nAdded value of this studyWe analysed data from the DATCOV national active surveillance system for COVID-19 hospitalisations, comparing in-hospital mortality and other patient characteristics between the first and second waves of COVID-19. The study revealed that after adjusting for weekly COVID-19 hospital admissions, there was a 20% increased risk of in-hospital mortality in the second wave. Our study also describes the demographic shift from the first to the second wave of COVID-19 in South Africa, and quantifies the impact of overwhelmed hospital capacity on in-hospital mortality.\n\nImplications of all the available evidenceOur data suggest that the new lineage (501Y.V2) in South Africa may be associated with increased in-hospital mortality during the second wave. Our data should be interpreted with caution however as our analysis is based on a comparison of mortality in the first and second wave as a proxy for dominant lineage and we did not have individual-level data on lineage. Individual level studies comparing outcomes of people with and without the new lineage based on sequencing data are needed. To prevent high mortality in a potential third wave, we require a combination of strategies to slow the transmission of SARS-CoV-2, to spread out the peak of the epidemic, which would prevent hospital capacity from being breached.\n\nC_TEXTBOX", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Jana L. Hirschtick", - "author_inst": "University of Michigan" + "author_name": "Waasila Jassat", + "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa." }, { - "author_name": "Andrea R. Titus", - "author_inst": "University of Michigan" + "author_name": "Caroline Mudara", + "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa." }, { - "author_name": "Elizabeth Slocum", - "author_inst": "University of Michigan" + "author_name": "Lovelyn Ozougwu", + "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa." }, { - "author_name": "Laura E. Power", - "author_inst": "University of Michigan" + "author_name": "Stefano Tempia", + "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa." }, { - "author_name": "Robert E. Hirschtick", - "author_inst": "Northwestern University" + "author_name": "Lucille Blumberg", + "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa." }, { - "author_name": "Michael R. Elliott", - "author_inst": "University of Michigan" + "author_name": "Mary-Ann Davies", + "author_inst": "Western Cape Government: Health, Health Impact Assessment Directorate, Cape Town, South Africa." }, { - "author_name": "Patricia McKane", - "author_inst": "Michigan Department of Health and Human Services" + "author_name": "Yogan Pillay", + "author_inst": "Clinton Health Access Initiative, Pretoria, South Africa" }, { - "author_name": "Nancy L. Fleischer", - "author_inst": "University of Michigan" + "author_name": "Terrence Carter", + "author_inst": "Clinton Health Access Initiative, Pretoria, South Africa" + }, + { + "author_name": "Ramphelane Morewane", + "author_inst": "National Department of Health, Pretoria, South Africa" + }, + { + "author_name": "Milani Wolmarans", + "author_inst": "National Department of Health, Pretoria, South Africa" + }, + { + "author_name": "Anne von Gottberg", + "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa." + }, + { + "author_name": "Jinal N Bhiman", + "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa." + }, + { + "author_name": "Sibongile Walaza", + "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa." + }, + { + "author_name": "Cheryl Cohen", + "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa." } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.03.09.21252764", @@ -861373,69 +860269,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.07.21252786", - "rel_title": "SARS-COV-2 antibody prevalence in patients on dialysis in the US in January 2021", + "rel_doi": "10.1101/2021.03.08.21253117", + "rel_title": "Single-Arm, Open-Label Phase 2 Trial of Preemptive Methylprednisolone to Avert Progression to Respiratory Failure in High-Risk Patients with COVID-19", "rel_date": "2021-03-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.07.21252786", - "rel_abs": "BackgroundTo estimate seroprevalence of SARS-CoV-2 antibodies in the US, the country with the worlds largest absolute numbers of COVID19 cases and deaths, we conducted a cross-sectional assessment from a sample of patients receiving dialysis in January 2021.\n\nMethodsWe tested remainder plasma of 21,424 patients receiving dialysis through the third-largest US dialysis organization, with facilities located nationwide. We used the Siemens spike protein receptor binding domain total antibody assay to estimate crude SARS-CoV-2 seroprevalence, and then estimated seroprevalence for the US dialysis and adult population by standardizing by age, sex and region. We also compared January 2021 seroprevalence and case-detection rates to that from a similar subsample of patients receiving dialysis who had been tested in July 2020.\n\nResultsPatients in the sample were disproportionately from older age and minority race/ethnic groups. Seroprevalence of SARS-CoV-2 was 18.9% (95% CI: 18.3-19.5%) in the sample, 18.7% (18.1-19.2%) standardized to the US dialysis population, and 21.3% (20.3-22.3%) standardized to the US adult population (range 15.3-20.8% in the Northeast and South respectively). Younger age groups (18-44 years), and persons self-identifying as Hispanic or living in Hispanic neighborhoods, and persons living in the poorest neighborhoods were among the subgroups with the highest seroprevalence (25.9% (24.1-27.8%), 25.1% (23.6-26.4%), 24.8% (23.2-26.5%) respectively). Compared to data from July 2020, we observed diminished variability in seroprevalence by geographic region and urban-rural status. Estimated case detection rate increased from 14% to 23% in July 2020 to January 2021.\n\nConclusionsA year after the first case of SARS-CoV-2 infection was detected in the US, fewer than one in four adults have evidence of SARS-CoV-2 antibodies. Vaccine roll out to majority minority neighborhoods and poorer neighborhoods will be critical to disrupting the spread of infection.\n\nFundingAscend Clinical Laboratories funded remainder-plasma testing.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.08.21253117", + "rel_abs": "IntroductionCovid-19 is a triphasic disorder first typified by a viral phase that lasts from the first onset of symptoms until seven days later. This is followed by a second and third phase, initially characterized by the appearance of lung infiltrates, followed in 20% by respiratory failure. The second phase is usually heralded by an elevation of serologic inflammatory markers including CRP, ferritin, IL-6, LDH as well as D-dimers. Approximately 20% proceed to the second phase and are usually then treated with dexamethasone, provided they are oxygen-dependent since these are the only cases that benefit from dexamethasone. If we had objective criteria to predict this 20% that develop severe illness, they could preemptively be treated with steroids. In this exploratory study we investigated the early use of preemptive steroids in the setting of early disease, in high-risk non-oxygen dependent cases.\n\nMethodsEligible patients were those 21 years or older with a diagnosis of Covid-19 and oxygen saturation [≥]91%. For patients to be classified as high-risk, they had to exhibit two or more of the following abnormalities 7-10 days after first symptom: IL-6 [≥] 10 pg/ml, ferritin > 500 ng/ml, D-dimer > 1 mg/L (1,000 ng/ml), CRP > 10 mg/dL (100 mg/L), LDH above normal range lymphopenia (absolute lymphocyte count <1,000 /{micro}L), oxygen saturation between 91-94%, or CT chest with evidence of ground glass infiltrates. Primary endpoint was progression to respiratory failure. CALL score method was used to predict the expected number of cases of respiratory failure. High risk patients received methylprednisolone (MPS) 80 mg IV daily x 5 days starting no earlier than seven days from first onset of symptoms. The primary endpoint was progression to hypoxemic respiratory failure defined as PaO2 <60 mm Hg or oxygen saturation [≤]90%. Secondary endpoints included survival at 28 days from registration, admission to intensive care and live discharge from the hospital. Change in levels of inflammatory markers and length of hospitalization were also assessed.\n\nResultsIn 76 patients, the expected number with respiratory failure was 30 (39.5%), yet only 4 (5.3%) developed that complication (p=.00001). Survival at 28 days was 98.6%.\n\nImprovement in inflammatory markers correlated with favorable outcome.\n\nConclusionsOur results are encouraging and suggest that this approach is both effective and safe.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Shuchi Anand", - "author_inst": "Stanford University" - }, - { - "author_name": "Maria Montez-Rath", - "author_inst": "Stanford University" - }, - { - "author_name": "Jialin Han", - "author_inst": "Stanford University" - }, - { - "author_name": "LinaCel Cadden", - "author_inst": "Ascend Clinical" - }, - { - "author_name": "Patti Hunsader", - "author_inst": "Ascend Clinical" + "author_name": "Fernando Cabanillas", + "author_inst": "University of Puerto Rico School of Medicine" }, { - "author_name": "Russell Kerschmann", - "author_inst": "Ascend Clinical" + "author_name": "Javier Morales", + "author_inst": "Clinical Research Puerto Rico" }, { - "author_name": "Paul Beyer", - "author_inst": "Ascend Clinical" + "author_name": "Jose G. Conde", + "author_inst": "University of Puerto Rico Medical Sciences Campus" }, { - "author_name": "Scott D Boyd", - "author_inst": "Stanford University" + "author_name": "Jorge Bertran-Pasarell", + "author_inst": "University of Puerto Rico School of Medicine" }, { - "author_name": "Pablo Garcia", - "author_inst": "Stanford University" + "author_name": "Ricardo Fernandez", + "author_inst": "San Juan Bautista School of Medicine" }, { - "author_name": "Mary Dittrich", - "author_inst": "US Renal Care" + "author_name": "Yaimara Hernandez-Silva", + "author_inst": "Auxilio Mutuo Hospital" }, { - "author_name": "Geoffery A Block", - "author_inst": "US Renal Care" + "author_name": "Idalia Liboy", + "author_inst": "Auxilio Mutuo Hospital" }, { - "author_name": "Julie Parsonnet", - "author_inst": "Stanford University" + "author_name": "James Bryan-Diaz", + "author_inst": "University of Puerto Rico School of Medicine" }, { - "author_name": "Glenn M Chertow", - "author_inst": "Stanford University" + "author_name": "Juan Arraut-Gonzalez", + "author_inst": "Auxilio Mutuo Hospital" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -863935,31 +862815,31 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2021.03.08.434440", - "rel_title": "Comparative host interactomes of the SARS-CoV-2 nonstructural protein 3 and human coronavirus homologs", + "rel_doi": "10.1101/2021.03.08.434384", + "rel_title": "Comparative studies of the seven human coronavirus envelope proteins using topology prediction and molecular modelling to understand their pathogenicity", "rel_date": "2021-03-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.08.434440", - "rel_abs": "Human coronaviruses have become an increasing threat to global health; three highly pathogenic strains have emerged since the early 2000s, including most recently SARS-CoV-2, the cause of COVID-19. A better understanding of the molecular mechanisms of coronavirus pathogenesis is needed, including how these highly virulent strains differ from those that cause milder, common-cold like disease. While significant progress has been made in understanding how SARS-CoV-2 proteins interact with the host cell, non-structural protein 3 (nsp3) has largely been omitted from the analyses. Nsp3 is a viral protease with important roles in viral protein biogenesis, replication complex formation, and modulation of host ubiquitinylation and ISGylation. Herein, we use affinity purification-mass spectrometry to study the host-viral protein-protein interactome of nsp3 from five coronavirus strains: pathogenic strains SARS-CoV-2, SARS-CoV, and MERS-CoV; and endemic common-cold strains hCoV-229E and hCoV-OC43. We divide each nsp3 into three fragments and use tandem mass tag technology to directly compare the interactors across the five strains for each fragment. We find that few interactors are common across all variants for a particular fragment, but we identify shared patterns between select variants, such as ribosomal proteins enriched in the N-terminal fragment (nsp3.1) dataset for SARS-CoV-2 and SARS-CoV. We also identify unique biological processes enriched for individual homologs, for instance nuclear protein important for the middle fragment of hCoV-229E, as well as ribosome biogenesis of the MERS nsp3.2 homolog. Lastly, we further investigate the interaction of the SARS-CoV-2 nsp3 N-terminal fragment with ATF6, a regulator of the unfolded protein response. We show that SARS-CoV-2 nsp3.1 directly binds to ATF6 and can suppress the ATF6 stress response. Characterizing the host interactions of nsp3 widens our understanding of how coronaviruses co-opt cellular pathways and presents new avenues for host-targeted antiviral therapeutics.", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.08.434384", + "rel_abs": "Human (h) coronaviruses (CoVs) 229E, NL63, OC43, and HKU1 are less virulent and cause mild, self-limiting respiratory tract infections, while SARS-CoV, MERS-CoV, and SARS-CoV-2, are more virulent and have caused severe outbreaks. The CoV envelope (E) protein, an important contributor to the pathogenesis of severe hCoVs infections, may provide insight into this disparate severity of the disease. Topology prediction programs and 3D modelling software was used to predict and visualize structural aspects of the hCoV E protein related to its functions. All seven hCoV E proteins largely adopted different topologies, with some distinction between the more virulent and less virulent ones. The 3D models refined this distinction, showing the PDZ-binding motif (PBM) of SARS-CoV, MERS-CoV, and SARS-CoV-2 to be more flexible than the PBM of hCoVs 229E, NL63, OC43, and HKU1. We speculate that the increased flexibility of the PBM may provide the more virulent hCoVs with a greater degree of freedom, which can allow them to bind to different host proteins and can contribute to a more severe form of the disease. This is the first paper to predict the topologies and model 3D structures of all seven hCoVs E proteins, providing novel insights for possible drug and/or vaccine development.", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Katherine M Almasy", - "author_inst": "Vanderbilt University" + "author_name": "Dewald Schoeman", + "author_inst": "University of the Western Cape" }, { - "author_name": "Jonathan P Davies", - "author_inst": "Vanderbilt University" + "author_name": "Ruben Cloete", + "author_inst": "University of the Western Cape" }, { - "author_name": "Lars Plate", - "author_inst": "Vanderbilt University" + "author_name": "Burtram Fielding", + "author_inst": "University of the Western Cape" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "biochemistry" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.03.06.434059", @@ -865453,45 +864333,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.05.21251351", - "rel_title": "A single-center retrospective cohort study of Covid-19 medications: Remdesivir, Favipiravir, Methylprednisolone, Dexamethasone, and Interferon \u03b21a and their combinations", + "rel_doi": "10.1101/2021.03.04.21252942", + "rel_title": "Covid-19 in the California State Prison System: An Observational Study of Decarceration, Ongoing Risks, and Risk Factors", "rel_date": "2021-03-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.05.21251351", - "rel_abs": "Many drugs have been suggested to be used for Covid-19. A suitable and efficient choice of drug would make the course of Covid-19 easier. we have investigated the efficacy of different treatment regimen in reducing hospitalization period (HP) and mortality of 324 confirmed Covid-19 patients. Received drugs included single therapy or combinations of Methylprednisolone, Remdesivir, Favipiravir, Interferon {beta}1a, and Dexamethasone. HP and mortality were compared between different treatment groups to evaluate efficacy of each drug. HP and mortality were also calculated for patients in each treatment group based on their underlying diseases and age. we suggest that using IFN-{beta}1a, RDV and corticosteroids might not have a significant effect on the HP or mortality of the Covid-19 patients as it was thought before.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.04.21252942", + "rel_abs": "BackgroundCorrectional institutions nationwide are seeking to mitigate Covid-19-related risks.\n\nObjectiveTo quantify changes to Californias prison population since the pandemic began and identify risk factors for Covid-19 infection.\n\nDesignWe described residents demographic characteristics, health status, Covid-19 risk scores, room occupancy, and labor participation. We used Cox proportional hazard models to estimate the association between rates of Covid-19 infection and room occupancy and out-of-room labor, respectively.\n\nSettingCalifornia state prisons (March 1-October 10, 2020).\n\nParticipantsResidents of California state prisons.\n\nMeasurementsChanges in the incarcerated populations size, composition, housing, and activities. For the risk factor analysis, the exposure variables were room type (cells vs dormitories) and labor participation (any room occupant participating in the prior 2 weeks) and the outcome variable was incident Covid-19 case rates.\n\nResultsThe incarcerated population decreased 19.1% (119,401 to 96,623) during the study period.On October 10, 2020, 11.5% of residents were aged [≥]60, 18.3% had high Covid-19 risk scores, 31.0% participated in out-of-room labor, and 14.8% lived in rooms with [≥]10 occupants. Nearly 40% of residents with high Covid-19 risk scores lived in dormitories. In 9 prisons with major outbreaks (6,928 rooms; 21,750 residents), dormitory residents had higher infection rates than cell residents (adjusted hazard ratio [AHR], 2.51 95%CI, 2.25-2.80) and residents of rooms with labor participation had higher rates than residents of other rooms (AHR, 1.56; 95%CI, 1.39-1.74).\n\nLimitationsInability to measure density of residents living conditions or contact networks among residents and staff.\n\nConclusionDespite reductions in room occupancy and mixing, California prisons still house many medically vulnerable residents in risky settings. Reducing risks further requires a combination of strategies, including rehousing, decarceration, and vaccination.\n\nFunding SourcesHorowitz Family Foundation; National Institute on Drug Abuse; National Science Foundation Graduate Research Fellowship; Open Society Foundations.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Sahand Tehrani Fateh", - "author_inst": "Tehran University of Medical Sciences" + "author_name": "Elizabeth T Chin", + "author_inst": "Stanford University" }, { - "author_name": "Sepand Tehrani Fateh", - "author_inst": "Shahid Beheshti University of Medical Sciences" + "author_name": "Theresa Ryckman", + "author_inst": "Stanford University" }, { - "author_name": "Esmaeil Salehi", - "author_inst": "Isfahan University of Medical Sciences" + "author_name": "Lea Prince", + "author_inst": "Stanford University" }, { - "author_name": "Nima Rezai", - "author_inst": "Tehran University of Medical Sciences" + "author_name": "David Leidner", + "author_inst": "No Affiliation" + }, + { + "author_name": "Fernando Alarid-Escudero", + "author_inst": "Center for Research and Teaching in Economics (CIDE)" }, { - "author_name": "Nazanin Haririan", - "author_inst": "Science and Research Branch, Islamic Azad University" + "author_name": "Jason R Andrews", + "author_inst": "Stanford University" }, { - "author_name": "Abdollah Asgari", - "author_inst": "Isfahan University of Medical Sciences" + "author_name": "Joshua A Salomon", + "author_inst": "Stanford University" }, { - "author_name": "Amir Salehi-Najafabadi", - "author_inst": "University of Tehran" + "author_name": "David M Studdert", + "author_inst": "Stanford University" + }, + { + "author_name": "Jeremy D Goldhaber-Fiebert", + "author_inst": "Stanford University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -867383,63 +866271,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.05.21253011", - "rel_title": "Inflammatory but not respiratory symptoms associated with ongoing upper airway viral replication in outpatients with uncomplicated COVID-19", + "rel_doi": "10.1101/2021.03.06.21252603", + "rel_title": "BNT162b2 COVID-19 mRNA vaccine elicits a rapid and synchronized antibody response in blood and milk of breastfeeding women", "rel_date": "2021-03-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.05.21253011", - "rel_abs": "BackgroundThe vast majority of SARS-CoV-2 infections are uncomplicated and do not require hospitalization, but contribute to ongoing transmission. Our understanding of the clinical course of uncomplicated COVID-19 remains limited.\n\nMethodsWe detailed the natural history of uncomplicated COVID-19 among 120 outpatients enrolled in a randomized clinical trial of Peginterferon Lambda. We characterized symptom trajectory and clusters using exploratory factor analysis, assessed predictors of symptom resolution and cessation of oropharyngeal viral shedding using Cox proportional hazard models, and evaluated associations between symptoms and viral shedding using mixed effects linear models.\n\nResultsHeadache, myalgias and chills peaked at day 4 after symptom onset; cough peaked on day 9. Two distinct symptom cluster trajectories were identified; one with mild, upper respiratory symptoms, and the other with more severe and prolonged inflammatory symptoms. The median time to symptom resolution from earliest symptom onset was 17 days (95% CI 14-18). Neither enrollment SARS-CoV-2 IgG levels (Hazard ratio [HR] 1.88, 95% CI 0.84-4.20) nor oropharyngeal viral load at enrollment (HR 1.01, 95% CI 0.98-1.05) were significantly associated with the time to symptom resolution. The median time to cessation of viral shedding was 10 days (95% CI 8-12), with higher SARS-CoV-2 IgG levels at enrollment associated with hastened resolution of viral shedding (HR 3.12, 95% CI 1.4-6.9, p=0.005). Myalgia, joint pains, and chills were associated with a significantly greater odds of oropharyngeal SARS-CoV-2 RNA detection.\n\nConclusionsIn this outpatient cohort, inflammatory symptoms peaked early and were associated with ongoing SARS-CoV-2 replication. SARS-CoV-2 antibody levels were associated with more rapid viral shedding cessation, but not with time to symptom resolution. These findings have important implications for COVID-19 screening approaches and clinical trial design.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.06.21252603", + "rel_abs": "We describe the dynamics of the vaccine-specific antibody response in the breastmilk and serum in a prospective cohort of ten lactating women who received two doses of the Pfizer-BioNTech BNT162b2 COVID-19 mRNA vaccine. The antibody response was rapid and highly synchronized between breastmilk and serum, reaching stabilization 14 days after the second dose. The predominant serum antibody was IgG. The response in the breastmilk included both IgG and IgA with neutralizing capacity.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Karen Blake Jacobson", - "author_inst": "Stanford University" - }, - { - "author_name": "Natasha Purington", - "author_inst": "Stanford University" - }, - { - "author_name": "Julie Parsonnet", - "author_inst": "Stanford University" - }, - { - "author_name": "Jason R Andrews", - "author_inst": "Stanford University" + "author_name": "Michal Rosenberg Friedman", + "author_inst": "Tel Aviv Sourasky Medical Center" }, { - "author_name": "Vidhya Balasubramanian", - "author_inst": "Stanford University" + "author_name": "Aya Kigel", + "author_inst": "Tel Aviv University" }, { - "author_name": "Hector Bonilla", - "author_inst": "Stanford University" + "author_name": "Yael Bahar", + "author_inst": "Tel aviv university" }, { - "author_name": "Karlie Edwards", - "author_inst": "Stanford University" + "author_name": "Yariv Yogev", + "author_inst": "Tel Aviv Sourasky Medical Center" }, { - "author_name": "Manisha Desai", - "author_inst": "Stanford University" + "author_name": "Yael Dror", + "author_inst": "Tel aviv university" }, { - "author_name": "Upinder Singh", - "author_inst": "Stanford University" + "author_name": "Ronit lubetzky", + "author_inst": "Tel Aviv Sourasky Medical Center" }, { - "author_name": "Haley Hedlin", - "author_inst": "Stanford University" + "author_name": "Ariel Many", + "author_inst": "Tel Aviv Sourasky Medical Center" }, { - "author_name": "Prasanna Jagannathan", - "author_inst": "STANFORD SCHOOL OF MEDICINE" + "author_name": "Yariv Wine", + "author_inst": "Tel Aviv University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2021.03.06.21253058", @@ -869449,37 +868325,77 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.03.21252846", - "rel_title": "Short-stay admissions and lower staffing associated with larger COVID-19 outbreaks in Maryland nursing homes", + "rel_doi": "10.1101/2021.03.02.21252767", + "rel_title": "Geographic disparities in COVID-19 case rates are not reflected in seropositivity rates using a neighborhood survey in Chicago", "rel_date": "2021-03-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.03.21252846", - "rel_abs": "ObjectivesIdentify facility factors associated with a larger COVID-19 outbreak among residents in Maryland nursing homes (NHs).\n\nDesignObservational\n\nSetting and ParticipantsAll Maryland NHs.\n\nMethodsResident COVID-19 cases were collected for each Maryland NH from January 1, 2020 through July 1, 2020. Cumulative COVID-19 incidence through July 1, 2020 was collected for each county and Baltimore City. Facility characteristics for each Maryland NH were collected from time periods prior to January 1, 2020. NH outbreaks were defined as larger when total resident COVID-19 cases exceeded 10% of licensed beds. Descriptive and multivariable analyses were conducted to assess the strongest predictors for the primary outcome of larger COVID-19 outbreak.\n\nResultsNHs located in counties with high cumulative incidence of COVID-19 were more likely to have larger outbreaks (OR 4.5, 95% CI 2.3-8.7, p<0.01). NHs with at least 100 beds were more likely to have larger outbreaks, especially among facilities with >140 licensed beds (100-140 beds vs <100 beds: OR 1.9, 95% CI 0.9-4.1, p=0.09; >140 beds vs <100 beds: OR 2.9, 95% CI 1.3-6.1, p<0.01). NHs with more short-stay residents (OR 2.2, 95% CI 1.1-4.8, p=0.04) or fewer Certified Nursing Assistant hours daily (OR 2.6, 95% CI 1.3-5.3, p<0.01) also were more likely to have larger outbreaks. Resident race and gender were not significant predictors of larger outbreaks after adjustment for other factors.\n\nConclusionsLarge NHs with lower staffing levels and many short-stay residents in counties with high COVID-19 incidence were at increased risk for COVID-19 outbreaks. Understanding the characteristics of nursing homes associated with larger outbreaks can help us prepare for the next pandemic.\n\nBrief summaryMaryland nursing homes in counties with a high COVID-19 incidence, more licensed beds, a higher proportion of short-stay residents, or lower CNA staffing hours were more likely to have a larger outbreak early in the pandemic.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.02.21252767", + "rel_abs": "To date, COVID-19 case rates are disproportionately higher in Black and Latinx communities across the U.S., leading to more hospitalizations and deaths in those communities. These differences in case rates are evident in comparisons of Chicago neighborhoods with differing race/ethnicities of their residents. Disparities could be due to neighborhoods with more adverse health outcomes associated with poverty and other social determinants of health experiencing higher prevalence of SARS-CoV-2 infection or due to greater morbidity and mortality resulting from equivalent SARS-CoV-2 infection prevalence. We surveyed five pairs of adjacent ZIP codes in Chicago with disparate COVID-19 case rates for highly specific and quantitative serological evidence of any prior infection by SARS-CoV-2 to compare with their disparate COVID-19 case rates. Dried blood spot samples were self-collected at home by internet-recruited participants in summer 2020, shortly after Chicagos first wave of the COVID-19 pandemic. Pairs of neighboring ZIP codes with very different COVID-19 case rates had similar seropositivity rates for anti-SARS-CoV-2 receptor binding domain IgG antibodies. Overall, these findings of comparable exposure to SARS-CoV-2 across neighborhoods with very disparate COVID-19 case rates are consistent with social determinants of health, and the comorbidities related to them, driving differences in COVID-19 rates across neighborhoods.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "T. Joseph Mattingly II", - "author_inst": "University of Maryland School of Pharmacy" + "author_name": "Brian Mustanski", + "author_inst": "Institute for Sexual and Gender Minority Health and Wellbeing, Northwestern University; Department of Medical Social Sciences, Northwestern University" }, { - "author_name": "Alison Trinkoff", - "author_inst": "University of Maryland School of Nursing" + "author_name": "Rana Saber", + "author_inst": "Institute for Sexual and Gender Minority Health and Wellbeing, Northwestern University; Department of Medical Social Sciences, Northwestern University" }, { - "author_name": "Alison D Lydecker", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Daniel T. Ryan", + "author_inst": "Institute for Sexual and Gender Minority Health and Wellbeing, Northwestern University; Department of Medical Social Sciences, Northwestern University" }, { - "author_name": "Justin J Kim", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Nanette Benbow", + "author_inst": "Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University" }, { - "author_name": "Jung Min Yoon", - "author_inst": "University of Maryland School of Nursing" + "author_name": "Krystal Madkins", + "author_inst": "Institute for Sexual and Gender Minority Health and Wellbeing, Northwestern University; Department of Medical Social Sciences, Northwestern University" }, { - "author_name": "Mary-Claire Roghmann", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Christina Hayford", + "author_inst": "Third Coast Center for AIDS Research, Northwestern University" + }, + { + "author_name": "Michael E. Newcomb", + "author_inst": "Institute for Sexual and Gender Minority Health and Wellbeing, Northwestern University; Department of Medical Social Sciences, Northwestern University" + }, + { + "author_name": "Joshua M. Schrock", + "author_inst": "Institute for Sexual and Gender Minority Health and Wellbeing, Northwestern University; Department of Medical Social Sciences, Northwestern University" + }, + { + "author_name": "Lauren A. Vaught", + "author_inst": "Center for Genetic Medicine, Northwestern University; Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine" + }, + { + "author_name": "Nina L. Reiser", + "author_inst": "Center for Genetic Medicine, Northwestern University; Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine" + }, + { + "author_name": "Matthew P. Velez", + "author_inst": "Center for Genetic Medicine, Northwestern University; Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine" + }, + { + "author_name": "Ryan Hsieh", + "author_inst": "Center for Genetic Medicine, Northwestern University; Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine" + }, + { + "author_name": "Alexis R. Demonbreun", + "author_inst": "Center for Genetic Medicine, Northwestern University; Department of Pharmacology, Northwestern University Feinberg School of Medicine" + }, + { + "author_name": "Richard D'Aquila", + "author_inst": "Division of Infectious Diseases, Dept. of Medicine, Northwestern University Feinberg School of Medicine" + }, + { + "author_name": "Elizabeth M. McNally", + "author_inst": "Center for Genetic Medicine, Northwestern University; Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine; Depar" + }, + { + "author_name": "Thomas W. McDade", + "author_inst": "Department of Anthropology, Northwestern University; Institute for Policy Research, Northwestern University" } ], "version": "1", @@ -871143,107 +870059,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.03.05.434038", - "rel_title": "Scent dog identification of SARS-CoV-2 infections, similar across different body fluids", + "rel_doi": "10.1101/2021.03.05.433666", + "rel_title": "Analysis of SARS-CoV-2 Mutations Over Time Reveals Increasing Prevalence of Variants in the Spike Protein and RNA-Dependent RNA Polymerase", "rel_date": "2021-03-05", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.05.434038", - "rel_abs": "BackgroundThe main strategy to contain the current SARS-CoV-2 pandemic remains to implement a comprehensive testing, tracing and quarantining strategy until vaccination of the population is adequate.\n\nMethodsTen dogs were trained to detect SARS-CoV-2 infections in beta-propiolactone inactivated saliva samples. The subsequent cognitive transfer performance for the recognition of non-inactivated samples were tested on saliva, urine, and sweat in a randomised, double-blind controlled study.\n\nResultsDogs were tested on a total of 5242 randomised sample presentations. Dogs detected non-inactivated saliva samples with a diagnostic sensitivity of 84% and specificity of 95%. In a subsequent experiment to compare the scent recognition between the three non-inactivated body fluids, diagnostic sensitivity and specificity were 95% and 98% for urine, 91% and 94% for sweat, 82%, and 96% for saliva respectively.\n\nConclusionsThe scent cognitive transfer performance between inactivated and non-inactivated samples as well as between different sample materials indicates that global, specific SARS-CoV-2-associated volatile compounds are released across different body secretions, independently from the patients symptoms.\n\nFundingThe project was funded as a special research project of the German Armed Forces. The funding source DZIF-Fasttrack 1.921 provided us with means for biosampling.", - "rel_num_authors": 22, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.05.433666", + "rel_abs": "Amid the ongoing COVID-19 pandemic, it has become increasingly important to monitor the mutations that arise in the SARS-CoV-2 virus, to prepare public health strategies and guide the further development of vaccines and therapeutics. The spike (S) protein and the proteins comprising the RNA-Dependent RNA Polymerase (RdRP) are key vaccine and drug targets, respectively, making mutation surveillance of these proteins of great importance.\n\nFull protein sequences for the spike proteins and RNA-dependent RNA polymerase proteins were downloaded from the GISAID database, aligned, and the variants identified. Polymorphisms in the protein sequence were investigated at the protein structural level and examined longitudinally in order to identify sequence and strain variants that are emerging over time. Our analysis revealed a group of variants in the spike protein and the polymerase complex that appeared in August, and account for around five percent of the genomes analyzed up to the last week of October. A structural analysis also facilitated investigation of several unique variants in the receptor binding domain and the N-terminal domain of the spike protein, with high-frequency mutations occurring more commonly in these regions. The identification of new variants emphasizes the need for further study on the effects of these mutations and the implications of their increased prevalence, particularly as these mutations may impact vaccine or therapeutic efficacy.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Paula Jendrny", - "author_inst": "Department of Small Animal Medicine and Surgery, University of Veterinary Medicine Hannover, Hannover, Germany" - }, - { - "author_name": "Friederike Twele", - "author_inst": "Department of Small Animal Medicine and Surgery, University of Veterinary Medicine Hannover, Hannover, Germany" - }, - { - "author_name": "Sebastian Meller", - "author_inst": "Department of Small Animal Medicine and Surgery, University of Veterinary Medicine Hannover, Hannover, Germany" - }, - { - "author_name": "Claudia Schulz", - "author_inst": "Research Center for Emerging Infections and Zoonoses, University of Veterinary Medicine Hannover, Hannover, Germany" - }, - { - "author_name": "Maren von Koeckritz-Blickwede", - "author_inst": "Research Center for Emerging Infections and Zoonoses, University of Veterinary Medicine Hannover, Hannover, Germany; Department of Biochemistry, University of V" - }, - { - "author_name": "Albert Osterhaus", - "author_inst": "Research Center for Emerging Infections and Zoonoses, University of Veterinary Medicine Hannover, Hannover, Germany" - }, - { - "author_name": "Hans Ebbers", - "author_inst": "KynoScience UG, Hoerstel, Germany" - }, - { - "author_name": "Janek Ebbers", - "author_inst": "KynoScience UG, Hoerstel, Germany" - }, - { - "author_name": "Veronika Pilchova", - "author_inst": "Research Center for Emerging Infections and Zoonoses, University of Veterinary Medicine Hannover, Hannover, Germany" - }, - { - "author_name": "Isabell Pink", - "author_inst": "Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany" - }, - { - "author_name": "Tobias Welte", - "author_inst": "Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany" - }, - { - "author_name": "Michael Peter Manns", - "author_inst": "Hannover Medical School, Hannover, Germany" - }, - { - "author_name": "Anahita Fathi", - "author_inst": "Department of Medicine, Division of Infectious Diseases, University Medical-Center Hamburg-Eppendorf, Hamburg, Germany; Department for Clinical Immunology of In" - }, - { - "author_name": "Marylyn Martina Addo", - "author_inst": "Department of Medicine, Division of Infectious Diseases, University Medical-Center Hamburg-Eppendorf, Hamburg, Germany; Department for Clinical Immunology of In" - }, - { - "author_name": "Christiane Ernst", - "author_inst": "Bundeswehr Medical Service Headquarters, Koblenz, Germany" - }, - { - "author_name": "Wencke Schaefer", - "author_inst": "Bundeswehr School of Dog handling, Ulmen, Germany" - }, - { - "author_name": "Michael Engels", - "author_inst": "Bundeswehr School of Dog handling, Ulmen, Germany" - }, - { - "author_name": "Anja Petrov", - "author_inst": "Central Institute of the Bundeswehr Medical Service Kiel, Kronshagen, Germany" - }, - { - "author_name": "Katharina Marquart", - "author_inst": "Central Institute of the Bundeswehr Medical Service Kiel, Kronshagen, Germany" + "author_name": "William M Showers", + "author_inst": "National Jewish Health" }, { - "author_name": "Ulrich Schotte", - "author_inst": "Central Institute of the Bundeswehr Medical Service Kiel, Kronshagen, Germany" + "author_name": "Sonia M Leach", + "author_inst": "National Jewish Health" }, { - "author_name": "Esther Schalke", - "author_inst": "Bundeswehr School of Dog handling, Ulmen, Germany" + "author_name": "Katerina Kechris", + "author_inst": "University of Colorado, Anschutz Medical Campus" }, { - "author_name": "Holger Andreas Volk", - "author_inst": "Department of Small Animal Medicine and Surgery, University of Veterinary Medicine Hannover, Hannover, Germany" + "author_name": "Michael Strong", + "author_inst": "National Jewish Health" } ], "version": "1", - "license": "cc_by_nc", - "type": "new results", - "category": "animal behavior and cognition" + "license": "cc_by_nd", + "type": "confirmatory results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.03.05.434152", @@ -873045,45 +871889,141 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.01.21252696", - "rel_title": "Genetic variation of IFNL4 is associated with COVID-19", + "rel_doi": "10.1101/2021.02.22.21252091", + "rel_title": "A single dose of SARS CoV 2 FINLAY FR 1A dimeric RBD recombinant vaccine enhances neutralization response in COVID19 convalescents, with excellent safety profile. A preliminary report of an open-label phase 1 clinical trial", "rel_date": "2021-03-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.01.21252696", - "rel_abs": "COVID-19 currently represents a major public health problem. The causes that underlying susceptibility to infection in have not yet been determined. Interferons (IFNs) are intensively being investigated because of their antiviral properties. Among them, Interferon lambda 4 (IFNL4) has been reported to have antiviral activity against viral infections of the upper respiratory tract, Hepatitis virus C (HCV), and coronaviruses. The importance of this cytokine was shown by the fact that genetic variants of IFNL4 have been associated with viral clearance and response to IFNs-based therapies in HCV and other infections by RNA virus. In this study, we have investigated whether the rs12979860 polymorphism within the IFNL4 was also associated with COVID-19. Our findings show that the presence of the CC allele of rs12979860 was significantly lower in SARS-CoV-2 infected patients with regard to non-COVID-19 controls (38% vs 55%, p<0001). These results were not affected by sex, age, and severity of disease. These findings suggest that the CC allele may also confer protection against COVID-19. They may contribute to understanding the mechanisms of disease, the response to IFN-based treatments, and the racial differences observed in the disease.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.22.21252091", + "rel_abs": "We evaluated response to a single dose of the FINLAY-FR-1A recombinant dimeric-RBD base vaccine during a phase I clinical trial with 30 COVID-19 convalescents, to test its capacity for boosting natural immunity. This short report shows: a) an excellent safety profile one month after vaccination for all participants, similar to that previously found during vaccination of naive individuals; b) a single dose of vaccine induces a >20 fold increase in antibody response one week after vaccination and remarkably 4-fold higher virus neutralization compared to the median obtained for Cuban convalescent serum panel. These preliminary results prompt initiation of a phase II trial in order to establish a general vaccination protocol for convalescents.", + "rel_num_authors": 31, "rel_authors": [ { - "author_name": "Jose Maria R Saponi-Cortes", - "author_inst": "Servicio Medicina Interna, Complejo Hospitalario Universitario de Caceres" + "author_name": "Arturo Chang-Monteagudo", + "author_inst": "Institute of Hematology and Immunology, Havana, Cuba" }, { - "author_name": "Maria Dolores Rivas", - "author_inst": "Unidad de Investigacion, Complejo Hospitalario Universitario de Caceres" + "author_name": "Rolando Ochoa-Azze", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba." }, { - "author_name": "Fernando Calle", - "author_inst": "Deparamento deEstadistica, Universidad de Extrremadura, Caceres, Spain" + "author_name": "Yanet Climent-Ruiz", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" }, { - "author_name": "Juan Francisco Sanchez Munoz-Torrero", - "author_inst": "Servicio de Medicina Interna, Complejo Hospitalario Universitario de Caceres" + "author_name": "Consuelo Macias-Abraham", + "author_inst": "Institute of Hematology and Immunology, Havana, Cuba" }, { - "author_name": "Alberto Costo", - "author_inst": "Servicio Medicina Interna. Complejo Hospitalario Universitario de Caceres" + "author_name": "Laura Rodriguez-Noda", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" }, { - "author_name": "Carlos Martin", - "author_inst": "Servicio Medicina Interna. Complejo Hospitalario Universitario de Caceres" + "author_name": "Carmen Valenzuela-Silva", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" }, { - "author_name": "Jose Zamorano", - "author_inst": "Unidad de Investigacion, Complejo Hospitalario Universitario de Caceres" + "author_name": "Belinda Sanchez-Ramirez", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" + }, + { + "author_name": "Rocmira Perez-Nicado", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" + }, + { + "author_name": "Raul Gonzalez-Mugica", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" + }, + { + "author_name": "Tays Hernandez-Garcia", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" + }, + { + "author_name": "Ivette Orosa-Vazquez", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" + }, + { + "author_name": "Marianniz Diaz-Hernandez", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" + }, + { + "author_name": "Maria de los A. Garcia-Garcia", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" + }, + { + "author_name": "Yanet Jerez-Barcelo", + "author_inst": "Institute of Hematology and Immunology, Havana, Cuba" + }, + { + "author_name": "Yenisey Triana-Marrero", + "author_inst": "Institute of Hematology and Immunology, Havana, Cuba" + }, + { + "author_name": "Laura Ruiz-Villegas", + "author_inst": "Institute of Hematology and Immunology, Havana, Cuba" + }, + { + "author_name": "Luis Rodriguez-Prieto", + "author_inst": "Institute of Hematology and Immunology, Havana, Cuba" + }, + { + "author_name": "Rinaldo Puga-Gomez", + "author_inst": "Cira Garcia Clinic, Calle 20 NO. 4101 esq. a Av. 41 Miramar, La Habana" + }, + { + "author_name": "Pedro Pablo Guerra-Chaviano", + "author_inst": "National Center for Coordination of Clinical Trial (CENCEC) Calle 5ta A e/ 60 y 62 Miramar, Playa, CP 11300, La Habana, Cuba" + }, + { + "author_name": "Yaima Zuniga-Rosales", + "author_inst": "National Center of Medical Genetics, Ave. 31 Esq.146 No 3102, Reparto Cubanacan CP. 11400" + }, + { + "author_name": "Beatriz Marcheco-Teruel", + "author_inst": "National Center of Medical Genetics, Ave. 31 Esq.146 No 3102, Reparto Cubanacan CP. 11400" + }, + { + "author_name": "Mireida Rodriguez-Acosta", + "author_inst": "National Civil Defense Research Laboratory, Cuba" + }, + { + "author_name": "Enrique Noa-Romero", + "author_inst": "National Civil Defense Research Laboratory, Cuba" + }, + { + "author_name": "Juliet Enriquez-Puertas", + "author_inst": "National Civil Defense Research Laboratory, Cuba" + }, + { + "author_name": "Delia Porto-Gonzalez", + "author_inst": "National Blood Program, Ministry of Health, Cuba" + }, + { + "author_name": "Kalet Leon-Monzon", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" + }, + { + "author_name": "Guang-Wu Chen", + "author_inst": "Chengdu Olisynn Biotech. Co. Ltd., and State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, Peoples Re" + }, + { + "author_name": "Luis Herrera Martinez", + "author_inst": "Biocubafarma, Ave. Independencia #8126, esq. a Calle 100. Boyeros. La Habana. Cuba" + }, + { + "author_name": "Yury Valdes-Balbin", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" + }, + { + "author_name": "Dagmar Garcia-Rivera", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" + }, + { + "author_name": "Vicente Verez-Bencomo", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba." } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -875367,25 +874307,93 @@ "category": "nephrology" }, { - "rel_doi": "10.1101/2021.02.28.21252642", - "rel_title": "Modeling COVID-19 Nonpharmaceutical Interventions: Exploring periodic NPI strategies", + "rel_doi": "10.1101/2021.02.27.21252427", + "rel_title": "Comparative performance of SARS-CoV-2 lateral flow antigen tests demonstrates their utility for high sensitivity detection of infectious virus in clinical specimens", "rel_date": "2021-03-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.28.21252642", - "rel_abs": "In April 2020, we developed a COVID-19 transmission model used as part of RANDs web-based COVID-19 decision support tool that compares the effects of different nonphar-maceutical public health interventions (NPIs) on health and economic outcomes. An interdis-ciplinary approach informed the selection and use of multiple NPIs, combining quantitative modeling of the health/economic impacts of interventions with qualitative assessments of other important considerations (e.g., cost, ease of implementation, equity). We previously published a description of our approach as a RAND report describing how the epidemiological model, the economic model, and a systematic assessment of NPIs informed the web-tool. This paper provides further details of our model, describes extensions that we made to our model since April, presents sensitivity analyses, and analyzes periodic NPIs. Our findings suggest that there are opportunities to shape the tradeoffs between economic and health outcomes by carefully evaluating a more comprehensive range of reopening policies. We consider strategies that periodically switch between a base NPI level and a higher NPI level as our working example.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.27.21252427", + "rel_abs": "BackgroundRapid antigen lateral flow devices (LFDs) are set to become a cornerstone of SARS-CoV-2 mass community testing. However, their reduced sensitivity compared to PCR has raised questions of how well they identify infectious cases. Understanding their capabilities and limitations is therefore essential for successful implementation. To address this, we evaluated six commercial LFDs on the same collection of clinical samples and assessed their correlation with infectious virus culture and cycle threshold (Ct) values.\n\nMethodsA head-to-head comparison of specificities and sensitivities was performed on six commercial rapid antigen tests using combined nasal/oropharyngeal swabs, and their limits of detection determined using viral plaque forming units (PFU). Three of the LFDs were selected for a further study, correlating antigen test result with RT-PCR Ct values and positive viral culture in Vero-E6 cells. This included sequential swabs and matched serum samples obtained from four infected individuals with varying disease severities. Detection of antibodies was performed using an IgG/IgM Rapid Test Cassette, and neutralising antibodies by infectious virus assay. Finally, the sensitivities of selected rapid antigen LFTs were assessed in swabs with confirmed B.1.1.7 variant, currently the dominant genotype in the UK.\n\nFindingsMost of the rapid antigen LFDs showed a high specificity (>98%), and accurately detected 50 PFU/test (equivalent N1 Ct of 23.7 or RNA copy number of 3x106/ml). Sensitivities of the LFDs performed on clinical samples ranged from 65 to 89%. These sensitivities increased in most tests to over 90% for samples with Cts lower than 25. Positive virus culture was achieved for 57 out of 141 samples, with 80% of the positive cultures from swabs with Cts lower than 23. Importantly, sensitivity of the LFDs increased to over 95% when compared with the detection of infectious virus alone, irrespective of Ct. Longitudinal studies of PCR-positive samples showed that most of the tests identified all infectious samples as positive, but differences in test sensitivities can lead to missed cases in the absence of repeated testing. Finally, test performance was not impacted when re-assessed against swabs positive for the dominant UK variant B.1.1.7.\n\nInterpretationIn this comprehensive comparison of antigen LFD and virus infectivity, we demonstrate a clear relationship between Ct values, quantitative culture of infectious virus and antigen LFD positivity in clinical samples. Our data support regular testing of target groups using LFDs to supplement the current PCR testing capacity, to rapidly identify infected individuals in situations where they would otherwise go undetected.\n\nFundingKings Together Rapid COVID-19, Medical Research Council, Wellcome Trust, Huo Family Foundation.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Raffaele Vardavas", - "author_inst": "RAND Corporation" + "author_name": "Suzanne Pickering", + "author_inst": "Department of Infectious Diseases, School of Immunology & Microbial Sciences, King's College London, London, United Kingdom" }, { - "author_name": "Pedro Nascimento de Lima", - "author_inst": "RAND Corporation" + "author_name": "Rahul Batra", + "author_inst": "Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom" }, { - "author_name": "Lawrence Baker", - "author_inst": "RAND Corporation" + "author_name": "Luke B Snell", + "author_inst": "Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom" + }, + { + "author_name": "Blair Merrick", + "author_inst": "Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom" + }, + { + "author_name": "Gaia Nebbia", + "author_inst": "Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom" + }, + { + "author_name": "Sam Douthwaite", + "author_inst": "Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom" + }, + { + "author_name": "Amita Patel", + "author_inst": "Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom" + }, + { + "author_name": "Mark TK Ik", + "author_inst": "Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom" + }, + { + "author_name": "Bindi Patel", + "author_inst": "Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom" + }, + { + "author_name": "Themoula Charalampous", + "author_inst": "Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom" + }, + { + "author_name": "Adela Alcolea-Medina", + "author_inst": "Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom" + }, + { + "author_name": "Maria Jose Lista", + "author_inst": "Department of Infectious Diseases, School of Immunology & Microbial Sciences, King's College London, London, United Kingdom" + }, + { + "author_name": "Penelope R Cliff", + "author_inst": "Viapath Group LLP, Guy's and St Thomas' NHS Foundation Trust, London, UK" + }, + { + "author_name": "Emma Cunningham", + "author_inst": "Viapath Group LLP, Guy's and St Thomas' NHS Foundation Trust, London, UK" + }, + { + "author_name": "Jane Mullen", + "author_inst": "Viapath Group LLP, Guy's and St Thomas' NHS Foundation Trust, London, UK" + }, + { + "author_name": "Katie J Doores", + "author_inst": "Department of Infectious Diseases, School of Immunology & Microbial Sciences, King's College London, London, United Kingdom" + }, + { + "author_name": "Jonathan D Edgeworth", + "author_inst": "Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom" + }, + { + "author_name": "Michael H Malim", + "author_inst": "Department of Infectious Diseases, School of Immunology & Microbial Sciences, King's College London, London, United Kingdom" + }, + { + "author_name": "Stuart JD Neil", + "author_inst": "Department of Infectious Diseases, School of Immunology & Microbial Sciences, King's College London, London, United Kingdom" + }, + { + "author_name": "Rui Pedro Galao", + "author_inst": "Department of Infectious Diseases, School of Immunology & Microbial Sciences, King's College London, London, United Kingdom" } ], "version": "1", @@ -877313,67 +876321,63 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.03.01.433130", - "rel_title": "Safety and Immunogenicity Evaluation of Inactivated whole-virus-SARS-COV-2 In Mice As Emerging Vaccine Development In Egypt", + "rel_doi": "10.1101/2021.03.01.433501", + "rel_title": "In vitro evaluation of the activity of terpenes and cannabidiol against Human Coronavirus E229", "rel_date": "2021-03-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.01.433130", - "rel_abs": "The current worldwide pandemic COVID-19 is causing severe human health problems, with high numbers of mortality rates and huge economic burdens that require an urgent demand for safe, and effective and vaccine development. Our study was the first trail to development and evaluation of safety and immune response to inactivated whole SARS-COV-2 virus vaccine adjuvanted with aluminium hydroxide. We used characterized SARS-COV-2 strain, severe acute respiratory syndrome coronavirus 2 isolates (SARS-CoV-2/human/EGY/Egy-SERVAC/2020) with accession numbers; MT981440; MT981439; MT981441; MT974071; MT974069 and MW250352 at GenBank that isolated from Egyptian patients SARS-CoV-2-positive. Development of the vaccine was carried out in a BSL - 3 facilities and the immunogenicity was determined in mice at two doses (55{micro}g and 100{micro}g per dose). All vaccinated mice were received a booster dose 14 days post first immunization. Our results demonstrated distinct cytopathic effect on the vero cell monolayers induced through SARS-COV-2 propagation and the viral particles were identified as Coronaviridae by transmission electron microscopy. SARS-CoV-2 was identified by RT-PCR performed on the cell culture. Immunogenicity of the developed vaccine indicated the high antigen-binding and neutralizing antibody titers, regardless the dose concentration, with excellent safety profiles.However, no deaths or clinical symptoms in mice groups. The efficacy of the inactivated vaccine formulation was tested by wild virus challenge the vaccinated mice and detection of viral replication in lung tissues. Vaccinated mice recorded complete protection from challenge infection three weeks post second dose. SARS-COV-2 replication was not observed in the lungs of mice following SARS-CoV-2 challenge, regardless of the level of serum neutralizing antibodies. This finding will support the future trials for evaluation an applicable SARS-CoV-2 vaccine candidate.", - "rel_num_authors": 12, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.01.433501", + "rel_abs": "The activity of a new, terpene-based formulation, code-named NT-VRL-1, against Human Coronavirus (HCoV) strain 229E was evaluated in human lung fibroblasts (MRC-5 cells), with and without the addition of cannabidiol (CBD). The tested formulation exhibited an antiviral effect when it was pre-incubated with the host cells prior to virus infection. The combination of NT-VRL-1 with CBD potentiated the antiviral effect better than the positive controls pyrazofurin and glycyrrhizin. There was a strong correlation between the quantitative results from a cell-viability assay and the cytopathic effect seen under the microscope after 72 h. To the best of our knowledge, this is the first report of activity of a combination of terpenes and CBD against a coronavirus.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Amani Ali Ali", - "author_inst": "VSVRI- veterinary serum and vaccine research institute" + "author_name": "Lior Chatow", + "author_inst": "Eybna Technologies Ltd." }, { - "author_name": "Mohamed A Saad", - "author_inst": "A.R.C. Veterinary Serum Vaccine Research Institute (VSVRI) Cairo, Egypt" + "author_name": "Adi Nudel", + "author_inst": "Eybna Technologies Ltd." }, { - "author_name": "Islam Ryan", - "author_inst": "Egyptian Army Veterinary Corps, Cairo Egypt" + "author_name": "Iris Nesher", + "author_inst": "Eybna Technologies Ltd." }, { - "author_name": "Magdy Amin", - "author_inst": "Military Medical Services, Cairo, Egypt" + "author_name": "David Hayo Hemo", + "author_inst": "Eybna Technologies Ltd." }, { - "author_name": "Mohamed I Shindy", - "author_inst": "Egyptian Army Veterinary Corps, Cairo Egypt" + "author_name": "Perri Rozenberg", + "author_inst": "Pharmaseed Ltd." }, { - "author_name": "Wael A Hassan", - "author_inst": "Egypt Center for Research and Regenerative Medicine, Cairo, Egypt" + "author_name": "Hanna Voropaev", + "author_inst": "Pharmaseed Ltd." }, { - "author_name": "Mahmoud Samir", - "author_inst": "Egypt Center for Research and Regenerative Medicine, Cairo, Egypt" + "author_name": "Ilan Winkler", + "author_inst": "Pharmaseed Ltd." }, { - "author_name": "Ayman A Khattab", - "author_inst": "Egypt Center for Research and Regenerative Medicine, Cairo, Egypt" + "author_name": "Ronnie Levy", + "author_inst": "Pharmaseed Ltd." }, { - "author_name": "Sherein S Abdelgayed", - "author_inst": "Faculty of Veterinary Medicine, Cairo University, Giza, Egypt" - }, - { - "author_name": "Mohamed Gomaa Seadawy", - "author_inst": "MCL-- Main Chemical Laboratories, Egypt Army" + "author_name": "Zohar Kerem", + "author_inst": "Hebrew University of Jerusalem" }, { - "author_name": "Fahmy M Fahmy", - "author_inst": "Faculty of Medicine, Ain Shams University, Cairo, Egypt" + "author_name": "Zohara Yaniv", + "author_inst": "ARO, Volcani Center" }, { - "author_name": "Khaled Amer", - "author_inst": "Egypt Center for Research and Regenerative Medicine, Cairo, Egypt" + "author_name": "Nadav Eyal", + "author_inst": "Eybna Technologies Ltd." } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.03.01.21252598", @@ -878935,151 +877939,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.27.21252169", - "rel_title": "Risk factors for illness severity among pregnant women with confirmed SARS-CoV-2 infection - Surveillance for Emerging Threats to Mothers and Babies Network, 20 state, local, and territorial health departments, March 29, 2020 -January 8, 2021", + "rel_doi": "10.1101/2021.03.01.433344", + "rel_title": "In vitro screening of herbal medicinal products for their supportive curing potential in the context of SARS-CoV-2", "rel_date": "2021-03-01", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.27.21252169", - "rel_abs": "BackgroundPregnant women with coronavirus disease 2019 (COVID-19) are at increased risk for severe illness compared with nonpregnant women. Data to assess risk factors for illness severity among pregnant women with COVID-19 are limited. This study aimed to determine risk factors associated with COVID-19 illness severity among pregnant women with SARS-CoV-2 infection.\n\nMethodsPregnant women with SARS-CoV-2 infection confirmed by molecular testing were reported during March 29, 2020-January 8, 2021 through the Surveillance for Emerging Threats to Mothers and Babies Network (SET-NET). Criteria for illness severity (asymptomatic, mild, moderate-to-severe, or critical) were adapted from National Institutes of Health and World Health Organization criteria. Crude and adjusted risk ratios for moderate-to-severe or critical COVID-19 illness were calculated for selected demographic and clinical characteristics.\n\nResultsAmong 5,963 pregnant women with SARS-CoV-2 infection, moderate-to-severe or critical COVID-19 illness was associated with age 30-39 years, Black/Non-Hispanic race/ethnicity, healthcare occupation, pre-pregnancy obesity, chronic lung disease, chronic hypertension, cardiovascular disease, and pregestational diabetes mellitus. Risk of moderate-to-severe or critical illness increased with the number of underlying medical or pregnancy-related conditions.\n\nConclusionsPregnant women with moderate-to-severe or critical COVID-19 illness were more likely to be older and have underlying medical conditions compared to pregnant women with asymptomatic infection or mild COVID-19 illness. This information might help pregnant women understand their risk for moderate-to-severe or critical COVID-19 illness and inform targeted public health messaging.\n\nSummaryAmong pregnant women with COVID-19, older age and underlying medical conditions were risk factors for increased illness severity. These findings can be used to inform pregnant women about their risk for severe COVID-19 illness and public health messaging.", - "rel_num_authors": 33, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.01.433344", + "rel_abs": "BackgroundHerbal medicinal products have a long-standing history of use in the therapy of common respiratory infections. In the COVID-19 pandemic, they may have the potential for symptom relief in non-severe or moderate disease cases. Here we describe the results derived by in vitro screening of five herbal medicinal products with regard to their potential to i) interfere with the binding of the human Angiotensin-converting enzyme 2 (ACE2) receptor with the SARS-CoV-2 Spike S1 protein, ii) modulate the release of the human defensin HBD1 and cathelicidin LL-37 from human A549 lung cells upon Spike S1 protein stimulation and iii) modulate the release of IFN-{gamma} from activated human peripheral blood mononuclear cells (PBMC). The investigated extracts were: Sinupret extract (SINx), Bronchipret thyme-ivy (BRO TE), Bronchipret thyme-primrose (BRO TP), Imupret (IMU), and Tonsipret (TOP).\n\nMethodsThe inhibitory effect of the herbal medicinal products on the binding interaction of Spike S1 protein and the human ACE2 receptor was measured by ELISA. The effects on intracellular IFN-{gamma} expression in stimulated human PBMCs were measured by flow cytometry. Regulation on HBD1 and LL-37 expression and secretion was assessed in 25d long-term cultured human lung A549 epithelial cells by RT-PCR and ELISA.\n\nResultsIMU and BRO TE concentration-dependently inhibited the interaction between spike protein and the ACE2 Receptor. However, this effect was only observed in the cell-free assay at a concentration range which was later on determined as cytotoxic to human PBMC. SINx, TOP and BRO TP significantly upregulated the intracellular expression of antiviral IFN{gamma} from stimulated PBMC. Co-treatment of A549 cells with IMU or BRO TP together with SARS-CoV-2 spike protein significantly upregulated mRNA expression (IMU) and release (IMU and BRO TP) of HBD1 and LL-37 (BRO TP).\n\nConclusionsThe in vitro screening results provide first evidence for an immune activating potential of some of the tested herbal medicinal extracts in the context of SARS-CoV-2. Whether these could be helpful in prevention of SARS-CoV-2 invasion or supportive in recovery from SARS-CoV-2 infection needs deeper understanding of the observations.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Romeo R Galang", - "author_inst": "CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA" - }, - { - "author_name": "Suzanne M Newton", - "author_inst": "CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA" - }, - { - "author_name": "Kate R Woodworth", - "author_inst": "CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA" - }, - { - "author_name": "Isabel Griffin", - "author_inst": "CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA" - }, - { - "author_name": "Titilope Oduyebo", - "author_inst": "CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA" - }, - { - "author_name": "Christina L Sancken", - "author_inst": "CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA" - }, - { - "author_name": "Emily O'Malley Olsen", - "author_inst": "CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA" - }, - { - "author_name": "Kathy Aveni", - "author_inst": "Division of Family Health Services, New Jersey Department of Health, Trenton, New Jersey, USA" - }, - { - "author_name": "Heather Wingate", - "author_inst": "Communicable and Environmental Disease and Emergency Preparedness, Tennessee Department of Health, Nashville, Tennessee, USA" - }, - { - "author_name": "Hanna Shephard", - "author_inst": "Bureau of Family Health and Nutrition, Massachusetts Department of Public Health, Boston, Massachusetts, USA" - }, - { - "author_name": "Chris Fussman", - "author_inst": "Maternal and Child Health Epidemiology Section, Michigan Department of Health and Human Services, Lansing, Michigan, USA" - }, - { - "author_name": "Zahra S Alaali", - "author_inst": "Division of Epidemiology, New York State Department of Health, Albany, New York, USA" - }, - { - "author_name": "Samantha Siebman", - "author_inst": "Emerging Infections Program, Minnesota Department of Health, St. Paul, Minnesota, USA" - }, - { - "author_name": "Umme-Aiman Halai", - "author_inst": "Acute Communicable Disease Control Program, Los Angeles County Department of Public Health, Los Angeles, California, USA" - }, - { - "author_name": "Camille Delgado Lopez", - "author_inst": "Division of Children with Special Medical Needs, Puerto Rico Department of Health, San Juan, Puerto Rico, Puerto Rico" - }, - { - "author_name": "Jerusha Barton", - "author_inst": "Epidemiology Division, Georgia Department of Public Health, Atlanta, GA, USA" - }, - { - "author_name": "Mamie Lush", - "author_inst": "Division of Public Health, Nebraska Department of Health and Human Services, Lincoln, Nebraska, USA" - }, - { - "author_name": "Paul H Patrick", - "author_inst": "Perinatal and Reproductive Health Division, Oklahoma State Department of Health, Oklahoma City, Oklahoma, USA" - }, - { - "author_name": "Levi Schlosser", - "author_inst": "Division of Disease Control, North Dakota Department of Health, Bismarck, North Dakota, USA" - }, - { - "author_name": "Ayomide Sokale", - "author_inst": "Division of Maternal, Child and Family Health, Philadelphia Department of Public Health, Philadelphia, Pennsylvania" - }, - { - "author_name": "Ifrah Chaudhary", - "author_inst": "Division of Disease Prevention and Control, Houston Health Department, Houston, Texas, USA" - }, - { - "author_name": "Bethany Reynolds", - "author_inst": "Bureau of Epidemiology, Pennsylvania Department of Health, Pittsburgh, Pennsylvania, USA" - }, - { - "author_name": "Similoluwa Sowunmi", - "author_inst": "Center for Family Health, California Department of Public Health, Sacramento, California, USA" - }, - { - "author_name": "Nicole Gaarenstroom", - "author_inst": "Nevada High Sierra Area Health Education Center, Reno, Nevada, USA," - }, - { - "author_name": "Jennifer S Read", - "author_inst": "Infectious Disease Epidemiology, Vermont Department of Health, Burlington, Vermont, USA and Larner College of Medicine" - }, - { - "author_name": "Sarah Chicchelly", - "author_inst": "Infectious Disease Epidemiology and Response, Kansas Department of Health and Environment, Topeka, Kansas, USA" - }, - { - "author_name": "Leah de Wilde", - "author_inst": "Epidemiology Division, US Virgin Islands Department of Health, Christiansted, St. Croix, United States Virgin Islands" - }, - { - "author_name": "Eduardo Azziz-Baumgartner", - "author_inst": "CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA" - }, - { - "author_name": "Aron J Hall", - "author_inst": "CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA" + "author_name": "Hoai Tran", + "author_inst": "University of Freiburg" }, { - "author_name": "Van T Tong", - "author_inst": "CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA" + "author_name": "Philipp Peterburs", + "author_inst": "Bionorica SE" }, { - "author_name": "Sascha Ellington", - "author_inst": "CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA" + "author_name": "Jan Seibel", + "author_inst": "Bionorica SE" }, { - "author_name": "Suzanne M Gilboa", - "author_inst": "CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA" + "author_name": "Dimitri Abramov-Sommariva", + "author_inst": "Bionorica SE" }, { - "author_name": "- CDC COVID-19 Response Pregnancy and Infant Linked Outcomes Team", - "author_inst": "CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA" + "author_name": "Evelyn Lamy", + "author_inst": "University of Freiburg" } ], "version": "1", - "license": "cc0", - "type": "PUBLISHAHEADOFPRINT", - "category": "obstetrics and gynecology" + "license": "cc_by_nd", + "type": "new results", + "category": "pharmacology and toxicology" }, { "rel_doi": "10.1101/2021.03.01.433314", @@ -880725,29 +879617,37 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.02.24.21252406", - "rel_title": "Impact of a new SARS-CoV-2 variant on the population: A mathematical modeling approach", + "rel_doi": "10.1101/2021.02.24.21252414", + "rel_title": "Mental Health of International Migrant Workers Amidst Large-Scale Dormitory Outbreaks of COVID-19: A Population Survey", "rel_date": "2021-03-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.24.21252406", - "rel_abs": "Several SARS-CoV-2 variants have emerged around the world and the appearance of other variants depends on many factors. These new variants might have different characteristics that can affect the transmissibility and death rate. The administration of vaccines against the coronavirus disease 2019 (COVID-19) started in early December of 2020 and in some countries the vaccines will not soon be widely available. In this article, we study the impact of a new more transmissible SARS-CoV-2 strain on prevalence, hospitalizations, and deaths related to the SARS-CoV-2 virus. We study different scenarios regarding the transmissibility in order to provide a scientific support for public health policies and bring awareness of potential future situations related to the COVID-19 pandemic. We construct a compartmental mathematical model based on differential equations to study these different scenarios. In this way, we are able to understand how a new, more infectious strain of the virus can impact the dynamics of the COVID-19 pandemic. We study several metrics related to the possible outcomes of the COVID-19 pandemic in order to assess the impact of a higher transmissibility of a new SARS-CoV-2 strain on these metrics. We found that, even if the new variant has the same death rate, its high transmissibility can increase the number of infected people, those hospitalized, and deaths. The simulation results show that health institutions need to focus on increasing non-pharmaceutical interventions and the pace of vaccine inoculation since a new variant with higher transmissibility as, for example, VOC-202012/01 of lineage B.1.1.7, may cause more devastating outcomes in the population.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.24.21252414", + "rel_abs": "BackgroundIn the COVID-19 pandemic, international migrant workers have faced increased vulnerability on account of their status. This study examined the mental health burden of COVID-19 amongst low-waged migrant workers involved in large-scale dormitory outbreaks within Singapore.\n\nMethodsBetween 22 June to 11 October 2020, questionnaires were distributed in-person and online to 1011 migrant workers undergoing movement restrictions. Mental health symptoms were measured using the 21-item Depression, Anxiety and Stress Scale (DASS-21). As covariates, we assessed participants socio-demographics, quarantine status, COVID-19 health concerns, financial stability, and exposure to news and misinformation. Linear regression models were fitted to identify factors associated with each DASS-21 subscale.\n\nFindingsComplete movement restrictions were associated with increased depression and stress symptoms, while being diagnosed with COVID-19 was associated with increased anxiety. Participants who harboured fears about their health or job, perceived their health to be poorer, or had greater exposure to COVID-19 rumours reported higher depression, anxiety, and stress levels. Across the cohort, rates of severe or extremely severe depression (3.1%, 95% CI: 2.1-4.3%), anxiety (4.1%, 95% CI: 2.9-5.5%), and stress (1.3%, 95% CI: 0.7-2.2%) were similar to those observed in the general population for the host country (Singapore).\n\nInterpretationThe risk factors identified underscore how the ongoing pandemic may impact the mental health of migrant workers. At the same time, we observed resilience within the cohort, with no evidence of increased symptomology (relative to the general population).\n\nFundingJY Pillay Global Asia Grant\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed and Google Scholar for articles published in English between Jan 1, 2020 and Feb 20, 2021 using the following keywords: (\"COVID*\" OR \"coronavirus\") AND (\"mental*\" OR \"psychiatr*\") AND (\"labo*r migra*\" OR \"migrant work\" OR \"foreign-work\" OR \"immigrant work\" OR \"economic migra*\" OR \"economic immigra*\"). Focusing on international migrant workers employed in low-wage manual labour positions, we identified commentaries and interview-based studies describing the stressors faced by workers during the COVID-19 pandemic. However, we found no study documenting mental health symptoms within this group.\n\nAdded value of this studyTo our knowledge, this is the first mental health survey of low-wage migrant workers during the COVID-19 pandemic. We observed that the mental health burden was highest amongst participants who encountered pandemic-related adversities (complete movement restrictions, testing positive for COVID-19), perceived the situation negatively (being fearful of their health or job, or judging their health to be poorer), or had higher exposure to COVID-19 rumours.\n\nImplications of the available evidenceOur findings provide a basis to identify and support at-risk migrant workers during the pandemic. Although we did not observe elevated rates of depression, anxiety, and stress symptoms within the migrant worker cohort, individual workers who experience poor mental health may find it harder to access health-care services (relative to the general population). Correspondingly, targeted support for at-risk migrant workers may serve to reduce mental health inequalities.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Gilberto Gonzalez-Parra", - "author_inst": "New Mexico Tech" + "author_name": "Young Ern Saw", + "author_inst": "Yale-NUS College" }, { - "author_name": "David Martinez-Rodriguez", - "author_inst": "Universitat Politecnica de Valencia" + "author_name": "Edina YQ Tan", + "author_inst": "Yale-NUS College" }, { - "author_name": "Rafael Villanueva-Mico", - "author_inst": "Universidad Politecnica de Valencia, Spain." + "author_name": "P Buvanaswari", + "author_inst": "National University Hospital" + }, + { + "author_name": "Kinjal Doshi", + "author_inst": "Singapore General Hospital" + }, + { + "author_name": "Jean CJ Liu", + "author_inst": "Yale-NUS College" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -882195,45 +881095,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.24.21252426", - "rel_title": "COVID-19 symptom frequency comparison: non-hospitalised positively and negatively tested persons with flu-like symptoms in Austria", + "rel_doi": "10.1101/2021.02.24.21252340", + "rel_title": "Longitudinal analysis of SARS-CoV-2 seroprevalence using multiple serology platforms", "rel_date": "2021-02-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.24.21252426", - "rel_abs": "BackgroundMost clinical studies report the symptoms experienced by those infected with Coronavirus disease 2019 (COVID-19) via patients already hospitalised. Here we analyse the symptoms experienced by the general population in Vienna.\n\nMethodsThe Vienna Social Fund (FSW, Vienna, Austria), the Public Health Services of the City of Vienna (MA15) and the private company Symptoma collaborated to implement Viennas official online COVID-19 symptom checker. Users answered 12 yes/no questions about symptoms to assess their risk for COVID-19. They could also specify their age and sex, and whether they had contact with someone who tested positive for COVID-19. Depending on the assessed risk of COVID-19 positivity, a SARS-CoV-2 nucleic acid amplification test (NAAT) was performed. In this publication, we analysed which factors (symptoms, sex or age) are associated with COVID-19 positivity. We also trained a classifier to correctly predict COVID-19 positivity from the collected data.\n\nResultsBetween the 2nd of November 2020 and the 18th of November 2021, 9133 people experiencing COVID-19-like symptoms were assessed as high risk by the chatbot and were subsequently tested by a NAAT. Symptoms significantly associated with a positive COVID-19 test were malaise, fatigue, headache, cough, fever, dysgeusia and hyposmia. Our classifier could successfully predict COVID-19 positivity with an Area Under the Curve (AUC) of 0.74.\n\nConclusionThis study provides reliable COVID-19 symptom statistics based on the general population verified by NAATs.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.24.21252340", + "rel_abs": "Serological tests are important tools helping to determine previous infection with severe acute respiratory disease coronavirus 2 (SARS-CoV-2) and to monitor immune responses. The current tests are based on spike (S), the receptor binding domain (RBD), or the nucleoprotein (NP) as substrate. Here, we used samples from a high seroprevalence cohort of health care workers (HCWs) to perform a longitudinal analysis of the antibody responses using three distinct serological assays. 501 serum samples were tested using: a) a research-grade RBD and spike based tandem enzyme-linked immunosorbent assay (MS-RBD ELISA, MS-spike ELISA), b) a commercial RBD and spike based tandem ELISA (Kantaro-RBD, -spike), and c) a commercial NP-based chemiluminescent microparticle immunoassay (CMIA, Abbott Architect). Seroprevalence ranged around 28% during the early stage of the pandemic (a: 28.4% positives; b: 28.1%; c: 27.3%). Good correlation was observed between the MS and Kantaro RBD ELISAs and between the MS and Kantaro spike ELISAs. By contrast, modest correlations were observed between the Abbott Architect and both RBD and spike-based assays. A proportion of HCWs (n=178) were sampled again 3-5 months after the first time point. Although antibody levels declined in most of the positive individuals, the overall seroprevalence measured by RBD-spike based assays remained unchanged. However the seroprevalence of NP-reactive antibodies significantly declined. Lastly, we tested six samples of individuals who received two doses of SARS-CoV-2 mRNA vaccine and found that seroconversion was detected by the RBD-spike assays but - of course as expected - not the NP based assay. In summary, our results consolidate the strength of different serological assays to assess the magnitude and duration of antibodies to SARS-CoV-2.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Nicolas Munsch", - "author_inst": "Symptoma" - }, - { - "author_name": "Stefanie Gruarin", - "author_inst": "Symptoma" + "author_name": "Juan Manuel Carreno", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Alistair Martin", - "author_inst": "Symptoma" + "author_name": "Damodara Rao Mendu", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Jama Nateqi", - "author_inst": "Symptoma" + "author_name": "Viviana Simon", + "author_inst": "Icahn School of Medicine" }, { - "author_name": "Thomas Lutz", - "author_inst": "Symptoma" + "author_name": "Masood A Shariff", + "author_inst": "NYC Health + Hospitals/Lincoln" }, { - "author_name": "Michael Binder", - "author_inst": "Vienna Health Care Company, Vienna, Austria" + "author_name": "Gagandeep Singh", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Judith Aberle", - "author_inst": "Medical University of Vienna" + "author_name": "Vidya Menon", + "author_inst": "NYC Health + Hospitals/Lincoln" }, { - "author_name": "Bernhard Knapp", - "author_inst": "Symptoma" + "author_name": "Florian Krammer", + "author_inst": "Icahn School of Medicine at Mount Sinai" } ], "version": "1", @@ -884381,71 +883277,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.02.23.21252259", - "rel_title": "A Novel SARS-CoV-2 Variant of Concern, B.1.526, Identified in New York", + "rel_doi": "10.1101/2021.02.23.21252296", + "rel_title": "The differential impact of the COVID-19 epidemic on Medicaid expansion and non-expansion states", "rel_date": "2021-02-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.23.21252259", - "rel_abs": "Recent months have seen surges of SARS-CoV-2 infection across the globe with considerable viral evolution1-3. Extensive mutations in the spike protein may threaten efficacy of vaccines and therapeutic monoclonal antibodies4. Two signature mutations of concern are E484K, which plays a crucial role in the loss of neutralizing activity of antibodies, and N501Y, a driver of rapid worldwide transmission of the B.1.1.7 lineage. Here, we report the emergence of variant lineage B.1.526 that contains E484K and its alarming rise to dominance in New York City in early 2021. This variant is partially or completely resistant to two therapeutic monoclonal antibodies in clinical use and less susceptible to neutralization by convalescent plasma or vaccinee sera, posing a modest antigenic challenge. The B.1.526 lineage has now been reported from all 50 states in the US and numerous other countries. B.1.526 rapidly replaced earlier lineages in New York upon its emergence, with an estimated transmission advantage of 35%. Such transmission dynamics, together with the relative antibody resistance of its E484K sub-lineage, likely contributed to the sharp rise and rapid spread of B.1.526. Although SARS-CoV-2 B.1.526 initially outpaced B.1.1.7 in the region, its growth subsequently slowed concurrent with the rise of B.1.1.7 and ensuing variants.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.23.21252296", + "rel_abs": "Medicaid expansion is a federally-funded program to expand health care access and coverage to economically challenged populations by increasing eligibility to Medicaid enrollment and investing in public health preventive services in the individual states. Yet, when the COVID-19 epidemic plagued the country, fourteen states were practicing their chosen decision not to enact the Medicaid expansion policy. We examined the consequences of this nationwide split in Medicaid design on the spread of the COVID-19 epidemic between the expansion and non-expansion states. Our study shows that, on average, the expansion states had 217.56 fewer confirmed COVID-19 cases per 100,000 residents than the non-expansion states [-210.41; 95%CI (-411.131) - (-2.05); P<0.05]. Also, the doubling time of COVID-19 cases in Medicaid expansion states was longer than that of non-expansion states by an average of 1.68 days [1.6826; 95%CI 0.4035-2.9617; P<0.05]. These findings suggest that proactive investment in public health preparedness was an effective protective policy measure in this crisis, unsurpassed by the benefits of COVID-19 emergency plans and funds. The study findings could be relevant to policymakers and healthcare strategists in non-expansion states considering their states preparations for such public health crises.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Medini K Annavajhala", - "author_inst": "Columbia University Irving Medical Center, Medicine - Infectious Diseases" - }, - { - "author_name": "Hiroshi Mohri", - "author_inst": "Columbia University Irving Medical Center, Aaron Diamond AIDS Research Center" - }, - { - "author_name": "Pengfei Wang", - "author_inst": "Columbia University Irving Medical Center, Aaron Diamond AIDS Research Center" - }, - { - "author_name": "Manoj S Nair", - "author_inst": "Columbia University Irving Medical Center, Aaron Diamond AIDS Research Center" - }, - { - "author_name": "Jason E Zucker", - "author_inst": "Columbia University Irving Medical Center" - }, - { - "author_name": "Zizhang Sheng", - "author_inst": "Columbia University Irving Medical Center, Medicine - Infectious Diseases" - }, - { - "author_name": "Angela Gomez-Simmonds", - "author_inst": "Columbia University Irving Medical Center, Medicine - Infectious Diseases" + "author_name": "Muhammad Ragaa Hussein", + "author_inst": "Uiversity of Texas UTHealth School of Public Health, TX, USA" }, { - "author_name": "Anne L Kelley", - "author_inst": "Columbia University Irving Medical Center, Medicine - Infectious Diseases" + "author_name": "Islam Morsi", + "author_inst": "German University in Cairo, Cairo, Egypt" }, { - "author_name": "Maya Tagliavia", - "author_inst": "Columbia University Irving Medical Center, Medicine - Infectious Diseases" + "author_name": "Engy A. Awad", + "author_inst": "Scientific Collaboration Development Center, IA, USA" }, { - "author_name": "Yaoxing Huang", - "author_inst": "Columbia University Irving Medical Center, Aaron Diamond AIDS Research Center" + "author_name": "Dina Fayed", + "author_inst": "Alexandria University, Alexandria, Egypt" }, { - "author_name": "Trevor Bedford", - "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center" + "author_name": "Thamer AlSulaiman", + "author_inst": "University of Iowa, Computer Science Department, IA, USA" }, { - "author_name": "David D Ho", - "author_inst": "Columbia University Irving Medical Center, Aaron Diamond AIDS Research Center" + "author_name": "Mohamed Fouad Habib", + "author_inst": "Scientific Collaboration Development Center, IA, USA" }, { - "author_name": "Anne-Catrin Uhlemann", - "author_inst": "Columbia University Irving Medical Center, Medicine - Infectious Diseases" + "author_name": "John R. Herbold", + "author_inst": "University of Texas UTHealth School of Public Health, TX, USA" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.02.23.21252294", @@ -886415,41 +885287,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.23.21251891", - "rel_title": "Evidence of long-lasting humoral and cellular immunity against SARS-CoV-2 even in elderly COVID-19 convalescents showing a mild to moderate disease progression", + "rel_doi": "10.1101/2021.02.22.21252002", + "rel_title": "SARS CoV-2 escape variants exhibit differential infectivity and neutralization sensitivity to convalescent or post-vaccination sera", "rel_date": "2021-02-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.23.21251891", - "rel_abs": "After the novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in China in late 2019, a pandemic evolved that has claimed millions of lives so far. While about 80 % of infections cause mild or moderate COVID-19 disease, some individuals show a severe progression or even die. Most countries are far from achieving herd-immunity, however, the first approved vaccines offer hope for containment of the virus. Although much is known about the virus, there is a lack of information on the immunity of convalescent individuals.\n\nWe here evaluate the humoral and cellular immune response against SARS-CoV-2 in 41 COVID-19 convalescents. As previous studies mostly included younger individuals, one advantage of our study is the comparatively high mean age of the convalescents included in the cohort considered (54 {+/-} 8.4 years). While anti-SARS-CoV-2 antibodies were still detectable in 95 % of convalescents up to 8 months post infection, an antibody-decay over time was generally observed in most donors. Using a multiplex assay, our data additionally reveal that most convalescents exhibit a broad humoral immunity against different viral epitopes. We demonstrate by flow cytometry that convalescent donors show a significantly elevated number of natural killer cells when compared to healthy controls, while no differences were found concerning other leucocyte subpopulations. We detected a specific long-lasting cellular immune response in convalescents by stimulating immune cells with SARS-CoV-2-specific peptides, covering domains of the viral spike, membrane and nucleocapsid protein, and measuring interferon-{gamma} (IFN-{gamma}) release thereafter. We modified a commercially available ELISA assay for IFN-{gamma} determination in whole-blood specimens of COVID-19 convalescents. One advantage of this assay is that it does not require special equipment and can, thus, be performed in any standard laboratory. In conclusion, our study adds knowledge regarding the persistence of immunity of convalescents suffering from mild to moderate COVID-19. Moreover, our study provides a set of simple methods to characterize and confirm experienced COVID-19.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.22.21252002", + "rel_abs": "Towards eradicating COVID19, developing vaccines that induce high levels of neutralizing antibodies is a main goal. As counter measurements, viral escape mutants rapidly emerge and potentially compromise vaccine efficiency. Herein we monitored ability of convalescent or Pfizer-BTN162b2 post-vaccination sera to neutralize wide-type SARS-CoV2 or its UK-B.1.1.7 and SA-B.1.351 variants. Relative to convalescent sera, post-vaccination sera exhibited higher levels of neutralizing antibodies against wild-type or mutated viruses. However, while SARS-CoV2 wild-type and UK-N501Y were similarly neutralized by tested sera, the SA-N501Y/K417N/E484K variant moderately escaped neutralization. Significant contribution to infectivity and sensitivity to neutralization was attributed to each of the variants and their single or combined mutations, highlighting alternative mechanisms by which prevalent variants with either N501Y or E484K/K417N mutations spread. Our study validates the clinical significance of currently administered vaccines, but emphasizes that their efficacy may be compromised by circulated variants, urging the development of new ones with broader neutralization functions.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Bastian Fischer", - "author_inst": "Herz- und Diabeteszentrum NRW" + "author_name": "Alona Kuzmina", + "author_inst": "Ben Gurion University of the Negev" }, { - "author_name": "Christopher Lindenkamp", - "author_inst": "Herz- und Diabeteszentrum NRW" + "author_name": "Yara Khalaila", + "author_inst": "Ben Gurion University of the Negev" }, { - "author_name": "Christoph Lichtenberg", - "author_inst": "Herz- und Diabeteszentrum NRW" + "author_name": "Olga Voloshin", + "author_inst": "Soroka Medical Center" }, { - "author_name": "Ingvild Edda Birschmann", - "author_inst": "Herz- und Diabeteszentrum NRW" + "author_name": "Ayelet Keren-Naus", + "author_inst": "Soroka Medical Center" }, { - "author_name": "Cornelius Knabbe", - "author_inst": "Herz- und Diabeteszentrum NRW" + "author_name": "Liora Bohehm", + "author_inst": "Soroka Medical Center" }, { - "author_name": "Doris Hendig", - "author_inst": "Herz- und Diabeteszentrum NRW" + "author_name": "Yael Raviv", + "author_inst": "Soroka Medical Center" + }, + { + "author_name": "Yonat Shemer-Avni", + "author_inst": "Ben Gurion University of the Negev" + }, + { + "author_name": "Elli Rosenberg", + "author_inst": "Soroka Medical Center" + }, + { + "author_name": "Ran Taube", + "author_inst": "Ben Gurion University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -888313,53 +887197,45 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.02.22.21251646", - "rel_title": "Occupational exposures and mitigation strategies among homeless shelter workers at risk of COVID-19", + "rel_doi": "10.1101/2021.02.21.21251597", + "rel_title": "Controlling the first wave of the COVID-19 pandemic in Malawi: results from a panel study", "rel_date": "2021-02-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.22.21251646", - "rel_abs": "ObjectiveTo describe the work environment and COVID-19 mitigation measures for homeless shelter workers and assess occupational risk factors for COVID-19 infection\n\nMethodsBetween June 9-August 10, 2020, we conducted a self-administered survey among homeless shelter workers in Washington, Massachusetts, Utah, Maryland, and Georgia. We calculated frequencies for work environment, personal protective equipment use, and SARS-CoV-2 testing history. We used generalized linear models to produce unadjusted prevalence ratios (PR) to assess risk factors for SARS-CoV-2 infection.\n\nResultsOf the 106 respondents, 43.4% reported frequent close contact with clients; 75% were worried about work-related SARS-CoV-2 infections; 15% reported testing positive. Close contact with clients was associated with testing positive for SARS-CoV-2 (PR 3.97, 95%CI 1.06, 14.93).\n\nConclusionsHomeless shelter workers may be at higher risk of being infected with SARS-CoV-2 during the course of their work. Protecting these critical essential workers by implementing mitigation measures and prioritizing for COVID-19 vaccination, is imperative during the pandemic.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.21.21251597", + "rel_abs": "Many African countries have experienced a first wave of the COVID-19 pandemic between June and August of 2020. According to case counts reported daily by epidemiological surveillance systems, infection rates remained low in most countries. This defied early models of the potential impact of COVID-19 on the continent, that projected large outbreaks and massive strain on health systems. Theories proposed to explain the apparently limited spread of the novel coronavirus in most African countries have emphasized 1) early actions by health authorities (e.g., border closures) and 2) biological or environmental determinants of the transmissibility of SARS-CoV-2 (e.g., warm weather, cross-immunity). In this paper, we explored additional factors that might contribute to the low recorded burden of COVID-19 in Malawi, a low-income country in Southeastern Africa. To do so, we used 4 rounds of panel data collected among a sample of adults during the first 6 months of the pandemic in the country. Our analyses of survey data on SARS-CoV-2 testing and COVID-related symptoms indicate that the size of the outbreak that occurred in June-August 2020 might be larger than recorded by surveillance systems that rely on RT-PCR testing. Our data also document the widespread adoption of physical distancing and mask use in response to the outbreak, whereas most measured patterns of social contacts remained stable during the course of the panel study. These findings will help better project, and respond to, future waves of the pandemic in Malawi and similar settings.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Carol Rao", - "author_inst": "CDC" - }, - { - "author_name": "Tashina Robinson", - "author_inst": "CDC" - }, - { - "author_name": "Karin Huster", - "author_inst": "Public Health-Seattle & King County" + "author_name": "Jethro Banda", + "author_inst": "Malawi Epidemiological and Intervention Research Unit" }, { - "author_name": "Rebecca Laws", - "author_inst": "CDC" + "author_name": "Albert. N. Dube", + "author_inst": "Malawi Epidemiological and Intervention Research Unit" }, { - "author_name": "Ryan Keating", - "author_inst": "CDC" + "author_name": "Sarah Brumfield", + "author_inst": "Boston University School of Public Health" }, { - "author_name": "Farrell Tobolowsky", - "author_inst": "CDC" + "author_name": "Amelia C. Crampin", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Temet McMichael", - "author_inst": "CDC" + "author_name": "Georges Reniers", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Elysia Gonzales", - "author_inst": "Public Health-Seattle & King County" + "author_name": "Abena S. Amoah", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Emily Mosites", - "author_inst": "CDC" + "author_name": "St\u00e9phane Helleringer", + "author_inst": "New York University - Abu Dhabi" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -890283,37 +889159,29 @@ "category": "emergency medicine" }, { - "rel_doi": "10.1101/2021.02.22.21252189", - "rel_title": "Modelling the Impact of Delaying Vaccination Against SARS-CoV-2 Assuming Unlimited Vaccines Supply", + "rel_doi": "10.1101/2021.02.20.21252138", + "rel_title": "An efficient benchmark for COVID-19 pandemic testing effectiveness", "rel_date": "2021-02-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.22.21252189", - "rel_abs": "BackgroundAt the moment we have more than 109 million cases and 2.4 million deaths around the world and vaccination represents the only hope to control the pandemic. Imperfections in planning vaccine acquisition and difficulties in implementing distribution among the population, however, have hampered the control of the virus so far.\n\nMethodsWe propose a new mathematical model to estimate the impact of vaccination delay against COVID-19 on the number of cases and deaths by the disease in Brazil. We apply the model to Brazil as a whole and to the State of Sao Paulo, the most affected by COVID-19 in Brazil. We simulated the model for the populations of the State of Sao Paulo and Brazil as a whole, varying the scenarios related to vaccine efficacy and compliance from the populations.\n\nResultsThe model projects that, in the absence of vaccination, almost 170 thousand deaths and more than 350 thousand deaths until the end of 2021 for Sao Paulo and Brazil, respectively. If in contrast, Sao Paulo and Brazil had enough vaccine supply and so started a vaccination campaign in January with the maximum vaccination rate, compliance and efficacy, they could have averted more than 112 thousand deaths and 127 thousand deaths, respectively. In addition, that for each month of delay the number of deaths increases monotonically in a logarithm fashion, for both the State of Sao Paulo and Brazil as a whole.\n\nConclusionsOur model shows that the current delay in the vaccination schedules that is observed in many countries has serious consequences in terms of mortality by the disease and should serve as an alert to health authorities to speed the process up such that the highest number of people to be immunized is reached in the shortest period of time.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.20.21252138", + "rel_abs": "The positivity rate of testing is currently used both as a benchmark of testing adequacy and for assessing the evolution of the COVID-19 pandemic. However, since the former is a prerequisite for the latter, its interpretation is often conflicting. We propose as a benchmark for COVID-19 testing effectiveness a new metric, termed Severity Detection Rate (SDR), that represents the daily needs for new Intensive Care Unit (ICU) admissions, per 100 cases detected (t-i) days ago, per 10,000 tests performed (t-i) days ago. Based on the announced COVID-19 monitoring data in Greece from May 2020 until August 2021, we show that beyond a certain threshold of daily tests, SDR reaches a plateau of very low variability that begins to reflect testing adequacy. Due to the stabilization of SDR, it was possible to predict with great accuracy the daily needs for new ICU admissions, 12 days ahead of each testing data point, over a period of 10 months, with Pearson r = 0.98 (p = 10-197), RMSE = 7,16. We strongly believe that this metric will help guide the timely decisions of both scientists and government officials to tackle pandemic spread and prevent ICU overload by setting effective testing requirements for accurate pandemic monitoring. We propose further study of this novel metric with data from more countries to confirm the validity of the current findings.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Eduardo Massad", - "author_inst": "Fundacao Getulio Vargas" + "author_name": "Dimitris Nikoloudis", + "author_inst": "Center for Preventive Medicine & Longevity, Bioiatriki Healthcare Group, 11525 Athens, Greece" }, { - "author_name": "Marcos Amaku", - "author_inst": "University of Sao Paulo" - }, - { - "author_name": "Dimas Tadeu Covas", - "author_inst": "Instituto Butantan" + "author_name": "Dimitrios Kountouras", + "author_inst": "Center for Preventive Medicine & Longevity, Bioiatriki Healthcare Group, 11525 Athens, Greece" }, { - "author_name": "Raymundo Soares de azevedo Neto", - "author_inst": "Universidade de Sao Paulo" - }, - { - "author_name": "Francisco Antonio Bezerra Coutinho", - "author_inst": "University of Sao Paulo" + "author_name": "Asimina Hiona", + "author_inst": "Center for Preventive Medicine & Longevity, Bioiatriki Healthcare Group, 11525 Athens, Greece" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -892009,87 +890877,75 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2021.02.19.21252045", - "rel_title": "SARS-CoV-2 serostatus of healthcare worker in the Austrian state Vorarlberg between June 2020 and January 2021", + "rel_doi": "10.1101/2021.02.21.432168", + "rel_title": "Structural Basis for Accommodation of Emerging B.1.351 and B.1.1.7 Variants by Two Potent SARS-CoV-2 Neutralizing Antibodies", "rel_date": "2021-02-22", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.19.21252045", - "rel_abs": "BackgroundAustria, and particularly its westernmost federal state Vorarlberg, developed an extremely high COVID-19 incidence rate in November 2020. Health care workers (HCW) may be at higher risk of contracting the disease within the working environment and therefore the seroprevalence in this population is of particular interest. Here, we analyzed SARS-CoV-2-specific antibody response in Vorarlberg HCW in a prospective cohort study.\n\nMethodsA total of 395 HCW have been tested at three different time points for the prevalence of anti-SARS-CoV-2 IgG antibodies specific for NP and RBD. Enrollment started in June 2020 (t1), two months after the end of the first wave. Re-testing took place between October to November at the beginning of the second wave (t2), and again at the end of the second wave in January 2021 (t3).\n\nResultsAt t1, 3% of HCW showed a strong IgG-specific responses to either NP or RBD. At t2, the rate increased to 4%, and after the second wave in January 2021, 14% had a strong response, which was assessed to be stable for up to ten months. The amount of HCW with anti-SARS-CoV-2 IgG antibodies was 38% higher than the number of infections found by RT-PCR.\n\nConclusionWe found low numbers of SARS-CoV-2-seropositive HCW in a hotspot setting after the first wave but a very high increase during the second massive wave. Though the seroprevalence in HCW was comparable to the general population. Our findings offer support for the routine application of serological testing in management of the ongoing COVID-19 pandemic.\n\nMain summaryA relatively low percentage of 3% SARS-CoV-2 seropositive HCW with strong IgG-specific antibody responses was found in the Austrian federal state Vorarlberg after the first wave increasing to 14% after the second massive wave lasting until January 2021.", - "rel_num_authors": 17, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.21.432168", + "rel_abs": "Emerging SARS-CoV-2 strains, B.1.1.7 and B.1.351, from the UK and South Africa, respectively show decreased neutralization by monoclonal antibodies and convalescent or vaccinee sera raised against the original wild-type virus, and are thus of clinical concern. However, the neutralization potency of two antibodies, 1-57 and 2-7, which target the receptor-binding domain (RBD) of spike, was unaffected by these emerging strains. Here, we report cryo-EM structures of 1-57 and 2-7 in complex with spike, revealing each of these antibodies to utilize a distinct mechanism to bypass or accommodate RBD mutations. Notably, each antibody represented a response with recognition distinct from those of frequent antibody classes. Moreover, many epitope residues recognized by 1-57 and 2-7 were outside hotspots of evolutionary pressure for both ACE2 binding and neutralizing antibody escape. We suggest the therapeutic use of antibodies like 1-57 and 2-7, which target less prevalent epitopes, could ameliorate issues of monoclonal antibody escape.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Michele Atzl", - "author_inst": "Academic Teaching Hospital Feldkirch" - }, - { - "author_name": "Axel Muendlein", - "author_inst": "Vorarlberg Institute for Vascular Investigation and Treatment (VIVIT)" - }, - { - "author_name": "Thomas Winder", - "author_inst": "Academic Teaching Hospital Feldkirch" - }, - { - "author_name": "Peter Fraunberger", - "author_inst": "Medical Central Laboratories Feldkirch" + "author_name": "Gabriele Cerutti", + "author_inst": "Columbia University" }, { - "author_name": "Eva-Maria Brandtner", - "author_inst": "Vorarlberg Institute for Vascular Investigation and Treatment (VIVIT)" + "author_name": "Micah Rapp", + "author_inst": "Columbia University" }, { - "author_name": "Kathrin Geiger", - "author_inst": "Vorarlberg Institute for Vascular Investigation and Treatment (VIVIT)" + "author_name": "Yicheng Guo", + "author_inst": "Columbia University" }, { - "author_name": "Miriam Klausberger", - "author_inst": "University of Natural Resources and Life Sciences (BOKU) Vienna" + "author_name": "Fabiana Bahna", + "author_inst": "Columbia University" }, { - "author_name": "Mark Duerkop", - "author_inst": "University of Natural Resources and Life Sciences (BOKU) Vienna" + "author_name": "Jude Bimela", + "author_inst": "Columbia University" }, { - "author_name": "Lukas Sprenger", - "author_inst": "Academic Teaching Hospital Feldkirch" + "author_name": "Eswar R Reddem", + "author_inst": "Columbia University" }, { - "author_name": "Beatrix Mutschlechner", - "author_inst": "Academic Teaching Hospital Feldkirch" + "author_name": "Jian Yu", + "author_inst": "Columbia University" }, { - "author_name": "Andreas Volgger", - "author_inst": "Academic Teaching Hospital Feldkirch" + "author_name": "Pengfei Wang", + "author_inst": "Columbia University Vagelos College of Physicians and Surgeons" }, { - "author_name": "Magdalena Benda", - "author_inst": "Academic Teaching Hospital Feldkirch" + "author_name": "Lihong Liu", + "author_inst": "Columbia University Irving Medical Center" }, { - "author_name": "Luciano Severgnini", - "author_inst": "Academic Teaching Hospital Feldkirch" + "author_name": "Yaoxing Huang", + "author_inst": "Columbia University" }, { - "author_name": "Johannes B Jaeger", - "author_inst": "Academic Teaching Hospital Feldkirch" + "author_name": "David D Ho", + "author_inst": "Columbia University Irving Medical Center" }, { - "author_name": "Heinz Drexel", - "author_inst": "Academic Teaching Hospital Bregenz" + "author_name": "Peter D Kwong", + "author_inst": "Columbia University, Vaccine Research Center" }, { - "author_name": "Alois Lang", - "author_inst": "Agency for Preventive and Social Medicine" + "author_name": "Zizhang Sheng", + "author_inst": "Columbia University" }, { - "author_name": "Andreas Leiherer", - "author_inst": "Vorarlberg Institute for Vascular Investigation and Treatment (VIVIT)" + "author_name": "Lawrence Shapiro", + "author_inst": "Columbia University" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "license": "cc_no", + "type": "new results", + "category": "biochemistry" }, { "rel_doi": "10.1101/2021.02.20.432046", @@ -893815,35 +892671,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.02.20.432085", - "rel_title": "KLF2 is a therapeutic target for COVID-19 induced endothelial dysfunction", + "rel_doi": "10.1101/2021.02.18.21251551", + "rel_title": "Persisting adaptive immunity to SARS-CoV-2 in Lower Austria", "rel_date": "2021-02-20", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.20.432085", - "rel_abs": "Coronavirus disease 2019 (COVID-19) is regarded as an endothelial disease (endothelialitis) with its mechanism being incompletely understood. Emerging evidence has demonstrated that the endothelium represents the Achilles' heel in COVID-19 patients and that endothelial dysfunction precipitates COVID-19 and accompanying multi-organ injuries. Thus, pharmacotherapies targeting endothelial dysfunction have potential to ameliorate COVID-19 and its cardiovascular complications. Primary human umbilical vein endothelial cells (HUVECs) and human pulmonary microvascular endothelial cells (HPMECs) were treated with serum from control subjects or COVID-19 patients. Downstream monocyte adhesion and associated gene/protein expression was evaluated in endothelial cells exposed to COVID-19 patient serum in the presence of KLF2 activator (Atorvastatin) or KLF2 overexpression by an adenoviral vector. Here, we demonstrate that the expression of KLF2 was significantly reduced and monocyte adhesion was increased in endothelial cells treated with COVID-19 patient serum due to elevated levels of pro-adhesive molecules, ICAM1 and VCAM1. IL-1{beta} and TNF-, two cytokines observed in cytokine release syndrome in COVID-19 patients, decreased KLF2 gene expression. Next-generation RNA-sequencing data showed that atorvastatin treatment leads to a cardiovascular protective transcriptome associated with improved endothelial function (vasodilation, anti-inflammation, antioxidant status, anti-thrombosis/-coagulation, anti-fibrosis and reduced angiogenesis). Treatment of HPMECs with atorvastatin or KLF2 adenovirus ameliorate COVID-19 serum-induced increase in endothelial inflammation and monocyte adhesion by increasing KLF2 expression. Altogether, the present study demonstrates that genetic and pharmacological activation of KLF2 represses COVID-19 associated endothelial dysfunction, heralding a potentially new direction to treat endothelialitis accompanying COVID-19.", - "rel_num_authors": 4, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.18.21251551", + "rel_abs": "The prevalence and persistence of adaptive immunity responses following a SARS-CoV-2 infection provides insights into potential population immunity. Adaptive immune responses comprise of antibody-based responses as well as T cell responses mainly addressing viruses and virus-infected human cells, respectively. A comprehensive analysis of both types of adaptive immunity is essential to follow population-based SARS-CoV-2-specific immunity. In this study, we assessed SARS-CoV-2-specific immunoglobulin A (IgA) levels, SARS-CoV-2-specific immunoglobulin G (IgG) levels, and SARS-CoV-2-specific T cell activities in patients who recovered from a COVID-19 infection in spring and autumn 2020. Here we observed a robust and stable SARS-CoV-2-specific adaptive immune response in both groups with persisting IgA and IgG levels as well as stable T cell activity. Moreover, there was a positive correlation of a lasting immune response with the severity of disease. Our data give evidence for a persisting adaptive immune memory, which suggest a continuing immunity for more than six months post infection.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Suowen Xu", - "author_inst": "University of Rochester" + "author_name": "Dennis Ladage", + "author_inst": "Danube Private University" }, { - "author_name": "Sihui Luo", - "author_inst": "University of Science and Technology of China" + "author_name": "Oliver Harzer", + "author_inst": "Danube Private University" }, { - "author_name": "Xueying Zheng", - "author_inst": "University of Science and Technology of China" + "author_name": "Peter Engel", + "author_inst": "Danube Private University" }, { - "author_name": "Jianping Weng", - "author_inst": "University of Science and Technology of China" + "author_name": "Hannes Winkler", + "author_inst": "Austrian Red Cross" + }, + { + "author_name": "Ralf Braun", + "author_inst": "Danube Private University" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "pharmacology and toxicology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.02.16.21251838", @@ -895221,35 +894081,51 @@ "category": "neurology" }, { - "rel_doi": "10.1101/2021.02.09.21251106", - "rel_title": "Predictive Modeling of COVID-19 Case Growth Highlights Evolving Demographic Risk Factors in Tennessee and Georgia", + "rel_doi": "10.1101/2021.02.09.21251319", + "rel_title": "SARS-CoV-2 seropositivity after infection and antibody response to mRNA-based vaccination", "rel_date": "2021-02-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.09.21251106", - "rel_abs": "The COVID-19 pandemic has exposed the need to understand the unique risk drivers that contribute to uneven morbidity and mortality in US communities. Addressing the community-specific social determinants of health that correlate with spread of SARS-CoV-2 provides an opportunity for targeted public health intervention to promote greater resilience to viral respiratory infections in the future.\n\nOur work combined publicly available COVID-19 statistics with county-level social determinants of health information. Machine learning models were trained to predict COVID-19 case growth and understand the unique social, physical and environmental risk factors associated with higher rates of SARS-CoV-2 infection in Tennessee and Georgia counties. Model accuracy was assessed comparing predicted case counts to actual positive case counts in each county. The predictive models achieved a mean r-squared (R2) of 0.998 in both states with accuracy above 90% for all time points examined. Using these models, we tracked the social determinants of health, with a specific focus on demographics, that were strongly associated with COVID-19 case growth in Tennessee and Georgia counties. The demographic results point to dynamic racial trends in both states over time and varying, localized patterns of risk among counties within the same state.\n\nIdentifying the specific risk factors tied to COVID-19 case growth can assist public health officials and policymakers target regional interventions to mitigate the burden of future outbreaks and minimize long-term consequences including emergence or exacerbation of chronic diseases that are a direct consequence of infection.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.09.21251319", + "rel_abs": "The effect of SARS-CoV-2 seropositivity on the immune response to mRNA-based SARS-CoV-2 vaccines has not been well-described. Here we report longitudinal SARS-CoV-2-specific antibody responses pre- and post-vaccination among a cohort of healthcare personnel, with and without prior infection, from a large academic medical center. Our results provide preliminary evidence that prior SARS-CoV-2 infection may prime the response to the first mRNA-based SARS-CoV-2 vaccine dose. These findings could have significant impact on the allocation of mRNA-based vaccines and support the need for future research into the effect of prior infection on magnitude and durability of vaccination response.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Jamieson D Gray", - "author_inst": "Decode Health, Inc." + "author_name": "Emily J. Ciccone", + "author_inst": "University of North Carolina School of Medicine" }, { - "author_name": "Coleman R Harris", - "author_inst": "Vanderbilt University School of Medicine; Decode Health, Inc." + "author_name": "Deanna R. Zhu", + "author_inst": "University of North Carolina Gillings School of Global Public Health" }, { - "author_name": "Lukasz S Wylezinski", - "author_inst": "Vanderbilt University School of Medicine; Decode Health, Inc." + "author_name": "Rawan Ajeen", + "author_inst": "University of North Carolina Gillings School of Global Public Health" }, { - "author_name": "Charles F Spurlock III", - "author_inst": "Vanderbilt University School of Medicine; Decode Health, Inc." + "author_name": "Evans K Lodge", + "author_inst": "University of North Carolina Gillings School of Global Public Health" + }, + { + "author_name": "Bonnie E. Shook-Sa", + "author_inst": "University of North Carolina Gillings School of Global Public Health" + }, + { + "author_name": "Ross M. Boyce", + "author_inst": "University of North Carolina School of Medicine" + }, + { + "author_name": "- COVID HCP Study Team", + "author_inst": "" + }, + { + "author_name": "Allison E. Aiello", + "author_inst": "University of North Carolina Gillings School of Global Public Health" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.02.16.21251625", @@ -896867,45 +895743,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.17.21251867", - "rel_title": "Evaluation of sampling frequency and normalization of SARS-CoV-2 wastewater concentrations for capturing COVID-19 burdens in the community", + "rel_doi": "10.1101/2021.02.17.21251839", + "rel_title": "Country differences in transmissibility, age distribution and case-fatality of SARS-CoV-2: a global ecological analysis", "rel_date": "2021-02-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.17.21251867", - "rel_abs": "Wastewater surveillance for SARS-CoV-2 provides an approach for assessing the infection burden across a city. For these data to be useful for public health, measurement variability and the relationship to case data need to be established. We measured SARS-CoV-2 RNA concentrations in the influent of twelve wastewater treatment plants from August 2020 to January 2021. Replicate samples demonstrated that N1 gene target concentrations varied by {+/-}21% between technical replicate filters and by {+/-}14% between duplicate assays. COVID-19 cases were correlated significantly (rho[≥]0.70) to wastewater SARS-CoV-2 RNA concentrations for seven plants, including large and small cities. SARS-CoV-2 data normalized to flow improved correlations to reported COVID-19 cases for some plants but normalizing to a spiked recovery control (BCoV) or a fecal marker (PMMoV or HF183) generally reduced correlations. High frequency sampling demonstrated that a minimum of two samples collected per week was needed to maintain accuracy in trend analysis. We found a significantly different ratio of COVID-19 cases to SARS-CoV-2 loads in one of three large communities, suggesting a higher rate of undiagnosed cases. These data demonstrate that SARS-CoV-2 wastewater surveillance can provide a useful community-wide metric to assess the course of the COVID-19 pandemic.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.17.21251839", + "rel_abs": "IntroductionSARS-CoV-2 has spread rapidly across the world yet the first pandemic waves in many low-income countries appeared milder than initially forecasted through mathematical models. Hypotheses for this observed difference include under-ascertainment of cases and deaths, country population age structure, and immune modulation secondary to exposure to endemic parasitic infections. We conducted a country-level ecological study to describe patterns in key SARS-CoV-2 outcomes by country and region and to explore possible associations of the potential explanatory factors with these outcomes.\n\nMethodsWe collected publicly available data at country level and compared them using standardisation techniques. We then explored the association between exposures and outcomes using alternative approaches: random forest (RF) regression and linear (LM) regression. We adjusted for potential confounders and plausible effect modifications.\n\nResultsAltogether, data on the mean time-varying reproduction number (mean Rt) were available for 153 countries, but standardised averages for the age of cases and deaths and for the case-fatality ratio (CFR) could only be computed for 61, 39 and 31 countries respectively. While mean Rt was highest in the WHO Europe and Americas regions, median age of death was lower in the Africa region even after standardisation, with broadly similar CFR. Population age was strongly associated with mean Rt and the age-standardised median age of observed cases and deaths in both RF and LM models. The models highlighted other plausible roles of population density, testing intensity and co-morbidity prevalence, but yielded uncertain results as regards exposure to common parasitic infections.\n\nConclusionsThe average age of a population seems to be an important country-level factor explaining both transmissibility and the median age of observed cases and deaths, even after age-standardisation. Potential associations between endemic infections and COVID-19 are worthy of further exploration but seem unlikely, from this analysis, to be key drivers of the variation in observed COVID-19 epidemic trends. Our study was limited by the availability of outcome data and its causally uncertain ecological design, with the observed distribution of age amongst reported cases and deaths suggesting key differences in surveillance and testing strategy and capacity by country and the representativeness of case reporting of infection. Research at subnational and individual level is needed to explore hypotheses further.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Sandra L. McLellan", - "author_inst": "University of Wisconsin-Milwaukee" - }, - { - "author_name": "Shuchen Feng", - "author_inst": "University of Wisconsin-Milwaukee" - }, - { - "author_name": "Adelaide Roguet", - "author_inst": "University of Wisconsin-Milwaukee" + "author_name": "Caroline Favas", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Jill S. McClary-Gutierrez", - "author_inst": "University of Wisconsin-Milwaukee" + "author_name": "Prudence Jarrett", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Ryan J. Newton", - "author_inst": "University of Wisconsin-Milwaukee" + "author_name": "Ruwan Ratnayake", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Nathan Kloczko", - "author_inst": "Wisconsin Department of Health Services" + "author_name": "Oliver J Watson", + "author_inst": "Imperial College London" }, { - "author_name": "Jonathan G. Meiman", - "author_inst": "Wisconsin Department of Health Services" + "author_name": "Francesco Checchi", + "author_inst": "London School of Hygiene and Tropical Medicine" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -898589,55 +897457,55 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.02.12.21251640", - "rel_title": "Optimal Allocation of COVID-19 Vaccines in the Philippines", + "rel_doi": "10.1101/2021.02.15.21251572", + "rel_title": "A disproportionate epidemic: COVID-19 cases and deaths among essential workers in Toronto, Canada", "rel_date": "2021-02-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.12.21251640", - "rel_abs": "Vaccine allocation is a national concern especially for countries such as the Philippines that have limited resources in acquiring COVID-19 vaccines. As such, certain groups are suggested to be prioritized for vaccination to protect the most vulnerable before vaccinating others. Our model suggests an allocation of vaccines such that COVID-19 deaths are minimized while the prioritization framework is satisfied. Results of the model show that a vaccine coverage of at least 50 to 70% of the population can be enough for a community with limited supplies, and an increase in vaccine supply is beneficial if initial coverage is less than the specified target range. Also, among the vaccines considered in the study, the one with 89.9% effectiveness and has a 183 Philippine peso (Php) price per dose projected the least number of deaths. Compared to other model variations and common allocation approaches, the model has achieved both an optimal and equitable allocation. This will be helpful for policymakers in determining a vaccine distribution for a resource-constrained community.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.15.21251572", + "rel_abs": "Shelter-in-place mandates and closure of non-essential businesses have been central to COVID-19 response strategies including in Toronto, Canada. Approximately half of the working population in Canada are employed in occupations that do not allow for remote work suggesting potentially limited impact of some of the strategies proposed to mitigate COVID-19 acquisition and onward transmission risks and associated morbidity and mortality. We compared per-capita rates of COVID-19 cases and deaths from January 23, 2020 to January 24, 2021, across neighborhoods in Toronto by proportion of the population working in essential services. We used person-level data on laboratory-confirmed COVID-19 community cases (N=74,477) and deaths (N=2319), and census data for neighborhood-level attributes. Cumulative per-capita rates of COVID-19 cases and deaths were 3-fold and 2.5-fold higher, respectively, in neighborhoods with the highest versus lowest concentration of essential workers. Findings suggest that the population who continued to serve the essential needs of society throughout COVID-19 shouldered a disproportionate burden of transmission and deaths. Taken together, results signal the need for active intervention strategies to complement restrictive measures to optimize both the equity and effectiveness of COVID-19 responses.", "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Christian Alvin H Buhat", - "author_inst": "University of the Philippines Los Banos" + "author_name": "Amrita Rao", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" }, { - "author_name": "Destiny SM Lutero", - "author_inst": "University of the Philippines Los Banos" + "author_name": "Huiting Ma", + "author_inst": "St. Michael's Hospital, University of Toronto" }, { - "author_name": "Yancee H Olave", - "author_inst": "University of the Philippines Los Banos" + "author_name": "Gary Moloney", + "author_inst": "St. Michael's Hospital, University of Toronto" }, { - "author_name": "Kemuel M Quindala", - "author_inst": "University of the Philippines Los Banos" + "author_name": "Jeff Kwong", + "author_inst": "ICES" }, { - "author_name": "Mary Grace P Recreo", - "author_inst": "University of the Philippines Los Banos" + "author_name": "Peter Juni", + "author_inst": "St. Michael's Hospital, University of Toronto" }, { - "author_name": "Dylan Antonio SJ Talabis Jr.", - "author_inst": "University of the Philippines Los Banos" + "author_name": "Beate Sander", + "author_inst": "ICES; Institute of Health Policy, Management and Evaluation, University of Toronto; Public Health Ontario, Toronto, Canada" }, { - "author_name": "Monica C Torres", - "author_inst": "University of the Philippines Los Banos" + "author_name": "Rafal Kustra", + "author_inst": "Dalla Lana School of Public Health, University of Toronto" }, { - "author_name": "Jerrold M Tubay", - "author_inst": "University of the Philippines Los Banos" + "author_name": "Stefan D Baral", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" }, { - "author_name": "Jomar F Rabajante", - "author_inst": "University of the Philippines Los Banos" + "author_name": "Sharmistha Mishra", + "author_inst": "St. Michael's Hospital, University of Toronto;Division of Infectious Diseases, Department of Medicine, University of Toronto" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.02.15.21249420", @@ -900231,39 +899099,275 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.15.21251777", - "rel_title": "Overall burden and characteristics of COVID-19 in the United States during 2020", + "rel_doi": "10.1101/2021.02.12.21251294", + "rel_title": "Seroprevalence of anti-SARS-CoV-2 IgG antibodies among truck drivers and assistants in Kenya", "rel_date": "2021-02-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.15.21251777", - "rel_abs": "The COVID-19 pandemic disrupted health systems and economies throughout the world during 2020 and was particularly devastating for the United States. Many of epidemiological features that produced observed rates of morbidity and mortality have not been thoroughly assessed. Here we use a data-driven model-inference approach to simulate the pandemic at county-scale in the United States during 2020 and estimate critical, time-varying epidemiological properties underpinning the dynamics of the virus. The pandemic in the US during 2020 was characterized by an overall ascertainment rate of 21.6% (95% credible interval (CI):18.9 - 25.5%). Population susceptibility at years end was 68.8% (63.4 - 75.3%), indicating roughly one third of the US population had been infected. Community infectious rates, the percentage of people harboring a contagious infection, rose above 0.8% (0.6 - 1.0%) before the end of the year, and were as high as 2.4% in some major metropolitan areas. In contrast, the infection fatality rate fell to 0.3% by years end; however, community control of transmission, estimated from trends of the time-varying reproduction number, Rt, slackened during successive pandemic waves. In the coming months, as vaccines are distributed and administered and new more transmissible virus variants emerge and spread, greater use of non-pharmaceutical interventions will be needed.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.12.21251294", + "rel_abs": "In October 2020, anti-SARS-CoV-2 IgG seroprevalence among truck drivers and their assistants (TDA) in Kenya was 42.3%, higher than among other key populations. TDA transport essential supplies during the COVID-19 pandemic, placing them at increased risk of being infected and of transmitting SARS-CoV-2 infection over a wide geographical area.", + "rel_num_authors": 64, "rel_authors": [ { - "author_name": "Sen Pei", - "author_inst": "Columbia University" + "author_name": "E Wangeci Kagucia", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Teresa K. Yamana", - "author_inst": "Columbia University" + "author_name": "John N Gitonga", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Sasikiran Kandula", - "author_inst": "Columbia University" + "author_name": "Catherine Kalu", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Marta Galanti", - "author_inst": "Columbia University" + "author_name": "Eric Ochomo", + "author_inst": "KEMRI Centre for Global Health Research (CGHR), Kisumu, Kenya" }, { - "author_name": "Jeffrey Shaman", - "author_inst": "Columbia University" + "author_name": "Benard Ochieng", + "author_inst": "KEMRI Centre for Global Health Research (CGHR), Kisumu, Kenya" + }, + { + "author_name": "Nickline Kuya", + "author_inst": "KEMRI Centre for Global Health Research (CGHR), Kisumu, Kenya" + }, + { + "author_name": "Angela Karani", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "James Nyagwange", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Boniface Karia", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Daisy Mugo", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Henry K Karanja", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "James Tuju", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Agnes Mutiso", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Hosea Maroko", + "author_inst": "KEMRI Centre for Infectious and Parasitic Diseases Control Research, Alupe, Kenya" + }, + { + "author_name": "Lucy Okubi", + "author_inst": "KEMRI Centre for Infectious and Parasitic Diseases Control Research, Alupe, Kenya" + }, + { + "author_name": "Eric Maitha", + "author_inst": "Department of Health, Kilifi County, Kenya" + }, + { + "author_name": "Hossan Ajuck", + "author_inst": "Department of Health, Kilifi County, Kenya" + }, + { + "author_name": "Mary Bogita", + "author_inst": "Department of Health, Kilifi County, Kenya" + }, + { + "author_name": "Richmond Mudindi", + "author_inst": "Department of Health, Kilifi County, Kenya" + }, + { + "author_name": "David Mukabi", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "Wycliffe Moracha", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "David Bulimu", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "Nelson Andanje", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "Evans Shiraku", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "Rosemary Okuku", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "Monicah Ogutu", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "Rashid Aman", + "author_inst": "Ministry of Health, Government of Kenya, Nairobi, Kenya" + }, + { + "author_name": "Mercy Mwangangi", + "author_inst": "Ministry of Health, Government of Kenya, Nairobi, Kenya" + }, + { + "author_name": "Patrick Amoth", + "author_inst": "Ministry of Health, Government of Kenya, Nairobi, Kenya" + }, + { + "author_name": "Kadondi Kasera", + "author_inst": "Ministry of Health, Government of Kenya, Nairobi, Kenya" + }, + { + "author_name": "Wangari Ng'ang'a", + "author_inst": "Presidential Policy and Strategy Unit, The Presidency, Government of Kenya" + }, + { + "author_name": "Rodgers Mariga", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "Tobias Munabi", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "Susan M Ramadhan", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "Janet Mwikali", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "Rose Nasike", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "Cornelius Andera", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "Roselyne Nechesa", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "Benson K Kiplagat", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "Julius Omengo", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "Simon Oteba", + "author_inst": "Department of Health, Busia County, Kenya" + }, + { + "author_name": "Arthur Mwangi", + "author_inst": "Department of Health, Kilifi County, Kenya" + }, + { + "author_name": "Dorcas Mkanyi", + "author_inst": "Department of Health, Kilifi County, Kenya" + }, + { + "author_name": "George Karisa", + "author_inst": "Department of Health, Kilifi County, Kenya" + }, + { + "author_name": "Judith K Migosi", + "author_inst": "Department of Health, Kilifi County, Kenya" + }, + { + "author_name": "Patrick Msili", + "author_inst": "Department of Health, Kilifi County, Kenya" + }, + { + "author_name": "Samson Mwambire", + "author_inst": "Department of Health, Kilifi County, Kenya" + }, + { + "author_name": "Anthony M Boniface", + "author_inst": "Department of Health, Kilifi County, Kenya" + }, + { + "author_name": "Amek Nyaguara", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Shirine Voller", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK" + }, + { + "author_name": "Mark Otiende", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Christian Bottomley", + "author_inst": "Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK" + }, + { + "author_name": "Charles N Agoti", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Lynette I Ochola-Oyier", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Ifedayo M O Adetifa", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK" + }, + { + "author_name": "Anthony O Etyang", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Katherine E Gallagher", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK" + }, + { + "author_name": "Sophie Uyoga", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Edwine Barasa", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Philip Bejon", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya; Nuffield Department of Medicine, Oxford University, UK" + }, + { + "author_name": "Benjamin Tsofa", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "Ambrose Agweyu", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" + }, + { + "author_name": "George M Warimwe", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya; Nuffield Department of Medicine, Oxford University, UK" + }, + { + "author_name": "J Anthony G Scott", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK; Nuffi" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.02.15.21251781", @@ -902032,45 +901136,101 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2021.02.16.430255", - "rel_title": "A chicken IgY can efficiently inhibit the entry and replication of SARS-CoV-2 by targeting the ACE2 binding domain in vitro", + "rel_doi": "10.1101/2021.02.15.431215", + "rel_title": "Characterization of humoral and SARS-CoV-2 specific T cell responses in people living with HIV", "rel_date": "2021-02-16", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.16.430255", - "rel_abs": "COVID-19 pneumonia has now spread widely in the world. Currently, no specific antiviral drugs are available. The vaccine is the most effective way to control the epidemic. Passive immune antibodies are also an effective method to prevent and cure COVID-19 pneumonia. We used the SARS-CoV-2 S receptor-binding domain (RBD) as an antigen to immunize layers in order to extract, separate, and purify SARS-CoV-2-IgY from egg yolk. SARS-CoV-2-IgY (S-IgY)can block the entry of SARS-CoV-2 into the Cells and reduce the viral load in cells. The Half effective concentration (EC50) of W3-IgY (S-IgY in the third week after immunization) is 1.35 {+/-} 0.15nM. The EC50 of W9-IgY (S-IgY in the ninth week after immunization) is 2.76 {+/-} 1.54 nM. When the dose of S-IgY is 55 nM, the fluorescence representing intracellular viral protein is obviously weakened in Immunofluorescence microscopy.\n\nResults of Sars-CoV-2 /Vero E6 cell experiment confirmed that S-IgY has a strong antiviral effect on SARS-CoV-2, and its (EC50) is 27.78 {+/-}1.54 nMvs 3,259 {+/-} 159.62 nM of Redesivir (differ > 106 times P<0.001).\n\nS-IgY can inhibit the entry and replication of SARS-CoV-2, which is related to its targeting the ACE2 binding domain.\n\nS-IgY is safe, efficient, stable, and easy to obtain. This antibody can be an effective tool for preventing and treating COVID-19 pneumonia.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC=\"FIGDIR/small/430255v3_fig1.gif\" ALT=\"Figure 1\">\nView larger version (38K):\norg.highwire.dtl.DTLVardef@f24996org.highwire.dtl.DTLVardef@bd26b9org.highwire.dtl.DTLVardef@3956bborg.highwire.dtl.DTLVardef@6d4785_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 1.C_FLOATNO Graphical Abstract\n\nThe figure briefly illustrates that the preparation and extraction of S-IgY and its anti-S-CoV-2 mechanism is to inhibit the entry and replication of SARS-CoV-2 by targeting the ACE2.\n\nC_FIG", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.15.431215", + "rel_abs": "There is an urgent need to understand the nature of immune responses generated against SARS-CoV-2, to better inform risk-mitigation strategies for people living with HIV (PLWH). Although not all PLWH are considered immunosuppressed, residual cellular immune deficiency and ongoing inflammation could influence COVID-19 disease severity, the evolution and durability of protective memory responses. Here, we performed an integrated analysis, characterizing the nature, breadth and magnitude of SARS-CoV-2-specific immune responses in PLWH, controlled on ART, and HIV negative subjects. Both groups were in the convalescent phase of predominately mild COVID-19 disease. The majority of PLWH mounted SARS-CoV-2 Spike- and Nucleoprotein-specific antibodies with neutralizing activity and SARS-CoV-2-specific T cell responses, as measured by ELISpot, at levels comparable to HIV negative subjects. T cell responses against Spike, Membrane and Nucleocapsid were the most prominent, with SARS-CoV-2-specific CD4 T cells outnumbering CD8 T cells. Notably, the overall magnitude of SARS-CoV-2-specific T cell responses related to the size of the naive CD4 T cell pool and the CD4:CD8 ratio in PLWH, in whom disparate antibody and T cell responses were observed. Both humoral and cellular responses to SARS-CoV-2 were detected at 5-7 months post-infection, providing evidence of medium-term durability of responses irrespective of HIV serostatus. Incomplete immune reconstitution on ART and a low CD4:CD8 ratio could, however, hamper the development of immunity to SARS-CoV-2 and serve as a useful tool for risk stratification of PLWH. These findings have implications for the individual management and potential effectiveness of vaccination against SARS-CoV-2 in PLWH.\n\nOne Sentence SummaryAdaptive immune responses to SARS-CoV-2 in the setting of HIV infection", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Wei Jingchen", - "author_inst": "Guilin Medical University" + "author_name": "Aljawharah Alrubayyi", + "author_inst": "Nuffield Dept of Clinical Medicine, University of Oxford, United Kingdom" }, { - "author_name": "Lu Yunfei", - "author_inst": "Guilin medical University" + "author_name": "Ester Gea-Mallorqui", + "author_inst": "Nuffield Dept of Clinical Medicine, University of Oxford, United Kingdom" }, { - "author_name": "Rui Ying", - "author_inst": "Guilin medical University" + "author_name": "Emma Touizer", + "author_inst": "University College London (UCL)" }, { - "author_name": "Zhu Xuanyu", - "author_inst": "Guilin medical University" + "author_name": "Dan Hameiri-Bowen", + "author_inst": "Nuffield Dept of Clinical Medicine, University of Oxford, United Kingdom" }, { - "author_name": "He Songqing", - "author_inst": "The first affiliated hospital of Guangxi medical university" + "author_name": "Jakub Kopycinski", + "author_inst": "Nuffield Dept of Clinical Medicine, University of Oxford, United Kingdom" }, { - "author_name": "Wu Shuwen", - "author_inst": "Wuhan university" + "author_name": "Bethany Charlton", + "author_inst": "Nuffield Dept of Clinical Medicine, University of Oxford, United Kingdom" + }, + { + "author_name": "Narasha Fisher-Pearson", + "author_inst": "Nuffield Dept of Clinical Medicine, University of Oxford, United Kingdom" + }, + { + "author_name": "Luke Muir", + "author_inst": "Division of Infection and Immunity, University College London, London, United Kingdom" + }, + { + "author_name": "Annachiara Rosa", + "author_inst": "Chromatin Structure and Mobile DNA Laboratory, The Francis Crick Institute, London, United Kingdom" + }, + { + "author_name": "Chloe Roustan", + "author_inst": "Chromatin Structure and Mobile DNA Laboratory, The Francis Crick Institute, London, United Kingdom" + }, + { + "author_name": "Christopher Earl", + "author_inst": "Chromatin Structure and Mobile DNA Laboratory, The Francis Crick Institute, London, United Kingdom" + }, + { + "author_name": "Peter Cherepanov", + "author_inst": "The Francis Crick Institute" + }, + { + "author_name": "Pierre Pellegrino", + "author_inst": "Mortimer Market Centre, Department of HIV, CNWL NHS Trust, London, United Kingdom" + }, + { + "author_name": "Laura Waters", + "author_inst": "Mortimer Market Centre, Department of HIV, CNWL NHS Trust, London, United Kingdom" + }, + { + "author_name": "Fiona Burns", + "author_inst": "Institute for Global Health UCL, London, United Kingdom" + }, + { + "author_name": "Sabine Kinloch", + "author_inst": "Royal Free London NHS Foundation Trust, London, United Kingdom" }, { - "author_name": "Xu Qing", - "author_inst": "Guilin Medical University" + "author_name": "Tao Dong", + "author_inst": "University of Oxford" + }, + { + "author_name": "Lucy Dorrell", + "author_inst": "Nuffield Dept of Clinical Medicine, University of Oxford, United Kingdom" + }, + { + "author_name": "Sarah Rowland-Jones", + "author_inst": "Nuffield Dept of Clinical Medicine, University of Oxford, United Kingdom" + }, + { + "author_name": "Laura E McCoy", + "author_inst": "University College London" + }, + { + "author_name": "Dimitra Peppa", + "author_inst": "University of Oxford" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "immunology" }, @@ -903761,47 +902921,51 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.02.14.431122", - "rel_title": "In vitro efficacy of Artemisia extracts against SARS-CoV-2", + "rel_doi": "10.1101/2021.02.14.431174", + "rel_title": "Direct activation of endothelial cells by SARS-CoV-2 nucleocapsid protein is blocked by Simvastatin", "rel_date": "2021-02-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.14.431122", - "rel_abs": "Traditional medicines based on herbal extracts have been proposed as affordable treatments for patients suffering from coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Teas and drinks containing extracts of Artemisia annua and Artemisia afra have been widely used in Africa in efforts to prevent and fight COVID-19 infections. We sought to study the ability of different A. annua and A. afra extracts and the Covid-Organics drink produced in Madagascar to inhibit SARS-CoV-2 and feline coronavirus (FCoV) replication in vitro. Several extracts as well as Covid-Organics inhibit SARS-CoV-2 and FCoV replication at concentrations that did not affect cell viability. It remains unclear whether peak plasma concentrations in humans can reach levels needed to inhibit viral replication following consumption of teas or Covid-Organics. Clinical studies are required to evaluate the utility of these drinks for COVID-19 prevention or treatment in patients.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.14.431174", + "rel_abs": "Emerging evidence suggests that endothelial activation plays a central role in the pathogenesis of acute respiratory distress syndrome (ARDS) and multi-organ failure in patients with COVID-19. However, the molecular mechanisms underlying endothelial activation in COVID-19 patients remain unclear. In this study, the SARS-CoV-2 viral proteins that potently activate human endothelial cells were screened to elucidate the molecular mechanisms involved with endothelial activation. It was found that nucleocapsid protein (NP) of SARS-CoV-2 significantly activated human endothelial cells through TLR2/NF-{kappa}B and MAPK signaling pathways. Moreover, by screening a natural microbial compound library containing 154 natural compounds, simvastatin was identified as a potent inhibitor of NP-induced endothelial activation. Remarkablely, though the protein sequences of N proteins from coronaviruses are highly conserved, only NP from SARS-CoV-2 induced endothelial activation. The NPs from other coronaviruses such as SARS-CoV, MERS-CoV, HUB1-CoV and influenza virus H1N1 did not affect endothelial activation. These findings are well consistent with the results from clinical investigations showing broad endotheliitis and organ injury in severe COVID-19 patients. In conclusion, the study provides insights on SARS-CoV-2-induced vasculopathy and coagulopathy, and suggests that simvastatin, an FDA-approved lipid-lowering drug, may benefit to prevent the pathogenesis and improve the outcome of COVID-19 patients.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Chuanxiong Nie", - "author_inst": "Freie Universitat Berlin" + "author_name": "Yisong Qian", + "author_inst": "University of Missouri Kansas City" }, { - "author_name": "Jakob Trimpert", - "author_inst": "Freie Universitat Berlin" + "author_name": "Tianhua Lei", + "author_inst": "University of Missouri Kansas City" }, { - "author_name": "Sooyeon Moon", - "author_inst": "Max-Planck Institute for Colloids and Interfaces" + "author_name": "Parth Patel", + "author_inst": "University of Missouri Kansas City" }, { - "author_name": "Rainer Haag", - "author_inst": "Freie Universitat Berlin" + "author_name": "Chi Lee", + "author_inst": "University of Missouri Kansas City" }, { - "author_name": "Kerry Gilmore", - "author_inst": "University of Connecticut" + "author_name": "Paula Monaghan-Nichols", + "author_inst": "University of Missouri Kansas City" }, { - "author_name": "Benedikt B. Kaufer", - "author_inst": "Freie Universitat Berlin" + "author_name": "Hong-Bo Xin", + "author_inst": "Nanchang University" }, { - "author_name": "Peter H. Seeberger", - "author_inst": "Max Planck Institute for Colloids and Interfaces" + "author_name": "Jianming Qiu", + "author_inst": "University of Kansas Medical Center" + }, + { + "author_name": "Mingui Fu", + "author_inst": "University of Missouri Kansas City" } ], "version": "1", - "license": "", + "license": "cc_no", "type": "new results", - "category": "pharmacology and toxicology" + "category": "immunology" }, { "rel_doi": "10.1101/2021.02.12.431032", @@ -905283,31 +904447,75 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2021.02.09.21251280", - "rel_title": "Demographic and Hygienic Factors as Predictors of Face Mask Wearing During Covid-19 Pandemic in Malaysia", + "rel_doi": "10.1101/2021.02.09.21251433", + "rel_title": "A Comparative Analysis of COVID-19 Physical Distancing Policies in Botswana, India, Jamaica, Mozambique, Namibia, Ukraine, and the United States", "rel_date": "2021-02-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.09.21251280", - "rel_abs": "Wearing a face mask has been recognised as an effective way of slowing down the spread of the Covid-19 pandemic. However, there is scarce evidence on predictors of face mask wearing during a pandemic. This research aims to investigate which demographic and hygienic factors could predict the compliance for face mask wearing in Malaysia. We employed a structured online survey of 708 Malaysian adult respondents. Among the factors examined, we found gender, hand washing and wearing of personal protective equipment significantly predicted face mask wearing.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.09.21251433", + "rel_abs": "BackgroundUnderstanding the differences in timing and composition of physical distancing policies is important to evaluate the early global response to COVID-19. A physical distancing intensity framework comprising 16 domains was recently published to compare physical distancing approaches between U.S. States. We applied this framework to a diverse set of low and middle-income countries (LMICs) (Botswana, India, Jamaica, Mozambique, Namibia, and Ukraine) to test the appropriateness of this framework in the global context and to compare the policy responses in this set of LMICs and with a sample of U.S. States during the first 100-days of the epidemic.\n\nResultsAll six of the LMICs in our sample adopted wide ranging physical distancing policies. The highest peak daily physical distancing intensity in each country was: Botswana (4.60); India (4.40); Ukraine (4.40); Namibia (4.20); and Jamaica (3.80). The number of days each country stayed at peak intensity ranged from 12-days (Jamaica) to more than 67-days (Mozambique). We found some key similarities and differences, including substantial differences in whether and how countries expressly required certain groups to stay at home. We also found that the LMICs generally implemented physical distancing policies when there were few confirmed cases and the easing of physical distancing policies did not discernably correlate with change in COVID-19 incidence. The physical distancing responses in the LMIC sample were generally more intense than in a sample of U.S. States, but results vary depending on the U.S. State. For example, California had a peak intensity of 4.29, which would place California below the peak intensity for Botswana, India, and Ukraine but above Mozambique, Namibia and Jamaica. The U.S. State of Georgia had a peak intensity of 3.07, which would place it lower than all of the LMICs in this sample. The peak intensity for the U.S. 12-state average was 3.84, which would place it lower than every LMIC in this sample except Jamaica.\n\nConclusionThis analysis helps to highlight the differing paths taken by the countries in this sample and may provide lessons to other countries regarding options for structuring physical distancing policies in response to COVID-19 and future outbreaks.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Kim Hoe Looi", - "author_inst": "Xiamen University Malaysia" + "author_name": "Jeff Lane", + "author_inst": "University of Washington" }, { - "author_name": "Stephen X. Zhang", - "author_inst": "University of Adelaide" + "author_name": "Arianna Means", + "author_inst": "University of Washington" }, { - "author_name": "Nicolas Li", - "author_inst": "University of Dundee" + "author_name": "Kevin Bardosh", + "author_inst": "University of Washington" + }, + { + "author_name": "Anna Shapoval", + "author_inst": "International Training and Education Center for Health - Ukraine" + }, + { + "author_name": "Ferruccio Vio", + "author_inst": "International Training and Education Center for Health - Mozambique" + }, + { + "author_name": "Clive Anderson", + "author_inst": "International Training and Education Center for Health - Jamaica" + }, + { + "author_name": "Anya Cushnie", + "author_inst": "International Training and Education Center for Health - Jamaica" + }, + { + "author_name": "Norbert Forster", + "author_inst": "International Training and Education Center for Health - Namibia" + }, + { + "author_name": "Jenny Ledikwe", + "author_inst": "International Training and Education Center for Health - Botswana" + }, + { + "author_name": "Gabrielle O'Malley", + "author_inst": "University of Washington" + }, + { + "author_name": "Shreshth Mawandia", + "author_inst": "International Training and Education Center for Health - Botswana" + }, + { + "author_name": "Anwar Parvez", + "author_inst": "UW International Training and Education Center for Health, private limited, India" + }, + { + "author_name": "Lucy Perrone", + "author_inst": "University of Washington" + }, + { + "author_name": "Florindo Mudender", + "author_inst": "International Training and Education Center for Health - Mozambique" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "health policy" }, { "rel_doi": "10.1101/2021.02.10.21251478", @@ -907015,46 +906223,74 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.10.21250862", - "rel_title": "Seroprevalence of SARS-CoV-2, symptom profiles and seroneutralization during the first COVID-19 wave in a suburban area, France", + "rel_doi": "10.1101/2021.02.10.21251242", + "rel_title": "Response to Whole-Lung Low-Dose Radiation Therapy (LD-RT) Predicts Freedom from Intubation in Patients Receiving Dexamethasone and/or Remdesevir for COVID-19-Related Acute Respiratory Distress Syndrome (ARDS)", "rel_date": "2021-02-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.10.21250862", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.10.21251242", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Anne G\u00e9gout-Petit", - "author_inst": "Universit\u00e9 de Lorraine" + "author_name": "Clayton Burnett Hess", + "author_inst": "Emory University" + }, + { + "author_name": "Tony Y Eng", + "author_inst": "Emory University" }, { - "author_name": "H\u00e9l\u00e8ne Jeulin", - "author_inst": "Centre Hospitalier R\u00e9gional Universitaire de Nancy/Universit\u00e9 de Lorraine" + "author_name": "Tahseen H Nasti", + "author_inst": "Emory University" }, { - "author_name": "Karine Legrand", - "author_inst": "CHRU Nancy, INSERM, Universit\u00e9 de Lorraine" + "author_name": "Vishal Ramesh Dhere", + "author_inst": "Emory University" }, { - "author_name": "Agathe Bochnakian", - "author_inst": "CHRU Nancy, INSERM, Universit\u00e9 de Lorraine" + "author_name": "Troy Kleber", + "author_inst": "Emory University" }, { - "author_name": "Pierre Vallois", - "author_inst": "Universit\u00e9 de Lorraine" + "author_name": "Jeffery M Switchenko", + "author_inst": "Emory University" }, { - "author_name": "Evelyne Schvoerer", - "author_inst": "Centre Hospitalier R\u00e9gional Universitaire de Nancy/Universit\u00e9 de Lorraine" + "author_name": "Brent D Weinberg", + "author_inst": "Emory University" + }, + { + "author_name": "Nadine Rouphael", + "author_inst": "Emory University" + }, + { + "author_name": "Sibo Tian", + "author_inst": "Emory University" + }, + { + "author_name": "Soumon Rudra", + "author_inst": "Emory University" + }, + { + "author_name": "Louisa S Taverna", + "author_inst": "Emory University" + }, + { + "author_name": "Alvaro Perez", + "author_inst": "Emory University" + }, + { + "author_name": "Rafi Ahmed", + "author_inst": "Emory University" }, { - "author_name": "Francis Guillemin", - "author_inst": "CHRU Nancy, INSERM, Universit\u00e9 de Lorraine" + "author_name": "Mohammad K Khan", + "author_inst": "Emory University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.02.10.21251247", @@ -909007,39 +908243,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.03.21250661", - "rel_title": "Implementation of an in-house real-time reverse transcription-PCR assay to detect the emerging SARS-CoV-2 N501Y variants", + "rel_doi": "10.1101/2021.02.08.21250291", + "rel_title": "Hospitalizations, resource use and outcomes of acute pulmonary embolism in Germany during the Covid-19 pandemic - Emergence of different phenotypes of thrombotic disease?", "rel_date": "2021-02-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.03.21250661", - "rel_abs": "The real-time detection of emerging SARS-CoV-2 variants is critical to manage patients appropriately, and monitor and assess their epidemiological and clinical features. Sequencing is not a feasible comprehensive detection strategy considering the very large number of SARS-CoV-2 cases in our current setting. SARS-CoV-2 variants currently of greatest concern carry the N501Y substitution within the spike receptor binding domain. They have become predominant in England (20I/501Y.V1) and were detected in South Africa (20H/501Y.V2), Brazil and dozens of other countries worldwide. The 20I/501Y.V1 variant has started to spread worldwide including in France. It has been reported as 50-74% more transmissible than preexisting strains, suspected to evade anti-spike antibodies, and it caused a reinfection. We have implemented an in-house one-step real-time reverse transcription-PCR (qPCR) assay that specifically detects SARS-CoV-2 N501Y. It was found reliable to detect specifically the N501Y substitution and preliminarily allowed estimating 20I/501Y.V1 variant prevalence to 4% among our current SARS-CoV-2 diagnoses since January.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.08.21250291", + "rel_abs": "BackgroundThere is discussion evolving around the emergence of different phenotypes of Covid-19-associated thromboembolic disease, i.e. acute pulmonary embolism vs pulmonary thrombosis and different phenotypes of in situ thrombosis. With this study, we wish to provide hospitalization, treatment and in-hospital outcome data for pulmonary embolism during the 2020 Covid-19 pandemic and a corresponding 2016 - 2019 control period.\n\nMethodsWe performed a retrospective analysis of claims data of Helios hospitals in Germany. Consecutive cases with a hospital admission between January 1 and December 15, 2020 and pulmonary embolism as primary discharge diagnosis were analyzed and compared to a corresponding period covering the same weeks in 2016 - 2019.\n\nResultsAs previously reported for other emergent medical conditions, there was a hospitalization deficit coinciding with the 1st pandemic wave. Beginning with the 12-week interval May 6 - July 28, there was a stable surplus of hospital admissions in 2020. During this surplus period (May 6 - December 15, 2020), there were 2,449 hospitalizations including 45 PCR-confirmed Covid-19 cases (1.8%) as opposed to 8,717 in 2016 - 2019 (IRR 1.12, 95% CI 1.07 - 1.18, P<0.01). When excluding Covid-19 cases IRR was 1.10 (95% CI 1.05 - 1.15, P<0.01). While overall comorbidities expressed as weighted AHRQ Elixhauser Comorbidity Index (14.1 {+/-} 10.1 vs. 13.9 {+/-}10.3, P=0.28), the presence of thrombosis (46.1 vs 45.4%, P=0.55) and surgery (3.8 vs. 4.3%, P=0.33) were comparable, coagulopathy (3.3 vs 4.5%, P=0.01) and metastatic cancer (3.0 vs 4.0%, P=0.03) as contributing factors were less frequently observed during the 2020 surplus. Interventional treatments (thrombolytic therapy, thrombectomy or inferior vena cava filter placement) were less frequently used (4.7 vs 6.6%, OR 0.72, 95% CI 0.58 - 0.89, P< 0.01). Similarly, intensive care (35.1 vs 38.8%, OR 0.83, 95% CI 0.75 - 0.92, P< 0.01) and mechanical ventilation utilization (7.2 vs 8.1%, OR 0.88, 95% CI 0.74 - 1.04, P=0.14) as well as in-hospital-mortality rates (7.8 vs 9.8%, OR 0.76, 95% CI 0.64 - 0.90, P< 0.01) were lower in 2020 compared with 2016 - 2019. This was associated with a shorter length of hospital stay (6.4 {+/-}5.4 vs. 7.2 {+/-}5.7 days, P< 0.01) during the 2020 surplus period.\n\nConclusionsOnly a minority of cases were associated with PCR-confirmed Covid-19 but this does not rule out preceding or undetected SARS-CoV-2 infection. Although there is a shift towards milder disease course, the increased incidence of hospitalizations for pulmonary embolism requires immediate attention, close surveillance and further studies.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Marielle Bedotto", - "author_inst": "IHU Mediterranee Infection" + "author_name": "Daniela Husser", + "author_inst": "Heart Center Leipzig at University of Leipzig and Leipzig Heart Institute" }, { - "author_name": "Pierre-Edouard Fournier", - "author_inst": "IHU Mediterranee Infection" + "author_name": "Sven Hohenstein", + "author_inst": "Heart Center Leipzig at University of Leipzig and Leipzig Heart Institute" }, { - "author_name": "Linda Houhamdi", - "author_inst": "IHU Mediterranee Infection" + "author_name": "Vincent Pellissier", + "author_inst": "Heart Center Leipzig at University of Leipzig and Leipzig Heart Institute" }, { - "author_name": "Philippe Colson", - "author_inst": "Aix-Marseille university IHU Mediterranee Infection" + "author_name": "Sebastian Koenig", + "author_inst": "Heart Center Leipzig at University of Leipzig and Leipzig Heart Institute" }, { - "author_name": "Didier Raoult", - "author_inst": "Aix Marseille Universite IHU Mediterranee Infection" + "author_name": "Laura Ueberham", + "author_inst": "Heart Center Leipzig at University of Leipzig and Leipzig Heart Institute" + }, + { + "author_name": "Gerhard Hindricks", + "author_inst": "Heart Center Leipzig at University of Leipzig and Leipzig Heart Institute" + }, + { + "author_name": "Andreas Meier-Hellmann", + "author_inst": "Helios Hospitals" + }, + { + "author_name": "Ralf Kuhlen", + "author_inst": "Helios Health" + }, + { + "author_name": "ANDREAS BOLLMANN", + "author_inst": "Heart Center Leipzig at University of Leipzig and Leipzig Heart Institute" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2021.02.08.21250309", @@ -911269,77 +910521,53 @@ "category": "neuroscience" }, { - "rel_doi": "10.1101/2021.02.09.430458", - "rel_title": "Intranasal type I interferon treatment is beneficial only when administered before clinical signs onset in the SARS-CoV-2 hamster model", + "rel_doi": "10.1101/2021.02.09.430349", + "rel_title": "A Human 3D neural assembloid model for SARS-CoV-2 infection", "rel_date": "2021-02-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.09.430458", - "rel_abs": "Impaired type I interferons (IFNs) production or signaling have been associated with severe COVID-19, further promoting the evaluation of recombinant type I IFNs as therapeutics against SARS-CoV-2 infection. In the Syrian hamster model, we show that intranasal administration of IFN- starting one day pre-infection or one day post-infection limited weight loss and decreased viral lung titers. By contrast, intranasal administration of IFN- starting at the onset of symptoms three days post-infection had no impact on the clinical course of SARS-CoV-2 infection. Our results provide evidence that early type I IFN treatments are beneficial, while late interventions are ineffective, although not associated with signs of enhanced disease.\n\nOne Sentence SummaryThe timing of type I interferon treatment is a critical determinant of its efficacy against SARS-CoV-2 infection.", - "rel_num_authors": 16, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.09.430349", + "rel_abs": "Clinical evidence suggests the central nervous system (CNS) is frequently impacted by SARS-CoV-2 infection, either directly or indirectly, although mechanisms remain unclear. Pericytes are perivascular cells within the brain that are proposed as SARS-CoV-2 infection points1. Here we show that pericyte-like cells (PLCs), when integrated into a cortical organoid, are capable of infection with authentic SARS-CoV-2. Prior to infection, PLCs elicited astrocytic maturation and production of basement membrane components, features attributed to pericyte functions in vivo. While traditional cortical organoids showed little evidence of infection, PLCs within cortical organoids served as viral replication hubs, with virus spreading to astrocytes and mediating inflammatory type I interferon transcriptional responses. Therefore, PLC-containing cortical organoids (PCCOs) represent a new assembloid model2 that supports SARS-CoV-2 entry and replication in neural tissue, and PCCOs serve as an experimental model for neural infection.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Pierre Bessiere", - "author_inst": "Ecole nationale veterinaire de Toulouse, ENVT, INRAE, UMR 1225, IHAP, Universite de Toulouse, Toulouse, France" - }, - { - "author_name": "Marine Wasniewsk", - "author_inst": "Nancy laboratory for rabies and wildlife, ANSES, Lyssavirus Unit, Malzeville, France" - }, - { - "author_name": "Evelyne Picard-Meyer", - "author_inst": "Nancy laboratory for rabies and wildlife, ANSES, Lyssavirus Unit, Malzeville, France" - }, - { - "author_name": "Alexandre Servat", - "author_inst": "Nancy laboratory for rabies and wildlife, ANSES, Lyssavirus Unit, Malzeville, France" - }, - { - "author_name": "Thomas Figueroa", - "author_inst": "Ecole nationale veterinaire de Toulouse, ENVT, INRAE, UMR 1225, IHAP, Universite de Toulouse, Toulouse, France" - }, - { - "author_name": "Charlotte Foret-Lucas", - "author_inst": "Ecole nationale veterinaire de Toulouse, ENVT, INRAE, UMR 1225, IHAP, Universite de Toulouse, Toulouse, France" - }, - { - "author_name": "Amelia Coggon", - "author_inst": "Ecole nationale veterinaire de Toulouse, ENVT, INRAE, UMR 1225, IHAP, Universite de Toulouse, Toulouse, France" + "author_name": "Joseph G Gleeson", + "author_inst": "UCSD" }, { - "author_name": "Sandrine Lesellier", - "author_inst": "Nancy laboratory for rabies and wildlife, ANSES, Atton experimental facility, Atton, France" + "author_name": "Lu Wang", + "author_inst": "UCSD" }, { - "author_name": "Frank Boue", - "author_inst": "Nancy laboratory for rabies and wildlife, ANSES, Lyssavirus Unit, Malzeville, France" + "author_name": "David Sievert", + "author_inst": "UCSD" }, { - "author_name": "Nathan Cebron", - "author_inst": "Ecole nationale veterinaire de Toulouse, ENVT, INRAE, UMR 1225, IHAP, Universite de Toulouse, Toulouse, France" + "author_name": "Alex E Clark", + "author_inst": "UCSD" }, { - "author_name": "Blandine Gausseres", - "author_inst": "Ecole nationale veterinaire de Toulouse, ENVT, INRAE, UMR 1225, IHAP, Universite de Toulouse, Toulouse, France" + "author_name": "Hannah Federman", + "author_inst": "Center for Immunity and Inflammation, New Jersey Medical School" }, { - "author_name": "Catherine Trumel", - "author_inst": "Ecole nationale veterinaire de Toulouse, ENVT, CREFRE, INSERM, Universite de Toulouse, Toulouse, France" + "author_name": "Benjamin D Gastfriend", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Gilles Foucras", - "author_inst": "Ecole nationale veterinaire de Toulouse, ENVT, INRAE, UMR 1225, IHAP, Universite de Toulouse, Toulouse, France" + "author_name": "Eric Shusta", + "author_inst": "University of Wisconsin" }, { - "author_name": "Francisco Javier Salguero", - "author_inst": "National Infection Service, Public Health England (PHE), Porton Down, Salisbury, Wiltshire, SP4 0JG, UK" + "author_name": "Sean Palecek", + "author_inst": "University of Wisconsin - Madison" }, { - "author_name": "Elodie Monchatre-Leroy", - "author_inst": "Nancy laboratory for rabies and wildlife, ANSES, Lyssavirus Unit, Malzeville, France" + "author_name": "Aaron Carlin", + "author_inst": "UCSD" }, { - "author_name": "Romain Volmer", - "author_inst": "Ecole nationale veterinaire de Toulouse, ENVT, INRAE, UMR 1225, IHAP, Universite de Toulouse, Toulouse, France" + "author_name": "Alex E. Clark", + "author_inst": "UC San Diego" } ], "version": "1", @@ -912867,115 +912095,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.02.04.21251134", - "rel_title": "Inhaled budesonide in the treatment of early COVID-19 illness: a randomised controlled trial", + "rel_doi": "10.1101/2021.02.04.21251169", + "rel_title": "DrugWAS: Leveraging drug-wide association studies to facilitate drug repurposing for COVID-19", "rel_date": "2021-02-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.04.21251134", - "rel_abs": "BackgroundMultiple early hospital cohorts of coronavirus disease 2019 (COVID-19) showed that patients with chronic respiratory disease were significantly under-represented. We hypothesised that the widespread use of inhaled glucocorticoids was responsible for this finding and tested if inhaled glucorticoids would be an effective treatment for early COVID-19 illness.\n\nMethodsWe conducted a randomised, open label trial of inhaled budesonide, compared to usual care, in adults within 7 days of the onset of mild Covid-19 symptoms. The primary end point was COVID-19-related urgent care visit, emergency department assessment or hospitalisation. The trial was stopped early after independent statistical review concluded that study outcome would not change with further participant enrolment.\n\nResults146 patients underwent randomisation. For the per protocol population (n=139), the primary outcome occurred in 10 participants and 1 participant in the usual care and budesonide arms respectively (difference in proportion 0.131, p=0.004). The number needed to treat with inhaled budesonide to reduce COVID-19 deterioration was 8. Clinical recovery was 1 day shorter in the budesonide arm compared to the usual care arm (median of 7 days versus 8 days respectively, logrank test p=0.007). Proportion of days with a fever and proportion of participants with at least 1 day of fever was lower in the budesonide arm. Fewer participants randomised to budesonide had persistent symptoms at day 14 and day 28 compared to participants receiving usual care.\n\nConclusionEarly administration of inhaled budesonide reduced the likelihood of needing urgent medical care and reduced time to recovery following early COVID-19 infection.\n\n(Funded by Oxford NIHR Biomedical Research Centre and AstraZeneca; ClinicalTrials.gov number, NCT04416399)\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThe majority of interventions studied for the COVID-19 pandemic are focused on hospitalised patients. Widely available and broadly relevant interventions for mild COVID-19 are urgently needed.\n\nAdded value of this studyIn this open label randomised controlled trial, inhaled budesonide, when given to adults with early COVID-19 illness, reduces the likelihood of requiring urgent care, emergency department consultation or hospitalisation. There was also a quicker resolution of fever, a known poor prognostic marker in COVID-19 and a faster self-reported and questionnaire reported symptom resolution. There were fewer participants with persistent COVID-19 symptoms at 14 and 28 days after budesonide therapy compared to usual care.\n\nImplications of all the available evidenceThe STOIC trial potentially provides the first easily accessible effective intervention in early COVID-19. By assessing health care resource utilisation, the study provides an exciting option to help with the worldwide pressure on health care systems due to the COVID-19 pandemic. Data from this study also suggests a potentially effective treatment to prevent the long term morbidity from persistent COVID-19 symptoms.", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.04.21251169", + "rel_abs": "ImportanceThere is an unprecedented need to rapidly identify safe and effective treatments for the novel coronavirus disease 2019 (COVID-19).\n\nObjectiveTo systematically investigate if any of the available drugs in Electronic Health Record (EHR), including prescription drugs and dietary supplements, can be repurposed as potential treatment for COVID-19.\n\nDesign, Setting, and ParticipantsBased on a retrospective cohort analysis of EHR data, drug-wide association studies (DrugWAS) were performed on COVID-19 patients at Vanderbilt University Medical Center (VUMC). For each drug study, multivariable logistic regression with overlap weighting using propensity score was applied to estimate the effect of drug exposure on COVID-19 disease outcomes.\n\nExposuresPatient exposure to a drug during 1-year prior to the pandemic and COVID-19 diagnosis was chosen as exposure of interest. Natural language processing was employed to extract drug information from clinical notes, in addition to the prescription drug data available in structured format.\n\nMain Outcomes and MeasuresAll-cause of death was selected as primary outcome. Hospitalization, admission to the intensive care unit (ICU), and need for mechanical ventilation were identified as secondary outcomes.\n\nResultsThe study included 7,768 COVID-19 patients, of which 509 (6.55%) were hospitalized, 82 (1.06%) were admitted to ICU, 64 (0.82%) received mechanical ventilation, and 90 (1.16%) died. Overall, 15 drugs were significantly associated with decreased COVID-19 severity. Previous exposure to either Streptococcus pneumoniae vaccines (adjusted odds ratio [OR], 0.38; 95% CI, 0.14-0.98), diphtheria toxoid vaccine (OR, 0.39; 95% CI, 0.15-0.98), and tetanus toxoid vaccine (OR, 0.39; 95% CI, 0.15-0.98) were significantly associated with a decreased risk of death (primary outcome). Secondary analyses identified several other significant associations showing lower risk for COVID-19 outcomes: 2 vaccines (acellular pertussis, Streptococcus pneumoniae), 3 dietary supplements (turmeric extract, flaxseed extract, omega-3 fatty acids), methylprednisolone acetate, pseudoephedrine, ethinyl estradiol, estradiol, ibuprofen, and fluticasone.\n\nConclusions and RelevanceThis cohort study leveraged EHR data to identify a list of drugs that could be repurposed to improve COVID-19 outcomes. Further randomized clinical trials are needed to investigate the efficacy of the proposed drugs.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSCan Electronic Health Records (EHRs) be used to search for drug candidates that could be repurposed to treat the coronavirus disease 2019 (COVID-19)?\n\nFindingsDrug-wide association studies (DrugWAS) of COVID-19 severity outcomes were conducted on a cohort of 7,768 COVID-19 patients. The study found 15 drug ingredients that are significantly associated with a decreased risk of death and other severe COVID-19 outcomes.\n\nMeaningThe list of drugs proposed by this study could provide additional insights into developing new candidates for COVID-19 treatment.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Sanjay Ramakrishnan", - "author_inst": "1.\tNuffield Department of Clinical Medicine, University of Oxford, United Kingdom 2.\tNational Institute for Health Research (NIHR) Oxford Biomedical Research Ce" - }, - { - "author_name": "Dan V Nicolau Jr.", - "author_inst": "1.\tNuffield Department of Clinical Medicine, University of Oxford, United Kingdom 4.\tUQ Centre for Clinical Research, The University of Queensland, Brisbane, Au" - }, - { - "author_name": "Beverly Langford", - "author_inst": "1.\tNuffield Department of Clinical Medicine, University of Oxford, United Kingdom 2.\tNational Institute for Health Research (NIHR) Oxford Biomedical Research Ce" - }, - { - "author_name": "Mahdi Mahdi", - "author_inst": "1.\tNuffield Department of Clinical Medicine, University of Oxford, United Kingdom 2.\tNational Institute for Health Research (NIHR) Oxford Biomedical Research Ce" - }, - { - "author_name": "Helen Jeffers", - "author_inst": "1.\tNuffield Department of Clinical Medicine, University of Oxford, United Kingdom 2.\tNational Institute for Health Research (NIHR) Oxford Biomedical Research Ce" - }, - { - "author_name": "Christine Mwasuku", - "author_inst": "1.\tNuffield Department of Clinical Medicine, University of Oxford, United Kingdom 2.\tNational Institute for Health Research (NIHR) Oxford Biomedical Research Ce" - }, - { - "author_name": "Karolina Krassowska", - "author_inst": "1.\tNuffield Department of Clinical Medicine, University of Oxford, United Kingdom 2.\tNational Institute for Health Research (NIHR) Oxford Biomedical Research Ce" - }, - { - "author_name": "Robin Fox", - "author_inst": "6.\tBicester Health Centre, Coker Close, Bicester, United Kingdom 7.\tNational Institute for Health Research (NIHR) Thames Valley and South Midlands, United Kingd" - }, - { - "author_name": "Ian Binnian", - "author_inst": "8.\tEynsham Medical Group, Eynsham, United Kingdom" - }, - { - "author_name": "Victoria Glover", - "author_inst": "9.\tWhite Horse Medical Practice, Faringdon, United Kingdom" - }, - { - "author_name": "Stephen Bright", - "author_inst": "10.\tWindrush Medical Practice, Witney, United Kingdom" - }, - { - "author_name": "Christopher Butler", - "author_inst": "11.\tNuffield Department of Primary Health Care Sciences, University of Oxford, United Kingdom" - }, - { - "author_name": "Jennifer L Cane", - "author_inst": "1.\tNuffield Department of Clinical Medicine, University of Oxford, United Kingdom 2.\tNational Institute for Health Research (NIHR) Oxford Biomedical Research Ce" - }, - { - "author_name": "Andreas Halner", - "author_inst": "1.\tNuffield Department of Clinical Medicine, University of Oxford, United Kingdom" - }, - { - "author_name": "Philippa C Matthews", - "author_inst": "1.\tNuffield Department of Clinical Medicine, University of Oxford, United Kingdom 12.\tDepartment of Infectious Diseases and Microbiology, Oxford University Hosp" - }, - { - "author_name": "Louise E Donnelly", - "author_inst": "13.\tNational Heart and Lung Institute, Imperial College, London, United Kingdom" - }, - { - "author_name": "Jodie L Simpson", - "author_inst": "14.\tPriority Research Centre for Healthy Lungs, School of Medicine and Public Health, University of Newcastle, NSW Australia." - }, - { - "author_name": "Jonathan R Baker", - "author_inst": "13.\tNational Heart and Lung Institute, Imperial College, London, United Kingdom" - }, - { - "author_name": "Nabil T Fadai", - "author_inst": "15.\tSchool of Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom" + "author_name": "Cosmin A Bejan", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Stefan Peterson", - "author_inst": "16.\tSTATMIND, Lund, Sweden" + "author_name": "Katherine N Cahill", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Thomas Bengtsson", - "author_inst": "16.\tSTATMIND, Lund, Sweden" + "author_name": "Patrick J Staso", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Peter J Barnes", - "author_inst": "13.\tNational Heart and Lung Institute, Imperial College, London, United Kingdom" + "author_name": "Leen Choi", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Richard E K Russell", - "author_inst": "1.\tNuffield Department of Clinical Medicine, University of Oxford, United Kingdom 2.\tNational Institute for Health Research (NIHR) Oxford Biomedical Research Ce" + "author_name": "Josh F Peterson", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Mona Bafadhel", - "author_inst": "1.\tNuffield Department of Clinical Medicine, University of Oxford, United Kingdom 2.\tNational Institute for Health Research (NIHR) Oxford Biomedical Research Ce" + "author_name": "Elizabeth Jane Phillips", + "author_inst": "Vanderbilt University Medical Center" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "primary care research" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.02.04.21251131", @@ -914657,63 +913813,307 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.02.05.21250792", - "rel_title": "Estimated SARS-CoV-2 Seroprevalence in Children and Adolescents in Mississippi, May Through September 2020", + "rel_doi": "10.1101/2021.02.05.21251118", + "rel_title": "Estimation of real-infection and immunity against SARS-CoV-2 in Indian populations", "rel_date": "2021-02-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.05.21250792", - "rel_abs": "Case-based tracking of COVID-19 in children and adolescents may underestimate infection, and compared with adults there is little pediatric SARS-CoV-2 seroprevalence data. To assess evidence of previous SARS-CoV-2 infections among children and adolescents in Mississippi, serologic testing for antibodies to SARS-CoV-2 was conducted on a convenience sample of residual serum specimens collected for routine laboratory testing by an academic medical center laboratory during May 17 through September 19, 2020. Seroprevalence by calendar month was standardized to the state population by race/ethnicity; cumulative numbers of infections were estimated by extrapolating seroprevalence to all those aged <18 years in Mississippi. Serum specimens from 1,603 individuals were tested; 175 (10.9%) were positive for SARS-CoV-2 antibodies. Among 1,579 (98.5%) individuals for whom race/ethnicity was known, the number testing positive was 16 (23.2%) of 69 Hispanic individuals, 117 (13.0%) of 901 non-Hispanic Black individuals and 30 (5.3%) of 565 non-Hispanic White individuals. Population-weighted seroprevalence estimates among those aged <18 years increased from 2.6% in May to 16.9% in September 2020. Cumulative numbers of infections extrapolated from seroprevalence data, however, were estimated at 117,805 (95% confidence interval [CI] = 68,771-168,708), suggesting that cases in children and adolescents are much higher than what was reported to the Mississippi State Department of Health (9,044 cases during this period). Further data to appreciate the burden of pediatric disease to inform public health policy is urgently needed.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.05.21251118", + "rel_abs": "Infection born by Coronavirus SARS-CoV-2 has swept the world within a time of a few months. It has created a devastating effect on humanity with social and economic depression. Europe and America were the hardest hit continents. India has also lost lives, making the country fourth most deadly worldwide. However, the infection and death rate per million and the case fatality ratio in India were substantially lower than in many developed nations. Several factors have been proposed including genetics. One of the important facts is that a large chunk of Indian population is asymptomatic to the SARS-CoV-2 infection. Thus, the real infection in India is much higher than the reported number of cases. Therefore, the majority of people are already immune in the country. To understand the dynamics of real infection as well as the level of immunity against SARS-CoV-2, we have performed antibody testing (serosurveillance) in the urban region of fourteen Indian districts encompassing six states. In our survey, the seroprevalence frequency varied between 0.01-0.48, suggesting high variability of viral transmission between states. We also found out that the cases reported by the government were several fold lower than the real incidence of infection. This discrepancy is mainly driven by the higher number of asymptomatic cases. Overall, we suggest that with the high level of immunity developed against SARS-CoV-2 in the majority of the districts, the case fatality rate of second wave in India will be minor than first wave.", + "rel_num_authors": 72, "rel_authors": [ { - "author_name": "Charlotte V. Hobbs", - "author_inst": "University of Mississippi Medical Center" + "author_name": "Prajjval Pratap Singh", + "author_inst": "Cytogenetics Laboratory Department of Zoology , Banaras Hindu University, India" }, { - "author_name": "Jan Drobeniuc", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Rakesh Tamang", + "author_inst": "Department of Zoology, University of Calcutta, India" }, { - "author_name": "Theresa Kittle", - "author_inst": "Mississippi State Department of Health" + "author_name": "Manoj Shukla", + "author_inst": "Department of Medicinal Chemistry, Institute of Medical Science, Banaras Hindu University, India" }, { - "author_name": "John M. Williams", - "author_inst": "University of Mississippi Medical Center" + "author_name": "Abhishek Pathak", + "author_inst": "Department of Neurology, Institute of Medical Science, Banaras Hindu University, India" }, { - "author_name": "Paul Byers", - "author_inst": "Mississippi State Department of Health" + "author_name": "Anshika Srivastava", + "author_inst": "Cytogenetics Laboratory Department of Zoology , Banaras Hindu University, India" }, { - "author_name": "Subbian S. Panayampalli", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Pranav Gupta", + "author_inst": "Independent Reseracher, Varanasi, India" }, { - "author_name": "Meagan Stephenson", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Alay Bhatt", + "author_inst": "School of Arts and Sciences, Ahmedabad University, India" }, { - "author_name": "Sara S. Kim", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Abhishek K. Shrivastava", + "author_inst": "Department of Biotechnology, Mohd. Hasan P. G. College, Jaunpur, India" }, { - "author_name": "Manish Patel", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Sudhir K. Upadhyay", + "author_inst": "Department of Environmental Science,Veer Bahadur Singh Purvanchal University, Jaunpur, India" }, { - "author_name": "Brendan Flannery", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Ashish Singh", + "author_inst": "Genome Foundation Rural Centre Kalavari, Jaunpur, India, 222131" }, { - "author_name": "- CDC COVID-19 Response Team", - "author_inst": "" + "author_name": "Sanjeev Maurya", + "author_inst": "Genome Foundation Rural Centre Kalavari, Jaunpur, India, 222131" + }, + { + "author_name": "Purnendu Saxena", + "author_inst": "VY Hospital, Raipur, Chhattisgarh, India" + }, + { + "author_name": "Vanya Singh", + "author_inst": "Cytogenetics Laboratory Department of Zoology , Banaras Hindu University, India" + }, + { + "author_name": "Akhilesh Kumar Chaubey", + "author_inst": "Krishi Vigyan Kendra, Singrauli, Jawaharlal Nehru Krishi Vishwavidyalay, Jabalpur, Madhya Pradesh, India" + }, + { + "author_name": "Dinesh Kumar Mishra", + "author_inst": "Mishra Polyclinic, Waidhan, Madhya Pradesh, India, 486886" + }, + { + "author_name": "Yashvant Patel", + "author_inst": "Cytogenetics Laboratory Department of Zoology , Banaras Hindu University, India" + }, + { + "author_name": "Rudra Kumar Pandey", + "author_inst": "Cytogenetics Laboratory Department of Zoology , Banaras Hindu University, India" + }, + { + "author_name": "Ankit Srivastava", + "author_inst": "Dr. A.P.J. Abdul Kalam Institute of Forensic Science & Criminology, Bundelkhand University,Jhansi, India" + }, + { + "author_name": "Nargis Khanam", + "author_inst": "Cytogenetics Laboratory Department of Zoology , Banaras Hindu University, India" + }, + { + "author_name": "Debashruti Das", + "author_inst": "Cytogenetics Laboratory Department of Zoology , Banaras Hindu University, India" + }, + { + "author_name": "Audditiya Bandopadhyay", + "author_inst": "Cytogenetics Laboratory Department of Zoology , Banaras Hindu University, India" + }, + { + "author_name": "Urgyan Chorol", + "author_inst": "Cytogenetics Laboratory Department of Zoology , Banaras Hindu University, India" + }, + { + "author_name": "Nagarjuna Pasupuleti", + "author_inst": "Birbal Sahni Institutes of Palaeosciences, Lucknow, India" + }, + { + "author_name": "Sachin Kumar", + "author_inst": "Birbal Sahni Institute of Palaeosciences, Lucknow, India" + }, + { + "author_name": "Satya Prakash", + "author_inst": "Birbal Sahni Institute of Palaeosciences, Lucknow, India" + }, + { + "author_name": "Astha Mishra", + "author_inst": "Birbal Sahni Institute of Palaeosciences, Lucknow, India and Amity University, Noida, Uttar Pradesh, India" + }, + { + "author_name": "Pavan Kumar Dubey", + "author_inst": "Prosthodontics Unit, Faculty of Dental Sciences, Institute of Medical Sciences, Varanasi, India" + }, + { + "author_name": "Ajit Parihar", + "author_inst": "Orthodontics Unit, Faculty of Dental Sciences, Institute of Medical Sciences, Varanasi, India" + }, + { + "author_name": "Priyoneel Basu", + "author_inst": "Multidisciplinary Research Unit, Institute of Medical Science, Banaras Hindu University, India" + }, + { + "author_name": "Jaison J Sequeira", + "author_inst": "Department of Applied Zoology, Mangalore University, Mangalagangothri-574199, mangalore, Karnataka, India" + }, + { + "author_name": "Lavanya KC", + "author_inst": "Department of Applied Zoology, Mangalore University, Mangalagangothri-574199, mangalore, Karnataka, India" + }, + { + "author_name": "Vijayalaxmi Vijayalaxmi", + "author_inst": "Department of Applied Zoology, Mangalore University, Mangalagangothri-574199, mangalore, Karnataka, India" + }, + { + "author_name": "Vishnu Shreekara Bhat.K", + "author_inst": "Department of Applied Zoology, Mangalore University, Mangalagangothri-574199, mangalore, Karnataka, India" + }, + { + "author_name": "Thadiyan Parambil Ijinu", + "author_inst": "Amity Institute for Herbal and Biotech Products Development, Ravi Nagar, Peroorkada,Thiruvananthapuram 695005, Kerala, India" + }, + { + "author_name": "Dau Dayal Aggarwal", + "author_inst": "Department of Biochemistry, University of Delhi, South Campus, New Delhi, India" + }, + { + "author_name": "Anand Prakash", + "author_inst": "Sardar Ballabhbhai Patel College, Bhabua Kaimur, Bihar, India" + }, + { + "author_name": "Kiran Yadav", + "author_inst": "Male Reproductive Physiology Laboratory, Department of Zoology, Banaras Hindu University, India" + }, + { + "author_name": "Anupam Yadav", + "author_inst": "Male Reproductive Physiology Laboratory, Department of Zoology, Banaras Hindu University, India" + }, + { + "author_name": "Vandana Upadhyay", + "author_inst": "Abhay Degree College, Varanasi, India" + }, + { + "author_name": "Gunjan Mukim", + "author_inst": "Department of Zoology, University of Calcutta, India" + }, + { + "author_name": "Ankan Bhandari", + "author_inst": "Department of Zoology, University of Calcutta, India" + }, + { + "author_name": "Ankita Ghosh", + "author_inst": "Department of Zoology, University of Calcutta, India" + }, + { + "author_name": "Akash Kumar", + "author_inst": "Dr. A.P.J. Abdul Kalam Institute of Forensic Science & Criminology, Bundelkhand University,Jhansi, India" + }, + { + "author_name": "Vijay Kumar Yadav", + "author_inst": "Dr. A.P.J. Abdul Kalam Institute of Forensic Science & Criminology, Bundelkhand University,Jhansi, India" + }, + { + "author_name": "Kriti Nigam", + "author_inst": "Dr. A.P.J. Abdul Kalam Institute of Forensic Science & Criminology, Bundelkhand University,Jhansi, India" + }, + { + "author_name": "Abhimanyu Harshey", + "author_inst": "Dr. A.P.J. Abdul Kalam Institute of Forensic Science & Criminology, Bundelkhand University,Jhansi, India" + }, + { + "author_name": "Tanurup Das", + "author_inst": "Dr. A.P.J. Abdul Kalam Institute of Forensic Science & Criminology, Bundelkhand University,Jhansi, India" + }, + { + "author_name": "Deepa Devadas", + "author_inst": "Department of Anatomy,Institute of Medical Science, Banaras Hindu University, India" + }, + { + "author_name": "Surendra Pratap Mishra", + "author_inst": "Department of Biochemistry,Institute of Medical Science, Banaras Hindu University, India" + }, + { + "author_name": "Ashish Kumar", + "author_inst": "Department of Anatomy,Institute of Medical Science, Banaras Hindu University, India" + }, + { + "author_name": "Abhay Kumar Yadav", + "author_inst": "Department of Anatomy,Institute of Medical Science, Banaras Hindu University, India" + }, + { + "author_name": "Nitish Kumar Singh", + "author_inst": "Department of Anatomy,Institute of Medical Science, Banaras Hindu University, India" + }, + { + "author_name": "Manpreet Kaur", + "author_inst": "Department of Anatomy,Institute of Medical Science, Banaras Hindu University, India" + }, + { + "author_name": "Sanjay Kumar", + "author_inst": "Multidisciplinary Research Unit, Institute of Medical Science, Banaras Hindu University, India" + }, + { + "author_name": "Nikhil Srivastava", + "author_inst": "Cytogenetics Laboratory Department of Zoology , Banaras Hindu University,India" + }, + { + "author_name": "Charu Sharma", + "author_inst": "Cytogenetics Laboratory Department of Zoology , Banaras Hindu University,India" + }, + { + "author_name": "Ritabrata Chowdhury", + "author_inst": "Cytogenetics Laboratory Department of Zoology , Banaras Hindu University,India" + }, + { + "author_name": "Dharmendra Jain", + "author_inst": "Department of Cardiology,Institute of Medical Science, Banaras Hindu University, India" + }, + { + "author_name": "Abhai Kumar", + "author_inst": "Department of Neurology, Institute of Medical Science, Banaras Hindu University, India" + }, + { + "author_name": "Ritesh Shukla", + "author_inst": "School of Arts and Sciences, Ahmedabad University, India" + }, + { + "author_name": "Raghav Kumar Mishra", + "author_inst": "Male Reproductive Physiology Laboratory, Department of Zoology, Banaras Hindu University, India" + }, + { + "author_name": "Royana Singh", + "author_inst": "Department of Anatomy,Institute of Medical Science, Banaras Hindu University, India and Multidisciplinary Research Unit, Institute of Medical Science, Banaras H" + }, + { + "author_name": "Yamini B Tripathi", + "author_inst": "Department of Medicinal Chemistry, Institute of Medical Science, Banaras Hindu University, India" + }, + { + "author_name": "Vijay Nath Mishra", + "author_inst": "Department of Neurology, Institute of Medical Science, Banaras Hindu University, India" + }, + { + "author_name": "Mohammed S. Mustak", + "author_inst": "Department of Applied Zoology, Mangalore University, Mangalagangothri-574199, mangalore, Karnataka, India" + }, + { + "author_name": "Niraj Rai", + "author_inst": "Birbal Sahni Institute of Palaeosciences, Lucknow, India" + }, + { + "author_name": "Sumit Kumar Rawat", + "author_inst": "Department of Microbiology, Bundelkhand Medical College, Sagar, India" + }, + { + "author_name": "Prashant Survajhala", + "author_inst": "Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research Statue Circle, Jaipur, Rajasthan, India" + }, + { + "author_name": "Keshav K singh", + "author_inst": "Department of Genetics, School of Medicine, University of Alabama at Birmingham, Kaul Genetics Building, Birmingham,Alabama" + }, + { + "author_name": "Chandana Basu Mallick", + "author_inst": "Centre for Genetic Disorders, Banaras Hindu University, India" + }, + { + "author_name": "Pankaj Shrivastava", + "author_inst": "DNA Fingerprinting Unit, State Forensic Science Laboratory, Department of Home (Police), Government of MP, Sagar, India" + }, + { + "author_name": "Gyaneshwer Chaubey", + "author_inst": "Cytogenetics Laboratory Department of Zoology , Banaras Hindu University, India" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.02.06.21251099", @@ -916387,95 +915787,87 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.02.04.21251143", - "rel_title": "Symptom Prediction and Mortality Risk Calculation for COVID-19 Using Machine Learning", + "rel_doi": "10.1101/2021.02.04.21251012", + "rel_title": "Prioritizing allocation of COVID-19 vaccines based on social contacts increases vaccination effectiveness", "rel_date": "2021-02-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.04.21251143", - "rel_abs": "BackgroundEarly prediction of symptoms and mortality risks for COVID-19 patients would improve healthcare outcomes, allow for the appropriate distribution of healthcare resources, reduce healthcare costs, aid in vaccine prioritization and self-isolation strategies, and thus reduce the prevalence of the disease. Such publicly accessible prediction models are lacking, however.\n\nMethodsBased on a comprehensive evaluation of existing machine learning (ML) methods, we created two models based solely on the age, gender, and medical histories of 23,749 hospital-confirmed COVID-19 patients from February to September 2020: a symptom prediction model (SPM) and a mortality prediction model (MPM). The SPM predicts 12 symptom groups for each patient: respiratory distress, consciousness disorders, chest pain, paresis or paralysis, cough, fever or chill, gastrointestinal symptoms, sore throat, headache, vertigo, loss of smell or taste, and muscular pain or fatigue. The MPM predicts the death of COVID-19-positive individuals.\n\nResultsThe SPM yielded ROC-AUCs of 0.53-0.78 for symptoms. The most accurate prediction was for consciousness disorders at a sensitivity of 74% and a specificity of 70%. 2440 deaths were observed in the study population. MPM had a ROC-AUC of 0.79 and could predict mortality with a sensitivity of 75% and a specificity of 70%. About 90% of deaths occurred in the top 21 percentile of risk groups. To allow patients and clinicians to use these models easily, we created a freely accessible online interface at www.aicovid.org.\n\nConclusionsThe ML models predict COVID-19-related symptoms and mortality using information that is readily available to patients as well as clinicians. Thus, both can rapidly estimate the severity of the disease, allowing shared and better healthcare decisions with regard to hospitalization, self-isolation strategy, and COVID-19 vaccine prioritization in the coming months.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=124 SRC=\"FIGDIR/small/21251143v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (45K):\norg.highwire.dtl.DTLVardef@1766f83org.highwire.dtl.DTLVardef@931198org.highwire.dtl.DTLVardef@1681ec2org.highwire.dtl.DTLVardef@bb837d_HPS_FORMAT_FIGEXP M_FIG C_FIG", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.04.21251012", + "rel_abs": "We study allocation of COVID-19 vaccines to individuals based on the structural properties of their underlying social contact network. Even optimistic estimates suggest that most countries will likely take 6 to 24 months to vaccinate their citizens. These time estimates and the emergence of new viral strains urge us to find quick and effective ways to allocate the vaccines and contain the pandemic. While current approaches use combinations of age-based and occupation-based prioritizations, our strategy marks a departure from such largely aggregate vaccine allocation strategies. We propose a novel agent-based modeling approach motivated by recent advances in (i) science of real-world networks that point to efficacy of certain vaccination strategies and (ii) digital technologies that improve our ability to estimate some of these structural properties. Using a realistic representation of a social contact network for the Commonwealth of Virginia, combined with accurate surveillance data on spatio-temporal cases and currently accepted models of within- and between-host disease dynamics, we study how a limited number of vaccine doses can be strategically distributed to individuals to reduce the overall burden of the pandemic. We show that allocation of vaccines based on individuals degree (number of social contacts) and total social proximity time is significantly more effective than the currently used age-based allocation strategy in terms of number of infections, hospitalizations and deaths. Our results suggest that in just two months, by March 31, 2021, compared to age-based allocation, the proposed degree-based strategy can result in reducing an additional 56-110k infections, 3.2-5.4k hospitalizations, and 700-900 deaths just in the Commonwealth of Virginia. Extrapolating these results for the entire US, this strategy can lead to 3-6 million fewer infections, 181-306k fewer hospitalizations, and 51-62k fewer deaths compared to age-based allocation. The overall strategy is robust even: (i) if the social contacts are not estimated correctly; (ii) if the vaccine efficacy is lower than expected or only a single dose is given; (iii) if there is a delay in vaccine production and deployment; and (iv) whether or not non-pharmaceutical interventions continue as vaccines are deployed. For reasons of implementability, we have used degree, which is a simple structural measure and can be easily estimated using several methods, including the digital technology available today. These results are significant, especially for resource-poor countries, where vaccines are less available, have lower efficacy, and are more slowly distributed.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Elham Jamshidi", - "author_inst": "Division of Pulmonary Medicine, Department of Medicine, Lausanne University Hospital (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland" - }, - { - "author_name": "Amirhossein Asgary", - "author_inst": "Department of Biotechnology, College of Sciences, University of Tehran, Tehran, Iran." - }, - { - "author_name": "Nader Tavakoli", - "author_inst": "Trauma and Injury Research Center, Iran University of Medical Sciences, Tehran, Iran." + "author_name": "Jiangzhuo Chen", + "author_inst": "University of Virginia" }, { - "author_name": "Alireza Zali", - "author_inst": "Functional Neurosurgery Research Center, Shohada Tajrish Comprehensive Neurosurgical Center of Excellence, Shahid Beheshti University of Medical Sciences, Tehra" + "author_name": "Stefan Hoops", + "author_inst": "University of Virginia" }, { - "author_name": "Farzaneh Dastan", - "author_inst": "Department of Clinical Pharmacy, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran." + "author_name": "Achla Marathe", + "author_inst": "University of Virginia" }, { - "author_name": "Amir Daaee", - "author_inst": "School of Mechanical Engineering, Sharif University of Technology, Tehran, Iran." + "author_name": "Henning Mortveit", + "author_inst": "University of Virginia" }, { - "author_name": "Mohammadtaghi Badakhshan", - "author_inst": "School of Electrical and Computer Engineering, Engineering Faculty, University of Tehran, Tehran, Iran." + "author_name": "Bryan Lewis", + "author_inst": "University of Virginia" }, { - "author_name": "Hadi Esmaily", - "author_inst": "Department of Clinical Pharmacy, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran." + "author_name": "Srinivasan Venkatramanan", + "author_inst": "University of Virginia" }, { - "author_name": "Seyed Hamid Jamaldini", - "author_inst": "Department of Genetic, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran." + "author_name": "Arash Haddadan", + "author_inst": "University of Virginia" }, { - "author_name": "Saeid Safari", - "author_inst": "Functional Neurosurgery Research Center, Shohada Tajrish Comprehensive Neurosurgical Center of Excellence, Shahid Beheshti University of Medical Sciences, Tehra" + "author_name": "Parantapa Bhattacharya", + "author_inst": "University of Virginia" }, { - "author_name": "Ehsan Bastanhagh", - "author_inst": "Department of Anesthesiology, Tehran University of Medical Sciences, Tehran, Iran" + "author_name": "Abhijin Adiga", + "author_inst": "University of Virginia" }, { - "author_name": "Ali Maher", - "author_inst": "School of Management and Medical Education, Shahid Beheshti University of Medical Sciences, Tehran, Iran." + "author_name": "Anil Vullikanti", + "author_inst": "University of Virginia" }, { - "author_name": "Amirhesam Babajani", - "author_inst": "Department of Pharmacology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran" + "author_name": "Aravind Srinivasan", + "author_inst": "University of Maryland" }, { - "author_name": "Maryam Mehrazi", - "author_inst": "Trauma and Injury Research Center, Iran University of Medical Sciences, Tehran, Iran." + "author_name": "Mandy Wilson", + "author_inst": "University of Virginia" }, { - "author_name": "Mohammad Ali Sendani Kashi", - "author_inst": "Department of Business Management, Faculty of Management, University of Tehran, Tehran, Iran" + "author_name": "Gal Ehrlich", + "author_inst": "Ehrlich Group" }, { - "author_name": "Masoud Jamshidi", - "author_inst": "Department of Exercise Physiology, Tehran University, Tehran, Iran" + "author_name": "Maier Fenster", + "author_inst": "Ehrlich Group" }, { - "author_name": "Mohammad Hassan Sendani", - "author_inst": "Department of Computer Engineering, Sharif University of Technology, Tehran, Iran" + "author_name": "Stephen Eubank", + "author_inst": "University of Virginia" }, { - "author_name": "Sahand Jamal Rahi", - "author_inst": "Laboratory of the Physics of Biological Systems, Institute of Physics, Ecole polytechnique federale de Lausanne (EPFL), Lausanne, Switzerland" + "author_name": "Christopher Barrett", + "author_inst": "University of Virginia" }, { - "author_name": "Nahal Mansouri", - "author_inst": "Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, Ecole polytechnique federale de Lausanne (EPFL), Lausanne, Switzerland" + "author_name": "Madhav Marathe", + "author_inst": "University of Virginia" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.02.04.21251111", @@ -918289,25 +917681,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.03.21251088", - "rel_title": "A Comparison of Methylprednisolone and Dexamethasone in Intensive Care Patients with COVID-19", + "rel_doi": "10.1101/2021.02.02.21251023", + "rel_title": "A Dynamic Bayesian Model for Identifying High-Mortality Risk in Hospitalized COVID-19 Patients", "rel_date": "2021-02-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.03.21251088", - "rel_abs": "OBJECTIVESThis study retrospectively compares the effectiveness of methylprednisolone to dexamethasone in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or COVID-19) requiring ICU care.\n\nDESIGNThis is an institutional review board approved cohort study in patients with COVID-19 requiring intensive care unit admission. Patients admitted and requiring oxygen supplementation were treated with either methylprednisolone or dexamethasone.\n\nSETTINGThis study takes place in the intensive care units at a large, tertiary, public teaching hospital serving a primarily low-income community in urban Los Angeles.\n\nPATIENTSAll eligible patients admitted to the intensive care unit for COVID-19 respiratory failure from March 1 to July 31, 2020 were included in this study.\n\nINTERVENTIONSA total of 262 patients were grouped as receiving usual care (n=75), methylprednisolone dosed at least at 1mg/kg/day for [≥] 3 days (n=104), or dexamethasone dosed at least at 6 mg for [≥] 7 days (n=83).\n\nMEASUREMENTS and MAIN RESULTSAll-cause mortality within 50 days of initial corticosteroid treatment as compared to usual care was calculated. The mortality effect was then stratified based on levels of respiratory support received by the patient.\n\nIn this cohort of 262 patients with severe COVID-19, all-cause mortalities in the usual care, methylprednisolone, and dexamethasone groups were 41.3%, 16.4% and 26.5% at 50 days (p <0.01) respectively. In patients requiring mechanical ventilation, mortality was 42% lower in the methylprednisolone group than in the dexamethasone group (hazard ratio 0.48, 95% CI: 0.235-0.956, p=0.0385).\n\nCONCLUSIONSIn COVID-19 patients requiring mechanical ventilation, sufficiently dosed methylprednisolone can lead to a further decreased mortality as compared to dexamethasone.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.02.21251023", + "rel_abs": "IntroductionAs COVID-19 hospitalization rates remain high, there is an urgent need to identify prognostic factors to improve treatment. Our analysis, to our knowledge, is one of the first to quantify the risk associated with dynamic clinical measurements taken throughout the course of hospitalization.\n\nMethodsWe collected data for 553 PCR-positive COVID-19 patients admitted to hospital whose eventual outcomes were known. The data collected for the patients included demographics, comorbidities and laboratory values taken at admission and throughout the course of hospitalization. We trained multivariate Markov prognostic models to identify high-risk patients at admission along with a dynamic measure of risk incorporating time-dependent changes in patients laboratory values.\n\nResultsFrom the set of factors available upon admission, the Markov model determined that age >80 years, history of coronary artery disease and chronic obstructive pulmonary disease increased mortality risk. The lab values upon admission most associated with mortality included neutrophil percentage, RBC, RDW, protein levels, platelets count, albumin levels and MCHC. Incorporating dynamic changes in lab values throughout hospitalization lead to dramatic gains in the predictive accuracy of the model and indicated a catalogue of variables for determining high-risk patients including eosinophil percentage, WBC, platelets, pCO2, RDW, LUC count, alkaline phosphatase and albumin.\n\nConclusionOur prognostic model highlights the nuance of determining risk for COVID-19 patients and indicates that, rather than a single variable, a range of factors (at different points in hospitalization) are needed for effective risk stratification.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Renli Qiao", - "author_inst": "University of Southern California" + "author_name": "Amir Momeni-Boroujeni", + "author_inst": "Department of Pathology, Brigham and Women's Hospital" }, { - "author_name": "Justine Ko", - "author_inst": "USC" + "author_name": "Rachelle Mendoza", + "author_inst": "Department of Pathology, SUNY Downstate Medical Center" }, { - "author_name": "Wei Yang", - "author_inst": "University of Nevada at Reno" + "author_name": "Isaac J. Stopard", + "author_inst": "MRC Centre for Global Infectious Disease Analysis, School of Public Health, Faculty of Medicine, Imperial College of London, London, UK" + }, + { + "author_name": "Ben Lambert", + "author_inst": "MRC Centre for Global Infectious Disease Analysis, School of Public Health, Faculty of Medicine, Imperial College of London, London, UK" + }, + { + "author_name": "Alejandro Zuretti", + "author_inst": "Department of Pathology, SUNY Downstate Medical Center" } ], "version": "1", @@ -921115,43 +920515,67 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.02.04.429765", - "rel_title": "Large-scale analysis of SARS-CoV-2 spike-glycoprotein mutants demonstrates the need for continuous screening of virus isolates", + "rel_doi": "10.1101/2021.02.03.429627", + "rel_title": "Site-specific O-glycosylation analysis of SARS-CoV-2 spike protein produced in insect and human cells", "rel_date": "2021-02-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.04.429765", - "rel_abs": "Due to the widespread of the COVID-19 pandemic, the SARS-CoV-2 genome is evolving in diverse human populations. Several studies already reported different strains and an increase in the mutation rate. Particularly, mutations in SARS-CoV-2 spike-glycoprotein are of great interest as it mediates infection in human and recently approved mRNA vaccines are designed to induce immune responses against it.\n\nWe analyzed 146,917 SARS-CoV-2 genome assemblies and 2,393 NGS datasets from GISAID, NCBI Virus and NCBI SRA archives focusing on non-synonymous mutations in the spike protein.\n\nOnly around 13.8% of the samples contained the wild-type spike protein with no variation from the reference. Among the spike protein mutants, we confirmed a low mutation rate exhibiting less than 10 non-synonymous mutations in 99.98% of the analyzed sequences, but the mean and median number of spike protein mutations per sample increased over time. 2,592 distinct variants were found in total. The majority of the observed variants were recurrent, but only nine and 23 recurrent variants were found in at least 0.5% of the mutant genome assemblies and NGS samples, respectively. Further, we found high-confidence subclonal variants in about 15.1% of the NGS data sets with mutant spike protein, which might indicate co-infection with various SARS-CoV-2 strains and/or intra-host evolution. Lastly, some variants might have an effect on antibody binding or T-cell recognition.\n\nThese findings demonstrate the increasing importance of monitoring SARS-CoV-2 sequences for an early detection of variants that require adaptations in preventive and therapeutic strategies.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.03.429627", + "rel_abs": "Enveloped viruses hijack not only the host translation processes, but also its glycosylation machinery, and to a variable extent cover viral surface proteins with tolerogenic host-like structures. SARS-CoV-2 surface protein S presents as a trimer on the viral surface and is covered by a dense shield of N-linked glycans, and a few O-glycosites have been reported. The location of O-glycans is controlled by a large family of initiating enzymes with variable expression in cells and tissues and hence difficult to predict. Here, we used our well-established O-glycoproteomic workflows to map the precise positions of O-linked glycosylation sites on three different entities of protein S - insect cell or human cell-produced ectodomains, or insect cell derived receptor binding domain (RBD). In total 25 O-glycosites were identified, with similar patterns in the two ectodomains of different cell origin, and a distinct pattern of the monomeric RBD. Strikingly, 16 out of 25 O-glycosites were located within three amino acids from known N-glycosites. However, O-glycosylation was primarily found on peptides that were unoccupied by N-glycans, and otherwise had low overall occupancy. This suggests possible complementary functions of O-glycans in immune shielding and negligible effects of O-glycosylation on subunit vaccine design for SARS-CoV-2.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Barbara Schroers", - "author_inst": "TRON gGmbH" + "author_name": "Ieva Bagdonaite", + "author_inst": "University of Copenhagen" }, { - "author_name": "Ranganath Gudimella", - "author_inst": "TRON gGmbH" + "author_name": "Andrew J. Thompson", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Thomas Bukur", - "author_inst": "TRON gGmbH" + "author_name": "Xiaoning Wang", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Thomas Roesler", - "author_inst": "TRON gGmbH" + "author_name": "Max Soegaard", + "author_inst": "ExpreS2ion Biotechnologies" }, { - "author_name": "Martin Loewer", - "author_inst": "TRON gGmbH" + "author_name": "Cyrielle Fougeroux", + "author_inst": "University of Copenhagen; AdaptVac Aps" }, { - "author_name": "Ugur Sahin", - "author_inst": "BioNTech SE" + "author_name": "Martin Frank", + "author_inst": "Biognos AB" + }, + { + "author_name": "Jolene K. Diedrich", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "John R. Yates III", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Ali Salanti", + "author_inst": "University of Copenhagen" + }, + { + "author_name": "Sergey Y. Vakhrushev", + "author_inst": "University of Copenhagen" + }, + { + "author_name": "James C. Paulson", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Hans H. Wandall", + "author_inst": "University of Copenhagen" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "genomics" + "category": "molecular biology" }, { "rel_doi": "10.1101/2021.02.03.429646", @@ -922949,89 +922373,33 @@ "category": "gastroenterology" }, { - "rel_doi": "10.1101/2021.02.01.21250950", - "rel_title": "SARS-CoV-2 transmission from the healthcare setting into the home: a prospective longitudinal cohort study", + "rel_doi": "10.1101/2021.02.01.21250936", + "rel_title": "Inference on the dynamics of the COVID pandemic from observational data", "rel_date": "2021-02-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.01.21250950", - "rel_abs": "ObjectiveTo assess the incidence of symptomatic and asymptomatic SARS-CoV-2 seropositivity in healthcare workers and subsequent transmission to their close contacts within their household. To assess changes in immunoglobulin (Ig) and neutralising antibodies (nAbs) in exposed participants.\n\nSettingTwo acute National Health Service (NHS) hospitals within the East Midlands region of England.\n\nBackgroundThe UK has been one of the most severely affected countries during the COVID-19 pandemic. Transmission from healthcare workers to the wider community is a potential major vector for spread of SARS-CoV-2 which is not well described in the current literature.\n\nMethodsHealthcare workers (HCW) were recruited from two Hospitals within the East Midlands of England and underwent serial blood sampling for anti-SARS-CoV-2 antibodies (both nucleocapsid and spike protein for IgG, IgM and IgA) between 20 April and 30 July 2020, with the presence of neutralising antibodies (nAbs) assessed for positive participants. Cohabitees of the volunteers were invited to attend testing in July -August 2020 and underwent identical serological testing as the HCWs.\n\nResults633 healthcare professionals were recruited. 178 household contacts of 137 professionals volunteered for the study. 18% of healthcare professionals (115 out of 633) tested as seropositive during the study period, compared to an estimated seroprevalence of 7% within the general population. The rate of symptomatic COVID-19 was 27.5% compared to an asymptomatic rate of 15.1%. Rates of positivity declined across the study period for all immunoglobulins (overall positivity from 16.7% to 6.9%).\n\n7.2% of the cohabitees tested as seropositive. 58 cohabitees lived with a serologically positive HCW; this group had a seropositive rate of 15.5%, compared to 2.5% of cohabitees without a seropositive HCW, a six-fold increase in risk (Odds ratio 7.16 95% CI 1.86 to 27.59), p = 0.0025). Given the observed decay rates and data from Public Health England, we estimate that the proportion of seropositive cohabitees living with a seropositive HCW at the height of the first wave could have been as high as 44%.\n\n110 out of 115 (95.7%) HCWs and 12 out of 13 (92.3%) cohabitees who tested positive developed detectable nAbs. 56.5% (65 out of 115) of SARS-CoV-2 positive HCWs developed a neutralising titre with an IC50[≥]1/300; no cohabitee achieved this level..\n\nConclusionsTransmission of SARS-CoV-2 between healthcare professionals and their home contacts appears to be a significant factor of viral transmission, but, even accounting for the decline in seropositivity over time, less than 44% of adult cohabitees of seropositive healthcare workers became seropositive. Routine screening and priority vaccination of both healthcare professionals and their close contacts should be implemented to reduce viral transmission from hospitals to the community.\n\nSUMMARY BOXESO_ST_ABSSection 1: What is already known on this topicC_ST_ABSO_LIHealthcare workers (HCWs) have increased rates of SARS-CoV-2 infection compared with the general population due, at least in part, to high levels of occupational exposure.\nC_LIO_LIIgA, IgM and IgG are detectable for most patients after 11 days post SARS-CoV-2 infection but all decline in the weeks following SAR-CoV-2 exposure.\nC_LIO_LIRates of transmission to healthcare workers, and therefore subsequent transmission to their close contacts, may be reduced with effective PPE.\nC_LI\n\nSection 2: What this study addsO_LIThe amount of neutralising antibodies formed may be dependent on IgG response as it is much lower among seropositive cohabitees than seropositive healthcare workers.\nC_LIO_LINHS Healthcare workers had a far greater seroprevalence of SARS-CoV-2 infection compared to the general population.\nC_LIO_LICohabitees of positive healthcare workers have a 6-fold increased risk of developing serological evidence of SARS-CoV-2 infection compared to the general population.\nC_LIO_LIDespite this increased risk, transmission at home is less than 50% even from highly exposed healthcare workers, but remains an important potential vector of transmission from hospitals to the wider community.\nC_LI\n\nResearch into contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for articles published between January 1 2020 and January 27, 2021 with the terms \"Covid-19\", \"healthcare workers\", and \"transmission\" \"home {NOT nursing} or household\". We did not restrict our search by language or type of publication. We identified 38 studies of which only one assessed the prevalence among HCW households using Canadian national databases. Our PubMed search yielded only one serological study within the German Healthcare system, which suggested very low transmission from healthcare workers to their close cohabitees.\n\nAdded value of this studyTo our knowledge, this is the largest longitudinal serological cohort study assessing transmission of SARS-CoV-2 infection from the UK healthcare environment to the home (n = 633 healthcare workers, 178 cohabitees). Our findings showed that serological evidence within the HCW was high with 18% of healthcare professionals (115 out of 633) tested as seropositive during the study period, compared to an estimated seroprevalence of 7% within the general population. A cohabitee of a seropositive HCW had a six-fold increase of being seropositive themselves compared to a baseline rate of 2.5%. Despite this increased risk, transmission at home is less than 50% even from highly exposed healthcare workers, but remains an important potential vector of transmission from hospitals to the wider community. Rates of positivity declined across the study period for all immunoglobulins (overall positivity from 16.7% to 6.9%). Given the observed decay rates and data from Public Health England, we estimate that the proportion of seropositive cohabitees living with a seropositive HCW at the height of the first wave could have been as high as 44%.\n\nImplications of all available evidenceUnderstanding the transmission during the first wave from the healthcare setting into the home and the extent of such transmissions is essential to understand containment strategies of novel SARS-CoV-2 variants or to understand viral transmission of future respiratory viruses. NHS workers appeared to be at an increased risk of contracting of SARS-CoV-2 infection compared to the HCWs of other nations; we hypothesise that this may be related to a scarcity of appropriate personal protective equipment during the initial wave of SARS-CoV-2. Healthcare workers (HCWs) have increased rates of SARS-CoV-2 infection compared with the general population. An infected HCW, whether symptomatic or not, appears to be a significant bridge for transmission of SARS-CoV-2 to their close home contacts.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.01.21250936", + "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWWe describe a time dependent stochastic dynamic model in discrete time for the evolution of the COVID-19 pandemic in various states of USA. The proposed multi-compartment model is expressed through a system of difference equations that describe their temporal dynamics. Various compartments in our model is connected to the social distancing measures and diagnostic testing rates. A nonparametric estimation strategy is employed for obtaining estimates of interpretable temporally static and dynamic epidemiological rate parameters. The confidence bands of the parameters are obtained using a residual bootstrap procedure. A key feature of the methodology is its ability to estimate latent compartments such as the trajectory of the number of asymptomatic but infected individuals which are the key vectors of COVID-19 spread. The nature of the disease dynamics is further quantified by the proposed epidemiological markers, which use estimates of such key latent compartments.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Simon Craxford", - "author_inst": "Nottingham University Hospitals NHS Trust" - }, - { - "author_name": "Jessica Nightingale", - "author_inst": "1.\tDivision of Rheumatology, Orthopaedics and Dermatology, School of Medicine, The University of Nottingham, Nottingham, NG7 2UH, UK" - }, - { - "author_name": "Adeel Ikram", - "author_inst": "1.\tDivision of Rheumatology, Orthopaedics and Dermatology, School of Medicine, The University of Nottingham, Nottingham, NG7 2UH, UK" - }, - { - "author_name": "Ben Arthur Marson", - "author_inst": "1.\tDivision of Rheumatology, Orthopaedics and Dermatology, School of Medicine, The University of Nottingham, Nottingham, NG7 2UH, UK" - }, - { - "author_name": "Anthony Kelly", - "author_inst": "Division of Rheumatology, Orthopaedics and Dermatology, School of Medicine, The University of Nottingham, Nottingham, NG7 2UH, UK" - }, - { - "author_name": "Alan Norrish", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Amrita Vijay", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Stuart Astbury", - "author_inst": "2.\tNIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham, UK" - }, - { - "author_name": "Lola Cusin", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Waheed Ashraf", - "author_inst": "1.Division of Rheumatology, Orthopaedics and Dermatology, School of Medicine, The University of Nottingham, Nottingham, NG7 2UH, UK" - }, - { - "author_name": "Jayne Newham", - "author_inst": "1.\tDivision of Rheumatology, Orthopaedics and Dermatology, School of Medicine, The University of Nottingham, Nottingham, NG7 2UH, UK" - }, - { - "author_name": "Guruprasad Aithal", - "author_inst": "NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham, UK" - }, - { - "author_name": "Patrick Tighe", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Jonathan Ball", - "author_inst": "NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham, UK" - }, - { - "author_name": "Alexander W Tarr", - "author_inst": "University of Nottingham" + "author_name": "Satarupa Bhattacharjee", + "author_inst": "Department of Statistics, University of California, Davis" }, { - "author_name": "Richard A Urbanowicz", - "author_inst": "2.\tNIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham, UK" + "author_name": "Shuting Liao", + "author_inst": "Graduate Group in BioStatistics, University of California, Davis" }, { - "author_name": "Ana Valdes", - "author_inst": "1.\tDivision of Rheumatology, Orthopaedics and Dermatology, School of Medicine, The University of Nottingham, Nottingham, NG7 2UH, UK" + "author_name": "Debashis Paul", + "author_inst": "Department of Statistics, University of California, Davis" }, { - "author_name": "Benjamin Ollivere", - "author_inst": "1.\tDivision of Rheumatology, Orthopaedics and Dermatology, School of Medicine, The University of Nottingham, Nottingham, NG7 2UH, UK" + "author_name": "Sanjay Chaudhuri", + "author_inst": "Deapartment of Statistics and Applied Probability, National University of Singapore" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -924923,37 +924291,89 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.02.02.429469", - "rel_title": "Identification of the SHREK family of proteins as broad-spectrum host antiviral factors", + "rel_doi": "10.1101/2021.02.03.429211", + "rel_title": "Full Brain and Lung Prophylaxis against SARS-CoV-2 by Intranasal Lentiviral Vaccination in a New hACE2 Transgenic Mouse Model or Golden Hamsters", "rel_date": "2021-02-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.02.429469", - "rel_abs": "Mucins and mucin-like molecules are highly glycosylated, high-molecular-weight cell surface proteins that possess a semi-rigid and highly extended extracellular domain. P-selectin glycoprotein ligand-1 (PSGL-1), a mucin-like glycoprotein, has recently been found to restrict HIV-1 infectivity through virion incorporation that sterically hinders virus particle attachment to target cells. Here, we report the identification of a family of antiviral cellular proteins, named the Surface-Hinged, Rigidly-Extended Killer (SHREK) family of virion inactivators (PSGL-1, CD43, TIM-1, CD34, PODXL1, PODXL2, CD164, MUC1, MUC4, and TMEM123), that share similar structural characteristics with PSGL-1. We demonstrate that SHREK proteins block HIV-1 infectivity by inhibiting virus particle attachment to target cells. In addition, we demonstrate that SHREK proteins are broad-spectrum host antiviral factors that block the infection of diverse viruses such as influenza A. Furthermore, we demonstrate that a subset of SHREKs also blocks the infectivity of a hybrid alphavirus-SARS-CoV-2 virus-like particle. These results suggest that SHREK proteins may be a part of host innate immunity against enveloped viruses.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.03.429211", + "rel_abs": "Non-integrative, non-cytopathic and non-inflammatory lentiviral vectors are particularly suitable for mucosal vaccination and recently emerge as a promising strategy to elicit sterilizing prophylaxis against SARS-CoV-2 in preclinical animal models. Here, we demonstrate that a single intranasal administration of a lentiviral vector encoding a prefusion form of SARS-CoV-2 spike glycoprotein induces full protection of respiratory tracts and totally avoids pulmonary inflammation in the susceptible hamster model. More importantly, we generated a new transgenic mouse strain, expressing the human Angiotensin Converting Enzyme 2, with unprecedent brain permissibility to SARS-CoV-2 replication and developing a lethal disease in <4 days post infection. Even though the neurotropism of SARS-CoV-2 is now well established, so far other vaccine strategies under development have not taken into the account the protection of central nervous system. Using our highly stringent transgenic model, we demonstrated that an intranasal booster immunization with the developed lentiviral vaccine candidate achieves full protection of both respiratory tracts and brain against SARS-CoV-2.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Deemah Dabbagh", - "author_inst": "George Mason University" + "author_name": "Min-Wen Ku", + "author_inst": "Institut Pasteur-TheraVectys Joint Lab" }, { - "author_name": "Sijia He", - "author_inst": "George Mason University" + "author_name": "Pierre Authie", + "author_inst": "Institut Pasteur-TheraVectys Joint Lab" }, { - "author_name": "Brian Hetrick", - "author_inst": "George Mason University" + "author_name": "Maryline Bourgine", + "author_inst": "Institut Pasteur" }, { - "author_name": "Linda Chilin", - "author_inst": "George Mason University" + "author_name": "Francois Anna", + "author_inst": "Institut Pasteur-TheraVectys Joint Lab" }, { - "author_name": "Ali Andalibi", - "author_inst": "George Mason University" + "author_name": "Amandine Noirat", + "author_inst": "Institut Pasteur-TheraVectys Joint Lab" }, { - "author_name": "Yuntao Wu", - "author_inst": "George Mason University" + "author_name": "Fanny Moncoq", + "author_inst": "Institut Pasteur-TheraVectys Joint Lab" + }, + { + "author_name": "Benjamin Vesin", + "author_inst": "Institut Pasteur-TheraVectys Joint Lab" + }, + { + "author_name": "Fabien Nevo", + "author_inst": "Institut Pasteur-TheraVectys Joint Lab" + }, + { + "author_name": "Jodie Lopez", + "author_inst": "Institut Pasteur-TheraVectys Joint Lab" + }, + { + "author_name": "Philippe Souque", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Catherine Blanc", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Sebastien Chardenoux", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Ilta Lafosse", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "David Hardy", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Kirill Nemirov", + "author_inst": "Institut Pasteur-TheraVectys Joint Lab" + }, + { + "author_name": "Francoise Guinet", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Francina Langa Vives", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Laleh Majlessi", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Pierre Charneau", + "author_inst": "Institut Pasteur" } ], "version": "1", @@ -926833,43 +926253,35 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.01.31.428851", - "rel_title": "Discovery of re-purposed drugs that slow SARS-CoV-2 replication in human cells", + "rel_doi": "10.1101/2021.01.31.429007", + "rel_title": "Expression of human ACE2 N-terminal domain, part of the receptor for SARS-CoV-2, in fusion with maltose binding protein, E. coli ribonuclease I and human RNase A", "rel_date": "2021-02-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.31.428851", - "rel_abs": "COVID-19 vaccines based on the Spike protein of SARS-CoV-2 have been developed that appear to be largely successful in stopping infection. However, vaccine escape variants might arise leading to a re-emergence of COVID. In anticipation of such a scenario, the identification of repurposed drugs that stop SARS-CoV-2 replication could have enormous utility in stemming the disease. Here, using a nano-luciferase tagged version of the virus (SARS-CoV-2- DOrf7a-NLuc) to quantitate viral load, we evaluated a range of human cell types for their ability to be infected and support replication of the virus, and performed a screen of 1971 FDA-approved drugs. Hepatocytes, kidney glomerulus, and proximal tubule cells were particularly effective in supporting SARS-CoV-2 replication, which is in- line with reported proteinuria and liver damage in patients with COVID-19. We identified 35 drugs that reduced viral replication in Vero and human hepatocytes when treated prior to SARS-CoV-2 infection and found amodiaquine, atovaquone, bedaquiline, ebastine, LY2835219, manidipine, panobinostat, and vitamin D3 to be effective in slowing SARS-CoV-2 replication in human cells when used to treat infected cells. In conclusion, our study has identified strong candidates for drug repurposing, which could prove powerful additions to the treatment of COVID.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.31.429007", + "rel_abs": "The SARS-CoV-2 viral genome contains a positive-strand single-stranded RNA of ~30 kb. Human ACE2 protein is the receptor for SARS-CoV-2 virus attachment and initiation of infection. We propose to use ribonucleases (RNases) as antiviral agents to destroy the viral genome in vitro. In the virions the RNA is protected by viral capsid proteins, membrane proteins and nucleocapsid proteins. To overcome this protection we set out to construct RNase fusion with human ACE2 receptor N-terminal domain (ACE2NTD). We constructed six proteins expressed in E. coli cells: 1) MBP-ACE2NTD, 2) ACE2NTD-GFP, 3) RNase I (6xHis), 4) RNase III (6xHis), 5) RNase I-ACE2NTD (6xHis), and 6) human RNase A-ACE2NTD150 (6xHis). We evaluated fusion expression in different E. coli strains, partially purified MBP-ACE2NTD protein from the soluble fraction of bacterial cell lysate, and refolded MBP-ACE2NTD protein from inclusion body. The engineered RNase I-ACE2NTD (6xHis) and hRNase A-ACE2NTD (6xHis) fusions are active in cleaving COVID-19 RNA in vitro. The recombinant RNase I (6xHis) and RNase III (6xHis) are active in cleaving RNA and dsRNA in test tube. This study provides a proof-of-concept for construction of fusion protein between human cell receptor and nuclease that may be used to degrade viral nucleic acids in our environment.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC=\"FIGDIR/small/429007v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (25K):\norg.highwire.dtl.DTLVardef@1b966e0org.highwire.dtl.DTLVardef@1111393org.highwire.dtl.DTLVardef@1c4cc2org.highwire.dtl.DTLVardef@1f35dd7_HPS_FORMAT_FIGEXP M_FIG Cartoon illustration part of this work (Human ACE2 N-terminal domain tethered to RNase A and RNA degradation by the fusion enzyme).\n\nC_FIG", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Adam Pickard", - "author_inst": "University of Manchester" - }, - { - "author_name": "Ben C Calverley", - "author_inst": "University of Manchester" - }, - { - "author_name": "Joan Chang", - "author_inst": "University of Manchester" + "author_name": "Shuang-yong Xu", + "author_inst": "New England Biolabs, Inc." }, { - "author_name": "Richa Garva", - "author_inst": "University of Manchester" + "author_name": "Alexey Fomenkov", + "author_inst": "New England Biolabs, Inc." }, { - "author_name": "Yinhui Lu", - "author_inst": "University of Manchester" + "author_name": "Tien-Hao Chen", + "author_inst": "New England Biolabs, Inc." }, { - "author_name": "Karl E Kadler", - "author_inst": "University of Manchester" + "author_name": "Erbay Yigit", + "author_inst": "New England Biolabs, Inc." } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.01.31.429023", @@ -928415,165 +927827,77 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.28.21250486", - "rel_title": "PCR assay to enhance global surveillance for SARS-CoV-2 variants of concern", + "rel_doi": "10.1101/2021.01.28.21250365", + "rel_title": "Differences in detected viral loads guide use of SARS-CoV-2 antigen-detection assays towards symptomatic college students and children.", "rel_date": "2021-02-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.28.21250486", - "rel_abs": "With the emergence of SARS-CoV-2 variants that may increase transmissibility and/or cause escape from immune responses1-3, there is an urgent need for the targeted surveillance of circulating lineages. It was found that the B.1.1.7 (also 501Y.V1) variant first detected in the UK4,5 could be serendipitously detected by the ThermoFisher TaqPath COVID-19 PCR assay because a key deletion in these viruses, spike {Delta}69-70, would cause a \"spike gene target failure\" (SGTF) result. However, a SGTF result is not definitive for B.1.1.7, and this assay cannot detect other variants of concern that lack spike {Delta}69-70, such as B.1.351 (also 501Y.V2) detected in South Africa6 and P.1 (also 501Y.V3) recently detected in Brazil7. We identified a deletion in the ORF1a gene (ORF1a {Delta}3675-3677) in all three variants, which has not yet been widely detected in other SARS-CoV-2 lineages. Using ORF1a {Delta}3675-3677 as the primary target and spike {Delta}69-70 to differentiate, we designed and validated an open source PCR assay to detect SARS-CoV-2 variants of concern8. Our assay can be rapidly deployed in laboratories around the world to enhance surveillance for the local emergence spread of B.1.1.7, B.1.351, and P.1.", - "rel_num_authors": 38, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.28.21250365", + "rel_abs": "Limitations in timely testing for SARS-CoV-2 drive the need for new approaches in suspected COVID-19 disease. We queried whether viral load (VL) in the upper airways at presentation could improve the management and diagnosis of patients. This study was conducted in a 9 hospital system in Allegheny County, Pennsylvania between March 1-August 31 2020. Viral load was determined by PCR assays for patients presenting to the Emergency Departments (ED), community pediatrics practices and college health service. We found that for the ED patients, VL did not vary substantially between those admitted and not. VL was relatively equivalent across ages, except for the under 25 age groups that tended to present with higher loads. To determine if rapid antigen testing (RAT) could aid diagnosis in certain populations, we compared BD Veritor and Quidel Sofia to SOC PCR-based tests. The antigen assay provided a disease-detection sensitivity of >90% in a selection of 32 positive students and was modeled to have an 80% sensitivity in all positive students. In the outpatient pediatric population, the antigen assay detected 70% of PCR-positives. Extrapolating these findings to viral loads in older hospitalized patients, a minority would be detected by RAT (40%). Higher loads did correlate with death, though the prognostic value was marginal (ROC AUC of only 0.66). VL did not distinguish between those needing mechanical ventilation and routine inpatients. We conclude that VL in upper airways, while not prognostic for disease management, may aid in selecting proper testing methodologies for certain patient populations.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Chantal BF Vogels", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Mallery I Breban", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Tara Alpert", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Mary E Petrone", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Anne E Watkins", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Isabel M Ott", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Jaqueline Goes de Jesus", - "author_inst": "Universidade de Sao Paulo" - }, - { - "author_name": "Ingra Morales Claro", - "author_inst": "Universidade de Sao Paulo" - }, - { - "author_name": "Giulia Magalhaes Ferreira", - "author_inst": "Universidade de Sao Paulo" - }, - { - "author_name": "Myuki AE Crispim", - "author_inst": "Fundacao Hospitalar de Hematologia e Hemoterapia do Amazonas" - }, - { - "author_name": "- Brazil-UK CADDE Genomic Network", - "author_inst": "" - }, - { - "author_name": "Lavanya Singh", - "author_inst": "University of KwaZulu-Natal" - }, - { - "author_name": "Houriiyah Tegally", - "author_inst": "University of KwaZulu-Natal" - }, - { - "author_name": "Ugochukwu J Anyaneji", - "author_inst": "University of KwaZulu-Natal" - }, - { - "author_name": "- NGS-SA", - "author_inst": "" - }, - { - "author_name": "Emma Hodcroft", - "author_inst": "University of Bern" - }, - { - "author_name": "Christopher E Mason", - "author_inst": "Tempus Labs" - }, - { - "author_name": "Gaurav Khullar", - "author_inst": "Tempus Labs" - }, - { - "author_name": "Metti Jessica", - "author_inst": "Tempus Labs" - }, - { - "author_name": "Joel T Dudley", - "author_inst": "Tempus Labs" - }, - { - "author_name": "Matthew J Mackay", - "author_inst": "Tempus Labs" - }, - { - "author_name": "Megan Nash", - "author_inst": "Tempus Labs" - }, - { - "author_name": "Jianhui Wang", - "author_inst": "Yale University School of Medicine," + "author_name": "Juan Luis Gomez Marti", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Chen Liu", - "author_inst": "Yale University School of Medicine," + "author_name": "Jamie Gribschaw", + "author_inst": "UPMC" }, { - "author_name": "Pei Hui", - "author_inst": "Yale University School of Medicine," + "author_name": "Melissa McCullough", + "author_inst": "UPMC" }, { - "author_name": "Steven Murphy", - "author_inst": "Murphy Medical Associates" + "author_name": "Abbie Mallon", + "author_inst": "UPMC" }, { - "author_name": "Caleb Neal", - "author_inst": "Murphy Medical Associates" + "author_name": "Jamie Acero", + "author_inst": "UPMC" }, { - "author_name": "Eva Laszlo", - "author_inst": "Murphy Medical Associates" + "author_name": "Amy Kinzler", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Marie L Landry", - "author_inst": "Yale School of Medicine" + "author_name": "Jamie Godesky", + "author_inst": "UPMC" }, { - "author_name": "Anthony Muyombwe", - "author_inst": "Connecticut State Department of Public Health" + "author_name": "Kelly Heidenreich", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Randy Downing", - "author_inst": "Connecticut State Department of Public Health" + "author_name": "Jennifer Iagnemma", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Jafar Razeq", - "author_inst": "Connecticut State Department of Public Health" + "author_name": "Marian Vanek", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Tulio de Oliveira", - "author_inst": "University of KwaZulu-Natal" + "author_name": "A William Pasculle", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Nuno R Faria", - "author_inst": "Universidade de Sao Paulo" + "author_name": "Tung Phan", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Ester C. Sabino C Sabino", - "author_inst": "Universidade de Sao Paulo" + "author_name": "Alejandro Hoberman", + "author_inst": "University of Pittburgh" }, { - "author_name": "Richard A Neher", - "author_inst": "Swiss Institute of Bioinformatics" + "author_name": "John V Williams", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Joseph R Fauver", - "author_inst": "Yale School of Public Health" + "author_name": "Stephanie Mitchell", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Nathan D Grubaugh", - "author_inst": "Yale School of Public Health" + "author_name": "Alan Wells", + "author_inst": "University of Pittsburgh" } ], "version": "1", @@ -930257,37 +929581,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.01.29.21250788", - "rel_title": "COVID-19 Hospitalizations in Five California Hospitals", + "rel_doi": "10.1101/2021.01.30.21250828", + "rel_title": "Strategies for vaccination against SARS-CoV-2 to efficiently bring R<1", "rel_date": "2021-02-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.29.21250788", - "rel_abs": "STRUCTURED ABSTRACTO_ST_ABSImportanceC_ST_ABSCharacterization of a diverse cohort hospitalized with COVID-19 in a health care system in California is needed to further understand the impact of SARS-CoV-2 and improve patient outcomes.\n\nObjectivesTo investigate the characteristics of patients hospitalized with COVID-19 and assess factors associated with poor outcomes.\n\nDesignPatient-level retrospective cohort study\n\nSettingUniversity of California five academic hospitals.\n\nParticipantsPatients [≥]18 years old with a confirmed test result for SAR-CoV-2 virus hospitalized at five UC hospitals.\n\nExposureConfirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection by positive results on polymerase chain reaction testing of a nasopharyngeal sample among patients requiring hospital admission.\n\nMain Outcomes and MeasuresAdmission to the intensive care unit, death during hospitalization, and the composite of both outcomes.\n\nResultsOutcomes were assessed for 4,730 patients who were discharged or died during a hospitalization. A total of 846 patients were treated at UC Davis, 1,564 UC Irvine, 1,283 UC Los Angeles, 471 UC San Diego, and 566 UC San Francisco. More than 20% of patients were [≥]75 years of age (75-84: 12.3%, [≥]85: 10.5%), male (56.5%), Hispanic/Latino (45.7%), and Asian (10.3%). The most common comorbidities were hypertension (35.2%), cardiac disease (33.3%), and diabetes (24.0%). The ICU admission rate was 25.2% (1194/4730), with 7.0% (329/4730) in-hospital mortality. Among patients admitted to the ICU, 18.8% (225/1194) died; 2.9% (104/3536) died without ICU admission. The rate of the composite outcome (ICU admission and/or death) was 27.4% (1,298/4,730). While controlling for comorbidities, patients of age 75-84 (OR 1.47, 95% CI: 1.11-1.93) and 85-59 (OR 1.39, 95% CI: 1.04-1.87) were more likely to experience a composite outcome than 18-34 year-olds. Males (OR 1.39, 95% CI: 1.21-1.59), and patients identifying as Hispanic/Latino (OR 1.35, 95% CI: 1.14-1.61), and Asian (OR 1.43, 95% CI: 1.23-1.82), were also more likely to experience a composite outcome than White. Patients with 5 or more comorbidities were exceedingly likely to experience a composite outcome (OR 2.74, 95% CI: 2.32-3.25).\n\nConclusionsMales, older patients, those with pre-existing comorbidities, and those identifying as Hispanic/Latino or Asian experienced an increased risk of ICU admission and/or death.\n\nKEY POINTSO_ST_ABSQuestionC_ST_ABSWhat are the characteristics and outcomes of patients with SARS-CoV-2 infection hospitalized at five UC Health medical centers in California?\n\nFindingsIn this retrospective case series of 4,730 patients requiring hospitalization for COVID-19 in UC Healths five medical centers, male (OR 1.41, 95% CI: 1.23-1.61), Hispanic/Latino (OR 1.35, 95% CI: 1.14-1.61), and Asian (OR 1.43, 95% CI: 1.12-1.82) were more likely to be admitted to the ICU and/or die after adjustment for age and comorbidity. ICU admission and/or death was more likely among older individuals and greater numbers of pre-existing conditions.\n\nMeaningThis study describes the experience of a large, diverse cohort of patients with COVID-19 hospitalized in five hospitals in California between December 14, 2019 and January 6, 2021.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.30.21250828", + "rel_abs": "With limited availability of vaccines, an efficient use of the limited supply of vaccines in order to achieve herd immunity will be an important tool to combat the wide-spread prevalence of COVID-19. Here, we compare a selection of strategies for vaccine distribution, including a novel targeted vaccination approach (EHR) that provides a noticeable increase in vaccine impact on disease spread compared to age-prioritized and random selection vaccination schemes. Using high-fidelity individual-based computer simulations with Oslo, Norway as an example, we find that for a community reproductive number in a setting where the base pre-vaccination reproduction number R = 2.1 without population immunity, the EHR method reaches herd immunity at 48% of the population vaccinated with 90% efficiency, whereas the common age-prioritized approach needs 89%, and a population-wide random selection approach requires 61%. We find that age-based strategies have a substantially weaker impact on epidemic spread and struggle to achieve herd immunity under the majority of conditions. Furthermore, the vaccination of minors is essential to achieving herd immunity, even for ideal vaccines providing 100% protection.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Miriam Nuno", - "author_inst": "Department of Public Health Sciences, University of California Davis" - }, - { - "author_name": "Yury Garcia", - "author_inst": "Centro de Investigacion en Matematica Pura y Aplicada (CIMPA), University of Costa Rica" - }, - { - "author_name": "Ganesh Rajasekar", - "author_inst": "Department of Surgery, University of California Davis" + "author_name": "Andre Voigt", + "author_inst": "Norwegian University of Science and Technology" }, { - "author_name": "Diego Pinheiro", - "author_inst": "Department of Internal Medicine, School of Medicine, University of California Davis" + "author_name": "Stig William Omholt", + "author_inst": "Norwegian University of Science and Technology" }, { - "author_name": "Alec J Schmidt", - "author_inst": "Department of Public Health Sciences, University of California Davis" + "author_name": "Eivind Almaas", + "author_inst": "Norwegian University of Science and Technology" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -932031,61 +931347,41 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.01.28.21250692", - "rel_title": "A control framework to optimize public health policies in the course of the COVID-19 pandemic", + "rel_doi": "10.1101/2021.01.28.21249411", + "rel_title": "Racial and Ethnic Disparities in Years of Potential Life Lost Attributable to COVID-19 in the United States: An Analysis of 45 States and the District of Columbia", "rel_date": "2021-01-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.28.21250692", - "rel_abs": "The SARS-CoV-2 pandemic triggered substantial economic and social disruptions. Mitigation policies varied across countries based on resources, political conditions, and human behavior. In the absence of widespread vaccination able to induce herd immunity, strategies to coexist with the virus while minimizing risks of surges are paramount, which should work in parallel with reopening societies. To support these strategies, we present a predictive control system coupled with a nonlinear model able to optimize the level of policies to stop epidemic growth. We applied this system to study the unfolding of COVID-19 in Bahia, Brazil, also assessing the effects of varying population compliance. We show the importance of finely tuning the levels of enforced measures to achieve SARS-CoV-2 containment, with periodic interventions emerging as an optimal control strategy in the long-term.\n\nOne-sentence summaryWe present an adaptive predictive control algorithm to provide optimal public health measures to slow the COVID-19 transmission rate.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.28.21249411", + "rel_abs": "The coronavirus disease 2019 (COVID-19) epidemic in the United States has disproportionately impacted communities of color across the country. Focusing on COVID-19-attributable mortality, we expand upon a national comparative analysis of years of potential life lost (YPLL) attributable to COVID-19 by race/ethnicity (Bassett et al., 2020), estimating percentages of total YPLL for non-Hispanic Whites, non-Hispanic Blacks, Hispanics, non-Hispanic Asians, and non-Hispanic American Indian or Alaska Natives, contrasting them with their respective percent population shares, as well as age-adjusted YPLL rate ratios - anchoring comparisons to non-Hispanic Whites - in each of 45 states and the District of Columbia using data from the National Center for Health Statistics as of December 30, 2020. Using a novel Monte Carlo simulation procedure to quantify estimation uncertainty, our results reveal substantial racial/ethnic disparities in COVID-19-attributable YPLL across states, with a prevailing pattern of non-Hispanic Blacks and Hispanics experiencing disproportionately high and non-Hispanic Whites experiencing disproportionately low COVID-19-attributable YPLL. Furthermore, observed disparities are generally more pronounced when measuring mortality in terms of YPLL compared to death counts, reflecting the greater intensity of the disparities at younger ages. We also find substantial state-to-state variability in the magnitudes of the estimated racial/ethnic disparities, suggesting that they are driven in large part by social determinants of health whose degree of association with race/ethnicity varies by state.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Igor M. L. Pataro", - "author_inst": "University of Almeria" - }, - { - "author_name": "Juliane F. Oliveira", - "author_inst": "University of Porto" - }, - { - "author_name": "Marcelo M. Morato", - "author_inst": "Federal University of Santa Catarina" - }, - { - "author_name": "Alan A. S. Amad", - "author_inst": "College of Engineering, Swansea University" - }, - { - "author_name": "Pablo I. P. Ramos", - "author_inst": "Center for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation (FIOCRUZ)" - }, - { - "author_name": "Felipe A. C. Pereira", - "author_inst": "Department of Mining and Petroleum Engineering, University of Sao Paulo" + "author_name": "Jay J Xu", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Mateus S. Silva", - "author_inst": "Federal University of Bahia" + "author_name": "Jarvis T Chen", + "author_inst": "Harvard University" }, { - "author_name": "Daniel C. P. Jorge", - "author_inst": "Federal University of Bahia" + "author_name": "Thomas R Belin", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Roberto F. S. Andrade", - "author_inst": "Institute of Collective Health, Federal University of Bahia" + "author_name": "Ronald S Brookmeyer", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Mauricio L. Barreto", - "author_inst": "Institute of Collective Health, Federal University of Bahia" + "author_name": "Marc A Suchard", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Marcus Americano da Costa", - "author_inst": "Federal University of Bahia" + "author_name": "Christina M Ramirez", + "author_inst": "University of California, Los Angeles" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -933841,53 +933137,73 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.27.21249186", - "rel_title": "SARS-CoV-2 in Ivory Coast: serosurveillance survey among mines workers", + "rel_doi": "10.1101/2021.01.28.21250664", + "rel_title": "Risk of SARS-CoV-2 exposure among hospital healthcare workers in relation to patient contact and type of care", "rel_date": "2021-01-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.27.21249186", - "rel_abs": "BackgroundEight months after the detection of the first COVID-19 case in Africa, 1,262,476 cases have been reported in African countries compared to 72 million worldwide. The real burden of SARS-CoV-2 infection in West Africa is not clearly defined. The aim of the study was to evaluate the seroprevalence of SARS-CoV-2 in half of the 3,380 workers of several mining companies operating in two mines in the Ivory Coast and having its headquarters in the economic capital Abidjan.\n\nMethodsFrom 15th July to 13th October 2020, a voluntary serological test campaign was performed in the 3 sites where the companies operate: two mines, and the headquarters in Abidjan.We performed a COVID-PRESTO rapid test for the detection of IgG and IgM on capillary blood. A multivariate analysis was performed to identify independent sociodemographic characteristics associated with a higher SARS-CoV-2 seroprevalence rate.\n\nResultsA total of 1,687 subjects were tested. 91% were male (n= 1,536) and mean age was 37 years old. The overall crude seroprevalence rate was 25.1% (n=422), but differing significantly between different sites, rising from 13.6% (11.2%-16.1%) in mine A to 34.4% (31.1%-37.7%) in mine B and 34.7% (26.2%-43.2%) in Abidjan. Non-resident workers in mines had a significantly lower prevalence rate than those living full-time in mines. Seroprevalence was 26.5% in natives of the Ivory Coast, while people coming from countries other than Africa were less likely to be SARS-CoV-2 seropositive. Among the 422 positive subjects, 74 reported mild symptoms in the three previous months and one was hospitalized for a severe COVID-19 infection.\n\nConclusionThe prevalence of SARS-CoV-2 infection among mine workers in Ivory Coast is high. The low morbidity observed has probably led to an underestimation of the burden of this infection in West Africa. The high prevalence reported in subjects living in Abidjan, who have not any close contact with mine workers, may be indicative of the real seroprevalence in the Ivory Coast capital.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.28.21250664", + "rel_abs": "AimWe aimed to assess the risk for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection in a large cohort of healthcare workers (HCWs).\n\nMethodsFrom May 11 until June 11, 2020, 3,981 HCWs at a large Swedish Emergency Care hospital provided serum samples and questionnaire data. Exposure was measured by assaying IgG antibodies to SARS-CoV-2.\n\nResultsThe total seroprevalence was 17.7% and increased during the study period. Among the seropositive HCWs, 10.5% had been entirely asymptomatic. Participants who worked with COVID-19 patients had higher odds for seropositivity: ORadj 1.96 (95% CI 1.59 - 2.42). HCWs from three of the departments managing COVID-19 patients had significantly higher seroprevalences, whereas the prevalence among HCWs from the Intensive Care Unit (also managing COVID-19 patients) was significantly lower.\n\nConclusionHCWs in contact with SARS-CoV-2 infected patients had a variable, but on average higher, likelihood for SARS-CoV-2 infections.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Jean- Marie Milleliri", - "author_inst": "Groupe d'Intervention en Sante Publique et Epidemiologie (GISPE), Marseille, France" + "author_name": "Susanna Klevebro", + "author_inst": "Karolinska Institutet, Stockholm South General Hospital" }, { - "author_name": "Daouda Coulibaly", - "author_inst": "Institut National d'Hygiene Publique (INHP), Abidjan, Ivory Coast" + "author_name": "Fuad Bahram", + "author_inst": "Karolinska Institutet, Stockholm South General Hospital" }, { - "author_name": "Blaise Nyobe", - "author_inst": "Medicis, Abidjan, Ivory Coast" + "author_name": "Miriam K Elfstrom", + "author_inst": "Karolinska University Hospital" }, { - "author_name": "Jean-Loup Rey", - "author_inst": "Groupe d'Intervention en Sante Publique et Epidemiologie (GISPE), Marseille, France" + "author_name": "Ulrika Hellberg", + "author_inst": "Karolinska Institutet, Stockholm South General Hospital" }, { - "author_name": "Franck Lamontagne", - "author_inst": "Groupe d'Intervention en Sante Publique et Epidemiologie, Marseille, France" + "author_name": "Sophia Hober", + "author_inst": "KTH Royal Institute of Technology, SciLifeLab" }, { - "author_name": "Laurent Hocqueloux", - "author_inst": "Departement des Maladies Infectieuses et Tropicales, CHR Orleans, Orleans, France" + "author_name": "Simon K Merid", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Susanna Giache", - "author_inst": "Departement des Maladies Infectieuses et Tropicales, CHR Orleans, Orleans, France" + "author_name": "Inger Kull", + "author_inst": "Karolinska Institutet, Stockholm South General Hospital" + }, + { + "author_name": "Peter Nilsson", + "author_inst": "KTH Royal Institute of Technology, SciLifeLab" }, { - "author_name": "Antoine Valery", - "author_inst": "Departement d'information medicale, CHR Orleans, Orleans, France" + "author_name": "Per Tornvall", + "author_inst": "Karolinska Institutet, Stockholm South General Hospital" }, { - "author_name": "thierry prazuck", - "author_inst": "CHR Orleans" + "author_name": "Gang Wang", + "author_inst": "Karolinska Institutet and Sichuan University" + }, + { + "author_name": "Kalle Conneryd-Lundgren", + "author_inst": "Karolinska University Hospital" + }, + { + "author_name": "Sari Ponzer", + "author_inst": "Karolinska Institutet, Stockholm South General Hospital" + }, + { + "author_name": "Joakim Dillner", + "author_inst": "Karolinska University Hospital" + }, + { + "author_name": "Erik Melen", + "author_inst": "Karolinska Institutet, Stockholm South General Hospital" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -935467,75 +934783,59 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2021.01.22.21250054", - "rel_title": "Distinctive features of SARS-CoV-2-specific T cells predict recovery from severe COVID-19", + "rel_doi": "10.1101/2021.01.27.428543", + "rel_title": "Genome-scale metabolic modeling reveals SARS-CoV-2-induced host metabolic reprogramming and identifies metabolic antiviral targets", "rel_date": "2021-01-28", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.22.21250054", - "rel_abs": "Although T cells are likely players in SARS-CoV-2 immunity, little is known about the phenotypic features of SARS-CoV-2-specific T cells associated with recovery from severe COVID-19. We analyzed T cells from longitudinal specimens of 34 COVID-19 patients with severities ranging from mild (outpatient) to critical culminating in death. Relative to patients that succumbed, individuals that recovered from severe COVID-19 harbored elevated and increasing numbers of SARS-CoV-2-specific T cells capable of homeostatic proliferation. In contrast, fatal COVID-19 displayed elevated numbers of SARS-CoV-2-specific regulatory T cells and a time-dependent escalation in activated bystander CXCR4+ T cells. Together with the demonstration of increased proportions of inflammatory CXCR4+ T cells in the lungs of severe COVID-19 patients, these results support a model whereby lung-homing T cells activated through bystander effects contribute to immunopathology, while a robust, non-suppressive SARS-CoV-2-specific T cell response limits pathogenesis and promotes recovery from severe COVID-19.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=197 SRC=\"FIGDIR/small/21250054v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (73K):\norg.highwire.dtl.DTLVardef@c82ec8org.highwire.dtl.DTLVardef@778d7forg.highwire.dtl.DTLVardef@ea9130org.highwire.dtl.DTLVardef@1e21805_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LIDysfunctional spike-specific T cells are characteristic of severe COVID-19\nC_LIO_LISpike-specific CD127+ Th1 cells are increased in survivors of severe COVID-19\nC_LIO_LISpike-specific Tregs and IL6+ CD8+ T cells are increased in fatal COVID-19\nC_LIO_LIEscalation of activated lung-homing CXCR4+ T cells associates with fatal COVID-19\nC_LI\n\nBRIEF SUMMARYBy conducting CyTOF on total and SARS-CoV-2-specific T cells from longitudinal specimens spanning the entire spectrum of COVID-19 diseases, Neidleman et al. demonstrate that spike-specific Th1 cells capable of IL7-dependent homeostatic proliferation predict survival from severe COVID-19, while Tregs and IL6+ CD8+ T cells recognizing spike predict fatal outcome. Fatal COVID-19 is characterized by escalating activation of bystander CXCR4+ T cells in the lungs. Boosting SARS-CoV-2-specific CD4+ T effector responses while diminishing CXCR4-mediated homing may help recovery from severe disease.", - "rel_num_authors": 14, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.27.428543", + "rel_abs": "Tremendous progress has been made to control the COVID-19 pandemic caused by the SARS-CoV-2 virus. However, effective therapeutic options are still rare. Drug repurposing and combination represent practical strategies to address this urgent unmet medical need. Viruses, including coronaviruses, are known to hijack host metabolism to facilitate viral proliferation, making targeting host metabolism a promising antiviral approach. Here, we describe an integrated analysis of 12 published in vitro and human patient gene expression datasets on SARS-CoV-2 infection using genome-scale metabolic modeling (GEM), revealing complicated host metabolism reprogramming during SARS-CoV-2 infection. We next applied the GEM-based metabolic transformation algorithm to predict anti-SARS-CoV-2 targets that counteract the virus-induced metabolic changes. We successfully validated these targets using published drug and genetic screen data and by performing an siRNA assay in Caco-2 cells. Further generating and analyzing RNA-sequencing data of remdesivir-treated Vero E6 cell samples, we predicted metabolic targets acting in combination with remdesivir, an approved anti-SARS-CoV-2 drug. Our study provides clinical data-supported candidate anti-SARS-CoV-2 targets for future evaluation, demonstrating host metabolism-targeting as a promising antiviral strategy.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Jason Neidleman", - "author_inst": "Gladstone/UCSF" - }, - { - "author_name": "Xiaoyu Luo", - "author_inst": "Gladstone/UCSF" - }, - { - "author_name": "Ashley F. George", - "author_inst": "Gladstone/UCSF" - }, - { - "author_name": "Matthew McGregor", - "author_inst": "Gladstone/UCSF" - }, - { - "author_name": "Junkai Yang", - "author_inst": "Emory University" + "author_name": "Kuoyuan Cheng", + "author_inst": "Cancer Data Science Laboratory (CDSL), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD, USA." }, { - "author_name": "Cassandra Yun", - "author_inst": "UCSF" + "author_name": "Laura Martin-Sancho", + "author_inst": "Immunity and Pathogenesis Program, Infectious and Inflammatory Disease Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA." }, { - "author_name": "Victoria Murray", - "author_inst": "UCSF" + "author_name": "Lipika Ray Pal", + "author_inst": "Cancer Data Science Laboratory (CDSL), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD, USA." }, { - "author_name": "Gurjot Gill", - "author_inst": "UCSF" + "author_name": "Yuan Pu", + "author_inst": "Immunity and Pathogenesis Program, Infectious and Inflammatory Disease Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA." }, { - "author_name": "Warner C. Greene", - "author_inst": "Gladstone/UCSF" + "author_name": "Laura Riva", + "author_inst": "Immunity and Pathogenesis Program, Infectious and Inflammatory Disease Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA." }, { - "author_name": "Joshua Vasquez", - "author_inst": "UCSF" + "author_name": "Xin Yin", + "author_inst": "Immunity and Pathogenesis Program, Infectious and Inflammatory Disease Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA." }, { - "author_name": "Sulggi Lee", - "author_inst": "UCSF" + "author_name": "Sanju Sinha", + "author_inst": "Cancer Data Science Laboratory (CDSL), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD, USA." }, { - "author_name": "Eliver Ghosn", - "author_inst": "Emory University" + "author_name": "Nishanth Ulhas Nair", + "author_inst": "Cancer Data Science Laboratory (CDSL), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD, USA." }, { - "author_name": "Kara Lynch", - "author_inst": "UCSF" + "author_name": "Sumit K. Chanda", + "author_inst": "Immunity and Pathogenesis Program, Infectious and Inflammatory Disease Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA." }, { - "author_name": "Nadia R. Roan", - "author_inst": "University of California, San Francisco; and Gladstone Institutes" + "author_name": "Eytan Ruppin", + "author_inst": "Cancer Data Science Laboratory (CDSL), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD, USA." } ], "version": "1", - "license": "cc_by_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "systems biology" }, { "rel_doi": "10.1101/2021.01.27.428516", @@ -937401,39 +936701,31 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2021.01.27.428466", - "rel_title": "Synthetic nanobody-SARS-CoV-2 receptor-binding domain structures identify distinct epitopes", + "rel_doi": "10.1101/2021.01.27.428384", + "rel_title": "SARS-CoV-2 emerging complexity", "rel_date": "2021-01-27", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.27.428466", - "rel_abs": "The worldwide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) demands unprecedented attention. We report four X-ray crystal structures of three synthetic nanobodies (sybodies) (Sb16, Sb45 and Sb68) bind to the receptor-binding domain (RBD) of SARS-CoV-2: binary complexes of Sb16-RBD and Sb45-RBD; a ternary complex of Sb45-RBD-Sb68; and Sb16 unliganded. Sb16 and Sb45 bind the RBD at the ACE2 interface, positioning their CDR2 and CDR3 loops diametrically. Sb16 reveals a large CDR2 shift when binding the RBD. Sb68 interacts peripherally at the ACE2 interface; steric clashes with glycans explain its mechanism of viral neutralization. Superposing these structures onto trimeric spike (S) protein models indicates these sybodies bind conformations of the mature S protein differently, which may aid therapeutic design.\n\nOne Sentence SummaryX-ray structures of synthetic nanobodies complexed with the receptor-binding domain of the spike protein of SARS-CoV-2 reveal details of CDR loop interactions in recognition of distinct epitopic sites.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.27.428384", + "rel_abs": "The novel SARS_CoV-2 virus, prone to variation when interacting with spatially extended ecosystems and within hosts1 can be considered a complex dynamic system2. Therefore, it behaves creating several space-time manifestations of its dynamics. However, these physical manifestations in nature have not yet been fully disclosed or understood. Here we show 4-3 and 2-D space-time patterns of rate of infected individuals on a global scale, giving quantitative measures of transitions between different dynamical behaviour. By slicing the spatio-temporal patterns, we found manifestations of the virus behaviour such as cluster formation and bifurcations. Furthermore, by analysing the morphogenesis processes by entropy, we have been able to detect the virus phase transitions, typical of adaptive biological systems3. Our results for the first time describe the virus patterning behaviour processes all over the world, giving for them quantitative measures. We know that the outcomes of this work are still partial and more advanced analyses of the virus behaviour in nature are necessary. However, we think that the set of methods implemented can provide significant advantages to better analyse the viral behaviour in the approach of system biology4, thus expanding knowledge and improving pandemic problem solving.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Javeed Ahmad", - "author_inst": "NIAID/NIH" - }, - { - "author_name": "Jiansheng Jiang", - "author_inst": "NIAID/NIH" - }, - { - "author_name": "Lisa F Boyd", - "author_inst": "NIAID/NIH" + "author_name": "Francesca Bertacchini", + "author_inst": "University of Calabria Faculty of Mathematical Physical and Natural Sciences: Universita della Calabria" }, { - "author_name": "Kannan Natarajan", - "author_inst": "NIAID/NIH" + "author_name": "Eleonora Bilotta", + "author_inst": "Universit\u00e0 della Calabria" }, { - "author_name": "David H Margulies", - "author_inst": "NIAID/NIH" + "author_name": "Pietro S. Pantano", + "author_inst": "University of Calabria Faculty of Mathematical Physical and Natural Sciences: Universita della Calabria" } ], "version": "1", - "license": "", + "license": "cc_by", "type": "new results", - "category": "immunology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.01.26.428208", @@ -939099,65 +938391,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.22.21250287", - "rel_title": "Two original observations concerning bacterial infections in COVID-19 patients hospitalized in intensive care units during the first wave of the epidemic in France", + "rel_doi": "10.1101/2021.01.25.21249679", + "rel_title": "Ultrasensitive measurement of both SARS-CoV2 RNA and serology from saliva", "rel_date": "2021-01-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.22.21250287", - "rel_abs": "Among 197 COVID-19 patients hospitalized in ICU, 88 (44.7%) experienced at least one bacterial infection, with pneumonia (39.1%) and bloodstream infections (15,7%) being the most frequent. Unusual findings include frequent suspicion of bacterial translocations originating from the digestive tract as well as bacterial persistence in the lungs despite adequate therapy.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.25.21249679", + "rel_abs": "Tests for COVID-19 generally measure SARS-CoV2 viral RNA from nasal swabs or antibodies against the virus from blood. It has been shown, however, that both viral particles and antibodies against those particles are present in saliva, which is more accessible than both swabs and blood. We present methods for highly sensitive measurements of both viral RNA and serology from the same saliva sample. We developed an efficient saliva RNA extraction method and combined it with an ultrasensitive serology test based on Single Molecule Array (Simoa) technology. We apply our test to the saliva of patients who presented to the hospital with COVID-19 symptoms, some of whom tested positive with a conventional RT-qPCR nasopharyngeal swab test. We demonstrate that combining viral RNA detection by RT-qPCR with serology identifies more patients as infected than either method alone. Our results suggest the utility of combining viral RNA and serology testing from saliva, a single easily accessible biofluid.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Camille d'Humieres", - "author_inst": "AP-HP, Hopital Bichat, Bacteriology, F-75018 Paris, France, Universite de Paris, INSERM, IAME, F-75006 Paris, France" - }, - { - "author_name": "Juliette Patrier", - "author_inst": "AP-HP, Hopital Bichat, Medical and Infectious Diseases ICU (MI2), F-75018 Paris, France" - }, - { - "author_name": "Brice Lortat-Jacob", - "author_inst": "AP-HP, Hopital Bichat, Department of anesthesiology and surgical critical care, F-75018 Paris, France" - }, - { - "author_name": "Alexy Tran-dinh", - "author_inst": "AP-HP, Hopital Bichat, Department of anesthesiology and surgical critical care, F-75018 Paris, France - Universite de Paris, INSERM U 1148, F-75006 Paris, Franc" - }, - { - "author_name": "Lotfi Chemali", - "author_inst": "AP-HP, Hopital Bichat, Bacteriology, F-75018 Paris, France" - }, - { - "author_name": "Naouale Maataoui", - "author_inst": "AP-HP, Hopital Bichat, Bacteriology, F-75018 Paris, France; Universite de Paris, INSERM, IAME, F-75006 Paris, France" + "author_name": "Dmitry Ter-Ovanesyan", + "author_inst": "Wyss Institute for Biologically Inspired Engineering" }, { - "author_name": "Emilie Rondinaud", - "author_inst": "AP-HP, Hopital Bichat, Bacteriology, F-75018 Paris, France; Universite de Paris, INSERM, IAME, F-75006 Paris, France" + "author_name": "Tal Gilboa", + "author_inst": "Brigham and Womens Hospital" }, { - "author_name": "Etienne Ruppe", - "author_inst": "AP-HP, Hopital Bichat, Bacteriology, F-75018 Paris, France; Universite de Paris, INSERM, IAME, F-75006 Paris, France" + "author_name": "Roey Lazarovits", + "author_inst": "Wyss Institute for Biologically Inspired Engineering" }, { - "author_name": "Charles Burdet", - "author_inst": "Universite de Paris, INSERM, IAME, F-75006 Paris, France; AP-HP, Hopital Bichat, Departement d Epidemiologie, Biostatistique et Recherche Clinique, F-75018 Pari" + "author_name": "Alexandra Rosenthal", + "author_inst": "Brigham and Womens Hospital" }, { - "author_name": "Stephane Ruckly", - "author_inst": "AP-HP, Hopital Bichat, Medical and Infectious Diseases ICU (MI2), F-75018 Paris, France" + "author_name": "Xu G Yu", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Philippe Montravers", - "author_inst": "AP-HP, Hopital Bichat, Department of anesthesiology and surgical critical care, F-75018 Paris, France; INSERM 1152" + "author_name": "Jonathan Z Li", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School" }, { - "author_name": "Jean-Francois Timsit", - "author_inst": "AP-HP, Hopital Bichat, Medical and Infectious Diseases ICU (MI2), F-75018 Paris, France; Universite de Paris, INSERM, IAME, F-75006 Paris, France" + "author_name": "George M Church", + "author_inst": "Harvard Medical School" }, { - "author_name": "Laurence Armand-Lefevre", - "author_inst": "AP-HP, Hopital Bichat, Bacteriology, F-75018 Paris, France; Universite de Paris, INSERM, IAME, F-75006 Paris, France" + "author_name": "David R Walt", + "author_inst": "Brigham and Womens Hospital" } ], "version": "1", @@ -941097,29 +940369,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.25.21250509", - "rel_title": "Logistic advantage of two-step screening strategy for SARS-CoV-2 at airport quarantine", + "rel_doi": "10.1101/2021.01.25.21249974", + "rel_title": "Emergence and fast spread of B.1.1.7 lineage in Lebanon.", "rel_date": "2021-01-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.25.21250509", - "rel_abs": "BackgroundAirport quarantine is required to reduce the risk of entry of travelers infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, it is challenging for both high accuracy and rapid turn-around time to coexist in testing; polymerase chain reaction (PCR) is time-consuming with high accuracy, while antigen testing is rapid with less accuracy.\n\nMethods88,924 (93.2%) of 95,457 arrivals at three international airports in Japan were tested for SARS-CoV-2 using self-collected saliva by a screening strategy with initial chemiluminescent enzyme immunoassay (CLEIA) followed by confirmatory nucleic acid amplification tests (NAAT) only for intermediate range antigen concentrations.\n\nResults254 (0.27%) persons were found to be SARS-CoV-2 antigen positive ([≥] 4.0 pg/mL) by CLEIA. NAAT was required for confirmatory testing in 513 (0.54%) persons with intermediate antigen concentrations (0.67-4.0 pg/mL) whereby the virus was detected in 34 (6.6%) persons. This two-step strategy dramatically reduced the utilization of NAAT to approximately one out of every 200 test subjects.\n\nEstimated performance of this strategy did not show significant increase in false negatives as compared to performing NAAT in all subjects. Further reduction in imported cases may be achieved by post-screening quarantine.\n\nConclusionsPoint of care testing by quantitative CLEIA using self-collected saliva is less labor-intensive and yields results rapidly, thus suitable as an initial screening test. Reserving NAAT for CLEIA indeterminate cases may prevent compromising accuracy while significantly improving the logistics of administering mass-screening at large venues.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.25.21249974", + "rel_abs": "The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains a rapid spread emerging disease. Recently, a new variant of this virus called SARS-CoV-2 VOC 202012/01 (or B.1.1.7 lineage), described in the United Kingdom (UK), has become highly prevalent in several countries. Its rate of transmission has been estimated to be greatly higher. B.1.1.7 lineage harbors 23 mutations co-existed for the first time in the same variant. Herein, we are interested only by the deletion mutation {Delta}H69/{Delta}V70 in the spike protein.\n\nIn the UK they were able to identify the increase of this new variant through the increase in the false negative result for the spike target of a three-target RT-PCR assay from Thermo Fisher Scientific (TaqPath kit). Later, the manufacturer announced that this false negative result is because of the deletion {Delta}H69/{Delta}V70 in the area targeted by the TaqPath Kit. Furthermore, The European CDC recommended that the use of this kit help to track the new variant.\n\nGenome sequencing is the gold method to confirm the new variant, but observational studies provide also stronger evidence if similar models are observed in multiple countries, especially when randomized studies are not possible. In Lebanon, the highest number of confirmed cases were reported in first week of 2021. In the present study, we show the emergence and the fast spreading of the new variant in Lebanon and a relationship between SARS-CoV-2 transmission intensity and the frequency of the new variant during the first twelve days of January.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Isao Yokota", - "author_inst": "Hokkaido University" + "author_name": "mahmoud younes", + "author_inst": "Research department, Beirut cardiac institute" }, { - "author_name": "Peter Y Shane", - "author_inst": "Hokkaido University" + "author_name": "kassem hamze", + "author_inst": "Lebanese university" }, { - "author_name": "Takanori Teshima", - "author_inst": "Hokkaido University" + "author_name": "hassan nassar", + "author_inst": "Bahman hospital" + }, + { + "author_name": "mohammad makki", + "author_inst": "Research department, Beirut cardiac institute" + }, + { + "author_name": "Mayssa Ghaddar", + "author_inst": "Bahman Hospital" + }, + { + "author_name": "paul Nguewa", + "author_inst": "University of Navarra, ISTUN Instituto de Salud Tropical, Department of Microbiology and Parasitology" + }, + { + "author_name": "fadi abdel sater", + "author_inst": "Lebanese university, Molecular Biology and cancer Immunology" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -942799,33 +942087,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.24.21250408", - "rel_title": "Harnessing testing strategies and public health measures to avert COVID-19 outbreaks during ocean cruises", + "rel_doi": "10.1101/2021.01.22.21250042", + "rel_title": "Detection of SARS-CoV-2 infection by rapid antigen test in comparison with RT-PCR in a public setting", "rel_date": "2021-01-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.24.21250408", - "rel_abs": "To ensure the safe operation of schools, workplaces, nursing homes, and other businesses during COVID-19 pandemic there is an urgent need to develop cost-effective public health strategies. Here we focus on the cruise industry which was hit early by the COVID-19 pandemic, with more than 40 cruise ships reporting COVID-19 infections. We apply mathematical modeling to assess the impact of testing strategies together with social distancing protocols on the spread of the novel coronavirus during ocean cruises using an individual-level stochastic model of the transmission dynamics of COVID-19. We model the contact network, the potential importation of cases arising during shore excursions, the temporal course of infectivity at the individual level, the effects of social distancing strategies, different testing scenarios characterized by the tests sensitivity profile, and the testing frequency. Our findings indicate that PCR testing at embarkation and daily testing of all individuals aboard, together with increased social distancing and other public health measures, should allow for rapid detection and isolation of COVID-19 infections and dramatically reducing the probability of onboard COVID-19 community spread. In contrast, relying only on PCR testing at embarkation would not be sufficient to avert outbreaks, even when implementing substantial levels of social distancing measures.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.22.21250042", + "rel_abs": "BackgroundRapid and accurate detection of SARS-CoV-2 infection is essential in limiting the spread of infection during the ongoing COVID-19 pandemic. The aim of this study was to determine the accuracy of the STANDARD Q COVID-19 Ag test (SD BIOSENSOR) by comparison with RT-PCR in a public setting.\n\nMethodIndividuals aged 18 years or older who had booked an appointment for a RT-PCR test on December 26-31, 2020 at a public test center in Copenhagen, Denmark, were invited to participate. An oropharyngeal swab was collected for RT-PCR analysis, immediately followed by a nasopharyngeal swab examined by the STANDARD Q COVID-19 Ag test (SD BIOSENSOR). Sensitivity, specificity, positive and negative predictive values of the antigen test were calculated with test results from RT-PCR as reference.\n\nResultsOverall, 4697 individuals were included (female n=2456, 53.3%; mean age: 44.7 years, SD: 16.9 years); 196 individuals were tested twice or more. Among 4811 paired conclusive test results from the RT-PCR and antigen tests, 221 (4.6%) RT-PCR tests were positive. The overall sensitivity and specificity of the antigen test were 69.7% and 99.5%, the positive and negative predictive values were 87.0% and 98.5%. Ct values were significantly higher among individuals with false negative antigen tests compared to true positives.\n\nConclusionThe sensitivity, specificity, and predictive values found indicate that the STANDARD Q COVID-19 Ag is a good supplement to RT-PCR testing.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Gerardo Chowell", - "author_inst": "School of Public Health, Georgia State university" + "author_name": "Kathrine Kronberg Jakobsen", + "author_inst": "Department of Otorhinolaryngology, Head and Neck Surgery and Audiology, Rigshospitalet. University of Copenhagen, Copenhagen, Denmark" }, { - "author_name": "Sushma Dahal", - "author_inst": "Georgia State University" + "author_name": "Jakob Schmidt Jensen", + "author_inst": "Department of Otorhinolaryngology, Head and Neck Surgery and Audiology, Rigshospitalet. University of Copenhagen, Copenhagen, Denmark" }, { - "author_name": "Raquel Bono", - "author_inst": "Johns Hopkins University Applied Physics Laboratory" + "author_name": "Tobias Todsen", + "author_inst": "Department of Otorhinolaryngology, Head and Neck Surgery and Audiology, Rigshospitalet. University of Copenhagen, Copenhagen, Denmark" }, { - "author_name": "Kenji Mizumoto", - "author_inst": "Kyoto University, Japan" + "author_name": "Freddy Lippert", + "author_inst": "Copenhagen Emergency Medical Services, University of Copenhagen, Copenhagen, Denmark" + }, + { + "author_name": "Cyril Jean-Marie Martel", + "author_inst": "Testcenter Danmark, Statens Serum Institut, Copenhagen, Denmark" + }, + { + "author_name": "Mads Klokker", + "author_inst": "Department of Otorhinolaryngology, Head and Neck Surgery and Audiology, Rigshospitalet. University of Copenhagen, Copenhagen, Denmark" + }, + { + "author_name": "Christian von Buchwald", + "author_inst": "Department of Otorhinolaryngology, Head and Neck Surgery and Audiology, Rigshospitalet. University of Copenhagen, Copenhagen, Denmark" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -944801,43 +944101,27 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.01.24.428004", - "rel_title": "Lost in translation: codon optimization inactivates SARS-CoV-2 RdRp", + "rel_doi": "10.1101/2021.01.24.427990", + "rel_title": "Molecular Dynamics Reveals the Effects of Temperature on Critical SARS-CoV-2 Proteins", "rel_date": "2021-01-25", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.24.428004", - "rel_abs": "The catalytic subunit of SARS-CoV-2 RNA-dependent RNA polymerase (RdRp), Nsp12, has a unique NiRAN domain that transfers nucleoside monophosphates to the Nsp9 protein. The NiRAN and RdRp modules form a dynamic interface distant from their catalytic sites and both activities are essential for viral replication. We report that codon-optimized (for the pause-free translation) Nsp12 exists in inactive state in which NiRAN/RdRp interactions are broken, whereas translation by slow ribosomes and incubation with accessory Nsp7/8 subunits or NTPs partially rescue RdRp activity. Our data show that adenosine and remdesivir triphosphates promote synthesis of A-less RNAs, as does ppGpp, while amino acid substitutions at the NiRAN/RdRp interface augment activation, suggesting that ligand binding to the NiRAN catalytic site modulates RdRp activity. The existence of allosterically-linked nucleotidyl transferase sites that utilize the same substrates has important implications for understanding the mechanism of SARS-CoV-2 replication and design of its inhibitors.\n\nHighlightsO_LICodon-optimization of Nsp12 triggers misfolding and activity loss\nC_LIO_LISlow translation, accessory Nsp7 and Nsp8 subunits, and NTPs rescue Nsp12\nC_LIO_LINon-substrate nucleotides activate RNA chain synthesis, likely via NiRAN domain\nC_LIO_LICrosstalk between two Nsp12 active sites that bind the same ligands\nC_LI", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.24.427990", + "rel_abs": "Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a newly identified RNA virus that causes the serious infection Coronavirus Disease 2019 (COVID-19). The incidence of COVID-19 is still increasing worldwide despite the summer heat and cool winter. However, little is known about seasonal stability of SARS-CoV-2. Herein, we employ Molecular Dynamics (MD) simulations to explore the effect of temperature on four critical SARS-CoV-2 proteins. Our work demonstrates that the spike Receptor Binding Domain (RBD), Main protease (Mpro), and nonstructural protein 3 (macro X) possesses extreme thermos-stability when subjected to temperature variations rendering them attractive drug targets. Furthermore, our findings suggest that these four proteins are well adapted to habitable temperatures on earth and are largely insensitive to cold and warm climates. Furthermore, we report that the critical residues in SARS-CoV-2 RBD were less responsive to temperature variations as compared to the critical residues in SARS-CoV. As such, extreme summer and winter climates, and the transition between the two seasons, are expected to have a negligible effect on the stability of SARS-CoV-2 which will marginally suppress transmission rates until effective therapeutics are available world-wide.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Bing Wang", - "author_inst": "Ohio State University" - }, - { - "author_name": "Vladimir Svetlov", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Yuri I. Wolf", - "author_inst": "National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA" - }, - { - "author_name": "Eugene V. Koonin", - "author_inst": "National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA" - }, - { - "author_name": "Evgeny Nudler", - "author_inst": "NYU Grossman School of Medicine" + "author_name": "Paul Morgan", + "author_inst": "University of Belize" }, { - "author_name": "Irina Artsimovitch", - "author_inst": "The Ohio State University" + "author_name": "Chih-Wen Shu", + "author_inst": "National Sun Yat-Sen University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc", "type": "new results", - "category": "molecular biology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.01.25.428136", @@ -946387,57 +945671,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.21.21250273", - "rel_title": "Do Pandemics Obey the Elliott Wave Principle of Financial Markets?", + "rel_doi": "10.1101/2021.01.21.21250268", + "rel_title": "Personalized Virus Load Curves of SARS-CoV-2 Infection", "rel_date": "2021-01-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.21.21250273", - "rel_abs": "The Elliott Wave principle is a time-honored, oft-used method for predicting variations in the financial markets. It is based on the notion that human emotions drive financial decisions. In the fight against COVID-19, human emotions are similarly decisive, for instance in that they determine ones willingness to be vaccinated, and/or to follow preventive measures including the wearing of masks, the application of social distancing protocols, and frequent handwashing. On this basis, we postulated that the Elliott Wave Principle may similarly be used to predict the future evolution of the COVID-19 pandemic. We demonstrated that this method reproduces the data pattern especially well for USA (daily new cases). Potential scenarios were then extrapolated, from the best-case corresponding to a rapid, full vaccination of the population, to the utterly disastrous case of slow vaccination, and poor adherence to preventive protocols.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.21.21250268", + "rel_abs": "We introduce an explicit function that describes virus-load curves on a patient-specific level. This function is based on simple and intuitive model parameters. It allows virus load analysis without solving a full virus load dynamic model. We validate our model on data from influenza A as well as SARS-CoV-2 infection data for Macaque monkeys and humans. Further, we compare the virus load function to an established target model of virus dynamics, which shows an excellent fit. Our virus-load function offers a new way to analyse patient virus load data, and it can be used as input to higher level models for the physiological effects of a virus infection, for models of tissue damage, and to estimate patient risks.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Prashant Dogra", - "author_inst": "Houston Methodist Research Institute" - }, - { - "author_name": "Eugene J. Koay", - "author_inst": "MD Anderson Cancer Center" - }, - { - "author_name": "Zhihui Wang", - "author_inst": "Houston Methodist Research Institute" - }, - { - "author_name": "Farhaan Vahidy", - "author_inst": "Houston Methodist Research Institute" - }, - { - "author_name": "Mauro Ferrari", - "author_inst": "University of Washington" - }, - { - "author_name": "Renata Pasqualini", - "author_inst": "Rutgers Cancer Institute of New Jersey" - }, - { - "author_name": "Wadih Arap", - "author_inst": "Rutgers Cancer Institute of New Jersey" - }, - { - "author_name": "Marc L. Boom", - "author_inst": "Houston Methodist" + "author_name": "Thomas Hillen", + "author_inst": "University of Alberta" }, { - "author_name": "H. Dirk Sostman", - "author_inst": "Houston Methodist Research Institute" + "author_name": "Carlos Contreras", + "author_inst": "University of Alberta" }, { - "author_name": "Vittorio Cristini", - "author_inst": "Houston Methodist Research Institute" + "author_name": "Jay M Newby", + "author_inst": "University of Alberta" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -948073,23 +947329,67 @@ "category": "scientific communication and education" }, { - "rel_doi": "10.1101/2021.01.15.21249732", - "rel_title": "Regression Tree Modelling to Predict Total Average Extra Costs in Household Spending During COVID-19 Pandemic", + "rel_doi": "10.1101/2021.01.15.21249884", + "rel_title": "Estimating the effects of non-pharmaceutical interventions on the number of new infections with COVID-19 during the first epidemic wave", "rel_date": "2021-01-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.15.21249732", - "rel_abs": "BackgroundPrevention of coronavirus (COVID-19) regarding households has many aspects, such as buying masks, hand sanitizer, face shield, and many others. As a result of buying the previous items, the household spending per month will be increase during the COVID-19 pandemic period.\n\nAimsTo calculate the average costs of each extra item involved in households spending during COVID-19 pandemic and to predict the total average extra costs spending by households.\n\nMethodsA cross-sectional study was conducted at High Institute of Public Health (HIPH), University Alexandria. Exponential snowball sampling was used to recruit students at HIPH and their friends. Trimming costs was done to remove extreme low and high values. A regression tree modelling was implemented to predict the total extra costs spending during COVID-19 pandemic.\n\nResultsMost of the respondents were female (81%) and aged between 30 and 40 (56.3%). About 63.1% of families had the same monthly income while 35.4% had a decrease in monthly income. A significant reduction in days of leaving home before and after COVID-19 pandemic was observed (before; mean= 5.86, after; mean = 4.66, P=0.000). The extra spending in grocery was the dominated item compared to other items (mean = 707.2, SD = 530.7). Regarding regression tree, the maximum average extra costs due to COVID-19 pandemic was 1386 L.E/month (around 88.23$/month) while the minimum average extra costs was 217 L.E/month (around 13.81$/month).\n\nConclusionsThe effect of COVID-19 pandemic in households spending varies largely between households, it depends on what they do to prevent COVID-19.\n\n*Hint: Convert form L.E to dollar performed according to price of dollar at 18-12-2020", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.15.21249884", + "rel_abs": "The novel coronavirus (SARS-CoV-2) has rapidly developed into a global epidemic. To control its spread, countries have implemented non-pharmaceutical interventions (NPIs), such as school closures, gathering bans, or even stay-at-home orders. Here we study the effectiveness of seven NPIs in reducing the number of new infections, which was inferred from the reported cases of COVID-19 using a semi-mechanistic Bayesian hierarchical model. Based on data from the first epidemic wave of n = 20 countries (i.e., the United States, Canada, Australia, the EU-15 countries, Norway, and Switzerland), we estimate the relative reduction in the number of new infections attributed to each NPI. Among the NPIs considered, event bans were most effective, followed by venue and school closures, whereas stay-at-home orders and work bans were least effective. With this retrospective cross-country analysis, we provide estimates regarding the effectiveness of different NPIs during the first epidemic wave.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Nesma Lotfy", - "author_inst": "High Institute of Public Health" + "author_name": "Nicolas Banholzer", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Eva van Weenen", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Adrian Lison", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Alberto Cenedese", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Arne Seeliger", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Bernhard Kratzwald", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Daniel Tschernutter", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Joan Puig Salles", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Pierluigi Bottrighi", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Sonja Lehtinen", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Stefan Feuerriegel", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Werner Vach", + "author_inst": "University of Basel" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "health policy" }, { "rel_doi": "10.1101/2021.01.15.21249893", @@ -949475,25 +948775,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.01.18.21250053", - "rel_title": "Forecasting the Spread of the COVID-19 Epidemic in Lombardy: A Dynamic Model Averaging Approach", + "rel_doi": "10.1101/2021.01.19.21249816", + "rel_title": "Modelling the COVID-19 Fatality Rate in England and its Regions", "rel_date": "2021-01-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.18.21250053", - "rel_abs": "Forecasting with accuracy the evolution of COVID-19 daily incidence curves is one of the most important exercises in the field of epidemic modeling. We examine the forecastability of daily COVID-19 cases in the Italian region of Lombardy using Dynamic Model Averaging and Dynamic Model Selection methods. To investigate the predictive accuracy of this approach, we compute forecast performance metrics of sequential out-of-sample real-time forecasts in a back-testing exercise ranging from March 1 to December 10 of 2020. We find that (i) Dynamic Model Averaging leads to a consistent and substantial predictive improvements over alternative epidemiological models and machine learning approaches when producing short-run forecasts. Using estimated posterior inclusion probabilities we also provide evidence on which set of predictors are relevant for forecasting in each period. Our findings also suggest that (ii) future incidences can be forecasted by exploiting information on the epidemic dynamics of neighboring regions, human mobility patterns, pollution and temperatures levels.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.19.21249816", + "rel_abs": "A model to account for the fatality rate in England and its regions is proposed. It follows the clear observation that, rather than two connected waves, there have been many waves of infections and fatalities in the regions of England of various magnitudes, usually overlapping. The waves are self-limiting, in that clear peaks are seen, particularly in reported positive test rates. The present model considers fatalities as the data reported are more reliable than positive test rates, particularly so during the first wave when so little testing was done.\n\nThe model considers the observed waves are essentially similar in form and can be modelled using a single wave form, whose final state is only dependent on its peak height and start date. The basic wave form was modelled using the observed fatality rates for London, which unlike the other regions, exhibited almost completely as a single wave in the \"first wave\". Its form matches rather well with the \"Do Nothing\" model reported by Imperial College on 16th March 2020, but reduced substantially from its expected peak.\n\nThere are, essentially, only two adjustable parameters used in the model, the start date of the relevant wave and its height. The modelled fatalities for each wave are summated per day and a cumulative curve is matched to that reported. The minimal number of adjustable parameters, alongside the fact that the waves invariably overlap, provides highly stringent conditions on the fitting process.\n\nResults are presented for each region for both the \"first\" and \"second waves. High levels of accuracy are obtained with R2 values approaching 100% against the ideal fit for both waves. It can also be seen that there are fundamental differences between the underlying behaviour of the \"first\" and \"second\" waves and reasons as to why those differences have arisen is briefly discussed.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Lisa Gianmoena", - "author_inst": "University of Pisa" - }, - { - "author_name": "Vicente Rios", - "author_inst": "University of Milan" + "author_name": "Nigel Saunders", + "author_inst": "Thermotech Ltd., Surrey Technology Centre, The Surrey Research Park, Guildford, Surrey GU2 7YG, U.K." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -951341,75 +950637,39 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.01.19.427310", - "rel_title": "A Universal Bacteriophage T4 Nanoparticle Platform to Design Multiplex SARS-CoV-2 Vaccine Candidates by CRISPR Engineering", + "rel_doi": "10.1101/2021.01.19.427355", + "rel_title": "Increased elastase sensitivity and decreased intramolecular interactions in the more transmissible SARS-CoV-2 variants' spike protein", "rel_date": "2021-01-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.19.427310", - "rel_abs": "A \"universal\" vaccine design platform that can rapidly generate multiplex vaccine candidates is critically needed to control future pandemics. Here, using SARS-CoV-2 pandemic virus as a model, we have developed such a platform by CRISPR engineering of bacteriophage T4. A pipeline of vaccine candidates were engineered by incorporating various viral components into appropriate compartments of phage nanoparticle structure. These include: expressible spike genes in genome, spike and envelope epitopes as surface decorations, and nucleocapsid proteins in packaged core. Phage decorated with spike trimers is found to be the most potent vaccine candidate in mouse and rabbit models. Without any adjuvant, this vaccine stimulated robust immune responses, both TH1 and TH2 IgG subclasses, blocked virus-receptor interactions, neutralized viral infection, and conferred complete protection against viral challenge. This new type of nanovaccine design framework might allow rapid deployment of effective phage-based vaccines against any emerging pathogen in the future.", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.19.427355", + "rel_abs": "Two SARS-CoV-2 variants showing increased transmissibility relative to the Wuhan virus have recently been identified. Although neither variant causes more severe illness or increased risk of death, the faster spread of the virus is a major threat. Using computational tools, we found that the new SARS-CoV-2 variants may acquire an increased transmissibility by increasing the propensity of its spike protein to expose the receptor binding domain. This information leads to the identification of potential treatments to avert the imminent threat of these more transmittable SARS-CoV-2 variants.\n\nTeaserThe more infective SARS-CoV-2 variants may expose its Achilles Heel - an opportunity to reduce their spreading.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Venigalla B Rao", - "author_inst": "The Catholic University of America" - }, - { - "author_name": "Jingen Zhu", - "author_inst": "The Catholic University of America" - }, - { - "author_name": "Neeti Ananthaswamy", - "author_inst": "The Catholic University of America" - }, - { - "author_name": "Swati Jain", - "author_inst": "The Catholic University of America" - }, - { - "author_name": "Himanshu Batra", - "author_inst": "The Catholic University of America" - }, - { - "author_name": "Wei-Chun Tang", - "author_inst": "The Catholic University of America" - }, - { - "author_name": "Douglass A. Lewry", - "author_inst": "Virovax LLC" - }, - { - "author_name": "Michael L. Richards", - "author_inst": "Virovax LLC" - }, - { - "author_name": "Sunil A. David", - "author_inst": "Virovax LLC" - }, - { - "author_name": "Paul B Kilgore", - "author_inst": "University of Texas Medical Branch" + "author_name": "Benjamin R Kraemer", + "author_inst": "Stanford University" }, { - "author_name": "Jian Sha", - "author_inst": "University of Texas Medical Branch" + "author_name": "Daria Mochly-Rosen", + "author_inst": "Stanford University" }, { - "author_name": "Aleksandra Drelich", - "author_inst": "University of Texas Medical Branch" + "author_name": "Suman Pokhrel", + "author_inst": "Stanford University" }, { - "author_name": "Chien-Te Tseng", - "author_inst": "University of Texas Medical Branch" + "author_name": "Lucia Lee", + "author_inst": "Stanford University" }, { - "author_name": "Ashok K. Chopra", - "author_inst": "University of Texas Medical Branch" + "author_name": "Kate Samardzic", + "author_inst": "Stanford University" } ], "version": "1", - "license": "", + "license": "cc_by_nd", "type": "new results", - "category": "microbiology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2021.01.19.426622", @@ -953119,127 +952379,31 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2021.01.19.427194", - "rel_title": "BRD2 inhibition blocks SARS-CoV-2 infection in vitro by reducing transcription of the host cell receptor ACE2", + "rel_doi": "10.1101/2021.01.18.427189", + "rel_title": "Sterically-Confined Rearrangements of SARS-CoV-2 Spike Protein Control Cell Invasion", "rel_date": "2021-01-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.19.427194", - "rel_abs": "SARS-CoV-2 infection of human cells is initiated by the binding of the viral Spike protein to its cell-surface receptor ACE2. We conducted a targeted CRISPRi screen to uncover druggable pathways controlling Spike protein binding to human cells. We found that the protein BRD2 is required for ACE2 transcription in human lung epithelial cells and cardiomyocytes, and BRD2 inhibitors currently evaluated in clinical trials potently block endogenous ACE2 expression and SARS-CoV-2 infection of human cells, including those of human nasal epithelia. Moreover, pharmacological BRD2 inhibition with the drug ABBV-744 inhibited SARS-CoV-2 replication in Syrian hamsters. We also found that BRD2 controls transcription of several other genes induced upon SARS-CoV-2 infection, including the interferon response, which in turn regulates the antiviral response. Together, our results pinpoint BRD2 as a potent and essential regulator of the host response to SARS-CoV-2 infection and highlight the potential of BRD2 as a novel therapeutic target for COVID-19.", - "rel_num_authors": 27, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.18.427189", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly contagious, and transmission involves a series of processes that may be targeted by vaccines and therapeutics. During transmission, host cell invasion is controlled by a large-scale conformational change of the Spike protein. This conformational rearrangement leads to membrane fusion, which creates transmembrane pores through which the viral genome is passed to the host. During Spike-protein-mediated fusion, the fusion peptides must be released from the core of the protein and associate with the host membrane. Interestingly, the Spike protein possesses many post-translational modifications, in the form of branched glycans that flank the surface of the assembly. Despite the large number of glycosylation sites, until now, the specific role of glycans during cell invasion has been unclear. Here, we propose that glycosylation is needed to provide sufficient time for the fusion peptides to reach the host membrane, otherwise the viral particle would fail to enter the host. To understand this process, an all-atom model with simplified energetics was used to perform thousands of simulations in which the protein transitions between the prefusion and postfusion conformations. These simulations indicate that the steric composition of the glycans induces a pause during the Spike protein conformational change. We additionally show that this glycan-induced delay provides a critical opportunity for the fusion peptides to capture the host cell. This previously-unrecognized role of glycans reveals how the glycosylation state can regulate infectivity of this pervasive pathogen.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Avi J Samelson", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Quang Dinh Tran", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Remy Robinot", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Lucia Carrau", - "author_inst": "Icahn School of Medicine" - }, - { - "author_name": "Veronica V Rezelj", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Alice Mac Kain", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Merissa Chen", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Gokul N Ramadoss", - "author_inst": "Gladstone Institutes" - }, - { - "author_name": "Xiaoyan Guo", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Shion A Lim", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Irene Lui", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "James Nunez", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Sarah J Rockwood", - "author_inst": "Gladstone Institutes" - }, - { - "author_name": "Jianhui Wang", - "author_inst": "Southern University of Science and Technology" - }, - { - "author_name": "Na Liu", - "author_inst": "Southern University of Science and Technology" - }, - { - "author_name": "Jared Carlson-Stevermer", - "author_inst": "Synthego Corporation" - }, - { - "author_name": "Jennifer Oki", - "author_inst": "Synthego Corporation" - }, - { - "author_name": "Travis Maures", - "author_inst": "Synthego Corporation" - }, - { - "author_name": "Kevin Holden", - "author_inst": "Synthego Corporation" - }, - { - "author_name": "Jonathan S Weissman", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "James A Wells", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Bruce Conklin", - "author_inst": "Gladstone Institutes" - }, - { - "author_name": "Benjamin R TenOever", - "author_inst": "Icahn School of Medicine" - }, - { - "author_name": "Lisa A Chakrabarti", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Marco Vignuzzi", - "author_inst": "Institut Pasteur" + "author_name": "Esteban Dodero Rojas", + "author_inst": "Rice University" }, { - "author_name": "Ruilin Tian", - "author_inst": "University of California, San Francisco" + "author_name": "Jose Nelson Onuchic", + "author_inst": "Rice University" }, { - "author_name": "Martin Kampmann", - "author_inst": "University of California, San Francisco" + "author_name": "Paul Whitford", + "author_inst": "Northeastern University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "cell biology" + "category": "biophysics" }, { "rel_doi": "10.1101/2021.01.19.427282", @@ -955733,16 +954897,49 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.01.13.21249598", - "rel_title": "Implementing Essential Coaching for Every Mother during COVID-19: A Pilot Pre-Post Intervention Study", + "rel_doi": "10.1101/2021.01.15.21249843", + "rel_title": "Sterilization of disposable face masks with respect to COVID-19 shortages; a nationwide field study including 19 sterilisation departments", "rel_date": "2021-01-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.13.21249598", - "rel_abs": "ObjectivesThe primary objective was to evaluate the preliminary impact of Essential Coaching for Every Mother on self-efficacy, social support, postpartum anxiety and postpartum depression. The second objective was to explore the acceptability of the Essential Coaching for Every Mother program provided during the COVID-19 pandemic.\n\nMethodsA prospective pre-post study was conducted with first time mothers in Nova Scotia, Canada between July 15th and September 19th, 2020. Participants completed a self-report survey at enrolment (after birth) and six-weeks postpartum. Various standardized measures were used and qualitative feedback on the program was also collected. Paired t-tests were carried out to determine changes from baseline to follow-up on psychosocial outcomes and qualitative feedback was analysed through thematic analysis.\n\nResultsA total of 88 women enrolled. Self-efficacy increased between baseline (B) and follow-up (F) (B:33.33; F:37.11, p=0.000) while anxiety (STAI) declined (B:38.49; F:34.79; p=0.004). In terms of acceptability, 89% of participants felt that the number of messages were just right, 84.5% felt the messages contained all the information they needed relative to caring for a newborn and 98.8% indicated they would recommend this program to other new mothers.\n\nConclusionEssential Coaching for Every Mother may play a role in increasing maternal self-efficacy and decreasing anxiety, although future work with a control group is needed to delineate the true effects of the program. Overall, mothers were satisfied with the Essential Coaching for Every Mother program and would recommend it for other mothers, during COVID-19 and beyond.", - "rel_num_authors": 0, - "rel_authors": null, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.15.21249843", + "rel_abs": "ObjectiveFace masks also referred to as half masks are essential to protect healthcare professionals, working in close contact with patients having Covid-19 related symptoms. During the threating deficit, healthcare institutions sought an approach to re-use face masks or to acquire imported masks. The objective of this study is to assess the quality of sterilised and imported FFP2/KN95 face mask materials.\n\nDesignprospective, bench-to-bedside\n\nSettingGeneral healthcare including 19 hospitals in the Netherlands\n\nInterventionsFace masks were reprocessed using a medical autoclave at 121{degrees}C.\n\nMethodsA 48 minutes steam sterilization process of single-use face masks with 15 min holding time at a 121 {degrees}C was developed, validated and implemented in 19 different hospitals. Steam and H2O2 plasma sterilized as well as new, imported masks are tested in a custom-made, non-standard EN-149, test set-up that measures Particle Filtration Efficiency (PFE) and pressure drops.\n\nResultsPFE validation data of 84 masks indicated differences of 2.3{+/-}2 % (mean{+/-}SD) between the custom build test set-up and a continues flow according to the EN-149. Test data showed the mean PFE values of 444 sterilised FFP2 face masks from 19 CSSD were 90{+/-}11% (mean{+/-}SD) and of 474 imported KN95/FFP2 face masks 83{+/-}16% (mean{+/-}SD). Differences in PFE between sterilisation departments were found.\n\nConclusionFace masks can be reprocessed with 121 0 C steam or H2O2 plasma sterilization with minimum reduction of PFE. PFE comparison between sterilised mask and new, imported mask filter material indicates that most reprocessed masks of high quality brands outperform new imported face masks of unknown brands. Although the PFE of tested face mask material from different sterilisation departments remained efficient, different types of sterilisation equipment can result in different PFE outcomes.\n\nStrengths and limitations of this study- Reprocessing face masks at 121 {degrees}C steam Sterilization, a simple method to be used by hospitals in times of shortages\n- Laboratory findings to evaluate the safety and quality of face mask material\n- The study is limited and restricted to selected FFP-2 face masks\n- This study is a first of its kind in quality and safety check of the vast growing face masks, entering our markets\n- The study focusses on testing environmental dry particles in a rapid test setup", + "rel_num_authors": 8, + "rel_authors": [ + { + "author_name": "Bart van Straten", + "author_inst": "Delft University of technology" + }, + { + "author_name": "Daniel Robertson", + "author_inst": "Delft University of Technology" + }, + { + "author_name": "Harry Oussoren", + "author_inst": "Amsterdam University Medical Center" + }, + { + "author_name": "Sue Ellen Pereira Espindola", + "author_inst": "Delft University of technology" + }, + { + "author_name": "Elmira Ghanbari", + "author_inst": "Delft University of Technology" + }, + { + "author_name": "Jenny Dankelman", + "author_inst": "Delft University of Technology" + }, + { + "author_name": "Stephen Picken", + "author_inst": "Delft University of Technology" + }, + { + "author_name": "Tim Horeman", + "author_inst": "Delft University of Technology" + } + ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -957642,41 +956839,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.12.21249613", - "rel_title": "Genomic surveillance at scale is required to detect newly emerging strains at an early timepoint", + "rel_doi": "10.1101/2021.01.12.21249708", + "rel_title": "Impact of COVID-19 shelter-in-place order on transmission of gastrointestinal pathogens in Northern California", "rel_date": "2021-01-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.12.21249613", - "rel_abs": "Genomic surveillance in the setting of the coronavirus disease 2019 (COVID-19) pandemic has the potential to identify emerging SARS-CoV-2 strains that may be more transmissible, virulent, evade detection by standard diagnostic tests, or vaccine escapes. The rapid spread of the SARS-CoV-2 B.1.1.7 strain from southern England to other parts of the country and globe is a clear example of the impact of such strains. Early discovery of the B.1.1.7 strain was enabled through the proactive COVID-19 Genomics UK (COG-UK) program and the UKs commitment to genomic surveillance, sequencing about 10% of positive samples.1 In order to enact more aggressive public health measures to minimize the spread of such strains, genomic surveillance needs to be of sufficient scale to detect early emergence and expansion in the broader virus population. By modeling common performance characteristics of available diagnostic and sequencing tests, we developed a model that assesses the sampling required to detect emerging strains when they are less than 1% of all strains in a population. This model demonstrates that 5% sampling of all positive tests allows the detection of emerging strains when they are a prevalence of 0.1% to 1.0%. While each country will determine their risk tolerance for the emergence of novel strains, as vaccines are distributed and we work to end the pandemic and prevent future SARS-CoV-2 outbreaks, genomic surveillance will be an integral part of success.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.12.21249708", + "rel_abs": "Society-wide cessation of human interaction outside the household due to the COVID-19 shelter-in-place created a unique opportunity in modern history to reexamine the transmission of communicable gastrointestinal pathogens. We conducted a quasi-experimental study from January 1, 2018 to Sept 30, 2020 to investigate the effect of Californias COVID-19 shelter-in-place order on the community transmission of viral, bacterial, and parasitic gastrointestinal pathogens detected with the FilmArray GI Panel (BioFire Diagnostics, Salt Lake City, UT). The incidence of viral causes of gastroenteritis, enteroaggregative/enteropathogenic/enterotoxigenic Escherichia coli, Shigella, and Cyclospora cayetanensis decreased sharply after shelter-in place took effsect, whilst Salmonella, Campylobacter, shiga toxin-producing E. coli (O157 and non-O157) and other bacterial and parasitic causes of gastroenteritis were largely unaffected. Findings suggest community spread of viral gastroenteritis, pathogenic E. coli (except for shiga toxin-producing E. coli), Shigella, and Cyclospora is more susceptible to changes associated with shelter-in-place than other gastrointestinal pathogens.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Darcy Vavrek", - "author_inst": "Illumina, Inc." - }, - { - "author_name": "Lucia Speroni", - "author_inst": "Illumina, Inc." + "author_name": "Philip L. Bulterys", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Kirsten J Curnow", - "author_inst": "Illumina, Inc." + "author_name": "Nicole Y Leung", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Michael Oberholzer", - "author_inst": "Illumina, Inc." + "author_name": "Atif Saleem", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Vanessa Moeder", - "author_inst": "Illumina, Inc." + "author_name": "Indre Budvytiene", + "author_inst": "Stanford University Medical Center" }, { - "author_name": "Phillip G Febbo", - "author_inst": "Illumina, Inc." + "author_name": "Niaz Banaei", + "author_inst": "Stanford University School of Medicine" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -959564,73 +958757,73 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.13.21249254", - "rel_title": "An optimized stepwise algorithm combining rapid antigen and RT-qPCR for screening of COVID-19 patients", + "rel_doi": "10.1101/2021.01.12.20249080", + "rel_title": "Early Analysis of a potential link between viral load and the N501Y mutation in the SARS-COV-2 spike protein", "rel_date": "2021-01-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.13.21249254", - "rel_abs": "BackgroundDiagnosing SARS CoV-2 infection with certainty is essential for appropriate case management. We investigated the combination of rapid antigen detection (RAD) and RT-qPCR assays in a stepwise procedure to optimize the detection of COVID-19.\n\nMethodsFrom August 2020 to November 2020, 43,399 patients were screened in our laboratory for COVID-19 diagnostic by RT-qPCR using nasopharyngeal swab. Overall, 4,691 of the 43,399 were found to be positive, and 200 were retrieved for RAD testing allowing comparison of diagnostic accuracy between RAD and RT-qPCR. Cycle threshold (Ct) and time from symptoms onset (TSO) were included as covariates.\n\nResultsThe overall sensitivity, specificity, PPV, NPV, LR-, and LR+ of RAD compared with RT- qPCR were 72% (95%CI 62%-81%), 99% (95% CI95%-100%), 99% (95%CI 93%-100%), and 78% (95%CI 70%-85%), 0.28 (95%CI 0.21-0.39), and 72 (95%CI 10-208) respectively. Sensitivity was higher for patients with Ct [≤] 25 regardless of TSO: TSO [≤] 4 days 92% (95%CI 75%-99%), TSO > 4 days 100% (95%CI 54%-100%), and asymptomatic 100% (95%CI 78-100%). Overall, combining RAD and RT-qPCR would allow reducing from only 4% the number of RT-qPCR needed.\n\nConclusionThis study highlights the risk of misdiagnosing COVID-19 in 28% of patients if RAD is used alone. Thus, negative results from RAD needs to be confirmed by RT-qPCR prior to making treatment decisions. A stepwise analysis that combines RAD and RT-qPCR would be an efficient screening procedure for COVID-19 detection and may facilitate the control of the outbreak.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.12.20249080", + "rel_abs": "A new variant of SARS-CoV-2 has emerged which is increasing in frequency, primarily in the South East of England (lineage B.1.1.7 (1); VUI-202012/01). One potential hypothesis is that infection with the new variant results in higher viral loads, which in turn may make the virus more transmissible. We found higher (sequence derived) viral loads in samples from individuals infected with the new variant with median inferred viral loads were three-fold higher in individuals with the new variant. Most of the new variants were sampled in Kent and Greater London. We observed higher viral loads in Kent compared to Greater London for both the new variant and other circulating lineages. Outside Greater London, the variant has higher viral loads, whereas within Greater London, the new variant does not have significantly higher viral loads compared to other circulating lineages. Higher variant viral loads outside Greater London could be due to demographic effects, such as a faster variant growth rate compared to other lineages or concentration in particular age-groups. However, our analysis does not exclude a causal link between infection with the new variant and higher viral loads. This is a preliminary analysis and further work is needed to investigate any potential causal link between infection with this new variant and higher viral loads, and whether this results in higher transmissibility, severity of infection, or affects relative rates of symptomatic and asymptomatic infection\n\nDocument Description and PurposeThis is an updated report submitted to NERVTAG in December 2020 as part of urgent investigations into the new variant of SARS-COV-2 (VUI-202012/01). It makes full use of (and is restricted to) all sequence data and associated metadata available to us at the time this original report was submitted and remains provisional. Under normal circumstances more genomes and metadata would be obtained and included before making this report public. We will update this preprint when more genomes and metadata are available and before submitting for peer review.", "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Philippe HALFON", - "author_inst": "Laboratoire ALPHABIO" + "author_name": "Tanya Golubchik", + "author_inst": "University of Oxford" }, { - "author_name": "Guillaume PENARANDA", - "author_inst": "Laboratoire ALPHABIO" + "author_name": "Katrina A Lythgoe", + "author_inst": "University of Oxford" }, { - "author_name": "Hacene KHIRI", - "author_inst": "Laboratoire ALPHABIO" + "author_name": "Matthew D Hall", + "author_inst": "University of Oxford" }, { - "author_name": "Vincent GARCIA", - "author_inst": "Laboratoire ALPHABIO" + "author_name": "Luca Ferretti", + "author_inst": "University of Oxford" }, { - "author_name": "Hortense DROUET", - "author_inst": "Hopital Europeen, Marseille" + "author_name": "Helen R Fryer", + "author_inst": "University of Oxford" }, { - "author_name": "Patrick PHILIBERT", - "author_inst": "Hopital Europeen, Marseille" + "author_name": "George MacInyre-Cockett", + "author_inst": "University of Oxford" }, { - "author_name": "Christina PSOMAS", - "author_inst": "Hopital Europeen, Marseille" + "author_name": "Mariateresa de Cesare", + "author_inst": "University of Oxford" }, { - "author_name": "Marion DELORD", - "author_inst": "Hopital Europeen, Marseille" + "author_name": "Amy Trebes", + "author_inst": "University of Oxford" }, { - "author_name": "Julie ALLEMAND-SOURRIEU", - "author_inst": "Hopital Europeen, Marseille" + "author_name": "Paolo Piazza", + "author_inst": "University of Oxford" }, { - "author_name": "Frederique RETORNAZ", - "author_inst": "Hopital Europeen, Marseille" + "author_name": "David Buck", + "author_inst": "University of Oxford" }, { - "author_name": "Caroline CHARPIN", - "author_inst": "Hopital Europeen, Marseille" + "author_name": "John A Todd", + "author_inst": "University of Oxford" }, { - "author_name": "Thomas Gonzales", - "author_inst": "Hopital Europeen, Marseille" + "author_name": "- The COVID-19 Genomics UK (COG-UK) consortium", + "author_inst": "The COVID-19 Genomics UK (COG-UK) consortium" }, { - "author_name": "Herve PEGLIASCO", - "author_inst": "Hopital Europeen, Marseille" + "author_name": "Christophe Fraser", + "author_inst": "University of Oxford" }, { - "author_name": "Jerome ALLARDET-SERVENT", - "author_inst": "Hopital Europeen, Marseille" + "author_name": "David Bonsall", + "author_inst": "University of Oxford" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -961542,53 +960735,29 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2021.01.11.21249610", - "rel_title": "National interest may require distributing COVID-19 vaccines to other countries", + "rel_doi": "10.1101/2021.01.11.21249612", + "rel_title": "The feasibility of targeted test-trace-isolate for the control of B.1.1.7", "rel_date": "2021-01-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.11.21249610", - "rel_abs": "As the clinical trials for COVID-19 vaccine progress, understanding how to distribute the initially scarce doses is of paramount importance and a quantitative analysis of the trade-offs involved in domestic-only versus cooperative distribution is still missing. In this study we use a network Susceptible-Infected-Removed (SIR) model to show under which circumstances it is in a countrys self-interest to ensure other countries can also obtain a COVID-19 vaccine rather than focusing only on vaccination of their own residents. In particular, we focus our analysis on the USs decision and estimate the internal burden of COVID-19 disease under different scenarios about vaccine cooperation. We show that in scenarios in which the US has reached the threshold for domestic herd immunity, the US may find it optimal to donate doses to other countries with lower vaccination coverage, as this would allow for a sharp reduction in the inflow of infected individuals from abroad.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.11.21249612", + "rel_abs": "The SARS-CoV-2 variant B.1.1.7 reportedly exhibits substantially higher transmission than the ancestral strain and may generate a major surge of cases before vaccines become widely available, while the P.1 and B.1.351 variants may be equally transmissible and also resist vaccines. All three variants can be sensitively detected by RT-PCR due to an otherwise rare del11288-11296 mutation in orf1ab; B.1.1.7 can also be detected using the common TaqPath kit. Testing, contact tracing, and isolation programs overwhelmed by SARS-CoV-2 could slow the spread of the new variants, which are still outnumbered by tracers in most countries. However, past failures and high rates of mistrust may lead health agencies to conclude that tracing is futile, dissuading them from redirecting existing tracers to focus on the new variants. Here we apply a branching-process model to estimate the effectiveness of implementing a variant-focused testing, contact tracing, and isolation strategy with realistic levels of performance. Our model indicates that bidirectional contact tracing can substantially slow the spread of SARS-CoV-2 variants even in regions where a large fraction of the population refuses to cooperate with contact tracers or to abide by quarantine and isolation requests.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Tiziano Rotesi", - "author_inst": "University of Lausanne" - }, - { - "author_name": "Paolo Pin", - "author_inst": "University of Siena" - }, - { - "author_name": "Maria Cucciniello", - "author_inst": "University of Edinburgh Business School" - }, - { - "author_name": "Amyn A. Malik", - "author_inst": "Yale Institute for Global Health" - }, - { - "author_name": "Elliott E. Paintsil", - "author_inst": "Yale Institute for Global Health" + "author_name": "William J Bradshaw", + "author_inst": "Max Planck Institute for the Biology of Ageing" }, { - "author_name": "Scott E. Bokemper", - "author_inst": "Yale University" - }, - { - "author_name": "Kathryn Willebrand", - "author_inst": "Yale Institute fior Global Health" - }, - { - "author_name": "Gregory A. Huber", - "author_inst": "Yale University" + "author_name": "Jonathan H Huggins", + "author_inst": "Boston University" }, { - "author_name": "Alessia Melegaro", - "author_inst": "Bocconi University" + "author_name": "Alun L Lloyd", + "author_inst": "North Carolina State University" }, { - "author_name": "Saad B. Omer", - "author_inst": "Yale Institute for Global Health" + "author_name": "Kevin M Esvelt", + "author_inst": "Massachusetts Institute of Technology" } ], "version": "1", @@ -963276,55 +962445,35 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2021.01.13.426537", - "rel_title": "Targeting conserved viral virulence determinants by single domain antibodies to block SARS-CoV2 infectivity", + "rel_doi": "10.1101/2021.01.11.426295", + "rel_title": "In vitro screening of anti-viral and virucidal effects against SARS-CoV-2 by Hypericum perforatum and Echinacea.", "rel_date": "2021-01-13", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.13.426537", - "rel_abs": "We selected SARS-CoV2 specific single domain antibodies (sdAbs) from a previously constructed phage display library using synthetic immunogenic peptides of the virus spike (S) protein as bait. The sdAbs targeting the cleavage site (CS) and the receptor binding domain (RBD) in S protein efficiently neutralised the infectivity of a pseudovirus expressing SARS-CoV2 S protein. Anti-CS sdAb blocked the virus infectivity by inhibiting proteolytic processing of SARS-CoV2 S protein. Both the sdAbs retained characteristic structure within the pH range of 2 to 12 and remained stable upto 65{degrees}C. Furthermore, structural disruptions induced by a high temperature in both the sdAbs were largely reversed upon their gradual cooling and the resulting products neutralised the reporter virus. Our results therefore suggest that targeting CS in addition to the RBD of S protein by sdAbs could serve as a viable option to reduce SARS-CoV2 infectivity and that proteolytic processing of the viral S protein is critical for infection.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.11.426295", + "rel_abs": "Special Infectious Agent Unit in King Fahd Medical Research Center at King Abdulaziz University, Jeddah, Saudi Arabia, has pursed the anti-viral project field to optimize the group of medicinal plants for human-infectious diseases. We have begun virtually in this field since COVID-19 pandemic, besides our divergence in the infectious agents. In this study and based on the previous review, Hypericum perforatum (St. Johns Wort) and Echinacea (gaia HERBS(R)) were tested in vitro using Vero E6 cells for their anti-viral effects against the newly identified Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) through its infectious cycle from 0 to 48 hours post infection. The hypericin (0.9 mg) of H. perforatum and the different parts (roots, seeds, aerial) of two types of Echinacea species (Echinacea purpurea and Echinacea angustifolia) were examined their efficacy in certain concentration and under light-dependent anti-viral activities to measure the inhibition of the SARS-CoV-2 mRNA expression of RNA-dependent RNA polymerase (RdRP) gene and the viral load with quantitative real-time polymerase chain reaction (qRT-PCR), and to assess the neutralization of the SARS-CoV-2 spike receptor binding on cell culture assay. Interestingly, the mixture (H.E.) of 100 mg/mL of H. perforatum and Echinacea was tested too on SARS-CoV-2 and showed crucial anti-viral activity competing H. perforatum then Echinacea effects as anti-viral treatment. Therefore, the results of gaia HERBS(R) products, H. perforatum and Echinacea species, applied in this study showed significant anti-viral and virucidal effects in the following order of potency: H. perforatum, H.E., and Echinacea on SARS-CoV-2 infectious cycle; and will definitely required a set up of clinical trial with specific therapeutic protocol based on the outcome of this study.\n\nAuthor SummaryAfter an outbreak of Rift Valley Fever in the Southern region of Saudi Arabia, particularly in May 2003, Special Infectious Agents Unit (SIAU) was established and founded by Prof. Esam Ibraheem Azhar. This unit contains a full range of facilities including Biosafety Level 3, allows him and his research groups to ambulate and culture risk group 3 viruses in Saudi Arabia & Gulf States for the first time. Since that time, SIAU and our international collaboration have been extended to implement a standard protocols in the infectious agents diagnostics procedure through different mode of collaboration including exchange of expertise, joint research program and more recently a technology transfer agreements with number of international institute sharing same interests. Furthermore, we have been engaged in number of researches related to Hajj & Umrah plus number of national services with the Ministry of Health (MOH) through which, we utilize our Mobile biosafety level 3 Lab to enhance the diagnostics of MERS CoV in the Holly sites during Hajj since 2014.\n\nIn our SIAU and with a powerful team, we have excellent researches made valuable contributions through in vivo and in vitro animal and human studies, and several human viral pathogens which are a threat to global health security due to millions of pilgrims visiting Saudi Arabia every year from 182 countries: with particular areas of interests in: Alkhurma Viral Hemorrhagic Fever, Dengue Hemorrhagic Fever Viruses, Rift Valley Fever Virus, MERS-CoV and more recently the new global infectious diseases threat, Sever Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2).", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Sudhakar Singh", - "author_inst": "IISER Mohali" - }, - { - "author_name": "Surbhi Dahiya", - "author_inst": "IISER Mohali" - }, - { - "author_name": "Yuviana J Singh", - "author_inst": "IISER Mohali" - }, - { - "author_name": "Komal Beeton", - "author_inst": "IISER Mohali" - }, - { - "author_name": "Ayush Jain", - "author_inst": "IISER Mohali" - }, - { - "author_name": "Roman Sarkar", - "author_inst": "IISER Mohali" + "author_name": "Leena Hussein Bajrai", + "author_inst": "King Abdulaziz University" }, { - "author_name": "Abhishek Dubey", - "author_inst": "IISER Mohali" + "author_name": "Sherif Ali El-kafrawy", + "author_inst": "King Abdulaziz University" }, { - "author_name": "Syed Azeez Tehseen", - "author_inst": "IISER Mohali" + "author_name": "Rabie Saleh Alnahas", + "author_inst": "King Abdulaziz University" }, { - "author_name": "Sharvan Sehrawat", - "author_inst": "Indian Institute of Science Education and Research Mohali" + "author_name": "Esam Ibraheem Azhar", + "author_inst": "King Abdulaziz University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.01.09.21249489", @@ -964858,99 +964007,111 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.01.10.21249532", - "rel_title": "Effectiveness of regional restrictions in reducing SARS-CoV-2 transmission during the second wave of COVID-19, Italy.", + "rel_doi": "10.1101/2021.01.10.21249333", + "rel_title": "Proteomic and Metabolomic Investigation of COVID-19 Patients with Elevated Serum Lactate Dehydrogenase", "rel_date": "2021-01-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.10.21249532", - "rel_abs": "To counter the second COVID-19 wave in autumn 2020, the Italian government introduced a system of physical distancing measures organized in progressively restrictive tiers (coded as yellow, orange, and red) and imposed on a regional basis according to epidemiological risk assessments. The individuals attendance to locations outside the residential settings was progressively reduced with tiers, but less than during the national lockdown against the first COVID-19 wave in the spring. The reproduction number Rt decreased below the epidemic threshold in 85 out of 107 provinces after the introduction of the tier system, reaching average values of about 0.99, 0.89 and 0.77 in the yellow, orange and red tier, respectively. We estimate that the reduced transmissibility resulted in averting about 37% of the hospitalizations between November 5 and November 25, 2020. These results are instrumental to inform public health efforts aimed at preventing future resurgence of cases.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.10.21249333", + "rel_abs": "Serum lactate dehydrogenase (LDH) has been established as a prognostic indicator given its differential expression in COVID-19 patients. However, the molecular mechanisms underneath remain poorly understood. In this study, 144 COVID-19 patients were enrolled to monitor the clinical and laboratory parameters over three weeks. Serum lactate dehydrogenase (LDH) was shown elevated in the COVID-19 patients on admission and declined throughout disease course, and its ability to classify patient severity outperformed other biochemical indicators. A threshold of 247 U/L serum LDH on admission was determined for severity prognosis. Next, we classified a subset of 14 patients into high- and low-risk groups based on serum LDH expression and compared their quantitative serum proteomic and metabolomic differences. The results found COVID-19 patients with high serum LDH exhibited differentially expressed blood coagulation and immune responses including acute inflammatory responses, platelet degranulation, complement cascade, as well as multiple different metabolic responses including lipid metabolism, protein ubiquitination and pyruvate fermentation. Specifically, activation of hypoxia responses was highlighted in patients with high LDH expressions. Taken together, our data showed that serum LDH levels are associated COVID-19 severity, and that elevated serum LDH might be consequences of hypoxia and tissue injuries induced by inflammation.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Mattia Manica", - "author_inst": "Fondazione Bruno Kessler" + "author_name": "Haixi Yan", + "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" }, { - "author_name": "Giorgio Guzzetta", - "author_inst": "Fondazione Bruno Kessler" + "author_name": "Xiao Liang", + "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University" }, { - "author_name": "Flavia Riccardo", - "author_inst": "Istituto Superiore di Sanita'" + "author_name": "Juping Du", + "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" }, { - "author_name": "Antonio Valenti", - "author_inst": "Italian Workers Compensation Authority (INAIL)" + "author_name": "Zebao He", + "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" }, { - "author_name": "Piero Poletti", - "author_inst": "Fondazione Bruno Kessler" + "author_name": "Yu Wang", + "author_inst": "Hongqiao International Institute of Medicine, Shanghai Tongren Hospital and Faculty of Public Health, Shanghai Jiao Tong University School of Medicine" }, { - "author_name": "Valentina Marziano", - "author_inst": "Fondazione Bruno Kessler" + "author_name": "Mengge Lyu", + "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University" }, { - "author_name": "Filippo Trentini", - "author_inst": "Fondazione Bruno Kessler" + "author_name": "Liang Yue", + "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University" }, { - "author_name": "Xanthi Andrianou", - "author_inst": "Istituto Superiore di Sanita'" + "author_name": "Fangfei Zhang", + "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University" }, { - "author_name": "Alberto Mateo Urdiales", - "author_inst": "Istituto Superiore di Sanita'" + "author_name": "Zhangzhi Xue", + "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University" }, { - "author_name": "Martina Del Manso", - "author_inst": "Istituto Superiore di Sanita'" + "author_name": "Luang Xu", + "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University" }, { - "author_name": "Massimo Fabiani", - "author_inst": "Istituto Superiore di Sanita'" + "author_name": "Guan Ruan", + "author_inst": "Westlake Omics (Hangzhou) Biotechnology Co., Ltd. No.1" }, { - "author_name": "Maria Fenicia Vescio", - "author_inst": "Istituto Superiore di Sanita'" + "author_name": "Jun Li", + "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" }, { - "author_name": "Matteo Spuri", - "author_inst": "Istituto Superiore di Sanita'" + "author_name": "Hongguo Zhu", + "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" }, { - "author_name": "Daniele Petrone", - "author_inst": "Istituto Superiore di Sanita'" + "author_name": "Jiaqin Xu", + "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" }, { - "author_name": "Antonino Bella", - "author_inst": "Istituto Superiore di Sanita'" + "author_name": "Shiyong Chen", + "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" }, { - "author_name": "Sergio Iavicoli", - "author_inst": "Italian Workers Compensation Authority (INAIL)" + "author_name": "Chao Zhang", + "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" }, { - "author_name": "Marco Ajelli", - "author_inst": "Indiana University School of Public Health" + "author_name": "Dongqing Lv", + "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" }, { - "author_name": "Silvio Brusaferro", - "author_inst": "Istituto Superiore di Sanita'" + "author_name": "Zongmei Lin", + "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" }, { - "author_name": "Patrizio Pezzotti", - "author_inst": "Istituto Superiore di Sanita'" + "author_name": "Bo Shen", + "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" }, { - "author_name": "Stefano Merler", - "author_inst": "Fondazione Bruno Kessler" + "author_name": "Yi Zhu", + "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University" + }, + { + "author_name": "Biyun Qian", + "author_inst": "Hongqiao International Institute of Medicine, Shanghai Tongren Hospital and Faculty of Public Health, Shanghai Jiao Tong University School of Medicine" + }, + { + "author_name": "Haixiao Chen", + "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University" + }, + { + "author_name": "Tiannan Guo", + "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2021.01.10.21249548", @@ -967224,35 +966385,27 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.01.08.21249468", - "rel_title": "Women in Health Care Experiencing Occupational Stress and Burnout during COVID-19: A Review", + "rel_doi": "10.1101/2021.01.08.21249474", + "rel_title": "Deep learning-based detection of COVID-19 using wearables data", "rel_date": "2021-01-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.08.21249468", - "rel_abs": "ContextCOVID-19 has had an unprecedent impact on physicians, nurses, and other health professionals around the world, and a serious health care burnout crisis is emerging as a result of this pandemic.\n\nObjectivesWe aim to identify the causes of occupational stress and burnout in women in medicine, nursing, and other health professions during the COVID-19 pandemic and interventions that can support female health professionals deal with this crisis through a rapid review.\n\nMethodsWe searched MEDLINE, Embase, CINAHL, PsycINFO, and ERIC from December 2019 through September 30, 2020. The review protocol was registered in PROSPERO and is available online. We selected all empirical studies that discussed stress and burnout in women health care workers during the COVID-19 pandemic.\n\nResultsThe literature search identified 6148 citations. A review of abstracts led to the retrieval of 721 full-text articles for assessment, of which 47 articles were included for review. Our findings show that concerns of safety (65%), staff and resource adequacy (43%), workload and compensation (37%), job roles and security (41%) appeared as common triggers of stress in the literature.\n\nConclusions and RelevanceThe current literature primarily focuses on self-focused initiatives such as wellness activities, coping strategies, reliance of family, friends and work colleagues to organizational led initiatives such as access to psychological support and training. Very limited evidence exists about the organizational interventions such as work modification, financial security, and systems improvement.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.08.21249474", + "rel_abs": "BackgroundCOVID-19 is an infectious disease caused by SARS-CoV-2 that is primarily diagnosed using laboratory tests, which are frequently not administered until after symptom onset. However, SARS-CoV-2 is contagious multiple days before symptom onset and diagnosis, thus enhancing its transmission through the population.\n\nMethodsIn this retrospective study, we collected 15 seconds to one-minute heart rate and steps interval data from Fitbit devices during the COVID-19 period (February 2020 until June 2020). Resting heart rate was computed by selecting the heart rate intervals where steps were zero for 12 minutes ahead of an interrogated time point. Data for each participant was divided into train or baseline by taking the days before the non-infectious period and test data by taking the days during the COVID-19 infectious period. Data augmentation was used to increase the size of the training days. Here, we developed a deep learning approach based on a Long Short-Term Memory Networks-based autoencoder, called LAAD, to predict COVID-19 infection by detecting abnormal resting heart rate in test data relative to the users baseline.\n\nFindingsWe detected an abnormal resting heart rate during the period of viral infection (7 days before the symptom onset and 21 days after) in 92% (23 out of 25 cases) of patients with laboratory-confirmed COVID-19. In 56% (14) of cases, LAAD detection identified cases in their pre-symptomatic phase whereas 36% (9 cases) were detected after the onset of symptoms with an average precision score of 0{middle dot}91 (SD 0{middle dot}13, 95% CI 0{middle dot}854-0{middle dot}967), a recall score of 0{middle dot}36 (0{middle dot}295, 0{middle dot}232-0{middle dot}487), and a F-beta score of 0{middle dot}79 (0{middle dot}226, 0{middle dot}693-0{middle dot}888). In COVID-19 positive patients, abnormal RHR patterns start 5 days before symptom onset (6{middle dot}9 days in pre-symptomatic cases and 1{middle dot}9 days later in post-symptomatic cases). COVID-19+ patients have longer abnormal resting heart rate periods (89 hours or 3{middle dot}7 days) as compared to healthy individuals (25 hours or 1{middle dot}1 days).\n\nInterpretationThese findings show that deep learning neural networks and wearables data are an effective method for the early detection of COVID-19 infection. Additional validation data will help guide the use of this and similar techniques in real-world infection surveillance and isolation policies to reduce transmission and end the pandemic.\n\nFundingThis work was supported by NIH grants and gifts from the Flu Lab, as well as departmental funding from the Stanford Genetics department. The Google Cloud Platform costs were covered by Google for Education academic research and COVID-19 grant awards.\n\nResearch in contextO_ST_ABSEvidence before the studyC_ST_ABSCOVID-19 resulted in up to 1{middle dot}7 million deaths worldwide in 2020. COVID-19 detection using laboratory tests is usually performed after symptom onset. This delay can allow the spread of viral infection and can cause outbreaks. We searched PubMed, Google, and Google Scholar for research articles published in English up to Dec 1, 2020, using common search terms including \"COVID-19 and wearables\", \"Resting heart rate and viral infection\", \"Resting heart rate and COVID-19\", \"machine learning and COVID-19\" and \"deep-learning and COVID-19\". Previous studies have attempted to use an elevated resting heart rate as an indicator of viral infection. Although these studies have investigated the early prediction of COVID-19 using resting heart rate and other wearables data, studies to investigate a deep learning-based prediction model with performance evaluation metrics at the user level has not been reported.\n\nAdded value of this studyIn this study, we created a deep-learning system that used wearables data such as abnormal resting heart rate to predict COVID-19 before the symptom onset. The deep-learning system was created using retrospective time-series datasets collected from 25 COVID-19+ patients, 11 non-COVID-19, and 70 healthy individuals. To our knowledge, this is the first deep-learning model to identify an early viral infection using wearables data at the user level. This study also greatly extends our previous phase-1 study and factors unpredictable behavior and time-series nature of the data, limited data size, and lack of data labels to evaluate performance metrics. The use of a real-time version of this model using more data along with user feedback may help to scale early detection as the number of patients with COVID-19 continues to grow.\n\nImplications of all the available evidenceIn the future, wearable devices may provide high-resolution sleep, temperature, saturated oxygen, respiration rate, and electrocardiogram, which could be used to further characterize an individuals baseline and improve the deep-learning model performance for infectious disease detection. Using multi-sensor data with a real-time deep-learning model has the potential to alert individuals of illness prior to symptom onset and may greatly reduce the viral spread.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Abi Sriharan", - "author_inst": "University of Toronto" - }, - { - "author_name": "Savithiri Ratnapalan", - "author_inst": "Hospital for Sick Kids" - }, - { - "author_name": "Andrea C. Tricco", - "author_inst": "Li Ka Shing Research Institute, Knowledge Translation Program, St. Michael's Hospital" + "author_name": "Gireesh K Bogu", + "author_inst": "Stanford Unniversity" }, { - "author_name": "Doina Lupea", - "author_inst": "Ontario Medical Association" + "author_name": "Michael P Snyder", + "author_inst": "Stanford University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health systems and quality improvement" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.01.08.20249041", @@ -969046,89 +968199,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.07.21249406", - "rel_title": "High prevalence of long-term psychophysical olfactory dysfunction in patients with COVID-19", + "rel_doi": "10.1101/2021.01.08.21249426", + "rel_title": "Ultrasensitive RNA biosensors for SARS-CoV-2 detection in a simple color and luminescence assay", "rel_date": "2021-01-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.07.21249406", - "rel_abs": "This study prospectively assessed the long-term prevalence of self-reported and psychophysically measured olfactory dysfunction in subjects with mild-to-moderate COVID-19. Self-reported smell or taste impairment was prospectively evaluated by SNOT-22 at diagnosis, 4-week, 8-week, and 6-month. At 6 months from the diagnosis, psychophysical evaluation of olfactory function was also performed using the 34-item culturally adapted University of Pennsylvania Smell Identification Test (CA-UPSIT). 145 completed both the 6-month subjective and psychophysical olfactory evaluation. According to CA-UPSIT, 87 subjects (60.0%) exhibited some smell dysfunction, with 54 (37.2) being mildly microsmic, 16 (11.0%) moderately microsmic, 7 (4.8%) severely microsmic, and 10 patients (6.9%) being anosmic. At the time CA-UPSIT was administered, a weak correlation was observed between the self-reported alteration of sense of smell or taste and olfactory test scores (Spearmans r=-0.26). Among 112 patients who self-reported normal sense of smell at last follow-up, CA-UPSIT revealed normal smell in 46 (41.1%), mild microsmia in 46 (41.1%), moderate microsmia in 11 (9.8%), severe microsmia in 3 (2.3%), and anosmia in 6 (5.4%) patients; however, of those patients self-reporting normal smell but who were found to have hypofunction on testing, 62 out of 66 had self-reported reduction in sense of smell or taste at an earlier time point. Despite most patients report a subjectively normal sense of smell, we observed a high percentage of persistent smell dysfunction at 6 months from the diagnosis of SARS-CoV-2 infection, with 11.7% of patients being anosmic or severely microsmic. These data highlight a significant long-term rate of smell alteration in patients with previous SARS-CoV-2 infection.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.08.21249426", + "rel_abs": "The COVID-19 pandemic underlines the need for versatile diagnostic strategies. Here, we have designed and developed toehold RNA-based sensors for direct and ultrasensitive SARS-CoV-2 RNA detection. In our assay, isothermal amplification of a fragment of SARS-CoV-2 RNA coupled with activation of our biosensors leads to a conformational switch in the sensor. This leads to translation of a reporter-protein e.g. LacZ or Nano-lantern that is easily detected using color/luminescence. This response can be visualized by the human eye, or a simple cell phone camera as well as quantified using a spectrophotometer/luminometer. By optimizing RNA-amplification and biosensor-design, we have generated a highly-sensitive diagnostic assay; with sensitivity down to attomolar (100 copies of) SARS-CoV-2 RNA. Finally, this PHAsed NASBA-Translation Optical Method (PHANTOM) efficiently detects the presence of viral RNA in human patient samples, with clear distinction from samples designated negative for the virus. The biosensor response correlates well with Ct values from RT-qPCR tests and thus presents a powerful and easily accessible strategy for detecting Covid infection.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Paolo Boscolo-Rizzo", - "author_inst": "University of Trieste, Italy" - }, - { - "author_name": "Anna Menegaldo", - "author_inst": "AULSS 2 Treviso, Italy" - }, - { - "author_name": "Cristoforo Fabbris", - "author_inst": "AULSS 2 Treviso, Italy" - }, - { - "author_name": "Giacomo Spinato", - "author_inst": "University of Padova, Italy" - }, - { - "author_name": "Daniele Borsetto", - "author_inst": "Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom" - }, - { - "author_name": "Luigi Angelo Vaira", - "author_inst": "University of Sassari, Italy" - }, - { - "author_name": "Leonardo Calvanese", - "author_inst": "University of Padova, Italy" - }, - { - "author_name": "Andrea Pettorelli", - "author_inst": "University of Padova, Italy" - }, - { - "author_name": "Massimo Sonego", - "author_inst": "AULSS 2, Treviso, Italy" - }, - { - "author_name": "Daniele Frezza", - "author_inst": "AULSS 2, Treviso, Italy" + "author_name": "Anirudh Chakravarthy", + "author_inst": "InStem - Institute for Stem Cell Science and Regenerative Medicine, Bangalore 560065" }, { - "author_name": "Andy Bertolin", - "author_inst": "AULSS2, Vittorio Veneto, Italy" + "author_name": "Anirudh K N", + "author_inst": "3National Centre for Biological Sciences, GKVK Campus, Bellary Road, Bangalore, India 560065" }, { - "author_name": "Walter Cestaro", - "author_inst": "AULSS 2, Montebelluna, Italy" + "author_name": "Geen George", + "author_inst": "InStem - Institute for Stem Cell Science and Regenerative Medicine, Bangalore 560065" }, { - "author_name": "Roberto Rigoli", - "author_inst": "AULSS 2, Treviso, Italy" + "author_name": "Shyamsundar Ranganathan", + "author_inst": "Red Hat, Inc., Westford, MA 01886" }, { - "author_name": "Giancarlo Tirelli", - "author_inst": "University of Trieste, Italy" + "author_name": "Nishan Shettigar", + "author_inst": "National Centre for Biological Sciences, GKVK Campus, Bellary Road, Bangalore, India 560065" }, { - "author_name": "Maria Cristina Da Mosto", - "author_inst": "University of Padova" + "author_name": "Suchitta U", + "author_inst": "National Centre for Biological Sciences, GKVK Campus, Bellary Road, Bangalore, India 560065" }, { - "author_name": "Anna Menini", - "author_inst": "SISSA, Scuola Internazionale Superiore di Studi Avanzati, Trieste, Italy" + "author_name": "Dasaradhi Palakodeti", + "author_inst": "InStem - Institute for Stem Cell Science and Regenerative Medicine, Bangalore 560065" }, { - "author_name": "Jerry Polesel", - "author_inst": "Aviano National Cancer Institute, IRCCS, Aviano, Italy" + "author_name": "Akash Gulyani", + "author_inst": "Department of Biochemistry, School of Life Sciences, University of Hyderabad, Hyderabad 500046" }, { - "author_name": "Claire Hopkins", - "author_inst": "Guys and St Thomas Hospitals, London, United Kingdom" + "author_name": "Arati Ramesh", + "author_inst": "National Centre for Biological Sciences, GKVK Campus, Bellary Road, Bangalore, India 560065" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -970503,17 +969620,49 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.01.05.21249255", - "rel_title": "Viral Variants and Vaccinations: If We Can Change the COVID-19 Vaccine, Should We?", + "rel_doi": "10.1101/2021.01.05.20248973", + "rel_title": "Associations between Stress and Child Verbal Abuse and Corporal Punishment during the COVID-19 Pandemic and Potential Effect Modification by Lockdown Measures", "rel_date": "2021-01-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.05.21249255", - "rel_abs": "As we close in on one year since the COVID-19 pandemic began, hope has been placed on bringing the virus under control through mass administration of recently developed vaccines. Unfortunately, newly emerged, fast-spreading strains of COVID-19 threaten to undermine progress by interfering with vaccine efficacy. While a long-term solution to this challenge would be to develop vaccines that simultaneously target multiple different COVID-19 variants, this approach faces both developmental and regulatory hurdles. A simpler option would be to switch the target of the current vaccine to better match the newest viral variant. I use a stochastic simulation to determine when it is better to target a newly emerged viral variant and when it is better to target the dominant but potentially less transmissible strain. My simulation results suggest that it is almost always better to target the faster spreading strain, even when the initial prevalence of this variant is much lower. In scenarios where targeting the slower spreading variant is best, all vaccination strategies perform relatively well, meaning that the choice of vaccination strategy has a small effect on public health outcomes. In scenarios where targeting the faster spreading variant is best, use of vaccines against the faster spreading viral variant can save many lives. My results provide rule of thumb guidance for those making critical decisions about vaccine formulation over the coming months.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.05.20248973", + "rel_abs": "BackgroundChild abuse appears to be on the increase during the COVID-19 pandemic, but the extent that lockdown measures modified the association between stress and abuses has not been systematically assessed.\n\nObjectivesTo assess: 1) the association between caregivers stress and self-reported verbal abuse and corporal punishment of a child in the household, and; 2) modification of the stated association by experienced COVID-19 lockdown measures.\n\nParticipants and settingsCaregivers residing in villages on lockdown in the Deep South of Thailand (n=466 participants)\n\nMethodsWe randomly sampled 12 villages in the study area, and 40 households per village. Trained enumerators who were residents of the sampled villages collected the data using phone-based interview. We measured stress level using the standard ST-5 questionnaire. We developed and pilot-tested questions for measurement of child abuse and lockdown experiences specifically for this study.\n\nResultsCaregivers with moderate and higher levels of stress were more likely than caregivers with low level of stress to report verbal abuse (48% vs. 23%, respectively; Adj. OR = 3.12, 95% CI = 1.89, 5.15) and corporal punishment (28% vs. 8%, respectively; Adj. OR = 2.76, 95% CI = 1.41, 5.42). We found that COVID-19 lockdown experiences modified the associations between stress and verbal abuse and corporal punishment.\n\nConclusionThere were associations between stress and abuses, which were modified by lockdown experiences. However, social desirability, lack of details in the answers, and potential confounding by mental illness co-morbidities were notable limitations of the study. Caveat is advised in the interpretation of the study findings.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Sharon Bewick", - "author_inst": "Clemson University" + "author_name": "Rohani Jeharsae", + "author_inst": "Faculty of Nursing Pattani Campus, Prince of Songkla University, Mueang Pattani, Thailand" + }, + { + "author_name": "Manusameen Jae-noh", + "author_inst": "Faculty of Nursing Pattani Campus, Prince of Songkla University, Mueang Pattani, Thailand" + }, + { + "author_name": "Haneefah Jae-a-lee", + "author_inst": "Faculty of Nursing Pattani Campus, Prince of Songkla University, Mueang Pattani, Thailand" + }, + { + "author_name": "Suhaida Waeteh", + "author_inst": "Faculty of Nursing Pattani Campus, Prince of Songkla University, Mueang Pattani, Thailand" + }, + { + "author_name": "Nisuraida Nimu", + "author_inst": "Faculty of Nursing Pattani Campus, Prince of Songkla University, Mueang Pattani, Thailand" + }, + { + "author_name": "Corliyoh Chewae", + "author_inst": "Pattani Provincial Public Health Office, Mueang Pattani, Thailand" + }, + { + "author_name": "Malinee Yama", + "author_inst": "Pattani Provincial Public Health Office, Mueang Pattani, Thailand" + }, + { + "author_name": "Nurin Dureh", + "author_inst": "Faculty of Science and Technology, Prince of Songkla University, Mueang Pattani, Thailand" + }, + { + "author_name": "Wit Wichaidit", + "author_inst": "Epidemiology Unit, Faculty of Medicine, Prince of Songkla University. Hat Yai, Thailand" } ], "version": "1", @@ -972309,37 +971458,57 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2021.01.06.21249341", - "rel_title": "Construction of a demand and capacity model for intensive care and hospital ward beds, and mortality from COVID-19", + "rel_doi": "10.1101/2021.01.05.20248590", + "rel_title": "Evaluation of at-home methods for N95 filtering facepiece respirator decontamination", "rel_date": "2021-01-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.06.21249341", - "rel_abs": "BackgroundThis paper describes the construction of a model used to estimate the number of excess deaths that could be expected as a direct consequence of a lack of hospital bed and intensive care unit (ICU) capacity.\n\nMethodsA series of compartmental models was used to estimate the number of deaths under different combinations of care required (ICU or ward), and care received (ICU, ward or no care) in England up to the end of April 2021. Model parameters were sourced from publicly available government information, organisations collating COVID-19 data and calculations using existing parameters. A compartmental sub-model was used to estimate the mortality scalars that represent the increase in mortality that would be expected from a lack of provision of an ICU or general ward bed when one is required. Three illustrative scenarios for admissions numbers, Optimistic, Middling and Pessimistic, are described showing how the model can be used to estimate mortality rates under different scenarios of capacity.\n\nResultsThe key output of our collaboration was the model itself rather than the results of any of the scenarios. The model allows a user to understand the excess mortality impact arising as a direct consequence of capacity being breached under various scenarios or forecasts of hospital admissions. The scenarios described in this paper are illustrative and are not forecasts.\n\nThere were no excess deaths from a lack of capacity in any of the Optimistic scenario applications in sensitivity analysis.\n\nSeveral of the Middling scenario applications under sensitivity testing resulted in excess deaths directly attributable to a lack of capacity. Most excess deaths arose when we modelled a 20% reduction compared to best estimate ICU capacity. This led to 597 deaths (0.7% increase).\n\nAll the Pessimistic scenario applications under sensitivity analysis had excess deaths. These ranged from 49,219 (19.4% increase) when we modelled a 20% increase in ward bed availability over the best-estimate, to 103,845 (40.9% increase) when we modelled a 20% shortfall in ward bed availability below the best-estimate. The emergence of a new, more transmissible variant (VOC 202012/01) increases the likelihood of real world outcomes at, or beyond, those modelled in our Pessimistic scenario.\n\nThe results can be explained by considering how capacity evolves in each of the scenarios. In the Middling scenario, whilst ICU capacity may be approached and even possibly breached, there remains sufficient ward capacity to take lives who need either ward or ICU support, keeping excess deaths relatively low. However, the Pessimistic scenario sees ward capacity breached, and in many scenarios for a period of several weeks, resulting in much higher mortality in those lives who require care but do not receive it.\n\nConclusionsNo excess deaths from breaching capacity would be expected under the unadjusted Optimistic assumptions of demand. The Middling scenario could result in some excess deaths from breaching capacity, though these would be small (0.7% increase) relative to the total number of deaths in that scenario. The Pessimistic scenario would certainly result in significant excess deaths from breaching capacity. Our sensitivity analysis indicated a range between 49,219 (19.4% increase) and 103,845 (40.9% increase) excess deaths.\n\nWithout the new variant, exceeding capacity for hospital and ICU beds did not appear to be the most likely outcome but given the new variant it now appears more plausible and, if so, would result in a substantial increase in the number of deaths from COVID-19.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.05.20248590", + "rel_abs": "N95 filtering facepiece respirators (FFRs) are essential for the protection of healthcare professionals and other high-risk groups against Coronavirus Disease of 2019 (COVID-19). In response to shortages in FFRs during the ongoing COVID-19 pandemic, the Food and Drug Administration issued an Emergency Use Authorization permitting FFR decontamination and reuse. However, although industrial decontamination services are available at some large institutions, FFR decontamination is not widely accessible.\n\nTo be effective, FFR decontamination must 1) inactivate the virus; 2) preserve FFR integrity, specifically fit and filtering capability; and 3) be non-toxic and safe. Here we identify and test at-home heat-based methods for FFR decontamination that meet these requirements using common household appliances. Our results identify potential protocols for simple and accessible FFR decontamination, while also highlighting unsuitable methods that may jeopardize FFR integrity.\n\nOne sentence summarySurvey of at-home methods for N95 respirator decontamination using heat and evaluation of their effects on N95 respirator integrity.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Stuart McDonald", - "author_inst": "Lloyds Banking Group" + "author_name": "Tiffany X Chen", + "author_inst": "Columbia University" }, { - "author_name": "Christopher John Martin", - "author_inst": "Crystallise Ltd" + "author_name": "Ana Pinharanda", + "author_inst": "Columbia University" }, { - "author_name": "Steve Bale", - "author_inst": "Munich Re" + "author_name": "Keiko Yasuma-Mitobe", + "author_inst": "Columbia University" }, { - "author_name": "Michiel Luteijn", - "author_inst": "Hannover Re" + "author_name": "Elaine Lee", + "author_inst": "Columbia University" }, { - "author_name": "Rahuldeb Sarkar", - "author_inst": "Medway NHS Foundation Trust" + "author_name": "Natalie A Steinemann", + "author_inst": "Columbia University" + }, + { + "author_name": "Jaeseung Hahn", + "author_inst": "Columbia University" + }, + { + "author_name": "Lydia Wu", + "author_inst": "Columbia University" + }, + { + "author_name": "Stavros Fanourakis", + "author_inst": "Columbia University" + }, + { + "author_name": "Darcy S Peterka", + "author_inst": "Columbia University" + }, + { + "author_name": "Elizabeth M. C. Hillman", + "author_inst": "Columbia University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -973523,35 +972692,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.12.31.20249105", - "rel_title": "Prediction of COVID-19 Pandemic of Top Ten Countries in the World Establishing a Hybrid AARNN LTM Model", + "rel_doi": "10.1101/2021.01.03.21249183", + "rel_title": "Value of radiomics features from adrenal gland and periadrenal fat CT images predicting COVID-19 progression", "rel_date": "2021-01-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.31.20249105", - "rel_abs": "The novel COVID-19 global pandemic has become a public health emergency of international concern affecting 215 countries and territories around the globe. As of 28 November 2020, it has caused a pandemic outbreak with a total of more than 6,171,5119 confirmed infections and more than 1,44,4235 confirmed deaths reported worldwide. The main focus of this paper is to generate LTM real-time out of sample forecasts of the future COVID-19 confirmed and death cases respectively for the top ten profoundly affected countries including for the world. To solve this problem we introduced a novel hybrid approach AARNN model based on ARIMA and ARNN forecasting model that can generate LTM (fifty days ahead) out of sample forecasts of the number of daily confirmed and death COVID-19 cases for the ten countries namely USA, India, Brazil, Russia, France, Spain, UK, Italy, Argentina, Colombia and also for the world respectively. The predictions of the future outbreak for different countries will be useful for the effective allocation of health care resources and will act as early-warning system for health warriors, corporate leaders, economists, government/public-policy makers, and scientific experts.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.03.21249183", + "rel_abs": "BackgroundValue of radiomics features from the adrenal gland and periadrenal fat CT images for predicting disease progression in patients with COVID-19 has not been studied.\n\nMethodsA total of 1,245 patients (685 moderate and 560 severe patients) were enrolled in a retrospective study. We proposed 3D V-Net to segment adrenal glands in onset CT images automatically, and periadrenal fat was obtained using inflation operation around the adrenal gland. Next, we built a clinical model (CM), three radiomics models (adrenal gland model [AM], periadrenal fat model [PM], and fusion of adrenal gland and periadrenal fat model [FM]), and radiomics nomogram (RN) after radiomics features extracted to predict disease progression in patients with COVID-19.\n\nResultsThe auto-segmentation framework yielded a dice value of 0.79 in the training set. CM, AM, PM, FM, and RN obtained AUCs of 0.712, 0.692, 0.763, 0.791, and 0.806, respectively in the training set. FM and RN had better predictive efficacy than CM (P < 0.0001) in the training set. RN showed that there was no significant difference in the validation set (mean absolute error [MAE] = 0.04) and test set (MAE = 0.075) between predictive and actual results. Decision curve analysis showed that if the threshold probability was more than 0.3 in the validation set or between 0.4 and 0.8 in the test set, it could gain more net benefits using RN than FM and CM.\n\nConclusionRadiomics features extracted from the adrenal gland and periadrenal fat CT images may predict progression in patients with COVID-19.\n\nFundingThis study was funded by Science and Technology Foundation of Guizhou Province (QKHZC [2020]4Y002, QKHPTRC [2019]5803), the Guiyang Science and Technology Project (ZKXM [2020]4), Guizhou Science and Technology Department Key Lab. Project (QKF [2017]25), Beijing Medical and Health Foundation (YWJKJJHKYJJ-B20261CS) and the special fund for basic Research Operating Expenses of public welfare research institutes at the central level from Chinese Academy of Medical Sciences (2019PT320003).", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "PADMABATI GAHAN", - "author_inst": "DEPT. OF BUSINESS ADMINISTRATION; SAMBALPUR UNIVERSITY; ODISHA; INDIA-768019" + "author_name": "Mudan Zhang", + "author_inst": "Guizhou University School Of Medicine, Guiyang, Guizhou province, 550000, China" }, { - "author_name": "MONALISHA PATTNAIK", - "author_inst": "DEPT. OF STATISTICS; SAMBALPUR UNIVERSITY; ODISHA; INDIA-768019" + "author_name": "Xuntao Yin", + "author_inst": "Department of Radiology, Guizhou Provincial People' s Hospital, Guiyang, Guizhou Province 550002, China." + }, + { + "author_name": "Wuchao Li", + "author_inst": "Department of Radiology, Guizhou Provincial People' s Hospital, Guiyang Guizhou Province 550002, China." }, { - "author_name": "Agnibrata Nayak", - "author_inst": "Principal Associate, Capital One LLC,RICHMOND; USA" + "author_name": "Yan Zha", + "author_inst": "Guizhou University School Of Medicine, Guiyang, Guizhou province, 550000, China" }, { - "author_name": "Monee Kieran Roul", - "author_inst": "Process Engineer, Lam Research Corp. Portland-USA" + "author_name": "Xianchun Zeng", + "author_inst": "Department of Radiology, Guizhou Provincial People's Hospital Guiyang, Guizhou Province 550002 China" + }, + { + "author_name": "Xiaoyong Zhang", + "author_inst": "Department of Radiology, Guizhou Provincial People' s Hospital, Guiyang, Guizhou Province 550002, China;" + }, + { + "author_name": "Jingjing Cui", + "author_inst": "Shanghai United Imaging Intelligence, Co., Ltd., Shanghai, 201807, China;" + }, + { + "author_name": "Jie Tian", + "author_inst": "Key Laboratory of Molecular Imaging, Chinese Academy of Sciences, Beijing, 100190, China;" + }, + { + "author_name": "Rongpin Wang", + "author_inst": "Department of Radiology, Guizhou Provincial People' s Hospital, Guiyang, Guizhou Province 550002, China;" + }, + { + "author_name": "Chen Liu", + "author_inst": "Department of Radiology, Southwest Hospital, Third Military Medical University(Army Medical Univer" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "radiology and imaging" }, { "rel_doi": "10.1101/2021.01.04.21249195", @@ -975173,49 +974366,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.30.20249053", - "rel_title": "Is sickle cell disease a risk factor for severe COVID-19 : a multicenter national retrospective cohort", + "rel_doi": "10.1101/2020.12.29.20248989", + "rel_title": "Early measurement of blood sST2 is a good predictor of death and poor outcomes in patients admitted for COVID-19 infection", "rel_date": "2021-01-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.30.20249053", - "rel_abs": "IntroductionCoronavirus disease (COVID-19) caused by the novel coronavirus SARS-CoV-2 is an infectious disease which has evolved into a worldwide pandemic. Growing evidence suggests that individuals with pre-existing comorbidities are at higher risk of a more serious COVID-19 illness. Sickle cell disease (SCD) is an inherited hemoglobinopathy which increases the susceptibility to infections and as a consequent has higher risks of morbidity and mortality.\n\nThe impact of COVID-19 on SCD patients could lead to further increase in disease severity and mortality. Studies that examine the effect of SCD on COVID-19 outcomes are lacking. This study aims to determine whether SCD is a risk factor for severe COVID-19 infection in regards to the requirement of non-invasive ventilation/high flow nasal cannula (NIV/HFNC), mechanical intubation (MV) or death.\n\nMethodsRetrospective cohort study which included COVID-19 patients admitted to four Ministry of Health COVID-19 treatment facilities in Bahrain during the period of 24, February 2020, to 31, July 2020. All SCD patients with COVID-19 were included and compared to randomly selected non-SCD patients with COVID-19. Data for the selected patients were collected from the medical records. Multivariate logistic regression models were used to control for confounders and estimate the effect of SCD on the outcomes.\n\nResultsA total of 1,792 patients with COVID-19 were included; 38 of whom were diagnosed with SCD as well. In the SCD group, one (2.6%) patient required NIV/HFNC, one (2.6%) required MV and one (2.6%) death occurred. In comparison, 56 (3.2%) of the non-SCD patients required NIV/HFNC, 47 (2.7%) required MV and death occurred in 58 (3.3%) patients. Upon adjusting for confounders, SCD had an odds ratio of 1.847 (95% CI: 0.39 - 8.83; p=0.442).\n\nConclusionOur results indicate that SCD is not a risk factor for worse disease outcomes in COVID-19 patients.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.29.20248989", + "rel_abs": "ImportanceAlthough several biomarkers have shown correlation to prognosis in COVID-19 patients, their clinical value is limited because of lack of specificity, suboptimal sensibility, or poor dynamic behavior.\n\nObjectiveIn search of better prognostic markers in COVID-19, we hypothesized that circulating soluble ST2 (sST2) could be associated to a worse outcome, prompted by our previous knowledge of sST2 involvement in heart failure-associated lung deterioration, and by mounting evidence favoring a role of IL-33/ST2 axis in the disease.\n\nDesign, Setting and participantsOne hundred and fifty-two patients admitted for confirmed COVID-19 infection were included in a prospective non-interventional, observational study carried out in a tertiary teaching center. Blood samples were drawn at admission, 48-72 hours later and at discharge. sST2 concentrations, and routine blood laboratory were analyzed.\n\nMain outcomesPrimary end-points were admission at intensive care unit (ICU) and, mortality. Other outcomes were a need for high oxygen flow therapy (HOF) or increasing treatment at 48/72 hours.\n\nResultsMedian age was 57.5 years (SD: 12.8), 60.4% males. Ten per cent of patients (n=15) were derived to ICU and/or died during admission. The rest stayed hospitalized 8(IQR:6) days on average. About 34% (n=47), 38% (n=53) and 48.5% (n=66) needed HOF, up-titrate therapy or both, respectively.\n\nMedian (IQR) sST2 serum concentration (ng/mL) rose to 53.1(30.9) at admission, peaked at 48-72h (79.5[64]) and returned to admission levels at discharge (44.9[36.7]), remaining significantly elevated above healthy donor values (18.6[15.1]).\n\nA concentration of sST2 above 58.9 ng/mL identified patients progressing to ICU admission or death. These results remained significant after multivariable analysis. The area under the receiver operating characteristics curve (AUC) of sST2 for the occurrence of end-points was 0.776 (p=0.001). Admission sST2 was higher in patients who needed up-tritate therapy.\n\nConclusions and relevanceIn patients admitted for COVID-19 infection, measurement of sST2 measurement early within 24h after at admission was able to identify patients at risk of severe complications or death.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Abdulkarim Abdulrahman", - "author_inst": "National Taskforce for Combating the Coronavirus (COVID-19), Bahrain ; Mohammed Bin Khalifa Cardiac Centre, Bahrain" + "author_name": "MARTA S\u00c1NCHEZ-MARTELES", + "author_inst": "HOSPITAL CL\u00cdNICO UNIVERSITARIO \"LOZANO BLESA\" / ARAGON HEALTH RESEARCH INSTITUTE" }, { - "author_name": "Mohammed Wael", - "author_inst": "King Hamad University Hospital, Bahrain" + "author_name": "JORGE RUBIO-GRACIA", + "author_inst": "HOSPITAL CL\u00cdNICO UNIVERSITARIO \"LOZANO BLESA\"/ ARAGON HEALTH RESEARCH INSTITUTE" }, { - "author_name": "Fajer Alammadi", - "author_inst": "Ministry of Health, Bahrain" + "author_name": "NATACHA PE\u00d1A-FRESNEDA", + "author_inst": "ARAGON HEALTH RESEARCH INSTITUTE / INSTITUTO ARAGON\u00c9S DE CIENCIAS DE LA SALUD" }, { - "author_name": "Zahra Almosawi", - "author_inst": "Ministry of Health, Bahrain" + "author_name": "VANESA GARC\u00c9S-HORNA", + "author_inst": "HOSPITAL CL\u00cdNICO UNIVERSITARIO \"LOZANO BLESA\" /ARAGON HEALTH RESEARCH INSTITUTE" }, { - "author_name": "Reem AlSherooqi", - "author_inst": "Ministry of Health, Bahrain" + "author_name": "BORJA GRACIA-TELLO", + "author_inst": "HOSPITAL CL\u00cdNICO UNIVERSITARIO \"LOZANO BLESA\"" }, { - "author_name": "Manal Abduljalil", - "author_inst": "Bahrain Defence Force Hospital, Bahrain" + "author_name": "LUIS MART\u00cdNEZ-LOSTAO", + "author_inst": "HOSPITAL CL\u00cdNICO UNIVERSITARIO \"LOZANO BLESA\"" }, { - "author_name": "Nitya Kumar", - "author_inst": "Royal College of Surgeons in Ireland, Bahrain ; National Taskforce for Combating the Coronavirus (COVID-19), Bahrain ; Bahrain Defence Force hospital, Bahrain" + "author_name": "SILVIA CRESPO-AZN\u00c1REZ", + "author_inst": "HOSPITAL CL\u00cdNICO UNIVERSITARIO \"LOZANO BLESA\"" }, { - "author_name": "Manaf AlQahtani", - "author_inst": "Royal College of Surgeons in Ireland, Bahrain" + "author_name": "JUAN IGNACIO P\u00c9REZ-CALVO", + "author_inst": "UNIVERSITY OF ZARAGOZA /ARAG\u00d3N HEALTH RESEARCH INSTITUTE / HOSPITAL CL\u00cdNICO UNIVERSITARIO \"LOZANO BLESA\"" + }, + { + "author_name": "IGNACIO GIM\u00c9NEZ-L\u00d3PEZ", + "author_inst": "INSTITUTO ARAGON\u00c9S DE CIENCIAS DE LA SALUD / ARAG\u00d3N HEALTH RESEARCH INSTITUTE" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -976471,41 +975668,89 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.01.01.20248966", - "rel_title": "Survival analysis of all critically ill patients with COVID-19 admitted to the main hospital in Mogadishu, Somalia, 30 March to 12 June 2020: what interventions are proving effective?", + "rel_doi": "10.1101/2020.12.31.20248843", + "rel_title": "Implementing Building-Level SARS-CoV-2 Wastewater Surveillance on a University Campus", "rel_date": "2021-01-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.01.20248966", - "rel_abs": "OBJECTIVESTo determine risk factors for death in patients with COVID-19 admitted to the main public sector hospital in Somalia and identify interventions contributing to improved clinical outcome in a low-resource and fragile setting.\n\nSETTINGMain public sector tertiary hospital in Mogadishu, Somalia.\n\nPARTICIPANTSAll 131 laboratory-confirmed COVID-19 patients admitted to the main public tertiary hospital in Somalia between 30 March and 12 June 2020.\n\nMAIN OUTCOME MEASURESWe extracted demographic and clinical data from hospital records of all 131 COVID-19 patients admitted to hospital until their death or recovery. We used Kaplan-Meier statistics to estimate survival probabilities and the log-rank test to assess significant differences in survival between groups. We used the Cox proportional hazard model to estimate likelihood of death and assess the effect of risk factors on survival.\n\nRESULTSOf the 131 patients, 52 (40%) died in the hospital and 79 (60%) survived to discharge. The factors independently associated with increased risk of in-hospital death were: age [≥] 60 years - survival probability on day 21 in patients < 60 years was 0.789 (95% confidence interval (CI): 0.658-0.874) compared with 0.339 (95% CI: 0.205-0.478) in patients [≥] 60 years; cardiovascular disease (survival probability 0.478 (95% CI: 0.332-0.610) in patients with cardiovascular disease compared with 0.719 (95% CI: 0.601-0.807) in patients without cardiovascular disease); and non-invasive ventilation on admission - patients who were not ventilated were significantly more likely to survive than those who were (P < 0.001).\n\nCONCLUSIONOur study, which includes the largest cohort of COVID-19 patients admitted to a single hospital in a sub-Saharan African country, confirms that underlying conditions and age are associated with increased risk of in-hospital death in patients with COVID-19. Our results show the advantage of medical oxygen over non-invasive ventilation in the treatment of patients with severe COVID-19 symptoms.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.31.20248843", + "rel_abs": "The COVID-19 pandemic has been a source of ongoing challenges and presents an increased risk of illness in group environments, including jails, long term care facilities, schools, and, of course, residential college campuses. Early reports that the SARS-CoV-2 virus was detectable in wastewater in advance of confirmed cases sparked widespread interest in wastewater based epidemiology (WBE) as a tool for mitigation of COVID-19 outbreaks. One hypothesis was that wastewater surveillance might provide a cost-effective alternative to other more expensive approaches such as pooled and random testing of groups. In this paper, we report the outcomes of a wastewater surveillance pilot program at the University of North Carolina at Charlotte, a large urban university with a substantial population of students living in on-campus dormitories. Surveillance was conducted at the building level on a thrice-weekly schedule throughout the universitys fall residential semester. In multiple cases, wastewater surveillance enabled identification of asymptomatic COVID-19 cases that were not detected by other components of the campus monitoring program, which also included in-house contact tracing, symptomatic testing, scheduled testing of student athletes, and daily symptom reporting. In the context of all cluster events reported to the University community during the fall semester, wastewater-based testing events resulted in identification of smaller clusters than were reported in other types of cluster events. Wastewater surveillance was able to detect single asymptomatic individuals in dorms with total resident populations of 150-200. While the strategy described was developed for COVID-19, it is likely to be applicable to mitigation of future pandemics in universities and other group-living environments.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Mohamed M Ali", - "author_inst": "Department of Sexual and Reproductive Health and Research, World Health Organization" + "author_name": "Cynthia J Gibas", + "author_inst": "University of North Carolina at Charlotte" }, { - "author_name": "Mamunur Rahman Malik", - "author_inst": "World Health Organization Country Office, Mogadishu, Somalia" + "author_name": "Kevin Lambirth", + "author_inst": "University of North Carolina at Charlotte" + }, + { + "author_name": "Neha Mittal", + "author_inst": "University of North Carolina at Charlotte" }, { - "author_name": "Abdulrazaq Yusuf Ahmed", - "author_inst": "Demartino Hospital, Ministry of Health and Human Services, Federal Government of Somalia Mogadishu, Somalia" + "author_name": "Md Ariful Islam Juel", + "author_inst": "University of North Carolina at Charlotte" }, { - "author_name": "Ahmed Mohamed Bashir", - "author_inst": "Demartino Hospital, Ministry of Health and Human Services, Federal Government of Somalia Mogadishu, Somalia" + "author_name": "Visva Bharati Barua", + "author_inst": "University of North Carolina at Charlotte" }, { - "author_name": "Abdulmunim Mohamed", - "author_inst": "World Health Organization Country Office, Mogadishu, Somalia" + "author_name": "Lauren Roppolo Brazell", + "author_inst": "University of North Carolina at Charlotte" }, { - "author_name": "Abdulkadir Abdi", - "author_inst": "World Health Organization Country Office, Mogadishu, Somalia" + "author_name": "Keshawn Hinton", + "author_inst": "University of North Carolina at Charlotte" }, { - "author_name": "Majdouline Obtel", - "author_inst": "World Health Organization Country Office, Mogadishu, Somalia" + "author_name": "Jordan Lontai", + "author_inst": "University of North Carolina at Charlotte" + }, + { + "author_name": "Nicholas Stark", + "author_inst": "University of North Carolina at Charlotte" + }, + { + "author_name": "Isaiah Young", + "author_inst": "University of North Carolina at Charlotte" + }, + { + "author_name": "Cristine Quach", + "author_inst": "University of North Carolina at Charlotte" + }, + { + "author_name": "Morgan Russ", + "author_inst": "University of North Carolina at Charlotte" + }, + { + "author_name": "Jacob Kauer", + "author_inst": "University of North Carolina at Charlotte" + }, + { + "author_name": "Bridgette Nicolosi", + "author_inst": "University of North Carolina at Charlotte" + }, + { + "author_name": "Srinivas Akella", + "author_inst": "University of North Carolina at Charlotte" + }, + { + "author_name": "Wenwu Tang", + "author_inst": "University of North Carolina at Charlotte" + }, + { + "author_name": "Don Chen", + "author_inst": "University of North Carolina at Charlotte" + }, + { + "author_name": "Jessica Schlueter", + "author_inst": "University of North Caroilna at Charlotte" + }, + { + "author_name": "Mariya Munir", + "author_inst": "University of North Carolina at Charlotte" } ], "version": "1", @@ -977989,55 +977234,71 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.04.425289", - "rel_title": "TMPRSS2 structure-phylogeny repositions Avoralstat for SARS-CoV-2 prophylaxis in mice", + "rel_doi": "10.1101/2021.01.04.425198", + "rel_title": "The impact of COVID-19 vaccination campaigns accounting for antibody-dependent enhancement", "rel_date": "2021-01-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.04.425289", - "rel_abs": "Drugs targeting host proteins can act prophylactically to reduce viral burden early in disease and limit morbidity, even with antivirals and vaccination. Transmembrane serine protease 2 (TMPRSS2) is a human protease required for SARS-CoV-2 viral entry and may represent such a target.1-3 We hypothesized drugs selected from proteins related by their tertiary structure, rather than their primary structure, were likely to interact with TMPRSS2. We created a structure-based phylogenetic computational tool 3DPhyloFold to systematically identify structurally similar serine proteases with known therapeutic inhibitors and demonstrated effective inhibition of SARS-CoV-2 infection in vitro and in vivo.4,5 Several candidate compounds, Avoralstat, PCI-27483, Antipain, and Soybean-Trypsin-Inhibitor, inhibited TMPRSS2 in biochemical and cell infection assays. Avoralstat, a clinically tested Kallikrein-related B1 inhibitor,6 inhibited SARS-CoV-2 entry and replication in human airway epithelial cells. In an in vivo proof of principle,5 Avoralstat significantly reduced lung tissue titers and mitigated weight-loss when administered prophylactically to SARS-CoV-2 susceptible mice indicating its potential to be repositioned for COVID-19 prophylaxis in humans.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.04.425198", + "rel_abs": "BackgroundCOVID-19 vaccines are approved, vaccination campaigns are launched, and worldwide return to normality seems within close reach. Nevertheless, concerns about the safety of COVID-19 vaccines arose, due to their fast emergency approval. In fact, the problem of antibody-dependent enhancement was raised in the context of COVID-19 vaccines.\n\nMethods and findingsWe introduce a complex extension of the model underlying the pandemic preparedness tool CovidSim 1.1 (http://covidsim.eu/) to optimize vaccination strategies with regard to the onset of campaigns, vaccination coverage, vaccination schedules, vaccination rates, and efficiency of vaccines. Vaccines are not assumed to immunize perfectly. Some individuals fail to immunize, some reach only partial immunity, and - importantly - some develop antibody-dependent enhancement, which increases the likelihood of developing symptomatic and severe episodes (associated with higher case fatality) upon infection. Only a fraction of the population will be vaccinated, reflecting vaccination hesitancy or contraindications. The model is intended to facilitate decision making by exploring ranges of parameters rather than to be fitted by empirical data.\n\nWe parameterized the model to reflect the situation in Germany and predict increasing incidence (and prevalence) in early 2021 followed by a decline by summer. Assuming contact reductions (curfews, social distancing, etc.) to be lifted in summer, disease incidence will peak again. Fast vaccine deployment contributes to reduce disease incidence in the first quarter of 2021, and delay the epidemic outbreak after the summer season. Higher vaccination coverage results in a delayed and reduced epidemic peak. A coverage of 75% - 80% is necessary to prevent an epidemic peak without further drastic contact reductions.\n\nConclusionsWith the vaccine becoming available, compliance with contact reductions is likely to fade. To prevent further economic damage from COVID-19, high levels of immunization need to be reached before next years flu season, and vaccination strategies and disease management need to be flexibly adjusted. The predictive model can serve as a refined decision support tool for COVID-19 management.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Young Joo Sun", - "author_inst": "Stanford University" + "author_name": "Nessma Adil M. Y.", + "author_inst": "Hochschule Mittweida" }, { - "author_name": "Gabriel Velez", - "author_inst": "Stanford University" + "author_name": "Henri Christian Junior Tsoungui Obama", + "author_inst": "Mittweida University of Applied Sciences: Hochschule Mittweida" }, { - "author_name": "Dylan Parsons", - "author_inst": "Stanford University" + "author_name": "Jordan Ngucho Yvan Mbeutchou", + "author_inst": "AIMS - Cameroon: African Institute for Mathematical Sciences Cameroon" }, { - "author_name": "Kun Li", - "author_inst": "University of Iowa" + "author_name": "Sandy Frank Kwamou Ngaha", + "author_inst": "Mittweida University of Applied Sciences: Hochschule Mittweida" }, { - "author_name": "Miguel Ortiz", - "author_inst": "University of Iowa" + "author_name": "Loyce Kayanula", + "author_inst": "Mittweida University of Applied Sciences: Hochschule Mittweida" }, { - "author_name": "Shaunik Sharma", - "author_inst": "University of Iowa" + "author_name": "George Kamanga", + "author_inst": "Mittweida University of Applied Sciences: Hochschule Mittweida" }, { - "author_name": "Paul B McCray", - "author_inst": "University of Iowa" + "author_name": "Toheeb B. Ibrahim", + "author_inst": "Mittweida University of Applied Sciences: Hochschule Mittweida" }, { - "author_name": "Alexander G Bassuk", - "author_inst": "University of Iowa" + "author_name": "Patience Bwanu Iliya", + "author_inst": "Mittweida University of Applied Sciences: Hochschule Mittweida" }, { - "author_name": "Vinit B Mahajan", - "author_inst": "Stanford University" + "author_name": "Sulyman B. Iyanda", + "author_inst": "Mittweida University of Applied Sciences: Hochschule Mittweida" + }, + { + "author_name": "Looli H. M. Alawam Nemer", + "author_inst": "AIMS - Cameroon: African Institute for Mathematical Sciences Cameroon" + }, + { + "author_name": "Kristina Barbara Helle", + "author_inst": "University of Applied Sciences Mittweida: Hochschule Mittweida" + }, + { + "author_name": "Miranda I. Teboh-Ewungkem", + "author_inst": "Lehigh University" + }, + { + "author_name": "Kristan Alexander Schneider", + "author_inst": "Hochschule Mittweida" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "new results", - "category": "microbiology" + "category": "immunology" }, { "rel_doi": "10.1101/2020.12.26.20248878", @@ -979723,31 +978984,39 @@ "category": "dentistry and oral medicine" }, { - "rel_doi": "10.1101/2020.12.25.20248859", - "rel_title": "Factors influencing intention to adhere to precautionary behavior in times of COVID- 19 pandemic in Sudan: an application of the Health Belief Model", - "rel_date": "2020-12-31", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.25.20248859", - "rel_abs": "BackgroundCorona virus disease (COVID-19) is highly infectious disease caused by the novel corona virus (SARS-CoV-2). Several public health and social protective measures that may prevent or slow down the transmission of COVID-19 were introduced. However, these measures are unfortunately neglected or deliberately ignored by some individuals.\n\nMethodsWe did a cross sectional online based survey to identify possible factors influencing intention to adhere to precautionary measures and preventive guidelines against COVID-19 during lockdown periods in Sudan. The questionnaire was used to collect socio-demographic data of study participants, their health beliefs and intention regarding adherence to precautionary measures against COVID-19 based on the constructs of the Health Belief Model.\n\nResultsTotal of 680 respondents completed and returned the online questionnaire. Significant predictors of intention to adhere to the precautionary measures against COVID-19 were gender ({beta} =3.34, P <0.001), self-efficacy ({beta}= 0.476, P<0.001), perceived benefits ({beta}= 0.349, P<0.001) and perceived severity ({beta}= 0.113, P=0.005). These factors explained 43% of the variance in respondents intention to adhere to COVID-19 precautionary measures. Participants who were female, confident in their ability to adhere to the protective measures when available, believing in the benefits of the protective measures against COVID-19 and perceiving that the disease could have serious consequences were more likely to be willing to adhere to the protective measures.\n\nConclusionFemale respondents and respondents having higher self-efficacy, higher perceived benefits and higher perceived severity were more likely to be willing to adhere to the protective measures against COVID-19 in Sudan.", - "rel_num_authors": 3, + "rel_doi": "10.1101/2020.12.29.424739", + "rel_title": "Meta-analysis of virus-induced host gene expression reveals unique signatures of immune dysregulation induced by SARS-CoV-2", + "rel_date": "2020-12-30", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.29.424739", + "rel_abs": "The clinical outcome of COVID-19 has an extreme age, genetic and comorbidity bias that is thought to be driven by an impaired immune response to SARS-CoV-2, the causative agent of the disease. The unprecedented impact of COVID-19 on global health has resulted in multiple studies generating extensive gene expression datasets in a relatively short period of time. In order to better understand the immune dysregulation induced by SARS-CoV-2, we carried out a meta-analysis of these transcriptomics data available in the published literature. Datasets included both those available from SARS-CoV-2 infected cell lines in vitro and those from patient samples. We focused our analysis on the identification of viral perturbed host functions as captured by co-expressed gene module analysis. Transcriptomics data from lung biopsies and nasopharyngeal samples, as opposed to those available from other clinical samples and infected cell lines, provided key signatures on the role of the hosts immune response on COVID-19 pathogenesis. For example, severity of infection and patients age are linked to the absence of stimulation of the RIG-I-like receptor signaling pathway, a known critical immediate line of defense against RNA viral infections that triggers type-I interferon responses. In addition, co-expression analysis of age-stratified transcriptional data provided evidence that signatures of key immune response pathways are perturbed in older COVID-19 patients. In particular, dysregulation of antigen-presenting components, down-regulation of cell cycle mechanisms and signatures of hyper-enriched monocytes were strongly correlated with the age of older individuals infected with SARS-CoV-2. Collectively, our meta-analysis highlights the ability of transcriptomics and gene-module analysis of aggregated datasets to aid our improved understanding of the host-specific disease mechanisms underpinning COVID-19.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Azzaa Mehanna", - "author_inst": "Health Administration and Behavioral Sciences Department, High Institute of Public Health, Alexandria University, Egypt." + "author_name": "Srikeerthana Kuchi", + "author_inst": "University of Glasgow" }, { - "author_name": "Yasir Ahmed Mohammed Elhadi", - "author_inst": "Health Administration and Behavioral Sciences Department, High Institute of Public Health, Alexandria University, Egypt." + "author_name": "Quan Gu", + "author_inst": "University of Glasgow" }, { - "author_name": "Don Eliseo Lucero-Prisno III", - "author_inst": "Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom" + "author_name": "Massimo Palmarini", + "author_inst": "University of Glasgow" + }, + { + "author_name": "Sam J Wilson", + "author_inst": "University of Glasgow" + }, + { + "author_name": "David L Robertson", + "author_inst": "University of Glasgow" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by_nc", + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.12.29.424728", @@ -981380,55 +980649,35 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.12.29.424712", - "rel_title": "Rapid expression of COVID-19 proteins by transient expression in tobacco.", + "rel_doi": "10.1101/2020.12.29.424619", + "rel_title": "SARS-CoV-2 spike glycoprotein S1 induces neuroinflammation in BV-2 microglia", "rel_date": "2020-12-29", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.29.424712", - "rel_abs": "In 2020 we suffered from a major global pandemic caused by the SARS-CoV-2 coronavirus. Efforts to contain the virus include the development of rapid tests and vaccines, which require a ready supply of viral proteins. Here we report the production of two SARS-CoV-2 proteins by transient transformation of tobacco, leading to high expression within three days, and subsequent purification of the intact proteins. Such efforts may help to develop testing resources to alleviate the major impacts of this global pandemic.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.29.424619", + "rel_abs": "In addition to respiratory complications produced by SARS-CoV-2, accumulating evidence suggests that some neurological symptoms are associated with the disease caused by this coronavirus. In this study, we investigated the effects of the SARS-CoV-2 spike protein S1 stimulation on neuroinflammation in BV-2 microglia. Analyses of culture supernatants revealed an increase in the production of TNF, IL-6, IL-1{beta} and iNOS/NO. S1 also increased protein levels of phospho-p65 and phospho-I{kappa}B, as well as enhancing DNA binding and transcriptional activity of NF-{kappa}B. These effects of the protein were blocked in the presence of BAY11-7082 (1 M). Exposure of S1 to BV-2 microglia also increased the protein levels of NLRP3 inflammasome and enhanced caspase-1 activity. Increased protein levels of p38 MAPK was observed in BV-2 microglia stimulated with the spike protein S1 (100 ng/mL), an action that was reduced in the presence of SKF 86002 (1 M). Results of immunofluorescence microscopy showed an increase in TLR4 protein expression in S1-stimulated BV-2 microglia. Furthermore, pharmacological inhibition with TAK 242 (1 M) and transfection with TLR4 siRNA resulted in significant reduction in TNF and IL-6 production in S1-stimulated BV-2 microglia. These results have provided the first evidence demonstrating S1-induced neuroinflammation in BV-2 microglia. We propose that induction of neuroinflammation by this protein in the microglia is mediated through activation of NF-{kappa}B and p38 MAPK, possibly as a result of TLR4 activation. These results contribute to our understanding of some of the mechanisms involved in CNS pathologies of SARS-CoV-2.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Penelope L Lindsay", - "author_inst": "Cold Spring Harbor Laboratory" - }, - { - "author_name": "Amanda Ackerman", - "author_inst": "Cold Spring Harbor Laboratory" - }, - { - "author_name": "Yinan Jian", - "author_inst": "Cold Spring Harbor Laboratory" - }, - { - "author_name": "Oliver Artz", - "author_inst": "Cold Spring Harbor Laboratory" - }, - { - "author_name": "Daniele Rosado", - "author_inst": "Cold Spring Harbor Laboratory" - }, - { - "author_name": "Tara Skopelitis", - "author_inst": "Cold Spring Harbor Laboratory" + "author_name": "Olumayokun A Olajide", + "author_inst": "University of Huddersfield" }, { - "author_name": "Munenori Kitagawa", - "author_inst": "Cold Spring Harbor Laboratory" + "author_name": "Victoria U Iwuanyanwu", + "author_inst": "University of Huddersfield" }, { - "author_name": "Ullas V Pedmale", - "author_inst": "Cold Spring Harbor Laboratory" + "author_name": "Oyinkansola D Adegbola", + "author_inst": "University of Huddersfield" }, { - "author_name": "David Jackson", - "author_inst": "Cold Spring Harbor Laboratory" + "author_name": "Alaa A Al-Hindawi", + "author_inst": "University of Huddersfield" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "plant biology" + "category": "neuroscience" }, { "rel_doi": "10.1101/2020.12.28.424622", @@ -983173,23 +982422,143 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2020.12.23.20248740", - "rel_title": "Does COVID-19 Testing Create More Cases? An Empirical Evidence on the Importance of Mass Testing During a Pandemic", + "rel_doi": "10.1101/2020.12.22.20248753", + "rel_title": "Oral clarithromycin in COVID-19 of moderate severity: the ACHIEVE open-label trial using concurrent matched comparators", "rel_date": "2020-12-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.23.20248740", - "rel_abs": "The importance of testing and surveillance of an infectious disease cannot be underestimated. The testing is the first step to detect an infectious disease, and mass testing can slow or mitigate the spread of an infectious disease. Despite overwhelming evidence and the importance of testing discussed in the literature, there have been claims that \"more COVID-19 testing creates more cases\". Therefore, there is a need to study whether massive testing is the reason for detecting more positive COVID-19 cases. In this research, we used a dataset from the U.S. Department of Health & Human Services and empirically showed that by increasing the COVID-19 testing in the U.S., the spread of the COVID-19 decreased significantly. Our results indicate a negative relationship between the number of positive cases and the number of tests performed in the past months. The large-scale testing may have helped identify positive and asymptomatic cases early in the course of illness, which enabled individuals to isolate themselves, thus reducing the chances of spreading the diseases and slowing the spread of the pandemic.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.22.20248753", + "rel_abs": "Background: To study the efficacy of oral clarithromycin in moderate COVID-19. Methods: An open-label non-randomized trial in 90 patients with COVID-19 of moderate severity was conducted between May and October 2020. The primary endpoint was defined at the end-of-treatment (EOT) as no need for hospital re-admission and no progression into lower respiratory tract infection (LRTI) for patients with upper respiratory tract infection; and as at least 50% decrease of the respiratory symptoms score the without progression into severe respiratory failure (SRF) for patients with LRTI. Viral load, biomarkers, the function of mononuclear cells, and safety were assessed. Results: The primary endpoint was attained in 86.7% of patients treated with clarithromycin (95% CIs 78.1-92.2%); this was 91.7% and 81.4% among patients starting clarithromycin the first 5 days from symptoms onset or later (odds ratio after multivariate analysis 6.62; p: 0.030). The responses were better for patients infected by non-B1.1 variants. Clarithromycin use was associated with decreases in circulating C-reactive protein, tumour necrosis factor-alpha and interleukin (IL)-6; by increase of Th1 to Th2 mononuclear responses; and by suppression of SARS-CoV-2 viral load. No safety concerns were reported. Conclusions: Early clarithromycin treatment provides most of clinical improvement in moderate COVID-19 (Trial Registration: ClinicalTrials.gov, NCT04398004)", + "rel_num_authors": 31, "rel_authors": [ { - "author_name": "Ali Ahmed", - "author_inst": "University of Massachusetts Lowell" + "author_name": "Konstantinos Tsiakos", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Antonios Tsakiris", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Gerorgios Tsibris", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Pantazis Voutsinas", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Periklis Panagopoulos", + "author_inst": "Democritus University of Thrace" + }, + { + "author_name": "Maria Kosmidou", + "author_inst": "University of Ioannina" + }, + { + "author_name": "Vasileios Petrakis", + "author_inst": "Democritus University of Thrace" + }, + { + "author_name": "Areti Gravvani", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Theologia Gkavogianni", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Eleftherios Klouras", + "author_inst": "University of Ioannina" + }, + { + "author_name": "Konstantina Katrini", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Panagiotis Koufargyris", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Iro Rapti", + "author_inst": "University of Ioannina" + }, + { + "author_name": "Athanassios Karageorgos", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Emmanouil Vrentzos", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Christina Damoulari", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Vagia Zarkada", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Chrysanthi Sidiropoulou", + "author_inst": "Tzaneion General Hospital of Piraeus" + }, + { + "author_name": "Sofia Artemi", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Anastasios Ioannidis", + "author_inst": "University of Peloponnese, Tripoli, Greece" + }, + { + "author_name": "Androniki Papapostolou", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Evangelos Michelakis", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Maria Georgiopoulou", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Dimitra-Melia Myrodia", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Panteleimon Tsiamalos", + "author_inst": "Tzaneion General Hospital of Piraeus" + }, + { + "author_name": "Konstantinos Syrigos", + "author_inst": "National and Kapodistrian University of Athen" + }, + { + "author_name": "George Chrysos", + "author_inst": "Tzaneion General Hospital of Piraeus" + }, + { + "author_name": "Thomas Nitsotolis", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Haralampos Milionis", + "author_inst": "University of Ioannina" + }, + { + "author_name": "Garyphallia Poulakou", + "author_inst": "National and Kapodistrian University of Athens" + }, + { + "author_name": "Evangelos Giamarellos-Bourboulis", + "author_inst": "National and Kapodistrian University of Athens" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.12.23.20248444", @@ -984867,43 +984236,67 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.12.24.424203", - "rel_title": "Experimental SARS-CoV-2 infection of bank voles - general susceptibility but lack of direct transmission", + "rel_doi": "10.1101/2020.12.24.424271", + "rel_title": "Real-time monitoring epidemic trends and key mutations in SARS-CoV-2 evolution by an automated tool", "rel_date": "2020-12-24", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.24.424203", - "rel_abs": "After experimental inoculation, SARS-CoV-2 infection was proven for bank voles by seroconversion within eight days and detection of viral RNA in nasal tissue for up to 21 days. However, transmission to contact animals was not detected. Therefore, bank voles are unlikely to establish effective SARS-CoV-2 transmission cycles in nature.\n\nArticle Summary LineBank voles show low-level viral replication and seroconversion upon infection with SARS-CoV-2, but lack transmission to contact animals.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.24.424271", + "rel_abs": "With the global epidemic of SARS-CoV-2, it is important to monitor the variation, haplotype subgroup epidemic trends and key mutations of SARS-CoV-2 over time effectively, which is of great significance to the development of new vaccines, the update of therapeutic drugs, and the improvement of detection reagents. The AutoVEM tool developed in the present study could complete all mutations detections, haplotypes classification, haplotype subgroup epidemic trends and key mutations analysis for 131,576 SARS-CoV-2 genome sequences in 18 hours on a 1 core CPU and 2G internal storage computer. Through haplotype subgroup epidemic trends analysis of 131,576 genome sequences, the great significance of the previous 4 specific sites (C241T, C3037T, C14408T and A23403G) was further revealed, and 6 new mutation sites of highly linked (T445C, C6286T, C22227T, G25563T, C26801G and G29645T) were discovered for the first time that might be related to the infectivity, pathogenicity or host adaptability of SARS-CoV-2. In brief, we proposed an integrative method and developed an efficient automated tool to monitor haplotype subgroup epidemic trends and screen out the key mutations in the evolution of SARS-CoV-2 over time for the first time, and all data could be updated quickly to track the prevalence of previous key mutations and new key mutations because of high efficiency of the tool. In addition, the idea of combinatorial analysis in the present study can also provide a reference for the mutation monitoring of other viruses.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Lorenz Ulrich", - "author_inst": "Friedrich-Loeffler-Institut" + "author_name": "Binbin Xi", + "author_inst": "School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China" }, { - "author_name": "Anna Michelitsch", - "author_inst": "Friedrich-Loeffler-Institut" + "author_name": "Dawei Jiang", + "author_inst": "School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China" }, { - "author_name": "Nico Halwe", - "author_inst": "Friedrich-Loeffler-Institut" + "author_name": "Shuhua Li", + "author_inst": "School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China" }, { - "author_name": "Kerstin Wernike", - "author_inst": "Friedrich-Loeffler-Institut" + "author_name": "Jerome R Lon", + "author_inst": "School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China" }, { - "author_name": "Donata Hoffmann", - "author_inst": "Friedrich-Loeffler-Institut" + "author_name": "Yunmeng Bai", + "author_inst": "School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China" }, { - "author_name": "Martin Beer", - "author_inst": "Friedrich-Loeffler-Institut" + "author_name": "Shudai Lin", + "author_inst": "School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China" + }, + { + "author_name": "Meiling Hu", + "author_inst": "School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China" + }, + { + "author_name": "Yuhuan Meng", + "author_inst": "School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China" + }, + { + "author_name": "Yimo Qu", + "author_inst": "School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China" + }, + { + "author_name": "Yuting Huang", + "author_inst": "School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China" + }, + { + "author_name": "Wei Liu", + "author_inst": "School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China" + }, + { + "author_name": "Hongli Du", + "author_inst": "School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "genomics" }, { "rel_doi": "10.1101/2020.12.23.424254", @@ -986593,83 +985986,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.22.20248747", - "rel_title": "Patterns of SARS-CoV-2 testing preferences in a national cohort in the United States", + "rel_doi": "10.1101/2020.12.23.20248763", + "rel_title": "Spotlight on the dark figure: Exhibiting dynamics in the case detection ratio of COVID-19 infections in Germany", "rel_date": "2020-12-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.22.20248747", - "rel_abs": "In order to understand preferences about SARS-CoV-2 testing, we conducted a discrete choice experiment among 4793 participants in the Communities, Households, and SARS-CoV-2 Epidemiology (CHASING COVID) Cohort Study from July 30-September 8, 2020. We used latent class analysis to identify distinct patterns of preferences related to testing and conducted a simulation to predict testing uptake if additional testing scenarios were offered. Five distinct patterns of SARS-CoV-2 testing emerged. \"Comprehensive testers\" (18.9%) ranked specimen type as most important and favored less invasive specimen types, with saliva most preferred, and also ranked venue and result turnaround time as highly important, with preferences for home testing and fast result turnaround time. \"Fast track testers\" (26.0%) ranked result turnaround time as most important and favored immediate and same day turnaround time. \"Dual testers\" (18.5%) ranked test type as most important and preferred both antibody and viral tests. \"Non-invasive dual testers\" (33.0%) ranked specimen type and test type as similarly most important, preferring cheek swab specimen type and both antibody and viral tests. \"Home testers\" (3.6%) ranked venue as most important and favored home-based testing. By offering less invasive (saliva specimen type), dual testing (both viral and antibody tests), and at home testing scenarios in addition to standard testing scenarios, simulation models predicted that testing uptake would increase from 81.7% to 98.1%. We identified substantial differences in preferences for SARS-CoV-2 testing and found that offering additional testing options, which consider this heterogeneity, would likely increase testing uptake.\n\nSIGNIFICANCEDuring the COVID-19 pandemic, diagnostic testing has allowed for early detection of cases and implementation of measures to reduce community transmission of SARS-CoV-2 infection. Understanding individuals preferences about testing and the service models that deliver tests are relevant in efforts to increase and sustain uptake of SARS-CoV-2 testing, which, despite vaccine availability, will be required for the foreseeable future. We identified substantial differences in preferences for SARS-CoV-2 testing in a discrete choice experiment among a large national cohort of adults in the US. Offering additional testing options that account for or anticipate this heterogeneity in preferences (e.g., both viral and antibody tests, at home testing), would likely increase testing uptake.\n\nClassificationBiological Sciences (major); Psychological and Cognitive Sciences (minor)", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.23.20248763", + "rel_abs": "The case detection ratio of COVID-19 infections varies over time due to changing testing capacities, modified testing strategies and also, apparently, due to the dynamics in the number of infected itself. In this paper we investigate these dynamics by jointly looking at the reported number of detected COVID-19 infections with non-fatal and fatal outcomes in different age groups in Germany. We propose a statistical approach that allows us to spotlight the case detection ratio and quantify its changes over time. With this we can adjust the case counts reported at different time points so that they become comparable. Moreover we can explore the temporal development of the real number of infections, shedding light on the dark number. The results show that the case detection ratio has increased and, depending on the age group, is four to six times higher at the beginning of the second wave compared to what it was at the peak of the first wave. The true number of infection in Germany in October was considerably lower as during the peak of the first wave, where only a small fraction of COVID-19 infections were detected. Our modelling approach also allows quantifying the effects of different testing strategies on the case detection ratio. The analysis of the dynamics in the case detection rate and in the true infection figures enables a clearer picture of the course of the COVID-19 pandemic.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Matthew L Romo", - "author_inst": "1.\tInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, 10027 USA 2.\tDepartment of Epidemiology a" - }, - { - "author_name": "Rebecca Zimba", - "author_inst": "1.\tInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, 10027 USA" - }, - { - "author_name": "Sarah Kulkarni", - "author_inst": "1.\tInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, 10027 USA" - }, - { - "author_name": "Amanda Berry", - "author_inst": "1.\tInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, 10027 USA" - }, - { - "author_name": "William You", - "author_inst": "1.\tInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, 10027 USA" - }, - { - "author_name": "Chloe Mirzayi", - "author_inst": "1.\tInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, 10027 USA" - }, - { - "author_name": "Drew Westmoreland", - "author_inst": "1.\tInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, 10027 USA" - }, - { - "author_name": "Angela M Parcesepe", - "author_inst": "3.\tDepartment of Maternal and Child Health, Gillings School of Public Health, University of North Carolina, Chapel Hill, NC, 27599 USA 4.\tCarolina Population C" - }, - { - "author_name": "Levi Waldron", - "author_inst": "1.\tInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, 10027 USA 2.\tDepartment of Epidemiology a" - }, - { - "author_name": "Madhura Rane", - "author_inst": "1.\tInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, 10027 USA" - }, - { - "author_name": "Shivani Kochhar", - "author_inst": "1.\tInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, 10027 USA" - }, - { - "author_name": "McKaylee Robertson", - "author_inst": "1.\tInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, 10027 USA" + "author_name": "Marc Schneble", + "author_inst": "LMU Munich" }, { - "author_name": "Andrew R Maroko", - "author_inst": "1.\tInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, 10027 USA; 5.Department of Environmental" + "author_name": "Giacomo De Nicola", + "author_inst": "Department of Statistics, LMU Munich" }, { - "author_name": "Christian Grov", - "author_inst": "1.\tInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, 10027 USA; 6.\tDepartment of Community Hea" + "author_name": "Goeran Kauermann", + "author_inst": "Department of Statistics, LMU Munich" }, { - "author_name": "Denis Nash", - "author_inst": "1.\tInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, 10027 USA 2.\tDepartment of Epidemiology a" - }, - { - "author_name": "- CHASING COVID Cohort Study Team", - "author_inst": "" + "author_name": "Ursula Berger", + "author_inst": "Institute for Medical Information Processing, Biometry, and Epidemiology, LMU Munich" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.12.23.20248790", @@ -988242,69 +987587,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.12.21.20248686", - "rel_title": "Knowledge, Attitudes, and Practices of People living with SCI towards COVID-19 and their Psychological State during In-patient Rehabilitation in Bangladesh", + "rel_doi": "10.1101/2020.12.18.20248460", + "rel_title": "Bringing COVID-19 home for Christmas: a need for enhanced testing in healthcare institutions after the holidays", "rel_date": "2020-12-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.21.20248686", - "rel_abs": "Study DesignA prospective cross-sectional survey.\n\nObjectiveThe study aimed to examine the Knowledge, Attitudes, and Practices (KAP) of people living with Spinal cord injury (SCI) towards COVID-19 and their psychological status during in-patient rehabilitation in Bangladesh.\n\nSettingThe Centre for the Rehabilitation of the Paralyzed (CRP) and the National Institute of Traumatology and Orthopedic Rehabilitation (NITOR), two tertiary level hospitals in Dhaka, Bangladesh.\n\nMethodsFrom July to September 2020, a prospective, cross-sectional survey of SCI subjects, 13-78 years of age, carried out in two SCI rehab centers in Bangladesh. Data has been collected by face to face interview through a pretested, and language validated questionnaire on KAP and Depression, Anxiety, Stress (DASS). Ethical approval and trial registration obtained prospectively. As all the patients were previously living with Spinal cord injury (SCI), therefore, all the patients admitted/ attend SCI rehab centers were considered as SCI positive samples.\n\nResultsA total of 207 people with SCI responded, 87%were male, and 13% were female with mean age34.18{+/-}12.9 years. 33.8% was tetraplegic and 66.2% was paraplegic and 63.8% of them were diagnosed ASIA-A, with motor score 45.38{+/-}19.5, sensory score 97.2{+/-}52, SpO2 95.07{+/-}3.3, and Vo2max 35.7{+/-}3.7mL/kg/min. 178 people had at least one health issue. Overall knowledge score was 8.59{+/-}2.3 out of 12, depression 11.18{+/-}8, anxiety 7.72{+/-}5.1, and stress was 9.32{+/-}6.7 from a total of 21 scores each. There was a correlation between Knowledge and DASS with age (P<.05); and Knowledge with gender (P<.05), and education (P<.01). Binary logistic regression found a higher association of Knowledge and DASS with gender (OR 6.6, 6.6, .95, 6.6; P<.01); and young age (OR.418, P<.01), illiterate (OR3.81, P<.01), and rural people (OR.48, P<.05) with knowledge. A linear relation was noted between depression and anxiety scores (r.45, P<.01) and stress scores (r.58, P<.01). A positive attitude was reported for the majority of subjects. SCI Persons reported they and the caregiver followed health advisory in consulting health professionals (65.7%), isolation (63.8%), droplet precaution (87.4%), and hygiene (90.3%).\n\nConclusionsDuring in-patient rehabilitation in Bangladesh, the majority of SCI reported that they had communicated with health professionals and practiced behaviors that would reduce transmission and risk of COVID-19.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.18.20248460", + "rel_abs": "Festive gatherings this 2020 holiday season threaten to cause a surge in new cases of novel coronavirus disease 2019 (COVID-19). Hospitals and long-term care facilities are key hotspots for COVID-19 outbreaks, and may be at elevated risk as patients and staff return from holiday celebrations in the community. Some settings and institutions have proposed fortified post-holiday testing regimes to mitigate this risk. We use an existing model to assess whether implementing a single round of post-holiday screening is sufficient to detect and manage holiday-associated spikes in COVID-19 introductions to the long-term care setting. We show that while testing early helps to detect cases prior to potential onward transmission, it likely to miss a substantial share of introductions owing to false negative test results, which are more probable early in infection. We propose a two-stage post-holiday testing regime as a means to maximize case detection and mitigate the risk of nosocomial COVID-19 outbreaks into the start of the new year. Whether all patients and staff should be screened, or only community-exposed patients, depends on available testing capacity: the former will be more effective, but also more resource-intensive.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Mohammad Anwar Hossain", - "author_inst": "Centre for the Rehabilitation of the Paralysed (CRP)" - }, - { - "author_name": "Iqbal Kabir Jahid", - "author_inst": "Jashore University of Science and Technology" - }, - { - "author_name": "K M Amran Hossain", - "author_inst": "Bangladesh Health Professions Institute" - }, - { - "author_name": "Mohamed Sakel", - "author_inst": "East Kent Hospitals University NHS Foundation Trust, Canterbury, UK" - }, - { - "author_name": "Md. Feroz Kabir", - "author_inst": "Jashore University of Science and Technology" - }, - { - "author_name": "Karen Saunders", - "author_inst": "East Kent Hospitals University NHS Foundation Trust, Canterbury, UK" - }, - { - "author_name": "Rafey Faruqui", - "author_inst": "Kent & Medway NHS and Social care Partnership Trust &University of Kent, Canterbury, UK" - }, - { - "author_name": "Mohammad Sohrab Hossain", - "author_inst": "Centre for the Rehabilitation of the Paralysed (CRP)" - }, - { - "author_name": "Zakir Uddin", - "author_inst": "McMaster University" + "author_name": "David RM Smith", + "author_inst": "Institut Pasteur / Inserm / UVSQ" }, { - "author_name": "Manzur Kader", - "author_inst": "Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden" + "author_name": "Audrey Duval", + "author_inst": "Institut Pasteur / Inserm / UVSQ" }, { - "author_name": "Lori Maria Walton", - "author_inst": "University of Scranton, Pennsylvania, USA" + "author_name": "Jean Ralph Zahar", + "author_inst": "Sorbonne Paris Cite" }, { - "author_name": "Md. Obaidul Haque", - "author_inst": "Bangladesh Health Professions Institute (BHPI)" + "author_name": "Lulla Opatowski", + "author_inst": "Institut Pasteur / Inserm / UVSQ" }, { - "author_name": "Rubayet Shafin", - "author_inst": "Bangladesh Health Professions Institute" + "author_name": "Laura Temime", + "author_inst": "Conservatoire National des Arts et Metiers" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -990244,45 +989557,53 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.12.21.20248594", - "rel_title": "Risk of incident SARS-CoV-2 infection among healthcare workers in Egyptian quarantine hospitals", + "rel_doi": "10.1101/2020.12.21.20248595", + "rel_title": "Preventing a cluster from becoming a new wave in settings with zero community COVID-19 cases", "rel_date": "2020-12-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.21.20248594", - "rel_abs": "In response to the COVID-19 epidemic, Egypt established a unique care model based on quarantine hospitals where only externally-referred confirmed COVID-19 patients were admitted, and healthcare workers resided continuously over 1-to 2-week working shifts. While the COVID-19 risk for HCWs has been widely reported in standard healthcare settings, it has not been evaluated yet in quarantine hospitals.\n\nHere, we relied on longitudinal data, including results of routine RT-PCR tests, collected within three quarantine hospitals located in Cairo and Fayoum, Egypt. Using a model-based approach that accounts for the time-since-exposure variation in false-negative rates of RT-PCR tests, we computed the incidence of SARS-CoV-2 infection among HCWs. Over a total follow-up of 6,064 person-days (PD), we estimated an incidence rate (per 100 PD) of 1.05 (95% CrI: 0.58-1.65) at Hospital 1, 1.92 (95% CrI: 0.93-3.28) at Hospital 2 and 7.62 (95% CrI: 3.47-13.70) at Hospital 3. The probability for an HCW to be infected at the end of a shift was 13.7% (95% CrI: 7.8%-20.8%) and 23.8% (95% CrI: 12.2%-37.3%) for a 2-week shift at Hospital 1 and Hospital 2, respectively, which lies within the range of risk levels previously documented in standard healthcare settings, whereas it was >3-fold higher for a 7-day shift at Hospital 2 (42.6%, 95%CrI: 21.9%-64.4%). Our model-based estimates unveil a proportion of undiagnosed infections among HCWs of 46.4% (95% CrI: 18.8%-66.7%), 45.0% (95% CrI: 5.6%-70.8%) and 59.2% (95% CrI: 34.8%-78.8%), for Hospitals 1 to 3, respectively.\n\nThe large variation in SARS-CoV-2 incidence we document here suggests that HCWs from quarantine hospitals may face a high occupational risk of infection, but that, with sufficient anticipation and infection control measures, this risk can be brought down to levels similar to those observed in standard healthcare settings.\n\nWHAT THIS PAPER ADDSO_ST_ABSWhat is already known on this topicC_ST_ABSPrevious studies conducted in standard care settings have documented that frontline healthcare workers (HCWs) face high risk of COVID-19. Whether risk levels differ in alternative care models, such as COVID-19 quarantine hospitals in Egypt where HCWs resided in the hospital days and nights for various durations, is unknown.\n\nWhat this study addsCOVID-19 risk for HCWs in quarantine hospitals varies substantially between facilities, from risk levels that are in the range of those documented in standard healthcare settings to levels that were approximatively 3 times higher.\n\nHow this study might affect research, practice or policyWith sufficient anticipation and infection control measures, occupational COVID-19 risk for HCWs working in quarantine hospitals can be brought down to levels similar to those observed in standard healthcare settings.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.21.20248595", + "rel_abs": "In settings with zero community transmission, any new SARS-CoV-2 outbreaks are likely to be the result of random incursions. The level of restrictions in place at the time of the incursion is likely to considerably affect possible outbreak trajectories. We used an agent-based model to investigate the relationship between ongoing restrictions and behavioural factors, and the probability of an incursion causing an outbreak and the resulting growth rate. We applied our model to the state of Victoria, Australia, which has reached zero community transmission as of November 2020.\n\nWe found that a future incursion has a 45% probability of causing an outbreak (defined as a 7-day average of >5 new cases per day within 60 days) if no restrictions were in place, decreasing to 23% with a mandatory masks policy, density restrictions on venues such as restaurants, and if employees worked from home where possible. A drop in community symptomatic testing rates was associated with up to a 10-percentage point increase in outbreak probability, highlighting the importance of maintaining high testing rates as part of a suppression strategy.\n\nBecause the chance of an incursion occurring is closely related to border controls, outbreak risk management strategies require an integrated approaching spanning border controls, ongoing restrictions, and plans for response. Each individual restriction or control strategy reduces the risk of an outbreak. They can be traded off against each other, but if too many are removed there is a danger of accumulating an unsafe level of risk. The outbreak probabilities estimated in this study are of particular relevance in assessing the downstream risks associated with increased international travel.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Sofia Jijon", - "author_inst": "Conservatoire national des Arts et Metiers" + "author_name": "Romesh G Abeysuriya", + "author_inst": "Burnet Institute; Monash University" }, { - "author_name": "Ahmad Al Shafie", - "author_inst": "Helwan University" + "author_name": "Dominic Delport", + "author_inst": "Burnet Institute" }, { - "author_name": "Essam Hassan", - "author_inst": "Tropical Medicine Department Faculty of Medicine, Fayoum University" + "author_name": "Robyn Margaret Stuart", + "author_inst": "University of Copenhagen; Burnet Institute" }, { - "author_name": "- the EMEA-MESuRS working group on nosocomial SARS-CoV-2 modelling", - "author_inst": "" + "author_name": "Rachel Sacks-Davis", + "author_inst": "Burnet Institute" }, { - "author_name": "Laura Temime", - "author_inst": "Conservatoire national des Arts et Metiers" + "author_name": "Cliff C Kerr", + "author_inst": "Institute for Disease Modeling; University of Sydney" }, { - "author_name": "Kevin Jean", - "author_inst": "Conservatoire national des Arts et Metiers" + "author_name": "Dina Mistry", + "author_inst": "Institute for Disease Modeling" }, { - "author_name": "Mohamed El Kassas", - "author_inst": "Helwan University" + "author_name": "Daniel J Klein", + "author_inst": "Institute for Disease Modeling" + }, + { + "author_name": "Margaret Hellard", + "author_inst": "Burnet Institute; Monash University" + }, + { + "author_name": "Nick Scott", + "author_inst": "Burnet Institute; Monash University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -991490,57 +990811,89 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.12.19.20248535", - "rel_title": "Development and Evaluation of Two Rapid Indigenous IgG-ELISA immobilized with ACE-2 Binding Peptides for Detection Neutralizing Antibodies Against SARS-CoV-2", + "rel_doi": "10.1101/2020.12.19.20248551", + "rel_title": "Immunogenicity and crossreactivity of antibodies to SARS-CoV-2 nucleocapsid protein", "rel_date": "2020-12-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.19.20248535", - "rel_abs": "COVID-19 pandemic situation demands effective serological tests with a view to adopting and developing policy for disease management, determining protective immunity as well as for sero-epidemiological study. Our study aims to develop and evaluate two rapid in-house ELISA assays targeting neutralizing antibodies (IgG) against S1 subunit of spike in SARS-CoV-2 and Receptor Binding Domain (RBD), as well as comparative analysis with nucleocapsid (NCP) ELISA. The assays were conducted with 184 samples in three panels collected from 134 patients. Panel 1 and 2 consist of RT-PCR positive samples collected within two weeks and after two weeks of symptom onset, respectively. Negative samples are included in panel 3 from healthy donors and pre-pandemic dengue patients. The total assay time has been set 30 minutes for both of the ELISA assays. Results show that S1 and RBD ELISA demonstrates 73.68% and 84.21% sensitivities, respectively for samples collected within two weeks, whereas 100% sensitivities were achieved by both for samples that were collected after two weeks of the onset of symptoms. S1-ELISA shows 0% positivity to panel 3 while for RBD-ELISA the figure is 1%. A strong correlation (rs=0.804, p<0.0001)) has been observed between these two assays. When compared with NCP-ELISA, S1 slightly better correlation (rs=0.800, p<0.0001) than RBD (rs=0.740, p<0.0001). Our study suggests S1-ELISA as more sensitive one than the RBD or nucleocapsid ELISA during the later phase of infection, while for overall sero-monitoring RBD specific IgG ELISA is recommended. Moreover, non-reactivity to dengue emphasize the use of these assays for serosurveillance of COVID-19 in the dengue endemic regions.\n\nHighlightsO_LIThe total assay time of these assays are 30 minutes.\nC_LIO_LISensitivity of S1 specific IgG ELISA for samples tested within 14 days of disease presentation is 73.68% while RBD specific ELISA demonstrates a sensitivity of 84.21%,\nC_LIO_LIBoth of the assays under investigation can successfully detect all the cases (100% sensitivity) if the samples are tested after 14 days of onset of diseases.\nC_LIO_LISpecificity of S1-ELISA assay is 100%, whereas RBD specific IgG ELISA is 99% specific.\nC_LIO_LIThe assays can be employed in dengue-endemic countries\nC_LIO_LIAmong the three in-house IgG ELISA, assay system specific to S1 is found to be more sensitive and specific for retrospective serosurveillance.\nC_LIO_LIFor acute to late phase, as well as retrospective serosurveillance of COVID-19, RBD-ELISA can be a method of choice for SARS-CoV-2 prevalent areas.\nC_LI", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.19.20248551", + "rel_abs": "COVID-19 patients elicit strong responses to the nucleocapsid (N) protein of SARS-CoV-2 but binding antibodies are also detected in prepandemic individuals, indicating potential crossreactivity with common cold human coronaviruses (HCoV) and questioning its utility in seroprevalence studies. We investigated the immunogenicity of the full-length and shorter fragments of the SARS-CoV-2 N protein, and the crossreactivity of antibodies with HCoV. We indentified a C-terminus region in SARS-CoV2 N of minimal sequence homology with HCoV that was more specific and highly immunogenic. IgGs to the full-length SARS-CoV-2 N also recognised N229E N, and IgGs to HKU1 N recognised SARS-CoV-2 N. Crossreactivity with SARS-CoV-2 was stronger for alpha-rather than beta-HCoV despite having less sequence identity, revealing the importance of conformational recognition. Higher preexisting IgG to OC43 N correlated with lower IgG to SARS-CoV-2 in rRT-PCR negative individuals, reflecting less exposure and indicating a potential protective association. Antibodies to SARS-CoV-2 N were higher in patients with more severe and longer symptoms and in females. IgGs remained stable for at least 3 months, while IgAs and IgMs declined faster. In conclusion, N is a primary target of SARS-CoV-2-specific and HCoV crossreactive antibodies, both of which may affect the acquisition of immunity to COVID-19.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Bijon Kumar Sil", - "author_inst": "Gonoshasthaya-RNA Molecular Diagnostic and Research Center" + "author_name": "Carlota Dobano", + "author_inst": "ISGlobal" }, { - "author_name": "Nihad Adnan", - "author_inst": "Jahangirnagar University" + "author_name": "Rebeca Santano", + "author_inst": "ISGlobal" + }, + { + "author_name": "Alfons Jimenez", + "author_inst": "ISGlobal" }, { - "author_name": "Mumtarin Jannat Oishee", - "author_inst": "Gonoshasthaya-RNA Molecular Diagnostic and Research Center, Dhanmondi" + "author_name": "Marta Vidal", + "author_inst": "ISGlobal" }, { - "author_name": "Tamanna Ali", - "author_inst": "Gonoshasthaya-RNA Molecular Diagnostic and Research Center" + "author_name": "Jordi Chi", + "author_inst": "ISGlobal" }, { - "author_name": "Nowshin Jahan", - "author_inst": "Gonoshasthaya-RNA Molecular Diagnostic and Research Center" + "author_name": "Natalia Rodrigo Melero", + "author_inst": "CRG" }, { - "author_name": "Shahad Saif Khandker", - "author_inst": "Gonoshasthaya-RNA Molecular Diagnostic and Research Center" + "author_name": "Matija Popovic", + "author_inst": "ISGlobal" }, { - "author_name": "Eiry Kobatake", - "author_inst": "Department of Life Science and Technology, School of Life Science and Technology, Tokyo Institute of Technology" + "author_name": "Ruben Lopez-Aladid", + "author_inst": "IDIBAPS" }, { - "author_name": "Masayasu Mie", - "author_inst": "Department of Life Science and Technology, School of Life Science and Technology, Tokyo Institute of Technology" + "author_name": "Laia Fernandez-Barat", + "author_inst": "IDIBAPS" }, { - "author_name": "Dr. Mohib Ullah Khondoker", - "author_inst": "Gonoshasthaya Samaj Vittik Medical College" + "author_name": "Marta Tortajada", + "author_inst": "Hospital Clinic" }, { - "author_name": "Md. Ahsanul Haq", - "author_inst": "Gonoshasthaya-RNA Molecular Diagnostic and Research Center" + "author_name": "Francisco Carmona-Torre", + "author_inst": "Clinica Universidad de Navarra" }, { - "author_name": "Mohd. Raeed Jamiruddin", - "author_inst": "Brac University" + "author_name": "Gabriel Reina", + "author_inst": "Clinica Universidad de Navarra" + }, + { + "author_name": "Antoni Torres", + "author_inst": "Hospital Clinic" + }, + { + "author_name": "Alfredo Mayor", + "author_inst": "ISGlobal" + }, + { + "author_name": "Carlo Carolis", + "author_inst": "CRG" + }, + { + "author_name": "Alberto L Garcia-Basteiro", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Ruth Aguilar", + "author_inst": "ISGlobal" + }, + { + "author_name": "Gemma Moncunill", + "author_inst": "ISGlobal" + }, + { + "author_name": "Luis Izquierdo", + "author_inst": "ISGlobal" } ], "version": "1", @@ -993772,47 +993125,127 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.12.21.423869", - "rel_title": "In Vitro Safety Clinical Trial of the Cardiac Liability of Hydroxychloroquine and Azithromycin as COVID19 Polytherapy", + "rel_doi": "10.1101/2020.12.18.422865", + "rel_title": "The Ensembl COVID-19 resource: Ongoing integration of public SARS-CoV-2 data", "rel_date": "2020-12-22", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.21.423869", - "rel_abs": "Despite global efforts, there are no effective FDA-approved medicines for the treatment of SARS-CoV-2 infection. Potential therapeutics focus on repurposed drugs, some with cardiac liabilities. Here we report on a preclinical drug screening platform, a cardiac microphysiological system (MPS), to assess cardiotoxicity associated with hydroxychloroquine (HCQ) and azithromycin (AZM) polytherapy in a mock clinical trial. The MPS contained human heart muscle derived from patient-specific induced pluripotent stem cells. The effect of drug response was measured using outputs that correlate with clinical measurements such as QT interval (action potential duration) and drug-biomarker pairing.\n\nChronic exposure to HCQ alone elicited early afterdepolarizations (EADs) and increased QT interval from day 6 onwards. AZM alone elicited an increase in QT interval from day 7 onwards and arrhythmias were observed at days 8 and 10. Monotherapy results closely mimicked clinical trial outcomes. Upon chronic exposure to HCQ and AZM polytherapy, we observed an increase in QT interval on days 4-8.. Interestingly, a decrease in arrhythmias and instabilities was observed in polytherapy relative to monotherapy, in concordance with published clinical trials. Furthermore, biomarkers, most of them measurable in patients serum, were identified for negative effects of single drug or polytherapy on tissue contractile function, morphology, and antioxidant protection.\n\nThe cardiac MPS can predict clinical arrhythmias associated with QT prolongation and rhythm instabilities. This high content system can help clinicians design their trials, rapidly project cardiac outcomes, and define new monitoring biomarkers to accelerate access of patients to safe COVID-19 therapeutics.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.18.422865", + "rel_abs": "The COVID-19 pandemic has seen unprecedented use of SARS-CoV-2 genome sequencing for epidemiological tracking and identification of emerging variants. Understanding the potential impact of these variants on the infectivity of the virus and the efficacy of emerging therapeutics and vaccines has become a cornerstone of the fight against the disease. To support the maximal use of genomic information for SARS-CoV-2 research, we launched the Ensembl COVID-19 browser, incorporating a new Ensembl gene set, multiple variant sets (including novel variation calls), and annotation from several relevant resources integrated into the reference SARS-CoV-2 assembly. This work included key adaptations of existing Ensembl genome annotation methods to model ribosomal slippage, stringent filters to elucidate the highest confidence variants and utilisation of our comparative genomics pipelines on viruses for the first time. Since May 2020, the content has been regularly updated and tools such as the Ensembl Variant Effect Predictor have been integrated. The Ensembl COVID-19 browser is freely available at https://covid-19.ensembl.org.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Berenice Charrez", - "author_inst": "UC Berkeley" + "author_name": "Nishadi H. De Silva", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" }, { - "author_name": "Verena Charwat", - "author_inst": "UC berkeley" + "author_name": "Jyothish Bhai", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" }, { - "author_name": "Brian Siemons", - "author_inst": "UC Berkeley" + "author_name": "Marc Chakiachvili", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" }, { - "author_name": "Henrik Finsberg", - "author_inst": "simula research laboratory" + "author_name": "Bruno Contreras-Moreira", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" }, { - "author_name": "Andrew Edwards", - "author_inst": "UC Davis" + "author_name": "Carla Cummins", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" }, { - "author_name": "Evan Miller", - "author_inst": "University of California, Berkeley" + "author_name": "Adam Frankish", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" }, { - "author_name": "Kevin Healy", - "author_inst": "UC Berkeley" + "author_name": "Astrid Gall", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Thiago Genez", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Kevin L. Howe", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Sarah E. Hunt", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Fergal J. Martin", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Benjamin Moore", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Denye Ogeh", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Anne Parker", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Andrew Parton", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Magali Ruffier", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Manoj Pandian Sakthivel", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Dan Sheppard", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "John Tate", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Anja Thormann", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "David Thybert", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Stephen J. Trevanion", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Andrea Winterbottom", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Daniel R. Zerbino", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Robert D. Finn", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Paul Flicek", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" + }, + { + "author_name": "Andrew D. Yates", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "new results", - "category": "bioengineering" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.12.22.423893", @@ -995598,18 +995031,163 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.12.19.423592", - "rel_title": "The polybasic cleavage site in the SARS-CoV-2 spike modulates viral sensitivity to Type I IFN and IFITM2", + "rel_doi": "10.1101/2020.12.18.423552", + "rel_title": "Sterilizing immunity against SARS-CoV-2 in hamsters conferred by a novel recombinant subunit vaccine", "rel_date": "2020-12-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.19.423592", - "rel_abs": "The cellular entry of severe acute respiratory syndrome-associated coronaviruses types 1 and 2 (SARS-CoV-1 and -2) requires sequential protease processing of the viral spike glycoprotein (S). The presence of a polybasic cleavage site in SARS-CoV-2 S at the S1/S2 boundary has been suggested to be a factor in the increased transmissibility of SARS-CoV-2 compared to SARS-CoV-1 by facilitating maturation of the S precursor by furin-like proteases in the producer cells rather than endosomal cathepsins in the target. We investigate the relevance of the polybasic cleavage site in the route of entry of SARS-CoV-2 and the consequences this has for sensitivity to interferons, and more specifically, the IFN-induced transmembrane (IFITM) protein family that inhibit entry of diverse enveloped viruses. We found that SARS-CoV-2 is restricted predominantly by IFITM2 and the degree of this restriction is governed by route of viral entry. Removal of the cleavage site in the spike protein renders SARS-CoV-2 entry highly pH- and cathepsin-dependent in late endosomes where, like SARS-CoV-1 S, it is more sensitive to IFITM2 restriction. Furthermore, we find that potent inhibition of SARS-CoV-2 replication by type I but not type II IFNs is alleviated by targeted depletion of IFITM2 expression. We propose that the polybasic cleavage site allows SARS-CoV-2 to mediate viral entry in a pH-independent manner, in part to mitigate against IFITM-mediated restriction and promote replication and transmission. This suggests therapeutic strategies that target furin-mediated cleavage of SARS-CoV-2 S may reduce viral replication through the activity of type I IFNs.\n\nIMPORTANCEThe furin cleavage site in the S protein is a distinguishing feature of SARS-CoV-2 and has been proposed to be a determinant for the higher transmissibility between individuals compared to SARS-CoV-1. One explanation for this is that it permits more efficient activation of fusion at or near the cell surface rather than requiring processing in the endosome of the target cell. Here we show that SARS-CoV-2 is inhibited by antiviral membrane protein IFITM2, and that the sensitivity is exacerbated by deletion of the furin cleavage site which restricts viral entry to low pH compartments. Furthermore, we find that IFITM2 is a significant effector of the antiviral activity of type I interferons against SARS-CoV-2 replication. We suggest one role of the furin cleavage site is to reduce SARS-CoV-2 sensitivity to innate immune restriction, and thus may represent a potential therapeutic target for COVID-19 treatment development.", - "rel_num_authors": 0, - "rel_authors": null, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.18.423552", + "rel_abs": "A safe and effective SARS-CoV-2 vaccine is essential to avert the on-going COVID-19 pandemic. Here, we developed a subunit vaccine, which is comprised of CHO-expressed spike ectodomain protein (StriFK) and nitrogen bisphosphonates-modified zinc-aluminum hybrid adjuvant (FH002C). This vaccine candidate rapidly elicited the robust humoral response, Th1/Th2 balanced helper CD4 T cell and CD8 T cell immune response in animal models. In mice, hamsters, and non-human primates, 2-shot and 3-shot immunization of StriFK-FH002C generated 28- to 38-fold and 47- to 269-fold higher neutralizing antibody titers than the human COVID-19 convalescent plasmas, respectively. More importantly, the StriFK-FH002C immunization conferred sterilizing immunity to prevent SARS-CoV-2 infection and transmission, which also protected animals from virus-induced weight loss, COVID-19-like symptoms, and pneumonia in hamsters. Vaccine-induced neutralizing and cell-based receptor-blocking antibody titers correlated well with protective efficacy in hamsters, suggesting vaccine-elicited protection is immune-associated. The StriFK-FH002C provided a promising SARS-CoV-2 vaccine candidate for further clinical evaluation.", + "rel_num_authors": 36, + "rel_authors": [ + { + "author_name": "yangtao wu", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Xiaofen Huang", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Lunzhi Yuan", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Shaojuan Wang", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Yali Zhang", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Hualong Xiong", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Rirong Chen", + "author_inst": "State Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Hong Kong, P. R. China." + }, + { + "author_name": "Jian Ma", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Ruoyao Qi", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Meifeng Nie", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Jingjing Xu", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Zhigang Zhang", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Liqiang Chen", + "author_inst": "State Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Hong Kong, P. R. China." + }, + { + "author_name": "Min Wei", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Ming Zhou", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Minping Cai", + "author_inst": "State Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Hong Kong, P. R. China." + }, + { + "author_name": "Yang Shi", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Liang Zhang", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Huan Yu", + "author_inst": "State Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Hong Kong, P. R. China." + }, + { + "author_name": "Junping Hong", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Zikang Wang", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Yunda Hong", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Mingxi Yue", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Zonglin Li", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Dabing Chen", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Qingbing Zheng", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Shaowei Li", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Yixin Chen", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Tong Cheng", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Jun Zhang", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Tianying Zhang", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Huacheng Zhu", + "author_inst": "State Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Hong Kong, P. R. China." + }, + { + "author_name": "Qinjian Zhao", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Quan Yuan", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + }, + { + "author_name": "Yi Guan", + "author_inst": "State Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Hong Kong, P. R. China." + }, + { + "author_name": "NingShao Xia", + "author_inst": "State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Schoo" + } + ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.12.19.423597", @@ -997571,41 +997149,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.18.20248452", - "rel_title": "Current evidence for COVID-19 therapies: a systematic literature review", + "rel_doi": "10.1101/2020.12.18.20248450", + "rel_title": "On the timing of interventions to preserve hospital capacity: lessons to be learned from the Belgian SARS-CoV-2 pandemic", "rel_date": "2020-12-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.18.20248452", - "rel_abs": "Effective therapeutic interventions for the treatment and prevention of COVID-19 are urgently needed. A systematic review was conducted to identify clinical trials of pharmacological interventions for COVID-19 published between 1 December 2019 and 14 October 2020. Data regarding efficacy of interventions, in terms of mortality, hospitalisation and need for ventilation, were extracted from identified studies and synthesised qualitatively.\n\nIn total, 42 clinical trials were included. Interventions assessed included antiviral, mucolytic, anti-malarial, anti-inflammatory and immunomodulatory therapies. Some reductions in mortality, hospitalisation and need for ventilation were seen with interferons and remdesivir, particularly when administered early, and with the mucolytic drug, bromhexine. Most studies of lopinavir/ritonavir and hydroxychloroquine did not show significant efficacy over standard care/placebo. Dexamethasone significantly reduced mortality, hospitalisation and need for ventilation versus standard care, particularly in patients with severe disease. Evidence for other classes of interventions was limited. Many trials had a moderate-to-high risk of bias, particularly in terms of blinding; most were short-term; and some included low patient numbers.\n\nThis review highlights the need for well-designed clinical trials of therapeutic interventions for COVID-19 to increase the quality of available evidence. It also emphasises the importance of tailoring interventions to disease stage and severity for maximum efficacy.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.18.20248450", + "rel_abs": "Using publicly available data on the number of new hospitalisations we use a newly developed phase portrait to monitor the epidemic allowing for assessing whether or not intervention measures are needed to keep hospital capacity under control. Using this phase portrait, we show that intervention measures were effective in mitigating a Summer resurgence but that too little too late was done to prevent a large autumn wave in Belgium.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Tobias Welte", - "author_inst": "Department of Pulmonary and Infectious Diseases, Hannover University School of Medicine, Germany" - }, - { - "author_name": "Lucy J. Ambrose", - "author_inst": "Prime Global, Oxford, UK" - }, - { - "author_name": "Gillian C. Sibbring", - "author_inst": "Prime Global, Knutsford, UK" - }, - { - "author_name": "Shehla Sheikh", - "author_inst": "AstraZeneca, Cambridge, UK" + "author_name": "Niel Hens", + "author_inst": "Hasselt University and University of Antwerp" }, { - "author_name": "Hana M\u00fcllerov\u00e1", - "author_inst": "AstraZeneca, Cambridge, UK" + "author_name": "Christel Faes", + "author_inst": "Hasselt University" }, { - "author_name": "Ian Sabir", - "author_inst": "AstraZeneca, Cambridge, UK" + "author_name": "Marius Gilbert", + "author_inst": "Universite Libre de Bruxelles" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -999461,67 +999027,71 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.16.20248243", - "rel_title": "Association of working shifts, inside and outside of healthcare, with risk of severe COVID-19: An observational study", + "rel_doi": "10.1101/2020.12.15.20246819", + "rel_title": "PTSD symptoms related to COVID-19 as a high risk factor for suicide - Key to prevention", "rel_date": "2020-12-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.16.20248243", - "rel_abs": "BackgroundHealth and key workers are at an increased risk of developing severe COVID-19; it is not known, however, if this risk is exacerbated in those with irregular work patterns. We aimed to investigate the risk of severe COVID-19 in health and shift workers.\n\nMethodsWe included UK Biobank participants in employment or self-employed at baseline and with linked COVID-19 data to 31st August 2020. Participants were grouped as neither a health worker nor shift worker (reference category), health worker only, shift worker only, or both and associations with severe COVID-19 investigated in logistic regressions.\n\nFindingsOf 235,685 participants (81{middle dot}5% neither health nor shift worker, 1{middle dot}4% health worker only, 16{middle dot}9% shift worker only, and 0{middle dot}3% both), there were 580 (0{middle dot}25%) cases of severe COVID-19. The risk of severe COVID-19 was higher in health workers (adjusted odds ratio: 2.32 [95% CI: 1{middle dot}33, 4{middle dot}05]; shift workers (2{middle dot}06 [1{middle dot}72, 2{middle dot}47]); and in health workers who worked shifts (7{middle dot}56 [3{middle dot}86, 14{middle dot}79]). Being both a health worker and a shift worker had a possible greater impact on the risk severe COVID-19 in South Asian and Black and African Caribbean ethnicities compared to White individuals.\n\nInterpretationBoth health and shift work were independently associated with over twice the risk of severe COVID-19; the risk was over seven times higher in health workers who work shifts. Vaccinations, therapeutic and preventative options should take into consideration not only health and key worker status but also shift worker status.\n\nFundingNational Institute for Health Research, UK Research and Innovation.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThe risk of developing severe COVID-19 is greater in occupational groups with higher levels of viral exposure, e.g. health and key workers. We searched PubMed and medRxiv up to December 8, 2020 for papers on shift work patterns, health work and incidence of COVID-19 using the keywords \"COVID-19\", \"SARS-CoV-2\", \"shift work\" \"health worker\". Recent evidence suggests shift workers are also at increased risk of severe COVID-19 but it is not clear if the risk is exacerbated in those who work shifts in healthcare.\n\nAdded value of this studyThis study uses data from UK Biobank, a prospective cohort of >500,000 adults aged 40-69 years with baseline assessments between March 2006 and July 2010. Participants occupation was categorised according to whether or not they were health workers and/or shift workers at baseline. Results showed that being a health worker, or working shifts, were similarly and independently associated with over twice the population level risk of severe COVID-19 independent of age, sex, ethnicity, deprivation and co-morbidities. The risk was seven times higher in health workers with shift working patterns. The impact of health and shift work tended to be higher in males and in minority ethnic groups, who are already at an increased risk of severe COVID-19. In people over the age of retirement, the risk of developing severe COVID-19 associated with baseline health worker status was no longer apparent, suggesting the risk is likely explained by exposure to the virus. However, the elevated risk associated with baseline shift worker status persisted, albeit attenuated.\n\nImplications of all the available evidenceShift workers are at elevated risk of developing severe COVID-19. The persistence of an elevated risk in people who are now over retirement age, but had a shift worker status at baseline, suggests the risk may not be fully explained by increased exposure to the virus. Vaccination, therapeutic and prevention programmes are being prioritised for health care workers. Our data suggests that shift workers should also be prioritised for these preventive measures.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.15.20246819", + "rel_abs": "BackgroundRising rates of suicide, the most dreadful consequence of mental health effects elicited by the coronavirus pandemic (COVID-19) are cause for grave concern. However, the exact association between mental health problems and suicide remains largely unknown in relation to COVID-19.\n\nMethodsTo determine the impact of COVID-19 on suicide trajectory, we used an interrupted time-series design to analyze monthly suicides rates extracted from Japans national database. We next used mixed-effects regression models to investigate the relationship between the nationwide suicide increase in August 2020 and psychiatric states of 4,348 individuals from an online survey performed immediately before (December 2019) and during (August 2020) the pandemic. Psychiatric states included depression, anxiety, and COVID-19-related PTSD, a form of severe event-related stress.\n\nFindingsIn Japan, suicides had gradually decreased before COVID-19 ({beta} = -0{middle dot}7x10-3, t57 = -14{middle dot}2, p = 8{middle dot}6x10-46), but increased drastically after a state of emergency was declared in April 2020 ({beta} = 0{middle dot}9x10-2, t57 = 17{middle dot}3, p = 2{middle dot}3x10-67). We found that PTSD symptoms reliably predict COVID-19s impact on suicide rates ({beta} = 6{middle dot}3x10-4, t3936 = 5{middle dot}96, p = 2{middle dot}7x10-9). In contrast, depression scores are a reliable indicator of stress vulnerability (i.e. future suicide increases, {beta} = 0{middle dot}001, t3936 = 6{middle dot}6, p = 4{middle dot}5x10-11). Simulations revealed that a one-point reduction in PTSD score could decrease suicides by up to 3{middle dot}1 per ten million people per month in Japan.\n\nInterpretationPTSD symptoms may help to identify high-risk groups so as to increase efficacy of prevention policies.\n\nFundingKDDI collaborative research contract, the Innovative Science and Technology Initiative for Security (JPJ004596), ATLA and AMED (JP20dm0307008).\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed on December 2, 2020, for \"COVID\" and \"suicid*\" in the titles or abstracts of published articles and obtained 269 hits. No language restrictions were applied to the search. Nearly all previous articles on suicide and COVID-19 have reported simulation studies of suicide counts and rates in case studies, editorials, letters, and commentaries. To date, no study has analyzed the association between psychiatric states and suicide increases in the context of the COVID-19 pandemic.\n\nAdded value of this studyTo the best of our knowledge, this is the first study reporting a concrete approach to predict suicide rate increases from psychiatric states during the COVID-19 pandemic. Our findings indicate that PTSD symptoms are a reliable surrogate endpoint of pandemic-related suicide increase.\n\nImplications of all available evidenceThis work provides a new perspective on preparing guidelines for suicide prevention. Efforts should focus on reducing PTSD severity for single individuals and populations to reduce the overall suicide risk.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Alex Rowlands", - "author_inst": "University of Leicester" + "author_name": "Toshinori Chiba", + "author_inst": "Advanced Telecommunications Research Institute International" }, { - "author_name": "Clare Gillies", - "author_inst": "University of Leicester" + "author_name": "Taiki Oka", + "author_inst": "Advanced Telecommunications Research Institute International" }, { - "author_name": "Yogini Chudasama", - "author_inst": "University of Leicester" + "author_name": "Toshitaka Hamamura", + "author_inst": "Innovation center KDDI Research, Inc" }, { - "author_name": "Melanie Davies", - "author_inst": "Leicester General Hospital" + "author_name": "Nao Kobayashi", + "author_inst": "KDDI CORPORATION" }, { - "author_name": "Nazrul Islam", - "author_inst": "University of Oxford" + "author_name": "Masaru Honjo", + "author_inst": "Innovation center KDDI Research, Inc" }, { - "author_name": "David Kloecker", - "author_inst": "University of Leicester" + "author_name": "Yuka Miyake", + "author_inst": "KDDI CORPORATION" }, { - "author_name": "Claire Lawson", - "author_inst": "University of Leicester" + "author_name": "Takatomi Kubo", + "author_inst": "Advanced Telecommunications Research Institute International" }, { - "author_name": "Manish Pareek", - "author_inst": "University of Leicester" + "author_name": "Hiroyuki Toda", + "author_inst": "National Defense Medical College" }, { - "author_name": "Cameron Razieh", - "author_inst": "University of Leicester" + "author_name": "Akitoyo Hishimoto", + "author_inst": "Yokohama City University Graduate School of Medicine" }, { - "author_name": "Francesco Zaccardi", - "author_inst": "University of Leicester" + "author_name": "Shuken Boku", + "author_inst": "Kumamoto University Faculty of Life Sciences" }, { - "author_name": "Thomas Yates", - "author_inst": "University of Leicester" + "author_name": "Tetsufumi Kanazawa", + "author_inst": "Osaka Medical College" }, { - "author_name": "Kamlesh Khunti", - "author_inst": "University of Leicester" + "author_name": "Mitsuo Kawato", + "author_inst": "Advanced Telecommunications Research Institute International" + }, + { + "author_name": "Aurelio Cortese", + "author_inst": "Advanced Telecommunications Research Institute International" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2020.12.17.20248382", @@ -1001079,39 +1000649,31 @@ "category": "oncology" }, { - "rel_doi": "10.1101/2020.12.11.20203224", - "rel_title": "Physiological Effects of Exercising at Different Intensities Wearing TNT or Double-layer Cotton Facemasks Compared to Not Wearing a Mask", + "rel_doi": "10.1101/2020.12.16.423118", + "rel_title": "Modelling conformational state dynamics and its role on infection for SARS-CoV-2 Spike protein variants", "rel_date": "2020-12-17", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.11.20203224", - "rel_abs": "We compared the physiological differences between exercising wearing a TNT or a double-layer-cotton (DLC) facemask (FM) and not wearing a mask (NM). Sixteen volunteers underwent 4 sets (S) of 2 sequential bouts (B). B1 and B2 corresponded to light and moderate intensity cycling, respectively. FMs were used as follows: S1: NM; S2: TNT or DLC; S3: DLC or TNT; and S4: NM. Metabolic, pulmonary, and perceptual variables were collected. The main results are expressed as effect sizes and confidence intervals (ES [95%CI]) for TNT and DLC unless otherwise indicated. Compared to NM, FM increased the duty cycle (B1=1.11[0.58-1.61] and 1.53[0.81-2.18]; B2=1.27[0.63-1.84] and 1.93[0.97-2.68]) and decreased breath frequency (B1=0.59[0.23-0.94] and 1.43[0.79-2.07], B2=0.39[0.05-0.71] and 1.33[0.71-1.94]). Only B1 tidal volume increased (0.33[0.09-0.56] and 0.62[0.18-1.05]) enough to avoid a ventilation reduction with TNT but not with DLC (B1=0.52[0.23-0.79]; B2=0.84[0.44-1.22]). Both FMs reduced oxygen saturation in B1 (0.56 [0.07-1.03] and 0.69 [0.09-1.28]) but only DLC did so in B2 (0.66 [0.11-1.13]). Both end tidal CO2 (B1=0.23[0.05-0.4] and 0.71[0.38-1.02]; B2=0.56[0.2-0.9] and 1.20[0.65-1.68]) and mixed-expired-CO2 (B1=0.74[0.38-1.08] 1.71[1.03-2.37], B2=0.94[0.45-1.38] and 1.78[0.97-2.42]) increased with FMs. Ventilatory adaptations imposed during FM exercising influenced blood-lung gas exchange. Larger ESs were seen with DLC. No adverse changes to human health were observed.\n\nNovelty BulletsO_LIFacemasks affect the breathing pattern by changing the frequency and amplitude of pulmonary ventilation.\nC_LIO_LIThe augmented ventilatory work increases VO2, VCO2, and RPE and promotes non-concerning drops in SpO2 and CO2 retention.\nC_LIO_LIIncreased inspiratory and expiratory pressure can account for the reduction in pulmonary physiological dead space.\nC_LI", - "rel_num_authors": 5, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.16.423118", + "rel_abs": "The SARS-CoV-2 Spike protein needs to be in an open-state conformation to interact with ACE2 as part of the viral entry mechanism. We utilise coarse-grained normal-mode analyses to model the dynamics of Spike and calculate transition probabilities between states for 17081 Spike variants. Our results correctly model an increase in open-state occupancy for the more infectious D614G via an increase in flexibility of the closed-state and decrease of flexibility of the open-state. We predict the same effect for several mutations on Glycine residues (404, 416, 504, 252) as well as residues K417, D467 and N501, including the N501Y mutation, explaining the higher infectivity of the B.1.1.7 and 501.V2 strains. This is, to our knowledge, the first use of normal-mode analysis to model conformational state transitions and the effect of mutations thereon. The specific mutations of Spike identified here may guide future studies to increase our understanding of SARS-CoV-2 infection mechanisms and guide public health in their surveillance efforts.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Fabricio Braga", - "author_inst": "Laboratorio de Performance Humana" - }, - { - "author_name": "Gabriel Espinosa", - "author_inst": "Laboratorio de Performance Humana" - }, - { - "author_name": "Amanda Monteiro", - "author_inst": "Laboratorio de Performance Humana" + "author_name": "Nat\u00e1lia Teruel", + "author_inst": "Universit\u00e9 de Montr\u00e9al" }, { - "author_name": "Beatriz Marinho", - "author_inst": "Laboratorio de Performance Humana" + "author_name": "Olivier Mailhot", + "author_inst": "Universit\u00e9 de Montr\u00e9al" }, { - "author_name": "Eduardo Drummond", - "author_inst": "Laboratorio de Performance Humana" + "author_name": "Rafael Najmanovich", + "author_inst": "Universit\u00e9 de Montr\u00e9al" } ], "version": "1", - "license": "cc_by_nc", - "type": "PUBLISHAHEADOFPRINT", - "category": "sports medicine" + "license": "cc_by", + "type": "new results", + "category": "biophysics" }, { "rel_doi": "10.1101/2020.12.17.423130", @@ -1002629,77 +1002191,173 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2020.12.15.20248264", - "rel_title": "Development of a Rapid Point-Of-Care Test that Measures Neutralizing Antibodies to SARS-CoV-2", + "rel_doi": "10.1101/2020.12.15.20247031", + "rel_title": "Diagnostic accuracy of Loop mediated isothermal amplification coupled to Nanopore sequencing for the detection of SARS-CoV-2 infection at scale in symptomatic and asymptomatic populations", "rel_date": "2020-12-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.15.20248264", - "rel_abs": "BackgroundAfter receiving a COVID-19 vaccine, most recipients want to know if they are protected from infection and for how long. Since neutralizing antibodies are a correlate of protection, we developed a lateral flow assay (LFA) that measures levels of neutralizing antibodies from a drop of blood. The LFA is based on the principle that neutralizing antibodies block binding of the receptor-binding domain (RBD) to angiotensin-converting enzyme 2 (ACE2).\n\nMethodsThe ability of the LFA was assessed to correctly measure neutralization of sera, plasma or whole blood from patients with COVID-19 using SARS-CoV-2 microneutralization assays. We also determined if the LFA distinguished patients with seasonal respiratory viruses from patients with COVID-19. To demonstrate the usefulness of the LFA, we tested previously infected and non-infected COVID-19 vaccine recipients at baseline and after first and second vaccine doses.\n\nResultsThe LFA compared favorably with SARS-CoV-2 microneutralization assays with an area under the ROC curve of 98%. Sera obtained from patients with seasonal coronaviruses did not show neutralizing activity in the LFA. After a single mRNA vaccine dose, 87% of previously infected individuals demonstrated high levels of neutralizing antibodies. However, if individuals were not previously infected only 24% demonstrated high levels of neutralizing antibodies after one vaccine dose. A second dose boosted neutralizing antibody levels just 8% higher in previously infected individuals, but over 63% higher in non-infected individuals.\n\nConclusionsA rapid, semi-quantitative, highly portable and inexpensive neutralizing antibody test might be useful for monitoring rise and fall in vaccine-induced neutralizing antibodies to COVID-19.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.15.20247031", + "rel_abs": "IntroductionRapid, high throughput diagnostics are a valuable tool, allowing the detection of SARS-CoV-2 in populations, in order to identify and isolate people with asymptomatic and symptomatic infections. Reagent shortages and restricted access to high throughput testing solutions have limited the effectiveness of conventional assays such as reverse transcriptase quantitative PCR (RT-qPCR), particularly throughout the first months of the COVID-19 pandemic. We investigated the use of LamPORE, where loop mediated isothermal amplification (LAMP) is coupled to nanopore sequencing technology, for the detection of SARS-CoV-2 in symptomatic and asymptomatic populations.\n\nMethodsIn an asymptomatic prospective cohort, for three weeks in September 2020 health care workers across four sites (Birmingham, Southampton, Basingstoke and Manchester) self-swabbed with nasopharyngeal swabs weekly and supplied a saliva specimen daily. These samples were tested for SARS-CoV-2 RNA using the Oxford Nanopore LamPORE system and a reference RT-qPCR assay on extracted sample RNA. A second retrospective cohort of 848 patients with influenza like illness from March 2020 - June 2020, were similarly tested from nasopharyngeal swabs.\n\nResultsIn the asymptomatic cohort a total of 1200 participants supplied 23,427 samples (3,966 swab, 19,461 saliva) over a three-week period. The incidence of SARS-CoV-2 detection using LamPORE was 0.95%. Diagnostic sensitivity and specificity of LamPORE was >99.5% in both swab and saliva asymptomatic samples when compared to the reference RT-qPCR test. In the retrospective symptomatic cohort, the incidence was 13.4% and the sensitivity and specificity were 100%.\n\nConclusionsLamPORE is a highly accurate methodology for the detection of SARS-CoV-2 in both symptomatic and asymptomatic population settings and can be used as an alternative to RT-qPCR.", + "rel_num_authors": 39, "rel_authors": [ { - "author_name": "Douglas F. Lake", - "author_inst": "Arizona State University" + "author_name": "Anetta Ptasinska", + "author_inst": "University of Bimingham" }, { - "author_name": "Alexa J. Roeder", - "author_inst": "Arizona State University" + "author_name": "Celina Whalley", + "author_inst": "University of Bimingham" }, { - "author_name": "Erin Kaleta", - "author_inst": "Mayo Clinic Arizona" + "author_name": "Andrew Bosworth", + "author_inst": "University of Bimingham" }, { - "author_name": "Paniz Jasbi", - "author_inst": "Arizona State University" + "author_name": "Charlie Poxon", + "author_inst": "University of Bimingham" }, { - "author_name": "Kirsten Pfeffer", - "author_inst": "Arizona State University" + "author_name": "Clare Bryer", + "author_inst": "University of Bimingham" }, { - "author_name": "Calvin J Koelbel", - "author_inst": "Arizona State University" + "author_name": "Seden Grippon", + "author_inst": "Department of Microbiology, Basingstoke & North Hants Hospital, Hampshire Hospitals" }, { - "author_name": "Sivakumar Periasamy", - "author_inst": "University of Texas Medical Branch at Galveston" + "author_name": "Emma Wise", + "author_inst": "Department of Microbiology, Basingstoke & North Hants Hospital, Hampshire Hospitals" }, { - "author_name": "Natalia Kuzmina", - "author_inst": "University of Texas Medical Branch at Galveston" + "author_name": "Bryony Armson", + "author_inst": "Department of Microbiology, Basingstoke & North Hants Hospital, Hampshire Hospitals" }, { - "author_name": "Alexander Bukreyev", - "author_inst": "University of Texas Medical Branch at Galveston" + "author_name": "Alice Goring", + "author_inst": "Department of Microbiology, Basingstoke & North Hants Hospital, Hampshire Hospitals" }, { - "author_name": "Thomas E Grys", - "author_inst": "Mayo Clinic Arizona" + "author_name": "Nicholas J Cortes", + "author_inst": "Department of Microbiology, Basingstoke & North Hants Hospital, Hampshire Hospitals" }, { - "author_name": "Liang Wu", - "author_inst": "Mayo Clinic Rochester" + "author_name": "Emma Howson", + "author_inst": "Department of Microbiology, Basingstoke & North Hants Hospital, Hampshire Hospitals" }, { - "author_name": "John R. Mills", - "author_inst": "Mayo Clinic Rochester" + "author_name": "Gemma Snell", + "author_inst": "University of Southampton" }, { - "author_name": "Kathrine McAulay", - "author_inst": "Mayo Clinic Arizona" + "author_name": "Jade Forster", + "author_inst": "University of Southampton" }, { - "author_name": "Alim Seit-Nebi", - "author_inst": "Axim Biotechnologies" + "author_name": "Chris Mattocks", + "author_inst": "University of Southampton" }, { - "author_name": "Sergei Svarovsky", - "author_inst": "Axim Biotechnologies" + "author_name": "Sarah Frampton", + "author_inst": "University of Southampton" + }, + { + "author_name": "Rebecca Anderson", + "author_inst": "University of Southampton" + }, + { + "author_name": "David Cleary", + "author_inst": "University of Southampton" + }, + { + "author_name": "Joe Parker", + "author_inst": "University of Southampton" + }, + { + "author_name": "Konstantinos Boukas", + "author_inst": "University of Southampton" + }, + { + "author_name": "Nichola Graham", + "author_inst": "University of Southampton" + }, + { + "author_name": "Doriana Cellura", + "author_inst": "University of Southampton" + }, + { + "author_name": "Emma Garratt", + "author_inst": "University of Southampton" + }, + { + "author_name": "Rachel Skilton", + "author_inst": "University of Southampton" + }, + { + "author_name": "Hana Sheldon", + "author_inst": "University of Southampton" + }, + { + "author_name": "Alla Collins", + "author_inst": "University of Southampton" + }, + { + "author_name": "Nusreen Ahmad", + "author_inst": "University of Southampton" + }, + { + "author_name": "Simon Friar", + "author_inst": "University of Southampton" + }, + { + "author_name": "Keith Godfrey", + "author_inst": "University of Southampton" + }, + { + "author_name": "Tim Williams", + "author_inst": "University of Southampton" + }, + { + "author_name": "Sandi Deans", + "author_inst": "Univesity of Edinburgh" + }, + { + "author_name": "Angela Douglas", + "author_inst": "Department of Health and Social Care" + }, + { + "author_name": "Sue L Hill", + "author_inst": "Department of Health and Social Care" + }, + { + "author_name": "Michael Kidd", + "author_inst": "University of Bimingham" + }, + { + "author_name": "Deborah Porter", + "author_inst": "Department of Health and Social Care" + }, + { + "author_name": "Stephen P Kidd", + "author_inst": "Department of Microbiology, Basingstoke & North Hants Hospital, Hampshire Hospitals" + }, + { + "author_name": "Veronica Fowler", + "author_inst": "Eco Animal Health Limited" + }, + { + "author_name": "Tony Williams", + "author_inst": "University of Southampton" + }, + { + "author_name": "Alex G Richter", + "author_inst": "University of Bimingham" + }, + { + "author_name": "Andrew D Beggs", + "author_inst": "University of Birmingham" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1004311,99 +1003969,35 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.12.14.422791", - "rel_title": "Potent SARS-CoV-2 binding and neutralization through maturation of iconic SARS-CoV-1 antibodies", + "rel_doi": "10.1101/2020.12.15.422866", + "rel_title": "No detectable signal for ongoing genetic recombination in SARS-CoV-2", "rel_date": "2020-12-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.14.422791", - "rel_abs": "Antibodies against coronavirus spike protein potently protect against infection and disease, however it remains unclear if such protection can be extended to variant coronaviruses. This is exemplified by a set of iconic and well-characterized monoclonal antibodies developed after the 2003 SARS outbreak including mAbs m396, CR3022, CR3014 and 80R, which potently neutralize SARS-CoV-1, but not SARS-CoV-2. Here we explore antibody maturation strategies to change and broaden their specificity, enabling potent binding and neutralization of SARS-CoV-2. Using targeted mutagenesis as well as light chain shuffling on phage, we identified variants with considerably increased affinity and neutralization potential. The most potent antibody, derived from the NIH-developed mAb m396, neutralized live SARS-CoV-2 virus with a half-maximal inhibitory concentration (IC50) of 160 ng/ml. Intriguingly, while many of the matured clones maintained specificity of the parental antibody, new specificities were also observed, which was further confirmed by X-ray crystallography and cryo-electron microscopy, indicating that a limited set of antibodies can give rise to variants targeting diverse epitopes. Our findings open up over 15 years of antibody development efforts against SARS-CoV-1 to the SARS-CoV-2 field and outline general principles for the maturation of antibody specificity against emerging viruses.", - "rel_num_authors": 20, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.15.422866", + "rel_abs": "The COVID-19 pandemic has led to an unprecedented global sequencing effort of its viral agent SARS-CoV-2. The first whole genome assembly of SARS-CoV-2 was published on January 5 2020. Since then, over 150,000 high-quality SARS-CoV-2 genomes have been made available. This large genomic resource has allowed tracing of the emergence and spread of mutations and phylogenetic reconstruction of SARS-CoV-2 lineages in near real time. Though, whether SARS-CoV-2 undergoes genetic recombination has been largely overlooked to date. Recombination-mediated rearrangement of variants that arose independently can be of major evolutionary importance. Moreover, the absence of recombination is a key assumption behind the application of phylogenetic inference methods. Here, we analyse the extant genomic diversity of SARS-CoV-2 and show that, to date, there is no detectable hallmark of recombination. We assess our detection power using simulations and validate our method on the related MERS-CoV for which we report evidence for widespread genetic recombination.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Romain Rouet", - "author_inst": "Garvan Institute" - }, - { - "author_name": "Ohan Mazigi", - "author_inst": "Garvan Institute" - }, - { - "author_name": "Gregory J Walker", - "author_inst": "UNSW Sydney" - }, - { - "author_name": "David B Langley", - "author_inst": "Garvan Institute" - }, - { - "author_name": "Meghna Sobti", - "author_inst": "Victor Chang Cardiac Research Institute" - }, - { - "author_name": "Peter Schofield", - "author_inst": "Garvan Institute" - }, - { - "author_name": "Helen Lenthall", - "author_inst": "Garvan Institute" - }, - { - "author_name": "Jennifer Jackson", - "author_inst": "Garvan Institute" - }, - { - "author_name": "Stephanie Ubiparipovic", - "author_inst": "Garvan Institute" - }, - { - "author_name": "Jake Y Henry", - "author_inst": "Garvan Institute" - }, - { - "author_name": "Arunasingam Abayasingam", - "author_inst": "Kirby Institute" - }, - { - "author_name": "Deborah Burnett", - "author_inst": "Garvan Institute" - }, - { - "author_name": "Anthony Kelleher", - "author_inst": "UNSW Sydney" - }, - { - "author_name": "Robert Brink", - "author_inst": "Garvan Institute" - }, - { - "author_name": "Rowena A Bull", - "author_inst": "Kirby Institute" - }, - { - "author_name": "Stuart Turville", - "author_inst": "Kirby Institute" - }, - { - "author_name": "Alastair G Stewart", - "author_inst": "Victor Chang Cardiac Research Institute" + "author_name": "Damien Richard", + "author_inst": "UCL" }, { - "author_name": "Christopher C Goodnow", - "author_inst": "Garvan Institute" + "author_name": "Christopher J Owen", + "author_inst": "UCL" }, { - "author_name": "William D Rawlinson", - "author_inst": "UNSW Sydney" + "author_name": "Lucy van Dorp", + "author_inst": "UCL Genetics Institute" }, { - "author_name": "Daniel Christ", - "author_inst": "Garvan Institute of Medical Research" + "author_name": "Fran\u00e7ois Balloux", + "author_inst": "Imperial College Faculty of Medicine" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "new results", - "category": "immunology" + "category": "genomics" }, { "rel_doi": "10.1101/2020.12.14.422793", @@ -1006069,71 +1005663,55 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.12.12.20247841", - "rel_title": "Maintenance therapy with infliximab or vedolizumab in inflammatory bowel disease is not associated with increased SARS-CoV-2 seroprevalence: UK experience in the 2020 pandemic", + "rel_doi": "10.1101/2020.12.11.20247551", + "rel_title": "Modeling of aerosol transmission of airborne pathogens in ICU rooms of COVID-19 patients with acute respiratory failure", "rel_date": "2020-12-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.12.20247841", - "rel_abs": "BackgroundThere has been great concern amongst clinicians and patients that immunomodulatory treatments for IBD may increase risk of SARS-CoV-2 susceptibility or progression to severe disease.\n\nMethodsSera from 640 patients attending for maintenance infliximab or vedolizumab infusions between April and June 2020 at the John Radcliffe Hospital (Oxford, UK) and Royal London Hospital (London, UK) were tested using the Abbott SARS-CoV-2 IgG assay. Demographic and clinical data were collated from electronic patient records and research databases.\n\nResultsSeropositivity rates of 3.0% (12/404), 7.2% (13/180), and 12.5% (7/56) were found in the Oxford and London adult IBD cohorts and London paediatric IBD cohorts respectively. Seroprevalence rates in the Oxford adult IBD cohort were lower than that seen in non-patient facing health-care workers within the same hospital (7.2%). Seroprevalence rates of the London paediatric IBD cohort were comparable to a contemporary healthy cohort collected at the same hospital (54/396, 13.6%).\n\nConclusionsSARS-CoV-2 seropositivity rates are not elevated in patients with IBD receiving maintenance infliximab or vedolizumab infusions. There is no rationale based on these data for elective interruption of maintenance therapy, and we recommend continuation of maintenance therapy. These data do not address the efficacy of vaccination in these patients.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.11.20247551", + "rel_abs": "The COVID-19 pandemic has generated many concerns about cross-contamination risks, particularly in hospital settings and Intensive Care Units (ICU). Virus-laden aerosols produced by infected patients can propagate throughout ventilated rooms and put medical personnel entering them at risk. Experimental results found with a schlieren optical method have shown that the air flows generated by a cough and normal breathing were modified by the oxygenation technique used, especially when using High Flow Nasal Canulae, increasing the shedding of potentially infectious airborne particles. This study also uses a 3D Computational Fluid Dynamics model based on a Lattice Boltzmann Method to simulate the air flows as well as the movement of numerous airborne particles produced by a patients cough within an ICU room under negative pressure. The effects of different mitigation scenarii on the amount of aerosols potentially containing SARS-CoV-2 that are extracted through the ventilation system are investigated. Numerical results indicate that adequate bed orientation and additional air treatment unit positioning can increase by 40% the number of particles extracted and decrease by 25% the amount of particles deposited on surfaces 45s after shedding. This approach could help lay the grounds for a more comprehensive way to tackle contamination risks in hospitals, as the model can be seen as a proof of concept and be adapted to any room configuration.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Colleen GC McGregor", - "author_inst": "Translational Gastroenterology Unit, NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK" - }, - { - "author_name": "Alex Adams", - "author_inst": "Translational Gastroenterology Unit, NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK" - }, - { - "author_name": "Ross Sadler", - "author_inst": "Department of Laboratory Immunology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK" - }, - { - "author_name": "Carolina V Arancibia-C\u00e1rcamo", - "author_inst": "Translational Gastroenterology Unit, NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK" - }, - { - "author_name": "Rebecca Palmer", - "author_inst": "Translational Gastroenterology Unit, NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK" + "author_name": "Cyril Crawford", + "author_inst": "Ecole Polytechnique" }, { - "author_name": "Tim Ambrose", - "author_inst": "Translational Gastroenterology Unit, NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK" + "author_name": "Emmanuel Vanoli", + "author_inst": "Dassault Systemes" }, { - "author_name": "Oliver Brain", - "author_inst": "Translational Gastroenterology Unit, NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK" + "author_name": "Baptiste Decorde", + "author_inst": "Ecole Polytechnique" }, { - "author_name": "Alissa Walsh", - "author_inst": "Translational Gastroenterology Unit, NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK" + "author_name": "Maxime Lancelot", + "author_inst": "Ecole Polytechnique" }, { - "author_name": "Paul Klenerman", - "author_inst": "Translational Gastroenterology Unit, NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK" + "author_name": "Camille Duprat", + "author_inst": "LadHyX, CNRS & Ecole Polytechnique, UMR 7646" }, { - "author_name": "Simon Travis", - "author_inst": "Translational Gastroenterology Unit, NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK" + "author_name": "Christophe Josserand", + "author_inst": "LadHyX, CNRS & Ecole Polytechnique, UMR 7646" }, { - "author_name": "Nicholas M Croft", - "author_inst": "Queen Mary University of London, London, UK. Royal London Hospital, Barts Health NHS Trust, London, UK" + "author_name": "Jonathan Jilesen", + "author_inst": "Dassault Systemes" }, { - "author_name": "James O Lindsay", - "author_inst": "Queen Mary University of London, London, UK. Royal London Hospital, Barts Health NHS Trust, London, UK" + "author_name": "Lila Bouadma", + "author_inst": "AP-HP, Bichat Claude Bernard Hospital, Medical and infectious diseases ICU (MI2)" }, { - "author_name": "Jack Satsangi", - "author_inst": "Translational Gastroenterology Unit, NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK" + "author_name": "Jean-Francois Timsit", + "author_inst": "AP-HP, Bichat Claude Bernard Hospital, Medical and infectious diseases ICU (MI2)" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "gastroenterology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.12.14.20248160", @@ -1007826,39 +1007404,63 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.12.08.20246041", - "rel_title": "Intention of health care workers to accept COVID-19 vaccination and related factors: a systematic review and meta-analysis", + "rel_doi": "10.1101/2020.12.02.20237974", + "rel_title": "Effects of photobiomodulation therapy combined with static magnetic field (PBMT-sMF) in patients with severe COVID-19 requiring intubation: a pragmatic randomized placebo-controlled trial", "rel_date": "2020-12-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.08.20246041", - "rel_abs": "Considering medical and economic burden of the coronavirus disease 2019 (COVID-19), a high COVID-19 vaccination coverage among health care workers (HCWs) is an urgent need. The aim of this systematic review and meta-analysis was to estimate the intention of HCWs to accept COVID-19 vaccination and to find out related factors. We searched PubMed, Medline, Scopus, Web of Science, ProQuest, CINAHL and medRxiv until July 14, 2021. The heterogeneity between results was very high and thus we applied a random effect model to estimate pooled effects. We performed subgroup and meta-regression analysis to identify possible resources of heterogeneity. Twenty four studies, including 39,617 HCWs met the inclusion criteria. The overall proportion of HCWs that intend to accept COVID-19 vaccination was 63.5% (95% confidence interval: 56.5-70.2%) with a wide range among studies from 27.7% to 90.1%. The following factors were associated with increased HCWs willingness to get vaccinated against COVID-19: male gender, older age, white HCWs, physician profession, higher education level, comorbidity among HCWs, seasonal influenza vaccination, stronger vaccine confidence, positive attitude towards a COVID-19 vaccine, fear about COVID-19, individual perceived risk about COVID-19, and contact with suspected or confirmed COVID-19 patients. The reluctance of HCWs to vaccinate against COVID-19 could diminish the trust of individuals and trigger a ripple effect in the general public. Since vaccination is a complex behavior, understanding the way that HCWs take the decision to accept or not COVID-19 vaccination will give us the opportunity to develop the appropriate interventions to increase COVID-19 vaccination uptake.\n\nKey MessagesO_LIThe overall proportion of health care workers that intent to accept COVID-19 vaccination was moderate.\nC_LIO_LISeveral factors affect health care workers willingness to get vaccinated against COVID-19.\nC_LIO_LICOVID-19 vaccine hesitancy among health care workers should be eliminated to inspire the general public towards a positive attitude regarding a novel COVID-19 vaccine.\nC_LI", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.02.20237974", + "rel_abs": "BackgroundPhotobiomodulation therapy (PBMT) when used isolated or combined with static magnetic field (PBMT-sMF) has been proven benefits on skeletal muscle increasing performance and reducing fatigue, increasing oxygen saturation, and modulating inflammatory process. However, it is unknown whether the effects observed with this therapy on respiratory muscles will be similar to the effects previously observed on skeletal muscles.\n\nObjectiveWe aimed to investigate whether PBMT-sMF is able to decrease the length of stay in the intensive care unit (ICU) and to reduce the mortality rate of patients with severe COVID-19 requiring invasive mechanical ventilation, increasing the respiratory function and modulating the inflammatory process.\n\nMethodsWe conducted a prospectively registered, pragmatic, triple-blinded (patients, therapists and outcome assessors), randomized, placebo-controlled trial of PBMT-sMF in patients with severe COVID-19, requiring invasive mechanical ventilation, admitted to the ICU. Patients were randomly assigned to receive either PBMT-sMF (6 sites at the lower thorax - 189 J total, and 2 sites at the neck area - 63 J total) or placebo PBMT-sMF daily during all the ICU stay. The primary outcome was length of stay in the ICU defined by either discharge or death. The secondary outcomes were survival rate, muscle function of diaphragm, change in blood tests, change in mechanical ventilation parameters and change in arterial blood gas analysis.\n\nResultsA total of 30 patients underwent randomization (with 15 assigned to PBMT-sMF and 15 to placebo) and were analyzed. The length of stay in the ICU for the placebo group was 23.06 days while for the PBMT-sMF group was 16.26. However, there was no statistically difference between groups for the length of stay in the ICU (mean difference - MD = - 6.80; 95% CI = - 18.71 to 5.11). Regarding the secondary outcomes were observed statistically differences in favor of PBMT-sMF for diaphragm thickness, fraction of inspired oxygen, partial pressure of oxygen/fraction of inspired oxygen ratio, C-reactive protein, lymphocytes count, and hemoglobin (p<0.05).\n\nConclusionAmong patients with severe COVID-19 requiring invasive mechanical ventilation, PBMT-sMF was not statistically different than placebo to the length of stay in the ICU. However, it is important to highlight that our sample size was underpowered to detect statistical differences to the primary outcome. In contrast, PBMT-sMF increased muscle function of diaphragm, improved ventilatory parameters, decreased C-reactive protein levels and hemoglobin count, and increased lymphocytes count.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Petros A Galanis", - "author_inst": "National and Kapodistrian University of Athens" + "author_name": "Thiago De Marchi", + "author_inst": "University Center of Bento Goncalves (UNICNEC)" }, { - "author_name": "Irene Vraka", - "author_inst": "P & A Kyriakou Children's Hospital" + "author_name": "Fabiano Francio", + "author_inst": "University Center of Bento Goncalves (UNICNEC)" }, { - "author_name": "Despoina Fragkou", - "author_inst": "National and Kapodistrian University of Athens" + "author_name": "Joao Vitor Ferlito", + "author_inst": "Hospital Tacchini" }, { - "author_name": "Angeliki Bilali", - "author_inst": "P & A Kyriakou Children's Hospital" + "author_name": "Renata Monteiro Weigert", + "author_inst": "Hospital Tacchini" }, { - "author_name": "Daphne Kaitelidou", - "author_inst": "National and Kapodistrian University of Athens" + "author_name": "Cristiane Aparecida de Oliveira", + "author_inst": "Hospital Tacchini" + }, + { + "author_name": "Ana Paula Merlo", + "author_inst": "Hospital Tacchini" + }, + { + "author_name": "Delcio Luis Pandini", + "author_inst": "Hospital Tacchini" + }, + { + "author_name": "Bolivar Antonio Pasqual Junior", + "author_inst": "Hospital Tacchini" + }, + { + "author_name": "Daniela Frare Giovanella", + "author_inst": "Hospital Tacchini" + }, + { + "author_name": "Shaiane Silva Tomazoni", + "author_inst": "University of Bergen" + }, + { + "author_name": "Ernesto Cesar Pinto Leal-Junior", + "author_inst": "Nove de Julho University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "rehabilitation medicine and physical therapy" }, { "rel_doi": "10.1101/2020.11.22.20235184", @@ -1009660,63 +1009262,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.09.20246413", - "rel_title": "Clinical characteristics of critically ill patients with COVID-19", + "rel_doi": "10.1101/2020.12.09.20246157", + "rel_title": "Assessing the Performance of COVID-19 Forecasting Models in the U.S.", "rel_date": "2020-12-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.09.20246413", - "rel_abs": "ObjectiveDescribe the clinical and respiratory characteristics of critical patients with coronavirus disease 2019 (COVID-19).\n\nDesignObservational and retrospective study over 6 months.\n\nSettingIntensive care unit (ICU) of a high complexity hospital in Buenos Aires, Argentina.\n\nPatientsPatients older than 18 years with laboratory-confirmed COVID-19 by reverse transcriptase-polymerase chain reaction (RT-PCR) for SARS-CoV-2 were included in the study.\n\nVariables of interestDemographic characteristics such as sex and age, comorbidities, laboratory results, imaging results, ventilatory mechanics data, complications, and mortality were recorded.\n\nResultsA total of 168 critically ill patients with COVID-19 were included. 66% were men with a median age of 65 years (58-75. 79.7% had at least one comorbidity. The most frequent comorbidity was arterial hypertension, affecting 52.4% of the patients. 67.9 % required invasive mechanical ventilation (MV), and no patient was treated with non-invasive ventilation. Most of the patients in MV (73.7%) required neuromuscular blockade due to severe hypoxemia. 36% of patients were ventilated in the prone position. The length of stay in the ICU was 13 days (6-24) and the mortality in the ICU was 25%.\n\nConclusionsIn this study of critical patients infected by SARS-CoV-2 in a high-complexity hospital, the majority were comorbid elderly men, a large percentage required invasive mechanical ventilation, and ICU mortality was 25%.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.09.20246157", + "rel_abs": "To combat the spread of coronavirus disease 2019 (COVID-19), decision-makers and the public may desire forecasts of the cases, hospitalizations, and deaths that are likely to occur. Thankfully, dozens of COVID-19 forecasting models exist and many of their forecasts have been made publicly available. However, there has been little published peer-reviewed information regarding the performance of these models and what is available has focused mostly on the performance of their central estimates (i.e., predictive performance). There has been little reported on the accuracy of their uncertainty estimates (i.e., probabilistic performance), which could inform users how often they would be surprised by observations outside forecasted confidence intervals. To address this gap in knowledge, we borrow from the literature on formally elicited expert judgment to demonstrate one commonly used approach for resolving this issue. For two distinct periods of the pandemic, we applied the Classical Model (CM) to evaluate probabilistic model performance and constructed a performance-weighted ensemble based on this evaluation. Some models which exhibited good predictive performance were found to have poor probabilistic performance, and vice versa. Only two of the nine models considered exhibited superior predictive and probabilistic performance. Additionally, the CM-weighted ensemble outperformed the equal-weighted and predictive-weighted ensembles. With its limited scope, this study does not provide definitive conclusions on model performance. Rather, it highlights the evaluation methodology and indicates the utility associated with using the CM when assessing probabilistic performance and constructing high performing ensembles, not only for COVID-19 modeling but other applications as well.\n\nSignificance StatementCoronavirus disease 2019 (COVID-19) forecasting models can provide critical information for decision-makers and the public. Unfortunately, little information on their performance has been published, particularly regarding the accuracy of their uncertainty estimates (i.e., probabilistic performance). To address this research gap, we demonstrate the Classical Model (CM), a commonly used approach from the literature on formally elicited expert judgment, which considers both the tightness of forecast confidence intervals and frequency in which confidence intervals contain the observation. Two models exhibited superior performance and the CM-based ensemble consistently outperformed the other constructed ensembles. While these results are not definitive, they highlight the evaluation methodology and indicate the value associated with using the CM when assessing probabilistic performance and constructing high performing ensembles.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Indalecio Carboni Bisso", - "author_inst": "Intensive Care Unit, Hospital Italiano de Buenos Aires" - }, - { - "author_name": "Ivan Huespe", - "author_inst": "Intensive Care Unit, Hospital Italiano de Buenos Aires" - }, - { - "author_name": "Carolina Lockhart", - "author_inst": "Intensive Care Unit, Hospital Italiano de Buenos Aires" - }, - { - "author_name": "Agustin Masso", - "author_inst": "Intensive Care Unit, Hospital Italiano de Buenos Aires" - }, - { - "author_name": "Julieta Gonzalez Anaya", - "author_inst": "Intensive Care Unit, Hospital Italiano de Buenos Aires" - }, - { - "author_name": "Micaela Hornos", - "author_inst": "Intensive Care Unit, Hospital Italiano de Buenos Aires" - }, - { - "author_name": "Romina Famiglietti", - "author_inst": "Rehabilitation and Respiratory Care Division - Physiotherapy Service, Hospital Italiano de Buenos Aires" - }, - { - "author_name": "Marcelo Di Grazia", - "author_inst": "Rehabilitation and Respiratory Care Division - Physiotherapy Service, Hospital Italiano de Buenos Aires" - }, - { - "author_name": "Pablo Coria", - "author_inst": "Rehabilitation and Respiratory Care Division - Physiotherapy Service, Hospital Italiano de Buenos Aires" + "author_name": "Kyle J. Colonna", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Eduardo San Roman", - "author_inst": "Intensive Care Unit, Hospital Italiano de Buenos Aires" + "author_name": "Roger M. Cooke", + "author_inst": "Resources for the Future; Department of Mathematics, Delft University of Technology" }, { - "author_name": "Marcos Jose Las Heras", - "author_inst": "Intensive Care Unit, Hospital Italiano de Buenos Aires" + "author_name": "John S. Evans", + "author_inst": "Harvard T.H. Chan School of Public Health" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.12.10.20246884", @@ -1011362,61 +1010932,125 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.10.20244350", - "rel_title": "Development And Performance Evaluation of A Rapid In-House ELISA for Retrospective Serosurveillance of SARS-CoV-2", + "rel_doi": "10.1101/2020.12.10.20247171", + "rel_title": "Environmental monitoring shows SARS-CoV-2 contamination of surfaces in food plants", "rel_date": "2020-12-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.10.20244350", - "rel_abs": "BackgroundIn the ongoing pandemic situation of COVID-19, serological tests can complement the molecular diagnostic methods, and can be one of the important tools of sero-surveillance and vaccine evaluation.\n\nAimTo develop and evaluate a rapid SARS-CoV-2 specific ELISA for detection of anti-SARS-CoV2 IgG from patients biological samples.\n\nMethodsIn order to develop the ELISA, three panels of samples (n=184) have been used: panel 1 (n=19) and panel 2 (n=60) were collected from RT-PCR positive patients within 14 and after 14 days of onset of clinical symptoms respectively, whereas panel 3 consisted of negative samples (n=105) collected either from healthy donors or pre-pandemic dengue patients. As a capturing agent full-length SARS-CoV2 specific recombinant nucleocapsid was immobilized. Commercial SARS-CoV2 IgG kit based on chemiluminescent assay was used for the selection of samples and optimization of the assay. The threshold cut-off point, inter-assay and intra-assay variations were determined. The total assay time for this in-house ELISA was set for 30 minutes.\n\nResultsThe assay time was set at a total of 30 minutes with the sensitivity of 84% (95% confidence interval, CI, 60.4%, 96.6%) and 98% (95% CI, 91.1%, 100.0%), for panel 1 and 2 respectively, with over all 94.9% sensitivity (95% CI 87.5%, 98.6%). Moreover, the clinical specificity is 97.1% (95% CI, 91.9%, 99.4%) with no cross reaction with dengue sample. The overall positive and negative predictive values are 96.2% (95% CI 89.2%, 99.2%) and 96.2% (95% CI, 90.6% 99.0%) respectively. In-house ELISA demonstrated 100% positive and negative percent agreement with ROCHE (Elecsys; Anti-SARS-CoV-2), with a Cohens kappa value of 1.00 (very strong agreement), while comparing 13 positive and 17 negative confirmed cases.\n\nConclusionThe assay is rapid and can be applied as one of the early and retrospective sero-monitoring tools in all over the affected areas.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.10.20247171", + "rel_abs": "The SARS-CoV-2 pandemic has presented new challenges to food manufacturers. In addition to preventing the spread of microbial contamination of food, with SARS-CoV-2, there is an additional focus on preventing SARS-CoV-2 infections in food plant personnel. During the early phase of the pandemic, several large outbreaks of Covid-19 occurred in food manufacturing plants resulting in deaths and economic loss. In March of 2020, we assisted in implementation of environmental monitoring programs for SARS-CoV-2 in 116 food production facilities. All participating facilities had already implemented measures to prevent symptomatic personnel from coming to work. During the study period, from March 17, 2020 to September 3, 2020, 1.23% of the 22,643 environmental samples tested positive for SARS-CoV-2, suggesting that infected individuals are actively shedding virus. Virus contamination was commonly found on frequently touched surfaces. Most plants managed to control their environmental contamination when they became aware of the positive findings. Comparisons of the personnel test results to environmental contamination in one plant showed a good correlation between the two. Our work illustrates that environmental monitoring for SARS-CoV-2 can be used as a surrogate for identifying the presence of asymptomatic and pre-symptomatic personnel in workplaces and may aid in controlling infection spread.\n\nHighlightsO_LIEnvironmental contamination by SARS-CoV-2 virus was detected in food plants\nC_LIO_LIOut of 22,643 environmental swabs, 278 (1.23%) were positive for SARS-CoV-2\nC_LIO_LIFrequently touched surfaces had the most contamination\nC_LIO_LISurface testing for SARS-CoV-2 may indicate presence of asymptomatic carriers\nC_LI", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Bijon Kumar Sil", - "author_inst": "Gonoshasthay-RNA Molecular Diagnostic and Research Center" + "author_name": "Ziwen Ming", + "author_inst": "Institute for Environmental Health" }, { - "author_name": "Mumtarin Jannat Oishee", - "author_inst": "Gonoshasthay-RNA Molecular Diagnostic and Research Center" + "author_name": "Sukkyun Han", + "author_inst": "Institute for Environmental Health" }, { - "author_name": "Md. Ahsanul Haq", - "author_inst": "Gonoshasthay-RNA Molecular Diagnostic and Research Center" + "author_name": "Kai Deng", + "author_inst": "Institute for Environmental Health" }, { - "author_name": "Nowshin Jahan", - "author_inst": "Gonoshasthay-RNA Molecular Diagnostic and Research Center" + "author_name": "Youngsil Ha", + "author_inst": "Institute for Environmental Health" }, { - "author_name": "Tamanna Ali", - "author_inst": "Gonoshasthay-RNA Molecular Diagnostic and Research Center" + "author_name": "SungSoo Kim", + "author_inst": "Institute for Environmental Health" }, { - "author_name": "Shahad Saif Khandker", - "author_inst": "Gonoshasthay-RNA Molecular Diagnostic and Research Center" + "author_name": "Enrique Reyes", + "author_inst": "Institute for Environmental Health" }, { - "author_name": "Eiry Kobatake", - "author_inst": "Tokyo Institute of Technology" + "author_name": "Yu Zhao", + "author_inst": "Institute for Environmental Health" }, { - "author_name": "Masayasu Mie", - "author_inst": "Tokyo Institute of Technology" + "author_name": "Anatoly Dobritsa", + "author_inst": "Institute for Environmental Health" }, { - "author_name": "Mohib Ullah Khondoker", - "author_inst": "Gonoshasthaya Samaj Vittik Medical College" + "author_name": "Meiting Wu", + "author_inst": "Institute for Environmental Health" }, { - "author_name": "Mohd. Raeed Jamiruddin", - "author_inst": "BRAC University" + "author_name": "Dandan Zhao", + "author_inst": "Institute for Environmental Health" }, { - "author_name": "Nihad Adnan", - "author_inst": "Jahangirnagar University" + "author_name": "David P Cox", + "author_inst": "Institute for Environmental Health" + }, + { + "author_name": "Emma Joyner", + "author_inst": "Institute for Environmental Health" + }, + { + "author_name": "Hemantha Kulasekara", + "author_inst": "Institute for Environmental Health" + }, + { + "author_name": "Seong Hong Kim", + "author_inst": "Institute for Environmental Health" + }, + { + "author_name": "Yong Seog Jang", + "author_inst": "Institute for Environmental Health" + }, + { + "author_name": "Curtis Fowler", + "author_inst": "Institute for Environmental Health" + }, + { + "author_name": "Xing Fei", + "author_inst": "Institute for Environmental Health" + }, + { + "author_name": "Hikari Akasaki", + "author_inst": "Institute for Environmental Health" + }, + { + "author_name": "Eni Themeli", + "author_inst": "Institute for Environmental Health" + }, + { + "author_name": "Alexander Agapov", + "author_inst": "Institute for Environmental Health" + }, + { + "author_name": "Dylan Bruneau", + "author_inst": "Institute for Environmental Health" + }, + { + "author_name": "Thao Tran", + "author_inst": "Institute for Environmental Health" + }, + { + "author_name": "Cameron Szczesny", + "author_inst": "Institute for Environmental Health" + }, + { + "author_name": "Casey Kienzle", + "author_inst": "Institute for Environmental Health" + }, + { + "author_name": "Kristina Tenney", + "author_inst": "Institute for Environmental Health" + }, + { + "author_name": "Hao Geng", + "author_inst": "Institute for Environmental Health" + }, + { + "author_name": "Mansour Samadpour", + "author_inst": "Institute for Environmental Health" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1013474,18 +1013108,127 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.12.08.416875", - "rel_title": "Single dose immunization with a COVID-19 DNA vaccine encoding a chimeric homodimeric protein targeting receptor binding domain (RBD) to antigen-presenting cells induces rapid, strong and long-lasting neutralizing IgG, Th1 dominated CD4+ T cells and strong CD8+ T cell responses in mice", + "rel_doi": "10.1101/2020.12.09.417519", + "rel_title": "Intra-host variability in global SARS-CoV-2 genomes as signatures of RNA editing: implications in viral and host response outcomes", "rel_date": "2020-12-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.08.416875", - "rel_abs": "The pandemic caused by the SARS-CoV-2 virus in 2020 has led to a global public health emergency, and non-pharmaceutical interventions required to limit the viral spread are severely affecting health and economies across the world. A vaccine providing rapid and persistent protection across populations is urgently needed to prevent disease and transmission. We here describe the development of novel COVID-19 DNA plasmid vaccines encoding homodimers consisting of a targeting unit that binds chemokine receptors on antigen-presenting cells (human MIP-1 /LD78{beta}), a dimerization unit (derived from the hinge and CH3 exons of human IgG3), and an antigenic unit (Spike or the receptor-binding domain (RBD) from SARS-CoV-2). The candidate encoding the longest RBD variant (VB2060) demonstrated high secretion of a functional protein and induced rapid and dose-dependent RBD IgG antibody responses that persisted up to at least 3 months after a single dose of the vaccine in mice. Neutralizing antibody (nAb) titers against the live virus were detected from day 7 after one dose. All tested dose regimens reached titers that were higher or comparable to those seen in sera from human convalescent COVID-19 patients from day 28. T cell responses were detected already at day 7, and were subsequently characterized to be multifunctional CD8+ and Th1 dominated CD4+ T cells. Responses remained at sustained high levels until at least 3 months after a single vaccination, being further strongly boosted by a second vaccination at day 89. These findings, together with the simplicity and scalability of plasmid DNA manufacturing, safety data on the vaccine platform in clinical trials, low cost of goods, data indicating potential long term storage at +2{degrees} to 8{degrees}C and simple administration, suggests the VB2060 candidate is a promising second generation candidate to prevent COVID-19.", - "rel_num_authors": 0, - "rel_authors": null, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.09.417519", + "rel_abs": "During the course of the COVID-19 pandemic, large-scale genome sequencing of SARS-CoV-2 has been useful in tracking its spread and in identifying Variants Of Concern (VOC). Besides, viral and host factors could contribute to variability within a host that can be captured in next-generation sequencing reads as intra-host Single Nucleotide Variations (iSNVs). Analysing 1, 347 samples collected till June 2020, we recorded 18, 146 iSNV sites throughout the SARS-CoV-2 genome. Both, mutations in RdRp as well as APOBEC and ADAR mediated RNA editing seem to contribute to the differential prevalence of iSNVs in hosts. Noteworthy, 41% of all unique iSNVs were reported as SNVs by 30th September 2020 in samples submitted to GISAID, which increased to [~]80% by 30th June 2021. Following this, analysis of another set of 1, 798 samples sequenced in India between November 2020 and May 2021 revealed that majority of the Delta (B.1.617.2) and Kappa (B.1.617.1) variations appeared as iSNVs before getting fixed in the population. We also observe hyper-editing events at functionally critical residues in Spike protein that could alter the antigenicity and may contribute to immune escape. Thus, tracking and functional annotation of iSNVs in ongoing genome surveillance programs could be important for early identification of potential variants of concern and actionable interventions.\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=177 SRC=\"FIGDIR/small/417519v3_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (41K):\norg.highwire.dtl.DTLVardef@12b6ac2org.highwire.dtl.DTLVardef@16df897org.highwire.dtl.DTLVardef@dbbec2org.highwire.dtl.DTLVardef@c8de14_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 27, + "rel_authors": [ + { + "author_name": "Ankit K. Pathak", + "author_inst": "CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India" + }, + { + "author_name": "Gyan Prakash Mishra", + "author_inst": "Institute of Life Sciences, Bhubaneswar, Odisha, India" + }, + { + "author_name": "Bharathram Uppili", + "author_inst": "CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India" + }, + { + "author_name": "Safal Walia", + "author_inst": "Institute of Life Sciences, Bhubaneswar" + }, + { + "author_name": "Saman Fatihi", + "author_inst": "CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India" + }, + { + "author_name": "Tahseen Abbas", + "author_inst": "CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India" + }, + { + "author_name": "Sofia Banu", + "author_inst": "CSIR - Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, Telangana, India" + }, + { + "author_name": "Arup Ghosh", + "author_inst": "Institute of Life Sciences, Bhubaneswar, Odisha, India" + }, + { + "author_name": "Amol Kanampalliwar", + "author_inst": "Institute of Life Sciences, Bhubaneswar" + }, + { + "author_name": "Atimukta Jha", + "author_inst": "Institute of Life Sciences, Bhubaneswar" + }, + { + "author_name": "Sana Fatima", + "author_inst": "Institute of Life Sciences, Bhubaneswar" + }, + { + "author_name": "Shifu Aggarwal", + "author_inst": "Institute of Life Sciences, Bhubaneswar" + }, + { + "author_name": "Mahesh Shanker Dhar", + "author_inst": "National Centre for Disease Control, Delhi" + }, + { + "author_name": "Robin Marwal", + "author_inst": "National Centre for Disease Control, Delhi" + }, + { + "author_name": "Radhakrishnan V. S.", + "author_inst": "National Centre for Disease Control, Delhi" + }, + { + "author_name": "Kalaiarasan Ponnusamy", + "author_inst": "National Centre for Disease Control, Delhi" + }, + { + "author_name": "Sandhya Kabra", + "author_inst": "National Centre for Disease Control, Delhi" + }, + { + "author_name": "Partha Rakshit", + "author_inst": "National Centre for Disease Control, Delhi" + }, + { + "author_name": "Rahul C. Bhoyar", + "author_inst": "CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India" + }, + { + "author_name": "Abhinav Jain", + "author_inst": "CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India" + }, + { + "author_name": "Mohit Kumar Divakar", + "author_inst": "CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India" + }, + { + "author_name": "Mohamed Imran", + "author_inst": "CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India" + }, + { + "author_name": "Mohammed Faruq", + "author_inst": "CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India" + }, + { + "author_name": "Divya Tej Sowpati", + "author_inst": "CSIR - Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, Telangana, India" + }, + { + "author_name": "Lipi Thukral", + "author_inst": "CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India" + }, + { + "author_name": "Sunil K. Raghav", + "author_inst": "Institute of Life Sciences, Bhubaneswar, Odisha, India" + }, + { + "author_name": "Mitali Mukerji", + "author_inst": "CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India" + } + ], "version": "1", "license": "", "type": "new results", - "category": "microbiology" + "category": "genomics" }, { "rel_doi": "10.1101/2020.12.08.416677", @@ -1015222,14 +1014965,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.07.20245225", - "rel_title": "Relative Sensitivity of ID NOW and RT-PCR for Detection of SARS-CoV-2 in an Ambulatory Population: Clinical Evaluation, Systematic Review and Meta-analysis", + "rel_doi": "10.1101/2020.12.07.20245233", + "rel_title": "Association between RT-PCR Ct Values and COVID-19 New Daily Cases: A Multicenter Cross-Sectional Study", "rel_date": "2020-12-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.07.20245225", - "rel_abs": "Diagnosis of the SARS-CoV-2 (COVID-19) requires confirmation by Reverse-Transcription Polymerase Chain Reaction (RT-PCR). Abbott ID NOW provides fast results but has been criticized for low sensitivity. Here we determine the sensitivity of ID NOW in an ambulatory population presenting for testing. The study enrolled 785 symptomatic patients, 21 of whom were positive by both ID NOW and RT-PCR, and 2 only by RT-PCR. All 189 asymptomatic patients tested negative. The positive percent agreement between the ID NOW assay and the RT-PCR assay was 91.3%, and negative percent agreement was 100%. The results from the current study were included into a larger systematic review of literature where at least 20 subjects were simultaneously tested using ID NOW and RT-PCR. The overall sensitivity for ID NOW assay was calculated at 84% (95% CI 55-96%), and had the highest correlation to RT-PCR at viral loads most likely to be associated with transmissible infections.", - "rel_num_authors": 0, - "rel_authors": null, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.07.20245233", + "rel_abs": "IntroductionProactive prediction of the epidemiologic dynamics of viral diseases and outbreaks of the likes of COVID-19 has remained a difficult pursuit for scientists, public health researchers, and policymakers. It is unclear whether RT-PCR Cycle Threshold (Ct) values of COVID-19--or any other virus--as indicator of viral load, could represent a possible predictor for underlying epidemiologic changes on a population level.\n\nObjectivesTo investigate whether population-wide changes in SARS-CoV-2 RT-PCR Ct values over time are associated with the daily fraction of positive COVID-19 tests. In addition, this study analyses the factors that could influence the RT-PCR Ct values.\n\nMethodA retrospective cross-sectional study was conducted on 63,879 patients from May 4, 2020 to September 30, 2020, in all COVID-19 facilities in the Kingdom of Bahrain. Data collected included number of tests and newly diagnosed cases, as well as Ct values, age, gender nationality, and symptomatic status.\n\nResultsCt values were found to be negatively and very weakly correlated with the fraction of daily positive cases in the population r = -0.06 (CI95%: -0.06; -0.05; p=0.001). The R-squared for the regression model (adjusting for age and number of daily tests) showed an accuracy of 45.3%. Ct Values showed an association with nationality (p=0.012). After the stratification, the association between Ct values and the fraction of daily positive cases was only maintained for the female gender and Bahraini-nationality. Symptomatic presentation was significantly associated with lower Ct values (higher viral loads). Ct values do not show any correlation with age (p=0.333) or gender (p=0.522).\n\nConclusionWe report one of the first and largest studies to investigate the epidemiologic associations of Ct values with COVID-19. Ct values offer a potentially simple and widely accessible tool to predict and model epidemiologic dynamics on a population level. More population studies and predictive models from global cohorts are necessary.", + "rel_num_authors": 6, + "rel_authors": [ + { + "author_name": "Abdulkarim Abdulrahman", + "author_inst": "National Taskforce for Combating the Coronavirus (COVID-19), Bahrain ; Mohammed Bin Khalifa Cardiac Centre, Bahrain" + }, + { + "author_name": "Saad Mallah", + "author_inst": "Royal College of Surgeons in Ireland, Bahrain" + }, + { + "author_name": "Abdulla Ismael AlAwadhi", + "author_inst": "National Taskforce for Combating the Coronavirus (COVID-19), Bahrain ; Bahrain Defence Force hospital, Bahrain" + }, + { + "author_name": "Simone Perna", + "author_inst": "Department of Biology, College of Science, University of Bahrain, Sakhir Campus, Kingdom of Bahrain" + }, + { + "author_name": "Essam Janahi", + "author_inst": "Independent Researcher, Bahrain" + }, + { + "author_name": "Manaf AlQahtani", + "author_inst": "Royal College of Surgeons in Ireland, Bahrain ; National Taskforce for Combating the Coronavirus (COVID-19), Bahrain ; Bahrain Defence Force hospital, Bahrain" + } + ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", @@ -1016702,27 +1016470,75 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.12.04.20244079", - "rel_title": "Association of COVID-19 spread with on-demand testing", + "rel_doi": "10.1101/2020.12.05.20243568", + "rel_title": "Antibiotic prescriptions in children with COVID-19 and Multisystem Inflammatory Syndrome: a multinational experience in 990 cases from Latin America", "rel_date": "2020-12-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.04.20244079", - "rel_abs": "Comparisons of COVID-19 testing policies in 99 countries indicate that testing on demand is associated with an increase in cases 14 days after the tests. Adjusted for number of new cases and the positivity rate, for each 10,000 negative tests on a given day there were 90-110 new cases in 14 days that would not have otherwise occurred. Approximately 3.1 million or 21 percent of new cases in periods of on-demand testing are likely due to that policy through early November 2020. During periods in a given country when only persons with symptoms were tested, or persons with symptoms and key vulnerable populations were tested, negative tests were associated with fewer new cases 14 days out. Apparently when tests are available on demand, those who test negative are engaging in activities that increase the risk of exposure.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.05.20243568", + "rel_abs": "BackgroundTo date, there are no comprehensive data on antibiotic use in children with COVID-19 and Multisystem Inflammatory Syndrome (MIS-C).\n\nMethodsMulticenter cohort study from 5 Latin American countries. Children 17 years of age or younger with microbiologically confirmed SARS-CoV-2 infection or fulfilling MIS-C definition were included. Antibiotic prescriptions were collected and factors associated with their use were calculated.\n\nFindings990 children were included, with a median age of 3 years (interquartile range 1-9). Of these, 69 (7.0%) were diagnosed with MIS-C. The prevalence of antibiotic use was 24.5% (n = 243). MIS-C with (OR = 45.48) or without (OR = 10.35) cardiac involvement, provision of intensive care (OR = 9.60), need for hospital care (OR = 6.87), pneumonia and/or ARDS detected through chest X-rays (OR = 4.40), administration of systemic corticosteroids (OR = 4.39), oxygen support, mechanical ventilation or CPAP (OR = 2.21), pyrexia (OR = 1.84), and female sex (OR = 1.50) were independently associated with increased use of antibiotics. On the contrary, lower respiratory tract infections without radiologic evidence of pneumonia/ARDS and not requiring respiratory support (OR = 0.34) were independently associated with decreased use of antibiotics. There was significant variation in antibiotic use across the hospitals.\n\nConclusionsOur study showed a relatively high rate of antibiotic prescriptions in children with COVID-19 and in particular in those with severe disease or MIS-C. Importantly, we found a significant variation in reasons for prescriptions of antibiotics and type of chosen therapies, as well in hospital practices, highlighting current uncertainties and lack of guidelines for the recognition of bacterial infections in children with COVID-19. Prospective studies are needed to provide better evidence on the recognition and management of bacterial infections in COVID-19 children.\n\nWhat is knownCOVID-19 may worsen antibiotic prescription practices\n\nWhat this newCOVID-19 and MIS-C children frequently received antibiotics\n\nThere was a wide variation in antibiotic prescriptions among institutions, highlighting the lack of practicle guidelines in the use of antibiotics in children with COVID-19", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Leon S Robertson", - "author_inst": "Yale University" + "author_name": "Adriana Yock", + "author_inst": "Pediatric Emergency Department, Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", CCSS, San Jose, Costa Rica." }, { - "author_name": "Leon S. Robertson", - "author_inst": "Yale University" + "author_name": "Jacopo Lenzi", + "author_inst": "Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum - University of Bologna, Bologna, Italy" + }, + { + "author_name": "Rolando Ulloa-Gutierrez", + "author_inst": "Infectious Disease Department. Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", CCSS, San Jose, Costa Rica." + }, + { + "author_name": "Jessica Gomez-Vargas", + "author_inst": "Pediatric Emergency Department, Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", CCSS, San Jose, Costa Rica." + }, + { + "author_name": "Omar Antunez-Montes", + "author_inst": "Departamento de Docencia e Investigacion, Instituto Latinoamericano de Ecografia en Medicina (ILEM), Ciudad de Mexico, Mexico" + }, + { + "author_name": "Jorge Alberto Rios Aida", + "author_inst": "CLINICA JAS MEDICA, Lima, Peru" + }, + { + "author_name": "Olguita del Aguila", + "author_inst": "Unidad de Infectologia Pediatrica del Hospital Nacional Edgardo Rebagliati Martins-Lima-Peru" + }, + { + "author_name": "Erick Arteaga-Menchaca", + "author_inst": "Hospital General Regional 200 IMSS, Mexico" + }, + { + "author_name": "Francisco Campos", + "author_inst": "Hospital Madre Nino San Bartolome, Lima, Peru" + }, + { + "author_name": "Fadia Uribe", + "author_inst": "Hospital Madre Nino San Bartolome, Lima, Peru" + }, + { + "author_name": "Andrea Parra Buitrago", + "author_inst": "Hospital Pablo Tobon Uribe Medellin, Colombia" + }, + { + "author_name": "Lina Maria Betancur Londono", + "author_inst": "Hospital Pablo Tobon Uribe Medellin, Colombia" + }, + { + "author_name": "Martin Brizuela", + "author_inst": "Pediatric Infectious Disease, Hospital isidoro Iriarte, Quilmes, Buenos Aires, Argentina" + }, + { + "author_name": "Danilo Buonsenso", + "author_inst": "Fondazione Policlinico Universitario A. Gemelli" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pediatrics" }, { "rel_doi": "10.1101/2020.12.05.20244426", @@ -1018052,63 +1017868,103 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.12.07.414706", - "rel_title": "Spike Protein of SARS-CoV-2 Activates Macrophages and Contributes to Induction of Acute Lung Inflammations in Mice", + "rel_doi": "10.1101/2020.12.07.413252", + "rel_title": "Paradoxical effects of cigarette smoke and COPD on SARS-CoV2 infection and disease", "rel_date": "2020-12-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.07.414706", - "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19) patients exhibit multiple organ malfunctions with a primary manifestation of acute and diffuse lung injuries. The Spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is crucial to mediate viral entry into host cells; however, whether it can be cellularly pathogenic and contribute to pulmonary hyper-inflammations in COVID-19 is not well known.\n\nMethods and FindingsIn this study, we developed a Spike protein-pseudotyped (Spp) lentivirus with the proper tropism of SARS-CoV-2 Spike protein on the surface and tracked down the fate of Spp in wild type C57BL/6J mice receiving intravenous injection of the virus. A lentivirus with vesicular stomatitis virus glycoprotein (VSV-G) was used as the control. Two hours post-infection (hpi), Spp showed more than 27-75 times more viral burden in the lungs than other organs; it also exhibited about 3-5 times more viral burden than VSV-G lentivirus in the lungs, liver, kidney and spleen. Acute pneumonia was evident in animals 24 hpi. Spp lentivirus was mainly found in LDLR+ macrophages and pneumocytes in the lungs, but not in MARC1+ macrophages. IL6, IL10, CD80 and PPAR-{gamma} were quickly upregulated in response to infection of Spp lentivirus in the lungs in vivo as well as in macrophage-like RAW264.7 cells in vitro. We further confirmed that forced expression of the Spike protein in RAW264.7 cells could significantly increase the mRNA levels of the same panel of inflammatory factors.\n\nConclusionsOur results demonstrate that the Spike protein of SARS-CoV-2 alone can induce cellular pathology, e.g. activating macrophages and contributing to induction of acute inflammatory responses.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.07.413252", + "rel_abs": "IntroductionHow cigarette smoke (CS) and chronic obstructive pulmonary disease (COPD) affect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and severity is controversial. We investigated the protein and mRNA expression of SARS-CoV-2 entry receptor ACE2 and proteinase TMPRSS2 in lungs from COPD patients and controls, and lung tissue from mice exposed acutely and chronically to CS. Also, we investigated the effects of CS exposure on SARS-CoV-2 infection in human bronchial epithelial cells.\n\nMethodsIn Cohort 1, ACE2-positive cells were quantified by immunostaining in FFPE sections from both central and peripheral airways. In Cohort 2, we quantified pulmonary ACE2 protein levels by immunostaining and ELISA, and both ACE2 and TMPRSS2 mRNA levels by RT-qPCR. In C57BL/6 WT mice exposed to air or CS for up to 6 months, pulmonary ACE2 protein levels were quantified by triple immunofluorescence staining and ELISA. The effects of CS exposure on SARS-CoV-2 infection were evaluated after 72hr in vitro infection of Calu-3 cells. After SARS-CoV-2 infection, the cells were fixed for IF staining with dsRNA-specific J2 monoclonal Ab, and cell lysates were harvested for WB of viral nucleocapsid (N) protein. Supernatants (SN) and cytoplasmic lysates were obtained to measure ACE2 levels by ELISA.\n\nResultsIn both human cohorts, ACE2 protein and mRNA levels were decreased in peripheral airways from COPD patients versus both smoker and NS controls, but similar in central airways. TMPRSS2 levels were similar across groups. Mice exposed to CS had decreased ACE2 protein levels in their bronchial and alveolar epithelia versus air-exposed mice exposed to 3 and 6 months of CS. In Calu3 cells in vitro, CS-treatment abrogated infection to levels below the limit of detection. Similar results were seen with WB for viral N protein, showing peak viral protein synthesis at 72hr.\n\nConclusionsACE2 levels were decreased in both bronchial and alveolar epithelial cells from uninfected COPD patients versus controls, and from CS-exposed versus air-exposed mice. CS-pre-treatment did not affect ACE2 levels but potently inhibited SARS-CoV-2 replication in this in vitro model. These findings urge to further investigate the controversial effects of CS and COPD on SARS-CoV2 infection.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Xiaoling Cao", - "author_inst": "University of South Carolina School of Medicine" + "author_name": "Michael Tomchaney", + "author_inst": "University of Arizona" }, { - "author_name": "Yan Tian", - "author_inst": "University of South Carolina School of Medicine" + "author_name": "Marco Contoli", + "author_inst": "University of Ferrara" }, { - "author_name": "Vi Nguyen", - "author_inst": "University of South Carolina School of Medicine" + "author_name": "Jonathan Mayo", + "author_inst": "University of Arizona" }, { - "author_name": "Yuping Zhang", - "author_inst": "University of South Carolina School of Medicine" + "author_name": "Simonetta Baraldo", + "author_inst": "University of Padova" }, { - "author_name": "Chao Gao", - "author_inst": "University of South Carolina School of Medicine" + "author_name": "Shuaizhi Li", + "author_inst": "University of Arizona" }, { - "author_name": "Rong Yin", - "author_inst": "University of South Carolina School of Medicine" + "author_name": "Carly Cabel", + "author_inst": "University of Arizona" }, { - "author_name": "Wayne Carver", - "author_inst": "University of South Carolina School of Medicine" + "author_name": "David Bull", + "author_inst": "University of Arizona" }, { - "author_name": "Daping Fan", - "author_inst": "University of South Carolina School of Medicine" + "author_name": "Scott Lick", + "author_inst": "University of Arizona" }, { - "author_name": "Helmut Albrecht", - "author_inst": "University of South Carolina School of Medicine" + "author_name": "Joshua Malo", + "author_inst": "University of Arizona" }, { - "author_name": "Taixing Cui", - "author_inst": "University of South Carolina School of Medicine" + "author_name": "Steve Knoper", + "author_inst": "University of Arizona" }, { - "author_name": "Wenbin Tan", - "author_inst": "University of South Carolina, School of Medicine" + "author_name": "Samuel Kim", + "author_inst": "University of Arizona" + }, + { + "author_name": "Judy Tram", + "author_inst": "University of Arizona" + }, + { + "author_name": "Joselyn Rojas Quintero", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Monica Kraft", + "author_inst": "University of Arizona" + }, + { + "author_name": "Julie Ledford", + "author_inst": "University of Arizona" + }, + { + "author_name": "Fernando D Martinez", + "author_inst": "University of Arizona" + }, + { + "author_name": "Curtis Thorne", + "author_inst": "University of Arizona" + }, + { + "author_name": "Farrah Kheradmand", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Samuel K Campos", + "author_inst": "University of Arizona" + }, + { + "author_name": "Alberto Papi", + "author_inst": "University of Ferrara" + }, + { + "author_name": "Francesca Polverino", + "author_inst": "University of Arizona" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "pathology" + "license": "cc_no", + "type": "contradictory results", + "category": "immunology" }, { "rel_doi": "10.1101/2020.12.06.413443", @@ -1019978,51 +1019834,27 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2020.12.01.20242024", - "rel_title": "Food insecurity during COVID-19: A multi-state research collaborative", + "rel_doi": "10.1101/2020.12.02.20242685", + "rel_title": "Determinants of COVID-19 Incidence and Mortality in the US: Spatial Analysis", "rel_date": "2020-12-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.01.20242024", - "rel_abs": "The COVID-19 pandemic has had profound impacts on the global food system, supply chain, and employment, which, in turn, has created numerous challenges to food access and food security. Early exploratory studies suggest significant increases in food insecurity in the United States. Comprehensive longitudinal research across multiple locations is needed to understand the range of impacts and responses at the household level and to improve preparedness for future events. This protocol paper outlines the formation of the National Food Access and COVID research Team (NFACT), a collaborative, interdisciplinary, multi-state research effort that will utilize common measurement tools, codebooks, code, data aggregation tools, and outreach materials to collectively examine and communicate the effect of COVID-19 on household food access and security. NFACT is led by an executive committee of researchers from four institutions, with additional NFACT collaborating institutions across more than a dozen states. A survey was developed by the NFACT executive team in March 2020, with additional refinements in May 2020, using both existing validated questions and new original questions, which were piloted and validated in Vermont. The project provides suggestive guidance for recruitment, and is designed to allow each study site to adopt recruitment strategies that meet their budget and needs. Primary outcomes of interest include food security status, employment status, food access challenges and concerns, dietary intake, and use of food assistance programs. Additional outcomes assess emotional eating, stigma, COVID-19 perceptions and experiences, and pro-environmental purchasing behaviors. This protocol and the establishment of NFACT provide important advancements in COVID-19 and food security research by generating harmonized data and assessing comparable outcomes across geographies and time. The collaborative, open-source approach makes research tools available to teams who might not have the resources to design their own tools, and can enable streamlined data collection, large-scale comparative analyses, and cost savings through reduced administrative tasks. The project has contributed to building new networks between and within states. Enabling facilitation and implementation of instruments in study sites has provided flexibility and meaningful opportunity for local stakeholder engagement and relevant outreach for informed public health decision-making.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.02.20242685", + "rel_abs": "OBJECTIVESThe US continues to account for the highest proportion of the global Coronavirus Disease-2019 (COVID-19) cases and deaths. Currently, it is important to contextualize the spread and success of mitigation efforts. The objective of this study was to assess the ecological determinants (policy, health behaviors, socio-economic, physical environment, and clinical care) of COVID-19 incidence and mortality in the US.\n\nMETHODSData from the New York Times COVID-19 repository (01/21/2020-10/27/2020), 2020 County Health Rankings, 2016 County Presidential Election Returns, and 2018-2019 Area Health Resource File were used. County-level logged incidence and mortality rate/million were modeled using the Spatial Autoregressive Combined model and spatial lag model.\n\nRESULTSCounties with higher proportions of racial minorities (African American {beta}= 0.007, Native Americans {beta}= 0.008, Hispanics {beta}= 0.015), non-English speakers ({beta}= 0.010), population density ([logged] {beta}= 0.028), and air pollution ({beta}= 0.062) were significantly associated with high COVID-19 incidence rates. Subsequently, counties with higher Republican voters ({beta}= 0.017), excessive drinkers ({beta}= 0.107), children in single-parent households ({beta}= 0.018), uninsured adults ({beta}= 0.038), racial minorities (African American {beta}= 0.032, Native Americans {beta}= 0.034, Hispanics {beta}= 0.037), females ({beta}= 0.101), and population density ([logged] {beta}= 0.270), air pollution ({beta}= 0.130), and non-Whites/Whites residential segregation ({beta}= 0.014) were significantly associated with high COVID-19 mortality rates. Additionally, longer state-level restrictions were associated with lower COVID-19 incidence and mortality rates.\n\nCONCLUSIONSThe spatial models identified longer state-level restrictions, population density, air pollution, uninsured rate, and race/ethnicity as important determinants of the geographic disparities in COVID-19 incidence and mortality.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Meredith T. Niles", - "author_inst": "University of Vermont" - }, - { - "author_name": "Emily H. Belarmino", - "author_inst": "University of Vermont" - }, - { - "author_name": "Farryl Bertmann", - "author_inst": "University of Vermont" - }, - { - "author_name": "Erin Biehl", - "author_inst": "Johns Hopkins University" - }, - { - "author_name": "Francesco Acciai", - "author_inst": "Arizona State University" - }, - { - "author_name": "Anna L. Josephson", - "author_inst": "University of Arizona" - }, - { - "author_name": "Punam Ohri-Vachaspati", - "author_inst": "Arizona State University" + "author_name": "Niranjan Kathe", + "author_inst": "Complete HEOR Solution" }, { - "author_name": "Roni Neff", - "author_inst": "Johns Hopkins University" + "author_name": "Rajvi J Wani", + "author_inst": "Amgen Canada Inc" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "nutrition" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.12.02.20242925", @@ -1021680,31 +1021512,51 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.12.03.20243493", - "rel_title": "Supervised Image Classification Algorithm Using Representative Spatial Texture Features: Application to COVID-19 Diagnosis Using CT Images", + "rel_doi": "10.1101/2020.12.03.20243592", + "rel_title": "Surgery & COVID-19: A rapid scoping review of the impact of COVID-19 on surgical services during public health emergencies", "rel_date": "2020-12-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.03.20243493", - "rel_abs": "Although there is no universal definition for texture, the concept in various forms is nevertheless widely used and a key element of visual perception to analyze images in different fields. The present works main idea relies on the assumption that there exist representative samples, which we refer to as references as well, i.e., \"good or bad\" samples that represent a given dataset investigated in a particular data analysis problem. These representative samples need to be accounted for when designing predictive models with the aim of improving their performance. In particular, based on a selected subset of texture gray-level co-occurrence matrices (GLCMs) from the training cohort, we propose new representative spatial texture features, which we incorporate into a supervised image classification pipeline. The pipeline relies on the support vector machine (SVM) algorithm along with Bayesian optimization and the Wasserstein metric from optimal mass transport (OMT) theory. The selection of the best, \"good and bad,\" GLCM references is considered for each classification label and performed during the training phase of the SVM classifier using a Bayesian optimizer. We assume that sample fitness is defined based on closeness (in the sense of the Wasserstein metric) and high correlation (Spearmans rank sense) with other samples in the same class. Moreover, the newly defined spatial texture features consist of the Wasserstein distance between the optimally selected references and the remaining samples. We assessed the performance of the proposed classification pipeline in diagnosing the corona virus disease 2019 (COVID-19) from computed tomographic (CT) images.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.03.20243592", + "rel_abs": "BackgroundHealthcare systems globally have been challenged by the COVID-19 pandemic, necessitating the reorganization of surgical services to free capacity within healthcare systems.\n\nObjectivesTo understand how surgical services have been reorganized during and following public health emergencies, and the consequences of these changes for patients, healthcare providers and healthcare systems.\n\nMethodsThis rapid scoping review searched academic databases and grey literature sources to identify studies examining surgical service delivery during public health emergencies including COVID-19, and the impact on patients, providers and healthcare systems. Recommendations and guidelines were excluded. Screening was completed in partial (title, abstract) or complete (full text) duplicate following pilot reviews of 50 articles to ensure reliable application of eligibility criteria.\n\nResultsOne hundred and thirty-two studies were included in this review; 111 described reorganization of surgical services, 55 described the consequences of reorganizing surgical services and six reported actions taken to rebuild surgical capacity in public health emergencies. Reorganizations of surgical services were grouped under six domains: case selection/triage, PPE regulations and practice, workforce composition and deployment, outpatient and inpatient patient care, resident and fellow education, and the hospital or clinical environment. Service reorganizations led to large reductions in non-urgent surgical volumes, increases in surgical wait times, and impacted medical training (i.e., reduced case involvement) and patient outcomes (e.g., increases in pain). Strategies for rebuilding surgical capacity were scarce, but focused on the availability of staff, PPE, and patient readiness for surgery as key factors to consider before resuming services.\n\nConclusionsReorganization of surgical services in response to public health emergencies appears to be context-dependent and has far-reaching consequences that must be better understood in order to optimize future health system responses to public health emergencies.\n\nARTICLE SUMMARYO_ST_ABSStrengths and limitations of the studyC_ST_ABSO_LIThis rapid scoping review provides an exhaustive and rigorous summary of the academic and grey literature regarding modifications to surgical services in response to public health emergencies, especially COVID-19.\nC_LIO_LIThis study did not limit studies based on location or language of publication to ensure a worldwide pandemic had contributions from worldwide voices.\nC_LIO_LIBoth quantitative and qualitative outcomes were included, with a mix of inductive and deductive data abstraction approaches to provide a comprehensive understanding of surgical services during public health emergencies.\nC_LIO_LIStudies with potential relevance to this question are emerging at an unprecedented rate in response to the COVID-19 pandemic and as such, some may not be included in the current review.\nC_LI\n\nOriginal protocol for the studyAs requested, the original unpublished protocol for this study is included as a supplementary file.\n\nFunding statementThis study did not receive grant from any funding agency in the public, commercial or not-for-profit sectors.\n\nCompeting interest statementAll authors declare that they have no competing interests in accordance with the International Committee of Medical Journal Editors uniform declaration of competing interests.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Zehor Belkhatir", - "author_inst": "Leicester" + "author_name": "Connor O'Rielly", + "author_inst": "University of Calgary, Cumming School of Medicine" }, { - "author_name": "Raul San Jose Estepar", - "author_inst": "Brigham and Women's Hospital-Harvard Medical School, Boston, MA, USA" + "author_name": "Joshua Ng Kamstra", + "author_inst": "University of Calgary, Cumming School of Medicine" }, { - "author_name": "Allen R Tannenbaum", - "author_inst": "Stony Brook UNiversity" + "author_name": "Ania Kania-Richmond", + "author_inst": "Alberta Health Services" + }, + { + "author_name": "Joseph C Dort", + "author_inst": "University of Calgary, Cumming School of Medicine" + }, + { + "author_name": "Jonathan White", + "author_inst": "University of Alberta" + }, + { + "author_name": "Jill Robert", + "author_inst": "Alberta Health Services" + }, + { + "author_name": "Mary Brindle", + "author_inst": "University of Calgary, Cumming School of Medicine" + }, + { + "author_name": "Khara M Sauro", + "author_inst": "University of Calgary" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "radiology and imaging" + "category": "surgery" }, { "rel_doi": "10.1101/2020.12.03.20239681", @@ -1023174,83 +1023026,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.01.20237784", - "rel_title": "Extrapolation of United Kingdom Pillar 2 Care home Covid-19 test data to ascertain effectiveness of lateral flow testing in low prevalence settings", + "rel_doi": "10.1101/2020.12.01.20242172", + "rel_title": "Implications of delayed reopening in controlling the COVID-19 surge in Southern and West-Central USA", "rel_date": "2020-12-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.01.20237784", - "rel_abs": "Lateral flow devices are quickly being implemented for use in large scale population surveillance programs for SARS-CoV-2 infection in the United Kingdom. These programs have been piloted in city wide screening in the city of Liverpool, and are now being rolled out to support care home visits and the return home of University students for the Christmas break. Here we present data on the performance of Lateral Flow devices to test almost 8,000 students at the University of Birmingham between December 2nd and December 9th 2020. The performance is validated against almost 800 samples using PCR performed in the University Pillar 2 testing lab, and theoretically validated on thousands of Pillar 2 PCR testing results performed on low-prevalence care home testing samples. Our data shows that Lateral Flow Devices do not detect infections presenting with PCR Ct values over 29-30, meaning that only 3.2% (95% CI 0.6% to 15.6%) of total cases in the student population were detected, but that as many of 85% of cases tested in the Pillar 2 PCR lab would have been detected theoretically", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.01.20242172", + "rel_abs": "1In the wake of the rapid surge in the Covid-19 infected cases seen in Southern and West-Central USA in the period of June-July 2020, there is an urgent need to develop robust, data-driven models to quantify the effect which early reopening had on the infected case count increase. In particular, it is imperative to address the question: How many infected cases could have been prevented, had the worst affected states not reopened early? To address this question, we have developed a novel Covid-19 model by augmenting the classical SIR epidemiological model with a neural network module. The model decomposes the contribution of quarantine strength to the infection timeseries, allowing us to quantify the role of quarantine control and the associated reopening policies in the US states which showed a major surge in infections. We show that the upsurge in the infected cases seen in these states is strongly co-related with a drop in the quarantine/lockdown strength diagnosed by our model. Further, our results demonstrate that in the event of a stricter lockdown without early reopening, the number of active infected cases recorded on 14 July could have been reduced by more than 40% in all states considered, with the actual number of infections reduced being more than 100, 000 for the states of Florida and Texas. As we continue our fight against Covid-19, our proposed model can be used as a valuable asset to simulate the effect of several reopening strategies on the infected count evolution; for any region under consideration.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Jack Ferguson", - "author_inst": "University of Birmimgham" - }, - { - "author_name": "Steven Dunn", - "author_inst": "University of Birmimgham" - }, - { - "author_name": "Angus Best", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Jeremy Mirza", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Benita Percival", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Megan Mayhew", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Oliver Megram", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Fiona Ashford", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Thomas White", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Emma Moles-Garcia", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Tim Plant", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Andrew Bosworth", - "author_inst": "Public Health England" - }, - { - "author_name": "Mike Kidd", - "author_inst": "University of Birmingham" + "author_name": "Raj Abhijit Dandekar", + "author_inst": "Massachusetts Institute of Technology" }, { - "author_name": "Alex Richter", - "author_inst": "University of Birminghan" + "author_name": "Emma Wang", + "author_inst": "Massachusetts Institute of Technology" }, { - "author_name": "Jonathan J Deeks", - "author_inst": "University of Birmingham" + "author_name": "George Barbastathis", + "author_inst": "Massachusetts Institute of Technology" }, { - "author_name": "Alan McNally", - "author_inst": "University of Birmingham" + "author_name": "Chris Rackauckas", + "author_inst": "Massachusetts Institute of Technology" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.12.01.20241885", @@ -1024708,35 +1024512,43 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.11.30.20241380", - "rel_title": "Smoking increases the risk of COVID-19 positivity, while Never-smoking reduces the risk", + "rel_doi": "10.1101/2020.11.30.20234393", + "rel_title": "Distribution of SARS-CoV-2 RNA Signal in a Home with COVID-19 Positive Occupants", "rel_date": "2020-12-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.30.20241380", - "rel_abs": "IntroductionDoes smoking decrease the risk of testing positive for COVID-19 because the never-smokers (84%) prevalence is high and the current-smokers prevalence is low among COVID-19 positive patients? 1,2,3,4,5,6 We sought to determine whether never smoking increases the risk of COVID-19 positivity among the 50 to 69-year old patients because they are more likely to test positive for COVID-19.7\n\nMethodWe conducted a retrospective chart review of COVID-19 Polymerase chain reaction, in-hospital tested [≥]18-year-old patients. A Poisson regression analysis stratified into never-smokers and history of smoking (current + former smokers) was conducted.\n\nResults277 COVID-19 negative and 117 COVID-19 positive patients charts with a never-smokers prevalence of 42.32% and 54% respectively were analyzed. The never-smokers prevalence was 54%, 20-39-years; 61 %, 40 -49-years; 41%, 50 - 69-years; and 43%, 70 - 100-years.\n\nThe 40-49-year-old current and former smokers were more likely to test positive for COVID-19 [1.309 (1.047 - 1.635)], unlike the 40-49-year-old never-smokers [0.976 (0.890-1.071)] who had a lower risk.\n\nRegardless of their smoking status, males [1.084(1.021 - 1.151)] and the 50-69-year-old patients [1.082 (1.014 -1.154)] were more likely to test positive for COVID-19, while end stage renal disease [0.908(0.843-0.978)] and non-COVID-19 respiratory viral illness [0.907 (0.863 - 0.953)] patients had a lower risk of COVID-19 positivity.\n\nHeart failure [0.907 (0.830 - 0.991)], chronic obstructive pulmonary disease (COPD) [0.842 (0.745 - 0.952)] and Parkinsons disease [0.823 (0.708 - 0.957)] never-smokers were less likely to test positive for COVID-19.\n\nConclusionThis is the first study to show that smoking increases the risk of COVID-19 positivity among the 40-49-year-old patients, while not smoking reduces the risk of COVID-19 positivity among the heart failure, COPD and Parkinsons disease patients. This study emphasizes that COVID-19 positivity risk is not reduced by smoking and not increased by not smoking.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.30.20234393", + "rel_abs": "Although many COVID-19 patients quarantine and recover at home, the dispersal of SARS-CoV-2 onto surfaces and dust within the home environment remains poorly understood. To investigate the distribution and persistence of SARS-CoV-2 in a quarantine home, samples were collected from a household with two confirmed COVID-19 cases (one adult and one child). Home surface swab and dust samples were collected two months after symptom onset (and one month after symptom resolution) in the household. The strength of the SARS-CoV-2 molecular signal in fomites varied as a function of sample location, surface material and cleaning practices. Notably, the SARS-CoV-2 RNA signal was detected at several locations throughout the household although cleaning appears to have attenuated the signal on many surfaces. Of the 24 surfaces sampled, 46% were SARS-CoV-2 positive at the time of sampling. The SARS-CoV-2 concentrations in dust recovered from floor and HVAC filter samples ranged from 104-105 N2 gene copies/g dust. While detection of viral RNA does not imply infectivity, this study confirms that the SARS-CoV-2 RNA signal can be detected at several locations within a COVID-19 quarantine home and can persist after symptoms have resolved. In addition, the concentration of SARS-CoV-2 (normalized per unit mass of dust) recovered in home HVAC filters may prove useful for estimating SARS-CoV-2 airborne levels in homes.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "samson barasa", - "author_inst": "PeaceHealth Sacred Heart Center" + "author_name": "Juan P Maestre", + "author_inst": "The University of Texas at Austin" }, { - "author_name": "Josephine Kiage-Mokaya", - "author_inst": "Peace Health Sacred Heart Medical Center Riverbend, Eugene Oregon USA" + "author_name": "David Jarma", + "author_inst": "The University of Texas at Austin" }, { - "author_name": "Michael Friedlander", - "author_inst": "Peace Health Sacred Heart Medical Center Riverbend, Eugene Oregon USA" + "author_name": "Cesca Yu", + "author_inst": "The University of Texas at Austin" + }, + { + "author_name": "Jeffrey Siegel", + "author_inst": "University of Toronto" }, { - "author_name": "Katya Cruz-Madrid", - "author_inst": "Geriatric department University of Illinois at Chicago, Chicago Illinois USA" + "author_name": "Sharon Horner", + "author_inst": "The University of Texas at Austin" + }, + { + "author_name": "Kerry A Kinney", + "author_inst": "The University of Texas at Austin" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2020.12.01.20241570", @@ -1026298,67 +1026110,47 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.12.01.406934", - "rel_title": "MTX-COVAB, a human-derived antibody with potent neutralizing activity against SARS-CoV-2 infection in vitro and in a hamster model of COVID-19", - "rel_date": "2020-12-02", + "rel_doi": "10.1101/2020.12.01.406025", + "rel_title": "The N-glycosylation sites and Glycan-binding ability of S-protein in SARS-CoV-2 Coronavirus", + "rel_date": "2020-12-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.01.406934", - "rel_abs": "Fast track microfluidic screening of the antibody repertoires of 12 convalescent COVID-19 donors comprising 2.8mio antibodies yielded MTX-COVAB, a human-derived monoclonal antibody with low picomolar neutralization IC50 of SARS-CoV-2. COVAB neutralization potency is on par with the Regeneron cocktail as demonstrated in a comparative neutralization assay. MTX-COVAB shows strong efficacy in vivo and binds to all currently identified clinically relevant variants of SARS-CoV-2. MTX-COVAB completes GMP manufacturing by the end of this year and will be tested in the clinic in March 2021.", - "rel_num_authors": 12, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.01.406025", + "rel_abs": "The emerging acute respiratory disease, COVID-19, caused by SARS-CoV-2 Coronavirus (SARS2 CoV) has spread fastly all over the word. As a member of RNA viruses, the glycosylation of envelope glycoprotein plays the crucial role in protein folding, evasing host immune system, invading host cell membrane, even affecting host preference. Therefore, detail glyco-related researches have been adopted in the Spike protein (S-protein) of SARS2 CoV from the bioinformatic perspective. Phylogenic analysis of S-protein sequences revealed the evolutionary relationship of N-glycosylation sites in different CoVs. Structural comparation of S-proteins indicated their similarity and distributions of N-glycosylation sites. Further potential sialic acid or galactose affinity domains have been described in the S-protein by docking analysis. Molecular dynamic simulation for the glycosylated complexus of S-protein-ACE2 implied that the complicate viral binding of receptor-binding domain may be influenced by peripheric N-glycans from own and adjacent monoers. These works will contribute to investigate the N-glycosylation in S-protein and explain the highly contagious of COVID-19.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Christoph Esslinger", - "author_inst": "Memo Therapeutics AG" - }, - { - "author_name": "Simone Schmitt", - "author_inst": "Memo Therapeutics AG" - }, - { - "author_name": "Marcel Weber", - "author_inst": "Memo Therapeutics AG" - }, - { - "author_name": "Matthias Hillenbrand", - "author_inst": "Memo Therapeutics" - }, - { - "author_name": "Jemima Seidenberg", - "author_inst": "MTX" - }, - { - "author_name": "Andreas Zingg", - "author_inst": "MTX / University of Basel" + "author_name": "Wentian Chen", + "author_inst": "Northwest University" }, { - "author_name": "Catherine Townsend", - "author_inst": "MTX" + "author_name": "Ziye Hui", + "author_inst": "Northwest University" }, { - "author_name": "Barbara Eicher", - "author_inst": "MTX" + "author_name": "Xiameng Ren", + "author_inst": "Northwest University" }, { - "author_name": "Justina Rutkauskaite", - "author_inst": "MTX" + "author_name": "Yijie Luo", + "author_inst": "Northwest University" }, { - "author_name": "Peggy Riese", - "author_inst": "HZI" + "author_name": "Jian Shu", + "author_inst": "Northwest University" }, { - "author_name": "Carlos Alberto Guzman", - "author_inst": "HZI" + "author_name": "Hanjie Yu", + "author_inst": "Northwest University" }, { - "author_name": "Karsten Fischer", - "author_inst": "MTX" + "author_name": "Zheng Li", + "author_inst": "Northwest University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "new results", - "category": "immunology" + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2020.12.01.405738", @@ -1028476,39 +1028268,27 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.25.20238956", - "rel_title": "Impact of the COVID-19 pandemic on developmental care practices for infants born preterm", + "rel_doi": "10.1101/2020.11.29.20240481", + "rel_title": "Are psychiatric disorders risk factors for COVID-19 susceptibility and severity?a two-sample, bidirectional, univariable and multivariable Mendelian Randomization study", "rel_date": "2020-11-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.25.20238956", - "rel_abs": "ObjectivesTo assess the impact of the COVID-19 pandemic on rates of hospital visitation and rates and durations of developmental care practices for infants born preterm delivered by both families and clinical staff.\n\nMethodsWe analyzed electronic medical record data from infants born at less than 32 weeks gestational age (GA) cared for in the Lucile Packard Childrens Hospital neonatal intensive care unit (NICU) in a COVID-19-affected period (March 8, 2020 to May 31, 2020) and the analogous period in 2019. Our final sample consisted of 52 infants (n=27, 2019 cohort; n=25, 2020 cohort). Rates of family visitation and of family- and clinical staff-delivered developmental care were compared across cohorts, adjusting for GA at start of study period.\n\nResultsResults indicated that families of infants in the 2020 cohort visited less frequently (47% of available days) than those in the 2019 cohort (97%; p=0.001). Infants received developmental care activities less frequently in the 2020 cohort (3.51 vs. 4.72 activities per day; p=0.04), with a lower number of minutes per day (99.91 vs. 145.14; p=0.04) and a shorter duration per instance (23.41 vs. 29.65; p=0.03). Similar reductions occurred in both family- and staff-delivered developmental care activities.\n\nConclusionsThe COVID-19 pandemic has negatively impacted family visitation and preterm infant developmental care practices in the NICU, both experiences associated with positive health benefits. Hospitals should create programs to improve family visitation and engagement, while also increasing staff-delivered developmental care. Careful attention should be paid to long-term follow up of preterm infants and families.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.29.20240481", + "rel_abs": "Observational studies have suggested bidirectional associations between psychiatric disorders and COVID-19 phenotypes, but results of such studies are inconsistent. Mendelian Randomization (MR) may overcome limitations of observational studies, e.g. unmeasured confounding and uncertainties about cause and effect. We aimed to elucidate associations between neuropsychiatric disorders and COVID-19 susceptibility and severity. To that end, we applied a two-sample, bidirectional, univariable and multivariable MR design to genetic data from genome-wide association studies (GWASs) of neuropsychiatric disorders and COVID-19 phenotypes (released on 20 Oct. 2020). In single-variable Generalized Summary MR analysis the most significant and only Bonferroni-corrected significant result was found for genetic liability to BIP-SCZ (a combined GWAS of bipolar disorder and schizophrenia as cases vs. controls) increasing risk of COVID-19 (OR = 1.17, 95% CI, 1.06-1.28). However, we found a significant, positive genetic correlation between BIP-SCZ and COVID-19 of 0.295 and could not confirm causal or horizontally pleiotropic effects using another method. No genetic liabilities to COVID-19 phenotypes increased risk of (neuro)psychiatric disorders. In multivariable MR using both neuropsychiatric and a range of other phenotypes, only genetic instruments of BMI remained causally associated with COVID-19. All sensitivity analyses confirmed the results. In conclusion, while genetic liability to bipolar disorder and schizophrenia combined slightly increased COVID-19 susceptibility in one univariable analysis, other MR and multivariable analyses could only confirm genetic underpinnings of BMI to be causally implicated in COVID-19 susceptibility. Thus, using MR we found no consistent proof of genetic liabilities to (neuro)psychiatric disorders contributing to COVID-19 liability or vice versa, which is in line with at least two observational studies. Previously reported positive associations between psychiatric disorders and COVID-19 by others may have resulted from statistical models incompletely capturing BMI as a continuous covariate.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Melissa Scala", - "author_inst": "Stanford University School of Medicine" - }, - { - "author_name": "Virginia A. Marchman", - "author_inst": "Stanford University School of Medicine" - }, - { - "author_name": "Edith Brignoni-P\u00e9rez", - "author_inst": "Stanford University School of Medicine" - }, - { - "author_name": "Maya Chan Morales", - "author_inst": "Stanford University School of Medicine" + "author_name": "Jurjen Luykx", + "author_inst": "UMCU" }, { - "author_name": "Katherine E. Travis", - "author_inst": "Stanford University School of Medicine" + "author_name": "Bochao Lin", + "author_inst": "UMCU" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2020.11.26.20239103", @@ -1030086,57 +1029866,69 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.27.20240051", - "rel_title": "The impact of vaccination on COVID-19 outbreaks in the United States", + "rel_doi": "10.1101/2020.11.27.20238980", + "rel_title": "Evaluating recovery, cost, and throughput of different concentration methods for SARS-CoV-2 wastewater-based epidemiology", "rel_date": "2020-11-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.27.20240051", - "rel_abs": "BackgroundGlobal vaccine development efforts have been accelerated in response to the devastating COVID-19 pandemic. We evaluated the impact of a 2-dose COVID-19 vaccination campaign on reducing incidence, hospitalizations, and deaths in the United States (US).\n\nMethodsWe developed an agent-based model of SARS-CoV-2 transmission and parameterized it with US demographics and age-specific COVID-19 outcomes. Healthcare workers and high-risk individuals were prioritized for vaccination, while children under 18 years of age were not vaccinated. We considered a vaccine efficacy of 95% against disease following 2 doses administered 21 days apart achieving 40% vaccine coverage of the overall population within 284 days. We varied vaccine efficacy against infection, and specified 10% pre-existing population immunity for the base-case scenario. The model was calibrated to an effective reproduction number of 1.2, accounting for current non-pharmaceutical interventions in the US.\n\nResultsVaccination reduced the overall attack rate to 4.6% (95% CrI: 4.3% - 5.0%) from 9.0% (95% CrI: 8.4% - 9.4%) without vaccination, over 300 days. The highest relative reduction (54-62%) was observed among individuals aged 65 and older. Vaccination markedly reduced adverse outcomes, with non-ICU hospitalizations, ICU hospitalizations, and deaths decreasing by 63.5% (95% CrI: 60.3% - 66.7%), 65.6% (95% CrI: 62.2% - 68.6%), and 69.3% (95% CrI: 65.5% - 73.1%), respectively, across the same period.\n\nConclusionsOur results indicate that vaccination can have a substantial impact on mitigating COVID-19 outbreaks, even with limited protection against infection. However, continued compliance with non-pharmaceutical interventions is essential to achieve this impact.\n\nKey pointsVaccination with a 95% efficacy against disease could substantially mitigate future attack rates, hospitalizations, and deaths, even if only adults are vaccinated. Non-pharmaceutical interventions remain an important part of outbreak response as vaccines are distributed over time.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.27.20238980", + "rel_abs": "As the COVID-19 pandemic continues to affect communities across the globe, the need to contain the spread of the outbreaks is of paramount importance. Wastewater monitoring of the SARS-CoV-2 virus, the causative agent responsible for COVID-19, has emerged as a promising tool for health officials to anticipate outbreaks. As interest in wastewater monitoring continues to grow and municipalities begin to implement this approach, there is a need to further identify and evaluate methods used to concentrate SARS-CoV-2 virus RNA from wastewater samples. Here we evaluate the recovery, cost, and throughput of five different concentration methods for quantifying SARS-CoV-2 virus RNA in wastewater samples. We tested the five methods on six different wastewater samples. We also evaluated the use of a bovine coronavirus vaccine as a process control and pepper mild mottle virus as a normalization factor. Of the five methods we tested head-to-head, we found that HA filtration with bead beating performed the best in terms of sensitivity and cost. This evaluation can serve as a guide for laboratories establishing a protocol to perform wastewater monitoring of SARS-CoV-2.\n\nHighlightsO_LIFive methods for concentrating SARS-CoV-2 RNA from wastewater evaluated\nC_LIO_LIMethod performance characterized via recovery, cost, throughput, and variability\nC_LIO_LIHA filtration with bead beating had highest recovery for comparatively low cost\nC_LIO_LIBovine coronavirus, pepper mild mottle virus assessed as possible recovery controls\nC_LI", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Seyed M. Moghadas", - "author_inst": "York University" + "author_name": "Zachary W LaTurner", + "author_inst": "Rice University" }, { - "author_name": "Thomas N. Vilches", - "author_inst": "University of Campinas" + "author_name": "David M Zong", + "author_inst": "Rice University" }, { - "author_name": "Kevin Zhang", - "author_inst": "University of Toronto" + "author_name": "Prashant Kalvapalle", + "author_inst": "Rice University" }, { - "author_name": "Chad R. Wells", - "author_inst": "Yale University" + "author_name": "Kiara ReyesGamas", + "author_inst": "Rice University" }, { - "author_name": "Affan Shoukat", - "author_inst": "Yale University" + "author_name": "Austen Terwilliger", + "author_inst": "Baylor College of Medicine" }, { - "author_name": "Burton H. Singer", - "author_inst": "University of Florida" + "author_name": "Tessa Crosby", + "author_inst": "Rice University" }, { - "author_name": "Lauren Ancel Meyers", - "author_inst": "The University of Texas at Austin" + "author_name": "Priyanka Ali", + "author_inst": "Rice University" }, { - "author_name": "Kathleen M. Neuzil", - "author_inst": "University of Maryland" + "author_name": "Vasanthi Avadhanula", + "author_inst": "Baylor College of Medicine" }, { - "author_name": "Joanne M. Langley", - "author_inst": "Dalhousie University" + "author_name": "Haroldo Hernandez Santos", + "author_inst": "Baylor College of Medicine" }, { - "author_name": "Meagan C. Fitzpatrick", - "author_inst": "University of Maryland" + "author_name": "Kyle Weesner", + "author_inst": "Baylor College of Medicine" }, { - "author_name": "Alison P. Galvani", - "author_inst": "Yale University" + "author_name": "Loren Hopkins", + "author_inst": "Houston Health Department" + }, + { + "author_name": "Pedro A Piedra", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Anthony Maresso", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Lauren Stadler", + "author_inst": "Rice University" } ], "version": "1", @@ -1031512,83 +1031304,63 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.11.30.404905", - "rel_title": "Characterization of SARS-CoV-2 N protein reveals multiple functional consequences of the C-terminal domain", + "rel_doi": "10.1101/2020.11.30.404624", + "rel_title": "A Neutralizing Antibody-Conjugated Photothermal Nanoparticle Captures and Inactivates SARS-CoV-2", "rel_date": "2020-11-30", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.30.404905", - "rel_abs": "Nucleocapsid protein (N) is the most abundant viral protein encoded by SARS-CoV-2, the causative agent of COVID-19. N plays key roles at different steps in the replication cycle and is used as a serological marker of infection. Here we characterize the biochemical properties of SARS-CoV-2 N. We define the N domains important for oligomerization and RNA binding that are associated with spherical droplet formation and suggest that N accessibility and assembly may be regulated by phosphorylation. We also map the RNA binding interface using hydrogen-deuterium exchange mass spectrometry. Finally, we find that the N protein C-terminal domain is the most immunogenic by sensitivity, based upon antibody binding to COVID-19 patient samples from the US and Hong Kong. Together, these findings uncover domain-specific insights into the significance of SARS-CoV-2 N and highlight the diagnostic value of using N domains as highly specific and sensitive markers of COVID-19.", - "rel_num_authors": 16, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.30.404624", + "rel_abs": "The outbreak of 2019 coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in a global pandemic. Despite intensive research including several clinical trials, currently there are no completely safe or effective therapeutics to cure the disease. Here we report a strategy incorporating neutralizing antibodies conjugated on the surface of a photothermal nanoparticle to actively capture and inactivate SARS-CoV-2. The photothermal nanoparticle is comprised of a semiconducting polymer core and a biocompatible polyethylene glycol surface decorated with neutralizing antibodies. Such nanoparticles displayed efficient capture of SARS-CoV-2 pseudoviruses, excellent photothermal effect, and complete inhibition of viral entry into ACE2-expressing host cells via simultaneous blocking and inactivating of the virus. This photothermal nanoparticle is a flexible platform that can be readily adapted to other SARS-CoV-2 antibodies and extended to novel therapeutic proteins, thus providing a broad range of protection against multiple strains of SARS-CoV-2.\n\nO_FIG O_LINKSMALLFIG WIDTH=192 HEIGHT=200 SRC=\"FIGDIR/small/404624v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (66K):\norg.highwire.dtl.DTLVardef@44a5a8org.highwire.dtl.DTLVardef@d7bcd5org.highwire.dtl.DTLVardef@1ae6e70org.highwire.dtl.DTLVardef@d4a4f5_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Chao Wu", - "author_inst": "Washington University in St. Louis" - }, - { - "author_name": "Abraham J Qavi", - "author_inst": "Washington University in St. Louis" - }, - { - "author_name": "Asamaa Hachim", - "author_inst": "The University of Hong Kong" - }, - { - "author_name": "Niloufar Kavian", - "author_inst": "The University of Hong Kong" - }, - { - "author_name": "Aidan R. Cole", - "author_inst": "Washington University in St. Louis" - }, - { - "author_name": "Austin B. Moyle", - "author_inst": "Washington University in St. Louis" + "author_name": "Xiaolei Cai", + "author_inst": "University of Chicago" }, { - "author_name": "Nicole D. Wagner", - "author_inst": "Washington University in St. Louis" + "author_name": "Aleksander Prominski", + "author_inst": "University of Chicago" }, { - "author_name": "Joyce Sweeney-Gibbons", - "author_inst": "Georgia State University" + "author_name": "Yiliang Lin", + "author_inst": "University of Chicago" }, { - "author_name": "Henry W. Rohrs", - "author_inst": "Washington University in St. Louis" + "author_name": "Nicholas Ankenbruck", + "author_inst": "University of Chicago" }, { - "author_name": "Michael L. Gross", - "author_inst": "Washington University in St. Louis" + "author_name": "Jillian Rosenberg", + "author_inst": "University of Chicago" }, { - "author_name": "J. S. Malik Peiris", - "author_inst": "The University of Hong Kong" + "author_name": "Min Chen", + "author_inst": "University of Chicago" }, { - "author_name": "Christopher F. Basler", - "author_inst": "Georgia State University" + "author_name": "Jiuyun Shi", + "author_inst": "University of Chicago" }, { - "author_name": "Christopher W. Farnsworth", - "author_inst": "Washington University in St. Louis" + "author_name": "Eugene B. Chang", + "author_inst": "Univeristy of Chicago" }, { - "author_name": "Sophie A. Valkenburg", - "author_inst": "The University of Hong Kong" + "author_name": "Pablo Penaloza-MacMaster", + "author_inst": "Northwestern University" }, { - "author_name": "Gaya K. Amarasinghe", - "author_inst": "Washington University in St. Louis" + "author_name": "Bozhi Tian", + "author_inst": "University of Chicago" }, { - "author_name": "Daisy W. Leung", - "author_inst": "Washington University in St. Louis" + "author_name": "Jun Huang", + "author_inst": "University of Chicago" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "new results", - "category": "biochemistry" + "category": "bioengineering" }, { "rel_doi": "10.1101/2020.11.30.20240721", @@ -1032870,33 +1032642,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.24.20238055", - "rel_title": "How Timing of Stay-home Orders and Mobility Reductions Impacted First-Wave COVID-19 Deaths in US Counties", + "rel_doi": "10.1101/2020.11.24.20237628", + "rel_title": "Development of an Optical Assay to Detect SARS-CoV-2 Spike Protein Binding Interactions with ACE2 and Disruption of these Interactions Using Electric Current", "rel_date": "2020-11-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.24.20238055", - "rel_abs": "As SARS-CoV-2 transmission continues to evolve, understanding how location-specific variations in non-pharmaceutical interventions and behaviors contributed to disease transmission during the initial epidemic wave will be key for future control strategies. We offer a rigorous statistical analysis of the relative effectiveness of the timing of both official stay-at-home orders and population mobility reductions during the initial stage of the US epidemic. We use a Bayesian hierarchical regression to fit county-level mortality data from the first case on Jan 21 2020 through Apr 20 2020 and quantify associations between the timing of stay-at-home orders and population mobility with epidemic control. We find that among 882 counties with an early local epidemic, a 10-day delay in the enactment of stay-at-home orders would have been associated with 14,700 additional deaths by Apr 20 (95% credible interval: 9,100, 21,500), whereas shifting orders 10 days earlier would have been associated with nearly 15,700 fewer lives lost (95% credible interval: 11,350, 18,950). Analogous estimates are available for reductions in mobility--which typically occurred before stay-at-home orders--and are also stratified by county urbanicity, showing significant heterogeneity. Results underscore the importance of timely policy and behavioral action for early-stage epidemic control.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.24.20237628", + "rel_abs": "This study proposes a novel optical method of detecting and reducing SARS-CoV-2 transmission, the virus responsible for the COVID-19 pandemic that is sweeping the world today. SARS-CoV-2 belongs to the {beta}-coronaviruses characterized by the crown-shaped spike protein that protrudes out of the virus particles, giving the virus a \"corona\" shape; hence the name coronavirus. This virus is similar to the viruses that caused SARS (severe acute respiratory syndrome) and MERS (Middle East respiratory syndrome), the other two coronavirus epidemics that were recently contained within the last ten years. The technique being proposed uses a light source from a smart phone and a mobile spectrophotometer to enable detection of viral proteins in solution or paper as well as protein-protein interactions. The proof-of-concept is shown by detecting soluble preparations of spike protein subunits from SARS-CoV-2, followed by detection of the actual binding potential of the spike protein with its host receptor, the angiotensin-converting enzyme 2 (ACE2). The results are validated by showing that this method can detect antigen-antibody binding using two independent viral protein-antibody pairs. The binding could be detected optically both in solution and on a solid support such as nitrocellulose membrane. Finally, this technique is combined with DC bias to show that introduction of a current into the system can be used to disrupt the antigen-antibody reaction, suggesting that the proposed extended technique can be a potential means of not only detecting the virus, but also reducing virus transmission by disrupting virus-receptor interactions electrically.\n\nSignificanceThe measured intensity of light can reveal information about different cellular parameters under study. When light passes through a bio-composition, the intensity is associated with its content. The nuclei size, cell shape and the refractive index variation of cells contributes to light intensity. In this work, an optical label-free real time detection method incorporating the smartphone light source and a portable mini spectrometer for SARS-CoV-2 detection was developed based on the ability of its spike protein to interact with the ACE2 receptor. The light interactions with control and viral protein solutions were capable of providing a quick decision regarding whether the sample under test was positive or negative, thus enabling SARS-CoV-2 detection in a rapid manner.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Michelle Audirac", - "author_inst": "Independent Researcher" - }, - { - "author_name": "Mauricio Tec", - "author_inst": "The University of Texas at Austin" + "author_name": "Mahmoud Al Ahmad", + "author_inst": "UAEU" }, { - "author_name": "Spencer J Fox", - "author_inst": "The University of Texas at Austin" + "author_name": "Farah Mustafa", + "author_inst": "UAEU" }, { - "author_name": "Lauren Ancel Meyers", - "author_inst": "The University of Texas at Austin" + "author_name": "Neena Panicker", + "author_inst": "UAEU" }, { - "author_name": "Corwin Matthew Zigler", - "author_inst": "The University of Texas at Austin" + "author_name": "Tahir Rizvi", + "author_inst": "UAEU" } ], "version": "1", @@ -1034808,31 +1034576,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.25.394288", - "rel_title": "Inactivation of SARS-CoV-2 on surfaces and in solution with Virusend (TX-10), a novel disinfectant", + "rel_doi": "10.1101/241349", + "rel_title": "Massively parallel interrogation of protein fragment secretability using SECRiFY reveals features influencing secretory system transit", "rel_date": "2020-11-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.25.394288", - "rel_abs": "Until an effective vaccine against SARS-CoV-2 is available on a widespread scale, the control of the COVID-19 pandemic is reliant upon effective pandemic control measures. The ability of SARS-CoV-2 to remain viable on surfaces and in aerosols, means indirect contact transmission can occur and so there is an opportunity to reduce transmission using effective disinfectants in public and communal spaces. Virusend (TX-10), a novel disinfectant, has been developed as a highly effective disinfectant against a range of microbial agents. Here we investigate the ability of Virusend (TX-10) to inactivation SARS-CoV-2. Using surface and solution inactivation assays, we show that Virusend (TX-10) is able to reduce SARS-CoV-2 viral titre by 4log10 PFU/mL within 1 minute of contact. Ensuring disinfectants are highly effective against SARS-CoV-2 is important in eliminating environmental sources of the virus to control the COVID-19 pandemic.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/241349", + "rel_abs": "While transcriptome- and proteome-wide technologies to assess processes in protein biogenesis are now widely available, we still lack global approaches to assay post-ribosomal biogenesis events, in particular those occurring in the eukaryotic secretory system. We here developed a method, SECRiFY, to simultaneously assess the secretability of >105 protein fragments by two yeast species, S. cerevisiae and P. pastoris, using custom fragment libraries, surface display and a sequencing-based readout. Screening human proteome fragments with a median size of 50 - 100 amino acids, we generated datasets that enable datamining into protein features underlying secretability, revealing a striking role for intrinsic disorder and chain flexibility. SECRiFY is the first methodology that generates sufficient amounts of annotated data for advanced machine learning methods to deduce secretability predictors. The finding that secretability is indeed a learnable feature of protein sequences is of significant impact in the broad area of recombinant protein expression and de novo protein design.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Enyia R Anderson", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Siqi Wu", + "author_inst": "1. College of Life and Health Sciences, Northeastern University, Shenyang, Liaoning, China, 2. Key Laboratory of Data Analytics and Optimization for Smart Indu" }, { - "author_name": "Grant L Hughes", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Chang Tian", + "author_inst": "1. College of Life and Health Sciences, Northeastern University, Shenyang, Liaoning, China, 2. Key Laboratory of Data Analytics and Optimization for Smart Indus" }, { - "author_name": "Edward I Patterson", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Panpan Liu", + "author_inst": "1. College of Life and Health Sciences, Northeastern University, Shenyang, Liaoning, China, 2. Key Laboratory of Data Analytics and Optimization for Smart Indus" + }, + { + "author_name": "Dongjie Guo", + "author_inst": "1. College of Life and Health Sciences, Northeastern University, Shenyang, Liaoning, China, 2. Key Laboratory of Data Analytics and Optimization for Smart Indus" + }, + { + "author_name": "Wei Zheng", + "author_inst": "3. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, USA" + }, + { + "author_name": "Xiaoqiang Huang", + "author_inst": "3. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, USA" + }, + { + "author_name": "Yang Zhang", + "author_inst": "3. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, USA, 4. Department of Biological Chemistry, University of Michiga" + }, + { + "author_name": "Lijun Liu", + "author_inst": "1. College of Life and Health Sciences, Northeastern University, Shenyang, Liaoning, China, 2. Key Laboratory of Data Analytics and Optimization for Smart Indus" } ], - "version": "1", + "version": "4", "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2020.11.25.399055", @@ -1036442,111 +1036230,47 @@ "category": "geriatric medicine" }, { - "rel_doi": "10.1101/2020.11.23.20237313", - "rel_title": "Identifying optimal combinations of symptoms to trigger diagnostic work-up of suspected COVID-19 cases in vaccine trials: analysis from a community-based, prospective, observational cohort", + "rel_doi": "10.1101/2020.11.23.20236703", + "rel_title": "Evidence of the effectiveness of travel-related measures during the early phase of the COVID-19 pandemic: a rapid systematic review", "rel_date": "2020-11-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.23.20237313", - "rel_abs": "ObjectivesDiagnostic work-up following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify optimal symptom combinations to capture most cases using fewer tests with implications for COVID-19 vaccine developers across different resource settings and public health.\n\nMethodsUK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms and an RT-PCR test within seven days of symptom onset were included. Sensitivity, specificity, and number of RT-PCR tests needed to identify one case (test per case [TPC]) were calculated for different symptom combinations. A multi-objective evolutionary algorithm was applied to generate combinations with optimal trade-offs between sensitivity and specificity.\n\nFindingsUK and US cohorts included 122,305 (1,202 positives) and 3,162 (79 positive) individuals. Within three days of symptom onset, the COVID-19 specific symptom combination (cough, dyspnoea, fever, anosmia/ageusia) identified 69% of cases requiring 47 TPC. The combination with highest sensitivity (fatigue, anosmia/ageusia, cough, diarrhoea, headache, sore throat) identified 96% cases requiring 96 TPC.\n\nInterpretationWe confirmed the significance of COVID-19 specific symptoms for triggering RT-PCR and identified additional symptom combinations with optimal trade-offs between sensitivity and specificity that maximize case capture given different resource settings.\n\nHighlightsO_LIWidely recommended symptoms identified only [~]70% COVID-19 cases\nC_LIO_LIAdditional symptoms increased case finding to > 90% but tests needed doubled\nC_LIO_LIOptimal symptom combinations maximise case capture considering available resources\nC_LIO_LIImplications for COVID-19 vaccine efficacy trials and wider public health\nC_LI", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.23.20236703", + "rel_abs": "ObjectiveTo review evidence of the effectiveness of travel measures implemented during the early stages of the COVID-19 pandemic in order to recommend change on how evidence is incorporated in the International Health Regulations (2005) (IHR).\n\nDesignWe used an abbreviated preferred reporting items for systematic reviews and meta-analysis protocol (PRISMA-P) and a search strategy aimed to identify studies that investigated the effectiveness of travel-related measures (advice, entry and exit screening, medical examination or vaccination requirements, isolation or quarantine, the refusal of entry, and entry restrictions), pre-printed or published by June 1, 2020.\n\nResultsWe identified 29 studies, of which 26 were modelled (vs. observational). Thirteen studies investigated international measures while 17 investigated domestic measures (one investigated both), including suspended transportation (24 studies), border restrictions (21), and screening (5). There was a high level of agreement that the adoption of travel measures led to important changes in the dynamics of the early phases of the COVID-19 pandemic. However, most of the identified studies investigated the initial export of cases out of Wuhan, which was found to be highly effective, but few studies investigated the effectiveness of measures implemented in other contexts. Early implementation was identified as a determinant of effectiveness. Most studies of international travel measures failed to account for domestic travel measures, and thus likely led to biased estimates. Poor data and other factors contributed to the low quality of the studies identified.\n\nConclusionTravel measures, especially those implemented in Wuhan, played a key role in shaping the early transmission dynamics of the COVID-19 pandemic, however, the effectiveness of these measures was short-lived. There is an urgent need to address important evidence gaps, but also a need to review the way in which evidence is incorporated in the IHR in the early phases of a novel infectious disease outbreak.\n\nWhat is already known on this subject?O_LIPrevious reviews of the evidence from outbreaks of influenza and other infectious disease have generally found that there is limited evidence that travel-measures are effective at containing outbreaks.\nC_LIO_LIHowever, it is unclear if the lessons from other infectious disease outbreaks would be relevant in the context of COVID-19.\nC_LIO_LIBased on evidence at the time, WHO did not recommend any travel restrictions when it declared COVID-19 a Public Health Emergency of International Concern.\nC_LI\n\nWhat does this study add?O_LIThis study rapidly reviews the evidence on the effectiveness of travel measures implemented in the early phase of the pandemic on epidemiological countries.\nC_LIO_LIThe study investigated both international and domestic travel measures and a wide range of travel measures.\nC_LIO_LIThe study finds that the domestic travel measures implemented in Wuhan were effective at reducing the importation of cases internationally and within China. The study also finds that travel measures are more effective when implemented earlier in the outbreak.\nC_LIO_LIThe findings generate recommendations on how to incorporate evidence into the International Health Regulations and highlights important research gaps that remain.\nC_LI\n\nHow might this affect future outbreaks?O_LIThe findings of this study suggest the need to decouple recommendations of travel measures from the declaration of a public health emergency of international concern.\nC_LIO_LIHighlights the need to evaluate the potential effectiveness of travel measures for each outbreak, and not just assume effectiveness based on past outbreak scnearios.\nC_LI", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Michela Antonelli", - "author_inst": "King's College London" - }, - { - "author_name": "Joan Capdevila", - "author_inst": "Zoe Global" - }, - { - "author_name": "Amol Chaudhari", - "author_inst": "Coalition for Epidemic Preparedness Innovations" - }, - { - "author_name": "Julia Granerod", - "author_inst": "Coalition for Epidemic Preparedness Innovations" - }, - { - "author_name": "Liane S Canas", - "author_inst": "King's College London" - }, - { - "author_name": "Mark S Graham", - "author_inst": "King's College London" - }, - { - "author_name": "Kerstin Klaser", - "author_inst": "King's College London" - }, - { - "author_name": "Marc Modat", - "author_inst": "King's College London" - }, - { - "author_name": "Erika Molteni", - "author_inst": "King's College London" - }, - { - "author_name": "Ben Murray", - "author_inst": "King's College London" - }, - { - "author_name": "Carole H Sudre", - "author_inst": "University College London" - }, - { - "author_name": "Richard Davies", - "author_inst": "Zoe Global" - }, - { - "author_name": "Anna May", - "author_inst": "Zoe Global" - }, - { - "author_name": "Long H Nguyen", - "author_inst": "Massachusetts General Hospital and Harvard Medical School" - }, - { - "author_name": "David A Drew", - "author_inst": "Massachusetts General Hospital and Harvard Medical School" - }, - { - "author_name": "Amit Joshi", - "author_inst": "Massachusetts General Hospital and Harvard Medical School" - }, - { - "author_name": "Andrew T Chan", - "author_inst": "Massachusetts General Hospital and Harvard Medical School" + "author_name": "Karen Ann Grepin", + "author_inst": "University of Hong Kong" }, { - "author_name": "Jakob Cramer", - "author_inst": "Coalition for Epidemic Preparedness Innovations" + "author_name": "Tsi-Lok Ho", + "author_inst": "University of Hong Kong" }, { - "author_name": "Tim Spector", - "author_inst": "King's College London" + "author_name": "Zhihan Liu", + "author_inst": "University of Hong Kong" }, { - "author_name": "Jonathan Wolf", - "author_inst": "Zoe Global" + "author_name": "Summer Marion", + "author_inst": "University of Maryland" }, { - "author_name": "Sebastien Ourselin", - "author_inst": "King's College London" + "author_name": "Julianne Piper", + "author_inst": "Simon Fraser University" }, { - "author_name": "Claire J Steves", - "author_inst": "King's College London" + "author_name": "Catherin Z Worsnop", + "author_inst": "University of Maryland" }, { - "author_name": "Alfred E Loeliger", - "author_inst": "Coalition for Epidemic Preparedness Innovations" + "author_name": "Kelley Lee", + "author_inst": "Simon Fraser University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "health policy" }, { "rel_doi": "10.1101/2020.11.23.20237198", @@ -1038316,35 +1038040,23 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.20.20235267", - "rel_title": "Analytical and diagnostic performances of a high-throughput immunoassay for SARS-CoV-2 IgM and IgG", - "rel_date": "2020-11-24", + "rel_doi": "10.1101/2020.11.20.20235689", + "rel_title": "Comparative analysis of the first wave of the COVID-19 pandemic in South Korea, Italy, Spain, France, Germany, the United Kingdom, the USA and the New-York state", + "rel_date": "2020-11-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.20.20235267", - "rel_abs": "BackgroundO_ST_ABSAbstractC_ST_ABSReliable SARS-CoV-2 serological assays are required for diagnosing infections, for the serosurveillance of past exposures and for assessing the response to future vaccines. In this study, the analytical and clinical performances of a chemiluminescent immunoassays for SARS-CoV-2 IgM and IgG detection (Mindray CL-1200i), targeting Nucleocapsid (N) and receptor binding domain (RBD) portion of the Spike protein, were evaluated.\n\nMethodsPrecision and linearity were evaluated using standardized procedures. A total of 157 leftover serum samples from 81 hospitalized confirmed COVID-19 patients (38 with moderate and 43 with severe disease) and 76 SARS-CoV-2 negative subjects (44 healthcare workers, 20 individuals with rheumatic disorders, 12 pregnant women) were included in the study. In an additional series of 44 SARS-CoV-2 positive, IgM and IgG time kinetics were also evaluated in a time-period of 38 days.\n\nResultsPrecision was below or equal to 4% for both IgM and IgG, in all the studied levels, whilst a slightly significant deviation from linearity was observed for both assays in the range of values covering the manufacturers cut-off. Considering a time frame [≥] 12 days post symptom onset, sensitivity and specificity for IgM were 92.3% (95%CI:79.1%-98.4%) and 92.1% (95%CI:83.6%-97.0%). In the same time frame, sensitivity and specificity for IgG were 100% (95%CI:91.0%-100%) and 93.4% (95%CI:85.3%-97.8%). The assays agreement was 73.9% (Cohens kappa of 0.373). Time kinetics showed a substantial overlapping of IgM and IgG response, the latter values being elevated up to 38 days from symptoms onset.\n\nConclusionsAnalytical imprecision is satisfactory as well as the linearity, particularly when taking into account the fact that both assays are claimed to be qualitative. Diagnostic sensitivity of IgG was excellent, especially considering specimens collected [≥]12 days post symptom onset. Time kinetics suggest that IgM and IgG are detectable early in the course of infection, but the role of SARS-CoV-2 antibodies in clinical practice still requires further evaluations.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.20.20235689", + "rel_abs": "We use an exponential growth model to analyze the first wave of the COVID-19 pandemic in South Korea, Italy, Spain, France, Germany, the United Kingdom, the USA and the New-York state. This model uses the number of officially reported patients tested positive and deaths to estimate an infected hindcast of the cumulative number of patients who later tested positive or who later die. For each region, an epidemic timeline is established, obtaining a precise knowledge of the chronology of the main epidemiological events during the full course of the first wave. It includes, in particular, the time that the virus has been in free circulation before the impact of the social distancing measures were observable. The results of the study suggest that among the analyzed regions, only South Korea and Germany possessed, at the beginning of the epidemic, a testing capacity that allowed to correctly follow the evolution of the epidemic. Anticipation in taking measures in these two countries caused the virus to spend less time in free circulation than in the rest of the regions. The analysis of the growth rates in the different regions suggests that the exponential growth rate of the cumulative number of infected, when the virus is in free circulation, is around 0.250737. In addition, we also study the ability of the model to properly forecast the epidemic spread at the beginning of the epidemic outbreak when very little data and information about the coronavirus were available. In the case of France, we obtain a reasonable estimate of the peak of the new cases of patients tested positive 9 days in advance and only 7 days after the implementation of a strict lockdown.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Andrea Padoan", - "author_inst": "university of padova" - }, - { - "author_name": "Chiara Cosma", - "author_inst": "University of Padova" - }, - { - "author_name": "Paolo Zaupa", - "author_inst": "University of Padova" - }, - { - "author_name": "Mario Plebani", - "author_inst": "University of Padova" + "author_name": "Luis Alvarez", + "author_inst": "Universidad de Las Palmas de Gran Canaria" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.11.20.20233890", @@ -1039726,35 +1039438,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.20.20235424", - "rel_title": "Covid-19 pandemic lessons: Uncritical communication of test results can induce more harm than benefit and raises questions on standardized quality criteria for communication and liability", + "rel_doi": "10.1101/2020.11.21.20236083", + "rel_title": "Sensitivity Analysis on Predictive Capability of SIRD Model for Coronavirus Disease (COVID-19)", "rel_date": "2020-11-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.20.20235424", - "rel_abs": "BackgroundThe COVID-19 pandemic is characterized by both health and economic risks. A safety loop model postulates risk-related decisions are not based on objective and measurable risks but on the subjective perception of those risks. We here illustrate a quantification of the difference between objective and subjective risks.\n\nMethodThe objective risks (or chances) can be obtained from traditional 2 x 2 tables by calculating the positive (+LR) and negative (-LR) likelihood ratios. The subjective perception of objective risks is calculated from the same 2 x 2 tables by exchanging the X- and Y-axes. The traditional 2 x 2 table starts with the hypothesis, uses a test and a gold standard to confirm or exclude the investigated condition. The 2 x 2 table with inverted axes starts with the communication of a test result and presumes that the communication of bad news (whether right or false) will induce perceived anxiety while good news will induce perceived safety. Two different functions (confirmation and exclusion) of both perceptions (perceived anxiety and safety) can be quantified with those calculations.\n\nResultsThe analysis of six published tests and of one incompletely reported test on COVID-19 polymerase chain reactions (completed by four assumptions on high and low sensitivities and specificities) demonstrated that none of these tests induces perceived safety. Eight of the ten tests confirmed the induction of perceived anxiety with +LRs (range 3.1 - 5900). In two of these eight tests a -LR (0.25 and 0.004) excluded the induction of perceived safety.\n\nConclusionsCommunication of test results caused perceived anxiety but not perceived safety in 80% of the investigated tests. Medical tests - whether right or false - generate strong psychological messages. In the case of COVID-19 tests may induce more perceived anxiety than safety.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.21.20236083", + "rel_abs": "SIR model is one of the simplest methods used in prediction of endemic/pandemic outbreaks. We examined SIRD model for development of COVID-19 in Kuwait which was started on 24 February 2020 by 5 patients in Kuwait. This paper investigates sensitivity of SIRD model for development of COVID-19 in Kuwait based on duration of progressed days of data. For Kuwait, we have fitted SIRD model to COVID-19 data for 20, 40, 60, 80, 100, and 116 days of data and assessed sensitivity of the model with number of days of data. The parameters of SIRD model are obtained using an optimization algorithm (lsqcurvefit) in MATLAB. The total population of 50,000 is equally applied for all Kuwait time intervals. Results of SIRD model indicates that after 40 days the peak infectious day can be adequately predicted; althogh, error percentage from sensetivity analysis indicates that different exposed population sizes are not correctly predicted. SIRD type models are too simple to robustly capture all features of COVID-19 and more precise methods are needed to tackle nonlinear dynamics of a pandemic.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Franz Porzsolt", - "author_inst": "Institute of Clinical Economics" + "author_name": "Ahmad Sedaghat", + "author_inst": "School of Engineering, Australian College of Kuwait, Safat 13015, Kuwait;" }, { - "author_name": "Gerit Pfuhl", - "author_inst": "UiT The Arctic University of Norway" + "author_name": "Fadi Alkhatib", + "author_inst": "School of Engineering, Australian College of Kuwait, Safat 13015, Kuwait" }, { - "author_name": "Robert M Kaplan", - "author_inst": "Stanford University" + "author_name": "Seyed Amir Abbas Oloomi", + "author_inst": "Department of Mechanical Engineering, Yazd Branch, Islamic Azad University, Yazd, Iran" }, { - "author_name": "Martin Eisemann", - "author_inst": "UiT The Arctic University of Norway" + "author_name": "Mahdi Ashtian Malayer", + "author_inst": "Young Researchers and Elite Club, Yazd Branch, Islamic Azad University, Yazd, Iran" + }, + { + "author_name": "Amir MOSAVI", + "author_inst": "Obuda University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.11.21.392555", @@ -1041360,49 +1041076,157 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.19.20235077", - "rel_title": "At the dawn of winter: comparing COVID-19and influenza presentation and trajectory", + "rel_doi": "10.1101/2020.11.19.20234229", + "rel_title": "Microbial context predicts SARS-CoV-2 prevalence in patients and the hospital built environment", "rel_date": "2020-11-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.19.20235077", - "rel_abs": "BackgroundCOVID-19 is a newly recognized illness with a predominantly respiratory presentation. It is important to characterize the differences in disease presentation and trajectory between COVID-19 patients and other patients with common respiratory illnesses. These differences can enhance knowledge of pathogenesis and help in guiding treatment.\n\nMethodsData from electronic medical records were obtained from individuals admitted with respiratory illnesses to Rambam Health Care Campus, Haifa, Israel, between October 1st, 2014 and October 1st, 2020. Four groups of patients were defined: COVID-19 (693), influenza (1,612), severe acute respiratory infection (SARI) (2,292) and Others (4,054). The variable analyzed include demographics (7), vital signs (8), lab tests (38),and comorbidities (15) from a total of 8,651 hospitalized adult patients. Statistical analysis was performed on biomarkers measured at admission and for their disease trajectory in the first 48 hours of hospitalization, and on comorobidity prevalence.\n\nResultsCOVID-19 patients were overall younger in age and had higher body mass index, compared to influenza and SARI. Comorbidity burden was lower in the COVID-19 group compared to influenza and SARI. Severely- and moderately-ill COVID-19 patients older than 65 years of age suffered higher rate of in-hospital mortality compared to hospitalized influenza patients. At admission, white blood cells and neutrophils were lower among COVID-19 patients compared to influenza and SARI patients, while pulse rate and lymphoctye percentage were higher. Trajectories of variables during the first two days of hospitalization revealed that white blood count, neutrophils percentage and glucose in blood increased among COVID-19 patients, while decreasing among other patients.\n\nConclusionsThe intrinsic virulence of COVID-19 appeared higher than influenza. In addition, several critical functions, such as immune response, coagulation, heart and respiratory function and metabolism were uniquely affected by COVID-19.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.19.20234229", + "rel_abs": "Synergistic effects of bacteria on viral stability and transmission are widely documented but remain unclear in the context of SARS-CoV-2. We collected 972 samples from hospitalized patients with coronavirus disease 2019 (COVID-19), their health care providers, and hospital surfaces before, during, and after admission. We screened for SARS-CoV-2 using RT-qPCR, characterized microbial communities using 16S rRNA gene amplicon sequencing, and contextualized the massive microbial diversity in this dataset through meta-analysis of over 20,000 samples. Sixteen percent of surfaces from COVID-19 patient rooms were positive, with the highest prevalence in floor samples next to patient beds (39%) and directly outside their rooms (29%). Although bed rail samples increasingly resembled the patient microbiome over time, SARS-CoV-2 was detected less there (11%). Despite viral surface contamination in almost all patient rooms, no health care workers contracted the disease, suggesting that personal protective equipment was effective in preventing transmissions. SARS-CoV-2 positive samples had higher bacterial phylogenetic diversity across human and surface samples, and higher biomass in floor samples. 16S microbial community profiles allowed for high SARS-CoV-2 classifier accuracy in not only nares, but also forehead, stool, and floor samples. Across distinct microbial profiles, a single amplicon sequence variant from the genus Rothia was highly predictive of SARS-CoV-2 across sample types and had higher prevalence in positive surface and human samples, even compared to samples from patients in another intensive care unit prior to the COVID-19 pandemic. These results suggest that bacterial communities may contribute to viral prevalence both in the host and hospital environment.\n\nOne Sentence SummaryMicrobial classifier highlights specific taxa predictive of SARS-CoV-2 prevalence across diverse microbial niches in a COVID-19 hospital unit.", + "rel_num_authors": 35, "rel_authors": [ { - "author_name": "Anat Reiner Benaim", - "author_inst": "Rambam Health Care Campus, Haifa, Israel" + "author_name": "Clarisse Marotz", + "author_inst": "University of California San Diego" }, { - "author_name": "Jonathan Aryeh Sobel", - "author_inst": "Technion" + "author_name": "Pedro Belda-Ferre", + "author_inst": "University of California San Diego" }, { - "author_name": "Ronit Almog", - "author_inst": "Rambam Health Care Campus, Haifa, Israel" + "author_name": "Farhana Ali", + "author_inst": "University of California San Diego" }, { - "author_name": "Snir Lugassy", - "author_inst": "Faculty of Biomedical Engineering, Technion, Israel Institute of Technology, Haifa, Israel" + "author_name": "Promi Das", + "author_inst": "University of California San Diego" }, { - "author_name": "Tsviel Ben Shabbat", - "author_inst": "Faculty of Biomedical Engineering, Technion, Israel Institute of Technology, Haifa, Israel" + "author_name": "Shi Huang", + "author_inst": "University of California San Diego" }, { - "author_name": "Alistair Johnson", - "author_inst": "MIT Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA" + "author_name": "Kalen Cantrel", + "author_inst": "University of California San Diego" }, { - "author_name": "Danny Eytan", - "author_inst": "Rambam Health Care Campus, Haifa, Israel" + "author_name": "Lingjing Jiang", + "author_inst": "University of California San Diego" }, { - "author_name": "Joachim A. Behar", - "author_inst": "Faculty of Biomedical Engineering, Technion, Israel Institute of Technology, Haifa, Israel" + "author_name": "Cameron Martino", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Rachel Diner", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Gibraan Rahman", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Daniel McDonald", + "author_inst": "University of California San Diego" + }, + { + "author_name": "George Armstrong", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Sho Kodera", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Sonya Donato", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Gertrude Ecklu-Mensah", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Neil Gottel", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Mariana Salas Garcia", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Leslie Chiang", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Rodolfo A. Salido", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Justin P. Shaffer", + "author_inst": "University of California San Diego" + }, + { + "author_name": "MacKenzie Bryant", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Karenina Sanders", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Greg Humphrey", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Gail Ackermann", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Niina Haiminen", + "author_inst": "IBM" + }, + { + "author_name": "Kristen L. Beck", + "author_inst": "IBM" + }, + { + "author_name": "Ho-Cheol Kim", + "author_inst": "IBM" + }, + { + "author_name": "Anna Paola Carrieri", + "author_inst": "IBM" + }, + { + "author_name": "Laxmi Parida", + "author_inst": "IBM" + }, + { + "author_name": "Yoshiki Vazquez-Baeza", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Francesca J. Torriani", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Rob Knight", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Jack Gilbert", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Daniel Sweeney", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Sarah M. Allard", + "author_inst": "University of California San Diego" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1043658,131 +1043482,167 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.11.19.390187", - "rel_title": "AI-Driven Multiscale Simulations Illuminate Mechanisms of SARS-CoV-2 Spike Dynamics", + "rel_doi": "10.1101/2020.11.16.20229047", + "rel_title": "Two independent introductions of SARS-CoV-2 into the Iranian outbreak", "rel_date": "2020-11-20", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.19.390187", - "rel_abs": "We develop a generalizable AI-driven workflow that leverages heterogeneous HPC resources to explore the time-dependent dynamics of molecular systems. We use this workflow to investigate the mechanisms of infectivity of the SARS-CoV-2 spike protein, the main viral infection machinery. Our workflow enables more efficient investigation of spike dynamics in a variety of complex environments, including within a complete SARS-CoV-2 viral envelope simulation, which contains 305 million atoms and shows strong scaling on ORNL Summit using NAMD. We present several novel scientific discoveries, including the elucidation of the spikes full glycan shield, the role of spike glycans in modulating the infectivity of the virus, and the characterization of the flexible interactions between the spike and the human ACE2 receptor. We also demonstrate how AI can accelerate conformational sampling across different systems and pave the way for the future application of such methods to additional studies in SARS-CoV-2 and other molecular systems.\n\nACM Reference FormatLorenzo Casalino1{dagger}, Abigail Dommer1{dagger}, Zied Gaieb1{dagger}, Emilia P. Barros1, Terra Sztain1, Surl-Hee Ahn1, Anda Trifan2,3, Alexander Brace2, Anthony Bogetti4, Heng Ma2, Hyungro Lee5, Matteo Turilli5, Syma Khalid6, Lillian Chong4, Carlos Simmerling7, David J. Hardy3, Julio D. C. Maia3, James C. Phillips3, Thorsten Kurth8, Abraham Stern8, Lei Huang9, John McCalpin9, Mahidhar Tatineni10, Tom Gibbs8, John E. Stone3, Shantenu Jha5, Arvind Ramanathan2*, Rommie E. Amaro1*. 2020. AI-Driven Multiscale Simulations Illuminate Mechanisms of SARS-CoV-2 Spike Dynamics. In Supercomputing 20: International Conference for High Performance Computing, Networking, Storage, and Analysis. ACM, New York, NY, USA, 14 pages. https://doi.org/finalDOI", - "rel_num_authors": 28, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.16.20229047", + "rel_abs": "The SARS-CoV-2 virus has been rapidly spreading globally since December 2019, triggering a pandemic, soon after its emergence, with now more than one million deaths around the world. While Iran was among the first countries confronted with rapid spread of virus in February, no real-time SARS-CoV-2 whole-genome tracking is performed in the country.\n\nTo address this issue, we provided 50 whole-genome sequences of viral isolates ascertained from different geographical locations in Iran during March-July 2020. The corresponding analysis on origins, transmission dynamics and genetic diversity, represented at least two introductions of the virus into the country, constructing two major clusters defined as B.4 and B.1*. The first entry of the virus occurred around 26 December 2019, as suggested by the time to the most recent common ancestor, followed by a rapid community transmission, led to dominancy of B.4 lineage in early epidemic till the end of June. Gradually, reduction in dominancy of B.4 occurred possibly as a result of other entries of the virus, followed by surge of B.1.* lineages, as of mid-May.\n\nRemarkably, variation tracking of the virus indicated the increase in frequency of D614G mutation, along with B.1* lineages, which showed continuity till October 2020.\n\nAccording to possible role of D614G in increased infectivity and transmission of the virus, and considering the current high prevalence of the disease, dominancy of this lineage may push the country into a critical health situation. Therefore, current data warns for considering stronger prohibition strategies preventing the incidence of larger crisis in future.", + "rel_num_authors": 37, "rel_authors": [ { - "author_name": "Lorenzo Casalino", - "author_inst": "University of California San Diego" + "author_name": "Zohreh Fattahi", + "author_inst": "1.\tGenetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran. 2.\tKariminejad-Najmabadi Pathology & Genetics Center, Tehra" }, { - "author_name": "Abigail C Dommer", - "author_inst": "UC San Diego" + "author_name": "Marzieh Mohseni", + "author_inst": "1.\tGenetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran. 2.\tKariminejad-Najmabadi Pathology & Genetics Center, Tehra" }, { - "author_name": "Zied Gaieb", - "author_inst": "University of California, San Diego" + "author_name": "Khadijeh Jalalvand", + "author_inst": "1.\tGenetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran." }, { - "author_name": "Emilia P. Barros", - "author_inst": "University of California, San Diego" + "author_name": "Fatemeh Aghakhani Moghadam", + "author_inst": "1.\tGenetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran." }, { - "author_name": "Terra Sztain", - "author_inst": "University of California, San Diego" + "author_name": "Azam Ghaziasadi", + "author_inst": "4.\tDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. 5.\tResearch Center for Clinical Virology, Tehran Univer" }, { - "author_name": "Surl-Hee Ahn", - "author_inst": "UC San Diego" + "author_name": "Fatemeh Keshavarzi", + "author_inst": "1.\tGenetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran." }, { - "author_name": "Anda Trifan", - "author_inst": "Argonne National Lab" + "author_name": "Jila Yavarian", + "author_inst": "4.\tDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran." }, { - "author_name": "Alexander Brace", - "author_inst": "Argonne National Lab" + "author_name": "Ali Jafarpour", + "author_inst": "4.\tDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. 5.\tResearch Center for Clinical Virology, Tehran Univer" }, { - "author_name": "Heng Ma", - "author_inst": "Argonne National Lab" + "author_name": "Seyedeh elham Mortazavi", + "author_inst": "6.\tDepartment of Microbiology, Faculty of Biology, College of Science, University of Science & Research, Tehran, Iran." }, { - "author_name": "Hyungro Lee", - "author_inst": "Rutgers University" + "author_name": "Fatemeh Ghodratpour", + "author_inst": "1.\tGenetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran." }, { - "author_name": "Matteo Turilli", - "author_inst": "Rutgers University" + "author_name": "Hanieh Behravan", + "author_inst": "1.\tGenetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran." }, { - "author_name": "Anthony Bogetti", - "author_inst": "University of Pittsburgh" + "author_name": "Mohammad Khazeni", + "author_inst": "4.\tDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. 7.\tBooali laboratory, Qom, Iran." }, { - "author_name": "Syma Khalid", - "author_inst": "University of Southampton" + "author_name": "Seyed Amir Momeni", + "author_inst": "7.\tBooali laboratory, Qom, Iran." }, { - "author_name": "Lillian Chong", - "author_inst": "University of Pittsburgh" + "author_name": "Issa Jahanzad", + "author_inst": "8.\tPars hospital lab, Rasht, Iran." }, { - "author_name": "Carlos Simmerling", - "author_inst": "Stony Brook University" + "author_name": "Abdolvahab Moradi", + "author_inst": "9.\tInfectious Diseases Research Center, Golestan University of Medical Sciences, Golestan, Iran." }, { - "author_name": "David Hardy", - "author_inst": "University of Illinois at Urbana-Champaign" + "author_name": "Alijan Tabarraei", + "author_inst": "9.\tInfectious Diseases Research Center, Golestan University of Medical Sciences, Golestan, Iran." }, { - "author_name": "Julio Maia", - "author_inst": "University of Illinois at Urbana-Champaign" + "author_name": "Sadegh Ali Azimi", + "author_inst": "9.\tInfectious Diseases Research Center, Golestan University of Medical Sciences, Golestan, Iran." }, { - "author_name": "James Phillips", - "author_inst": "University of Illinois at Urbana-Champaign" + "author_name": "Ebrahim Kord", + "author_inst": "10.\tInfectious Disease and Tropical Medicine Research Center, Resistant Tuberculosis Institute, Zahedan University of Medical Sciences, Zahedan, Iran." }, { - "author_name": "Thorsten Kurth", - "author_inst": "NVIDIA Corp" + "author_name": "Seyed Mohammad Hashemi-Shahri", + "author_inst": "10.\tInfectious Disease and Tropical Medicine Research Center, Resistant Tuberculosis Institute, Zahedan University of Medical Sciences, Zahedan, Iran." }, { - "author_name": "Abraham Stern", - "author_inst": "NVIDIA Corp" + "author_name": "Azarakhsh Azaran", + "author_inst": "11.\tDepartment of Virology, School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran." }, { - "author_name": "Lei Huang", - "author_inst": "University of Texas Austin" + "author_name": "Farid Yousefi", + "author_inst": "11.\tDepartment of Virology, School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran." }, { - "author_name": "John McCalpain", - "author_inst": "University of Texas Austin" + "author_name": "Zakiye Mokhames", + "author_inst": "12.\tDepartment of Molecular Diagnostic, Emam Ali Educational and Therapeutic Center, Alborz University of Medical Sciences, Karaj, Iran." }, { - "author_name": "Mahidhar Tatineni", - "author_inst": "UC San Diego" + "author_name": "Alireza Soleimani", + "author_inst": "12.\tDepartment of Molecular Diagnostic, Emam Ali Educational and Therapeutic Center, Alborz University of Medical Sciences, Karaj, Iran." }, { - "author_name": "Tom Gibbs", - "author_inst": "NVIDIA Corp" + "author_name": "Shokouh Ghafari", + "author_inst": "13.\tInfectious Diseases Research Center, Birjand University of Medical Sciences, Birjand, Iran." }, { - "author_name": "John E. Stone", - "author_inst": "University of Illinois at Urbana-Champaign" + "author_name": "Masood Ziaee", + "author_inst": "13.\tInfectious Diseases Research Center, Birjand University of Medical Sciences, Birjand, Iran." }, { - "author_name": "Shantenu Jha", - "author_inst": "Rutgers University" + "author_name": "Shahram Habibzadeh", + "author_inst": "14.\tDepartment of Infectious Disease, Ardabil University of Medical Sciences, Ardabil, Iran." }, { - "author_name": "Arvind Ramanathan", - "author_inst": "Argonne National Lab" + "author_name": "Farhad Jeddi", + "author_inst": "14.\tDepartment of Infectious Disease, Ardabil University of Medical Sciences, Ardabil, Iran." }, { - "author_name": "Rommie E Amaro", - "author_inst": "University of California, San Diego" + "author_name": "Azar Hadadi", + "author_inst": "15.\tDepartment of Infectious Disease, School of Medicine, Sina Hospital, Tehran University of Medical Sciences, Tehran, Iran." + }, + { + "author_name": "Alireza Abdollahi", + "author_inst": "16.\tDepartment of Pathology, School of Medicine, Tehran University of Medical Sciences, Tehran Iran." + }, + { + "author_name": "Gholam Abbas Kaydani", + "author_inst": "17.\tDepartment of Laboratory Sciences, School of Allied Medical Sciences, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran." + }, + { + "author_name": "Saber Soltani", + "author_inst": "4.\tDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. 5.\tResearch Center for Clinical Virology, Tehran Univer" + }, + { + "author_name": "Talat Mokhtari-Azad", + "author_inst": "4.\tDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran." + }, + { + "author_name": "Reza Najafipour", + "author_inst": "18.\tCell and Molecular Research Center, Qazvin University of Medical Sciences, Qazvin, Iran." + }, + { + "author_name": "Reza Malekzadeh", + "author_inst": "19.\tDigestive Disease Research Institute, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran." + }, + { + "author_name": "Kimia Kahrizi", + "author_inst": "1.\tGenetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran." + }, + { + "author_name": "Seyed Mohammad Jazayeri", + "author_inst": "4.\tDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. 5.\tResearch Center for Clinical Virology, Tehran Univer" + }, + { + "author_name": "Hossein Najmabadi", + "author_inst": "Genetics Research Center, University of Social Welfare & Rehabilitation Sciences" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "biophysics" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.11.18.20225029", @@ -1045364,63 +1045224,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.16.20232686", - "rel_title": "Globally Local: Hyper-local Modeling for Accurate Forecast of COVID-19", + "rel_doi": "10.1101/2020.11.16.20232413", + "rel_title": "Socioeconomic determinants of mobility responses during the first wave of COVID-19 in Italy: from provinces to neighbourhoods", "rel_date": "2020-11-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.16.20232686", - "rel_abs": "Multiple efforts to model the epidemiology of SARS-CoV-2 have recently been launched in support of public health response at the national, state, and county levels. While the pandemic is global, the dynamics of this infectious disease varies with geography, local policies, and local variations in demographics. An underlying assumption of most infectious disease compartment modeling is that of a well mixed population at the resolution of the areas being modeled. The implicit need to model at fine spatial resolution is impeded by the quality of ground truth data for fine scale administrative subdivisions. To understand the trade-offs and benefits of such modeling as a function of scale, we compare the predictive performance of a SARS-CoV-2 modeling at the county, county cluster, and state level for the entire United States. Our results demonstrate that accurate prediction at the county level requires hyper-local modeling with county resolution. State level modeling does not accurately predict community spread in smaller sub-regions because state populations are not well mixed, resulting in large prediction errors. As an important use case, leveraging high resolution modeling with public health data and admissions data from Hillsborough County Florida, we performed weekly forecasts of both hospital admission and ICU bed demand for the county. The repeated forecasts between March and August 2020 were used to develop accurate resource allocation plans for Tampa General Hospital.\n\n2010 MSC92-D30, 91-C20", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.16.20232413", + "rel_abs": "As the second wave of SARS-CoV-2 infections is surging across Europe, it is crucial to identify the drivers of mobility responses to mitigation efforts during different restriction regimes, for planning interventions that are both economically and socially sustainable while effective in controlling the outbreak. Here, using anonymous and privacy enhanced cell phone data from Italy, we investigate the determinants of spatial variations of reductions in mobility and co-location in response to the adoption and the lift of restrictions, considering both provinces and city neighbourhoods. In large urban areas, our analysis uncovers the desertification of historic city centers, which persisted after the end of the lockdown. At the province level, the local structure of the labour market mainly explained the variations in mobility responses, together with other demographic factors, such as populations age and sex composition. In the future, targeted interventions should take into account how the ability to comply with restrictions varies across geographic areas and socio-demographic groups.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Vishrawas Gopalakrishnan", - "author_inst": "IBM Watson Health" - }, - { - "author_name": "Sayali Pethe", - "author_inst": "IBM Watson Health" - }, - { - "author_name": "Sarah Kefayati", - "author_inst": "IBM Watson Health" - }, - { - "author_name": "Raman Srinivasan", - "author_inst": "IBM Watson Health" - }, - { - "author_name": "Paul Hake", - "author_inst": "IBM Watson Health" - }, - { - "author_name": "Ajay Deshpande", - "author_inst": "IBM Watson Health" + "author_name": "Laetitia Gauvin", + "author_inst": "ISI Foundation" }, { - "author_name": "Xuan Liu", - "author_inst": "IBM Watson Health" + "author_name": "Paolo Bajardi", + "author_inst": "ISI Foundation" }, { - "author_name": "Etter Hoang", - "author_inst": "Tampa General Hospital" + "author_name": "Emanuele Pepe", + "author_inst": "ISI Foundation" }, { - "author_name": "Marbelly Davila", - "author_inst": "Tampa General Hospital" + "author_name": "Brennan Lake", + "author_inst": "Cuebiq Inc." }, { - "author_name": "Simone Bianco", - "author_inst": "IBM Almaden Research Center" + "author_name": "Filippo Privitera", + "author_inst": "Cuebiq Inc" }, { - "author_name": "James H Kaufman", - "author_inst": "IBM Almaden Research Center" + "author_name": "Michele Tizzoni", + "author_inst": "ISI Foundation" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.11.16.20232850", @@ -1046802,37 +1046642,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.18.20233122", - "rel_title": "Regular universal screening for SARS-CoV-2 infection may not allow reopening of society after controlling a pandemic wave", + "rel_doi": "10.1101/2020.11.17.20233221", + "rel_title": "Detection of transmission change points during unlock-3 and unlock-4 measures controlling COVID-19 in India", "rel_date": "2020-11-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.18.20233122", - "rel_abs": "BackgroundTo limit societal and economic costs of lockdown measures, public health strategies are needed that control the spread of SARS-CoV-2 and simultaneously allow lifting of disruptive measures. Regular universal random screening of large proportions of the population regardless of symptoms has been proposed as a possible control strategy.\n\nMethodsWe developed a mathematical model that includes test sensitivity depending on infectiousness for PCR-based and antigen-based tests, and different levels of onward transmission for testing and non-testing parts of the population. Only testing individuals participate in high-risk transmission events, allowing more transmission in case of unnoticed infection. We calculated the required testing interval and coverage to bring the effective reproduction number due to universal random testing (Rrt) below 1, for different scenarios of risk behavior of testing and non-testing individuals.\n\nFindingsWith R0 = 2.5, lifting all control measures for tested subjects with negative test results would require 100% of the population being tested every three days with a rapid test method with similar sensitivity as PCR-based tests. With remaining measures in place reflecting Re = 1.3, 80% of the population would need to be tested once a week to bring Rrt below 1. With lower proportions tested and with lower test sensitivity, testing frequency should increase further to bring Rrt below 1. With similar Re values for tested and non-tested subjects, and with tested subjects not allowed to engage in higher risk events, at least 80% of the populations needs to test every five days to bring Rrt below. The impact of the test-sensitivity on the reproduction number is far less than the frequency of testing.\n\nInterpretationRegular universal random screening followed by isolation of infectious individuals is not a viable strategy to reopen society after controlling a pandemic wave of SARS-CoV-2. More targeted screening approaches are needed to better use rapid testing such that it can effectively complement other control measures.\n\nFundingRECOVER (H2020-101003589) (MJMB), ZonMw project 10430022010001 (MK, HH), FCT project 131_596787873 (GR). ZonMw project 91216062 (MK)", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.17.20233221", + "rel_abs": "Documentation in scientific literature is not available on prospective evaluation of the efficiency of the unlock measure related to COVID-19 transmission change points in India, projecting the infected population, planning suitable measures related to future interventions and lifting of restrictions so that the economic settings are not damaged beyond repair. We have applied SIR model and Bayesian approach combined with Monte Carlo Markov algorithms on the Indian COVID-19 daily new infected cases from 1 August 2020 to 30 September 2020. We showed that the COVID-19 epidemic declined after implementing unlock-4 measure and the identified change-points were consistent with the timelines of announced unlock-3 and unlock-4 measure, on 1 August 2020 and 1 September 2020, respectively, effectiveness of which were quantified as the change in both effective transmission rates (100% reduction) and the basic reproduction number attaining 1, implying measures taken to control and mitigate the COVID-19 epidemic in India managed to flatten and recede the epidemic curve.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Martin CJ Bootsma", - "author_inst": "Utrecht University" - }, - { - "author_name": "Mirjam E Kretzschmar", - "author_inst": "University Medical Center Utrecht" - }, - { - "author_name": "Ganna Rozhnova", - "author_inst": "Univeristy Medical Center Utrecht" - }, - { - "author_name": "Hans Heesterbeek", - "author_inst": "Utrecht University" - }, - { - "author_name": "JAN J. A. J. W. kluytmans", - "author_inst": "Amphia Hosptial" + "author_name": "Manisha Mandal", + "author_inst": "Department of Physiology, MGM Medical College, Kishanganj-855107, India" }, { - "author_name": "Marc JM Bonten", - "author_inst": "University Medical Center Utrecht" + "author_name": "Shyamapada Mandal", + "author_inst": "Department of Zoology, University of Gour Banga, Malda-732103, India" } ], "version": "1", @@ -1048332,99 +1048156,79 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.11.18.388819", - "rel_title": "COVID-19-associated olfactory dysfunction reveals SARS-CoV-2 neuroinvasion and persistence in the olfactory system", + "rel_doi": "10.1101/2020.11.18.388710", + "rel_title": "Universally available herbal teas based on sage and perilla elicit potent antiviral activity against SARS-CoV-2 in vitro", "rel_date": "2020-11-18", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.18.388819", - "rel_abs": "While recent investigations have revealed viral, inflammatory and vascular factors involved in SARS-CoV-2 lung pathogenesis, the pathophysiology of neurological disorders in COVID-19 remains poorly understood. Yet, olfactory and taste dysfunction are rather common in COVID-19, especially in pauci-symptomatic patients which constitutes the most frequent clinical manifestation of the infection. We conducted a virologic, molecular, and cellular study of the olfactory system from COVID-19 patients presenting acute loss of smell, and report evidence that the olfactory epithelium represents a highly significant infection site where multiple cell types, including olfactory sensory neurons, support cells and immune cells, are infected. Viral replication in the olfactory epithelium is associated with local inflammation. Furthermore, we show that SARS-CoV-2 induces acute anosmia and ageusia in golden Syrian hamsters, both lasting as long as the virus remains in the olfactory epithelium and the olfactory bulb. Finally, olfactory mucosa sampling in COVID-19 patients presenting with persistent loss of smell reveals the presence of virus transcripts and of SARS-CoV-2-infected cells, together with protracted inflammation. Viral persistence in the olfactory epithelium therefore provides a potential mechanism for prolonged or relapsing symptoms of COVID-19, such as loss of smell, which should be considered for optimal medical management and future therapeutic strategies.", - "rel_num_authors": 20, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.18.388710", + "rel_abs": "The current SARS-CoV-2/COVID-19 pandemic wreaks medical and socioeconomic havoc. Despite the availability of vaccines, cost-effective acute treatment options preventing morbidity and mortality are urgently needed. To identify affordable, ubiquitously available, and effective treatments, we tested herbs consumed worldwide as herbal teas regarding their antiviral activity against SARS-CoV-2. Aqueous infusions prepared by boiling leaves of the Lamiaceae perilla and sage elicit potent and sustained antiviral activity against SARS-CoV-2 in therapeutic as well as prophylactic regimens. The herbal infusions exerted antiviral effects comparable to interferon-{beta} and remdesivir but outperformed convalescent sera and interferon-2 upon short-term treatment early after infection. Based on protein fractionation analyses, we identified caffeic acid, perilla aldehyde, and perillyl alcohol as antiviral compounds. Global mass spectrometry (MS) analyses performed comparatively in two different cell culture infection models revealed changes of the proteome upon treatment with herbal infusions and provided insights into the mode of action. As inferred by the MS data, induction of heme oxygenase 1 (HMOX-1) was confirmed as effector mechanism by the antiviral activity of the HMOX-1-inducing compounds sulforaphane and fraxetin. In conclusion, herbal teas based on perilla and sage exhibit antiviral activity against SARS-CoV-2 including variants of concern such as Alpha, Beta, Delta, and Omicron.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Guilherme Dias De Melo", - "author_inst": "Institut Pasteur, Paris" - }, - { - "author_name": "Francoise Lazarini", - "author_inst": "Institut Pasteur, Paris" - }, - { - "author_name": "Sylvain Levallois", - "author_inst": "Institut Pasteur, Paris" - }, - { - "author_name": "Charlotte Hautefort", - "author_inst": "Hopital Lariboisiere, Paris" + "author_name": "Vu Thuy Khanh Le-Trilling", + "author_inst": "Institute for Virology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany" }, { - "author_name": "Vincent Michel", - "author_inst": "Institut Pasteur, Paris" + "author_name": "Denise Mennerich", + "author_inst": "Institute for Virology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany" }, { - "author_name": "Florence Larrous", - "author_inst": "Institut Pasteur, Paris" + "author_name": "Corinna Schuler", + "author_inst": "Institute for Virology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany" }, { - "author_name": "Benjamin Verillaud", - "author_inst": "Hopital Lariboisiere, Paris" + "author_name": "Roman Sakson", + "author_inst": "Leibniz-Institut fuer Analytische Wissenschaften - ISAS - e.V., Dortmund, Germany" }, { - "author_name": "Caroline Aparicio", - "author_inst": "Hopital Lariboisiere, Paris" + "author_name": "Julia K. Lill", + "author_inst": "Leibniz-Institut fuer Analytische Wissenschaften - ISAS - e.V., Dortmund, Germany" }, { - "author_name": "Sebastien Wagner", - "author_inst": "Institut Pasteur, Paris" + "author_name": "Dominik Kopczynski", + "author_inst": "Leibniz-Institut fuer Analytische Wissenschaften - ISAS - e.V., Dortmund, Germany" }, { - "author_name": "Gilles Gheusi", - "author_inst": "Institut Pasteur, Paris" + "author_name": "Stefan Loroch", + "author_inst": "Leibniz-Institut fuer Analytische Wissenschaften - ISAS - e.V., Dortmund, Germany" }, { - "author_name": "Lauriane Kergoat", - "author_inst": "Institut Pasteur, Paris" - }, - { - "author_name": "Etienne Kornobis", - "author_inst": "Institut Pasteur, Paris" - }, - { - "author_name": "Thomas Cokelaer", - "author_inst": "Institut Pasteur, Paris" + "author_name": "Yulia Flores-Martinez", + "author_inst": "Institute for Virology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany" }, { - "author_name": "Remi Hervochon", - "author_inst": "GHU Pitie-Salpetriere, Paris" + "author_name": "Benjamin Katschinski", + "author_inst": "Institute for Virology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany" }, { - "author_name": "Yoann Madec", - "author_inst": "Institut Pasteur, Paris" + "author_name": "Kerstin Wohlgemuth", + "author_inst": "Institute for Virology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany" }, { - "author_name": "Emmanuel Roze", - "author_inst": "Sorbonne Universite, Paris" + "author_name": "Matthias Gunzer", + "author_inst": "Institute for Experimental Immunology and Imaging, University Hospital Essen, University of Duisburg-Essen, Essen, Germany" }, { - "author_name": "Dominique Salmon", - "author_inst": "Cochin Hotel Dieu Hospital, Paris" + "author_name": "Folker Meyer", + "author_inst": "Institute for AI in Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany" }, { - "author_name": "Herve Bourhy", - "author_inst": "Institut Pasteur, Paris" + "author_name": "Ulf Dittmer", + "author_inst": "Institute for Virology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany" }, { - "author_name": "Marc Lecuit", - "author_inst": "Institut Pasteur, Paris" + "author_name": "Albert Sickmann", + "author_inst": "Leibniz-Institut fuer Analytische Wissenschaften - ISAS - e.V., Dortmund, Germany" }, { - "author_name": "Pierre-Marie Lledo", - "author_inst": "Institut Pasteur, Paris" + "author_name": "Mirko Trilling", + "author_inst": "Institute for Virology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "neuroscience" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.11.16.20231100", @@ -1050498,37 +1050302,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.12.20230615", - "rel_title": "Knowledge and perceptions of COVID-19 among government employees in Ethiopia", + "rel_doi": "10.1101/2020.11.12.20230888", + "rel_title": "Association between climate and new daily diagnoses of COVID-19", "rel_date": "2020-11-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.12.20230615", - "rel_abs": "BackgroundIn the absence of effective treatments or vaccines, the spread of the novel coronavirus disease 2019 (COVID-19) pandemic can be minimized by effectively implementing preventive measures. Knowledge and perceptions of the public about COVID-19 play a critical role in behavioral changes. This study aimed to assess the knowledge and perceptions of COVID-19 as well as source of information about the disease among government employees.\n\nMethodsA cross-sectional survey of 1,573 government employees from 46 public institutions located in Addis Ababa was undertaken from 8th to 19th June 2020. Paper-based self-administered questionnaires were used for data collection. ANOVA test and t-test were used to assess the difference between groups.\n\nResultsThe respondents demonstrated very high knowledge of the cause of COVID-19 (93%), its main clinical symptoms (>90%), the main modes of transmission (89%), the main preventive measures (>90%). Almost all respondents reported that people with recent travel history (86.8%) or people who had contact with COVID-19 patients (93.5%) were the high-risk groups to be infected with coronavirus. In addition, more than half (50.9%) of the study participants reported that people without travel history nor had contact with confirmed cases are also most likely to be infected with the virus. About 84% of the respondents perceived that older adults and elderly were most at risk to die from COVID-19. Similarly, the majority of the respondents reported that adults with other underlying health problems (95.4%), cigarette smokers (88.1%) and substance users (87.5%) were more likely to die from the disease. An electronic media such as television (85.5%), social media (74.1%), online materials (71.1%) and radio (60.8%) constituted the primary sources of information about COVID-19, followed by healthcare workers (66.6%) and print materials (35.4%). Television (32.2%) and health workers (30.5%) constituted the most trusted sources of information related to COVID-19.\n\nConclusionsThis study has showed higher level of knowledge and favorable perception among respondents about COVID-19. Knowledge and perceptions have great roles in behavioral change and efforts should be focused on improving the perceived susceptibility, severity, and benefits of preventive behavioral changes by providing timely and adequate information.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.12.20230888", + "rel_abs": "BackgroundAlthough evidence is accumulating that climate conditions may positively or negatively influence the scale of coronavirus disease 2019 (COVID-19) outbreaks, uncertainty remains concerning the real impact of climate factors on viral transmission. Methods. The number of new daily cases of COVID-19 diagnosed in Verona (Italy) was retrieved from the official website of Veneto Region, while information on daily weather parameters in the same area was downloaded from IlMeteo website, a renowned Italian technological company specialized in weather forecasts. The search period ranged between March 1 to November 11, 2020. The number of new daily COVID-19 cases and meteorological data in Verona were correlated using both univariate and multivariate analysis.\n\nResultsThe number of daily COVID-19 diagnoses in Verona was positively associated with the number of days in lockdown and humidity, and inversely correlated with mean, min and max temperature, mean wind speed and number of days with rainfall. Days of lockdown, mean air temperature, humidity, mean wind speed and number of days with rainfall remained significantly associated in multivariate analysis. The four weather parameters contributed to explaining 61% of variance in new daily COVID-19 diagnoses. Each 1% increase in air temperature, 1% decrease in humidity, 1 km/h increase in wind speed and day with rainfall were independently associated with 1.0%, 0.3%, 1.2% and 5.4% reduction in new COVID-19 daily diagnoses. A significant difference was observed in values of all-weather parameters recorded in Verona between days with <100 or [≥]100 new daily COVID-19diagnoses.\n\nConclusionsClimate conditions may play an essential role in conditions of viral transmission, and influence the likelihood or course of local outbreaks. Preventive measures, testing policies and hospital preparedness should be reinforced during periods of higher meteorological risk and in local environments with adverse climate conditions.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Wakgari Deressa", - "author_inst": "Department of Preventive Medicine, School of Public Health, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia" - }, - { - "author_name": "Alemayehu Worku", - "author_inst": "Department of Preventive Medicine, School of Public Health, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia" - }, - { - "author_name": "Wondwossen Amogne", - "author_inst": "Department of Internal Medicine, School of Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia" + "author_name": "Camilla Mattiuzzi", + "author_inst": "Service of Clinical Governance, Provincial Agency for Social and Sanitary Services, Trento, Italy" }, { - "author_name": "Sefonias Getachew", - "author_inst": "Department of Preventive Medicine, School of Public Health, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia" + "author_name": "Brandon Michael Henry", + "author_inst": "Cardiac Intensive Care Unit, The Heart Institute, Cincinnati Children's Hospital Medical Center, Ohio, USA" }, { - "author_name": "Awgichew Kifle", - "author_inst": "Department of Preventive Medicine, School of Public Health, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia" + "author_name": "Fabian Sanchis-Gomar", + "author_inst": "Department of Physiology, Faculty of Medicine, University of Valencia and INCLIVA Biomedical Research Institute, Valencia, Spain" }, { - "author_name": "Workeabeba Abebe", - "author_inst": "Department of Pediatrics and Child Health, School of Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia" + "author_name": "Giuseppe Lippi", + "author_inst": "Section of Clinical Biochemistry, University of Verona, Verona, Italy" } ], "version": "1", @@ -1052148,35 +1051944,83 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.13.20231480", - "rel_title": "COVID-19 vaccine hesitancy and resistance: Correlates in a nationally representative longitudinal survey of the Australian population", + "rel_doi": "10.1101/2020.11.12.20230565", + "rel_title": "Electrocardiographic Abnormalities and Troponin Elevation in COVID-19", "rel_date": "2020-11-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.13.20231480", - "rel_abs": "BackgroundHigh levels of vaccination coverage in populations will be required even with vaccines that have high levels of effectiveness to prevent and stop outbreaks of coronavirus. The World Health Organisation has suggested that governments take a proactive response to vaccine hesitancy hotspots based on social and behavioural insights.\n\nMethodsRepresentative longitudinal online survey of over 3000 adults from Australia that examines the demographic, attitudinal, political and social attitudes and COVID-19 health behavior correlates of vaccine hesitance and resistance to a COVID-19 vaccine.\n\nResultsOverall, 59% would definitely get the vaccine, 29% had low levels of hesitancy, 7% had high levels of hesitancy and 6% were resistant. Females, those living in disadvantaged areas, those who reported that risks of COVID-19 was overstated, those who had more populist views and higher levels of religiosity were more likely to be hesitant or resistant while those who had higher levels of household income, those who had higher levels of social distancing, who downloaded the COVID-Safe App, who had more confidence in their state or territory government or confidence in their hospitals, or were more supportive of migration were more likely to intend to get vaccinated.\n\nConclusionsOur findings suggest that vaccine hesitancy, which accounts for a significant proportion of the population can be addressed by public health messaging but for a significant minority of the population with strongly held beliefs, alternative policy measures may well be needed to achieve sufficient vaccination coverage to end the pandemic.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.12.20230565", + "rel_abs": "Backgroundthe COVID19 pandemic has resulted in worldwide morbidity at unprecedented scale. Troponin elevation is a frequent laboratory finding in hospitalized patients with the disease, and may reflect direct vascular injury or nonspecific supply-demand imbalance. In this work, we assessed the correlation between different ranges of Troponin elevation, Electrocardiographic (ECG) abnormalities and mortality.\n\nMethodsWe retrospectively studied 204 consecutive patients hospitalized at NYU Langone Health with COVID19. Serial ECG tracings were evaluated in conjunction with laboratory data including Troponin. Mortality was analyzed in respect to the degree of Troponin elevation and the presence of ECG changes including ST elevation, ST depression or T wave inversion.\n\nResultsMortality increased in parallel with increase in Troponin elevation groups and reached 60% when Troponin was >1 ng/ml. In patients with mild Troponin rise (0.05 - 1.00 ng/ml) the presence of ECG abnormality resulted in significantly greater mortality.\n\nConclusionECG repolarization abnormalities may represent a marker of clinical severity in patients with mild elevation in Troponin values. This finding can be used to enhance risk stratification in patients hospitalized with COVID19.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Ben Edwards", - "author_inst": "Australian National University" + "author_name": "Ehud Chorin", + "author_inst": "NYU Langone Health" }, { - "author_name": "Nicholas Biddle", - "author_inst": "Australian National University" + "author_name": "Matthew Dai", + "author_inst": "NYU Langone Health" }, { - "author_name": "Matthew Gray", - "author_inst": "Australian National University" + "author_name": "Edward Kogan", + "author_inst": "NYU Langone Health" }, { - "author_name": "Kate Sollis", - "author_inst": "Australian National University" + "author_name": "Lalit Wadhwani", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "Eric Shulman", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "Charles Nadeau-Routhier", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "Robert Knotts", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "Roi Bar-Cohen", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "Chirag Barbhaiya", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "Anthony Aizer", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "Douglas Holmes", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "Scott Bernstein", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "Michael Spinelli", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "David Park", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "Larry Chinitz", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "Lior Jankelosn", + "author_inst": "NYU Langone Health" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2020.11.13.20231571", @@ -1053962,51 +1053806,151 @@ "category": "ecology" }, { - "rel_doi": "10.1101/2020.11.13.381228", - "rel_title": "Analysis of the Dynamics and Distribution of SARS-CoV-2 Mutations and its Possible Structural and Functional Implications", + "rel_doi": "10.1101/2020.11.12.20229898", + "rel_title": "Low uptake of COVID-19 prevention behaviours and high socioeconomic impact of lockdown measures in South Asia: evidence from a large-scale multi-country surveillance programme", "rel_date": "2020-11-14", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.13.381228", - "rel_abs": "After eight months of the pandemic declaration, COVID-19 has not been globally controlled. Several efforts to control SARS-CoV-2 dissemination are still running including vaccines and drug treatments. The effectiveness of these procedures depends, in part, that the regions to which these treatments are directed do not vary considerably. Although, it is known that the mutation rate of SARS-CoV-2 is relatively low it is necessary to monitor the adaptation and evolution of the virus in the different stages of the pandemic. Thus, identification, analysis of the dynamics, and possible functional and structural implication of mutations are relevant. Here, we first estimate the number of COVID-19 cases with a virus with a specific mutation and then calculate its global relative frequency (NRFp). Using this approach in a dataset of 100 924 genomes from GISAID, we identified 41 mutations to be present in viruses in an estimated number of 750 000 global COVID-19 cases (0.03 NRFp). We classified these mutations into three groups: high-frequent, low-frequent non-synonymous, and low-frequent synonymous. Analysis of the dynamics of these mutations by month and continent showed that high-frequent mutations appeared early in the pandemic, all are present in all continents and some of them are almost fixed in the global population. On the other hand, low-frequent mutations (non-synonymous and synonymous) appear late in the pandemic and seems to be at least partially continent-specific. This could be due to that high-frequent mutation appeared early when lockdown policies had not yet been applied and low-frequent mutations appeared after lockdown policies. Thus, preventing global dissemination of them. Finally, we present a brief structural and functional review of the analyzed ORFs and the possible implications of the 25 identified non-synonymous mutations.", - "rel_num_authors": 8, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.12.20229898", + "rel_abs": "BackgroundSouth Asia has become a major epicentre of the COVID-19 pandemic. Understanding South Asians awareness, attitudes and experiences of early measures for the prevention of COVID-19 is key to improving the effectiveness and mitigating the social and economic impacts of pandemic responses at a critical time for the Region.\n\nMethodsWe assessed the knowledge, behaviours, health and socio-economic circumstances of 29,809 adult men and women, at 93 locations across four South Asian countries. Data were collected during the national lockdowns implemented from March to July 2020, and compared with data collected prior to the pandemic as part of an ongoing prospective surveillance initiative.\n\nResultsParticipants were 61% female, mean age 45.1 years. Almost half had one or more chronic disease, including diabetes (16%), hypertension (23%) or obesity (16%). Knowledge of the primary COVID-19 symptoms and transmission routes was high, but access to hygiene and personal protection resources was low (running water 63%, hand sanitisers 53%, paper tissues 48%). Key preventive measures were not widely adopted. Knowledge, access to, and uptake of COVID-19 prevention measures were low amongst people from disadvantaged socio-economic groups. Fifteen percent of people receiving treatment for chronic diseases reported loss of access to long-term medications; 40% reported symptoms suggestive of anxiety or depression. The prevalence of unemployment rose from 9.3% to 39.4% (P<0.001), and household income fell by 52% (P<0.001) during the lockdown. Younger people and those from less affluent socio-economic groups were most severely impacted. Sedentary time increased by 32% and inadequate fruit and vegetable intake increased by 10% (P<0.001 for both), while tobacco and alcohol consumption dropped by 41% and 80%, respectively (P<0.001), during the lockdown.\n\nConclusionsOur results identified important knowledge, access and uptake barriers to the prevention of COVID-19 in South Asia, and demonstrated major adverse impacts of the pandemic on chronic disease treatment, mental health, health-related behaviours, employment and household finances. We found important sociodemographic differences for impact, suggesting a widening of existing inequalities. Our findings underscore the need for immediate large-scale action to close gaps in knowledge and access to essential resources for prevention, along with measures to safeguard economic production and mitigate socio-economic impacts on the young and the poor.", + "rel_num_authors": 33, "rel_authors": [ { - "author_name": "Santiago Justo Arevalo Mr", - "author_inst": "Universidad de Sao Paulo" + "author_name": "Dian Kusuma", + "author_inst": "Imperial College Business School" + }, + { + "author_name": "Rajendra Pradeepa", + "author_inst": "Madras Diabetes Research Foundation, Chennai, India" }, { - "author_name": "Daniela Zapata Sifuentes Ms", - "author_inst": "Facultad de Ciencias Biologicas, Universidad Ricardo Palma" + "author_name": "Khadija I Khawaja", + "author_inst": "Services Institute of Medical Sciences" }, { - "author_name": "Cesar Huallpa Robles Mr", - "author_inst": "Facultad de Ciencias, Universidad Nacional Agraria La Molina" + "author_name": "Mehedi Hasan", + "author_inst": "BRAC James P Grant School of Public Health, BRAC University" }, { - "author_name": "Gianfranco Landa Bianchi Mr", - "author_inst": "Facultad de Ciencias Biologicas, Universidad Ricardo Palma" + "author_name": "Samreen Siddiqui", + "author_inst": "Max Healthcare" }, { - "author_name": "Adriana Castillo Chavez Ms", - "author_inst": "Facultad de Ciencias Biologicas, Universidad Ricardo Palma" + "author_name": "Sara Mahmood", + "author_inst": "Services Institute of Medical Sciences" }, { - "author_name": "Romina Garavito-Salini Casas Ms", - "author_inst": "Facultad de Ciencias Biologicas, Universidad Ricardo Palma" + "author_name": "Syed Mohsin Ali Shah", + "author_inst": "Punjab Institute of Cardiology" }, { - "author_name": "Roberto Pineda Chavarria Prof.", - "author_inst": "Facultad de Ciencias Biologicas, Universidad Ricardo Palma" + "author_name": "Chamini K De Silva", + "author_inst": "Faculty of Medicine, University of Kelaniya" }, { - "author_name": "Gullermo Uceda-Campos Mr", - "author_inst": "Facultad de Ciencias Biologicas, Universidad Nacional Pedro Ruiz Gallo; Instituto de Quimica, Universidad de Sao Paulo" + "author_name": "Laksara de Silva", + "author_inst": "Faculty of Medicine, University of Colombo" + }, + { + "author_name": "Manoja Gamage", + "author_inst": "Faculty of Medicine, University of Colombo" + }, + { + "author_name": "Menka Loomba", + "author_inst": "Max Healthcare" + }, + { + "author_name": "Vindya P Rajakaruna", + "author_inst": "Faculty of Medicine, University of Kelaniya" + }, + { + "author_name": "Abu AM Hanif", + "author_inst": "BRAC James P Grant School of Public Health, BRAC University" + }, + { + "author_name": "Rajan Babu Kamalesh", + "author_inst": "Madras Diabetes Research Foundation, Chennai, India" + }, + { + "author_name": "Balachandran Kumarendran", + "author_inst": "Faculty of Medicine, University of Jaffna" + }, + { + "author_name": "Marie Loh", + "author_inst": "Imperial College London" + }, + { + "author_name": "Archa Misra", + "author_inst": "Max Healthcare" + }, + { + "author_name": "Asma Tassawar", + "author_inst": "Punjab Institute of Cardiology" + }, + { + "author_name": "Akansha Tyagi", + "author_inst": "Max Healthcare" + }, + { + "author_name": "Swati Waghdhare", + "author_inst": "Max Healthcare" + }, + { + "author_name": "Saira Burney", + "author_inst": "Services Institute of Medical Sciences" + }, + { + "author_name": "Sajjad Ahmad", + "author_inst": "Punjab Institute of Cardiology" + }, + { + "author_name": "Viswanathan Mohan", + "author_inst": "Madras Diabetes Research Foundation, Chennai, India" + }, + { + "author_name": "Malabika Sarker", + "author_inst": "BRAC James P Grant School of Public Health, BRAC University" + }, + { + "author_name": "Ian Y Goon", + "author_inst": "School of Public Health, Imperial College London" + }, + { + "author_name": "Anu Kasturiratne", + "author_inst": "University of Kelaniya Faculty of Medicine" + }, + { + "author_name": "Jaspal S Kooner", + "author_inst": "NHLI, Imperial College London" + }, + { + "author_name": "Prasad Katulanda", + "author_inst": "Faculty of Medicine, University of Colombo" + }, + { + "author_name": "Sujeet Jha", + "author_inst": "Max Healthcare" + }, + { + "author_name": "Ranjit Mohan Anjana", + "author_inst": "Madras Diabetes Research Foundation, Chennai, India" + }, + { + "author_name": "Malay K Mridha", + "author_inst": "BRAC James P Grant School of Public Health, BRAC University" + }, + { + "author_name": "Franco Sassi", + "author_inst": "Imperial College Business School" + }, + { + "author_name": "John Chambers", + "author_inst": "Imperial College London" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "genomics" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2020.11.11.20229815", @@ -1055604,53 +1055548,85 @@ "category": "geriatric medicine" }, { - "rel_doi": "10.1101/2020.11.10.20228890", - "rel_title": "SARS-CoV-2 antibody signatures for predicting the outcome of COVID-19", + "rel_doi": "10.1101/2020.11.10.20228361", + "rel_title": "Metabolomic/lipidomic profiling of COVID-19 and individual response to tocilizumab", "rel_date": "2020-11-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.10.20228890", - "rel_abs": "The COVID-19 global pandemic is far from ending. There is an urgent need to identify applicable biomarkers for early predicting the outcome of COVID-19. Growing evidences have revealed that SARS-CoV-2 specific antibodies evolved with disease progression and severity in COIVD-19 patients. We assumed that antibodies may serve as biomarkers for predicting disease outcome. By taking advantage of a newly developed SARS-CoV-2 proteome microarray, we surveyed IgG responses against 20 proteins of SARS-CoV-2 in 1,034 hospitalized COVID-19 patients on admission and followed till 66 days. The microarray results were further correlated with clinical information, laboratory test results and patient outcomes. Cox proportional hazards model was used to explore the association between SARS-CoV-2 specific antibodies and COVID-19 mortality. We found that nonsurvivors induced higher levels of IgG responses against most of non-structural proteins than survivors on admission. In particular, the magnitude of IgG antibodies against 8 non-structural proteins (NSP1, NSP4, NSP7, NSP8, NSP9, NSP10, RdRp, and NSP14) and 2 accessory proteins (ORF3b and ORF9b) possessed significant predictive power for patient death, even after further adjustments for demographics, comorbidities, and common laboratory biomarkers for disease severity (all with p trend < 0.05). Additionally, IgG responses to all of these 10 non-structural/accessory proteins were also associated with the severity of disease, and differential kinetics and serum positive rate of these IgG responses were confirmed in COVID-19 patients of varying severities within 20 days after symptoms onset. The AUCs for these IgG responses, determined by computational cross-validations, were between 0.62 and 0.71. Our findings have important implications for improving clinical management, and especially for developing medical interventions and vaccines.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.10.20228361", + "rel_abs": "The current pandemic emergence of novel coronavirus disease (COVID-19) poses a relevant threat to global health. SARS-CoV-2 infection is characterized by a wide range of clinical manifestations, ranging from absence of symptoms to severe forms that need intensive care treatment. Here, plasma-EDTA samples of 30 patients compared with age- and sex-matched controls were analyzed via untargeted nuclear magnetic resonance (NMR)-based metabolomics and lipidomics. With the same approach, the effect of tocilizumab administration was evaluated in a subset of patients. Despite the heterogeneity of the clinical symptoms, COVID-19 patients are characterized by common plasma metabolomic and lipidomic signatures (91.7% and 87.5% accuracy, respectively, when compared to controls). Tocilizumab treatment resulted in at least partial reversion of the metabolic alterations due to SARS-CoV-2 infection. In conclusion, NMR-based metabolomic and lipidomic profiling provides novel insights into the pathophysiological mechanism of human response to SARS-CoV-2 infection and to monitor treatment outcomes.\n\nAuthor summaryThe current COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is markedly affecting the world population. Here we report about the small-molecule profile of patients hospitalized during the first wave of the COVID-19 pandemic. Using magnetic resonance spectroscopy, we showed that the infection induces profound changes in the metabolome. The analysis of the specific metabolite changes and correlations with clinical data enabled the identification of potential biochemical determinants of the disease fingerprint. We also followed how metabolic alterations revert towards those of the control group upon treatment with tocilizumab, a recombinant humanised monoclonal antibody against the interleukin-6 receptor. These results open up possibilities for the monitoring of novel patients and their individual response to treatment.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Qing Lei", - "author_inst": "Huazhong University of Science and Technology" + "author_name": "Gaia Meoni", + "author_inst": "University of Florence" }, { - "author_name": "Caizheng Yu", - "author_inst": "Huazhong University of Science and Technology" + "author_name": "Veronica Ghini", + "author_inst": "University of Florence" }, { - "author_name": "Yang Li", - "author_inst": "Shanghai Jiao Tong University" + "author_name": "Laura Maggi", + "author_inst": "University of Florence" }, { - "author_name": "Hongyan Hou", - "author_inst": "Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Alessia Vignoli", + "author_inst": "University of Florence" }, { - "author_name": "Zhaowei Xu", - "author_inst": "Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China" + "author_name": "Alessio Mazzoni", + "author_inst": "University of Florence" }, { - "author_name": "Meian He", - "author_inst": "Huazhong University of Science and Technology" + "author_name": "Lorenzo Salvati", + "author_inst": "University of Florence" }, { - "author_name": "Ziyong Sun", - "author_inst": "Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Manuela Capone", + "author_inst": "University of Florence" }, { - "author_name": "Feng Wang", - "author_inst": "Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Anna Vanni", + "author_inst": "University of Florence" }, { - "author_name": "Sheng-ce Tao", - "author_inst": "Shanghai Jiao Tong University" + "author_name": "Leonardo Tenori", + "author_inst": "University of Florence" }, { - "author_name": "Xionglin Fan", - "author_inst": "Huazhong University of Science and Technology" + "author_name": "Paolo Fontanari", + "author_inst": "Careggi University Hospital" + }, + { + "author_name": "Federico Lavorini", + "author_inst": "University of Florence" + }, + { + "author_name": "Adriano Peris", + "author_inst": "Careggi University Hospital" + }, + { + "author_name": "Alessandro Bartoloni", + "author_inst": "University of Florence" + }, + { + "author_name": "Francesco Liotta", + "author_inst": "University of Florence" + }, + { + "author_name": "Lorenzo Cosmi", + "author_inst": "University of Florence" + }, + { + "author_name": "Claudio Luchinat", + "author_inst": "University of Florence" + }, + { + "author_name": "Francesco Annunziato", + "author_inst": "University of Florence" + }, + { + "author_name": "Paola Turano", + "author_inst": "University of Florence" } ], "version": "1", @@ -1057550,39 +1057526,31 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.11.12.379487", - "rel_title": "Mental Health Status of Adolescents During the COVID-19 Pandemic: A Cross-sectional Survey among the Bangladeshi Graduate Students at Dhaka City", + "rel_doi": "10.1101/2020.11.12.379537", + "rel_title": "A retrospective cluster analysis of COVID-19 cases by county", "rel_date": "2020-11-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.12.379487", - "rel_abs": "ObjectivesTo identify the level of Mental Health Status of Adolescents During the COVID-19 Pandemic among the Bangladeshi Graduate Student at Dhaka\n\nMethodA cross-sectional survey was conducted with 330 students from different public and Private Universities in Dhaka, Bangladesh between April 01, 2020 and July 31, 2020 amid the COVID-19 lockdown period in Bangladesh. A standard, self-administered online questionnaire consisting of questions on socio-demographic variables, mental health status, as well as stress management sent to the respondents through social networking platforms. Data were analyzed using descriptive statistics, t-test, one-way ANOVA and correlation tests.\n\nResultsThe mean score of mental health status was 2.08 based on four points scale. They felt problem in decision making (3.04), in doing the things well (2.92), in enjoying normal day to day life (2.88), in playing a useful part in life (2.85), in doing their task (2.75), living in perfectly well and in good health (2.70). The respondents also developed a suicidal tendency (2.55), felt nervous in strung-up (2.24), took longer time to do things (2.14), felt tightness and pressure in head (2.12), and found themselves pressurized by various stuff (2.05). This study also found a significant positive relationship between mental health status and age, living with parents, and parents attitude. Finally, this study revealed that the respondents managed their stress by chatting with their friends, parents and siblings, and by sleeping.\n\nConclusionMental health status of adolescents was found moderate in this study. This study suggests further large-scale study including different socio-economic settings in order to figure out the real scenario of adolescents mental health status of the country during the pandemic.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.12.379537", + "rel_abs": "The COVID-19 pandemic in the U.S. has exhibited distinct waves, the first beginning in March 2020, the second beginning in early June, and additional waves currently emerging. Paradoxically, almost no county has exhibited this multi-wave pattern. We aim to answer three research questions: (1) How many distinct clusters of counties exhibit similar COVID-19 patterns in the time-series of daily confirmed cases?; (2) What is the geographic distribution of the counties within each cluster? and (3) Are county-level demographic, socioeconomic and political variables associated with the COVID-19 case patterns? We analyzed data from counties in the U.S. from March 1 to October 24, 2020. Time series clustering identified clusters in the daily confirmed cases of COVID-19. An explanatory model was used to identify demographic, socioeconomic and political variables associated the cluster patterns. Four patterns were identified from the timing of the outbreaks including counties experiencing a spring, an early summer, a late summer, and a fall outbreak. Several county-level demographic, socioeconomic, and political variables showed significant associations with the identified clusters. The timing of the outbreak is related both to the geographic location within the U.S. and several variables including age, poverty distribution, and political association. These results show that the reported pattern of cases in the U.S. is observed through aggregation of the COVID-19 cases, suggesting that local trends may be more informative. The timing of the outbreak varies by county, and is associated with important demographic, socioeconomic and geographic factors.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Taha Husain", - "author_inst": "Begum Rokeya University" - }, - { - "author_name": "Saber Ahmed Chowdhury", - "author_inst": "Dhaka University" + "author_name": "Fadel M. Megahed", + "author_inst": "Miami University Farmer School of Business" }, { - "author_name": "Mohammad Main Uddin", - "author_inst": "BUP: Bangladesh University of Professionals" + "author_name": "L. Allison Jones-Farmer", + "author_inst": "Miami University Farmer School of Business" }, { - "author_name": "Nazmul Ahsan Kalimullah", - "author_inst": "Begum Rokeya University" - }, - { - "author_name": "4", - "author_inst": "" + "author_name": "Steven E Rigdon", + "author_inst": "Saint Louis University" } ], "version": "1", "license": "cc_by", "type": "new results", - "category": "scientific communication and education" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.11.08.20227819", @@ -1059500,83 +1059468,31 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2020.11.09.20228791", - "rel_title": "Economic impact of the first wave of the COVID-19 pandemic on acute care hospitals in Japan", + "rel_doi": "10.1101/2020.11.09.20228718", + "rel_title": "Public participation in crisis policymaking. How 30,000 Dutch citizens advised their government on relaxing COVID-19 lockdown measures", "rel_date": "2020-11-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.09.20228791", - "rel_abs": "BackgroundIn response to the coronavirus diseases 2019 (COVID-19) pandemic, the Japanese government declared a state of emergency on April 7, 2020. Six days earlier, the Japan Surgical Society had recommended postponing elective surgical procedures. Along with the growing public fear of COVID-19, hospital visits in Japan decreased.\n\nMethodsUsing claims data from the Quality Indicator/Improvement Project (QIP) database, this study aimed to clarify the impact of the first wave of the pandemic, considered to be from March to May 2020, on case volume and claimed hospital charges in acute care hospitals during this period. To make year-over-year comparisons, we considered cases from July 2018 to June 2020.\n\nResultsA total of 2,739,878 inpatient and 53,479,658 outpatient cases from 195 hospitals were included. In the year-over-year comparisons, total claimed hospital charges decreased in April, May, June 2020 by 7%, 14%, and 5%, respectively, compared to the same months in 2019. Our results also showed that per-case hospital charges increased during this period, possibly to compensate for the reduced case volumes. Regression results indicated that the hospital charges in April and May 2020 decreased by 6.3% for hospitals without COVID-19 patients. For hospitals with COVID-19 patients, there was an additional decrease in proportion with the length of hospital stay of COVID-19 patients including suspected cases. The mean additional decrease per COVID-19 patients was estimated to 5.5 million JPY.\n\nConclusionIt is suggested that the hospitals treating COVID-19 patients were negatively incentivized.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.09.20228718", + "rel_abs": "Following the outbreak of COVID-19, governments took unprecedented measures to curb the spread of the virus. Public participation in decisions regarding (the relaxation of) these measures has been notably absent, despite being recommended in the literature. Here, as one of the exceptions, we report the results of 30,000 citizens advising the government on eight different possibilities for relaxing lockdown measures in the Netherlands. By making use of the novel method Participatory Value Evaluation (PVE), participants were asked to recommend which out of the eight options they prefer to be relaxed. Participants received information regarding the societal impacts of each relaxation option, such as the impact of the option on the healthcare system. The results of the PVE informed policymakers about peoples preferences regarding (the impacts of) the relaxation options. For instance, we established that participants assign an equal value to a reduction of 100 deaths among citizens younger than 70 years and a reduction of 168 deaths among citizens older than 70 years. We show how these preferences can be used to rank options in terms of desirability. Citizens advised to relax lockdown measures, but not to the point at which the healthcare system becomes heavily overloaded. We found wide support for prioritising the re-opening of contact professions. Conversely, participants disfavoured options to relax restrictions for specific groups of citizens as they found it important that decisions lead to \"unity\" and not to \"division\". 80% of the participants state that PVE is a good method to let citizens participate in government decision-making on relaxing lockdown measures. Participants felt that they could express a nuanced opinion, communicate arguments, and appreciated the opportunity to evaluate relaxation options in comparison to each other while being informed about the consequences of each option. This increased their awareness of the dilemmas the government faces.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Jung-ho Shin", - "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" - }, - { - "author_name": "Daisuke Takada", - "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" - }, - { - "author_name": "Tetsuji Morishita", - "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" - }, - { - "author_name": "Hueiru Lin", - "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" - }, - { - "author_name": "Seiko Bun", - "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" - }, - { - "author_name": "Emi Teraoka", - "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" - }, - { - "author_name": "Takuya Okuno", - "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" - }, - { - "author_name": "Hisashi Itoshima", - "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" - }, - { - "author_name": "Hiroyuki Nagano", - "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" - }, - { - "author_name": "Kenji Kishimoto", - "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine" - }, - { - "author_name": "Hiromi Segawa", - "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" - }, - { - "author_name": "Yuka Asami", - "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" - }, - { - "author_name": "Takuya Higuchi", - "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" - }, - { - "author_name": "Kenta Minato", - "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" + "author_name": "Niek Mouter", + "author_inst": "Delft University of Technology" }, { - "author_name": "Susumu Kunisawa", - "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" + "author_name": "Jose Ignacio Hernandez", + "author_inst": "Delft University of Technology" }, { - "author_name": "Yuichi Imanaka", - "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" + "author_name": "Anatol Valerian Itten", + "author_inst": "Delft University of Technology" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "health policy" }, { "rel_doi": "10.1101/2020.11.09.20228684", @@ -1061738,91 +1061654,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.06.20226035", - "rel_title": "Healthcare disparities among anticoagulation therapies for severe COVID-19 patients in the multi-site VIRUS registry", + "rel_doi": "10.1101/2020.11.07.20220392", + "rel_title": "Universal epidemic curve for COVID-19 and its usage for forecasting", "rel_date": "2020-11-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.06.20226035", - "rel_abs": "COVID-19 patients are at an increased risk of thrombosis and various anticoagulants are being used in patient management without an established standard-of-care. Here, we analyze hospitalized and ICU patient outcomes from the Viral Infection and Respiratory illness Universal Study (VIRUS) registry. We find that severe COVID patients administered unfractionated heparin but not enoxaparin have a higher mortality-rate (311 deceased patients out of 760 total patients = 41%) compared to patients administered enoxaparin but not unfractionated heparin (214 deceased patients out of 1,432 total patients = 15%), presenting a risk ratio of 2.74 (95% C.I.: [2.35, 3.18]; p-value: 1.4e-41). This difference persists even after balancing on a number of covariates including: demographics, comorbidities, admission diagnoses, and method of oxygenation, with an amplified mortality rate of 39% (215 of 555) for unfractionated heparin vs. 23% (119 of 522) for enoxaparin, presenting a risk ratio of 1.70 (95% C.I.: [1.40, 2.05]; p-value: 2.5e-7). In these balanced cohorts, a number of complications occurred at an elevated rate for patients administered unfractionated heparin compared to those administered enoxaparin, including acute kidney injury (227 of 642 [35%] vs. 156 of 608 [26%] respectively, adjusted p-value 0.0019), acute cardiac injury (40 of 642 [6.2%] vs. 15 of 608 [2.5%] respectively, adjusted p-value 0.01), septic shock (118 of 642 [18%] vs. 73 of 608 [12%] respectively, adjusted p-value 0.01), and anemia (81 of 642 [13%] vs. 46 of 608 [7.6%] respectively, adjusted p-value 0.02). Furthermore, a higher percentage of Black/African American COVID patients (375 of 1,203 [31%]) were noted to receive unfractionated heparin compared to White/Caucasian COVID patients (595 of 2,488 [24%]), for a risk ratio of 1.3 (95% C.I.: [1.17, 1.45], adjusted p-value: 1.6e-5). After balancing upon available clinical covariates, this difference in anticoagulant use remained statistically significant (272 of 959 [28%] for Black/African American vs. 213 of 959 [22%] for White/Caucasian, adjusted p-value: 0.01, relative risk: 1.28, 95% C.I.: [1.09, 1.49]). While retrospective studies cannot suggest any causality, these findings motivate the need for follow-up prospective research in order to elucidate potential socioeconomic, racial, or other disparities underlying the use of anticoagulants to treat severe COVID patients.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.07.20220392", + "rel_abs": "We construct a universal epidemic curve for COVID-19 using the epidemic curves of eight nations that have reached saturation for the first phase, and then fit an eight-degree polynomial that passes through the universal curve. We take Indias epidemic curve up to September 22, 2020 and overlap it with the universal curve by minimizing square-root error. The constructed curve is used to forecast epidemic evolution up to January 1, 2021. The predictions of our model and those of supermodel for India are reasonably close to each other considering the uncertainties in data fitting.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Christian Kirkup", - "author_inst": "nference" - }, - { - "author_name": "Colin Pawlowski", - "author_inst": "nference" - }, - { - "author_name": "Arjun Puranik", - "author_inst": "nference" - }, - { - "author_name": "Ian Conrad", - "author_inst": "nference" - }, - { - "author_name": "John C O'Horo", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Dina Gomaa", - "author_inst": "University of Cincinnati" - }, - { - "author_name": "Valerie M Banner-Goodspeed", - "author_inst": "Beth Israel Deaconess Medical Center" - }, - { - "author_name": "Jarrod M Mosier", - "author_inst": "Banner University Medical Center" - }, - { - "author_name": "Igor Borisovich Zabolotskikh", - "author_inst": "Kuban State Medical University" - }, - { - "author_name": "Steven K Daugherty", - "author_inst": "Cox Medical Center" - }, - { - "author_name": "Michael A Bernstein", - "author_inst": "Stamford Health" - }, - { - "author_name": "Howard A Zaren", - "author_inst": "St. Joseph's Candler Health System" - }, - { - "author_name": "Vikas Bansal", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Brian Pickering", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Andrew D Badley", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Rahul Kashyap", - "author_inst": "Mayo Clinic" + "author_name": "Aryan Sharma", + "author_inst": "IIT Kanpur, Kanpur, India" }, { - "author_name": "AJ Venkatakrishnan", - "author_inst": "nference" + "author_name": "Srujan Sapkal", + "author_inst": "Defence Institute of Advanced Technology, Pune 411025, India" }, { - "author_name": "Venky Soundararajan", - "author_inst": "nference" + "author_name": "Mahendra K. Verma", + "author_inst": "I. I. T. Kanpur" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.11.07.20227462", @@ -1063312,23 +1063168,111 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.11.10.374777", - "rel_title": "Epidemiological transcriptomic data supports BCG protection in viral diseases including COVID-19", + "rel_doi": "10.1101/2020.11.10.376822", + "rel_title": "Highly potent bispecific sybodies neutralize SARS-CoV-2", "rel_date": "2020-11-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.10.374777", - "rel_abs": "Epidemiological and clinical evidence suggests that Bacille Calmette-Guerin (BCG) vaccine induced trained immunity protects against non-specific infections. Multiple clinical trials are currently underway to assess effectiveness of the vaccine in the coronavirus disease 2019 (COVID-19). However, the durability and mechanism of BCG trained immunity remain unclear. Here, an integrative analysis of available epidemiological transcriptomic data related to BCG vaccination and respiratory tract viral infections, and transcriptomic alterations reported in COVID-19 is presented toward addressing this gap. Results suggest that the vaccine induces very long-lasting transcriptomic changes that, unsurprisingly, mimic viral infections by upregulated antiviral defense response, and, counterintuitively. oppose viral infections by downregulated myeloid cell activation. These durability and mechanistic insights have immediate implications in fight against the COVID-19 pandemic.", - "rel_num_authors": 1, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.10.376822", + "rel_abs": "The ongoing COVID-19 pandemic represents an unprecedented global health crisis. Here, we report the identification of a synthetic nanobody (sybody) pair (Sb#15 and Sb#68) that can bind simultaneously to the SARS-CoV-2 spike-RBD and efficiently neutralize pseudotyped and live-viruses by interfering with ACE2 interaction. Two spatially-discrete epitopes identified by cryo-EM translated into the rational design of bispecific and tri-bispecific fusions constructs, exhibiting up to 100- and 1000-fold increase in neutralization potency. Cryo-EM of the sybody-spike complex further revealed a novel up-out RBD conformation. While resistant viruses emerged rapidly in the presence of single binders, no escape variants were observed in presence of the bispecific sybody. The multivalent bispecific constructs further increased the neutralization potency against globally-circulating SARS- CoV-2 variants of concern. Our study illustrates the power of multivalency and biparatopic nanobody fusions for the development of clinically relevant therapeutic strategies that mitigate the emergence of new SARS-CoV-2 escape mutants.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Abhay Sharma", - "author_inst": "CSIR-Institute of Genomics and Integrative Biology" + "author_name": "Justin D. Walter", + "author_inst": "Institute of Medical Microbiology, University of Zurich" + }, + { + "author_name": "Cedric A.J. Hutter", + "author_inst": "Institute of Medical Microbiology, University of Zurich" + }, + { + "author_name": "Alisa A. Garaeva", + "author_inst": "Department of Membrane Enzymology at the Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen" + }, + { + "author_name": "Melanie Scherer", + "author_inst": "Division of Experimental and Clinical Research, Vetsuisse Faculty, University of Bern" + }, + { + "author_name": "Iwan Zimmermann", + "author_inst": "Institute of Medical Microbiology, University of Zurich and Linkster Therapeutics AG, Zurich" + }, + { + "author_name": "Marianne Wyss", + "author_inst": "Division of Experimental and Clinical Research, Vetsuisse Faculty, University of Bern" + }, + { + "author_name": "Jan Rheinberger", + "author_inst": "Department of Structural Biology at the Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen" + }, + { + "author_name": "Yelena Ruedin", + "author_inst": "Institute of Virology and Immunology, Vetsuisse Faculty, University of Bern and Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty, Universi" + }, + { + "author_name": "Jennifer C. Earp", + "author_inst": "Institute of Medical Microbiology, University of Zurich" + }, + { + "author_name": "Pascal Egloff", + "author_inst": "Institute of Medical Microbiology, University of Zurich and Linkster Therapeutics AG, Zurich" + }, + { + "author_name": "Mich\u00e8le Sorgenfrei", + "author_inst": "Institute of Medical Microbiology, University of Zurich" + }, + { + "author_name": "Lea H\u00fcrlimann", + "author_inst": "Institute of Medical Microbiology, University of Zurich" + }, + { + "author_name": "Imre Gonda", + "author_inst": "Institute of Medical Microbiology, University of Zurich" + }, + { + "author_name": "Gianmarco Meier", + "author_inst": "Institute of Medical Microbiology, University of Zurich" + }, + { + "author_name": "Sille Remm", + "author_inst": "Institute of Medical Microbiology, University of Zurich" + }, + { + "author_name": "Sujani Thavarasah", + "author_inst": "Institute of Medical Microbiology, University of Zurich" + }, + { + "author_name": "Gerrit van Geest", + "author_inst": "Interfaculty Bioinformatics Unit and Swiss Institute of Bioinformatics, University of Bern, Bern, Switzerland" + }, + { + "author_name": "R\u00e9my Bruggman", + "author_inst": "Interfaculty Bioinformatics Unit and Swiss Institute of Bioinformatics, University of Bern, Bern, Switzerland" + }, + { + "author_name": "Gert Zimmer", + "author_inst": "Institute of Virology and Immunology, Vetsuisse Faculty, University of Bern and Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty, Universit" + }, + { + "author_name": "Dirk J Slotboom", + "author_inst": "Department of Membrane Enzymology at the Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen" + }, + { + "author_name": "Cristina Paulino", + "author_inst": "Department of Membrane Enzymology at the Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen and Department of Structural Biol" + }, + { + "author_name": "Philippe Plattet", + "author_inst": "Division of Experimental and Clinical Research, Vetsuisse Faculty, University of Bern" + }, + { + "author_name": "Markus A. Seeger", + "author_inst": "Institute of Medical Microbiology, University of Zurich" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", - "category": "genomics" + "category": "biochemistry" }, { "rel_doi": "10.1101/2020.11.10.376673", @@ -1064973,77 +1064917,45 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.11.06.372037", - "rel_title": "Landscape analysis of escape variants identifies SARS-CoV-2 spike mutations that attenuate monoclonal and serum antibody neutralization", + "rel_doi": "10.1101/2020.11.07.367649", + "rel_title": "in vitro: Natural Compounds (Thymol, Carvacrol, Hesperidine, And Thymoquinone) Against SARS-CoV2 Strain Isolated From Egyptian Patients", "rel_date": "2020-11-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.06.372037", - "rel_abs": "Although neutralizing antibodies against the SARS-CoV-2 spike (S) protein are a goal of COVID-19 vaccines and have received emergency use authorization as therapeutics, viral escape mutants could compromise their efficacy. To define the immune-selected mutational landscape in S protein, we used a VSV-eGFP-SARS-CoV-2-S chimeric virus and 19 neutralizing monoclonal antibodies (mAbs) against the receptor-binding domain (RBD) to generate 50 different escape mutants. The variants were mapped onto the RBD structure and evaluated for cross-resistance to mAbs and convalescent human sera. Each mAb had a unique resistance profile, although many shared residues within an epitope. Some variants (e.g., S477N) were resistant to neutralization by multiple mAbs, whereas others (e.g., E484K) escaped neutralization by convalescent sera, suggesting some humans induce a narrow repertoire of neutralizing antibodies. Comparing the antibody-mediated mutational landscape in S with sequence variation in circulating SARS-CoV-2, we define substitutions that may attenuate neutralizing immune responses in some humans.", - "rel_num_authors": 16, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.07.367649", + "rel_abs": "The current pandemic of the coronavirus disease-2019 (COVID-19) has badly affected our life during the year 2020. SARS-CoV-2 is the primary causative agent of the newly emerged pandemic. Natural flavonoids, Terpenoid and Thymoquinone are tested against different viral and host-cell protein targets. These natural compounds have a good history in treating Hepatitis C Virus (HCV) and Human Immunodeficiency Virus (HIV). Molecular docking combined with cytotoxicity and plaque reduction assay is used to test the natural compounds against different viral (Spike, RdRp, and Mpro) and host-cell (TMPRSS II, keap 1, and ACE2) targets. The results demonstrate the binding possibility of the natural compounds (Thymol, Carvacrol, Hesperidine, and Thymoquinone) to the viral main protease (Mpro). Some of these natural compounds were approved to start clinical trail from Egypt Center for Research and Regenerative Medicine ECRRM IRB (Certificate No.IRB00012517)", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Zhuoming Liu", - "author_inst": "Washington University in Saint Louis" - }, - { - "author_name": "Laura A VanBlargan", - "author_inst": "Washington University in Saint Louis" - }, - { - "author_name": "Louis-Marie Bloyet", - "author_inst": "Washington University in St. Louis" - }, - { - "author_name": "Paul W Rothlauf", - "author_inst": "Harvard Medical School; Washington University in St. Louis" - }, - { - "author_name": "Rita E Chen", - "author_inst": "Washington University in Saint Louis" - }, - { - "author_name": "Spencer Stumpf", - "author_inst": "Washington University in Saint Louis" - }, - { - "author_name": "Haiyan Zhao", - "author_inst": "Washington University in Saint Louis" - }, - { - "author_name": "John M Errico", - "author_inst": "Washington University in Saint Louis" - }, - { - "author_name": "Elitza S Theel", - "author_inst": "Mayo Clinic" + "author_name": "Mohamed Gomaa Seadawy", + "author_inst": "main laboratories, Egypt Army" }, { - "author_name": "Mariel J. Liebeskind", - "author_inst": "Washington University in St. Louis" + "author_name": "Ahmed F Gad", + "author_inst": "Main chemical laboratories, Egypt Army" }, { - "author_name": "Brynn Alford", - "author_inst": "Washington University in St. Louis" + "author_name": "Bassem E Harty", + "author_inst": "Main chemical laboratories, Egypt Army" }, { - "author_name": "William J. Buchser", - "author_inst": "Washington University in St. Louis" + "author_name": "Mostfa Fetooh Mohamed", + "author_inst": "Main chemical laboratories, Egypt Army" }, { - "author_name": "Ali H Ellebedy", - "author_inst": "Washington University in Saint Louis" + "author_name": "Mohamed Shamel ELdesoky", + "author_inst": "Main chemical laboratories, Egypt Army" }, { - "author_name": "Daved H Fremont", - "author_inst": "Washington University in Saint Louis" + "author_name": "Abdo A Elfiky", + "author_inst": "Biophysics Department, Faculty of Science, Cairo University" }, { - "author_name": "Michael S Diamond", - "author_inst": "Washington University in Saint Louis" + "author_name": "Aya Ahmed", + "author_inst": "Molecular Virology and Immunology Unit, Cancer Biology Department, National Cancer Institute, Cairo University, Cairo, Egypt." }, { - "author_name": "Sean P. J. Whelan", - "author_inst": "Washington University in Saint Louis" + "author_name": "Abdel N Zekri", + "author_inst": "National Cancer Institute, Cairo University, Giza," } ], "version": "1", @@ -1066835,27 +1066747,67 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.11.04.20226050", - "rel_title": "Demographic and psychological correlates of SARS-CoV-2 vaccination intentions in a sample of Canadian families", + "rel_doi": "10.1101/2020.11.04.20225797", + "rel_title": "CT-based Rapid Triage of COVID-19 Patients: Risk Prediction and Progression Estimation of ICU Admission, Mechanical Ventilation, and Death of Hospitalized Patients", "rel_date": "2020-11-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.04.20226050", - "rel_abs": "The COVID-19 pandemic has been ongoing for close to a year, with second waves occurring presently and many viewing a vaccine as the most likely way to curb successive waves and promote herd immunity. Reaching herd immunity status likely necessitates that children, as well as their parents, receive a vaccine targeting SARS-CoV-2. In this exploratory study, we investigated the demographic, experiential, and psychological factors associated with the anticipated likelihood and speed of having children receive a SARS-CoV-2 vaccine in a sample of 455 Canadian families (857 children). Using linear mixed effects and proportional odds logistic regression models, we demonstrated that older parental age, living in the Prairies (relative to Central Canada), more complete child and parental vaccination history, more positive attitudes towards vaccines generally, higher psychological avoidance of the pandemic and a greater tendency to prioritize the risks of the disease relative to the risks of side effects (i.e., lower omission bias), were associated with higher likelihoods of intention to vaccinate participants children. In some models, subjective evaluations of proximal COVID-19 risk and higher levels of state anxiety were associated with increased likelihood of having children vaccinated. Faster speed of intended vaccination was predicted by a similar constellation of variables, with higher SES emerging as a trend-level predictor of vaccination speed. Results are discussed with respect to public health knowledge mobilization.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.04.20225797", + "rel_abs": "The wave of COVID-19 continues to overwhelm the medical resources, especially the stressed intensive care unit (ICU) capacity and the shortage of mechanical ventilation (MV). Here we performed CT-based analysis combined with electronic health records and clinical laboratory results on Cohort 1 (n = 1662 from 17 hospitals) with prognostic estimation for the rapid stratification of PCR confirmed COVID-19 patients. These models, validated on Cohort 2 (n = 700) and Cohort 3 (n = 662) constructed from 9 external hospitals, achieved satisfying performance for predicting ICU, MV and death of COVID-19 patients (AUROC 0.916, 0.919 and 0.853), even on events happened two days later after admission (AUROC 0.919, 0.943 and 0.856). Both clinical and image features showed complementary roles in events prediction and provided accurate estimates to the time of progression (p<.001). Our findings are valuable for delivering timely treatment and optimizing the use of medical resources in the pandemic of COVID-19.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Christine L Lackner", - "author_inst": "Mount Saint Vincent University" + "author_name": "Qinmei Xu", + "author_inst": "Nanjing University" + }, + { + "author_name": "Xianghao Zhan", + "author_inst": "Stanford University" + }, + { + "author_name": "Zhen Zhou", + "author_inst": "Deepwise Inc." + }, + { + "author_name": "Yiheng Li", + "author_inst": "Stanford University" + }, + { + "author_name": "Peiyi Xie", + "author_inst": "The Sixth Affiliated Hospital of Sun Yat-sen University" + }, + { + "author_name": "Shu Zhang", + "author_inst": "Deepwise Inc." }, { - "author_name": "Charles H Wang", - "author_inst": "Queen Elizabeth II Health Sciences Center" + "author_name": "Xiuli Li", + "author_inst": "Deepwise Inc." + }, + { + "author_name": "Yizhou Yu", + "author_inst": "Deepwise Inc." + }, + { + "author_name": "Changsheng Zhou", + "author_inst": "Jinling Hospital" + }, + { + "author_name": "Long Jiang Zhang", + "author_inst": "Jinling Hospital, Medical School of Nanjing University" + }, + { + "author_name": "Olivier Gevaert", + "author_inst": "Stanford University" + }, + { + "author_name": "Guangming Lu", + "author_inst": "Nanjing University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "radiology and imaging" }, { "rel_doi": "10.1101/2020.11.05.20226472", @@ -1068753,87 +1068705,55 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.11.06.371971", - "rel_title": "Genomic and phenotypic analysis of COVID-19-associated pulmonary aspergillosis isolates of Aspergillus fumigatus", + "rel_doi": "10.1101/2020.11.06.370999", + "rel_title": "Differing impacts of global and regional responses on SARS-CoV-2 transmission cluster dynamics", "rel_date": "2020-11-06", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.06.371971", - "rel_abs": "The ongoing global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the coronavirus disease 2019 (COVID-19) first described from Wuhan, China. A subset of COVID-19 patients has been reported to have acquired secondary infections by microbial pathogens, such as fungal opportunistic pathogens from the genus Aspergillus. To gain insight into COVID-19 associated pulmonary aspergillosis (CAPA), we analyzed the genomes and characterized the phenotypic profiles of four CAPA isolates of Aspergillus fumigatus obtained from patients treated in the area of North Rhine-Westphalia, Germany. By examining the mutational spectrum of single nucleotide polymorphisms, insertion-deletion polymorphisms, and copy number variants among 206 genes known to modulate A. fumigatus virulence, we found that CAPA isolate genomes do not exhibit major differences from the genome of the Af293 reference strain. By examining virulence in an invertebrate moth model, growth in the presence of osmotic, cell wall, and oxidative stressors, and the minimum inhibitory concentration of antifungal drugs, we found that CAPA isolates were generally, but not always, similar to A. fumigatus reference strains Af293 and CEA17. Notably, CAPA isolate D had more putative loss of function mutations in genes known to increase virulence when deleted (e.g., in the FLEA gene, which encodes a lectin recognized by macrophages). Moreover, CAPA isolate D was significantly more virulent than the other three CAPA isolates and the A. fumigatus reference strains tested. These findings expand our understanding of the genomic and phenotypic characteristics of isolates that cause CAPA.", - "rel_num_authors": 17, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.06.370999", + "rel_abs": "Although the global response to COVID-19 has not been entirely unified, the opportunity arises to assess the impact of regional public health interventions and to classify strategies according to their outcome. Analysis of genetic sequence data gathered over the course of the pandemic allows us to link the dynamics associated with networks of connected individuals with specific interventions. In this study, clusters of transmission were inferred from a phylogenetic tree representing the relationships of patient sequences sampled from December 30, 2019 to April 17, 2020. Metadata comprising sampling time and location were used to define the global behavior of transmission over this earlier sampling period, but also the involvement of individual regions in transmission cluster dynamics. Results demonstrate a positive impact of international travel restrictions and nationwide lockdowns on global cluster dynamics. However, residual, localized clusters displayed a wide range of estimated initial secondary infection rates, for which uniform public health interventions are unlikely to have sustainable effects. Our findings highlight the presence of so-called \"super-spreaders\", with the propensity to infect a larger-than-average number of people, in countries, such as the USA, for which additional mitigation efforts targeting events surrounding this type of spread are urgently needed to curb further dissemination of SARS-CoV-2.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Jacob L. Steenwyk", - "author_inst": "Vanderbilt University" - }, - { - "author_name": "Matthew E Mead", - "author_inst": "Vanderbilt University" - }, - { - "author_name": "Patricia A. Castro", - "author_inst": "University of Sao Paulo, Brazil" - }, - { - "author_name": "Clara Valero", - "author_inst": "University of Sao Paulo, Brazil" - }, - { - "author_name": "Andre Damasio", - "author_inst": "University of Campinas (UNICAMP), Brazil" - }, - { - "author_name": "Renato A. C. Santos", - "author_inst": "University of Sao Paulo, Brazil" - }, - { - "author_name": "Abigail L. LaBella", - "author_inst": "Vanderbilt University" - }, - { - "author_name": "Yuanning Li", - "author_inst": "Vanderbilt University" - }, - { - "author_name": "Sonja L. Knowles", - "author_inst": "University of North Carolina at Greensboro" + "author_name": "Brittany Rife Magalis", + "author_inst": "University of Florida" }, { - "author_name": "Huzefa A. Raja", - "author_inst": "University of North Carolina at Greensboro" + "author_name": "Andrea Ramirez-Mata", + "author_inst": "University of Florida" }, { - "author_name": "Nicholas H. Oberlies", - "author_inst": "University of North Carolina at Greensboro" + "author_name": "Anna Zhukova", + "author_inst": "Institut Pasteur" }, { - "author_name": "Xiaofan Zhou", - "author_inst": "South China Agricultural University" + "author_name": "Carla Mavian", + "author_inst": "University of Florida" }, { - "author_name": "Oliver A. Cornely", - "author_inst": "University of Cologne" + "author_name": "Simone Marini", + "author_inst": "University of Florida" }, { - "author_name": "Frieder Fuchs", - "author_inst": "University of Cologne" + "author_name": "Frederic Lemoine", + "author_inst": "Institut Pasteur" }, { - "author_name": "Philipp Koehler", - "author_inst": "University of Cologne" + "author_name": "Mattia Prosperi", + "author_inst": "University of Florida" }, { - "author_name": "Gustavo Goldman", - "author_inst": "University of Sao Paulo, Brazil" + "author_name": "Olivier Gascuel", + "author_inst": "Institut Pasteur" }, { - "author_name": "Antonis Rokas", - "author_inst": "Vanderbilt University" + "author_name": "Marco Salemi", + "author_inst": "University of Florida" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "new results", - "category": "microbiology" + "category": "genomics" }, { "rel_doi": "10.1101/2020.11.06.370676", @@ -1071302,117 +1071222,61 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.11.04.361576", - "rel_title": "Human Identical Sequences of SARS-CoV-2 Promote Clinical Progression of COVID-19 by Upregulating Hyaluronan via NamiRNA-Enhancer Network", + "rel_doi": "10.1101/2020.11.04.369165", + "rel_title": "Rapid High Throughput Whole Genome Sequencing of SARS-CoV-2 by using One-step RT-PCR Amplification with Integrated Microfluidic System and Next-Gen Sequencing", "rel_date": "2020-11-05", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.04.361576", - "rel_abs": "The COVID-19 pandemic is a widespread and deadly public health crisis. The pathogen SARS-CoV-2 replicates in the lower respiratory tract and causes fatal pneumonia. Although tremendous efforts have been put into investigating the pathogeny of SARS-CoV-2, the underlying mechanism of how SARS-CoV-2 interacts with its host is largely unexplored. Here, by comparing the genomic sequences of SARS-CoV-2 and human, we identified five fully conserved elements in SARS-CoV-2 genome, which were termed as \"human identical sequences (HIS)\". HIS are also recognized in both SARS-CoV and MERS-CoV genome. Meanwhile, HIS-SARS-CoV-2 are highly conserved in the primate. Mechanically, HIS-SARS-CoV-2, behaving as virus-derived miRNAs, directly target to the human genomic loci and further interact with host enhancers to activate the expression of adjacent and distant genes, including cytokines gene and angiotensin converting enzyme II (ACE2), a well-known cell entry receptor of SARS-CoV-2, and hyaluronan synthase 2 (HAS2), which further increases hyaluronan formation. Noteworthily, hyaluronan level in plasma of COVID-19 patients is tightly correlated with severity and high risk for acute respiratory distress syndrome (ARDS) and may act as a predictor for the progression of COVID-19. HIS antagomirs, which downregulate hyaluronan level effectively, and 4-Methylumbelliferone (MU), an inhibitor of hyaluronan synthesis, are potential drugs to relieve the ARDS related ground-glass pattern in lung for COVID-19 treatment. Our results revealed that unprecedented HIS elements of SARS-CoV-2 contribute to the cytokine storm and ARDS in COVID-19 patients. Thus, blocking HIS-involved activating processes or hyaluronan synthesis directly by 4-MU may be effective strategies to alleviate COVID-19 progression.", - "rel_num_authors": 25, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.04.369165", + "rel_abs": "The long-lasting global COVID-19 pandemic demands timely genomic investigation of SARS-CoV-2 viruses. Here we report a simple and efficient workflow for whole genome sequencing utilizing one-step RT-PCR amplification on a microfluidic platform, followed by MiSeq amplicon sequencing. The method uses Fluidigm IFC and instruments to amplify 48 samples with 39 pairs of primers in a single step. Application of this method on RNA samples from both viral isolate and clinical specimens demonstrate robustness and efficiency of this method in obtaining the full genome sequence of SARS-CoV-2.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Wei Li", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" - }, - { - "author_name": "Shuai Yang", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" - }, - { - "author_name": "Peng Xu", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" - }, - { - "author_name": "Dapeng Zhang", - "author_inst": "State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences" - }, - { - "author_name": "Ying Tong", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" - }, - { - "author_name": "Lu Chen", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" - }, - { - "author_name": "Ben Jia", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" - }, - { - "author_name": "Ang Li", - "author_inst": "Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University" - }, - { - "author_name": "Daoping Ru", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" - }, - { - "author_name": "Baolong Zhang", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" - }, - { - "author_name": "Mengxing Liu", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" - }, - { - "author_name": "Cheng Lian", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" - }, - { - "author_name": "Cancan Chen", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" - }, - { - "author_name": "Weihui Fu", - "author_inst": "Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University" - }, - { - "author_name": "Songhua Yuan", - "author_inst": "Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University" + "author_name": "Jun Hang", + "author_inst": "Walter Reed Army Institute of Research" }, { - "author_name": "Xiaoguang Ren", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" + "author_name": "Tao Li", + "author_inst": "Walter Reed Army Institute of Research" }, { - "author_name": "Ying Liang", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" + "author_name": "Hye Kyung Chung", + "author_inst": "Walter Reed Army Institute of Research" }, { - "author_name": "Zhicong Yang", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" + "author_name": "Papa K Pireku", + "author_inst": "Walter Reed Army Institute of Research" }, { - "author_name": "Wenxuan Li", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" + "author_name": "Brett Beitzel", + "author_inst": "US Army Medical Research Institute of Infectious Diseases" }, { - "author_name": "Shaoxuan Wang", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" + "author_name": "Mark A Sanborn", + "author_inst": "Walter Reed Army Institute of Research" }, { - "author_name": "Xiaoyan Zhang", - "author_inst": "Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University" + "author_name": "Cynthia Tang", + "author_inst": "University of Missouri" }, { - "author_name": "Hongzhou Lu", - "author_inst": "Shanghai Public Health Clinical Center, Fudan University" + "author_name": "Richard Hammer", + "author_inst": "University of Missouri" }, { - "author_name": "Jianqing Xu", - "author_inst": "Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University" + "author_name": "Detlef G Ritter", + "author_inst": "University of Missouri Health System" }, { - "author_name": "Hailing Wang", - "author_inst": "State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences" + "author_name": "Xiu-Feng Wan", + "author_inst": "University of Missouri" }, { - "author_name": "Wenqiang Yu", - "author_inst": "Shanghai Public Health Clinical Center and Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute and Laboratory of RNA Epigenetics, Insti" + "author_name": "Irina Maljkovic Berry", + "author_inst": "Walter Reed Army Institute of Research" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "new results", "category": "molecular biology" }, @@ -1072840,51 +1072704,87 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.11.01.20220376", - "rel_title": "Modelling the impact of COVID-19-related control programme interruptions on progress towards the WHO 2030 target for soil-transmitted helminths", + "rel_doi": "10.1101/2020.11.01.20217497", + "rel_title": "CSF of SARS-CoV-2 patients with neurological syndromes reveals hints to understand pathophysiology", "rel_date": "2020-11-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.01.20220376", - "rel_abs": "BackgroundOn the 1st of April 2020, the World Health Organization (WHO) recommended an interruption of all neglected tropical disease control programmes, including soil-transmitted helminths (STH), in response to the COVID-19 pandemic. This paper investigates the impact of this disruption on the achieved progress towards the WHO 2030 target for STH.\n\nMethodsWe used two stochastic individual-based models to simulate the impact of missing one or more preventive chemotherapy (PC) rounds in different endemicity settings. We also investigate the extent to which the impact can be lessened by mitigation strategies, such as semi-annual or community-wide PC.\n\nResultsBoth models show that even without a mitigation strategy, control programmes will catch up by 2030. The catch-up time is limited to a maximum of 4.5 years after the interruption. Mitigations strategies may reduce this catch-up time by up to two years and can even increase the probability of achieving the 2030 target.\n\nConclusionsThough a PC interruption will only temporarily impact the progress towards the WHO 2030 target, programmes are encouraged to restart as soon as possible to minimise the impact on morbidity. The implementation of suitable mitigation strategies can turn the interruption into an opportunity to accelerate the progress toward reaching the target.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.01.20217497", + "rel_abs": "ObjectiveCoronavirus disease (COVID-19) has been associated with a large variety of neurological disorders. However the mechanisms underlying these neurological complications remain elusive. In this study we aimed at determining whether neurological symptoms were caused by SARS-CoV-2 direct infection or by either systemic or local pro-inflammatory mediators.\n\nMethodsWe checked for SARS-CoV-2 RNA by RT-qPCR, SARS-CoV-2-specific antibodies and for 49 cytokines/chemokines/growth factors (by Luminex) in the cerebrospinal fluids (CSF) +/-sera of a cohort of 22 COVID-19 patients with neurological presentation and 55 neurological control patients (inflammatory [IND], non-inflammatory [NIND], multiple sclerosis [MS]).\n\nResultsWe detected SARS-CoV-2 RNA and virus-specific antibodies in the CSF of 0/22 and 10/21 COVID-19 patients, respectively. Of the four categories of tested patients, the CSF of IND exhibited the highest level of cytokines, chemokines and growth factors. In contrast, COVID-19 patients did not present overall upregulation of inflammatory mediators in the CSF. However, the CSF of patients with severe COVID-19 (ICU patients) exhibited higher concentrations of CCL2, CXCL8, and VEGF-A in the CSF than patients with a milder form of COVID-19. In addition, we could show that intrathecal CXCL8 synthesis was linked to an elevated barrier index and correlated to the increase of peripheral inflammation (serum HGF and CXCL10).\n\nConclusionOur results point at an absence of massive SARS-CoV-2 infection or inflammation of the central nervous system, but highlight a specific impairment of the neurovascular unit linked to intrathecal production of CXCL8.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Veronica Malizia", - "author_inst": "Erasmus MC, University Medical Center Rotterdam" + "author_name": "Raphael Bernard-Valnet", + "author_inst": "Centre Hospitalier Universitaire Vaudois" }, { - "author_name": "Federica Giardina", - "author_inst": "Erasmus MC, University Medical Center Rotterdam" + "author_name": "Sylvain Perriot", + "author_inst": "Centre Hospitalier Universitaire Vaudois" }, { - "author_name": "Carolin Vegvari", - "author_inst": "Imperial College London" + "author_name": "Mathieu Canales", + "author_inst": "Centre Hospitalier Universitaire Vaudois" }, { - "author_name": "Sumali Bajaj", - "author_inst": "Imperial College London" + "author_name": "Beatrice Pizzarotti", + "author_inst": "Centre Hospitalier Universitaire Vaudois" }, { - "author_name": "Kevin McRae-McKee", - "author_inst": "Imperial College London" + "author_name": "Leonardo Caranzano", + "author_inst": "Centre Hospitalier Universitaire Vaudois" }, { - "author_name": "Roy M Anderson", - "author_inst": "Imperial College London" + "author_name": "Mayte Castro-Jimenez", + "author_inst": "Centre Hospitalier Universitaire Vaudois" }, { - "author_name": "Sake J De Vlas", - "author_inst": "Erasmus MC, University Medical Center Rotterdam" + "author_name": "Jean-Benoit Epiney", + "author_inst": "Centre Hospitalier Universitaire Vaudois" }, { - "author_name": "Luc E. Coffeng", - "author_inst": "Erasmus MC, University Medical Center Rotterdam" + "author_name": "Sergiu Vijiala", + "author_inst": "Centre Hospitalier Universitaire Vaudois" + }, + { + "author_name": "Paolo Salvioni Chiabotti", + "author_inst": "Centre Hospitalier Universitaire Vaudois" + }, + { + "author_name": "Angelica Anichini", + "author_inst": "Centre Hospitalier Universitaire Vaudois" + }, + { + "author_name": "Alexander Salerno", + "author_inst": "Centre Hospitalier Universitaire Vaudois" + }, + { + "author_name": "Katia Jaton", + "author_inst": "Centre Hospitalier Universitaire Vaudois" + }, + { + "author_name": "Julien Vaucher", + "author_inst": "Centre Hospitalier Universitaire Vaudois" + }, + { + "author_name": "Matthieu Perreau", + "author_inst": "Centre Hospitalier Universitaire Vaudois" + }, + { + "author_name": "Gilbert Greub", + "author_inst": "Centre Hospitalier Universitaire Vaudois" + }, + { + "author_name": "Giuseppe Pantaleo", + "author_inst": "Centre Hospitalier Universitaire Vaudois" + }, + { + "author_name": "Renaud Du Pasquier", + "author_inst": "Centre Hospitalier Universitaire Vaudois" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "neurology" }, { "rel_doi": "10.1101/2020.11.02.20224519", @@ -1074398,127 +1074298,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.02.20224824", - "rel_title": "The duration, dynamics and determinants of SARS-CoV-2 antibody responses in individual healthcare workers", + "rel_doi": "10.1101/2020.11.02.20224774", + "rel_title": "Sharing ventilators in the Covid-19 pandemics. A bench study", "rel_date": "2020-11-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.02.20224824", - "rel_abs": "BackgroundSARS-CoV-2 IgG antibody measurements can be used to estimate the proportion of a population exposed or infected and may be informative about the risk of future infection. Previous estimates of the duration of antibody responses vary.\n\nMethodsWe present 6 months of data from a longitudinal seroprevalence study of 3217 UK healthcare workers (HCWs). Serial measurements of IgG antibodies to SARS-CoV-2 nucleocapsid were obtained. Bayesian mixed linear models were used to investigate antibody waning and associations with age, gender, ethnicity, previous symptoms and PCR results.\n\nResultsIn this cohort of working age HCWs, antibody levels rose to a peak at 24 (95% credibility interval, CrI 19-31) days post-first positive PCR test, before beginning to fall. Considering 452 IgG seropositive HCWs over a median of 121 days (maximum 171 days) from their maximum positive IgG titre, the mean estimated antibody half-life was 85 (95%CrI, 81-90) days. The estimated mean time to loss of a positive antibody result was 137 (95%CrI 127-148) days. We observed variation between individuals; higher maximum observed IgG titres were associated with longer estimated antibody half-lives. Increasing age, Asian ethnicity and prior self-reported symptoms were independently associated with higher maximum antibody levels, and increasing age and a positive PCR test undertaken for symptoms with longer antibody half-lives.\n\nConclusionIgG antibody levels to SARS-CoV-2 nucleocapsid wane within months, and faster in younger adults and those without symptoms. Ongoing longitudinal studies are required to track the long-term duration of antibody levels and their association with immunity to SARS-CoV-2 reinfection.\n\nSummarySerially measured SARS-CoV-2 anti-nucleocapsid IgG titres from 452 seropositive healthcare workers demonstrate levels fall by half in 85 days. From a peak result, detectable antibodies last a mean 137 days. Levels fall faster in younger adults and following asymptomatic infection.", - "rel_num_authors": 27, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.02.20224774", + "rel_abs": "COVID-19 pandemics sets the healthcare system to a shortage of ventilators. We aimed at assessing tidal volume (VT) delivery and air recirculation during expiration when one ventilator is divided into 2 patients. The study was performed in a research laboratory in a medical ICU of a University hospital. An ICU-dedicated (V500) and a lower-level ventilator (Elisee 350) were attached to two test-lungs (QuickLung) through a dedicated flow-splitter. A 50 mL/cmH2O Compliance (C) and 5 cmH2O/L/s Resistance (R) were set in both A and B lungs (step1), C50R20 in A / C20R20 in B (step 2), C20R20 in A / C10R20 in B (step 3), and C50R20 in A / C20R5 in B (step 4). Each ventilator was set in volume and pressure control mode to deliver 0.8L VT. We assessed VT from a pneumotachograph placed immediately before each lung, rebreathed volume, and expiratory resistance (circuit and valve). Values are median (1st-3rd quartiles) and compared between ventilators by non-parametric tests. Between Elisee 350 and V500 in volume control VT in A/B patients were 0.381/0.387 vs. 0.412/0.433L in step 1, 0.501/0.270 vs. 0.492/0.370L in step 2, 0.509/0.237 vs. 0.496/0.332L in step 3, and 0.496/0.281 vs. 0.480/0.329L in step 4. In pressure control the corresponding values were 0.373/0.336 vs. 0.430/0.414L, 0.416/0.185/0.322/0.234L, 0.193/0.108 vs. 0.176/0.092L and 0.422/0.201 vs. 0.481/0.329L, respectively (P<0.001 between ventilators at each step for each volume). Rebreathed air volume ranged between 0.7 to 37.8 ml and negatively correlated with expiratory resistance in steps 2 and 3. The lower-level ventilator performed closely to the ICU-dedicated ventilator. Due to dependence of VT to C pressure control should be used to maintain adequate VT at least in one patient when C and/or R changes abruptly and monitoring of VT should be done carefully. Increasing expiratory resistance should reduce rebreathed volume.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Sheila F Lumley", - "author_inst": "University of Oxford" - }, - { - "author_name": "Jia Wei", - "author_inst": "University of Oxford" - }, - { - "author_name": "Nicole Stoesser", - "author_inst": "University of Oxford" - }, - { - "author_name": "Philippa Matthews", - "author_inst": "University of Oxford" - }, - { - "author_name": "Alison Howarth", - "author_inst": "University of Oxford" - }, - { - "author_name": "Stephanie Hatch", - "author_inst": "University of Oxford" - }, - { - "author_name": "Brian Marsden", - "author_inst": "University of Oxford" - }, - { - "author_name": "Stuart Cox", - "author_inst": "Oxford University Hospitals" - }, - { - "author_name": "Tim James", - "author_inst": "Oxford University Hospitals" - }, - { - "author_name": "Liam Peck", - "author_inst": "University of Oxford" - }, - { - "author_name": "Thomas Ritter", - "author_inst": "University of Oxford" - }, - { - "author_name": "Zoe de Toledo", - "author_inst": "University of Oxford" - }, - { - "author_name": "Richard Cornall", - "author_inst": "University of Oxford" - }, - { - "author_name": "E Yvonne Jones", - "author_inst": "University of Oxford" - }, - { - "author_name": "David I Stuart", - "author_inst": "University of Oxford" - }, - { - "author_name": "Gavin Screaton", - "author_inst": "University of Oxford" - }, - { - "author_name": "Daniel Ebner", - "author_inst": "University of Oxford" - }, - { - "author_name": "Sarah Hoosdally", - "author_inst": "University of Oxford" - }, - { - "author_name": "Derrick Crook", - "author_inst": "University of Oxford" - }, - { - "author_name": "- Oxford University Hospitals Staff Testing Group", - "author_inst": "" - }, - { - "author_name": "Christopher P Conlon", - "author_inst": "University of Oxford" + "author_name": "Claude Guerin", + "author_inst": "Hospices civils de Lyon" }, { - "author_name": "Koen Pouwels", - "author_inst": "University of Oxford" + "author_name": "Martin Cour", + "author_inst": "Hospices civils de Lyon" }, { - "author_name": "Ann Sarah Walker", - "author_inst": "University of Oxford" + "author_name": "Neven Stevic", + "author_inst": "Hospices civils de Lyon" }, { - "author_name": "Tim EA Peto", - "author_inst": "University of Oxford" + "author_name": "Florian Degivry", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Timothy M Walker", - "author_inst": "University of Oxford" + "author_name": "Erwan L'Her", + "author_inst": "CHU DE BREST" }, { - "author_name": "Katie Jeffery", - "author_inst": "Oxford University Hospitals" + "author_name": "Bruno Louis", + "author_inst": "Institut Mondor de Recherches Biomedicales" }, { - "author_name": "David W Eyre", - "author_inst": "University of Oxford" + "author_name": "Laurent Argaud", + "author_inst": "Hospices civils de Lyon" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.11.02.20224642", @@ -1075968,81 +1075788,97 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.28.20219014", - "rel_title": "Residual SARS-CoV-2 viral antigens detected in gastrointestinal and hepatic tissues from two recovered COVID-19 patients", + "rel_doi": "10.1101/2020.10.28.20221853", + "rel_title": "The power and limitations of genomics to track COVID-19 outbreaks: a case study from New Zealand", "rel_date": "2020-11-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.28.20219014", - "rel_abs": "Residual SARS-CoV-2 RNA has been detected in stool samples and gastrointestinal tissues during the convalescence phase of COVID-19 infection. This raises concern for persistence of SARS-CoV-2 virus particles and faecal-oral transmissibility in recovered COVID-19 patients. Using multiplex immunohistochemistry, we unexpectedly detected SARS-CoV-2 viral antigens in intestinal and liver tissues, in surgical samples obtained from two patients who recovered from COVID-19. We further validated the presence of virus by RT-PCR and flow cytometry to detect SARS-CoV-2-specific immunity in the tissues. These findings might have important implications in terms of disease management and public health policy regarding transmission of COVID-19 via faecal-oral and iatrogenic routes during the convalescence phase.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.28.20221853", + "rel_abs": "BackgroundReal-time genomic sequencing has played a major role in tracking the global spread and local transmission of SARS-CoV-2, contributing greatly to disease mitigation strategies. After effectively eliminating the virus, New Zealand experienced a second outbreak of SARS-CoV-2 in August 2020. During this August outbreak, New Zealand utilised genomic sequencing in a primary role to support its track and trace efforts for the first time, leading to a second successful elimination of the virus.\n\nMethodsWe generated the genomes of 80% of the laboratory-confirmed samples of SARS-CoV-2 from New Zealands August 2020 outbreak and compared these genomes to the available global genomic data.\n\nFindingsGenomic sequencing was able to rapidly identify that the new COVID-19 cases in New Zealand belonged to a single cluster and hence resulted from a single introduction. However, successful identification of the origin of this outbreak was impeded by substantial biases and gaps in global sequencing data.\n\nInterpretationAccess to a broader and more heterogenous sample of global genomic data would strengthen efforts to locate the source of any new outbreaks.\n\nFundingThis work was funded by the Ministry of Health of New Zealand, New Zealand Ministry of Business, Innovation and Employment COVID-19 Innovation Acceleration Fund (CIAF-0470), ESR Strategic Innovation Fund and the New Zealand Health Research Council (20/1018 and 20/1041).", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Chun Chau Lawrence Cheung", - "author_inst": "Department of Anatomical Pathology, Singapore General Hospital" + "author_name": "Jemma L Geoghegan", + "author_inst": "University of Otago, Dunedin, New Zealand; Institute of Environmental Science and Research, Wellington, New Zealand." }, { - "author_name": "Denise Goh", - "author_inst": "Institute of Molecular and Cell Biology (IMCB), Agency of Science, Technology and Research (A*STAR)" + "author_name": "Jordan Douglas", + "author_inst": "Centre for Computational Evolution, School of Computer Science, University of Auckland, Auckland, New Zealand" }, { - "author_name": "Xinru Lim", - "author_inst": "Institute of Molecular and Cell Biology (IMCB), Agency of Science, Technology and Research (A*STAR)" + "author_name": "Xiaoyun Ren", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand." }, { - "author_name": "Tracy Zhijun Tien", - "author_inst": "Institute of Molecular and Cell Biology (IMCB), Agency of Science, Technology and Research (A*STAR)" + "author_name": "Matt Storey", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand." }, { - "author_name": "Jeffrey Chun Tatt Lim", - "author_inst": "Institute of Molecular and Cell Biology (IMCB), Agency of Science, Technology and Research (A*STAR)" + "author_name": "James Hadfield", + "author_inst": "Fred Hutchinson Cancer Research Centre, Seattle, Washington, USA." }, { - "author_name": "Sanjna Nilesh Nerurkar", - "author_inst": "Yong Loo Lin School of Medicine, National University of Singapore" + "author_name": "Olin K Silander", + "author_inst": "School of Natural and Computational Sciences, Massey University, Auckland, New Zealand" }, { - "author_name": "Shihleone Loong", - "author_inst": "Department of Anatomical Pathology, Singapore General Hospital" + "author_name": "Nikki E Freed", + "author_inst": "School of Natural and Computational Sciences, Massey University, Auckland, New Zealand." }, { - "author_name": "Peng Chung Cheow", - "author_inst": "Department of Hepatopancreatobiliary and Transplant Surgery, Singapore General Hospital" + "author_name": "Lauren Jelley", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand." }, { - "author_name": "Chung Yip Chan", - "author_inst": "Department of Hepatopancreatobiliary and Transplant Surgery, Singapore General Hospital" + "author_name": "Sarah Jefferies", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand." }, { - "author_name": "Ye Xin Koh", - "author_inst": "Department of Hepatopancreatobiliary and Transplant Surgery, Singapore General Hospital" + "author_name": "Jillian Sherwood", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand." }, { - "author_name": "Thuan Tong Tan", - "author_inst": "Department of Infectious Diseases, Singapore General Hospital" + "author_name": "Shevaun Paine", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand." }, { - "author_name": "Shirin Kalimuddin", - "author_inst": "Department of Infectious Diseases, Singapore General Hospital" + "author_name": "Sue Huang", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand." }, { - "author_name": "Wai Meng David Tai", - "author_inst": "National Cancer Centre Singapore" + "author_name": "Andrew Sporle", + "author_inst": "Department of Statistics, University of Auckland, New Zealand; iNZight Analytics Ltd., Auckland, New Zealand." }, { - "author_name": "Jia Lin Ng", - "author_inst": "Department of Colorectal Surgery, Singapore General Hospital" + "author_name": "Michael G Baker", + "author_inst": "Department of Public Health, University of Otago, Wellington, New Zealand." }, { - "author_name": "Jenny Guek Hong Low", - "author_inst": "Department of Infectious Diseases, Singapore General Hospital" + "author_name": "David R Murdoch", + "author_inst": "Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand." }, { - "author_name": "Joe Yeong", - "author_inst": "Institute of Molecular and Cell Biology (IMCB), Agency of Science, Technology and Research (A*STAR)" + "author_name": "Alexei J Drummond", + "author_inst": "Centre for Computational Evolution, School of Computer Science, University of Auckland, Auckland, New Zealand." }, { - "author_name": "Tony Kiat Hon Lim", - "author_inst": "Department of Anatomical Pathology, Singapore General Hospital" + "author_name": "David Welch", + "author_inst": "Centre for Computational Evolution, School of Computer Science, University of Auckland, Auckland, New Zealand." + }, + { + "author_name": "Colin R Simpson", + "author_inst": "School of Health, Wellington Faculty of Health, Victoria University of Wellington, Wellington, New Zealand." + }, + { + "author_name": "Nigel French", + "author_inst": "School of Veterinary Science, Massey University, Palmerston North, New Zealand." + }, + { + "author_name": "Edward C Holmes", + "author_inst": "Marie Bashir Institute for Infectious Diseases and Biosecurity, School of Life and Environmental Sciences and School of Medical Sciences, The University of Sydn" + }, + { + "author_name": "Joep de Ligt", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand." } ], "version": "1", @@ -1077930,57 +1077766,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.28.20220673", - "rel_title": "SARS-CoV-2 detection by nasal strips: a superior tool for surveillance of pediatric populations.", + "rel_doi": "10.1101/2020.10.29.20220426", + "rel_title": "Occupational risk of COVID-19 in the 1st vs 2nd wave of infection", "rel_date": "2020-11-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.28.20220673", - "rel_abs": "BackgroundDeep throat saliva (DTS) and pooled nasopharyngeal swab and throat swab (NPSTS) are utilized for viral detection. DTS is challenging for children. Swabbing the respiratory mucosa requires trained personnel and may trigger sneezing and coughing, which generate droplets. A reliable, simple and safe sampling method applicable to a wide age range is required for community-based surveillance.\n\nMethodsWe introduced nasal strip as an easy and low-risk collection method. Asymptomatic and symptomatic SARS-CoV-2 infected patients (n = 38) were recruited. Nasal epithelial lining fluid (NELF) (n = 43) strip paired with nasal swab (n = 13) were collected by a healthcare worker to compare with NPSTS (n = 21) or DTS (n =22) collected within 24 hours as reference. All samples were subjected to viral RNA quantitation by real-time PCR targeting the nucleoprotein gene.\n\nResultsComparable Ct values were observed between paired nasal strip and nasal swab samples. The agreement between nasal strip samples and NPSTS was 94.44% and 100% for NPSTS positive and negative samples. Higher viral RNA concentration was detected in nasal strips than DTS samples. False-negative results were recorded in six DTS specimens, of which four were from children. Storage at room temperature up to 72 (n = 3) hours did not affect diagnostic yield of nasal strips.\n\nConclusionsNasal strip is a reliable and non-invasive sampling method for SARS-CoV-2 detection, and viral detection remains stable for at least 72 hours. It can be used as an alternative tool for community-based surveillance.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.29.20220426", + "rel_abs": "AimTo study whether employees in occupations that typically imply close contact with other people are tested more and at higher risk of confirmed SARS-CoV-2 infection (COVID-19) and related hospitalization, in the 1st and 2nd wave of infection in Norway.\n\nMethodsIn all 3 559 694 residents of Norway on January 1st 2020 aged 20-70 (with mean [SD] age 44.1 [14.3] years and 51% men), we studied COVID-19 testing patterns sorted by occupation (using Standard Classification of Occupations [ISCO-08]). We also studied whether selected occupations had a higher risk of 1) confirmed COVID-19 and 2) hospitalization with COVID-19, compared to everyone else aged 20-70 years using logistic regression adjusted for age, sex, testing behavior, and own and maternal country of birth.\n\nResultsOccupations with high frequency of testing (e.g. health personnel and teachers) had a low frequency of positive tests. Nurses, physicians, dentists, physiotherapists, bus/tram and taxi drivers had 1.1-4 times the odds of COVID-19 during the 1st wave, whereas bartenders, waiters, transport conductors and travel stewards had 1.1-3 times the odds of COVID-19 during the 2nd wave (when compared to everyone else). Teachers had moderately increased odds of COVID-19. Occupation may be of limited relevance for hospitalization with the disease.\n\nConclusionStudying the entire Norwegian population using international standardized codes of occupations, our findings may be of relevance to national and regional authorities in handling the pandemic. Also, our findings provide a knowledge foundation for the more targeted future studies of lockdown, testing strategies and disease control measures.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Renee WY Chan", - "author_inst": "The Chinese University of Hong Kong" - }, - { - "author_name": "Kate CC Chan", - "author_inst": "The Chinese University of Hong Kong" - }, - { - "author_name": "Kathy Yuen Yee Chan", - "author_inst": "The Chinese University of Hong Kong" - }, - { - "author_name": "Grace Chung Yan Lui", - "author_inst": "The Chinese University of Hong Kong" - }, - { - "author_name": "Joseph GS Tsun", - "author_inst": "The Chinese University of Hong Kong" - }, - { - "author_name": "Rity YK Wong", - "author_inst": "The Chinese University of Hong Kong" - }, - { - "author_name": "Michelle WL Yu", - "author_inst": "The Prince of Wales Hospital, Hong Kong" + "author_name": "Karin Magnusson", + "author_inst": "Norwegian Institute of Public Health" }, { - "author_name": "Maggie Wang", - "author_inst": "The Chinese University of Hong Kong" + "author_name": "Karin Maria Nygard", + "author_inst": "Norwegian Institute of Public Health" }, { - "author_name": "Paul KS Chan", - "author_inst": "The Chinese University of Hong Kong" + "author_name": "Fredrik Methi", + "author_inst": "Norwegian Institute of Public Health" }, { - "author_name": "Hugh Simon Lam", - "author_inst": "The Chinese University of Hong Kong" + "author_name": "Line Vold", + "author_inst": "Norwegian Institute of Public Health" }, { - "author_name": "Albert M Li", - "author_inst": "The Chinese University of Hong Kong" + "author_name": "Kjetil Elias Telle", + "author_inst": "Norwegian Institute of Public Health" } ], "version": "1", @@ -1079683,35 +1079495,35 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.11.02.365551", - "rel_title": "COVID-19 risk haplogroups differ between populations, deviate from Neanderthal haplotypes and compromise risk assessment in non-Europeans", + "rel_doi": "10.1101/2020.10.27.20219717", + "rel_title": "COVID-19 Mortality Following Mass Gatherings", "rel_date": "2020-11-03", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.02.365551", - "rel_abs": "Recent genome wide association studies (GWAS) have identified genetic risk factors for developing severe COVID-19 symptoms. The first published study reported a 1bp insertion rs11385942 on chromosome 3 (1) and subsequent studies single nucleotide variants (SNVs) such as rs35044562, rs67959919 (2) and rs13078854 (3), all highly correlated with each other. Zeberg and Paabo (4) subsequently traced them back to Neanderthal origin. They found that a 49.4 kb genomic region including the risk allele of rs35044562 is inherited from Neanderthals of Vindija in Croatia. Here we add a differently focused evaluation of this major genetic risk factor to these recent analyses. We show that (i) COVID-19-related genetic factors of three previously assessed Neanderthals deviate from those of modern humans and that (ii) they differ among world-wide human populations, which compromises risk prediction in non-Europeans. Currently, caution is thus advised in the genetic risk assessment of non-Europeans during this world-wide COVID-19 pandemic.", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.27.20219717", + "rel_abs": "We examined Coronavirus Disease-2019 (COVID-19) mortality following 5 mass gatherings at outdoor rallies in the United States, during August 2020. We found that COVID-19 mortality started increasing 19-24 days after the mass gathering. In a 50-mile radius there was a 2.1-fold increase in COVID-19 mortality, and in a 51-100 miles radius there was a 1.4-fold increase. Our results suggest that precautions should be taken in mass gatherings and in at least a 50-mile radius, in order to limit COVID-19 mortality.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Inken Wohlers", - "author_inst": "University of L\u00fcbeck" + "author_name": "Oren Miron", + "author_inst": "Ben Gurion University" }, { - "author_name": "Ver\u00f3nica Calonga-Sol\u00eds", - "author_inst": "University of L\u00fcbeck" + "author_name": "Kun-Hsing Yu", + "author_inst": "Harvard Medical School" }, { - "author_name": "Jan-Niklas Jobst", - "author_inst": "University of L\u00fcbeck" + "author_name": "Rachel Wilf-Miron", + "author_inst": "Tel Aviv University" }, { - "author_name": "Hauke Busch", - "author_inst": "University of L\u00fcbeck" + "author_name": "Nadav Davidovitch", + "author_inst": "Ben Gurion University" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "genetics" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.10.27.20220707", @@ -1081493,49 +1081305,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.27.20220905", - "rel_title": "Longitudinal monitoring of SARS-CoV-2 RNA on high-touch surfaces in a community setting", + "rel_doi": "10.1101/2020.10.28.20221127", + "rel_title": "Features of \u03b1-Hydroxybutyrate Dehydrogenase during various specific periods in COVID-19 patients within Xiangyang, China: a cohort study", "rel_date": "2020-11-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.27.20220905", - "rel_abs": "Environmental surveillance of surface contamination is an unexplored tool for understanding transmission of SARS-CoV-2 in community settings. We conducted longitudinal swab sampling of high-touch non-porous surfaces in a Massachusetts town during a COVID-19 outbreak from April to June 2020. Twenty-nine of 348 (8.3 %) surface samples were positive for SARS-CoV-2, including crosswalk buttons, trash can handles, and door handles of essential business entrances (grocery store, liquor store, bank, and gas station). The estimated risk of infection from touching a contaminated surface was low (less than 5 in 10,000), suggesting fomites play a minimal role in SARS-CoV-2 community transmission. The weekly percentage of positive samples (out of n=33 unique surfaces per week) best predicted variation in city-level COVID-19 cases using a 7-day lead time. Environmental surveillance of SARS-CoV-2 RNA on high-touch surfaces could be a useful tool to provide early warning of COVID-19 case trends.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.28.20221127", + "rel_abs": "BackgroundCoronavirus disease-2019 (COVID-19) has spread all over the world and brought extremely huge losses. There is no study to systematically analyse the features of hydroxybutyrate dehydrogenase (-HBDH) in COVID-19 patients during the periods before and after illness progression, before death and course from exposure onset.\n\nMethodsWe collected all included patients general information, clinical type, -HBDH value and outcome, and analyzed -HBDH values within different initial time and different periods.\n\nResultsIn the first 30 days after symptom onset, the -HBDH median value was 156.33 U/L. The first test of -HBDH since exposure onset appeared on the 8th day, it increased from the 8th day to 18th day and decreased after the 18th day. -HBDH median value showed a slight change until it started to increase 1 day before transforming to severe type, while it continued to increase during 4 days before and after transforming to critical type. The -HBDH median value ranged from 191.11 U/L to 455.11U/L before death.\n\nConclusions-HBDH value increases in some COVID-19 patients, obviously in severe type, critical type and death patients, and mainly in 18 days after exposure onset and 10 days after symptom onset. -HBDH increases 1 day before transforming to severe type, continues to increase in critical type and death patients, increases rapidly 5 days before death. The increase of -HBDH suggests that COVID-19 patients have tissues and organs damage, mainly in heart. In brief, -HBDH is an important indicator to judge the severity and prognosis of COVID-19.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Abigail P. Harvey", - "author_inst": "Tufts University" - }, - { - "author_name": "Erica R. Fuhrmeister", - "author_inst": "Tufts University" + "author_name": "Haoming Zhu", + "author_inst": "Center of Evidence-Based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang, 441000, China" }, { - "author_name": "Molly Cantrell", - "author_inst": "Tufts University" + "author_name": "Gaojing Qu", + "author_inst": "Center of Evidence-Based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang, 441000, China" }, { - "author_name": "Ana K. Pitol", - "author_inst": "Imperial College London" + "author_name": "Hui Yu", + "author_inst": "Center of Evidence-Based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang, 441000, China" }, { - "author_name": "Jenna M. Swarthout", - "author_inst": "Tufts University" + "author_name": "Guoxin Huang", + "author_inst": "Center of Evidence-Based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang, 441000, China" }, { - "author_name": "Julie E. Powers", - "author_inst": "Tufts University" + "author_name": "Lei Chen", + "author_inst": "Center of Evidence-Based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang, 441000, China" }, { - "author_name": "Maya L. Nadimpalli", - "author_inst": "Tufts University" + "author_name": "Meiling Zhang", + "author_inst": "Center of Evidence-Based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang, 441000, China" }, { - "author_name": "Timothy R. Julian", - "author_inst": "Eawag" + "author_name": "Shanshan Wan", + "author_inst": "Postgraduate Training Basement of Jinzhou Medical University, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang, 441000, China" }, { - "author_name": "Amy J. Pickering", - "author_inst": "University of California, Berkeley" + "author_name": "Bin Pei", + "author_inst": "Center of Evidence-Based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang, 441000, China" } ], "version": "1", @@ -1083099,25 +1082907,57 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.28.20191981", - "rel_title": "Retrospective assessment of SARS-COV2 virus circulation during lockdown in two hospital childcare centers hosting healthcare workers children in a French area of high transmission.", + "rel_doi": "10.1101/2020.10.28.20221580", + "rel_title": "The Risk of Indoor Sports and Culture Events for the Transmission of COVID-19 (Restart-19)", "rel_date": "2020-10-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.28.20191981", - "rel_abs": "BackgroundEvidence as to whether childcare and school closure limits the spread of SARS-CoV-2 virus is limited, especially because the role of children in SARS-CoV2 transmission remains unclear.\n\nMethodsBetween May 29 and July 2, 2020, a retrospective cohort study was conducted among two populations: requisitioned health-care workers and requisitioned staff from hospitals childcare centers, to investigate the virus circulation during lockdown, in a French area of high transmission.\n\nResultsThe infection attack rate was 6/52 (11.6%) and 8/46 (17.4%) among health-care workers and childcare staff, respectively. An early epidemic occurred among Montreuil s hospital childcare staff, but the parents were not affected (p=0.029). Among Aulnay-sous-bois childcare center, three staff members were infected but none of them was in charge of a child whose parents were infected. Also among the parents of the children they cared for, none developed antibodies. Out of 14 infections, 12 were reliable to a source of transmission, mostly among colleagues.\n\nDiscussion-conclusionThe assessment of viral circulation among healthcare workers and childcare staff suggests that the children did not contribute to SARS-CoV-2 spread in our setting.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.28.20221580", + "rel_abs": "Nearly all mass gathering events (MGEs) worldwide have been banned since the outbreak of SARS-CoV-2 as they are supposed to pose a considerable risk for transmission of COVID-19. We investigated transmission risk of SARS-CoV-2 by droplets and aerosols during an experimental indoor MGE (using N95 masks and contact tracing devices) and conducted a simulation study to estimate the resulting burden of disease under conditions of controlled epidemics. The number of exposed contacts was <10 for scenarios with hygiene concept and good ventilation, but substantially higher otherwise. Of subsequent cases, 0%-23% were attributable to MGEs. Overall, the expected additional effect of indoor MGEs on burden of infections is low if hygiene concepts are applied and adequate ventilation exists.\n\nOne Sentence SummarySeated indoor events, when conducted under hygiene precautions and with adequate ventilation, have small effects on the spread of COVID-19.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Pauline Penot", - "author_inst": "Centre hospitalier intercommunal Andre Gregoire" + "author_name": "Stefan Moritz", + "author_inst": "University Hospital Halle (Saale)" + }, + { + "author_name": "Cornelia Gottschick", + "author_inst": "Martin-Luther-University Halle-Wittenberg" + }, + { + "author_name": "Johannes Horn", + "author_inst": "Martin-Luther-University Halle-Wittenberg" + }, + { + "author_name": "Mario Popp", + "author_inst": "University Hospital Halle (Saale)" }, { - "author_name": "Anne Delaval", - "author_inst": "hopital intercommunal Robert Ballanger" + "author_name": "Susan Langer", + "author_inst": "Martin-Luther-University Halle-Wittenberg" + }, + { + "author_name": "Bianca Klee", + "author_inst": "Martin-Luther-University Halle-Wittenberg" + }, + { + "author_name": "Oliver Purschke", + "author_inst": "Martin-Luther-University Halle-Wittenberg" + }, + { + "author_name": "Michael Gekle", + "author_inst": "Martin-Luther-University Halle-Wittenberg" + }, + { + "author_name": "Angelika Ihling", + "author_inst": "University Hospital Halle (Saale)" + }, + { + "author_name": "Rafael Mikolajczyk", + "author_inst": "Martin-Luther-University Halle-Wittenberg" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1085941,51 +1085781,95 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.10.28.357137", - "rel_title": "Extracellular vesicle-based vaccine platform displaying native viral envelope proteins elicits a robust anti-SARS-CoV-2 response in mice.", + "rel_doi": "10.1101/2020.10.27.358259", + "rel_title": "SARS-CoV-2 desensitizes host cells to interferon through inhibition of the JAK-STAT pathway", "rel_date": "2020-10-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.28.357137", - "rel_abs": "Extracellular vesicles (EVs) emerge as essential mediators of intercellular communication. DNA vaccines encoding antigens presented on EVs efficiently induce T-cell responses and EV-based vaccines containing the Spike (S) proteins of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) are highly immunogenic in mice. Thus, EVs may serve as vaccine platforms against emerging diseases, going beyond traditional strategies, with the antigen displayed identically to the original protein embedded in the viral membrane and presented as such to the immune system. Compared to their viral and pseudotyped counterparts, EV-based vaccines overcome many safety issues including pre-existing immunity against these vectors. Here, we applied our technology in natural EVs engineering, to express the S proteins of SARS-CoV-2 embedded in the EVs, which mimic the virus with its fully native spikes. Immunizations with a two component CoVEVax vaccine, comprising DNA vector (DNAS-EV) primes, allowing in situ production of Spike harbouring EVs, and a boost using S-EVs produced in mammalian cells, trigger potent neutralizing and cellular responses in mice, in the absence of any adjuvants. CoVEVax would be the prototype of vaccines, where the sole exchange of the envelope proteins on EVs leads to the generation of new vaccine candidates against emerging viruses.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.27.358259", + "rel_abs": "SARS-CoV-2 can infect multiple organs, including lung, intestine, kidney, heart, liver, and brain. The molecular details of how the virus navigates through diverse cellular environments and establishes replication are poorly defined. Here, we performed global proteomic analysis of the virus-host interface in a newly established panel of phenotypically diverse, SARS-CoV-2-infectable human cell lines representing different body organs. This revealed universal inhibition of interferon signaling across cell types following SARS-CoV-2 infection. We performed systematic analyses of the JAK-STAT pathway in a broad range of cellular systems, including immortalized cell lines and primary-like cardiomyocytes, and found that several pathway components were targeted by SARS-CoV-2 leading to cellular desensitization to interferon. These findings indicate that the suppression of interferon signaling is a mechanism widely used by SARS-CoV-2 in diverse tissues to evade antiviral innate immunity, and that targeting the viral mediators of immune evasion may help block virus replication in patients with COVID-19.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Katarzyna Polak", - "author_inst": "Ciloa SAS, Montpellier, France" + "author_name": "Da-Yuan Chen", + "author_inst": "Boston University" + }, + { + "author_name": "Nazimuddin Khan", + "author_inst": "Boston University" + }, + { + "author_name": "Brianna J. Close", + "author_inst": "Boston University" + }, + { + "author_name": "Raghuveera K. Goel", + "author_inst": "Boston University" }, { - "author_name": "No\u00e9mie Greze", - "author_inst": "Ciloa SAS, Montpellier, France" + "author_name": "Benjamin Blum", + "author_inst": "Boston University" }, { - "author_name": "Ma\u00eblle Lachat", - "author_inst": "Ciloa SAS, Montpellier, France" + "author_name": "Alexander H. Tavares", + "author_inst": "Boston University" }, { - "author_name": "Delphine Merle", - "author_inst": "Ciloa SAS, Montpellier, France" + "author_name": "Devin Kenney", + "author_inst": "Boston University" }, { - "author_name": "Steve Chiumento", - "author_inst": "Ciloa SAS, Montpellier, France" + "author_name": "Hasahn L. Conway", + "author_inst": "Boston University" }, { - "author_name": "Christelle Bertrand-Gaday", - "author_inst": "DMEM, Univ Montpellier, INRAE, Montpellier, France" + "author_name": "Jourdan K. Ewoldt", + "author_inst": "Boston University" }, { - "author_name": "Bernadette Trentin", - "author_inst": "Ciloa SAS, Montpellier, France" + "author_name": "Sebastian Kapell", + "author_inst": "Boston University" }, { - "author_name": "Robert Z. Mamoun", - "author_inst": "Ciloa SAS, Montpellier, France" + "author_name": "Vipul C. Chitalia", + "author_inst": "Boston University" + }, + { + "author_name": "Nicholas A. Crossland", + "author_inst": "Boston University" + }, + { + "author_name": "Christopher S. Chen", + "author_inst": "Boston University" + }, + { + "author_name": "Darrell N. Kotton", + "author_inst": "Boston University" + }, + { + "author_name": "Susan C. Baker", + "author_inst": "Loyola University" + }, + { + "author_name": "John H. Connor", + "author_inst": "Boston University" + }, + { + "author_name": "Florian Douam", + "author_inst": "Boston University" + }, + { + "author_name": "Andrew Emili", + "author_inst": "Boston University" + }, + { + "author_name": "Mohsan Saeed", + "author_inst": "Boston University School of Medicine" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.10.28.355305", @@ -1087503,77 +1087387,29 @@ "category": "medical education" }, { - "rel_doi": "10.1101/2020.10.23.20218172", - "rel_title": "Dexamethasone use and Mortality in Hospitalized Patients with Coronavirus Disease 2019: a Multicenter Retrospective Observational Study", + "rel_doi": "10.1101/2020.10.23.20218099", + "rel_title": "Quantification of a Viromed Klinik Akut V 500 disinfection device to reduce the indirect risk of SARS-CoV-2 infection by aerosol particles", "rel_date": "2020-10-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.23.20218172", - "rel_abs": "ObjectiveTo examine the association between dexamethasone use and mortality among hospitalized patients for COVID-19.\n\nDesignMulticenter observational retrospective cohort study.\n\nSettingGreater Paris University hospitals, France.\n\nParticipants12,217 adults hospitalized with COVID-19 between 24 January and 20 May 2020, including 171 patients (1.4%) who received dexamethasone orally or by intravenous perfusion during the visit.\n\nData sourceAssistance Publique-Hopitaux de Paris Health Data Warehouse.\n\nMain outcome measuresThe primary endpoint was time to death. We compared this endpoint between patients who received dexamethasone and those who did not in time-to-event analyses adjusting for sex, age, obesity, current smoking status, any medical condition associated with increased COVID-19-related mortality, and clinical and biological severity of COVID-19 at admission, while stratifying by the need of respiratory support (i.e., oxygen or intubation). The primary analysis was a multivariable Cox model and the secondary analysis used a univariate Cox regression in a matched analytic sample.\n\nResultsAmong patients who required respiratory support, the end-point event of death occurred in 10 patients (15.9%) who received dexamethasone and 298 patients (26.4%) who did not. In this group of patients, there was a significant association between dexamethasone use and reduced mortality in both the crude, unadjusted analysis (hazard ratio (HR), 0.40; 95% CI, 0.18 to 0.87, p=0.021) and the adjusted multivariable analysis (HR, 0.46; 95% CI, 0.22 to 0.96, p=0.039). In the sensitivity analysis, the univariate Cox regression model in the matched analytic sample yielded a same tendency, albeit non-significant (HR, 0.31; 95% CI, 0.08 to 1.14, p=0.077). Among patients without respiratory support, the end-point event of death occurred in 14 patients (13.0%) who received dexamethasone and 1,086 patients (10.0%) who did not. In this group of patients, there was no significant association between dexamethasone use and the endpoint. When examining the association between the cumulative dose of dexamethasone received during the visit and the endpoint, we found that the administration of a cumulative dose between 60 mg to 150 mg among patients who required respiratory support was significantly associated with a lower risk of death in the crude, unadjusted analysis (HR, 0.28; SE, 0.58, p=0.028), the adjusted multivariable analysis (HR, 0.24; SE, 0.65, p=0.030), and in the univariate Cox regression model in the matched analytic sample (HR, 0.32; SE, 0.58, p=0.048), whereas no significant association was observed with a different dose. Among patients without respiratory support, there was no significant association between the cumulative dose of dexamethasone and the endpoint in the crude and in the adjusted multivariable analyses.\n\nConclusionsIn this observational study involving patients with Covid-19 who had been admitted to the hospital, dexamethasone use administered either orally or by intravenous injection at a cumulative dose between 60 mg and 150 mg was associated with decreased mortality among those requiring respiratory support.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.23.20218099", + "rel_abs": "Indoor SARS-CoV-2 infections by droplets and aerosols are currently considered to be particularly significant. FFP2/3 respirator masks, which fit tightly and gap free, generally provide very good protection. In public transport, while shopping or in waiting rooms, they are therefore ideally suited to protect against direct and indirect infection. Unfortunately, these masks make it difficult to breathe and can be uncomfortable to wear in the long run. Therefore, these masks should be worn for a maximum of 3 x 75 minutes per day. These masks are therefore hardly suitable for schools or at work. The question therefore arises as to how people in closed rooms can be permanently protected from a SARS-CoV-2 infection. Large safety distances provide both self protection and protection of third parties, but they do not protect against indirect infection if the virus load in the room is high. Mouth and nose covers only offer protection of others against direct infection, but they do not protect the user against indirect infection. The same applies to faceshields and small protective walls. Indirect infections can be effectively prevented by free ventilation with windows or air conditioning systems that supply 100% outside air into the room, provided the air exchange rate is at minimum six times the room volume per hour. However, free ventilation by means of windows is rarely efficient enough, and in winter at the latest, it is no longer possible to open windows without wasting massive amounts of energy and endangering the health and well-being of people. The operation of air conditioning systems is also very energy-intensive during the cold season. Furthermore, most buildings do not have air conditioning systems. The question is therefore, how a largely safe protection against an indirect SARS-CoV-2 infection can be realized in closed rooms without wasting thermal energy and thus valuable resources. Technically, the problem can be solved with mobile disinfection devices or room air cleaners that separate the dangerous aerosol particles or inactivate the viruses by UV radiation or by contact with charge carriers. The potential of these devices is great and, since many German manufacturers produce these devices, they are also available. However, many of the devices offered do not provide effective protection because the volume flow is too small, the separation efficiency of the filters is too low and the performance of the UV and ionization unit is too weak. The Viromed Klinik Akut V 500 disinfection unit appears to meet the performance requirements and therefore the device is analyzed and evaluated in this study for its suitability to protect against SARS-CoV-2 infection.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Nicolas Hoertel", - "author_inst": "Universit\u00e9 de Paris" - }, - { - "author_name": "Marina S\u00e1nchez", - "author_inst": "Universidad Complutense de Madrid" - }, - { - "author_name": "Rapha\u00ebl Vernet", - "author_inst": "Assistance Publique - H\u00f4pitaux de Paris" - }, - { - "author_name": "Nathana\u00ebl Beeker", - "author_inst": "Assistance Publique - H\u00f4pitaux de Paris" - }, - { - "author_name": "Antoine Neuraz", - "author_inst": "Necker-Enfants Malades Hospital" - }, - { - "author_name": "Jes\u00fas Alvarado", - "author_inst": "Universidad Complutense de Madrid" - }, - { - "author_name": "Christel Daniel", - "author_inst": "Assistance Publique - H\u00f4pitaux de Paris" - }, - { - "author_name": "Nicolas Paris", - "author_inst": "Assistance Publique - H\u00f4pitaux de Paris" - }, - { - "author_name": "Alexandre Gramfort", - "author_inst": "Universit\u00e9 Paris-Saclay" - }, - { - "author_name": "Guillaume Lemaitre", - "author_inst": "Universit\u00e9 Paris-Saclay" - }, - { - "author_name": "Elisa Salamanca", - "author_inst": "Banque Nationale de Donn\u00e9es Maladies Rares" - }, - { - "author_name": "M\u00e9lodie Bernaux", - "author_inst": "Assistance Publique - H\u00f4pitaux de Paris" - }, - { - "author_name": "Ali Bellamine", - "author_inst": "Assistance Publique - H\u00f4pitaux de Paris" + "author_name": "Christian J. K\u00e4hler", + "author_inst": "Universit\u00e4t der Bundeswehr M\u00fcnchen, Institute of Fluid Mechanics and Aerodynamics" }, { - "author_name": "Anita Burgun", - "author_inst": "INSERM" + "author_name": "Thomas Fuchs", + "author_inst": "Universit\u00e4t der Bundeswehr M\u00fcnchen, Institute of Fluid Mechanics and Aerodynamics" }, { - "author_name": "Fr\u00e9d\u00e9ric Limosin", - "author_inst": "Universit\u00e9 de Paris" + "author_name": "Rainer Hain", + "author_inst": "Universit\u00e4t der Bundeswehr M\u00fcnchen, Institute of Fluid Mechanics and Aerodynamics" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1088945,41 +1088781,225 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.25.20219147", - "rel_title": "Fluctuating High Throughput Serological Assay Results in Recurrent Convalescent Plasma Donors", + "rel_doi": "10.1101/2020.10.25.20218875", + "rel_title": "Baseline phenotype and 30-day outcomes of people tested for COVID-19: an international network cohort including >3.32 million people tested with real-time PCR and >219,000 tested positive for SARS-CoV-2 in South Korea, Spain and the United States", "rel_date": "2020-10-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.25.20219147", - "rel_abs": "The clinical and scientific communities rely on serology testing to analyze the degree of antibody-mediated immunity afforded to recovered patients from SARS-CoV-2 infection. Neutralizing antibodies present in COVID-19 convalescent plasma (CCP) remains a practical therapy to treat COVID-19 patients requiring hospitalization. However, it remains unclear how long antibody levels persist in CCP donors after recovery. An accurate estimation of antibody kinetics in CCP donors provide an important observation to further define the extent of long-term immunity in recovered patient and simultaneously inform CCP collection processes in efforts to improve CCP dosing and therapeutic outcome. In this study, we analyzed 63 donors and measured antibody levels using two high throughput screening assays (HTSA) designed to detect antibodies targeting the spike protein (S1) and nucleocapsid protein (NP) of SARS-CoV-2 and monitored antibody levels between 2-8 consecutive donations. We show that anti-S1 antibody levels, as measured using the Ortho Total Ig HTSA, increased over time in repeat CCP donors while anti-NP antibody levels, as measured using the Abbott IgG HTSA, were unchanged or decreased over time. When we normalized these data, we found that both the absolute levels of anti-S1 antibodies and the ratio between S1 and NP antibodies tends to increase over time. These data have important implications for the convalescent donation process, patient protection from future infection and characterization of the SARS-CoV-2 immune response.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.25.20218875", + "rel_abs": "Early identification of symptoms and comorbidities most predictive of COVID-19 is critical to identify infection, guide policies to effectively contain the pandemic, and improve health systems response. Here, we characterised socio-demographics and comorbidity in 3,316,107persons tested and 219,072 persons tested positive for SARS-CoV-2 since January 2020, and their key health outcomes in the month following the first positive test. Routine care data from primary care electronic health records (EHR) from Spain, hospital EHR from the United States (US), and claims data from South Korea and the US were used. The majority of study participants were women aged 18-65 years old. Positive/tested ratio varied greatly geographically (2.2:100 to 31.2:100) and over time (from 50:100 in February-April to 6.8:100 in May-June). Fever, cough and dyspnoea were the most common symptoms at presentation. Between 4%-38% required admission and 1-10.5% died within a month from their first positive test. Observed disparity in testing practices led to variable baseline characteristics and outcomes, both nationally (US) and internationally. Our findings highlight the importance of large scale characterization of COVID-19 international cohorts to inform planning and resource allocation including testing as countries face a second wave.", + "rel_num_authors": 53, "rel_authors": [ { - "author_name": "Larry L Luchsinger", - "author_inst": "New York Blood Center" + "author_name": "Asieh Golozar", + "author_inst": "Regeneron Pharmaceutical, NY USA; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, MD USA" }, { - "author_name": "Shiraz Rehmani", - "author_inst": "New York Blood Center" + "author_name": "Lana YH Lai", + "author_inst": "Division of Cancer Sciences, School of Medical Sciences, University of Manchester, UK" }, { - "author_name": "Andrew Opalka", - "author_inst": "New York Blood Center" + "author_name": "Anthony Sena", + "author_inst": "Janssen R&D, Titusville NJ, USA; Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands" }, { - "author_name": "Donna Strauss", - "author_inst": "New York Blood Center" + "author_name": "David Vizcaya", + "author_inst": "Bayer Pharmaceuticals, Sant Joan Despi, Spain" }, { - "author_name": "Christopher D Hillyer", - "author_inst": "New York Blood Center" + "author_name": "Lisa M Schilling", + "author_inst": "Data Science to Patient Value Program, University of Colorado Anschutz Medical Campus" }, { - "author_name": "Patricia Shi", - "author_inst": "New York Blood Center" + "author_name": "Vojtech Huser", + "author_inst": "National Library of Medicine, National Institutes of Health, Bethesda, MD, USA" }, { - "author_name": "Bruce S Sachais", - "author_inst": "New York Blood Center" + "author_name": "Fredrik Nyberg", + "author_inst": "School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden" + }, + { + "author_name": "Scott L Duvall", + "author_inst": "VINCI, VA Salt Lake City Health Care System, Salt Lake City, VA, & Division of Epidemiology, University of Utah, Salt Lake City, UT" + }, + { + "author_name": "Daniel R Morales", + "author_inst": "Division of Population Health and Genomics, University of Dundee, UK" + }, + { + "author_name": "Thamir M Alshammari", + "author_inst": "Medication Safety Research Chair, King Saud University, Riyadh, Saudi Arabia" + }, + { + "author_name": "Hamed Abedtash", + "author_inst": "Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN" + }, + { + "author_name": "Waheed-Ul-Rahman Ahmed", + "author_inst": "Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK College of Medicine and Health, University of E" + }, + { + "author_name": "Osaid Alser", + "author_inst": "Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA" + }, + { + "author_name": "Heba Alghoul", + "author_inst": "Faculty of Medicine, Islamic University of Gaza, Palestine" + }, + { + "author_name": "Ying Zhang", + "author_inst": "DHC Technologies Co. Ltd, Beijing, China" + }, + { + "author_name": "Mengchun Gong", + "author_inst": "DHC Technologies Co. Ltd, Beijing, China" + }, + { + "author_name": "Yin Guan", + "author_inst": "DHC Technologies Co. Ltd, Beijing, China" + }, + { + "author_name": "Carlos Areia", + "author_inst": "Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK" + }, + { + "author_name": "Jitendra Jonnagaddala", + "author_inst": "School of Public Health and Community Medicine, UNSW Sydney, Australia" + }, + { + "author_name": "Karishma Shah", + "author_inst": "Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK" + }, + { + "author_name": "Jennifer C Lane", + "author_inst": "Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK" + }, + { + "author_name": "Albert Prats-Uribe", + "author_inst": "Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK" + }, + { + "author_name": "Jose D Posada", + "author_inst": "Stanford University School of Medicine, Stanford, California, USA" + }, + { + "author_name": "Nigam H Shah", + "author_inst": "Stanford University School of Medicine, Stanford, California, USA" + }, + { + "author_name": "Vignesh Subbian", + "author_inst": "College of Engineering, The University of Arizona, Tucson, Arizona, USA" + }, + { + "author_name": "Lin Zhang", + "author_inst": "School of Population Medicine and Public Health, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China; Melbourne School of Popul" + }, + { + "author_name": "Maria Tereza Fernandes Abrahao", + "author_inst": "Faculty Medicine University of Sao Paulo, Sao Paulo, Brazil" + }, + { + "author_name": "Peter R Rijnbeek", + "author_inst": "Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands" + }, + { + "author_name": "Seng Chan You", + "author_inst": "Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, South Korea" + }, + { + "author_name": "Paula Casajust", + "author_inst": "Real-World Evidence, Trial Form Support, Barcelona, Spain" + }, + { + "author_name": "Elena Roel", + "author_inst": "Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain" + }, + { + "author_name": "Martina Recalde", + "author_inst": "Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain; Universitat Autonoma de Barcelon" + }, + { + "author_name": "Sergio Fernandez-Bertolin", + "author_inst": "Fundacio Institut Universitari per a la recerca a l'Atencil Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain" + }, + { + "author_name": "Alan Andryc", + "author_inst": "Janssen R&D, Titusville NJ, USA" + }, + { + "author_name": "Jason A Thomas", + "author_inst": "Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA" + }, + { + "author_name": "Adam B Wilcox", + "author_inst": "Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA UW; Medicine, Seattle, WA, USA" + }, + { + "author_name": "Stephen Fortin", + "author_inst": "Observational Health Data Analytics, Janssen Research and Development, Raritan, NJ, USA" + }, + { + "author_name": "Clair Blacketer", + "author_inst": "Janssen R&D, Titusville NJ, USA; Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands" + }, + { + "author_name": "Frank DeFalco", + "author_inst": "Janssen R&D, Titusville NJ, USA" + }, + { + "author_name": "Karthik Natarajan", + "author_inst": "Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY 10032, USA; New York-Presbyterian Hospital, 622 W 168 St, PH20 New" + }, + { + "author_name": "Thomas Falconer", + "author_inst": "Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY 10032, USA" + }, + { + "author_name": "Matthew Spotnitz", + "author_inst": "Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY 10032, USA" + }, + { + "author_name": "Anna Ostropolets", + "author_inst": "Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY 10032, USA" + }, + { + "author_name": "George Hripcsak", + "author_inst": "Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY 10032, USA; New York-Presbyterian Hospital, 622 W 168 St, PH20 New" + }, + { + "author_name": "Marc Suchard", + "author_inst": "Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, USA" + }, + { + "author_name": "Kristine E Lynch", + "author_inst": "VINCI, VA Salt Lake City Health Care System, Salt Lake City, VA, & Division of Epidemiology, University of Utah, Salt Lake City, UT" + }, + { + "author_name": "Michael E Matheny", + "author_inst": "VINCI, Tennessee Valley Healthcare System VA, Nashville, TN & Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN" + }, + { + "author_name": "Andrew Williams", + "author_inst": "Tufts Institute for Clinical Research and Health Policy Studies, US" + }, + { + "author_name": "Christian Reich", + "author_inst": "Real World Solutions, IQVIA, Cambridge, MA, USA" + }, + { + "author_name": "Talita Duarte-Salles", + "author_inst": "Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain" + }, + { + "author_name": "Kristin Kostka", + "author_inst": "Real World Solutions, IQVIA, Cambridge, MA, USA" + }, + { + "author_name": "Patrick B Ryan", + "author_inst": "Janssen R&D, Titusville NJ, USA; Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands" + }, + { + "author_name": "DANIEL PRIETO-ALHAMBRA", + "author_inst": "University of Oxford" } ], "version": "1", @@ -1090415,61 +1090435,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.26.20219550", - "rel_title": "Human movement can inform the spatial scale of interventions against COVID-19 transmission", + "rel_doi": "10.1101/2020.10.26.20219683", + "rel_title": "PREVALENCE OF MOLECULAR AND SEROLOGICAL TESTS OF THE NEW CORONAVIRUS (SARS-CoV-2) IN CARLOS CHAGAS-SABIN LABORATORIES IN CUIABA", "rel_date": "2020-10-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.26.20219550", - "rel_abs": "BackgroundIn 2020, the UK enacted an intensive, nationwide lockdown on March 23 to mitigate transmission of COVID-19. As restrictions began to ease, resurgences in transmission were targeted by geographically-limited interventions of various stringencies. Understanding the spatial scale of networks of human interaction, and how these networks change over time, is critical to inform interventions targeted at the most at-risk areas without unnecessarily restricting areas at low risk of resurgence.\n\nMethodsWe use detailed human mobility data aggregated from Facebook users to determine how the spatially-explicit network of movements changed before and during the lockdown period, in response to the easing of restrictions, and to the introduction of locally-targeted interventions. We also apply community detection techniques to the weighted, directed network of movements to identify geographically-explicit movement communities and measure the evolution of these community structures through time.\n\nFindingsWe found that the mobility network became more sparse and the number of mobility communities decreased under the national lockdown, a change that disproportionately affected long distance journeys central to the mobility network. We also found that the community structure of areas in which locally-targeted interventions were implemented following epidemic resurgence did not show reorganization of community structure but did show small decreases in indicators of travel outside of local areas.\n\nInterpretationWe propose that communities detected using Facebook or other mobility data be used to assess the impact of spatially-targeted restrictions and may inform policymakers about the spatial extent of human movement patterns in the UK. These data are available in near real-time, allowing quantification of changes in the distribution of the population across the UK, as well as changes in travel patterns to inform our understanding of the impact of geographically-targeted interventions.\n\nPutting Research Into ContextO_ST_ABSEvidence before this studyC_ST_ABSLarge-scale intensive interventions in response to the COVID-19 pandemic have been implemented globally, significantly affecting human movement patterns. Mobility data show spatially-explicit network structure, but it is not clear how that structure changed in response to national or locally-targeted interventions.\n\nAdded value of this studyWe used daily mobility data aggregated from Facebook users to quantify changes in the travel network in the UK during the national lockdown, and in response to local interventions. We identified changes in human behaviour in response to interventions and identified the community structure inherent in these networks. This approach to understanding changes in the travel network can help quantify the extent of strongly connected communities of interaction and their relationship to the extent of spatially-explicit interventions.\n\nImplications of all the available evidenceWe show that spatial mobility data available in near real-time can give information on connectivity that can be used to understand the impact of geographically-targeted interventions and in the future, to inform spatially-targeted intervention strategies.\n\nData SharingData used in this study are available from the Facebook Data for Good Partner Program by application. Code and supplementary information for this paper are available online (https://github.com/hamishgibbs/facebook_mobility_uk), alongside publication.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.26.20219683", + "rel_abs": "BACKGROUNDCOVID-19, the disease caused by the new coronavirus (SARS-CoV-2), became a pandemic in 2020 with mortality rate of 2% and high transmissibility, which makes studies with an epidemiological profile essential.\n\nOBJECTIVESTo characterize the population that performed the SARS-CoV-2 molecular and serological tests in Carlos Chagas-Sabin laboratories in Cuiaba.\n\nMETHODSA retrospective cross-sectional study was carried out with all the samples collected from nasal swab tested by RT-PCR and serological for SARM-CoV-2 IgM / IgG from the population served between April and July 2020.\n\nFINDINGSIn the analyzed period, 11,113 PCR-Covid-19 exams were registered. Of this total of cases, 3,912 (35.20%) tested positive, while 6,889 (61.90%) did not detect viral RNA and 312 (2.80%) of the visits resulted as undetermined. The peak of positive RT-PCR performed in July (n = 5878), with 35.65% (n = 2096). A total of 6,392 tests performed on SOROVID-19, with a peak of 1161 (18.16%) of the positive tests for SARS-CoV-2 in July.\n\nMAIN CONCLUSIONSMolecular positivity and serological tests, both peaked in July 2020, were mostly present in women aged 20-39, characterizing Cuiaba as the epicenter of the Midwest region in this period due to the high rate of transmissibility of SARS-CoV-2.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Hamish Gibbs", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Cristiane Coimbra de Paula", + "author_inst": "Centro Universitario de Varzea Grande (Univag) e Universidade Federal de Mato Grosso (UFMT)-Cuiaba-MT-Brasil" }, { - "author_name": "Emily Nightingale", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Joao Pedro Castoldo Passos", + "author_inst": "Centro Universitario de Varzea Grande (Univag)-MT-Brasil" }, { - "author_name": "Yang Liu", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Walkiria Shimoya Bittencour IV", + "author_inst": "Universidade de Cuiaba (UNIC), Cuiaba, Mato Grosso, Brasil." }, { - "author_name": "James Cheshire", - "author_inst": "University College London" + "author_name": "Caroline Aquino Vieira de Lamare II", + "author_inst": "a P Graduate program in Sciences Applied to Hospital Care, Hospital Universitario Julio Muller (HUJM), Cuiaba, MT, Brazil." }, { - "author_name": "Leon Danon", - "author_inst": "University of Exeter" - }, - { - "author_name": "Liam Smeeth", - "author_inst": "London School of Hygiene & Tropical Medicine" - }, - { - "author_name": "Carl AB Pearson", - "author_inst": "London School of Hygiene & Tropical Medicine" - }, - { - "author_name": "Chris Grundy", - "author_inst": "London School of Hygiene & Tropical Medicine" - }, - { - "author_name": "- LSHTM CMMID COVID-19 Working Group", - "author_inst": "" - }, - { - "author_name": "Adam J Kucharski", - "author_inst": "London School of Hygiene & Tropical Medicine" - }, - { - "author_name": "Rosalind M Eggo", - "author_inst": "London School of Hygiene & Tropical Medicine" + "author_name": "Ruberlei Godinho de Oliveira Sr.", + "author_inst": "a P Graduate program in Sciences Applied to Hospital Care, Hospital Universitario Julio Muller (HUJM)" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1092533,83 +1092529,63 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2020.10.26.353300", - "rel_title": "Remdesivir Metabolite GS-441524 Efficiently Inhibits SARS-CoV-2 Infection in Mouse Model", + "rel_doi": "10.1101/2020.10.26.356048", + "rel_title": "ISG15-dependent Activation of the RNA Sensor MDA5 and its Antagonism by the SARS-CoV-2 papain-like protease", "rel_date": "2020-10-27", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.26.353300", - "rel_abs": "The outbreak of coronavirus disease 2019 (COVID-19) rapidly spreads across worldwide and becomes a global pandemic. Remdesivir is the only COVID-19 treatment approved by U.S. Food and Drug Administration (FDA); however, its effectiveness is still under questioning as raised by the results of a large WHO Solidarity Trial. Herein, we report that the parent nucleotide of remdesivir, GS-441524, potently inhibits the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Vero E6 and other cells. It exhibits good plasma distribution and longer half-life (t1/2=4.8h) in rat PK study. GS-441524 is highly efficacious against SARS-CoV-2 in AAV-hACE2 transduced mice and murine hepatitis virus (MHV) in mice, reducing the viral titers in CoV-attacked organs, without noticeable toxicity. Given that GS-441524 was the predominant metabolite of remdesivir in the plasma, the anti-COVID-19 effect of remdesivir may partly come from the effect of GS-441524. Our results also supported that GS-441524 as a promising and inexpensive drug candidate in the treatment of COVID-19 and future emerging CoVs diseases.", - "rel_num_authors": 16, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.26.356048", + "rel_abs": "Activation of the RIG-I-like receptors, RIG-I and MDA5, establishes an antiviral state by upregulating interferon (IFN)-stimulated genes (ISGs). Among these is ISG15 whose mechanistic roles in innate immunity still remain enigmatic. Here we report that ISGylation is essential for antiviral IFN responses mediated by the viral RNA sensor MDA5. ISG15 conjugation to the caspase activation and recruitment domains of MDA5 promotes the formation of higher-order assemblies of MDA5 and thereby triggers activation of innate immunity against a range of viruses including coronaviruses, flaviviruses and picornaviruses. The ISG15-dependent activation of MDA5 is antagonized through direct de-ISGylation mediated by the papain-like protease (PLpro) of SARS-CoV-2, a recently emerged coronavirus that causes the COVID-19 pandemic. Our work demonstrates a crucial role for ISG15 in the MDA5-mediated antiviral response, and also identifies a novel immune evasion mechanism of SARS-CoV-2, which may be targeted for the development of new antivirals and vaccines to combat COVID-19.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Yingjun Li", - "author_inst": "Southern University of Science and Technology" - }, - { - "author_name": "Liu Cao", - "author_inst": "Sun Yat-sen University" - }, - { - "author_name": "Ge Li", - "author_inst": "Guangdong Laboratory Animals Monitoring Institute" - }, - { - "author_name": "Feng Cong", - "author_inst": "Guangdong Laboratory Animals Monitoring Institute" - }, - { - "author_name": "Yunfeng Li", - "author_inst": "Guangdong Laboratory Animals Monitoring Institute" - }, - { - "author_name": "Jing Sun", - "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention" + "author_name": "GuanQun Liu", + "author_inst": "Florida Research and Innovation Center, Cleveland Clinic" }, { - "author_name": "Yinzhu Luo", - "author_inst": "Guangdong Laboratory Animals Monitoring Institute" + "author_name": "Jung-Hyun Lee", + "author_inst": "Florida Research and Innovation Center, Cleveland Clinic" }, { - "author_name": "Guijiang Chen", - "author_inst": "Guangdong Laboratory Animals Monitoring Institute" + "author_name": "Zachary M Parker", + "author_inst": "University of Chicago" }, { - "author_name": "Guanguan Li", - "author_inst": "Southern University of Science and Technology" + "author_name": "Dhiraj Acharya", + "author_inst": "Florida Research and Innovation Center, Cleveland Clinic" }, { - "author_name": "Ping Wang", - "author_inst": "Southern University of Science and Technology" + "author_name": "Jessica J Chiang", + "author_inst": "Harvard University" }, { - "author_name": "Fan Xing", - "author_inst": "Sun Yat-sen University" + "author_name": "Michiel van Gent", + "author_inst": "Florida Research and Innovation Center, Cleveland Clinic" }, { - "author_name": "Yanxi Ji", - "author_inst": "Sun Yat-sen University" + "author_name": "William Riedl", + "author_inst": "Florida Research and Innovation Center, Cleveland Clinic" }, { - "author_name": "Jincun Zhao", - "author_inst": "GIRH" + "author_name": "Meredith E Davis-Gardner", + "author_inst": "Emory University" }, { - "author_name": "Yu Zhang", - "author_inst": "Guangdong Laboratory Animals Monitoring Institute" + "author_name": "Effi Wies", + "author_inst": "Harvard University" }, { - "author_name": "Deyin Guo", - "author_inst": "Sun Yat-sen University" + "author_name": "Cindy Chiang", + "author_inst": "Florida Research and Innovation Center, Cleveland Clinic" }, { - "author_name": "Xumu Zhang", - "author_inst": "Southern University of Science and Technology" + "author_name": "Michaela U Gack", + "author_inst": "Florida Research and Innovation Center, Cleveland Clinic" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "pharmacology and toxicology" + "category": "immunology" }, { "rel_doi": "10.1101/2020.10.27.357954", @@ -1094091,43 +1094067,107 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.10.25.354548", - "rel_title": "Diversity of ACE2 and its interaction with SARS-CoV-2 receptor binding domain", + "rel_doi": "10.1101/2020.10.26.354811", + "rel_title": "Post-exposure protection of SARS-CoV-2 lethal infected K18-hACE2 transgenic mice by neutralizing human monoclonal antibody", "rel_date": "2020-10-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.25.354548", - "rel_abs": "COVID-19, the clinical syndrome caused by the SARS-CoV-2 virus, has rapidly spread globally causing tens of millions of infections and over a million deaths. The potential animal reservoirs for SARS-CoV-2 are currently unknown, however sequence analysis has provided plausible potential candidate species. SARS-CoV-2 binds to the angiotensin I converting enzyme 2 (ACE2) to enable its entry into host cells and establish infection. We analyzed the binding surface of ACE2 from several important animal species to begin to understand the parameters for the ACE2 recognition by the SARS-CoV-2 spike protein receptor binding domain (RBD). We employed Shannon entropy analysis to determine the variability of ACE2 across its sequence and particularly in its RBD interacting region, and assessed differences between various species ACE2 and human ACE2. As cattle are a known reservoir for coronaviruses with previous human zoonotic transfer, and has a relatively divergent ACE2 sequence, we compared the binding kinetics of bovine and human ACE2 to SARS-CoV-2 RBD. This revealed a nanomolar binding affinity for bovine ACE2 but an approximate ten-fold reduction of binding compared to human ACE2. Since cows have been experimentally infected by SARS-CoV-2, this lower affinity sets a threshold for sequences with lower homology to human ACE2 to be able to serve as a productive viral receptor for SARS-CoV-2.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.26.354811", + "rel_abs": "Coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), exhibits high levels of mortality and morbidity and has dramatic consequences on human life, sociality and global economy. Neutralizing antibodies constitute a highly promising approach for treating and preventing infection by this novel pathogen. In the present study, we characterized and further evaluated the recently identified human monoclonal MD65 antibody for its ability to provide protection against a lethal SARS-CoV-2 infection of K18-hACE2 transgenic mice. Eighty percent of the untreated mice succumbed 6-9 days post-infection while administration of the MD65 antibody as late as 3 days after exposure, rescued all infected animals. In addition, the efficiency of the treatment is supported by prevention of morbidity and ablation of the load of infective virions in the lungs of treated animals. The data unprecedentedly demonstrate, the therapeutic value of human monoclonal antibodies as a life-saving treatment of severe COVID-19 infection.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Jessie L Gan", - "author_inst": "San Diego Jewish Academy, Applied Biomedical Science Institute" + "author_name": "Ronit Rosenfeld", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Ruiqi Huang", - "author_inst": "Applied Biomedical Science Institute" + "author_name": "Tal Noy-Porat", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Adva Mechaly", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Efi Makdasi", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Yinon Levy", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Gabrielle Warner", - "author_inst": "Applied Biomedical Science Institute" + "author_name": "Ron Alcalay", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Abigail Kelley", - "author_inst": "Applied Biomedical Science Institute" + "author_name": "Reut Falach", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Duncan McGregor", - "author_inst": "Applied Biomedical Science Institute" + "author_name": "Moshe Aftalion", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Vaughn V. Smider", - "author_inst": "The Applied Biomedical Science Institute, The Scripps Research Institute" + "author_name": "Eyal Epstein", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "David Gur", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Theodor Chitlaru", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Einat B. Vitner", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Sharon Melamed", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Boaz Politi", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Ayelet Zauberman", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Shirley Lazar", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Adi Beth-Din", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Yentl Evgy", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Shmuel Yitzhaki", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Shmuel C. Shapira", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Tomer Israely", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Ohad Mazor", + "author_inst": "Israel Institute for Biological Research" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "molecular biology" + "category": "immunology" }, { "rel_doi": "10.1101/2020.10.25.354571", @@ -1095473,31 +1095513,35 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.10.21.20216218", - "rel_title": "Anti-vaccine attitudes and risk factors for not agreeing to vaccination against COVID-19 amongst 32,361 UK adults: Implications for public health communications", + "rel_doi": "10.1101/2020.10.20.20216150", + "rel_title": "Mining transcriptomics and clinical data reveals ACE2 expression modulators and identifies cardiomyopathy as a risk factor for mortality in COVID-19 patients", "rel_date": "2020-10-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.21.20216218", - "rel_abs": "BackgroundNegative attitudes towards vaccines and an uncertainty or unwillingness to receive vaccinations are major barriers to managing the COVID-19 pandemic in the long-term. We estimate predictors of four domains of negative attitudes towards vaccines and identify groups most at risk of uncertainty and unwillingness to receive a COVID-19 vaccine in a large sample of UK adults.\n\nMethodsData were from 32,361 adults in the UCL COVID-19 Social Study. Ordinary least squares regression analyses examined the impact of socio-demographic and COVID-19 related factors on four types of negative vaccine attitudes: mistrust of vaccine benefit, worries about unforeseen effects, concerns about commercial profiteering, and preference for natural immunity. Multinomial logistic regression examined the impact of socio-demographic and COVID-19 related factors, negative vaccine attitudes, and prior vaccine behaviour on uncertainty and unwillingness to be vaccinated for COVID-19.\n\nFindings16% of respondents displayed high levels of mistrust or misinformation about vaccines across one or more domains. Distrustful attitudes towards vaccination were higher amongst individuals from ethnic minority backgrounds, with lower levels of education, lower annual income, poor knowledge of COVID-19, and poor compliance with government COVID-19 guidelines. Overall, 14% of respondents reported unwillingness to receive a vaccine for COVID-19, whilst 22% were unsure. The largest predictors of both COVID-19 vaccine uncertainty and refusal were low income (< {pound}30,000 a year), having not received a flu vaccine last year, poor adherence to COVID-19 government guidelines, female gender, and living with children. Amongst vaccine attitudes, intermediate to high levels of vaccine benefit mistrust and concerns about future unforeseen side effects were the most important determinants of both uncertainty and unwillingness to vaccinate against COVID-19.\n\nInterpretationNegative attitudes towards vaccines are major public health concerns in the UK. General mistrust in vaccines and concerns about future side effects in particular will be barriers to achieving population immunity to COVID-19 through vaccination. Public health messaging should be tailored to address these concerns.\n\nFundingThe Nuffield Foundation [WEL/FR-000022583], the MARCH Mental Health Network funded by the Cross-Disciplinary Mental Health Network Plus initiative supported by UK Research and Innovation [ES/S002588/1], and the Wellcome Trust [221400/Z/20/Z and 205407/Z/16/Z].\n\nO_TEXTBOXEvidence before this studyWe searched PubMed for articles published in English from 1 January 2020 to 20 September 2020 with the following keywords: (\"COVID19 vaccine\" OR \"coronavirus vaccine\") and (\"intent*\" OR \"refusal\"). Our search found 639 titles. Several previous studies have examined predictors of intent to vaccinate for COVID-19 when it becomes available. Reasons for unwillingness to receive the COVID-19 vaccination when it becomes available centred on concerns about its newness, safety, and potential side effects. However, estimates and predictors of negative vaccine attitudes in general and how these attitudes predict uncertainty and unwillingness to vaccinate in the context of COVID-19 are unavailable.\n\nAdded value of this studyThe attitudinal and behavioural barriers to being unsure about receiving a COVID-19 vaccine and not intending to receive one were largely overlapping; 1) didnt get a flu vaccine last year, 2) poor adherence to government guidelines, 3) concerns about the unforeseen future effects of vaccines, and 4) and general mistrust in the benefits of vaccines.\n\nImplications of all of the available evidenceMistrust towards vaccines represent a significant challenge in achieving the vaccination coverage required for population immunity. Taken together, there is evidence that groups most vulnerable to falling ill and dying of COVID-19 (e.g. those from ethnic minority backgrounds and who have lower incomes) have more negative attitudes towards vaccines and are less willing to vaccinate against COVID-19. Not everyone who intends to receive a COVID-19 vaccination will be able to do so because of practical barriers such as lack of accessibility and government decisions on the availability of the vaccine, underscoring the importance of improving vaccine attitudes in the general population to improve vaccine uptake amongst those who are offered a vaccine and prevent widening socio-economic health inequalities. Vaccine safety communication to increase public trust by the time a COVID-19 vaccine is available should begin now.\n\nC_TEXTBOX", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.20.20216150", + "rel_abs": "Angiotensin-converting enzyme 2 (ACE2) is the cell-entry receptor for SARS-CoV-2. It plays critical roles in both the transmission and the pathogenesis of the coronavirus disease 2019 (COVID-19). Comprehensive profiling of ACE2 expression patterns will help researchers to reveal risk factors of severe COVID-19 illness. While the expression of ACE2 in healthy human tissues has been well characterized, it is not known which diseases and drugs might modulate the ACE2 expression. In this study, we developed GENEVA (GENe Expression Variance Analysis), a semi-automated framework for exploring massive amounts of RNA-seq datasets. We applied GENEVA to 28,6650 publicly available RNA-seq samples to identify any previously studied experimental conditions that could directly or indirectly modulate ACE2 expression. We identified multiple drugs, genetic perturbations, and diseases that modulate the expression of ACE2, including cardiomyopathy, HNF1A overexpression, and drug treatments with RAD140 and Itraconazole. Our unbiased meta-analysis of seven datasets confirms ACE2 up-regulation in all cardiomyopathy categories. Using electronic health records data from 3936 COVID19 patients, we demonstrate that patients with pre-existing cardiomyopathy have an increased mortality risk than age-matched patients with other cardiovascular conditions. GENEVA is applicable to any genes of interest and is freely accessible at http://genevatool.org.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Elise Paul", - "author_inst": "University College London" + "author_name": "Navchetan Kaur", + "author_inst": "UCSF" }, { - "author_name": "Andrew Steptoe", - "author_inst": "University College London" + "author_name": "Boris Oskotsky", + "author_inst": "UCSF" }, { - "author_name": "Daisy Fancourt", - "author_inst": "University College London" + "author_name": "Atul J Butte", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Zicheng Hu", + "author_inst": "UCSF" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "health informatics" }, { "rel_doi": "10.1101/2020.10.20.20215608", @@ -1097191,35 +1097235,47 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.10.20.20215723", - "rel_title": "Twitter Engagement of U.S. Psychiatry Residency Programs with Black Lives Matter and Coronavirus Disease 2019 (COVID-19)", + "rel_doi": "10.1101/2020.10.21.20216978", + "rel_title": "Exposome changes in primary school children following the wide population non-pharmacological interventions implemented due to COVID-19 in Cyprus: a national survey", "rel_date": "2020-10-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.20.20215723", - "rel_abs": "Social media have become popular platforms to disseminate information, especially related to politicized topics such as BLM and COVID-19. To better understand how medical institutions have engaged with the social media discourse on BLM and COVID-19, we examined psychiatry residency programs tweets in response to George Floyds murder and during the first 6 months of the COVID-19 pandemic in the U.S. Only 14% of the 249 evaluated psychiatry residency programs had Twitter accounts (we included programs with their own account or their affiliated psychiatry department account) indicating a substantial absence on social media. Of those programs, 78% tweeted at least once about COVID-19 (1,153 tweets) and 56% tweeted at least once about the BLM movement (117 tweets). The top three purposes of tweets were sharing media, posting about an event, and sharing a resource.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.21.20216978", + "rel_abs": "BackgroundSchool closures were part of a series of non-pharmacological intervention (NPI) measures addressing the COVID-19 pandemic in Cyprus. We aimed to study changes in the environment, diet, behavior, personal hygiene, contacts, lifestyle choices and the degree of compliance to NPI measures by primary school children in Cyprus at school and at home for two periods, i.e., before lockdown and during the school re-opening using the methodological context of the human exposome.\n\nMethodsDuring June 2020, an online survey questionnaire was forwarded to parents of primary school children through schools administrations, with questions about the childrens lifestyle/behaviours for two periods; school re-opening, following the population-wide lockdown (May 21-June 26, 2020), and the school period before lockdown (before March 2020). Descriptive statistics and exposome wide association analysis were implemented to agnostically assess associations of demographic, lifestyle and behavioral parameters with the degree of compliance to NPI measures.\n\nFindingsA total of 1509 children from more than 180 primary schools (out of 330 schools) in Cyprus were included. Median number of contacts per day at home, school and other places during weekdays was lower (p<0.001) in the post-lockdown period compared to the pre-lockdown period (5 vs 12, 10 vs 29 and 6 vs 14, respectively). Vulnerable contacts with children also decreased from 2[1, 3] in the pre-lockdown to 1[0, 2] in the post-lockdown period (p<0.001). Differences in sugary and ready-made food consumption, physical activity, screen time, digital communication and hand hygiene were noted between the two periods. More than 72% of children complied with the NPI measures, with the exception of the decrease in number of vulnerable contact(s) indicator (48%). Eating meat more frequently post-lockdown and doing less physical activity during school break post-lockdown were positively associated with increased time spent at home post-lockdown. Furthermore, the odds of compliance, as indicated by the time spent at home post-lockdown were lower with days elapsing from school re-opening, living in smaller town and using antiseptic more frequently pre-lockdown.\n\nInterpretationIn this national survey, children showed a high degree of compliance to most NPI measures for the community and primary school settings in Cyprus. The initial NPI measures may have affected the childrens exposome profile in the following months, by altering their diet, physical activity, sedentary lifestyle and hand hygiene habits.\n\nFundingThe study was partially funded by the EXPOSOGAS project, H2020 under grant agreement #810995\n\nPanel: Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for studies published until September 30, 2020 using the search terms: COVID-19, children and lifestyle. Only six peer-reviewed, English-language studies were retrieved on the effect of COVID-19 measures on childrens lifestyle. The impact of non-pharmacological intervention (NPI) measures on childrens health during the pandemic period has been sporadically studied by focusing on a few risk factors at a time without using the exposomes methodological framework, which is defined as the comprehensive characterization of all environmental exposures during ones lifetime.\n\nAdded value of this studyA survey targeted all primary schools of Cyprus to comprehensively study the impact of the initial population-wide NPI measures (lockdown) (March 13-May 4) on the childrens exposome during the school re-opening period (May 21 - June 26). To the best of our knowledge, this is the first study looking at the post-confinement (lockdown) exposome profile changes of children during schools re-opening, after the initial population-wide NPI measures of COVID-19 response. The comprehensive and agnostic description of the childrens exposome profile may help to comprehensively account for both known and possibly unknown effects of NPI measures on childrens health and for delineating the childrens degree of compliance to infection prevention and control protocols at school and at home.\n\nImplications of all the available evidenceThis dataset could inform COVID-19 risk-based public health response strategies targeted for school settings. Future response strategies to epidemic waves shall consider elements of promoting a healthy lifestyle for children at school and at home. Public health policy could ultimately benefit from the inclusion of the human exposome methodological framework and its tools towards the improved identification of susceptible sub-population groups and to facilitate the deployment of site-tailored public health measures; this may be particularly relevant for children and their potential to spread the disease to vulnerable groups.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Osama El-Gabalawy", - "author_inst": "Stanford University School of Medicine" + "author_name": "Corina Konstantinou", + "author_inst": "Cyprus University of Technology" }, { - "author_name": "Candice Kim", - "author_inst": "Stanford University Graduate School of Education" + "author_name": "Xanthi D Andrianou", + "author_inst": "Cyprus University of Technology" }, { - "author_name": "Amanda Chen", - "author_inst": "Dartmouth College, Hanover, New Hampshire" + "author_name": "Andria Constantinou", + "author_inst": "Cyprus University of Technology" }, { - "author_name": "Shaan Kamal", - "author_inst": "University of Connecticut School of Medicine" + "author_name": "Anastasia Perikkou", + "author_inst": "Cyprus University of Technology" + }, + { + "author_name": "Eliza Markidou", + "author_inst": "Cyprus Ministry of Health" + }, + { + "author_name": "Costas A Christophi", + "author_inst": "Cyprus University of Technology" + }, + { + "author_name": "Konstantinos C Makris", + "author_inst": "Cyprus University of Technology" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.10.21.20216960", @@ -1098873,21 +1098929,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.19.20215525", - "rel_title": "Modifiable lifestyle factors and severe COVID-19 risk: Evidence from Mendelian randomization analysis", + "rel_doi": "10.1101/2020.10.19.20215376", + "rel_title": "What predicts adherence to COVID-19 government guidelines? Longitudinal analyses of 51,000 UK adults.", "rel_date": "2020-10-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.19.20215525", - "rel_abs": "BackgroundLifestyle factors including obesity and smoking are suggested to be related to increased risk of COVID-19 severe illness or related death. However, little is known about whether these relationships are causal, or the relationships between COVID-19 severe illness and other lifestyle factors, such as alcohol consumption and physical activity.\n\nMethodsGenome-wide significant genetic variants associated with body mass index (BMI), lifetime smoking, alcohol consumption and physical activity identified by large-scale genome-wide association studies (GWAS) were selected as instrumental variables. GWAS summary statistics of these genetic variants for relevant lifestyle factors and severe illness of COVID-19 were obtained. Two-sample Mendelian randomization (MR) analyses were conducted.\n\nResultsBoth genetically predicted BMI and lifetime smoking were associated with about 2-fold increased risks of severe respiratory COVID-19 and COVID-19 hospitalization (all P<0.05). Genetically predicted physical activity was associated with about 5-fold (95% confidence interval [CI], 1.4, 20.3; P=0.02) decreased risk of severe respiratory COVID-19, but not with COVID-19 hospitalization, though the majority of the 95% CI did not include one. No evidence of association was found for genetically predicted alcohol consumption, but associations were found when using pleiotropy robust methods.\n\nConclusionEvidence is found that BMI and smoking causally increase and physical activity causally decreases the risk of COVID-19 severe illness. This study highlights the importance of maintaining a healthy lifestyle in protecting from COVID-19 severe illness and its public health value in fighting against COVID-19 pandemic.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.19.20215376", + "rel_abs": "In the absence of a vaccine, governments have focused on social distancing, self-isolation, and increased hygiene procedures to reduce the transmission of SARS-CoV-2 (COVID-19). Compliance with these measures requires voluntary cooperation from citizens. Yet, compliance is not complete, and existing studies provide limited understanding of what factors influence compliance; in particular modifiable factors. We use weekly panel data from 51,000 adults across the first three months of lockdown in the UK to identify factors that are related to compliance with COVID-19 guidelines. We find evidence that increased confidence in government to tackle the pandemic is longitudinally related to higher compliance, but little evidence that factors such as mental health and wellbeing, worries about future adversities, and social isolation and loneliness are related to changes in compliance. Our results suggest that to effectively manage the pandemic, governments should ensure that confidence is maintained, something which has not occurred in all countries.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Shuai Li", - "author_inst": "The University of Melbourne" + "author_name": "Liam Wright", + "author_inst": "University College London" + }, + { + "author_name": "Andrew Steptoe", + "author_inst": "University College London" + }, + { + "author_name": "Daisy Fancourt", + "author_inst": "University College London" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1100450,23 +1100514,71 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.18.20214783", - "rel_title": "2.5 Million Person-Years of Life Have Been Lost Due to COVID-19 in the United States", + "rel_doi": "10.1101/2020.10.14.20212795", + "rel_title": "A Sensitive, Rapid, and Portable CasRx-based Diagnostic Assay for SARS-CoV2", "rel_date": "2020-10-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.18.20214783", - "rel_abs": "The COVID-19 pandemic, caused by tens of millions of SARS-CoV-2 infections world-wide, has resulted in considerable levels of mortality and morbidity. The United States has been hit particularly hard having 20 percent of the worlds infections but only 4 percent of the world population. Unfortunately, significant levels of misunderstanding exist about the severity of the disease and its lethality. As COVID-19 disproportionally impacts elderly populations, the false impression that the impact on society of these deaths is minimal may be conveyed by some because elderly individuals are closer to a natural death. To assess the impact of COVID-19 in the US, I have performed calculations of person-years of life lost as a result of 194,000 premature deaths due to SARS-CoV-2 infection as of early October, 2020. By combining actuarial data on life expectancy and the distribution of COVID-19 associated deaths we estimate that over 2,500,000 person-years of life have been lost so far in the pandemic in the US alone, averaging over 13.25 years per person with differences noted between males and females. Importantly, nearly half of the potential years of life lost occur in non-elderly populations. Issues impacting refinement of these models and the additional morbidity caused by COVID-19 beyond lethality are discussed.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.14.20212795", + "rel_abs": "Since its first emergence from China in late 2019, the SARS-CoV-2 virus has spread globally despite unprecedented containment efforts, resulting in a catastrophic worldwide pandemic. Successful identification and isolation of infected individuals can drastically curtail virus spread and limit outbreaks. However, during the early stages of global transmission, point-of-care diagnostics were largely unavailable and continue to remain difficult to procure, greatly inhibiting public health efforts to mitigate spread. Furthermore, the most prevalent testing kits rely on reagent- and time-intensive protocols to detect viral RNA, preventing rapid and cost-effective diagnosis. Therefore the development of an extensive toolkit for point-of-care diagnostics that is expeditiously adaptable to new emerging pathogens is of critical public health importance. Recently, a number of novel CRISPR-based diagnostics have been developed to detect COVID-19. Herein, we outline the development of a CRISPR-based nucleic acid molecular diagnostic utilizing a Cas13d ribonuclease derived from Ruminococcus flavefaciens (CasRx) to detect SARS-CoV-2, an approach we term SENSR (Sensitive Enzymatic Nucleic-acid Sequence Reporter). We demonstrate SENSR robustly detects SARS-CoV-2 sequences in both synthetic and patient-derived samples by lateral flow and fluorescence, thus expanding the available point-of-care diagnostics to combat current and future pandemics.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "STEPHEN J ELLEDGE", - "author_inst": "Harvard Medical School" + "author_name": "Daniel J Brogan", + "author_inst": "UCSD" + }, + { + "author_name": "Duverney Chaverra-Rodriguez", + "author_inst": "UCSD" + }, + { + "author_name": "Calvin P Lin", + "author_inst": "UCSD" + }, + { + "author_name": "Andrea L Smidler", + "author_inst": "UCSD" + }, + { + "author_name": "Ting Yang", + "author_inst": "UCSD" + }, + { + "author_name": "Lenissa M Alcantara", + "author_inst": "UCSD" + }, + { + "author_name": "Igor Antoshechkin", + "author_inst": "Caltech" + }, + { + "author_name": "Junru Liu", + "author_inst": "UCSD" + }, + { + "author_name": "Robyn R Raban", + "author_inst": "UCSD" + }, + { + "author_name": "Pedro Belda-ferre", + "author_inst": "UCSD" + }, + { + "author_name": "Rob Knight", + "author_inst": "UCSD" + }, + { + "author_name": "Elizabeth A Komives", + "author_inst": "Ucsd" + }, + { + "author_name": "Omar S. Akbari", + "author_inst": "UCSD" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.10.14.20212662", @@ -1102188,75 +1102300,23 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.16.20213850", - "rel_title": "Field evaluation of a rapid antigen test (Panbio COVID-19 Ag Rapid Test Device) for the diagnosis of COVID-19 in primary healthcare centers", + "rel_doi": "10.1101/2020.10.16.20213835", + "rel_title": "A Study on the Effects of Containment Policies and Vaccination on the Spread of SARS-CoV-2", "rel_date": "2020-10-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.16.20213850", - "rel_abs": "We evaluated the Panbio COVID-19 AG Rapid Test Device (RAD) for the diagnosis of COVID-19 in symptomatic patients attended in primary healthcare centers (n=412). Overall specificity and sensitivity of RAD was 100% and 79.6%, respectively, taking RT-PCR as the reference. SARS-CoV-2 could not be cultured from specimens yielding RT-PCR+/RAD- results.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.16.20213835", + "rel_abs": "This paper presents a method to predict the spread of the SARS-CoV-2 in a population with a known age-structure, and then, to quantify the effects of various containment policies, including those policies that affect each age-group differently. The model itself is a compartmental model in which each compartment is divided into a number of age-groups. The parameters of the model are estimated using an optimisation scheme and some known results from the theory of monotone systems such that the model output agrees with some collected data on the spread of SARS-CoV-2.\n\nTo highlight the strengths of this framework, a few case studies are presented in which different populations are subjected to different containment strategies. They include cases in which the containment policies switch between scenarios with different levels of severity. Then a case study on herd immunity due to vaccination is presented. And then it is shown how we can use this framework to optimally distribute a limited number of vaccine units in a given population to maximise their impact and reduce the total number of infectious individuals.\n\nMSC subclass92C60, 92C50", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Eliseo Albert", - "author_inst": "Microbiology Service, Hospital Clinico Universitario, INCLIVA Research Institute, Valencia, Spain." - }, - { - "author_name": "Ignacio Torres", - "author_inst": "Microbiology Service, Hospital Clinico Universitario, INCLIVA Research Institute, Valencia, Spain." - }, - { - "author_name": "Felipe Bueno", - "author_inst": "Microbiology Service, Hospital Clinico Universitario, INCLIVA Research Institute, Valencia, Spain." - }, - { - "author_name": "Dixie Huntley", - "author_inst": "Microbiology Service, Hospital Clinico Universitario, INCLIVA Research Institute, Valencia, Spain." - }, - { - "author_name": "Estefania Moya", - "author_inst": "Instituto Valenciano de Microbiologia, Betera, Valencia, Spain." - }, - { - "author_name": "Miguel Angel Fernandez-Funtes", - "author_inst": "Instituto Valenciano de Microbiologia, Betera, Valencia, Spain." - }, - { - "author_name": "Mireia Martinez", - "author_inst": "Microbiology Service, Hospital Clinico Universitario, INCLIVA Research Institute, Valencia, Spain." - }, - { - "author_name": "Sandrine Poujois", - "author_inst": "Microbiology Service, Hospital Clinico Universitario, INCLIVA Research Institute, Valencia, Spain." - }, - { - "author_name": "Lorena Forque", - "author_inst": "Microbiology Service, Hospital Clinico Universitario, INCLIVA Research Institute, Valencia, Spain." - }, - { - "author_name": "Arantxa Valdivia", - "author_inst": "Microbiology Service, Hospital Clinico Universitario, INCLIVA Research Institute, Valencia, Spain." - }, - { - "author_name": "Carlos Solano de la Asuncion", - "author_inst": "Microbiology Service, Hospital Clinico Universitario, INCLIVA Research Institute, Valencia, Spain." - }, - { - "author_name": "Josep Ferrer", - "author_inst": "Microbiology Service, Hospital Clinico Universitario, INCLIVA Research Institute, Valencia, Spain." - }, - { - "author_name": "Javier Colomina", - "author_inst": "Microbiology Service, Hospital Clinico Universitario, INCLIVA Research Institute, Valencia, Spain." - }, - { - "author_name": "David Navarro", - "author_inst": "Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." + "author_name": "Vahid Bokharaie", + "author_inst": "Max Planck Institute" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.10.17.20214312", @@ -1103766,23 +1103826,51 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.10.20.347641", - "rel_title": "Viral surface geometry shapes influenza and coronavirus spike evolution", - "rel_date": "2020-10-20", + "rel_doi": "10.1101/2020.10.19.344911", + "rel_title": "SARS-CoV-2 genome-wide mapping of CD8 T cell recognition reveals strong immunodominance and substantial CD8 T cell activation in COVID-19 patients", + "rel_date": "2020-10-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.20.347641", - "rel_abs": "The evolution of circulating viruses is shaped by their need to evade antibody response, which mainly targets the glycoprotein (spike). However, not all antigenic sites are targeted equally by antibodies, leading to complex immunodominance patterns. We used 3D computational models to estimate antibody pressure on the seasonal influenza H1N1 and SARS spikes. Analyzing publically available sequences, we show that antibody pressure, through the geometrical organization of spikes on the viral surface, shaped their mutability. Studying the mutability patterns of SARS-CoV-2 and the 2009 H1N1 pandemic spikes, we find that they are not predominantly shaped by antibody pressure. However, for SARS-CoV-2, we find that over time, it acquired mutations at antibody-accessible positions, which could indicate possible escape as define by our model. We offer a geometry-based approach to predict and rank the probability of surface resides of SARS-CoV-2 spike to acquire antibody escaping mutations.", - "rel_num_authors": 1, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.19.344911", + "rel_abs": "To understand the CD8+ T cell immunity related to viral protection and disease severity in COVID-19, we evaluated the complete SARS-CoV-2 genome (3141 MHC-I binding peptides) to identify immunogenic T cell epitopes, and determine the level of CD8+ T cell involvement using DNA-barcoded peptide-major histocompatibility complex (pMHC) multimers. COVID-19 patients showed strong T cell responses, with up to 25% of all CD8+ lymphocytes specific to SARS-CoV-2-derived immunodominant epitopes, derived from ORF1 (open reading frame 1), ORF3, and Nucleocapsid (N) protein. A strong signature of T cell activation was observed in COVID-19 patients, while no T cell activation was seen in the non-exposed and high exposure risk healthy donors. Interestingly, patients with severe disease displayed the largest T cell populations with a strong activation profile. These results will have important implications for understanding the T cell immunity to SARS-CoV-2 infection, and how T cell immunity might influence disease development.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Assaf Amitai", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Sunil Kumar Saini", + "author_inst": "Department of Health Technology, Section of Experimental and Translational Immunology, Technical University of Denmark, Kongens Lyngby, Denmark." + }, + { + "author_name": "Ditte Stampe Hersby", + "author_inst": "Department of Haematology, Herlev Hospital, Copenhagen University Hospital, Herlev, Denmark" + }, + { + "author_name": "Tripti Tamhane", + "author_inst": "Department of Health Technology, Section of Experimental and Translational Immunology, Technical University of Denmark, Kongens Lyngby, Denmark" + }, + { + "author_name": "Helle Rus Povlsen", + "author_inst": "Department of Health Technology, Section of Bioinformatics, Technical University of Denmark, Kongens Lyngby, Denmark" + }, + { + "author_name": "Susana Patricia Amaya Hernandez", + "author_inst": "Department of Health Technology, Section of Experimental and Translational Immunology, Technical University of Denmark, Kongens Lyngby, Denmark" + }, + { + "author_name": "Morten Nielsen", + "author_inst": "Department of Health Technology, Section of Bioinformatics, Technical University of Denmark, Kongens Lyngby, Denmark" + }, + { + "author_name": "Anne Ortved Gang", + "author_inst": "Department of Haematology, Herlev Hospital, Copenhagen University Hospital, Herlev, Denmark" + }, + { + "author_name": "Sine Reker Hadrup", + "author_inst": "Department of Health Technology, Section of Experimental and Translational Immunology, Technical University of Denmark, Kongens Lyngby, Denmark" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", - "category": "biophysics" + "category": "immunology" }, { "rel_doi": "10.1101/2020.10.15.20208041", @@ -1105371,43 +1105459,47 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.10.12.336644", - "rel_title": "Ongoing Adaptive Evolution and Globalization of Sars-Cov-2", + "rel_doi": "10.1101/2020.10.14.20212381", + "rel_title": "shinyCurves, a shiny web application to analyse multisource qPCR amplification data: a COVID 19 case study", "rel_date": "2020-10-16", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.12.336644", - "rel_abs": "Understanding the trends in SARS-CoV-2 evolution is paramount to control the COVID- 19 pandemic. We analyzed more than 300,000 high quality genome sequences of SARS-CoV-2 variants available as of January 2021. The results show that the ongoing evolution of SARS-CoV-2 during the pandemic is characterized primarily by purifying selection, but a small set of sites appear to evolve under positive selection. The receptor-binding domain of the spike protein and the nuclear localization signal (NLS) associated region of the nucleocapsid protein are enriched with positively selected amino acid replacements. These replacements form a strongly connected network of apparent epistatic interactions and are signatures of major partitions in the SARS-CoV-2 phylogeny. Virus diversity within each geographic region has been steadily growing for the entirety of the pandemic, but analysis of the phylogenetic distances between pairs of regions reveals four distinct periods based on global partitioning of the tree and the emergence of key mutations. The initial period of rapid diversification into region- specific phylogenies that ended in February 2020 was followed by a major extinction event and global homogenization concomitant with the spread of D614G in the spike protein, ending in March 2020. The NLS associated variants across multiple partitions rose to global prominence in March-July, during a period of stasis in terms of inter- regional diversity. Finally, beginning July 2020, multiple mutations, some of which have since been demonstrated to enable antibody evasion, began to emerge associated with ongoing regional diversification, which might be indicative of speciation.\n\nSignificanceUnderstanding the ongoing evolution of SARS-CoV-2 is essential to control and ultimately end the pandemic. We analyzed more than 300,000 SARS-CoV-2 genomes available as of January 2021 and demonstrate adaptive evolution of the virus that affects, primarily, multiple sites in the spike and nucleocapsid protein. Selection appears to act on combinations of mutations in these and other SARS-CoV-2 genes. Evolution of the virus is accompanied by ongoing adaptive diversification within and between geographic regions. This diversification could substantially prolong the pandemic and the vaccination campaign, in which variant-specific vaccines are likely to be required.", - "rel_num_authors": 6, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.14.20212381", + "rel_abs": "SummaryQuantitative, reverse transcription polymerase chain reaction (qRT-PCR) has been the gold-standard tool for viral detection during the SARS-CoV-2 pandemic. However, the desperate rush for a quick diagnosis led the use of very different types of machines and proprietary software, leading to an unbearable complexity of data analysis with a limited parameter setup. Here, we present shinyCurves, a shiny web application created to analyse multisource qPCR amplification data from independent multi-plate format. Furthermore, our automated system allows the classification of the results as well as the plot of both amplification and melting curves. Altogether, our web application is an automated qPCR analysis resource available to the research community.\n\nAvailabilityThe shinyCurves web application to analyze multisource qPCR amplification data is publicly available under CC license (CC BY-NC-SA 4.0) at https://biosol.shinyapps.io/shinycurves/ and https://github.com/biosol/shinyCurves.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Nash D Rochman", - "author_inst": "NIH" + "author_name": "Sonia Olaechea-Lazaro", + "author_inst": "University of the Basque Country (UPV/EHU)" }, { - "author_name": "Yuri I. Wolf", - "author_inst": "NCBI/NLM/NIH" + "author_name": "Iraia Garcia-Santisteban", + "author_inst": "University of the Basque Country (UPV/EHU)" }, { - "author_name": "Guilhem Faure", - "author_inst": "Broad Institute of MIT and Harvard" + "author_name": "Jose Ramon Pineda", + "author_inst": "University of the Basque Country (UPV/EHU)" }, { - "author_name": "Pascal Mutz", - "author_inst": "NCBI/NIH" + "author_name": "Iker Badiola", + "author_inst": "University of the Basque Country (UPV/EHU)" }, { - "author_name": "Feng Zhang", - "author_inst": "Broad Institute of MIT and Harvard" + "author_name": "Santos Alonso", + "author_inst": "University of the Basque Country (UPV/EHU)" }, { - "author_name": "Eugene V. Koonin", - "author_inst": "NIH" + "author_name": "Jose Ramon Bilbao", + "author_inst": "University of the Basque Country (UPV/EHU)" + }, + { + "author_name": "Nora Fernandez-Jimenez", + "author_inst": "University of the Basque Country (UPV/EHU)" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "type": "PUBLISHAHEADOFPRINT", + "category": "health informatics" }, { "rel_doi": "10.1101/2020.10.14.20212449", @@ -1107221,43 +1107313,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.13.20211771", - "rel_title": "Thermal Effect On The Persistence Of SARS-CoV2 Egyptian Isolates As Measured By Quantitative RT-PCR", + "rel_doi": "10.1101/2020.10.13.20211888", + "rel_title": "Knowledge and practices towards COVID-19 among Palestinians during the COVID-19 outbreak: A second round cross-sectional survey", "rel_date": "2020-10-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.13.20211771", - "rel_abs": "Coronavirus pandemic that caused by severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) appeared in China in 2019 then spread all over the world .COVID-19 firstly appeared in Egypt in Feb 2020. Studies on the thermal stability of the virus is crucial proper specimens transportation for molecular study. Oropharyngeal swabs were taken from recently infected military people with COVID-19 from Egypt during April 2020. Samples were aliquoted and the thermal stability of the virus was measured using quantitative real Time RT-PCR for samples treated at different temperature ranges from 20 {degrees}C to 70 {degrees}C for 2,4and 6 hours. Results shown that inactivation of the virus and significant reduction in the {Delta}Cq values begin at 40 {degrees}C/4h. Complete virus inactivation and loss of {Delta}Cq values were seen at 50 {degrees}C/6h and 60 {degrees}C. Tested samples showed no significant difference in thermal stability at any temp/time combinations tested.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.13.20211888", + "rel_abs": "Coronavirus disease 2019 (COVID-19) is a highly transmissible illness that spreads rapidly through human-to-human transmission. To assess the knowledge and practices of Palestinians towards COVID-19 after the ease of movement restrictions, we collected data from Palestinian adults between June 15th and June 30th 2020. The participants pool represented a stratified sample of 1355 adults from Palestinian households across 11 governorates in the West Bank. The questionnaire included 7 demographic questions, 13 questions about participants knowledge and awareness of COVID-19, and 4 questions regarding the participants safety measures that had been taken in the last three months. Based on the results of this study, we conclude that the majority of participants have a good knowledge about COVID-19, but were not adequately committed to the infection control measures necessary to protect themselves and others. The findings may provide valuable feedback to lawmakers and health administrators to prevent the spread of the epidemic.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Mohamed Gomaa Seadawy", - "author_inst": "MCL" - }, - { - "author_name": "Ahmed Fawzy Gad", - "author_inst": "MCL" - }, - { - "author_name": "Bassem Elsayed Harty", - "author_inst": "MCL" + "author_name": "Nouar Qutob", + "author_inst": "arab american university" }, { - "author_name": "Mostfa Fatoh Elhoseiny", - "author_inst": "MCL" + "author_name": "Faisal Awartani", + "author_inst": "Arab American University" }, { - "author_name": "Mohamed Desoky Shamel", - "author_inst": "MCL" + "author_name": "Mohammad Asia", + "author_inst": "Arab American University" }, { - "author_name": "Yousef Adel Soliman", - "author_inst": "CLEVB" + "author_name": "Imad Abu Khader", + "author_inst": "Arab American University" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.10.14.20090985", @@ -1108635,79 +1108719,115 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.12.20211227", - "rel_title": "High and increasing prevalence of SARS-CoV-2 swab positivity in England during end September beginning October 2020: REACT-1 round 5 updated report", + "rel_doi": "10.1101/2020.10.12.20209809", + "rel_title": "Derivation and validation of a triage tool for acutely ill adults with suspected COVID-19: The PRIEST observational cohort study", "rel_date": "2020-10-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.12.20211227", - "rel_abs": "BackgroundREACT-1 is quantifying prevalence of SARS-CoV-2 infection among random samples of the population in England based on PCR testing of self-administered nose and throat swabs. Here we report results from the fifth round of observations for swabs collected from the 18th September to 5th October 2020. This report updates and should be read alongside our round 5 interim report.\n\nMethodsRepresentative samples of the population aged 5 years and over in England with sample size ranging from 120,000 to 175,000 people at each round. Prevalence of PCR-confirmed SARS-CoV-2 infection, estimation of reproduction number (R) and time trends between and within rounds using exponential growth or decay models.\n\nResults175,000 volunteers tested across England between 18th September and 5th October. Findings show a national prevalence of 0.60% (95% confidence interval 0.55%, 0.71%) and doubling of the virus every 29 (17, 84) days in England corresponding to an estimated national R of 1.16 (1.05, 1.27). These results correspond to 1 in 170 people currently swab-positive for the virus and approximately 45,000 new infections each day. At regional level, the highest prevalence is in the North West, Yorkshire and The Humber and the North East with strongest regional growth in North West, Yorkshire and The Humber and West Midlands.\n\nConclusionRapid growth has led to high prevalence of SARS-CoV-2 virus in England, with highest rates in the North of England. Prevalence has increased in all age groups, including those at highest risk. Improved compliance with existing policy and, as necessary, additional interventions are required to control the spread of SARS-CoV-2 in the community and limit the numbers of hospital admissions and deaths from COVID-19.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.12.20209809", + "rel_abs": "ObjectivesWe aimed to derive and validate a triage tool, based on clinical assessment alone, for predicting adverse outcome in acutely ill adults with suspected COVID-19 infection.\n\nMethodsWe undertook a mixed prospective and retrospective observational cohort study in 70 emergency departments across the United Kingdom (UK). We collected presenting data from 22445 people attending with suspected COVID-19 between 26 March 2020 and 28 May 2020. The primary outcome was death or organ support (respiratory, cardiovascular, or renal) by record review at 30 days. We split the cohort into derivation and validation sets, developed a clinical score based on the coefficients from multivariable analysis using the derivation set, and the estimated discriminant performance using the validation set.\n\nResultsWe analysed 11773 derivation and 9118 validation cases. Multivariable analysis identified that age, sex, respiratory rate, systolic blood pressure, oxygen saturation/inspired oxygen ratio, performance status, consciousness, history of renal impairment, and respiratory distress were retained in analyses restricted to the ten or fewer predictors. We used findings from multivariable analysis and clinical judgement to develop a score based on the NEWS2 score, age, sex, and performance status. This had a c-statistic of 0.80 (95% confidence interval 0.79-0.81) in the validation cohort and predicted adverse outcome with sensitivity 0.98 (0.97-0.98) and specificity 0.34 (0.34-0.35) for scores above four points.\n\nConclusionA clinical score based on NEWS2, age, sex, and performance status predicts adverse outcome with good discrimination in adults with suspected COVID-19 and can be used to support decision-making in emergency care.\n\nRegistrationISRCTN registry, ISRCTN28342533, http://www.isrctn.com/ISRCTN28342533", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Steven Riley", - "author_inst": "Dept Inf Dis Epi, Imperial College" + "author_name": "Steve Goodacre", + "author_inst": "University of Sheffield" }, { - "author_name": "Kylie E. C. Ainslie", - "author_inst": "Imperial College London" + "author_name": "Benjamin Thomas", + "author_inst": "University of Sheffield" }, { - "author_name": "Oliver Eales", - "author_inst": "Imperial College London" + "author_name": "Laura Sutton", + "author_inst": "University of Sheffield" }, { - "author_name": "Caroline E Walters", - "author_inst": "Imperial College London" + "author_name": "Matthew Burnsall", + "author_inst": "University of Sheffield" }, { - "author_name": "Haowei Wang", - "author_inst": "Imperial College London" + "author_name": "Ellen Lee", + "author_inst": "University of Sheffield" }, { - "author_name": "Christina J Atchison", - "author_inst": "Imperial College London" + "author_name": "Mike Bradburn", + "author_inst": "University of Sheffield" }, { - "author_name": "Claudio Fronterre", - "author_inst": "Lancaster University" + "author_name": "Amanda Loban", + "author_inst": "University of Sheffield" }, { - "author_name": "Peter J Diggle", - "author_inst": "Lancaster University" + "author_name": "Simon Waterhouse", + "author_inst": "University of Sheffield" }, { - "author_name": "Deborah Ashby", - "author_inst": "Imperial College London" + "author_name": "Richard Simmonds", + "author_inst": "University of Sheffield" }, { - "author_name": "Christl A. Donnelly", - "author_inst": "Imperial College London" + "author_name": "Catherine Biggs", + "author_inst": "University of Sheffield" }, { - "author_name": "Graham Cooke", - "author_inst": "Imperial College" + "author_name": "Carl Marincowitz", + "author_inst": "University of Sheffield" }, { - "author_name": "Wendy Barclay", - "author_inst": "Imperial College London" + "author_name": "Jose Schutter", + "author_inst": "University of Sheffield" }, { - "author_name": "Helen Ward", - "author_inst": "Imperial College London" + "author_name": "Sarah Connelly", + "author_inst": "University of Sheffield" }, { - "author_name": "Ara Darzi", - "author_inst": "Imperial College London" + "author_name": "Elena Sheldon", + "author_inst": "University of Sheffield" }, { - "author_name": "Paul Elliott", - "author_inst": "Imperial College London School of Public Health" + "author_name": "Jamie Hall", + "author_inst": "University of Sheffield" + }, + { + "author_name": "Emma Young", + "author_inst": "University of Sheffield" + }, + { + "author_name": "Andrew Bentley", + "author_inst": "Manchester University NHS Foundation Trust" + }, + { + "author_name": "Kirsty Challen", + "author_inst": "Lancashire Teaching Hospitals NHS Foundation Trust" + }, + { + "author_name": "Chris Fitzsimmons", + "author_inst": "Sheffield Children's NHS Foundation Trust" + }, + { + "author_name": "Tim Harris", + "author_inst": "Barts Health NHS Trust" + }, + { + "author_name": "Fiona Lecky", + "author_inst": "University of Sheffield" + }, + { + "author_name": "Andrew Lee", + "author_inst": "University of Sheffield" + }, + { + "author_name": "Ian Maconochie", + "author_inst": "Imperial College Healthcare NHS Trust" + }, + { + "author_name": "Darren Walter", + "author_inst": "Manchester University NHS Foundation Trust" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "emergency medicine" }, { "rel_doi": "10.1101/2020.10.11.20211045", @@ -1110269,29 +1110389,41 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.11.20211037", - "rel_title": "Symptom-based testing in a compartmental model of COVID-19", + "rel_doi": "10.1101/2020.10.13.20211813", + "rel_title": "Precautionary breaks: planned, limited duration circuit breaks to control the prevalence of COVID-19", "rel_date": "2020-10-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.11.20211037", - "rel_abs": "Testing and isolation of cases is an important component of our strategies to fight SARS-CoV-2. In this work, we consider a compartmental model for COVID-19 including a nonlinear term representing symptom-based testing. We analyze how the considered clinical spectrum of symptoms and the testing rate affect the outcome and the severity of the outbreak.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.13.20211813", + "rel_abs": "The COVID-19 pandemic in the UK has been characterised by periods of exponential growth and decline, as different non-pharmaceutical interventions (NPIs) are brought into play. During the early uncontrolled phase of the outbreak (early March 2020) there was a period of prolonged exponential growth with epidemiological observations such as hospitalisation doubling every 3-4 days (growth rate r {approx} 0.2). The enforcement of strict lockdown measures led to a noticeable decline in all epidemic quantities (r {approx} -0.06) that slowed during the summer as control measures were relaxed (r {approx} -0.02). Since August, infections, hospitalisations and deaths have been rising (precise estimation of the current growth rate is difficult due to extreme regional heterogeneity and temporal lags between the different epidemiological observations) and various NPIs have been applied locally throughout the UK in response.\n\nControlling any rise in infection is a compromise between public health and societal costs, with more stringent NPIs reducing cases but damaging the economy and restricting freedoms. Currently, NPI imposition is made in response to the epidemiological state, are of indefinite length and are often imposed at short notice, greatly increasing the negative impact. An alternative approach is to consider planned, limited duration periods of strict NPIs aiming to purposefully reduce prevalence before such emergency NPIs are required. These \"precautionary breaks\" may offer a means of keeping control of the epidemic, while their fixed duration and the forewarning may limit their society impact. Here, using simple analysis and age-structured models matched to the unfolding UK epidemic, we investigate the action of precautionary breaks. In particular we consider their impact on the prevalence of infection, as well as the total number of predicted hospitalisations and deaths. We find that precautionary breaks provide the biggest gains when the growth rate is low, but offer a much needed brake on increasing infection when the growth rate is higher, potentially allowing other measures (such as contact tracing) to regain control.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Ferenc A. Bartha", - "author_inst": "Bolyai Institute, University of Szeged" + "author_name": "Matt J Keeling", + "author_inst": "University of Warwick" }, { - "author_name": "J\u00e1nos Karsai", - "author_inst": "Bolyai Institute, University of Szeged" + "author_name": "Glen Guyver-Fletcher", + "author_inst": "University of Warwick" }, { - "author_name": "Tam\u00e1s Tekeli", - "author_inst": "Bolyai Institute, University of Szeged" + "author_name": "Alexander Holmes", + "author_inst": "University of Warwick" }, { - "author_name": "Gergely R\u00f6st", - "author_inst": "Bolyai Institute, University of Szeged" + "author_name": "Louise J Dyson", + "author_inst": "University of Warwick" + }, + { + "author_name": "Michael Tildesley", + "author_inst": "University of Warwick" + }, + { + "author_name": "Edward M Hill", + "author_inst": "University of Warwick" + }, + { + "author_name": "Graham F Medley", + "author_inst": "London School of Hygiene and Tropical Medicine" } ], "version": "1", @@ -1111987,43 +1112119,35 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.09.20210351", - "rel_title": "Estimating COVID-19 cases and outbreaks on-stream through phone-calls", + "rel_doi": "10.1101/2020.10.11.20210625", + "rel_title": "Mental health service activity during COVID-19 lockdown among individuals with learning disabilities: South London and Maudsley data on services and mortality from January to July 2020", "rel_date": "2020-10-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.09.20210351", - "rel_abs": "One of the main problems in controlling COVID-19 epidemic spread is the delay in confirming cases. Having information on changes in the epidemic evolution or outbreaks rise before lab-confirmation is crucial in decision making for Public Health policies. We present an algorithm to estimate on-stream the number of COVID-19 cases using the data from telephone calls to a COVID-line. By modeling the calls as background (proportional to population) plus signal (proportional to infected), we fit the calls in Province of Buenos Aires (Argentina) with coefficient of determination R2 > 0.85. This result allows us to estimate the number of cases given the number of calls from a specific district, days before the lab results are available. We validate the algorithm with real data. We show how to use the algorithm to track on-stream the epidemic, and present the Early Outbreak Alarm to detect outbreaks in advance to lab results. One key point in the developed algorithm is a detailed track of the uncertainties in the estimations, since the alarm uses the significance of the observables as a main indicator to detect an anomaly. We present the details of the explicit example in Villa Azul (Quilmes) where this tool resulted crucial to control an outbreak on time. The presented tools have been designed in urgency with the available data at the time of the development, and therefore have their limitations which we describe and discuss. We consider possible improvements on the tools, many of which are currently under development.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.11.20210625", + "rel_abs": "The lockdown and social distancing policy imposed due to the COVID-19 pandemic is likely to have had a widespread impact on mental healthcare service provision and use. Previous reports from the South London and Maudsley NHS Trust (SLaM; a large mental health service provider for 1.2m residents in South London) highlighted a shift to virtual contacts among those accessing community mental health and home treatment teams and an increase in deaths over the pandemics first wave. However, there is a need to quantify this for individuals with particular vulnerabilities, including those with learning disabilities and other neurodevelopmental disorders. Taking advantage of the Clinical Record Interactive Search (CRIS) data resource with 24-hourly updates of electronic mental health records data, this paper describes daily caseloads and contact numbers (face-to-face and virtual) for individuals with potential neurodevelopmental disorders across community, specialist, crisis and inpatient services. The report focussed on the period 1st January to 31st July 2020. We also report on daily accepted and discharged trust referrals, total trust caseloads and daily inpatient admissions and discharges for individuals with potential neurodevelopmental disorders. In addition, daily deaths are described for all current and previous SLaM service users with potential neurodevelopmental disorders over this period. In summary, comparing periods before and after 16th March 2020 there was a shift from face-to-face contacts to virtual contacts across all teams. The largest declines in caseloads and total contacts were seen in Home Treatment Team, Liaison/A&E and Older Adult teams. Reduced accepted referrals and inpatient admissions were observed and there was an 103% increase in average daily deaths in the period after 16th March, compared to the period 1st January to 15th March (or a 282% increase if the 2-month period from 16th March to 15th May was considered alone).", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Ezequiel Alvarez", - "author_inst": "University of San Martin" - }, - { - "author_name": "Franco Marsico", - "author_inst": "Health Ministry of Buenos Aires Province, Argentina" - }, - { - "author_name": "Nicolas Kreplak", - "author_inst": "Health Ministry of Buenos Aires Province, Argentina" + "author_name": "Evangelia Martin", + "author_inst": "King's College London" }, { - "author_name": "Senastian Crespo", - "author_inst": "Health Ministry of Buenos Aires Province, Argentina" + "author_name": "Eleanor Nuzum", + "author_inst": "King's College London" }, { - "author_name": "Daniela Obando", - "author_inst": "Health Ministry of Buenos Aires Province, Argentina" + "author_name": "Matthew Broadbent", + "author_inst": "South London and Maudsley NHS Foundation Trust" }, { - "author_name": "Enio Garcia", - "author_inst": "Health Ministry of Buenos Aires Province, Argentina" + "author_name": "Robert Stewart", + "author_inst": "King's College London" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2020.10.09.20210039", @@ -1114144,47 +1114268,59 @@ "category": "hiv aids" }, { - "rel_doi": "10.1101/2020.10.08.20208751", - "rel_title": "Characteristics and clinical features of SARS-CoV-2 infections among ambulatory and hospitalized children and adolescents in an integrated health care system in Tennessee", + "rel_doi": "10.1101/2020.10.08.20209692", + "rel_title": "A rapid and cost-effective multiplex ARMS-PCR method for the simultaneous genotyping of the circulating SARS-CoV-2 phylogenetic clades", "rel_date": "2020-10-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.08.20208751", - "rel_abs": "BackgroundLittle is known regarding the full spectrum of illness among children with SARS-CoV-2 infection across ambulatory and inpatient settings.\n\nMethodsActive surveillance was performed for SARS-CoV-2 by polymerase chain reaction among asymptomatic and symptomatic individuals in a quaternary care academic hospital laboratory in Tennessee from March 12-July 17, 2020. For symptomatic patients [≤]18 years of age, we performed phone follow-up and medical record review to obtain sociodemographic and clinical data on days 2, 7, and 30 after diagnosis and on day 30 for asymptomatic patients [≤]18 years. Daily and 7-day average test positivity frequencies were calculated for children and adults beginning April 26, 2020.\n\nResultsSARS-CoV-2 was detected in 531/10327 (5.1%) specimens from patients [≤]18 years, including 46/5752 (0.8%) asymptomatic and 485/4575 (10.6%) specimens from 459 unique symptomatic children. Cough (51%), fever (42%), and headache (41%) were the most common symptoms associated with SARS-CoV-2 infection. SARS-CoV-2-related hospitalization was uncommon (18/459 children; 4%); no children with SARS-CoV-2 infection during the study period required intensive care unit admission. Symptom resolution occurred by follow-up day 2 in 192/459 (42%), by day 7 in 332/459 (72%), and by day 30 in 373/396 (94%). The number of cases and percent positivity rose in late June and July in all ages.\n\nConclusionsIn an integrated healthcare network, most pediatric SARS-CoV-2 infections were mild, brief, and rarely required hospital admission, despite increasing cases as community response measures were relaxed.\n\nKey pointsIn an integrated healthcare network in the Southeastern United States, symptomatic SARS-CoV-2 infection in children was generally mild, resolved rapidly, and rarely required hospitalization. Cases increased in children and adults as community mitigation measures became less restrictive.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.08.20209692", + "rel_abs": "Tracing the globally circulating SARS-CoV-2 mutants is essential for the outbreak alerts and far-reaching epidemiological surveillance. The available technique to identify the phylogenetic clades through high-throughput sequencing is costly, time-consuming, and labor-intensive that hinders the viral genotyping in low-income countries. Here, we propose a rapid, simple and cost-effective amplification-refractory mutation system (ARMS)-based multiplex reverse-transcriptase PCR assay to identify six distinct phylogenetic clades: S, L, V, G, GH, and GR. This approach is applied on 24 COVID-19 positive samples as confirmed by CDC approved real-time PCR assay for SARS-CoV-2. Our multiplex PCR is designed in a mutually exclusive way to identify V-S and G-GH-GR clade variants separately. The pentaplex assay included all five variants and the quadruplex comprised of the triplex variants alongside either V or S clade mutations that created two separate subsets. The procedure was optimized in the primer concentration (0.2-0.6 {micro}M) and annealing temperature (56-60{degrees}C) of PCR using 3-5 ng/{micro}l cDNA template synthesized upon random- and oligo(dT)-primer based reverse transcription. The different primer concentration for the triplex and quadruplex adjusted to different strengths ensured an even amplification with a maximum resolution of all targeted amplicons. The targeted Sanger sequencing further confirmed the presence of the clade-featured mutations with another set of our designed primers. This multiplex ARMS-PCR assay is sample, cost-effective, and convenient that can successfully discriminate the circulating phylogenetic clades of SARS-CoV-2.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Leigh M Howard", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Md. Tanvir Islam", + "author_inst": "Department of Microbiology, Jashore University of Science and Technology, Jashore, Bangladesh" }, { - "author_name": "Kathryn Garguilo", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "A. S. M. Rubayet Ul Alam", + "author_inst": "Department of Microbiology, Jashore University of Science and Technology, Jashore, Bangladesh" }, { - "author_name": "Jessica Gillon", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Najmuj Sakib", + "author_inst": "Department of Microbiology, Jashore University of Science and Technology, Jashore, Bangladesh" }, { - "author_name": "Adam C Seegmiller", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Md. Shazid Hasan", + "author_inst": "Department of Microbiology, Jashore University of Science and Technology, Jashore, Bangladesh" }, { - "author_name": "Jonathan E Schmitz", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Tanay Chakrovarty", + "author_inst": "Department of Microbiology, Jashore University of Science and Technology, Jashore, Bangladesh" }, { - "author_name": "Steven A Webber", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Md. Tawyabur", + "author_inst": "Department of Microbiology, Jashore University of Science and Technology, Jashore, Bangladesh" }, { - "author_name": "Ritu Banerjee", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Ovinu Kibria Islam", + "author_inst": "Department of Microbiology, Jashore University of Science and Technology, Jashore, Bangladesh" + }, + { + "author_name": "Hassan M. Al-Emran", + "author_inst": "Department of Biomedical Engineering, Jashore University of Science and Technology, Jashore, Bangladesh" + }, + { + "author_name": "Iqbal Kabir Jahid", + "author_inst": "Department of Microbiology, Jashore University of Science and Technology, Jashore, Bangladesh" + }, + { + "author_name": "M. Anwar Hossain", + "author_inst": "Vice-Chancellor, Jashore University of Science and Technology, Jashore, Bangladesh" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.10.08.20204750", @@ -1115761,27 +1115897,59 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.10.09.333948", - "rel_title": "The effect of salt on the dynamics of CoV-2 RBD at ACE2", + "rel_doi": "10.1101/2020.10.07.20208660", + "rel_title": "Estimated Seroprevalence of SARS-CoV-2 Antibodies Among Adults in Orange County, California", "rel_date": "2020-10-12", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.09.333948", - "rel_abs": "In this article, we investigate the effect of electrolytes on the stability of the complex between the coronavirus type 2 spike protein receptor domain (CoV-2 RBD) and ACE2, which plays an important role in the activation cascade at the viral entry of CoV-2 into human cells. At the cellular surface, electrolytes play an important role, especially in the interaction of proteins near the membrane surface. Additionally, the binding interface of the CoV-2 RBD - ACE2 complex is highly hydrophilic. We simulated the CoV-2 RBD - ACE2 complex at varying salt concentrations over the concentration range from 0.03 M to 0.3 M of calcium and sodium chloride over an individual simulation length of 750 ns in 9 independent simulations (6.75 {micro}s total). We observe that the CoV-2 RBD - ACE2 complex is stabilized independent of the salt concentration. We identify a strong negative electrostatic potential at the N-terminal part of CoV-2 RBD and we find that CoV-2 RBD binds even stronger at higher salt concentrations. We observe that the dynamics of the N-terminal part of CoV-2 RBD stabilize the protein complex leading to strong collective motions and a stable interface between CoV-2 RBD and ACE2. We state that the sequence of CoV-2 RBD might be optimized for a strong binding to ACE2 at varying salt concentrations at the cellular surface, which acts as a key component in the activation of CoV-2 for its viral entry.\n\nSIGNIFICANCEA novel coronavirus, coronavirus type 2 (CoV-2), was identified as primary cause for a worldwide pandemic of the severe acute respiratory syndrome (SARS CoV-2). The CoV-2 spike protein is a major target for the development of a vaccine and potential strategies to inhibit the viral entry into human cells. At the cellular surface, CoV-2 activation involves the direct interaction between ACE2 and CoV-2 RBD. At the cellular surface, electrolytes play an important role, especially in the interaction of proteins near the membrane surface. We thus investigate the effect of ion conditions on the interaction of the CoV-2 RBD - ACE2 complex and find stabilizing effects. We speculate that CoV-2 RBD is optimized for strong binding to ACE2 at varying salt concentrations.", - "rel_num_authors": 2, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.07.20208660", + "rel_abs": "BackgroundClinic-based estimates of SARS-CoV-2 may considerably underestimate the total number of infections. Access to testing in the US has been heterogeneous and symptoms vary widely in infected persons. Public health surveillance efforts and metrics are therefore hampered by underreporting. We set out to provide a minimally biased estimate of SARS-CoV-2 seroprevalence among adults for a large and diverse county (Orange County, CA, population 3.2 million).\n\nMethodsWe implemented a surveillance study that minimizes response bias by recruiting adults to answer a survey without knowledge of later being offered a SARS-CoV-2 test. Several methodologies were used to retrieve a population-representative sample. Participants (n=2,979) visited one of 11 drive-thru test sites from July 10th to August 16th, 2020 (or received an in-home visit) to provide a finger pin-prick sample. We applied a robust SARS-CoV-2 Antigen Microarray technology, which has superior measurement validity relative to FDA-approved tests.\n\nFindingsParticipants include a broad age, gender, racial/ethnic, and income representation. Adjusted seroprevalence of SARS-CoV-2 infection was 11.5% (95% CI: 10.5% to 12.4%). Formal bias analyses produced similar results. Prevalence was elevated among Hispanics (vs. other non-Hispanic: prevalence ratio [PR]= 1.47, 95% CI: 1.22 to 1.78) and household income <$50,000 (vs. >$100,000: PR= 1.42, 95% CI: 1.14 to 1.79).\n\nInterpretationResults from a diverse population using a highly specific and sensitive microarray indicate a SARS-CoV-2 seroprevalence of [~]12 percent. This population-based seroprevalence is seven-fold greater than that using official County statistics. In this region, SARS-CoV-2 also disproportionately affects Hispanic and low-income adults.\n\nFundingOrange County Healthcare Agency", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Emanuel Peter", - "author_inst": "Forschungszentrum J\u00fclich" + "author_name": "Tim-Allen Bruckner", + "author_inst": "Public Health, University of California, Irvine" }, { - "author_name": "Alexander Schug", - "author_inst": "Forschungszentrum J\u00fclich" + "author_name": "Daniel M. Parker", + "author_inst": "Public Health, University of California, Irvine" + }, + { + "author_name": "Scott Bartell", + "author_inst": "Department of Statistics, University of California, Irvine" + }, + { + "author_name": "Veronica Vieira", + "author_inst": "Public Health, University of California, Irvine" + }, + { + "author_name": "Saahir Khan", + "author_inst": "School of Medicine, University of California, Irvine" + }, + { + "author_name": "Andrew Noymer", + "author_inst": "Public Health, University of California, Irvine" + }, + { + "author_name": "Emily Drum", + "author_inst": "Public Health, University of California, Irvine" + }, + { + "author_name": "Bruce Albala", + "author_inst": "Center for Clinical Research, School of Medicine, University of California, Irvine" + }, + { + "author_name": "Matthew Zahn", + "author_inst": "Orange County Health Care Agency" + }, + { + "author_name": "Bernadette Boden-Albala", + "author_inst": "Public Health, University of California, Irvine" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "biophysics" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.10.10.20203034", @@ -1117447,53 +1117615,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.09.20210229", - "rel_title": "Prevalence and Longevity of SARS-CoV-2 Antibodies in Healthcare Workers: A Single Center Study", + "rel_doi": "10.1101/2020.10.08.20208447", + "rel_title": "District level correlates of COVID-19 pandemic in India", "rel_date": "2020-10-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.09.20210229", - "rel_abs": "Understanding SARS-CoV-2 antibody prevalence as a marker of prior infection in a spectrum of healthcare workers (HCWs) may guide risk stratification and enactment of better health policies and procedures.\n\nThe present study reported on cross-sectional study to determine the prevalence and longevity of SARS-CoV-2 antibodies in HCWs at a regional hospital system in Orange County, California, between May and August, 2020.\n\nData from HCWs (n=3,458) were included in the analysis. Data from first responders (n=226) were also analyzed for comparison. A blood sample was collected at study enrollment and 8-week follow-up. Information on job duties, location, COVID-19 symptoms, polymerase chain reaction test history, travel since January 2020, and household contacts with COVID-19 was collected. Comparisons to estimated community prevalence were also evaluated.\n\nObserved antibody prevalence was 0.93% and 2.58% at initial and 8-week follow-up, respectively, for HCWs, and 5.31% and 4.35% for first responders. For HCWs, significant differences (p < .05) between negative vs. positive at initial assessment were found for age, race, fever, and loss of smell, and at 8-week follow-up for age, race, and all symptoms. Antibody positivity persisted at least 8 weeks in this cohort. Among 75 HCWs with self-reported prior PCR-confirmed COVID-19, 35 (46.7%) were antibody negative. Significant differences between negative vs. positive were observed in age and frequency of symptoms.\n\nThis study found considerably lower SARS-CoV-2 antibody prevalence among HCWs compared with prior published studies. This may be explained by better safety measures in the workplace, heightened awareness inside and outside of the workplace, possibly lower susceptibility due to innate immunity and other biological heterogeneity, and low COVID-19 prevalence in the community itself. HCWs with initial positive results had persistent positive serologies at 8 weeks. Further research is warranted to investigate factors influencing such lower prevalence in our HCWs.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.08.20208447", + "rel_abs": "BackgroundThe number of patients with coronavirus infection (COVID-19) has amplified in India. Understanding the district level correlates of the COVID-19 infection ratio (IR) is therefore essential for formulating policies and intervention.\n\nObjectivesThe present study examines the association between socio-economic and demographic characteristics of Indias population and the COVID-19 infection ratio at district level...\n\nData and MethodsUsing crowdsourced data on the COVID-19 prevalence rate, we analyzed state and district level variation in India from March 14 to July 31 2020. We identified hotspot and cold spot districts for COVID-19 cases and infection ratio. We have also carried out a regression analysis to highlight the district level demographic, socio-economic, infrastructure, and health-related correlates of the COVID-19 infection ratio.\n\nResultsThe results showed that the IR is 42.38 per one hundred thousand population in India. The highest IR was observed in Andhra Pradesh (145.0), followed by Maharashtra (123.6), and was the lowest in Chhattisgarh (10.1). About 80 per cent of infected cases, and 90 per cent of deaths were observed in nine Indian states (Tamil Nadu, Andhra Pradesh, Telangana, Karnataka, Maharashtra, Delhi, Uttar Pradesh, West Bengal, and Gujarat). Moreover, we observed COVID-19 cold-spots in central, northern, western, and north-eastern regions of India. Out of 736 districts, six metropolitan cities (Mumbai, Chennai, Thane, Pune, Bengaluru, and Hyderabad) emerged as the major hotspots in India, containing around 30 per cent of confirmed total COVID-19 cases in the country. Simultaneously, parts of the Konkan coast in Maharashtra, parts of Delhi, the southern part of Tamil Nadu, the northern part of Jammu & Kashmir were identified as hotspots of COVID-19 infection. Morans-I value of 0.333showed a positive spatial clusteringlevel in the COVID-19 IR case over neighboring districts. Our regression analysis found that district-level population density ({beta}: 0.05, CI:004-0.06), the percent of urban population ({beta}:3.08, CI: 1.05-5.11), percent of Scheduled Caste Population ({beta}: 3.92, CI: 0.12-7.72),and district-level testing ratio ({beta}: 0.03, CI: 0.01-0.04) are positively associated with the prevalence of COVID-19.\n\nConclusionCOVID-19 cases were heavily concentrated in 9 states of India. Several demographic, socio-economic, and health-related variables are correlated with COVID-19 prevalence rate. However, after adjusting the role of socio-economic and health-related factors, the COVID-19 infection rate was found to be more rampant in districts with a higher population density, a higher percentage of the urban population, and a higher percentage of deprived castes and with a higher level of testing ratio. The identified hotspots and correlates in this study give crucial information for policy discourse.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Michael Brant-Zawadzki", - "author_inst": "Hoag Center for Research and Education, Hoag Memorial Hospital Presbyterian" - }, - { - "author_name": "Deborah Fridman", - "author_inst": "Hoag Center for Research and Education, Hoag Memorial Hospital Presbyterian" + "author_name": "Vandana Tamrakar", + "author_inst": "Jawaharlal Nehru University, New Delhi, India" }, { - "author_name": "Philip Robinson", - "author_inst": "Infection Prevention, Hoag Memorial Hospital Presbyterian" + "author_name": "Ankita Srivastava", + "author_inst": "Jawaharlal Nehru University, New Delhi, India" }, { - "author_name": "Matthew Zahn", - "author_inst": "Orange County Healthcare Agency" + "author_name": "Mukesh C. Parmar", + "author_inst": "Jawaharlal Nehru University, New Delhi, India" }, { - "author_name": "Clayton Chau", - "author_inst": "Orange County Healthcare Agency" + "author_name": "Sudheer Kumar Shukla", + "author_inst": "Jawaharlal Nehru University, New Delhi, India" }, { - "author_name": "Randy German", - "author_inst": "Laboratory Administrative Services, Hoag Memorial Hospital Presbyterian" + "author_name": "Shewli Shabnam", + "author_inst": "Bidhannagar College, Kolkata, India" }, { - "author_name": "Marcus Breit", - "author_inst": "Hoag Family Cancer Institute, Hoag Memorial Hospital Presbyterian" + "author_name": "Bandita Boro", + "author_inst": "Jawaharlal Nehru University, New Delhi, India" }, { - "author_name": "Elmira Burke", - "author_inst": "Quality Management, Hoag Memorial Hospital Presbyterian" + "author_name": "Apala Saha", + "author_inst": "Banaras Hindu University, Varanasi, India" }, { - "author_name": "Jason R. Bock", - "author_inst": "Medical Care Corporation" + "author_name": "Benjamin Debbarma", + "author_inst": "Jawaharlal Nehru University, New Delhi, India" }, { - "author_name": "Junko Hara", - "author_inst": "Medical Care Corporation; Hoag Center for Research and Education, Hoag Memorial Hospital Presbyterian" + "author_name": "Nandita Saikia", + "author_inst": "Jawaharlal Nehru University, New Delhi, India" } ], "version": "1", @@ -1119245,59 +1119409,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.07.20208264", - "rel_title": "Detecting and isolating false negatives ofSARS-CoV-2 primers and probe sets among the Japanese Population: A laboratory testing methodology and study", + "rel_doi": "10.1101/2020.10.07.20208561", + "rel_title": "Reliability and limits of transport-ventilators to safely ventilate severe patients in special surge situations.", "rel_date": "2020-10-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.07.20208264", - "rel_abs": "ObjectivesIn this study, a comparative study between primers from Japans and USs disease control centers was conducted. As further investigation, virus sequence alignment with primers oligonucleotide was analyzed.\n\nDesign or methods11,652 samples from Japanese population were tested for SARS-CoV-2 positive using recommended RT-PCR primer-probe sets from Japan National Institute of Infectious Disease (NIID) and US Centers for Disease Control and Prevention (CDC).\n\nResultsOf the 102 positive samples, 17 samples (16.7% of total positives) showed inconsistent results when tested simultaneously for the following primers: JPN-N2, JPN-N1, CDC-N1, and CDC-N2. As a result, CDC recommended primer-probe sets showed relatively higher sensitivity and accuracy. Further virus sequence alignment analysis showed evidences for virus mutation happening at primers binding sites.\n\nConclusionsThe inconsistency in the RT-PCR results for JPN-N1, JPN-N2, CDC-N1, and CDC-N2 primer-probe sets could be attributed to differences in virus mutation at primers binding site as observed in sequence analysis. The use of JPN-N2 combined with CDC-N2 primer produces the most effective result to reduce false negatives in Japan region. In addition, adding CDC-N1 will also help to detect false negatives.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.07.20208561", + "rel_abs": "BackgroundSeveral Intensive Care Units (ICU) have been overwhelmed by the surge of COVID-19 patients thus necessitating to extend ventilation capacity outside the ICU where air and oxygen pressure are not always available. Transport ventilators requiring only O2 source may be used to deliver volume-controlled ventilation.\n\nObjectiveTo evaluate the performances of four transport ventilators compared to an ICU ventilator simulating severe respiratory conditions.\n\nMaterials and methodsTwo pneumatic transport ventilators, (Oxylog 3000, Draeger; Osiris 3, Air Liquide Medical Systems) and two turbine transport ventilators (Elisee 350, ResMed; Monnal T60, Air Liquide Medical Systems) were compared to an ICU ventilator (Engstrom Carestation - GE Healthcare) using a Michigan training test lung. We tested each ventilator with different set volumes Vtset (350, 450, 550 ml) and different compliances (20 or 50 ml/cmH2O) and a resistance of 15 cmH2 0/L/sec based on values recently described in COVID-19 Acute Respiratory Distress Syndrome. Volume error was measured, as well as the trigger time delay during assist-control ventilation simulating spontaneous breathing activity with a P0.1 of 4 cmH20.\n\nResultsGrouping all conditions, the volume error was 2.9 {+/-} 2.2 % for Engstrom Carestation; 3.6 {+/-} 3.9 % for Osiris 3; 2.5 {+/-} 2.1 % for Oxylog 3000; 5.4 {+/-} 2.7 % for Monnal T60 and 8.8 {+/-} 4.8 % for Elisee 350. Grouping all conditions, trigger delay was 42 {+/-} 4 ms, 65 {+/-} 5 ms, 151 {+/-} 14 ms, 51 {+/-} 6 and 64 {+/-} 5 ms for Engstrom Carestation, Osiris 3, Oxylog 3000, Monnal T60 and Elisee 350, respectively.\n\nConclusionsIn special surge situations such as COVID-19 pandemic, most transport ventilators may be used to safely deliver volume-controlled ventilation in locations where only oxygen pressure supply is available with acceptable volume accuracy. Performances regarding triggering function are generally acceptable but vary across ventilators.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Wataru Tsutae", - "author_inst": "Genesis Institute of Genetic Research, Genesis Healthcare Corporation, Tokyo, Japan" - }, - { - "author_name": "Wirawit Chaochaisit", - "author_inst": "Genesis Institute of Genetic Research, Genesis Healthcare Corporation, Tokyo, Japan" + "author_name": "Dominique Savary", + "author_inst": "-\tEmergency Department, Angers University Hospital, Angers, France -\tInserm, EHESP, University of Rennes, Irset (Institut de recherche en sant" }, { - "author_name": "Hideyuki Aoshima", - "author_inst": "Genesis Institute of Genetic Research, Genesis Healthcare Corporation, Tokyo, Japan" + "author_name": "Arnaud Lesimple", + "author_inst": "- CNRS, INSERM 1083, MITOVASC, Angers University Hospital -\tMed2Lab, ALMS, Antony, France" }, { - "author_name": "Chiharu Ida", - "author_inst": "Genesis Institute of Genetic Research, Genesis Healthcare Corporation, Tokyo, Japan" + "author_name": "Francois Beloncle", + "author_inst": "MD, Critical Care Department, Angers University Hospital, Angers, France" }, { - "author_name": "Shino Miyakawa", - "author_inst": "Genesis Institute of Genetic Research, Genesis Healthcare Corporation, Tokyo, Japan" + "author_name": "Francois Morin", + "author_inst": "MD, Emergency Department, Angers University Hospital, Angers, France" }, { - "author_name": "Hiroko Sekine", - "author_inst": "Genesis Institute of Genetic Research, Genesis Healthcare Corporation, Tokyo, Japan" + "author_name": "Francois Templier", + "author_inst": "MD, Emergency Department, Angers University Hospital, Angers, France" }, { - "author_name": "Afzal Sheikh", - "author_inst": "Genesis Institute of Genetic Research, Genesis Healthcare Corporation, Tokyo, Japan" + "author_name": "Alexandre Broc", + "author_inst": "the Telecom-Physic-Strasbourg, Strasbourg University France" }, { - "author_name": "Iri Sato Baran", - "author_inst": "Genesis Institute of Genetic Research, Genesis Healthcare Corporation, Tokyo, Japan" + "author_name": "Laurent Brochard", + "author_inst": "- Keenan Resarch Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada -\tInterdep" }, { - "author_name": "Toshiharu Furukawa", - "author_inst": "Department of Surgery, School of Medicine, Keio University, Tokyo, Japan" + "author_name": "Jean-Christophe Richard", + "author_inst": "-\tCritical Care Department, Angers University Hospital, Angers, France -\tINSERM UMR 955 Eq13" }, { - "author_name": "Akihiro Sekine", - "author_inst": "Department of Emergency and Critical Care Medicine, Chiba University, Chiba, Japan" + "author_name": "Alain Mercat", + "author_inst": "MD, PHD, Critical Care Department, Angers University Hospital, Angers, France" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.10.09.20209965", @@ -1120866,43 +1121026,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.06.20207514", - "rel_title": "Plasma ACE2 activity is persistently elevated following SARS-CoV-2 infection: implications for COVID-19 pathogenesis and consequences", + "rel_doi": "10.1101/2020.10.06.20208033", + "rel_title": "Mask mandates can limit COVID spread: Quantitative assessment of month-over-month effectiveness of governmental policies in reducing the number of new COVID-19 cases in 37 US States and the District of Columbia", "rel_date": "2020-10-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.06.20207514", - "rel_abs": "COVID-19 causes persistent endothelial inflammation, lung and cardiovascular complications. SARS-CoV-2 utilises the catalytic site of full-length membrane-bound angiotensin converting enzyme 2 (ACE2) for cell entry causing downregulation of tissue ACE2. We reported downregulation of cardiac ACE2 is associated with increased plasma ACE2 activity. In this prospective observational study in recovered COVID-19 patients, we hypothesised that SARS-CoV-2 infection would be associated with shedding of ACE2 from cell membranes and increased plasma ACE2 activity.\n\nMethodsWe measured plasma ACE2 catalytic activity using a validated, sensitive quenched fluorescent substrate-based assay in a cohort of Australians aged [≥]18 years (n=66) who had recovered from mild, moderate or severe SARS-CoV-2 infection (positive result by PCR testing) and age and gender matched uninfected controls (n=70). Serial samples were available in 23 recovered SARS-CoV-2 patients.\n\nResultsPlasma ACE2 activity at a median of 35 days post-infection [interquartile range 30-38 days] was 97-fold higher in recovered SARS-CoV-2 patients compared to controls (5.8 [2-11.3] vs. 0.06 [0.02-2.2] pmol/min/ml, p<0.0001). There was a significant difference in plasma ACE2 activity according to disease severity (p=0.033), with severe COVID-19 associated with higher ACE2 activity compared to mild disease (p=0.027). Men (n=39) who were SARS-CoV-2 positive had higher median plasma ACE2 levels compared to women (n=27) (p<0.0001). We next analysed whether an elevated plasma ACE2 activity level persisted following SARS-CoV-2 infection in subjects with blood samples at 63 [56-65] and 114 [111-125] days post infection. Plasma ACE2 activity remained persistently elevated in almost all subjects, with no significant differences between timepoints in post-hoc comparisons (p>0.05).\n\nDiscussionThis is the first description that plasma ACE2 activity is elevated after COVID-19 infection, and the first with longitudinal data indicating plasma ACE2 activity remains elevated out to a median of 114 days post-infection. Larger studies are now needed to determine if persistent elevated plasma ACE2 activity identifies people at risk of prolonged illness following COVID-19.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.06.20208033", + "rel_abs": "IntroductionSARS-CoV-2 is the beta-coronavirus responsible for COVID-19. Facemask use has been qualitatively associated with reduced COVID-19 cases, but no study has quantitatively assessed the impact of government mask mandates (MM) on new COVID-19 cases across multiple US States.\n\nData and MethodsWe utilized a non-parametric machine-learning algorithm to test the a priori hypothesis that MM were associated with reductions in new COVID-19 cases. Publicly available data were used to analyze new COVID-19 cases from 37 States and the District of Columbia (i.e., \"38 States\"). We conducted confirmatory All-States and State-Wise analyses, validity analyses [e.g., leave-one-out (LOO) and bootstrap resampling], and covariate analyses.\n\nResultsNo statistically significant difference in the daily number of new COVID-19 infections was discernable in the All-States analysis. In State-Wise LOO validity analysis, 11 States exhibited reductions in new COVID-19 and the reductions in four of these States (AK, MA, MN, VA) were significant in bootstrap resampling. Only the Social Capital Index predicted MM success (training p<0.028 and LOO p<0.013).\n\nConclusionResults obtained when studying the impact of MM on COVID-19 cases varies as a function of the heterogeneity of the sample being considered, providing clear evidence of Simpsons Paradox and thus of confounded findings. As such, studies of MM effectiveness should be conducted on disaggregated data. Since transmissions occur at the individual rather than at the collective level, additional work is needed to identify optimal social, psychological, environmental, and educational factors which will reduce the spread of SARS-CoV-2 and facilitate MM effectiveness across diverse settings.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Sheila K Patel", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Jennifer A Juno", - "author_inst": "University of Melbourne" - }, - { - "author_name": "P Mark Hogarth", - "author_inst": "Burnet Institute" - }, - { - "author_name": "Wen Shi Lee", - "author_inst": "University of Melbourne" + "author_name": "Michael J Maloney", + "author_inst": "Proof School" }, { - "author_name": "Stephen J Kent", - "author_inst": "University of Melbourne" + "author_name": "Nathaniel James Rhodes", + "author_inst": "Midwestern University" }, { - "author_name": "Louise M Burrell", - "author_inst": "University of Melbourne" + "author_name": "Paul R Yarnold", + "author_inst": "Optimal Data Analysis, LLC" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.10.06.20207993", @@ -1122448,65 +1122596,229 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.04.20206540", - "rel_title": "Markers Of Coagulation And Hemostatic Activation Identify COVID-19 Patients At High Risk For Thrombotic Events, ICU Admission and Intubation", + "rel_doi": "10.1101/2020.10.02.20205831", + "rel_title": "A haemagglutination test for rapid detection of antibodies to SARS-CoV-2", "rel_date": "2020-10-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.04.20206540", - "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19) has been associated with a coagulopathy giving rise to venous and arterial thrombotic events. The objective of our study was to determine whether markers of coagulation and hemostatic activation (MOCHA) on admission could identify COVID-19 patients at risk for thrombotic events and other complications.\n\nMethodsCOVID-19 patients admitted to a tertiary academic healthcare system from April 3, 2020 to July 31, 2020 underwent standardized admission testing of MOCHA profile parameters (plasma d-dimer, prothrombin fragment 1.2, thrombin-antithrombin complex, and fibrin monomer) with abnormal MOCHA defined as [≥] 2 markers above the reference. Prespecified thrombotic endpoints included deep vein thrombosis, pulmonary embolism, myocardial infarction, ischemic stroke, and access line thrombosis; other complications included ICU admission, intubation and mortality. We excluded patients on anticoagulation therapy prior to admission and those who were pregnant.\n\nResultsOf 276 patients (mean age 59 {+/-} 6.4 years, 47% female, 62% African American race) who met study criteria, 45 (16%) had a thrombotic event. Each coagulation marker on admission was independently associated with a vascular endpoint (p<0.05). Admission MOCHA with [≥] 2 abnormalities (n=203, 74%) was associated with in-hospital vascular endpoints (OR 3.3, 95% CI 1.2-8.8), as were admission D-dimer [≥] 2000 ng/mL (OR 3.1, 95% CI 1.5-6.6), and admission D-dimer [≥] 3000 ng/mL (OR 3.6, 95% CI 1.6-7.9). However, only admission MOCHA with [≥] 2 abnormalities was associated with ICU admission (OR 3.0, 95% CI 1.7-5.2) and intubation (OR 3.2, 95% CI 1.6-6.4), while admission D-dimer [≥]2000 ng/mL and admission D-dimer [≥] 3000 ng/mL were not associated. MOCHA and D-dimer cutoffs were not associated with mortality. Admission MOCHA with <2 abnormalities (26% of the cohort) had a sensitivity of 88% and negative predictive value of 93% for a vascular endpoint.\n\nConclusionsAdmission MOCHA with [≥] 2 abnormalities identified COVID-19 patients at increased risk of ICU admission and intubation during hospitalization more effectively than isolated admission D-dimer measurement. Admission MOCHA with <2 abnormalities identified a subgroup of patients at low risk for vascular events. Our results suggest that an admission MOCHA profile can be useful to risk-stratify COVID-19 patients.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.02.20205831", + "rel_abs": "Serological detection of antibodies to SARS-CoV-2 is essential for establishing rates of seroconversion in populations, detection of seroconversion after vaccination, and for seeking evidence for a level of antibody that may be protective against COVID-19 disease. Several high-performance commercial tests have been described, but these require centralised laboratory facilities that are comparatively expensive, and therefore not available universally. Red cell agglutination tests have a long history in blood typing, and general serology through linkage of reporter molecules to the red cell surface. They do not require special equipment, are read by eye, have short development times, low cost and can be applied as a Point of Care Test (POCT). We describe a red cell agglutination test for the detection of antibodies to the SARS-CoV-2 receptor binding domain (RBD). We show that the Haemagglutination Test (\"HAT\") has a sensitivity of 90% and specificity of 99% for detection of antibodies after a PCR diagnosed infection. The HAT can be titrated, detects rising titres in the first five days of hospital admission, correlates well with a commercial test that detects antibodies to the RBD, and can be applied as a point of care test. The developing reagent is composed of a previously described nanobody to a conserved glycophorin A epitope on red cells, linked to the RBD from SARS-CoV-2. It can be lyophilised for ease of shipping. We have scaled up production of this reagent to one gram, which is sufficient for ten million tests, at a cost of [~]0.27 UK pence per test well. Aliquots of this reagent are ready to be supplied to qualified groups anywhere in the world that need to detect antibodies to SARS-CoV-2, but do not have the facilities for high throughput commercial tests.", + "rel_num_authors": 54, "rel_authors": [ { - "author_name": "Darwish Alabyad", - "author_inst": "Morehouse School of Medicine" + "author_name": "Alain Townsend", + "author_inst": "University of Oxford" }, { - "author_name": "Srikant Rangaraju", - "author_inst": "Emory University" + "author_name": "Pramila Rijal", + "author_inst": "University of Oxford" }, { - "author_name": "Michael Liu", - "author_inst": "Emory University" + "author_name": "Julie Xiao", + "author_inst": "University of Oxford" }, { - "author_name": "Rajeel Imran", - "author_inst": "Emory University" + "author_name": "Tiong Kit Tan", + "author_inst": "University of Oxford" }, { - "author_name": "Christine Kempton", - "author_inst": "Emory University" + "author_name": "Kuan-Ying A Huang", + "author_inst": "Chang Gung Memorial Hospital, Taoyuan, Taiwan" }, { - "author_name": "Milad Sharifpour", - "author_inst": "Emory University" + "author_name": "Lisa Schimanski", + "author_inst": "University of Oxford" }, { - "author_name": "Sara Auld", - "author_inst": "Emory University" + "author_name": "Jiangdong Ho", + "author_inst": "The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK" }, { - "author_name": "Manila Gaddh", - "author_inst": "Emory University" + "author_name": "Nimesh Gupta", + "author_inst": "Vaccine Immunology Laboratory, National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India" }, { - "author_name": "Roman Sniecinski", - "author_inst": "Emory University" + "author_name": "Rolle Rahikainen", + "author_inst": "University of Oxford" }, { - "author_name": "Cheryl L Maier", - "author_inst": "Emory University School of Medicine" + "author_name": "Philippa C Matthews", + "author_inst": "University of Oxford" }, { - "author_name": "Jeannette Guarner", - "author_inst": "Emory University" + "author_name": "Derrick Crook", + "author_inst": "Oxford NIHR Biomedical Research Centre, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK" }, { - "author_name": "Alexander Duncan", - "author_inst": "Emory University" + "author_name": "Sarah Hoosdally", + "author_inst": "University of Oxford" }, { - "author_name": "Fadi Nahab", - "author_inst": "Emory University" + "author_name": "Teresa Street", + "author_inst": "University of Oxford" + }, + { + "author_name": "Justine Rudkin", + "author_inst": "University of Oxford" + }, + { + "author_name": "Nicole Stoesser", + "author_inst": "University of Oxford" + }, + { + "author_name": "Fredrik Karpe", + "author_inst": "University of Oxford" + }, + { + "author_name": "Matthew Neville", + "author_inst": "University of Oxford" + }, + { + "author_name": "Rutger Ploeg", + "author_inst": "University of Oxford" + }, + { + "author_name": "Marta Oliveira", + "author_inst": "University of Oxford" + }, + { + "author_name": "David J Roberts", + "author_inst": "NHS Blood and Transplant, John Radcliffe Hospital, Headington, Oxford OX3 9BQ, UK" + }, + { + "author_name": "Abigail A Lamikanra", + "author_inst": "John Radcliffe Hospital" + }, + { + "author_name": "Hoi Pat Tsang", + "author_inst": "John Radcliffe Hospital" + }, + { + "author_name": "Abbie Bown", + "author_inst": "Public Health England" + }, + { + "author_name": "Richard Vipond", + "author_inst": "Public Health England" + }, + { + "author_name": "Alexander J Mentzer", + "author_inst": "University of Oxford" + }, + { + "author_name": "Julian C Knight", + "author_inst": "University of Oxford" + }, + { + "author_name": "Andrew Kwok", + "author_inst": "University of Oxford" + }, + { + "author_name": "Gavin Screaton", + "author_inst": "University of Oxford" + }, + { + "author_name": "Juthathip Mongkolsapaya", + "author_inst": "University of Oxford" + }, + { + "author_name": "Wanwisa Dejnirattisai", + "author_inst": "University of Oxford" + }, + { + "author_name": "Piyada Supasa", + "author_inst": "University of Oxford" + }, + { + "author_name": "Paul Klenerman", + "author_inst": "University of Oxford" + }, + { + "author_name": "Christina Dold", + "author_inst": "University of Oxford" + }, + { + "author_name": "Kenneth Baillie", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Shona C Moore", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Peter JM Openshaw", + "author_inst": "Imperial College London" + }, + { + "author_name": "Malcolm G Semple", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Lance CW Turtle", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Mark Ainsworth", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Alice Allcock", + "author_inst": "University of Oxford" + }, + { + "author_name": "Sally Beer", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Sagida Bibi", + "author_inst": "University of Oxford" + }, + { + "author_name": "Elizabeth Clutterbuck", + "author_inst": "University of Oxford" + }, + { + "author_name": "Alexis Espinosa", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Maria Mendoza", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Dominique Georgiou", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Teresa Lockett", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Jose Martinez", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Elena Perez", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Veronica Sanchez", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Giuseppe Scozzafava", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Alberto Sobrinodiaz", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Hannah Thraves", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Etienne Joly", + "author_inst": "University of Toulouse" } ], "version": "1", @@ -1123814,25 +1124126,53 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.03.20206391", - "rel_title": "Dilution-based Evaluation of Airborne Infection Risk - Thorough Expansion of Wells-Riley Model", + "rel_doi": "10.1101/2020.10.04.20206763", + "rel_title": "Intra-county modeling of COVID-19 infection with human mobility: assessing spatial heterogeneity with business traffic, age and race", "rel_date": "2020-10-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.03.20206391", - "rel_abs": "Evaluation of airborne infection risk with spatial and temporal resolutions is indispensable for the design of proper interventions fighting infectious respiratory diseases (e.g., COVID-19), because the distribution of aerosol contagions is both spatially and temporally non-uniform. However, the well-recognized Wells-Riley model and modified Wells-Riley model (i.e., the rebreathed-fraction model) are limited to the well-mixed condition and unable to evaluate airborne infection risk spatially and temporally, which could result in overestimation or underestimation of airborne infection risk. This study proposes a dilution-based evaluation method for airborne infection risk. The method proposed is benchmarked by the Wells-Riley model and modified Wells-Riley model, which indicates that the method proposed is a thorough expansion of the Wells-Riley model for evaluation of airborne infection risk with both spatial and temporal resolutions. Experiments in a mock hospital ward also demonstrate that the method proposed effectively evaluates the airborne infection risk both spatially and temporally.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.04.20206763", + "rel_abs": "The novel coronavirus disease (COVID-19) pandemic is a global threat presenting health, economic and social challenges that continue to escalate. Meta-population epidemic modeling studies in the susceptible-exposed-infectious-removed (SEIR) style have played important roles in informing public health and shaping policy making to mitigate the spread of COVID-19. These models typically rely on a key assumption on the homogeneity of the population. This assumption certainly cannot be expected to hold true in real situations; various geographic, socioeconomic and cultural environments affect the behaviors that drive the spread of COVID-19 in different communities. Whats more, variation of intra-county environments creates spatial heterogeneity of transmission in different sub-regions. To address this issue, we develop a new human mobility flow-augmented stochastic SEIR-style epidemic modeling framework with the ability to distinguish different regions and their corresponding behavior. This new modeling framework is then combined with data assimilation and machine learning techniques to reconstruct the historical growth trajectories of COVID-19 confirmed cases in two counties in Wisconsin. The associations between the spread of COVID-19 and human mobility, business foot-traffic, race & ethnicity, and age-group are then investigated. The results reveal that in a college town (Dane County) the most important heterogeneity is spatial, while in a large city area (Milwaukee County) ethnic heterogeneity becomes more apparent. Scenario studies further indicate a strong response of the spread rate on various reopening policies, which suggests that policymakers may need to take these heterogeneities into account very carefully when designing policies for mitigating the spread of COVID-19 and reopening.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Sheng ZHANG", - "author_inst": "City University of Hong Kong" + "author_name": "Xiao Hou", + "author_inst": "Department of Mathematics, University of Wisconsin-Madison" }, { - "author_name": "Zhang Lin", - "author_inst": "City University of Hong Kong" + "author_name": "Song Gao", + "author_inst": "Geospatial Data Science Lab, University of Wisconsin-Madison" + }, + { + "author_name": "Qin Li", + "author_inst": "Department of Mathematics, University of Wisconsin-Madison" + }, + { + "author_name": "Yuhao Kang", + "author_inst": "Geospatial Data Science Lab, University of Wisconsin-Madison" + }, + { + "author_name": "Nan Chen", + "author_inst": "Department of Mathematics, University of Wisconsin-Madison" + }, + { + "author_name": "Kaiping Chen", + "author_inst": "Department of Life Sciences Communication, University of Wisconsin-Madison" + }, + { + "author_name": "Jinmeng Rao", + "author_inst": "Geospatial Data Science Lab, University of Wisconsin-Madison" + }, + { + "author_name": "Jordan S. Ellenberg", + "author_inst": "Department of Mathematics, University of Wisconsin-Madison" + }, + { + "author_name": "Jonathan A. Patz", + "author_inst": "School of Medicine and Public Health, University of Wisconsin-Madison" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1125412,31 +1125752,27 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.10.04.325415", - "rel_title": "Activation of ACE2 and interferon-stimulated transcriptomes in human airway epithelium is curbed by Janus Kinase inhibitors", + "rel_doi": "10.1101/2020.10.02.20196113", + "rel_title": "Design Of A Rapid And Reversible Fluorescence Assay To Detect COVID-19 And Other Pathogens", "rel_date": "2020-10-05", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.04.325415", - "rel_abs": "The angiotensin-converting enzyme 2 (ACE2) receptor is the gateway for SARS-CoV-2 to airway epithelium1,2 and the strong inflammatory response after viral infection is a hallmark in COVID-19 patients. Deciphering the regulation of the ACE2 gene is paramount for understanding the cell tropism of SARS-CoV-2 infection. Here we identify candidate regulatory elements in the ACE2 locus in human primary airway cells and lung tissue. Activating histone and promoter marks and Pol II loading characterize the intronic dACE2 and define novel candidate enhancers distal to the genuine ACE2 promoter and within additional introns. dACE2, and to a lesser extent ACE2, RNA levels increased in primary bronchial cells treated with interferons and this induction was mitigated by Janus kinase (JAK) inhibitors that are used therapeutically in COVID-19 patients. Our analyses provide insight into regulatory elements governing the ACE2 locus and highlight that JAK inhibitors are suitable tools to suppress interferon-activated genetic programs in bronchial cells.", - "rel_num_authors": 3, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.02.20196113", + "rel_abs": "We describe a rapid and reusable biophysical method to assay COVID-19 and other pathogens. The method uses fluorescent sensors (i.e. molecular beacons) designed to detect COVID-19 RNA or any RNA of interest, concurrent with an internal control without the need for amplification. The molecular beacons are stem-loop structures in which a [~]10 nucleotide loop region has the complementary sequence of a region of the target RNA, and a fluorophore and quencher are placed on the 5 and 3 ends of the stem. The energy of hybridization of the loop with its target is designed to be greater than the hybridization energy of the energy of the stem so that when the beacon encounters its target RNA, the structure opens resulting in dequenching of the fluorophore. Here, we designed a COVID-19 beacon that is completely quenched in its native form and undergoes a 50-fold increase in fluorescence when exposed to nanomolar amounts of synthetic viral oligonucleotide. No changes in intensity are seen when control RNA is added. A control beacon to a human GAPDH RNA, chosen for its high levels in saliva, behaved similar to the COVID-19 beacon. This increase in fluorescence with beacon opening can be completely reversed upon addition of single stranded DNA complementary to COVID-19 beacon loop region. Beacons can be attached to an insert matrix allowing their use in concentrated form and can be made from morphilino oligonucleotides that are resistant to RNases. We present an analysis of the parameters that will allow the development of test strips to detect virus in aerosol, body fluids and community waste.\n\nStatement of significanceA platform for reusable and rapid detection of COVID-19 RNA and other pathogenic RNAs without the need for amplification or sophisticated instrumentation in a complex environment is described.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Hye Kyung Lee", - "author_inst": "NIDDK, NIH" - }, - { - "author_name": "Olive Jung", - "author_inst": "National Center for Advancing Translational Sciences, NIH" + "author_name": "Suzanne Scarlata", + "author_inst": "Worcester Polytechnic Institute" }, { - "author_name": "Lothar Hennighausen", - "author_inst": "National Institute of Diabetes, Digestive and Kidney Diseases, NIH" + "author_name": "V Siddartha Yerramilli", + "author_inst": "Worcester Polytechnic Institute" } ], "version": "1", - "license": "cc0", - "type": "new results", - "category": "genomics" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.10.02.20200931", @@ -1126930,39 +1127266,127 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.10.01.20205377", - "rel_title": "Racial-ethnic disparities in case fatality ratio narrowed after age standardization: A call for race-ethnicity-specific age distributions in State COVID-19 data", + "rel_doi": "10.1101/2020.10.01.20204073", + "rel_title": "COVID-19 Classification of X-ray Images Using Deep Neural Networks", "rel_date": "2020-10-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.01.20205377", - "rel_abs": "ImportanceCOVID-19 racial disparities have gained significant attention yet little is known about how age distributions obscure racial-ethnic disparities in COVID-19 case fatality ratios (CFR).\n\nObjectiveWe filled this gap by assessing relevant data availability and quality across states, and in states with available data, investigating how racial-ethnic disparities in CFR changed after age adjustment.\n\nDesign/Setting/Participants/ExposureWe conducted a landscape analysis as of July 1st, 2020 and developed a grading system to assess COVID-19 case and death data by age and race in 50 states and DC. In states where age- and race-specific data were available, we applied direct age standardization to compare CFR across race-ethnicities. We developed an online dashboard to automatically and continuously update our results.\n\nMain Outcome and MeasureOur main outcome was CFR (deaths per 100 confirmed cases). We examined CFR by age and race-ethnicities.\n\nResultsWe found substantial variations in disaggregating and reporting case and death data across states. Only three states, California, Illinois and Ohio, had sufficient age- and race-ethnicity-disaggregation to allow the investigation of racial-ethnic disparities in CFR while controlling for age. In total, we analyzed 391,991confirmed cases and 17,612 confirmed deaths. The crude CFRs varied from, e.g. 7.35% among Non-Hispanic (NH) White population to 1.39% among Hispanic population in Ohio. After age standardization, racial-ethnic differences in CFR narrowed, e.g. from 5.28% among NH White population to 3.79% among NH Asian population in Ohio, or an over one-fold difference. In addition, the ranking of race-ethnic-specific CFRs changed after age standardization. NH White population had the leading crude CFRs whereas NH Black and NH Asian population had the leading and second leading age-adjusted CFRs respectively in two of the three states. Hispanic populations age-adjusted CFR were substantially higher than the crude. Sensitivity analysis did not change these results qualitatively.\n\nConclusions and RelevanceThe availability and quality of age- and race-ethnic-specific COVID-19 case and death data varied greatly across states. Age distributions in confirmed cases obscured racial-ethnic disparities in COVID-19 CFR. Age standardization narrows racial-ethnic disparities and changes ranking. Public COVID-19 data availability, quality, and harmonization need improvement to address racial disparities in this pandemic.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat are the racial-ethnic disparities in COVID-19 case fatality ratios (CFR) across states after adjusting for age?\n\nFindingsWe conducted direct standardization among 391,991 COVID-19 cases and 17,612 deaths from California, Illinois and Ohio to compare age-adjusted CFR across race-ethnicities. The racial-ethnic disparities in CFR narrowed and the ranking changed after age standardization.\n\nMeaningAge distributions in confirmed cases obscured racial-ethnic disparities in COVID-19 CFR.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.01.20204073", + "rel_abs": "ObjectivesIn the midst of the coronavirus disease 2019 (COVID-19) outbreak, chest X-ray (CXR) imaging is playing an important role in diagnosis and monitoring of patients with COVID-19. Machine learning solutions have been shown to be useful for X-ray analysis and classification in a range of medical contexts. In this study, we propose a machine learning model for detection of patients tested positive for COVID-19 from CXRs that were collected from inpatients hospitalized in four different hospitals. We additionally present a tool for retrieving similar patients according to the models results on their CXRs.\n\nMethodsIn this retrospective study, 1384 frontal CXRs, of COVID-19 confirmed patients imaged between March-August 2020, and 1024 matching CXRs of non-COVID patients imaged before the pandemic, were collected and used to build a deep learning classifier for detecting patients positive for COVID-19. The classifier consists of an ensemble of pre-trained deep neural networks (DNNS), specifically, ReNet34, ReNet50, ReNet152, vgg16, and is enhanced by data augmentation and lung segmentation. We further implemented a nearest-neighbors algorithm that uses DNN-based image embeddings to retrieve the images most similar to a given image.\n\nResultsOur model achieved accuracy of 90.3%, (95%CI: 86.3%-93.7%) specificity of 90% (95%CI: 84.3%-94%), and sensitivity of 90.5% (95%CI: 85%-94%) on a test dataset comprising 15% (350/2326) of the original images. The AUC of the ROC curve is 0.96 (95%CI: 0.93-0.97).\n\nConclusionWe provide deep learning models, trained and evaluated on CXRs that can assist medical efforts and reduce medical staff workload in handling COVID-19.\n\nKey PointsO_LIA machine learning model was able to detect chest X-ray (CXR) images of patients tested positive for COVID-19 with accuracy and detection rate above 90%.\nC_LIO_LIA tool was created for finding existing CXR images with imaging characteristics most similar to a given CXR, according to the models image embeddings.\nC_LI", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Ishaan Pathak", - "author_inst": "Department of Population, Family and Reproductive Health, Bloomberg School of Public Health, Johns Hopkins University" + "author_name": "Elisha Goldstein", + "author_inst": "Bioinformatics Unit, Life Sciences Core Facilities, Weizmann Institute of Science, Rehovot, Israel" }, { - "author_name": "Yoonjoung Choi", - "author_inst": "iSquared" + "author_name": "Daphna Keidar", + "author_inst": "ETH zurich, D-INFK, Zurich, Switzerland" }, { - "author_name": "Dazhi Jiao", - "author_inst": "Institute of Clinical and Translational Research, School of Medicine, Johns Hopkins University" + "author_name": "Daniel Yaron", + "author_inst": "Dept. of Math and Computer Science, Weizmann Institute of Science, Rehovot, Israel" }, { - "author_name": "Diana Yeung", - "author_inst": "Department of International Health, Bloomberg School of Public Health, Johns Hopkins University" + "author_name": "Yair Shachar", + "author_inst": "Eyeway Vision Ltd., Yoni Netanyahu St 3, Or Yehuda" }, { - "author_name": "Li Liu", - "author_inst": "Department of Population, Family and Reproductive Health, Bloomberg School of Public Health, Johns Hopkins University" + "author_name": "Ayelet Blass", + "author_inst": "Dept. of Math and Computer Science, Weizmann Institute of Science, Rehovot, Israel" + }, + { + "author_name": "Leonid Charbinsky", + "author_inst": "Department of Radiology, HaEmek Medical Center, Afula, Israel" + }, + { + "author_name": "Israel Aharony", + "author_inst": "Department of Radiology, HaEmek Medical Center, Afula, Israel" + }, + { + "author_name": "Liza Lifshitz", + "author_inst": "Department of Radiology, HaEmek Medical Center, Afula, Israel" + }, + { + "author_name": "Dimitri Lumelsky", + "author_inst": "Department of Radiology, HaEmek Medical Center, Afula, Israel" + }, + { + "author_name": "Ziv Neeman", + "author_inst": "Department of Radiology, HaEmek Medical Center, Afula, Israel" + }, + { + "author_name": "Matti Mizrachi", + "author_inst": "Department of Otolaryngology, Head and Neck Surgery, Galilee Medical Center, Nahariya, Israel; The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Isra" + }, + { + "author_name": "Majd Hajouj", + "author_inst": "Department of Otolaryngology, Head and Neck Surgery, Galilee Medical Center, Nahariya, Israel; The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Isra" + }, + { + "author_name": "Nethanel Eizenbach", + "author_inst": "Department of Otolaryngology, Head and Neck Surgery, Galilee Medical Center, Nahariya, Israel; The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Isra" + }, + { + "author_name": "Eyal Sela", + "author_inst": "Department of Otolaryngology, Head and Neck Surgery, Galilee Medical Center, Nahariya, Israel; The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Isra" + }, + { + "author_name": "Chedva Weiss", + "author_inst": "Cardiothoracic Imaging Unit, Shaare Zedek Medical Center, Jerusalem, Israel" + }, + { + "author_name": "Philip Levin", + "author_inst": "Cardiothoracic Imaging Unit, Shaare Zedek Medical Center, Jerusalem, Israel" + }, + { + "author_name": "Ofer Benjaminov", + "author_inst": "Cardiothoracic Imaging Unit, Shaare Zedek Medical Center, Jerusalem, Israel" + }, + { + "author_name": "Gil N Bachar", + "author_inst": "Radiology department, Rabin Medical Center, Jabotinsky Rd 39, Petah Tikva; Sakler School of Medicin, Tel-Aviv University, Ramat Aviv, Tel-Aviv" + }, + { + "author_name": "Shlomit Tamir", + "author_inst": "Radiology department, Rabin Medical Center, Jabotinsky Rd 39, Petah Tikva; Sakler School of Medicin, Tel-Aviv University, Ramat Aviv, Tel-Aviv" + }, + { + "author_name": "Yael Rapson", + "author_inst": "Radiology department, Rabin Medical Center, Jabotinsky Rd 39, Petah Tikva; Sakler School of Medicin, Tel-Aviv University, Ramat Aviv, Tel-Aviv" + }, + { + "author_name": "Dror Suhami", + "author_inst": "Radiology department, Rabin Medical Center, Jabotinsky Rd 39, Petah Tikva; Sakler School of Medicin, Tel-Aviv University, Ramat Aviv, Tel-Aviv" + }, + { + "author_name": "amiel a dror", + "author_inst": "Department of Otolaryngology, Head and Neck Surgery, Galilee Medical Center, Nahariya, Israel; The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Isra" + }, + { + "author_name": "Naama Bogot", + "author_inst": "Cardiothoracic Imaging Unit, Shaare Zedek Medical Center, Jerusalem, Israel" + }, + { + "author_name": "Ahuva Grubstein", + "author_inst": "Radiology department, Rabin Medical Center, Jabotinsky Rd 39, Petah Tikva; Sakler School of Medicin, Tel-Aviv University, Ramat Aviv, Tel-Aviv" + }, + { + "author_name": "Nogah Shabsin", + "author_inst": "Department of Radiology, HaEmek Medical Center, Afula, Israel" + }, + { + "author_name": "Yishai M Elyada", + "author_inst": "Mobileye Vision Technologies, Ltd., Hartom 13, Jerusalem" + }, + { + "author_name": "Yonina Eldar", + "author_inst": "Dept. of Math and Computer Science, Weizmann Institute of Science, Rehovot, Israel" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "radiology and imaging" }, { "rel_doi": "10.1101/2020.09.30.20204537", @@ -1128616,35 +1129040,67 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.01.20205047", - "rel_title": "Tracing and testing the COVID-19 contact chain: cost-benefit tradeoffs", + "rel_doi": "10.1101/2020.09.30.20203844", + "rel_title": "A One-Minute Blood Test to Monitor Immune Responses in COVID-19 Patients and Predict Clinical Risks of Developing Moderate to Severe Symptoms", "rel_date": "2020-10-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.01.20205047", - "rel_abs": "Traditional contact tracing for COVID-19 tests the direct contacts of those who test positive even if the contacts do not show any symptom. But, why should the testing stop at direct contacts, and not test secondary, tertiary contacts or even contacts further down? The question arises because by the time an infected individual is tested the infection starting from him may have infected a chain of individuals. One deterrent in testing long chains of individuals right away may be that it substantially increases the testing load, or does it? We investigate the costs and benefits of testing the contact chain of an individual who tests positive. For this investigation, we utilize multiple human contact networks, spanning two real-world data sets of spatio-temporal records of human presence over certain periods of time, as also networks of a classical synthetic variety. Over the diverse set of contact patterns, we discover that testing the contact chain can both substantially reduce over time both the cumulative infection count and the testing load. We consider elements of human behavior that enhance the spread of the disease and lower the efficacy of testing strategies, and show that testing the contact chain enhances the resilience to adverse impacts of these elements. We also discover a phenomenon of diminishing return beyond a threshold value on the depth of the chain to be tested in one go, the threshold then provides the most desirable tradeoff between benefit in terms of reducing the cumulative infection count, enhancing resilience to adverse impacts of human behavior, and cost in terms of increasing the testing load.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.30.20203844", + "rel_abs": "Coronavirus disease 2019 (COVID-19) has brought enormous loss and interruption to human life and the global economy since the first outbreak reported in China between late 2019 to early 2020, and will likely remain a public health threat in the months and years to come. Upon infection with SARS-CoV-2, the virus that causes COVID-19, most people will develop no or mild symptoms, however, a small percentage of the population will become severely ill, require hospitalization, intensive care, and some succumb to death. The current knowledge of COVID-19 disease progression with worsening symptom complex implicates the critical importance of identifying patients with high clinical risk compared to those who would be at lower risk for disease control and patient management with better therapeutic output. Currently no clinical test is available that can predict risk factors and immune status change at different severity scales. The immune system plays a critical role in the defense against infectious diseases. Extensive research has found that COVID-19 patients with poor clinical outcomes differ significantly in their immune responses to the virus from those who exhibit milder symptoms. We previously developed a nanoparticle-enabled blood test that can detect the humoral immune status change in animals. In this study, we applied this new test to analyze the immune response in relation to disease severity in COVID-19 patients. From the testing of 153 COVID-19 patient samples and 142 negative controls, we detected statistically significant differences between COVID-19 patients with no or mild symptoms from those who developed moderate to severe symptoms. Mechanistic study suggests that these differences are associated with type 1 versus type 2 immune responses. We conclude that this new rapid test could potentially become a valuable clinical tool for COVID-19 patient risk stratification and management.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Jungyeol Kim", - "author_inst": "University of Pennsylvania" + "author_name": "Chirajyoti Deb", + "author_inst": "Orlando Health" }, { - "author_name": "Xingran Chen", - "author_inst": "University of Pennsylvania" + "author_name": "Allan N Salinas", + "author_inst": "Orlando Health" }, { - "author_name": "Shirin Saeedi Bidokhti", - "author_inst": "University of Pennsylvania" + "author_name": "Aurea Middleton", + "author_inst": "Orlando Health" }, { - "author_name": "Saswati Sarkar", - "author_inst": "University of Pennsylvania" + "author_name": "Katelyn Kern", + "author_inst": "Orlando Health" + }, + { + "author_name": "Daleen Penoyer", + "author_inst": "Orlando Health" + }, + { + "author_name": "Rahul Borsadia", + "author_inst": "Orlando Health" + }, + { + "author_name": "Charles Hunley", + "author_inst": "OrlandoHealth" + }, + { + "author_name": "Vijay Mehta", + "author_inst": "Orlando Health" + }, + { + "author_name": "Laura Irastorza", + "author_inst": "Orlando Health" + }, + { + "author_name": "Devendra I Mehta", + "author_inst": "Orlando Health" + }, + { + "author_name": "Tianyu Zheng", + "author_inst": "Nano Discovery Inc." + }, + { + "author_name": "QUN HUO", + "author_inst": "University of Central Florida" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.10.02.323915", @@ -1130434,45 +1130890,61 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.29.20193110", - "rel_title": "Hydroxychloroquine (HCQ) reverses anti-PD-1 immune murine checkpoint blockade: TCF1 as a marker in humans for COVID-19 and HCQ therapy", + "rel_doi": "10.1101/2020.09.29.20200469", + "rel_title": "Global, regional, and national estimates of target population sizes for COVID-19 vaccination", "rel_date": "2020-09-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.29.20193110", - "rel_abs": "Coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a serious threat to global public health. Hydroxychloroquine (HCQ) and the antibiotic azithromycin (AZ) are still being used by thousands and numerous hospitals to treat COVID-19. In a related context, immunotherapy using checkpoint blockade (ICB) with antibodies such as anti-PD-1 has revolutionised cancer therapy. Given that cancer patients on ICB continue to be infected with SARS-CoV-2, an understanding of the effects of HCQ and AZ on the elimination of tumors by anti-PD-1 ICB is urgently needed. In this study, we report that HCQ alone, or in combination with AZ, at doses used to treat COVID-19 patients, reverses the therapeutic benefit of anti-PD-1 in controlling B16 melanoma tumor growth in mice. No deleterious effect was seen on untreated tumors, or in using AZ alone in anti-PD-1 immunotherapy. Mechanistically, HCQ and HCQ/AZ inhibited PD-L1 expression on tumor cells, while specifically targeting the anti-PD-1 induced increase in progenitor CD8+CD44+PD-1+TCF1+ tumor infiltrating T-cells (TILs) and the generation of CD8+CD44+PD-1+ effectors. Surprisingly, it also blocked the appearance of a subset of terminally exhausted CD8+ TILs. No effect was seen on the presence of CD4+ T-cells, FoxP3+ Tregs, thymic subsets, B-cells, antibody production, myeloid cells, or the vasculature of mice. Lastly, we identified TCF-1 expression in peripheral CD8+ T-cells from cancer or non-cancer human patients infected with SARs CoV2 as a marker for the effects of COVID-19 and HCQ on the immune system. This study indicates for the first time that HCQ and HCQ/AZ negatively impact the ability of anti-PD-1 checkpoint blockade to promote tumor rejection.\n\nGraphic Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC=\"FIGDIR/small/20193110v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (21K):\norg.highwire.dtl.DTLVardef@1e77642org.highwire.dtl.DTLVardef@1051e66org.highwire.dtl.DTLVardef@10ecf94org.highwire.dtl.DTLVardef@15e0545_HPS_FORMAT_FIGEXP M_FIG C_FIG", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.29.20200469", + "rel_abs": "BackgroundCOVID-19 vaccine prioritization and allocation strategies that maximize health benefit through efficient use of limited resources are urgently needed. We aimed to provide global, regional, and national estimates of target population sizes for COVID-19 vaccination to inform country-specific immunization strategies on a global scale.\n\nMethodsBased on a previous study of international allocation for pandemic COVID-19 vaccines, we classified the entire world population into eleven priority groups. Information on priority groups was derived from a multi-pronged search of official websites, media sources and academic journal articles. The sizes of different priority groups were projected for 194 countries globally.\n\nResultsOverall, the size of COVID-19 vaccine recipient population varied markedly by goals of the vaccination program and geography. The general population aged <60 years without any underlying condition accounts for the majority of the total population (5.2 billion people, 68%), followed by 2.3 billion individuals at risk of severe disease, and 246.9 million essential workers which are critical to maintaining a functional society. Differences in the demographic structure, presence of underlying conditions, and number of essential workers led to highly variable estimates of target populations both at the WHO region and country level. In particular, Europe has the highest share of essential workers (6.8%) and the highest share of individuals with underlying conditions (37.8%), two priority categories to maintain societal functions and reduce severe burden. In contrast, Africa has the highest share of healthy adults, school-age individuals, and infants (77.6%), which are the key groups to target to reduce community transmission.\n\nInterpretationThe sizeable distribution of target groups on a country and regional bases underlines the importance of equitable and efficient vaccine prioritization and allocation globally. The direct and indirect benefits of COVID-19 vaccination should be balanced by considering local differences in demography and health.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Janna Kreuger", - "author_inst": "Research Center Maisonneuve-Rosemont Hospital and Universite de Montreal" + "author_name": "Wei Wang", + "author_inst": "Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" }, { - "author_name": "Francois Santinon", - "author_inst": "Research Center Maisonneuve-Rosemont Hospital and Universite de Montreal" + "author_name": "Qianhui Wu", + "author_inst": "Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" }, { - "author_name": "Alexandra Kazanova", - "author_inst": "Research Center Maisonneuve-Rosemont Hospital and Universite de Montreal" + "author_name": "Juan Yang", + "author_inst": "Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" }, { - "author_name": "Mark Issa", - "author_inst": "Research Center Maisonneuve-Rosemont Hospital and Universite de Montreal" + "author_name": "Kaige Dong", + "author_inst": "Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" }, { - "author_name": "Bruno Larrivee", - "author_inst": "Research Center Maisonneuve-Rosemont Hospital and Universite de Montreal" + "author_name": "Xinghui Chen", + "author_inst": "Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" }, { - "author_name": "Catalin Milhalcioiu", - "author_inst": "McGill University" + "author_name": "Xufang Bai", + "author_inst": "Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" }, { - "author_name": "Christopher E. Rudd", - "author_inst": "Centre de Recherche Hopital Maisonneuve-Rosemont, Universite de Montreal" + "author_name": "Xinhua Chen", + "author_inst": "Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" + }, + { + "author_name": "Zhiyuan Chen", + "author_inst": "Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" + }, + { + "author_name": "C\u00e9cile Viboud", + "author_inst": "National Institutes of Health, Bethesda, MD, USA" + }, + { + "author_name": "Marco Ajelli", + "author_inst": "Indiana University School of Public Health, Bloomington, IN, USA; Northeastern University, Boston, MA USA" + }, + { + "author_name": "Hongjie Yu", + "author_inst": "Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1132168,71 +1132640,59 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.25.20195818", - "rel_title": "Broad SARS-CoV-2 cell tropism and immunopathology in lung tissues from fatal COVID-19", + "rel_doi": "10.1101/2020.09.27.20201590", + "rel_title": "SARS-CoV-2 cell entry gene ACE2 expression in immune cells that infiltrate the placenta in infection-associated preterm birth", "rel_date": "2020-09-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.25.20195818", - "rel_abs": "Background Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection in patients with Coronavirus Disease 2019 (COVID-19) prominently manifests with pulmonary symptoms histologically reflected by diffuse alveolar damage (DAD), excess inflammation, pneumocyte hyperplasia and proliferation, and formation of platelet aggregates or thromboemboli. However, the mechanisms mediating these processes remain unclear. Methods We performed multicolor staining for viral proteins, and lineage cell markers to identify SARS-CoV-2 tropism and to define the lung pathobiology in postmortem tissues from five patients with fatal SARS-CoV-2 infections. Findings The lung parenchyma showed severe DAD with thromboemboli in all cases. SARS-CoV-2 infection was found in an extensive range of cells including alveolar epithelial type II/pneumocyte type II (AT2) cells (HT2-280), ciliated cells (tyr--tubulin), goblet cells (MUC5AC), club-like cells (MUC5B) and endothelial cells (CD31 and CD34). Greater than 90% of infiltrating immune cells were positive for viral proteins including macrophages and monocytes (CD68 and CD163), neutrophils (ELA-2), natural killer (NK) cells (CD56), B-cells (CD19 and CD20), and T-cells (CD3{varepsilon}). Most but not all infected cells were positive for the viral entry receptor angiotensin-converting enzyme-2 (ACE2). The numbers of infected and ACE2-positive cells correlated with the extent of tissue damage. The infected tissues exhibited low numbers of B-cells and abundant CD3{varepsilon}+ T-cells consisting of mainly T helper cells (CD4), few cytotoxic T cells (CTL, CD8), and no T regulatory cell (FOXP3). Antigen presenting molecule HLA-DR of B and T cells was abundant in all cases. Robust interleukin-6 (IL-6) expression was present in most uninfected and infected cells, with higher expression levels observed in cases with more tissue damage. Interpretation In lung tissues from severely affected COVID-19 patients, there is evidence for broad SARS-CoV-2 cell tropisms, activation of immune cells, and clearance of immunosuppressive cells, which could contribute to severe tissue damage, thromboemboli, excess inflammation and compromised adaptive immune responses.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.27.20201590", + "rel_abs": "COVID-19 infection during pregnancy is associated with an increased incidence of preterm birth but neonatal infection is rare. We assessed pathways by which SARS-CoV-2 could access the placenta and contribute to fetal transmission. Placentas from pregnancies complicated with chorioamnionitis (ChA), exhibited increased expression of ACE2 mRNA. Treatment of 2nd trimester placental explants with LPS, induced an acute increase in cytokine expression followed by ACE2 mRNA. Placental ACE2 protein localized to syncytiotrophoblast, in fetal blood vessels and M1/M2 macrophage and neutrophils within the villous stroma. Increased numbers of M1 macrophage and neutrophils were present in the placenta of ChA pregnancies. Maternal peripheral immune cells (mainly granulocytes and monocytes) express the ACE2 mRNA and protein. These data suggest that in COVID19 positive pregnancies complicated by ChA, ACE2 positive immune cells have the potential to traffic SARS-CoV-2 virus to the placenta and increase the risk of vertical transmission to the placenta/fetus.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Suzane Ramos da Silva", - "author_inst": "Cancer Virology Program, UPMC Hillman Cancer Center and Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsbur" - }, - { - "author_name": "Enguo Ju", - "author_inst": "Cancer Virology Program, UPMC Hillman Cancer Center and Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsbur" - }, - { - "author_name": "Wen Meng", - "author_inst": "Cancer Virology Program, UPMC Hillman Cancer Center and Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsbur" - }, - { - "author_name": "Alberto E. Paniz Mondolfi", - "author_inst": "Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York" + "author_name": "Phatcharawan Lye", + "author_inst": "Department of Physiology, University of Toronto, Toronto, Ontario, Canada" }, { - "author_name": "Sanja Dacic", - "author_inst": "Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh" + "author_name": "Caroline Dunk", + "author_inst": "Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada" }, { - "author_name": "Anthony Green", - "author_inst": "Tissue and Research Pathology Core, UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh" + "author_name": "Jianhong Zhang", + "author_inst": "Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada" }, { - "author_name": "Clare Bryce", - "author_inst": "Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York" + "author_name": "Yanxing Wei", + "author_inst": "Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada" }, { - "author_name": "Zachary Grimes", - "author_inst": "Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York" + "author_name": "Jittanan Nakpu", + "author_inst": "Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada" }, { - "author_name": "Mary E Fowkes", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Hirotaka Hamada", + "author_inst": "Department of Physiology, University of Toronto, Toronto, Ontario, Canada" }, { - "author_name": "Emilia M. Sordillo", - "author_inst": "Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York" + "author_name": "Guinever Imperio", + "author_inst": "Department of Physiology, University of Toronto, Toronto, Ontario, Canada" }, { - "author_name": "Carlos Cordon-Cardo", - "author_inst": "Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York" + "author_name": "Enrrico Bloise", + "author_inst": "Department of Morphology, Federal University of Minas Gerais, Belo Horizonte, Brazil" }, { - "author_name": "Haitao Guo", - "author_inst": "Cancer Virology Program, UPMC Hillman Cancer Center and Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsbur" + "author_name": "Stephen M Matthews", + "author_inst": "Department of Physiology, University of Toronto, Toronto, Ontario, Canada" }, { - "author_name": "Shou-Jiang Gao", - "author_inst": "Cancer Virology Program, UPMC Hillman Cancer Center and Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsbur" + "author_name": "Stephen James Lye", + "author_inst": "Lunenfeld-Tanenbaum Research Institute" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "obstetrics and gynecology" }, { "rel_doi": "10.1101/2020.09.28.20200915", @@ -1133974,43 +1134434,83 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.29.20203505", - "rel_title": "Causal Analysis of Health Interventions and Environments for Influencing the Spread of COVID-19 in the United States of America", + "rel_doi": "10.1101/2020.09.28.311480", + "rel_title": "Prime-boost vaccination of mice and Rhesus macaques with two novel adenovirus vectored COVID-19 vaccine candidates", "rel_date": "2020-09-29", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.29.20203505", - "rel_abs": "As of August 27, 2020, the number of cumulative cases of COVID-19 in the US exceeded 5,863,363 and included 180,595 deaths, thus causing a serious public health crisis. Curbing the spread of Covid-19 is still urgently needed. Given the lack of potential vaccines and effective medications, non-pharmaceutical interventions are the major option to curtail the spread of COVID-19. An accurate estimate of the potential impact of different non-pharmaceutical measures on containing, and identify risk factors influencing the spread of COVID-19 is crucial for planning the most effective interventions to curb the spread of COVID-19 and to reduce the deaths. Additive model-based bivariate causal discovery for scalar factors and multivariate Granger causality tests for time series factors are applied to the surveillance data of lab-confirmed Covid-19 cases in the US, University of Maryland Data (UMD) data, and Google mobility data from March 5, 2020 to August 25, 2020 in order to evaluate the contributions of social-biological factors, economics, the Google mobility indexes, and the rate of the virus test to the number of the new cases and number of deaths from COVID-19. We found that active cases/1000 people, workplaces, tests done/1000 people, imported COVID-19 cases, unemployment rate and unemployment claims/1000 people, mobility trends for places of residence (residential), retail and test capacity were the most significant risk factor for the new cases of COVID-19 in 23, 7, 6, 5, 4, 2, 1 and 1 states, respectively, and that active cases/1000 people, workplaces, residential, unemployment rate, imported COVID cases, unemployment claims/1000 people, transit stations, mobility trends (transit) , tests done/1000 people, grocery, testing capacity, retail, percentage of change in consumption, percentage of working from home were the most significant risk factor for the deaths of COVID-19 in 17, 10, 4, 4, 3, 2, 2, 2, 1, 1, 1, 1 states, respectively. We observed that no metrics showed significant evidence in mitigating the COVID-19 epidemic in FL and only a few metrics showed evidence in reducing the number of new cases of COVID-19 in AZ, NY and TX. Our results showed that the majority of non-pharmaceutical interventions had a large effect on slowing the transmission and reducing deaths, and that health interventions were still needed to contain COVID-19.", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.28.311480", + "rel_abs": "COVID-19 vaccines are being developed urgently worldwide, among which single-shot adenovirus vectored vaccines represent a major approach. Here, we constructed two novel adenovirus vectored COVID-19 vaccine candidates on simian adenovirus serotype 23 (Sad23L) and human adenovirus serotype 49 vectors (Ad49L) carrying the full-length gene of SARS-CoV-2 spike protein (S), designated Sad23L-nCoV-S and Ad49L-nCoV-S vaccines, respectively. The immunogenicity elicited by these two vaccine strains was individually evaluated in mice. Specific humoral and cellular immune responses were proportionally observed in a dose-dependent manner, and stronger response was obtained by boosting. Furthermore, five rhesus macaques were intramuscularly injected with a dose of 5x109 PFU Sad23L-nCoV-S vaccine for prime vaccination, followed by boosting with 5x109 PFU of Ad49L-nCoV-S vaccine at 4-week interval. Three macaques were injected with Sad23L-GFP and Ad49L-GFP vectorial viruses as negative controls. Both mice and macaques tolerated well the vaccine inoculations without detectable clinical or pathologic changes. In macaques, prime-boost vaccination regimen induced high titers of 103.16 S-binding antibody (S-BAb), 102.75 cell receptor binding domain (RBD)-BAb and 102.38 neutralizing antibody (NAb) to pseudovirus a week after boosting injection, followed by sustained high levels over 10 weeks of observation. Robust IFN-{gamma} secreting T-cell response (712.6 SFCs/106 cells), IL-2 secreting T-cell response (334 SFCs/106 cells) and intracellular IFN-{gamma} expressing CD4+/CD8+ T cell response (0.39%/0.55%) to S peptides were detected in the vaccinated macaques. It was concluded that prime-boost immunization with Sad23L-nCoV-S and Ad49L-nCoV-S vaccines can safely elicit strong immunity in animals in preparation of clinical phase 1/2 trials.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "zhouxuan Li", - "author_inst": "The University of Texas Health Science Center at Houston, TX, USA" + "author_name": "Shengxue Luo", + "author_inst": "Department of Pediatrics, Shenzhen Hospital, Southern Medical University, Shenzhen, China" }, { - "author_name": "Tao Xu", - "author_inst": "The University of Texas Health Science Center at Houston, Houston, TX , USA" + "author_name": "Panli Zhang", + "author_inst": "Southern Medical University" }, { - "author_name": "Kai Zhang", - "author_inst": "The University of Texas Health Science Center at Houston, Houston, TX , USA" + "author_name": "Bochao Li", + "author_inst": "Southern Medical University" }, { - "author_name": "Hong-Wen Deng", - "author_inst": "Tulane Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane" + "author_name": "Chan Yang", + "author_inst": "Southern Medical University" }, { - "author_name": "Eric Boerwinkle", - "author_inst": "University of Texas Health Science Center at Houston" + "author_name": "Chaolan Liang", + "author_inst": "Southern Medical University" }, { - "author_name": "Momiao Xiong", - "author_inst": "University of Texas School of Public Health" + "author_name": "Qi Wang", + "author_inst": "Southern Medical University" + }, + { + "author_name": "Ling Zhang", + "author_inst": "Southern Medical University" + }, + { + "author_name": "Xi Tang", + "author_inst": "Southern Medical University" + }, + { + "author_name": "Jinfeng Li", + "author_inst": "Southern Medical University" + }, + { + "author_name": "Shuiping Hou", + "author_inst": "Southern Medical University" + }, + { + "author_name": "Jinfeng Zeng", + "author_inst": "Shenzhen Blood Center" + }, + { + "author_name": "Yongshui Fu", + "author_inst": "Guangzhou Blood Center" + }, + { + "author_name": "Jean-Pierre Allain", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Tingting Li", + "author_inst": "Southern Medical University" + }, + { + "author_name": "Yuming Zhang", + "author_inst": "Shenzhen Hospital, Southern Medical University" + }, + { + "author_name": "Chengyao Li", + "author_inst": "Southern Medical University" } ], "version": "1", - "license": "cc0_ng", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_by_nd", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2020.09.29.317289", @@ -1135692,30 +1136192,50 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.09.27.312538", - "rel_title": "No evidence that plasmablasts transdifferentiate into developing neutrophils in severe COVID-19 disease", + "rel_doi": "10.1101/2020.09.26.314971", + "rel_title": "Ultrafast Sample Placement on Existing Trees (UShER) Empowers Real-Time Phylogenetics for the SARS-CoV-2 Pandemic", "rel_date": "2020-09-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.27.312538", - "rel_abs": "A recent study by Wilk et al. of the transcriptome of peripheral blood mononuclear cells (PBMCs) in seven patients hospitalized with COVID-19 described a population of \"developing neutrophils\" that were \"phenotypically related by dimensionality reduction\" to plasmablasts, and that these two cell populations represent a \"linear continuum of cellular phenotype\"1. The authors suggest that, in the setting of acute respiratory distress syndrome (ARDS) secondary to severe COVID-19, a \"differentiation bridge from plasmablasts to developing neutrophils\" connected these distantly related cell types. This conclusion is controversial as it appears to violate several basic principles in cell biology relating to cell lineage identity and fidelity. Correctly classifying cells and their developmental history is an important issue in cell biology and we suggest that this conclusion is not supported by the data as we show here that: (1) regressing out covariates such as unique molecular identifiers (UMIs) can lead to overfitting; and (2) that UMAP embeddings may reflect the expression of similar genes but not necessarily direct cell lineage relationships.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.26.314971", + "rel_abs": "As the SARS-CoV-2 virus spreads through human populations, the unprecedented accumulation of viral genome sequences is ushering a new era of \"genomic contact tracing\" - that is, using viral genome sequences to trace local transmission dynamics. However, because the viral phylogeny is already so large - and will undoubtedly grow many fold - placing new sequences onto the tree has emerged as a barrier to real-time genomic contact tracing. Here, we resolve this challenge by building an efficient, tree-based data structure encoding the inferred evolutionary history of the virus. We demonstrate that our approach improves the speed of phylogenetic placement of new samples and data visualization by orders of magnitude, making it possible to complete the placements under real-time constraints. Our method also provides the key ingredient for maintaining a fully-updated reference phylogeny. We make these tools available to the research community through the UCSC SARS-CoV-2 Genome Browser to enable rapid cross-referencing of information in new virus sequences with an ever-expanding array of molecular and structural biology data. The methods described here will empower research and genomic contact tracing for laboratories worldwide.\n\nSoftware AvailabilityUSHER is available to users through the UCSC Genome Browser at https://genome.ucsc.edu/cgi-bin/hgPhyloPlace. The source code and detailed instructions on how to compile and run UShER are available from https://github.com/yatisht/usher.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Jose Alquicira-Hernandez", - "author_inst": "Garvan Institute of Medical Research" + "author_name": "Yatish Turakhia", + "author_inst": "University of California, Santa Cruz" }, { - "author_name": "Joseph Powell", - "author_inst": "Garvan-Weizmann Centre for Cellular Genomics" + "author_name": "Bryan Thornlow", + "author_inst": "University of California, Santa Cruz" }, { - "author_name": "Tri Giang Phan", - "author_inst": "Garvan Institute of Medical Research" + "author_name": "Angie S Hinrichs", + "author_inst": "University of California at Santa Cruz" + }, + { + "author_name": "Nicola de Maio", + "author_inst": "European Bioinformatics Institute" + }, + { + "author_name": "Landen Gozashti", + "author_inst": "Harvard University" + }, + { + "author_name": "Robert Lanfear", + "author_inst": "Australia National University" + }, + { + "author_name": "David Haussler", + "author_inst": "UC Santa Cruz" + }, + { + "author_name": "Russ Corbett-Detig", + "author_inst": "UC Santa Cruz" } ], "version": "1", - "license": "cc_by_nd", - "type": "contradictory results", + "license": "cc_no", + "type": "new results", "category": "genomics" }, { @@ -1137102,39 +1137622,35 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.09.23.20200055", - "rel_title": "Combinations of PCR and isothermal amplification techniques are suitable for fast and sensitive detection of SARS-CoV-2 viral RNA", + "rel_doi": "10.1101/2020.09.23.20200485", + "rel_title": "Electrostatic filters to reduce COVID-19 spread in bubble CPAP: an in vitro study of safety and efficacy.", "rel_date": "2020-09-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.23.20200055", - "rel_abs": "The newly identified coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causes coronavirus disease 2019 (COVID-19) and has affected over 25 million people worldwide as of 31 August 2020. To aid in the development of diagnostic kits for rapid and sensitive detection of the virus, we evaluated a combination of polymerase chain reaction (PCR) and isothermal nucleic acid amplification techniques. Here, we compared conventional PCR and loop-mediated isothermal amplification (LAMP) methods with hybrid techniques such as polymerase chain displacement reaction (PCDR) and a newly developed PCR-LAMP method. We found that the hybrid methods demonstrated higher sensitivity and assay reaction rates than those of the classic LAMP and PCR techniques and can be used to for SARS-CoV-2 detection. The proposed methods based on the modern hybrid amplification techniques markedly improve virus detection and, therefore, can be extremely useful in the development of new diagnostic kits.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.23.20200485", + "rel_abs": "BackgroundBubble CPAP may be used in infants with suspected or confirmed COVID-19. Electrostatic filters may reduce cross-infection. This study aims to determine if including a filter in the bubble CPAP circuit impacts stability of pressure delivery.\n\nMethodsA new electrostatic filter was placed before (pre) or after (post) the bubble CPAP generator, or with no filter (control) in an in vitro study. Pressure was recorded at the nasal interface for 18 h (6 L/min; 7 cmH2O) on three occasions for each configuration. Filter failure was defined as pressure >9 cmH20 for 60 continuous minutes. The filter was weighed before and after each experiment.\n\nResultsMean (SD) time to reach the fail-point was 257 (116) min and 525 (566) min for filter placement pre- and post-CPAP generator, respectively. Mean pressure was higher throughout in the pre-generator position compared to control. The filter weight was heavier at study end in the pre-compared to the post-generator position.\n\nConclusionsPlacement of the filter at the pre-generator position in a bubble CPAP circuit should be avoided due to unstable mean pressure. Filters are likely to become saturated with water over time. The post-generator position may accommodate a filter, but regular pressure monitoring and early replacement are required.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Dmitriy A Varlamov", - "author_inst": "Syntol, Moscow" + "author_name": "Jonathan W Davis", + "author_inst": "King Edward Memorial and Perth Children's Hospital" }, { - "author_name": "Konstantin A Blagodatskikh", - "author_inst": "Pirogov Russian National Research Medical University Moscow, Russia" + "author_name": "J Jane Pillow", + "author_inst": "School of Human Sciences, University of Western Australia" }, { - "author_name": "Evgeniya V Smirnova", - "author_inst": "Institute of Bioorganic Chemistry (RAS)" - }, - { - "author_name": "Vladimir M. V Kramarov", - "author_inst": "Institut obsej genetiki imeni N I Vavilova RAN" + "author_name": "Matt Cooper", + "author_inst": "Biometrics, Telethon Kids Institute, University of Western Australia" }, { - "author_name": "Konstantin B Ignatov", - "author_inst": "Institut obsej genetiki imeni N I Vavilova RAN" + "author_name": "Mar Janna Dahl", + "author_inst": "School of Human Sciences, University of Western Australia" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pediatrics" }, { "rel_doi": "10.1101/2020.09.22.20195628", @@ -1138888,25 +1139404,37 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2020.09.25.20201376", - "rel_title": "COVID-19 mortality rate in Russia: forecasts and reality evaluation", + "rel_doi": "10.1101/2020.09.24.20200303", + "rel_title": "Serum SARS-CoV-2 nucleocapsid antigen detection is essential for primary diagnostics of SARS-CoV-2-associated pneumonia", "rel_date": "2020-09-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.25.20201376", - "rel_abs": "COVID-19 is an extremely dangerous disease that not only spreads quickly, but is also characterized by a high mortality rate. Therefore, predicting the number of deaths from the new coronavirus is an urgent task. The aim of the study is to analyze the factors affecting COVID-19 mortality rate in various countries, to predict direct and indirect victims of the pandemic in the Russian Federation, and to estimate additional mortality during the pandemic based on the demographic data. The main research method is econometric modeling. Comparison of various data was also applied. The authors' calculations were based on data from the RSSS, the World Bank, as well as specialized sites with coronavirus statistics in Russia and in the world. A predictive estimation of the deceased number of people due to the pandemic in Russia was made. It is confirmed that the deaths proportion of the completed cases of the disease depends on the level of testing. It is shown that the revealed mortality of the disease depends on the proportion of completed cases, on the population age structure, and on how early the pandemic entered the country compared to the other countries. It is determined that the number of additional deaths due to the coronavirus is approximately 31 thousand people. The analysis revealed that the relatively low proportion of COVID in Russia is the result of a special approach to the cause of death determination. The mortality rate in Russia in April 2020 was about 3% higher than in April 2019. The share of the deceased health workers in the total coronavirus mortality in the Russian Federation is higher than in the developed countries, which indicates an underestimation of the data on COVID- 19 deaths in the Russian Federation, and the unsatisfactory quality of the Russian healthcare system. The number of direct and indirect victims of the pandemic in the Russian Federation at the end of July was approximately 43 thousand people.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.24.20200303", + "rel_abs": "The article highlights the diagnostic value of SARS-CoV-2 seroconversion in patients with pneumonia based on the results of a retrospective study conducted at the height of the COVID-19 pandemic in Moscow, Russia", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Marina Lifshits", - "author_inst": "Institute of Economics of the Ural Branch of the Russian Academy of Sciences" + "author_name": "Yuri S. Lebedin", + "author_inst": "Xema-Medica Co. Ltd" + }, + { + "author_name": "Olga V. Lyang", + "author_inst": "Pirogov Russian National Research Medical University" + }, + { + "author_name": "Anaida G. Galstyan", + "author_inst": "Federal Center of Brain Research and Neurotechnologies" }, { - "author_name": "Natalia Neklyudova", - "author_inst": "Institute of Economics, Ural Branch of the Russian Academy of Sciences, Yekaterinburg, Russia" + "author_name": "Vsevolod V. Belousov", + "author_inst": "Federal Center of Brain Research and Neurotechnologies" + }, + { + "author_name": "Denis V. Rebrikov", + "author_inst": "Pirogov Russian National Research Medical University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1140634,39 +1141162,99 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.22.20194183", - "rel_title": "Modelling optimal vaccination strategy for SARS-CoV-2.", + "rel_doi": "10.1101/2020.09.23.20197251", + "rel_title": "Role of IgG against N-protein of SARS-CoV2 in COVID19 clinical outcomes", "rel_date": "2020-09-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.22.20194183", - "rel_abs": "The COVID-19 outbreak has highlighted our vulnerability to novel infections. Faced with this threat and no effective treatment, in line with many other countries, the UK adopted enforced social distancing (lockdown) to reduce transmission- successfully reducing the reproductive number, R, below one. However, given the large pool of susceptible individuals that remain, complete relaxation of controls is likely to generate a substantial second wave. Vaccination remains the only foreseeable means of both containing the infection and returning to normal interactions and behaviour. Here, we consider the optimal targeting of vaccination within the UK, with the aim of minimising future deaths or quality adjusted life year (QALY) losses. We show that, for a range of assumptions on the action and efficacy of the vaccine, targeting older age groups first is optimal and can avoid a second wave if the vaccine prevents transmission as well as disease.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.23.20197251", + "rel_abs": "The Nucleocapsid Protein (N Protein) of severe acute respiratory syndrome Coronavirus 2 (SARS-CoV2) is located in the viral core. Immunoglobulin G (IgG) targeting N protein is detectable in the serum of infected patients. The effect of high titers of IgG against N-protein on clinical outcomes of SARS-CoV2 disease has not been described. We studied 400 RT-PCR confirmed SARS-CoV2 patients to determine independent factors associated with poor outcomes, including MICU admission, prolonged MICU stay and hospital admissions, and in-hospital mortality. We also measured serum IgG against the N protein and correlated its concentrations with clinical outcomes. We found that several factors, including Charlson comorbidity Index (CCI), high levels of IL6, and presentation with dyspnea were associated with poor clinical outcomes. It was shown that higher CCI and higher IL6 levels were independently associated with in-hospital mortality. Anti-N protein IgG was detected in the serum of 55 (55%) patients at the time of admission. A high concentration of antibodies, defined as signal to cut off ratio (S/Co)> 1.5 (75 percentile of all measurements), was found in 25 (25%) patients. The multivariable logistic regression models showed that between being an African American, higher CCI, lymphocyte counts, and S/Co ratio> 1.5, only S/Co ratio were independently associated with MICU admission and longer length of stay in hospital. This study recommends that titers of IgG targeting N-protein of SARS-CoV2 at admission is a prognostic factor for the clinical course of disease and should be measured in all patients with SARS-CoV2 infection.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Sam Moore", - "author_inst": "University of Warwick" + "author_name": "Mayank Batra", + "author_inst": "University of Miami" }, { - "author_name": "Edward M Hill", - "author_inst": "University of Warwick" + "author_name": "Runxia Tian", + "author_inst": "Miami VA Healthcare System" }, { - "author_name": "Louise Dyson", - "author_inst": "University of Warwick" + "author_name": "Chongxu Zhang", + "author_inst": "Miami VA Healthcare System" }, { - "author_name": "Michael Tildesley", - "author_inst": "University of Warwick" + "author_name": "Emile Clarence", + "author_inst": "University of Miami" }, { - "author_name": "Matt J Keeling", - "author_inst": "University of Warwick" + "author_name": "Camila Sofia Sacher", + "author_inst": "University of Miami" + }, + { + "author_name": "Justin Nestor Miranda", + "author_inst": "University of Miami" + }, + { + "author_name": "Justin Rafa O De La Fuente", + "author_inst": "University of Miami" + }, + { + "author_name": "Megan Mathew", + "author_inst": "University of Miami" + }, + { + "author_name": "Desmond Green", + "author_inst": "University of Miami" + }, + { + "author_name": "Sayari Patel", + "author_inst": "University of Miami" + }, + { + "author_name": "Maria Virginia Perez Bastidas", + "author_inst": "University of Miami" + }, + { + "author_name": "Sara Haddadi", + "author_inst": "University of Miami" + }, + { + "author_name": "Mukunthan Murthi", + "author_inst": "University of Miami" + }, + { + "author_name": "Miguel Santiago Gonzalez", + "author_inst": "University of Miami" + }, + { + "author_name": "Shweta Kambali", + "author_inst": "University of Miami" + }, + { + "author_name": "Kayo HM Santos", + "author_inst": "University of Miami" + }, + { + "author_name": "Huda Asif", + "author_inst": "University of Miami" + }, + { + "author_name": "Farzaneh Modarresi", + "author_inst": "Express Gene" + }, + { + "author_name": "Mohammad Faghihi", + "author_inst": "Express Gene" + }, + { + "author_name": "Mehdi Mirsaeidi", + "author_inst": "University of Miami" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2020.09.23.310565", @@ -1142360,43 +1142948,55 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.09.22.20199265", - "rel_title": "A Cost Analysis of Childbirth for Pregnant Women with COVID-19 in the Epicentre of Nigeria", + "rel_doi": "10.1101/2020.09.22.20199661", + "rel_title": "Risk of adverse COVID-19 outcomes for people living with HIV: a rapid review and meta-analysis", "rel_date": "2020-09-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.22.20199265", - "rel_abs": "The Coronavirus disease 2019 (COVID-19) has been a major disruptor of health systems globally. Its emergence has warranted the need to reorganize maternity services for childbirth. However, it is not known if this comes at an additional cost to women. We conducted a hospital-based cost analysis to estimate the out-of-pocket cost of spontaneous vaginal delivery (SVD) and caesarean delivery (CD). Specifically, we collected facility-based and household costs of all nine pregnant women with COVID-19 who were managed between 1st April and 30th August 2020 at the largest teaching hospital in Lagos, the epicentre of COVID-19 in Nigeria. We compared the mean facility-based costs for the cohort with costs paid by pregnant women pre-COVID-19, identifying major cost drivers. We also estimated what would have been paid without subsidies, testing assumptions with a sensitivity analysis. Findings showed that total utilization cost ranged from US$494 (N190,150) for SVD with mild COVID-19 to US$4,553 (N1,751,165) for emergency CD with severe COVID-19. Though 32-66% of facility-based cost has been subsidized, cost of SVD and CD have doubled and tripled respectively during the pandemic compared to those paid pre-COVID. Out of the facility-based costs paid, cost of personal protective equipment (PPE) was the major cost driver (50%) for SVD and CD. Supplemental oxygen was a major cost driver when women had severe COVID-19 symptoms and required long admission (48%). Excluding treatment costs specifically for COVID-19, mean facility-based costs for SVD and CD are US$228 (N87,750) and US$948 (N364,551) respectively. Our study demonstrates that despite cost exemptions and donations, utilization costs remain prohibitive. Regulation of the PPE and medical oxygen supply chain can help drive down utilization cost and reduce mark-ups being passed to users. The pandemic offers an opportunity to expand advocacy for subscription to health insurance schemes in order to avoid any catastrophic health expenditure.\n\nKEY MESSAGESO_LITotal utilization cost ranged from US$494 (N190,150) for spontaneous vaginal delivery with mild COVID-19 to US$4,553 (N1,751,165) for emergency caesarean delivery with severe COVID-19.\nC_LIO_LICost of personal protective equipment was the major cost driver (50%) for vaginal and elective caesarean deliveries. Medical oxygen was a major cost driver when women had severe COVID-19 symptoms (48%) and required long admission.\nC_LIO_LIThough 32-66% of total cost have been subsidized, facility-based cost of vaginal and caesarean deliveries has doubled and tripled respectively during the pandemic compared to those paid pre-COVID.\nC_LIO_LIThe study findings highlight the urgent need to implement strategies that can help to minimize the rising costs that pregnant women with COVID-19 face in accessing and utilizing critical intra-partum care.\nC_LI", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.22.20199661", + "rel_abs": "ObjectiveTo assess whether people living with HIV (PLWH) are at increased risk of COVID-19 mortality or adverse outcomes, and whether antiretroviral therapy (ART) influences this risk.\n\nDesignRapid review with meta-analysis and narrative synthesis.\n\nMethodsWe searched databases including Embase, Medline, medRxiv, and Google Scholar up to 26th August 2020 for studies describing COVID-19 outcomes in PLWH and conducted a meta-analysis of higher quality studies.\n\nResultsWe identified 1,908 studies and included 19 in the review. In a meta-analysis of five studies, PLWH had a higher risk of COVID-19 mortality (hazard ratio (HR) 1.93, 95% Confidence Interval (CI): 1.59-2.34) compared to people without HIV. Risk of death remained elevated for PLWH in a subgroup analysis of hospitalised cohorts (HR 1.54, 95% CI: 1.05-2.24) and studies of PLWH across all settings (HR 2.08, 95%CI: 1.69-2.56). Eight other studies assessed the association between HIV and COVID-19 outcomes, but provided inconclusive, lower-quality evidence due to potential confounding and selection bias.\n\nThere were insufficient data on the effect of CD4+ T cell count and HIV viral load on COVID-19 outcomes. Eleven studies reported COVID-19 outcomes by ART-regimen. In the two largest studies, tenofovir-disoproxil-fumarate (TDF)-based regimens were associated with a lower risk of adverse COVID-19 outcomes, although these analyses are susceptible to confounding by comorbidities.\n\nConclusionEvidence is emerging that suggests a moderately increased risk of COVID-19 mortality amongst PLWH. Further investigation into the relationship between COVID-19 outcomes and CD4+ T cell count, HIV viral load, ART and the use of TDF is warranted.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Aduragbemi Banke-Thomas", - "author_inst": "London School of Economics and Political Science" + "author_name": "Maya Mellor", + "author_inst": "Medical Sciences Division, University of Oxford, Oxford, UK" }, { - "author_name": "Christian Chigozie Makwe", - "author_inst": "Lagos University Teaching Hospital" + "author_name": "Anne Bast", + "author_inst": "Medical Sciences Division, University of Oxford, Oxford, UK" }, { - "author_name": "Mobolanle Balogun", - "author_inst": "Lagos University Teaching Hospital" + "author_name": "Nicholas Jones", + "author_inst": "Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK" }, { - "author_name": "Bosede Bukola Afolabi", - "author_inst": "Lagos University Teaching Hospital" + "author_name": "Nia Roberts", + "author_inst": "Outreach Librarian Knowledge Centre, Bodleian Health Care Libraries, Oxford, UK" }, { - "author_name": "Theresa Amaogechukwu Alex-Nwangwu", - "author_inst": "Lagos University Teaching Hospital" + "author_name": "Jose Ordonez-Mena", + "author_inst": "Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK and NIHR Biomedical Research Centre, Oxford University Hospitals NHS Found" }, { - "author_name": "Charles Anawo Ameh", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Alastair Reith", + "author_inst": "Medical Sciences Division, University of Oxford, Oxford, UK" + }, + { + "author_name": "Christopher C Butler", + "author_inst": "Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK." + }, + { + "author_name": "Philippa C Matthews", + "author_inst": "Nuffield Department of Medicine, University of Oxford, Oxford, UK and Department of Infectious Diseases and Microbiology, Oxford University Hospitals NHS Founda" + }, + { + "author_name": "Jienchi Dorward", + "author_inst": "Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK and Centre for the AIDS Programme of Research in South Africa, University " } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "hiv aids" }, { "rel_doi": "10.1101/2020.09.22.20198465", @@ -1144178,35 +1144778,67 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.17.20192872", - "rel_title": "Cold plasma for SARS-CoV-2 Inactivation", + "rel_doi": "10.1101/2020.09.17.20195867", + "rel_title": "DOSING OF THROMBOPROPHYLAXIS AND MORTALITY IN CRITICALLY ILL COVID-19 PATIENTS", "rel_date": "2020-09-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.17.20192872", - "rel_abs": "SARS-CoV-2 infectious virions are viable on various surfaces (e.g., plastic, metals, cardboard) for several hours. This presents a transmission cycle for the human infection that can be broken by developing new inactivation approaches. We employed an efficient cold atmospheric plasma (CAP) with argon feed gas to inactivate SARS-CoV-2 on various surfaces including plastic, metal, cardboard, basketball composite leather, football leather, and baseball leather. These results demonstrate the great potential of CAP as a safe and effective means to prevent virus transmission and infections.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.17.20195867", + "rel_abs": "BackgroundA substantial proportion of critically ill COVID-19 patients develop thromboembolic complications, but it is unclear whether higher doses of thromboprophylaxis are associated with lower mortality rates. The purpose of the study was to evaluate the association of initial dosing strategy of thromboprophylaxis in critically ill COVID-19 patients and the risk of death, thromboembolism, and bleeding.\n\nMethodAll critically ill COVID-19 patients admitted to two intensive care units in March and April 2020 were eligible. Patients were categorized into three groups according to initial daily dose of thromboprophylaxis; low (2500-4500 IU tinzaparin or 2500-5000 IU dalteparin), medium (>4500 IU but <175 IU/kilogram, kg, of body weight tinzaparin or >5000 IU but <200 IU/kg of body weight dalteparin), and high dose ([≥] 175 IU/kg of body weight tinzaparin or [≥]200 IU/kg of body weight dalteparin). Thromboprophylaxis dosage was based on local standardized recommendations, not on degree of critical illness or risk of thrombosis. Cox proportional hazards regression was used to estimate hazard ratios with corresponding 95% confidence intervals of death within 28 days from ICU admission. Multivariable models were adjusted for sex, age, body-mass index, Simplified Acute Physiology Score III, invasive respiratory support, and initial dosing strategy of thromboprophylaxis.\n\nResultsA total of 152 patients were included; 67 received low, 48 medium, and 37 high dose thromboprophylaxis. Baseline characteristics did not differ between groups. Mortality was lower in high (13.5%) vs medium (25.0%) and low dose thromboprophylaxis (38.8%) groups, p=0.02. The hazard ratio of death was 0.33 (95% confidence intervals 0.13 - 0.87) among those who received high dose, respectively 0.88 (95% confidence intervals 0.43 - 1.83) among those who received medium dose, as compared with those who received low dose thromboprophylaxis. There were fewer thromboembolic events in the high (2.7%) vs medium (18.8%) and low dose thromboprophylaxis (17.9%) groups, p=0.04, but no difference in the proportion of bleeding events, p=0.16.\n\nConclusionsAmong critically ill COVID-19 patients with respiratory failure, high dose thromboprophylaxis was associated with a lower risk of death and a lower cumulative incidence of thromboembolic events compared with lower doses.\n\nTrial registrationClinicaltrials.gov NCT04412304 June 2 2020, retrospectively registered", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Zhitong Chen", - "author_inst": "University of California, Los Angeles" + "author_name": "Sandra Jonmarker", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Gustavo Garcia Jr.", - "author_inst": "University of California, Los Angeles" + "author_name": "Jacob Hollenberg", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Vaithilingaraja Arumugaswami", - "author_inst": "University of California, Los Angeles" + "author_name": "Martin Dahlberg", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Richard E. Wirz", - "author_inst": "University of California, Los Angeles" + "author_name": "Otto Stackelberg", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Jacob Litorell", + "author_inst": "S\u00f6dersjukhuset" + }, + { + "author_name": "\u00c5sa Everhov", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Hans J\u00e4rnbert-Pettersson", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "M\u00e5rten S\u00f6derberg", + "author_inst": "S\u00f6dersjukhuset" + }, + { + "author_name": "Jonathan Grip", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Anna Schandl", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Mattias G\u016bnther", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Maria Cronhjort", + "author_inst": "Karolinska Institutet" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.09.20.20197608", @@ -1145956,33 +1146588,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.21.20199182", - "rel_title": "Treatment of Moderate to Severe Respiratory COVID-19--A Cost-Utility Analysis", + "rel_doi": "10.1101/2020.09.22.20199422", + "rel_title": "The effect of ABO blood group and antibody class on the risk of COVID-19 infection and severity of clinical outcomes.", "rel_date": "2020-09-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.21.20199182", - "rel_abs": "BackgroundDue to COVID-19s significant morbidity and mortality, identifying the most cost-effective pharmacologic treatment strategy is critical. As such, we determined the most cost-effective strategy for moderate to severe COVID-19 respiratory infections using the United States health care system as a representative model.\n\nMethodsA decision analytic model modelled a base case scenario of a 60-year-old patient admitted to hospital with COVID-19. Patients requiring oxygen were considered moderate severity, and patients with severe COVID-19 required intubation with intensive care. Strategies modelled included giving remdesivir to all patients, remdesivir in severe infections, remdesivir in moderate infections, dexamethasone to all patients, dexamethasone in severe infections, remdesivir in moderate/dexamethasone in severe infections, and best supportive care. Data for the model came from the published literature. The time horizon was 1 year; no discounting was performed due to the short duration. The perspective was of the payer in the United States health care system.\n\nResultsSupportive care for moderate/severe COVID-19 cost $11,112.98/0.8256 QALY. Remdesivir in moderate/dexamethasone in severe infections was the most cost-effective with an incremental cost-effectiveness ratio of $19,764.56/QALY gained compared to supportive care. Probabilistic sensitivity analyses showed remdesivir for moderate/dexamethasone for severe COVID-19 infection was most cost-effective in 88.6% of scenarios and dexamethasone in moderate-severe infections in 11.4% of scenarios. With lower willingness to pay thresholds ($250-$37,500), dexamethasone for severe infections was favoured.\n\nConclusionsRemdesivir for moderate/dexamethasone for severe COVID-19 infections was the0020most cost-effective strategy. Further data is required for remdesivir to better assess its cost effectiveness in treatment of COVID-19.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.22.20199422", + "rel_abs": "The current COVID-19 pandemic has affected more than 22 million cases and caused immense burdens on governments and healthcare systems worldwide. Since its emergence in December 2019, research has been focused on ways to not only treat the infected but also identify those at risk and prevent spread. There is currently no known biological biomarker that can predict the risk of being infected. A growing set of studies have emerged that show an association between ABO blood group and the risk of COVID-19 infection. In this study, we used retrospective observational data in Bahrain to investigate the association between ABO blood group and risk of infection as well as susceptibility to a more severe ICU-requiring infection. We found that individuals with blood group B were at a higher risk of infection, while those with blood group AB were at a lower risk. No association was observed between blood group and the risk of a severe ICU-requiring COVID-19 infection. We extended the analysis to study the association by antibodies present; anti-a (blood groups B and O) and anti-b (blood groups A and O). Antibodies were not found to be associated with either risk of infection or susceptibility to severe infection. The current study, along with the variation in blood group association results, indicates that blood group may not be the most ideal biomarker to predict risk of COVID-19 infection.", "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Stephen E Congly", - "author_inst": "University of Calgary" + "author_name": "Marwa AlMadhi", + "author_inst": "National Task Force for Combatting the Corona Virus (COVID19), Bahrain" }, { - "author_name": "Rhea A Varughese", - "author_inst": "University of Alberta" + "author_name": "Abdulkarim Abdulrahman", + "author_inst": "National Task Force for Combatting the Corona Virus (COVID19), Bahrain" }, { - "author_name": "Crystal E Brown", - "author_inst": "University of Washington" + "author_name": "Abdulla AlAwadhi", + "author_inst": "National Task Force for Combatting the Corona Virus (COVID19), Bahrain" }, { - "author_name": "Fiona M Clement", - "author_inst": "University of Calgary" + "author_name": "Ali Rabaan", + "author_inst": "John Hopkins Aramco Health Care, Saudi Arabia" }, { - "author_name": "Lynora Saxinger", - "author_inst": "University of Alberta" + "author_name": "Manaf AlQahtani", + "author_inst": "National Task Force for Combatting the Corona Virus (COVID19)" } ], "version": "1", @@ -1147721,47 +1148353,67 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.09.21.305490", - "rel_title": "Critical Interactions Between the SARS-CoV-2 Spike Glycoprotein and the Human ACE2 Receptor", + "rel_doi": "10.1101/2020.09.21.305441", + "rel_title": "A natural mutation between SARS-CoV-2 and SARS-CoV determines neutralization by a cross-reactive antibody", "rel_date": "2020-09-21", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.21.305490", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects human cells upon binding of its spike (S) glycoproteins to ACE2 receptors and causes the coronavirus disease 2019 (COVID-19). Therapeutic approaches to prevent SARS-CoV-2 infection are mostly focused on blocking S-ACE2 binding, but critical residues that stabilize this interaction are not well understood. By performing all-atom molecular dynamics (MD) simulations, we identified an extended network of salt bridges, hydrophobic and electrostatic interactions, and hydrogen bonding between the receptor-binding domain (RBD) of the S protein and ACE2. Mutagenesis of these residues on the RBD was not sufficient to destabilize binding but reduced the average work to unbind the S protein from ACE2. In particular, the hydrophobic end of RBD serves as the main anchor site and unbinds last from ACE2 under force. We propose that blocking the hydrophobic surface of RBD via neutralizing antibodies could prove an effective strategy to inhibit S-ACE2 interactions.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.21.305441", + "rel_abs": "Epitopes that are conserved among SARS-like coronaviruses are attractive targets for design of cross-reactive vaccines and therapeutics. CR3022 is a SARS-CoV neutralizing antibody to a highly conserved epitope on the receptor binding domain (RBD) on the spike protein that can cross-react with SARS-CoV-2, but with lower affinity. Using x-ray crystallography, mutagenesis, and binding experiments, we illustrate that of four amino acid differences in the CR3022 epitope between SARS-CoV-2 and SARS-CoV, a single mutation P384A fully determines the affinity difference. CR3022 does not neutralize SARS-CoV-2, but the increased affinity to SARS-CoV-2 P384A mutant now enables neutralization with a similar potency to SARS-CoV. We further investigated CR3022 interaction with the SARS-CoV spike protein by negative-stain EM and cryo-EM. Three CR3022 Fabs bind per trimer with the RBD observed in different up-conformations due to considerable flexibility of the RBD. In one of these conformations, quaternary interactions are made by CR3022 to the N-terminal domain (NTD) of an adjacent subunit. Overall, this study provides insights into antigenic variation and potential for cross-neutralizing epitopes on SARS-like viruses.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Elhan Taka", - "author_inst": "Istanbul Technical University" + "author_name": "Nicholas C. Wu", + "author_inst": "University of Illinois at Urbana-Champaign" }, { - "author_name": "Sema Zeynep Yilmaz", - "author_inst": "Istanbul Technical University" + "author_name": "Meng Yuan", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Mert Golcuk", - "author_inst": "Istanbul Technical University" + "author_name": "Sandhya Bangaru", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Ceren Kilinc", - "author_inst": "Istanbul Technical University" + "author_name": "Deli Huang", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Umut Aktas", - "author_inst": "Istanbul Technical University" + "author_name": "Xueyong Zhu", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Ahmet Yildiz", - "author_inst": "University of California Berkeley" + "author_name": "Chang-Chun D. Lee", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Mert Gur", - "author_inst": "Istanbul Technical University" + "author_name": "Hannah L. Turner", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Linghang Peng", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Linlin Yang", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "David Nemazee", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Andrew B. Ward", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Ian A. Wilson", + "author_inst": "The Scripps Research Institute" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.09.20.297242", @@ -1149075,37 +1149727,77 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.15.20194506", - "rel_title": "Distribution equality as an optimal epidemic mitigation strategy", + "rel_doi": "10.1101/2020.09.15.20194985", + "rel_title": "Longitudinal analysis of the utility of liver biochemistry in hospitalised COVID-19 patients as prognostic markers", "rel_date": "2020-09-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.15.20194506", - "rel_abs": "Upon the development of a drug or vaccine, a successful response to a global pandemic, such as COVID-19, requires the capacity for efficient distribution at a global scale. Considering constraints on production and shipping, most existing strategies seek to maximize the outflow of therapeutics, hence optimizing for rapid dissemination. Surprisingly, we find that this intuitive approach is counterproductive. The reason is that focusing strictly on the quantity of disseminated therapeutics, such strategies disregard their specific spreading patterns, most crucially, they overlook the interplay of these spreading patterns with those of the pathogens. This results in a discrepancy between supply and demand, that prohibits efficient mitigation even under optimal conditions of superfluous drug/vaccine flow. Therefore, here, we design a dissemination strategy that naturally follows the predicted spreading patterns of the epidemic, optimizing not just for supply volume, but also for its congruency with the anticipated demand. Specifically, we show that epidemics spread relatively uniformly across all destinations, and hence we introduce an equality constraint into our dissemination that prioritizes supply homogeneity. This strategy may, at times, slow down the supply rate in certain locations, however, thanks to its egalitarian nature, which mimics the flow of the viral spread, it provides a dramatic leap in overall mitigation efficiency, saving more lives with orders of magnitude less resources.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.15.20194985", + "rel_abs": "Background: COVID-19, the clinical syndrome caused by infection with SARS-CoV-2, has been associated with deranged liver biochemistry in studies from China, Italy and the USA. However, the clinical utility of liver biochemistry as a prognostic marker of outcome for COVID-19 is currently debated. Methods: We extracted routinely collected clinical data from a large teaching hospital in the UK, matching 585 hospitalised SARS-CoV-2 RT-PCR-positive patients to 1165 hospitalised SARS-CoV-2 RT-PCR-negative patients for age, gender, ethnicity and pre-existing comorbidities. Liver biochemistry was compared between groups over time to determine whether derangement was associated with outcome. Results: 26.8% (157/585) of COVID-19 patients died, compared to 11.9% (139/1165) in the non-COVID-19 group (p<0.001). At presentation, a significantly higher proportion of the COVID-19 group had elevated alanine aminotransferase (20.7% vs. 14.6%, p=0.004) and hypoalbuminaemia (58.7% vs. 35.0%, p<0.001), compared to the non-COVID-19 group. Within the COVID-19 group, those with hypoalbuminaemia at presentation had 1.83-fold increased hazards of death compared to those with normal albumin (adjusted hazard ratio [HR] 1.83, 95% CI 1.25-2.67), whilst the hazard of death was ~4-fold higher in those aged [≥]75 years (adjusted HR 3.96, 95% CI 2.59-6.04) and ~3-fold higher in those with pre-existing liver disease (adjusted HR 3.37, 95% CI 1.58-7.16). In the COVID-19 group, alkaline phosphatase increased (R=0.192, p<0.0001) and albumin declined (R=-0.123, p=0.0004) over time in patients who died. We did not find a significant association between other liver biochemistry and death. Conclusion: In this UK population, liver biochemistry is commonly deranged in patients with COVID-19 but only baseline low albumin and a rising alkaline phosphatase over time are prognostic markers for death.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Adar Hacohen", - "author_inst": "Bar-Ilan University, Ramat-Gan, Israel / Augmanity , Rehovot, Israel" + "author_name": "Tingyan Wang", + "author_inst": "University of Oxford" + }, + { + "author_name": "David A Smith", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Cori Campbell", + "author_inst": "University of Oxford" }, { - "author_name": "Reuven Cohen", - "author_inst": "Department of Mathematics, Bar-Ilan University, Ramat-Gan, Israel" + "author_name": "Steve Harris", + "author_inst": "University of Oxford" }, { - "author_name": "Sol Efroni", - "author_inst": "Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel" + "author_name": "Hizni Salih", + "author_inst": "University of Oxford" }, { - "author_name": "Ido Bachelet", - "author_inst": "Augmanity, Rehovot, Israel" + "author_name": "Kinga A Varnai", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" }, { - "author_name": "Baruch Barzel", - "author_inst": "Department of Mathematics, Bar-Ilan University, Ramat-Gan, Israel/The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel" + "author_name": "Kerrie Woods", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Theresa Noble", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Oliver Freeman", + "author_inst": "University of Oxford" + }, + { + "author_name": "Zuzana Moysova", + "author_inst": "University of Oxford" + }, + { + "author_name": "Thomas Marjot", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Gwilym J Webb", + "author_inst": "Addenbrooke's Hospital" + }, + { + "author_name": "Jim Davies", + "author_inst": "University of Oxford" + }, + { + "author_name": "Eleanor Barnes", + "author_inst": "University of Oxford" + }, + { + "author_name": "Philippa C Matthews", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1150969,83 +1151661,79 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.09.15.20195453", - "rel_title": "Improvement and Multi-Population Generalizability of a Deep Learning-Based Chest Radiograph Severity Score for COVID-19", + "rel_doi": "10.1101/2020.09.16.20194316", + "rel_title": "Graphene nanoplatelet and Graphene oxide functionalization of face mask materials inhibits infectivity of trapped SARS-CoV-2", "rel_date": "2020-09-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.15.20195453", - "rel_abs": "PurposeTo improve and test the generalizability of a deep learning-based model for assessment of COVID-19 lung disease severity on chest radiographs (CXRs) from different patient populations.\n\nMaterials and MethodsA published convolutional Siamese neural network-based model previously trained on hospitalized patients with COVID-19 was tuned using 250 outpatient CXRs. This model produces a quantitative measure of COVID-19 lung disease severity (pulmonary x-ray severity (PXS) score). The model was evaluated on CXRs from four test sets, including 3 from the United States (patients hospitalized at an academic medical center (N=154), patients hospitalized at a community hospital (N=113), and outpatients (N=108)) and 1 from Brazil (patients at an academic medical center emergency department (N=303)). Radiologists from both countries independently assigned reference standard CXR severity scores, which were correlated with the PXS scores as a measure of model performance (Pearson r). The Uniform Manifold Approximation and Projection (UMAP) technique was used to visualize the neural network results.\n\nResultsTuning the deep learning model with outpatient data improved model performance in two United States hospitalized patient datasets (r=0.88 and r=0.90, compared to baseline r=0.86). Model performance was similar, though slightly lower, when tested on the United States outpatient and Brazil emergency department datasets (r=0.86 and r=0.85, respectively). UMAP showed that the model learned disease severity information that generalized across test sets.\n\nConclusionsPerformance of a deep learning-based model that extracts a COVID-19 severity score on CXRs improved using training data from a different patient cohort (outpatient versus hospitalized) and generalized across multiple populations.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.16.20194316", + "rel_abs": "Recent advancements in bidimensional nanoparticles such as Graphene nanoplatelets (G) and the derivative Graphene oxide (GO) have the potential to meet the need for highly functional personal protective equipment (PPE) that confers increased protection against SARS-CoV-2 infection and the spread COVID-19. The ability of G and GO to interact with and bind microorganisms as well as RNA and DNA provides an opportunity to develop engineered textiles for use in PPE. The face masks widely used in health care and other high-risk settings for COVID transmission provide only a physical barrier that decreases likelihood of infection and do not inactivate the virus. Here, we show pre-incubation of viral particles with free GO inhibits SARS-CoV-2 infection of VERO cells. Highly relevant to PPE materials, when either polyurethane or cotton material was loaded with G or GO and culture medium containing SARS-CoV-2 viral particles either filtered through or incubated with the functionalized materials, the infectivity of the medium was nearly completely inhibited. The findings presented here constitute an important nanomaterials-based strategy to significantly increase face mask and other PPE efficacy in protection against the SARS-CoV-2 virus and COVID-19 that may be applicable to additional anti-SARS-CoV-2 measures including water filtration, air purification, and diagnostics.\n\nOne Sentence SummaryCotton and polyurethane materials functionalized with bidimensional Graphene nanoplatelets trap SARS-CoV-2 and have the potential to reduce spread of COVID-19.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Matthew D Li", - "author_inst": "Massachusetts General Hospital" + "author_name": "Flavio De Maio", + "author_inst": "Fondazione Policlinico Universitario A. Gemelli IRCSS and Universita Cattolica del Sacro Cuore, Rome, Italy" }, { - "author_name": "Nishanth T Arun", - "author_inst": "Massachusetts General Hospital" + "author_name": "Valentina Palmieri", + "author_inst": "Universita Cattolica del Sacro Cuore; Fondazione Policlinico Universitario A. Gemelli IRCSS; & Istituto dei Sistemi Complessi, CNR, Rome, Italy" }, { - "author_name": "Mehak Aggarwal", - "author_inst": "Massachusetts General Hospital" + "author_name": "Gabriele Babini", + "author_inst": "Fondazione Policlinico Universitario A. Gemelli, IRCCS, Rome, Italy" }, { - "author_name": "Sharut Gupta", - "author_inst": "Massachusetts General Hospital" + "author_name": "Alberto Augello", + "author_inst": "Universita Cattolica del Sacro Cuore, Rome, Italy" }, { - "author_name": "Praveer Singh", - "author_inst": "Massachusetts General Hospital" + "author_name": "Ivana Palucci", + "author_inst": "Fondazione Policlinico Universitario A. Gemelli IRCSS & Universita Cattolica del Sacro Cuore, Rome, Italy" }, { - "author_name": "Brent P Little", - "author_inst": "Massachusetts General Hospital" + "author_name": "Giordano Perini", + "author_inst": "Universita Cattolica del Sacro Cuore, Rome, Italy" }, { - "author_name": "Dexter P Mendoza", - "author_inst": "Massachusetts General Hospital" + "author_name": "Alessandro Salustri", + "author_inst": "Universita Cattolica del Sacro Cuore, Rome, Italy" }, { - "author_name": "Gustavo C.A. Corradi", - "author_inst": "Diagnosticos da America SA (DASA)" + "author_name": "Marco De Spirito", + "author_inst": "Universita Cattolica del Sacro Cuore & Fondazione Policlinico Universitario A. Gemelli IRCSS, Rome, Italy" }, { - "author_name": "Marcelo S Takahashi", - "author_inst": "Diagnosticos da America SA (DASA)" + "author_name": "Maurizio Sanguinetti", + "author_inst": "Fondazione Policlinico Universitario A. Gemelli IRCSS & Universita Cattolica del Sacro Cuore, Rome, Italy" }, { - "author_name": "Suely F Ferraciolli", - "author_inst": "Diagnosticos da America SA (DASA)" + "author_name": "Giovanni Delogu", + "author_inst": "Universita Cattolica del Sacro Cuore, Rome & Mater Olbia Hospital, Olbia, Italy" }, { - "author_name": "Marc D Succi", - "author_inst": "Massachusetts General Hospital" + "author_name": "Laura Giorgia Rizzi", + "author_inst": "Directa Plus S.p.A. c/o ComoNExT, Lomazzo, Italy" }, { - "author_name": "Min Lang", - "author_inst": "Massachusetts General Hospital" + "author_name": "Giulio Cesareo", + "author_inst": "Directa Plus S.p.A. c/o ComoNExT, Lomazzo, Italy" }, { - "author_name": "Bernardo C Bizzo", - "author_inst": "Massachusetts General Hospital" - }, - { - "author_name": "Ittai Dayan", - "author_inst": "Massachusetts General Hospital" + "author_name": "Patrick Soon-Shiong", + "author_inst": "NantWorks" }, { - "author_name": "Felipe C Kitamura", - "author_inst": "Diagnosticos da America SA (DASA)" + "author_name": "Michela Sali", + "author_inst": "Fondazione Policlinico Universitario A. Gemelli IRCSS & Universita Cattolica del Sacro Cuore, Rome, Italy" }, { - "author_name": "Jayashree Kalpathy-Cramer", - "author_inst": "Massachusetts General Hospital" + "author_name": "Massimiliano Papi", + "author_inst": "Universita Cattolica del Sacro Cuore & Fondazione Policlinico Universitario A. Gemelli IRCSS, Rome, Italy" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "radiology and imaging" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2020.09.16.20195685", @@ -1152503,393 +1153191,37 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.09.16.20194571", - "rel_title": "Mortality outcomes with hydroxychloroquine and chloroquine in COVID-19: an international collaborative meta-analysis of randomized trials", + "rel_doi": "10.1101/2020.09.18.20195776", + "rel_title": "Urban rail transport and SARS-CoV-2 infections: an ecological study in Lisbon Metropolitan Area", "rel_date": "2020-09-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.16.20194571", - "rel_abs": "Substantial COVID-19 research investment has been allocated to randomized clinical trials (RCTs) on hydroxychloroquine/chloroquine, which currently face recruitment challenges or early discontinuation. We aimed to estimate the effects of hydroxychloroquine and chloroquine on survival in COVID-19 from all currently available RCT evidence, published and unpublished. We conducted a rapid meta-analysis of ongoing, completed, or discontinued RCTs on hydroxychloroquine or chloroquine treatment for any COVID-19 patients (protocol: https://osf.io/QESV4/). We systematically identified unpublished RCTs (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, Cochrane COVID-registry up to June 11, 2020), and published RCTs (PubMed, medRxiv and bioRxiv up to October 16, 2020). All-cause mortality was extracted (publications/preprints) or requested from investigators and combined in random-effects meta-analyses, calculating odds ratios (ORs) with 95% confidence intervals (CIs), separately for hydroxychloroquine and chloroquine. Prespecified subgroup analyses included patient setting, diagnostic confirmation, control type, and publication status. Sixty-three trials were potentially eligible. We included 14 unpublished trials (1308 patients) and 14 publications/preprints (9011 patients). Results for hydroxychloroquine are dominated by RECOVERY and WHO SOLIDARITY, two highly pragmatic trials, which employed relatively high doses and included 4716 and 1853 patients, respectively (67% of the total sample size). The combined OR on all-cause mortality for hydroxychloroquine was 1.11 (95% CI: 1.02, 1.20; I2=0%; 26 trials; 10,012 patients) and for chloroquine 1.77 (95%CI: 0.15, 21.13, I2=0%; 4 trials; 307 patients). We identified no subgroup effects. We found that treatment with hydroxychloroquine was associated with increased mortality in COVID-19 patients, and there was no benefit of chloroquine. Findings have unclear generalizability to outpatients, children, pregnant women, and people with comorbidities.", - "rel_num_authors": 94, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.18.20195776", + "rel_abs": "Introduction: Large number of passengers, limited space and shared surfaces can transform public transportation into a hub of epidemic spread. This study was conducted to investigate whether proximity to railway stations, a proxy for utilization, was associated with higher rates of SARS-CoV-2 infection across small-areas of Lisbon Metropolitan Area (Portugal). Methods: The number of SARS-CoV-2 confirmed infections from March 2 until July 5, 2020 at parish-level was obtained from the National Epidemiological Surveillance System. We used a Geographic Information System to estimate proximity to railway stations from the six railway lines operating in the area. Then, we fitted a quasi-Poisson generalized linear regression model to estimate the relative risks (RR) and corresponding 95% Confidence Intervals (95%CI). Results: Between May 2 and July 5, 2020, there were a total of 17,168 SARS-CoV-2 infections in the Lisbon Metropolitan Area, with wide disparities between parishes. Globally, parishes near one of the railway lines (Sintra) presented significantly higher SARS-CoV-2 infection rates (RR=1.42, 95%CI 1.16, 1.75) compared to those parishes located far away from railway stations, while the opposite happened for parishes near other railway lines (Sado/Fertagus), whose infection rates were significantly lower than those observed in parishes located far away from railway stations (RR=0.66, 95%CI 0.50, 0.87). However, the associations varied according to the stage of the epidemic and according to mitigation measures in place. Regression results also revealed an increasing influence of socioeconomic deprivation on SARS-CoV-2 infections. Conclusions: We found no consistent association between proximity to railway stations and SARS-CoV-2 infection rates in the most affected metropolitan area of the country, suggesting that other factors (e.g. socioeconomic deprivation) might play a more prominent role in the epidemic dynamics.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Cathrine Axfors", - "author_inst": "Stanford University" - }, - { - "author_name": "Andreas M Schmitt", - "author_inst": "University of Basel" - }, - { - "author_name": "Perrine Janiaud", - "author_inst": "University of Basel" - }, - { - "author_name": "Janneke van 't Hooft", - "author_inst": "Amsterdam University" - }, - { - "author_name": "Sherief Abd-Elsalam", - "author_inst": "Tanta University" - }, - { - "author_name": "Ehab F Abdo", - "author_inst": "Assiut University" - }, - { - "author_name": "Benjamin S Abella", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Javed Akram", - "author_inst": "University of Health Sciences, Lahore" - }, - { - "author_name": "Ravi K Amaravadi", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Derek C Angus", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Yaseen M Arabi", - "author_inst": "King Saud Bin Abdulaziz University for Health Sciences and King Abdullah International Medical Research Center" - }, - { - "author_name": "Shehnoor Azhar", - "author_inst": "University of Health Sciences, Lahore" - }, - { - "author_name": "Lindsey R Baden", - "author_inst": "Brigham and Women's Hospital" - }, - { - "author_name": "Arthur W Baker", - "author_inst": "Duke University Medical Center" - }, - { - "author_name": "Leila Belkhir", - "author_inst": "Cliniques universitaires Saint-Luc, Universite Catholique de Louvain" - }, - { - "author_name": "Thomas Benfield", - "author_inst": "Copenhagen University Hospital, Amager and Hvidovre" - }, - { - "author_name": "Marvin A H Berrevoets", - "author_inst": "Elisabeth-Tweesteden hospital" - }, - { - "author_name": "Cheng-Pin Chen", - "author_inst": "Taoyuan General Hospital, Ministry of Health and Welfare" - }, - { - "author_name": "Tsung-Chia Chen", - "author_inst": "Taichung Hospital, Ministry of Health and Welfare" - }, - { - "author_name": "Shu-Hsing Cheng", - "author_inst": "Taoyuan General Hospital, Ministry of Health and Welfare" - }, - { - "author_name": "Chien-Yu Cheng", - "author_inst": "Taoyuan General Hospital, Ministry of Health and Welfare" - }, - { - "author_name": "Wei-Sheng Chung", - "author_inst": "Taichung Hospital, Ministry of Health and Welfare" - }, - { - "author_name": "Yehuda Z Cohen", - "author_inst": "Sanofi" - }, - { - "author_name": "Lisa N Cowan", - "author_inst": "Sanofi" - }, - { - "author_name": "Olav Dalgard", - "author_inst": "Akershus University Hospital" - }, - { - "author_name": "Fernando F de Almeida e Val", - "author_inst": "Fundacao de Medicina Tropical Dr. Heitor Vieira Dourado" - }, - { - "author_name": "Marcus V G de Lacerda", - "author_inst": "Fundacao de Medicina Tropical Dr. Heitor Vieira Dourado" - }, - { - "author_name": "Gisely C de Melo", - "author_inst": "Fundacao de Medicina Tropical Dr. Heitor Vieira Dourado" - }, - { - "author_name": "Lennie Derde", - "author_inst": "University Medical Center Utrecht" - }, - { - "author_name": "Vincent Dubee", - "author_inst": "Angers University Hospital" - }, - { - "author_name": "Anissa Elfakir", - "author_inst": "Ividata Life Sciences" - }, - { - "author_name": "Anthony C Gordon", - "author_inst": "Imperial College London and Imperial College Healthcare NHS Trust" - }, - { - "author_name": "Carmen M Hernandez-Cardenas", - "author_inst": "Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas" - }, - { - "author_name": "Thomas Hills", - "author_inst": "Medical Research Institute of New Zealand" - }, - { - "author_name": "Andy I M Hoepelman", - "author_inst": "University Medical Center Utrecht" - }, - { - "author_name": "Yi-Wen Huang", - "author_inst": "Chang Hua Hospital, Ministry of Health and Welfare" - }, - { - "author_name": "Bruno Igau", - "author_inst": "Sanofi" - }, - { - "author_name": "Ronghua Jin", - "author_inst": "Beijing Youan Hospital, Capital Medical University" - }, - { - "author_name": "Felipe Jurado-Camacho", - "author_inst": "Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas" - }, - { - "author_name": "Khalid S Khan", - "author_inst": "University of Granada" - }, - { - "author_name": "Peter G Kremsner", - "author_inst": "University of Tubingen" - }, - { - "author_name": "Benno Kreuels", - "author_inst": "University Medical Center Hamburg-Eppendorf" - }, - { - "author_name": "Cheng-Yu Kuo", - "author_inst": "Pingtung Hospital, Ministry of Health and Welfare" - }, - { - "author_name": "Thuy Le", - "author_inst": "Duke University Medical Center" - }, - { - "author_name": "Yi-Chun Lin", - "author_inst": "Taoyuan General Hospital, Ministry of Health and Welfare" - }, - { - "author_name": "Wu-Pu Lin", - "author_inst": "Taipei Hospital, Ministry of Health and Welfare" - }, - { - "author_name": "Tse-Hung Lin", - "author_inst": "Chang Hua Hospital, Ministry of Health and Welfare" - }, - { - "author_name": "Magnus Nakrem Lyngbakken", - "author_inst": "Akershus University Hospital" - }, - { - "author_name": "Colin McArthur", - "author_inst": "Medical Research Institute of New Zealand" - }, - { - "author_name": "Bryan McVerry", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Patricia Meza-Meneses", - "author_inst": "Hospital Regional de Alta especialidad de Ixtapaluca" - }, - { - "author_name": "Wuelton M Monteiro", - "author_inst": "Fundacao de Medicina Tropical Dr. Heitor Vieira Dourado" - }, - { - "author_name": "Susan C Morpeth", - "author_inst": "Middlemore Hospital" - }, - { - "author_name": "Ahmad Mourad", - "author_inst": "Duke University Medical Center" - }, - { - "author_name": "Mark J Mulligan", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Srinivas Murthy", - "author_inst": "University of British Columbia School of Medicine" - }, - { - "author_name": "Susanna Naggie", - "author_inst": "Duke University Medical Center" - }, - { - "author_name": "Shanti Narayanasamy", - "author_inst": "Duke University Medical Center" - }, - { - "author_name": "Alistair Nichol", - "author_inst": "Monash University" - }, - { - "author_name": "Lewis A Novack", - "author_inst": "Brigham and Women's Hospital, Harvard Medical School" - }, - { - "author_name": "Sean M O'Brien", - "author_inst": "Duke University Medical Center and Duke Clinical Research Institute" - }, - { - "author_name": "Nwora Lance Okeke", - "author_inst": "Duke University Medical Center" - }, - { - "author_name": "Lena Perez", - "author_inst": "Excelya" - }, - { - "author_name": "Rogelio Perez-Padilla", - "author_inst": "Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas" - }, - { - "author_name": "Laurent Perrin", - "author_inst": "Sanofi" - }, - { - "author_name": "Arantxa Remigio-Luna", - "author_inst": "Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas" - }, - { - "author_name": "Norma E Rivera-Martinez", - "author_inst": "Hospital Regional de Alta especialidad de Oaxaca" - }, - { - "author_name": "Frank W Rockhold", - "author_inst": "Duke University Medical Center and Duke Clinical Research Institute" - }, - { - "author_name": "Sebastian Rodriguez-Llamazares", - "author_inst": "Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas" - }, - { - "author_name": "Robert Rolfe", - "author_inst": "Duke University Medical Center" - }, - { - "author_name": "Rossana Rosa", - "author_inst": "UnityPoint Health" - }, - { - "author_name": "Helge Rosjo", - "author_inst": "Akershus University Hospital" - }, - { - "author_name": "Vanderson S Sampaio", - "author_inst": "Fundacao de Medicina Tropical Dr. Heitor Vieira Dourado" - }, - { - "author_name": "Todd B Seto", - "author_inst": "University of Hawaii John A. Burns School of Medicine" - }, - { - "author_name": "Muhammad Shehzad", - "author_inst": "University of Health Sciences, Lahore" - }, - { - "author_name": "Shaimaa Soliman", - "author_inst": "Menoufia University" - }, - { - "author_name": "Jason E Stout", - "author_inst": "Duke University Medical Center" - }, - { - "author_name": "Ireri Thirion-Romero", - "author_inst": "Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas" - }, - { - "author_name": "Andrea B Troxel", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Ting-Yu Tseng", - "author_inst": "Taichung Hospital, Ministry of Health and Welfare" - }, - { - "author_name": "Nicholas A Turner", - "author_inst": "Duke University Medical Center" - }, - { - "author_name": "Robert J Ulrich", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Stephen R Walsh", - "author_inst": "Brigham and Women's Hospital" - }, - { - "author_name": "Steve A Webb", - "author_inst": "Monash University" - }, - { - "author_name": "Jesper M Weehuizen", - "author_inst": "University Medical Center Utrecht" - }, - { - "author_name": "Maria Velinova", - "author_inst": "PRA Health Science" - }, - { - "author_name": "Hon-Lai Wong", - "author_inst": "Keelung Hospital, Ministry of Health and Welfare" - }, - { - "author_name": "Rebekah Wrenn", - "author_inst": "Duke University Medical Center" - }, - { - "author_name": "Fernando G Zampieri", - "author_inst": "HCor-Hospital do Coracao" - }, - { - "author_name": "Wu Zhong", - "author_inst": "National Engineering Research Center for the Emergency Drug, Beijing Institute of Pharmacology and Toxicology" + "author_name": "Milton Severo", + "author_inst": "1-EPIUnit - Instituto de Saude Publica, Universidade do Porto, Rua das Taipas, nr 135, 4050-600 Porto, Portugal. 2-Departamento de Ciencias da Saude Publica e F" }, { - "author_name": "David Moher", - "author_inst": "Ottawa Hospital Research Institute" + "author_name": "Ana Isabel Ribeiro", + "author_inst": "1-EPIUnit - Instituto de Saude Publica, Universidade do Porto, Rua das Taipas, nr 135, 4050-600 Porto, Portugal." }, { - "author_name": "Steven N Goodman", - "author_inst": "Stanford University" + "author_name": "Raquel Lucas", + "author_inst": "1-EPIUnit - Instituto de Saude Publica, Universidade do Porto, Rua das Taipas, nr 135, 4050-600 Porto, Portugal. 2-Departamento de Ciencias da Saude Publica e F" }, { - "author_name": "John P A Ioannidis", - "author_inst": "Stanford University" + "author_name": "Teresa Leao", + "author_inst": "1-EPIUnit - Instituto de Saude Publica, Universidade do Porto, Rua das Taipas, nr 135, 4050-600 Porto, Portugal. 2-Departamento de Ciencias da Saude Publica e F" }, { - "author_name": "Lars G Hemkens", - "author_inst": "University of Basel" + "author_name": "Henrique Barros", + "author_inst": "1-EPIUnit - Instituto de Saude Publica, Universidade do Porto, Rua das Taipas, nr 135, 4050-600 Porto, Portugal. 2-Departamento de Ciencias da Saude Publica e F" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1154601,51 +1154933,67 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2020.09.14.20194670", - "rel_title": "Estimating Risk of Mechanical Ventilation and Mortality Among Adult COVID-19 patients Admitted to Mass General Brigham: The VICE and DICE Scores", + "rel_doi": "10.1101/2020.09.17.300996", + "rel_title": "Monocytes and macrophages, targets of SARS-CoV-2: the clue for Covid-19 immunoparalysis", "rel_date": "2020-09-17", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.14.20194670", - "rel_abs": "BackgroundRisk stratification of COVID-19 patients upon hospital admission is key for their successful treatment and efficient utilization of hospital resources.\n\nObjectiveTo evaluate the risk factors associated with ventilation need and mortality.\n\nDesign, setting and participantsWe established a retrospective cohort of COVID-19 patients from Mass General Brigham hospitals. Demographic, clinical, and admission laboratory data were obtained from electronic medical records of patients admitted to hospital with laboratory-confirmed COVID-19 before May 19th, 2020. Using patients admitted to Massachusetts General Hospital (MGH, derivation cohort), multivariable logistic regression analyses were used to construct the Ventilation in COVID Estimator (VICE) and Death in COVID Estimator (DICE) risk scores.\n\nMeasurementsThe primary outcomes were ventilation status and death.\n\nResultsThe entire cohort included 1042 patients (median age, 64 years; 56.8% male). The derivation and validation cohorts for the risk scores included 578 and 464 patients, respectively. We found seven factors to be independently predictive for ventilation requirement (diabetes mellitus, dyspnea, alanine aminotransferase, troponin, C-reactive protein, neutrophil-lymphocyte ratio, and lactate dehydrogenase), and 10 factors to be predictors of in-hospital mortality (age, sex, diabetes mellitus, chronic statin use, albumin, C-reactive protein, neutrophil-lymphocyte ratio, mean corpuscular volume, platelet count, and procalcitonin). Using these factors, we constructed the VICE and DICE risk scores, which performed with C-statistics of at least 0.8 in our cohorts. Importantly, the chronic use of a statin was associated with protection against death due to COVID-19. The VICE and DICE score calculators have been placed on an interactive website freely available to the public (https://covid-calculator.com/).\n\nLimitationsOne potential limitation is the modest sample sizes in both our derivation and validation cohorts.\n\nConclusionThe risk scores developed in this study may help clinicians more appropriately determine which COVID-19 patients will need to be managed with greater intensity.", - "rel_num_authors": 8, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.17.300996", + "rel_abs": "To date, the Covid-19 pandemic affected more than 18 million individuals and caused more than 690, 000 deaths. Its clinical expression is pleiomorphic and severity is related to age and comorbidities such as diabetes and hypertension. The pathophysiology of the disease relies on aberrant activation of immune system and lymphopenia that has been recognized as a prognosis marker. We wondered if the myeloid compartment was affected in Covid-19 and if monocytes and macrophages could be infected by SARS-CoV-2. We show here that SARS-CoV-2 efficiently infects monocytes and macrophages without any cytopathic effect. Infection was associated with the secretion of immunoregulatory cytokines (IL-6, IL-10, TGF-{beta}) and the induction of a macrophagic specific transcriptional program characterized by the upregulation of M2-type molecules. In addition, we found that in vitro macrophage polarization did not account for the permissivity to SARS-CoV-2, since M1-and M2-type macrophages were similarly infected. Finally, in a cohort of 76 Covid-19 patients ranging from mild to severe clinical expression, all circulating monocyte subsets were decreased, likely related to massive emigration into tissues. Monocytes from Covid-19 patients exhibited decreased expression of HLA-DR and increased expression of CD163, irrespective of the clinical status. Hence, SARS-CoV-2 drives circulating monocytes and macrophages inducing immunoparalysis of the host for the benefit of Covid-19 disease progression.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Christopher J Nicholson", - "author_inst": "Massachusetts General Hospital/Harvard Medical School" + "author_name": "Asma Boumaza", + "author_inst": "Aix-Marseille Univ, IRD, APHM, MEPHI, IHU-Mediterranee Infection" }, { - "author_name": "Luke Wooster", - "author_inst": "Case Western Reserve University School of Medicine" + "author_name": "Laetitia Gay", + "author_inst": "Aix-Marseille Univ, IRD, APHM, MEPHI, IHU-Mediterranee Infection" }, { - "author_name": "Haakon H Sigurslid", - "author_inst": "Massachusetts General Hospital" + "author_name": "Soraya Mezouar", + "author_inst": "Aix-Marseille Univ, IRD, APHM, MEPHI, IHU-Mediterranee Infection" }, { - "author_name": "Rebecca F Li", - "author_inst": "Massachusetts General Hospital" + "author_name": "Aissatou Bailo Diallo", + "author_inst": "Aix-Marseille Univ, IRD, APHM, MEPHI, IHU-Mediterranee Infection" }, { - "author_name": "Wanlin Jiang", - "author_inst": "Massachusetts General Hospital" + "author_name": "Moise Michel", + "author_inst": "Aix-Marseille Univ, IRD, APHM, MEPHI, IHU-Mediterranee Infection" }, { - "author_name": "Wenjie Tian", - "author_inst": "Massachusetts General Hospital" + "author_name": "Benoit Desnues", + "author_inst": "Aix-Marseille Univ, IRD, APHM, MEPHI, IHU-Mediterranee Infection" + }, + { + "author_name": "Didier Raoult", + "author_inst": "Aix-Marseille Univ, IRD, APHM, MEPHI, IHU-Mediterranee Infection" }, { - "author_name": "Christian Lino Cardenas", - "author_inst": "MassachusettsGeneral Hospital" + "author_name": "Bernard LA SCOLA", + "author_inst": "Aix-Marseille Univ, IRD, APHM, MEPHI, IHU-Mediterranee Infection" }, { - "author_name": "Rajeev Malhotra", - "author_inst": "Massachusetts General Hospital/Harvard Medical School" + "author_name": "Philippe Halfon", + "author_inst": "Aix-Marseille Univ, IRD, APHM, MEPHI, IHU-Mediterranee Infection" + }, + { + "author_name": "Joana Vitte", + "author_inst": "Aix-Marseille Univ, IRD, APHM, MEPHI, IHU-Mediterranee Infection" + }, + { + "author_name": "Daniel Olive", + "author_inst": "Centre de Recherche en Cancerologie de Marseille, CRCM" + }, + { + "author_name": "Jean-Louis Mege", + "author_inst": "Aix-Marseille Univ, IRD, APHM, MEPHI, IHU-Mediterranee Infection" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2020.09.16.300871", @@ -1156459,29 +1156807,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.14.20190447", - "rel_title": "A Comparative Study to Find a Suitable Model for an Improved Real-Time Monitoring of The Interventions to Contain COVID-19 Outbreak in The High Incidence States of India", + "rel_doi": "10.1101/2020.09.14.20194159", + "rel_title": "Containment to outbreak tipping points in COVID-19", "rel_date": "2020-09-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.14.20190447", - "rel_abs": "Background On March 11, 2020, The World Health Organization (WHO) declared coronavirus disease (COVID-19) as a global pandemic. There emerged a need for reliable models to estimate the imminent incidence and overall assessment of the outbreak, in order to develop effective interventions and control strategies. One such vital metrics for monitoring the transmission trends over time is the time-dependent effective reproduction number (Rt). Rt is an estimate of secondary cases caused by an infected individual at a time during the outbreak, given that a certain population proportion is already infected. Misestimated Rt is particularly concerning when probing the association between the changes in transmission rate and the changes in the implemented policies. In this paper, we substantiate the implementation of the instantaneous reproduction number (Rins) method over the conventional method to estimate Rt viz case reproduction number (Rcase), by unmasking the real-time estimation ability of both methodologies using credible datasets. Materials & Methods We employed the daily incidence dataset of COVID-19 for India and high incidence states to estimate Rins and Rcase. We compared the real-time projection obtained through these methods by corroborating those states that are containing a high number of COVID19 cases and are conducting high and efficient COVID-19 testing. The Rins and Rcase were estimated using R0 and EpiEstim packages respectively in R software 4.0.0. Results Although, both the Rins and Rcase for the selected states were higher during the lockdown phases (March 25 - June 1, 2020) and subsequently stabilizes co-equally during the unlock phase (June 1- August 23, 2020), Rins demonstrated variations in accordance with the interventions while Rcase remained generalized and under- & overestimated. A larger difference in Rins and Rcase estimates were also observed for states that are conducting high testing. Conclusion Of the two methods, Rins elucidated a better real-time progression of the COVID-19 outbreak conceptually and empirically, than that of Rcase. However, we also suggest considering the assumptions corroborated in the implementations which may result in misleading conclusions in the real world.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.14.20194159", + "rel_abs": "Non-pharmaceutical interventions (NPIs) have been a cornerstone in managing emergent diseases such as COVID-191-4. However, despite their potential to contain or attenuate the epidemic, the effects of NPIs on disease dynamics are not well understood1,5-7. We show that saturation of NPIs with the increase in infected individuals, an expected consequence of limited contact tracing and healthcare capacities, produces a positive feedback in the disease growth rate and a threshold between two alternative states--containment and outbreak8. These alternative states were previously related with the strength of NPIs but not with the infection number2,9-11. Furthermore, the transition between these states involves an abrupt acceleration in disease dynamics, which we report here for several COVID-19 outbreaks around the world. The consequences of a positive feedback in population dynamics at low numbers is a phenomenon widely studied in ecology--the Allee effect. This effect is a determinant of extinction-outbreak states, geographic synchronization, spatial spread, and the effect of exogenous variables, as vaccination12-15. As countries are relaxing containing measures, recognizing an NPI-induced Allee effect may be essential for deploying containment strategies within and among countries16 and acknowledges the need for early warning indicators of approaching epidemic tipping points17.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Amrutha G.S", - "author_inst": "International Institute for Population Sciences (IIPS)" + "author_name": "Matias Arim", + "author_inst": "Universidad de la Republica, Uruguay" }, { - "author_name": "Abhibhav Sharma", - "author_inst": "Jawaharlal Nehru University" + "author_name": "Daniel Herrera-Esposito", + "author_inst": "Universidad de la Republica, Uruguay" }, { - "author_name": "Anudeepti Sharma", - "author_inst": "Central University of Rajasthan" + "author_name": "Paola Bermolen", + "author_inst": "Universidad de la Republica, Uruguay" + }, + { + "author_name": "Alvaro Cabana", + "author_inst": "Universidad de la Republica, Uruguay" + }, + { + "author_name": "Maria Ines Fariello", + "author_inst": "Universidad de la Republica, Uruguay" + }, + { + "author_name": "Mauricio Lima", + "author_inst": "Pontificia Universidad Catolica, Chile" + }, + { + "author_name": "Hector Romero", + "author_inst": "Universidad de la Republica, Uruguay" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1158297,33 +1158661,81 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.13.20193524", - "rel_title": "Differences in innate Intracellular viral suppression competencies may explain variations in morbidity and mortality from SARS-CoV-2 infection.", + "rel_doi": "10.1101/2020.09.12.20193391", + "rel_title": "Characterizing COVID-19 Clinical Phenotypes and Associated Comorbidities and Complication Profiles", "rel_date": "2020-09-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.13.20193524", - "rel_abs": "SARS-CoV-2 infection and COVID-19 ravage the world with wide variations in morbidity and mortality that have remained largely unexplained, even by mutations in protein coding regions. In this study, we analyzed available complete SARS-CoV-2 sequences using the CpG index as a signature of Zinc finger antiviral protein (ZAP) activity to examine population variations in innate intracellular antiviral competencies. The result suggests that differential ZAP activity may be a major determinant of the outcome of SARS-CoV-2 infection. SARS-CoV-2 sequences from Africa, Asia, and pools of asymptomatic patients had I_CpG signature evidence of high ZAP activity, while SARS-CoV-2 sequences from North America and Intensive Care Unit or Deceased patients had I_CpG signature of low ZAP activity. ZAP activity is linked to the interferon system. Low ZAP activity may be part of the explanation for the increased morbidity of SARS-CoV-2 in the elderly and with comorbidities like diabetes, obesity, and hypertension. It may also provide some insight into the discrepancies between invitro anti-SARS-CoV-2 activities of candidate therapies and performance in clinical trials. Furthermore, our results suggest that asymptomatic patients may paradoxically shed a more dangerous virus.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.12.20193391", + "rel_abs": "Background: There is limited understanding of heterogeneity in outcomes across hospitalized patients with coronavirus disease 2019 (COVID-19). Identification of distinct clinical phenotypes may facilitate tailored therapy and improve outcomes. Objective: Identify specific clinical phenotypes across COVID-19 patients and compare admission characteristics and outcomes. Design, Settings, and Participants: Retrospective analysis of 1,022 COVID-19 patient admissions from 14 Midwest U.S. hospitals between March 7, 2020 and August 25, 2020. Methods: Ensemble clustering was performed on a set of 33 vitals and labs variables collected within 72 hours of admission. K-means based consensus clustering was used to identify three clinical phenotypes. Principal component analysis was performed on the average covariance matrix of all imputed datasets to visualize clustering and variable relationships. Multinomial regression models were fit to further compare patient comorbidities across phenotype classification. Multivariable models were fit to estimate the association between phenotype and in-hospital complications and clinical outcomes. Main outcomes and measures: Phenotype classification (I, II, III), patient characteristics associated with phenotype assignment, in-hospital complications, and clinical outcomes including ICU admission, need for mechanical ventilation, hospital length of stay, and mortality. Results: The database included 1,022 patients requiring hospital admission with COVID-19 (median age, 62.1 [IQR: 45.9-75.8] years; 481 [48.6%] male, 412 [40.3%] required ICU admission, 437 [46.7%] were white). Three clinical phenotypes were identified (I, II, III); 236 [23.1%] patients had phenotype I, 613 [60%] patients had phenotype II, and 173 [16.9%] patients had phenotype III. When grouping comorbidities by organ system, patients with respiratory comorbidities were most commonly characterized by phenotype III (p=0.002), while patients with hematologic (p<0.001), renal (p<0.001), and cardiac (p<0.001) comorbidities were most commonly characterized by phenotype I. The adjusted odds of respiratory (p<0.001), renal (p<0.001), and metabolic (p<0.001) complications were highest for patients with phenotype I, followed by phenotype II. Patients with phenotype I had a far greater odds of hepatic (p<0.001) and hematological (p=0.02) complications than the other two phenotypes. Phenotypes I and II were associated with 7.30-fold (HR: 7.30, 95% CI: (3.11-17.17), p<0.001) and 2.57-fold (HR: 2.57, 95% CI: (1.10-6.00), p=0.03) increases in the hazard of death, respectively, when compared to phenotype III. Conclusion: In this retrospective analysis of patients with COVID-19, three clinical phenotypes were identified. Future research is urgently needed to determine the utility of these phenotypes in clinical practice and trial design.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Shaibu Oricha Bello", - "author_inst": "College Of Health Sciences, Usmanu Danfodiyo University" + "author_name": "Elizabeth R Lusczek", + "author_inst": "University of Minnesota" }, { - "author_name": "Ehimario Igumbor", - "author_inst": "School of Public Health, University of the Western Cape, Cape Town, South Africa" + "author_name": "Nicholas E Ingraham", + "author_inst": "University of Minnesota" }, { - "author_name": "Yusuf Yahaya Deeni", - "author_inst": "Department of Microbiology & Biotechnology, Federal University Dutse, PMB 7156, Jigawa State, Nigeria." + "author_name": "Basil Karam", + "author_inst": "Medical College of Wisconsin" }, { - "author_name": "Chinwe Lucia Ochu", - "author_inst": "Nigeria Center for Disease Control, Abuja, Nigeria" + "author_name": "Jennifer Proper", + "author_inst": "University of Minnesota" }, { - "author_name": "Mustapha Ayodele Popoola", - "author_inst": ". Research & Development Matters, Tertiary Education Trust Fund, Abuja" + "author_name": "Lianne Siegel", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Erika Helgeson", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Sahar Lotfi-Emran", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Emily J. Zolfaghari", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Emma Jones", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Michael Usher", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Jeffrey Chipman", + "author_inst": "University of Minnesota" + }, + { + "author_name": "R. Adams Dudley", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Bradley Benson", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Genevieve B Melton", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Anthony Charles", + "author_inst": "University of North Carolina" + }, + { + "author_name": "Monica I Lupei", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Christopher J Tignanelli", + "author_inst": "University of Minnesota" } ], "version": "1", @@ -1159723,81 +1160135,81 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.11.20191940", - "rel_title": "Shedding of infectious SARS-CoV-2 from airways in hospitalized COVID-19 patients in relation to serum antibody responses", + "rel_doi": "10.1101/2020.09.11.20192690", + "rel_title": "Development of a serological assay to identify SARS-CoV-2 antibodies in COVID-19 patients", "rel_date": "2020-09-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.11.20191940", - "rel_abs": "To understand the risk of transmission of SARS-CoV-2 in hospitalized COVID-19 patients we simultaneously assessed the presence of SARS-CoV-2 RNA, live infectious virus in the airways, and virus-specific IgG and neutralizing antibodies in sera in 36 hospitalized COVID-19 patients. SARS-CoV-2 could be cultured from four patients, all with low or undetectable antibody response. Our data suggests that the level of SARS-CoV-2 antibodies may correlate to risk for shedding live SARS-CoV-2 virus in hospitalized COVID-19 patients.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.11.20192690", + "rel_abs": "Coronavirus Disease 2019 (COVID-19) is a global pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). While detection of SARS-CoV-2 by polymerase chain reaction with reverse transcription (RT-PCR) is currently used to diagnose acute COVID-19 infection, serological assays are needed to study the humoral immune response to SARS-CoV-2. SARS-CoV-2 IgG/A/M antibodies against SARS-CoV-2 spike (S) protein and its receptor-binding domain (RBD) were characterized using an enzyme-linked immunosorbent assay (ELISA) and assessed for their ability to neutralize live SARS-CoV-2 virus in recovered subjects who were RT-PCR-positive (n=153), RT-PCR-negative (n=55), and control samples collected pre-COVID-19 (n=520). Anti-SARS-CoV-2 antibodies were detected in 90.9% of resolved subjects up to 180 days post-symptom onset. Anti-S protein and anti-RBD IgG titers correlated (r= 0.5157 and r = 0.6010, respectively) with viral neutralization. Of the RT-PCR-positive subjects, 22 (14.3%) did not have anti-SARS-CoV-2 antibodies; and of those, 17 had RT-PCR cycle threshold (Ct) values >27, raising the possibility that these indeterminate results are from individuals who were not infected, or had mild infection that failed to elicit an antibody response. This study highlights the importance of serological surveys to determine population-level immunity based on infection numbers as determined by RT-PCR.", "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Hedvig Glans", - "author_inst": "Karolinska Institutet" + "author_name": "Angela Huynh", + "author_inst": "McMaster University" }, { - "author_name": "Sara Gredmark-Russ", - "author_inst": "Karolinska Institutet" + "author_name": "Donald M Arnold", + "author_inst": "McMaster University" }, { - "author_name": "Mikaela Olausson", - "author_inst": "Public Health Agency of Sweden" + "author_name": "James W Smith", + "author_inst": "McMaster University" }, { - "author_name": "Sara Falck-Jones", - "author_inst": "Karolinska Institutet" + "author_name": "Jane C Moore", + "author_inst": "McMaster University" }, { - "author_name": "Renata Varnaite", - "author_inst": "Karolinska Institutet" + "author_name": "Ali Zhang", + "author_inst": "McMaster University" }, { - "author_name": "Wanda Christ", - "author_inst": "Karolinska Institutet" + "author_name": "Zain Chagla", + "author_inst": "McMaster University" }, { - "author_name": "Kimia T Maleki", - "author_inst": "Karolinska Institutet" + "author_name": "Bart J Harvey", + "author_inst": "Hamilton Public Health Services" }, { - "author_name": "Maria Lind Karlberg", - "author_inst": "Public health Agency of Sweden" + "author_name": "Hannah D Stacey", + "author_inst": "McMaster University" }, { - "author_name": "Sandra Broddesson", - "author_inst": "Public Health Agency of Sweden" + "author_name": "Jann C Ang", + "author_inst": "McMaster University" }, { - "author_name": "Ryan Falck-Jones", - "author_inst": "Karolinska Institutet" + "author_name": "Rumi Clare", + "author_inst": "McMaster University" }, { - "author_name": "Max Bell", - "author_inst": "Karolinska Institutet" + "author_name": "Nikola Ivetic", + "author_inst": "McMaster University" }, { - "author_name": "Niclas Johansson", - "author_inst": "Karolinska Institutet" + "author_name": "Vasudhevan T Chetty", + "author_inst": "Hamilton Health Sciences" }, { - "author_name": "Anna Farnert", - "author_inst": "Karolinska Institutet" + "author_name": "Dawn ME Bowdish", + "author_inst": "McMaster University" }, { - "author_name": "Anna Smed Sorensen", - "author_inst": "Karolinska Institutet" + "author_name": "Matthew S Miller", + "author_inst": "McMaster University" }, { - "author_name": "Jonas Klingstrom", - "author_inst": "Center for Infectious Medicine, Department of Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden" + "author_name": "John G Kelton", + "author_inst": "McMaster University" }, { - "author_name": "Andreas Brave", - "author_inst": "Public Health Agency of Sweden" + "author_name": "Ishac Nazy", + "author_inst": "McMaster University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1161585,31 +1161997,31 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.09.09.20191320", - "rel_title": "How to Make COVID-19 Contact Tracing Apps work: Insights From Behavioral Economics", + "rel_doi": "10.1101/2020.09.10.20191890", + "rel_title": "Novel Coronavirus (COVID-19) health awareness among the United Arab Emirates Population", "rel_date": "2020-09-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.09.20191320", - "rel_abs": "Due to network effects, Contact Tracing Apps (CTAs) are only effective if many people download them. However, the response to CTAs has been tepid. For example, in France less than 2 million people (roughly 3% of the population) downloaded the CTA. Against this background, we carry out an online experiment to show that CTAs can still play a key role in containing the spread of COVID-19, provided that they are re-conceptualized to account for insights from behavioral science. We start by showing that carefully devised in-app notifications are effective in inducing prudent behavior like wearing a mask or staying home. In particular, people that are notified that they are taking too much risk and could become a superspreader engage in more prudent behavior. Building on this result, we suggest that CTAs should be re-framed as Behavioral Feedback Apps (BFAs). The main function of BFAs would be providing users with information on how to minimize the risk of contracting COVID-19, like how crowded a store is likely to be. Moreover, the BFA could have a rating system that allows users to flag stores that do not respect safety norms like wearing masks. These functions can inform the behavior of app users, thus playing a key role in containing the spread of the virus even if a small percentage of people download the BFA. While effective contact tracing is impossible when only 3% of the population downloads the app, less risk taking by small portions of the population can produce large benefits. BFAs can be programmed so that users can also activate a tracing function akin to the one currently carried out by CTAs. Making contact tracing an ancillary, opt-in function might facilitate a wider acceptance of BFAs.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.10.20191890", + "rel_abs": "BackgroundIn response to the global (COVID-19) epidemic, the United Arab Emirates (UAE) government is taking precautionary action to mitigate the spread of the virus and protect the safety and well-being of citizens, residents, and visitors. The knowledge and practices of individuals will probably have an important bearing on the course of the coronavirus disease 2019 pandemic. The aim of this study was to evaluate the knowledge and practices toward COVID-19 among the general public in the UAE during the current outbreak COVID-19.\n\nMethodsA cross-sectional online survey of 1356 of respondents in the UAE we conducted during the epidemic outbreak between 9th to 24th June-2020. The questionnaire consisted of three sections: Socio-demographic, participants knowledge, and participants practices. Independent-samples t-test, one-way analysis of variance (ANOVA), chi-square, and binary logistic regression have used. A p-value of (p < 0.05) was considered statistically significant.\n\nResultsOf the total sample, 72% were females, 47% % were aged between 30-49 years, 57.2% were from Sharjah, 65.6% had a college degree, and 40.6% were unemployed. The total correct score of knowledge and practices questions was high 85% and 90%, respectively.\n\nMales gender, other marital status, and illiterate/primary educational levels had a lower level of knowledge and practices than others. participants aged 18-29 had little higher knowledge than other ages but had a lower level in practices, people who live in Abu Dhabi had better knowledge and practice than other emirates, employed people had a lower level of knowledge but higher in practice. Binary logistic regression analysis presented that females, 18-29 years, and married participants significantly associated with a higher score of knowledge, while female gender, over 30 years old, the martial status of singles, college-level and higher, unemployed, were significantly associated with high mean practice score.\n\nConclusionsTo our knowledge, the current study is one of the first studies to evaluate the knowledge and practices of UAE population toward COVID-19. Most of the respondents demonstrate an excellent level of knowledge and awareness as well as proper conscious practices. Continuing to implement the health education programs pursued by the UAE is highly important to maintain the appropriate level of awareness among the public.", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Ian Ayres", - "author_inst": "Yale Law School" + "author_name": "Balsam Qubais", + "author_inst": "University of Sharjah" }, { - "author_name": "Alessandro Romano", - "author_inst": "Bocconi Law School/ Yale Law School" + "author_name": "Iffat Elbarazi", + "author_inst": "Institute of Public Health" }, { - "author_name": "Chiara Sotis", - "author_inst": "London School of Economics and Political Science and Political Science" + "author_name": "Mai Barakat", + "author_inst": "Mansoura University" } ], "version": "1", "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.09.10.20192195", @@ -1163119,37 +1163531,77 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.10.20191965", - "rel_title": "Estimating COVID-19 contribution to total excess mortality", + "rel_doi": "10.1101/2020.09.10.20191189", + "rel_title": "SARS-CoV-2 detection by extraction-free qRT-PCR for massive and rapid COVID-19 diagnosis during a pandemic", "rel_date": "2020-09-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.10.20191965", - "rel_abs": "We compared the total excess mortality per week in relation to the reported Covid-19 related deaths in the Stockholm region (Sweden). Total excess mortality peaked under the weeks of high COVID-19-related mortality, but 25% of these deaths were not recognized as Covid-related. Most of these deaths occurred outside hospitals. Total all-cause mortality in excess to average all-cause mortality during the epidemic peak period may provide a comprehensive picture of the total burden of COVID19-related deaths.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.10.20191189", + "rel_abs": "COVID-19 pandemic severely impacted the healthcare and economy on a global scale. It is widely recognized that mass testing is an efficient way to contain the infection spread as well as the development of informed policies for disease management. However, the current COVID-19 worldwide infection rates increased demand in the rapid and reliable screening of SARS-CoV-2 infection.\n\nWe compared the performance of qRT-PCR in direct heat-inactivated, heat-inactivated/pelleted samples against RNA in a group of 74 subjects (44 positive and 30 negative). In addition, we compared the sensitivity of heat-inactivated/pelleted in another group of 196 COVID-19 positive samples.\n\nOur study suggests that swab sample heat-inactivation and pelleting show higher accuracy for SARS-CoV-2 detection PCR assay compared to heat-inactivation only (89% vs 83% of the detection in RNA). The accuracy of detection using direct samples varied depending on the sample transport and storage media as well as the concentration of viral particles.\n\nOur study suggests that purified RNA provides more accurate results, however, direct qRT-PCR may help to significantly increase testing capacity. Switching to the direct sample testing is justified if the number of tests is doubled at least.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Ville N Pimenoff", - "author_inst": "Karolinska Institutet" + "author_name": "Diana Avetyan", + "author_inst": "Institute of Molecular Biology NAS RA" }, { - "author_name": "Miriam Elfstrom", - "author_inst": "Karolinska Institutet" + "author_name": "Andranik Chavushyan", + "author_inst": "Institute of Molecular Biology NAS RA" }, { - "author_name": "Iacopo Baussano", - "author_inst": "International Agency for Research on Cancer" + "author_name": "Hovsep Ghazaryan", + "author_inst": "Institute of Molecular Biology NAS RA" }, { - "author_name": "Mikael Bjornstedt", - "author_inst": "Karolinska Institutet" + "author_name": "Ani Melkonyan", + "author_inst": "Institute of Molecular Biology NAS RA" }, { - "author_name": "Joakim Dillner", - "author_inst": "Karolinska Institutet" + "author_name": "Ani Stepanyan", + "author_inst": "Institute of Molecular Biology NAS RA" + }, + { + "author_name": "Roksana Zakharyan", + "author_inst": "Russian-Armenian University" + }, + { + "author_name": "Varduhi Hayrapetyan", + "author_inst": "Institute of Molecular Biology NAS RA" + }, + { + "author_name": "Sofi Atshemyan", + "author_inst": "Institute of Molecular Biology NAS RA" + }, + { + "author_name": "Gevorg Martirosyan", + "author_inst": "Davidyants Laboratories" + }, + { + "author_name": "Gayane Melik-Andreasyan", + "author_inst": "National Center of Disease Control and Prevention, Ministry of Health RA" + }, + { + "author_name": "Shushan Sargsyan", + "author_inst": "National Center of Disease Control and Prevention, Ministry of Health RA" + }, + { + "author_name": "Armine Ghazazyan", + "author_inst": "National Center of Disease Control and Prevention, Ministry of Health RA" + }, + { + "author_name": "Naira Aleksanyan", + "author_inst": "National Center of Disease Control and Prevention, Ministry of Health RA" + }, + { + "author_name": "Xiushan Yin", + "author_inst": "Shenyang University of Chemical Technology" + }, + { + "author_name": "Arsen Arakelyan", + "author_inst": "Institute of Molecular Biology NAS RA" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1164637,55 +1165089,83 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.09.20191114", - "rel_title": "Epidemiology and clinical outcome of COVID-19: A multi-centre cross sectional study from Bangladesh", + "rel_doi": "10.1101/2020.09.09.20191122", + "rel_title": "Robust SARS-COV-2 serological population screens via multi-antigen rules-based approach", "rel_date": "2020-09-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.09.20191114", - "rel_abs": "ObjectivesTo investigate SARS-CoV-2 associated epidemiology and clinical outcomes in Bangladesh to understand the course of COVID-19 pandemic and suggest prevention measures.\n\nMethodsA cross-sectional retrospective study was conducted among 1,021 RT-PCR confirmed but recovered COVID-19 cases from six participating hospitals in Bangladesh.\n\nResultsOf the total sample, 111 (10.9%) cases were asymptomatic while the number of symptomatic cases were 910 (89.1%). Higher prevalence of COVID-19 persisted in the male population (75%) and for the 31-40 age group. More than 85% of the samples reported BCG vaccination mark. Common symptoms observed in our study samples were fever (72.4%), cough (55.9%), loss of taste (40.7%) and body ache (40%); whereas for the biochemical parameters, Neutrophil (46.4%), D-dimer (46.1%), Ferritin (37.9%) and SGPT (36.8%) levels were found elevated. Post-COVID complications including pain (31.8%), loss of concentration (24.4%) and anxiety or depression (23.1%) were found significantly prevalent.\n\nConclusionOur study has shown that adult males aged between 31-40 in Bangladesh are more vulnerable to being infected with COVID-19. With an indication for the rising trend of the asymptomatic cases, deployment of interventions to curb further community spread is necessary to avoid the grave outcomes of COVID-19 in Bangladesh.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.09.20191122", + "rel_abs": "More than 300 SARS-COV-2 serological tests have recently been developed using either the nucleocapsid phosphoprotein (N), the spike glycoprotein subunit (S1), and more recently the receptor binding domain (RBD). Most of the assays report very good clinical performance characteristics in well-controlled clinical settings. However, there is a growing belief that good performance characteristics that are obtained during clinical performance trials might not be sufficient to deliver good diagnostic results in population-wide screens that are usually characterized with low seroprevalence. In this paper, we developed a serological assay against N, S1 and RBD using a bead-based multiplex platform and a rules-based computational approach to assess the performance of single and multi-antigen readouts in well-defined clinical samples and in a population-wide serosurvey from blood donors. Even though assays based on single antigen readouts performed similarly well in the clinical samples, there was a striking difference between the antigens on the population-wide screen. Asymptomatic individuals with low antibody titers and sub-optimal assay specificity might contribute to the large discrepancies in population studies with low seroprevalence. A multi-antigen assay requiring partial agreement between RBD, N and S1 readouts exhibited enhanced specificity, less dependency on assay cut-off values and an overall more robust performance in both sample settings. Our data suggest that assays based on multiple antigen readouts combined with a rules-based computational consensus can provide a more robust platform for routine antibody screening.\n\nOne Sentence SummaryClinical and Population-level performance of single and multiplex SARS-CoV-2 serological assays.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Adnan Mannan", - "author_inst": "Department of Genetic Engineering & Biotechnology, Faculty of Biological Sciences, University of Chittagong, Chattogram-4331, Bangladesh" + "author_name": "Christos F Fotis", + "author_inst": "Biomedical Systems Laboratory, National Technical University of Athens, Athens, Greece" }, { - "author_name": "H.M. Hamidullah Mehedi", - "author_inst": "Dept. of Medicine, 250 Beded General Hospital Chittagong, Bangladesh." + "author_name": "Nikolaos Meimetis", + "author_inst": "Biomedical Systems Laboratory, National Technical University of Athens, Athens, Greece" }, { - "author_name": "Naim Hasan Chy", - "author_inst": "University of Chittagong, Bangladesh." + "author_name": "Nikos Tsolakos", + "author_inst": "ProtATonce Ltd" }, { - "author_name": "Md. Omar Qayum", - "author_inst": "Institute of Epidemiology, Disease Control & Research (IEDCR), Dhaka, Bangladesh." + "author_name": "Marianna Politou", + "author_inst": "Department of Clinical Therapeutics, Alexandra General Hospital, National and Kapodistrian University of Athens, Athens, Greece" }, { - "author_name": "Farhana Akter", - "author_inst": "Chittagong Medical College, Bangladesh." + "author_name": "Karolina Akinosoglou", + "author_inst": "Department of Internal Medicine, Division of Infectious Diseases, University Hospital of Patras, Patras, Greece" }, { - "author_name": "Abdur Rob", - "author_inst": "250 beded General Hospital Chittagong" + "author_name": "Vicky Pliaka", + "author_inst": "ProtATonce Ltd," + }, + { + "author_name": "Angeliki Minia", + "author_inst": "ProtATonce Ltd" + }, + { + "author_name": "Evangelos Terpos", + "author_inst": "Department of Clinical Therapeutics, Alexandra General Hospital, National and Kapodistrian University of Athens, Athens, Greece" + }, + { + "author_name": "Ioannis P. Trougakos", + "author_inst": "Department of Cell Biology and Biophysics, Faculty of Biology, National and Kapodistrian University of Athens, Athens, Greece" + }, + { + "author_name": "Andreas Mentis", + "author_inst": "Medicinal Microbiology Laboratory, Hellenic Pasteur Institute, Athens, Greece" + }, + { + "author_name": "Markos Marangos", + "author_inst": "Department of Internal Medicine, Division of Infectious Diseases, University Hospital of Patras, Patras, Greece" + }, + { + "author_name": "George Panayiotakopoulos", + "author_inst": "Pharmacology Laboratory, University of Patras, Patras, Greece & National Public Health Organization, Athens, Greece" + }, + { + "author_name": "Meletios A. Dimopoulos", + "author_inst": "Department of Clinical Therapeutics, Alexandra General Hospital, National and Kapodistrian University of Athens, Athens, Greece" }, { - "author_name": "Prasun Biswas", - "author_inst": "Mymensingh Medical College (MMC), Mymensingh, Bangladesh" + "author_name": "Charalampos Gogos", + "author_inst": "Department of Internal Medicine, Division of Infectious Diseases, University Hospital of Patras, Patras, Greece" }, { - "author_name": "Sanjida Hossain", - "author_inst": "Dhaka Mohanagar General Hospital, Dhaka, Bangladesh." + "author_name": "Alexandros Spyridonidis", + "author_inst": "Department of Internal Medicine, BMT Unit and CBMDP Donor Center, University of Patras, Patras, Greece" }, { - "author_name": "Mustak Ibn Ayub", - "author_inst": "Department of Genetic Engineering & Biotechnology, University of Dhaka, Ramna, Dhaka-1000, Bangladesh" + "author_name": "Leonidas G. Alexopoulos", + "author_inst": "Biomedical Systems Laboratory, National Technical University of Athens, Athens, Greece & ProtATonce Ltd, Demokritos Science Park, Athens, Greece" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.09.09.20191700", @@ -1166099,41 +1166579,97 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.06.20189456", - "rel_title": "Household transmission in people infected with SARS-CoV-2 (COVID-19) in Metropolitan Lima", + "rel_doi": "10.1101/2020.09.07.20189274", + "rel_title": "Early Evidence of Effectiveness of Digital Contact Tracing for SARS-CoV-2 in Switzerland", "rel_date": "2020-09-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.06.20189456", - "rel_abs": "ObjectiveDescribe the characteristics of SARS-CoV-2 infection among household members with a confirmed primary case of COVID-19 in low burden districts in Metropolitan Lima.\n\nMaterials and MethodsA retrospective, secondary database review study was conducted. The information was collected from an epidemiological surveillance activity in close contacts (co-inhabitants) in 52 households in Metropolitan Lima with only one member with COVID-19. A reevaluation was carried out in 10 households. Epidemiological and clinical variables were evaluated and its association with the result of the rapid serological test (presence of IgG, IgM or both).\n\nResultsSecondary cases were found in 40 households, which represents an average of 49.9% identification per household. A secondary attack rate of 53.0% (125 cases) was found among cohabitants, with 77.6% of cases being symptomatic (symptomatic / asymptomatic ratio: 3.5). The presence of fever and / or chills was found in 40.0% of people with a positive result, followed by a sore throat, in 39.2%. Ageusia and anosmia were present in 22.4% and 20.8% of cases, respectively. A reevaluation in 40 family members 33.6 {+/-} 2.7 days after the first evaluation, show the persistence of positive IgM and IgG in the 20 positive cases in the first evaluation.\n\nConclusionHaving a primary case of COVID-19 in home, the secondary attack rate of this infection is 53%; however, in a significant proportion of households evaluated there was no positive case, beyond the primary case. The epidemiological and clinical characteristics found in this case were in accordance with what has already been reported in other international series.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.07.20189274", + "rel_abs": "In the wake of the pandemic of coronavirus disease 2019 (COVID-19), contact tracing has become a key element of strategies to control the spread of severe acute respiratory syndrome coronavirus 2019 (SARS-CoV-2). Given the rapid and intense spread of SARS-CoV-2, digital contact tracing has emerged as a potential complementary tool to support containment and mitigation efforts. Early modelling studies highlighted the potential of digital contact tracing to break transmission chains, and Google and Apple subsequently developed the Exposure Notification (EN) framework, making it available to the vast majority of smartphones. A growing number of governments have launched or announced EN-based contact tracing apps, but their effectiveness remains unknown. Here, we report early findings of the digital contact tracing app deployment in Switzerland. We demonstrate proof-of-principle that digital contact tracing reaches exposed contacts, who then test positive for SARS-CoV-2. This indicates that digital contact tracing is an effective complementary tool for controlling the spread of SARS-CoV-2. Continued technical improvement and international compatibility can further increase the efficacy, particularly also across country borders.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Yolanda Angulo-Baz\u00e1n", - "author_inst": "Instituto Nacional de Salud" + "author_name": "Marcel Salath\u00e9", + "author_inst": "EPFL" }, { - "author_name": "Gilmer Solis", - "author_inst": "Instituto Nacional de Salud" + "author_name": "Christian L Althaus", + "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Interfaculty Platform for Data and Computational Science (INPUT), University" }, { - "author_name": "Joshi Acosta", - "author_inst": "Instituto Nacional de Salud" + "author_name": "Nanina Anderegg", + "author_inst": "Institute of Social and Preventive Medicine, University of Bern" }, { - "author_name": "Fany Cardenas", - "author_inst": "Instituto Nacional de Salud" + "author_name": "Daniele Antonioli", + "author_inst": "EPFL" }, { - "author_name": "Ana Jorge", - "author_inst": "Instituto Nacional de Salud" + "author_name": "Tala Ballouz", + "author_inst": "Epidemiology, Biostatistics & Prevention Institute, University of Zurich, Zurich, Switzerland" }, { - "author_name": "C\u00e9sar Cabezas", - "author_inst": "Instituto Nacional de Salud" + "author_name": "Edouard Bugnion", + "author_inst": "EPFL" + }, + { + "author_name": "Srjan Capkun", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Dennis Jackson", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Sang-Il Kim", + "author_inst": "Federal Office of Public Health, Liebefeld, Switzerland" + }, + { + "author_name": "James Larus", + "author_inst": "EPFL" + }, + { + "author_name": "Nicola Low", + "author_inst": "University of Bern" + }, + { + "author_name": "Wouter Lueks", + "author_inst": "EPFL" + }, + { + "author_name": "Dominik Menges", + "author_inst": "Epidemiology, Biostatistics & Prevention Institute, University of Zurich, Zurich, Switzerland" + }, + { + "author_name": "Cedric Moullet", + "author_inst": "Federal Office of Information Technology, Systems and Telecommunication, Bern, Switzerland" + }, + { + "author_name": "Mathias Payer", + "author_inst": "EPFL" + }, + { + "author_name": "Julien Riou", + "author_inst": "University of Bern" + }, + { + "author_name": "Theresa Stadler", + "author_inst": "EPFL" + }, + { + "author_name": "Carmela Troncoso", + "author_inst": "EPFL" + }, + { + "author_name": "Effy Vayena", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Viktor von Wyl", + "author_inst": "University of Zurich" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1167745,29 +1168281,41 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.09.08.20190710", - "rel_title": "COVID-19 Transmission Dynamics and Effectiveness of Public Health Interventions in New York City during the 2020 Spring Pandemic Wave", + "rel_doi": "10.1101/2020.09.09.20190454", + "rel_title": "The risk of introducing SARS-CoV-2 to the UK via international travel in August 2020", "rel_date": "2020-09-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.08.20190710", - "rel_abs": "New York City experienced a large COVID-19 pandemic wave during March - May 2020. We model the transmission dynamics of COVID-19 in the city during the pandemic and estimate the effectiveness of public health interventions (overall and for each major intervention separately) for the entire population and by age group. We estimate that the overall effective reproductive number was 2.99 at the beginning of the pandemic wave and reduced to 0.93 one week after the stay-at-home mandate. Most age groups experienced similar reductions in transmission. Interventions reducing contact rates were associated with a 70.7% (95% CI: 65.0 - 76.4%) reduction of transmission overall and > 50% for all age groups during the pandemic. Face covering was associated with a 6.6% (95% CI: 0.8 - 12.4%) reduction of transmission overall and up to 20% for 65+ year-olds during the first month of implementation. Accounting for the amount of time masks are in use (i.e. mainly outside homes), these findings indicate universal masking could reduce transmission by up to 28-32% when lockdown-like measures are lifted, if the high effectiveness estimated for older adults were achieved for all ages. These estimates are verified by out-of-fit projections and support the need for implementing multiple interventions simultaneously in order to effectively mitigate the spread of COVID-19.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.09.20190454", + "rel_abs": "International travel poses substantial risks for continued introduction of SARS-CoV-2. As of the 17th August 2020, travellers from 12 of the top 25 countries flying into the UK are required to self-isolate for 14 days. We estimate that 895 (CI: 834-958) infectious travellers arrive in a single week, of which 87% (779, CI: 722-837) originate from countries on the UK quarantine list. We compare alternative measures to the 14 day self-isolation (78.0% effective CI: 74.4-81.6) which could be more feasible long-term. A single RT-PCR taken upon arrival at the airport is 39.6% (CI: 35.2-43.7) effective, or equivalently, it would only detect 2 in 5 infectious passengers. Alternatively, testing four days after arrival is 64.3% (CI: 60.0-68.3) effective whereas a test at the airport plus additional test four days later is 68.9% (CI: 64.9-73.0) effective. Rapidly implementing control measures for travellers from risky countries is vital to protect public health; this methodology can be quickly updated to assess the impact of any further changes to international travel policy or disease occurrence.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Wan Yang", - "author_inst": "Columbia University" + "author_name": "Rachel Taylor", + "author_inst": "Department of Epidemiological Sciences, Animal and Plant Health Agency (APHA), UK" }, { - "author_name": "Jaimie Shaff", - "author_inst": "New York City Department of Health and Mental Hygiene" + "author_name": "Catherine A McCarthy", + "author_inst": "Department of Epidemiological Sciences, Animal and Plant Health Agency (APHA), UK" }, { - "author_name": "Jeffrey Shaman", - "author_inst": "Columbia University" + "author_name": "Virag Patel", + "author_inst": "Department of Epidemiological Sciences, Animal and Plant Health Agency (APHA), UK" + }, + { + "author_name": "Ruth Moir", + "author_inst": "Epidemiology and Risk Policy Advice, Animal and Plant Health Agency (APHA), UK" + }, + { + "author_name": "Louise Kelly", + "author_inst": "Department of Mathematics and Statistics, University of Strathclyde, Glasgow, UK" + }, + { + "author_name": "Emma Snary", + "author_inst": "Department of Epidemiological Sciences, Animal and Plant Health Agency (APHA), UK" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1169723,29 +1170271,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.05.20188839", - "rel_title": "Frequency and accuracy of proactive testing for COVID-19", + "rel_doi": "10.1101/2020.09.05.20188755", + "rel_title": "Quantifying Inaccuracies in Modeling COVID-19 Pandemic within a Continuous Time Picture", "rel_date": "2020-09-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.05.20188839", - "rel_abs": "September 5, 2020\n\nThe SARS-CoV-2 coronavirus has proven difficult to control not only because of its high transmissibility, but because those who are infected readily spread the virus before symptoms appear, and because some infected individuals, though contagious, never exhibit symptoms. Proactive testing of asymptomatic individuals is therefore a powerful, and probably necessary, tool for preventing widespread infection in many settings. This paper explores the effectiveness of alternative testing regimes, in which the frequency, the accuracy, and the delay between testing and results determine the time path of infection. For a simple model of disease transmission, we present analytic formulas that determine the effect of testing on the expected number of days of during which an infectious individual is exposed to the population at large. This allows us to estimate the frequency of testing that would be required to prevent uncontrolled outbreaks, and to explore the trade-offs between frequency, accuracy, and delay in achieving this objective. We conclude by discussing applications to outbreak control on college and university campuses.\n\nCompeting Interest StatementTed Bergstrom and Haoran Li have no competing interests. Carl Bergstrom consults for Color Genomics on COVID testing schedules.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.05.20188755", + "rel_abs": "Typically, mathematical simulation studies on COVID-19 pandemic forecasting are based on deterministic differential equations which assume that both the number (n) of individuals in various epidemiological classes and the time (t) on which they depend are quantities that vary continuous. This picture contrasts with the discrete representation of n and t underlying the real epidemiological data reported in terms daily numbers of infection cases, for which a description based on finite difference equations would be more adequate. Adopting a logistic growth framework, in this paper we present a quantitative analysis of the errors introduced by the continuous time description. This analysis reveals that, although the height of the epidemiological curve maximum is essentially unaffected, the position [Formula] obtained within the continuous time representation is systematically shifted backwards in time with respect to the position [Formula] predicted within the discrete time representation. Rather counterintuitively, the magnitude of this temporal shift [Formula] is basically insensitive to changes in infection rate{kappa} . For a broad range of{kappa} values deduced from COVID-19 data at extreme situations (exponential growth in time and complete lockdown), we found a rather robust estimate{tau} [~=] -2.65 day-1. Being obtained without any particular assumption, the present mathematical results apply to logistic growth in general without any limitation to a specific real system.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Ted Bergstrom", - "author_inst": "University of California Santa Barbara" - }, - { - "author_name": "Carl T. Bergstrom", - "author_inst": "University of Washington" - }, - { - "author_name": "Haoran Li", - "author_inst": "University of California Santa Barbara" + "author_name": "Ioan Baldea", + "author_inst": "Heidelberg University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1172493,59 +1173033,107 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.09.04.20188185", - "rel_title": "Efficacy assessment of newly-designed and locally-produced filtering facemasks during the SARS-CoV-2 pandemic.", + "rel_doi": "10.1101/2020.09.02.20185892", + "rel_title": "Prognostic accuracy of emergency department triage tools for adults with suspected COVID-19: The PRIEST observational cohort study", "rel_date": "2020-09-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.04.20188185", - "rel_abs": "The SARS-CoV-2 pandemic resulted in shortages of production and test capacity of FFP2-respirators. Such facemasks are required to be worn by healthcare professionals when performing aerosol-generating procedures on COVID-19 patients. In response to the high demand and short supply, we designed three models of facemasks that are suitable for local production. As these facemasks should meet the requirements of an FFP2-certified facemask, the newly-designed facemasks were tested on the filtration efficiency of the filter material, inward leakage, and breathing resistance with custom-made experimental setups. In these tests, the locally-produced facemasks were benchmarked against a commercial FFP2 facemask. Furthermore, the protective capacity of the facemasks was tested for the first time with coronavirus-loaded aerosols under physiologically relevant conditions. This multidisciplinary effort resulted in the design and production of facemasks that meet the FFP2 requirements, and which can be mass-produced at local production facilities.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.02.20185892", + "rel_abs": "ObjectivesThe World Health Organisation (WHO) and National Institute for Health and Care Excellence (NICE) recommend various triage tools to assist decision-making for patients with suspected COVID-19. We aimed to estimate the accuracy of triage tools for predicting severe illness in adults presenting to the emergency department (ED) with suspected COVID-19 infection.\n\nMethodsWe undertook a mixed prospective and retrospective observational cohort study in 70 EDs across the United Kingdom (UK). We collected data from people attending with suspected COVID-19 between 26 March 2020 and 28 May 2020, and used presenting data to determine the results of assessment with the following triage tools: the WHO algorithm, NEWS2, CURB-65, CRB-65, PMEWS and the swine flu adult hospital pathway (SFAHP). We used 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome.\n\nResultsWe analysed data from 20892 adults, of whom 4672 (22.4%) died or received organ support (primary outcome), with 2058 (9.9%) receiving organ support and 2614 (12.5%) dying without organ support (secondary outcomes). C-statistics for the primary outcome were: CURB-65 0.75; CRB-65 0.70; PMEWS 0.77; NEWS2 (score) 0.77; NEWS2 (rule) 0.69; SFAHP (6-point) 0.70; SFAHP (7-point) 0.68; WHO algorithm 0.61. All triage tools showed worse prediction for receipt of organ support and better prediction for death without organ support.\n\nAt the recommended threshold, PMEWS and the WHO criteria showed good sensitivity (0.96 and 0.95 respectively), at the expense of specificity (0.31 and 0.27 respectively). NEWS2 showed similar sensitivity (0.96) and specificity (0.28) when a lower threshold than recommended was used.\n\nConclusionCURB-65, PMEWS and NEWS2 provide good but not excellent prediction for adverse outcome in suspected COVID-19, and predicted death without organ support better than receipt of organ support. PMEWS, the WHO criteria and NEWS2 (using a lower threshold than usually recommended) provide good sensitivity at the expense of specificity.\n\nRegistrationISRCTN registry, ISRCTN28342533, http://www.isrctn.com/ISRCTN28342533", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Bob Boogaard", - "author_inst": "Erasmus MC" + "author_name": "Ben Thomas", + "author_inst": "University of Sheffield" }, { - "author_name": "Joep Nijssen", - "author_inst": "Delft University of Technology" + "author_name": "Steve Goodacre", + "author_inst": "University of Sheffield" }, { - "author_name": "Freek Broeren", - "author_inst": "Delft University of Technology" + "author_name": "Ellen Lee", + "author_inst": "University of Sheffield" }, { - "author_name": "John van den Dobbelsteen", - "author_inst": "Delft University of Technology" + "author_name": "Laura Sutton", + "author_inst": "University of Sheffield" }, { - "author_name": "Vincent Verhoeven", - "author_inst": "Reinier de Graaf Gasthuis" + "author_name": "Amanda Loban", + "author_inst": "University of Sheffield" }, { - "author_name": "Jip Pluim", - "author_inst": "Reinier de Graaf Gasthuis" + "author_name": "Simon Waterhouse", + "author_inst": "University of Sheffield" }, { - "author_name": "Sing Dekker", - "author_inst": "Reinier de Graaf Gasthuis" + "author_name": "Richard Simmonds", + "author_inst": "University of Sheffield" }, { - "author_name": "Eric Snijder", - "author_inst": "Leiden University Medical Center (LUMC)" + "author_name": "Katie Biggs", + "author_inst": "University of Sheffield" }, { - "author_name": "Martijn van Hemert", - "author_inst": "Leiden University Medical Center (LUMC)" + "author_name": "Carl Marincowitz", + "author_inst": "University of Sheffield" }, { - "author_name": "Sander Herfst", - "author_inst": "Erasmus MC" + "author_name": "Jose Schutter", + "author_inst": "University of Sheffield" + }, + { + "author_name": "Sarah Connelly", + "author_inst": "University of Sheffield" + }, + { + "author_name": "Elena Sheldon", + "author_inst": "University of Sheffield" + }, + { + "author_name": "Jamie Hall", + "author_inst": "University of Sheffield" + }, + { + "author_name": "Emma Young", + "author_inst": "University of Sheffield" + }, + { + "author_name": "Andrew Bentley", + "author_inst": "Manchester University NHS Foundation Trust" + }, + { + "author_name": "Kirsty Challen", + "author_inst": "Lancashire Teaching Hospitals NHS Foundation Trust" + }, + { + "author_name": "Chris Fitzsimmons", + "author_inst": "Sheffield Children's NHS Foundation Trust" + }, + { + "author_name": "Tim Harris", + "author_inst": "Barts Health NHS Trust" + }, + { + "author_name": "Fiona Lecky", + "author_inst": "University of Sheffield" + }, + { + "author_name": "Andrew Lee", + "author_inst": "University of Sheffield" + }, + { + "author_name": "Ian Maconochie", + "author_inst": "Imperial College Healthcare NHS Trust" + }, + { + "author_name": "Darren Walter", + "author_inst": "Manchester University NHS Foundation Trust" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "emergency medicine" }, { "rel_doi": "10.1101/2020.09.04.20185645", @@ -1174235,39 +1174823,83 @@ "category": "otolaryngology" }, { - "rel_doi": "10.1101/2020.09.04.20187906", - "rel_title": "Public Preferences for Government Response Policies on Outbreak Control", + "rel_doi": "10.1101/2020.09.03.20187286", + "rel_title": "Severe COVID-19 infection is associated with increased antibody-mediated platelet apoptosis", "rel_date": "2020-09-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.04.20187906", - "rel_abs": "ObjectivesTo assess the extent to which public support for outbreak containment policies varies with respect to the severity of an infectious disease outbreak.\n\nMethodsA web-enabled survey was administered to 1,017 residents of Singapore during the COVID-19 pandemic, and was quota-sampled based on age, gender and ethnicity. A fractional-factorial design was used to create hypothetical outbreak vignettes characterised by morbidity and fatality rates, and local and global spread of an infectious disease. Each respondent was asked to indicate which response policies (among 5 policies restricting local movement and 4 border control policies) they would support in 5 randomly-assigned vignettes. Binomial logistic regressions were used to predict the probabilities of support as a function of outbreak attributes, personal characteristics and perceived policy effectiveness.\n\nResultsLikelihood of support varied across government response policies; however, was generally higher for border control policies compared to internal policies. The fatality rate was the most important factor for internal policies while the degree of global spread was the most important for border control policies. In general, individuals who were less healthy, had higher income and were older were more likely to support these policies. Perceived effectiveness of a policy was a consistent and positive predictor of public support.\n\nConclusionsOur findings suggest that campaigns to promote public support should be designed specifically to each policy and tailored to different segments of the population. They should also be adapted based on the evolving conditions of the outbreak in order to receive continued public support.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.03.20187286", + "rel_abs": "The pathophysiology of COVID-19 associated thrombosis seems to be multifactorial, involving interplay between cellular and plasmatic elements of the hemostasis. We hypothesized that COVID-19 is accompanied by platelet apoptosis with subsequent alteration of the coagulation system. We investigated depolarization of mitochondrial inner transmembrane potential ({Delta}{Psi}m), cytosolic calcium (Ca2+) concentration, and phosphatidylserine (PS) externalization by flow cytometry. Platelets from intensive care unit (ICU) COVID-19 patients (n=21) showed higher {Delta}{Psi}m depolarization, cytosolic Ca2+ concentration and PS externalization, compared to healthy controls (n=18) and COVID-19 non-ICU patients (n=4). Moreover significant higher cytosolic Ca2+ concentration and PS was observed compared to septic ICU control group (ICU control). In ICU control group (n=5; ICU non-COVID-19) cytosolic Ca2+ concentration and PS externalization was comparable to healthy control, with an increase {Delta}{Psi}m depolarization. Sera from ICU COVID-19 13 patients induced significant increase in apoptosis markers ({Delta}{Psi}m depolarization, cytosolic Ca2+ concentration and PS externalization). compared to healthy volunteer and septic ICU control. Interestingly, immunoglobulin G (IgG) fractions from COVID-19 patients induced an Fc gamma receptor IIA dependent platelet apoptosis ({Delta}{Psi}m depolarization, cytosolic Ca2+ concentration and PS externalization). Enhanced PS externalization in platelets from ICU COVID-19 patients was associated with increased sequential organ failure assessment (SOFA) score (r=0.5635) and DDimer (r=0.4473). Most importantly, patients with thrombosis had significantly higher PS externalization compared to those without. The strong correlations between apoptosis markers and increased D-Dimer levels as well as the incidence of thrombosis may indicate that antibody-mediated platelet apoptosis potentially contributes to sustained increased thromboembolic risk in ICU COVID-19 patients.\n\nKey pointsO_LISevere COVID-19 is associated with increased antibody-mediated platelet apoptosis.\nC_LIO_LIPlatelet apoptosis in severe COVID-19 is correlated with D-Dimer and higher incidence of thromboembolisms.\nC_LI", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Semra Ozdemir", - "author_inst": "Duke-NUS Medical School" + "author_name": "Karina Althaus", + "author_inst": "Center for Clinical Transfusion Medicine, University Hospital Tuebingen, Germany" }, { - "author_name": "Si Ning Germaine Tan", - "author_inst": "Duke-NUS Medical School" + "author_name": "Irene Marini", + "author_inst": "Transfusion Medicine, Medical Faculty of Tuebingen, University of Tuebingen, Germany" }, { - "author_name": "Isha Chaudhry", - "author_inst": "Duke-NUS Medical School" + "author_name": "Jan Zlamal", + "author_inst": "Transfusion Medicine, Medical Faculty of Tuebingen, University of Tuebingen, Germany" }, { - "author_name": "Chetna Malhotra", - "author_inst": "Duke-NUS Medical School" + "author_name": "Lisann Pelzl", + "author_inst": "Transfusion Medicine, Medical Faculty of Tuebingen, University of Tuebingen, Germany" }, { - "author_name": "Eric Finkelstein", - "author_inst": "Duke-NUS Medical School" + "author_name": "Helene Haeberle", + "author_inst": "Department of Anesthesiology and Intensive Care Medicine, University Hospital of Tuebingen" + }, + { + "author_name": "Martin Mehrlaender", + "author_inst": "Department of Anesthesiology and Intensive Care Medicine, University Hospital of Tuebingen" + }, + { + "author_name": "Stefanie Hammer", + "author_inst": "Centre for Clinical Transfusion Medicine, University Hospital of Tuebingen" + }, + { + "author_name": "Harald Schulze", + "author_inst": "Institute for Experimental Biomedicine, Chair I, University Hospital Wuerzburg" + }, + { + "author_name": "Michael Bitzer", + "author_inst": "Department of Internal Medicine I, University Hospital of Tuebingen" + }, + { + "author_name": "Nisar Malek", + "author_inst": "Department of Internal Medicine I, University Hospital of Tuebingen" + }, + { + "author_name": "Dominik Rath", + "author_inst": "Department of Medicine III, University Hospital of Tuebingen" + }, + { + "author_name": "Hans Boesmueller", + "author_inst": "Institute for Pathology, University Hospital of Tuebingen" + }, + { + "author_name": "Bernard Nieswandt", + "author_inst": "Institute for Experimental Biomedicine, Chair I, University Hospital Wuerzburg" + }, + { + "author_name": "Meinrad Gawaz", + "author_inst": "Department of Medicine III, University Hospital of Tuebingen" + }, + { + "author_name": "Tamam Bakchoul", + "author_inst": "Centre for Clinical Transfusion Medicine, University Hospital of Tuebingen" + }, + { + "author_name": "Peter Rosenberger", + "author_inst": "Department of Anesthesiology and Intensive Care Medicine, University Hospital of Tuebingen" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "hematology" }, { "rel_doi": "10.1101/2020.09.03.20187757", @@ -1175721,35 +1176353,91 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.09.04.283358", - "rel_title": "Clustering analysis of single nucleotide polymorphism data reveals population structure of SARS-CoV-2 worldwide", + "rel_doi": "10.1101/2020.09.04.282640", + "rel_title": "Seroprevalence of SARS-CoV-2 specific IgG antibodies in District Srinagar, northern India - a cross-sectional study", "rel_date": "2020-09-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.04.283358", - "rel_abs": "Identifying the population structure of the newly emerged coronavirus SARS-CoV-2 has significant potential to inform public health management and diagnosis. As SARS-CoV-2 sequencing data accrued, grouping them into clusters is important for organizing the landscape of the population structure of the virus. Due to the limited prior information on the newly emerged coronavirus, we utilized four different clustering algorithms to group 16,873 SARS-CoV-2 strains, which automatically enables the identification of spatial structure for SARS-CoV-2. A total of six distinct genomic clusters were identified using mutation profiles as input features. Comparison of the clustering results reveals that the four algorithms produced highly consistent results, but the state-of-the-art unsupervised deep learning clustering algorithm performed best and produced the smallest intra-cluster pairwise genetic distances. The varied proportions of the six clusters within different continents revealed specific geographical distributions. In particular, our analysis found that Oceania was the only continent on which the strains were dispersively distributed into six clusters. In summary, this study provides a concrete framework for the use of clustering methods to study the global population structure of SARS-CoV-2. In addition, clustering methods can be used for future studies of variant population structures in specific regions of these fast-growing viruses.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.04.282640", + "rel_abs": "BackgroundPrevalence of IgG antibodies against SARS-CoV-2 infection provides essential information for deciding disease prevention and mitigation measures. We estimate the seroprevalence of SARS-CoV-2 specific IgG antibodies in District Srinagar.\n\nMethods2906 persons >18 years of age selected from hospital visitors across District Srinagar participated in the study. We tested samples for the presence of SARS-CoV-2 specific IgG antibodies using a chemiluminescent microparticle immunoassay-based serologic test.\n\nResultsAge- and gender-standardized seroprevalence was 3.6% (95% CI 2.9% to 4.3%). Age 30-69 years, a recent history of symptoms of an influenza-like-illness, and a history of being placed under quarantine were significantly related to higher odds of the presence of SARS-CoV-2 specific IgG antibodies. The estimated number of SARS-CoV-2 infections during the two weeks preceding the study, adjusted for test performance, was 32602 with an estimated (median) infection-to-known-case ratio of 46 (95% CI 36 to 57).\n\nConclusionsThe seroprevalence of SARS-CoV-2 specific IgG antibodies is low in the District. A large proportion of the population is still susceptible to the infection. A sizeable number of infections remain undetected, and a substantial proportion of people with symptoms compatible with COVID-19 are not tested.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Yawei Li", - "author_inst": "Department of Preventive Medicine, Northwestern University, Feinberg School of Medicine" + "author_name": "S Muhammad Salim Khan", + "author_inst": "Government Medical College Srinagar" }, { - "author_name": "Qingyun Liu", - "author_inst": "Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health" + "author_name": "Mariya Amin Qurieshi", + "author_inst": "Government Medical College Srinagar" }, { - "author_name": "Zexian Zeng", - "author_inst": "Department of Data Science, Dana Farber Cancer Institute, Harvard T.H. Chan School of Public Health" + "author_name": "Inaamul Haq", + "author_inst": "Government Medical College Srinagar" }, { - "author_name": "Yuan Luo", - "author_inst": "Department of Preventive Medicine, Northwestern University, Feinberg School of Medicine" + "author_name": "Sabhiya Majid", + "author_inst": "Government Medical College Srinagar" + }, + { + "author_name": "Arif Akbar Bhat", + "author_inst": "Government Medical College Srinagar" + }, + { + "author_name": "Sahila Nabi", + "author_inst": "Government Medical College Srinagar" + }, + { + "author_name": "Nisar Ahmad Ganai", + "author_inst": "Government Medical College Srinagar" + }, + { + "author_name": "Nazia Zahoor", + "author_inst": "Government Medical College Srinagar" + }, + { + "author_name": "Auqfeen Nisar", + "author_inst": "Government Medical College Srinagar" + }, + { + "author_name": "Iqra Nisar Chowdri", + "author_inst": "Government Medical College Srinagar" + }, + { + "author_name": "Tanzeela Bashir Qazi", + "author_inst": "Government Medical College Srinagar" + }, + { + "author_name": "Rafiya Kousar", + "author_inst": "Government Medical College Srinagar" + }, + { + "author_name": "Abdul Aziz Lone", + "author_inst": "Government Medical College Srinagar" + }, + { + "author_name": "Iram Sabah", + "author_inst": "Government Medical College Srinagar" + }, + { + "author_name": "Shahroz Nabi", + "author_inst": "Government Medical College Srinagar" + }, + { + "author_name": "Ishtiyaq Ahmad Sumji", + "author_inst": "Government Medical College Srinagar" + }, + { + "author_name": "Misbah Ferooz Kawoosa", + "author_inst": "Government Medical College Srinagar" + }, + { + "author_name": "Shifana Ayoub", + "author_inst": "Government Medical College Srinagar" } ], "version": "1", "license": "cc_by", "type": "new results", - "category": "genetics" + "category": "immunology" }, { "rel_doi": "10.1101/2020.09.01.20185793", @@ -1177147,41 +1177835,89 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.01.20135194", - "rel_title": "Defining the role of asymptomatic SARS-CoV-2 transmission: a living systematic review", + "rel_doi": "10.1101/2020.09.01.20184713", + "rel_title": "The impact of high frequency rapid viral antigen screening on COVID-19 spread and outcomes: a validation and modeling study", "rel_date": "2020-09-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.01.20135194", - "rel_abs": "BackgroundReports suggest that asymptomatic individuals (those with no symptoms at all throughout the infection) with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are infectious, but the extent of asymptomatic transmission requires further understanding.\n\nPurposeThis living review aims to critically appraise available data about secondary attack rates from people with asymptomatic and pre-symptomatic SARS-CoV-2 infection.\n\nData sourcesMedline, EMBASE, China Academic Journals full-text database (CNKI), and preprint servers were searched from 30 December 2019 to 3 July 2020 using relevant MESH terms.\n\nStudy selectionStudies that report on contact tracing of index cases with asymptomatic or pre-symptomatic SARS-CoV-2 infection, in either English or Chinese were included.\n\nData extractionTwo authors independently extracted data and assessed study quality and risk of bias. We calculated the secondary attack rate as the number of contacts with SARS-CoV-2, divided by the number of contacts tested.\n\nData synthesisOf 928 studies identified, 19 were included. Secondary attack rates from asymptomatic index cases ranged from 0% to 2.8% (9 studies). Pre-symptomatic secondary attack rates ranged from 0.7% to 31.8% (10 studies). The highest secondary attack rates were found in contacts who lived in the same household as the index case. Other activities associated with transmission were group activities such as sharing meals or playing board games with the index case.\n\nLimitationsWe excluded some studies because the index case or number of contacts were unclear. Owing to the anticipated heterogeneity, we did not produce a summary estimate of the included studies.\n\nConclusionAsymptomatic patients can transmit SARS-CoV-2 to others, but our findings indicate that such individuals are responsible for fewer secondary infections than people with symptoms in the same studies.\n\nSystematic review registrationPROSPERO CRD42020188168\n\nFundingNo funding was received", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.01.20184713", + "rel_abs": "High frequency screening of populations has been proposed as a strategy in facilitating control of the COVID-19 pandemic. We use computational modeling, coupled with clinical data from rapid antigen tests, to predict the impact of frequent viral antigen rapid testing on COVID-19 spread and outcomes. Using patient nasal or nasopharyngeal swab specimens, we demonstrate that the sensitivity/specificity of two rapid antigen tests compared to quantitative real-time polymerase chain reaction (qRT-PCR) are 82.0%/100% and 84.7%/85.7%, respectively; moreover, sensitivity correlates directly with viral load. Based on COVID-19 data from three regions in the United States and Sao Jose do Rio Preto, Brazil, we show that high frequency, strategic population-wide rapid testing, even at varied accuracy levels, diminishes COVID-19 infections, hospitalizations, and deaths at a fraction of the cost of nucleic acid detection via qRT-PCR. We propose large-scale antigen-based surveillance as a viable strategy to control SARS-CoV-2 spread and to enable societal re-opening.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Xueting Qiu", - "author_inst": "Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, Boston, USA" + "author_name": "Beatrice Nash", + "author_inst": "E25Bio, Inc., Cambridge, MA, USA" }, { - "author_name": "Ali Ihsan Nergiz", - "author_inst": "School of Medicine, Cerrahpasa University, Istanbul" + "author_name": "Anthony Badea", + "author_inst": "E25Bio, Inc., Cambridge, MA, USA" }, { - "author_name": "Alberto Enrico Maraolo", - "author_inst": "First Division of Infectious Diseases, Cotugno Hospital, AORN dei Colli, Naples, Italy" + "author_name": "Ankita Reddy", + "author_inst": "E25Bio, Inc., Cambridge, MA, USA" }, { - "author_name": "Isaac I Bogoch", - "author_inst": "Division of Infectious Diseases, Toronto General Hospital and University of Toronto, Toronto Canada" + "author_name": "Miguel Bosch", + "author_inst": "E25Bio, Inc., Cambridge, MA, USA" }, { - "author_name": "Nicola Low", - "author_inst": "University of Bern" + "author_name": "Nol Salcedo", + "author_inst": "E25Bio, Inc., Cambridge, MA, USA" }, { - "author_name": "Muge Cevik", - "author_inst": "Division of Infection and Global Health Research, School of Medicine, University of St. Andrews, Fife, Scotland, UK" + "author_name": "Adam R. Gomez", + "author_inst": "E25Bio, Inc., Cambridge, MA, USA" + }, + { + "author_name": "Alice Versiani", + "author_inst": "Faculdade de Medicina de S\u00e3o Jos\u00e9 do Rio Preto (FAMERP), S\u00e3o Jos\u00e9 do Rio Preto, Brazil" + }, + { + "author_name": "Gislaine Celestino Dutra", + "author_inst": "Faculdade de Medicina de S\u00e3o Jos\u00e9 do Rio Preto (FAMERP), S\u00e3o Jos\u00e9 do Rio Preto, Brazil" + }, + { + "author_name": "Thayza Maria Izabel Lopes dos Santos", + "author_inst": "Faculdade de Medicina de S\u00e3o Jos\u00e9 do Rio Preto (FAMERP), S\u00e3o Jos\u00e9 do Rio Preto, Brazil" + }, + { + "author_name": "Bruno H. G. A. Milhim", + "author_inst": "Faculdade de Medicina de S\u00e3o Jos\u00e9 do Rio Preto (FAMERP), S\u00e3o Jos\u00e9 do Rio Preto, Brazil" + }, + { + "author_name": "Marilia M. Moraes", + "author_inst": "Faculdade de Medicina de S\u00e3o Jos\u00e9 do Rio Preto (FAMERP), S\u00e3o Jos\u00e9 do Rio Preto, Brazil" + }, + { + "author_name": "Guilherme Rodrigues Fernandes Campos", + "author_inst": "Faculdade de Medicina de S\u00e3o Jos\u00e9 do Rio Preto (FAMERP), S\u00e3o Jos\u00e9 do Rio Preto, Brazil" + }, + { + "author_name": "Fl\u00e1via Quieroz", + "author_inst": "Faculdade de Medicina de S\u00e3o Jos\u00e9 do Rio Preto (FAMERP), S\u00e3o Jos\u00e9 do Rio Preto, Brazil" + }, + { + "author_name": "Andreia Francesli Negri Reis", + "author_inst": "Faculdade de Medicina de S\u00e3o Jos\u00e9 do Rio Preto (FAMERP), S\u00e3o Jos\u00e9 do Rio Preto, Brazil" + }, + { + "author_name": "Mauricio L. Nogueira", + "author_inst": "Faculdade de Medicina de S\u00e3o Jos\u00e9 do Rio Preto (FAMERP), S\u00e3o Jos\u00e9 do Rio Preto, Brazil" + }, + { + "author_name": "Elena N. Naumova", + "author_inst": "Division of the Nutrition Epidemiology and Data Science, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA" + }, + { + "author_name": "Irene Bosch", + "author_inst": "E25Bio, Inc., Cambridge, MA, USA" + }, + { + "author_name": "Bobby Brooke Herrera", + "author_inst": "E25Bio, Inc., Cambridge, MA, USA" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1178761,53 +1179497,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.01.20186254", - "rel_title": "Equivalent SARS-CoV-2 viral loads between nasopharyngeal swab and saliva in symptomatic patients", + "rel_doi": "10.1101/2020.09.01.20186080", + "rel_title": "Early elevation of FIB-4 liver fibrosis score is associated with adverse outcomes among patients with COVID-19", "rel_date": "2020-09-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.01.20186254", - "rel_abs": "COVID-19 is diagnosed by detecting SARS-CoV-2 by nasopharyngeal swab (NPS) using real-time quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). Emerging evidences have shown the utility of saliva, although conflicting results have been reported regarding viral loads between NPS and saliva. We conducted a study to compare the viral loads in 42 patients with COVID-19. Both NPS and saliva specimens were simultaneously obtained at a median of 6 days (range, 1-12) after symptom onset. SARS-CoV-2 was detected in 34 (81%) using NPS (median Ct value [IQR]=27.4 [21.3, 35.6]) and 38 (90%) using saliva (median Ct value [IQR]= 28.9 [23.1, 33.6]). There was no significance difference between them (Wilcoxon signed rank test: P=0.79) and Kendalls W was 0.82, showing a high degree of agreement, indicating equivalent viral loads in NPS and saliva. After symptom onset, the Ct values of both NPS and saliva continued to increase over time, with no substantial difference. Self-collected saliva has a detection sensitivity comparable to that of NPS and is a useful diagnostic tool with mitigating uncomfortable process and the risk of aerosol transmission to healthcare workers.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.01.20186080", + "rel_abs": "BackgroundLimited prior data suggest that pre-existing liver disease was associated with adverse outcomes among patients with COVID-19. FIB-4 is a noninvasive index of readily available laboratory measurements that represents hepatic fibrosis. The association of FIB-4 with COVID-19 outcomes has not been previously evaluated.\n\nMethodsFIB-4 was evaluated at admission in a cohort of 267 patients admitted with early-stage COVID-19 confirmed through RT-PCR. Hazard of ventilator use and of high-flow oxygen was estimated using Cox regression models controlled for covariates. Risk of progress to severe cases and of death/prolonged hospitalization (>30 days) were estimated using logistic regression models controlled for same covariates.\n\nResultsForty-one (15%) patients progressed to severe cases, 36 (14%) required high-flow oxygen support, 10 (4%) required mechanical ventilator support, and 1 died. Patients with high FIB-4 score (>3.25) were more likely to be older with pre-existing conditions. FIB-4 between 1.45-3.25 was associated with over 5-fold (95% CI: 1.2-28) increased hazard of high-flow oxygen use, over 4-fold (95% CI: 1.5-14.6) increased odds of progress to severe stage, and over 3-fold (95% CI: 1.4-7.7) increased odds of death or prolonged hospitalization. FIB-4>3.25 was associated with over 12-fold (95% CI: 2.3-68. 7) increased hazard of high-flow oxygen use and over 11-fold (95% CI: 3.1-45) increased risk of progress to severe disease. All associations were independent of sex, number of comorbidities, and inflammatory markers (D-dimer, C-reactive protein).\n\nConclusionsFIB-4 at early-stage of COVID-19 disease had an independent and dose-dependent association with adverse outcomes during hospitalization. FIB-4 provided significant prognostic value to adverse outcomes among COVID-19 patients.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Isao Yokota", - "author_inst": "Hokkaido University" - }, - { - "author_name": "Takeshi Hattori", - "author_inst": "Hokkaido Medical Center" + "author_name": "Fangfei Xiang", + "author_inst": "Guangzhou No. 8 Peoples Hospital" }, { - "author_name": "Peter Y Shane", - "author_inst": "Hokkaido University" - }, - { - "author_name": "Satoshi Konno", - "author_inst": "Hokkaido University Hospital" + "author_name": "Jing Sun", + "author_inst": "Johns Hopkins University Bloomberg School of Public Health" }, { - "author_name": "Atsushi Nagasaka", - "author_inst": "Sapporo City General Hospital" + "author_name": "Po-Hung Chen", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Kimihiro Takeyabu", - "author_inst": "Otaru Kyokai Hospital" + "author_name": "Peijin Han", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Shinichi Fujisawa", - "author_inst": "Hokkaido University" + "author_name": "Haipeng Zheng", + "author_inst": "Guangzhou Eighth Peoples Hospital" }, { - "author_name": "Mutsumi Nishida", - "author_inst": "Hokkaido University" + "author_name": "Shujiang Cai", + "author_inst": "Guangzhou Eighth Peoples Hospital" }, { - "author_name": "Takanori Teshima", - "author_inst": "Hokkaido University" + "author_name": "Gregory D Kirk", + "author_inst": "Johns Hopkins University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1180551,21 +1181279,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.31.20185256", - "rel_title": "Modeling an epidemic in an imaginary small town", + "rel_doi": "10.1101/2020.08.31.20185108", + "rel_title": "Could Deficiencies in South African Data Be the Explanation for Its Early SARS-CoV-2 Peak?", "rel_date": "2020-09-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.31.20185256", - "rel_abs": "The course of an epidemic in an imaginary small town has been simulated with an agent-based model. The reproduction number R of the virus could be counted directly, and was roughly, but not precisely, exponentially distributed. The number of secondary infections was greater for an infection which was itself one of many secondary infections because of environmental heterogeneity, which created variance of R among sites and could drive the spread of infection, even when global R < 1. Different kinds of intervention were deployed to curtail the spread of infection. Measures applied to the general population, such as closing down sites and services or regulating individual behaviour, did not reduce the total number of individuals infected during the epidemic unless they were maintained until the virus became extinct. This was primarily because measures taken to reduce indirect transmission tended to increase direct transmission, and vice versa. Consequently, the overall effect of any combination of interventions was much less than the sum of their separate effects. On the other hand, the quarantine of infected or exposed individuals was effective in driving the virus to extinction and caused a permanent and substantial reduction in the number of cases.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.31.20185108", + "rel_abs": "The SARS-CoV-2 pandemic peaked very early in comparison to the thresholds predicted by an analysis of prior lockdown regimes. The most convenient explanation is that some, external factor changed the value of the basic reproduction number, r0; and there certainly are arguments for this. Other factors could, nonetheless, have played a role. This research attempts to reconcile the observed peak with the thresholds predicted by lockdown regimes similar to the one in force at the time. It contemplates the effect of two, different, hypothetical errors in the data: The first is that the true level of infection has been underestimated by a multiplicative factor, while the second is that of an imperceptible, pre-existing, immune fraction of the population. While it is shown that it certainly is possible to manufacture the perception of an early peak as extreme as the one observed, solely by way of these two phenomena, the values need to be fairly high. The phenomena would not, by any measure, be insignificant. It also remains an inescapable fact that the early peak in infections coincided with a fairly profound change in r0; in all the contemplated scenarios of data-deficiency.", "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Graham Bell", - "author_inst": "McGill University" + "author_name": "Simon John Childs", + "author_inst": "University of Fort Hare" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1182157,165 +1182885,57 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.08.31.20169946", - "rel_title": "Determinants of SARS-CoV-2 receptor gene expression in upper and lower airways", + "rel_doi": "10.1101/2020.08.31.20185363", + "rel_title": "Development and calibration of a simple mortality risk score for hospitalized COVID-19 adults", "rel_date": "2020-09-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.31.20169946", - "rel_abs": "BackgroundThe recent outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), has led to a worldwide pandemic. A subset of COVID-19 patients progresses to severe disease, with high mortality and limited treatment options. Detailed knowledge of the expression regulation of genes required for viral entry into respiratory epithelial cells is urgently needed.\n\nMethodsHere we assess the expression patterns of genes required for SARS-CoV-2 entry into cells, and their regulation by genetic, epigenetic and environmental factors, throughout the respiratory tract using samples collected from the upper (nasal) and lower airways (bronchi).\n\nFindingsGenes encoding viral receptors and activating protease are increased in the nose compared to the bronchi in matched samples and associated with the proportion of secretory epithelial cells in cellular deconvolution analyses. Current or ex-smoking was found to increase expression of these genes only in lower airways, which was associated with a significant increase in the predicted proportion of goblet cells. Both acute and second hand smoke exposure were found to increase ACE2 expression while inhaled corticosteroids decrease ACE2 expression in the lower airways. A strong association of DNA- methylation with ACE2 and TMPRSS2- mRNA expression was identified.\n\nInterpretationGenes associated with SARS-CoV-2 viral entry into cells are high in upper airways, but strongly increased in lower airways by smoke exposure. In contrast, ICS decreases ACE2 expression, indicating that inhaled corticosteroids are unlikely to increase the risk for more severe COVID-19 disease.\n\nFundingThis work was supported by a Seed Network grant from the Chan Zuckerberg Initiative to M.C.N. and by the European Unions H2020 Research and Innovation Program under grant agreement no. 874656 (discovAIR) to M.C.N. U BIOPRED was supported by an Innovative Medicines Initiative Joint Undertaking (No. 115010), resources from the European Unions Seventh Framework Programme (FP7/2007-2013) and EFPIA companies in kind contribution (www.imi.europa.eu). Longfonds Junior Fellowship. We acknowledge the contribution of the whole U-BIOPRED team as listed in the Appendix S1. SDB, FM and RFS would like to thank the Helmholtz Association, Germany, for support.\" NIH K08HL146943; Parker B. Francis Fellowship; ATS Foundation/Boehringer Ingelheim Pharmaceuticals Inc. Research Fellowship in IPF. RCR is part funded by Cancer Research UK Cambridge Centre and the Cambridge NIHR Biomedical Research Centre. BAP was funded by programme support from Cancer Research UK. The CRUKPAP Study was supported by the CRUK Cambridge Cancer Centre, by the NIHR Cambridge Biomedical Research Centre and by the Cambridge Bioresource. PIAMA was supported by The Netherlands Organization for Health Research and Development; The Netherlands Organization for Scientific Research; The Netherlands Lung Foundation (with methylation studies supported by AF 4.1.14.001); The Netherlands Ministry of Spatial Planning, Housing, and the Environment; and The Netherlands Ministry of Health, Welfare, and Sport. Dr. Qi is supported by a grant from the China Scholarship Council.", - "rel_num_authors": 38, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.31.20185363", + "rel_abs": "ObjectivesMortality risk scores, such as SOFA, qSOFA, and CURB-65, are quick, effective tools for communicating a patients prognosis and guiding therapeutic decisions. Most use simple calculations that can be performed by hand. While several COVID-19 specific risk scores exist, they lack the ease of use of these simpler scores. The objectives of this study were (1) to design, validate, and calibrate a simple, easy-to-use mortality risk score for COVID-19 patients and (2) to recalibrate SOFA, qSOFA, and CURB-65 in a hospitalized COVID-19 population.\n\nDesignRetrospective cohort study incorporating demographic, clinical, laboratory, and admissions data from electronic health records.\n\nSettingMulti-hospital health system in New York City. Five hospitals were included: one quaternary care facility, one tertiary care facility, and three community hospitals.\n\nParticipantsPatients (n=4840) with laboratory-confirmed SARS-CoV2 infection who were admitted between March 1 and April 28, 2020.\n\nMain outcome measuresGrays K-sample test for the cumulative incidence of a competing risk was used to assess and rank 48 different variables associations with mortality. Candidate variables were added to the composite score using DeLongs test to evaluate their effect on predictive performance (AUC) of in-hospital mortality. Final AUCs for the new score, SOFA, qSOFA, and CURB-65 were assessed on an independent test set.\n\nResultsOf 48 variables investigated, 36 (75%) displayed significant (p<0.05 by Grays test) associations with mortality. The variables selected for the final score were (1) oxygen support level, (2) troponin, (3) blood urea nitrogen, (4) lymphocyte percentage, (5) Glasgow Coma Score, and (6) age. The new score, COBALT, outperforms SOFA, qSOFA, and CURB-65 at predicting mortality in this COVID-19 population: AUCs for initial, maximum, and mean COBALT scores were 0.81, 0.91, and 0.92, compared to 0.77, 0.87, and 0.87 for SOFA. We provide COVID-19 specific mortality estimates at all score levels for COBALT, SOFA, qSOFA, and CURB-65.\n\nConclusionsThe COBALT score provides a simple way to estimate mortality risk in hospitalized COVID-19 patients with superior performance to SOFA and other scores currently in widespread use. Evaluation of SOFA, qSOFA, and CURB-65 in this population highlights the importance of recalibrating mortality risk scores when they are used under novel conditions, such as the COVID-19 pandemic. This studys approach to score design could also be applied in other contexts to create simple, practical and high-performing mortality risk scores.\n\nTrial registrationNA\n\nFunding sourceThe authors declare that there was no external funding provided.\n\nSummary boxO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIMortality risk scores are widely used in clinical settings to facilitate communication with patients and families, guide goals of care discussions, and optimize resource allocation.\nC_LIO_LIAlthough popular mortality risk scores like SOFA, qSOFA, and CURB-65 are routinely used in COVID-19 populations, they were originally calibrated in different contexts and their true performance among hospitalized COVID-19 patients is unknown.\nC_LIO_LISeveral dedicated COVID-19 mortality risk scores have been created during the 2019-2020 pandemic, but all use complicated formulae or machine learning algorithms and are difficult or impossible to calculate by hand, limiting their applicability at the bedside.\nC_LI\n\nWhat this study addsO_LIWe describe a data-driven, simple, and hand-calculable COVID-specific mortality risk score (COBALT) that has superior performance to SOFA, qSOFA, and CURB-65 in a hospitalized COVID-19 patient population.\nC_LIO_LIWe provide COVID-specific mortality estimates for SOFA, qSOFA, and CURB-65 using data from 4840 patients in a large and diverse New York City multihospital health system.\nC_LI", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Hananeh Aliee", - "author_inst": "Institute of Computational Biology, Helmholtz Centre, Munich, Germany" - }, - { - "author_name": "Florian Massip", - "author_inst": "Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Robert-Rossle-Str. 10, 13125 Berlin, Germany" - }, - { - "author_name": "Cancan Qi", - "author_inst": "University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD, Groningen, the Netherlands." - }, - { - "author_name": "Maria Stella de Biase", - "author_inst": "Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Robert-Rossle-Str. 10, 13125 Berlin, Germany" - }, - { - "author_name": "Johannes L van Nijnatten", - "author_inst": "University of Technology Sydney, Respiratory Bioinformatics and Molecular Biology (RBMB), School of Life Sciences, Sydney, Australia." - }, - { - "author_name": "Elin T.G. Kersten", - "author_inst": "University of Groningen, University Medical Center Groningen, Department of Pediatric Pulmonology and Pediatric Allergy, Beatrix Childrens Hospital, Groningen, " - }, - { - "author_name": "Nazanin Z. Kermani", - "author_inst": "Department of computing, Data Science Institute, Imperial College London, London, UK" - }, - { - "author_name": "Basil Khuder", - "author_inst": "Northwestern University Feinberg School of Medicine, Division of Pulmonary and Critical Care Medicine, Chicago, IL, USA." - }, - { - "author_name": "Judith M Vonk", - "author_inst": "University of Groningen, University Medical Center Groningen, Department of epidemiology, Groningen, the Netherlands" - }, - { - "author_name": "Roel C H Vermeulen", - "author_inst": "Julius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands" - }, - { - "author_name": "- U-BIOPRED study group", - "author_inst": "" - }, - { - "author_name": "- Cambridge Lung Cancer Early Detection Programme", - "author_inst": "" - }, - { - "author_name": "- INER-Ciencias Mexican Lung Program", - "author_inst": "" - }, - { - "author_name": "- NHLBI LungMAP Consortium", - "author_inst": "" - }, - { - "author_name": "Margaret Neighbors", - "author_inst": "OMNI Biomarker Development, Genentech Inc. South San Francisco. CA, USA." - }, - { - "author_name": "Gaik W. Tew", - "author_inst": "Product Development Immunology, Infectious Disease & Opthalmology, Genentech Inc. South San Francisco. CA, USA." - }, - { - "author_name": "Michele Grimbaldeston", - "author_inst": "OMNI Biomarker Development, Genentech Inc. South San Francisco. CA, USA." - }, - { - "author_name": "Nick H.T. ten Hacken", - "author_inst": "University of Groningen, University Medical Center Groningen, Department of Pulmonary Diseases, Groningen, the Netherlands." - }, - { - "author_name": "Sile Hu", - "author_inst": "Department of statistics, university of Oxford, Oxford, UK" - }, - { - "author_name": "Yike Guo", - "author_inst": "Department of computing, Data Science Institute, Imperial College London, London, UK" - }, - { - "author_name": "Xiaoyu Zhang", - "author_inst": "National Heart and Lung Institute, London, UK" - }, - { - "author_name": "Kai Sun", - "author_inst": "National Heart and Lung Institute, London, UK" - }, - { - "author_name": "Pieter S. Hiemstra", - "author_inst": "Department of Pulmonology, Leiden University Medical Center, Leiden, The Netherlands" - }, - { - "author_name": "Bruce A. Ponder", - "author_inst": "Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge CB2 0RE, UK" - }, - { - "author_name": "Mika J Makela", - "author_inst": "Dept. of Allergy, University of Helsinki and Helsinki University Hospital, PO Box 160, FI-00029, Helsinki, Finland." - }, - { - "author_name": "Kristiina Malmstrom", - "author_inst": "Dept. of Allergy, University of Helsinki and Helsinki University Hospital, PO Box 160, FI-00029, Helsinki, Finland." - }, - { - "author_name": "Robert C. Rintoul", - "author_inst": "Department of Oncology, University of Cambridge, Hutchison/MRC Research Centre, Box 197, Cambridge Biomedical Campus, CB2 0XZ, UK" - }, - { - "author_name": "Paul A. Reyfman", - "author_inst": "Northwestern University Feinberg School of Medicine, Division of Pulmonary and Critical Care Medicine, Chicago, IL, USA." + "author_name": "Edwin Yoo", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Fabian J. Theis", - "author_inst": "Institute of Computational Biology, Helmholtz Centre, Munich, Germany" + "author_name": "Bethany Percha", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Corry-A Brandsma", - "author_inst": "University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD, Groningen, the Netherlands." + "author_name": "Max Tomlinson", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Ian Adcock", - "author_inst": "National Heart and Lung Institute, London, UK" + "author_name": "Victor Razuk", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Wim Timens", - "author_inst": "University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD, Groningen, the Netherlands." + "author_name": "Stephanie Pan", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Cheng J. Xu", - "author_inst": "Research group Bioinformatics and Computational Genomics, Centre for Individualised Infection Medicine, CiiM, a joint venture between the Hannover Medical Schoo" + "author_name": "Madeleine Basist", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Maarten van den Berge", - "author_inst": "University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD, Groningen, the Netherlands" + "author_name": "Pranai Tandon", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Roland F. Schwarz", - "author_inst": "Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Robert-Rossle-Str. 10, 13125 Berlin, Germany" + "author_name": "Jing Gennie Wang", + "author_inst": "Ohio State University" }, { - "author_name": "Gerard H. Koppelman", - "author_inst": "University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD, Groningen, the Netherlands." + "author_name": "Cynthia Gao", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Martijn C. Nawijn", - "author_inst": "University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD, Groningen, the Netherlands." + "author_name": "Sonali Bose", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Alen Faiz", - "author_inst": "University of Technology Sydney, Respiratory Bioinformatics and Molecular Biology (RBMB), School of Life Sciences, Sydney, Australia." + "author_name": "Umesh K Gidwani", + "author_inst": "Mount Sinai Hospital" } ], "version": "1", @@ -1184251,35 +1184871,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.26.20182378", - "rel_title": "Predictors of healthcare worker burnout during the COVID-19 pandemic", + "rel_doi": "10.1101/2020.08.26.20182352", + "rel_title": "Willingness to pay tuition and risk-taking proclivities among students: A fundamental conundrum for universities", "rel_date": "2020-09-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.26.20182378", - "rel_abs": "ObjectiveWe aim to provide a snapshot of the levels of burnout, anxiety, depression and distress among healthcare workers during the COVID-19 pandemic.\n\nDesign, setting, participantsWe distributed an online survey via social media in June 2020 that was open to any UK healthcare worker. The primary outcome measure was symptoms of burnout as measured using the Copenhagen Burnout Inventory (CBI). Secondary outcomes of depression, anxiety and distress as measured using the Patient Health Questionnaire-9, General Anxiety Scale-7, and Impact of Events Scale-Revised were recorded along with subjective measures of stress. Multivariate logistic regression analysis was performed to identify factors associated with burnout, depression, anxiety and distress.\n\nResultsOf 539 persons responding to the survey, 90% were female, and 26% were aged 41-50 years, 53% were nurses. Participants with moderate-to-severe burnout were younger (49% [206/424] versus 33% [38/115] under 40 years, P=0.004), and more likely to have pre-existing comorbidities (21% versus 12%, P=0.031). They were twice as likely to have been redeployed from their usual role (22% versus 11%; adjusted odds ratio [OR] 2.2, 95% confidence interval [CI] 1.5-3.3, P=0.042), or to work in an area dedicated to COVID-19 patients (50% versus 32%, adjusted OR 1.6, 95% CI 1.4-1.8, P<0.001), and were almost 4-times more likely to have previous depression (24% versus 7%; adjusted OR 3.6, 95% CI 2.2-5.9, P=0.012). A supportive workplace team and male sex protected against burnout reducing the odds by 40% (adjusted OR 0.6, 95% CI 0.5-0.7, P<0.001) and 70% (adjusted OR 0.3, 95% CI 0.2-0.5, P=0.003), respectively.\n\nConclusionIndependent predictors of burnout were younger staff, redeployment to a new working area, working with patients with confirmed COVID-19 infection, and being female or having a previous history of depression. Evaluation of existing psychological support interventions is required with targeted approaches to ensure support is available to those most at risk.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.26.20182352", + "rel_abs": "ImportanceAs universities around the world decide whether to remain open or to close their campuses because of the COVID-19 pandemic, they often are doing so without objective information on the preferences and risk tolerance of their students.\n\nObjectivesTo quantify students: 1) risk tolerance for in-person instruction; 2) willingness to pay for in-person instruction versus online-only instruction; and 3) risk-tolerance for social activities held off campus.\n\nDesign, Setting, and ParticipantsWe developed an automated survey tool that administered a \"standard gamble\" exercise grounded in game theory to 46 Columbia University public health graduate students who were knowledgeable about COVID-19 and who had experience with both online and offline coursework. Students were asked to trade between the risk of becoming infected with COVID-19 and: 1) attending classes in-person versus online and 2) attending parties in the greater New York City area. We also assessed their willingness to pay for online only tuition, and plans to travel off campus.\n\nMain Outcome MeasuresThe decision point in iterative trade-offs between risk of infection with COVID-19 and a desired goal (taking classes in-person or attending social events).\n\nResultsOn average, students were willing to accept a 23% (standard error [SE]: 4%) risk of infection on campus over the semester in exchange for the opportunity to attend classes in-person. Students were willing-to-pay only 48% (SE: 3%) of typical in-person tuition were courses held exclusively online, and no students were willing to pay full price for online-only instruction. Students planned to leave campus an average of 3.6 times per week (SE: 0.54), and 15% of the students would be willing to attend a party in the community surrounding the university even if the prevalence of circulating COVID-19 were high.\n\nConclusions and RelevanceStudents with a strong knowledge of COVID-19 transmission and risks are an enigma: they are willing to pay only around 50% for online classes but likely to engage in activities that present significant barriers to holding in-person classes This enigma underscores the conundrum facing universities.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Amy V Ferry", - "author_inst": "University of Edinburgh" + "author_name": "Zafar Zafari", + "author_inst": "University of Maryland" }, { - "author_name": "Ryan Wereski", - "author_inst": "University of Edinburgh" + "author_name": "Lee Goldman", + "author_inst": "Columbia University" }, { - "author_name": "Fiona E Strachan", - "author_inst": "University of Edinburgh" + "author_name": "Katia Korvizhkin", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Nicholas L Mills", - "author_inst": "University of Edinburgh" + "author_name": "Peter Muennig", + "author_inst": "Columbia University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "health policy" }, { "rel_doi": "10.1101/2020.08.27.20182923", @@ -1185861,29 +1186481,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.27.20183574", - "rel_title": "Data-driven Optimized Control of the COVID-19 Epidemics", + "rel_doi": "10.1101/2020.08.27.20183350", + "rel_title": "A Rational-Choice Model of Covid-19 Transmission with Endogenous Quarantining and Two-sided Prevention", "rel_date": "2020-09-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.27.20183574", - "rel_abs": "Optimizing the impact on the economy of control strategies aiming at containing the spread of COVID-19 is a critical challenge. We use daily new case counts of COVID-19 patients reported by local health administrations from different Metropolitan Statistical Areas (MSAs) within the US to parametrize a model that well describes the propagation of the disease in each area. We then introduce a time-varying control input that represents the level of social distancing imposed on the population of a given area and solve an optimal control problem with the goal of minimizing the impact of social distancing on the economy in the presence of relevant constraints, such as a desired level of suppression for the epidemics at a terminal time. We find that with the exception of the initial time and of the final time, the optimal control input is well approximated by a constant, specific to each area, which contrasts with the implemented system of reopening in phases. For all the areas considered, this optimal level corresponds to stricter social distancing than the level estimated from data. Proper selection of the time period for application of the control action optimally is important: depending on the particular MSA this period should be either short or long or intermediate. We also consider the case that the transmissibility increases in time (due e.g. to increasingly colder weather), for which we find that the optimal control solution yields progressively stricter measures of social distancing. We finally compute the optimal control solution for a model modified to incorporate the effects of vaccinations on the population and we see that depending on a number of factors, social distancing measures could be optimally reduced during the period over which vaccines are administered to the population.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.27.20183350", + "rel_abs": "This paper offers a parsimonious, rational-choice model to study the effect of pre-existing inequalities on the transmission of COVID-19. Agents decide whether to \"go out\" (or self-quarantine) and, if so, whether to wear protection such as masks. Three elements distinguish the model from existing work. First, non-symptomatic agents do not know if they are infected. Second, some of these agents unknowingly transmit infections. Third, we permit two-sided prevention via the use of non-pharmaceutical interventions: the probability of a person catching the virus from another depends on protection choices made by each. We find that a mean-preserving increase in pre-existing income inequality unambiguously increases the equilibrium proportion of unprotected, socializing agents and may increase or decrease the proportion who self-quarantine. Strikingly, while higher pre-COVID inequality may or may not raise the overall risk of infection, it increases the risk of disease in social interactions.", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Afroza Shirin", - "author_inst": "University of New Mexico" + "author_name": "Joydeep Bhattacharya", + "author_inst": "iowa state university" }, { - "author_name": "Yen Ting Lin", - "author_inst": "Los Alamos National Laboratory" + "author_name": "Shankha Chakraborty", + "author_inst": "University of Oregon" }, { - "author_name": "Francesco Sorrentino", - "author_inst": "University of New Mexico" + "author_name": "Xiumei Yu", + "author_inst": "Zhongnan University of Economics and Law" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1187447,103 +1188067,51 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.28.20180463", - "rel_title": "Population-based seroprevalence of SARS-CoV-2 is more than halfway through the herd immunity threshold in the State of Maranhao, Brazil", + "rel_doi": "10.1101/2020.08.28.20183848", + "rel_title": "Social Determinants Associated with COVID-19 Mortality in the United States", "rel_date": "2020-09-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.28.20180463", - "rel_abs": "BackgroundFew population-based studies on the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been performed to date, and most of them have used lateral flow immunoassays with finger-prick, which may yield false-negative results and thus underestimate the true infection rate.\n\nMethodsA population-based household survey was performed in the State of Maranhao, Brazil, from 27 July 2020 to 8 August 2020 to estimate the seroprevalence of SARS-CoV-2 using a serum testing electrochemiluminescence immunoassay. A three-stage cluster sampling stratified by four state regions was used. The estimates took clustering, stratification, and non-response into account. Qualitative detection of IgM and IgG antibodies was performed in a fully-automated Elecsys(R) Anti-SARS-CoV-2 electrochemiluminescence immunoassay on the Cobas(R) e601 analyser (Roche Diagnostics).\n\nFindingsA total of 3156 individuals were interviewed. Seroprevalence of total antibodies against SARS-CoV-2 was 40{middle dot}4% (95%CI 35{middle dot}6-45{middle dot}3). Population adherence to non-pharmaceutical interventions was higher at the beginning of the pandemic than in the last month. SARS-CoV-2 infection rates were significantly lower among mask wearers and among those who maintained social and physical distancing in the last month compared to their counterparts. Among the infected, 62{middle dot}2% had more than three symptoms, 11{middle dot}1% had one or two symptoms, and 26{middle dot}0% were asymptomatic. The infection fatality rate was 0{middle dot}17%, higher for males and advanced age groups. The ratio of estimated infections to reported cases was 22{middle dot}2.\n\nInterpretationTo the best of our knowledge, the seroprevalence of SARS-CoV-2 estimated in this population-based survey was the highest and the closest to the herd immunity threshold reported to date. Our results suggest that the herd immunity threshold is not as low as 20%, but at least higher than or equal to around 40%. The infection fatality rate was one of the lowest reported so far, and the proportion of asymptomatic cases was low.", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.28.20183848", + "rel_abs": "This study examines social determinants associated with disparities in COVID-19 mortality rates in the United States. Using county-level data, 42 negative binomial mixed models were used to evaluate the impact of social determinants on COVID-19 outcome. First, to identify proper controls, the effect of 24 high-risk factors on COVID-19 mortality rate was quantified. Then, the high-risk terms found to be significant were controlled for in an association study between 41 social determinants and COVID-19 mortality rates. The results describe that ethnic minorities, immigrants, socioeconomic inequalities, and early exposure to COVID-19 are associated with increased COVID-19 mortality, while the prevalence of asthma, suicide, and excessive drinking is associated with decreased mortality. Overall, we recognize that social inequality places disadvantaged groups at risk, which must be addressed through future policies and programs. Additionally, we reveal possible relationships between lung disease, mental health, and COVID-19 that need to be explored on a clinical level.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Ant\u00f4nio Augusto Moura da Silva", - "author_inst": "Universidade Federal do Maranh\u00e3o" - }, - { - "author_name": "L\u00eddio Gon\u00e7alves Lima Neto", - "author_inst": "Secretaria de Estado de Sa\u00fade do Maranh\u00e3o" - }, - { - "author_name": "Concei\u00e7\u00e3o de Maria Pedrozo e Silva de Azevedo", - "author_inst": "Universidade Federal do Maranh\u00e3o" - }, - { - "author_name": "L\u00e9a M\u00e1rcia Melo da Costa", - "author_inst": "Secretaria de Estado de Sa\u00fade do Maranh\u00e3o" - }, - { - "author_name": "Maylla Luana Barbosa Martins Bragan\u00e7a", - "author_inst": "Universidade Federal do Maranh\u00e3o" - }, - { - "author_name": "Allan Kardec Duailibe Barros Filho", - "author_inst": "Universidade Federal do Maranh\u00e3o" - }, - { - "author_name": "Bernardo Bastos Wittlin", - "author_inst": "Hospital Universit\u00e1rio da Universidade Federal do Maranh\u00e3o" - }, - { - "author_name": "Bruno Feres de Souza Sr.", - "author_inst": "Universidade Federal do Maranh\u00e3o" - }, - { - "author_name": "Bruno Luciano Carneiro Alves de Oliveira", - "author_inst": "Universidade Federal do Maranh\u00e3o" - }, - { - "author_name": "Carolina Abreu de Carvalho", - "author_inst": "Universidade Federal do Maranh\u00e3o" - }, - { - "author_name": "\u00c9rika B\u00e1rbara Abreu Fonseca Thomaz", - "author_inst": "Universidade Federal do Maranh\u00e3o" - }, - { - "author_name": "Eudes Alves Sim\u00f5es Neto", - "author_inst": "Universidade Federal do Maranh\u00e3o" - }, - { - "author_name": "Jamesson Ferreira Leite J\u00fanior", - "author_inst": "Secretaria de Estado de Sa\u00fade do Maranh\u00e3o" - }, - { - "author_name": "L\u00e9cia Maria Sousa Santos Cosme", - "author_inst": "Secretaria de Estado de Sa\u00fade do Maranh\u00e3o" + "author_name": "Shayom Debopadhaya", + "author_inst": "Rensselaer Polytechnic Institute" }, { - "author_name": "Marcos Adriano Garcia Campos", - "author_inst": "Universidade Federal do Maranh\u00e3o" + "author_name": "Ariella D Sprague", + "author_inst": "Rensselaer Polytechnic Institute" }, { - "author_name": "Rejane Christine de Sousa Queiroz", - "author_inst": "Universidade Federal do Maranh\u00e3o" + "author_name": "Hongxi Mou", + "author_inst": "Rensselaer Polytechnic Institute" }, { - "author_name": "S\u00e9rgio Souza Costa", - "author_inst": "Universidade Federal do Maranh\u00e3o" + "author_name": "Tiburon L Benavides", + "author_inst": "Rensselaer Polytechnic Institute" }, { - "author_name": "Vit\u00f3ria Abreu de Carvalho", - "author_inst": "Universidade Federal do Maranh\u00e3o" + "author_name": "Sarah M Ahn", + "author_inst": "Rensselaer Polytechnic Institute" }, { - "author_name": "Vanda Maria Ferreira Sim\u00f3es", - "author_inst": "Universidade Federal do Maranh\u00e3o" + "author_name": "Cole A Reschke", + "author_inst": "Rensselaer Polytechnic Institute" }, { - "author_name": "Maria Teresa Seabra Soares de Britto e Alves", - "author_inst": "Universidade Federal do Maranh\u00e3o" + "author_name": "John S Erickson", + "author_inst": "Rensselaer Polytechnic Institute" }, { - "author_name": "Alcione Miranda dos Santos", - "author_inst": "Universidade Federal do Maranh\u00e3o" + "author_name": "Kristin P Bennett", + "author_inst": "Rensselaer Polytechnic Institute" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "health informatics" }, { "rel_doi": "10.1101/2020.08.29.20126201", @@ -1189341,37 +1189909,125 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.25.20182030", - "rel_title": "The urgent need for phased university reopenings to mitigate the spread of COVID-19 and conserve institutional resources: A modeling study", + "rel_doi": "10.1101/2020.08.25.20171595", + "rel_title": "Multiple introductions followed by ongoing community spread of SARS-CoV-2 at one of the largest metropolitan areas in the Northeast of Brazil", "rel_date": "2020-08-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.25.20182030", - "rel_abs": "IntroductionRecent outbreaks of COVID-19 in universities across the United States highlight the difficulties in containing the spread of COVID-19 on college campuses. While research has shown that mitigation strategies such as frequent student testing, contact tracing, and isolation of confirmed and suspected cases can detect early outbreaks, such mitigation strategies may have limited effectiveness if large outbreaks occur. A phased reopening is a practical intervention to limit early outbreaks, conserve institutional resources, and ensure proper safety protocols are in place before the return of additional students to campus.\n\nMethodsWe develop dynamic compartmental transmission models of SARS-CoV-2 to assess the impact of a phased reopening and pre-arrival testing on minimizing outbreaks (measured by daily infections) and conserving university resources (measured by isolation bed capacity). We assume that one-third of the student population returns to campus each month as part of the phased reopening, and that pre-arrival testing removes 90% of infections at the semester start. We assume an on-campus population of N = 7500, an active COVID-19 prevalence of 2% at baseline, and that 60% of infected students require isolation for an average period of 11 days. We vary the reproductive number (Rt) between 1.25 and 4 to represent the effectiveness of alternative mitigation strategies throughout the semester, where Rt is constant or improving throughout the semester (ranging from 4 to 1.25).\n\nResultsCompared to pre-arrival testing only or neither intervention, phased reopening with pre-arrival testing reduced peak daily infections by 6% and 18% (Rt=1.25), 44% and 48% (Rt=2.5), 63% and 64% (Rt=4), and 72% and 74% (improving Rt), respectively, and reduced the proportion of on-campus beds needed for isolation from 10%-25% to 5%-9% across different values of Rt.\n\nConclusionPhased reopening with pre-arrival testing substantially reduces the peak number of daily infections throughout the semester and conserves university resources compared to strategies involving the simultaneous return of all students to campus. Phased reopenings allow institutions to improve safety protocols, adjust for factors that drive outbreaks, and if needed, preemptively move online before the return of additional students to campus, thus preventing unnecessary harm to students, institutional faculty and staff, and local communities.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.25.20171595", + "rel_abs": "The emergence of SARS-CoV-2 in the human population has caused a huge pandemic that is still unfolding in many countries around the world. Multiple epicenters of the pandemic have emerged since the first pneumonia cases in Wuhan, first in Italy followed by the USA and Brazil. Up to now, Brazil is the second most affected country, however, genomic sequences of SARS-CoV-2 strains circulating in the country are restricted to some highly impacted states. Although the Pernambuco state, located in the Northeast Region, is the sixth most affected brazilian state and the second considering lethality rate, there is a lack of high quality genomic sequences from the strains circulating in this region. Here, we sequenced 38 strains of SARS-CoV-2 from patients presenting Covid-19 symptoms. Phylogenetic reconstructions revealed that three lineages were circulating in the state and 36 samples belong to B1.1 lineage. We detected two introductions from European countries and five clades, corroborating the community spread of the virus between different municipalities of the state. Finally, we detected that all except one strain showed the D614G spike protein amino acid change that may impact virus infectivity in human cells. Our study brought new light to the spread of SARS-CoV-2 strains in one of the most heavily impacted states of Brazil.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Lior Rennert", - "author_inst": "Clemson University" + "author_name": "Marcelo Henrique Santos Paiva", + "author_inst": "Universidade Federal de Pernambuco" }, { - "author_name": "Corey Kalbaugh", - "author_inst": "Clemson University" + "author_name": "Duschinka Ribeiro Duarte Guedes", + "author_inst": "Oswaldo Cruz Foundation" }, { - "author_name": "Christopher McMahan", - "author_inst": "Clemson University" + "author_name": "Cassia Docena", + "author_inst": "Oswaldo Cruz Foundation" }, { - "author_name": "Lu Shi", - "author_inst": "Clemson University" + "author_name": "Matheus Filgueira Bezerra", + "author_inst": "Oswaldo Cruz Foundation" }, { - "author_name": "Christopher C Colenda", - "author_inst": "Wake Forest University" + "author_name": "Filipe Zimmer Dezordi", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Lais Ceschini Machado", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Larissa Krokovsky", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Elisama Helvecio", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Alexandre Freitas da Silva", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Luydson Richardson Silva Vasconcelos", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Antonio Mauro Rezende", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Severino Jefferson Ribeiro da Silva", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Kamila Gaudencio da Silva Sales", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Bruna Santos Lima Figueiredo de Sa", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Derciliano Lopes da Cruz", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Claudio Eduardo Cavalcanti", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Armando de Menezes Neto", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Caroline Targino Alves da Silva", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Renata Pessoa Germano Mendes", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Maria Almerice Lopes da Silva", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Michelle da Silva Barros", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Wheverton Ricardo Correia do Nascimento", + "author_inst": "Universidade Federal de Pernambuco" + }, + { + "author_name": "Rodrigo Moraes Loyo Arcoverde", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Luciane Caroline Albuquerque Bezerra", + "author_inst": "Secretaria de Saude de Pernambuco" + }, + { + "author_name": "Sinval Pinto Brandao Filho", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Constancia Flavia Junqueira Ayres", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Gabriel Luz Wallau", + "author_inst": "Oswaldo Cruz Foundation" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1191475,37 +1192131,21 @@ "category": "dentistry and oral medicine" }, { - "rel_doi": "10.1101/2020.08.24.20181271", - "rel_title": "Real-time, interactive website for US-county level Covid-19 event risk assessment", + "rel_doi": "10.1101/2020.08.24.20181214", + "rel_title": "Universal properties of the dynamics of the Covid-19 pandemics", "rel_date": "2020-08-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.24.20181271", - "rel_abs": "Large events and gatherings, particularly those taking place indoors, have been linked to multi-transmission events that have accelerated the pandemic spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To provide real-time, geo-localized risk information, we developed an interactive online dashboard that estimates the risk that at least one individual with SARS-CoV-2 is present in gatherings of different sizes in the United States. The website combines documented case reports at the county level with ascertainment bias information obtained via population-wide serological surveys to estimate real time circulating, per-capita infection rates. These rates are updated daily as a means to visualize the risk associated with gatherings, including county maps and state-level plots. The website provides data-driven information to help individuals and policy-makers make prudent decisions (e.g., increasing mask wearing compliance and avoiding larger gatherings) that could help control the spread of SARS-CoV-2, particularly in hard-hit regions.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.24.20181214", + "rel_abs": "We present evidence for existence of a universal lower bound for the initial growth rate of the epidemic curve of the SARS-CoV-2 coronavirus. This can be used to infer that, on average, an asymptomatic infected individual is infectious during 5.6 {+/-} 0.3 days. We further present evidence of an average time scale of 12 days for halving the number of new cases, or new deaths, during the extinction period of the first phase of the epidemic.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Aroon Chande", - "author_inst": "Georgia Institute of Technology & the Applied Bioinformatics Laboratory" - }, - { - "author_name": "Seolha Lee", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "Mallory Harris", - "author_inst": "Stanford University" - }, - { - "author_name": "Troy Hilley", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "Clio Andris", - "author_inst": "Georgia Institute of Technology" + "author_name": "Piotr T. Chru\u015bciel", + "author_inst": "University of Vienna" }, { - "author_name": "Joshua S Weitz", - "author_inst": "Georgia Institute of Technology" + "author_name": "Sebastian J. Szybka", + "author_inst": "Obserwatorium Astronomiczne UJ, Krak\u00f3w, Poland" } ], "version": "1", @@ -1193244,31 +1193884,71 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2020.08.27.269456", - "rel_title": "Designing of Epitope-Based Vaccine from the Conserved Region of the Spike Glycoprotein of SARS-CoV-2", + "rel_doi": "10.1101/2020.08.24.20181123", + "rel_title": "The Coronavirus Health and Impact Survey (CRISIS) reveals reproducible correlates of pandemic-related mood states across the Atlantic.", "rel_date": "2020-08-27", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.27.269456", - "rel_abs": "The emergence of COVID-19 as a pandemic with a high morbidity rate is posing serious global concern. There is an urgent need to design a suitable therapy or vaccine that could fight against SARS-CoV-2 infection. As spike glycoprotein of SARS-CoV-2 plays a crucial role in receptor binding and membrane fusion inside the host, it could be a suitable target for designing of an epitope-based vaccine. SARS-CoV-2 is an RNA virus and thus has a property to mutate. So, a conserved peptide region of spike glycoprotein was used for predicting suitable B cell and T cell epitopes. 4 T cell epitopes were selected based on stability, antigenicity, allergenicity and toxicity. Further, MHC-I were found from the immune database that could best interact with the selected epitopes. Population coverage analysis was also done to check the presence of identified MHC-I, in the human population of the affected countries. The T cell epitope that binds with the respective MHC-I with highest affinity was chosen. Molecular dynamic simulation results show that the epitope is well selected. This is an in-silico based study that predicts a novel T cell epitope from the conserved spike glycoprotein that could act as a target for designing of the epitope-based vaccine. Further, B cell epitopes have also been found but the main work focuses on T cell epitope as the immunity generated by it is long lasting as compared to B cell epitope.", - "rel_num_authors": 3, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.24.20181123", + "rel_abs": "The COVID-19 pandemic and its social and economic consequences have had adverse impacts on physical and mental health worldwide and exposed all segments of the population to protracted uncertainty and daily disruptions. The CoRonavIruS health and Impact Survey (CRISIS) was developed for use as an easy to implement and robust questionnaire covering key domains relevant to mental distress and resilience during the pandemic. In the current work, we demonstrate the feasibility, psychometric structure and construct validity of this survey. We then show that pre-existing mood states, perceived COVID risk, and lifestyle changes are strongly associated with negative mood states during the pandemic in population samples of adults and in parents reporting on their children in the US and UK. Ongoing studies using CRISIS include international studies of COVID-related ill health conducted during different phases of the pandemic and follow-up studies of cohorts characterized before the COVID pandemic.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Vidhu Agarwal", - "author_inst": "Indian Institute of Information Technology, Allahabad" + "author_name": "Aki Nikolaidis", + "author_inst": "Child Mind Institute" }, { - "author_name": "Akhilesh Tiwari", - "author_inst": "Indian Insitute of Information Technology, Allahabad" + "author_name": "Diana Paksarian", + "author_inst": "National Institute of Mental Health" }, { - "author_name": "Pritish Kumar Varadwaj", - "author_inst": "Indian Institute of Information Technology Allahabad" + "author_name": "Lindsay Alexander", + "author_inst": "Child Mind Institute" + }, + { + "author_name": "Jacob DeRosa", + "author_inst": "Child Mind Institute" + }, + { + "author_name": "Julia Dunn", + "author_inst": "National Institute of Mental Health" + }, + { + "author_name": "Dylan M Nielson", + "author_inst": "National Institute of Mental Health" + }, + { + "author_name": "Irene Droney", + "author_inst": "Child Mind Institute" + }, + { + "author_name": "Minji Kang", + "author_inst": "Child Mind Institute" + }, + { + "author_name": "Ioanna Douka", + "author_inst": "National Institute of Mental Health" + }, + { + "author_name": "Evelyn Bromet", + "author_inst": "Stony Brook University" + }, + { + "author_name": "Michael P Milham", + "author_inst": "Child Mind Institute" + }, + { + "author_name": "Argyris Stringaris", + "author_inst": "National Institute of Mental Health" + }, + { + "author_name": "Kathleen R Merikangas", + "author_inst": "National Institute of Mental Health" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "bioinformatics" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2020.08.27.270637", @@ -1194762,87 +1195442,83 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.24.20169789", - "rel_title": "Serum lipid profile changes and their clinical diagnostic significance in COVID-19 Mexican Patients", + "rel_doi": "10.1101/2020.08.26.266304", + "rel_title": "Inhibiting coronavirus replication in cultured cells by chemical ER stress", "rel_date": "2020-08-26", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.24.20169789", - "rel_abs": "BackgroundCOVID-19 has been recognized as an emerging and rapidly evolving health condition. For this reason, efforts to determine changes in laboratory parameters of COVID-19 patients as biomarkers are urgent. Lipids are essential components of the human body, and their modulation has been observed implicated in some viral infections.\n\nMethodsTo evaluate the clinical diagnosis utility of the lipid profile changes in Mexican COVID-19 patients, the lipid profile of one hundred two COVID-19 positive patients from three hospitals in Culiacan, Sinaloa in northwest Mexico, was analyzed. ROC curves and binary logistic regression analysis were used as a predictive model to determine their clinical diagnostic utility.\n\nResultsSignificant changes in the serum lipid profile of patients with COVID-19, such as low levels of cholesterol, LDL, and HDL, while high triglycerides and VLDL were observed. The same abnormalities in the lipid profile among non-critical and critical COVID-19 patients were detected. The predictive model analysis suggests that cholesterol and LDL have AUC values of 0.710 and 0.769, respectively, for COVID-19 (p= 0.0002 and p= <0.0001), and LDL low levels might be a risk factor for critical COVID-19 (OR= 2.07, 95% IC: 1.18 to 3.63; p= 0.01).\n\nConclusionOur findings suggest that low cholesterol and LDL levels could be considered an acceptable predictor for COVID-19, and low levels of LDL might be a risk factor for critical COVID-19 patients.", - "rel_num_authors": 17, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.26.266304", + "rel_abs": "Coronaviruses (CoVs) are important human pathogens for which no specific treatment is available. Here, we provide evidence that pharmacological reprogramming of ER stress pathways can be exploited to suppress CoV replication. We found that the ER stress inducer thapsigargin efficiently inhibits coronavirus (HCoV-229E, MERS-CoV, SARS-CoV-2) replication in different cell types, (partially) restores the virus-induced translational shut-down, and counteracts the CoV-mediated downregulation of IRE1 and the ER chaperone BiP. Proteome-wide data sets revealed specific pathways, protein networks and components that likely mediate the thapsigargin-induced antiviral state, including HERPUD1, an essential factor of ER quality control, and ER-associated protein degradation complexes. The data show that thapsigargin hits a central mechanism required for CoV replication, suggesting that thapsigargin (or derivatives thereof) may be developed into broad-spectrum anti-CoV drugs.\n\nOne Sentence Summary / Running titleSuppression of coronavirus replication through thapsigargin-regulated ER stress, ERQC / ERAD and metabolic pathways", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Juan Fidel Osuna-Ramos", - "author_inst": "Cinvestav" - }, - { - "author_name": "Horacio Rendon Aguilar", - "author_inst": "Hospital General de Culiacan" + "author_name": "Mohammed Samer Shaban", + "author_inst": "Justus Liebig University Giessen" }, { - "author_name": "Luis Adrian De Jesus-Gonzalez", - "author_inst": "Cinvestav" + "author_name": "Christin Mueller", + "author_inst": "Justus Liebig University Giessen" }, { - "author_name": "Jose Manuel Reyes Ruiz", - "author_inst": "Cinvestav" + "author_name": "Christin Mayr-Buro", + "author_inst": "Justus Liebig University Giessen" }, { - "author_name": "Arely Montserrat Espinoza Ortega", - "author_inst": "Hospital General de Culiacan, Sinaloa" + "author_name": "Hendrik Weiser", + "author_inst": "Justus Liebig University Giessen" }, { - "author_name": "Luis Antonio Ochoa Ramirez", - "author_inst": "Hospital General de Culiacan, Sinaloa" + "author_name": "Benadict Vincent Albert", + "author_inst": "Justus Liebig University Giessen" }, { - "author_name": "Alejandra Romero Utrilla", - "author_inst": "IMSS" + "author_name": "Axel Weber", + "author_inst": "Justus Liebig University Giessen" }, { - "author_name": "Efren Rios Burgueno", - "author_inst": "CIDOCS-UAS" + "author_name": "Uwe Linne", + "author_inst": "Philipps University Marburg" }, { - "author_name": "Alejandro Soto-Almaral", - "author_inst": "Hospital General de Culiacan" + "author_name": "Torsten Hain", + "author_inst": "Justus Liebig University Giessen" }, { - "author_name": "Juan Jose Rios-Tostado", - "author_inst": "Hospital General de Culiacan" + "author_name": "Ilya Babayev", + "author_inst": "Justus Liebig University Giessen" }, { - "author_name": "Jose Geovanni Romero-Quintana", - "author_inst": "UAS" + "author_name": "Nadja Karl", + "author_inst": "Justus Liebig University Giessen" }, { - "author_name": "Hector Ponce Ramos", - "author_inst": "Hospital General de Culiacan" + "author_name": "Nina Hofmann", + "author_inst": "Justus Liebig University Giessen" }, { - "author_name": "Carlos Noe Farfan Morales", - "author_inst": "Cinvestav" + "author_name": "Stephan Becker", + "author_inst": "Philipps University Marburg" }, { - "author_name": "Rosa Maria del Angel", - "author_inst": "Cinvestav" + "author_name": "Susanne Herold", + "author_inst": "Justus Liebig University Giessen" }, { - "author_name": "Hector Barajas Martinez", - "author_inst": "LIMR" + "author_name": "M. Lienhard Schmitz", + "author_inst": "Justus Liebig University Giessen" }, { - "author_name": "Jose Rodriguez Millan", - "author_inst": "Hospital General de Culiacan" + "author_name": "John Ziebuhr", + "author_inst": "Justus Liebig University Giessen" }, { - "author_name": "Jesus Salvador Velarde Felix", - "author_inst": "Escuela de Biologia, UAS" + "author_name": "Michael Kracht", + "author_inst": "Justus Liebig University Giessen" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2020.08.26.266825", @@ -1196808,47 +1197484,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.23.20180224", - "rel_title": "Wastewater sample site selection to estimate geographically-resolved community prevalence of COVID-19: A research protocol", + "rel_doi": "10.1101/2020.08.24.20176321", + "rel_title": "Suitability of Google Trends \u2122 for digital surveillance during ongoing COVID-19 epidemic: a case study from India", "rel_date": "2020-08-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.23.20180224", - "rel_abs": "BackgroundWastewater monitoring for virus infections within communities can complement conventional clinical surveillance. Currently, most SARS-CoV-2 testing is performed during clinical encounters with symptomatic individuals, and therefore likely underrepresents actual population prevalence. Randomized testing on a regular basis to estimate population-level infection rates is prohibitively costly and is hampered by a range of barriers associated with participation in clinical research. In comparison, community-level fecal monitoring can be performed through wastewater surveillance and can effectively surveil communities with less temporal lag than other surveillance methods. However, epidemiologically-defined protocols for wastewater sample site selection are lacking.\n\nMethodsHerein we describe methods for developing a geographically-resolved population-level wastewater sampling approach in Jefferson County, Kentucky which may have general applicability for cities throughout the United States. This approach was developed by the selection of sampling locations along sewer lines transporting raw wastewater from geographically and demographically distinct areas that correspond with locations where random testing of residents occurs.\n\nConclusionsDevelopment of this protocol for population-level sampling for SARS-CoV-2 prevalence in wastewater can be utilized to inform consistent wastewater monitoring among cities for up-to-date and geographically-resolved information on COVID-19 prevalence within communities. This information could substantially supplement public health surveillance of COVID-19 and thus serve to better guide targeted mitigation strategies throughout the United States.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.24.20176321", + "rel_abs": "BackgroundIndia went into the largest population-level lockdown on 25th March 2020 in response to the declaration of COVID-19 pandemic by World Health Organization (WHO). Digital surveillance has been shown to be useful to supplement the traditional surveillance. Google Trends (GT) is one such platform reported to be useful during pandemics of H1N1, Ebola and MERS.\n\nObjectiveWe used GT to correlate the information seeking behaviour regarding COVID-19 of Indians with curiosity and apprehensiveness generated through media coverage as well as status of the epidemic both at national and state levels.\n\nMethodsWe retrieved GT data between 1st January 2020 to 31st May 2020 for India using a comprehensive search strategy. We obtained data on daily tests and cases from WHO, ECDC and covid19india.org websites. We explored the trends of COVID-19 in the form of relative search volume (RSV) from GT platform and correlated them with media reports. We used time-lag correlation analysis to assess the temporal relationships between Google search terms and daily new COVID-19 cases and daily tests for 14 days.\n\nResultsPeaks in RSV correlated with media coverage or government declarations suggestive of curiosity and apprehensiveness both at national level and high-burden states. High time-lag correlation was observed between both the daily reported number of tests and cases and RSV for the terms \"COVID 19\", \"COVID\", \"social distancing\", \"soap\" and \"lockdown\" at national level. Similar high time-lag correlation was observed for the terms \"COVID 19\", \"COVID\", \"Corona\", \"social distancing\", \"soap\", \"lockdown\" in five high-burden states.\n\nConclusionThis study reveals the advantages of infodemiology using GT to monitor an emerging infectious disease like COVID-19 in India. Google searches in India during the ongoing COVID-19 pandemic reflects mostly curiosity and apprehension of citizens. GT can also complement traditional surveillance in India as well as high burden states.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Ray A Yeager", - "author_inst": "Christina Lee Brown Envirome Institute, University of Louisville" - }, - { - "author_name": "Rochelle H Holm", - "author_inst": "Christina Lee Brown Envirome Institute, University of Louisville" - }, - { - "author_name": "Kumar Saurabh", - "author_inst": "James Graham Brown Canter Center, University of Louisville" - }, - { - "author_name": "Joshua L Fuqua", - "author_inst": "Center for Predictive Medicine, University of Louisville" - }, - { - "author_name": "Daymond Talley", - "author_inst": "Louisville/Jefferson County Metropolitan Sewer District, Morris Forman Water Quality Treatment Center" + "author_name": "Parmeshwar D Satpathy", + "author_inst": "AIIMS BHOPAL" }, { - "author_name": "Aruni Bhatnagar", - "author_inst": "Christina Lee Brown Envirome Institute, University of Louisville" + "author_name": "Sanjeev Kumar", + "author_inst": "AIIMS Bhopal" }, { - "author_name": "Ted R Smith", - "author_inst": "University of Louisville" + "author_name": "Pankaj Prasad", + "author_inst": "AIIMS Bhopal" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.08.23.20180307", @@ -1198569,59 +1199229,39 @@ "category": "bioengineering" }, { - "rel_doi": "10.1101/2020.08.23.263327", - "rel_title": "A negative feedback model to explain regulation of SARS-CoV-2 replication and transcription", + "rel_doi": "10.1101/2020.08.24.264465", + "rel_title": "Dynamics of the N-terminal domain of SARS-CoV-2 nucleocapsid protein drives dsRNA melting in a counterintuitive tweezer-like mechanism", "rel_date": "2020-08-24", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.23.263327", - "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although a preliminary understanding of the replication and transcription mechanisms of SARS-CoV-2 has recently emerged, their regulation remains unclear.\n\nResultsBased on reanalysis of public data, we propose a negative feedback model to explain the regulation of replication and transcription in--but not limited to--SARS-CoV-2. The key step leading to new discoveries was the identification of the cleavage sites of nsp15--an RNA uridylate-specific endoribonuclease, encoded by CoVs. According to this model, nsp15 regulates the synthesis of subgenomic RNAs (sgRNAs) and genomic RNAs (gRNAs) by cleaving transcription regulatory sequences in the body. The expression level of nsp15 determines the relative proportions of sgRNAs and gRNAs, which in turn change the expression level of nps15 to reach equilibrium between the replication and transcription of CoVs.\n\nConclusionsThe replication and transcription of CoVs are regulated by a negative feedback mechanism that influences the persistence of CoVs in hosts. Our findings enrich fundamental knowledge in the field of gene expression and its regulation, and provide new clues for future studies. One important clue is that nsp15 may be an important and ideal target for the development of drugs (e.g. uridine derivatives) against CoVs.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.24.264465", + "rel_abs": "The N protein of betacoronaviruses is responsible for nucleocapsid assembly and other essential regulatory functions. Its N-terminal domain (NTD) interacts and melts the double-stranded transcriptional regulatory sequences (dsTRS), regulating the discontinuous subgenome transcription process. Here, we used molecular dynamics (MD) simulations to study the binding of SARS-CoV-2 N-NTD to non-specific (NS) and TRS dsRNAs. We probed dsRNAs Watson and Crick (WC) base-pairing over 25 replicas of 100 ns MD simulations, showing that only one N-NTD of dimeric N is enough to destabilize dsRNAs, initiating melting. N-NTD dsRNA destabilizing activity was more efficient for dsTRS than dsNS. N-NTD dynamics, especially a tweezer-like motion of {beta}2-{beta}3 and 2-{beta}5 loops, played a key role in WC base-pairing destabilization. Based on experimental information available in the literature, we constructed kinetics models for N-NTD-mediated dsRNA melting. Our results support a 1:1 stoichiometry (N-NTD:dsRNA), matching MD simulations and raising different possibilities for N-NTD action: (i) two N-NTDs of dimeric N would act independently, increasing efficiency; (ii) two N-NTDs of dimeric N would bind to two different RNA sites, bridging distant regions of the genome; and (iii) monomeric N would be active, opening up the possibility of a regulatory dissociation event.\n\nIMPORTANCECoronaviruses are among the largest positive-sense RNA viruses. They display a unique discontinous transcription mechanism, involving N protein as a major player. The N-NTD promote the dsRNA melting releasing the nascent sense negative strand via a poorly known mechanism of action. It specifically recognizes the body TRS conserved RNA motif located at the 5 end of each ORF. N protein has the ability to transfer the nascent RNA strand to the leader TRS. The mechanism is essential and one single mutation at the RNA binding site of the N-NTD impairs the viral replication. Here, we describe a counterintuitive mechanism of action of N-NTD based on molecular dynamics simulation and kinetic modelling of the experimental melting activity of N-NTD. This data impacts directly in the understanding of the way N protein acts in the cell and will guide future experiments.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Gao Shan", - "author_inst": "Nankai University" - }, - { - "author_name": "Cheng Zhi", - "author_inst": "Nankai University" - }, - { - "author_name": "Jin Xiufeng", - "author_inst": "Nankai University" + "author_name": "Icaro Putinhon Caruso", + "author_inst": "Federal University of Rio de Janeiro and Sao Paulo State University" }, { - "author_name": "Wang Fang", - "author_inst": "The Second Hospital of Tianjin Medical University" - }, - { - "author_name": "Xuan Yibo", - "author_inst": "Hebei Normal University" - }, - { - "author_name": "Zhou Hao", - "author_inst": "Nankai University" - }, - { - "author_name": "Liu Chang", - "author_inst": "Nankai University" + "author_name": "Karoline Sanches", + "author_inst": "Federal University of Rio de Janeiro and Sao Paulo State University" }, { - "author_name": "Ruan Jishou", - "author_inst": "Nankai University" + "author_name": "Andrea Da Poian", + "author_inst": "Federal University of Rio de Janeiro" }, { - "author_name": "Duan Guangyou", - "author_inst": "Qilu Normal University" + "author_name": "Anderson Pinheiro", + "author_inst": "Federal University of Rio de Janeiro" }, { - "author_name": "Li Xin", - "author_inst": "Nankai University" + "author_name": "Fabio C. L. Almeida", + "author_inst": "Federal University of Rio de Janeiro" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "bioinformatics" + "category": "biophysics" }, { "rel_doi": "10.1101/2020.08.24.264077", @@ -1200123,47 +1200763,99 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.20.20177949", - "rel_title": "Examining the status of improved air quality due to COVID-19 lockdown and an associated reduction in anthropogenic emissions", + "rel_doi": "10.1101/2020.08.21.262329", + "rel_title": "Impaired cytotoxic CD8+ T cell response in elderly COVID-19 patients", "rel_date": "2020-08-24", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.20.20177949", - "rel_abs": "Clean air is a fundamental necessity for human health and well-being. The COVID-19 lockdown worldwide resulted in controls on anthropogenic emission that have a significant synergistic effect on air quality ecosystem services (ESs). This study utilised both satellite and surface monitored measurements to estimate air pollution for 20 cities across the world. Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI) data were used for evaluating tropospheric air quality status during the lockdown period. Surface measurement data were retrieved from the Environmental Protection Agency (EPA, USA) for a more explicit assessment of air quality ESs. Google Earth Engine TROPOMI application was utilised for a time series assessment of air pollution during the lockdown (1 Feb to 11 May 2020) compared with the lockdown equivalent periods (1 Feb to 11 May 2019). The economic valuation for air pollution reduction services was measured using two approaches: (1) median externality value coefficient approach; and (2) public health burden approach. Human mobility data from Apple (for city-scale) and Google (for country scale) was used for examining the connection between human interferences on air quality ESs. Using satellite data, the spatial and temporal concentration of four major pollutants such as nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO) and the aerosol index (AI) were measured. For NO2, the highest reduction was found in Paris (46%), followed by Detroit (40%), Milan (37%), Turin (37%), Frankfurt (36%), Philadelphia (34%), London (34%), and Madrid (34%), respectively. At the same time, a comparably lower reduction of NO2 is observed in Los Angeles (11%), Sao Paulo (17%), Antwerp (24%), Tehran (25%), and Rotterdam (27%), during the lockdown period. Using the adjusted value coefficients, the economic value of the air quality ESs was calculated for different pollutants. Using the public health burden valuation method, the highest economic benefits due to the reduced anthropogenic emission (for NO2) was estimated in US$ for New York (501M $), followed by London (375M $), Chicago (137M $), Paris (124M $), Madrid (90M $), Philadelphia (89M $), Milan (78M $), Cologne (67M $), Los Angeles (67M $), Frankfurt (52M $), Turin (45M $), Detroit (43M $), Barcelona (41M $), Sao Paulo (40M $), Tehran (37M $), Denver (30M $), Antwerp (16M $), Utrecht (14 million $), Brussels (9 million $), Rotterdam (9 million $), respectively. In this study, the public health burden and median externality valuation approaches were adopted for the economic valuation and subsequent interpretation. This one dimension and linear valuation may not be able to track the overall economic impact of air pollution on human welfare. Therefore, research that broadens the scope of valuation in environmental capitals needs to be initiated for exploring the importance of proper monetary valuation in natural capital accounting.", - "rel_num_authors": 7, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.21.262329", + "rel_abs": "SARS-CoV-2 infection induces a T cell response that most likely contributes to virus control in COVID-19 patients, but may also induce immunopathology. Until now, the cytotoxic T cell response has not been very well characterized in COVID-19 patients.\n\nHere, we analyzed the differentiation and cytotoxic profile of T cells in 30 cases of mild COVID-19 during acute infection. SARS-CoV-2 infection induced a cytotoxic response of CD8+ T cells, but not CD4+ T cells, characterized by the simultaneous production of granzyme A and B, as well as perforin within different effector CD8+ T cell subsets. PD-1 expressing CD8+ T cells also produced cytotoxic molecules during acute infection indicating that they were not functionally exhausted. However, in COVID-19 patients over the age of 80 years the cytotoxic T cell potential was diminished, especially in effector memory and terminally differentiated effector CD8+ cells, showing that elderly patients have impaired cellular immunity against SARS-CoV-2.\n\nOur data provides valuable information about T cell responses in COVID-19 patients that may also have important implications for vaccine development.\n\nImportanceCytotoxic T cells are responsible for the elimination of infected cells and are key players for the control of viruses. CD8+ T cells with an effector phenotype express cytotoxic molecules and are able to perform target cell killing. COVID-19 patients with a mild disease course were analyzed for the differentiation status and cytotoxic profile of CD8+ T cells. SARS-CoV-2 infection induced a vigorous cytotoxic CD8+ T cell response. However, this cytotoxic profile of T cells was not detected in COVID-19 patients over the age of 80 years. Thus, the absence of a cytotoxic response in elderly patients might be a possible reason for the more frequent severity of COVID-19 in this age group in comparison to younger patients.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Srikanta Sannigrahi", - "author_inst": "School of Architecture, Planning and Environmental Policy, University College Dublin Richview, Clonskeagh, Dublin, D14 E099, Ireland." + "author_name": "Jaana Westmeier", + "author_inst": "University Hospital Essen" }, { - "author_name": "Anna Molter", - "author_inst": "University College Dublin, University of Manchester." + "author_name": "Krystallenia Paniskaki", + "author_inst": "University Hospital Essen, University of Duisburg-Essen," }, { - "author_name": "Prashant Kumar", - "author_inst": "Global Centre for Clean Air Research (GCARE), Department of Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Sur" + "author_name": "Zehra Karak\u00f6se", + "author_inst": "University Hospital Essen, University of Duisburg-Essen," }, { - "author_name": "Qi Zhang", - "author_inst": "Frederick S. Pardee Center for the Study of the Longer-Range Future, Frederick S. Pardee School of Global Studies, Boston University, Boston, MA 02215, USA" + "author_name": "Tanja Werner", + "author_inst": "University Hospital Essen" }, { - "author_name": "Bidroha Basu", - "author_inst": "School of Architecture, Planning and Environmental Policy, University College Dublin Richview, Clonskeagh, Dublin, D14 E099, Ireland." + "author_name": "Kathrin Sutter", + "author_inst": "University of Duisburg-Essen" }, { - "author_name": "Arunima Sarkar Basu", - "author_inst": "School of Architecture, Planning and Environmental Policy, University College Dublin Richview, Clonskeagh, Dublin, D14 E099, Ireland." + "author_name": "Sebastian Dolff", + "author_inst": "University Hospital Essen, University of Duisburg-Essen" }, { - "author_name": "Francesco Pilla", - "author_inst": "University College Dublin" + "author_name": "Marvin Overbeck", + "author_inst": "University of Duisburg-Essen" + }, + { + "author_name": "Andreas Limmer", + "author_inst": "University Hospital Essen, University of Duisburg-Essen" + }, + { + "author_name": "Jia Liu", + "author_inst": "Department of Infectious Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Xin Zheng", + "author_inst": "Union Hospital of Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Thorsten Brenner", + "author_inst": "Essen University Hospital" + }, + { + "author_name": "Marc M. Berger", + "author_inst": "University Hospital Essen, University of Duisburg-Essen" + }, + { + "author_name": "Oliver Witzke", + "author_inst": "Universit\u00e4tsmedizin Essen" + }, + { + "author_name": "Mirko Trilling", + "author_inst": "Institute for Virology, University Hospital Essen, University of Duisburg-Essen" + }, + { + "author_name": "Mengji Lu", + "author_inst": "University Hospital Essen, University Duisburg-Essen" + }, + { + "author_name": "Dongliang Yang", + "author_inst": "Union Hospital of Tonji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Nina Babel", + "author_inst": "Medical Department I, Marien Hospital Herne, University Hospital of the Ruhr-University Bochum" + }, + { + "author_name": "Timm Westhoff", + "author_inst": "Medical Department I, Marien Hospital Herne, University Hospital of the Ruhr-University Bochum" + }, + { + "author_name": "Ulf Dittmer", + "author_inst": "University of Duisburg-Essen" + }, + { + "author_name": "Gennadiy Zelinskyy", + "author_inst": "University Hospital Essen" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2020.08.23.255364", @@ -1201801,55 +1202493,47 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.08.19.20178319", - "rel_title": "Evaluating aerosol and splatter during orthodontic debonding: implications for the COVID-19 pandemic", + "rel_doi": "10.1101/2020.08.20.20178509", + "rel_title": "Lockdown, relaxation, and ACME period in COVID-19: A study of disease dynamics on Hermosillo, Sonora, Mexico", "rel_date": "2020-08-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.19.20178319", - "rel_abs": "IntroductionDental procedures often produce splatter and aerosol which have potential to spread pathogens such as SARS-CoV-2. Mixed guidance exists on the aerosol generating potential of orthodontic procedures. The aim of this study was to evaluate aerosol and/or splatter contamination during an orthodontic debonding procedure.\n\nMaterial and MethodsFluorescein dye was introduced into the oral cavity of a mannequin. Orthodontic debonding was carried out in triplicate with filter papers placed in the immediate environment. Composite bonding cement was removed using a slow-speed handpiece with dental suction. A positive control condition included a high-speed air-turbine crown preparation. Samples were analysed using digital image analysis and spectrofluorometric analysis.\n\nResultsContamination across the 8-metre experimental rig was 3% of the positive control on spectrofluorometric analysis and 0% on image analysis. There was contamination of the operator, assistant, and mannequin, representing 8%, 25%, and 28% of the positive control spectrofluorometric measurements, respectively.\n\nDiscussionOrthodontic debonding produces splatter within the immediate locality of the patient. Widespread aerosol generation was not observed.\n\nConclusionsOrthodontic debonding procedures are low risk for aerosol generation, but localised splatter is likely. This highlights the importance of personal protective equipment for the operator, assistant, and patient.\n\nThree In brief pointsO_LIOrthodontic debonding, including removal of composite using a slow speed handpiece with dental suction, appears to be a low risk procedure for aerosol generation.\nC_LIO_LISplatter was produced during the debonding procedure, however this was mainly localised to the patient, operator and assistant.\nC_LIO_LIA single positive reading was identified 3.5 meters away from the patient, highlighting the need for suitable distancing and/or barriers in open clinical environments.\nC_LI", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.20.20178509", + "rel_abs": "Lockdown and social distancing measures have been implemented for many countries to mitigate the impacts of the COVID-19 pandemic and prevent overwhelming of health services. However, success on this strategy depends not only on the timing of its implementation, but also on the relaxation measures adopted within each community. We developed a mathematical model to evaluate the impacts of the lockdown implemented in Hermosillo, Mexico. We compared this intervention with some hypothetical ones, varying the starting date and also the population proportion that is released, breaking the confinement. A Monte Carlo study was performed by considering three scenarios to define our baseline dynamics. Results showed that a hypothetical delay of two weeks, on the lockdown measures, would result in an early ACME around May 9 for hospitalization prevalence and an increase on cumulative deaths, 42 times higher by May 31, when compared to baseline. On the other hand, results concerning relaxation dynamics showed that the ACME levels depend on the proportion of people who gets back to daily activities as well as the individual behavior with respect to prevention measures. Analysis regarding different relaxing mitigation measures were provided to the Sonoran Health Ministry, as requested. It is important to stress that, according to information provided by health authorities, the ACME occurring time was closed to the one given by our model. Hence, we considered that our model resulted useful for the decision-making assessment, and that an extension of it can be used for the study of a potential second wave.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Hayley Llandro", - "author_inst": "Newcastle University" - }, - { - "author_name": "James Allison", - "author_inst": "Newcastle University" - }, - { - "author_name": "Charlotte Currie", - "author_inst": "Newcastle University" + "author_name": "Mayra Tocto-Erazo", + "author_inst": "University of Sonora" }, { - "author_name": "David Edwards", - "author_inst": "Newcastle University" + "author_name": "Jorge A. Esp\u00edndola-Zepeda", + "author_inst": "University of Sonora" }, { - "author_name": "Charlotte Bowes", - "author_inst": "Newcastle University" + "author_name": "Jos\u00e9 A. Montoya-Laos", + "author_inst": "University of Sonora" }, { - "author_name": "Justin Durham", - "author_inst": "Newcastle University" + "author_name": "Manuel Adrian Acu\u00f1a-Zegarra", + "author_inst": "University of Sonora" }, { - "author_name": "Nicholas Jakubovics", - "author_inst": "Newcastle University" + "author_name": "Daniel Olmos-Liceaga", + "author_inst": "University of Sonora" }, { - "author_name": "Nadia Rostami", - "author_inst": "Newcastle University" + "author_name": "Pablo A. Reyes-Castro", + "author_inst": "El Colegio de Sonora" }, { - "author_name": "Richard Holliday", - "author_inst": "Newcastle University" + "author_name": "Gudelia Figueroa-Preciado", + "author_inst": "University of Sonora" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "dentistry and oral medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.08.19.20178129", @@ -1203335,37 +1204019,25 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2020.08.18.20173500", - "rel_title": "The Mental Health of Healthcare Staff during the COVID-19 Pandemic: It Depends on How Much They Work and Their Age", + "rel_doi": "10.1101/2020.08.17.20176628", + "rel_title": "Summer COVID-19 third wave: faster high altitude spread suggests high UV adaptation", "rel_date": "2020-08-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.18.20173500", - "rel_abs": "BackgroundHealthcare staff are the forefront of fight against COVID-19 and they are under enormous pressure due to the fast growth in the number and severity of infected cases. This creates their mental issues such as distress, depression and anxiety. Exploring healthcare staffs mental health during the pandemic contributes to improving their persistence in the growing challenges created by COVID-19 and enabling effective management of their mental health.\n\nMethodsAn online survey of 280 healthcare staff in all the 31 provinces of Iran was conducted during April 5-20, 2020. The survey assessed staffs distress, depression and anxiety in the COVID-19 pandemic.\n\nResultsNearly a third of healthcare staff suffered from distress, depression and anxiety. Females and more educated healthcare staff were more likely to experience distress. Compared to personnel who did not have COVID-19, those who were unsure whether they had COVID-19 were more likely to experience distress and depression. The number of COVID-19 cases among the staffs colleagues or friends positively predicted their anxiety. Compared to radio technologists, doctors were less likely to experience distress and anxiety. Technicians and obstetrics experienced less anxiety. Analysis the interaction between weekly working days and age of the staff indicated the chance of experiencing distress and depression varied greatly by working days among younger but not older healthcare staff.\n\nConclusionThe predictors of mental health issues assists healthcare organizations to identify healthcare staff with mental health issues in sever crises such as the COVID-19 pandemic. Our research highlight the need to identify more working characteristics as predictors for healthcare staff at different ages.\n\nFundingThis work was supported by Tsinghua University-INDITEX Sustainable Development Fund (No. TISD201904).", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.17.20176628", + "rel_abs": "We present spread parameters for first and second waves of the COVID-19 pandemy for USA states, and third wave for 32 regions (19 countries and 13 states of the USA) detected beginning of August 2020. USA first/second wave spreads increase/decrease with population density, are uncorrelated with temperature and median population age. Pooling all 32 regions, third wave spread is slower than for first wave, similar to second wave, and increases with mean altitude (second wave slopes decrease above 900m). Apparently, viruses adapted in spring (second wave) to high temperatures and infecting the young, and in summer (third) waves for spread at altitudes above 1000m. Third wave slopes are not correlated to temperature, so patterns with elevation presumably indicate resistance to relatively high UV regimes. Environmental trends of the COVID-19 pandemy change at incredible rates, making predictions based on classical epidemiological knowledge particularly uncertain.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Xingzi Xu", - "author_inst": "Tsinghua University" - }, - { - "author_name": "Stephen X. Zhang", - "author_inst": "University of Adelaide" - }, - { - "author_name": "Asghar Afshar Jahanshahi", - "author_inst": "Pontificia Universidad Catolica del Peru" - }, - { - "author_name": "Jizhen Li", - "author_inst": "Tsinghua University" + "author_name": "Herve Seligmann", + "author_inst": "The Hebrew University of Jerusalem" }, { - "author_name": "Afsaneh Bagheri", - "author_inst": "University of Tehran" + "author_name": "Nicolas Vuillerme", + "author_inst": "University Grenoble Alpes" }, { - "author_name": "Khaled Nawaser", - "author_inst": "Arvandan Non-profit Higher Education Institute" + "author_name": "Jacques Demongeot", + "author_inst": "University Grenoble Alpes" } ], "version": "1", @@ -1204965,47 +1205637,43 @@ "category": "pathology" }, { - "rel_doi": "10.1101/2020.08.20.259747", - "rel_title": "COVID-19 and Cholinergic Anti-inflammatory Pathway: In silico Identification of an Interaction between alpha7 Nicotinic Acetylcholine Receptor and the Cryptic Epitopes of SARS-CoV and SARS-CoV-2 Spike Glycoproteins", + "rel_doi": "10.1101/2020.08.20.259531", + "rel_title": "Morphometry of SARS-CoV and SARS-CoV-2 particles in ultrathin sections of infected Vero cell cultures.", "rel_date": "2020-08-21", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.20.259747", - "rel_abs": "SARS-CoV-2 is the coronavirus that originated in Wuhan in December 2019 and has spread globally. The observation of a low prevalence of smokers among hospitalized COVID-19 patients has led to the development of a hypothesis that nicotine could have protective effects by enhancing the cholinergic anti-inflammatory pathway. Based on clinical data and on modelling and docking experiments we have previously presented the potential interaction between SARS-CoV-2 Spike glycoprotein and nicotinic acetylcholine receptors (nAChRs), due to a \"toxin-like\" epitope on the Spike Glycoprotein, with homology to a sequence of a snake venom toxin. We here present that this epitope coincides with the well-described cryptic epitope for the human antibody CR3022 and with the epitope for the recently described COVA1-16 antibody. Both antibodies are recognizing neighboring epitopes, are not interfering with the ACE2 protein and are not able to inhibit SARS-CoV and SARS-CoV-2 infections. In this study we present the molecular complexes of both SARS-CoV and SARS-CoV-2 Spike Glycoproteins, at their open or closed conformations, with the molecular model of the human 7 nAChR. We found that the interface of all studied protein complexes involves a large part of the \"toxin-like\" sequences of SARS-CoV and SARS-CoV-2 Spike glycoproteins and toxin binding site of human 7 nAChR.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.20.259531", + "rel_abs": "SARS-CoV-2 is the causative of the COVID-19 disease, which has spread pandemically around the globe within a few months. It is therefore necessary to collect fundamental information about the disease, its epidemiology and treatment, as well as about the virus itself. While the virus has been identified rapidly, detailed ultrastructural analysis of virus cell biology and architecture is still in its infancy. We therefore studied the virus morphology and morphometry of SARS-CoV-2 in comparison to SARS-CoV as it appears in Vero cell cultures by using conventional thin section electron microscopy and electron tomography. Both virus isolates, SARS-CoV Frankfurt 1 and SARS-CoV-2 Italy-INMI1, were virtually identical at the ultrastructural level and revealed a very similar particle size distribution with a median of about 100 nm without spikes. Maximal spike length of both viruses was 23 nm. The number of spikes per virus particle was about 30% higher in the SARS-CoV than in the SARS-CoV-2 isolate. This result complements a previous qualitative finding, which was related to a lower productivity of SARS-CoV-2 in cell culture in comparison to SARS-CoV.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "George Lagoumintzis", - "author_inst": "Laboratory of Mol. Biology and Immunology, Department of Pharmacy, University of Patras" - }, - { - "author_name": "Christos Chasapis", - "author_inst": "Laboratory of Mol. Biology and Immunology, Department of Pharmacy, University of Patras" + "author_name": "Michael Laue", + "author_inst": "Robert Koch Institute" }, { - "author_name": "Nikolaos Alexandris", - "author_inst": "Laboratory of Mol. Biology and Immunology, Department of Pharmacy, University of Patras" + "author_name": "Anne Kauter", + "author_inst": "Robert Koch Institute" }, { - "author_name": "Socrates Tzartos", - "author_inst": "Laboratory of Mol. Biology and Immunology, Department of Pharmacy, University of Patras" + "author_name": "Tobias Hoffmann", + "author_inst": "RobertKoch Institute" }, { - "author_name": "Elias Eliopoulos", - "author_inst": "Agricultural University of Athens" + "author_name": "Lars Moeller", + "author_inst": "Robert Koch Institute" }, { - "author_name": "Konstantinos Farsalinos", - "author_inst": "Laboratory of Mol. Biology and Immunology, Department of Pharmacy, University of Patras" + "author_name": "Janine Michel", + "author_inst": "Robert Koch Institute" }, { - "author_name": "Konstantinos Poulas", - "author_inst": "Laboratory of Mol. Biology and Immunology, Department of Pharmacy, University of Patras" + "author_name": "Andreas Nitsche", + "author_inst": "Robert Koch Institute" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.08.20.260190", @@ -1206715,51 +1207383,23 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.18.20177600", - "rel_title": "COVID-19: Effectiveness of Non-Pharmaceutical Interventions in the United States before Phased Removal of Social Distancing Protections Varies by Region", + "rel_doi": "10.1101/2020.08.14.20174995", + "rel_title": "Covid19data.website", "rel_date": "2020-08-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.18.20177600", - "rel_abs": "Although coronavirus disease 2019 (COVID-19) emerged in January 2020, there is no quantified effect size for non-pharmaceutical interventions (NPI) to control the outbreak in the continental US. Objective. To quantify national and sub-national effect sizes of NPIs in the US. Design. This is an observational study for which we obtained daily county level COVID-19 cases and deaths from January 22, 2020 through the phased removal of social distancing protections. A stepped-wedge cluster-randomized trial (SW-CRT) analytical approach is used, leveraging the phased implementation of policies. Data include 3142 counties from all 50 US states and the District of Columbia. Exposures. County-level NPIs were obtained from online county and state policy databases, then classified into four intervention levels: Level 1 (low) - declaration of a State of Emergency; Level 2 (moderate) - school closures, restricting nursing home access, or closing restaurants and bars; Level 3 (high) - non-essential business closures, suspending non-violent arrests, suspending elective medical procedures, suspending evictions, or restricting mass gatherings of at least 10 people; and Level 4 (aggressive) - sheltering in place / stay-at-home, public mask requirements, or travel restrictions. Additional county-level data were obtained to record racial (Black, Hispanic), economic (educational level, poverty), demographic (rural/urban) and climate factors (temperature, specific humidity, solar radiation). Main Outcomes. The primary outcomes are rates of COVID-19 cases, deaths and case doubling times. NPI effects are measured separately for nine US Census Region (Pacific, Mountain, West North Central, East North Central, West South Central, East South Central, South Atlantic, Middle Atlantic, New England). Results. Aggressive NPIs (level 4) significantly reduced COVID-19 case and death rates in all US Census Regions, with effect sizes ranging from 4.1% to 25.7% and 5.5% to 25.5%, respectively, for each day they were active. No other intervention level achieved significance across all US Regions. Intervention levels 3 and 4 both increased COVID-19 doubling times, with effects peaking at 25 and 40 days after initiation of each policy, respectively. The effectiveness of level 3 NPIs varied, reducing case rates in all regions except North Central states, but associated with significantly higher death rates in all regions except Pacific states. Intervention levels 1 and 2 did not indicate any effect on COVID-19 propagation and, in some regions, these interventions were associated with increased COVID-19 cases and deaths. Heterogeneity of NPI effects are associated with racial composition, poverty, urban-rural environment, and climate factors. Conclusion. Aggressive NPIs are effective tools to reduce COVID-19 propagation and mortality. Reducing social and environmental disparities may improve NPI effects in regions where less strict policies are in place.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.14.20174995", + "rel_abs": "Covid19data.website Project is a website that contains more than 250 Dashboards about the COVID-19 Toll areas affected by the virus. You can follow-up every day using this website the number of COVID-19 cases, deaths, active cases, the shares by 1 Million population, the mortality rate, the active rate in every country, continent, and territory and all States in the United States. Unlike the other websites, you can also follow-up an estimation of the reproduction number in the previous sixteen days. These statistics tell you how many secondary infections are likely to occur in a specific area.\n\nFurthermore, I provide a classification algorithm of the countries and the affected areas. Its based on the observation during the previous 14 days of six criteria. A global score is then computed, allowing to evaluate the COVID-19 safeness toll of each area.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "William Pan", - "author_inst": "Duke University" - }, - { - "author_name": "Stefanos Tyrovolas", - "author_inst": "Parc Sanitari Sant Joan de Deu, Universitat de Barcelona" - }, - { - "author_name": "Iago Gine Vazquez", - "author_inst": "Parc Sanitari Sant Joan de Deu, Universitat de Barcelona" - }, - { - "author_name": "Rishav Raj", - "author_inst": "Duke University" - }, - { - "author_name": "Daniel Fernandez", - "author_inst": "Instituto de Salud Carlos III, Centro de Investigacion Biomedica en Red de Salud Mental, CIBERSAM" - }, - { - "author_name": "Ben Zaitchik", - "author_inst": "Johns Hopkins University" - }, - { - "author_name": "Paul Lantos", - "author_inst": "Duke University" - }, - { - "author_name": "Christopher W. Woods", - "author_inst": "Duke University School of Medicine" + "author_name": "dhafer malouche", + "author_inst": "ESSAI-University of Carthage" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.08.16.20175901", @@ -1208633,31 +1209273,87 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2020.08.15.20158725", - "rel_title": "Investigation into Quality of Life and Psychological Status of Different Populations during COVID-19 : A study concerning Surrounding Areas of Wuhan", + "rel_doi": "10.1101/2020.08.16.20172668", + "rel_title": "End-to-End Protocol for the Detection of SARS-CoV-2 from Built Environments", "rel_date": "2020-08-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.15.20158725", - "rel_abs": "ObjectiveTo investigate different populations quality of life and psychological status in surrounding areas of Wuhan during COVID-19 pandemic.\n\nMethodsThe data of 248 residents living in Anhui from February 4 to 6 of 2020 were collected through network surveys including age, gender, occupation, the World Health Organization Quality of Life measurement Scale short form (World Health Organization Quality of Life instrument brief, WHOQOL BREF), Zung Self-rating Anxiety Scale (Self-rating Anxiety Scale, SAS and Zung Self-Rating Depression Scale (SDS). Those surveyed, divided into two groups: medical staff (129 cases) and nonmedical staff (119 cases), were made statistic analysis according to the factors mentioned above.\n\nResultsThe WHOQOL-BREF of medical staff in this region was lower than that of nonmedical staff in the fields of physiology, psychology, social relations, and environment, among whom female medical staff scored significantly lower than that of male medical staff in four fields. There was no significant statistical difference in SAS and SDS scores between the two groups, and gender had no significant influence on SAS and SDS scores of medical staff.\n\nConclusionDuring the COVID-19 pandemic, medical staff enjoyed a lower quality of life in surrounding areas of Wuhan than that of nonmedical staff, and female medical staff even lower, which should arouse social concerns.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.16.20172668", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019, is a respiratory virus primarily transmitted from person to person through inhalation of droplets or aerosols, laden with viral particles. However, as some studies have shown, virions can remain infectious for up to 72 hours on surfaces, which can lead to transmission through contact. For this reason, a comprehensive study was conducted to determine the efficiency of protocols to recover SARS-CoV-2 from surfaces in built environments. This end-to-end (E2E) study showed that the effective combination of monitoring SARS-CoV-2 on surfaces include using an Isohelix swab as a collection tool, DNA/RNA Shield as a preservative, an automated system for RNA extraction, and reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) as the detection assay. Using this E2E approach, this study showed that, in some cases, SARS-CoV-2 viral standards were still recovered from surfaces as detected by RT-qPCR for as long as eight days even after bleach treatment. Additionally, debris associated with specific built environment surfaces appeared to negatively impact the recovery of RNA, with Amerstat inhibition as high as 90% when challenged with an inactivated viral control. Overall, it was determined that this E2E protocol required a minimum of 1,000 viral particles per 25 cm2 to successfully detect virus from test surfaces. When this method was employed to evaluate 368 samples collected from various built environmental surfaces, all samples tested negative, indicating that the surfaces were either void of virus or below the detection limit of the assay.\n\nImportanceThe ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (the virus responsible for coronavirus disease 2019; COVID-19) pandemic has led to a global slow down with far reaching financial and social impacts. The SARS-CoV-2 respiratory virus is primarily transmitted from person to person through inhalation of infected droplets or aerosols. However, some studies have shown virions can remain infectious on surfaces for days, and can lead to human infection from contact with infected surfaces. Thus, a comprehensive study was conducted to determine the efficiency of protocols to recover SARS-CoV-2 from surfaces in built environments. This end-to-end study showed that the effective combination of monitoring SARS-CoV-2 on surfaces required a minimum of 1,000 viral particles per 25 cm2 to successfully detect virus from surfaces. This comprehensive study can provide valuable information regarding surface monitoring of various materials as well as the capacity to retain viral RNA and allow for effective disinfection.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Zheng Liu", - "author_inst": "The First Affiliated Hospital of USTC,Division of Life Sciences and Medicine, University of Science" + "author_name": "Ceth W. Parker", + "author_inst": "Jet Propulsion Laboratory-NASA" + }, + { + "author_name": "Nitin Singh", + "author_inst": "Jet Propulsion Laboratory" + }, + { + "author_name": "Scott Tighe", + "author_inst": "University of Vermont" + }, + { + "author_name": "Adriana Blachowicz", + "author_inst": "California Institute of Technology" + }, + { + "author_name": "Jason M Wood", + "author_inst": "California Institute of Technology" + }, + { + "author_name": "Arman Seuylemezian", + "author_inst": "California Polytechnic University of Pomona" }, { - "author_name": "Jingsong Mu", - "author_inst": "The First Affiliated Hospital of USTC,Division of Life Sciences and Medicine, University of Science and Technology of China" + "author_name": "Parag Vaishampayan", + "author_inst": "Jet Propulsion Laboratory, California Institute of Technology" }, { - "author_name": "Wenxiang Fan", - "author_inst": "The First Affiliated Hospital of USTC,Division of Life Sciences and Medicine, University of Science and Technology of China" + "author_name": "Camilla Urbaniak", + "author_inst": "NASA Jet Propulsion Laboratory" + }, + { + "author_name": "Ryan Hendrickson", + "author_inst": "Jet Propulsion Lab" + }, + { + "author_name": "Pheobe Laaguiby", + "author_inst": "University of Vermont" + }, + { + "author_name": "Kevin Clark", + "author_inst": "Jet Propulsion Laboratory-NASA" + }, + { + "author_name": "Brian G Clement", + "author_inst": "NASA Jet Propulsion Laboratory" + }, + { + "author_name": "Niamh B O'Hara", + "author_inst": "Biotia" + }, + { + "author_name": "Mara Couto-Rodriguez", + "author_inst": "Biotia" + }, + { + "author_name": "Daniela Bezdan", + "author_inst": "Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology" + }, + { + "author_name": "Chris Mason", + "author_inst": "Cornell University" + }, + { + "author_name": "Kasthuri Venkateswaran", + "author_inst": "California Institute of Technology" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.08.17.20174821", @@ -1210507,23 +1211203,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.15.20175653", - "rel_title": "ESTIMATING PREVALENCE AND TIME COURSE OF SARS-CoV-2 BASED ON NEW HOSPITAL ADMISSIONS AND PCR TESTS", + "rel_doi": "10.1101/2020.08.14.20175372", + "rel_title": "The influence of climate factors on COVID-19 transmission in Malaysia: An autoregressive integrated moving average (ARIMA) model", "rel_date": "2020-08-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.15.20175653", - "rel_abs": "Data posted in the COVID 19 tracking website for RT-PCR (PCR) results and hospital admissions are used to estimate the time course of the SARS-CoV-2 pandemic in the United States (1) and individual states. Hospital admissions mitigate positive sampling bias in PCR tests since these were limited in numbers initially. Additionally, their intent was as a diagnostic rather than a surveying tool.\n\nBy September 17, the United States cumulative recovered population is estimated at 45% or 149 million. The remaining susceptible population is 55%, or 50%, excepting the currently infected 5% population. The estimated mortality rate of the cumulative of the total affected population is 0.13% death.\n\nStates have followed diverse epidemic time courses. New Jersey and New York show SARS-CoV-2 prevalence of 95% and 82%, respectively. Likewise, each state exhibits relatively low current positive PCR results at 1.2 % and 0.8%. Also, these states show about twice the mortality rate of the nation. By comparison, Florida, California, and Texas showed recovered populations percent around 50%, and higher current PCR positive test results ranging from 5% to 9%.\n\nThis novel approach provides an improved source of information on the pandemics full-time course in terms of precision and accuracy in contrast to serological testing, which only views a narrow time slice of its history due to the transient nature of the antibody response and its graduated expression dependency on the severity of the disease. The deficiency of serological testing to estimate the recovered population is made even more acute due to the large proportion of asymptomatic and sub-clinical cases in the COVID-19 pandemic (2,3). T-cell testing, reputedly capable of long-term detection of previously infected individuals, will provide a complete view of the recovered population when it becomes available for large scale use.\n\nThis New Hospital Admission based method informs a more effective and efficient deployment of a vaccination program since it provides not only a reliable estimate of the susceptible population by state, but it can also provide visibility down to the county level based on COVID-19 hospitalization record independent of PCR testing.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.14.20175372", + "rel_abs": "BackgroundA unique concern pertaining to the spread of COVID-19 across countries is the asymmetry of risk and the irrational fear of a new pandemic and its possible serious consequences. This study aimed to perform a time series analysis on the association between climate factors and daily cases of COVID-19 in Malaysia up to 15 July 2020. The second objective was to predict daily new cases using a forecasting technique. To address within-country variations, the analysis was extended to the state level with Sarawak state as an example.\n\nMethodology/Principal FindingsDatasets on the daily confirmed cases and climate variables in Malaysia and Sarawak state were obtained from publicly accessible official websites. A descriptive analysis was performed to characterize all the important variables over the study period. An autoregressive integrated moving average (ARIMA) model was introduced using daily cases as the dependent variable and climate parameters as the explanatory variables.\n\nFor Malaysia, the findings suggest that, ceteris paribus, the number of COVID-19 cases decreased with increasing average temperature (p=0.003) or wind speed (p=0.029). However, none of the climate parameters showed a significant relationship with the number of COVID-19 cases in Sarawak state. Forecasts from the ARIMA models showed that new daily COVID-19 cases had already reached the outbreak level and a decreasing trend in both settings. Holding other parameters constant, a small number of new cases (approximately a single digit) is a probable second wave in Sarawak state,\n\nConclusions/SignificanceThe findings suggest that climate parameters and forecasts are helpful for reducing the uncertainty in the severity of future COVID-19 transmission. A highlight is that forecasts will be a useful tool for making decisions and taking the appropriate interventions to contain the spread of the virus in the community.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Jose E Gonzalez", - "author_inst": "Aletheia Analytics LLC" + "author_name": "Cho Naing", + "author_inst": "International Medical University" + }, + { + "author_name": "Han Ni", + "author_inst": "SEGi University, Sibu Clinical Campus, Sarawak, Malaysia" + }, + { + "author_name": "Htar Htar Aung", + "author_inst": "International Medical University" + }, + { + "author_name": "Elaine Chan Wan Ling", + "author_inst": "International Medical University" + }, + { + "author_name": "Joon Wah Mak", + "author_inst": "International Medical University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.08.15.20175513", @@ -1212173,21 +1212885,61 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.14.20174557", - "rel_title": "Superspreading as a Regular Factor of the COVID-19 Pandemic: II. Quarantine Measures and the Second Wave", + "rel_doi": "10.1101/2020.08.14.20175224", + "rel_title": "The Common Interests of Health Protection and theEconomy: Evidence from Scenario Calculations ofCOVID-19 Containment Policies", "rel_date": "2020-08-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.14.20174557", - "rel_abs": "Within the framework of a two-component model of the COVID-19 epidemic, taking into account the special role of superspreaders, we consider the impact of the recovery factor and quarantine measures on the course of the epidemic, as well as the possibility of a second wave of morbidity. It is assumed that there is no long-term immunity in asymptomatic superspreaders who have undergone the infection, and the emergence of long-term immunity in those who have undergone severe illness. It is shown that, under these assumptions, the relaxation of quarantine measures leads to the resumption of virus circulation among asymptomatic superspreaders. Depending on the characteristics of the quarantine, its removal may or may not lead to a renewed wave of daily morbidity. A criterion for the occurrence of repeated wave of morbidity is proposed based on the analysis of the final phase of the first wave. Based on this criterion, the repeated wave of the epidemic is predicted in New Zealand. A natural explanation is given for the decrease in lethality among the infected against the background of an absolute increase in their number.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.14.20175224", + "rel_abs": "Several countries use shutdown strategies to contain the spread of the COVID-19 epidemic, at the expense of massive economic costs. While this suggests a conflict between health protection and economic objectives, we examine whether the economically optimal exit strategy can be reconciled with the containment of the epidemic. We use a novel combination of epidemiological and economic simulations for scenario calculations based on empirical evidence from Germany. Our findings suggest that a prudent opening is economically optimal, whereas costs are higher for a more extensive opening process. This rejects the view that there is a conflict with health protection. Instead, it is in the common interest of public health and the economy to relax non-pharmaceutical interventions in a manner that keeps the epidemic under control.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Juri Dimaschko", - "author_inst": "Fachhochschule Luebeck" + "author_name": "Florian Dorn", + "author_inst": "ifo Institute - Leibniz Institute for Economic Research at the University Munich Germany" + }, + { + "author_name": "Sahamoddin Khailaie", + "author_inst": "Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Germany" + }, + { + "author_name": "Marc Stoeckli", + "author_inst": "ifo Institute - Leibniz Institute for Economic Research at the University of Munich, Germany" + }, + { + "author_name": "Sebastian C Binder", + "author_inst": "Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Germany" + }, + { + "author_name": "Berit Lange", + "author_inst": "Department of Epidemiology, Helmholtz Centre for Infection Research, Germany" + }, + { + "author_name": "Stefan Lautenbacher", + "author_inst": "ifo Institute - Leibniz Institute for Economic Research at the University of Munich, Germany" + }, + { + "author_name": "Andreas Peichl", + "author_inst": "ifo Institute - Leibniz Institute for Economic Research at the University of Munich, Germany" + }, + { + "author_name": "Patrizio Vanella", + "author_inst": "Department of Epidemiology, Helmholtz Centre for Infection Research, Germany" + }, + { + "author_name": "Timo Wollmershaeuser", + "author_inst": "ifo Institute - Leibniz Institute for Economic Research at the University of Munich, Germany" + }, + { + "author_name": "Clemens Fuest", + "author_inst": "ifo Institute - Leibniz Institute for Economic Research at the University of Munich, Germany" + }, + { + "author_name": "Michael Meyer-Hermann", + "author_inst": "Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Germany" } ], "version": "1", - "license": "cc0_ng", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1214119,35 +1214871,91 @@ "category": "sports medicine" }, { - "rel_doi": "10.1101/2020.08.13.20171256", - "rel_title": "Has COVID-19 Hurt Resident Education? A network-wide resident survey on education and experience during the pandemic", + "rel_doi": "10.1101/2020.08.14.250258", + "rel_title": "Inhibition of Severe Acute Respiratory Syndrome Coronavirus 2 main protease by tafenoquine in vitro", "rel_date": "2020-08-15", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.13.20171256", - "rel_abs": "PurposeAs the COVID-19 pandemic continues to evolve, the healthcare system has been forced to adapt in myriad ways. Residents have faced significant changes in work schedules, deployment to COVID-19 units, and alterations to didactics. This study aims to identify the effects of the COVID-19 pandemic on resident perception of their own education within the Nuvance Health Network.\n\nMethodsWe conducted an observational study assessing resident perception of changes in education and lifestyle during the COVID-19 pandemic. A survey was developed to assess the quality and quantity of resident education during this time and administered anonymously to all residents within the healthcare network.\n\nResultsEighty-four (68%) residents responded to the survey from five different specialties, including general surgery, internal medicine, obstetrics and gynecology, pathology, and radiology. The average change in hours per week performing clinical work was -5.6 hours (SD=16.8), in time studying was +0.02 hours (SD=4.6), in weekly didactics was -1.7 hours (SD=3.1), and in attending involvement was -1.2 hours (SD=2.3). Additionally, 32% of residents expressed concern that the pandemic has diminished their preparedness to become an attending, 13% expressed concern about completing graduation requirements, and 3% felt they would need an additional year of training.\n\nConclusionsDuring the COVID-19 pandemic thus far, residents perceived that time spent on organized didactics/conferences decreased and that attending physicians are less involved in education. Furthermore, the majority of residents felt that the quality of didactic education diminished as a result of the pandemic. Surprisingly, while many residents expressed concerns about being prepared to become an attending, few were concerned about completing graduation requirements or needing an extra year of education. In light of these findings, it is critical to devote attention to the effects of the pandemic on residents professional trajectories and create innovative opportunities for improving education during this challenging time.", - "rel_num_authors": 4, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.14.250258", + "rel_abs": "The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing the current pandemic, coronavirus disease 2019 (COVID-19), has taken a huge toll on human lives and the global economy. Therefore, effective treatments against this disease are urgently needed. Here, we established a fluorescence resonance energy transfer (FRET)-based high-throughput screening platform to screen compound libraries to identify drugs targeting the SARS-CoV-2 main protease (Mpro), in particular those which are FDA-approved, to be used immediately to treat patients with COVID-19. Mpro has been shown to be one of the most important drug targets among SARS-related coronaviruses as impairment of Mpro blocks processing of viral polyproteins which halts viral replication in host cells. Our findings indicate that the anti-malarial drug tafenoquine (TFQ) induces significant conformational change in SARS-CoV-2 Mpro and diminishes its protease activity. Specifically, TFQ reduces the -helical content of Mpro, which converts it into an inactive form. Moreover, TFQ greatly inhibits SARS-CoV-2 infection in cell culture system. Hence, the current study provides a mechanistic insight into the mode of action of TFQ against SARS-CoV-2 Mpro. Moreover, the low clinical toxicity of TFQ and its strong antiviral activity against SARS-CoV-2 should warrant further testing in clinical trials.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Alexander Ostapenko", - "author_inst": "Danbury Hospital" + "author_name": "Yeh Chen", + "author_inst": "Institute of New Drug Development, China Medical University" }, { - "author_name": "Samantha McPeck", - "author_inst": "University of Connecticut" + "author_name": "Wen-Hao Yang", + "author_inst": "Graduate Institute of Biomedical Sciences, China Medical University" }, { - "author_name": "Shawn Liechty", - "author_inst": "Danbury Hospital" + "author_name": "Li-Min Huang", + "author_inst": "Department of Pediatrics, College of Medicine, National Taiwan University" }, { - "author_name": "Daniel Kleiner", - "author_inst": "Danbury Hospital" + "author_name": "Yu-Chuan Wang", + "author_inst": "Institute of New Drug Development, China Medical University" + }, + { + "author_name": "Chia-Shin Yang", + "author_inst": "Institute of New Drug Development, China Medical University" + }, + { + "author_name": "Yi-Liang Liu", + "author_inst": "Department of Life Sciences, National Chung Hsing University" + }, + { + "author_name": "Mei-Hui Hou", + "author_inst": "Institute of New Drug Development, China Medical University" + }, + { + "author_name": "Chia-Ling Tsai", + "author_inst": "Institute of New Drug Development, China Medical University" + }, + { + "author_name": "Yi-Zhen Chou", + "author_inst": "Institute of New Drug Development, China Medical University" + }, + { + "author_name": "Bao-Yue Huang", + "author_inst": "Graduate Institute of Biomedical Sciences, China Medical University" + }, + { + "author_name": "Chian-Fang Hung", + "author_inst": "Graduate Institute of Biomedical Sciences, China Medical University" + }, + { + "author_name": "Yu-Lin Hung", + "author_inst": "Program of Digital Health Innovation, China Medical University" + }, + { + "author_name": "Jin-Shing Chen", + "author_inst": "Department of Surgery, College of Medicine, National Taiwan University Hospital and National Taiwan University" + }, + { + "author_name": "Yu-Ping Chiang", + "author_inst": "Department of Pediatrics, College of Medicine, National Taiwan University" + }, + { + "author_name": "Der-Yang Cho", + "author_inst": "Department of Neurosurgery, China Medical University Hospital" + }, + { + "author_name": "Long-Bin Jeng", + "author_inst": "School of Medicine, China Medical University" + }, + { + "author_name": "Chang-Hai Tsai", + "author_inst": "School of Medicine, China Medical University" + }, + { + "author_name": "Mien-Chie Hung", + "author_inst": "Drug Development Center, Research Center for Cancer Biology and Center for Molecular Medicine, China Medical University" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "medical education" + "license": "cc_no", + "type": "new results", + "category": "biochemistry" }, { "rel_doi": "10.1101/2020.08.14.248880", @@ -1215669,41 +1216477,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.11.20172833", - "rel_title": "Lockdown Measures and their Impact on Single- and Two-age-structured Epidemic Model for the COVID-19 Outbreak in Mexico", + "rel_doi": "10.1101/2020.08.11.20172676", + "rel_title": "Is Blood Type Associated with COVID-19 Severity?", "rel_date": "2020-08-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.11.20172833", - "rel_abs": "The role of lockdown measures in mitigating COVID-19 in Mexico is investigated using a comprehensive nonlinear ODE model. The model includes both asymptomatic and presymptomatic populations with the latter leading to sickness (with recovery, hospitalization and death possibilities). We consider situations involving the application of social-distancing and other intervention measures in the time series of interest. We find optimal parametric fits to the time series of deaths (only), as well as to the time series of deaths and cumulative infections. We discuss the merits and disadvantages of each approach, we interpret the parameters of the model and assess the realistic nature of the parameters resulting from the optimization procedure. Importantly, we explore a model involving two sub-populations (younger and older than a specific age), to more accurately reflect the observed impact as concerns symptoms and behavior in different age groups. For definiteness and to separate people that are (typically) in the active workforce, our partition of population is with respect to members younger vs. older than the age of 65. The basic reproduction number of the model is computed for both the single- and the two-population variant. Finally, we consider what would be the impact of partial lockdown (involving only the older population) and full lockdown (involving the entire population) on the number of deaths and cumulative infections.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.11.20172676", + "rel_abs": "Blood type purportedly influences susceptibility to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, but whether it affects severity of coronavirus disease 2019 (COVID-19) is unclear. Therefore, we examined the association of blood type and rhesus with hospitalization and disease severity among 428 COVID-19 patients diagnosed at the University of Cincinnati health system. In the sample, 50.2% of participants had the blood type O, 38.7% had the blood type A, 17.5% had the blood type B, and 3.5% had the blood type AB. In analysis adjusted for sociodemographic characteristics and comorbidities, the blood types A (OR: 0.90, 95% CI: 0.54, 1.50), B (OR: 0.93, 95% CI: 0.51, 1.69), AB (OR: 0.69, 95% CI: 0.20, 2.41), and O (OR: 1.18, 95%: 0.74, 1.98) were not associated with hospitalization for COVID-19. Similarly, the blood types A (OR: 0.93, 95% CI: 0.52, 1.65), B (OR: 0.92, 95% CI: 0.46, 1.84), AB (OR: 0.30, 95% CI: 0.04, 2.44), and O (OR: 1.25, 95%: 0.73, 2.14) were not associated with admission to intensive care unit or death in COVID-19. In conclusion, blood type is not associated with hospitalization or disease severity in COVID-19; therefore, it may not be useful marker for identifying patients at risk for severe COVID-19.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Jes\u00fas Cuevas-Maraver", - "author_inst": "Universidad de Sevilla" - }, - { - "author_name": "Panayotis Kevrekidis", - "author_inst": "University of Massachusetts" - }, - { - "author_name": "Qian-Yong Chen", - "author_inst": "University of Massachusetts" - }, - { - "author_name": "George Kevrekidis", - "author_inst": "University of Massachusetts" + "author_name": "Angelico Mendy", + "author_inst": "University of Cincinnati" }, { - "author_name": "V\u00edctor Villalobos-Daniel", - "author_inst": "National Center of Disease Prevention and Control Programs - CENAPRECE" + "author_name": "Jason L Keller", + "author_inst": "University of Cincinnati" }, { - "author_name": "Zoi Rapti", - "author_inst": "University of Illinois" + "author_name": "Senu Apewokin", + "author_inst": "University of Cincinnati" }, { - "author_name": "Yannis Drossinos", - "author_inst": "European Comission" + "author_name": "Ardythe L Morrow", + "author_inst": "University of Cincinnati" } ], "version": "1", @@ -1217387,83 +1218183,75 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2020.08.12.20171694", - "rel_title": "Universal screening for SARS-CoV-2 infection among pregnant women at Elmhurst Hospital Center, Queens, New York", + "rel_doi": "10.1101/2020.08.12.20173690", + "rel_title": "Antibody prevalence for SARS-CoV-2 in England following first peak of the pandemic: REACT2 study in 100,000 adults", "rel_date": "2020-08-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.12.20171694", - "rel_abs": "BackgroundUniversal screening for SARS-CoV-2 infection on Labor and Delivery (L&D) units is a critical strategy to manage patient and health worker safety, especially in a vulnerable high-prevalence community. We describe the results of a SARS-CoV-2 universal screening program at the L&D Unit at Elmhurst Hospital in Queens, NY, a 545-bed public hospital serving a diverse, largely immigrant and low-income patient population and an epicenter of the global pandemic.\n\nMethods and findingsWe conducted a retrospective cross-sectional study. All pregnant women admitted to the L&D Unit of Elmhurst Hospital from March 29, 2020 to April 22, 2020 were included for analysis. The primary outcomes of the study were: (1) SARS-CoV-2 positivity among universally screened pregnant women, stratified by demographic characteristics, maternal comorbidities, and delivery outcomes; and (2) Symptomatic or asymptomatic presentation at the time of testing among SARS-CoV-2 positive women.\n\nA total of 126 obstetric patients were screened for SARS-CoV-2 between March 29 and April 22. Of these, 37% were positive. Of the women who tested positive, 72% were asymptomatic at the time of testing. Patients who tested positive for SARS-CoV-2 were more likely to be of Hispanic ethnicity (unadjusted difference 24.4 percentage points, CI 7.9, 41.0) and report their primary language as Spanish (unadjusted difference 32.9 percentage points, CI 15.8, 49.9) than patients who tested negative.\n\nConclusionsIn this retrospective cross-sectional study of data from a universal SARS-Cov-2 screening program implemented in the L&D unit of a safety-net hospital in Queens, New York, we found over one-third of pregnant women testing positive, the majority of those asymptomatic. The rationale for universal screening at the L&D Unit at Elmhurst Hospital was to ensure safety of patients and staff during an acute surge in SARS-Cov-2 infections through appropriate identification and isolation of pregnant women with positive test results. Women were roomed by their SARS-CoV-2 status given increasing space limitations. In addition, postpartum counseling was tailored to infection status. We quickly established discharge counseling and follow-up protocols tailored to their specific social needs. The experience at Elmhurst Hospital is instructive for other L&D units serving vulnerable populations and for pandemic preparedness.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.12.20173690", + "rel_abs": "BackgroundEngland, UK has experienced a large outbreak of SARS-CoV-2 infection. As in USA and elsewhere, disadvantaged communities have been disproportionately affected.\n\nMethodsNational REal-time Assessment of Community Transmission-2 (REACT-2) prevalence study using a self-administered lateral flow immunoassay (LFIA) test for IgG among a random population sample of 100,000 adults over 18 years in England, 20 June to 13 July 2020.\n\nResultsData were available for 109,076 participants, yielding 5,544 IgG positive results; adjusted (for test performance) and re-weighted (for sampling) prevalence was 6.0% (95% Cl: 5.8, 6.1). Highest prevalence was in London (13.0% [12.3, 13.6]), among people of Black or Asian (mainly South Asian) ethnicity (17.3% [15.8, 19.1] and 11.9% [11.0, 12.8] respectively) and those aged 18-24 years (7.9% [7.3, 8.5]). Adjusted odds ratio for care home workers with client-facing roles was 3.1 (2.5, 3.8) compared with non-essential workers. One third (32.2%, [31.0-33.4]) of antibody positive individuals reported no symptoms. Among symptomatic cases, most (78.8%) reported symptoms during the peak of the epidemic in England in March (31.3%) and April (47.5%) 2020. We estimate that 3.36 million (3.21, 3.51) people have been infected with SARS-CoV-2 in England to end June 2020, with an overall infection fatality ratio (IFR) of 0.90% (0.86, 0.94); age-specific IFR was similar among people of different ethnicities.\n\nConclusionThe SARS-CoV-2 pandemic in England disproportionately affected ethnic minority groups and health and care home workers. The higher risk of infection in minority ethnic groups may explain their increased risk of hospitalisation and mortality from COVID-19.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Sheela Maru", - "author_inst": "Icahn School of Medicine at Mount Sinai and New York City Health + Hospitals/Elmhurst" - }, - { - "author_name": "Uday Patil", - "author_inst": "Icahn School of Medicine at Mount Sinai and New York City Health + Hospitals/Elmhurst" - }, - { - "author_name": "Rachel Carroll-Bennett", - "author_inst": "Icahn School of Medicine at Mount Sinai and New York City Health + Hospitals/Elmhurst" + "author_name": "Helen Ward", + "author_inst": "Imperial College London" }, { - "author_name": "Aaron Baum", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Christina J Atchison", + "author_inst": "Imperial College London" }, { - "author_name": "Tracy Bohn-Hemmerdinger", - "author_inst": "Icahn School of Medicine at Mount Sinai and New York City Health + Hospitals/Elmhurst" + "author_name": "Matthew Whitaker", + "author_inst": "Imperial College London" }, { - "author_name": "Andrew Ditchik", - "author_inst": "Icahn School of Medicine at Mount Sinai and New York City Health + Hospitals/Elmhurst" + "author_name": "Kylie E. C. Ainslie", + "author_inst": "Imperial College London" }, { - "author_name": "Michael Scanlon", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Joshua Elliott", + "author_inst": "Imperial College London" }, { - "author_name": "Parvathy Krishnan", - "author_inst": "Icahn School of Medicine at Mount Sinai and New York City Health + Hospitals/Elmhurst" + "author_name": "Lucy C Okell", + "author_inst": "Imperial College London" }, { - "author_name": "Kelly Bogaert", - "author_inst": "Icahn School of Medicine at Mount Sinai and New York City Health + Hospitals/Elmhurst" + "author_name": "Rozlyn Redd", + "author_inst": "Imperial College London" }, { - "author_name": "Carson Woodbury", - "author_inst": "Icahn School of Medicine at Mount Sinai and New York City Health + Hospitals/Elmhurst" + "author_name": "Deborah Ashby", + "author_inst": "Imperial College London" }, { - "author_name": "Duncan Maru", - "author_inst": "Icahn School of Medicine at Mount Sinai and New York City Health + Hospitals/Elmhurst" + "author_name": "Christl A. Donnelly", + "author_inst": "Imperial College London" }, { - "author_name": "Lawrence Noble", - "author_inst": "Icahn School of Medicine at Mount Sinai and New York City Health + Hospitals/Elmhurst" + "author_name": "Wendy Barclay", + "author_inst": "Imperial College London" }, { - "author_name": "Randi Wasserman", - "author_inst": "Icahn School of Medicine at Mount Sinai and New York City Health + Hospitals/Elmhurst" + "author_name": "Ara Darzi", + "author_inst": "Imperial College London" }, { - "author_name": "Barry Brown", - "author_inst": "Icahn School of Medicine at Mount Sinai and New York City Health + Hospitals/Elmhurst" + "author_name": "Graham Cooke", + "author_inst": "Imperial College London" }, { - "author_name": "Rachel Vreeman", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Steven Riley", + "author_inst": "Dept Inf Dis Epi, Imperial College" }, { - "author_name": "Joseph Masci", - "author_inst": "Icahn School of Medicine at Mount Sinai and New York City Health + Hospitals/Elmhurst" + "author_name": "Paul Elliott", + "author_inst": "Imperial College London" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health systems and quality improvement" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.08.13.20174060", @@ -1218789,25 +1219577,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.13.20174011", - "rel_title": "In the face of the pandemic, are all equal? On the suitability of the Gini index to monitor time and geographic trends in incidence and death during the SARS-CoV-2 pandemic", + "rel_doi": "10.1101/2020.08.11.20170613", + "rel_title": "Automated molecular testing of saliva for SARS-CoV-2 detection", "rel_date": "2020-08-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.13.20174011", - "rel_abs": "BackgroundIt is of interest to explore the variability in how the COVID-19 pandemic evolved geographically during the first twelve months. To this end, we apply inequality indices over regions to incidences, infection related mortality, and infection fatality rates. If avoiding of inequality in health is an important political goal, a metric must be implemented to track geographical inequality over time.\n\nMethodsThe relative and absolute Gini index as well as the Theil index are used to quantify inequality. Data are taken from international data bases. Absolute counts are transformed to rates adjusted for population size.\n\nResultsComparing continents, the absolute Gini index shows an unfavorable development in four continents since February 2020. In contrast, the relative Gini as well as the Theil index support the interpretation of less inequality between European countries compared to other continents. Infection fatality rates within the EU as well as within the U.S. express comparable improvement towards more equality (as measured by both Gini indices).\n\nConclusionsThe use of inequality indices to monitor changes in geographic in-equality over time for key health indicators is a valuable tool to inform public health policies. The absolute and relative Gini index behave complementary and should be reported simultaneously in order to gain a meta-perspective on very complex dynamics.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.11.20170613", + "rel_abs": "With surging global demand for increased SARS-CoV-2 testing capacity, clinical laboratories seek automated, high-throughput molecular solutions, particularly for specimen types which do not rely upon supply of specialized collection devices or viral transport media (VTM). Saliva was evaluated as a diagnostic specimen for SARS-CoV-2 using the cobas(R) SARS-CoV-2 Test on the cobas(R) 6800 instrument. Saliva specimens submitted from various patient populations under investigation for COVID-19 from March-July 2020 were processed in the laboratory with sterile phosphate-buffered saline in a 1:2 dilution and vortexed with glass beads. The processed saliva samples were tested using a commercial assay for detection of the SARS-CoV-2 E gene (LightMix(R)) in comparison to the cobas(R) SARS-CoV-2 Test. 22/64 (34.4%) of the saliva samples were positive for SARS-CoV-2. Positive and negative concordance between the LightMix(R) and cobas(R) assays were 100%. There was no cross-contamination of samples observed on the cobas(R) 6800. The overall invalid rate for saliva on the cobas(R) 6800 (1/128, 0.78%) was similar to the baseline invalid rate observed for nasopharyngeal swabs/VTM and plasma samples. Saliva is a feasible specimen type for SARS-CoV-2 testing on the cobas(R) 6800, with potential to improve turnaround time and enhance testing capacity.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Kirsi Manz", - "author_inst": "Ludwig Maximilians University Munich" + "author_name": "Nancy Matic", + "author_inst": "Providence Health Care" }, { - "author_name": "Ulrich Mansmann", - "author_inst": "Ludwig Maximilians University Munich" + "author_name": "Tanya Lawson", + "author_inst": "Providence Health Care" + }, + { + "author_name": "Gordon Ritchie", + "author_inst": "Providence Health Care" + }, + { + "author_name": "Aleksandra Stefanovic", + "author_inst": "Providence Health Care" + }, + { + "author_name": "Victor Leung", + "author_inst": "Providence Health Care" + }, + { + "author_name": "Sylvie Champagne", + "author_inst": "Providence Health Care" + }, + { + "author_name": "Marc G. Romney", + "author_inst": "Providence Health Care" + }, + { + "author_name": "Christopher F. Lowe", + "author_inst": "Providence Health Care" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1220503,41 +1221315,81 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.09.20170803", - "rel_title": "COVID-19 Infection Among Healthcare Workers in a National Healthcare System: the Qatar Experience", + "rel_doi": "10.1101/2020.08.08.20170746", + "rel_title": "ApharSeq: An Extraction-free Early-Pooling Protocol for Massively Multiplexed SARS-CoV-2 Detection", "rel_date": "2020-08-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.09.20170803", - "rel_abs": "The study was conducted at Hamad Medical Corporation in Qatar, a national healthcare system with 14 hospitals and over 28,000 employees. A total of 16,912 staff members were tested for SARS-CoV-2 between March 10 and June 24, 2020 with 1,799 (10.6%) testing positive. Nurses and midwives had the highest number of infections (33.2% of all infected HCWs) followed by non-clinical support service staff (31.3%), administrative staff (14.6%), allied health professionals (12.7%), physicians (5.2% and other clinical support staff (2.9%). Among 671 infected HCW surveyed by the infection prevention and control team immediately after the positive COVID-19 test was reported, exposure to a family member or roommate with confirmed infection each were reported by 9.5%. Two-thirds of the infected HCWs were symptomatic with fever (34.6%), cough (32.2%) and sore throat (15.8%) being the most commonly reported symptoms. Among the survey respondents, 78 (11.6%) were hospitalized, 9 (1.3%) required supplemental oxygen, 4 (0.6%) were admitted to the intensive care unit) and 2 (0.3%) required mechanical ventilation. There were no deaths. To understand the transmission dynamics and impact of facility designation as COVID-19 or non-COVID-19 facility, we conducted a focused follow-up telephone survey on 393 COVID-19 positive HCW 1-6 weeks after diagnosis. Only 5% of respondents reported acquiring the virus from working at a COVID-19 designated facility while the remaining 95% reported working at a non-COVID-19 facility and acquired the infection from accidental exposure to a colleague (45%) or to a patient (29%). Among infected HCW at COVID-19 designated facilities, 82% reported used full PPE at all times while 68% of infected HCW at non-COVID-19 facilities reported using PPE as directed.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.08.20170746", + "rel_abs": "The global SARS-CoV-2 pandemic created a dire need for viral detection tests worldwide. Most current tests for SARS-CoV-2 are based on RNA extraction followed by quantitative reverse-transcription PCR assays. While automation and improved logistics increased the capacity of these tests, they cannot exceed the lower bound dictated by one extraction and one RT-PCR reaction per sample. Multiplexed next generation sequencing (NGS) assays provide a dramatic increase in throughput, and hold the promise of richer information including viral strains, host immune response, and multiple pathogens.\n\nHere, we establish a significant improvement of existing RNA-seq detection protocols. Our workflow, ApharSeq, includes a fast and cheap RNA capture step, that is coupled to barcoding of individual samples, followed by sample-pooling prior to the reverse transcription, PCR and massively parallel sequencing. Thus, only one non-enzymatic step is performed before pooling hundreds of barcoded samples for subsequent steps and further analysis. We characterize the quantitative aspects of the assay by applying ApharSeq to more than 500 clinical samples in a robotic workflow. The assay results are linear, and the empirical limit of detection is found to be Ct 33 (roughly 1000 copies/ml). A single ApharSeq test currently costs under 1.2$, and we estimate costs can further go down 3-10 fold. Similarly, we estimate a labor reduction of 10-100 fold, automated liquid handling of 5-10 fold, and reagent requirement reduction of 20-1000 fold compared to existing testing methods.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Jameela Alajmi", - "author_inst": "Hamad Medical Corporation" + "author_name": "Alon Chappleboim", + "author_inst": "Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel; Rachel and Selim Benin School of Computer Science, Hebrew Univer" }, { - "author_name": "Andrew M. Jeremijenko", - "author_inst": "Hamad Medical Corporation" + "author_name": "Daphna Joseph-Strauss", + "author_inst": "Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel; Rachel and Selim Benin School of Computer Science, Hebrew Univer" }, { - "author_name": "Joji C. Abraham", - "author_inst": "Hamad Medical Corporation" + "author_name": "Ayelet Rahat", + "author_inst": "Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel; Rachel and Selim Benin School of Computer Science, Hebrew Univer" }, { - "author_name": "Moza Ishaq", - "author_inst": "Hamad Medical Corporation" + "author_name": "Israa Sharkia", + "author_inst": "Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel; Rachel and Selim Benin School of Computer Science, Hebrew Univer" }, { - "author_name": "Elli G. Concepcion", - "author_inst": "Hamad Medical Corporation" + "author_name": "Miriam Adam", + "author_inst": "Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel; Edmond and Lily Safra Center for Brain Sciences, H" }, { - "author_name": "Adeel A Butt", - "author_inst": "Hamad Medical Corporation" + "author_name": "Daniel Kitsberg", + "author_inst": "Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel; Edmond and Lily Safra Center for Brain Sciences, H" }, { - "author_name": "Abdul-Badi Abou-Samra", - "author_inst": "Hamad Medical Corporation" + "author_name": "Gavriel Fialkoff", + "author_inst": "Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel; Rachel and Selim Benin School of Computer Science, Hebrew Univer" + }, + { + "author_name": "Matan Lotem", + "author_inst": "Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel; Rachel and Selim Benin School of Computer Science, Hebrew Univer" + }, + { + "author_name": "Omer Gershon", + "author_inst": "Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel; Rachel and Selim Benin School of Computer Science, Hebrew Univer" + }, + { + "author_name": "Anna-Kristina Schmidtner", + "author_inst": "Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel; Edmond and Lily Safra Center for Brain Sciences, H" + }, + { + "author_name": "Esther Oiknine-Djian", + "author_inst": "Hadassah - Hebrew University Medical Centre, Jerusalem 9112001, Israel; The Lautenberg Centre for Immunology and Cancer Research, IMRIC, Faculty of Medicine, Th" + }, + { + "author_name": "Agnes Klochendler", + "author_inst": "Department of Developmental Biology and Cancer Research, IMRIC, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 9112001, Israel" + }, + { + "author_name": "Ronen Sadeh", + "author_inst": "Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel; Rachel and Selim Benin School of Computer Science, Hebrew Univer" + }, + { + "author_name": "Yuval Dor", + "author_inst": "Department of Developmental Biology and Cancer Research, IMRIC, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 9112001, Israel" + }, + { + "author_name": "Dana Wolf", + "author_inst": "Hadassah - Hebrew University Medical Centre, Jerusalem 9112001, Israel; The Lautenberg Centre for Immunology and Cancer Research, IMRIC, Faculty of Medicine, Th" + }, + { + "author_name": "Naomi Habib", + "author_inst": "Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel; Edmond and Lily Safra Center for Brain Sciences, H" + }, + { + "author_name": "Nir Friedman", + "author_inst": "Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel; Rachel and Selim Benin School of Computer Science, Hebrew Univer" } ], "version": "1", @@ -1222081,73 +1222933,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.10.20171884", - "rel_title": "On the track of the D839Y mutation in the SARS-CoV-2 Spike fusion peptide: emergence and geotemporal spread of a highly prevalent variant in Portugal", + "rel_doi": "10.1101/2020.08.10.20171512", + "rel_title": "Improved COVID-19 testing by extraction free SARS-Cov-2 RT-PCR", "rel_date": "2020-08-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.10.20171884", - "rel_abs": "Mutations in the Spike motif predicted to correspond to the fusion peptide are considered of interest as this domain is a potential target for anti-viral drug development that plays a pivotal role in inserting SARS-CoV-2 into human cell membranes. We tracked the temporal and geographical spread of a SARS-CoV-2 variant with the Spike D839Y mutation in the fusion peptide, which was detected early during the COVID-19 epidemic in Portugal. We show that this variant was most likely imported from Italy in mid-late February 2020, becoming prevalent in the Northern and Central regions of Portugal, where represented 22% and 59% of the sampled genomes, respectively, until the end of April 2020. Based on our high sequencing sampling during the early epidemics [15,5% (1275/8251) and 6,0% (1500/24987) of all confirmed cases until the end of March and April, respectively)], we estimate that, between March 14th and April 9th (covering the exponential phase of the epidemic), the relative frequency of Spike Y839 variant increased at a rate of 12.1% (6.1%-18.2%, CI 95%) at every three days, being potentially associated with one in each four (20.8-29.7%, CI 95%) COVID-19 cases in Portugal during the same period. This observation places the Spike Y839 variant in the origin of the largest SARS-CoV-2 transmission chain during the first month of the COVID-19 epidemic in Portugal. We hypothesize that population/epidemiological effects (founder effects) and enhanced selective advantage might have concomitantly contributed to the increasing frequency trajectory of the Spike Y839 variant. Screening of the D839Y mutation globally confirmed its detection in 12 additional countries, even though the huge differences in genome sampling between countries hampers any accurate estimate of D839Y global frequency. In summary, our data points out that SARS-CoV-2 Spike Y839 variants, namely the descendent variant of the globally spread G614 variant detected in Portugal, need continuous and close surveillance.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.10.20171512", + "rel_abs": "The RNA extraction is an important checkpoint for the detection of SARS-CoV-2 in swab samples, but it is a major barrier to available and rapid COVID-19 testing. In this study, we validated the extraction-free RT-qPCR method by heat-treatment as an accurate option to nucleic acid purification in Algerian population.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "V\u00edtor Borges", - "author_inst": "Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal" - }, - { - "author_name": "Joana Isidro", - "author_inst": "Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal" - }, - { - "author_name": "Helena Cortes-Martins", - "author_inst": "Reference and Surveillance Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal" - }, - { - "author_name": "S\u00edlvia Duarte", - "author_inst": "Innovation and Technology Unit, Department of Human Genetics, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal" - }, - { - "author_name": "Lu\u00eds Vieira", - "author_inst": "Innovation and Technology Unit, Department of Human Genetics, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal" - }, - { - "author_name": "Ricardo Leite", - "author_inst": "Instituto Gulbenkian de Ci\u00eancia (IGC), Oeiras, Portugal" - }, - { - "author_name": "Isabel Gordo", - "author_inst": "Instituto Gulbenkian de Ci\u00eancia (IGC), Oeiras, Portugal." - }, - { - "author_name": "Constantino P. Caetano", - "author_inst": "Department of Epidemiology, National Institute of Health Doutor Ricardo Jorge, Lisbon, Portugal" - }, - { - "author_name": "Baltazar Nunes", - "author_inst": "Department of Epidemiology, National Institute of Health Doutor Ricardo Jorge, Lisbon, Portugal" - }, - { - "author_name": "Regina S\u00e1", - "author_inst": "Public Health Unit, Primary Care Cluster of Baixo Vouga, Central Regional Health Administration, Portugal" - }, - { - "author_name": "Ana Oliveira", - "author_inst": "Public Health Unit, Primary Care Cluster of Baixo Vouga, Central Regional Health Administration, Portugal" - }, - { - "author_name": "Raquel Guiomar", - "author_inst": "National Reference Laboratory for Influenza and other Respiratory Viruses, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge " - }, - { - "author_name": "Jo\u00e3o Paulo Gomes", - "author_inst": "Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal" - }, - { - "author_name": "- Portuguese network for SARS-CoV-2 genomics", - "author_inst": "" + "author_name": "khelil mohamed mokhtar", + "author_inst": "institut pasteur Algeria" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1223903,73 +1224703,89 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.08.20170787", - "rel_title": "Comparative Clinical Outcomes and Mortality in Prisoner and Non-Prisoner Populations Hospitalized with COVID-19: A Cohort from Michigan", + "rel_doi": "10.1101/2020.08.07.20170498", + "rel_title": "Management Strategies for People Experiencing Sheltered Homelessness during the COVID-19 Pandemic: Clinical Outcomes and Costs", "rel_date": "2020-08-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.08.20170787", - "rel_abs": "BackgroundPrisons in the United States have become a hotbed for spreading Covid-19 among incarcerated individuals. Covid-19 cases among prisoners are on the rise, with more than 46,000 confirmed cases to date. However, there is paucity of data addressing clinical outcomes and mortality in prisoners hospitalized with Covid-19.\n\nMethodsAn observational study of all patients hospitalized with Covid-19 between March 10 and May 10, 2020 at two Henry Ford Health System hospitals in Michigan. Clinical outcomes were compared amongst hospitalized prisoners and non-prisoner patients. The primary outcomes were intubation rates, in-hospital mortality, and 30-day mortality. Multivariable logistic regression and Cox-regression models were used to investigate primary outcomes.\n\nResultsOf the 706 hospitalized Covid-19 patients (mean age 66.7 {+/-} 16.1 years, 57% males, and 44% black), 108 were prisoners and 598 were non-prisoners. Compared to non-prisoners, prisoners were more likely to present with fever, tachypnea, hypoxemia, and markedly elevated inflammatory markers. Prisoners were more commonly admitted to the intensive care unit (ICU) (26.9% vs. 18.7%), required vasopressors (24.1% vs. 9.9%), and intubated (25.0% vs. 15.2%). Prisoners had higher unadjusted inpatient mortality (29.6% vs. 20.1%) and 30-day mortality (34.3% vs. 24.6%). In the adjusted models, prisoner status was associated with higher in-hospital death (odds ratio, 1.95; 95% confidence interval (CI), 1.07 to 3.57) and 30-day mortality (hazard ratio, 1.92; 95% CI, 1.24 to 2.98).\n\nConclusionsIn this cohort of hospitalized Covid-19 patients, prisoner status was associated with more severe clinical presentation, higher rates of ICU admissions, vasopressors requirement, intubation, inhospital mortality, and 30-day mortality.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.07.20170498", + "rel_abs": "ImportanceApproximately 356,000 people stay in homeless shelters nightly in the US. These individuals are at high risk for COVID-19.\n\nObjectiveTo assess clinical outcomes, costs, and cost-effectiveness of strategies for COVID-19 prevention and management among sheltered homeless adults.\n\nDesignWe developed a dynamic microsimulation model of COVID-19. We modeled sheltered homeless adults in Boston, Massachusetts, using cohort characteristics and costs from Boston Health Care for the Homeless Program. Disease progression, transmission, and clinical outcomes data were from published literature and national databases. We examined surging, growing, and slowing epidemics (effective reproduction numbers [Re] 2.6, 1.3, and 0.9). Costs were from a health care sector perspective; time horizon was 4 months.\n\nSetting & ParticipantsSimulated cohort of 2,258 adults residing in homeless shelters in Boston.\n\nInterventionsWe assessed combinations of daily symptom screening with same-day polymerase chain reaction (PCR) testing of screen-positive individuals, universal PCR testing every 2 weeks, hospital-based COVID-19 care, alternate care sites [ACSs] for mild/moderate COVID-19 management, and moving people from shelters to temporary housing, compared to no intervention.\n\nMain OutcomesInfections, hospital-days, costs, and cost-effectiveness.\n\nResultsCompared to no intervention, daily symptom screening with ACSs for those with pending tests or confirmed COVID-19 and mild/moderate disease leads to 37% fewer infections and 46% lower costs when Re=2.6, 75% fewer infections and 72% lower costs when Re=1.3, and 51% fewer infections and 51% lower costs when Re=0.9. Adding universal PCR testing every 2 weeks further decreases infections in all epidemic scenarios, with incremental cost per case prevented of $1,000 (Re=2.6), $27,000 (Re=1.3), and $71,000 (Re=0.9). In all scenarios, moving shelter residents to temporary housing with universal PCR testing every 2 weeks is most effective but substantially more costly than other options. Results are most sensitive to the cost and sensitivity of PCR testing and the efficacy of ACSs in preventing transmission.\n\nConclusions & RelevanceDaily symptom screening and ACSs for sheltered homeless adults will substantially decrease COVID-19 cases and reduce costs compared to no intervention. In a surging epidemic, adding universal PCR testing every 2 weeks further decreases cases at modest incremental cost and should be considered.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat are the projected clinical outcomes and costs of strategies for reducing COVID-19 infections among people experiencing sheltered homelessness?\n\nFindingsIn this microsimulation modeling study, daily symptom screening with polymerase chain reaction (PCR) testing of screen-positive individuals, paired with non-hospital care site management of people with mild to moderate COVID-19, substantially reduces infections and lowers costs over 4 months compared to no intervention, across a wide range of epidemic scenarios. In a surging epidemic, adding periodic universal PCR testing to symptom screening and non-hospital care site management improves clinical outcomes at modestly increased costs. Periodic universal PCR testing paired with temporary housing further reduces infections but at much higher cost.\n\nMeaningDaily symptom screening with PCR testing of screen-positive individuals and use of alternate care sites for COVID-19 management among sheltered homeless people will substantially prevent new cases and reduce costs compared to other strategies.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Ahmed M Altibi", - "author_inst": "Henry Ford Allegiance Health" + "author_name": "Travis P. Baggett", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "Justine A. Scott", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Pallavi Bhargava", - "author_inst": "Department of Internal Medicine, Division of Infectious Diseases, Henry Ford Hospital" + "author_name": "Mylinh H. Le", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Hassan Liaqat", - "author_inst": "Department of Internal Medicine, Henry Ford Allegiance Hospital, Henry Ford Health System" + "author_name": "Fatma M. Shebl", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Alexander A. Slota", - "author_inst": "Department of Internal Medicine, Henry Ford Allegiance Health" + "author_name": "Christopher Panella", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Radhika Sheth", - "author_inst": "Henry Ford Allegiance Hospital, Henry Ford Health System" + "author_name": "Elena Losina", + "author_inst": "Brigham and Women's Hospital" }, { - "author_name": "Lama Al Jebbawi", - "author_inst": "Henry Ford Allegiance Hospital, Henry Ford Health System" + "author_name": "Clare Flanagan", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Matthew E. George", - "author_inst": "Division of Hospital Medicine, Henry Ford West Bloomfield" + "author_name": "Jessie Gaeta", + "author_inst": "Boston Healthcare for the Homeless Program" }, { - "author_name": "Allison LeDuc", - "author_inst": "Henry Ford Allegiance Hospital, Henry Ford Health System" + "author_name": "Anne M. Neilan", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Enas Abdallah", - "author_inst": "Henry Ford Allegiance Hospital, Henry Ford Health System" + "author_name": "Emily P. Hyle", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Luke R. Russell", - "author_inst": "Henry Ford Allegiance Hospital, Henry Ford Health System" + "author_name": "Amir M. Mohareb", + "author_inst": "Harvard Medical School" }, { - "author_name": "Saniya Jain", - "author_inst": "Michigan State University College of Osteopathic Medicine" + "author_name": "Krishna P. Reddy", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "Mark P. Siedner", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Guy Harling", + "author_inst": "Harvard T.H. Chan School of Public Health" + }, + { + "author_name": "Milton C. Weinstein", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Narine Shirvanian", - "author_inst": "Henry Ford Allegiance Hospital, Henry Ford Health System" + "author_name": "Andrea Ciaranello", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Ahmad Masri", - "author_inst": "Knight Cardiovascular Institute, Oregon Health & Science University" + "author_name": "Pooyan Kazemian", + "author_inst": "Case Western Reserve University" }, { - "author_name": "Vivek Kak", - "author_inst": "Henry Ford Allegiance Hospital, Henry Ford Health System" + "author_name": "Kenneth A. Freedberg", + "author_inst": "Massachusetts General Hospital" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1225657,49 +1226473,93 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.10.20171652", - "rel_title": "Rapid Detection of SARS-CoV-2 Antibodies Using Electrochemical Impedance-Based Detector", + "rel_doi": "10.1101/2020.08.11.20172452", + "rel_title": "A diagnostic decision-making protocol combines a new-generation of serological assay and PCR to fully resolve ambiguity in COVID-19 diagnosis", "rel_date": "2020-08-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.10.20171652", - "rel_abs": "Emerging novel human contagious viruses and pathogens put humans at risk of hospitalization and possibly death due to the unavailability of vaccines and drugs which may take years to develop. Coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was classified as a pandemic by theWorld Health Organization and has caused over 550,000 deaths worldwide as of July 2020. Accurate and scalable point-of-care devices would increase screening, diagnosis, and monitoringof COVID-19 patients. Here, we demonstrate rapid label-free electrochemical detection of SARS-CoV-2 antibodies using a commercially available impedance sensing platform. A 16-well plate containing sensing electrodes was pre-coated with receptor binding domain (RBD) of SARS-CoV-2 spike protein, and subsequently tested with samples of anti-SARS-CoV-2 monoclonal antibody CR3022 (0.1 g/ml, 1.0 g/ml, 10 g/ml). Subsequent blinded testing was performed on six serum specimens taken from COVID-19 and non-COVID-19 patients (1:100 dilution factor). The platformwas able to differentiate spikes in impedance measurements from a negative control (1~ milk solution) for all CR3022 samples. Further, successful differentiation and detection of all positive clinical samples from negative control was achieved. Measured impedance values were consistent when compared to standard ELISA test results showing a strong correlation between them (R2 = 0:9). Detection occurs in less than five minutes and the well-based platform provides a simplified and familiar testing interface that can be readily adaptable for use in clinical settings.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.11.20172452", + "rel_abs": "The capacity to accurately diagnosis COVID-19 is essential for effective public health measures to manage the ongoing global pandemic, yet no presently available diagnostic technologies or clinical protocols can achieve full positive predictive value (PPV) and negative predictive value (NPV) performance. Two factors prevent accurate diagnosis: the failure of sampling methods (e.g., 40% false negatives from PCR testing of nasopharyngeal swabs) and sampling-time-dependent failures reflecting individual humoral responses of patients (e.g., serological testing outside of the sero-positive stage). Here, we report development of a diagnostic protocol that achieves full PPV and NPV based on a cohort of 500 confirmed COVID-19 cases, and present several discoveries about the sero-conversion dynamics throughout the disease course of COVID-19. The fundamental enabling technology for our study and diagnostic protocol--termed SANE, for Symptom (dpo)-Antibody-Nucleic acid-Epidemiological history--is our development of a peptide-protein hybrid microarray (PPHM) for COVID-19. The peptides comprising PPHMO_SCPLOWCOVIDC_SCPLOWO_SCPCAP-19C_SCPCAP were selected based on clinical sample data, and give our technology the unique capacity to monitor a patients humoral response throughout the disease course. Among other assay-development related and clinically relevant findings, our use of PPHMO_SCPLOWCOVIDC_SCPLOWO_SCPCAP-19C_SCPCAP revealed that 5% of COVID-19 patients are from an \"early sero-reversion\" subpopulation, thus explaining many of the mis-diagnoses we found in our comparative testing using PCR, CLIA, and PPHMO_SCPLOWCOVIDC_SCPLOWO_SCPCAP-19C_SCPCAP. Accordingly, the full SANE protocol incorporates orthogonal technologies to account for these patient variations, and successfully overcomes both the sampling method and sampling time limitations that have previously prevented doctors from achieving unambiguous, accurate diagnosis of COVID-19.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Mohamed Z. Rashed", - "author_inst": "University of Louisville" + "author_name": "Hu Cheng", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China. Nano Science and Technology I" }, { - "author_name": "Jonathan A. Kopecheck", - "author_inst": "University of Louisville" + "author_name": "Hao Chen", + "author_inst": "Department of Allergy and Clinical Immunology, Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, The First Affiliated Hosp" }, { - "author_name": "Mariah C. Priddy", - "author_inst": "University of Louisville" + "author_name": "Yiting Li", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." }, { - "author_name": "Krystal T. Hamorsky", - "author_inst": "University of Louisville" + "author_name": "Peiyan Zheng", + "author_inst": "Department of Allergy and Clinical Immunology, Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, The First Affiliated Hosp" }, { - "author_name": "Kenneth E. Palmer", - "author_inst": "University of Louisville" + "author_name": "Dayong Gu", + "author_inst": "Department of Clinical Laboratory, The First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen, 518035, China." }, { - "author_name": "Nikhil Mittal", - "author_inst": "ACEA Biosciences" + "author_name": "Shiping He", + "author_inst": "Department of Clinical Laboratory, The First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen, 518035, China." }, { - "author_name": "Joseph Valdez", - "author_inst": "ACEA Biosciences" + "author_name": "Dongli Ma", + "author_inst": "Shenzhen Children's Hospital, Shenzhen Engineering Laboratory for High-throughput Gene Sequencing of Pathogens, Shenzhen, 518038, China." }, { - "author_name": "Joseph Flynn", - "author_inst": "Norton Healthcare" + "author_name": "Ruifang Wang", + "author_inst": "State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National " }, { - "author_name": "Stuart Williams", - "author_inst": "University of Louisville" + "author_name": "Jun Han", + "author_inst": "State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National " + }, + { + "author_name": "Zhongxin Lu", + "author_inst": "Department of Medical Laboratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430014, China." + }, + { + "author_name": "Xinyi Xia", + "author_inst": "COVID-19 Research Center, Institute of Laboratory Medicine, Jinling Hospital, Nanjing University School of Medicine, Nanjing Clinical College of Southern Medica" + }, + { + "author_name": "Yi Deng", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." + }, + { + "author_name": "Lan Yang", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." + }, + { + "author_name": "Wenwen Xu", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." + }, + { + "author_name": "Shanhui Wu", + "author_inst": "Department of Allergy and Clinical Immunology, Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, The First Affiliated Hosp" + }, + { + "author_name": "Cuiying Liang", + "author_inst": "Department of Allergy and Clinical Immunology, Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, The First Affiliated Hosp" + }, + { + "author_name": "Hui Wang", + "author_inst": "Department of Medical Laboratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430014, China." + }, + { + "author_name": "Baoqing Sun", + "author_inst": "Department of Allergy and Clinical Immunology, Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, The First Affiliated Hosp" + }, + { + "author_name": "Nanshan Zhong", + "author_inst": "Department of Allergy and Clinical Immunology, Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, The First Affiliated Hosp" + }, + { + "author_name": "Hongwei Ma", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." } ], "version": "1", @@ -1227691,55 +1228551,139 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.08.07.242156", - "rel_title": "Sofosbuvir Terminated RNA is More Resistant to SARS-CoV-2 Proofreader than RNA Terminated by Remdesivir", + "rel_doi": "10.1101/2020.07.31.20161216", + "rel_title": "Immunogenicity and Safety of a SARS-CoV-2 Inactivated Vaccine in Healthy Adults Aged 18-59 years: Report of the Randomized, Double-blind, and Placebo-controlled Phase 2 Clinical Trial", "rel_date": "2020-08-10", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.07.242156", - "rel_abs": "SARS-CoV-2 is responsible for COVID-19, resulting in the largest pandemic in over a hundred years. After examining the molecular structures and activities of hepatitis C viral inhibitors and comparing hepatitis C virus and coronavirus replication, we previously postulated that the FDA-approved hepatitis C drug EPCLUSA (Sofosbuvir/Velpatasvir) might inhibit SARS-CoV-2.1 We subsequently demonstrated that Sofosbuvir triphosphate is incorporated by the relatively low fidelity SARS-CoV and SARS-CoV-2 RNA-dependent RNA polymerases (RdRps), serving as an immediate polymerase reaction terminator, but not by a host-like high fidelity DNA polymerase.2,3 Other investigators have since demonstrated the ability of Sofosbuvir to inhibit SARS-CoV-2 replication in lung and brain cells;4,5 additionally, COVID-19 clinical trials with EPCLUSA6 and with Sofosbuvir plus Daclatasvir7 have been initiated in several countries. SARS-CoV-2 has an exonuclease-based proofreader to maintain the viral genome integrity.8 Any effective antiviral targeting the SARS-CoV-2 RdRp must display a certain level of resistance to this proofreading activity. We report here that Sofosbuvir terminated RNA resists removal by the exonuclease to a substantially higher extent than RNA terminated by Remdesivir, another drug being used as a COVID-19 therapeutic. These results offer a molecular basis supporting the current use of Sofosbuvir in combination with other drugs in COVID-19 clinical trials.", - "rel_num_authors": 9, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.31.20161216", + "rel_abs": "BACKGROUNDThe top priority for the control of COVID-19 pandemic currently is the development of a vaccine. A phase 2 trial conducted to further evaluate the immunogenicity and safety of a SARS-CoV-2 inactivated vaccine (CoronaVac).\n\nMETHODSWe conducted a randomized, double-blind, placebo-controlled trial to evaluate the optimal dose, immunogenicity and safety of the CoronaVac. A total of 600 healthy adults aged 18-59 years were randomly assigned to receive 2 injections of the trial vaccine at a dose of 3 g/0.5 mL or 6 g /0.5mL, or placebo on Day 0,14 schedule or Day 0,28 schedule. For safety evaluation, solicited and unsolicited adverse events were collected after each vaccination within 7 days and 28 days, respectively. Blood samples were taken for antibody assay.\n\nRESULTSCoronaVac was well tolerated, and no dose-related safety concerns were observed. Most of the adverse reactions fell in the solicited category and were mild in severity. Pain at injection site was the most frequently reported symptoms. No Grade 3 adverse reaction or vaccine related SAEs were reported. CoronaVac showed good immunogenicity with the lower 3 g dose eliciting 92.4% seroconversion under Day 0,14 schedule and 97.4% under Day 0,28 schedule. 28 days after two-dose vaccination, the Nab levels of individual schedules range from 23.8 to 65.4 among different dosage and vaccination schedules.\n\nCONCLUSIONSFavorable safety and immunogenicity of CoronaVac was demonstrated on both schedules and both dosages, which support the conduction of phase 3 trial with optimum schedule/dosage per different scenarios.", + "rel_num_authors": 30, "rel_authors": [ { - "author_name": "Steffen Jockusch", - "author_inst": "Columbia University" + "author_name": "Yan-Jun Zhang", + "author_inst": "Department of Microbiology, Zhejiang Provincial Center for Disease Control and Prevention" }, { - "author_name": "Chuanjuan Tao", - "author_inst": "Columbia University" + "author_name": "Gang Zeng", + "author_inst": "Sinovac Biotech Ltd." }, { - "author_name": "Xiaoxu Li", - "author_inst": "Columbia University" + "author_name": "Hong-Xing Pan", + "author_inst": "Jiangsu Provincial Center for Disease Control and Prevention" }, { - "author_name": "Minchen Chien", - "author_inst": "Columbia University" + "author_name": "Chang-Gui Li", + "author_inst": "National Institutes for Food and Drug Control" }, { - "author_name": "Shiv Kumar", - "author_inst": "Columbia University" + "author_name": "Biao Kan", + "author_inst": "National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention" }, { - "author_name": "Irina Morozova", - "author_inst": "Columbia University" + "author_name": "Ya-Ling Hu", + "author_inst": "Sinovac Biotech Ltd." }, { - "author_name": "Sergey Kalachikov", - "author_inst": "Columbia University" + "author_name": "Hai-Yan Mao", + "author_inst": "Department of Microbiology, Zhejiang Provincial Center for Disease Control and Prevention" }, { - "author_name": "James J. Russo", - "author_inst": "Columbia University" + "author_name": "Qian-Qian Xin", + "author_inst": "Sinovac Biotech Ltd." }, { - "author_name": "Jingyue Ju", - "author_inst": "Columbia University" + "author_name": "Kai Chu", + "author_inst": "Jiangsu Provincial Center for Disease Control and Prevention" + }, + { + "author_name": "Wei-Xiao Han", + "author_inst": "Sinovac Biotech Ltd." + }, + { + "author_name": "Zhen Chen", + "author_inst": "National Institutes for Food and Drug Control" + }, + { + "author_name": "Rong Tang", + "author_inst": "Jiangsu Provincial Center for Disease Control and Prevention" + }, + { + "author_name": "Wei-Dong Yin", + "author_inst": "Sinovac Biotech Ltd." + }, + { + "author_name": "Xin Chen", + "author_inst": "Suining County Center for Disease Control and Prevention" + }, + { + "author_name": "Xue-Jie Gong", + "author_inst": "Sinovac Biotech Ltd." + }, + { + "author_name": "Chuan Qin", + "author_inst": "Key Laboratory of Human Disease Comparative Medicine, Chinese Ministry of Health, Beijing Key Laboratory for Animal Models of Emerging and Remerging Infectious " + }, + { + "author_name": "Yuan-Sheng Hu", + "author_inst": "Sinovac Biotech Ltd." + }, + { + "author_name": "Xiao-Yong Liu", + "author_inst": "Suining County Center for Disease Control and Prevention" + }, + { + "author_name": "Guo-Liang Cui", + "author_inst": "Sinovac Life Sciences Co., Ltd." + }, + { + "author_name": "Cong-Bing Jiang", + "author_inst": "Suining County Center for Disease Control and Prevention, Suining" + }, + { + "author_name": "Heng-Ming Zhang", + "author_inst": "Sinovac Biotech Ltd." + }, + { + "author_name": "Jing-Xin Li", + "author_inst": "Jiangsu Provincial Center for Disease Control and Prevention" + }, + { + "author_name": "Min-Nan Yang", + "author_inst": "CAS Key Laboratory of Infection and Immunity, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences" + }, + { + "author_name": "Xiao-Juan Lian", + "author_inst": "Sinovac Life Sciences Co., Ltd." + }, + { + "author_name": "Yan Song", + "author_inst": "Suining County Center for Disease Control and Prevention" + }, + { + "author_name": "Jin-Xing Lu", + "author_inst": "National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Changping" + }, + { + "author_name": "Xiang-Xi Wang", + "author_inst": "CAS Key Laboratory of Infection and Immunity, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences" + }, + { + "author_name": "Miao Xu", + "author_inst": "National Institutes for Food and Drug Control" + }, + { + "author_name": "Qiang Gao", + "author_inst": "Sinovac Life Sciences Co., Ltd." + }, + { + "author_name": "Feng-Cai Zhu", + "author_inst": "Jiangsu Provincial Center for Disease Control and Prevention" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "pharmacology and toxicology" + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2020.08.09.242867", @@ -1229497,33 +1230441,97 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.07.20169920", - "rel_title": "Wrong person, place and time: viral load and contact network structure predict SARS-CoV-2 transmission and super-spreading events", + "rel_doi": "10.1101/2020.08.06.20169771", + "rel_title": "CRISPR-based and RT-qPCR surveillance of SARS-CoV-2 in asymptomatic individuals uncovers a shift in viral prevalence among a university population", "rel_date": "2020-08-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.07.20169920", - "rel_abs": "SARS-CoV-2 is difficult to contain because many transmissions occur during the pre-symptomatic phase of infection. Moreover, in contrast to influenza, while most SARS-CoV-2 infected people do not transmit the virus to anybody, a small percentage secondarily infect large numbers of people. We designed mathematical models of SARS-CoV-2 and influenza which link observed viral shedding patterns with key epidemiologic features of each virus, including distributions of the number of secondary cases attributed to each infected person (individual R0) and the duration between symptom onset in the transmitter and secondarily infected person (serial interval). We identify that people with SARS-CoV-2 or influenza infections are usually contagious for fewer than one day congruent with peak viral load several days after infection, and that transmission is unlikely below a certain viral load. SARS-CoV-2 super-spreader events with over 10 secondary infections occur when an infected person is briefly shedding at a very high viral load and has a high concurrent number of exposed contacts. The higher predisposition of SARS-CoV-2 towards super-spreading events is not due to its 1-2 additional weeks of viral shedding relative to influenza. Rather, a person infected with SARS-CoV-2 exposes more people within equivalent physical contact networks than a person infected with influenza, likely due to aerosolization of virus. Our results support policies that limit crowd size in indoor spaces and provide viral load benchmarks for infection control and therapeutic interventions intended to prevent secondary transmission.\n\nOne Sentence SummaryWe developed a coupled within-host and between-host mathematical model to identify viral shedding levels required for transmission of SARS-CoV-2 and influenza, and to explain why super-spreading events occur more commonly during SARS-CoV-2 infection.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.06.20169771", + "rel_abs": "The progress of the COVID-19 pandemic profoundly impacts the health of communities around the world, with unique effects on colleges and universities. Here, we examined the prevalence of SARS-CoV-2 in 1808 asymptomatic individuals on a university campus in California, and compared for the first time the performance of CRISPR- and PCR-based assays for large-scale virus surveillance. Our study revealed that there were no COVID-19 cases in our study population in May/June of 2020. Using the same methods, we demonstrated a substantial shift in prevalence approximately one month later, which coincided with changes in community restrictions and public interactions. This increase in prevalence, in a young and asymptomatic population, indicated the leading wave of a local outbreak, and reflected the rising case counts in the surrounding county. Our results substantiate that large, population-level asymptomatic screening using CRISPR- or PCR-based assays is a feasible and instructive aspect of the public health approach within large campus communities.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Ashish Goyal", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Jennifer N Rauch", + "author_inst": "University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology; Neuroscience Research Institute, University of California" }, { - "author_name": "Daniel B Reeves", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Eric Valois", + "author_inst": "University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology" }, { - "author_name": "E. Fabian Cardozo-Ojeda", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Jose Carlos Ponce-Rojas", + "author_inst": "University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology" }, { - "author_name": "Joshua T Schiffer", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Zach Aralis", + "author_inst": "University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology" }, { - "author_name": "Bryan T. Mayer", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Ryan L Lach", + "author_inst": "University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology" + }, + { + "author_name": "Francesca Zappa", + "author_inst": "University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology" + }, + { + "author_name": "Morgane Audouard", + "author_inst": "University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology; Neuroscience Research Institute, University of California" + }, + { + "author_name": "Sabrina C Solley", + "author_inst": "University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology" + }, + { + "author_name": "Chinmay Vaidya", + "author_inst": "University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology" + }, + { + "author_name": "Michael Costello", + "author_inst": "University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology" + }, + { + "author_name": "Holly Smith", + "author_inst": "Student Health Service, University of California Santa Barbara" + }, + { + "author_name": "Ali Javanbakht", + "author_inst": "Student Health Service, University of California Santa Barbara" + }, + { + "author_name": "Betsy Malear", + "author_inst": "Student Health Service, University of California Santa Barbara" + }, + { + "author_name": "Laura Polito", + "author_inst": "Student Health Service, University of California Santa Barbara" + }, + { + "author_name": "Stewart Comer", + "author_inst": "Department of Pathology, Santa Barbara Cottage Hospital; Pacific Diagnostic Laboratories, Santa Barbara," + }, + { + "author_name": "Katherine Arn", + "author_inst": "Department of Medical Education and Division of Infectious Diseases, Santa Barbara Cottage Hospital" + }, + { + "author_name": "Kenneth S Kosik", + "author_inst": "University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology; Neuroscience Research Institute, University of California" + }, + { + "author_name": "Diego Acosta-Alvear", + "author_inst": "University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology; Neuroscience Research Institute, University of California" + }, + { + "author_name": "Maxwell Z Wilson", + "author_inst": "University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology; Neuroscience Research Institute, University of California" + }, + { + "author_name": "Lynn Fitzgibbons", + "author_inst": "Department of Medical Education and Division of Infectious Diseases, Santa Barbara Cottage Hospital" + }, + { + "author_name": "Carolina Arias", + "author_inst": "University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology, Neuroscience Research Institute, University of California" } ], "version": "1", @@ -1231271,37 +1232279,17 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.05.20168674", - "rel_title": "Insights into the first wave of the COVID-19 pandemic in Bangladesh: Lessons learned from a high-risk country", + "rel_doi": "10.1101/2020.08.04.20168195", + "rel_title": "Mathematical Analysis, Model and Prediction of COVID-19 Data", "rel_date": "2020-08-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.05.20168674", - "rel_abs": "BackgroundSouth Asian countries including Bangladesh have been struggling to control the COVID-19 pandemic despite imposing months of lockdown and other public health measures (as of June 30, 2020). In-depth epidemiological information from these countries is lacking. From the perspective of Bangladesh, this study aims to understand the epidemiological features and gaps in public health preparedness.\n\nMethodThis study used publicly available data (8 March-30 June 2020) from the respective health departments of Bangladesh and Johns Hopkins University Coronavirus Resource Centre. Descriptive statistics was used to report the incidence, case fatality rates (CFR), and trend analysis. Spatial distribution maps were created using ArcGIS Desktop. Infection dynamics were analyzed via SIR models.\n\nFindingsIn 66 days of nationwide lockdown and other public health efforts, a total of 47,153 cases and 650 deaths were reported. However, the incidence was increased by around 50% within a week after relaxing the lockdown. Males were disproportionately affected in terms of infections (71%) and deaths (77%) than females. The CFR for males was higher than females (1.38% vs 1.01%). Over 50% of infected cases were reported among young adults (20-40-year age group). Geospatial analysis between 7 June 2020 and 20 June 2020 showed that the incidences increased 4 to 10-fold in 12 administrative districts while it decreased in the epicenter. As compared to the EU and USA, trends of the cumulative incidence were slower in South Asia with lower mortality.\n\nConclusionOur findings on gaps in public health preparedness and epidemiological characteristics would contribute to facilitating better public health decisions for managing current and future pandemics like COVID-19 in the settings of developing countries.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.04.20168195", + "rel_abs": "A simple and effective mathematical procedure for the description of observed COVID-19 data and calculation of future projections is presented. An exponential function E(t) with a time-varying Growth Constant k(t) is used. E(t) closely approximates observed COVID-19 Daily Confirmed Cases with NRMSDs of 1 to 2%. An example of prediction of future cases is presented. The Effective Growth Rates of a discrete SIR model were estimated on the basis of k(t) for COVID-19 data for Germany, and were found to be consistent with those reported in a previous study (1). The proposed procedure, which involves less than ten basic algebraic, logarithm and exponentiation operations for each data point, is suitable for use in promoting interdisciplinary research, exchange and sharing of information.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Md. Hasanul Banna Siam", - "author_inst": "Biomedical Research Foundation, Dhaka, Bangladesh" - }, - { - "author_name": "Md Mahbub Hasan", - "author_inst": "Biomedical Research Foundation, Dhaka, Bangladesh" - }, - { - "author_name": "Enayetur Raheem", - "author_inst": "Biomedical Research Foundation, Dhaka, Bangladesh" - }, - { - "author_name": "Md. Hasinur rahaman Khan", - "author_inst": "Institute of Statistical Research and Training, University of Dhaka, Bangladesh" - }, - { - "author_name": "Mahbubul H Siddiqee", - "author_inst": "Biomedical Research Foundation, Dhaka, Bangladesh" - }, - { - "author_name": "Mohammad Sorowar Hossain", - "author_inst": "Biomedical Research Foundation" + "author_name": "Yit Chow Tong", + "author_inst": "Formerly : University of Melbourne - retired" } ], "version": "1", @@ -1233225,27 +1234213,55 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.08.05.20167411", - "rel_title": "Impact of COVID-19 on the Psychological Well-Being and Turnover Intentions of Frontline Nurses in the Community: A Cross-Sectional Study in the Philippines", + "rel_doi": "10.1101/2020.08.05.238998", + "rel_title": "Persistent bacterial coinfection of a COVID-19 patient caused by a genetically adapted Pseudomonas aeruginosa chronic colonizer", "rel_date": "2020-08-06", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.05.20167411", - "rel_abs": "PurposeThis study aimed to assess fear of COVID-19 among nurses in a community setting.\n\nMethodsThis study employed a cross-sectional design using self-report questionnaires.\n\nFindingsResults revealed that nurses display moderate to high fear of COVID-19 and that the female gender is correlated to fear of the virus. Moreover, the nurses fear influences their psychological distress and organizational and professional turnover intentions.\n\nConclusionFear of COVID-19 is universal among nurses. There is a need to assess the factors associated with the fear to better address the nurses psychological well-being and to avoid turnover intentions.", - "rel_num_authors": 2, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.05.238998", + "rel_abs": "This study characterized a genetically adapted Pseudomonas aeruginosa small colony variant isolated from a COVID-19 patient who suffered persistent bacterial coinfection and eventually recovered from critical illness. Specification and modification of the isolates discovered at genomic and transcriptomic levels with aligned phenotypic observations indicated that these isolates formed excessive biofilm with elevated quorum sensing systems.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Janet Alexis A. De los Santos", - "author_inst": "Visayas State University, Philippines" + "author_name": "Zhao Cai", + "author_inst": "School of Medicine, Southern University of Science and Technology" + }, + { + "author_name": "Yumei Liu", + "author_inst": "School of Medicine, Southern University of Science and Technology" + }, + { + "author_name": "XiangKe Duan", + "author_inst": "School of Medicine, Southern University of Science and Technology" + }, + { + "author_name": "Shuhong Han", + "author_inst": "School of Medicine, Southern University of Science and Technology" + }, + { + "author_name": "Yuao Zhu", + "author_inst": "School of Medicine, Southern University of Science and Technology" + }, + { + "author_name": "Yingdan Zhang", + "author_inst": "School of Medicine, Southern University of Science and Technology" + }, + { + "author_name": "Chao Zhuo", + "author_inst": "The state key laboratory of respiratory diseases, the first affiliated hospital of Guangzhou Medical University" + }, + { + "author_name": "Yang Liu", + "author_inst": "Medical Research Center, Southern University of Science and Technology Hospital, 518055, Shenzhen, China" }, { - "author_name": "Leodoro J. Labrague", - "author_inst": "Sultan Qaboos University, Oman" + "author_name": "Liang Yang", + "author_inst": "School of Medicine, Southern University of Science and Technology" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by_nc", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2020.08.06.239798", @@ -1235071,105 +1236087,77 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.31.20165704", - "rel_title": "R3T (Rapid Research Response Team) One-step RT-qPCR kit for COVID-19 diagnostic using in-house enzymes", + "rel_doi": "10.1101/2020.07.31.20165720", + "rel_title": "Evaluation of Convalescent Plasma versus Standard of Care for the Treatment of COVID-19 in Hospitalazed Patients: study protocol for a phase 2 randomized, open-label, controlled, multicenter trial", "rel_date": "2020-08-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.31.20165704", - "rel_abs": "One-step RT-qPCR is the most widely applied method for COVID-19 diagnostics. Designing in-house one-step RT-qPCR kits is restricted by the patent-rights for the production of enzymes and the lack of information about the components of the commercial kits. Here, we provide a simple, economical, and powerful one-step RT-qPCR kit based on patent-free, specifically-tailored versions of Moloney Murine Leukemia Virus Reverse Transcriptase and Thermus aquaticus DNA polymerase termed the R3T (Rapid Research Response Team) One-step RT-qPCR. Our kit was routinely able to reliably detect as low as 10 copies of the synthetic RNAs of the SARS-CoV-2. More importantly, our kit successfully detected COVID-19 in clinical samples of broad viral titers with similar reliability and selectivity as that of the Invitrogen SuperScript III Platinum One-step RT-qPCR and TaqPath 1-Step RT-qPCR kits. Overall, our kit has shown robust performance in both of laboratory settings and the Saudi Ministry of Health-approved testing facility.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.31.20165720", + "rel_abs": "BackgroundCOVID-19 is a respiratory disease caused by a novel coronavirus (SARS-CoV-2) and causes substantial morbidity and mortality. At the time this clinical trial was planned, there were no available vaccine or therapeutic agents with proven efficacy, but the severity of the condition prompted the use of several pharmacological and non-pharmacological interventions.\n\nIt has long been hypothesized that the use of convalescent plasma (CP) from infected patients who have developed an effective immune response is likely to be an option for the treatment of patients with a variety of severe acute respiratory infections (SARI) of viral etiology. The aim of this study is to assess the efficacy and safety of convalescent plasma in adult patients with severe COVID-19 pneumonia.\n\nMethods/DesignThe ConPlas-19 study is a multicenter, randomized, open-label controlled trial. The protocol has been prepared in accordance with the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) guidelines. The study has been planned to include 278 adult patients hospitalized with severe COVID-19 infection not requiring mechanical ventilation (invasive or non-invasive). Subjects are randomly assigned in a 1:1 ratio (139 per treatment arm), stratified by center, to receive intravenously administered CP (single infusion) plus SOC or SOC alone, and are to be followed for 30 days. The primary endpoint of the study is the proportion of patients that progress to categories 5, 6 or 7 (on the 7-point ordinal scale proposed by the WHO) at day 15. Interim analyses for efficacy and/or futility will be conducted once 20%, 40%, and 60% of the planned sample size are enrolled and complete D15 assessment.\n\nDiscussionThis clinical trial is designed to evaluate the efficacy and safety of passive immunotherapy with convalescent plasma for the treatment of adult patients hospitalized with COVID-19. The results of this study are expected to contribute to establishing the potential place of CP in the therapeutics for a new viral disease.\n\nTrial registrationTrial registration at clinicaltrials.gov; Registration Number: NCT04345523; https://clinicaltrials.gov/ct2/show/NCT04345523; Registered on 30 March, 2020. First posted date: April 14, 2020.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Masateru Takahashi", - "author_inst": "King Abdullah University of Science and Technology" - }, - { - "author_name": "Muhammad Tehseen", - "author_inst": "King Abdullah University of Science and Technology" - }, - { - "author_name": "Rahul Salunke", - "author_inst": "King Abdullah University of Science and Technology" - }, - { - "author_name": "Etsuko Takahashi", - "author_inst": "King Abdullah University of Science and Technology" - }, - { - "author_name": "Sara Mfarrej", - "author_inst": "King Abdullah University of Science and Technology" - }, - { - "author_name": "Mohamed A. Sobhy", - "author_inst": "King Abdullah University of Science and Technology" + "author_name": "Elena Diago-Sempere", + "author_inst": "Clinical Pharmacology Department. Hospital Universitario Puerta de Hierro Majadahonda, IISPHSA, Madrid, Spain" }, { - "author_name": "Fatimah Alhamlan", - "author_inst": "King Faisal Specialist Hospital and Research Centre" - }, - { - "author_name": "Sharif Hala", - "author_inst": "King Abdullah University of Science and Technology" - }, - { - "author_name": "Gerardo R. Mandujano", - "author_inst": "King Abdullah University of Science and Technology" + "author_name": "Jose Luis Bueno", + "author_inst": "Hemotherapy & Apheresis Units. Hematology and Hemotherapy Department. Hospital Universitario Puerta de Hierro Majadahonda." }, { - "author_name": "Ahmed A. Al-Qahtani", - "author_inst": "King Faisal Specialist Hospital and Research Center" + "author_name": "Aranzazu Sancho-Lopez", + "author_inst": "Clinical Pharmacology Department. Hospital Univ. Puerta de Hierro Majadahonda, IISPHSA, Madrid, Spain" }, { - "author_name": "Fadwa S. Alofi", - "author_inst": "King Fahad Hospital" + "author_name": "Elena Munez-Rubio", + "author_inst": "Internal Medicine Department. Infectious diseases unit. Hospital Universitario Puerta de Hierro Majadahonda. IISPHSA. Madrid, Spain" }, { - "author_name": "Afrah Alsomali", - "author_inst": "King Abdullah Medical Complex" + "author_name": "Ferran Torres", + "author_inst": "Clinical Pharmacology Department. Hospital Clinic Barcelona. Medical Statistics core facility. IDIBAPS. Barcelona, Spain" }, { - "author_name": "Anwar M. Hashem", - "author_inst": "King Fahd Medical Research Center" + "author_name": "Rosa Malo de Molina", + "author_inst": "Servicio de Pneumology. Hospital Universitario Puerta de Hierro Majadahonda" }, { - "author_name": "Asim Khogeer", - "author_inst": "General Directorate of Health Affairs Makkah Region" + "author_name": "Ana Fernandez-Cruz", + "author_inst": "Internal Medicine Department. Infectious diseases Unit. Hospital Universitario Puerta de Hierro Majadahonda" }, { - "author_name": "Naif A. M. Almontashiri", - "author_inst": "Taibah University" + "author_name": "Isabel Salcedo De Diego", + "author_inst": "Clinical Pharmacology Department. Hospital Univ. Puerta de Hierro Majadahonda, IISPHSA , Madrid, Spain" }, { - "author_name": "Jae Man Lee", - "author_inst": "Kyushu University" + "author_name": "Ana Velasco-Iglesias", + "author_inst": "SCReN, IIS Puerta de Hierro - Segovia de Arana, Madrid, Spain" }, { - "author_name": "Hiroaki Mon", - "author_inst": "Kyushu University" + "author_name": "Concepcion Payares Herrera", + "author_inst": "Clinical Pharmacology Department. Hospital Univ. Puerta de Hierro Majadahonda, IISPHSA, Madrid, Spain" }, { - "author_name": "Kosuke Sakashita", - "author_inst": "King Abdullah University of Science and Technology" + "author_name": "Inmaculada Casas Flecha", + "author_inst": "Flu and Respiratory Virus Unit. Centro Nacional de Microbiologia Instituto de Salud Carlos III" }, { - "author_name": "Mo Li", - "author_inst": "King Abdullah University of Science and Technology" + "author_name": "Cristina Avendano-Sola", + "author_inst": "Clinical Pharmacology Department. Hospital Univ. Puerta de Hierro Majadahonda, IISPHSA Madrid, Spain" }, { - "author_name": "Takahiro Kusakabe", - "author_inst": "Kyushu University" + "author_name": "Rafael Duarte Palomino", + "author_inst": "Hematology and Hemotherapy Department. Hospital Universitario Puerta de Hierro Majadahonda, Madrid, Spain" }, { - "author_name": "Arnab Pain", - "author_inst": "King Abdullah University of Science and Technology" + "author_name": "Antonio Ramos-Martinez", + "author_inst": "Internal Medicine Department. Infectious diseases Unit. Hospital Universitario Puerta de Hierro Majadahonda, Madrid, Spain" }, { - "author_name": "Samir M. Hamdan", - "author_inst": "King Abdullah University of Science and Technology" + "author_name": "Belen Ruiz-Antoran", + "author_inst": "Clinical Pharmacology Department. Hospital Univ. Puerta de Hierro Majadahonda, IISPHSA, Madrid, Spain" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1236961,91 +1237949,31 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.08.02.20166710", - "rel_title": "Effectiveness of Convalescent Plasma for Treatment of COVID-19 Patients", + "rel_doi": "10.1101/2020.08.01.20166371", + "rel_title": "Outcome of COVID-19 with co-existing surgical emergencies in children: our initial experiences and recommendations", "rel_date": "2020-08-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.02.20166710", - "rel_abs": "Background and objectiveThe outbreak of COVID-19 has become a global health concern. In this study, we evaluate the effectiveness and safety of convalescent plasma therapy in patients with severe and critically ill COVID-19.\n\nMethodsSixteen COVID-19 patients received transfusion of anti-COVID-19 antibody-positive convalescent plasma. The main outcome was time for viral nucleic acid amplification (NAA) test turning negative. Clinical laboratory parameters were measured at the baseline (d0) before plasma transfusion, and day 1 (d1), day 3 (d3) after transfusion as well.\n\nResultsAmong the 16 patients, 10 of them had a consistently positive result of viral NAA test before convalescent plasma transfusion. Eight patients (8/10) became negative from day 2 to day 8 after transfusion. Severe patients showed a shorter time for NAA test turning negative after transfusion (mean rank 2.17 vs 5{middle dot}90, P = 0.036). Two critically ill patients transfused plasma with lower antibody level remained a positive result of NAA test. CRP level demonstrated a decline 1 day after convalescent plasma treatment, compared with the baseline (P = 0.017). No adverse events were observed during convalescent plasma transfusion.\n\nConclusionsViral NAA test of most patients with COVID-19 who received convalescent plasma transfusion turned negative on the 2nd to 8th days after transfusion, and the negative time of severe patients was shorter than that of critically ill patients.\n\nTrial RegistrationChinese Clinical Trial Registry; No.: ChiCTR2000030627 URL:http://www.chictr.org", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.01.20166371", + "rel_abs": "BackgroundCOVID-19 has changed the practice of surgery vividly all over the world. Pediatric surgery is not an exception. Prioritization protocols allowing us to provide emergency surgical care to the children in need while controlling the pandemic spread. The aim of this study is to share our experiences with the outcome of children with COVID-19 who had a co-existing surgical emergency.\n\nMethodsThis is a retrospective observational study. We reviewed the epidemiological, clinical, and laboratory data of all patients admitted in our surgery department through the emergency department and later diagnosed to have COVID-19 by RT-PCR. The study duration was 3 months (April 2020 - June 2020). A nasopharyngeal swab was taken from all patients irrespective of symptoms to detect SARS CoV 2 by RT-PCR with the purpose of detecting asymptomatic patients and patients with atypical symptoms. Emergency surgical services were provided immediately without delay and patients with positive test results were isolated according to the hospital protocol. We divided the test positive patients into 4 age groups for the convenience of data analysis. Data were retrieved from hospital records and analyzed using SPSS (version 25) software. Ethical permission was taken from the hospital ethical review board.\n\nResultsTotal patients were 32. Seven (21.9%) of them were neonates. Twenty-four (75%) patients were male. The predominant diagnosis was acute abdomen followed by infantile hypertrophic pyloric stenosis (IHPS), myelomeningocele, and intussusception. Only two patients had mild respiratory symptoms (dry cough). Fever was present in 13 (40.6%) patients. Fourteen (43.8%) patients required surgical treatment. The mean duration of hospital stay was 5.5 days. One neonate with ARM died in the post-operative ward due to cardiac arrest. No patient had hypoxemia or organ failure. Seven health care workers (5.51%) including doctors & nurses got infected with SARS Co V2 during this period.\n\nConclusionOur study has revealed a milder course of COVID-19 in children with minimal infectivity even when present in association with emergency surgical conditions. This might encourage a gradual restart to mitigate the impact of COVID-19 on childrens surgery.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Shanshan Chen", - "author_inst": "The First Affiliated Hospital of Zhengzhou University" - }, - { - "author_name": "Chunya Lu", - "author_inst": "The First Affiliated Hospital of Zhengzhou University" - }, - { - "author_name": "Ping Li", - "author_inst": "The First Affiliated Hospital of Zhengzhou University" - }, - { - "author_name": "Lei Wang", - "author_inst": "The First Affiliated Hospital of Zhengzhou University" - }, - { - "author_name": "Huaqi Wang", - "author_inst": "The First Affiliated Hospital of Zhengzhou University" - }, - { - "author_name": "Qiankun Yang", - "author_inst": "The First Affiliated Hospital of Zhengzhou University" - }, - { - "author_name": "Liyinghui Chen", - "author_inst": "The First Affiliated Hospital of Zhengzhou University" - }, - { - "author_name": "Jianbin Li", - "author_inst": "Henan Red Cross Blood Center" - }, - { - "author_name": "Hongwei Ma", - "author_inst": "Henan Red Cross Blood Center" - }, - { - "author_name": "Qian Sang", - "author_inst": "The First Affiliated Hospital of Zhengzhou University" - }, - { - "author_name": "Jing Li", - "author_inst": "The First Affiliated Hospital of Zhengzhou University" - }, - { - "author_name": "Luyang Xu", - "author_inst": "The First Affiliated Hospital of Zhengzhou University" - }, - { - "author_name": "Xiangjin Song", - "author_inst": "The First Affiliated Hospital of Zhengzhou University" - }, - { - "author_name": "Fangfang Li", - "author_inst": "The First Affiliated Hospital of Zhengzhou University" - }, - { - "author_name": "Yi Zhang", - "author_inst": "The First Affiliated Hospital of Zhengzhou University" - }, - { - "author_name": "Yi Kang", - "author_inst": "Henan Provincial People's Hospital" + "author_name": "Md Samiul Hasan", + "author_inst": "Dhaka Shishu (Children) Hospital" }, { - "author_name": "Lihua Xing", - "author_inst": "The First Affiliated Hospital of Zhengzhou University" + "author_name": "Md Ayub Ali", + "author_inst": "Dhaka Shishu (Children) Hospital" }, { - "author_name": "Guojun Zhang", - "author_inst": "The First Affiliatied Hospital of Zhengzhou University" + "author_name": "Umama Huq", + "author_inst": "Bangladesh Institute of Child Health" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "surgery" }, { "rel_doi": "10.1101/2020.08.03.20167320", @@ -1238523,69 +1239451,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.02.20166819", - "rel_title": "Neutralizing antibody against SARS-CoV-2 spike in COVID-19 patients, health care workers and convalescent plasma donors: a cohort study using a rapid and sensitive high-throughput neutralization assay", + "rel_doi": "10.1101/2020.08.01.20166587", + "rel_title": "Peripheral innate and adaptive immune cells during COVID-19: Functional neutrophils, pro-inflammatory monocytes and half-dead lymphocytes", "rel_date": "2020-08-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.02.20166819", - "rel_abs": "Rapid and specific antibody testing is crucial for improved understanding, control, and treatment of COVID-19 pathogenesis. Herein, we describe and apply a rapid, sensitive, and accurate virus neutralization assay for SARS-CoV-2 antibodies. The new assay is based on an HIV-1 lentiviral vector that contains a secreted intron Gaussia luciferase or secreted Nano-luciferase reporter cassette, pseudotyped with the SARS-CoV-2 spike (S) glycoprotein, and is validated with a plaque reduction assay using an authentic, infectious SARS-CoV-2 strain. The new assay was used to evaluate SARS-CoV-2 antibodies in serum from individuals with a broad range of COVID-19 symptoms, including intensive care unit (ICU) patients, health care workers (HCWs), and convalescent plasma donors. The highest neutralizing antibody titers were observed among ICU patients, followed by general hospitalized patients, HCWs and convalescent plasma donors. Our study highlights a wide phenotypic variation in human antibody responses against SARS-CoV-2, and demonstrates the efficacy of a novel lentivirus pseudotype assay for high-throughput serological surveys of neutralizing antibody titers in large cohorts.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.01.20166587", + "rel_abs": "A better understanding of the innate and adaptive cells in the COVID-19 disease caused by the SARS-CoV-2 coronavirus is a necessity for the development of effective treatment methods and vaccines. We studied phenotypic features of innate and adaptive immune cells, oxidative burst, phagocytosis and apoptosis. One hundred and three patients with COVID-19 grouped according to their clinical features as mild (35%), moderate (40.8%), and severe (24.3%) were included in the study. Monocytes from all COVID-19 patients were CD16+ pro-inflammatory monocytes. Neutrophils were mature and functional. No defect has been found in ROS production of monocytes and neutrophils as well as no defect in their apoptosis. As bridging cells of the innate and adaptive immune system; the percentage of NK cells was in normal range whereas the percentages of CD3-CD8+CD56+ innate lymphoid and CD3+CD56+ NK like T cells were found to be high in the severe cases of COVID-19. Although absolute numbers of all lymphocyte subsets were low and showed a tendency for a gradual decrease in accord with the disease progression, in all COVID-19 patients, the lymphocyte subset with the most decreased absolute number was B lymphocytes, followed by CD4 + T cells in the severe cases. The percentages of suppressive, CD3+CD4-CD8-; HLA-DR+CD3+ and CD28-CD8+ cells were found to be significantly increased. Importantly, we demonstrated spontaneous caspase-3 activation and increased lymphocyte apoptosis. Altogether our data suggest that SARS-CoV-2 primarily affects lymphocytes not innate cells. So that, it may interrupt the cross-talk between adaptive and innate immune systems.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Cong Zeng", - "author_inst": "Center for Retrovirus Research, Department of Veterinary Biosciences, The Ohio State University" + "author_name": "Emel Eksioglu-Demiralp", + "author_inst": "Istanbul Memorial Sisli Hospital, Tissue Typing and Immunology Laboratory" }, { - "author_name": "John P Evans", - "author_inst": "Center for Retrovirus Research, Department of Veterinary Biosciences, Molecular, Cellular and Developmental Biology Program, The Ohio State University" + "author_name": "Servet Alan", + "author_inst": "Istanbul Memorial Sisli Hospital Department of Infectious Diseases and Clinical Microbiology" }, { - "author_name": "Rebecca Pearson", - "author_inst": "Department of Pathology, The Ohio State University" - }, - { - "author_name": "Panke Qu", - "author_inst": "Center for Retrovirus Research, Department of Veterinary Biosciences, The Ohio State University" - }, - { - "author_name": "Yi-Min Zheng", - "author_inst": "Center for Retrovirus Research, Department of Veterinary Biosciences, The Ohio State University" - }, - { - "author_name": "Richard T Robinson", - "author_inst": "Department of Microbial Infection and Immunity, The Ohio State University" - }, - { - "author_name": "Luanne Hall-Stoodley", - "author_inst": "Department of Microbial Infection and Immunity, The Ohio State University" - }, - { - "author_name": "Jacob Yount", - "author_inst": "Department of Microbial Infection and Immunity, The Ohio State University" + "author_name": "Uluhan Sili", + "author_inst": "Marmara University, School of Medicine, Department of Infectious Diseases and Clinical Microbiology" }, { - "author_name": "Sonal Pannu", - "author_inst": "Department of Medicine, The Ohio State University" + "author_name": "Dilek Bakan", + "author_inst": "Istanbul Memorial Sisli Hospital, Department of Chest Diseases" }, { - "author_name": "Rama K Mallampalli", - "author_inst": "Department of Medicine, The Ohio State University" + "author_name": "Ilhan Ocak", + "author_inst": "Istanbul Memorial Sisli Hospital, Department of Intensive Care" }, { - "author_name": "Linda Saif", - "author_inst": "Food Animal Health Research Program, Ohio Agricultural Research and Development Center, College of Food, Agricultural, and Environmental Sciences; Viruses and E" + "author_name": "Rayfe Yurekli", + "author_inst": "Istanbul Memorial Sisli Hospital Tissue Typing and Immunology Laboratory" }, { - "author_name": "Eugene Oltz", - "author_inst": "Department of Microbial Infection and Immunity, The Ohio State University" + "author_name": "Nadir Alpay", + "author_inst": "Istanbul Hizmet Hospital, Department of Nephrology" }, { - "author_name": "Gerard Lozanski", - "author_inst": "Department of Pathology, The Ohio State University" + "author_name": "Serpil Gorcin", + "author_inst": "Istanbul Memorial Sisli Hospital, Department of Nephrology" }, { - "author_name": "Shan-Lu Liu", - "author_inst": "Center for Retrovirus Research, Department of Veterinary Biosciences, Department of Microbial Infection and Immunity, Viruses and Emerging Pathogens Program, In" + "author_name": "Alaattin Yildiz", + "author_inst": "Istanbul Memorial Sisli Hospital, Department of Nephrology" } ], "version": "1", @@ -1240241,77 +1241149,229 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.08.04.236315", - "rel_title": "A distinct innate immune signature marks progression from mild to severe COVID-19", + "rel_doi": "10.1101/2020.08.04.235747", + "rel_title": "A valid protective immune response elicited in rhesus macaques by an inactivated vaccine is capable of defending against SARS-CoV-2 infection", "rel_date": "2020-08-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.04.236315", - "rel_abs": "Coronavirus disease 2019 (COVID-19) manifests with a range of severities, but immune signatures of mild and severe disease are still not fully understood. Excessive inflammation has been postulated to be a major factor in the pathogenesis of severe COVID-19 and innate immune mechanisms are likely to be central in the inflammatory response. We used 40-plex mass cytometry and targeted serum proteomics to profile innate immune cell populations from peripheral blood of patients with mild or severe COVID-19 and healthy controls. Sampling at different stages of COVID-19 allowed us to reconstruct a pseudo-temporal trajectory of the innate immune response. Despite the expected patient heterogeneity, we identified consistent changes during the course of the infection. A rapid and early surge of CD169+ monocytes associated with an IFN{gamma}+MCP-2+ signature quickly followed symptom onset; at symptom onset, patients with mild and severe COVID-19 had a similar signature, but over the course of the disease, the differences between patients with mild and severe disease increased. Later in the disease course, we observed a more pronounced re-appearance of intermediate/non-classical monocytes and mounting systemic CCL3 and CCL4 levels in patients with severe disease. Our data provide new insights into the dynamic nature of the early inflammatory response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and identifies sustained pathological innate immune responses as a likely key mechanism in severe COVID-19, further supporting investigation of targeted anti-inflammatory interventions in severe COVID-19.", - "rel_num_authors": 16, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.04.235747", + "rel_abs": "With the relatively serious global epidemic outbreak of SARS-CoV-2 infection, public concerns focus on not only clinical therapeutic measures and public quarantine for this disease but also the development of vaccines. The technical design of our SARS-CoV-2 inactivated vaccine provides a viral antigen that enables the exposure of more than one structural protein based upon the antibody composition of COVID-19 patients convalescent serum. This design led to valid immunity with increasing neutralizing antibody titers and a CTL response detected post-immunization of this vaccine by two injections in rhesus macaques. Further, this elicited immunoprotection in macaques enables not only to restrain completely viral replication in tissues of immunized animals, compared to the adjuvant control and those immunized by an RBD peptide vaccine, but also to significantly alleviate inflammatory lesion in lung tissues in histo-pathologic detection, compared to the adjuvant control with developed interstitial pneumonia. The data obtained from these macaques immunized with the inactivated vaccine or RBD peptide vaccine suggest that immunity with a clinically protective effect against SARS-CoV-2 infection should include not only specific neutralizing antibodies but also specific CTL responses against at least the S and N antigens.", + "rel_num_authors": 54, "rel_authors": [ { - "author_name": "St\u00e9phane Chevrier", - "author_inst": "Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland" + "author_name": "Hongbo Chen", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" }, { - "author_name": "Yves Zurbuchen", - "author_inst": "Department of Immunology, University Hospital Zurich (USZ), Zurich, Switzerland" + "author_name": "Zhongping Xie", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" }, { - "author_name": "Carlo Cervia", - "author_inst": "Department of Immunology, University Hospital Zurich (USZ), Zurich, Switzerland" + "author_name": "Runxiang Long", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" }, { - "author_name": "Sarah Adamo", - "author_inst": "Department of Immunology, University Hospital Zurich (USZ), Zurich, Switzerland" + "author_name": "Shengtao Fan", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" }, { - "author_name": "Miro E Raeber", - "author_inst": "Department of Immunology, University Hospital Zurich (USZ), Zurich, Switzerland" + "author_name": "Heng Li", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" }, { - "author_name": "Natalie de Souza", - "author_inst": "Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland" + "author_name": "Zhanlong He", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" }, { - "author_name": "Sujana Sivapatham", - "author_inst": "Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland" + "author_name": "Kanwei Xu", + "author_inst": "National Institute of Food and Drug Control, China" }, { - "author_name": "Andrea Jacobs", - "author_inst": "Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland" + "author_name": "Yun Liao", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" }, { - "author_name": "Esther B\u00e4chli", - "author_inst": "Clinic for Internal Medicine, Uster Hospital, Uster, Switzerland" + "author_name": "Lichun Wang", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" }, { - "author_name": "Alain Rudiger", - "author_inst": "Department of Medicine, Limmattal Hospital, Schlieren, Switzerland" + "author_name": "Ying Zhang", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" }, { - "author_name": "Melina St\u00fcssi-Helbling", - "author_inst": "Clinic for Internal Medicine, City Hospital Triemli Zurich, Zurich, Switzerland" + "author_name": "Xueqi Li", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" }, { - "author_name": "Lars C Huber", - "author_inst": "Clinic for Internal Medicine, City Hospital Triemli Zurich, Zurich, Switzerland" + "author_name": "Xingq Dong", + "author_inst": "Yunnan Provincial Infectious Disease Hospital" }, { - "author_name": "Dominik J Schaer", - "author_inst": "Department of Internal Medicine, USZ, Zurich, Switzerland" + "author_name": "Tangwei Mou", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" }, { - "author_name": "Jakob Nilsson", - "author_inst": "Department of Immunology, University Hospital Zurich (USZ), Zurich, Switzerland" + "author_name": "Xiaofang Zhou", + "author_inst": "Yunnan Center for disease control and prevention, Kunming, 650034, China" }, { - "author_name": "Onur Boyman", - "author_inst": "Department of Immunology, University Hospital Zurich (USZ), Zurich, Switzerland" + "author_name": "Yaoyun Yang", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" }, { - "author_name": "Bernd Bodenmiller", - "author_inst": "Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland" + "author_name": "Lei Guo", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Jianbo Yang", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Huiwen Zheng", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Xingli Xu", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Jing Li", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Yan Liang", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Dandan Li", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Zhimei Zhao", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Chao Hong", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Heng Zhao", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Guorun Jiang", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Yanchun Che", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Fengmei Yang", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Yunguang Hu", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Xi Wang", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Jing Pu", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Kaili Ma", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Chen Chen", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Weiguo Duan", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Dong Shen", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Hongling Zhao", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Ruiju Jiang", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Xinqiang Deng", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Yan Li", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Hailian Zhu", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Jian Zhou", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Li Yu", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Mingjue Xu", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Huijuan Yang", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Li Yi", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Zhenxin Zhou", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Jiafang Yang", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Nan Duan", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Huan Yang", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Wangli Zhao", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Wei Yang", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Changgui Li", + "author_inst": "National Institute of Food and Drug Control, China" + }, + { + "author_name": "Longding Liu", + "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences, China" + }, + { + "author_name": "Qihan Li", + "author_inst": "Institute of Medical Biology, CAMS" } ], "version": "1", @@ -1242198,169 +1243258,141 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.30.20165373", - "rel_title": "Comparison of sixteen serological SARS-CoV-2 immunoassays in sixteen clinical laboratories", + "rel_doi": "10.1101/2020.07.30.20165241", + "rel_title": "Temporal and Spatial Heterogeneity of Host Response to SARS-CoV-2 Pulmonary Infection", "rel_date": "2020-08-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.30.20165373", - "rel_abs": "Serological SARS-CoV-2 assays are needed to support clinical diagnosis and epidemiological investigations. Recently, assays for the large-volume detection of total antibodies (Ab) and immunoglobulin (Ig) G and M against SARS-CoV-2 antigens have been developed, but there are limited data on the diagnostic accuracy of these assays. This study was organized as a Danish national collaboration and included fifteencommercial and one in-house anti-SARS-CoV-2 assays in sixteen laboratories. Sensitivity was evaluated using 150 serum samples from individuals diagnosed with asymptomatic,mild or moderate nonhospitalized (n=129) or hospitalized (n=31) COVID-19, confirmed bynucleic acid amplification tests, collected 13-73 days from symptom onset. Specificity and cross-reactivity were evaluated in samples collected prior to the SARS-CoV-2 epidemic from > 586 blood donors and patients with autoimmune diseases or CMV or EBV infections. Predefined specificity criteria of [≥] 99% were met by all total-Ab and IgG assays except one (Diasorin/LiaisonXL-IgG 97.2%). The sensitivities in descending order were: Wantai/ELISA total-Ab (96.7%), CUH/NOVO in-house ELISA total-Ab (96.0%), Ortho/Vitros total-Ab (95.3%), YHLO/iFlash-IgG (94.0%), Ortho/Vitros-IgG (93.3%), Siemens/Atellica total-Ab (93.2%), Roche-Elecsys total-Ab (92.7%), Abbott-Architect-IgG (90.0%), Abbott/Alinity-IgG (median 88.0%), Diasorin/LiaisonXL-IgG (84.6%),Siemens/Vista total-Ab (81.0%), Euroimmun/ELISA-IgG (78.0%), and Snibe/Maglumi-IgG (median 78.0%). The IgM results were variable, but one assay (Wantai/ELISA-IgM) hadboth high sensitivity (82.7%) and specificity (99%). The rate of seropositivity increased with time from symptom onset and symptom severity. In conclusion, predefined sensitivity and specificity acceptance criteria of 90%/99%, respectively, for diagnostic use were met in five of six total-Ab and three of seven IgG assays.", - "rel_num_authors": 38, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.30.20165241", + "rel_abs": "The relationship of SARS-CoV-2 lung infection and severity of pulmonary disease is not fully understood. We analyzed autopsy specimens from 24 patients who succumbed to SARS-CoV-2 infection using a combination of different RNA and protein analytical platforms to characterize inter- and intra-patient heterogeneity of pulmonary virus infection. There was a spectrum of high and low virus cases that was associated with duration of disease and activation of interferon pathway genes. Using a digital spatial profiling platform, the virus corresponded to distinct spatial expression of interferon response genes and immune checkpoint genes demonstrating the intra-pulmonary heterogeneity of SARS-CoV-2 infection.", + "rel_num_authors": 31, "rel_authors": [ { - "author_name": "Lene Holm Harritshoej", - "author_inst": "Copenhagen University Hospital, Rigshospitalet" - }, - { - "author_name": "Mikkel Gybel-Brask", - "author_inst": "Copenhagen University Hospital, Rigshospitalet" - }, - { - "author_name": "Shoaib Afzal", - "author_inst": "Copenhagen University Hospital, Herlev and Gentofte Hospital" - }, - { - "author_name": "Pia R. Kamstrup", - "author_inst": "Copenhagen University Hospital, Herlev and Gentofte Hospital" - }, - { - "author_name": "Charlotte Svaerke Joergensen", - "author_inst": "Statens Serum Institut" - }, - { - "author_name": "Marianne K. Thomsen", - "author_inst": "Aarhus University Hospital" - }, - { - "author_name": "Linda M. Hilsted", - "author_inst": "Copenhagen University Hospital, Rigshospitalet" - }, - { - "author_name": "Lennart J. Friis-Hansen", - "author_inst": "Copenhagen University Hospital, Bispebjerg and Frederiksberg Hospital" + "author_name": "Niyati Desai", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Pal B. Szecsi", - "author_inst": "Holbaek Hospital" + "author_name": "Azfar Neyaz", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Lise Pedersen", - "author_inst": "Holbaek Hospital" + "author_name": "Annamaria Szabolcs", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Lene Nielsen", - "author_inst": "Copenhagen University Hospital, Herlev and Gentofte Hospital" + "author_name": "Angela R Shih", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Cecilie B. Hansen", - "author_inst": "Copenhagen University Hospital, Rigshospitalet" + "author_name": "Jonathan H Chen", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Peter Garred", - "author_inst": "Copenhagen University Hospital, Rigshospitalet" + "author_name": "Vishal Thapar", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Trine-Line Korsholm", - "author_inst": "Aarhus University Hospital" + "author_name": "Linda T Nieman", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Susan Mikkelsen", - "author_inst": "Aarhus University Hospital" + "author_name": "Alexander Solovyov", + "author_inst": "Memorial Sloan Kettering Cancer Center" }, { - "author_name": "Kirstine O. Nielsen", - "author_inst": "Aarhus University Hospital" + "author_name": "Arnav Mehta", + "author_inst": "Massachusetts General Hospital, The Broad Institute" }, { - "author_name": "Bjarne K. Moeller", - "author_inst": "Aarhus University Hospital" + "author_name": "David J Lieb", + "author_inst": "The Broad Institute" }, { - "author_name": "Anne T. Hansen", - "author_inst": "Copenhagen University Hospital, Rigshospitalet" + "author_name": "Anupriya S Kulkarni", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Kasper K. Iversen", - "author_inst": "Herlev og Gentofte Hospital, University of Copenhagen" + "author_name": "Christopher Jaicks", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Pernille B. Nielsen", - "author_inst": "Herlev og Gentofte Hospital, University of Copenhagen" + "author_name": "Christopher J Pinto", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Rasmus B. Hasselbalch", - "author_inst": "Herlev og Gentofte Hospital, University of Copenhagen" + "author_name": "Dejan Juric", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Kamille Fogh", - "author_inst": "Herlev og Gentofte Hospital, University of Copenhagen" + "author_name": "Ivan Chebib", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Jakob B. Norsk", - "author_inst": "Herlev og Gentofte Hospital, University of Copenhagen" + "author_name": "Robert B Colvin", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Jonas H. Kristensen", - "author_inst": "Herlev og Gentofte Hospital, University of Copenhagen" + "author_name": "Arthur Y Kim", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Kristian Schoenning", - "author_inst": "Copenhagen University Hospital, Rigshospitalet" + "author_name": "Robert Monroe", + "author_inst": "Advanced Cell Diagnostics" }, { - "author_name": "Nikolai S. Kirkby", - "author_inst": "Copenhagen University Hospital, Rigshospitalet" + "author_name": "Sarah E Warren", + "author_inst": "NanoString Inc." }, { - "author_name": "Alex C.Y. Nielsen", - "author_inst": "Copenhagen University Hospital, Rigshospitalet" + "author_name": "Patrick Danaher", + "author_inst": "NanoString Inc." }, { - "author_name": "Lone H. Landsy", - "author_inst": "Novo Nordisk A/S" + "author_name": "Jason W Reeves", + "author_inst": "NanoString Inc." }, { - "author_name": "Mette Loftager", - "author_inst": "Novo Nordisk A/S" + "author_name": "Jingjing Gong", + "author_inst": "NanoString Inc." }, { - "author_name": "Dorte K. Holm", - "author_inst": "Odense University Hospital" + "author_name": "Erroll H Rueckert", + "author_inst": "NanoString Inc." }, { - "author_name": "Anna C. Nilsson", - "author_inst": "Odense University Hospital" + "author_name": "Benjamin D Greenbaum", + "author_inst": "Memorial Sloan Kettering Cancer Center" }, { - "author_name": "Susanne G. Saekmose", - "author_inst": "Zealand University Hospital, Naestved Hospital" + "author_name": "Nir Hacohen", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Birgitte Grum-Svendsen", - "author_inst": "Zealand University Hospital, Naestved Hospital" + "author_name": "Stephen M Lagana", + "author_inst": "Columbia University Irving Medical Center" }, { - "author_name": "Bitten Aagaard", - "author_inst": "Aalborg University Hospital" + "author_name": "Miguel N Rivera", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Thoeger G. Jensen", - "author_inst": "Odense University Hospital" + "author_name": "Lynette M Sholl", + "author_inst": "Brigham and Woman's Hospital" }, { - "author_name": "Dorte M. Nielsen", - "author_inst": "Zealand University Hospital, Slagelse Hospital" + "author_name": "James R Stone", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Henrik Ullum", - "author_inst": "Copenhagen University Hospital, Rigshospitalet" + "author_name": "David T Ting", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Ram BC Dessau", - "author_inst": "Zealand University Hospital, Slagelse Hospital" + "author_name": "Vikram Deshpande", + "author_inst": "Massachusetts General Hospital" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1243916,75 +1244948,155 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.29.20164566", - "rel_title": "Forecasting COVID-19: Using SEIR-D quantitative modelling for healthcare demand and capacity", + "rel_doi": "10.1101/2020.07.29.20163907", + "rel_title": "Adjusting to Disrupted Assessments, Placements and Teaching (ADAPT): a snapshot of the early response by UK medical schools to COVID-19", "rel_date": "2020-08-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.29.20164566", - "rel_abs": "BackgroundThe world is at the cusp of experiencing local/regional hot-spots and spikes of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19 disease. We aimed to formulate an applicable epidemiological model to accurately predict and forecast the impact of local resurgence and outbreaks to guide the local healthcare demand and capacity, policy making, and public health decisions.\n\nMethodsThe model utilised the aggregated daily COVID-19 situation reports (including counts of daily admissions, discharges, and occupancy) from the local NHS hospitals and Covid-19 related weekly deaths in hospitals and other settings in Sussex (population 1-7M), Southeast England. These datasets corresponded to the first wave of COVID-19 infections from 24 March-15 June 2020. The counts of death registrations and regional population estimates were obtained from the Office of National Statistics. A novel epidemiological predictive and forecasting model was then derived based on the local/regional surveillance data. Through a rigorous inverse parameter inference approach, the model parameters were estimated by fitting the model to the data in an optimal sense and then subsequently validated to make predictions subject to 95% confidence.\n\nFindingsThe inferred parameters were physically reasonable and matched up to the widely used parameter values derived from the national datasets. Unlike other predictive models, which are restricted to a couple of days, our model can predict local hospital admissions, discharges (including deaths) and occupancy for the next 10, 20, and 30 days at the local level.\n\nInterpretationWe have demonstrated that by using local/regional data, our predictive and forecasting model can be utilised to guide the local healthcare demand and capacity, policy making, and public health decisions to mitigate the impact of COVID-19 on the local population. Understanding how future COVID-19 spikes/waves could possibly affect the regional populations empowers us to ensure the timely commissioning and organisation of services. Primary care and community services can be guided by the projected number of infectious and recovered patients and hospital admissions/discharges to project discharge pathways to bedded and community settings, thus allowing services to understand their likely load in future spikes/waves. The flexibility of timings in the model, in combination with other early warning systems, produces a timeframe for these services to prepare and isolate capacity for likely and potential demand within regional hospitals. The model also allows local authorities to plan potential mortuary capacity and understand the burden on crematoria and burial services. The model algorithms have been integrated into a web-based multi-institutional toolkit, which can be used by NHS hospitals, local authorities, and public health departments in other regions of the UK and elsewhere. The parameters, which are locally informed, form the basis of predicting and forecasting exercises accounting for different scenarios and impact of COVID-19 transmission.\n\nFundingThis study was supported by the Higher Education Innovation Fund through the University of Sussex (ECF, JVY, AMa). This work was partly supported by the Global Challenges Research Fund through the Engineering and Physical Sciences Research Council grant number EP/T00410X/1: UK-Africa Postgraduate Advanced Study Institute in Mathematical Sciences (AMa, ECF). ECF is supported by the Wellcome Trust grant number 204833/Z/16/Z.\n\nResearch in context Evidence before this studySince the beginning of the COVID-19 pandemic, healthcare managers and policy makers relied on epidemiological models based on national datasets to predict and mitigate the spread of the disease. The performance of these models has not always been validated against the available data, and they depend strongly on the values for the model parameters. Statistical models, e.g. those arising from time-series analysis, lack the temporal dynamics of the compartmentalised epidemiological model for the evolution of the disease and thus fail to capture the evolution far into the future with great accuracy. Compartmental models, on the other hand, capture the underlying dynamics of an infectious disease but typically use parameters estimated using datasets from other regions or countries, thus lacking the ability to capture local demographics and policy and therefore lack predicting local dynamics with accuracy.\n\nAdded value of this studyAlthough our compartmental model follows standard SEIR-D model structure, the inference algorithm described and applied in this report is novel, along with the prediction technique used to validate the model. We checked bioRxiv, medRxiv, and arXiv up to the end of August 2020 using the terms \"mathematical inference\", \"COVID-19\", and \"SIR\" and found that there is a substantial use of Bayesian approaches to fit parameters but none that use the combination of statistical approaches with compartmental models, hence the originality of our work. We designed a compartmentalised epidemiological model that captures the basic dynamics of the COVID-19 pandemic and revolves around the data that are available at the local/regional level. We estimated all the parameters in the model using the local surveillance data, and in consequence, our parameters reflect the characteristics of the local population. Furthermore, we validated the predictive power of the model by using only a subset of the available data to fit the parameters. To the best of our knowledge, this is the first study which combines statistical approaches with a compartmental model and as such benefits greatly from the ability to predict and forecast much further into the future using the dynamical structure of the compartmental model with a relatively much higher accuracy than previously presented in the literature. This research sets the gold-standard benchmark by laying the framework for future adaptations to the model when more precise (and comprehensive) datasets are made available.\n\nImplications of all the available evidenceThe predictive power of our model outperforms previously available models for local forecasting of the impact of COVID-19. Using local models, rather than trying to use national models at a local scale, ensures that the model reflects the local demographics and provides reliable local-data-driven predictions to guide the local healthcare demand and capacity, policy making, and public health decisions to mitigate the impact of COVID-19 on the local population. Local authorities can use these results for the planning of local hospital demand as well as death management services by developing scenario-based analysis to which different values of the reproduction number R exiting a COVID-19 lockdown are assumed and results, such as maximum hospital occupancy, are compared to the first wave to establish a potential strain on resources. This can work as an early warning detection system to see what value of R that is currently followed, which in turn informs the relevant capacity and resources needed to mitigate the impact of COVID-19. The Web toolkit developed by us as a result of this study (https://alpha.halogen-health.org) demonstrates the predictive power of our model as well as its flexibility with the scenario-based analysis. Although our model is based on the data from Sussex, using similar variables/data from other regions in our model would derive respective COVID-19 model parameters, and thus enable similar scenario-based investigations to predict and forecast the impact of local resurgence to guide the local healthcare demand and capacity, policy making, and public health decisions.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.29.20163907", + "rel_abs": "BackgroundMedical school assessments, clinical placements and teaching have been disrupted by the COVID-19 pandemic. The ADAPT consortium was formed to document and analyse the effects of the pandemic on medical education in the United Kingdom (UK), with the aim of capturing current and future snapshots of disruption to inform trends in the future performance of cohorts graduating during COVID-19.\n\nMethodsMembers of the consortium were recruited from various national medical student groups to ensure representation from medical schools across the UK. The groups involved were: Faculty of Medical Leadership and Management Medical Students Group (FMLM MSG); Neurology and Neurosurgery Interest Group (NANSIG); Doctors Association UK (DAUK); Royal Society of Medicine (RSM) Student Members Group and Medical Student Investigators Collaborative (MSICo.org). In total, 29 medical schools are represented by the consortium. Our members reported teaching postponement, examination status, alternative teaching provision, elective status and UK Foundation Programme Office (UKFPO) educational performance measure (EPM) ranking criteria relevant to their medical school during a data collection window (1st April 14:00 to 2nd April 23:59).\n\nResultsAll 29 medical schools began postponement of teaching between the 11th and 17th of March 2020. Changes to assessments were highly variable. Final year examinations had largely been completed before the onset of COVID-19. Of 226 exam sittings between Year 1 and Year 4 across 29 schools: 93 (41%) were cancelled completely; 14 (6%) had elements cancelled; 57 (25%) moved their exam sitting online. 23 exam sittings (10%) were postponed to a future date. 36% of cohorts with cancelled exams and 74% of cohorts with online exams were granted automatic progression to the next academic year. There exist 19 cohorts at 9 medical schools where all examinations (written and practical) were initially cancelled and automatic progression was granted.\n\nConclusionsThe approaches taken by medical schools have differed substantially, though there has been universal disruption to teaching and assessments. The data presented in this study represent initial responses, which are likely to evolve over time. In particular, the status of future elective cancellations and UK Foundation Programme Office (UKFPO) educational performance measure (EPM) decile calculations remains unclear. The long-term implications of the heterogeneous disruption to medical education remains an area of active research. Differences in specialty recruitment and performance on future postgraduate examinations may be affected and will be a focus of future phases of the ADAPT Study.", + "rel_num_authors": 34, "rel_authors": [ { - "author_name": "Eduard Campillo-Funollet", - "author_inst": "University of Sussex" + "author_name": "Anmol Arora", + "author_inst": "University of Cambridge" }, { - "author_name": "James Van Yperen", - "author_inst": "University of Sussex" + "author_name": "Georgios Solomou", + "author_inst": "Keele University" }, { - "author_name": "Phil Allman", - "author_inst": "NHS Sussex Commissioners" + "author_name": "Soham Bandyopadhyay", + "author_inst": "University of Oxford" }, { - "author_name": "Michael Bell", - "author_inst": "Brighton and Hove City Council" + "author_name": "Julia Simons", + "author_inst": "University of Cambridge" }, { - "author_name": "Warren Beresford", - "author_inst": "NHS Sussex Commissioneers" + "author_name": "Alex Osborne", + "author_inst": "University of Sheffield" }, { - "author_name": "Jacqueline Clay", - "author_inst": "West Sussex County Council" + "author_name": "Ioannis Georgiou", + "author_inst": "University of Aberdeen" }, { - "author_name": "Matthew Dorey", - "author_inst": "West Sussex County Council" + "author_name": "Catherine Dominic", + "author_inst": "Barts and the London School of Medicine and Dentistry" }, { - "author_name": "Graham Evans", - "author_inst": "East Sussex County Council" + "author_name": "Shumail Mahmood", + "author_inst": "University of Birmingham" }, { - "author_name": "Kate Gilchrist", - "author_inst": "Brighton and Hove City Council" + "author_name": "Shreya Badhrinarayanan", + "author_inst": "Brighton and Sussex Medical School" }, { - "author_name": "Pannu Gurprit", - "author_inst": "East Sussex Health Care Trust" + "author_name": "Syed Rayyan Ahmed", + "author_inst": "University of Bristol" }, { - "author_name": "Anjum Memon", - "author_inst": "Brighton and Sussex Medical School" + "author_name": "Jack Wellington", + "author_inst": "Cardiff University" + }, + { + "author_name": "Omar Kouli", + "author_inst": "University of Dundee" + }, + { + "author_name": "Robin Jacob Borchert", + "author_inst": "University of Edinburgh" }, { - "author_name": "Ryan Walkley", - "author_inst": "West Sussex County Council" + "author_name": "Joshua Feyi-Waboso", + "author_inst": "University of Exeter" + }, + { + "author_name": "Scott Dickson", + "author_inst": "University of Glasgow" + }, + { + "author_name": "Savraj Kalsi", + "author_inst": "Hull-York Medical School" }, { - "author_name": "Mark Watson", - "author_inst": "Sussex Health and Care Partnership" + "author_name": "Dimitrios Karponis", + "author_inst": "Imperial College London" + }, + { + "author_name": "Tim Boardman", + "author_inst": "King's College London" }, { - "author_name": "Anotida Madzvamuse", - "author_inst": "Universtiy of Sussex" + "author_name": "Harmani Daler", + "author_inst": "Lancaster University" + }, + { + "author_name": "Abbey Boyle", + "author_inst": "University of Leeds" + }, + { + "author_name": "Jessica Speller", + "author_inst": "Leicester Medical School" + }, + { + "author_name": "Connor S Gillespie", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Jie Man Low", + "author_inst": "University of Manchester" + }, + { + "author_name": "Ratnaraj Vaidya", + "author_inst": "Newcastle University" + }, + { + "author_name": "Ngan Hong Ta", + "author_inst": "Norwich Medical School" + }, + { + "author_name": "Steven Aldridge", + "author_inst": "University of Nottingham" + }, + { + "author_name": "Jonathan Coll Martin", + "author_inst": "University of Oxford" + }, + { + "author_name": "Natasha Douglas", + "author_inst": "Queen's University Belfast" + }, + { + "author_name": "Mary Goble", + "author_inst": "University of Sheffield" + }, + { + "author_name": "Tayyib Abdel-Hafiz Goolamallee", + "author_inst": "University of Southampton" + }, + { + "author_name": "Emma Jane Norton", + "author_inst": "St George's, University of London" + }, + { + "author_name": "Andre Chu", + "author_inst": "University of Central Lancashire" + }, + { + "author_name": "Inshal Imtiaz", + "author_inst": "University College London" + }, + { + "author_name": "Oliver Patrick Devine", + "author_inst": "University College London" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "medical education" }, { "rel_doi": "10.1101/2020.07.31.231746", @@ -1245650,51 +1246762,71 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.07.31.231274", - "rel_title": "Force-dependent stimulation of RNA unwinding by SARS-CoV-2 nsp13 helicase", + "rel_doi": "10.1101/2020.07.31.228486", + "rel_title": "SARS-CoV-2 protein subunit vaccination elicits potent neutralizing antibody responses", "rel_date": "2020-07-31", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.31.231274", - "rel_abs": "The superfamily-1 helicase non-structural protein 13 (nsp13) is required for SARS-CoV-2 replication, making it an important antiviral therapeutic target. The mechanism and regulation of nsp13 has not been explored at the single-molecule level. Specifically, force-dependent unwinding experiments have yet to be performed for any coronavirus helicase. Here, using optical tweezers, we find that nsp13 unwinding frequency, processivity, and velocity increase substantially when a destabilizing force is applied to the dsRNA, suggesting a passive unwinding mechanism. These results, along with bulk assays, depict nsp13 as an intrinsically weak helicase that can be potently activated by picoNewton forces. Such force-dependent behavior contrasts the known behavior of other viral monomeric helicases, drawing stronger parallels to ring-shaped helicases. Our findings suggest that mechanoregulation, which may be provided by a directly bound RNA-dependent RNA polymerase, enables on-demand helicase activity on the relevant polynucleotide substrate during viral replication.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.31.228486", + "rel_abs": "The outbreak and spread of SARS-CoV-2 (Severe Acute Respiratory Syndrome coronavirus 2), the cause of coronavirus disease 2019 (COVID-19), is a current global health emergency and a prophylactic vaccine is needed urgently. The spike glycoprotein of SARS-CoV-2 mediates entry into host cells, and thus is a target for neutralizing antibodies and vaccine design. Here we show that adjuvanted protein immunization with SARS-CoV-2 spike trimers, stabilized in prefusion conformation 1, results in potent antibody responses in mice and rhesus macaques with neutralizing antibody titers orders of magnitude greater than those typically measured in serum from SARS-CoV-2 seropositive humans. Neutralizing antibody responses were observed after a single dose, with exceptionally high titers achieved after boosting. Furthermore, neutralizing antibody titers elicited by a dose-sparing regimen in mice were similar to those obtained from a high dose regimen. Taken together, these data strongly support the development of adjuvanted SARS-CoV-2 prefusion-stabilized spike protein subunit vaccines.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Keith J Mickolajczyk", - "author_inst": "The Rockefeller University" + "author_name": "Marco Mandolesi", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Patrick M M Shelton", - "author_inst": "The Rockefeller University" + "author_name": "Daniel J Sheward", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Michael Grasso", - "author_inst": "The Rockefeller University" + "author_name": "Leo Hanke", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Xiaocong Cao", - "author_inst": "The Rockefeller University" + "author_name": "Junjie Ma", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Sara R Warrington", - "author_inst": "The Rockefeller University" + "author_name": "Pradeepa Pushparaj", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Amol Aher", - "author_inst": "The Rockefeller University" + "author_name": "Laura Perez Vidakovics", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Shixin Liu", - "author_inst": "The Rockefeller University" + "author_name": "Changil Kim", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Tarun M Kapoor", - "author_inst": "The Rockefeller University" + "author_name": "Karin Lor\u00e9", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Xaquin Castro Dopico", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Jonathan M Coquet", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Gerald McInerney", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Gunilla B Karlsson Hedestam", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Ben Murrell", + "author_inst": "Karolinska Institutet" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "new results", - "category": "biophysics" + "category": "immunology" }, { "rel_doi": "10.1101/2020.07.31.231472", @@ -1247232,141 +1248364,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.28.20164038", - "rel_title": "Initial evaluation of a mobile SARS-CoV-2 RT-LAMP testing strategy", + "rel_doi": "10.1101/2020.07.28.20164004", + "rel_title": "SARS-CoV-2 detection with de novo designed synthetic riboregulators", "rel_date": "2020-07-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.28.20164038", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) control in the United States remains hampered, in part, by testing limitations. We evaluated a simple, outdoor, mobile, colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay workflow where self-collected saliva is tested for SARS-CoV-2 RNA. From July 16 to November 19, 2020, 4,704 surveillance samples were collected from volunteers and tested for SARS-CoV-2 at 5 sites. A total of 21 samples tested positive for SARS-CoV-2 by RT-LAMP; 12 were confirmed positive by subsequent quantitative reverse-transcription polymerase chain reaction (qRT-PCR) testing, while 8 were negative for SARS-CoV-2 RNA, and 1 could not be confirmed because the donor did not consent to further molecular testing. We estimated the RT-LAMP assays false-negative rate from July 16 to September 17, 2020 by pooling residual heat-inactivated saliva that was unambiguously negative by RT-LAMP into groups of 6 or less and testing for SARS-CoV-2 RNA by qRT-PCR. We observed a 98.8% concordance between the RT-LAMP and qRT-PCR assays, with only 5 of 421 RT-LAMP negative pools (2,493 samples) testing positive in the more sensitive qRT-PCR assay. Overall, we demonstrate a rapid testing method that can be implemented outside the traditional laboratory setting by individuals with basic molecular biology skills and can effectively identify asymptomatic individuals who would not typically meet the criteria for symptom-based testing modalities.", - "rel_num_authors": 31, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.28.20164004", + "rel_abs": "Sars-CoV-2 is a human pathogen and is the main cause of COVID-19 disease. COVID-19 is announced as a global pandemic by World Health Organization. COVID-19 is characterized by severe conditions and early diagnosis can make dramatic changes both for personal and public health. In order to increase the reach for low cost equipment which requires a very limited technical knowledge can be beneficial to diagnose the viral infection. Such diagnostic capabilities can have a very critical role to control the transmission of the disease. Here we are reporting a state-of-the-art diagnostic tool developed by using an in vitro synthetic biology approach by employing engineered de novo riboregulators. Our design coupled with a home-made point-of-care device setting can detect and report presence of Sars-CoV-2 specific genes. The presence of Sars-CoV-2 related genes triggers translation of sfGFP mRNAs, resulting in green fluorescence output. The approach proposed here has the potential of being a game changer in Sars-COV-2 diagnostics by providing an easy-to-run, low-cost-demanding diagnostic capability.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Christina M Newman", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Mitchell D Ramuta", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Matthew T McLaughlin", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Roger W Wiseman", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Julie A Karl", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Dawn M Dudley", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Miranda R Stauss", - "author_inst": "Wisconsin National Primate Research Center" - }, - { - "author_name": "Robert J. Maddox", - "author_inst": "Wisconsin National Primate Research Center" - }, - { - "author_name": "Andrea M Weiler", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Mason I Bliss", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Katrina N Fauser", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Luis A. Haddock III", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Cecilia G Shortreed", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Amelia K Haj", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Molly A. Accola", - "author_inst": "University of Wisconsin Hospitals and Clinics" - }, - { - "author_name": "Anna S Heffron", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Hailey E. Bussan", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Matthew R Reynolds", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Olivia E. Harwood", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Ryan V. Moriarty", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Laurel M. Stewart", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Chelsea M. Crooks", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Trent M. Prall", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Emma K. Neumann", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Ilkay Cisil Koksaldi", + "author_inst": "Bilkent University UNAM" }, { - "author_name": "Elizabeth D. Somsen", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Recep Erdem Ahan", + "author_inst": "Bilkent University" }, { - "author_name": "Corrie B Burmeister", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Sila Kose", + "author_inst": "Bilkent University" }, { - "author_name": "Kristi L Hall", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Nedim Haciosmanoglu", + "author_inst": "Bilkent University UNAM" }, { - "author_name": "William M. Rehrauer", - "author_inst": "University of Wisconsin Hospitals and Clinics" + "author_name": "Ebru Sahin Kehribar", + "author_inst": "Bilkent University" }, { - "author_name": "Thomas C Friedrich", - "author_inst": "University of Wisconsin Madison" + "author_name": "Murat Alp Gungen", + "author_inst": "Bilkent University" }, { - "author_name": "Shelby L O'Connor", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Aykut Ozkul", + "author_inst": "Ankara University" }, { - "author_name": "David H O'Connor", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Urartu Ozgur Safak Seker", + "author_inst": "Bilkent University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1249010,63 +1250050,63 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.07.28.20164012", - "rel_title": "A meta-review of systematic reviews and an updated meta-analysis on the efficacy of chloroquine and hydroxychloroquine in treating COVID19 infection", + "rel_doi": "10.1101/2020.07.30.228643", + "rel_title": "Perception of and anxiety about COVID-19 infection and risk behaviors for spreading infection: An international comparison", "rel_date": "2020-07-30", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.28.20164012", - "rel_abs": "ObjectiveTo synthesize findings from systematic reviews and meta-analyses on the efficacy and safety of chloroquine (CQ) and hydroxychloroquine (HCQ) with or without Azithromycin for treating COVID-19, and to update the evidence using a meta-analysis.\n\nMethodsA comprehensive search was carried out in electronic databases for systematic reviews, meta-analyses and experimental studies which investigated the efficacy and safety of CQ, HCQ with or without Azithromycin to treat COVID-19. Findings from the reviews were synthesised using tables and forest plots and the quality effect model was used for the updated meta-analysis. The main outcomes were mortality, the need for intensive care services, disease exacerbation, viral clearance and occurrence of adverse events.\n\nResultsThirteen reviews with 40 primary studies were included. Two meta-analyses reported a high risk of mortality, with ORs of 2.2 and 3.0, and the two others found no association between HCQ and mortality. Findings from two meta-analyses showed that HCQ with Azithromycin increased the risk of mortality, with similar ORs of 2.5. The updated meta-analysis of experimental studies showed that the drugs were not effective in reducing mortality (RR 1.1, 95%CI 1.0-1.3, I2 =0.0%), need for intensive care services (OR 1.1, 95%CI 0.9-1.4, I2 =0.0%), virological cure (OR 1.5, 95%CI 0.5-4.4, I2 =39.6%) or disease exacerbation (OR 1.2, 95%CI 0.3-5.9, I2 =31.9%) but increased the odds of adverse events (OR 12,3, 95%CI 2.5-59.9, I2 =76.6%).\n\nConclusionThere is conclusive evidence that CQ and HCQ, with or without Azithromycin are not effective in treating COVID-19 or its exacerbation.\n\nRegistrationPROSPERO: CRD42020191353", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.30.228643", + "rel_abs": "To control the spread of the newly developed corona viral infection diseases (COVID-19), peoples appropriate precautionary behaviors should be promoted. We conducted a series of online questionnaire survey, to gather a total of 8,000 citizens responses on March 27-28, 2020 in Japan and April 17-21 in the UK and Spain. Compared to Japan, the knowledge and anxiety level and the frequency of precautionary behaviors were higher in the UK and Spain. Participants with infected acquaintances were more concerned about COVID-19. However, participants in the UK rarely wore a medical mask. Participants in the UK and Spain were eager to get information about COVID-19 compared to those in Japan. The participants in Spain tended not to trust official information and to believe specialists' comments instead. The urgency of the spread of COVID-19, cultural backgrounds, and recent political situations appear to contribute to the differences among countries revealed herein.", "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Tawanda Chivese", - "author_inst": "Qatar University" + "author_name": "Akihiro Shiina", + "author_inst": "Chiba University Center for Forensic Mental Health" }, { - "author_name": "Omran A.H. Musa", - "author_inst": "Collge of Medicine, Qatar University" + "author_name": "Tomihisa Niitsu", + "author_inst": "Chiba Daigaku Daigakuin Igaku Kenkyuin Igakubu" }, { - "author_name": "George Hindy", - "author_inst": "Collge of Medicine, Qatar University" + "author_name": "Osamu Kobori", + "author_inst": "Kokusai Iryo Fukushi Daigaku - Tokyo Akasaka Campus" }, { - "author_name": "Noor Wattary", - "author_inst": "Collge of Medicine, Qatar University" + "author_name": "Keita Idemoto", + "author_inst": "Chiba Daigaku Daigakuin Igaku Kenkyuin Igakubu" }, { - "author_name": "Saif Badran", - "author_inst": "Collge of Medicine, Qatar University" + "author_name": "Tasuku Hashimoto", + "author_inst": "Kokusai Iryo Fukushi Daigaku - Narita Campus" }, { - "author_name": "Nada Soliman", - "author_inst": "Collge of Medicine, Qatar University" + "author_name": "Tsuyoshi Sasaki", + "author_inst": "Chiba Daigaku Daigakuin Igaku Kenkyuin Igakubu" }, { - "author_name": "Ahmed TM Aboughalia", - "author_inst": "Collge of Medicine, Qatar University" + "author_name": "Yoshito Igarashi", + "author_inst": "Chiba University Center for Forensic Mental Health" }, { - "author_name": "Joshua T Matizanadzo", - "author_inst": "Brighton and Sussex Medical School, United Kingdom" + "author_name": "Eiji Shimizu", + "author_inst": "Chiba Daigaku Daigakuin Igaku Kenkyuin Igakubu" }, { - "author_name": "Mohamed M Emara", - "author_inst": "Basic Medical Sciences Department, College of Medicine, QU Health, Qatar University, Doha, Qatar" + "author_name": "Michiko Nakazato", + "author_inst": "Kokusai Iryo Fukushi Daigaku - Narita Campus" }, { - "author_name": "Lukman Thalib", - "author_inst": "Collge of Public Health, Qatar University" + "author_name": "Kenji Hashimoto", + "author_inst": "Chiba University Center for Forensic Mental Health" }, { - "author_name": "Suhail Doi", - "author_inst": "Collge of Medicine, Qatar University" + "author_name": "Masaomi Iyo", + "author_inst": "Chiba Daigaku Daigakuin Igaku Kenkyuin Igakubu" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_by", + "type": "new results", + "category": "scientific communication and education" }, { "rel_doi": "10.1101/2020.07.17.20156463", @@ -1250584,29 +1251624,41 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.27.20163063", - "rel_title": "A novel predictive mathematical model for COVID-19 pandemic with quarantine, contagion dynamics, and environmentally mediated transmission", + "rel_doi": "10.1101/2020.07.16.20127357", + "rel_title": "Contact tracing during Phase I of the COVID-19 pandemic in the Province of Trento, Italy: key findings and recommendations", "rel_date": "2020-07-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.27.20163063", - "rel_abs": "This work presents an ODE model for COVID-19 named SINDROME that incorporates quarantine, contagion dynamics, and environmentally mediated transmission based on the compartments. The SINDROME model introduces a new parameter that allows environmentally mediated transmission, moving quarantined individuals to the infected compartment. We developed a gray box model with the SINDROME, and fit over 169 regions.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.16.20127357", + "rel_abs": "IntroductionContact tracing is a key pillar of COVID-19 control. In response to the COVID-19 epidemic in the Autonomous Province of Trento (Italy) a software was developed to standardize data collection and facilitate surveillance of contacts and outbreaks and map the links between bases and contacts. In this paper, we present the results of contact tracing efforts during Phase I of the epidemic (March-April, 2020, mostly under lockdown), including sociodemographic characteristics of contacts who became cases and of the cases who infected one or more contact.\n\nMethodsA contact tracing website was developed that included components for geolocation and linking of cases and contacts using open source software. Information on community-based confirmed and probable cases and their contacts was centralized on the website. Information on cases came directly from the central case database, information on contacts was collected by telephone interviews following a standard questionnaire. Contacts were followed via telephone, emails, or an app.\n\nResultsThe 2,812 laboratory-diagnosed community cases of COVID-19 had 6,690 community contacts, of whom 890 (13.3%) developed symptoms. Risk of developing symptomatic disease increased with age and was higher in workplace contacts than cohabitants or non-cohabiting family or friends. The greatest risk of transmission to contacts was found for the 14 cases <15 years of age (22.4%); 8 of the 14, who ranged in age from <1 to 11 years) infected 11 of 49 contacts. Overall, 606 outbreaks were identified, 74% of which consisted of only two cases.\n\nDiscussionThe open-source software program permitted the centralized tracking of contacts and rapid identification of links between cases. Workplace contacts were at higher risk of developing symptoms. Although childhood contacts were less likely to become cases, children were more likely to infect household members, perhaps because of the difficulty of successfully isolating children in household settings.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Diego Carvalho", - "author_inst": "CEFET/RJ" + "author_name": "Pirous Fateh-Moghadam", + "author_inst": "Osservatorio per la salute, Dipartimento salute e politiche sociali, Provincia Autonoma di Trento" + }, + { + "author_name": "Laura Battisti", + "author_inst": "Osservatorio per la salute, Dipartimento salute e politiche sociali, Provincia Autonoma di Trento" }, { - "author_name": "Rafael Barbastefano", - "author_inst": "CEFET/RJ" + "author_name": "Silvia Molinaro", + "author_inst": "Servizio di Igiene pubblica, Dipartimento di Prevenzione, Azienda per i servizi sanitari di Trento" }, { - "author_name": "Dayse Pastore", - "author_inst": "CEFET/RJ" + "author_name": "Steno Fontanari", + "author_inst": "Mpa-solutions" }, { - "author_name": "Maria Clara Lippi", - "author_inst": "CEFET/RJ" + "author_name": "Gabriele Dallago", + "author_inst": "Mpa-solutions" + }, + { + "author_name": "Nancy Binkin", + "author_inst": "Department of Family Medicine and Public Health, School of Medicine, University of California, San Diego, La Jolla, California" + }, + { + "author_name": "Mariagrazia Zuccali", + "author_inst": "Servizio di Igiene pubblica, Dipartimento di Prevenzione, Azienda per i servizi sanitari di Trento" } ], "version": "1", @@ -1252482,79 +1253534,163 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2020.07.28.226092", - "rel_title": "Direct exposure to SARS-CoV-2 and cigarette smoke increases infection severity and alters the stemcell-derived airway repair response", + "rel_doi": "10.1101/2020.07.28.225912", + "rel_title": "Infection of human lymphomononuclear cells by SARS-CoV-2", "rel_date": "2020-07-29", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.28.226092", - "rel_abs": "Most demographic studies are now associating current smoking status with increased risk of severe COVID-19 and mortality from the disease but there remain many questions about how direct cigarette smoke exposure affects SARS-CoV-2 airway cell infection. We directly exposed mucociliary air-liquid interface (ALI) cultures derived from primary human nonsmoker airway basal stem cells (ABSCs) to short term cigarette smoke and infected them with live SARS-CoV-2. We found an increase in the number of infected airway cells after cigarette smoke exposure as well as an increased number of apoptotic cells. Cigarette smoke exposure alone caused airway injury that resulted in an increased number of ABSCs, which proliferate to repair the airway. But we found that acute SARS-CoV-2 infection or the combination of exposure to cigarette smoke and SARS-CoV-2 did not induce ABSC proliferation. We set out to examine the underlying mechanism governing the increased susceptibility of cigarette smoke exposed ALI to SARS-CoV-2 infection. Single cell profiling of the cultures showed that infected airway cells displayed a global reduction in gene expression across all airway cell types. Interestingly, interferon response genes were induced in SARS-CoV-2 infected airway epithelial cells in the ALI cultures but smoking exposure together with SARS-CoV-2 infection reduced the interferon response. Treatment of cigarette smoke-exposed ALI cultures with Interferon {beta}-1 abrogated the viral infection, suggesting that the lack of interferon response in the cigarette smoke-exposed ALI cultures allows for more severe viral infection and cell death. In summary, our data show that acute smoke exposure allows for more severe proximal airway epithelial disease from SARS-CoV-2 by reducing the mucosal innate immune response and ABSC proliferation and has implications for disease spread and severity in people exposed to cigarette smoke.", - "rel_num_authors": 15, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.28.225912", + "rel_abs": "Although SARS-CoV-2 severe infection is associated with a hyperinflammatory state, lymphopenia is an immunological hallmark, and correlates with poor prognosis in COVID-19. However, it remains unknown if circulating human lymphocytes and monocytes are susceptible to SARS-CoV-2 infection. In this study, SARS-CoV-2 infection of human peripheral blood mononuclear cells (PBMCs) was investigated both in vitro and in vivo. We found that in vitro infection of whole PBMCs from healthy donors was productive of virus progeny. Results revealed that monocytes, as well as B and T lymphocytes, are susceptible to SARS-CoV-2 active infection and viral replication was indicated by detection of double-stranded RNA. Moreover, flow cytometry and immunofluorescence analysis revealed that SARS-CoV-2 was frequently detected in monocytes and B lymphocytes from COVID-19 patients, and less frequently in CD4+T lymphocytes. The rates of SARS-CoV-2-infected monocytes in PBMCs from COVID-19 patients increased over time from symptom onset. Additionally, SARS-CoV-2-positive monocytes and B and CD4+T lymphocytes were detected by immunohistochemistry in post mortem lung tissue. SARS-CoV-2 infection of blood circulating leukocytes in COVID-19 patients may have important implications for disease pathogenesis, immune dysfunction, and virus spread within the host.", + "rel_num_authors": 36, "rel_authors": [ { - "author_name": "Arunima Purkayastha", - "author_inst": "University of California, Los Angeles" + "author_name": "Marjorie C Pontelli", + "author_inst": "Virology Research Center, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" }, { - "author_name": "Chandani Sen", - "author_inst": "University of California, Los Angeles" + "author_name": "Italo A Castro", + "author_inst": "Virology Research Center, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" }, { - "author_name": "Gustavo Garcia Jr.", - "author_inst": "University of California, Los Angeles" + "author_name": "Ronaldo B Martins", + "author_inst": "Virology Research Center, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" }, { - "author_name": "Justin Langerman", - "author_inst": "University of California, Los Angeles" + "author_name": "Flavio P Veras", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" }, { - "author_name": "Preethi Vijayaraj", - "author_inst": "University of California, Los Angeles" + "author_name": "Leonardo La Serra", + "author_inst": "Virology Research Center, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" }, { - "author_name": "David W. Shia", - "author_inst": "University of California, Los Angeles" + "author_name": "Daniele C Nascimento", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" }, { - "author_name": "Luisa K. Meneses", - "author_inst": "University of California, Los Angeles" + "author_name": "Ricardo S Cardoso", + "author_inst": "Virology Research Center, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" }, { - "author_name": "Tammy M. Rickabaugh", - "author_inst": "University of California, Los Angeles" + "author_name": "Roberta Rosales", + "author_inst": "Department of Cell and Molecular Biology and Pathogenic Bioagents, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" }, { - "author_name": "Apoorva Mulay", - "author_inst": "Cedars Sinai Medical Center" + "author_name": "Thais M Lima", + "author_inst": "Virology Research Center, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" }, { - "author_name": "Bindu Konda", - "author_inst": "Cedars Sinai Medical Center" + "author_name": "Juliano P Souza", + "author_inst": "Virology Research Center, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" }, { - "author_name": "Myung S. Sim", - "author_inst": "University of California, Los Angeles" + "author_name": "Diego B Caetite", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" }, { - "author_name": "Barry R. Stripp", - "author_inst": "Cedars Sinai Medical Center" + "author_name": "Mikhael HF Lima", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" }, { - "author_name": "Kathrin Plath", - "author_inst": "University of California, Los Angeles" + "author_name": "Juliana T Kawahisa", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" }, { - "author_name": "Vaithilingaraja Arumugaswami", - "author_inst": "University of California, Los Angeles" + "author_name": "Marcela C Giannini", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" }, { - "author_name": "Brigitte N. Gomperts", - "author_inst": "University of California, Los Angeles" + "author_name": "Leticia P Bonjorno", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Maria IF Lopes", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), Divisions of Clinical Immunology; University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Sabrina S Batah", + "author_inst": "Department of Pathology, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Li Siyuan", + "author_inst": "Department of Pathology, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Rodrigo L Assad", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), Divisions of Clinical Immunology, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Sergio CL Almeida", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), Divisions of Clinical Immunology, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Fabiola R Oliveira", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), Divisions of Clinical Immunology, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Maira N Benatti", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), Divisions of Clinical Immunology, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Lorena LF Pontes", + "author_inst": "Blood Center of Ribeirao Preto, Ribeirao Preto, Brazil" + }, + { + "author_name": "Rodrigo C Santana", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), Infectious Diseases, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Fernando C Villar", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), Infectious Diseases, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Maria A Martins", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), Intensive Care Unit, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Thiago M Cunha", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Rodrigo T Calado", + "author_inst": "Blood Center of Ribeirao Preto, Ribeirao Preto, Brazil" + }, + { + "author_name": "Jose C Alves-Filho", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Dario S Zamboni", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), Department of Cell and Molecular Biology and Pathogenic Bioagents, Ribeirao Preto Medical School" + }, + { + "author_name": "Alexandre Fabro", + "author_inst": "Department of Pathology, Ribeirao Preto Medical School University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Paulo Louzada-Junior", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), Divisions of Clinical Immunology, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Paulo Louzada-Junior", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), Divisions of Clinical Immunology, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Rene DR Oliveira", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), Divisions of Clinical Immunology, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Fernando Q Cunha", + "author_inst": "Center of Research in Inflammatory Diseases (CRID), University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Eurico Arruda", + "author_inst": "Virology Research Center, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "cell biology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.07.28.225581", @@ -1254128,33 +1255264,49 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.07.28.224576", - "rel_title": "Rapid host response to an infection with Coronavirus. Study of transcriptional responses with Porcine Epidemic Diarrhea Virus", + "rel_doi": "10.1101/2020.07.27.222562", + "rel_title": "The mutational analysis unveils the distribution of G614 genotype of SARS-CoV-2in different Indian states and its association with case fatality rate of COVID-19", "rel_date": "2020-07-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.28.224576", - "rel_abs": "The transcriptional response in Vero cells (ATCC(R) CCL-81) infected with the coronavirus Porcine Epidemic Diarrhea Virus (PEDV) was measured by RNAseq analysis 4 and 6 hours after infection. Differential expressed genes (DEGs) in PEDV infected cells were compared to DEGs responding in Vero cells infected with Mammalian Orthoreovirus (MRV). Functional analysis of MRV and PEDV DEGs showed that MRV increased the expression level of several cytokines and chemokines (e.g. IL6, CXCL10, IL1A, CXCL8 [alias IL8]) and antiviral genes (e.g. IFI44, IFIT1, MX1, OASL), whereas for PEDV no enhanced expression was observed for these \"hallmark\" antiviral and immune effector genes. Pathway and Gene Ontology \"enrichment analysis\" revealed that PEDV infection did not stimulate expression of genes able to activate an acquired immune response, whereas MRV did so within 6h. Instead, PEDV down-regulated the expression of a set of zinc finger proteins with putative antiviral activity and enhanced the expression of the transmembrane serine protease gene TMPRSS13 (alias MSPL) to support its own infection by virus-cell membrane fusion (Shi et al, 2017, Viruses, 9(5):114). PEDV also down-regulated expression of Ectodysplasin A, a cytokine of the TNF-family able to activate the canonical NFKB-pathway responsible for transcription of inflammatory genes like IL1B, TNF, CXCL8 and PTGS2. The only 2 cytokine genes found up-regulated by PEDV were Cardiotrophin-1, an IL6-type cytokine with pleiotropic functions on different tissues and types of cells, and Endothelin 2, a neuroactive peptide with vasoconstrictive properties. Furthermore, by comprehensive datamining in biological and chemical databases and consulting related literature we identified sets of PEDV-response genes with potential to influence i) the metabolism of biogenic amines (e.g. histamine), ii) the formation of cilia and \"synaptic clefts\" between cells, iii) epithelial mucus production, iv) platelets activation, and v) physiological processes in the body regulated by androgenic hormones (like blood pressure, salt/water balance and energy homeostasis). The information in this study describing a \"very early\" response of epithelial cells to an infection with a coronavirus may provide pharmacologists, immunological and medical specialists additional insights in the underlying mechanisms of coronavirus associated severe clinical symptoms including those induced by SARS-CoV-2. This may help them to fine-tune therapeutic treatments and apply specific approved drugs to treat COVID-19 patients.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.27.222562", + "rel_abs": "Pan genomic analysis of the global SARS-CoV-2 isolates has resulted in the identification of several regions of increased genetic variation but there is absence of research on its association with the clinical outcome. The present study fills the vacuum and does mutational analysis of genomic sequence of Indian SARS-CoV-2 isolates. Results reveal the existence of non-synonymous G614 spike protein mutation in 61.45% of the total study genome along with three other mutations. Further, temporal variation in the frequencies of G614 genotype in the country is observed. The examination of the probable association of G614 genotype with COVID-19 severity shows that CFR G614 genotype in India is positively and strongly correlated. It appears that the clinical outcome of the COVID-19 cases in India are significantly and adversely affected by the increasing trend in the G614 genotype; which needs to be addressed combining both laboratory experiments and epidemiological investigations.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Wei Hou", - "author_inst": "College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China" + "author_name": "Ballamoole Krishna Kumar", + "author_inst": "Nitte (Deemed to be University), Nitte University Centre for Science Education & Research, Mangaluru, Karnataka" }, { - "author_name": "Fei Liu", - "author_inst": "College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China" + "author_name": "Bakilapadavu Venkatraja", + "author_inst": "Department of Economics, Shri Dharmasthala Manjunatheshwara Institute for Management Development (SDMIMD), Mysuru, Karnataka" }, { - "author_name": "Wim H.M. van der Poel", - "author_inst": "Wageningen Bioveterinary Research, Lelystad, the Netherlands" + "author_name": "Kattapuni Suresh Prithvisagar", + "author_inst": "Nitte (Deemed to be University), Nitte University Centre for Science Education and Research, (NUCSER), Mangaluru, Karnataka" }, { - "author_name": "Marcel M Hulst", - "author_inst": "Wageningen Bioveterinary Research" + "author_name": "Praveen Rai", + "author_inst": "Nitte (Deemed to be University), Nitte University Centre for Science Education and Research, (NUCSER)" + }, + { + "author_name": "Anusha Rohit", + "author_inst": "Department of Microbiology, The Madras Medical Mission, Chennai, Tamil Nadu" + }, + { + "author_name": "Madhura Nagesh Hegde", + "author_inst": "Department of Information Science and Engineering, Sahyadri College of Engineering and Management, Mangaluru, Karnataka" + }, + { + "author_name": "Indrani Karunasagar", + "author_inst": "Nitte (Deemed to be University), Nitte University Centre for Science Education and Research, (NUCSER), Mangaluru, India" + }, + { + "author_name": "Iddya Karunasagar", + "author_inst": "Nitte (Deemed to be University), Mangaluru, Karnataka" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "microbiology" }, @@ -1255878,63 +1257030,47 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2020.07.27.190561", - "rel_title": "Antiviral effects of miRNAs in extracellular vesicles against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and mutations in SARS-CoV-2 RNA virus", + "rel_doi": "10.1101/2020.07.26.222026", + "rel_title": "Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Membrane (M) Protein Inhibits Type I and III Interferon Production by Targeting RIG-I/MDA-5 Signaling", "rel_date": "2020-07-27", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.27.190561", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus 2019 (COVID-19). No treatment is available. Micro-RNAs (miRNAs) in mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) are potential novel therapeutic agents because of their ability to regulate gene expression by inhibiting mRNA. Thus, they may degrade the RNA genome of SARS-CoV-2. EVs can transfer miRNAs to recipient cells and regulate conditions within them. MSC-EVs harbor major therapeutic miRNAs that play important roles in the biological functions of virus-infected host cells. Here, we examined their potential impact on viral and immune responses. MSC-EVs contained 18 miRNAs predicted to interact directly with the 3 UTR of SARS-CoV-2. These EVs suppressed SARS-CoV-2 replication in Vero E6 cells. In addition, five major miRNAs suppressed virus activity in a luciferase reporter assay by binding the 3 UTR. MSC-EVs showed strong regenerative effects and potent anti-inflammatory activity which may prevent lethal cytokine storms. We confirmed that EVs regulated inflammatory responses by several cell types, including human brain cells that express the viral receptor ACE2, suggesting that the brain may be targeted by SARS-CoV-2. miRNAs in MSC-EVs have several advantages as therapeutic agents against SARS-CoV-2: 1) they bind specifically to the viral 3 UTR, and are thus unlikely to have side effects; 2) because the 3 UTR is highly conserved and rarely mutates, MSC-EV miRNAs could be used against novel variants arising during viral replication; and 3) unique cargoes carried by MSC-EVs can have diverse effects, such as regenerating damaged tissue and regulating immunity.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.26.222026", + "rel_abs": "The coronavirus disease 2019 (COVID-19) caused by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has quickly spread worldwide and has infected more than ten million individuals. One of the typical features of COVID-19 is that both type I and III interferon (IFN)-mediated antiviral immunity are suppressed. However, the molecular mechanism by which SARS-CoV-2 evades this antiviral immunity remains elusive. Here, we report that the SARS-CoV-2 membrane (M) protein inhibits the production of type I and III IFNs induced by the cytosolic dsRNA-sensing pathway of RIG-I/MDA-5-MAVS signaling. The SARS-CoV2 M protein also dampens type I and III IFN induction stimulated by Sendai virus infection or poly (I:C) transfection. Mechanistically, the SARS-CoV-2 M protein interacts with RIG-I, MAVS, and TBK1 and prevents the formation of a multi-protein complex containing RIG-I, MAVS, TRAF3, and TBK1, thus impeding IRF3 phosphorylation, nuclear translocation, and activation. Consequently, the ectopic expression of the SARS-CoV2 M protein facilitates the replication of vesicular stomatitis virus (VSV). Taken together, the SARS-CoV-2 M protein antagonizes type I and III IFN production by targeting RIG-I/MDA-5 signaling, which subsequently attenuates antiviral immunity and enhances viral replication. This study provides insight into the interpretation of the SARS-CoV-2-induced antiviral immune suppression and sheds light on the pathogenic mechanism of COVID-19.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Jisook Moon", - "author_inst": "CHA University" - }, - { - "author_name": "Jae Hyun Park", - "author_inst": "CHA University" - }, - { - "author_name": "Yuri Choi", - "author_inst": "CHA University" - }, - { - "author_name": "Chul-Woo Lim", - "author_inst": "CHA University" - }, - { - "author_name": "Ji-Min Park", - "author_inst": "CHA University" + "author_name": "Pei-Hui Wang", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Shin-Hye Yu", - "author_inst": "Paean Biotechnology, Inc." + "author_name": "Yi Zheng", + "author_inst": "Shandong University" }, { - "author_name": "Yujin Kim", - "author_inst": "Paean Biotechnology, Inc." + "author_name": "Meng-Wei Zhuang", + "author_inst": "Shandong University" }, { - "author_name": "Hae Jung Han", - "author_inst": "Green Cross WellBeing Corporation" + "author_name": "Lulu Han", + "author_inst": "Shandong University" }, { - "author_name": "Chun-Hyung Kim", - "author_inst": "Paean Biotechnology, Inc." + "author_name": "Jing Zhang", + "author_inst": "Shandong University" }, { - "author_name": "Young-Sook Song", - "author_inst": "CHA University" + "author_name": "Mei-Ling Nan", + "author_inst": "Shandong University" }, { - "author_name": "Chul Kim", - "author_inst": "CHA University" + "author_name": "Chengjiang Gao", + "author_inst": "Shandong University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "molecular biology" + "category": "immunology" }, { "rel_doi": "10.1101/2020.07.27.223495", @@ -1257708,31 +1258844,43 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2020.07.20.20153577", - "rel_title": "Working from a distance: Who can afford to stay home during COVID-19? Evidence from mobile device data", + "rel_doi": "10.1101/2020.07.21.20149443", + "rel_title": "The adequacy of health system measures in reducing vulnerability to COVID 19 among the health care providers working in primary health care in Rajasthan, India A Cross sectional Study", "rel_date": "2020-07-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.20.20153577", - "rel_abs": "As the COVID-19 pandemic continues, local and state governments must weigh the costs and benefits of social distancing policy. However, the effectiveness of such policies depend on individuals willingness and ability to comply. We propose a simple method to infer sociodemographic heterogeneity in social distancing as measured by Safegraph mobile device data. We document evidence that peoples ability to work from home is a determinant of time spent at home since the beginning of the pandemic. On April 15th, census block groups that are more likely able to work from home spent 3 more hours at home compared to those who were not. We see supporting trends among block groups with differences in income and educational attainment.\n\nJELJ19, J69, Z00", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.21.20149443", + "rel_abs": "BackgroundThis paper examines the role of individual, facility and system level preparedness in reducing the physiological and psychological vulnerability among primary-level health care providers (HCPs) of COVID19 pandemic in Rajasthan, India.\n\nMethod and MaterialOnline and telephonic interviews are conducted among 274 HCPs working in 24 PHCs (17 rural and 7 urban), across 13 districts of Rajasthan. Five dimensions of vulnerability covering awareness, exposure to infection (daily contact; contact with high-risk individuals), physical and mental health conditions, while three aspects of preparedness - at individual (personal care) and facility (provider safety; management and supervision) level - are measured by employing factor analysis. Generalized ordered logit regression model is used to measure the effect of preparedness on COVID19 related vulnerability.\n\nResultAmong the 274 HCPs, majority of the staff are from rural PHCs (76 %), less than 35 years (87%), female (57%) and married (57 %). Almost half have high level exposure to COVID19, with mean contact rate is 90. Overall, 26% have comprehensive knowledge on COVID19, and 32% have any mental health issues. Although more than 70% of HCPs have reported more than one individual level preparedness, mental health measures adopted by the HCPs are comparably low. The facility level preparedness for enhancing safety are high such as social distance (79%) and maintaining record of each visitor (75%). However, management related measures adopted by the PHCs are perceived to be lower than the safety measures. The regression analyses suggest that safety related preparedness is significantly associated with reduction of vulnerability by 50%. The management-level preparedness has statistically no significant effect in explaining the variations in level of vulnerability.\n\nConclusionThe facility-level safety measures, which lowers chances of acquiring infection has a positive effect on reducing vulnerability of COVID19. However, the HCPs do not have adequate preparedness at individual, facility management (PHC) and system level to reduce COVID19 vulnerability. Findings suggest that there is a need for a non-conventional approach of monitoring and supervision, in the absence of such measures there is a chance of moral injury that will make the HCPs at the primary level vulnerable to both physiologically and psychologically.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Christine Dimke", - "author_inst": "Colorado State University" + "author_name": "Arup Kumar Das", + "author_inst": "Lords Education and Health Society| Wadhwani Initiative for Sustainable Healthcare (WISH)" }, { - "author_name": "Marissa C Lee", - "author_inst": "Colorado State University" + "author_name": "Ambey Kumar Srivastava", + "author_inst": "Lords Education and Health Society| Wadhwani Initiative for Sustainable Healthcare (WISH)" }, { - "author_name": "Jude Bayham", - "author_inst": "Colorado State University" + "author_name": "Saswata Ghosh", + "author_inst": "Institute of Development Studies Kolkata (IDSK)" + }, + { + "author_name": "Ruchi Bhargava", + "author_inst": "Lords Education and Health Society (LEHS)| Wadhwani Initiative for Sustainable Healthcare (WISH)" + }, + { + "author_name": "Rajan Kumar Gupt", + "author_inst": "Lords Education and Health Society| Wadhwani Initiative for Sustainable Healthcare (WISH)" + }, + { + "author_name": "Rajesh Ranjan Singh", + "author_inst": "Lords Education and Health Society| Wadhwani Initiative for Sustainable Healthcare (WISH)" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "health systems and quality improvement" }, { "rel_doi": "10.1101/2020.07.21.20156711", @@ -1259970,27 +1261118,35 @@ "category": "radiology and imaging" }, { - "rel_doi": "10.1101/2020.07.21.20158816", - "rel_title": "Similarities between the neurological symptoms of COVID-19 and Functional Neurological Disorder: A systematic overview of systematic reviews and implications for future neurological healthcare services", + "rel_doi": "10.1101/2020.07.23.20158592", + "rel_title": "Coronavirus-related online web search desire amidst the rising novel coronavirus incidence in Ethiopia: Google Trends-based infodemiology", "rel_date": "2020-07-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.21.20158816", - "rel_abs": "ObjectiveIn response to the rapid spread of COVID-19, this paper provides health professionals with better accessibility to available evidence, summarising findings from a systematic overview of systematic reviews of the neurological symptoms seen in patients with COVID-19. Implications of so-called Long Covid on neurological services and primary care and similarities with other neurological disorders are discussed.\n\nMethodsFirstly, a systematic overview of current reviews of neurological symptoms of COVID-19 was conducted. Secondly the implications of these findings are discussed in relation to the potential effect on neurological services and the similarities in the experience of patients with COVID-19 and those with other neurological disorders.\n\nResultsTwenty-nine systematic reviews were identified within seven databases, published between 11th April 2020 and 27th August 2020. The results indicated (so far), that COVID-19 exhibits two types of neurological symptoms; life threatening symptoms such as Guillain Barre Syndrome and encephalitis, and less devastating symptoms such as fatigue and myalgia. These so-called lesser symptoms appear to be emerging as longer-term for some sufferers and have been recently labelled Long Covid. When compared, these Long Covid symptoms are very similar to other neurological conditions such as Chronic Fatigue Syndrome (CFS) and Functional Neurological Disorder (FND).\n\nConclusionsImplications for neurological healthcare services in the UK may include longer waiting times and a need for more resources (including more qualified health professionals). There is also a possible change-effect on health professionals perceptions of other neurological conditions such as CFS and FND. Future research is recommended to explore changes in health professionals perceptions of neurological symptoms because of COVID-19.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.23.20158592", + "rel_abs": "BackgroundDuring disease outbreaks, social communication and behaviors are very important to contain the outbreak. Under such circumstances, individual activities on online platforms will increase tremendously. This will result in the circulation useful or misleading/misinformation (infodemic monikers) in the community. Thus, exploring the online trending information is highly crucial in the process of containing disease outbreak. Therefore, this study aimed to explore users concerns towards coronavirus-related online web search activities and to investigate the extent of misleading terms adopted for identifying the virus in the early stage of COVID-19 spread in Ethiopia.\n\nMethodsGoogle Trends was employed in exploring the tendency towards coronavirus-related web search activities in Ethiopia from March 13 to May 8, 2020. Keywords of the different names of COVID-19 and health-related issues were used to investigate the trends of public interest in searching from Google over time. Relative search volume (RSV) and Average peak comparison (APC) were used to compare the trends of online search interests. Pearson correlation coefficient was calculated to check for the presence of correlation.\n\nResultDuring the study period, \"corona,\" \"virus,\" \"coronavirus,\" \"corona virus\", \"China coronavirus,\" and \"COVID-19\", were the top names users adopted to identify the virus. In almost all search activities, the users employed infodemic monikers to identify the virus (99%). \"Updates\" related issues (APC=60, 95% CI, 55 - 66) were the most commonly trending health-related searches on Google followed by mortality (APC=27, 95% CI, 24 - 30) and symptoms (APC=55, 95% CI, 50 - 60) related issues. The regional comparison showed the highest cumulative peak for the Oromia region on querying health-related information from Google.\n\nConclusionThis study revealed an initial increase in the public interest of COVID-19 related Google search, but this interest was declined over time. Tremendous circulation of infodemic monikers for the identification of the virus was also noticed in the country. The authors recommend concerned stakeholders to work immensely to keep the public alert on coronavirus-related issues and to promote the official names of the virus to decrease the circulation of misleading and misinformation amid the outbreak.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Tamar Wildwing", - "author_inst": "Canterbury Christ Church University" + "author_name": "Behailu Terefe", + "author_inst": "Jimma university" }, { - "author_name": "Nicole Holt", - "author_inst": "Canterbury Christ Church University" + "author_name": "Alessandro Rovetta", + "author_inst": "Mensana srls" + }, + { + "author_name": "Asha K Rajan", + "author_inst": "Department of Pharmacy Practice, Jaya College of Paramedical Sciences, College of Pharmacy, Thiruninravur" + }, + { + "author_name": "Mengist Awoke", + "author_inst": "School of Pharmacy, Department of Clinical Pharmacy, Institute of Health, Jimma University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "health informatics" }, { "rel_doi": "10.1101/2020.07.18.20156828", @@ -1261544,73 +1262700,45 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.07.25.192310", - "rel_title": "\u03b2-Coronaviruses use lysosomal organelles for cellular egress.", + "rel_doi": "10.1101/2020.07.25.221135", + "rel_title": "SARS-CoV-2 differs from SARS-CoV in the requirements for receptor expression and proteolytic activation to trigger cell-cell fusion and is not inhibited by Bromhexine", "rel_date": "2020-07-25", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.25.192310", - "rel_abs": "{beta}-Coronaviruses are a family of positive-strand enveloped RNA viruses that include the severe acute respiratory syndrome-CoV2 (SARS-CoV2). While much is known regarding their cellular entry and replication pathways, their mode of egress remains uncertain; however, this is assumed to be via the biosynthetic secretory pathway by analogy to other enveloped viruses. Using imaging methodologies in combination with virus-specific reporters, we demonstrate that {beta}-Coronaviruses utilize lysosomal trafficking for egress from cells. This pathway is regulated by the Arf-like small GTPase Arl8b; thus, virus egress is insensitive to inhibitors of the biosynthetic secretory pathway. Coronavirus infection results in lysosome deacidification, inactivation of lysosomal degradation and disruption of antigen presentation pathways. This coronavirus-induced exploitation of lysosomes provides insights into the cellular and immunological abnormalities observed in patients and suggests new therapeutic modalities.", - "rel_num_authors": 15, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.25.221135", + "rel_abs": "The severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) infects cells through interaction of its spike protein (SARS2-S) with Angiotensin-converting enzyme 2 (ACE2) and activation by proteases, in particular transmembrane protease serine 2 (TMPRSS2). Viruses can also spread through fusion of infected with uninfected cells. We compared the requirements of ACE2 expression, proteolytic activation, and the sensitivity to inhibitors for SARS2-S-mediated and SARS-CoV-S(SARS1-S)-mediated cell-cell fusion. SARS2-S-driven fusion was moderately increased by TMPRSS2 and strongly by ACE2, while SARS1-S-driven fusion was strongly increased by TMPRSS2 and less so by ACE2 expression. In contrast to SARS1-S, SARS2-S-mediated cell-cell fusion was efficiently activated by Batimastat-sensitive metalloproteases. Mutation of the S1/S2 proteolytic cleavage site reduced effector-target-cell fusion when ACE2 or TMPRSS2 were limiting and rendered SARS2-S-driven cell-cell fusion more dependent on TMPRSS2. When both ACE2 and TMPRSS2 were abundant, initial target-effector-cell fusion was unaltered compared to wt SARS2-S, but syncytia remained smaller. Mutation of the S2 site specifically abrogated activation by TMPRSS2 for both cell-cell fusion and SARS2-S-driven pseudoparticle entry but still allowed for activation by metalloproteases for cell-cell fusion and by cathepsins for particle entry. Finally, we found that the TMPRSS2 inhibitor Bromhexine was unable to reduce TMPRSS2-activated cell-cell fusion by SARS1-S and SARS2-S as opposed to the inhibitor Camostat. Paradoxically, Bromhexine enhanced cell-cell fusion in the presence of TMPRSS2, while its metabolite Ambroxol exhibited inhibitory activity in some conditions. On Calu-3 lung cells, Ambroxol weakly inhibited SARS2-S-driven lentiviral pseudoparticle entry, and both substances exhibited a dose-dependent trend towards weak inhibition of authentic SARS-CoV-2.\n\nIMPORTANCECell-cell fusion allows the virus to infect neighboring cells without the need to produce free virus and contributes to tissue damage by creating virus-infected syncytia. Our results demonstrate that the S2 cleavage site is essential for activation by TMPRSS2 and unravel important differences between SARS-CoV and SARS-CoV-2, among those greater dependence of SARS-CoV-2 on ACE2 expression and activation by metalloproteases for cell-cell fusion. Bromhexine, reportedly an inhibitor of TMPRSS2, is currently tested in clinical trials against coronavirus disease 2019. Our results indicate that Bromhexine enhances fusion in some conditions. We therefore caution against use of Bromhexine in higher dosage until its effects on SARS-CoV-2 spike activation are better understood. The related compound Ambroxol, which similarly to Bromhexine is clinically used as an expectorant, did not exhibit activating effects on cell-cell fusion. Both compounds exhibited weak inhibitory activity against SARS-CoV-2 infection at high concentrations, which might be clinically attainable for Ambroxol.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Nihal Altan-Bonnet", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Gregoire Yves Altan-Bonnet", - "author_inst": "National Cancer Institute" + "author_name": "Bojan F H\u00f6rnich", + "author_inst": "Nachwuchsgruppe Herpesviren, Abteilung Infektionsbiologie, Deutsches Primatenzentrum - Leibniz-Institut f\u00fcr Primatenforschung, G\u00f6ttingen, Germany" }, { - "author_name": "Sourish Ghosh", - "author_inst": "National Institutes of Health" + "author_name": "Anna K Gro\u00dfkopf", + "author_inst": "Nachwuchsgruppe Herpesviren, Abteilung Infektionsbiologie, Deutsches Primatenzentrum - Leibniz-Institut f\u00fcr Primatenforschung, G\u00f6ttingen, Germany" }, { - "author_name": "Teegan Dellibovi-Ragheb", - "author_inst": "FDA" - }, - { - "author_name": "Eowyn Pak", - "author_inst": "Dartmouth College" - }, - { - "author_name": "Qi Qiu", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Matthew Fisher", - "author_inst": "National Institutes of Health" + "author_name": "Sarah Schlagowski", + "author_inst": "Nachwuchsgruppe Herpesviren, Abteilung Infektionsbiologie, Deutsches Primatenzentrum - Leibniz-Institut f\u00fcr Primatenforschung, G\u00f6ttingen, Germany" }, { - "author_name": "Peter Takvorian", - "author_inst": "State University of New Jersey-Rutgers University- Newark" - }, - { - "author_name": "Christopher Bleck", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Victor Hsu", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Anthony Fehr", - "author_inst": "University of Kentucky" + "author_name": "Matthias Tenbusch", + "author_inst": "Virologisches Institut, Universit\u00e4tsklinikum Erlangen, Erlangen, Germany" }, { - "author_name": "Stanley Perlman", - "author_inst": "University of Iowa" + "author_name": "Hannah Kleine-Weber", + "author_inst": "Abteilung Infektionsbiologie, Deutsches Primatenzentrum - Leibniz-Institut f\u00fcr Primatenforschung, G\u00f6ttingen, Germany" }, { - "author_name": "Marco Straus", - "author_inst": "Cornell University" + "author_name": "Frank Neipel", + "author_inst": "Virologisches Institut, Universit\u00e4tsklinikum Erlangen, Erlangen, Germany" }, { - "author_name": "Gary Whittaker", - "author_inst": "Cornell University" + "author_name": "Christiane Stahl-Hennig", + "author_inst": "Abteilung Infektionsmodelle, Deutsches Primatenzentrum - Leibniz-Institut f\u00fcr Primatenforschung, G\u00f6ttingen, Germany" }, { - "author_name": "C AM de Haan", - "author_inst": "Utrecht University" + "author_name": "Alexander S Hahn", + "author_inst": "Nachwuchsgruppe Herpesviren, Abteilung Infektionsbiologie, Deutsches Primatenzentrum - Leibniz-Institut f\u00fcr Primatenforschung, G\u00f6ttingen, Germany" } ], "version": "1", @@ -1263166,31 +1264294,55 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.07.24.217570", - "rel_title": "Adopting STING agonist cyclic dinucleotides as a potential adjuvant for SARS-CoV-2 vaccine", + "rel_doi": "10.1101/2020.07.22.214254", + "rel_title": "The answer lies in the energy: how simple atomistic molecular dynamics simulations may hold the key to epitope prediction on the fully glycosylated SARS-CoV-2 spike protein", "rel_date": "2020-07-24", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.24.217570", - "rel_abs": "A novel STING agonist CDGSF unilaterally modified with phosphorothioate and fluorine was synthesized. CDGSF displayed better STING activity over dithio CDG. Immunization of SARS-CoV-2 Spike protein with CDGSF as an adjuvant elicited an exceptional high antibody titer and a robust T cell response, which were better than the group using aluminium hydroxide as a adjuvant. These results highlighted the adjuvant potential of STING agonist in SARS-CoV-2 vaccine preparation for the first time.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.22.214254", + "rel_abs": "Betacoronavirus SARS-CoV-2 is posing a major threat to human health and its diffusion around the world is having dire socioeconomical consequences. Thanks to the scientific communitys unprecedented efforts, the atomic structure of several viral proteins has been promptly resolved. As the crucial mediator of host cell infection, the heavily glycosylated trimeric viral Spike protein (S) has been attracting the most attention and is at the center of efforts to develop antivirals, vaccines, and diagnostic solutions.\n\nHerein, we use an energy-decomposition approach to identify antigenic domains and antibody binding sites on the fully glycosylated S protein. Crucially, all that is required by our method are unbiased atomistic molecular dynamics simulations; no prior knowledge of binding properties or ad hoc combinations of parameters/measures extracted from simulations is needed. Our method simply exploits the analysis of energy interactions between all intra-protomer aminoacid and monosaccharide residue pairs, and cross-compares them with structural information (i.e., residueresidue proximity), identifying potential immunogenic regions as those groups of spatially contiguous residues with poor energetic coupling to the rest of the protein.\n\nOur results are validated by several experimentally confirmed structures of the S protein in complex with anti- or nanobodies. We identify poorly coupled sub-domains: on the one hand this indicates their role in hosting (several) epitopes, and on the other hand indicates their involvement in large functional conformational transitions. Finally, we detect two distinct behaviors of the glycan shield: glycans with stronger energetic coupling are structurally relevant and protect underlying peptidic epitopes; those with weaker coupling could themselves be poised for antibody recognition. Predicted Immunoreactive regions can be used to develop optimized antigens (recombinant subdomains, synthetic (glyco)peptidomimetics) for therapeutic applications.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Jun-Jun Wu", - "author_inst": "Department of Chemistry, Tsinghua University" + "author_name": "Stefano Serapian", + "author_inst": "University of Pavia, Department of Chemistry" }, { - "author_name": "Yong-Xiang Chen", - "author_inst": "Department of Chemistry, Tsinghua University" + "author_name": "Filippo Marchetti", + "author_inst": "University of Pavia" }, { - "author_name": "Yan-Mei Li", - "author_inst": "Department of Chemistry, Tsinghua University" + "author_name": "Alice Triveri", + "author_inst": "University of Pavia" + }, + { + "author_name": "Giulia Morra", + "author_inst": "SCITEC-CNR" + }, + { + "author_name": "Massimiliano Meli", + "author_inst": "SCITEC-CNR" + }, + { + "author_name": "Elisabetta Moroni", + "author_inst": "SCITEC-CNR" + }, + { + "author_name": "Giuseppe A Sautto", + "author_inst": "University of Georgia" + }, + { + "author_name": "Andrea Rasola", + "author_inst": "University of Padova" + }, + { + "author_name": "Giorgio Colombo", + "author_inst": "University of Pavia" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2020.07.24.217562", @@ -1264572,25 +1265724,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.23.20160697", - "rel_title": "A machine learning aided global diagnostic and comparative tool to assess effect of quarantine control in Covid-19 spread", + "rel_doi": "10.1101/2020.07.23.20160788", + "rel_title": "A Framework for SARS-CoV-2 Testing on a Large University Campus: Statistical Considerations", "rel_date": "2020-07-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.23.20160697", - "rel_abs": "1We have developed a globally applicable diagnostic Covid-19 model by augmenting the classical SIR epidemiological model with a neural network module. Our model does not rely upon previous epidemics like SARS/MERS and all parameters are optimized via machine learning algorithms employed on publicly available Covid-19 data. The model decomposes the contributions to the infection timeseries to analyze and compare the role of quarantine control policies employed in highly affected regions of Europe, North America, South America and Asia in controlling the spread of the virus. For all continents considered, our results show a generally strong correlation between strengthening of the quarantine controls as learnt by the model and actions taken by the regions respective governments. Finally, we have hosted our quarantine diagnosis results for the top 70 affected countries worldwide, on a public platform, which can be used for informed decision making by public health officials and researchers alike.\n\nArticle Summary LineData-driven epidemiological model to quantify and compare quarantine control policies in controlling COVID-19 spread in Europe, North America, South America and Asia.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.23.20160788", + "rel_abs": "We consider testing strategies for active SARS-CoV-2 infection for a large university community population, which we define. Components of such a strategy include individuals tested because they self-select or are recommended for testing by a health care provider for their own health care; individuals tested because they belong to a high-risk group where testing serves to disrupt transmission; and, finally, individuals randomly selected for testing from the university community population as part of a proactive community testing, or surveillance, program. The proactive community testing program is predicated on a mobile device application that asks individuals to self-monitor COVID-like symptoms daily. The goals of this report are (i) to provide a framework for estimating prevalence of SARS-CoV-2 infection in the university community wherein proactive community testing is a major component of the overall strategy, (ii) to address the issue of how many tests should be performed as part of the proactive community testing program, and (iii) to consider how effective proactive community testing will be for purposes of detection of new disease clusters.\n\nWe argue that a comprehensive prevalence estimate informed by all testing done of the university community is a good metric to obtain a global picture of campus SARS-CoV-2 infection rates at a particular point in time and to monitor the dynamics of infection over time, for example, estimating the population-level reproductive number, R0). Importantly, the prevalence metric can be useful to campus leadership for decision making. One example involves comparing campus prevalence to that in the broader off-campus community. We also show that under some reasonable assumptions, we can obtain valid statements about the comprehensive prevalence by only testing symptomatic persons in the proactive community testing component.\n\nThe number of tests performed for individual-level and high-risk group-level needs will depend on the disease dynamics, individual needs, and testing availability. For purposes of this report, we assume that, for these groups of individuals, inferential precision -- that is, the accuracy with which we can estimate the true prevalence from testing a random sample of individuals -- does not drive decisions on the number of tests.\n\nOn the other hand, for proactive community testing, the desired level of inferential precision in a fixed period of time can be used to justify the number of tests to perform in that period. For example, our results show that, if we establish a goal of ruling out with 98% confidence a background prevalence of 2% in a given week, and the actual prevalence is 1% among those eligible for proactive community testing, we would need to test 835 randomly-selected symptomatics (i.e., those presenting with COVID-like symptoms) per week via the proactive community testing program in a campus of 80k individuals. In addition to justifying decisions about the number of tests to perform, inferential precision can formalize the intuition that testing of symptomatic individuals should be prioritized over testing asymptomatic individuals in the proactive community testing program.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Raj Dandekar", - "author_inst": "Massachusetts Institute of Technology" - }, - { - "author_name": "Chris Rackauckas", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Paul J Rathouz", + "author_inst": "U of Texas at Austin" }, { - "author_name": "George Barbastathis", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Catherine A Calder", + "author_inst": "University of Texas at Austin" } ], "version": "1", @@ -1265810,39 +1266958,31 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.07.22.20160085", - "rel_title": "Homebound by COVID19: The Benefits and Consequences of Non-Pharmaceutical Intervention Strategies", - "rel_date": "2020-07-24", + "rel_doi": "10.1101/2020.07.17.20156604", + "rel_title": "Surges in COVID-19 are led by lax government interventions in initial outbreaks", + "rel_date": "2020-07-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.22.20160085", - "rel_abs": "ObjectivesTo evaluate the tradeoffs between potential benefits (e.g., reduction in infection spread and deaths) of non-pharmaceutical interventions for COVID19 and being homebound (i.e., refraining from community/workplace interactions).\n\nMethodsAn agent-based simulation model to project the disease spread and estimate the number of homebound people and person-days under multiple scenarios, including combinations of shelter-in- place, voluntary quarantine, and school closure in Georgia from March 1 to September 1, 2020.\n\nResultsCompared to no intervention, under voluntary quarantine, voluntary quarantine with school closure, and shelter-in-place with school closure scenarios 3.43, 19.8, and 200+ homebound adult-days were required to prevent one infection, with the maximum number of adults homebound on a given day in the range of 121K-268K, 522K-567K, 5,377K-5,380K, respectively.\n\nConclusionsVoluntary quarantine combined with school closure significantly reduced the number of infections and deaths with a considerably smaller number of homebound person-days compared to shelter-in-place.\n\nThree-question Summary BoxO_LIWhat is the current understanding of this subject?\nRecent research has been conducted by various countries and regions on the impact of non-pharmaceutical interventions (NPIs) on reducing the spread of COVID19.\nC_LIO_LIWhat does this report add to the literature?\nOur report assessed which intervention strategies provided the best results in terms of both reducing infection outcomes (cases, deaths, etc.) and minimizing their social and economic effects (e.g., number of people homebound, providing childcare, etc.).\nC_LIO_LIWhat are the implications for public health practice?\nVoluntary quarantine proved to be the most beneficial in terms of reducing infections and deaths compared to the number of people who were homebound.\nC_LI", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20156604", + "rel_abs": "Sharp increases in COVID-19 cases occurred after reopening in the United States. We show that the post-intervention effective reproduction number is a strong predictor of the surge in late June. Lax interventions in the early stages coupled with elevated virus spread are primarily responsible for surges in most affected states.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Buse Eylul Oruc Aglar", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "Arden Baxter", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "Pinar Keskinocak", - "author_inst": "Georgia Institute of Technology" + "author_name": "Hsiang-Yu Yuan", + "author_inst": "City University of Hong Kong" }, { - "author_name": "John Asplund", - "author_inst": "Georgia Institute of Technology" + "author_name": "Lindsey Wu", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Nicoleta Serban", - "author_inst": "Georgia Institute of Technology" + "author_name": "Dong-Ping Wang", + "author_inst": "Stony Brook University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "health policy" }, { "rel_doi": "10.1101/2020.07.17.20156075", @@ -1267524,285 +1268664,73 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.17.20155150", - "rel_title": "The Trans-omics Landscape of COVID-19", + "rel_doi": "10.1101/2020.07.15.20154443", + "rel_title": "Kinetics and Isotype Assessment of Antibodies Targeting the Spike Protein Receptor Binding Domain of SARS-CoV-2 In COVID-19 Patients as a function of Age and Biological Sex.", "rel_date": "2020-07-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20155150", - "rel_abs": "System-wide molecular characteristics of COVID-19, especially in those patients without comorbidities, have not been fully investigated. We compared extensive molecular profiles of blood samples from 231 COVID-19 patients, ranging from asymptomatic to critically ill, importantly excluding those with any comorbidities. Amongst the major findings, asymptomatic patients were characterized by highly activated anti-virus interferon, T/natural killer (NK) cell activation, and transcriptional upregulation of inflammatory cytokine mRNAs. However, given very abundant RNA binding proteins (RBPs), these cytokine mRNAs could be effectively destabilized hence preserving normal cytokine levels. In contrast, in critically ill patients, cytokine storm due to RBPs inhibition and tryptophan metabolites accumulation contributed to T/NK cell dysfunction. A machine-learning model was constructed which accurately stratified the COVID-19 severities based on their multi-omics features. Overall, our analysis provides insights into COVID-19 pathogenesis and identifies targets for intervening in treatment.", - "rel_num_authors": 68, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.15.20154443", + "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWSARS-CoV-2 is the newly emerged virus responsible for the global COVID-19 pandemic. There is an incomplete understanding of the host humoral immune response to SARS-CoV-2 during acute infection. Host factors such as age and sex as well the kinetics and functionality of antibody responses are important factors to consider as vaccine development proceeds. The receptor-binding domain of the CoV spike (RBD-S) protein is important in host cell recognition and infection and antibodies targeting this domain are often neutralizing. In a cross-sectional study of anti-RBD-S antibodies in COVID-19 patients we found equivalent levels in male and female patients and no age-related deficiencies even out to 93 years of age. The anti-RBD-S response was evident as little as 6 days after onset of symptoms and for at least 5 weeks after symptom onset. Anti-RBD-S IgG, IgM, and IgA responses were simultaneously induced within 10 days after onset, but isotype-specific kinetics differed such that anti-RBD-S IgG was most sustained over a 5-week period. The kinetics and magnitude of neutralizing antibody formation strongly correlated with that seen for anti-RBD-S antibodies. Our results suggest age- and sex-related disparities in COVID-19 fatalities are not explained by anti-RBD-S responses. The multi-isotype anti-RBD-S response induced by live virus infection could serve as a potential marker by which to monitor vaccine-induced responses.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Peng Wu", - "author_inst": "Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Techno" - }, - { - "author_name": "Dongsheng Chen", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" - }, - { - "author_name": "Wencheng Ding", - "author_inst": "Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Techno" - }, - { - "author_name": "Ping Wu", - "author_inst": "Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Techno" - }, - { - "author_name": "Hongyan Hou", - "author_inst": "Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" - }, - { - "author_name": "Yong Bai", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" - }, - { - "author_name": "Yuwen Zhou", - "author_inst": "1.BGI-Shenzhen, Shenzhen 518083, China; 2.BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Kezhen Li", - "author_inst": "Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Techno" - }, - { - "author_name": "Shunian Xiang", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" - }, - { - "author_name": "Panhong Liu", - "author_inst": "1.BGI-Shenzhen, Shenzhen 518083, China; 2.BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Jia Ju", - "author_inst": "1.BGI-Shenzhen, Shenzhen 518083, China; 2.BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Ensong Guo", - "author_inst": "Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Techno" - }, - { - "author_name": "Jia Liu", - "author_inst": "Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Techno" - }, - { - "author_name": "Bin Yang", - "author_inst": "Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Techno" - }, - { - "author_name": "Junpeng Fan", - "author_inst": "Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Techno" - }, - { - "author_name": "Liang He", - "author_inst": "Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Techno" - }, - { - "author_name": "Ziyong Sun", - "author_inst": "Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" - }, - { - "author_name": "Ling Feng", - "author_inst": "Department of Gynecology and obstetrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" - }, - { - "author_name": "Jian Wang", - "author_inst": "Department of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China" - }, - { - "author_name": "Tangchun Wu", - "author_inst": "Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong Univers" - }, - { - "author_name": "Hao Wang", - "author_inst": "Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong Univers" - }, - { - "author_name": "Jin Cheng", - "author_inst": "Department of Research, Xiangyang Central Hospital, Hubei University of Arts and Science, Xiangyang, Hubei, China" - }, - { - "author_name": "Hui Xing", - "author_inst": "Department of Obstetrics and Gynecology, Xiangyang Central Hospital, Hubei University of Arts and Science, Xiangyang, Hubei, China" - }, - { - "author_name": "Yifan Meng", - "author_inst": "Department of Gynecologic Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University" - }, - { - "author_name": "Yongsheng Li", - "author_inst": "Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, China" - }, - { - "author_name": "Yuanliang Zhang", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" - }, - { - "author_name": "Hongbo Luo", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" - }, - { - "author_name": "Gang Xie", - "author_inst": "1.BGI-Shenzhen, Shenzhen 518083, China; 2.BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Xianmei Lan", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" - }, - { - "author_name": "Ye Tao", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" - }, - { - "author_name": "Hao Yuan", - "author_inst": "1.BGI-Shenzhen, Shenzhen 518083, China; 2.BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Kang Huang", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" - }, - { - "author_name": "Wan Sun", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" - }, - { - "author_name": "Xiaobo Qian", - "author_inst": "1.BGI-Shenzhen, Shenzhen 518083, China; 2.BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Zhichao Li", - "author_inst": "1.BGI-Shenzhen, Shenzhen 518083, China; 2.BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Mingxi Huang", - "author_inst": "1.BGI-Shenzhen, Shenzhen 518083, China; 2.BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Peiwen Ding", - "author_inst": "1. BGI-Shenzhen, Shenzhen 518083, China; 2. BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Haoyu Wang", - "author_inst": "1. BGI-Shenzhen, Shenzhen 518083, China; 2. BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Jiaying Qiu", - "author_inst": "1. BGI-Shenzhen, Shenzhen 518083, China; 2. BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Feiyue Wang", - "author_inst": "1. BGI-Shenzhen, Shenzhen 518083, China; 2. BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Shiyou Wang", - "author_inst": "1. BGI-Shenzhen, Shenzhen 518083, China; 2. BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Jiacheng Zhu", - "author_inst": "1. BGI-Shenzhen, Shenzhen 518083, China; 2. BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Xiangning Ding", - "author_inst": "1. BGI-Shenzhen, Shenzhen 518083, China; 2. BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Chaochao Chai", - "author_inst": "1. BGI-Shenzhen, Shenzhen 518083, China; 2. BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Langchao Liang", - "author_inst": "1. BGI-Shenzhen, Shenzhen 518083, China; 2. BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Xiaoling Wang", - "author_inst": "1. BGI-Shenzhen, Shenzhen 518083, China; 2. BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Lihua Luo", - "author_inst": "1. BGI-Shenzhen, Shenzhen 518083, China; 2. BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China" - }, - { - "author_name": "Yuzhe Sun", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" - }, - { - "author_name": "Ying Yang", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" - }, - { - "author_name": "Zhenkun Zhuang", - "author_inst": "1.BGI-Shenzhen, Shenzhen 518083, China; 2.School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China" - }, - { - "author_name": "Tao Li", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" - }, - { - "author_name": "Lei Tian", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" - }, - { - "author_name": "Shaoqiao Zhang", - "author_inst": "BGI-Hubei, BGI-Shenzhen, Wuhan,430074 , China" - }, - { - "author_name": "Linnan Zhu", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" + "author_name": "Nancy R. Graham", + "author_inst": "University of Vermont" }, { - "author_name": "Lei Chen", - "author_inst": "College of Veterinary Medicine, Yangzhou University, Yangzhou, China" + "author_name": "Annalis N. Whitaker", + "author_inst": "University of Vermont" }, { - "author_name": "Yiquan Wu", - "author_inst": "HIV and AIDS Malignancy Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA." + "author_name": "Camilla A. Strother", + "author_inst": "University of Vermont" }, { - "author_name": "Xiaoyan Ma", - "author_inst": "Department of Biochemistry, University of Cambridge, UK" + "author_name": "Ashley K. Miles", + "author_inst": "University of Vermont" }, { - "author_name": "Fang Chen", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" + "author_name": "Dore Grier", + "author_inst": "University of Vermont" }, { - "author_name": "Yan Ren", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" + "author_name": "Benjamin D. McElvany", + "author_inst": "University of Vermont" }, { - "author_name": "Xun Xu", - "author_inst": "1.BGI-Shenzhen, Shenzhen 518083, China; 2.Guangdong Provincial Key Laboratory of Genome Read and Write, BGI-Shenzhen, Shenzhen, 518120, China" + "author_name": "Emily A Bruce", + "author_inst": "University of Vermont" }, { - "author_name": "Siqi Liu", - "author_inst": "BGI-Shenzhen, Shenzhen 518083, China" + "author_name": "Matthew E. Poynter", + "author_inst": "University of Vermont" }, { - "author_name": "Jian Wang", - "author_inst": "1.BGI-Shenzhen, Shenzhen 518083, China; 2.James D. Watson Institute of Genome Science, 310008 Hangzhou, China" + "author_name": "Kristen K. Pierce", + "author_inst": "University of Vermont" }, { - "author_name": "Huanming Yang", - "author_inst": "1.BGI-Shenzhen, Shenzhen 518083, China; 2.James D. Watson Institute of Genome Science, 310008 Hangzhou, China" + "author_name": "Beth D. Kirkpatrick", + "author_inst": "University of Vermont" }, { - "author_name": "Lin Wang", - "author_inst": "Department of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China" + "author_name": "Renee D. Stapleton", + "author_inst": "University of Vermont" }, { - "author_name": "Chaoyang Sun", - "author_inst": "Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Techno" + "author_name": "Gary An", + "author_inst": "University of Vermont" }, { - "author_name": "Ding Ma", - "author_inst": "Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Techno" + "author_name": "Jason W. Botten", + "author_inst": "University of Vermont" }, { - "author_name": "Xin Jin", - "author_inst": "1.BGI-Shenzhen, Shenzhen 518083, China; 2.School of Medicine, South China University of Technology, Guangzhou 510006, Guangdong, China" + "author_name": "Jessica W. Crothers", + "author_inst": "University of Vermont" }, { - "author_name": "Gang Chen", - "author_inst": "Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Techno" + "author_name": "Sean A. Diehl", + "author_inst": "University of Vermont" } ], "version": "1", @@ -1269282,31 +1270210,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.18.20156851", - "rel_title": "Transparency Assessment of COVID-19 Models", + "rel_doi": "10.1101/2020.07.20.20157560", + "rel_title": "Changes in Emergency Department attendances before and after COVID-19 lockdown implementation: a cross sectional study of one urban NHS Hospital Trust", "rel_date": "2020-07-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.18.20156851", - "rel_abs": "As the COVID-19 pandemic has caused major societal unrest, modelers have worked to project future trends of COVID-19 and predict upcoming challenges and impacts of policy action. These models, alone or in aggregate, are influential for decision-makers at every level. Therefore, the method and documentation of COVID-19 models must be highly transparent to ensure that projections and consequential policies put forth have sound epistemological grounds. We evaluated 29 COVID-19 models receiving high attention levels within the scientific community and/or informing government responses. We evaluated these models against 27 transparency criteria. We found high levels of transparency in model documentation aspects such as reporting uncertainty analysis; however, about half of the models do not share code and a quarter do not report equations. These discrepancies underscore the need for transparency and reproducibility to be at the forefront of researchers priorities, especially during a global health crisis when stakes are critically high.\n\nSummaryEvaluation of 29 impactful COVID-19 models reveals inconsistent adherence to best transparency practices; higher transparency is needed to inform policy.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.20.20157560", + "rel_abs": "BackgroundEmergency Department (ED) attendances have fallen across the UK since the lockdown introduced on 23rd March 2020 to limit the spread of coronavirus disease 2019 (COVID-19). We hypothesised that reductions would vary by patient age and disease type. We examined pre- and in-lockdown ED attendances for two COVID-19 unrelated diagnoses; one likely to be affected by lockdown measures (gastroenteritis) and one likely to be unaffected (appendicitis).\n\nMethodsRetrospective cross-sectional study conducted across two EDs in one London hospital Trust. We compared all adult and paediatric ED attendances, before (January 2020) and during lockdown (March/April 2020). Key patient demographics, method of arrival and discharge location were compared. We used SNOMED codes to define attendances for gastroenteritis and appendicitis.\n\nResultsED attendances fell from 1129 per day before lockdown to 584 in-lockdown; 51.7% of pre-lockdown rates. In-lockdown attendances were lowest for under-18s (16.0% of pre-lockdown). The proportion of patients admitted to hospital increased from 17.3% to 24.0% and the proportion admitted to intensive care increased four-fold. Attendances for gastroenteritis fell from 511 to 103; 20.2% of pre-lockdown rates. Attendances for appendicitis also decreased, from 144 to 41; 28.5% of pre-lockdown rates.\n\nConclusionED attendances fell substantially following lockdown implementation. The biggest reduction was for under-18s. We observed reductions in attendances for gastroenteritis and appendicitis. This may reflect lower rates of infectious disease transmission, though the fall in appendicitis-related attendances suggests that behavioural factors are also important. Larger studies are urgently needed to understand changing patterns of ED use and access to emergency care during the COVID-19 pandemic.\n\nO_TEXTBOXWhat this paper adds\n\nO_LIWhat is already known on this subject:\nO_LIED attendances have decreased during the COVID-19 associated lockdown.\nC_LIO_LIVarious theories have been suggested for changes in ED attendance, including lower transmission of infectious diseases and patients heeding recommendations from government bodies.\nC_LI\nC_LIO_LIWhat this study adds:\nO_LIReductions in ED attendances vary by age group and disease type.\nC_LIO_LIWe propose a conceptual casual framework for underlying reasons behind changes in ED attendance in England during the COVID-19 lockdown.\nC_LIO_LIFollowing lockdown implementation, we observed a reduction in ED attendances with both infectious and non-infectious diseases. This suggests that reduced transmission of infectious disease is not the only cause of lower overall ED attendances.\nC_LI\nC_LI\n\nC_TEXTBOX", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Mohammad S. Jalali", - "author_inst": "Harvard Medical School" + "author_name": "Kate Honeyford", + "author_inst": "Imperial College" }, { - "author_name": "Catherine DiGennaro", - "author_inst": "Harvard Medical School" + "author_name": "Charles Coughlan", + "author_inst": "Imperial College" }, { - "author_name": "Devi Sridhar", - "author_inst": "The University of Edinburgh" + "author_name": "Paul Expert", + "author_inst": "Imperial College" + }, + { + "author_name": "Gabriel Burcea", + "author_inst": "Imperial College" + }, + { + "author_name": "Ian Maconochie", + "author_inst": "Imperial College" + }, + { + "author_name": "Anne Kinderlerer", + "author_inst": "Imperial College NHS Healthcare Trust" + }, + { + "author_name": "Graham S Cooke", + "author_inst": "Imperial College" + }, + { + "author_name": "Ceire S Costelloe", + "author_inst": "Imperial College" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "emergency medicine" }, { "rel_doi": "10.1101/2020.07.20.20157602", @@ -1271044,33 +1271992,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.17.20152702", - "rel_title": "Evaluation of efficiency and sensitivity of 1D and 2D sample pooling strategies for diagnostic screening purposes", + "rel_doi": "10.1101/2020.07.09.20149450", + "rel_title": "Genetic validation of the use of tocilizumab, statins and dexamethasone in COVID-19", "rel_date": "2020-07-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20152702", - "rel_abs": "To increase the throughput, lower the cost, and save scarce test reagents, laboratories can pool patient samples before SARS-CoV-2 RT-qPCR testing. While different sample pooling methods have been proposed and effectively implemented in some laboratories, no systematic and large-scale evaluations exist using real-life quantitative data gathered throughout the different epidemiological stages. Here, we use anonymous data from 9673 positive cases to simulate and compare 1D and 2D pooling strategies. We show that the optimal choice of pooling method and pool size is an intricate decision with a testing population-dependent efficiency-sensitivity trade-off and present an online tool to provide the reader with custom real-time pooling strategy recommendations.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.09.20149450", + "rel_abs": "BackgroundNew means of treating COVID-19 are urgently needed. Genetic validation of drugs can foreshadow trial results, and help prioritize investigations. We assessed whether common drugs, suggested as possible treatments for COVID-19 (tocilizumab, anakinra and statins) with established genetic proxies, are effective in COVID-19. We also included dexamethasone as a positive control exposure because the RECOVERY trial suggested benefit in severe COVID-19.\n\nMethodsWe assessed, using Mendelian randomization, whether genetic proxies of tocilizumab, anakinra, statins and dexamethasone use affected risk of very severe (cases=536, non-cases=329391) or hospitalized (cases=3199, non-cases=897488) COVID-19 using a recent genome-wide association study.\n\nResultsUsing rs2228145 (IL6R) to proxy effects of tocilizumab use, no association with very severe COVID-19 was found, but possibly an inverse association with hospitalized COVID-19 (odds ratio (OR) 0.83 per standardized effect of higher soluble interleukin-6r, 95% confidence interval 0.67 to 1.02). Using rs12916 (HMGCR) to proxy effects of statins use, an inverse association with very severe COVID-19 was found (OR 0.30 per standardized effect, 95% CI 0.10 to 0.89). Using rs6743376 and rs1542176 to proxy effects of anakinra use, no associations with COVID-19 were found. Dexamethasone, instrumented by cortisol, was possibly inversely associated with very severe COVID-19 (OR 0.20 per standardized effect 95% CI 0.04 to 1.04).\n\nConclusionOur study provides some genetic validation for the use of both tocilizumab and statins in COVID-19, but not anakinra, whilst being consistent with the findings from the RECOVERY trial about dexamethasone. Investigation of the underlying mechanisms might facilitate re-purposing and development of effective treatments.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Jasper Verwilt", - "author_inst": "Ghent University" - }, - { - "author_name": "Jan Hellemans", - "author_inst": "Biogazelle" + "author_name": "C M Schooling", + "author_inst": "The University of Hong Kong and CUNY SPH" }, { - "author_name": "Tom Sante", - "author_inst": "Ghent University" + "author_name": "SL Au Yeung", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Pieter Mestdagh", - "author_inst": "Ghent University" + "author_name": "MK Kwok", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Jo Vandesompele", - "author_inst": "Ghent University" + "author_name": "JV Zhao", + "author_inst": "The University of Hong Kong" } ], "version": "1", @@ -1272546,25 +1273490,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.17.20156364", - "rel_title": "Preparing For the Next Pandemic: Learning Wild Mutational Patterns At Scale For For Analyzing Sequence Divergence In Novel Pathogens", + "rel_doi": "10.1101/2020.07.17.20156281", + "rel_title": "Rapid and sensitive detection of SARS-CoV-2 antibodies by biolayer interferometry", "rel_date": "2020-07-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20156364", - "rel_abs": "As we begin to recover from the COVID-19 pandemic, a key question is if we can avert such disasters in future. Current surveillance protocols generally focus on qualitative impact assessments of viral diversity 1. These efforts are primarliy aimed at ecosystem and human impact monitoring, and do not help to precisely quantify emergence. Currently, the similarity of biological strains is measured by the edit distance or the number of mutations that separate their genomic sequences 2-6, e.g. the number of mutations that make an avian flu strain human-adapted. However, ignoring the odds of those mutations in the wild keeps us blind to the true jump risk, and gives us little indication of which strains are more risky. In this study, we develop a more meaningful metric for comparison of genomic sequences. Our metric, the q-distance, precisely quantifies the probability of spontaneous jump by random chance. Learning from patterns of mutations from large sequence databases, the q-distance adapts to the specific organism, the background population, and realistic selection pressures; demonstrably improving inference of ancestral relationships and future trajectories. As important application, we show that the q-distance predicts future strains for seasonal Influenza, outperforming World Health Organization (WHO) recommended flu-shot composition almost consistently over two decades. Such performance is demonstrated separately for Northern and Southern hemisphere for different subtypes, and key capsidic proteins. Additionally, we investigate the SARS-CoV-2 origin problem, and precisely quantify the likelihood of different animal species that hosted an immediate progenitor, producing a list of related species of bats that have a quantifiably high likelihood of being the source. Additionally, we identify specific rodents with a credible likelihood of hosting a SARS-CoV-2 ancestor. Combining machine learning and large deviation theory, the analysis reported here may open the door to actionable predictions of future pandemics.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20156281", + "rel_abs": "Serological testing to evaluate antigen-specific antibodies in plasma is generally performed by rapid lateral flow test strips that lack quantitative results or by high complexity immunoassays that are time- and labor-intensive but provide quantitative results. Here, we describe a novel application of biolayer interferometry for the rapid detection of antigen-specific antibody levels in plasma samples, and demonstrate its utility for quantification of SARS-CoV-2 antibodies. Our biolayer interferometry immunosorbent assay (BLI-ISA) utilizes single-use biosensors in an automated \"dip-and-read\" format, providing real-time optical measurements of antigen loading, plasma antibody binding, and antibody isotype detection. Complete quantitative results are obtained in less than 20 minutes. BLI-ISA meets or exceeds the performance of high complexity methods such as Enzyme-Linked Immunosorbent Assay (ELISA) and Chemiluminescent Immunoassay. Importantly, our method can be immediately implemented on existing BLI platforms for urgent COVID-19 studies, such as serosurveillance and the evaluation of vaccine candidates. In a broader sense, BLI-ISA can be developed as a novel diagnostic platform to evaluate antibodies and other biomolecules in clinical specimens.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Jin Li", - "author_inst": "University of Chicago" + "author_name": "John V Dzimianski", + "author_inst": "University of California Santa Cruz" }, { - "author_name": "Timmy Li", - "author_inst": "University of Chicago" + "author_name": "Nicholas Lorig-Roach", + "author_inst": "University of California Santa Cruz" + }, + { + "author_name": "Sara M O'Rourke", + "author_inst": "University of California Santa Cruz" + }, + { + "author_name": "David L Alexander", + "author_inst": "Ontera Inc." }, { - "author_name": "Ishanu Chattopadhyay", - "author_inst": "University Of Chicago" + "author_name": "Jacqueline M Kimmey", + "author_inst": "University of California Santa Cruz" + }, + { + "author_name": "Rebecca M DuBois", + "author_inst": "University of California Santa Cruz" } ], "version": "1", @@ -1274348,37 +1275304,29 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.07.16.20155515", - "rel_title": "Are countries precautionary actions against COVID-19 effective? An assessment study of 175 countries worldwide", + "rel_doi": "10.1101/2020.07.16.20155523", + "rel_title": "The impact of climate temperature on counts, recovery, and death rates due to SARS-CoV-2 in South Africa.", "rel_date": "2020-07-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.16.20155515", - "rel_abs": "BackgroundThe Coronavirus Disease 2019 (COVID-19) pandemic has affected many countries negatively, particularly in terms of their health care and financial systems. Numerous countries have attempted to employ precautions to address this pandemic. This study was aimed at exploring and assessing the precautionary actions taken by 175 countries on six continents to prevent the spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2).\n\nMethodsAn observational study was conducted based on data collected during the period from December 31, 2019, until the end of April 2020. Several data were extracted, including information related to the date of the first reported case of SARS-CoV-2, total confirmed cases, total active cases, and more. In addition, seven validated indicators were used to assess the countries preparedness and precautionary actions.\n\nFindingsA total of 175 countries were included in the study. The total COVID-19 infection rate increased exponentially and rapidly in North America and Europe from March to April. The application of the precautions (indicators) varied between countries. School closures, quarantines and curfews were the most applied indicators among all countries. As for the relationship between the indicators and their effects on the infection rate, Italy and Spain were the top countries in Europe and adopted all indicators. Nevertheless, they faced high infection rates: 239,639 and 205,463 COVID-19 cases in Spain, and Italy, respectively.\n\nInterpretationThe precautionary actions might have played a role in limiting the spread of COVID-19 in several countries. However, many countries did not benefit from applying these indicators.\n\nFundingNo funding sources have been used for this work", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.16.20155523", + "rel_abs": "The impact of climate temperature on the counts (number of positive COVID-19 cases reported), recovery, and death rates of COVID-19 cases in South Africas nine provinces was investigated. The data for confirmed cases of COVID-19 were collected for March 25 and June 30, 2020 (14 weeks) from South Africas Government COVID-19 online resource, while the daily provincial climate temperatures were collected from the website of the South African Weather Service. Our result indicates that a higher or lower climate temperature does not prevent or delay the spread and death rates but shows significant positive impacts on the recovery rates of COVID-19 patients. Thus, it indicates that the climate temperature is unlikely to impose a strict limit on the spread of COVID-19. There is no correlation between the cases and death rates, an indicator that no particular temperature range is closely associated with a faster or slower death rate of COVID-19 patients. As evidence from our study, a warm climate temperature can only increase the recovery rate of COVID-19 patients, ultimately impacting the death and active case rates and freeing up resources quicker to enable health facilities to deal with those patients climbing rates who need treatment.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Thamir M Alshammari", - "author_inst": "King Saud University, Riyadh, Saudi Arabia, Saudi Food and Drug Authority, Riyadh, Saudi Arabia" - }, - { - "author_name": "Khalidah Alenzi", - "author_inst": "Ministry of Health, Tabuk, Saudi Arabia" - }, - { - "author_name": "Fatemah Alnofal", - "author_inst": "Saudi Food and Drug Authority, Riyadh, Saudi Arabia" + "author_name": "Prof. Naven Chetty", + "author_inst": "University of KwaZulu-Natal, South Africa" }, { - "author_name": "Ghada Fradees", - "author_inst": "Ministry of Health, Alqassim, Saudi Arabia" + "author_name": "Dr. Bamise Adeleye", + "author_inst": "University of KwaZulu-Natal, South Africa" }, { - "author_name": "Ali Altebainawi", - "author_inst": "Medication Safety Research Chair, King Saud University, Riyadh, Saudi Arabia, Saudi Ministry of Health, Hail, Saudi Arabia" + "author_name": "Abiola Olawale Ilori", + "author_inst": "University of KwaZulu-Natal" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1276390,177 +1277338,141 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.14.20152728", - "rel_title": "Vitamin D supplementation to prevent acute respiratory infections: systematic review and meta-analysis of aggregate data from randomised controlled trials", + "rel_doi": "10.1101/2020.07.15.20131789", + "rel_title": "SARS-CoV-2 Viral Load is Associated with Increased Disease Severity and Mortality", "rel_date": "2020-07-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.14.20152728", - "rel_abs": "ObjectivesTo assess the overall effect of vitamin D supplementation on risk of acute respiratory infection (ARI), and to identify factors modifying this effect.\n\nDesignWe conducted a systematic review and meta-analysis of data from randomised controlled trials (RCTs) of vitamin D for ARI prevention using a random effects model. Pre-specified sub-group analyses were done to determine whether effects of vitamin D on risk of ARI varied according to baseline 25-hydroxyvitamin D (25[OH]D) concentration or dosing regimen.\n\nData SourcesMEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, ClinicalTrials.gov and the International Standard RCT Number (ISRCTN) registry from inception to May 2020.\n\nEligibility Criteria for Selecting StudiesDouble-blind RCTs of supplementation with vitamin D or calcidiol, of any duration, were eligible if they were approved by a Research Ethics Committee and if ARI incidence was collected prospectively and pre-specified as an efficacy outcome.\n\nResultsWe identified 40 eligible RCTs (total 30,956 participants, aged 0 to 95 years). Data were obtained for 29,841 (96.5%) of 30,909 participants in 39 studies. For the primary comparison of vitamin D supplementation vs. placebo, the intervention reduced risk of ARI overall (Odds Ratio [OR] 0.89, 95% CI 0.81 to 0.98; P for heterogeneity 0.009). No statistically significant effect of vitamin D was seen for any of the sub-groups defined by baseline 25(OH)D concentration. However, protective effects were seen for trials in which vitamin D was given using a daily dosing regimen (OR 0.75, 95% CI 0.61 to 0.93); at daily dose equivalents of 400-1000 IU (OR 0.70, 95% CI 0.55 to 0.89); and for a duration of [≤]12 months (OR 0.82, 95% CI 0.72 to 0.94). Vitamin D did not influence the proportion of participants experiencing at least one serious adverse event (OR 0.94, 95% CI 0.81 to 1.08). Risk of bias within individual studies was assessed as being low for all but two trials. A funnel plot showed asymmetry, suggesting that small trials showing non-protective effects of vitamin D may have been omitted from the meta-analysis.\n\nConclusionsVitamin D supplementation was safe and reduced risk of ARI, despite evidence of significant heterogeneity across trials. The overall effect size may have been over-estimated due to publication bias. Protection was associated with administration of daily doses of 400-1000 IU vitamin D for up to 12 months. The relevance of these findings to COVID-19 is not known and requires investigation.\n\nSystematic Review RegistrationCRD42020190633\n\nO_TEXTBOXSummary Box\n\nWhat is already known on this subject?O_LIA previous individual participant data meta-analysis from 10,933 participants in 25 randomised controlled trials (RCTs) of vitamin D supplementation for the prevention of acute respiratory infection (ARI) demonstrated an overall protective effect (number needed to treat to prevent one ARI [NNT]=33).Sub-group analysis revealed most benefit in those with the lowest vitamin D status at baseline and not receiving bolus doses.\nC_LI\n\nWhat this study addsO_LIWe updated this meta-analysis with trial-level data from an additional 14 placebo-controlled RCTs published since December 2015 (i.e. new total of 39 studies with 29,841 participants).\nC_LIO_LIAn overall protective effect of vitamin D supplementation against ARI was seen (NNT=36).\nC_LIO_LIA funnel plot revealed evidence of publication bias, which could have led to an over-estimate of the protective effect.\nC_LIO_LINo statistically significant effect of vitamin D was seen for any of the sub-groups defined by baseline 25(OH)D concentration.\nC_LIO_LIStrongest protective effects were associated with administration of daily doses of 400-1000 IU vitamin D for [≤]12 months (NNT=8).\nC_LI\n\nC_TEXTBOX", - "rel_num_authors": 40, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.15.20131789", + "rel_abs": "The relationship between SARS-CoV-2 viral load and risk of disease progression remains largely undefined in coronavirus disease 2019 (COVID-19). We quantified SARS-CoV-2 viral load from participants with a diverse range of COVID-19 severity, including those requiring hospitalization, outpatients with mild disease, and individuals with resolved infection. SARS-CoV-2 plasma RNA was detected in 27% of hospitalized participants and 13% of outpatients diagnosed with COVID-19. Amongst the participants hospitalized with COVID-19, higher prevalence of detectable SARS-CoV-2 plasma viral load was associated with worse respiratory disease severity, lower absolute lymphocyte counts, and increased markers of inflammation, including C-reactive protein and IL-6. SARS-CoV-2 viral loads, especially plasma viremia, were associated with increased risk of mortality. SARS-CoV-2 viral load may aid in the risk stratification of patients with COVID-19 and its role in disease pathogenesis should be further explored.", + "rel_num_authors": 31, "rel_authors": [ { - "author_name": "David Jolliffe", - "author_inst": "Queen Mary University of London" - }, - { - "author_name": "Carlos A Camargo Jr.", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "John Sluyter", - "author_inst": "University of Auckland" - }, - { - "author_name": "Mary Aglipay", - "author_inst": "St Michael's Hospital, Toronto" - }, - { - "author_name": "John Aloia", - "author_inst": "Winthrop University Hospital" - }, - { - "author_name": "Peter Bergman", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Arturo Borzutzky", - "author_inst": "Pontificia Universidad Catolica de Chile" - }, - { - "author_name": "Camilla Damsgaard", - "author_inst": "University of Copenhagen" - }, - { - "author_name": "Gal Dubnov-Raz", - "author_inst": "Edmond and Lily Safra Children's Hospital, Tel Hashomer" - }, - { - "author_name": "Susanna Esposito", - "author_inst": "University of Parma" + "author_name": "Jesse M Fajnzylber", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Davaasambuu Ganmaa", - "author_inst": "Harvard School of Public Health" + "author_name": "James Regan", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Clare Gilham", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Kendyll Coxen", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Adit Ginde", - "author_inst": "University of Colorado School of Medicine" + "author_name": "Heather Corry", + "author_inst": "Brigham and Women's Hospital, Boston, MA" }, { - "author_name": "Inbal Golan-Tripto", - "author_inst": "Ben-Gurion University" + "author_name": "Colline Wong", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Cameron Grant", - "author_inst": "University of Auckland" + "author_name": "Alexandra Rosenthal", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Chris Griffiths", - "author_inst": "Queen Mary University of London" + "author_name": "Daniel Worrall", + "author_inst": "Ragon Institute of MGH, MIT and Harvard, Harvard Medical School, Cambridge, MA" }, { - "author_name": "Anna Maria Hibbs", - "author_inst": "Case Western Reserve University School of Medicine" + "author_name": "Francoise Giguel", + "author_inst": "Massachusetts General Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Wim Janssens", - "author_inst": "KU Leuven" + "author_name": "Alicja Piechocka-Trocha", + "author_inst": "Ragon Institute of MGH, MIT and Harvard, Harvard Medical School, Cambridge, MA" }, { - "author_name": "Anuradha Vaman Khadilkar", - "author_inst": "Hirabai Cowasji Jehangir Medical Research Institute" + "author_name": "Caroline Atyeo", + "author_inst": "Ragon Institute of MGH, MIT and Harvard, Harvard Medical School, Cambridge, MA" }, { - "author_name": "Ilkka Laaksi", - "author_inst": "University of Tampere" + "author_name": "Stephanie Fischinger", + "author_inst": "Ragon Institute of MGH, MIT and Harvard, Harvard Medical School, Cambridge, MA" }, { - "author_name": "Margaret T Lee", - "author_inst": "Columbia University Medical Center" + "author_name": "Andrew Chan", + "author_inst": "Massachusetts General Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Mark Loeb", - "author_inst": "McMaster University" + "author_name": "Keith T Flaherty", + "author_inst": "Massachusetts General Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Jonathon Maguire", - "author_inst": "University of Toronto" + "author_name": "Kathryn Hall", + "author_inst": "Massachusetts General Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "David T Mauger", - "author_inst": "Pennsylvania State University" + "author_name": "Michael Dougan", + "author_inst": "Massachusetts General Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Pawel Majak", - "author_inst": "University of Lodz" + "author_name": "Edward T Ryan", + "author_inst": "Massachusetts General Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Semira Manaseki-Holland", - "author_inst": "University of Birmingham" + "author_name": "Elizabeth Gillespie", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "David Murdoch", - "author_inst": "University of Otago" + "author_name": "Rida Chishti", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Akio Nakashima", - "author_inst": "Jikei University School of Medicine" + "author_name": "Yijia Li", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Rachel E Neale", - "author_inst": "QIMR Berghofer Medical Research Institute" + "author_name": "Nikolaus Jilg", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA and Massachusetts General Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Hai Pham", - "author_inst": "QIMR Berghofer" + "author_name": "Dusan Hanidziar", + "author_inst": "Massachusetts General Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Christine Rake", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Rebecca M Baron", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Judith Rees", - "author_inst": "Geisel School of Medicine at Dartmouth" + "author_name": "Lindsey Baden", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Jenni Rosendahl", - "author_inst": "University of Helsinki" + "author_name": "Athe M Tsibris", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Robert Scragg", - "author_inst": "University of Auckland" + "author_name": "Katrina A Armstrong", + "author_inst": "Massachusetts General Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Dheeraj Shah", - "author_inst": "University College of Medical Sciences, Delhi" + "author_name": "Daniel R Kuritzkes", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Yoshiki Shimizu", - "author_inst": "FANCL Corporation, Yokohama" + "author_name": "Galit Alter", + "author_inst": "Ragon Institute of MGH, MIT and Harvard, Harvard Medical School, Cambridge, MA and Massachusetts General Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Steve Simpson-Yap", - "author_inst": "University of Tasmania" + "author_name": "Bruce D Walker", + "author_inst": "Ragon Institute of MGH, MIT and Harvard, Harvard Medical School, Cambridge, MA and Massachusetts General Hospital, Harvard Medical School, Boston, MA and Howard" }, { - "author_name": "Geeta Trilok Kumar", - "author_inst": "University of Delhi" + "author_name": "Xu Yu", + "author_inst": "Ragon Institute of MGH, MIT and Harvard, Harvard Medical School, Cambridge, MA and Massachusetts General Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Mitsuyoshi Urashima", - "author_inst": "Jikei University School of Medicine" + "author_name": "Jonathan Li", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" }, { - "author_name": "Adrian R Martineau", - "author_inst": "Queen Mary University of London" + "author_name": "- Massachusetts Consortium for Pathogen Readiness", + "author_inst": "" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1278344,59 +1279256,83 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.07.16.206680", - "rel_title": "Simulations support the interaction of the SARS-CoV-2 spike protein with nicotinic acetylcholine receptors and suggest subtype specificity", + "rel_doi": "10.1101/2020.07.17.20156315", + "rel_title": "HIGH VERSUS STANDARD DOSES OF CORTICOSTEROIDS IN COVID-19 PATIENTS WITH AN ACUTE RESPIRATORY DISTRESS SYNDROME: a controlled observational comparative study.", "rel_date": "2020-07-17", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.16.206680", - "rel_abs": "Changeux et al. recently suggested that the SARS-CoV-2 spike (S) protein may interact with nicotinic acetylcholine receptors (nAChRs). Such interactions may be involved in pathology and infectivity. Here, we use molecular simulations of validated atomically detailed structures of nAChRs, and of the S protein, to investigate this nicotinic hypothesis. We examine the binding of the Y674-R685 loop of the S protein to three nAChRs, namely the human 4{beta}2 and 7 subtypes and the muscle-like {beta}{gamma}d receptor from Tetronarce californica. Our results indicate that Y674-R685 has affinity for nAChRs and the region responsible for binding contains the PRRA motif, a four-residue insertion not found in other SARS-like coronaviruses. In particular, R682 has a key role in the stabilisation of the complexes as it forms interactions with loops A, B and C in the receptors binding pocket. The conformational behaviour of the bound Y674-R685 region is highly dependent on the receptor subtype, adopting extended conformations in the 4{beta}2 and 7 complexes and more compact ones when bound to the muscle-like receptor. In the 4{beta}2 and {beta}{gamma}d complexes, the interaction of Y674-R685 with the receptors forces the loop C region to adopt an open conformation similar to other known nAChR antagonists. In contrast, in the 7 complex, Y674-R685 penetrates deeply into the binding pocket where it forms interactions with the residues lining the aromatic box, namely with TrpB, TyrC1 and TyrC2. Estimates of binding energy suggest that Y674-R685 forms stable complexes with all three nAChR subtypes. Analyses of the simulations of the full-length S protein show that the Y674-R685 region is accessible for binding, and suggest a potential binding orientation of the S protein with nAChRs.", - "rel_num_authors": 10, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20156315", + "rel_abs": "INTRODUCTIONDespite the increasing evidence of the benefit of corticosteroids for the treatment of moderate-severe Coronavirus disease 2019 (COVID-19) patients, no data are available about the potential role of high doses of steroids for these patients.\n\nMETHODSAll consecutive confirmed COVID-19 patients admitted to a single center were selected, including those treated with steroids and an acute respiratory distress syndrome (ARDS). Patients were allocated to the high doses (HD, [≥]250mg/day of methylprednisolone) of corticosteroids or the standard doses (SD, [≤]1.5mg/kg/day of methylprednisolone) at discretion of treating physician. The primary endpoint was the mortality between both cohorts and secondary endpoints were the risk of need for mechanical ventilation (MV) or death and the risk of developing a severe ARDS.\n\nRESULTS573 patients were included: 428 (74.7%) men, with a median (IQR) age of 64 (54-73) years. In HD cohort, a worse baseline respiratory situation was observed and male sex, older age and comorbidities were significantly more common. After adjusting by baseline characteristics, HD were associated with a higher mortality than SD (adjusted-OR 2.46, 95% CI 1.58 - 3.83, p<0.001) and with an increased risk of needing MV or death (adjusted-OR 2.50, p=0.001). Conversely, the risk of developing a severe ARDS was similar between groups. Interaction analysis showed that HD increased mortality exclusively in elderly patients.\n\nCONCLUSIONOur real-world experience advises against exceeding 1-1.5mg/kg/day of corticosteroids for severe COVID-19 with an ARDS, especially in older subjects. This reinforces the rationale of modulating rather than suppressing immune responses in these patients.\n\nSUMMARYIn patients with severe COVID-19, high doses of corticosteroids are associated with a higher mortality and risk of need for mechanical ventilation or death compared to standard doses. This deleterious effect is mainly observed in the elderly.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Ana Sofia Oliveira", - "author_inst": "University of Bristol" + "author_name": "Enric Monreal", + "author_inst": "Department of Neurology, Hospital Universitario Ramon y Cajal, Universidad de Alcala, IRYCIS, Madrid, Spain." }, { - "author_name": "Amaurys Avila Ibarra", - "author_inst": "University of Bristol" + "author_name": "Susana Sainz de la Maza", + "author_inst": "Department of Neurology, Hospital Universitario Ramon y Cajal, Universidad de Alcala, IRYCIS, Madrid, Spain." }, { - "author_name": "Isabel Bermudez", - "author_inst": "Oxford Brookes University" + "author_name": "Elena Natera-Villalba", + "author_inst": "Department of Neurology, Hospital Universitario Ramon y Cajal, Universidad de Alcala, IRYCIS, Madrid, Spain." }, { - "author_name": "Lorenzo Casalino", - "author_inst": "University of California, San Diego" + "author_name": "Alvaro Beltran-Corbellini", + "author_inst": "Department of Neurology, Hospital Universitario Ramon y Cajal, Universidad de Alcala, IRYCIS, Madrid, Spain." }, { - "author_name": "Zied Gaieb", - "author_inst": "University of California, San Diego" + "author_name": "Fernando Rodriguez-Jorge", + "author_inst": "Department of Neurology, Hospital Universitario Ramon y Cajal, Universidad de Alcala, IRYCIS, Madrid, Spain." }, { - "author_name": "Deborah K Shoemark", - "author_inst": "University of Bristol" + "author_name": "Jose Ignacio Fernandez-Velasco", + "author_inst": "Department of Immunology, Hospital Universitario Ramon y Cajal, Universidad de Alcala, IRYCIS, Madrid, Spain." }, { - "author_name": "Timothy Gallagher", - "author_inst": "University of Bristol" + "author_name": "Paulette Walo-Delgado", + "author_inst": "Department of Immunology, Hospital Universitario Ramon y Cajal, Universidad de Alcala, IRYCIS, Madrid, Spain." }, { - "author_name": "Richard B Sessions", - "author_inst": "University of Bristol" + "author_name": "Alfonso Muriel", + "author_inst": "Biostatistics Unit, Hospital Universitario Ramon y Cajal, Universidad de Alcala, IRYCIS, CIBERESP, Madrid, Spain." }, { - "author_name": "Rommie E Amaro", - "author_inst": "University of California, San Diego" + "author_name": "Javier Zamora", + "author_inst": "Biostatistics Unit, Hospital Universitario Ramon y Cajal, Universidad de Alcala, IRYCIS, CIBERESP, Madrid, Spain." }, { - "author_name": "Adrian J Mulholland", - "author_inst": "University of Bristol" + "author_name": "Araceli Alonso-Canovas", + "author_inst": "Department of Neurology, Hospital Universitario Ramon y Cajal, Universidad de Alcala, IRYCIS, Madrid, Spain." + }, + { + "author_name": "Jesus Fortun", + "author_inst": "Department of Infectious Diseases, Hospital Universitario Ramon y Cajal, Universidad de Alcala, IRYCIS, Madrid, Spain." + }, + { + "author_name": "Luis Manzano", + "author_inst": "Department of Internal Medicine, Hospital Universitario Ramon y Cajal, Universidad de Alcala, IRYCIS, Madrid, Spain." + }, + { + "author_name": "Beatriz Montero-Errasquin", + "author_inst": "Department of Geriatrics, Hospital Universitario Ramon y Cajal, Universidad de Alcala, IRYCIS, Madrid, Spain." + }, + { + "author_name": "Lucienne Costa-Frossard", + "author_inst": "Department of Neurology, Hospital Universitario Ramon y Cajal, Universidad de Alcala, IRYCIS, Madrid, Spain." + }, + { + "author_name": "Jaime Masjuan", + "author_inst": "Department of Neurology, Hospital Universitario Ramon y Cajal, Universidad de Alcala, IRYCIS, Madrid, Spain." + }, + { + "author_name": "Luisa Maria Villar", + "author_inst": "Department of Immunology, Hospital Universitario Ramon y Cajal, Universidad de Alcala, IRYCIS, Madrid, Spain." } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "biochemistry" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.07.17.20156117", @@ -1280162,29 +1281098,133 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.15.20154773", - "rel_title": "Improved COVID-19 Serology Test Performance by Integrating Multiple Lateral Flow Assays using Machine Learning", + "rel_doi": "10.1101/2020.07.15.20154690", + "rel_title": "The First Consecutive 5000 Patients with Coronavirus Disease 2019 from Qatar; a Nation-wide Cohort Study", "rel_date": "2020-07-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.15.20154773", - "rel_abs": "Mitigating transmission of SARS-CoV-2 has been complicated by the inaccessibility and, in some cases, inadequacy of testing options to detect present or past infection. Immunochromatographic lateral flow assays (LFAs) are a cheap and scalable modality for tracking viral transmission by testing for serological immunity, though systematic evaluations have revealed the low performance of some SARS-CoV-2 LFAs. Here, we re-analyzed existing data to present a proof-of-principle machine learning framework that may be used to inform the pairing of LFAs to achieve superior classification performance while enabling tunable False Positive Rates optimized for the estimated seroprevalence of the population being tested.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.15.20154690", + "rel_abs": "BackgroundThere are limited data on Coronavirus Disease 2019 (COVID-19) outcomes at a national level, and none after 60 days of follow up. The aim of this study was to describe national, 60-day all-cause mortality associated with COVID-19, and to identify risk factors associated with admission to an intensive care unit (ICU).\n\nMethodsThis was a retrospective cohort study including the first consecutive 5000 patients with COVID-19 in Qatar who completed 60 days of follow up by June 17, 2020. Outcomes included all-cause mortality at 60 days after COVID-19 diagnosis, and risk factors for admission to ICU.\n\nResultsIncluded patients were diagnosed with COVID-19 between February 28 and April 17, 2020. The majority (4436, 88.7%) were males and the median age was 35 years [interquartile range (IQR) 28- 43]. By 60 days after COVID-19 diagnosis, 14 patients (0.28%) had died, 10 (0.2%) were still in hospital, and two (0.04%) were still in ICU. Fatal COVID-19 cases had a median age of 59.5 years (IQR 55.8-68), and were mostly males (13, 92.9%). All included pregnant women (26, 0.5%), children (131, 2.6%), and healthcare workers (135, 2.7%) were alive and not hospitalized at the end of follow up.\n\nA total of 1424 patients (28.5%) required hospitalization, out of which 108 (7.6%) were admitted to ICU. Most frequent co-morbidities in hospitalized adults were diabetes (23.2%), and hypertension (20.7%). Multivariable logistic regression showed that older age [adjusted odds ratio (aOR) 1.041, 95% confidence interval (CI) 1.022-1.061 per year increase; P <0.001], male sex (aOR 4.375, 95% CI 1.964-9.744; P <0.001), diabetes (aOR 1.698, 95% CI 1.050-2.746; P 0.031), chronic kidney disease (aOR 3.590, 95% CI 1.596-8.079, P 0.002), and higher BMI (aOR 1.067, 95% CI 1.027-1.108 per unit increase; P 0.001), were all independently associated with increased risk of ICU admission.\n\nConclusionsIn a relatively younger national cohort with a low co-morbidity burden, COVID-19 was associated with low all-cause mortality. Independent risk factors for ICU admission included older age, male sex, higher BMI, and co-existing diabetes or chronic kidney disease.", + "rel_num_authors": 30, "rel_authors": [ { - "author_name": "Cody T Mowery", - "author_inst": "UCSF" + "author_name": "Ali S. Omrani", + "author_inst": "Hamad Medical Corporation" }, { - "author_name": "Alexander Marson", - "author_inst": "UCSF" + "author_name": "Muna A. Almaslamani", + "author_inst": "Hamad Medical Corporation" }, { - "author_name": "Yun S Song", - "author_inst": "UC Berkeley" + "author_name": "Joanne Daghfal", + "author_inst": "Hamad Medical Corporation" }, { - "author_name": "Chun Jimmie Ye", - "author_inst": "UCSF" + "author_name": "Rand A. Alattar", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Mohamed Elgara", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Shahd H. Shaar", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Tawheeda Ibrahim", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Ahmed Zaqout", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Dana Bakdach", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Abdelrauof Akkari", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Anas Baiou", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Bassem Alhariri", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Reem Elajez", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Ahmed Husain", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Mohamed N. Badawi", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Fatma Ben Abid", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Sulieman Abu Jarir", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Shiema Abdalla", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Anvar Kaleeckal", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Kris Choda", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Venkateswara R. Chinta", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Mohamed A. Sherbash", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Khalil Al Ismail", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Mohammed Abukhattab", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Ali Ait Hssain", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Peter V. Coyle", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Roberto Bertollini", + "author_inst": "Ministry of Public Health" + }, + { + "author_name": "Michael P. Frenneaux", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Abdullatif Alkhal", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Hanan M. Al Kuwari", + "author_inst": "Ministry of Public Health" } ], "version": "1", @@ -1281616,51 +1282656,35 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2020.07.15.20154146", - "rel_title": "Seasonality of non-SARS, non-MERS Corona viruses and the impact of meteorological factors", - "rel_date": "2020-07-16", + "rel_doi": "10.1101/2020.07.13.20151985", + "rel_title": "Size Dependent Particle Removal Efficiency and Pressure Drop of a Dust Cleaning Material For Use as Facemask Filters for Protection during COVID-19", + "rel_date": "2020-07-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.15.20154146", - "rel_abs": "BackgroundSeasonality is a characteristic of some respiratory viruses. The aim of our study was to evaluate the seasonality and the potential effects of different meteorological factors on the detection rate of the non-SARS Corona Virus detection by PCR.\n\nMethodsWe performed a retrospective analysis of 12763 respiratory tract sample results (288 positive and 12475 negative) for non-SARS, non-MERS Corona viruses (NL63, 229E, OC43, HKU1). The effect of seven single weather factors on the Corona virus detection rate was fitted in a logistic regression model with and without adjusting for other weather factors.\n\nResultsCorona virus infections followed a seasonal pattern peaking from December to March and plunging from July to September. The seasonal effect was less pronounced in immunosuppressed patients compared to immunocompetent. Different automatic variable selection processes agreed to select the predictors temperature, relative humidity, cloud cover and precipitation as remaining predictors in the multivariable logistic regression model including all weather factors, with low ambient temperature, low relative humidity, high cloud cover and high precipitation being linked to increased Corona virus detection rates.\n\nConclusionsCorona virus infections followed a seasonal pattern, which was more pronounced in immunocompetent patients compared to immunosuppressed. Several meteorological factors were associated with the Corona virus detection rate. However, when mutually adjusting for all weather factors, only temperature, relative humidity, precipitation and cloud cover contributed independently to predicting the Corona virus detection rate.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.13.20151985", + "rel_abs": "COVID-19 pandemic has caused a severe demand for facemasks, and this has resulted in the use of those made from alternate media. As SARS-CoV-2 spreads primarily due to airborne droplets, it is critical to verify the filtration efficiency of these alternate media based facemasks. While several media are being tested and used, commercially available dust cleaners have shown reasonable filtration efficiency. This may also be due to the potential electrostatic charge on the surface which enhances capture of the fine particles. In this manuscript, we report the size dependent filtration efficiency studied systematically in a filter holder-based system as 47 mm punches; and test results on a mannequin that was 3D printed wearing a bandana mask that was placed in a chamber.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Olympia E Anastasiou", - "author_inst": "Institute for Virology, University Hospital Essen, University of Duisburg-Essen, Germany" - }, - { - "author_name": "Anika Huesing", - "author_inst": "Institute of Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University Duisburg-Essen, Essen, Germany" - }, - { - "author_name": "Johannes Korth", - "author_inst": "Department of Nephrology, University Hospital Essen, University of Duisburg-Essen, Germany" - }, - { - "author_name": "Fotis Theodoropoulos", - "author_inst": "Department of Pulmonary Medicine, University Hospital of Essen - Ruhrlandklinik, Essen, Germany" - }, - { - "author_name": "Christian Taube", - "author_inst": "Department of Pulmonary Medicine, University Hospital of Essen - Ruhrlandklinik, Essen, Germany" + "author_name": "David Dhanraj", + "author_inst": "Washington University in St. Louis" }, { - "author_name": "Karl-Heinz Joeckel", - "author_inst": "Centre for Clinical Studies (ZKSE), Institute for Medical Informatics, Biometry and Epidemiology, Medical Faculty, University Duisburg-Essen, Essen, Germany" + "author_name": "Shruti Choudhary", + "author_inst": "Washington University in St. Louis" }, { - "author_name": "Andreas Stang", - "author_inst": "Institute of Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University Duisburg-Essen, Essen, Germany" + "author_name": "Pat Raven", + "author_inst": "Washington University in St. Louis" }, { - "author_name": "Ulf Dittmer", - "author_inst": "Institute for Virology, University Hospital Essen, University of Duisburg-Essen, Germany" + "author_name": "Pratim Biswas", + "author_inst": "Washington University in Saint Louis" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2020.07.13.20152231", @@ -1283110,135 +1284134,51 @@ "category": "toxicology" }, { - "rel_doi": "10.1101/2020.07.15.20151852", - "rel_title": "Effect of Hydroxychloroquine in Hospitalized Patients with COVID-19: Preliminary results from a multi-centre, randomized, controlled trial.", + "rel_doi": "10.1101/2020.07.14.202887", + "rel_title": "Bioinformatic analysis of shared B and T cell epitopes amongst relevant coronaviruses to human health: Is there cross-protection?", "rel_date": "2020-07-15", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.15.20151852", - "rel_abs": "BackgroundHydroxychloroquine and chloroquine have been proposed as treatments for coronavirus disease 2019 (COVID-19) on the basis of in vitro activity, uncontrolled data, and small randomized studies.\n\nMethodsThe Randomised Evaluation of COVID-19 therapy (RECOVERY) trial is a randomized, controlled, open-label, platform trial comparing a range of possible treatments with usual care in patients hospitalized with COVID-19. We report the preliminary results for the comparison of hydroxychloroquine vs. usual care alone. The primary outcome was 28-day mortality.\n\nResults1561 patients randomly allocated to receive hydroxychloroquine were compared with 3155 patients concurrently allocated to usual care. Overall, 418 (26.8%) patients allocated hydroxychloroquine and 788 (25.0%) patients allocated usual care died within 28 days (rate ratio 1.09; 95% confidence interval [CI] 0.96 to 1.23; P=0.18). Consistent results were seen in all pre-specified subgroups of patients. Patients allocated to hydroxychloroquine were less likely to be discharged from hospital alive within 28 days (60.3% vs. 62.8%; rate ratio 0.92; 95% CI 0.85-0.99) and those not on invasive mechanical ventilation at baseline were more likely to reach the composite endpoint of invasive mechanical ventilation or death (29.8% vs. 26.5%; risk ratio 1.12; 95% CI 1.01-1.25). There was no excess of new major cardiac arrhythmia.\n\nConclusionsIn patients hospitalized with COVID-19, hydroxychloroquine was not associated with reductions in 28-day mortality but was associated with an increased length of hospital stay and increased risk of progressing to invasive mechanical ventilation or death.\n\nFundingMedical Research Council and NIHR (Grant ref: MC_PC_19056).\n\nTrial registrationsThe trial is registered with ISRCTN (50189673) and clinicaltrials.gov (NCT04381936).", - "rel_num_authors": 29, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.14.202887", + "rel_abs": "Within the last 30 years 3 coronaviruses, SARS-CoV, MERS-CoV and SARS-CoV-2, have evolved and adapted to cause disease and spread amongst the human population. From the three, SARS-CoV-2 has spread world-wide and to July 2020 it has been responsible for more than 11 million confirmed cases and over half a million deaths. In the absence of an effective treatment or vaccine, social distancing has been the most effective measure to control the pandemic. However it has become evident that as the virus spreads the only tool that will allow us to fully control it is an effective vaccine. There are currently more than 150 vaccine candidates in different stages of development using a variety of viral antigens, with the S protein being the most targeted antigen. Although some new experimental evidence suggests cross-reacting responses between coronaviruses are present in the population, it remains unknown whether potential shared antigens between different coronaviruses could provide cross-protection. Given that coronaviruses are emerging pathogens and continue to represent a threat to global health, the development of a SARS-Cov-2 vaccine that could provide universal protection against other coronaviruses should be pushed forward. Here we present a thorough review of reported B and T cell epitopes shared between SARS-CoV-2 and other relevant coronaviruses, in addition we used web-based tools to predict novel B and T cell epitopes that have not been reported before. Analysis of experimental evidence that is constantly emerging complemented with the findings of this study allow us support the hypothesis that cross-reactive responses, particularly those coming from T cells, might play a key role in controlling infection by SARS-CoV-2. We hope that with the evidence presented in this manuscript we provide arguments to encourage the study of cross-reactive responses in order to elucidate their role in immunity to SARS-CoV-2. Finally we expect our findings will aid targeted analysis of antigen-specific immune responses and guide future vaccine design aiming to develop a cross reactive effective vaccine against respiratory diseases caused by coronaviruses.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Peter Horby", - "author_inst": "Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom" + "author_name": "Diana Laura Pacheco-Olvera", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica, UMAE Hospital de Especialidades del Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social (IMS" }, { - "author_name": "Marion Mafham", - "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" - }, - { - "author_name": "Louise Linsell", - "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" + "author_name": "Stephanie Saint Remy-Hernandez", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica, UMAE Hospital de Especialidades del Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social (IMS" }, { - "author_name": "Jennifer L Bell", - "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" - }, - { - "author_name": "Natalie Staplin", - "author_inst": "MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" - }, - { - "author_name": "Jonathan R Emberson", - "author_inst": "MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" - }, - { - "author_name": "Martin Wiselka", - "author_inst": "University Hospitals fo Leicester NHS Trust and University of Leicester" - }, - { - "author_name": "Andrew Ustianowski", - "author_inst": "Regional Infectious Diseases Unit, North Manchester General Hospital & University of Manchester, Manchester, UK" - }, - { - "author_name": "Einas Elmahi", - "author_inst": "Research and Development Department, Northampton General Hospital, Northampton, United Kingdom" - }, - { - "author_name": "Benjamin Prudon", - "author_inst": "Department of Respiratory Medicine, North Tees & Hartlepool NHS Foundation Trust, Stockton-on-Tees, United Kingdom" - }, - { - "author_name": "Anthony Whitehouse", - "author_inst": "University Hospitals Birmingham NHS Foundation Trust and Institute of Microbiology & Infection, University of Birmingham, United Kingdom" - }, - { - "author_name": "Timothy Felton", - "author_inst": "Univeristy of Manchester and Manchester University NHS Foundation Trust, Manchester, United Kingdom" - }, - { - "author_name": "John Williams", - "author_inst": "James Cook University Hospital, Middlesbrough, United Kingdom" - }, - { - "author_name": "Jakki Faccenda", - "author_inst": "North West Anglia NHS Foundation Trust, Peterborough, United Kingdom" - }, - { - "author_name": "Jonathan Underwood", - "author_inst": "Department of Infectious Diseases, Cardiff and Vale University Health Board; Division of Infection and Immunity, Cardiff University, Cardiff, United Kingdom" + "author_name": "Ernesto Acevedo-Ochoa", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica, UMAE Hospital de Especialidades del Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social (IMS" }, { - "author_name": "J Kenneth Baillie", - "author_inst": "Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom" - }, - { - "author_name": "Lucy Chappell", - "author_inst": "School of Life Sciences, King's College London, London, United Kingdom" - }, - { - "author_name": "Saul N Faust", - "author_inst": "NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, " - }, - { - "author_name": "Thomas Jaki", - "author_inst": "Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom; MRC Biostatistics Unit, University of Cambridge, Cambridge, United Ki" - }, - { - "author_name": "Katie Jeffery", - "author_inst": "Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom" - }, - { - "author_name": "Wei Shen Lim", - "author_inst": "Respiratory Medicine Department, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom" - }, - { - "author_name": "Alan Montgomery", - "author_inst": "School of Medicine, University of Nottingham, Nottingham, United Kingdom" - }, - { - "author_name": "Kathryn Rowan", - "author_inst": "Intensive Care National Audit & Research Centre, London, United Kingdom" - }, - { - "author_name": "Joel Tarning", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Centre for Tropical Medicine and Global Hea" - }, - { - "author_name": "James A Watson", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Centre for Tropical Medicine and Global Hea" + "author_name": "Lourdes Arriaga-Pizano", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica, UMAE Hospital de Especialidades del Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social (IMS" }, { - "author_name": "Nicholas J White", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Centre for Tropical Medicine and Global Hea" + "author_name": "Arturo Cerbulo-Vazquez", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica, UMAE Hospital de Especialidades del Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social (IMS" }, { - "author_name": "Edmund Juszczak", - "author_inst": "Nuffield Department of Population Health, University of Oxford, United Kingdom" + "author_name": "Eduardo Ferat-Osorio", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica, Division de Investigacion en Salud, Servicio de Gastrocirugia, UMAE Hospital de Especialidades del Centro Medic" }, { - "author_name": "Richard Haynes", - "author_inst": "MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" + "author_name": "Tania Rivera-Hernandez", + "author_inst": "Catedras CONACYT. Unidad de Investigacion Medica en Inmunoquimica, UMAE Hospital de Especialidades del Centro Medico Nacional Siglo XXI, Instituto Mexicano del " }, { - "author_name": "Martin J Landray", - "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" + "author_name": "Constantino Lopez-Macias", + "author_inst": "Unidad de Investigacion Medica en Inmunoquimica, UMAE Hospital de Especialidades del Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social (IMS" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "confirmatory results", + "category": "immunology" }, { "rel_doi": "10.1101/2020.07.15.176933", @@ -1285016,21 +1285956,29 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.07.13.201277", - "rel_title": "Single-nucleotide conservation state annotation of SARS-CoV-2 genome", + "rel_doi": "10.1101/2020.07.14.201905", + "rel_title": "Dynamic tracking of variant frequencies depicts the evolution of mutation sites amongst SARS-CoV-2 genomes from India", "rel_date": "2020-07-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.13.201277", - "rel_abs": "Given the global impact and severity of COVID-19, there is a pressing need for a better understanding of the SARS-CoV-2 genome and mutations. Multi-strain sequence alignments of coronaviruses (CoV) provide important information for interpreting the genome and its variation. We apply a comparative genomics method, ConsHMM, to the multi-strain alignments of CoV to annotate every base of the SARS-CoV-2 genome with conservation states based on sequence alignment patterns among CoV. The learned conservation states show distinct enrichment patterns for genes, protein domains, and other regions of interest. Certain states are strongly enriched or depleted of SARS-CoV-2 mutations, which can be used to predict potentially consequential mutations. We expect the conservation states to be a resource for interpreting the SARS-CoV-2 genome and mutations.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.14.201905", + "rel_abs": "With the exponential spread of the COVID-19 pandemic across the world within the twelve months, SARS-CoV-2 strains are continuously trying to adapt themselves in the host environment by random mutations. While doing so, some variants with evolutionary advantages such as better human to human transmissibility potential might get naturally selected. This short communication demonstrates how the mutation frequency patterns are evolving in 2,457 SAR-CoV-2 strains isolated from COVID-19 patients across diverse Indian states. We have identified 19 such variants showing contrasting mutational probabilities in the span of seven months. Out of these, 14 variants are showing increasing mutational probabilities suggesting their propagation with time due to their unexplored evolutionary advantages. Whereas mutational probabilities of five variants have significantly decreased in June onwards as compared to March/April, suggesting their termination with time. Further in-depth investigation of these identified variants will provide valuable knowledge about the evolution, infection strategies, transmission rates, and epidemiology of SARS-CoV-2.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Soo Bin Kwon", - "author_inst": "University of California, Los Angeles" + "author_name": "Shenu Hudson B.", + "author_inst": "Institute of Bioinformatics and Applied Biotechnology (IBAB), Bengaluru" }, { - "author_name": "Jason Ernst", - "author_inst": "University of California, Los Angeles" + "author_name": "Vaishnavi Kolte", + "author_inst": "Institute of Bioinformatics and Applied Biotechnology (IBAB), Bengaluru" + }, + { + "author_name": "Azra Khan", + "author_inst": "Institute of Bioinformatics and Applied Biotechnology (IBAB), Bengaluru" + }, + { + "author_name": "Gaurav Sharma", + "author_inst": "Institute of Bioinformatics and Applied Biotechnology (IBAB), Bengaluru" } ], "version": "1", @@ -1286598,55 +1287546,39 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2020.07.13.20152348", - "rel_title": "Development of a data-driven COVID-19 prognostication tool to inform triage and step-down care for hospitalised patients in Hong Kong: A population based cohort study", + "rel_doi": "10.1101/2020.07.11.20151522", + "rel_title": "Municipality- level predictors of COVID-19 mortality in Mexico: a cautionary tale", "rel_date": "2020-07-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.13.20152348", - "rel_abs": "BackgroundThis is the first study on prognostication in an entire cohort of laboratory-confirmed COVID-19 patients in the city of Hong Kong. Prognostic tool is essential in the contingency response for the next wave of outbreak. This study aims to develop prognostic models to predict COVID-19 patients clinical outcome on day 1 and day 5 of hospital admission.\n\nMethodsWe did a retrospective analysis of a complete cohort of 1,037 COVID-19 laboratory-confirmed patients in Hong Kong as of 30 April 2020, who were admitted to 16 public hospitals with their data sourced from an integrated electronic health records system. It covered demographic information, chronic disease(s) history, presenting symptoms as well as the worst clinical condition status, biomarkers readings and Ct value of PCR tests on Day-1 and Day-5 of admission. The study subjects were randomly split into training and testing datasets in a 8:2 ratio. Extreme Gradient Boosting (XGBoost) model was used to classify the training data into three disease severity groups on Day-1 and Day-5.\n\nResultsThe 1,037 patients had a mean age of 37.8 (SD{+/-}17.8), 53.8% of them were male. They were grouped under three disease outcome: 4.8% critical/serious, 46.8% stable and 48.4% satisfactory. Under the full models, 30 indicators on Day-1 and Day-5 were used to predict the patients disease outcome and achieved an accuracy rate of 92.3% and 99.5%. With a trade-off between practical application and predictive accuracy, the full models were reduced into simpler models with seven common specific predictors, including the worst clinical condition status (4-level), age group, and five biomarkers, namely, CRP, LDH, platelet, neutrophil/lymphocyte ratio and albumin/globulin ratio. Day-1 models accuracy rate, macro- and micro-averaged sensitivity and specificity were 91.3%, 84.9%-91.3% and 96.0%-95.7% respectively, as compared to 94.2%, 95.9%-94.2% and 97.8%-97.1% under Day-5 model.\n\nConclusionsBoth Day-1 and Day-5 models can accurately predict the disease severity. Relevant clinical management could be planned according to the predicted patients outcome. The model is transformed into a simple online calculator to provide convenient clinical reference tools at the point of care, with an aim to inform clinical decision on triage and step-down care.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.11.20151522", + "rel_abs": "BackgroundInequalities and burden of comorbidities of the Coronavirus disease 2019 (COVID-19) vary importantly inside the countries. We aimed to analyze the Municipality-level factors associated with a high COVID-19 mortality rate of in Mexico.\n\nMethodsWe retrieved information from 142,643 cumulative confirmed symptomatic cases and 18,886 deaths of COVID-19 as of June 20th, 2020 from the publicly available database of the Ministry of Health of Mexico. Public official data of the most recent census and surveys of the country were used to adjust a negative binomial regression model with the quintiles (Q) of the distribution of sociodemographic and health outcomes among 2,457 Municipality-level. Expected Mortality Rates (EMR), Incidence Rate Ratios (IRR) and 95% Confidence Intervals are reported.\n\nResultsFactors associated with high MR of COVID-19, relative to Quintile 1 (Q1), were; diabetes prevalence (Q4, IRR=2.60), obesity prevalence (Q5, IRR=1.93), diabetes mortality rate (Q5, IRR=1.58), proportion of indigenous population (Q2, IRR=1.68), proportion of economically active population (Q5, IRR=1.50), density of economic units that operate essential activities (Q4, IRR=1.54) and population density (Q5, IRR=2.12). We identified 1,351 Municipality-level without confirmed COVID-19 deaths, of which, 202 had nevertheless high (Q4, Mean EMR= 8.0 deaths per 100,000) and 82 very high expected COVID-19 mortality (Q5, Mean EMR= 13.8 deaths per 100,000).\n\nConclusionThis study identified 1,351 Municipality-level of Mexico that, in spite of not having confirmed COVID-19 deaths yet, share characteristics that could eventually lead to a high mortality scenario later in the epidemic and warn against premature easing of mobility restrictions. Local information should be used to reinforce strategies of prevention and control of outbreaks in communities vulnerable to COVID-19.\n\nKey messagesO_LIPredictors of COVID-19 mortality varied importantly between Municipality-level.\nC_LIO_LIMunicipality-level factors associated with high mortality of COVID-19 were the prevalence of obesity and diabetes, mortality rate of diabetes, the proportion of indigenous and economically active population and population density.\nC_LIO_LIMunicipality-level with high case-fatality rates of COVID-19 are likely undergoing insufficient testing and should improve its availability.\nC_LIO_LIIdentified predictors ought to be considered by local governments to reinforce tailored strategies to prevent casualties in populations vulnerable to COVID-19, as mortality is expected to be eventually high in some Municipality-level that may not have reached the apex of the epidemic yet.\nC_LI", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Eva L.H. TSUI", - "author_inst": "Hong Kong Hospital Authority" - }, - { - "author_name": "Carrie Lui", - "author_inst": "Hong Kong Hospital Authority" - }, - { - "author_name": "Pauline P.S. Woo", - "author_inst": "Hong Kong Hospital Authority" - }, - { - "author_name": "Alan T.L. CHEUNG", - "author_inst": "Hong Kong Hospital Authority" - }, - { - "author_name": "Peggo K.W. Lam", - "author_inst": "Hong Kong Hospital Authority" + "author_name": "Alejandra Contreras-Manzano", + "author_inst": "Independent consultant" }, { - "author_name": "T.W. Tang", - "author_inst": "Hong Kong Hospital Authority" + "author_name": "Carlos M Guerrero-Lopez", + "author_inst": "Mexican Social Security Institute, Mexico." }, { - "author_name": "C.F. YIU", - "author_inst": "Hong Kong Hospital Authority" + "author_name": "Mercedes Aguerrebere", + "author_inst": "National Autonomous University of Mexico, Mexico." }, { - "author_name": "C.H. Wan", - "author_inst": "Hong Kong Hospital Authority" + "author_name": "Ana Cristina Sedas", + "author_inst": "Department of Global Health and Social Medicine, Harvard Medical School, United States of America." }, { - "author_name": "Libby H.Y. Lee", - "author_inst": "Hong Kong Hospital Authority" + "author_name": "Hector Lamadrid-Figueroa", + "author_inst": "Center for Population Health Research, National Institute of Public Health, Mexico." } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "health policy" }, { "rel_doi": "10.1101/2020.07.13.20152355", @@ -1288260,27 +1289192,43 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.07.13.199562", - "rel_title": "Identifying Key Determinants of SARS-CoV-2/ACE2 Tight Interaction", - "rel_date": "2020-07-13", + "rel_doi": "10.1101/2020.07.12.199059", + "rel_title": "Tafenoquine inhibits replication of SARS-Cov-2 at pharmacologically relevant concentrations in vitro", + "rel_date": "2020-07-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.13.199562", - "rel_abs": "SARS-CoV-2 virus, the causative agent of Covid-19, has fired up a global pandemic. The virus interacts with the human receptor angiotensin-converting enzyme 2 (ACE2) for invasion via receptor binding domain (RBD) on its spike protein. To provide a deeper understanding of this interaction, we performed microsecond simulations of the RBD-ACE2 complex for SARS- CoV-2 and compared it with the closely related SARS-CoV discovered in 2003. We show residues in the RBD of SARS-CoV-2 that were mutated from SARS-CoV, collectively help make RBD anchor much stronger to the N-terminal part of ACE2 than the corresponding residues on RBD of SARS-CoV. This would result in reduced dissociation rate of SARS-CoV-2 from human recep- tor protein compared to SARS-CoV. This phenomenon was consistently observed in simulations beyond 500 ns and was reproducible across different force fields. Altogether, our study shed light on the key residues and their dynamics at the virus spike and human receptor binding interface and advance our knowledge for the development of diagnostics and therapeutics to combat the pandemic efficiently.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.12.199059", + "rel_abs": "Tafenoquine [TQ] exhibited EC50/90s of ~ 2.6/5.1 M against SARS-CoV-2 in VERO E6 cells and was 4-fold more potent than hydroxychloroquine [HCQ]. Time-of-addition experiments were consistent with a different mechanism for TQ v HCQ. Physiologically based pharmacokinetic (PBPK) modeling suggested that lung unbound concentrations of TQ in COVID-19 patients may exceed the EC90 for at least 8 weeks after administration. The therapeutic potential for TQ in management of COVID-19 should be further evaluated.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Van A Ngo", - "author_inst": "Los Alamos National Laboratory" + "author_name": "Geoffrey Dow", + "author_inst": "60 Degrees Pharmaceuticals LLC" }, { - "author_name": "Ramesh K Jha", - "author_inst": "Los Alamos National Laboratory" + "author_name": "Angela Luttick", + "author_inst": "360Biolabs" + }, + { + "author_name": "Jen Fenner", + "author_inst": "360Biolabs" + }, + { + "author_name": "David Wesche", + "author_inst": "Certara" + }, + { + "author_name": "Karen Rowland Yeo", + "author_inst": "Certara" + }, + { + "author_name": "Craid Rayner", + "author_inst": "Certara" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "biophysics" + "category": "pharmacology and toxicology" }, { "rel_doi": "10.1101/2020.07.12.199364", @@ -1289750,39 +1290698,59 @@ "category": "radiology and imaging" }, { - "rel_doi": "10.1101/2020.07.10.20150797", - "rel_title": "Genetic associations for two biological age measures point to distinct aging phenotypes", + "rel_doi": "10.1101/2020.07.10.20150946", + "rel_title": "Commercial Serology Assays Predict Neutralization Activity Against SARS-CoV-2", "rel_date": "2020-07-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.10.20150797", - "rel_abs": "Biological age measures outperform chronological age in predicting various aging outcomes, yet little is known regarding genetic predisposition. We performed genome-wide association scans of two age-adjusted biological age measures (PhenoAgeAcceleration and BioAgeAcceleration), estimated from clinical biochemistry markers1,2 in European-descent participants from UK Biobank. The strongest signals were found in the APOE gene, tagged by the two major protein-coding SNPs, PhenoAgeAccel--rs429358 (APOE e4 determinant) (p=1.50x10-72); BioAgeAccel--rs7412 (APOE e2 determinant) (p=3.16x10-60). Interestingly, we observed inverse APOE e2 and e4 associations and unique pathway enrichments when comparing the two biological age measures. Genes associated with BioAgeAccel were enriched in lipid related pathways, while genes associated with PhenoAgeAccel showed enrichment for immune system, cell function, and carbohydrate homeostasis pathways, suggesting the two measures capture different aging domains. Our study reaffirms that aging patterns are heterogenous across individuals, and the manner in which a person ages may be partly attributed to genetic predisposition.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.10.20150946", + "rel_abs": "BackgroundCurrently it is unknown whether a positive serology results correlates with protective immunity against SARS-CoV-2. There are also concerns regarding the low positive predictive value of SARS-CoV-2 serology tests, especially when testing populations with low disease prevalence.\n\nMethodsA neutralization assay was validated in a set of PCR confirmed positive specimens and in a negative cohort. 9,530 specimens were screened using the Diazyme SARS-CoV-2 IgG serology assay and all positive results (N=164) were reanalyzed using the neutralization assay, the Roche total immunoglobin assay, and the Abbott IgG assay. The relationship between the magnitude of a positive SARS-CoV-2 serology result and the levels of neutralizing antibodies detected was correlated. Neutralizing antibody titers (ID50) were also longitudinally monitored in SARS-CoV-2 PCR confirmed patients.\n\nResultsThe SARS-CoV-2 neutralization assay had a PPA of 96.6% with a SARS-CoV-2 PCR test and a NPA of 98.0% across 100 negative controls. ID50 neutralization titers positively correlated with all three clinical serology platforms. Longitudinal monitoring of hospitalized PCR confirmed COVID-19 patients demonstrates they made high neutralization titers against SARS-CoV-2. PPA between the Diazyme IgG assay alone and the neutralization assay was 50.6%, while combining the Diazyme IgG assay with either the Roche or Abbott platforms increased the PPA to 79.2% and 78.4%, respectively.\n\nConclusionsFor the first time, we demonstrate that three widely available clinical serology assays positively correlate with SARS-CoV-2 neutralization activity observed in COVID-19 patients. When a two-platform screen and confirm approach was used for SARS-CoV-2 serology, nearly 80% of two-platform positive specimens had neutralization titers (ID50 >50).\n\nSummaryClinical performance of a SARS-CoV-2 neutralization assay was evaluated using SARS-CoV-2 PCR confirmed patients and SARS-CoV-2 negative individuals. The neutralization assay was compared with results from SARS-CoV-2 positive serology specimens. We demonstrate that positive SARS-CoV-2 serology results correlate with the presence of neutralization activity against SARS-CoV-2. We show a high false positive rate when using a single SARS-CoV-2 serology platform to screen populations with low disease prevalence; and confirm that using a two-platform approach for COVID-19 seropositives greatly improves positive predictive value for neutralization.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Chia-Ling Kuo", - "author_inst": "University of Connecticut Health" + "author_name": "Raymond T Suhandynata", + "author_inst": "UC San Diego" }, { - "author_name": "Luke C Pilling", - "author_inst": "University of Exeter" + "author_name": "Melissa A Hoffman", + "author_inst": "UC San Diego" }, { - "author_name": "Zuyun Liu", - "author_inst": "Zhejiang University School of Medicine" + "author_name": "Deli Huang", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Janice L Atkins", - "author_inst": "University of Exeter" + "author_name": "Jenny T Tran", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Morgan Levine", - "author_inst": "Yale University" + "author_name": "Michael J Kelner", + "author_inst": "UC San Diego" + }, + { + "author_name": "Sharon L Reed", + "author_inst": "UC San Diego" + }, + { + "author_name": "Ronald W McLawhon", + "author_inst": "UC San Diego" + }, + { + "author_name": "James E Voss", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "David Nemazee", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Robert Fitzgerald", + "author_inst": "University of California San Diego" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.07.11.20151365", @@ -1291368,103 +1292336,51 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2020.07.10.197913", - "rel_title": "A simple protein-based SARS-CoV-2 surrogate neutralization assay", + "rel_doi": "10.1101/2020.07.11.198291", + "rel_title": "A Highly Immunogenic Measles Virus-based Th1-biased COVID-19 Vaccine", "rel_date": "2020-07-11", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.10.197913", - "rel_abs": "Most of the patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mount a humoral immune response to the virus within a few weeks of infection, but the duration of this response and how it correlates with clinical outcomes has not been completely characterized. Of particular importance is the identification of immune correlates of infection that would support public health decision-making on treatment approaches, vaccination strategies, and convalescent plasma therapy. While ELISA-based assays to detect and quantitate antibodies to SARS-CoV-2 in patient samples have been developed, the detection of neutralizing antibodies typically requires more demanding cell-based viral assays. Here, we present a safe and efficient protein-based assay for the detection of serum and plasma antibodies that block the interaction of the SARS-CoV-2 spike protein receptor binding domain (RBD) with its receptor, angiotensin converting-enzyme 2 (ACE2). The assay serves as a surrogate neutralization assay and is performed on the same platform and in parallel with an enzyme-linked immunosorbent assay (ELISA) for the detection of antibodies against the RBD, enabling a direct comparison. The results obtained with our assay correlate with those of two viral based assays, a plaque reduction neutralization test (PRNT) that uses live SARS-CoV-2 virus, and a spike pseudotyped viral-vector-based assay.", - "rel_num_authors": 21, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.11.198291", + "rel_abs": "The COVID-19 pandemic is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and has spread world-wide with millions of cases and hundreds of thousands of deaths to date. The gravity of the situation mandates accelerated efforts to identify safe and effective vaccines. Here, we generated measles virus (MeV)-based vaccine candidates expressing the SARS-CoV-2 spike glycoprotein (S). Insertion of the full-length S protein gene in two different MeV genomic positions resulted in modulated S protein expression. The variant with lower S protein expression levels was genetically stable and induced high levels of effective Th1-biased antibody and T cell responses in mice after two immunizations. In addition to neutralizing IgG antibody responses in a protective range, multifunctional CD8+ and CD4+ T cell responses with S protein-specific killing activity were detected. These results are highly encouraging and support further development of MeV-based COVID-19 vaccines.\n\nAuthor ContributionsCH performed research, analyzed data, and wrote the paper; CS performed research and analyzed data; AA performed research and analyzed data; AE performed research and analyzed data; SM performed research, analyzed data, and wrote the paper; MH developed the bioinformatics pipeline and analyzed data; BS contributed new reagents and concepts; MDM designed and supervised research, analyzed data and wrote the paper; all authors read, corrected and approved the final manuscript.\n\nSignificance StatementThe COVID-19 pandemic has caused hundreds of thousands of deaths, yet. Therefore, effective vaccine concepts are urgently needed. In search for such a concept, we have analysed a measles virus-based vaccine candidate targeting SARS-CoV-2. Using this well known, safe vaccine backbone, we demonstrate here induction of functional immune responses in both arms of adaptive immunity with the desired immune bias. Therefore, occurrence of immunopathologies such as antibody-dependent enhancement or enhanced respiratory disease is rather unlikely. Moreover, the candidate still induces immunity against the measles, recognized as a looming second menace, when countries are entrapped to stop routine vaccination campaigns in the face of COVID-19. Thus, a bivalent measles-based COVID-19 vaccine could be the solution for two significant public health threats.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Kento T Abe", - "author_inst": "Lunenfeld-Tanenbaum Research Institute, Mt Sinai" - }, - { - "author_name": "Zhijie Li", - "author_inst": "University of Toronto" - }, - { - "author_name": "Reuben Samson", - "author_inst": "Lunenfeld-Tanenbaum Research Institute" - }, - { - "author_name": "Payman Samavarchi-Tehrani", - "author_inst": "Lunenfeld-Tanenbaum Research Institute" - }, - { - "author_name": "Emelissa J Valcourt", - "author_inst": "National Microbiology Laboratory, Public Health Agency of Canada" - }, - { - "author_name": "Heidi Wood", - "author_inst": "National Microbiology Laboratory, Public Health Agency of Canada" - }, - { - "author_name": "Patrick Budylowski", - "author_inst": "University of Toronto" - }, - { - "author_name": "Alan P. Dupuis II", - "author_inst": "Wadsworth Center" - }, - { - "author_name": "Roxie C Girardin", - "author_inst": "Wadsworth Center" - }, - { - "author_name": "Bhavisha Rathod", - "author_inst": "Lunenfeld-Tanenbaum Research Institute" - }, - { - "author_name": "Karen Colwill", - "author_inst": "Lunenfeld-Tanenbaum Research Institute" - }, - { - "author_name": "Allison J. McGeer", - "author_inst": "Mount Sinai Hospital" - }, - { - "author_name": "Samira Mubareka", - "author_inst": "Sunnybrook Research Institute" - }, - { - "author_name": "Jennifer L. Gommerman", - "author_inst": "University of Toronto" + "author_name": "Cindy Hoerner", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "Yves Durocher", - "author_inst": "National Research Council Canada" + "author_name": "Christoph Schuermann", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "Mario Ostrowski", - "author_inst": "University of Toronto" + "author_name": "Arne Auste", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "Kathleen A McDonough", - "author_inst": "Wadsworth Center, NYSDOH" + "author_name": "Aileen Ebenig", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "Michael A. Drebot", - "author_inst": "National Microbiology Laboratory, Public Health Agency of Canada" + "author_name": "Samada Muraleedharan", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "Steven J. Drews", - "author_inst": "Canadian Blood Services" + "author_name": "Maike Herrmann", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "James M Rini", - "author_inst": "University of Toronto" + "author_name": "Barbara Schnierle", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "Anne-Claude Gingras", - "author_inst": "Lunenfeld-Tanenbaum Research Institute" + "author_name": "Michael D Muehlebach", + "author_inst": "Paul-Ehrlich-Institut" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.07.11.198770", @@ -1293226,113 +1294142,73 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.09.20149104", - "rel_title": "Distinct patterns of SARS-CoV-2 transmission in two nearby communities in Wisconsin, USA", + "rel_doi": "10.1101/2020.07.09.20149583", + "rel_title": "Evolution and impact of COVID-19 outbreaks in care homes: population analysis in 189 care homes in one geographic region", "rel_date": "2020-07-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.09.20149104", - "rel_abs": "Evidence-based public health approaches that minimize the introduction and spread of new SARS-CoV-2 transmission clusters are urgently needed in the United States and other countries struggling with expanding epidemics. Here we analyze 247 full-genome SARS-CoV-2 sequences from two nearby communities in Wisconsin, USA, and find surprisingly distinct patterns of viral spread. Dane County had the 12th known introduction of SARS-CoV-2 in the United States, but this did not lead to descendant community spread. Instead, the Dane County outbreak was seeded by multiple later introductions, followed by limited community spread. In contrast, relatively few introductions in Milwaukee County led to extensive community spread. We present evidence for reduced viral spread in both counties, and limited viral transmission between counties, following the statewide \"Safer at Home\" public health order, which went into effect 25 March 2020. Our results suggest that early containment efforts suppressed the spread of SARS-CoV-2 within Wisconsin.", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.09.20149583", + "rel_abs": "BackgroundCOVID-19 has had large impact on care-home residents internationally. This study systematically examines care-home outbreaks of COVID-19 in a large Scottish health board.\n\nMethodsAnalysis of testing, cases and deaths using linked care-home, testing and mortality data for 189 care-homes with 5843 beds in a large Scottish Health Board up to 15/06/20.\n\nFindings70 (37.0%) of care-homes experienced a COVID-19 outbreak, 66 of which were in care-homes for older people where care-home size was strongly associated with outbreaks (OR per 20-bed increase 3.50, 95%CI 2.06 to 5.94). There were 852 confirmed cases and 419 COVID-related deaths, 401 (95.7%) of which occurred in care-homes with an outbreak, 16 (3.8%) in hospital, and two in the 119 care-homes without a known outbreak. For non-COVID related deaths, there were 73 excess deaths in care-homes with an outbreak, but no excess deaths in care-homes without an outbreak, and 24 fewer deaths than expected of care-home residents in hospital. A quarter of COVID-19 related cases and deaths occurred in five (2.6%) care-homes, and half in 13 (6.9%) care-homes.\n\nInterpretationThe large impact on excess deaths appears to be primarily a direct effect of COVID-19, with cases and deaths are concentrated in a minority of care homes. A key implication is that there is a large pool of susceptible residents if community COVID-19 incidence increases again. Shielding residents from potential sources of infection and rapid action into minimise outbreak size where infection is introduced will be critical in any wave 2.\n\nFundingNot externally funded.\n\nO_TEXTBOXResearch in context\n\nEvidence before this study\n\nWe searched PubMed and the medRxiv preprint server using terms long-term care, nursing home, care home, or residential care combined with COVID-19 and/or SARS-CoV-2, updated to 25th June. The existing published literature highlights the large impact in care-homes, and that atypical disease presentation, asymptomatic carriage and a presymptomatic infectious period is common in both residents and staff. One living systematic review confirms the international outbreak burden among residents and staff and high but varied international mortality rates. International modelling studies have failed to take account of the care-home environment and context, making estimates informed by general community transmission of infection. Only one peer-reviewed study was identified which evaluated US nursing home characteristics associated with outbreaks, finding associations with larger facility size, urban location, and ethnicity, but no association with quality ratings or ownership.\n\nAdded value of this study\n\nThis study reports data for all 189 care homes in one large Scottish health board, where 37% experienced an outbreak of COVID-19, with 95% of outbreaks in care-homes for older people. The number of beds was the only care-home characteristic statistically significantly associated with the presence of an outbreak. One-third of affected care homes had only single cases or short outbreaks, but sustained outbreaks were common, and there was evidence of potential reintroduction of infection in some care-homes with >14 day gaps between confirmed cases. Cases and mortality were heavily concentrated. In care-homes with an outbreak there were 472 excess deaths (12.3% of bed capacity, 3.1 times the average in the previous five years), 85% of which were COVID-19 related. There were only 16 COVID-19 related deaths and 14 other deaths of care-home residents in hospital in the same period, consistent with [~]20 non-COVID excess deaths occurring in care-homes being deaths that would have happened anyway. 99% of the excess deaths and of the COVID-19 related deaths were in care-homes with an outbreak, suggesting that quality and safety of care in the wider care system was not affected.\n\nImplications of all the available evidence\n\nOutbreak patterns varied considerably and more detailed understanding of why some care homes avoided or controlled outbreaks would allow learning to prepare for wave two. Systematic, regular testing and use of whole genome sequencing will inform understanding of transmission dynamics and future outbreak management. Future research should consider the built environment and organisation of care as other potentially modifiable factors to support infection control. Improving national and local data on the care-home population is a priority both for COVID-19 and for ensuring this vulnerable population receives better care in the future.\n\nC_TEXTBOX", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Gage Kahl Moreno", - "author_inst": "University of Wisconsin - Madison" - }, - { - "author_name": "Katarina M Braun", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Kasen K Riemersma", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Michael A Martin", - "author_inst": "Emory University" - }, - { - "author_name": "Peter J Halfmann", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Chelsea M Crooks", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Trent Prall", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "David Baker", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "John J Baczenas", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Anna S Heffron", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Mitchell Ramuta", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Jennifer K Burton", + "author_inst": "University of Glasgow" }, { - "author_name": "Manjeet Khubbar", - "author_inst": "City of Milwaukee Health Department Laboratory" + "author_name": "Gwen Bayne", + "author_inst": "NHS Lothian" }, { - "author_name": "Andrea M. Weiler", - "author_inst": "University of Wisconsin Madison" + "author_name": "Christine Evans", + "author_inst": "NHS Lothiann" }, { - "author_name": "Molly A Accola", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Frederike Garbe", + "author_inst": "NHS Lothian" }, { - "author_name": "William M Rehrauer", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Dermot Gorman", + "author_inst": "NHS Lothian" }, { - "author_name": "Shelby L O'Connor", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Naomi Honhold", + "author_inst": "NHS Lothian" }, { - "author_name": "Nasia Safdar", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Duncan McCormick", + "author_inst": "NHS Lothian" }, { - "author_name": "Caitlin S Pepperell", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Richard Othieno", + "author_inst": "NHS Lothian" }, { - "author_name": "Trivikram Dasu", - "author_inst": "City of Milwaukee Health Department Laboratory" + "author_name": "Janet Stevenson", + "author_inst": "NHS Lothian" }, { - "author_name": "Sanjib Bhattacharyya", - "author_inst": "City of Milwaukee Health Department Laboratory" + "author_name": "Stefanie Swietlik", + "author_inst": "NHS Lothian" }, { - "author_name": "Yoshihiro Kawaoka", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Kate Templeton", + "author_inst": "NHS Lothian" }, { - "author_name": "Katia Koelle", - "author_inst": "Emory University" + "author_name": "Mette Tranter", + "author_inst": "NHS Lothian" }, { - "author_name": "David H O'Connor", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Lorna Willocks", + "author_inst": "NHS Lothian" }, { - "author_name": "Thomas C Friedrich", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Bruce Guthrie", + "author_inst": "University of Edinburgh" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1294984,503 +1295860,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.07.20143024", - "rel_title": "Digestive Manifestations in Patients Hospitalized with COVID-19", + "rel_doi": "10.1101/2020.07.08.20148882", + "rel_title": "Post-lockdown detection of SARS-CoV-2 RNA in the wastewater of Montpellier, France", "rel_date": "2020-07-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.07.20143024", - "rel_abs": "BackgroundThe prevalence and significance of digestive manifestations in COVID-19 remain uncertain.\n\nMethodsConsecutive patients hospitalized with COVID-19 were identified across a geographically diverse alliance of medical centers in North America. Data pertaining to baseline characteristics, symptomatology, laboratory assessment, imaging, and endoscopic findings from the time of symptom onset until discharge or death were manually abstracted from electronic health records to characterize the prevalence, spectrum, and severity of digestive manifestations. Regression analyses were performed to evaluate the association between digestive manifestations and severe outcomes related to COVID-19.\n\nResultsA total of 1992 patients across 36 centers met eligibility criteria and were included. Overall, 53% of patients experienced at least one gastrointestinal symptom at any time during their illness, most commonly diarrhea (34%), nausea (27%), vomiting (16%), and abdominal pain (11%). In 74% of cases, gastrointestinal symptoms were judged to be mild. In total, 35% of patients developed an abnormal alanine aminotransferase or total bilirubin level; these were elevated to less than 5 times the upper limit of normal in 77% of cases. After adjusting for potential confounders, the presence of gastrointestinal symptoms at any time (odds ratio 0.93, 95% confidence interval 0.76-1.15) or liver test abnormalities on admission (odds ratio 1.31, 95% confidence interval 0.80-2.12) were not independently associated with mechanical ventilation or death.\n\nConclusionsAmong patients hospitalized with COVID-19, gastrointestinal symptoms and liver test abnormalities were common but the majority were mild and their presence was not associated with a more severe clinical course", - "rel_num_authors": 121, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.08.20148882", + "rel_abs": "The evolution of the COVID-19 pandemic can be monitored through the detection of SARS-CoV-2 RNA in sewage. Here, we measured the amount of SARS-CoV-2 RNA at the inflow point of the main waste water treatment plant (WWTP) of Montpellier, France. We collected samples 4 days before the end of lockdown and up to 45 days post-lockdown. We detected increased amounts of SARS-CoV-2 RNA at the WWTP, which was not correlated with the number of newly diagnosed patients. Future epidemiologic investigations may explain such asynchronous finding.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "B. Joseph Elmunzer", - "author_inst": "Medical University of South Carolina" - }, - { - "author_name": "Rebecca L. Spitzer", - "author_inst": "Medical University of South Carolina" - }, - { - "author_name": "Lydia D. Foster", - "author_inst": "Medical University of South Carolina" - }, - { - "author_name": "Ambreen A. Merchant", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Eric F. Howard", - "author_inst": "Vanderbilt University Medical Center" - }, - { - "author_name": "Vaishali A. Patel", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Mary K. West", - "author_inst": "Vanderbilt University Medical Center" - }, - { - "author_name": "Emad Qayad", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Rosemary Nustas", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Ali Zakaria", - "author_inst": "Ascension Providence Hospital" - }, - { - "author_name": "Marc S. Piper", - "author_inst": "Ascension Providence Hospital" - }, - { - "author_name": "Jason R. Taylor", - "author_inst": "Saint Louis University" - }, - { - "author_name": "Lujain Jaza", - "author_inst": "Saint Louis University" - }, - { - "author_name": "Nauzer Forbes", - "author_inst": "University of Calgary" - }, - { - "author_name": "Millie Chau", - "author_inst": "University of Calgary" - }, - { - "author_name": "Luis F. Lara", - "author_inst": "The Ohio State University Wexner Medical Center" - }, - { - "author_name": "Georgios I. Papachristou", - "author_inst": "The Ohio State University Wexner Medical Center" - }, - { - "author_name": "Michael L. Volk", - "author_inst": "Loma Linda University" - }, - { - "author_name": "Liam G. Hilson", - "author_inst": "University of Southern California" - }, - { - "author_name": "Selena Zhou", - "author_inst": "University of Southern California" - }, - { - "author_name": "Vladimir M. Kushnir", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Alexandria M. Lenyo", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Caroline G. McLeod", - "author_inst": "Medical University of South Carolina" - }, - { - "author_name": "Sunil Amin", - "author_inst": "University of Miami Miller School of Medicine" - }, - { - "author_name": "Gabriela N. Kuftinec", - "author_inst": "University of Miami Miller School of Medicine" - }, - { - "author_name": "Dhiraj Yadav", - "author_inst": "University of Pittsburgh Medical Center" - }, - { - "author_name": "Charlie Fox", - "author_inst": "University of Colorado Anschutz Medical Campus" - }, - { - "author_name": "Jennifer M. Kolb", - "author_inst": "University of Colorado Anschutz Medical Campus" - }, - { - "author_name": "Swati Pawa", - "author_inst": "Wake Forest University School of Medicine" - }, - { - "author_name": "Rishi Pawa", - "author_inst": "Wake Forest University School of Medicine" - }, - { - "author_name": "Andrew Canakis", - "author_inst": "Boston University Medical Center" - }, - { - "author_name": "Christopher Huang", - "author_inst": "Boston University Medical Center" - }, - { - "author_name": "Laith H. Jamil", - "author_inst": "Beaumont Health" - }, - { - "author_name": "Andrew M. Aneese", - "author_inst": "Beaumont Health" - }, - { - "author_name": "Benita K. Glamour", - "author_inst": "University Hospitals of Cleveland Medical Center" - }, - { - "author_name": "Zachary L. Smith", - "author_inst": "University Hospitals of Cleveland Medical Center" - }, - { - "author_name": "Katherine A. Hanley", - "author_inst": "Northwestern University Feinberg School of Medicine" - }, - { - "author_name": "Jordan Wood", - "author_inst": "Northwestern University Feinberg School of Medicine" - }, - { - "author_name": "Harsh K. Patel", - "author_inst": "Ochsner Health" - }, - { - "author_name": "Janak N. Shah", - "author_inst": "Ochsner Health" - }, - { - "author_name": "Emil Agarunov", - "author_inst": "Columbia University Medical Center" - }, - { - "author_name": "Amrita Sethi", - "author_inst": "Columbia University Medical Center" - }, - { - "author_name": "Evan L. Fogel", - "author_inst": "Indiana University School of Medicine" - }, - { - "author_name": "Gail McNulty", - "author_inst": "Indiana University School of Medicine" - }, - { - "author_name": "Abdul Haseeb", - "author_inst": "Loyola University Medical Center" - }, - { - "author_name": "Judy A. Trieu", - "author_inst": "Loyola University Medical Center" - }, - { - "author_name": "Rebekah E. Dixon", - "author_inst": "Icahn School of Medicine at Mt. Sinai" - }, - { - "author_name": "Jeong Yun Yang", - "author_inst": "Icahn School of Medicine at Mt Sinai" - }, - { - "author_name": "Robin B. Mendelsohn", - "author_inst": "Memorial Sloan Kettering Cancer Center" - }, - { - "author_name": "Delia Calo", - "author_inst": "Memorial Sloan Kettering Cancer Center" - }, - { - "author_name": "Olga C. Aroniadis", - "author_inst": "Renaissance School of Medicine at Stony Brook University" - }, - { - "author_name": "Joseph F. LaComb", - "author_inst": "Renaissance School of Medicine at Stony Brook University" - }, - { - "author_name": "James M. Scheiman", - "author_inst": "University of Virginia Medical School" - }, - { - "author_name": "Bryan G. Sauer", - "author_inst": "University of Virginia Medical School" - }, - { - "author_name": "Duyen T. Dang", - "author_inst": "Henry Ford Health System" - }, - { - "author_name": "Cyrus R. Piraka", - "author_inst": "Henry Ford Health System" - }, - { - "author_name": "Eric D. Shah", - "author_inst": "Dartmouth-Hitchcock Health" - }, - { - "author_name": "Heiko Pohl", - "author_inst": "Dartmouth-Hitchcock Health" - }, - { - "author_name": "William M. Tierney", - "author_inst": "University of Oklahoma Health Sciences Center" - }, - { - "author_name": "Stephanie Mitchell", - "author_inst": "University of Oklahoma Health Sciences Center" - }, - { - "author_name": "Ashwinee Condon", - "author_inst": "David Geffen School of Medicine at UCLA" - }, - { - "author_name": "Adrienne Lenhart", - "author_inst": "David Geffen School of Medicine at UCLA" - }, - { - "author_name": "Kulwinder S. Dua", - "author_inst": "Medical College of Wisconsin" - }, - { - "author_name": "Vikram S. Kanagala", - "author_inst": "Medical College of Wisconsin" - }, - { - "author_name": "Ayesha Kamal", - "author_inst": "Johns Hopkins Medical Institutions" - }, - { - "author_name": "Vikesh K. Singh", - "author_inst": "Johns Hopkins Medical Institutions" - }, - { - "author_name": "Maria Ines Pinto-Sanchez", - "author_inst": "McMaster University Hamilton Health Sciences" - }, - { - "author_name": "Joy M. Hutchinson", - "author_inst": "McMaster University Hamilton Health Sciences" - }, - { - "author_name": "Richard S. Kwon", - "author_inst": "Michigan Medicine" - }, - { - "author_name": "Sheryl J. Korsnes", - "author_inst": "Michigan Medicine" - }, - { - "author_name": "Harminder Singh", - "author_inst": "University of Manitoba" - }, - { - "author_name": "Zahra Solati", - "author_inst": "University of Manitoba" - }, - { - "author_name": "Amar R. Deshpande", - "author_inst": "University of Miami Miller School of Medicine" - }, - { - "author_name": "Don C. Rockey", - "author_inst": "Medical University of South Carolina" - }, - { - "author_name": "Teldon B. Alford", - "author_inst": "Medical University of South Carolina" - }, - { - "author_name": "Valerie Durkalski", - "author_inst": "Medical University of South Carolina" - }, - { - "author_name": "Field F. Willingham", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Patrick S. Yachimski", - "author_inst": "Vanderbilt University Medical Center" - }, - { - "author_name": "Darwin L. Conwell", - "author_inst": "The Ohio State University Wexner Medical Center" - }, - { - "author_name": "Evan Mosier", - "author_inst": "Loma Linda University" - }, - { - "author_name": "Mohamed Azab", - "author_inst": "Loma Linda University" - }, - { - "author_name": "Anish Patel", - "author_inst": "Loma Linda University" - }, - { - "author_name": "James Buxbaum", - "author_inst": "University of Southern California" - }, - { - "author_name": "Sachin Wani", - "author_inst": "University of Colorado Anschutz Medical Campus" - }, - { - "author_name": "Amitabh Chak", - "author_inst": "University Hospitals of Cleveland Medical Center" - }, - { - "author_name": "Amy E. Hosmer", - "author_inst": "University Hospitals of Cleveland Medical Center" - }, - { - "author_name": "Rajesh N. Keswani", - "author_inst": "Northwestern University Feinberg School of Medicine" - }, - { - "author_name": "Christopher J. DiMaio", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Michael S. Bronze", - "author_inst": "University of Oklahoma Health Sciences Center" - }, - { - "author_name": "Raman Muthusamy", - "author_inst": "David Geffen School of Medicine at UCLA" - }, - { - "author_name": "Marcia I. Canto", - "author_inst": "Johns Hopkins Medical Institutions" - }, - { - "author_name": "V. Mihajlo Gjeorgjievski", - "author_inst": "Beaumont Health" - }, - { - "author_name": "Zaid Imam", - "author_inst": "Beaumont Health" - }, - { - "author_name": "Fadi Odish", - "author_inst": "Beaumont Health" - }, - { - "author_name": "Ahmed I. Edhi", - "author_inst": "Beaumont Health" - }, - { - "author_name": "Molly Orosey", - "author_inst": "Beaumont Health" - }, - { - "author_name": "Abhinav Tiwari", - "author_inst": "Beaumont Health" - }, - { - "author_name": "Soumil Patwardhan", - "author_inst": "Beaumont Health" - }, - { - "author_name": "Nicholas G. Brown", - "author_inst": "Beaumont Health" - }, - { - "author_name": "Anish A. Patel", - "author_inst": "Columbia University Medical Center" - }, - { - "author_name": "Collins O. Ordiah", - "author_inst": "Medical University of South Carolina" - }, - { - "author_name": "Ian P. Sloan", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Lilian Cruz", - "author_inst": "Renaissance School of Medicine at Stony Brook University" - }, - { - "author_name": "Casey L. Koza", - "author_inst": "Vanderbilt University Medical Center" - }, - { - "author_name": "Uchechi Okafor", - "author_inst": "The Ohio State University Wexner Medical Center" - }, - { - "author_name": "Thomas Hollander", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Nancy Furey", - "author_inst": "University Hospitals of Cleveland Medical Center" - }, - { - "author_name": "Olga Reykhart", - "author_inst": "Renaissance School of Medicine at Stony Brook University" - }, - { - "author_name": "Natalia H. Zbib", - "author_inst": "Dartmouth-Hitchcock Health" - }, - { - "author_name": "John A. Damianos", - "author_inst": "Dartmouth-Hitchcock Health" - }, - { - "author_name": "James Esteban", - "author_inst": "Medical College of Wisconsin" - }, - { - "author_name": "Nick Hajidiacos", - "author_inst": "University of Manitoba" - }, - { - "author_name": "Melissa Saul", - "author_inst": "University of Pittsburgh Medical Center" - }, - { - "author_name": "Melanie Mays", - "author_inst": "University of Pittsburgh Medical Center" - }, - { - "author_name": "Gulsum Anderson", - "author_inst": "University of Pittsburgh Medical Center" + "author_name": "Julie Trottier", + "author_inst": "CNRS" }, { - "author_name": "Kelley Wood", - "author_inst": "University of Pittsburgh Medical Center" + "author_name": "Regis Darques", + "author_inst": "CNRS" }, { - "author_name": "Laura Mathews", - "author_inst": "University of Pittsburgh Medical Center" + "author_name": "Nassim Ait Mouheb", + "author_inst": "INRAE" }, { - "author_name": "Galina Diakova", - "author_inst": "University of Virginia Medical School" + "author_name": "Emma Partiot", + "author_inst": "CNRS" }, { - "author_name": "Molly Caisse", - "author_inst": "Dartmouth-Hitchcock Health" + "author_name": "Wiliam Bakhache", + "author_inst": "CNRS" }, { - "author_name": "Lauren Wakefield", - "author_inst": "Medical University of South Carolina" + "author_name": "Maika S Deffieu", + "author_inst": "CNRS" }, { - "author_name": "Haley Nitchie", - "author_inst": "Medical University of South Carolina" + "author_name": "Raphael Gaudin", + "author_inst": "CNRS" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "gastroenterology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.07.09.194639", @@ -1297381,83 +1297801,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.06.20145938", - "rel_title": "Correlation of ELISA based with random access serologic immunoassays for identifying adaptive immune response to SARS-CoV-2", + "rel_doi": "10.1101/2020.07.07.20147918", + "rel_title": "Reflection of connectivism in medical education and learning motivation 4 during COVID-19", "rel_date": "2020-07-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.06.20145938", - "rel_abs": "Public health emergency of SARS-CoV-2 has facilitated diagnostic testing as a related medical countermeasure against COVID-19 outbreak. Numerous serologic antibody tests have become available through an expedited federal emergency use only process. This paper highlights the analytical characteristic of an ELISA based assay by AnshLabs and three random access immunoassay (RAIA) by DiaSorin, Roche, and Abbott that have been approved for emergency use authorization (EUA), at a tertiary academic center in a low disease-prevalence area. The AnshLabs gave higher estimates of sero-prevalence, over the three RAIA methods. For positive results, AnshLabs had 93.3% and 100% concordance with DiaSorin or Abbott and Roche respectively. For negative results, AnshLabs had 69.7% and 73.0% concordance with DiaSorin and Roche or Abbott respectively. All discrepant samples that were positive by AnshLabs and negative by RAIA tested positive by all-in-one step SARS-CoV-2 Total (COV2T) assay performed on the automated Siemens Advia Centaur XPT analyzer. None of these methods, however, are useful in early diagnosis of SARS-CoV-2.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.07.20147918", + "rel_abs": "The COVID-19 pandemic has not only affected the global healthcare and economy but threatened the world of education altogether. Malaysia is not spared from this pandemic as all universities were forced to close and initiate online learning with the implementation of Movement Control Order since mid-March 2020.The abrupt shift from conventional medical education to fully virtual learning definitely deserves a reflection on how it affects the learning motivation among medical students. Hence, this is the first study that compares the effect of digital learning on learning motivation among medical students in Universiti Kebangsaan Malaysia (UKM) prior to and during the COVID-19 pandemic. A modified Students Motivation towards Science Learning (SMTSL) was used to assess the learning motivation of UKM medical students throughout Year 1-5. The number of students that use digital learning during COVID-19 is significantly higher compared to before COVID-19 (p<0.05). However, there is no significant difference (p=0.872) in learning motivation among medical students before and during COVID-19 crisis. Higher frequency in digital learning usage frequency does not exert a great impact on learning motivation. Reflections from each participant were collated to justify the current situation. This could be due to motivation coming from the very choice to pursue medicine as a doctor, which is mainly influenced by intrinsic motivation, and ability to adapt in difficult situations. Thus, medical educators should be creative in enhancing extrinsic motivation by making use of digital learning as a platform so that medical students are able to independently fish for information in the vast pool of digital information and apply in actual medical practice in the future for life-long learning.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Nguyen N Nguyen", - "author_inst": "Baylor Scott & White" - }, - { - "author_name": "Manohar B Mutnal", - "author_inst": "Baylor Scott & White" - }, - { - "author_name": "Richard R Gomez", - "author_inst": "Baylor Scott & White" - }, - { - "author_name": "Huy N Pham", - "author_inst": "Baylor Scott & White" - }, - { - "author_name": "Lam T Nguyen", - "author_inst": "Baylor Scott & White" - }, - { - "author_name": "William Koss", - "author_inst": "Baylor Scott & White" - }, - { - "author_name": "Arundhati Rao", - "author_inst": "Baylor Scott & White" - }, - { - "author_name": "Alejandro C Arroliga", - "author_inst": "Baylor Scott & White" - }, - { - "author_name": "Liping Wang", - "author_inst": "Baylor Scott & White" - }, - { - "author_name": "Dapeng Wang", - "author_inst": "Baylor Scott & White" - }, - { - "author_name": "Yinan Hua", - "author_inst": "Baylor Scott & White" - }, - { - "author_name": "Priscilla R Powell", - "author_inst": "Baylor Scott & White" - }, - { - "author_name": "Li Chen", - "author_inst": "Baylor Scott & White" + "author_name": "Noor A.S. Ismail", + "author_inst": "Universiti Kebangsaan Malaysia" }, { - "author_name": "Colin McCormack", - "author_inst": "Baylor Scott & White" + "author_name": "Jun Xin Lee", + "author_inst": "Universiti Kebangsaan Malaysia" }, { - "author_name": "Walter J. Linz", - "author_inst": "Baylor Scott & White" + "author_name": "Ahmad Hathim Ahmad Azman", + "author_inst": "Universiti Kebangsaan Malaysia" }, { - "author_name": "Amin A Mohammad", - "author_inst": "Baylor Scott & White" + "author_name": "Jing Yi Ng", + "author_inst": "Universiti Kebangsaan Malaysia" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pathology" + "category": "medical education" }, { "rel_doi": "10.1101/2020.07.07.20148304", @@ -1299115,31 +1299487,71 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.07.06.190660", - "rel_title": "The global and local distribution of RNA structure throughout the SARS-CoV-2 genome", + "rel_doi": "10.1101/2020.07.07.191775", + "rel_title": "Favipiravir and severe acute respiratory syndrome coronavirus 2 in hamster model", "rel_date": "2020-07-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.06.190660", - "rel_abs": "SARS-CoV-2 is the causative viral agent of COVID-19, the disease at the center of the current global pandemic. While knowledge of highly structured regions is integral for mechanistic insights into the viral infection cycle, very little is known about the location and folding stability of functional elements within the massive, ~30kb SARS-CoV-2 RNA genome. In this study, we analyze the folding stability of this RNA genome relative to the structural landscape of other well-known viral RNAs. We present an in-silico pipeline to locate regions of high base pair content across this long genome and also identify well-defined RNA structures, a method that allows for direct comparisons of RNA structural complexity within the several domains in SARS-CoV-2 genome. We report that the SARS-CoV-2 genomic propensity to stable RNA folding is exceptional among RNA viruses, superseding even that of HCV, one of the most highly structured viral RNAs in nature. Furthermore, our analysis reveals varying levels of RNA structure across genomic functional regions, with accessory and structural ORFs containing the highest structural density in the viral genome. Finally, we take a step further to examine how individual RNA structures formed by these ORFs are affected by the differences in genomic and subgenomic contexts. The conclusions reported in this study provide a foundation for structure-function hypotheses in SARS-CoV-2 biology, and in turn, may guide the 3D structural characterization of potential RNA drug targets for COVID-19 therapeutics.View Full Text", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.07.191775", + "rel_abs": "Despite no or limited pre-clinical evidence, repurposed drugs are massively evaluated in clinical trials to palliate the lack of antiviral molecules against SARS-CoV-2. Here we used a Syrian hamster model to assess the antiviral efficacy of favipiravir, understand its mechanism of action and determine its pharmacokinetics. When treatment was initiated before or simultaneously to infection, favipiravir had a strong dose effect, leading to dramatic reduction of infectious titers in lungs and clinical alleviation of the disease. Antiviral effect of favipiravir correlated with incorporation of a large number of mutations into viral genomes and decrease of viral infectivity. The antiviral efficacy observed in this study was achieved with plasma drug exposure comparable with those previously found during human clinical trials and was associated with weight losses in animals. Thereby, pharmacokinetic and tolerance studies are required to determine whether similar effects can be safely achieved in humans.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Rafael de Cesaris Araujo Tavares", - "author_inst": "Yale University, Department of Chemistry" + "author_name": "Jean-S\u00e9lim Driouich", + "author_inst": "Unit\u00e9 des Virus \u00c9mergents, UVE: Aix Marseille Univ, IRD 190, INSERM 1207, Marseille, France" }, { - "author_name": "Gandhar Mahadeshwar", - "author_inst": "Yale University, Department of Molecular Biophysics and Biochemistry" + "author_name": "Maxime Cochin", + "author_inst": "Unit\u00e9 des Virus \u00c9mergents, UVE: Aix Marseille Univ, IRD 190, INSERM 1207, Marseille, France" }, { - "author_name": "Anna Marie Pyle", - "author_inst": "Yale University, Department of Molecular, Cellular and Developmental Biology & Department of Chemistry, Howard Hughes Medical Institute" + "author_name": "Guillaume Lingas", + "author_inst": "Universit\u00e9 de Paris, IAME, INSERM, F-75018 Paris, France" + }, + { + "author_name": "Gr\u00e9gory Moureau", + "author_inst": "Unit\u00e9 des Virus \u00c9mergents, UVE: Aix Marseille Univ, IRD 190, INSERM 1207, Marseille, France" + }, + { + "author_name": "Franck Touret", + "author_inst": "Unit\u00e9 des Virus \u00c9mergents, UVE: Aix Marseille Univ, IRD 190, INSERM 1207, Marseille, France" + }, + { + "author_name": "Paul-R\u00e9mi Petit", + "author_inst": "Unit\u00e9 des Virus \u00c9mergents, UVE: Aix Marseille Univ, IRD 190, INSERM 1207, Marseille, France" + }, + { + "author_name": "G\u00e9raldine Piorkowski", + "author_inst": "Unit\u00e9 des Virus \u00c9mergents, UVE: Aix Marseille Univ, IRD 190, INSERM 1207, Marseille, France" + }, + { + "author_name": "Karine Barth\u00e9l\u00e9my", + "author_inst": "Unit\u00e9 des Virus \u00c9mergents, UVE: Aix Marseille Univ, IRD 190, INSERM 1207, Marseille, France" + }, + { + "author_name": "Bruno Coutard", + "author_inst": "Unit\u00e9 des Virus \u00c9mergents, UVE: Aix Marseille Univ, IRD 190, INSERM 1207, Marseille, France" + }, + { + "author_name": "J\u00e9r\u00e9mie Guedj", + "author_inst": "Universit\u00e9 de Paris, IAME, INSERM, F-75018 Paris, France" + }, + { + "author_name": "Xavier de Lamballerie", + "author_inst": "Unit\u00e9 des Virus \u00c9mergents, UVE: Aix Marseille Univ, IRD 190, INSERM 1207, Marseille, France" + }, + { + "author_name": "Caroline Solas", + "author_inst": "Unit\u00e9 des Virus \u00c9mergents, UVE: Aix Marseille Univ, IRD 190, INSERM 1207, Marseille, France ; Laboratoire de Pharmacocin\u00e9tique et Toxicologie, H\u00f4pital La Timone" + }, + { + "author_name": "Antoine Nougair\u00e8de", + "author_inst": "Unit\u00e9 des Virus \u00c9mergents, UVE: Aix Marseille Univ, IRD 190, INSERM 1207, Marseille, France" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "biophysics" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.07.06.182972", @@ -1300321,67 +1300733,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.07.06.20147025", - "rel_title": "Association between consumption of fermented vegetables and COVID-19 mortality at a country level in Europe", + "rel_doi": "10.1101/2020.07.06.20147637", + "rel_title": "Evaluation of a genetic risk score for severity of COVID-19 using human chromosomal-scale length variation.", "rel_date": "2020-07-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.06.20147025", - "rel_abs": "BackgroundMany foods have an antioxidant activity and nutrition may mitigate COVID-19. Some of the countries with a low COVID-19 mortality are those with a relatively high consumption of traditional fermented foods. To test the potential role of fermented foods in COVID-19 mortality in Europe, we performed an ecological study.\n\nMethodsThe European Food Safety Authority (EFSA) Comprehensive European Food Consumption Database was used to study the country consumption of fermented vegetables, pickled/marinated vegetables, fermented milk, yoghurt and fermented sour milk. We obtained the COVID-19 mortality per number of inhabitants from the Johns Hopkins Coronavirus Resource Center. EuroStat data were used for data on potential confounders at the country level including Gross Domestic Product (GDP) (2019), population density (2018), percentage of people older than 64 years (2019), unemployment rate (2019) and percentage obesity (2014, to avoid missing values). Mortality counts were analyzed with quasi-Poisson regression models - with log of population as an offset - to model the death rate while accounting for over-dispersion.\n\nResultsOf all the variables considered, including confounders, only fermented vegetables reached statistical significance with the COVID-19 death rate per country. For each g/day increase in the average national consumption of fermented vegetables, the mortality risk for COVID-19 decreased by 35.4% (95% CI: 11.4%, 35.5%). Adjustment did not change the point estimate and results were still significant.\n\nDiscussionThe negative ecological association between COVID-19 mortality and consumption of fermented vegetables supports the a priory hypothesis previously reported. The hypothesis needs to be tested in individual studies performed in countries where the consumption of fermented vegetables is common.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.06.20147637", + "rel_abs": "IntroductionThe course of COVID-19 varies from asymptomatic to severe (acute respiratory distress, cytokine storms, and death) in patients. The basis for this range in symptoms is unknown. One possibility is that genetic variation is responsible for the highly variable response to infection. We evaluated how well a genetic risk score based on chromosome-scale length variation and machine learning classification algorithms could predict severity of response to SARS-CoV-2 infection.\n\nMethodsWe compared 981 patients from the UK Biobank dataset who had a severe reaction to SARS-COV-2 infection before 27 April 2020 to a similar number of age matched patients drawn for the general UK Biobank population. For each patient, we built a profile of 88 numbers characterizing the chromosome-scale length variability of their germ line DNA. Each number represented one quarter of the 22 autosomes. We used the machine learning algorithm XGBoost to build a classifier that could predict whether a person would have a severe reaction to Covid-19 based only on their 88-number classification.\n\nResultsWe found that the XGBoost classifier could differentiate between the two classes at a significant level p = 2 {middle dot} 10 as measured against a randomized control and p = 3 {middle dot} 10 measured against the expected value of a random guessing algorithm (AUC=0.5). However, we found that the AUC of the classifier was only 0.51, too low for a clinically useful test.\n\nConclusion", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Susana Fonseca", - "author_inst": "University of Porto" - }, - { - "author_name": "Ioar Rivas", - "author_inst": "ISGlobAL" - }, - { - "author_name": "Dora Romaguera", - "author_inst": "ISGlobAL" - }, - { - "author_name": "Marcos Quijal", - "author_inst": "ISGlobAL" - }, - { - "author_name": "Wienczyslawa Czarlewski", - "author_inst": "MASK-air" - }, - { - "author_name": "Alain Vidal", - "author_inst": "Paris Institute of Technology for Life, Food and Environmental Sciences" - }, - { - "author_name": "Joao Fonseca", - "author_inst": "CINTESIS" - }, - { - "author_name": "Joan Ballester", - "author_inst": "ISGlobAL" - }, - { - "author_name": "Josep Anto", - "author_inst": "ISGlobAL" - }, - { - "author_name": "Xavier Basagana", - "author_inst": "ISGlobAL" - }, - { - "author_name": "Luis M Cunha", - "author_inst": "University of Porto" + "author_name": "Chris Toh", + "author_inst": "University of California, Irvine" }, { - "author_name": "Jean Bousquet", - "author_inst": "Macvia France" + "author_name": "James P Brody", + "author_inst": "University of California, Irvine" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "nutrition" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2020.07.06.20147751", @@ -1301655,57 +1302027,121 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.03.20144758", - "rel_title": "Comparison of two commercial platforms and a laboratory developed test for detection of SARS-CoV-2 RNA", + "rel_doi": "10.1101/2020.07.04.20146027", + "rel_title": "Sample Pooling as an efficient strategy for SARS-COV-2 RT-PCR screening: a multicenter study in Spain", "rel_date": "2020-07-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.03.20144758", - "rel_abs": "Mitigation of the ongoing COVID-19 pandemic requires reliable and accessible laboratory diagnostic services. We evaluated the performance of one LDT and two commercial tests, cobas(R) SARS-CoV-2 (Roche) and Amplidiag(R) COVID-19 (Mobidiag), for the detection of SARS-CoV-2 RNA in respiratory specimens. 183 specimens collected from suspected COVID-19 patients were studied with all three methods to compare their performance. In relation to the reference standard, which was established as the result obtained by two of the three studied methods, the positive percent agreement (PPA) was highest for cobas(R) test (100%), followed by Amplidiag(R) test and the LDT (98.9%). The negative percent agreement (NPA) was lowest for cobas(R) test (89.4%), followed by Amplidiag(R) test (98.8%) and the highest value was obtained for LDT (100%). The dilution series conducted for specimens, however, suggests significantly higher sensitivity for the cobas(R) assay in comparison with the other two assays and the low NPA value may be due to the same reason. In general, all tested assays performed adequately. Both the time from sample to result and hands-on time per sample were shortest for cobas(R) test. Clinical laboratories need to be prepared for uninterrupted high-throughput testing during the coming months in mitigation of the pandemic. To secure that, it is of critical importance for clinical laboratories to maintain several simultaneous platforms in their SARS-CoV-2 nucleic acid testing.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.04.20146027", + "rel_abs": "ImportanceThe actual demand on SARS-CoV-2 diagnosis is a current challenge for clinical laboratories. Sample pooling may help to ameliorate workload in clinical laboratories.\n\nObjectiveto evaluate the efficacy of sample pooling compared to the individual analysis for the diagnosis of CoVID-19, by using different commercial platforms for nucleic acid extraction and amplification.\n\nDesign and settingsobservational, prospective, multicentre study across 9 Spanish clinical microbiology laboratories including SARS-CoV-2 RNA testing performed in April 2020, during the first three days after acceptance to participate.\n\nParticipants and Methods3519 naso-oro-pharyngeal samples received at the participating laboratories were processed individually and in pools (351 pools) according to the existing methodology in each of the centres.\n\nResultsWe found that 253 pools (2519 samples) were negative, and 99 pools (990 samples) were positive; with 241 positive samples (6.85%), our pooling strategy would have saved 2167 PCR tests. For 29 pools (made out of 290 samples) we found discordant results when compared to their correspondent individual samples: in 24/29 pools (30 samples), minor discordances were found; for five pools (5 samples), we found major discordances. Sensitivity, specificity, positive and negative predictive values for pooling were 97.93%, 100%, 100% and 99.85% respectively; accuracy was 99.86% and kappa concordant coefficient was 0.988. As a result of the sample dilution effect of pooling, a loss of 2-3 Cts was observed for E, N or RdRP genes.\n\nConclusionwe show a high efficiency of pooling strategies for SARS-CoV-2 RNA testing, across different RNA extraction and amplification platforms, with excellent performance in terms of sensitivity, specificity, and positive and negative predictive values. We believe that our results may help clinical laboratories to respond to the actual demand and clinical need on SARS-CoV-2 testing, especially for the screening of low prevalence populations.\n\nKey points\n\nQuestionMay clinical laboratories implement sample pooling as an efficient and safe strategy for SARS-COV-2 RT-PCR screening?\n\nFindingsSensitivity, specificity, positive and negative predictive values for pooling were 97.93%, 100%, 100% and 99.85% respectively; accuracy was 99.86% and kappa concordant coefficient was 0.988.\n\nMeaningSample pooling can be used safely at clinical laboratories, especially for the screening of low prevalence populations.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Laura Mannonen", - "author_inst": "HUS Diagnostic Center, HUSLAB" + "author_name": "Adolfo de Salazar", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario Clinico San Cecilio, Instituto de Investigacion Biosanitaria Ibs.Granada, Granada, Spain" }, { - "author_name": "Hannimari Kallio-Kokko", - "author_inst": "HUS Diagnostic Center, HUSLAB" + "author_name": "Antonio Aguilera", + "author_inst": "Clinical Microbiology Unit. Complexo Hospitalario Universitario de Santiago e Instituto de Investigacion Sanitaria de Santiago. Santiago de Compostela, Spain." }, { - "author_name": "Raisa Loginov", - "author_inst": "HUS Diagnostic Center, HUSLAB" + "author_name": "Rocio Trastoy", + "author_inst": "Clinical Microbiology Unit. Complexo Hospitalario Universitario de Santiago e Instituto de Investigacion Sanitaria de Santiago. Santiago de Compostela, Spain" }, { - "author_name": "Anu Jaaskelainen", - "author_inst": "HUS Diagnostic Center, HUSLAB" + "author_name": "Ana Fuentes", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario Clinico San Cecilio, Instituto de Investigacion Biosanitaria Ibs.Granada, Granada, Spain" }, { - "author_name": "Pia Jokela", - "author_inst": "HUS Diagnostic Center, HUSLAB" + "author_name": "Juan Carlos Alados", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario de Jerez, Cadiz, Spain" }, { - "author_name": "Jenni Antikainen", - "author_inst": "HUS Diagnostic Center, HUSLAB" + "author_name": "Manuel Causse", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario Reina Sofia. Instituto Maimonides de Investigacion Biomedica de Cordoba (IMIBIC), Cordoba, Spain" }, { - "author_name": "Paula Vare", - "author_inst": "HUS Diagnostic Center, HUSLAB" + "author_name": "Juan Carlos Galan", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario Ramon y Cajal. Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), Madrid, Spain. CIBER en Epidemiol" }, { - "author_name": "Eliisa Kekalainen", - "author_inst": "HUS Diagnostic Center, HUSLAB" + "author_name": "Antonio Moreno", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario Lucus Augusti de Lugo. Lugo, Spain." }, { - "author_name": "Satu Kurkela", - "author_inst": "HUS Diagnostic Center, HUSLAB" + "author_name": "Matilde Trigo", + "author_inst": "Clinical Microbiology Unit. Complexo Hospitalario Universitario de Pontevedra. Pontevedra, Spain." }, { - "author_name": "Hanna Jarva", - "author_inst": "HUS Diagnostic Center, HUSLAB" + "author_name": "Mercedes Perez", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario Virgen de las Nieves, Granada, Spain, Instituto de Investigacion Biosanitaria ibs.Granada, Spain" }, { - "author_name": "Maija Lappalainen", - "author_inst": "HUS Diagnostic Center, HUSLAB" + "author_name": "Carolina Roldan", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario de Jaen. Jaen, Spai" + }, + { + "author_name": "Maria Jose Pena", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario de Gran Canaria Dr. Negrin, Las Palmas de GC, Gran Canaria, Spain" + }, + { + "author_name": "Samuel Bernal", + "author_inst": "Unit of Infectious Disease and Clinical Microbiology. Hospital Universitario de Valme. Seville, Spain" + }, + { + "author_name": "Esther Serrano-Conde", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario Clinico San Cecilio, Instituto de Investigacion Biosanitaria Ibs.Granada, Granada, Spain" + }, + { + "author_name": "Gema Barbeito", + "author_inst": "Clinical Microbiology Unit. Complexo Hospitalario Universitario de Santiago e Instituto de Investigacion Sanitaria de Santiago. Santiago de Compostela, Spain." + }, + { + "author_name": "Eva Torres", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario de Jerez, Cadiz, Spain" + }, + { + "author_name": "Cristina Riazzo", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario Reina Sofia. Instituto Maimonides de Investigacion Biomedica de Cordoba (IMIBIC), Cordoba, Spain" + }, + { + "author_name": "Jose Luis Cortes-Cuevas", + "author_inst": "Clinical Microbiology Unit. Hospital Ramon y Cajal. Madrid, Spain" + }, + { + "author_name": "Natalia Chueca", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario Clinico San Cecilio, Instituto de Investigacion Biosanitaria Ibs.Granada, Granada, Spain" + }, + { + "author_name": "Amparo Coira", + "author_inst": "Clinical Microbiology Unit. Complexo Hospitalario Universitario de Santiago e Instituto de Investigacion Sanitaria de Santiago. Santiago de Compostela, Spain." + }, + { + "author_name": "Juan Manuel Sanchez-Calvo", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario de Jerez, Cadiz, Spain" + }, + { + "author_name": "Eduardo Marfil", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario Reina Sofia. Instituto Maimonides de Investigacion Biomedica de Cordoba (IMIBIC), Cordoba, Spain" + }, + { + "author_name": "Federico Becerra", + "author_inst": "Clinical Microbiology Unit. Hospital Ramon y Cajal. Madrid, Spain" + }, + { + "author_name": "Maria Jose Gude", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario Lucus Augusti de Lugo. Lugo, Spain." + }, + { + "author_name": "Angeles Pallares", + "author_inst": "Clinical Microbiology Unit. Complexo Hospitalario Universitario de Pontevedra. Pontevedra, Spain." + }, + { + "author_name": "Maria Luisa Perez del Molino", + "author_inst": "Clinical Microbiology Unit. Complexo Hospitalario Universitario de Santiago e Instituto de Investigacion Sanitaria de Santiago. Santiago de Compostela, Spain." + }, + { + "author_name": "Federico Garcia", + "author_inst": "Clinical Microbiology Unit. Hospital Universitario Clinico San Cecilio, Instituto de Investigacion Biosanitaria Ibs.Granada, Granada, Spain" } ], "version": "1", @@ -1302869,59 +1303305,43 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.07.02.20136721", - "rel_title": "An Automatic Computer-Based Method for Fast and Accurate Covid-19 Diagnosis", + "rel_doi": "10.1101/2020.07.02.20144832", + "rel_title": "Exposure assessment for airborne transmission of SARS-CoV-2 via breathing, speaking, coughing and sneezing", "rel_date": "2020-07-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.02.20136721", - "rel_abs": "At present, the whole world is witnessing a horrifying outbreak caused by the Coronavirus Disease 2019 (COVID-19). The virus responsible for this disease is called SARS-CoV-2. It affects its victims respiratory system and causes severe lung inflammation, making it harder for them to breathe. The virus is airborne, and so has a high infection rate. Originated in China last December, the virus has spread across seven continents, affecting the population of over 210 countries, making it one of the fiercest pandemics ever recorded. Despite multiple independent and collaborative attempts to develop a vaccine or a cure, an effective solution is yet to come out. While the disease has put the world in a standstill, detecting the positive subjects and isolating them from the others as soon as possible is the only way to minimize its spread. However, many countries are currently experiencing a massive shortage of diagnostic equipment and medical personals. This insufficiency inspired us to work on a computer-based automatic method for the diagnosis of COVID-19. In this paper, we proposed a sequential Convolutional Neural Network (CNN)-based model to detect COVID-19 through analyzing Computed Tomography (CT) scan images. The model is capable of identifying the disease with almost 92.5% accuracy. We believe the implementation of this model will help the physicians and pathologists all over the world to single out the victims quickly and thus reduce the prevalence of COVID-19.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.02.20144832", + "rel_abs": "BackgroundEvidence for indoor airborne transmission of SARS-CoV-2 is accumulating. If SARS-CoV-2 also spreads via aerosols, this has implications for measures taken to limit transmission.\n\nObjectivesThe aim of this study is to assess exposure to airborne SARS-CoV-2 particles from breathing, speaking, coughing and sneezing in an indoor environment.\n\nMethodsAn exposure assessment model was developed to estimate numbers of SARS-CoV-2 particles in aerosol droplets, expelled during breathing, speaking, coughing and sneezing by an infected person in an unventilated indoor environment, and subsequent inhalation by one or more persons. Scenarios encompass a range of virus concentrations, room sizes and exposure times.\n\nResultsThe calculated total volume of expelled aerosol droplets was highest for a sneeze, followed by a cough and speaking for 20 minutes, and lastly breathing for 20 minutes. A few to as much as tens of millions of virus particles were expelled. Exposure probability strongly depends on the viral concentration in mucus, as well as on the scenario. Exposure probabilities were generally below 1% at a virus concentration in mucus below 105 per mL for all scenarios, increasing steeply at different higher concentrations. According to nose / throat swab data collected from patients, 75%, 50% and 5% of infected individuals carry an estimated number of SARS-CoV-2 per mL mucus of at least 105, 106 and 108, respectively.\n\nDiscussionExposure to SARS-CoV-2 via aerosols generated during breathing, speaking, coughing and sneezing in an unventilated indoor environment is possible. This study forms a basis to estimate probabilities of exposure to SARS-Cov-2 by airborne transmission in indoor spaces. As long as it is uncertain what fraction of the airborne virus particles is infectious and as long as a dose response relation is lacking, it is recommended to be precautious.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Abdullah Al Jaid Jim", - "author_inst": "Electronics and Communication Engineering Discipline, Khulna University, Khulna 9208, Bangladesh" - }, - { - "author_name": "Ibrahim Rafi", - "author_inst": "Electronics and Communication Engineering Discipline, Khulna University, Khulna 9208, Bangladesh" - }, - { - "author_name": "Md. Sanaullah Chowdhury", - "author_inst": "Electronics and Communication Engineering Discipline, Khulna University, Khulna 9208, Bangladesh" - }, - { - "author_name": "Niloy Sikder", - "author_inst": "Computer Science and Engineering Discipline, Khulna University, Khulna 9208, Bangladesh" + "author_name": "Jack F. Schijven", + "author_inst": "National Institute for Public Health and the Environment (RIVM), and Utrecht University" }, { - "author_name": "M. A. Parvez Mahmud", - "author_inst": "School of Engineering, Deakin University, Geelong, VIC 3216, Australia" - }, - { - "author_name": "Saeed Rubaie", - "author_inst": "Department of Industrial and Systems Engineering Department of Mechanical and Materials Engineering University of Jeddah, KSA" + "author_name": "Lucie C Vermeulen", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" }, { - "author_name": "Mehedi Masud", - "author_inst": "Department of Computer Science, Taif University, Taif 21944, Saudi Arabia" + "author_name": "Arno Swart", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" }, { - "author_name": "Anupam Kumar Bairagi", - "author_inst": "Computer Science and Engineering Discipline, Khulna University, Khulna 9208, Bangladesh" + "author_name": "Adam Meijer", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" }, { - "author_name": "Kangkan Bhakta", - "author_inst": "Electronics and Communication Engineering Discipline, Khulna University, Khulna 9208, Bangladesh" + "author_name": "Erwin Duizer", + "author_inst": "National Institute for Public Health and the Environment (RIVM)" }, { - "author_name": "Abdullah-Al Nahid", - "author_inst": "Electronics and Communication Engineering Discipline, Khulna University, Khulna 9208, Bangladesh" + "author_name": "Ana Maria de Roda Husman", + "author_inst": "National Institute for Public Health and the Environment (RIVM), and Utrecht University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "radiology and imaging" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.07.02.20143032", @@ -1304443,25 +1304863,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.02.20145474", - "rel_title": "Forecasting COVID-19 cases using Machine Learning models", + "rel_doi": "10.1101/2020.07.03.20145649", + "rel_title": "The effect of opening up the US on COVID-19 spread", "rel_date": "2020-07-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.02.20145474", - "rel_abs": "As of April 26, 2020, more than 2,994,958 cases of COVID-19 infection have been confirmed globally, raising a challenging public health issue. A predictive model of the disease would help allocate medical resources and determine social distancing measures more efficiently. In this paper, we gathered case data from Jan 22, 2020 to April 14 for 6 countries to compare different models proficiency in COVID-19 cases prediction. We assessed the performance of 3 machine learning models including hidden Markov chain model (HMM), hierarchical Bayes model, and long-short-term-memory model (LSTM) using the root-mean-square error (RMSE). The LSTM model had the consistently smallest prediction error rates for tracking the dynamics of incidents cases in 4 countries. In contrast, hierarchical Bayes model provided the most realistic prediction with the capability of identifying a plateau point in the incidents growth curve.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.03.20145649", + "rel_abs": "In response to the pandemic development of the novel coronavirus (SARS-CoV-2), governments worldwide have implemented strategies of suppression by non-pharmaceutical interventions (NPIs). Such NPIs include social distancing, school closures, limiting international travel and complete lockdown. Worldwide the NPIs enforced to limit the spread of COVID-19 are now being lifted. Understanding how the risk increases when NPIs are lifted is important for decision making. Treating NPIs equally across countries and regions limits the possibility for modelling differences in epidemic response, as the response to the NPIs influences can vary between regions and this can affect the epidemic outcome, so do the strength and speed of lifting these. Our solution to this is to measure mobility changes from mobile phone data and their impacts on the basic reproductive number. We model the epidemic in all US states to compare the difference in outcome if NPIs are lifted or retained. We show that keeping NPIs just a few weeks longer has a substantial impact on the epidemic outcome.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Yuan Tian", - "author_inst": "The University of British Columbia" - }, - { - "author_name": "Ishika Luthra", - "author_inst": "The University of British Columbia" + "author_name": "Patrick Bryant", + "author_inst": "Stockholm University/Science for Life Laboratory" }, { - "author_name": "Xi Zhang", - "author_inst": "The University of British Columbia" + "author_name": "Arne Elofsson", + "author_inst": "Stockholm University" } ], "version": "1", @@ -1305905,89 +1306321,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.02.20144733", - "rel_title": "Plasma IL-6 Levels following Corticosteroid Therapy as an Indicator of ICU Length of Stay in Critically ill COVID-19 Patients", + "rel_doi": "10.1101/2020.07.02.20144717", + "rel_title": "Association between angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers use and the risk of infection and clinical outcome of COVID-19: a comprehensive systematic review and meta-analysis.", "rel_date": "2020-07-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.02.20144733", - "rel_abs": "Intensive Care Unit (ICU) admissions and mortality in severe COVID-19 patients are driven by \"cytokine storms\" and acute respiratory distress syndrome (ARDS). Interim clinical trial results suggest that the corticosteroid dexamethasone displays superior 28-day survival in severe COVID-19 patients requiring ventilation or oxygen. Among 16 patients with plasma IL-6 measurement post-corticosteroid administration, a higher proportion of patients with an IL-6 value over 10 pg/mL have worse outcomes (i.e. ICU Length of Stay > 15 days or death) when compared to 41 patients treated with non-corticosteroid drugs including antivirals, tocilizumab, azithromycin, and hydroxychloroquine (p-value = 0.0024). Given this unexpected clinical association between post-corticosteroid IL-6 levels and COVID-19 severity, we hypothesized that the Glucocorticoid Receptor (GR or NR3C1) may be coupled to IL-6 expression in specific cell types that govern cytokine release syndrome (CRS). Examining single cell RNA-seq data from bronchoalveolar lavage fluid of severe COVID-19 patients and nearly 2 million human cells from a pan-tissue scan shows that alveolar macrophages, smooth muscle cells, and endothelial cells co-express both NR3C1 and IL-6. The mechanism of Glucocorticoid Receptor (GR) agonists mitigating pulmonary and multi-organ inflammation in some COVID-19 patients with respiratory failure, may be in part due to their successful antagonism of IL-6 production within lung macrophages and vasculature.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.02.20144717", + "rel_abs": "BackgroundThe effect of using Angiotensin-converting enzyme inhibitors (ACEIs) and Angiotensin-receptor blockers (ARBs) on the risk of coronavirus disease 2019 (COVID-19) is a topic of recent debate. Although studies have examined the potential association between them, the results remain controversial. This study aims to determine the true effect of ACEI/ARBs use on the risk of infection and clinical outcome of COVID-19.\n\nMethodsFive electronic databases (PubMed, Web of science, Cochrane library, China National Knowledge Infrastructure database, medRxiv preprint server) were retrieved to find eligible studies. Meta-analysis was performed to examine the association between ACEI/ARBs use and the risk of infection and clinical outcome of COVID-19.\n\nResults22 articles containing 157,328 patients were included. Use of ACEI/ARBs was not associated with increased risk of infection (Adjusted OR: 0.96, 95% CI: 0.91-1.01, I2=5.8%) or increased severity (Adjusted OR: 0.90, 95% CI: 0.77-1.05, I2=27.6%) of COVID-19. The use of ACEI/ARBs was associated with lower risk of death from COVID-19 (Adjusted OR: 0.66, 95% CI: 0.44-0.99, I2=57.9%). Similar results of reduced risk of death were also found for ACEI/ARB use in COVID-19 patients with hypertension (Adjusted OR: 0.36, 95% CI: 0.17-0.77, I2=0).\n\nConclusionThis study provides evidence that ACEI/ARBs use for COVID-19 patients does not lead to harmful outcomes and may even provide a beneficial role and decrease mortality from COVID-19. Clinicians should not discontinue ACEI/ARBs for patients diagnosed with COVID-19 if they are already on these agents.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Samir Awasthi", - "author_inst": "nference" - }, - { - "author_name": "Tyler Wagner", - "author_inst": "nference" - }, - { - "author_name": "AJ Venkatakrishnan", - "author_inst": "nference" - }, - { - "author_name": "Arjun Puranik", - "author_inst": "nference" - }, - { - "author_name": "Matthew Hurchik", - "author_inst": "nference" - }, - { - "author_name": "Vineet Agarwal", - "author_inst": "nference" - }, - { - "author_name": "Ian Conrad", - "author_inst": "nference" - }, - { - "author_name": "Christian Kirkup", - "author_inst": "nference" - }, - { - "author_name": "Raman Arunachalam", - "author_inst": "nference Labs" + "author_name": "Guangbo Qu", + "author_inst": "Anhui Medical University" }, { - "author_name": "John O'Horo", - "author_inst": "Mayo Clinic" + "author_name": "Liqin Shu", + "author_inst": "Maternal and Child Health Care Hospital of Anhui Province (Affiliated Maternal and Child Health Care Hospital of Anhui Medical University)" }, { - "author_name": "Walter Kremers", - "author_inst": "Mayo Clinic" + "author_name": "Evelyn J Song", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Rahul Kashyap", - "author_inst": "Mayo Clinic" + "author_name": "Dhiran Verghese", + "author_inst": "AMITA Health Saint Joseph Hospital Chicago" }, { - "author_name": "William Morice", - "author_inst": "Mayo Clinic Laboratories" + "author_name": "John Patrick Uy", + "author_inst": "AMITA Health Saint Joseph Hospital Chicago" }, { - "author_name": "John Halamka", - "author_inst": "Mayo Clinic Platform" + "author_name": "Ce Cheng", + "author_inst": "Cape Fear Valley Medical Center" }, { - "author_name": "Amy W Williams", - "author_inst": "Mayo Clinic" + "author_name": "Qin Zhou", + "author_inst": "Mayo clinic" }, { - "author_name": "William A Faubion", - "author_inst": "Mayo Clinic" + "author_name": "Hongru Yang", + "author_inst": "Massachusetts College of Pharmacy and Health Science" }, { - "author_name": "Andrew D Badley", - "author_inst": "Mayo Clinic" + "author_name": "Zhichun Guo", + "author_inst": "Massachusetts college of Pharmacy and Health sciences" }, { - "author_name": "Gregory J Gores", - "author_inst": "Mayo Clinic" + "author_name": "Mengshi Chen", + "author_inst": "Central South University" }, { - "author_name": "Venky Soundararajan", - "author_inst": "nference" + "author_name": "Chenyu Sun", + "author_inst": "AMITA Health Saint Joseph Hospital Chicago" } ], "version": "1", @@ -1307459,85 +1307843,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.30.20143818", - "rel_title": "COVID-MATCH65 - A prospectively derived clinical decision rule for severe acute respiratory syndrome coronavirus 2", + "rel_doi": "10.1101/2020.07.01.20143917", + "rel_title": "Relative COVID-19 viral persistence and antibody kinetics", "rel_date": "2020-07-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.30.20143818", - "rel_abs": "Due to the ongoing COVID-19 pandemic and increased pressure on testing resources, understanding the clinical and epidemiological features closely associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is vital at point of care to enable risk stratification. We demonstrate that an internally derived and validated clinical decision rule, COVID-MATCH65, has a high sensitivity (92.6%) and NPV (99.5%) for SARS-CoV-2 and could be used to aid COVID-19 risk-assessment and resource allocation for SARS-CoV-2 diagnostics.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.01.20143917", + "rel_abs": "ImportanceThe COVID-19 antibody response is a critical indicator for evaluating immunity and also serves as the knowledge base for vaccine development. The picture is still not clear because of many limitations including testing tools, time of sampling, and the unclear impact of varying clinical status. In addition to these problems, antibody levels may not be equivalent to protective capacity.\n\nObjectiveTo define the key factor for the different patterns of COVID-19 antibody response.\n\nDesignWe elucidated the antibody response with time-series throat and serum samples for viral loads and antibody levels, then used a neutralization test to evaluate protectiveness.\n\nSettingA medical center that typically cares for patients with moderate to severe diseases. Because of the low prevalence of COVID-19 in Taiwan and local government policy, however, we also admit COVID-19 patients with mild disease or even those without symptoms for inpatient care.\n\nParticipantsRT-PCR-confirmed COVID-19 patients.\n\nResultsWe found that only patients with relative persistence of virus at pharynx displayed strong antibody responses that were proportional to the pharyngeal viral load. They also had proportional neutralization titers per unit of serum. Although antibody levels decreased around 2 weeks after symptom onset, the neutralization efficacy per unit antibody remained steady and even continued to increase over time. The antibody response in patients with rapid virus clearance was weak, but the neutralization efficacy per unit antibody in these patients was comparable to those with persistent presence of virus. The deceased were with higher viral load, higher level of antibody, and higher neutralization titers in the serum, but the neutralization capacity per unit antibody is relatively low.\n\nConclusions and RelevanceStrong antibody response depends on the relative persistence of the virus, instead of the absolute virus amount. The antibody response is still weak if large amount of virus is cleared quickly. The neutralization efficacy per unit antibody is comparable between high and low antibody patterns. Strong antibody response contains more inefficient and maybe even harmful antibodies. Low antibody response is also equipped with a capable B cell pool of efficient antibodies, which may expand with next virus encounter and confer protection.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSThe key factor for the different \"patterns\" of COVID-19 antibody response.\n\nFindingsStrong antibody response depends on the relative persistence of the virus, instead of the absolute virus amount. The antibody response is still weak if large amount of virus is cleared quickly. The neutralization efficacy per unit antibody is comparable between high and low antibody patterns. High antibody level contains more inefficient antibodies.\n\nMeaningStrong response contains inefficient and maybe harmful antibodies. Low antibody response is also equipped with a capable B cell pool of efficient antibodies, which may expand with next virus encounter and confer protection.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Jason A Trubiano", - "author_inst": "Austin Health" - }, - { - "author_name": "Sara Vogrin", - "author_inst": "Unviersity of Melbourne" - }, - { - "author_name": "Olivia C Smibert", - "author_inst": "Austin Health" - }, - { - "author_name": "Nada Marhoon", - "author_inst": "The Data Analytics Research and Evaluation (DARE) Centre, University of Melbourne" - }, - { - "author_name": "Adrian A Alexander", - "author_inst": "Austin Health" - }, - { - "author_name": "Kyra YL Chua", - "author_inst": "Austin Health" - }, - { - "author_name": "Fiona L James", - "author_inst": "Austin Health" - }, - { - "author_name": "Nicholas RL Jones", - "author_inst": "Austin Health" - }, - { - "author_name": "Sam E Grigg", - "author_inst": "Austin Health" + "author_name": "Chung-Guei Huang", + "author_inst": "1.Dept. of Laboratory Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan. 2.Dept. of Med. Biotech. & Lab. Sci., College of Med., Chang Gung University, Tao" }, { - "author_name": "Cecilia LH xu", - "author_inst": "Austin health" + "author_name": "Ching-Tai Huang", + "author_inst": "1. Division of infectious diseases, Department of Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan. 2. Division of infectious diseases, Department of Med" }, { - "author_name": "nasreen Moini", - "author_inst": "Austin Health" + "author_name": "Avijit Dutta", + "author_inst": "Division of infectious diseases, Department of Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan" }, { - "author_name": "Sam R Stanley", - "author_inst": "Austin Health" + "author_name": "Pi-Yueh Chang", + "author_inst": "1. Department of Laboratory Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan. 2. Department of Medical Biotechnology and Laboratory Science, College of M" }, { - "author_name": "Michael T Birrell", - "author_inst": "Austin Health" + "author_name": "Mei-Jen Hsiao", + "author_inst": "1. Department of Laboratory Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan. 2. Department of Medical Biotechnology and Laboratory Science, College of M" }, { - "author_name": "Morgan T Rose", - "author_inst": "Austin Health" + "author_name": "Yu-Chia Hsieh", + "author_inst": "1. Division of Infectious Diseases, Department of Pediatrics, Chang Gung Memorial Hospital, Taoyuan, Taiwan. 2. Division of Infectious Diseases, Department of P" }, { - "author_name": "Claire L Gordon", - "author_inst": "Austin Health" + "author_name": "Shin-Ru Shih", + "author_inst": "1.Dept. of Lab. Med., Chang Gung Memorial Hospital, Taoyuan, Taiwan. 2.Dept. of Med. Biotech. & Lab. Sci., College of Med., Chang Gung University, Taoyuan, Taiw" }, { - "author_name": "Jason C Kwong", - "author_inst": "Austin Health" + "author_name": "Kuo-Chien Tsao", + "author_inst": "1. Department of Laboratory Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan. 2. Department of Medical Biotechnology and Laboratory Science, College of M" }, { - "author_name": "Natasha E Holmes", - "author_inst": "Austin Health" + "author_name": "Cheng-Ta Yang", + "author_inst": "1. Department of Thoracic Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan. 2. Department of Respiratory Therapy, College of Medicine, Chang Gung Univers" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1309037,71 +1309389,59 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.06.29.178889", - "rel_title": "Discovery of Synergistic and Antagonistic Drug Combinations against SARS-CoV-2 In Vitro", + "rel_doi": "10.1101/2020.06.30.176537", + "rel_title": "Attenuated Subcomponent Vaccine Design Targeting the SARS-CoV-2 Nucleocapsid Phosphoprotein RNA Binding Domain: In silico analysis", "rel_date": "2020-07-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.29.178889", - "rel_abs": "COVID-19 is undoubtedly the most impactful viral disease of the current century, afflicting millions worldwide. As yet, there is not an approved vaccine, as well as limited options from existing drugs for treating this disease. We hypothesized that combining drugs with independent mechanisms of action could result in synergy against SARS-CoV-2. Using in silico approaches, we prioritized 73 combinations of 32 drugs with potential activity against SARS-CoV-2 and then tested them in vitro. Overall, we identified 16 synergistic and 8 antagonistic combinations, 4 of which were both synergistic and antagonistic in a dose-dependent manner. Among the 16 synergistic cases, combinations of nitazoxanide with three other compounds (remdesivir, amodiaquine and umifenovir) were the most notable, all exhibiting significant synergy against SARS-CoV-2. The combination of nitazoxanide, an FDA-approved drug, and remdesivir, FDA emergency use authorization for the treatment of COVID-19, demonstrate a strong synergistic interaction. Notably, the combination of remdesivir and hydroxychloroquine demonstrated strong antagonism. Overall, our results emphasize the importance of both drug repurposing and preclinical testing of drug combinations for potential therapeutic use against SARS-CoV-2 infections.", - "rel_num_authors": 13, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.30.176537", + "rel_abs": "ABSTRACTThe novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has previously never been identified with humans, thereby creating devastation in public health. The need for an effective vaccine to curb this pandemic cannot be overemphasized. In view of this, we, therefore, designed a subcomponent antigenic peptide vaccine targeting the N-terminal (NT) and C-terminal (CT) RNA binding domains of nucleocapsid protein that aid in viral replication. Promising antigenic B-cells and T cell epitopes were predicted using computational pipelines. The peptides \u201cRIRGGDGKMKDL\u201d and \u201cAFGRRGPEQTQGNFG\u201d were the B cell linear epitopes with good antigenic index and non-allergenic property. Two CD8+ and Three CD4+ T-cell epitopes were also selected considering their safe immunogenic profiling such as allergenicity, antigen level conservancy, antigenicity, peptide toxicity, and putative restrictions to a number of MHC-I and II alleles. With these selected epitopes, a non-allergenic chimeric peptide vaccine incapable of inducing a Type II hypersensitivity reaction was constructed. The molecular interaction between the toll-like receptor-5 (TLR5) which was triggered by the vaccine was analyzed by molecular docking and scrutinized using dynamics simulation. Finally, in silico cloning was performed to ensure the expression and translation efficiency of the vaccine, utilizing pET-28a vector. This research, therefore, provides a guide for experimental investigation and validation.Competing Interest StatementThe authors have declared no competing interest.View Full Text", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Tesia Bobrowski", - "author_inst": "University of North Carolina" - }, - { - "author_name": "Lu Chen", - "author_inst": "National Center for Advancing Translational Sciences" - }, - { - "author_name": "Rich T. Eastman", - "author_inst": "National Center for Advancing Translational Sciences, NIH" - }, - { - "author_name": "Zina Itkin", - "author_inst": "National Center for Advancing Translational Sciences" + "author_name": "Onyeka S. Chukwudozie", + "author_inst": "Department of Cell Biology and Genetics, University of Lagos" }, { - "author_name": "Paul Shinn", - "author_inst": "National Center for Advancing Translational Sciences" + "author_name": "Rebecca C Chukwuanukwu", + "author_inst": "Immunology Unit, Medical Laboratory Science Department, Nnamdi Azikiwe University, Nnewi Campus" }, { - "author_name": "Catherine Chen", - "author_inst": "National Center for Advancing Translational Sciences" + "author_name": "Iroanya O. Onyekachi", + "author_inst": "Department of Cell Biology and Genetics, University of Lagos, Akoka Lagos state, Nigeria." }, { - "author_name": "Hui Guo", - "author_inst": "National Center for Advancing Translational Sciences" + "author_name": "Eze M. Daniel", + "author_inst": "Molecular Genetics unit, Institute of Child Health, College of Medicine, University of Ibadan, Oyo state, Nigeria" }, { - "author_name": "Wei Zheng", - "author_inst": "National Center for Advancing Translational Sciences" + "author_name": "Duru C. Vincent", + "author_inst": "Immunology and Bioinformatics unit, Department of Parasitology and Entomology, Nnamdi Azikiwe University, Awka, Anambra state, Nigeria." }, { - "author_name": "Sam Michael", - "author_inst": "National Center for Advancing Translational Sciences" + "author_name": "Dele-Alimi T. Onaopemipo", + "author_inst": "Molecular Genetics unit, Institute of Child Health, College of Medicine, University of Ibadan, Oyo state, Nigeria." }, { - "author_name": "Anton Simeonov", - "author_inst": "National Center for Advancing Translational Sciences" + "author_name": "Kehinde B. David", + "author_inst": "University of Ibadan" }, { - "author_name": "Matthew Hall", - "author_inst": "NCATS" + "author_name": "Bankole T. Taiwo", + "author_inst": "Department of Cell Biology and Genetics, University of Lagos, Akoka Lagos state, Nigeria." }, { - "author_name": "Alexey V. Zakharov", - "author_inst": "National Center for Advancing Translational Sciences" + "author_name": "Obi C. Perpetua", + "author_inst": "Department of Science Laboratory and Technology (Microbiology Unit), Federal Polytechnic, Oko, Anambra State, Nigeria." }, { - "author_name": "Eugene N. Muratov", - "author_inst": "University of North Carolina" + "author_name": "Okinedo U. Elizabeth", + "author_inst": "Department of Cell Biology and Genetics, University of Lagos, Akoka Lagos state, Nigeria." } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "immunology" }, { "rel_doi": "10.1101/2020.06.23.20132522", @@ -1310819,87 +1311159,31 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.07.01.182709", - "rel_title": "Genetic architecture of host proteins interacting with SARS-CoV-2", + "rel_doi": "10.1101/2020.07.01.182618", + "rel_title": "Early data on the performance of a combined SARS-CoV-2 spike-nucleocapsid antibody lateral flow device compared to a nucleocapsid-only device", "rel_date": "2020-07-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.01.182709", - "rel_abs": "Strategies to develop therapeutics for SARS-CoV-2 infection may be informed by experimental identification of viral-host protein interactions in cellular assays and measurement of host response proteins in COVID-19 patients. Identification of genetic variants that influence the level or activity of these proteins in the host could enable rapid in silico assessment in human genetic studies of their causal relevance as molecular targets for new or repurposed drugs to treat COVID-19. We integrated large-scale genomic and aptamer-based plasma proteomic data from 10,708 individuals to characterize the genetic architecture of 179 host proteins reported to interact with SARS-CoV-2 proteins or to participate in the host response to COVID-19. We identified 220 host DNA sequence variants acting in cis (MAF 0.01-49.9%) and explaining 0.3-70.9% of the variance of 97 of these proteins, including 45 with no previously known protein quantitative trait loci (pQTL) and 38 encoding current drug targets. Systematic characterization of pQTLs across the phenome identified protein-drug-disease links, evidence that putative viral interaction partners such as MARK3 affect immune response, and establish the first link between a recently reported variant for respiratory failure of COVID-19 patients at the ABO locus and hypercoagulation, i.e. maladaptive host response. Our results accelerate the evaluation and prioritization of new drug development programmes and repurposing of trials to prevent, treat or reduce adverse outcomes. Rapid sharing and dynamic and detailed interrogation of results is facilitated through an interactive webserver (https://omicscience.org/apps/covidpgwas/).", - "rel_num_authors": 17, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.01.182618", + "rel_abs": "The authors have withdrawn their manuscript whilst they perform additional experiments to test some of their conclusions further. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Maik Pietzner", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Eleanor Wheeler", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Julia Carrasco-Zanini", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Johannes Raffler", - "author_inst": "Helmholtz Zentrum M\u00fcnchen - German Research Center for Environmental Health (GmbH)" + "author_name": "Christian A. Linares", + "author_inst": "Medical Microbiology Service, Pathology Department, East Kent Hospitals University NHS Foundation Trust, Ashford, Kent TN24 0LZ" }, { - "author_name": "Nicola D. Kerrison", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Erin Oerton", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Victoria P.W. Auyeung", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Chris Finan", - "author_inst": "University College London" - }, - { - "author_name": "Juan P. Casas", - "author_inst": "Harvard Medical School" + "author_name": "Felicity Ryan", + "author_inst": "Medical Microbiology Service, Pathology Department, East Kent Hospitals University NHS Foundation Trust, Ashford, Kent TN24 0LZ" }, { - "author_name": "Rachel Ostroff", - "author_inst": "SomaLogic Inc." - }, - { - "author_name": "Steve A. Williams", - "author_inst": "SomaLogic Inc." - }, - { - "author_name": "Gabi Kastenm\u00fcller", - "author_inst": "Helmholtz Zentrum M\u00fcnchen - German Research Center for Environmental Health (GmbH)" - }, - { - "author_name": "Markus Ralser", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Eric G. Gamazon", - "author_inst": "Vanderbilt University Medical Center" - }, - { - "author_name": "Nicholas J. Wareham", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Aroon Dinesh Hingorani", - "author_inst": "University College London" - }, - { - "author_name": "Claudia Langenberg", - "author_inst": "University of Cambridge" + "author_name": "Samuel E. Moses", + "author_inst": "East Kent Hospitals University NHS Foundation Trust; Honorary Senior Lecturer, University of Kent" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "genomics" + "category": "immunology" }, { "rel_doi": "10.1101/2020.06.30.181297", @@ -1312905,39 +1313189,51 @@ "category": "hematology" }, { - "rel_doi": "10.1101/2020.06.29.20142414", - "rel_title": "The Prevalence of ocular manifestations and ocular samples polymerase chain reaction positivity in patients with COVID 19 - a systematic review and meta-analysis", + "rel_doi": "10.1101/2020.06.29.20138628", + "rel_title": "Knowledge, attitudes, and practices towards COVID-19 among primary and middle school students during the COVID-19 outbreak period in Beijing: An online cross-sectional survey", "rel_date": "2020-06-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.29.20142414", - "rel_abs": "ObjectiveTo estimate the prevalence of ocular manifestations and ocular samples polymerase chain reaction (PCR) positivity among COVID-19 patients.\n\nMethodsA systematic literature review was performed using search engines (PubMed, Google Scholar, Medrixv and BioRixv) with keywords \"SARS-CoV-2\", \"novel coronavirus\", \"COVID-19\", \"ocular manifestations\", \"conjunctival congestion\", \"Ocular detection\", \"Polymerase chain reaction\", and \"conjunctivitis\". The measure of heterogeneity was evaluated with the I2 statistic. The pooled proportion of patients presenting with symptoms and ocular samples PCR positivity was estimated.\n\nResultsA total of 20 studies (14 studies and 6 case-reports) were included in the systematic review and 14 studies were included in the meta-analysis. The pooled prevalence of conjunctivitis was 5.17% (95% CI: 2.90-8.04). Conjunctivitis was reported as an initial symptom of the disease in 0.858 % (95% CI: 0.31-1.67). Common associated features include itching, chemosis, epiphora. Seven patients (29 %) with conjunctivitis showed positive results in ocular samples, whereas 13 patients (54%) showed positive only in their nasopharyngeal samples (NPs) or sputum samples and 4 patients (16 %) were negative for both NPs and Sputum as well as ocular samples. The pooled prevalence of ocular PCR positivity was 2.90 % (95% CI: 1.77 - 4.46) vs. NPs 89.8% (95% CI: 78.80-79.0).\n\nConclusionThe prevalence of conjunctivitis and ocular samples PCR positivity among COVID-19 patients was low indicating that the eye is a less affected organ. However, conjunctivitis may present as the first symptom of the disease making the patient seek medical care at the earliest.\n\nSynopsisViral conjunctivitis was the only symptom reported. The prevalence of conjunctivitis and ocular samples polymerase chain reaction positivity among COVID-19 patients was low indicating the eye is a less effected organ.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.29.20138628", + "rel_abs": "PurposeThis study investigated the KAP towards COVID-19 and their influencing factors among primary and middle school students during the self-quarantine period in Beijing.\n\nMethodsThis was a cross-sectional study among students from 18 primary and middle schools in Beijing during March 2020. Stratified cluster sampling was conducted. Demographic and KAP-related COVID-19 information was collected through an online questionnaire. The influencing factors were analyzed by multivariable logistic regression.\n\nResultsA total of 7,377 students were included. The overall correct rate for COVID-19 knowledge was 74.1%, while only 31.5% and 40.5% could identify the high-risk places of cross-infection and warning body temperature. Although 94.5% of respondents believed the epidemic could be controlled, over 50% expressed various concerns about the epidemic. The compliance rates for basic preventing behaviors were all over 80%, while those for \"rational and effective ventilation\" (39.2%) and \"dinning separately\" (38.6%) were low. The KAP levels were significantly differed according to various school categories of students. The COVID-19 knowledge (OR= 3.309, 95% CI: 2.921, 3.748) and attitude (OR=1.145, 95% CI: 1.003, 1.308) were associated with preventive practices. Besides, female, urban students, those with a healthy lifestyle, and those with the willingness to engage in healthcare tended to have better preventive practices.\n\nConclusionMost students in Beijing hold a high level of knowledge, optimistic attitudes and have appropriate practices towards COVID-19. However, targeted interventions are still necessary, especially for students with high-risk characteristics.\n\nImplications and contributionsThe performance and the potential factors of COVID-19-related knowledge, attitudes and practices (KAP) among students in primary and middle schools is still unclear.\n\nThis study investigates the characteristics and the level of KAP among students. The results of the study may contribute to the targeted education and interventions for students.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Soumen Sadhu", - "author_inst": "The Sankara Nethralaya Academy" + "author_name": "Fuyuan Wen", + "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemio" + }, + { + "author_name": "Yi Meng", + "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemio" + }, + { + "author_name": "Han Cao", + "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemio" + }, + { + "author_name": "Juan Xia", + "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemio" }, { - "author_name": "Sushmitha Arcot Dandapani", - "author_inst": "The Sankara Nethralaya" + "author_name": "Hui Li", + "author_inst": "School Health Department, Daxing District Center for Disease Control and Prevention, Beijing 100071, China." }, { - "author_name": "Deepmala Mazumdar", - "author_inst": "Vision Research Foundation, Sankara Nethralaya" + "author_name": "Han Qi", + "author_inst": "The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Cente" }, { - "author_name": "Sangeetha Srinivasan", - "author_inst": "Medical research Foundation , Sankara Nethralaya" + "author_name": "Kai Meng", + "author_inst": "Department of Health Management and Policy, School of Public Health, Capital Medical University, Beijing 100069, China." }, { - "author_name": "Jyotirmay Biswas", - "author_inst": "Medical Research Foundation, Sankara Nethralaya" + "author_name": "Ling Zhang", + "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemio" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "ophthalmology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.06.29.20140129", @@ -1314823,139 +1315119,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.26.20135319", - "rel_title": "Baricitinib restrains the immune dysregulation in COVID-19 patients", + "rel_doi": "10.1101/2020.06.26.20098434", + "rel_title": "Higher clinical acuity and 7-day hospital mortality in non-COVID-19 acute medical admissions: prospective observational study.", "rel_date": "2020-06-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.26.20135319", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the ongoing pandemic coronavirus disease 2019 (COVID-19). The majority of patients with COVID-19 have a good prognosis, but variable percentages in different countries develop pneumonia associated with lymphocytopenia and severe inflammatory response due to uncontrolled release of cytokines. These immune mediators are transcriptionally regulated by JAK-STAT molecular pathways, which can be disabled by small molecules. Here, we provide evidences on the efficacy of baricitinib, a JAK1/JAK2 inhibitor, in correcting the immune abnormalities observed in patients hospitalized with COVID-19. Indeed, we demonstrate a significant reduction in serum levels of interleukin (IL)-6, IL-1{beta} and tumor necrosis factor (TNF), a rapid recovery in circulating T and B cell frequencies and an increased antibody production against SARS-CoV-2 spike protein in baricitinib-treated patients. Moreover, treated patients underwent a rapid reduction in oxygen flow need and progressive increase in the P/F. Our work provides the basis on developing effective treatments against COVID-19 pathogenesis using on-target therapy.", - "rel_num_authors": 30, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.26.20098434", + "rel_abs": "ObjectivesTo understand the effect of COVID-19 lockdown measures on severity of illness and mortality in non-COVID-19 acute medical admissions.\n\nDesignA prospective observational study\n\nSetting3 large acute medical receiving units in NHS Lothian, Scotland. Participants: Non-covid-19 acute admissions (n = 1756) were examined over the first 31 days after the implementation of the COVID-19 lockdown policy in the United Kingdom on 23rd March 2019. Patients admitted over a matched interval in the previous 5 years were used as a comparator cohort (n = 14961).\n\nMain outcome measuresPatient demography, biochemical markers of clinical acuity and 7-day hospital inpatient mortality.\n\nResultsNon-covid-19 acute medical admissions reduced by a mean 43.8% (95% CI 27.3, 59.4) across all 3 sites in comparison to the mean of the preceding 5 years P < 0.001. The reduction in admissions predominated in the over 75 age category and a greater proportion arrived by emergency ambulance transport. Non-covid-19 admissions during lockdown had a greater incidence of severe renal injury, hyperlactataemia and over twice the risk of hospital death within 7 days 5.01% vs 2.49% which persisted after adjustment for confounders (OR 2.17, 95% CI 1.70,2.73, P < 0.0001)\n\nConclusionsThese data support current fears that patients are delaying seeking medical attention for acute illness which is associated with worsening clinical parameters and a higher risk of death following admission.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Vincenzo Bronte", - "author_inst": "Immunology Section of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Stefano Ugel", - "author_inst": "Immunology Section of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Elisa Tinazzi", - "author_inst": "Internal Medicine Section B of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Antonio Vella", - "author_inst": "Immunology Section of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Francesco De Sanctis", - "author_inst": "Immunology Section of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Stefania Can\u00e8", - "author_inst": "Immunology Section of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Veronica Batani", - "author_inst": "Immunology Section of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Rosalinda Trovato", - "author_inst": "Immunology Section of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Alessandra Fiore", - "author_inst": "Immunology Section of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Varvara Petrova", - "author_inst": "Immunology Section of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Francesca Hofer", - "author_inst": "Immunology Section of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Roza Maria Barouni", - "author_inst": "Immunology Section of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Chiara Musiu", - "author_inst": "Immunology Section of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Simone Caligola", - "author_inst": "Immunology Section of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Laura Pinton", - "author_inst": "Immunology Section of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Lorena Torroni", - "author_inst": "Unit of Epidemiology and Medical Statistics, Infectious Disease Section of Diagnostics and Public Health Department of University and Hospital Trust of Verona, " - }, - { - "author_name": "Enrico Polati", - "author_inst": "Anestesia and Rianimazione Section of Surgery, Dentistry, Maternity and Infant Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Katia Donadello", - "author_inst": "Anestesia and Rianimazione Section of Surgery, Dentistry, Maternity and Infant Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Simonetta Friso", - "author_inst": "Internal Medicine Section B of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Francesca Pizzolo", - "author_inst": "Internal Medicine Section B of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" - }, - { - "author_name": "Manuela Iezzi", - "author_inst": "CAST Center for Advanced Studies and Technology, University of G. D Annunzio of Chieti-Pescara" - }, - { - "author_name": "Federica Facciotti", - "author_inst": "European Institute of Oncology (IEO) IRCCS, Milano (MI), Italy" - }, - { - "author_name": "Pier Giuseppe Pelicci", - "author_inst": "European Institute of Oncology (IEO) IRCCS , Milano (MI), Italy" - }, - { - "author_name": "Daniela Righetti", - "author_inst": "Medicine Unit of Pederzoli Hospital Peschiera, Peschiera (VR), Italy" - }, - { - "author_name": "Paolo Bazzoni", - "author_inst": "Medicine Unit of Pederzoli Hospital Peschiera, Peschiera (VR), Italy" - }, - { - "author_name": "Marielisa Rampudda", - "author_inst": "Medicine Unit of Pederzoli Hospital Peschiera, Peschiera (VR), Italy" - }, - { - "author_name": "Andrea Comel", - "author_inst": "Pneumology Unit of Pederzoli Hospital Peschiera, Peschiera (VR), Italy" - }, - { - "author_name": "Walter Mosaner", - "author_inst": "Intensive Care Unit of Pederzoli Hospital Peschiera, Peschiera (VR), Italy" - }, - { - "author_name": "Caludio Lunardi", - "author_inst": "Internal Medicine Section B of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" + "author_name": "Marcus J Lyall", + "author_inst": "NHS Lothian" }, { - "author_name": "Oliviero Olivieri", - "author_inst": "Internal Medicine Section B of Medicine Department of University and Hospital Trust of Verona, Verona (VR), Italy" + "author_name": "Nazir Lone", + "author_inst": "Usher Institute, University of Edinburgh" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "emergency medicine" }, { "rel_doi": "10.1101/2020.06.27.20141689", @@ -1316397,77 +1316581,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.28.20142190", - "rel_title": "Seroconversion of a city: Longitudinal monitoring of SARS-CoV-2 seroprevalence in New York City", + "rel_doi": "10.1101/2020.06.28.20141655", + "rel_title": "Excess mortality and potential undercounting of COVID-19 deaths by demographic group in Ohio", "rel_date": "2020-06-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.28.20142190", - "rel_abs": "By conducting a retrospective, cross-sectional analysis of SARS-CoV-2 seroprevalence in a sentinel group (enriched for SARS-CoV-2 infections) and a screening group (representative of the general population) using >5,000 plasma samples from patients at Mount Sinai Hospital in New York City (NYC), we identified seropositive samples as early as in the week ending February 23, 2020. A stark increase in seropositivity in the sentinel group started the week ending March 22 and in the screening group in the week ending March 29. By the week ending April 19, the seroprevalence in the screening group reached 19.3%, which is well below the estimated 67% needed to achieve community immunity to SARS-CoV-2. These data potentially suggest an earlier than previously documented introduction of SARS-CoV-2 into the NYC metropolitan area.\n\nOne Sentence SummarySeroprevalence of SARS-CoV-2 in cross-sectional samples from New York City rose from 0% to 19.3% from early February to mid-April.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.28.20141655", + "rel_abs": "BackgroundThere are significant gaps in our understanding of the mortality effects of COVID-19 due to evolving diagnosis criteria, shortages of testing supplies, and challenges faced by physicians in treating patients in crisis environments. Accurate information on the number of deaths caused by COVID-19 is vital for policy makers and health care providers.\n\nMethodsWe performed a retrospective study of weekly data for Ohio. To estimate expected mortality in 2020 we employed data from 2010 through 2019, adjusted for secular trends and seasonality. We estimated excess mortality as the number of observed deaths less the number of expected deaths. We conducted the analysis for the entire population and by age, gender, and county.\n\nResultsWe estimated 2,088 (95% CI 1,119-3,119) excess deaths due to natural causes in Ohio from March 15, 2020 through June 6, 2020. While the largest number excess of deaths was observed in the 80+ age group, our estimate of 366 (95% CI 110-655) excess deaths for those between 20 and 49 years of age substantially exceeds the reported number of COVID-19 deaths of 66.\n\nConclusionsOur methodology addressed some of the challenges of estimating the number of deaths caused by COVID-19. Our finding of excess deaths being considerably greater than the reported number of COVID-19 deaths for those aged 20 to 49 years old suggests that current tracking methods may not capture a significant number of COVID-19 deaths for this group. Further, increases in the infection rates for this cohort may have a greater mortality impact than anticipated.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Daniel Stadlbauer", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Jessica Tan", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Kaijun Jiang", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Matthew Hernandez", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Shelcie Fabre", - "author_inst": "Mount Sinai Hospital" - }, - { - "author_name": "Fatima Amanat", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Catherine Teo", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Guh Asthagiri Arunkumar", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Meagan McMahon", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Jeffrey Jhang", - "author_inst": "Mount Sinai Hospital" - }, - { - "author_name": "Michael Nowak", - "author_inst": "Mount Sinai Hospital" - }, - { - "author_name": "Viviana Simon", - "author_inst": "Icahn School of Medicine" - }, - { - "author_name": "Emilia Sordillo", - "author_inst": "Mount Sinai Hospital" - }, - { - "author_name": "Harm van Bakel", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Troy Quast", + "author_inst": "University of South Florida, College of Public Health" }, { - "author_name": "Florian Krammer", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Ross Andel", + "author_inst": "University of South Florida, College of Behavioral and Community Sciences" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1317859,25 +1317991,17 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.26.20140921", - "rel_title": "Short Communication: Vitamin D and COVID-19 infection and mortality in UK Biobank", + "rel_doi": "10.1101/2020.06.26.20141135", + "rel_title": "Adjusting confirmed COVID-19 case counts for testing volume", "rel_date": "2020-06-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.26.20140921", - "rel_abs": "PurposeVitamin D has been proposed as a potential causal factor in COVID-19 risk. We aimed to establish whether blood 25-hydroxyvitamin D (25(OH)D) concentration was associated with COVID-19 mortality, and inpatient confirmed COVID-19 infection, in UK Biobank participants.\n\nMethodsUK Biobank recruited 502,624 participants aged 37-73 years between 2006 and 2010. Baseline exposure data, including 25(OH)D concentration, were linked to COVID-19 mortality. Univariable and multivariable Cox proportional hazards regression analyses were performed for the association between 25(OH)D and COVID-19 death, and poisson regression analyses for the association between 25(OH)D and severe COVID-19 infection.\n\nResultsComplete data were available for 341,484 UK Biobank participants, of which 656 had inpatient confirmed COVID-19 infection and 203 died of COVID-19 infection. Vitamin D was associated with severe COVID-19 infection and mortality univariably (mortality HR=0.99; 95% CI 0.98-0.998; p=0.016), but not after adjustment for confounders (mortality HR=0.998; 95% CI=0.99-1.01; p=0.696).\n\nConclusionsOur findings do not support a potential link between vitamin D concentrations and risk of severe COVID-19 infection and mortality. Recommendations for vitamin D supplementation to lessen COVID-19 risks may provide false reassurance.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.26.20141135", + "rel_abs": "When assessing the relative prevalence of the novel coronavirus (COVID-19), observers often point to the number of COVID-19 cases that have been confirmed through viral testing. However, comparisons based on confirmed case counts alone can be misleading since a higher case count may reflect either a higher disease prevalence or a better rate of disease detection. Using weekly records of viral test results for each state in the US, I demonstrate how confirmed case counts can be adjusted based on the percentage of COVID-19 tests that come back positive. A regression analysis indicates that case counts track better with future hospitalizations and deaths when employing this simple adjustment for testing coverage. Viral testing results can be used as a leading indicator of COVID-19 prevalence, but data reporting standards should be improved, and care should be taken to account for testing coverage when comparing confirmed case counts.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Claire E Hastie", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Jill P Pell", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Naveed Sattar", - "author_inst": "University of Glasgow" + "author_name": "Nathan Favero", + "author_inst": "American University" } ], "version": "1", @@ -1319505,25 +1319629,29 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2020.06.24.20139204", - "rel_title": "Contact Tracing Evaluation for COVID-19 Transmission during the Reopening Phase in a Rural College Town", + "rel_doi": "10.1101/2020.06.24.20139451", + "rel_title": "Estimating the global spread of COVID-19", "rel_date": "2020-06-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20139204", - "rel_abs": "Contact tracing can play a vital role in controlling human-to-human transmission of a highly contagious disease such as COVID-19. To investigate the benefits and costs of contact tracing, we develop an individual-based contact-network model and a susceptible-exposed-infected-confirmed (SEIC) epidemic model for the stochastic simulations of COVID-19 transmission. We estimate the unknown parameters (reproductive ratio R0 and confirmed rate{delta} 2) by using observed confirmed case data. After a two month-lockdown, states in the USA have started the reopening process. We investigate for four different reopening situations: under \"stay-at-home\" order or no reopening, 25 % reopening, 50 % reopening, and 75 % reopening. We model contact tracing in a two-layer network by modifying the basic SEIC epidemic model. The two-layer network is composed by the contact network in the first layer and the tracing network in the second layer. Since the full contact list of an infected individual patient can be hard to obtain, then we consider different fractions of contacts from 60% to 5%. The goal of this paper is to assess the effectiveness of contact tracing to control the COVID-19 spreading during the initial phase of the reopening process of a rural college town.\n\nIn this research, we assess the benefits and cost of contact tracing as a key mitigation strategy to control the spreading of COVID-19. In terms of benefits, our simulation results show that increasing the fraction of traced contacts decreases the size of the epidemic. For example, tracing 20% of the contacts is enough for all four reopening scenarios to reduce the epidemic size by half. Considering the act of quarantining susceptible households as the contact tracing cost, we have observed an interesting phenomenon. When we increase the fraction of traced contacts from 5% to 20%, the number of quarantined susceptible people increases because each individual confirmed case is mentioning more contacts. However, when we increase the fraction of traced contacts from 20% to 60%, the number of quarantined susceptible people decreases because the increment of the mentioned contacts is balanced by a reduced number of confirmed cases. The outcomes of this research are valuable in the reopening process of the USA. Furthermore, the framework is generic enough to use any locations and for other diseases as well.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20139451", + "rel_abs": "COVID-19 prevalence and mortality remain uncertain. For all 86 countries with reliable testing data we estimate how asymptomatic transmission, disease acuity, hospitalization, and behavioral responses to risk shape pandemic dynamics. Estimated cumulative cases and deaths through 10 July 2020 are 10.5 and 1.47 times official reports, yielding an infection fatality rate (IFR) of 0.65%, with wide variation across nations. Despite underestimation, herd immunity remains distant. Sufficient early testing could have averted 39.7 (35.3-45.3) million cases and 218 (191-257) thousand deaths. Responses to perceived risk cause the reproduction number to settle near 1, but with very different steady-state incidence, while some nations experience endogenous rebounds. Scenarios through March 2021 show modest enhancements in responsiveness could reduce cumulative cases {approx}80%, to 271 (254-412) million across these nations.\n\nOne Sentence SummaryCOVID-19 under-reporting is large, varies widely across nations, and strongly conditions projected outbreak dynamics.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Sifat afroj Moon", - "author_inst": "Kansas State University" + "author_name": "Hazhir Rahmandad", + "author_inst": "Massachusetts Institute of Technology" }, { - "author_name": "Caterina Scoglio", - "author_inst": "Kansas State University" + "author_name": "Tse Yang Lim", + "author_inst": "Massachusetts Institute of Technology" + }, + { + "author_name": "John Sterman", + "author_inst": "Massachusetts Institute of Technology" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1320771,43 +1320899,55 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.06.25.20140426", - "rel_title": "The psychological effects of quarantine during COVID-19 outbreak: Sentiment analysis of social media data", + "rel_doi": "10.1101/2020.06.25.20139881", + "rel_title": "Erythrocyte Sedimentation Rate in COVID-19 Infections", "rel_date": "2020-06-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.25.20140426", - "rel_abs": "We rely on social distancing measures such as quarantine and isolation to contain the COVID-19. However, the negative psychological effects of these measures are non-negligible. To supplement previous research on psychological effects after quarantine, this research will investigate the effects of quarantine amid COVID-19. We adopt a sentiment analysis approach to analyze the psychological state changes of 1,278 quarantined persons 214,874 tweets over four weeks spanning the period before, during, and after quarantine. We formed a control group of 1,278 unquarantined persons with 250,198 tweets. The tweets of both groups are analyzed by matching with a lexicon to measure the anxious depression level changes over time. We discovered a clear pattern of psychological changes for quarantined persons. Anxious depression levels significantly increased as quarantine starts, but gradually diminished as it progresses. However, anxious depression levels resurged after 14 days quarantine. It was found that quarantine has a negative impact on mental health of quarantined and unquarantined people. Whilst quarantine is deemed necessary, proper interventions such as emotion management should be introduced to mitigate its adverse psychological impacts.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.25.20139881", + "rel_abs": "ObjectivesTo compare the clinical characteristics between the rapid cohort and the normal cohort of erythrocyte sedimentation rate (ESR) in COVID-19 infections, analyze the variables with significant differences, and explore the influencing factors of rapid ESR.\n\nMethodsSelected a total of 80 patients with ESR detection during hospitalization were measured in 146 patients who received medical observation in concentrated isolation hospital in Guizhou province in China, collected and compared demographic information, epidemiological data, clinical symptoms, laboratory test data and CT image data during the observation between rapid cohort and normal group of ESR.\n\nResultsBy comparison, the proportion of male in the rapid cohort was higher than female. The average age was more than 35 years old, with a large age gap. The proportion of severe and critical patients was more than 26.53% (13/49). However, in the normal cohort the proportion of female was more than male, and the average age was about 8 years lower than the rapid cohort, and the age gap was smaller. The proportion of severe and critical patients was 12.90%, which was less than half of the rapid group. In the two groups, the proportion of clustered cases accounted for more than 50%, and the average number of patients in one family was more than 3. The most common clinical symptoms were cough, sputum, fever, sore throat and weakness of limbs. There were significant differences in ALT, {gamma}-GT and C-reactive protein between the rapid and normal cohort (P<0.05), but no statistically significant in other indicators. Hemoglobin and C-reactive protein have a significant effect on erythrocyte sedimentation rate.\n\nConclusionsIn this study, we found that ESR is related to Hemoglobin and C-reactive protein. (Funded by Science and Technology Department of Guizhou Province; Chinese ClinicalTrials.gov number, ChiCTR2000033346. opens in new tab.)", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Weisheng Lu", - "author_inst": "The University of Hong Kong" + "author_name": "Wei Zhang", + "author_inst": "Affiliated Hospital of Zunyi Medical University" }, { - "author_name": "Liang Yuan", - "author_inst": "Chongqing University" + "author_name": "Youshu Yuan", + "author_inst": "Guizhou University" }, { - "author_name": "Jinying Xu", - "author_inst": "The University of Hong Kong" + "author_name": "Shucheng Zhang", + "author_inst": "Zunyi Medical University" }, { - "author_name": "Fan Xue", - "author_inst": "The University of Hong Kong" + "author_name": "Can Jin", + "author_inst": "Affiliated Hospital of Zunyi Medical University" }, { - "author_name": "Bin Zhao", - "author_inst": "Chongqing University" + "author_name": "Linlin Wu", + "author_inst": "Affiliated Hospital of Zunyi Medical University" }, { - "author_name": "Chris Webster", - "author_inst": "The University of Hong Kong" + "author_name": "Hong Mei", + "author_inst": "Affiliated Hospital of Zunyi Medical University" + }, + { + "author_name": "Chen Miao", + "author_inst": "Affiliated Hospital of Zunyi Medical University" + }, + { + "author_name": "Zhixia Jiang", + "author_inst": "Affiliated Hospital of Zunyi Medical University" + }, + { + "author_name": "Zhixu He", + "author_inst": "Zunyi Medical University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.06.24.20139329", @@ -1322421,55 +1322561,59 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.06.24.20139048", - "rel_title": "A geotemporal survey of hospital bed saturation across England during the first wave of the COVID-19 Pandemic", + "rel_doi": "10.1101/2020.06.24.20138941", + "rel_title": "Co-occurrence of SARS-CoV-2 and Respiratory Pathogens in the Frail Elderly", "rel_date": "2020-06-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20139048", - "rel_abs": "BackgroundNon-pharmacological interventions were introduced based on modelling studies which suggested that the English National Health Service (NHS) would be overwhelmed by the COVID-19 pandemic. In this study, we describe the pattern of bed occupancy across England during the first wave of the pandemic, January 31st to June 5th 2020.\n\nMethodsBed availability and occupancy data was extracted from daily reports submitted by all English secondary care providers, between 27-Mar and 5-June. Two thresholds for safe occupancy were utilized (85% as per Royal College of Emergency Medicine and 92% as per NHS Improvement).\n\nFindingsAt peak availability, there were 2711 additional beds compatible with mechanical ventilation across England, reflecting a 53% increase in capacity, and occupancy never exceeded 62%. A consequence of the repurposing of beds meant that at the trough, there were 8{middle dot}7% (8,508) fewer general and acute (G&A) beds across England, but occupancy never exceeded 72%. The closest to (surge) capacity that any trust in England reached was 99{middle dot}8% for general and acute beds. For beds compatible with mechanical ventilation there were 326 trust-days (3{middle dot}7%) spent above 85% of surge capacity, and 154 trust-days (1{middle dot}8%) spent above 92%. 23 trusts spent a cumulative 81 days at 100% saturation of their surge ventilator bed capacity (median number of days per trust = 1 [range: 1 to 17]). However, only 3 STPs (aggregates of geographically co-located trusts) reached 100% saturation of their mechanical ventilation beds.\n\nInterpretationThroughout the first wave of the pandemic, an adequate supply of all bed-types existed at a national level. Due to an unequal distribution of bed utilization, many trusts spent a significant period operating above safe-occupancy thresholds, despite substantial capacity in geographically co-located trusts; a key operational issue to address in preparing for a potential second wave.\n\nFundingThis study received no funding.\n\nResearch In ContextO_ST_ABSEvidence Before This StudyC_ST_ABSWe identified information sources describing COVID-19 related bed and mechanical ventilator demand modelling, as well as bed occupancy during the first wave of the pandemic by performing regular searches of MedRxiv, PubMed and Google, using the terms COVID-19, mechanical ventilators, bed occupancy, England, UK, demand, and non-pharmacological interventions (NPIs), until June 20th, 2020. Two UK-specific studies were found that modelled the demand for mechanical ventilators, one of which incorporated sensitivity analysis based on the introduction of NPIs and found that their effects might prevent the healthcare system being overwhelmed. Separately, several news reports were found pertaining to a single hospital that reached ventilator capacity in England during the first wave of the pandemic, however, no single authoritative source was identified detailing impact across all hospital sites in England.\n\nAdded Value of This StudyThis national study of hospital-level bed occupancy in England provides unique and timely insight into bed-specific resource utilization during the first wave of the COVID-19 pandemic, nationally, and by specific (geographically defined) health footprints. We found evidence of an unequal distribution of resource utilization across England. Although occupancy of beds compatible with mechanical ventilation never exceeded 62% at the national level, 52 (30%) hospitals across England reached 100% saturation at some point during the first wave of the pandemic. Close examination of the geospatial data revealed that in the vast majority of circumstances there was relief capacity in geographically co-located hospitals. Over the first wave it was theoretically possible to markedly reduce (by 95.1%) the number of hospitals at 100% saturation of their mechanical ventilator bed capacity by redistributing patients to nearby hospitals.\n\nImplications Of All The Available EvidenceNow-casting using routinely collected administrative data presents a robust approach to rapidly evaluate the effectiveness of national policies introduced to prevent a healthcare system being overwhelmed in the context of a pandemic illness. Early investment in operational field hospital and an independent sector network may yield more overtly positive results in the winter, when G&A occupancy-levels regularly exceed 92% in England, however, during the first wave of the pandemic they were under-utilized. Moreover, in the context of the non-pharmacological interventions utilized during the first wave of COVID-19, demand for beds and mechanical ventilators was much lower than initially predicted, but despite this many trust spent a significant period of time operating above safe-occupancy thresholds. This finding demonstrates that it is vital that future demand (prediction) models reflect the nuances of local variation within a healthcare system. Failure to incorporate such geographical variation can misrepresent the likelihood of surpassing availability thresholds by averaging out over regions with relatively lower demand, and presents a key operational issue for policymakers to address in preparing for a potential second wave.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20138941", + "rel_abs": "BackgroundElderly SARS-CoV-2 patients are associated with higher hospitalization and mortality. Co-infection is critical in the severity of respiratory diseases. It is largely understudied for SARS-CoV-2.\n\nMethodsBetween March 24th and April 27th, 2020, nasopharyngeal and oropharyngeal swabs from 3,348 patients from nursing homes and assisted living facilities in 22 states in the US were tested by Capstone Healthcare for SARS-CoV-2, 24 other respiratory viruses, and 8 respiratory bacteria. Total nucleic acid was extracted with MagMAX Viral/Pathogen Ultra nucleic acid isolation kit. SARS-Co-V-2 was detected with the CDC 2019-novel coronavirus (2019-nCoV) diagnostic panel. Total nucleic acid was pre-amplified before analysis for other respiratory pathogens with Taqman OpenArray Respiratory Tract Microbiota Plate.\n\nResultsPatients mean age was 76.9 years. SARS-CoV-2 was detected in 1,413 patients (42.2%). Among them, 1,082 (76.6%) and 737 (43.7%) patients were detected with at least one bacterium or another virus, respectively. SARS-CoV-2-positive patients were more likely to have bacterial co-occurrences (76.6%) than SARS-CoV-2-negative patients (70.0%) (p<0.0001). The most common co-occurring bacteria were Staphylococcus aureus and Klebsiella pneumonia, detected in 55.8% and 40.1% SARS-CoV-2-positive patients, respectively. Staphylococcus aureus was associated with SARS-CoV-2, with higher detection rates in SARS-CoV-2-positive patients (55.8%) than SARS-CoV-2-negative patients (46.2%) (p<0.0001). Human herpes virus 6 (HHV6) also was common and associated with SARS-CoV-2, with higher detection rates in SARS-CoV-2-positive patients (26.6%) than SARS-CoV-2-negative patients (19.1%) (p<0.0001).\n\nConclusionsSARS-CoV-2-positive patients are more likely to be positive for certain respiratory bacteria and viruses. This observation may help explain high hospitalization and mortality rates in older patients.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Bilal A Mateen", - "author_inst": "The Alan Turing Institute; University of Warwick; Kings College Hospital NHS Foundation Trust" + "author_name": "David Baunoch", + "author_inst": "Pathnostics" }, { - "author_name": "Harrison Wilde", - "author_inst": "University of Warwick, Department of Statistics" + "author_name": "Alan Wolfe", + "author_inst": "Loyola University Chicago Stritch School of Medicine" }, { - "author_name": "John m Dennis", - "author_inst": "University of Exeter Medical School" + "author_name": "Dakun Wang", + "author_inst": "Stat4ward" }, { - "author_name": "Andrew Duncan", - "author_inst": "The Alan Turing Institute; Imperial College London, Faculty of Natural Sciences" + "author_name": "Ryan Gnewuch", + "author_inst": "Pathnostics" }, { - "author_name": "Nicholas John Meyrick Thomas", - "author_inst": "University of Exeter Medical School" + "author_name": "Xinhua Zhao", + "author_inst": "Stat4ward" }, { - "author_name": "Andrew P McGovern", - "author_inst": "Royal Devon and Exeter NHS Foundation Trust, Diabetes and Endocrinology; University of Exeter Medical School" + "author_name": "Thomas Halverson", + "author_inst": "Loyola University Chicago" }, { - "author_name": "Spiros Denaxas", - "author_inst": "University College London" + "author_name": "Patrick Cacdac", + "author_inst": "Pathnostics" }, { - "author_name": "Matt J Keeling", - "author_inst": "University of Warwick" + "author_name": "Shuguang Huang", + "author_inst": "Stat4ward" }, { - "author_name": "Sebastian J Vollmer", - "author_inst": "The Alan Turing Institute; University of Warwick, Department of Statistics" + "author_name": "Trisha Lauterbach", + "author_inst": "Capstone Laboratory" + }, + { + "author_name": "Natalie Luke", + "author_inst": "Pathnostics" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health systems and quality improvement" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.06.24.20138982", @@ -1324090,23 +1324234,31 @@ "category": "neuroscience" }, { - "rel_doi": "10.1101/2020.06.23.167916", - "rel_title": "In silico identification of conserved cis-acting RNA elements in the SARS-CoV-2 genome", + "rel_doi": "10.1101/2020.06.24.169268", + "rel_title": "Comparative transcriptome analyses reveal genes associated with SARS-CoV-2 infection of human lung epithelial cells", "rel_date": "2020-06-24", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.23.167916", - "rel_abs": "AimThe aim of this study was to computationally predict conserved RNA sequences and structures known as cis-acting RNA elements (CREs) located within the SARS-CoV-2 genome.\n\nMaterials & methodsBioinformatics tools were used to analyse and predict cis-acting regulatory elements by obtaining viral sequences from available databases.\n\nResultsComputational analysis prediction revealed the presence of RNA stem-loop structures within the 3 end of the ORF1ab region that are analogous to the previously identified SARS-CoV genomic packaging signals. Alignment-based RNA secondary structures prediction of the 5 end of the SARS-CoV-2 genome identified also conserved CREs.\n\nConclusionThese CREs could be used as potential targets for a vaccine and/or antiviral therapeutics developments; however, further studies would be required to confirm their roles in the SARS-CoV-2 life cycle.", - "rel_num_authors": 1, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.24.169268", + "rel_abs": "Understanding the molecular mechanism of SARS-CoV-2 infection (the cause of COVID-19) is a scientific priority for 2020. Various research groups are working toward development of vaccines and drugs, and many have published genomic and transcriptomic data related to this viral infection. The power inherent in publicly available data can be demonstrated via comparative transcriptome analyses. In the current study, we collected high-throughput gene expression data related to human lung epithelial cells infected with SARS-CoV-2 or other respiratory viruses (SARS, H1N1, rhinovirus, avian influenza, and Dhori) and compared the effect of these viruses on the human transcriptome. The analyses identified fifteen genes specifically expressed in cells transfected with SARS-CoV-2; these included CSF2 (colony-stimulating factor 2) and S100A8 and S100A9 (calcium-binding proteins), all of which are involved in lung/respiratory disorders. The analyses showed that genes involved in the Type1 interferon signaling pathway and the apoptosis process are commonly altered by infection of SARS-CoV-2 and influenza viruses. Furthermore, results of protein-protein interaction analyses were consistent with a functional role of CSF2 in COVID-19 disease. In conclusion, our analysis has revealed cellular genes associated with SARS-CoV-2 infection of the human lung epithelium; these are potential therapeutic targets.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Bader Y. Alhatlani", - "author_inst": "Qassim University - Unayzah Community College" + "author_name": "Darshan S Chandrashekar", + "author_inst": "University of Alabama at Birmingham" + }, + { + "author_name": "Upender Manne", + "author_inst": "University of Alabama at Birmingham" + }, + { + "author_name": "Sooryanarayana Varambally", + "author_inst": "University of Alabama at Birmingham" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.06.24.168534", @@ -1325243,95 +1325395,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.23.166397", - "rel_title": "Scalable, rapid and highly sensitive isothermal detection of SARS-CoV-2 for laboratory and home testing", + "rel_doi": "10.1101/2020.06.19.20109173", + "rel_title": "Short-Term Corticosteroids in SARS-CoV2 Patients: Hospitalists' Perspective", "rel_date": "2020-06-23", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.23.166397", - "rel_abs": "Global efforts to combat the Covid-19 pandemic caused by SARS-CoV-2 still heavily rely on RT-qPCR-based diagnostic tests. However, their high cost, moderate throughput and reliance on sophisticated equipment limit widespread implementation. Loop-mediated isothermal amplification after reverse transcription (RT-LAMP) is an alternative detection method that has the potential to overcome these limitations. We present a rapid, robust, sensitive and versatile RT-LAMP based SARS-CoV-2 detection assay. Our forty-minute procedure bypasses a dedicated RNA isolation step, is insensitive to carry-over contamination, and uses a hydroxynaphthol blue (HNB)-based colorimetric readout, which allows robust SARS-CoV-2 detection from various sample types. Based on this assay, we have substantially increased sensitivity and scalability by a simple nucleic acid enrichment step (bead-LAMP), established a pipette-free version for home testing (HomeDip-LAMP), and developed open source enzymes that can be produced in any molecular biology setting. Our advanced, universally applicable RT-LAMP assay is a major step towards population-scale SARS-CoV-2 testing.", - "rel_num_authors": 19, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.19.20109173", + "rel_abs": "BackgroundDexamethasone, a synthetic glucocorticoid, has anti-inflammatory and immunosuppressive properties. There is a hyperinflammatory response involved in the clinical course of patients with pneumonia due to SARS-CoV2. To date, there has been no definite therapy for COVID-19. We reviewed the charts of SARS-CoV2 patients with pneumonia and moderate to severely elevated CRP and worsening hypoxemia who were treated with early, short-term dexamethasone.\n\nMethodsWe describe a series of 21 patients who tested positive for SARS-CoV2 and were admitted to The Miriam Hospital in Providence and were treated with a short course of dexamethasone, either alone or in addition to current investigative therapies.\n\nResultsCRP levels decreased significantly following the start of dexamethasone from mean initial levels of 129.52 to 40.73 mg/L at time of discharge. 71% percent of the patients were discharged home with a mean length of stay of 7.8 days. None of the patients had escalation of care, leading to mechanical ventilation. Two patients were transferred to inpatient hospice facilities on account of persistent hypoxemia, in line with their documented goals of care.\n\nConclusionsA short course of systemic corticosteroids among inpatients with SARS-CoV2 with hypoxic respiratory failure was well tolerated, and most patients had improved outcomes. This limited case series may not offer concrete evidence towards the benefit of corticosteroids in COVID-19. However, patients positive response to short-term corticosteroids demonstrates that they may help blunt the severity of inflammation and prevent a severe hyperinflammatory phase, in turn reducing the length of stay, ICU admissions, and healthcare costs.\n\nSummaryIn this series, we demonstrate that timely, short-term use of systemic corticosteroids among hospitalized patients with hypoxic respiratory failure due to SARS-CoV2 was well tolerated with good outcomes. The outcomes were reflected by reductions in inpatient mortality, CRP levels, requirement for mechanical ventilation and escalation of care.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Max J Kellner", - "author_inst": "IMP, IMBA and LMB" - }, - { - "author_name": "James J Ross", - "author_inst": "IMBA, Vienna, Austria" - }, - { - "author_name": "Jakob Schnabl", - "author_inst": "IMBA, Vienna, Austria" - }, - { - "author_name": "Marcus P.S. Dekens", - "author_inst": "IMP, Vienna, Austria" - }, - { - "author_name": "Robert Heinen", - "author_inst": "IMP, IMBA, Vienna, Austria" - }, - { - "author_name": "Irina Grishkovskaya", - "author_inst": "IMP" - }, - { - "author_name": "Benedikt Bauer", - "author_inst": "IMP" - }, - { - "author_name": "Johannes Stadlmann", - "author_inst": "Department of Chemistry, University of Natural Resources and Life Sciences, Vienna" - }, - { - "author_name": "Luis Menendez-Arias", - "author_inst": "Centro de Biologia Molecular Severo Ochoa, Spain" - }, - { - "author_name": "Robert Fritsche-Polanz", - "author_inst": "Institute of Laboratory Diagnostics, Klinik Favoriten, Vienna, Austria" - }, - { - "author_name": "Marianna Traugott", - "author_inst": "4th Medical Department with Infectious Diseases and Tropical Medicine, Klinik Favoriten, Vienna, Austria" - }, - { - "author_name": "Tamara Seitz", - "author_inst": "4th Medical Department with Infectious Diseases and Tropical Medicine, Klinik Favoriten, 1100 Vienna, Austria" - }, - { - "author_name": "Alexander Zoufaly", - "author_inst": "4th Medical Department with Infectious Diseases and Tropical Medicine, Klinik Favoriten, 1100 Vienna, Austria" - }, - { - "author_name": "Manuela Foedinger", - "author_inst": "Institute of Laboratory Diagnostics, Klinik Favoriten; Sigmund Freud Private University, Vienna, Austria" - }, - { - "author_name": "Christoph Wenisch", - "author_inst": "4th Medical Department with Infectious Diseases and Tropical Medicine, Klinik Favoriten, Vienna, Austria" - }, - { - "author_name": "Johannes Zuber", - "author_inst": "IMP, Medical University of Vienna, Vienna, Austria" + "author_name": "Vijairam Selvaraj", + "author_inst": "The Miriam Hospital" }, { - "author_name": "- Vienna Covid-19 Diagnostics Initiative (VCDI)", - "author_inst": "-" + "author_name": "Kwame Dapaah-Afriyie", + "author_inst": "The Miriam Hospital" }, { - "author_name": "Andrea Pauli", - "author_inst": "IMP, Vienna, Austria" + "author_name": "Arkadiy Finn", + "author_inst": "The Miriam Hospital" }, { - "author_name": "Julius Brennecke", - "author_inst": "IMBA, Vienna, Austria" + "author_name": "Timothy Flanigan", + "author_inst": "Warren Alpert School of Medicine at Brown University" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "molecular biology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.06.15.20117747", @@ -1326713,69 +1326805,49 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.06.22.20137448", - "rel_title": "Humidity and deposition solution play a critical role in virus inactivation by heat treatment on N95 respirators", + "rel_doi": "10.1101/2020.06.22.20137216", + "rel_title": "Proteomic blood profiling in mild, severe and critical COVID-19 patients", "rel_date": "2020-06-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.22.20137448", - "rel_abs": "Supply shortages of N95 respirators during the coronavirus disease 2019 (COVID-19) pandemic have motivated institutions to develop feasible and effective N95 respirator reuse strategies. In particular, heat decontamination is a treatment method that scales well and can be implemented in settings with variable or limited resources. Prior studies using multiple inactivation methods, however, have often focused on a single virus under narrowly defined conditions, making it difficult to develop guiding principles for inactivating emerging or difficult-to-culture viruses. We systematically explored how temperature, humidity, and virus deposition solutions impact the inactivation of viruses deposited and dried on N95 respirator coupons. We exposed four virus surrogates across a range of structures and phylogenies, including two bacteriophages (MS2 and phi6), a mouse coronavirus (murine hepatitis virus, MHV), and a recombinant human influenza A virus subtype H3N2 (IAV), to heat treatment for 30 minutes in multiple deposition solutions across several temperatures and relative humidities (RH). We observed that elevated RH was essential for effective heat inactivation of all four viruses tested. For heat treatments between 72{degrees}C and 82{degrees}C, RH greater than 50% resulted in > 6-log10 inactivation of bacteriophages and RH greater than 25% resulted in > 3.5-log10 inactivation of MHV and IAV. Furthermore, deposition of viruses in host cell culture media greatly enhanced virus inactivation by heat and humidity compared to other deposition solutions such as phosphate buffered saline, phosphate buffered saline with bovine serum albumin, and human saliva. Past and future heat treatment methods or technologies must therefore explicitly account for deposition solutions as a factor that will strongly influence observed virus inactivation rates. Overall, our data set can inform the design and validation of effective heat-based decontamination strategies for N95 respirators and other porous surfaces, especially for emerging or low-titer viruses that may be of immediate public health concern such as SARS-CoV-2.\n\nImportanceShortages of personal protective equipment, including N95 respirators, during the coronavirus disease 2019 (COVID-19) pandemic have highlighted the need to develop effective decontamination strategies for their reuse. This is particularly important in healthcare settings for reducing exposure to respiratory viruses, like severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19. Although several treatment methods are available, a widely accessible strategy will be necessary to combat shortages on a global scale. We demonstrate that the combination of heat and humidity inactivates viruses similar in structure to SARS-CoV-2, namely MS2, phi6, influenza A virus, and mouse coronavirus, after deposition on N95 respirators, and achieves the United States Food and Drug Administration guidelines to validate N95 respirator decontamination technologies. We further demonstrate that depositing viruses onto surfaces when suspended in culture media can greatly enhance observed inactivation, adding caution to how heat and humidity treatments methods are validated.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.22.20137216", + "rel_abs": "The recent SARS-CoV-2 pandemic manifests itself as a mild respiratory tract infection in the majority of individuals leading to COVID-19 disease. However, in some infected individuals, this can progress to severe pneumonia and acute respiratory distress syndrome (ARDS), leading to multi-organ failure and death. The purpose of this study is to explore the proteomic differences between mild, severe and critical COVID-19 positive patients. Blood protein profiling was performed on 59 COVID-19 mild (n=26), severe (n=9) or critical (n=24) cases and 28 controls using the OLINK inflammation, autoimmune, cardiovascular and neurology panels. Differential expression analysis was performed within and between disease groups to generate nine different analyses. From the 368 proteins measured per individual, more than 75% were observed to be significantly perturbed in COVID-19 cases. Six proteins (IL6, CKAP4, Gal-9, IL-1ra, LILRB4 and PD-L1) were identified to be associated with disease severity. The results have been made readily available through an interactive web-based application for instant data exploration and visualization, and can be accessed at https://phidatalab-shiny.rosalind.kcl.ac.uk/COVID19/. Our results demonstrate that dynamic changes in blood proteins that associate with disease severity can potentially be used as early biomarkers to monitor disease severity in COVID-19 and serve as potential therapeutic targets.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Nicole Rockey", - "author_inst": "University of Michigan" - }, - { - "author_name": "Peter J. Arts", - "author_inst": "University of Michigan" - }, - { - "author_name": "Lucinda Li", - "author_inst": "University of Michigan" - }, - { - "author_name": "Katherine R. Harrison", - "author_inst": "University of Michigan" - }, - { - "author_name": "Kathryn Langenfeld", - "author_inst": "University of Michigan" - }, - { - "author_name": "William J. Fitzsimmons", - "author_inst": "University of Michigan Health System" + "author_name": "Hamel Patel", + "author_inst": "King's College London" }, { - "author_name": "Adam S. Lauring", - "author_inst": "University of Michigan Health System" + "author_name": "Nicholas J Ashton", + "author_inst": "University of Gothenburg" }, { - "author_name": "Nancy G. Love", - "author_inst": "University of Michigan" + "author_name": "Richard J Dobson", + "author_inst": "Kings College London" }, { - "author_name": "Keith S. Kaye", - "author_inst": "University of Michigan Health System" + "author_name": "Lars-magnus Anderson", + "author_inst": "Sahlgrenska university hospital" }, { - "author_name": "Lutgarde Raskin", - "author_inst": "University of Michigan" + "author_name": "Aylin Yilmaz", + "author_inst": "University of Gothenburg" }, { - "author_name": "William W. Roberts", - "author_inst": "University of Michigan Health System" + "author_name": "Kaj Blennow", + "author_inst": "University of Gothenburg" }, { - "author_name": "Bridget Hegarty", - "author_inst": "University of Michigan" + "author_name": "Magnus Gisslen", + "author_inst": "University of Gothenburg" }, { - "author_name": "Krista R. Wigginton", - "author_inst": "University of Michigan" + "author_name": "Henrik Zetterberg", + "author_inst": "University of Gothenburg" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1328219,43 +1328291,23 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.06.22.20137257", - "rel_title": "Cost-effectiveness and return on investment of protecting health workers in low- and middle-income countries during the COVID-19 pandemic", + "rel_doi": "10.1101/2020.06.22.20137133", + "rel_title": "Qualitative forecast and temporal evolution ofthe disease spreading using a simplified modeland COVID-19 data for Italy", "rel_date": "2020-06-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.22.20137257", - "rel_abs": "BackgroundIn this paper, we predict the health and economic consequences of immediate investment in personal protective equipment (PPE) for health care workers (HCWs) in low- and middle-income countries (LMICs).\n\nMethodsTo account for health consequences, we estimated mortality for health care workers (HCW), and present a cost-effectiveness and return on investment (ROI) analysis using a decision-analytic model with Bayesian multivariate sensitivity analysis and Monte Carlo simulation. Inputs were used from the World Health Organization Essential Supplies Forecasting Tool and the Imperial College of London epidemiologic model.\n\nResultsAn investment of $9.6 billion USD would adequately protect HCWs in all LMICs. This intervention saves 2,299,543 lives across LMICs, costing $59 USD per HCW case averted and $4,309 USD per HCW life saved. The societal ROI is $755.3 billion USD, the equivalent of a 7,932% return. Regional and national estimates are also presented. In scenarios where PPE remains scarce, 70-100% of HCWs will get infected, irrespective of nationwide social distancing policies. Maintaining HCW infection rates below 10% and mortality below 1% requires inclusion of a PPE scale-up strategy as part of the pandemic response.\n\nDiscussionIn conclusion, wide-scale procurement and distribution of PPE for LMICs is an essential strategy to prevent widespread HCW morbidity and mortality. It is cost-effective and yields a large downstream return on investment.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.22.20137133", + "rel_abs": "In a previous paper [1] a simplified SEIR model applied to COVID-19 cases detected in Italy, including the lockdown period, has shown a good fitting to the time evolution of the disease during the observed period.\n\nIn this paper that model is applied to the initial data available for Italy in order to forecast, in a qualitative way, the time evolution of the disease spreading. The values obtained are to be considered indicative.\n\nThe same model has been applied both to the data relating to Italy and to some italian regions (Lombardia, Piemonte, Lazio, Campania, Calabria, Sicilia, Sardegna), generally finding good qualitative results.\n\nThe only tuning parameter in the model is the incubation period{tau} .\n\nIn this modelization the tuning parameter, together with the calculated growth rate{kappa} of the exponential curve used to approximate the early stage data, are in strong relationship with the compartments transfer rates.\n\nThe relationships between the parameters simplify modeling by allowing a rough (not supported by statistical considerations) forecast of the time evolution, starting from the first period of growth of the diffusion.\n\nRevision historyRevision # 1\n\nO_LIErrata corrige in the system differential equation 1: in the the derivative of S were reported a wrong additional term N. Now the equation 1 is correct.\nC_LI", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Nicholas Risko", - "author_inst": "Johns Hopkins University" - }, - { - "author_name": "Kalin Werner", - "author_inst": "University of Cape Town, South Africa" - }, - { - "author_name": "O Agatha Offorjebe", - "author_inst": "University of South California Keck School of Medicine, Los Angeles, USA" - }, - { - "author_name": "Andres I Vecino-Ortiz", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" - }, - { - "author_name": "Lee A Wallis", - "author_inst": "University of Cape Town, South Africa" - }, - { - "author_name": "Junaid Razzak", - "author_inst": "Johns Hopkins University Schoolof Medicine" + "author_name": "Roberto Simeone", + "author_inst": "None" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.06.23.20137596", @@ -1329753,125 +1329805,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.19.20134379", - "rel_title": "COVID-19 severity is associated with immunopathology and multi-organ damage", + "rel_doi": "10.1101/2020.06.18.20134759", + "rel_title": "Genetic diversity among SARS-CoV2 strains in South America may impact performance of Molecular detection", "rel_date": "2020-06-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.19.20134379", - "rel_abs": "COVID-19 is characterised by dysregulated immune responses, metabolic dysfunction and adverse effects on the function of multiple organs. To understand how host responses contribute to COVID-19 pathophysiology, we used a multi-omics approach to identify molecular markers in peripheral blood and plasma samples that distinguish COVID-19 patients experiencing a range of disease severities. A large number of expressed genes, proteins, metabolites and extracellular RNAs (exRNAs) were identified that exhibited strong associations with various clinical parameters. Multiple sets of tissue-specific proteins and exRNAs varied significantly in both mild and severe patients, indicative of multi-organ damage. The continuous activation of IFN-I signalling and neutrophils, as well as a high level of inflammatory cytokines, were observed in severe disease patients. In contrast, COVID-19 in mild patients was characterised by robust T cell responses. Finally, we show that some of expressed genes, proteins and exRNAs can be used as biomarkers to predict the clinical outcomes of SARS-CoV-2 infection. These data refine our understanding of the pathophysiology and clinical progress of COVID-19 and will help guide future studies in this area.", - "rel_num_authors": 27, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.18.20134759", + "rel_abs": "Since its emergence in Wuhan (China) on December 2019 the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has rapidly spread worldwide. After its arrival in South America in February 2020 the virus has expanded throughout the region infecting over 900,000 individuals with approximately 41,000 reported deaths to date. In response to the rapidly growing number of cases, a number of different primer-probe sets have been developed. However, despite being highly specific most of these primer-probe sets are known to exhibit variable sensitivity.\n\nCurrently, there are more than 700 SARS-CoV2 whole genome sequences deposited in databases from Brazil, Chile, Ecuador, Colombia, Uruguay, Peru and Argentina. To test how regional viral diversity may impact oligo binding sites and affect test performance, we reviewed all available primer-probe sets targeting the E, N and RdRp genes against available South American SARS-CoV-2 genomes checking for nucleotide variations in annealing sites. Results from this in silico analysis showed no nucleotide variations on the E-gene target region, in contrast to the N and RdRp genes which showed massive nucleotide variations within oligo binding sites. In lines with previous data, our results suggest that E-gene stands as the most conserved and reliable target when considering single-gene target testing for molecular diagnosis of SARS-CoV-2 in South America.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Yan-Mei Chen", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Yuanting Zheng", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Ying Yu", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Yunzhi Wang", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Qingxia Huang", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Feng Qian", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Lei Sun", - "author_inst": "Institute of Developmental Biology and Molecular Medicine, Fudan University, Shanghai, China." - }, - { - "author_name": "Zhi-Gang Song", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Ziyin Chen", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Jinwen Feng", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Yanpeng An", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Jingcheng Yang", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Zhenqiang Su", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Shanyue Sun", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Fahui Dai", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Qinsheng Chen", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Qinwei Lu", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Pengcheng Li", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" - }, - { - "author_name": "Yun Ling", - "author_inst": "Shanghai Public Health Clinical Center" + "author_name": "Juan David Ramirez", + "author_inst": "Universidad del Rosario" }, { - "author_name": "Zhong Yang", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" + "author_name": "Marina Munoz", + "author_inst": "Universidad del Rosario" }, { - "author_name": "Huiru Tang", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" + "author_name": "Carolina Hernandez", + "author_inst": "Universidad del Rosario" }, { - "author_name": "Leming Shi", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" + "author_name": "Carolina Florez", + "author_inst": "Universidad del Rosario" }, { - "author_name": "Li Jin", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" + "author_name": "Sergio Gomez", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Edward C Holmes", - "author_inst": "Marie Bashir Institute for Infectious Diseases and Biosecurity" + "author_name": "Angelica Rico", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Chen Ding", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" + "author_name": "Lisseth Pardo", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Tong-Yu Zhu", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" + "author_name": "Esther C Barros", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Yong-Zhen Zhang", - "author_inst": "Shanghai Public Health Clinical Center, State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shan" + "author_name": "Alberto Paniz-Mondolfi", + "author_inst": "Icahn School of Medicina at Mount Sinai" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1331174,43 +1331154,79 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2020.06.18.156851", - "rel_title": "Various RNA-binding proteins and their conditional networks explain miRNA biogenesis and help to reveal the potential SARS-CoV-2 host miRNAome system", + "rel_doi": "10.1101/2020.06.22.165225", + "rel_title": "In vivo antiviral host response to SARS-CoV-2 by viral load, sex, and age", "rel_date": "2020-06-22", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.18.156851", - "rel_abs": "Formation of mature miRNAs and their expression is a highly controlled process. It is very much dependent upon the post-transcriptional regulatory events. Recent findings suggest that several RNA binding proteins beyond Drosha/Dicer are involved in the processing of miRNAs. Deciphering of conditional networks for these RBP-miRNA interactions may help to reason the spatio-temporal nature of miRNAs which can also be used to predict miRNA profiles. In this direction, >25TB of data from different platforms were studied (CLIP-seq/RNA-seq/miRNA-seq) to develop Bayesian causal networks capable of reasoning miRNA biogenesis. The networks ably explained the miRNA formation when tested across a large number of conditions and experimentally validated data. The networks were modeled into an XGBoost machine learning system where expression information of the network components was found capable to quantitatively explain the miRNAs formation levels and their profiles. The models were developed for 1,204 human miRNAs whose accurate expression level could be detected directly from the RNA-seq data alone without any need of doing separate miRNA profiling experiments like miRNA-seq or arrays. A first of its kind, miRbiom performed consistently well with high average accuracy (91%) when tested across a large number of experimentally established data from several conditions. It has been implemented as an interactive open access web-server where besides finding the profiles of miRNAs, their downstream functional analysis can also be done. miRbiom will help to get an accurate prediction of human miRNAs profiles in the absence of profiling experiments and will be an asset for regulatory research areas. The study also shows the importance of having RBP interaction information in better understanding the miRNAs and their functional projectiles where it also lays the foundation of such studies and software in future.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.22.165225", + "rel_abs": "Despite limited genomic diversity, SARS-CoV-2 has shown a wide range of clinical manifestations in different patient populations. The mechanisms behind these host differences are still unclear. Here, we examined host response gene expression across infection status, viral load, age, and sex among shotgun RNA-sequencing profiles of nasopharyngeal swabs from 430 individuals with PCR-confirmed SARS-CoV-2 and 54 negative controls. SARS-CoV-2 induced a strong antiviral response with upregulation of antiviral factors such as OAS1-3 and IFIT1-3, and Th1 chemokines CXCL9/10/11, as well as a reduction in transcription of ribosomal proteins. SARS-CoV-2 culture in human airway epithelial cultures replicated the in vivo antiviral host response. Patient-matched longitudinal specimens (mean elapsed time = 6.3 days) demonstrated reduction in interferon-induced transcription, recovery of transcription of ribosomal proteins, and initiation of wound healing and humoral immune responses. Expression of interferon-responsive genes, including ACE2, increased as a function of viral load, while transcripts for B cell-specific proteins and neutrophil chemokines were elevated in patients with lower viral load. Older individuals had reduced expression of Th1 chemokines CXCL9/10/11 and their cognate receptor, CXCR3, as well as CD8A and granzyme B, suggesting deficiencies in trafficking and/or function of cytotoxic T cells and natural killer (NK) cells. Relative to females, males had reduced B and NK cell-specific transcripts and an increase in inhibitors of NF-{kappa}B signaling, possibly inappropriately throttling antiviral responses. Collectively, our data demonstrate that host responses to SARS-CoV-2 are dependent on viral load and infection time course, with observed differences due to age and sex that may contribute to disease severity.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Upendra Kumar Pradhan", - "author_inst": "CSIR-Institute of Himalayan Bioresource Technology, Palampur-176061 (Himachal Pradesh), India" + "author_name": "Nicole A.P. Lieberman", + "author_inst": "University of Washington" }, { - "author_name": "Nitesh Kumar Sharma", - "author_inst": "CSIR-Institute of Himalayan Bioresource Technology, Palampur-176061 (Himachal Pradesh), India" + "author_name": "Vikas Peddu", + "author_inst": "University of Washington" }, { - "author_name": "Prakash Kumar", - "author_inst": "CSIR-Institute of Himalayan Bioresource Technology, Palampur-176061 (Himachal Pradesh), India" + "author_name": "Hong Xie", + "author_inst": "University of Washington" }, { - "author_name": "Ashwani Kumar", - "author_inst": "CSIR-Institute of Himalayan Bioresource Technology, Palampur-176061 (Himachal Pradesh), India" + "author_name": "Lasata Shrestha", + "author_inst": "University of Washington" + }, + { + "author_name": "Meeili Huang", + "author_inst": "University of Washington" + }, + { + "author_name": "Megan C Mears", + "author_inst": "University of Texas Medical Branch" + }, + { + "author_name": "Maria N Cajimat", + "author_inst": "University of Texas Medical Branch" + }, + { + "author_name": "Dennis A Bente", + "author_inst": "University of Texas Medical Branch" + }, + { + "author_name": "Pei-Yong Shi", + "author_inst": "University of Texas Medical Branch" + }, + { + "author_name": "Francesca Bovier", + "author_inst": "Columbia University Medical Center" + }, + { + "author_name": "Pavitra Roychoudhury", + "author_inst": "University of Washington" + }, + { + "author_name": "Keith R. Jerome", + "author_inst": "University of WA/Fred Hutchinson Cancer Research Center" + }, + { + "author_name": "Anne Moscona", + "author_inst": "Columbia University Medical Center" }, { - "author_name": "Sagar Gupta", - "author_inst": "CSIR-Institute of Himalayan Bioresource Technology, Palampur-176061 (Himachal Pradesh), India" + "author_name": "Matteo Porotto", + "author_inst": "Columbia University Medical Center" }, { - "author_name": "Ravi Shankar", - "author_inst": "CSIR-Institute of Himalayan Bioresource Technology, Palampur-176061 (Himachal Pradesh), India" + "author_name": "Alexander L. Greninger", + "author_inst": "University of Washington" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "new results", - "category": "bioinformatics" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.06.21.162396", @@ -1333136,27 +1333152,27 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2020.06.20.163006", - "rel_title": "Transcriptional response of signalling pathways to SARS-CoV-2 infection in normal human bronchial epithelial cells", + "rel_doi": "10.1101/2020.06.20.160499", + "rel_title": "Analysis of SARS-CoV-2 specific T-cell receptors in ImmuneCode reveals cross-reactivity to immunodominant Influenza M1 epitope", "rel_date": "2020-06-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.20.163006", - "rel_abs": "SARS-CoV-2 virus, the pathogen that causes Covid-19 disease, emerged in Wuhan region in China in 2019, infected more than 4M people and is responsible for death of at least 300K patients globally as of May 2020. Identification of the cellular response mechanisms to viral infection by SARS-CoV-2 may shed light on progress of the disease, indicate potential drug targets, and make design of new test methods possible.\n\nIn this study, we analysed transcriptomic response of normal human bronchial epithelial cells (NHBE) to SARS-CoV-2 infection and compared the response to H1N1 infection. Comparison of transcriptome of NHBE cells 24 hours after mock-infection and SARS-CoV-2 infection demonstrated that most genes that respond to infection were upregulated (320 genes) rather than being downregulated (115 genes).While upregulated genes were enriched in signalling pathways related to virus response, downregulated genes are related to kidney development. We mapped the upregulated genes on KEGG pathways to identify the mechanisms that mediate the response. We identified canonical NF{kappa}B, TNF and IL-17 pathways to be significantly upregulated and to converge to NF{kappa}B pathway via positive feedback loops. Although virus entry protein ACE2 has low expression in NHBE cells, pathogen response pathways are strongly activated within 24 hours of infection. Our results also indicate that immune response system is activated at the early stage of the infection and orchestrated by a crosstalk of signalling pathways. Finally, we compared transcriptomic SARS-CoV-2 response to H1N1 response in NHBE cells to elucidate the virus specificity of the response and virus specific extracellular proteins expressed by NHBE cells.", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.20.160499", + "rel_abs": "Adaptive Biotechnologies and Microsoft have recently partnered to release ImmuneCode, a database containing SARS-CoV-2 specific T-cell receptors derived through MIRA, a T-cell receptor (TCR) sequencing based sequencing approach to identify antigen-specific TCRs. Herein, we query the extent of cross reactivity between these derived SARS-CoV-2 specific TCRs and other known antigens present in McPas-TCR, a manually curated catalogue of pathology-associated TCRs. We reveal cross reactivity between SARS-CoV-2 specific TCRs and the immunodominant Influenza GILGFVFTL M1 epitope, suggesting the importance of further work in characterizing the implications of prior Influenza exposure or co-exposure to the pathology of SARS-CoV-2 illness.", "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Enes Ak", - "author_inst": "Gebze Technical University" + "author_name": "John-William Sidhom", + "author_inst": "Johns Hopkins University School of Medicine" }, { - "author_name": "Pinar Pir", - "author_inst": "Gebze Technical University" + "author_name": "Alexander S Baras", + "author_inst": "Johns Hopkins University School of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "bioinformatics" + "category": "immunology" }, { "rel_doi": "10.1101/2020.06.20.162560", @@ -1334538,33 +1334554,65 @@ "category": "emergency medicine" }, { - "rel_doi": "10.1101/2020.06.18.20134460", - "rel_title": "Simulation of COVID-19 Incubation Period and the Effect of Probability Distribution Functionon Model Training Using MIMANSA", + "rel_doi": "10.1101/2020.06.17.20133983", + "rel_title": "Bayesian nowcasting with adjustment for delayed and incomplete reporting to estimate COVID-19 infections in the United States", "rel_date": "2020-06-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.18.20134460", - "rel_abs": "Coronavirus disease 2019 (COVID-19) has infected people all over the world. While scientists are busy finding a vaccine and medicine, it becomes difficult to control the spread and manage patients. Mathematical models help one get a better feel for the challenges in patient management. With this in mind, our team developed a model called Multilevel Integrated Model with a Novel Systems Approach (MIMANSA) Welling et. al (2020). MIMANSA is a multi-parametric model. One of the challenges in the design of MIMANSA was to simulate the incubation period of coronavirus. The incubation period decides when virus-infected patients would show symptoms. The probability distribution function (PDF), when applied to the number of virus-infected cases, gives a good representation of the process of the incubation period. The probability distribution functions can take various forms. In this paper, we explore a variety of PDFs and their impact on parameter estimation in the MIMANSA model. For our experiments, we used Weibull, Gaussian, uniform, and Gamma distribution. To ensure a fair comparison of Weibull, Gaussian, and Gamma distribution, we matched the peak value of the distribution. Our results show that the Weibull distribution with shape 7.7 and scale 7 for 14 days gives a better training model and predictions.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.17.20133983", + "rel_abs": "Reported COVID-19 cases and deaths provide a delayed and incomplete picture of SARS-CoV-2 infections in the United States (US). Accurate estimates of both the timing and magnitude of infections are needed to characterize viral transmission dynamics and better understand COVID- 19 disease burden. We estimated time trends in SARS-CoV-2 transmission and other COVID-19 outcomes for every county in the US, from the first reported COVID-19 case in January 13, 2020 through January 1, 2021. To do so we employed a Bayesian modeling approach that explicitly accounts for reporting delays and variation in case ascertainment, and generates daily estimates of incident SARS-CoV-2 infections on the basis of reported COVID-19 cases and deaths. The model is freely available as the covidestim R package. Nationally, we estimated there had been 49 million symptomatic COVID-19 cases and 400,718 COVID-19 deaths by the end of 2020, and that 27% of the US population had been infected. The results also demonstrate wide county-level variability in the timing and magnitude of incidence, with local epidemiological trends differing substantially from state or regional averages, leading to large differences in the estimated proportion of the population infected by the end of 2020. Our estimates of true COVID-19 related deaths are consistent with independent estimates of excess mortality, and our estimated trends in cumulative incidence of SARS-CoV-2 infection are consistent with trends in seroprevalence estimates from available antibody testing studies. Reconstructing the underlying incidence of SARS-CoV-2 infections across US counties allows for a more granular understanding of disease trends and the potential impact of epidemiological drivers.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Abhilasha P. Patel", - "author_inst": "Applied Research Group, Pi Innovate, Pune, India" + "author_name": "Melanie H Chitwood", + "author_inst": "Yale School of Public Health" }, { - "author_name": "Arpita A. Welling", - "author_inst": "Applied Research Group, Pi Innovate, Pune, India" + "author_name": "Marcus Russi", + "author_inst": "Yale School of Public Health" }, { - "author_name": "Vinay G. Vaidya", - "author_inst": "Pi Innovate" + "author_name": "Kenneth Gunasekera", + "author_inst": "Yale School of Public Health" }, { - "author_name": "Padmaj S. Kulkarni", - "author_inst": "Dept. of Oncology, Deenanath Mangeshkar Hospital, Pune, India" + "author_name": "Joshua Havumaki", + "author_inst": "Yale School of Public Health" + }, + { + "author_name": "Fayette Klaassen", + "author_inst": "Harvard TH Chan School of Public Health" + }, + { + "author_name": "Virginia E. Pitzer", + "author_inst": "Yale School of Public Health" + }, + { + "author_name": "Joshua A Salomon", + "author_inst": "Stanford University" + }, + { + "author_name": "Nicole Swartwood", + "author_inst": "Harvard T.H. Chan School of Public Health" + }, + { + "author_name": "Joshua L Warren", + "author_inst": "Yale School of Public Health" + }, + { + "author_name": "Daniel Weinberger", + "author_inst": "Yale School of Public Health" + }, + { + "author_name": "Ted Cohen", + "author_inst": "Yale School of Public Health" + }, + { + "author_name": "Nicolas A Menzies", + "author_inst": "Harvard T.H. Chan School of Public Health" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1336804,63 +1336852,59 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.06.19.161000", - "rel_title": "Proteotyping SARS-CoV-2 virus from nasopharyngeal swabs: a proof-of-concept focused on a 3 min mass spectrometry window", + "rel_doi": "10.1101/2020.06.19.160879", + "rel_title": "Cross-neutralization activity against SARS-CoV-2 is present in currently available intravenous immunoglobulins", "rel_date": "2020-06-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.19.161000", - "rel_abs": "Rapid but yet sensitive, specific and high-throughput detection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in clinical samples is key to diagnose infected people and to better control the spread of the virus. Alternative methodologies to PCR and immunodiagnostic that would not require specific reagents are worth to investigate not only for fighting the COVID-19 pandemic, but also to detect other emergent pathogenic threats. Here, we propose the use of tandem mass spectrometry to detect SARS-CoV-2 marker peptides in nasopharyngeal swabs. We documented that the signal from the microbiota present in such samples is low and can be overlooked when interpreting shotgun proteomic data acquired on a restricted window of the peptidome landscape. Simili nasopharyngeal swabs spiked with different quantities of purified SARS-CoV-2 viral material were used to develop a nanoLC-MS/MS acquisition method, which was then successfully applied on COVID-19 clinical samples. We argue that peptides ADETQALPQR and GFYAQGSR from the nucleocapsid protein are of utmost interest as their signal is intense and their elution can be obtained within a 3 min window in the tested conditions. These results pave the way for the development of time-efficient viral diagnostic tests based on mass spectrometry.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.19.160879", + "rel_abs": "BackgroundThere is a crucial need for effective therapies that are immediately available to counteract COVID-19 disease. Recently, ELISA binding cross-reactivity against components of human epidemic coronaviruses with currently available intravenous immunoglobulins (IVIG) Gamunex-C and Flebogamma DIF (5% and 10%) have been reported. In this study, the same products were tested for neutralization activity against SARS-CoV-2, SARS-CoV and MERS-CoV and their potential as an antiviral therapy.\n\nMethodsThe neutralization capacity of six selected lots of IVIG was assessed against SARS-CoV-2 (two different isolates), SARS-CoV and MERS-CoV in cell cultures. Infectivity neutralization was measured by determining the percent reduction in plaque-forming units (PFU) and by cytopathic effects for two IVIG lots in one of the SARS-CoV-2 isolates. Neutralization was quantified using the plaque reduction neutralization test 50 (PRNT50) in the PFU assay and the half maximal inhibitory concentration (IC50) in the cytopathic/cytotoxic method (calculated as the minus log10 dilution which reduced the viral titer by 50%).\n\nResultsAll IVIG preparations showed neutralization of both SARS-CoV-2 isolates, ranging from 79 to 89.5% with PRNT50 titers from 4.5 to >5 for the PFU method and ranging from 47.0%-64.7% with an IC50 ~1 for the cytopathic method. All IVIG lots produced neutralization of SARS-CoV ranging from 39.5 to 55.1 % and PRNT50 values ranging from 2.0 to 3.3. No IVIG preparation showed significant neutralizing activity against MERS-CoV.\n\nConclusionIn cell culture neutralization assays, the tested IVIG products contain antibodies with significant cross-neutralization capacity against SARS-CoV-2 and SARS-CoV. However, no neutralization capacity was demonstrated against MERS-CoV. These preparations are currently available and may be immediately useful for COVID-19 management.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Duarte Gouveia", - "author_inst": "University Paris Saclay, CEA, INRAE" + "author_name": "Jos\u00e9 Mar\u00eda D\u00edez", + "author_inst": "Immunotherapies Unit, Bioscience Research and Development, Grifols, Barcelona, Spain" }, { - "author_name": "Guylaine Miotello", - "author_inst": "University Paris Saclay, CEA, INRAE" + "author_name": "Carolina Romero", + "author_inst": "Immunotherapies Unit, Bioscience Research and Development, Grifols, Barcelona, Spain" }, { - "author_name": "Fabrice Gallais", - "author_inst": "University Paris Saclay, CEA, INRAE" + "author_name": "J\u00falia Vergara Alert", + "author_inst": "IRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Campus de la Universitat Aut\u00f2noma de Barcelona (UAB), Bellaterra, Barcelona, Spain" }, { - "author_name": "Jean-Charles Gaillard", - "author_inst": "University Paris-Saclay, CEA, INRAE" + "author_name": "Melissa Bell\u00f3 P\u00e9rez", + "author_inst": "Laboratorio Coronavirus. Departamento de Biolog\u00eda Molecular y Celular, CNB-CSIC, Madrid. Spain" }, { - "author_name": "Stephanie Debroas", - "author_inst": "University Paris-Saclay, CEA, INRAE" - }, - { - "author_name": "Laurent Bellanger", - "author_inst": "University Paris-Saclay, CEA, INRAE" + "author_name": "Jordi Rodon", + "author_inst": "IRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Campus de la Universitat Aut\u00f2noma de Barcelona (UAB), Bellaterra, Barcelona, Spain" }, { - "author_name": "Jean-Philippe Lavigne", - "author_inst": "VBMI, INSERM U1047, Universite de Montpellier, Service de Microbiologie et Hygiene Hospitaliere, CHU Nimes" + "author_name": "Jos\u00e9 Manuel Honrubia", + "author_inst": "Laboratorio Coronavirus. Departamento de Biolog\u00eda Molecular y Celular, CNB-CSIC, Madrid. Spain" }, { - "author_name": "Albert Sotto", - "author_inst": "VBMI, INSERM U1047, Universite de Montpellier, Service des Maladies Infectieuses et Tropicales, CHU Nimes" + "author_name": "Joaquim Segal\u00e9s", + "author_inst": "Departament de Sanitat i Anatomia Animals, Universitat Aut\u00f2noma de Barcelona (UAB); Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Campus de la Universi" }, { - "author_name": "Lucia Grenga", - "author_inst": "University Paris-Saclay, CEA, INRAE" + "author_name": "Isabel Sola", + "author_inst": "Laboratorio Coronavirus. Departamento de Biolog\u00eda Molecular y Celular, CNB-CSIC, Madrid. Spain" }, { - "author_name": "Olivier Pible", - "author_inst": "University Paris-Saclay, CEA, INRAE" + "author_name": "Luis Enjuanes", + "author_inst": "Laboratorio Coronavirus. Departamento de Biolog\u00eda Molecular y Celular, CNB-CSIC, Madrid. Spain" }, { - "author_name": "Jean Armengaud", - "author_inst": "University Paris-Saclay, CEA, INRAE" + "author_name": "Rodrigo Gajardo", + "author_inst": "Immunotherapies Unit, Bioscience Research and Development, Grifols, Barcelona, Spain" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "immunology" }, { "rel_doi": "10.1101/2020.06.19.161687", @@ -1338330,29 +1338374,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.17.20133355", - "rel_title": "Stay-at-Home Orders, African American Population, Poverty and State-level Covid-19 Infections: Are there associations?", + "rel_doi": "10.1101/2020.06.16.20132563", + "rel_title": "A Counterfactual Graphical Model Reveals Economic and Sociodemographic Variables as Key Determinants of Country-Wise COVID-19 Burden", "rel_date": "2020-06-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.17.20133355", - "rel_abs": "ImportanceTo cope with the continuing COVID-19 pandemic, state and local health officials need information on the effectiveness of policies aimed at curbing contagion, as well as area-specific socio-demographic characteristics that can portend vulnerability to the disease.\n\nObjectiveTo investigate whether state-imposed stay-at-home orders, African American population in the state, state poverty and other state socio-demographic characteristics, were associated with the state-level incidence of COVID-19 infection.\n\nDesign, Setting, ParticipantsState-level, aggregated, publicly available data on positive COVID-19 cases and tests were used. The period considered was March 1st-May 4th. All U.S. states except Washington were included. Outcomes of interest were daily cumulative and daily incremental COVID-19 infection rates. Outcomes were log-transformed. Log-linear regression models with a quadratic time-trend and random intercepts for states were estimated. Covariates included log-transformed test-rates, a binary indicator for stay-at-home, percentage of African American, poverty, percentage elderly, state population and prevalence of selected comorbidities. Binary fixed effects for date each state first started reporting test data were included.\n\nResultsStay-at-home orders were associated with decreases in cumulative ({beta}:-1.23; T-stat: - 6.84) and daily ({beta}:-0.46; T-stat: -2.56) infection-rates. Predictive analyses indicated that expected cumulative infection rates would be 3 times higher and expected daily incremental rates about 60% higher in absence of stay-at-home orders. Higher African American population was associated with higher cumulative ({beta}: 0.08; T-stat: 4.01) and daily ({beta}: 0.06; T-stat: 3.50) rates. State poverty rates had mixed results and were not robust to model specifications. There was strong evidence of a quadratic daily trend for cumulative and daily rates. Results were largely robust to alternate specifications.\n\nConclusionsWe find evidence that stay-at-home orders, which were widely supported by public-health experts, helped to substantially curb COVID-19 infection-rates. As we move to a phased re-opening, continued precautions advised by public-health experts should be adhered to. Also, a larger African American population is strongly associated with incidence of COVID-19 infection. Policies and resources to help mitigate African American vulnerability to COVID-19 is an urgent public health and social justice issue, especially since the ongoing mass protests against police brutality may further exacerbate COVID-19 contagion in this community.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSDid the stay-at-home orders, African American population and other socio demographic factors across states have any associations with COVID-19 infection rates across states?\n\nFindingsMultivariate log-linear regression models using daily state level data from March-May found evidence that when stay-at-home orders were implemented, they helped reduce state COVID-19 cumulative and daily infection rates substantially. Further, we found that states with larger African-American population had higher COVID-19 infection rates.\n\nMeaningResults suggest that state-level stay-at-home orders helped reduce COVID-19 infection rates substantially, and also that African American populations may be especially vulnerable to COVID-19 infection.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.16.20132563", + "rel_abs": "ImportanceInsights into the country-wise differences in COVID-19 burden can impact the policies being developed to control disease spread.\n\nObjectivePresent study evaluated the possible socio-economic and health related factors (and their temporal consistency) determining the disease burden of COVID-19.\n\nDesignA retrospective analysis for identifying associations of COVID-19 burden.\n\nSettingData on COVID-19 statistics (number of cases, tests and deaths per million) was extracted from the website https://www.worldometers.info/coronavirus/ on 10th April and 12th May. Variables obtained to estimate the possible determinants for COVID-19 burden included economic-gross domestic product; socio-demographic-Sustainable Development Goals, SDGs indicators related to health systems, percentage Chinese diaspora; and COVID-19 trajectory-date of first case in each country, days between first reported case and 10th April, days between 100th and 1000th case, and government response stringency index (GRSI).\n\nMain outcomes and MeasuresCOVID-19 burden was modeled using economic and socio-demographic determinants. Consistency of inferences for two time points at three levels of increasing statistical rigor using (i) Spearman correlations, (ii) Bayesian probabilistic graphical model, and (iii) counterfactual impact was evaluated.\n\nResultsCountries economy (reflected by GDP), mainly through the testing rates, was the major and temporally consistent determinant of COVID-19 burden in the model. Reproduction number of COVID-19 was lower where mortality due to water, sanitation, and hygiene (WaSH) was higher, thus strengthening the hygiene hypothesis. There was no association between vaccination status or tuberculosis incidence and COVID burden, refuting the claims over BCG vaccination as a possible factor against COVID-19 trajectory.\n\nConclusion and RelevanceCountries economy, through testing power, was the major determinant of COVID-19 burden. There was weak evidence for hygiene hypothesis as a protective factor against COVID-19.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Bisakha P Sen", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Tavpritesh Sethi", + "author_inst": "IIIT-Delhi" }, { - "author_name": "Sangeetha Padalabalanarayanan", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Saurabh Kedia", + "author_inst": "All India Institute of Medical Sciences" }, { - "author_name": "Vidya Sagar Hanumanthu", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Raghav Awasthi", + "author_inst": "IIIT D" + }, + { + "author_name": "Rakesh Lodha", + "author_inst": "All India Institute of Medical Sciences" + }, + { + "author_name": "Vineet Ahuja", + "author_inst": "All India Institute of Medical Sciences" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1339840,35 +1339892,59 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.17.20133629", - "rel_title": "Introduction to and spread of COVID-19 in care homes in Norfolk, UK", + "rel_doi": "10.1101/2020.06.16.20133256", + "rel_title": "Exosomal microRNAs Drive Thrombosis in COVID-19", "rel_date": "2020-06-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.17.20133629", - "rel_abs": "BACKGROUNDResidential care homes for the elderly have been important settings for transmission of the SARS-CoV-2 virus that causes COVID-19 disease. METHODS: We undertook a secondary analysis of a dataset about 248 care homes in the county of Norfolk, eastern England. The dataset recorded categories of staff (nurses, care workers and non-care workers), their status (available, absent due to leave or sickness and extra staff needed to address the coronavirus pandemic) in the period 6 April -6 May 2020. Counts of residents (if any) at each care home with COVID-19 were also available, as well as descriptions of access by the home to personal protection equipment (PPE: gloves, masks, eye protection, aprons and Sanitiser). PPE access was categorised as (most to least) green, amber or red. We undertook two stage modelling, first for any detection of COVID-19 in the homes, and a second model to relate any increases in case counts after introduction to staffing or PPE levels. RESULTS: We found that the counts of non-care workers had strongest relationships (and only link significant at p < 0.05) to any introduction of SARS-CoV-2 to the homes. After a home had at least one detected case, higher staff levels and more severe PPE shortages were most linked to higher case counts (p < 0.05) during the monitoring period. CONCLUSION: Better managing aspects of staff interaction with residents and some working practices should help reduce ingression to and spread of COVID-19 within residential homes for the elderly.\n\nTHUMBNAIL SKETCH O_TEXTBOXWhat is already known on this subject?[tpltrtarr] Close to 40% of all UK with COVID-19 deaths in early May of 2020 were among care home residents.\n[tpltrtarr]That this care sector was underfunded and under-equipped to prevent disease introduction and spread is recognised but the mechanisms of how disease entered or spread have not been quantified.\n\n\nWhat this study adds?[tpltrtarr] Detection of any COVID-19 cases in homes was directly linked to the counts of staff members who were not directly involved in personal care.\n[tpltrtarr]Subsequent disease spread was directly most strongly linked to lack of facemasks and eye protection, somewhat less to total counts of care workers employed.\n[tpltrtarr]The findings demonstrate an inverse strong link between available PPE and case counts in care homes after disease became present.\n\n\nC_TEXTBOX", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.16.20133256", + "rel_abs": "Thrombotic and thromboembolic complications have been shown to play a critical role in the clinical outcome of COVID-19. Emerging evidence has shown that exosomal miRNAs are functionally involved in a number of physiologic and pathologic processes. However, neither exosomes nor miRNAs have been hitherto investigated in COVID-19. To test the hypothesis that exosomal miRNAs are a key determinant of thrombosis in COVID-19, we enrolled patients positive for COVID-19. Circulating exosomes were isolated from equal amounts of serum and levels of exosomal miRNAs were quantified. We divided our population in two groups based on the serum level of D-dimer on admission. Strikingly, we found that exosomal miR-424 was significantly upregulated whereas exosomal miR-103a, miR-145, and miR-885 were significantly downregulated in patients in the high D-dimer group compared to patients in the low D-Dimer group (p<0.0001).", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Julii Suzanne Brainard", - "author_inst": "University of East Anglia" + "author_name": "Jessica Gambardella", + "author_inst": "AECOM" }, { - "author_name": "Steven Rushton", - "author_inst": "Newcastle University" + "author_name": "Celestino Sardu", + "author_inst": "University of Campania \"Luigi Vanvitelli\"" }, { - "author_name": "Tim Winters", - "author_inst": "Norfolk County Council" + "author_name": "Marco Bruno Morelli", + "author_inst": "AECOM" }, { - "author_name": "Paul R Hunter", - "author_inst": "University of East Anglia" + "author_name": "Vincenzo Messina", + "author_inst": "Naples Univ" + }, + { + "author_name": "Vanessa Castellanos", + "author_inst": "AECOM" + }, + { + "author_name": "Raffaele Marfella", + "author_inst": "Naples Univ" + }, + { + "author_name": "Paolo Maggi", + "author_inst": "Naples Univ" + }, + { + "author_name": "Giuseppe Paolisso", + "author_inst": "Naples Univ." + }, + { + "author_name": "Xujun Wang", + "author_inst": "AECOM" + }, + { + "author_name": "Gaetano Santulli", + "author_inst": "Albert Einstein College of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2020.06.17.20133611", @@ -1341750,27 +1341826,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.06.18.156810", - "rel_title": "Variant analysis of SARS-CoV-2 strains in Middle Eastern countries", - "rel_date": "2020-06-18", + "rel_doi": "10.1101/2020.06.15.153239", + "rel_title": "Mutation density changes in SARS-CoV-2 are related to the pandemic stage but to a lesser extent in the dominant strain with mutations in spike and RdRp", + "rel_date": "2020-06-17", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.18.156810", - "rel_abs": "BackgroundSARS-CoV-2 is diverging from the initial Wuhan serotype, and different variants of the virus are reported. Mapping the variant strains and studying their pattern of evolution will provide better insights into the pandemic spread\n\nMethodsData on different SARS-CoV2 for WHO EMRO countries were obtained from the Chinese National Genomics Data Center (NGDC), Genbank and the Global Initiative on Sharing All Influenza Data (GISAID). Multiple sequence alignments (MSA) was performed to study the evolutionary relationship between the genomes. Variant calling, genome and variant alignment were performed to track the strains in each country. Evolutionary and phylogenetic analysis is used to explore the evolutionary hypothesis.\n\nFindingsOf the total 50 samples, 4 samples did not contain any variants. Variant calling identified 379 variants. Earliest strains are found in Iranian samples. Variant alignment indicates Iran samples have a low variant frequency. Saudi Arabia has formed an outgroup. Saudi Arabia, Qatar and Kuwait were the most evolved genomes and are the countries with the highest number of cases per million.\n\nInterpretationIran was exposed to the virus earlier than other countries in the Eastern Mediterranean Region.\n\nFundingNone", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.15.153239", + "rel_abs": "Since its emergence in Wuhan, China in late 2019, the origin and evolution of SARS-CoV-2 have been among the most debated issues related to COVID-19. Throughout its spread around the world, the viral genome continued acquiring new mutations and some of them became widespread. Among them, 14408 C>T and 23403 A>G mutations in RdRp and S, respectively, became dominant in Europe and the US, which led to debates regarding their effects on the mutability and transmissibility of the virus. In this study, we aimed to investigate possible differences between time-dependent variation of mutation densities (MDe) of viral strains that carry these two mutations and those that do not. Our analyses at the genome and gene level led to two important findings: First, time-dependent changes in the average MDe of circulating SARS-CoV-2 genomes showed different characteristics before and after the beginning of April, when daily new case numbers started levelling off. Second, this pattern was much delayed or even non-existent for the \"mutant\" (MT) strain that harbored both 14408 C>T and 23403 A>G mutations. Although these differences were not limited to a few hotspots, it is intriguing that the MDe increase is most evident in two critical genes, S and Orf1ab, which are also the genes that harbor the defining mutations of the MT genotype. The nature of these unexpected relationships warrant further research.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Khalid M Bindayna", - "author_inst": "Arabian Gulf University" + "author_name": "Do\u011fa Eskier", + "author_inst": "Izmir International Biomedicine and Genome Institute (iBG-Izmir)" }, { - "author_name": "Shane Crinion", - "author_inst": "National University of Ireland Galway" + "author_name": "Asl\u0131 Suner", + "author_inst": "Department of Biostatistics and Medical Informatics, Faculty of Medicine, Ege University" + }, + { + "author_name": "G\u00f6khan Karak\u016blah", + "author_inst": "Izmir Biomedicine and Genome Center (IBG)" + }, + { + "author_name": "Yavuz Oktay", + "author_inst": "Izmir Biomedicine and Genome Center (IBG)" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "genetics" }, { "rel_doi": "10.1101/2020.06.16.154559", @@ -1343388,43 +1343472,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.15.20132217", - "rel_title": "Identifiability of infection model parameters early in an epidemic", + "rel_doi": "10.1101/2020.06.16.151282", + "rel_title": "Time-series analyses of directional sequence changes in SARS-CoV-2 genomes and an efficient search method for advantageous mutations for growth in human cells", "rel_date": "2020-06-17", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.15.20132217", - "rel_abs": "It is known that the parameters in the deterministic and stochastic SEIR epidemic models are structurally identifiable. For example, from knowledge of the infected population time series I(t) during the entire epidemic, the parameters can be successfully estimated. In this article we observe that estimation will fail in practice if only infected case data during the early part of the epidemic (pre-peak) is available. This fact can be explained using a long-known phenomenon called dynamical compensation. We use this concept to derive an unidentifiability manifold in the parameter space of SEIR that consists of parameters indistin-guishable to I(t) early in the epidemic. Thus, identifiability depends on the extent of the system trajectory that is available for observation. Although the existence of the unidentifiability manifold obstructs the ability to exactly determine the parameters, we suggest that it may be useful for uncertainty quantification purposes. A variant of SEIR recently proposed for COVID-19 modeling is also analyzed, and an analogous unidentifiability surface is derived.", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.16.151282", + "rel_abs": "We first conducted time-series analysis of mono- and dinucleotide composition for over 10,000 SARS-CoV-2 genomes, as well as over 1500 Zaire ebolavirus genomes, and found clear time-series changes in the compositions on a monthly basis, which should reflect viral adaptations for efficient growth in human cells. We next developed a sequence alignment free method that extensively searches for advantageous mutations and rank them in an increase level for their intrapopulation frequency. Time-series analysis of occurrences of oligonucleotides of diverse lengths for SARS-CoV-2 genomes revealed seven distinctive mutations that rapidly expanded their intrapopulation frequency and are thought to be candidates of advantageous mutations for the efficient growth in human cells.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Timothy Sauer", - "author_inst": "George Mason University" - }, - { - "author_name": "Tyrus Berry", - "author_inst": "George Mason University" - }, - { - "author_name": "Donald Ebeigbe", - "author_inst": "Pennsylvania State University" - }, - { - "author_name": "Michael M. Norton", - "author_inst": "Pennsylvania State University" + "author_name": "Kennosuke Wada", + "author_inst": "Nagahama Institute of Bio-Science and Technology" }, { - "author_name": "Andrew Whalen", - "author_inst": "Harvard Medical School" + "author_name": "Yoshiko Wada", + "author_inst": "Nagahama Institute of Bio-Science and Technology" }, { - "author_name": "Steven J Schiff", - "author_inst": "Penn State University" + "author_name": "Toshimichi Ikemura", + "author_inst": "Nagahama Institute of Bio-Science and Technology" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_by", + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.06.16.151555", @@ -1345222,29 +1345294,33 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.06.13.20130153", - "rel_title": "Assessment of impact of COVID-19 outbreak & lockdown on mental health status & its associated risk and protective factors in adult Indian population", + "rel_doi": "10.1101/2020.06.13.20130054", + "rel_title": "What triggers online help-seeking retransmission during the COVID-19 period? Empirical evidence from Chinese social media", "rel_date": "2020-06-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.13.20130153", - "rel_abs": "BackgroundThe novel Corona virus has derailed the entire world and various steps have been taken by the health authorities to tackle this pandemic. Nationwide lockdown has been imposed to control the spread of COVID-19 outbreak in India, which could have psychological impact on the population.\n\nAimOur study aims to study the effect of the COVID-19 outbreak & subsequent lockdown on mental health status of adult Indian population along with identifying the high-risk groups.\n\nMethodologyAn online survey was conducted during 3rd phase of lockdown gathering details about sociodemographic variables, practice of precautionary measures, awareness and concerns regarding COVID-19 and mental health status of the participants through DASS21 questionnaire from 873 adults.\n\nResultsThe prevalence of depression, anxiety and stress were 18.56%, 25.66%, and 21.99% respectively including higher number of participants with mild depression (15.1%) and stress (14.5%) and moderate anxiety (16.3%). Female gender, age <25 years, unemployment, self-business, employed in private sector, lack of formal education, larger household size, parenthood (>2 kids) were associated with increased likelihood of negative mental health. Confidence in physicians ability to diagnose COVID-19 infection, decreased self-perceived likelihood of contracting COVID-19, lesser frequency of checking for information on COVID-19 and satisfaction of information received were protective against negative mental health.\n\nConclusionThis landmark study identified the protective and risk factors of mental health during COVID-19 pandemic, to help authorities and mental health workers to strategize and deliver interventional methods to maintain psychosocial wellbeing of the population.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.13.20130054", + "rel_abs": "The past nine months witnessed COVID-19s fast-spreading at the global level. Limited by medical resources shortage and uneven facilities distribution, online help-seeking becomes an essential approach to cope with public health emergencies for many ordinaries. This study explores the driving forces behind the retransmission of online help-seeking posts. We built an analytical framework that emphasized content characteristics, including information completeness, proximity, support seeking type, disease severity, and emotion of help-seeking messages. A quantitative content analysis was conducted with a probability sample consisting of 727 posts. The results illustrate the importance of individual information completeness, high proximity, instrumental support seeking. This study also demonstrates slight inconformity with the severity principle but stresses the power of anger in help-seeking messages dissemination. As one of the first online help-seeking diffusion analyses in the COVID-19 period, our research provides a reference for constructing compelling and effective help-seeking posts during a particular period. It also reveals further possibilities for harnessing social medias power to promote reciprocal and cooperative actions as a response to this deepening global concern.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Jayakumar Saikarthik", - "author_inst": "Majmaah University" + "author_name": "Chen Luo", + "author_inst": "School of Journalism and Communication, Tsinghua University" }, { - "author_name": "Ilango Saraswathi", - "author_inst": "Madha Medical College and Research Centre" + "author_name": "Yuru Li", + "author_inst": "Center for Media, Communication and Information Research, University of Bremen" }, { - "author_name": "Thirusangu Siva", - "author_inst": "Sri Ramachandra Medical College and Research Centre" + "author_name": "Anfan Chen", + "author_inst": "School of Humanity and Social Science, University of Science and Technology of China" + }, + { + "author_name": "Yulong Tang", + "author_inst": "Institute of Communication Studies, Communication University of China" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1346284,47 +1346360,55 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2020.06.14.20130724", - "rel_title": "The inevitability of Covid-19 related distress among healthcare workers: findings from a low caseload country under lockdown", + "rel_doi": "10.1101/2020.06.14.20130898", + "rel_title": "Covid-19 in Chile. The experience of a Regional reference Center. Preliminary report", "rel_date": "2020-06-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.14.20130724", - "rel_abs": "ObjectivesTo characterize psychological distress and factors associated with distress in healthcare practitioners working during a stringent lockdown in a country (Jordan) with one of the lowest incidence rates of Covid-19 globally.\n\nMethodsA cross-sectional online survey sent to physicians, nurses and technicians, and pharmacists working in various hospitals and community pharmacies. Demographic, professional and psychological characteristics (distress using Kessler-6 questionnaire, anxiety, depression, burnout, sleep issues, exhaustion) were measured as were potential sources of fear. Descriptive and multivariable statistics were performed using level of distress as the key outcome.\n\nResultsWe surveyed 1,006 practitioners (55.3% females). Approximately 63%, 13%, 17% and 7% were nurses/technicians, physicians, pharmacists, and other nonmedical personnel (respectively). 32% suffered from high distress while 20% suffered from severe distress. Exhaustion, anxiety, depression, and sleep disturbances were reported (in past seven days) by approximately 34%, 34%, 19%, and 29% of subjects (respectively). Being older or male, perception of effective protective institutional measures, and being satisfied at work, were significantly associated with lower distress. Conversely, suffering burnout; reporting sleep-related functional problems; exhaustion; being a pharmacist (relative to a physician) and working in a cancer center; harboring fear about virus spreading; fear that the virus threatened life; fear of alienation from family/friends; and fear of workload increases, were significantly associated with higher distress.\n\nConclusionDespite low caseloads, Jordanian practitioners still experienced high levels of distress. Identified demographic, professional and psychological factors influencing distress should inform interventions to improve medical professionals resilience and distress likelihood, regardless of the variable Covid-19 situation.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.14.20130898", + "rel_abs": "During the first pandemic wave Covid-19 reached Latin America cities.\n\nAimTo report clinical features and outcomes associated to Covid-19 in a group of patients admitted during the first wave in a regional reference Center in southern Chile designated to severe and critical cases.\n\nMethodsCases were identified by a compatible clinical picture associated to positive RT-PCR or serological testing. A standard protocol was applied.\n\nResults21 adult patients (20 diagnosed by PCR, one by serology) were admitted between epidemiological weeks 13 to 20, involving 8.8% of total regional cases. Hospitalization occurred at a median of 11 days after symptoms onset. Patients [≥]60 years old predominated (57.1%). Hypertension (61.9%), obesity (57.1%) and diabetes mellitus 2 (38.1%) were prevalent but 19% had no comorbid conditions nor were elderly. Two cases involved second-trimester pregnant women. Positive IgM or IgM/IgG results obtained by rapid serological testing were limited (19% at 1st week; 42.9% at 2nd week). Nine patients (42.9%, critical group) were transferred to ICU and connected to mechanical ventilation due to respiratory failure. By univariate analysis admission to ICU was significantly associated to tachypnea and higher plasmatic LDH values. One pregnant woman required urgent cesarean section given birth to a premature neonate without vertical transmission. Two patients died (in-hospital mortality 9.5%) and length of stay was [≥] 14 days in 57.9% of patients.\n\nConclusionIn our regional Center, Covid 19 was associated to known risk factors, had a prolonged stay and in-hospital mortality. Tachypnea [≥]30/min is predictive of transfer to ICU.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Feras Ibrahim Hawari", - "author_inst": "King Hussein Cancer Center" + "author_name": "Felipe Olivares", + "author_inst": "Hospital Base de Valdivia, Valdivia, Chile" }, { - "author_name": "Nour A Obeidat", - "author_inst": "King Hussein Cancer Center" + "author_name": "Daniel Munoz", + "author_inst": "Hospital Base de Valdivia, Valdivia, Chile" }, { - "author_name": "Yasmeen I Dodin", - "author_inst": "King Hussein Cancer Center" + "author_name": "Alberto Fica", + "author_inst": "Hospital Base de Valdivia, Valdivia, Chile" }, { - "author_name": "Asma S Albtoosh", - "author_inst": "The University of Jordan" + "author_name": "Ignacio Delama", + "author_inst": "Hospital Base de Valdivia, Valdivia, Chile" }, { - "author_name": "Rasha M Manasrah", - "author_inst": "King Hussein Cancer Center" + "author_name": "Ignacia Alvarez", + "author_inst": "Hospital Base de Valdivia, Valdivia, Chile" }, { - "author_name": "Ibrahim O Alaqeel", - "author_inst": "Ibn Alhaytham Hospital" + "author_name": "Maritza Navarrete", + "author_inst": "Hospital Base de Valdivia, Valdivia, Chile" }, { - "author_name": "Asem H Mansour", - "author_inst": "King Hussein Cancer Center" + "author_name": "Eileen Blackburn", + "author_inst": "Hospital Base de Valdivia, Valdivia, Chile" + }, + { + "author_name": "Pamela Garrido", + "author_inst": "Hospital Base de Valdivia, Valdivia, Chile" + }, + { + "author_name": "Juan Granjean", + "author_inst": "Hospital Base de Valdivia, Valdivia, Chile" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.06.13.20130617", @@ -1347994,49 +1348078,113 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.06.15.153197", - "rel_title": "Comparative analysis of coronavirus genomic RNA structure reveals conservation in SARS-like coronaviruses", + "rel_doi": "10.1101/2020.06.15.153411", + "rel_title": "The in vitro antiviral activity of the anti-hepatitis C virus (HCV) drugs daclatasvir and sofosbuvir against SARS-CoV-2", "rel_date": "2020-06-16", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.15.153197", - "rel_abs": "Coronaviruses, including SARS-CoV-2 the etiological agent of COVID-19 disease, have caused multiple epidemic and pandemic outbreaks in the past 20 years1-3. With no vaccines, and only recently developed antiviral therapeutics, we are ill equipped to handle coronavirus outbreaks4. A better understanding of the molecular mechanisms that regulate coronavirus replication and pathogenesis is needed to guide the development of new antiviral therapeutics and vaccines. RNA secondary structures play critical roles in multiple aspects of coronavirus replication, but the extent and conservation of RNA secondary structure across coronavirus genomes is unknown5. Here, we define highly structured RNA regions throughout the MERS-CoV, SARS-CoV, and SARS-CoV-2 genomes. We find that highly stable RNA structures are pervasive throughout coronavirus genomes, and are conserved between the SARS-like CoV. Our data suggests that selective pressure helps preserve RNA secondary structure in coronavirus genomes, suggesting that these structures may play important roles in virus replication and pathogenesis. Thus, disruption of conserved RNA secondary structures could be a novel strategy for the generation of attenuated SARS-CoV-2 vaccines for use against the current COVID-19 pandemic.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.15.153411", + "rel_abs": "Current approaches of drugs repurposing against 2019 coronavirus disease (COVID-19) have not proven overwhelmingly successful and the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic continues to cause major global mortality. Daclatasvir (DCV) and sofosbuvir (SFV) are clinically approved against hepatitis C virus (HCV), with satisfactory safety profile. DCV and SFV target the HCV enzymes NS5A and NS5B, respectively. NS5A is endowed with pleotropic activities, which overlap with several proteins from SARS-CoV-2. HCV NS5B and SARS-CoV-2 nsp12 are RNA polymerases that share homology in the nucleotide uptake channel. We thus tested whether SARS-COV-2 would be susceptible these anti-HCV drugs. DCV consistently inhibited the production of infectious SARS-CoV-2 in Vero cells, in the hepatoma cell line (HuH-7) and in type II pneumocytes (Calu-3), with potencies of 0.8, 0.6 and 1.1 M, respectively. Although less potent than DCV, SFV and its nucleoside metabolite inhibited replication in Calu-3 cells. Moreover, SFV/DCV combination (1:0.15 ratio) inhibited SARS-CoV-2 with EC50 of 0.7:0.1 M in Calu-3 cells. SFV and DCV prevented virus-induced neuronal apoptosis and release of cytokine storm-related inflammatory mediators, respectively. Both drugs inhibited independent events during RNA synthesis and this was particularly the case for DCV, which also targeted secondary RNA structures in the SARS-CoV-2 genome. Concentrations required for partial DCV in vitro activity are achieved in plasma at Cmax after administration of the approved dose to humans. Doses higher than those approved may ultimately be required, but these data provide a basis to further explore these agents as COVID-19 antiviral candidates.", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Wes Sanders", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Carolina Q. Sacramento", + "author_inst": "Fiocruz" }, { - "author_name": "Ethan J Fritch", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Natalia Fintelman-Rodrigues", + "author_inst": "Fiocruz" }, { - "author_name": "Emily A Madden", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Jairo R. Temerozo", + "author_inst": "Fiocruz" }, { - "author_name": "Rachel L Graham", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Aline de Paula Dias Da Silva", + "author_inst": "Fiocruz" }, { - "author_name": "Heather A Vincent", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Suelen da Silva Gomes Dias", + "author_inst": "Fiocruz" }, { - "author_name": "Mark T Heise", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Andre C. Ferreira", + "author_inst": "Fiocruz" }, { - "author_name": "Ralph S Baric", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Carine dos Santos da Silva", + "author_inst": "Fiocruz" }, { - "author_name": "Nathaniel J Moorman", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Mayara Mattos", + "author_inst": "Fiocruz" + }, + { + "author_name": "Camila R. R. Pao", + "author_inst": "Fiocruz" + }, + { + "author_name": "Caroline S. de Freitas", + "author_inst": "Fiocruz" + }, + { + "author_name": "Vinicius Cardoso Soares", + "author_inst": "Fiocruz" + }, + { + "author_name": "Lucas Villas Boas Hoelz", + "author_inst": "Fiocruz" + }, + { + "author_name": "Tacio Vinicio Amorim Fernandes", + "author_inst": "Instituto Nacional de Metrologia, Qualidade e Tecnologia (INMETRO)" + }, + { + "author_name": "Frederico Silva Castelo Branco", + "author_inst": "Fiocruz" + }, + { + "author_name": "Monica Macedo Bastos", + "author_inst": "Fiocruz" + }, + { + "author_name": "Nubia Boechat", + "author_inst": "Fiocruz" + }, + { + "author_name": "Felipe Betoni Saraiva", + "author_inst": "Fiocruz" + }, + { + "author_name": "Marcelo Alves Ferreira", + "author_inst": "Fiocruz" + }, + { + "author_name": "Rajith K. R. Rajoli", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Andrew Owen", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Fernando A. Bozza", + "author_inst": "Fiocruz" + }, + { + "author_name": "Dumith Chequer Bou-Habib", + "author_inst": "Fiocruz" + }, + { + "author_name": "Patricia T. Bozza", + "author_inst": "Fiocruz" + }, + { + "author_name": "Thiago Moreno L. Souza", + "author_inst": "Fiocruz" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", "category": "microbiology" }, @@ -1349836,37 +1349984,45 @@ "category": "genetics" }, { - "rel_doi": "10.1101/2020.06.12.20128736", - "rel_title": "Nasal-Swab Testing Misses Patients with Low SARS-CoV-2 Viral Loads", + "rel_doi": "10.1101/2020.06.12.20127555", + "rel_title": "Social media as a tool for scientific updating at the time of COVID pandemic", "rel_date": "2020-06-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.12.20128736", - "rel_abs": "The urgent need for large-scale diagnostic testing for SARS-CoV-2 has prompted pursuit of sample-collection methods of sufficient sensitivity to replace sampling of the nasopharynx (NP). Among these alternatives is collection of nasal-swab samples, which can be performed by the patient, avoiding the need for healthcare personnel and personal protective equipment.\n\nPrevious studies have reached opposing conclusions regarding whether nasal sampling is concordant or discordant with NP. To resolve this disagreement, we compared nasal and NP specimens collected by healthcare workers in a cohort consisting of individuals clinically suspected of COVID-19 and outpatients known to be SARS-CoV-2 RT-PCR positive undergoing follow-up. We investigated three different transport conditions, including traditional viral transport media (VTM) and dry swabs, for each of two different nasal-swab collection protocols on a total of 308 study participants, and compared categorical results and Ct values to those from standard NP swabs collected at the same time from the same patients. All testing was performed by RT-PCR on the Abbott SARS-CoV-2 RealTime EUA (limit of detection [LoD], 100 copies viral genomic RNA/mL transport medium). We found high concordance (Cohens kappa >0.8) only for patients with viral loads above 1,000 copies/mL. Those with viral loads below 1,000 copies/mL, the majority in our cohort, exhibited low concordance (Cohens kappa = 0.49); most of these would have been missed by nasal testing alone. Previous reports of high concordance may have resulted from use of assays with higher LoD ([≥]1,000 copies/mL). These findings counsel caution in use of nasal testing in healthcare settings and contact-tracing efforts, as opposed to screening of asymptomatic, low-prevalence, low-risk populations. Nasal testing is an adjunct, not a replacement, for NP.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.12.20127555", + "rel_abs": "In the face of the rapid evolution of the COVID-19 pandemic, healthcare professionals on the frontline are in urgent need of frequent updates in the accomplishment of their practice. Hence, clinicians started to search for prompt, valid information on sources parallel to academic journals publications. Aim of this work is to investigate the extent of this phenomenon.\n\nWe administered an anonymous online cross-sectional survey to 645 Italian clinicians. 369 questionnaires were returned. 19,5% (n=72) of respondents were younger than 30 years-old; 49,3% (n=182) worked in Infectious Diseases, Internal Medicine or Respiratory Medicine departments, 11.5% (n=42) in Intensive Care Unit and 7.4% (n=27) were general practitioner. 70% (n=261) of respondents reported that their use of social media to seek medical information increased during the pandemic. 39.3% (n = 145) consistently consulted Facebook groups and 53.1% (n = 196) Whatsapp chats. 47% (n = 174) of respondents reported that information shared on social media had a consistent impact on their daily practice. In the present study, we found no difference in social media usage between age groups or medical specialties.\n\nGiven the urgent need for scientific update in face of the present health emergency, these findings may help understanding how clinicians access new evidences and implement them in their daily practice.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Cody Callahan", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Rita Murri", + "author_inst": "Department of Infectious Diseases, Policlinico Universitario Agostino Gemelli IRCCS" }, { - "author_name": "Rose Lee", - "author_inst": "Beth Israel Deaconess Medical Center, Harvard Medical School" + "author_name": "Francesco Vladimiro Segala", + "author_inst": "Catholic University of the Sacred Heart, Rome, Italy" }, { - "author_name": "Ghee Lee", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Pierluigi Del Vecchio", + "author_inst": "Catholic University of the Sacred Heart, Rome, Italy" }, { - "author_name": "Kate E Zulauf", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Antonella Cingolani", + "author_inst": "Department of Infectious Diseases, Policlinico Universitario Agostino Gemelli IRCCS" }, { - "author_name": "James E Kirby", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Eleonora Taddei", + "author_inst": "Department of Infectious Diseases, Policlinico Universitario Agostino Gemelli IRCCS" }, { - "author_name": "Ramy Arnaout", - "author_inst": "Beth Israel Deaconess Medical Center, Harvard Medical School" + "author_name": "Giulia Micheli", + "author_inst": "Catholic University of the Sacred Heart, Rome, Italy" + }, + { + "author_name": "Massimo Fantoni", + "author_inst": "Department of Infectious Diseases, Policlinico Universitario Agostino Gemelli IRCCS" + }, + { + "author_name": "- COVID II Columbus Group", + "author_inst": "" } ], "version": "1", @@ -1351414,33 +1351570,17 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.12.20129403", - "rel_title": "Evaluating COVID-19 screening strategies based on serological tests", + "rel_doi": "10.1101/2020.06.12.20129429", + "rel_title": "Modelling of the second (and subsequent) waves of the coronavirus epidemic. Spain and Germany as case studies", "rel_date": "2020-06-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.12.20129403", - "rel_abs": "BackgroundFacing the SARS-CoV-2 epidemic requires intensive testing on the population to early identify and isolate infected subjects. Although RT-PCR is the most reliable technique to detect ongoing infections, serological tests are frequently proposed as tools in heterogeneous screening strategies. We analyze the performance of a screening strategy proposed in Tuscany (Italy), which first uses qualitative rapid tests for antibody detection, and then RT-PCR tests on the positive subjects.\n\nMethodsWe simulate the number of RT-PCR tests required by the screening strategy and the undetected ongoing infections in a pseudo-population of 500000 subjects, under different prevalence scenarios and assuming a sensitivity of the serological test ranging from 0.50 to 0.80 (specificity=0.98). A compartmental model is used to predict the number of new infections generated by the false negatives two months after the screening, under different values of the infection reproduction number.\n\nResultsAssuming a sensitivity equal to 0.80 and a prevalence of 0.3%, the screening procedure would require on average 11167.6 RT-PCR tests and would produce 300 false negatives, responsible after two months of a number of contagions ranging from 526 to 1132, under the optimistic scenario of a reproduction number between 0.5 to 1. Costs and false negatives increase with the prevalence.\n\nConclusionsThe analyzed screening procedure should be avoided unless the prevalence and the rate of contagion are very low. The cost and effectiveness of the screening strategies should be evaluated in the actual context of the epidemic, accounting for the fact that it may change over time.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.12.20129429", + "rel_abs": "The first wave of the coronavirus pandemic is waning in many countries. Some of them are starting to lift the confinement measures adopted to control it, but there is considerable uncertainty about if it is too soon and it may cause a second wave of the epidemic. To explore this issue, I fitted a SEIR model with time-dependent transmission and mortality rates to data from Spain and Germany as contrasting case studies. The model reached an excellent fit to the data. I then simulated the post-confinement epidemic under several scenarios. The model shows that (in the absence of a vaccine) a second wave is likely inevitable and will arrive soon, and that a strategy of adaptive confinement may be effective to control it. The model also shows that just a few days delay in starting the confinement may have caused and excess of thousands of deaths in Spain.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Michela Baccini", - "author_inst": "University of Florence" - }, - { - "author_name": "Alessandra Mattei", - "author_inst": "University of Florence" - }, - { - "author_name": "Emilia Rocco", - "author_inst": "University of Florence" - }, - { - "author_name": "Giulia Vannucci", - "author_inst": "University of Florence" - }, - { - "author_name": "Fabrizia Mealli", - "author_inst": "University of Florence" + "author_name": "Francisco de Castro", + "author_inst": "Agri-Food and Biosciences Institute" } ], "version": "1", @@ -1352768,45 +1352908,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.09.20116806", - "rel_title": "Pre exposure Hydroxychloroquine use is associated with reduced COVID19 risk in healthcare workers", + "rel_doi": "10.1101/2020.06.08.20050559", + "rel_title": "COVID-19: Dying is Bad--Losing Life is Worse", "rel_date": "2020-06-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.09.20116806", - "rel_abs": "BackgroundWhile several trials are ongoing for treatment of COVID-19, scientific research on chemoprophylaxis is still lacking even though it has potential to delay the pandemic allowing us time to complete research on vaccines.\n\nMethodsWe have conducted a cohort study amongst Health Care Workers (HCW) exposed to COVID-19 patients, at a tertiary care center in India where there was an abrupt cluster outbreak within on duty personnel. HCWs who had voluntarily taken hydroxychloroquine (HCQ) prior to exposure were considered one cohort while those who had not were considered to be another. All participants with a verifiable contact history were tested for COVID-19 by rtPCR. The two cohorts were comparable in terms of age, gender, comorbidities and exposure. The primary outcome was incidence rates of rtPCR positive COVID-19 infection amongst HCQ users and non users.\n\nResults106 healthcare workers were examined in this cohort study of whom 54 were HCQ users and rest were not. The comparative analysis of incidence of infection between the two groups demonstrated that voluntary HCQ usage was associated with lesser likelihood of developing SARS-CoV-2 infection, compared to those who were not on it, X2=14.59, p<0.001. None of the HCQ users noted any serious adverse effects.\n\nConclusionsThis study demonstrated that voluntary HCQ consumption as pre-exposure prophylaxis by HCWs is associated with a statistically significant reduction in risk of SARS-CoV-2. These promising findings therefore highlight the need to examine this association in greater detail among a larger sample using Randomised Controlled Trials (RCT).", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.08.20050559", + "rel_abs": "BackgroundCOVID-19 was the leading cause of death in the United States over the three-month period March through May 2020. Another perspective is COVID-19s toll in terms of years of life lost. We calculated years of life lost for COVID-19 and other leading causes of death over those three months in the US. We also predicted years of life lost for COVID-19 and ischemic heart diseases (which includes heart attacks) for March through August 2020.\n\nMethodsYears of life lost are the sum of differences between life expectancy at age of death and age at death. Average years of life lost, years of life lost divided by the number of deaths, were also calculated. We used the COVID-19 Projections Using Machine Learning model to predict years of life lost from COVID-19 through the end of August 2020.\n\nResultsCOVID-19 caused 12,035 more deaths than ischemic heart diseases during March through May 2020 but ischemic heart diseases years of life lost were 1.5% greater than those for COVID-19. Average years of life lost were 10.8 and 12.4 for COVID-19 and ischemic heart diseases, respectively. At the end of August, COVID-19 may overtake ischemic heart diseases as the leading cause of deaths and years of life lost in the US.\n\nConclusionEach COVID-19 death causes more than a decade of lost life in the US. We are reminded of a Danish Proverb that states \"Prediction is difficult, especially when dealing with the future.\" We suggest that while dying is bad, losing life is even worse.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Raja Bhattacharya", - "author_inst": "Medical College Kolkata" - }, - { - "author_name": "Sampurna Chowdhury", - "author_inst": "Medical College Kolkata" - }, - { - "author_name": "Rishav Mukherjee", - "author_inst": "Medical College Kolkata" - }, - { - "author_name": "Anita Nandi", - "author_inst": "Medical College Kolkata" - }, - { - "author_name": "Manish Kulshrestha", - "author_inst": "Medical College Kolkata" + "author_name": "Harry P Wetzler", + "author_inst": "Ofstead and Associates" }, { - "author_name": "Rohini Ghosh", - "author_inst": "Medical College Kolkata" + "author_name": "Erica A. Wetzler", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Souvik Saha", - "author_inst": "Presidency University" + "author_name": "Herbert W. Cobb", + "author_inst": "Independent Analyst" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1354118,63 +1354242,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.09.20126474", - "rel_title": "Clinical validation and performance evaluation of the automated Vitros Total Anti-SARS-CoV-2 Antibodies assay for screening of serostatus in COVID-19", + "rel_doi": "10.1101/2020.06.09.20126946", + "rel_title": "Use of face coverings by the public during the COVID-19 pandemic: an observational study", "rel_date": "2020-06-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.09.20126474", - "rel_abs": "ObjectivesEvaluation of serostatus against SARS-CoV-2 has emerged as an important tool in identification of exposure to COVID-19. We report on the validation of the Vitros Anti-SARS-CoV-2 Total (CoV2T) assay for qualitative serological testing of SARS-CoV-2 antibodies.\n\nMethodsWe performed validation studies according to COLA guidelines, using samples previously tested for SARS-CoV-2 by RT-PCR. We evaluated precision, analytical interferences, and cross-reactivity with other viral infections. We also evaluated concordance with molecular and other serological testing, and evaluated seroconversion.\n\nResultsThe Vitros CoV2T assay exhibited acceptable precision, was resistant to analytical interference, and did not exhibit cross-reactivity with samples positive for other respiratory viruses. The CoV2T assay exhibited 100% negative predictive agreement (56/56) and 71% positive predictive agreement (56/79) with RT-PCR across all patient samples, and was concordant with other serological assays. Concordance with RT-PCR was 97% > 7 days after symptom onset.\n\nConclusionsThe Vitros CoV2T assay was successfully validated in our laboratory. We anticipate it will be a useful tool in screening for exposure to SARS-CoV-2, however, the use of the CoV2T and other serological assays in clinical management of COVID-19 patients is yet unknown, and must be evaluated in future studies.\n\nKey pointsO_ST_ABSWhat issue or core problem does the study address?C_ST_ABSO_LIMultiple serological assays for detection of anti-SARS-CoV-2 antibodies have received FDA Emergency Use Authorizations, but few data have been published on the performance of these assays.\nC_LI\n\nWhat would one take-home point for the working medical professional be?O_LIThe Vitros Anti-SARS-CoV-2 Total assay is a total antibody test to be used as a serological screen for exposure to COVID-19. This assay performs well, and is comparable to other serological tests.\nC_LI\n\nWhat is the most significant or most interesting finding of the study?O_LIWe confirmed that the Vitros Anti-SARS-CoV-2 Total assay, like other serological tests, is not suitable for diagnosis of acute infection, as it is not sensitive to infection <7 days post-onset.\nC_LI", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.09.20126946", + "rel_abs": "Public health agencies have recommended that the public wear face coverings, including face masks, to mitigate COVID-19 transmission. However, the extent to which the public has adopted this recommendation is unknown. An observational study of 3,271 members of the public in May and June 2020 examined face covering use at grocery stores across Wisconsin. We found that only 41.2% used face coverings. Individuals who appeared to be female or older adults had higher odds of using face coverings. Additionally, location-specific variables such as expensiveness of store, county-level population and county-level COVID-19 case prevalence were associated with increased odds of using face coverings. To our knowledge, this is the first direct observational study examining face covering behavior by the public in the U.S., and our findings have implications for public health agencies during the COVID-19 pandemic.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Emily Garnett", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Joanna Jung", - "author_inst": "Baylor College of Medicine" + "author_name": "Nicholas L Arp", + "author_inst": "University of Wisconsin School of Medicine and Public Health" }, { - "author_name": "Estella Tam", - "author_inst": "Texas Children's Hospital" + "author_name": "Tung H Nguyen", + "author_inst": "University of Wisconsin School of Medicine and Public Health" }, { - "author_name": "Deepthi Rajapakshe", - "author_inst": "Texas Children's Hospital" + "author_name": "Emma J Graham Linck", + "author_inst": "University of Wisconsin School of Medicine and Public Health" }, { - "author_name": "Stephen Cheney", - "author_inst": "Baylor College of Medicine" + "author_name": "Austin K Feeney", + "author_inst": "University of Wisconsin School of Medicine and Public Health" }, { - "author_name": "Cameron Brown", - "author_inst": "Baylor College of Medicine" + "author_name": "Jonathan H Schrope", + "author_inst": "University of Wisconsin School of Medicine and Public Health" }, { - "author_name": "Kenneth L Muldrew", - "author_inst": "Baylor College of Medicine" + "author_name": "Katrina L Ruedinger", + "author_inst": "University of Wisconsin School of Medicine and Public Health" }, { - "author_name": "Jing Cao", - "author_inst": "Baylor College of Medicine" + "author_name": "Anqi Gao", + "author_inst": "University of Wisconsin School of Medicine and Public Health" }, { - "author_name": "Ila Singh", - "author_inst": "Baylor College of Medicine" + "author_name": "Margot Miranda-Katz", + "author_inst": "University of Wisconsin School of Medicine and Public Health" }, { - "author_name": "James Versalovic", - "author_inst": "Baylor College of Medicine" + "author_name": "Ashley E Kates", + "author_inst": "Department of Medicine, University of Wisconsin-Madison" }, { - "author_name": "Sridevi Devaraj", - "author_inst": "Baylor College of Medicine" + "author_name": "Nasia Safdar", + "author_inst": "Department of Medicine, University of Wisconsin-Madison" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pathology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.06.09.20126086", @@ -1355700,27 +1355820,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.10.20127183", - "rel_title": "The Computational Patient has Diabetes and a COVID", + "rel_doi": "10.1101/2020.06.10.20127886", + "rel_title": "INTRAREGIONAL PROPAGATION OF COVID-19 CASES IN PARA, BRAZIL. ASSESSMENT OF ISOLATION REGIME TO LOCKDOWN.", "rel_date": "2020-06-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.10.20127183", - "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWMedicine is moving from a curative discipline to a preventative discipline relying on personalised and precise treatment plans. The complex and multi level pathophysiological patterns of most diseases require a systemic medicine approach and are challenging current medical therapies. On the other hand, computational medicine is a vibrant interdisciplinary field that could help move from an organ-centered approach to a process-oriented approach. The ideal computational patient would require an international interdisciplinary effort, of larger scientific and technological interdisciplinarity than the Human Genome Project. When deployed, such a patient would have a profound impact on how healthcare is delivered to patients. Here we present a computational patient model that integrates, refines and extends recent mechanistic or phenomenological models of cardiovascular, RAS and diabetic processes. Our aim is twofold: analyse the modularity and composability of the model-building blocks of the computational patient and to study the dynamical properties of well-being and disease states in a broader functional context. We present results from a number of experiments among which we characterise the dynamic impact of COVID-19 and type-2 diabetes (T2D) on cardiovascular and inflammation conditions. We tested these experiments under different exercise, meal and drug regimens. We report results showing the striking importance of transient dynamical responses to acute state conditions and we provide guidelines for system design principles for the inter-relationship between modules and components in systemic medicine. Finally this initial computational Patient can be used as a toolbox for further modifications and extensions.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.10.20127886", + "rel_abs": "Due to the high incidence of COVID-19 case numbers internationally, the World Health Organization (WHO) declared a Public Health Emergency of global relevance, advising countries to follow protocols to combat pandemic advance through actions that can reduce spread and consequently avoid a collapse in the local health system. On March 18, 2020, Para notified the first case of COVID-19. After seven weeks, the number of confirmed cases reached 4,756 with 375 deaths. Knowing that infected people may be asymptomatic, the disease symptomatology absence and the populations neglect of isolation influence the spread, and factors such as chronic pneumonia, high age, obesity, chronic kidney diseases and other comorbidities favor the mortality rate. On the other hand, social isolation, quarantine and lockdown seek to contain the intraregional contagion advance. This study analyzes the dynamics of COVID-19 new cases advance among municipalities in the state of Para, Brazil. The results show it took 49 days for 81% of the states municipalities to register COVID-19 cases. The association between social isolation, quarantine and lockdown as an action to contain the infection was effective in reducing the regions new cases registration of COVID-19 in the short-term.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Pietro Barbiero", - "author_inst": "University of Cambridge, Cambridge, UK" + "author_name": "F\u00e9lix L\u00e9lis da Silva", + "author_inst": "Federal Institute of Education Science and Tecnology of Par\u00e1" }, { - "author_name": "Pietro Li\u00f3", - "author_inst": "University of Cambridge, Cambridge, UK" + "author_name": "Javier Dias Pita", + "author_inst": "Federal Institute of Science and Technology of Par\u00e1" + }, + { + "author_name": "Maryjane Diniz Ara\u00fajo Gomes", + "author_inst": "Federal Institute of Science and Technology of Par\u00e1" + }, + { + "author_name": "Andr\u00e9a Pereira L\u00e9lis da Silva", + "author_inst": "Metropolitan Regional Hospital" + }, + { + "author_name": "Gabriel L\u00e9lis P. da Silva", + "author_inst": "Est\u00e1cio de S\u00e1 College of Castanhal" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "cardiovascular medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.06.11.20127894", @@ -1357066,65 +1357198,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.11.20128041", - "rel_title": "Timing COVID-19 - Synchronization of longitudinal patient data to the underlying disease progression using CRP as a temporal marker", + "rel_doi": "10.1101/2020.06.11.20128587", + "rel_title": "Age Pattern of Premature Mortality under varying scenarios of COVID-19 Infection in India", "rel_date": "2020-06-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20128041", - "rel_abs": "Advances in medical technology and IT infrastructure have led to increased availability of continuous patient data that allows investigation of the longitudinal progression of novel and known diseases in unprecedented detail. However, to accurately describe any underlying pathophysiology with longitudinal data, the individual patient trajectories have to be synchronized based on temporal markers. In this study, we use longitudinal data from 28 critically ill ICU COVID-19 patients to compare the commonly used alignment markers \"onset of symptoms\", \"hospital admission\" and \"ICU admission\" with a novel objective method based on the peak value of inflammatory marker C-reactive protein (CRP). By applying our CRP-based method to align the progression of neutrophils and lymphocytes, we were able to define a pathophysiological window that allowed further risk stratification in our COVID-19 patient cohort. Our data highlights that proper synchronization of patient data is crucial to differentiate severity subgroups and to allow reliable interpatient comparisons.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20128587", + "rel_abs": "BackgroundIndia is vulnerable to community infection of COVID-19 due to crowded and poor living condition, high density, slums in urban areas and poor health care system. The number of COVID 19 infection has crossed 300,000 with over 7,500 deaths despite a prolonged period of lock down and restrictions in public spaces. Given the likely scale and magnitude of this pandemic, it is important to understand its impact on the age pattern of mortality under varying scenarios.\n\nObjectiveThe main objective of this paper is to understand the age pattern of mortality under varying scenarios of community infection.\n\nData and MethodsData from the Sample Registration System (SRS), covidi19india.org and country specific data from worldmeter is used in the analyses. Descriptive statistics, case-fatality ratio, case fatality ratio with 14 days delay, abridged life table,years of potential life lost (YPLL) and disability adjusted life years (DALY) is used.\n\nResultsThe case fatality ratio (CFR) with 14 days delay for India is at least twice higher (8.0) than CFR of 3.4. Considering 8% mortality rate and varying scenario of community infection by 0.5%, 1% and 2%, Indias life expectancy will reduce by 0.8, 1.5 and 3.0 years and potential life years lost by 12.1 million, 24.3 million and 48.6 million years respectively. A community infection of 0.5% may result in DALY by 6.2 per 1000 population. Major share of PYLL and DALY is accounted by the working ages.\n\nConclusionCOVID-19 has a visible impact on mortality with loss of productive life years in working ages. Sustained effort at containing the transmission at each administrative unit is recommended to arrest mortality owing to COVID-19 pandemic.\n\nWhat is known?The case fatality rate associated with COVID-19 is low in India compared to many other countries. The mortality level is higher among elderly and people with co-morbidity.\n\nContributionThe case fatality ratio is illusive in the sense that the same with 14 days delay for India is at least twice higher (8.0). The COVID-19 attributable mortality has the potential to reduce the longevity of the population. Unlike developed countries, about half of the COVID-19 attributable mortality would be in the working age group of 45-64 years. With any level of community infection, the years of potential life lost (YPLL) and disability adjusted life years (DALY) world be highest in the working age group (45-64 years).", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Martina A Maibach", - "author_inst": "Institute for Intensive Care Medicine, University and University Hospital Zurich, Switzerland" - }, - { - "author_name": "Ahmed Allam", - "author_inst": "Department of Quantitative Biomedicine, University and University Hospital Zurich, Switzerland" - }, - { - "author_name": "Matthias P Hilty", - "author_inst": "Institute for Intensive Care Medicine, University and University Hospital Zurich, Switzerland" - }, - { - "author_name": "Nicolas A Perez Gonzales", - "author_inst": "Department of Quantitative Biomedicine, University and University Hospital Zurich, Switzerland" - }, - { - "author_name": "Philipp K Buehler", - "author_inst": "Institute for Intensive Care Medicine, University and University Hospital Zurich, Switzerland" - }, - { - "author_name": "Pedro D Wendel Garcia", - "author_inst": "Institute for Intensive Care Medicine, University and University Hospital Zurich, Switzerland" - }, - { - "author_name": "Silvio D Brugger", - "author_inst": "Department of Department of Infectious Diseases and Hospital Epidemiology, University and University Hospital Zurich, Switzerland" - }, - { - "author_name": "Christoph C Ganter", - "author_inst": "Institute for Intensive Care Medicine, University and University Hospital Zurich, Switzerland" + "author_name": "Sanjay Kumar Mohanty", + "author_inst": "International Institute for Population Sciences, Mumbai, India" }, { - "author_name": "- The CoViD-19 ICU-Research Group Zurich", - "author_inst": "-" - }, - { - "author_name": "- The RISC-19-ICU Investigators", - "author_inst": "-" - }, - { - "author_name": "Michael Krauthammer", - "author_inst": "Department of Quantitative Biomedicine, University and University Hospital Zurich, Switzerland" + "author_name": "Umakanta Sahoo", + "author_inst": "International Institute for Population Sciences, Mumbai, India" }, { - "author_name": "Reto A Schuepbach", - "author_inst": "Institute for Intensive Care Medicine, University and University Hospital Zurich, Switzerland" + "author_name": "Udaya Shankar Mishra", + "author_inst": "Centre for Development Studies, Thiruvananthapuram, kerala, India" }, { - "author_name": "Jan Bartussek", - "author_inst": "Institute for Intensive Care Medicine, University and University Hospital Zurich, Switzerland" + "author_name": "Manisha Dubey", + "author_inst": "Independent Consultant, New Delhi, India" } ], "version": "1", @@ -1358972,47 +1359068,39 @@ "category": "synthetic biology" }, { - "rel_doi": "10.1101/2020.06.11.20128835", - "rel_title": "PROGNOSTIC VALUE OF COMORMIDITY FOR SEVERITY OF COVID-19: A SYSTEMATIC REVIEW AND META-ANALYSIS STUDY", + "rel_doi": "10.1101/2020.06.12.148577", + "rel_title": "Interactions of SARS-CoV-2 infection with chronic obesity inflammation: a complex network phenomenon", "rel_date": "2020-06-12", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20128835", - "rel_abs": "Background & AimWith the increase in the number of COVID-19 infections, global health is facing insufficient sources; this study aimed to provide additional data regarding the clinical characteristics of patients diagnosed with COVID-19 and in particular to analyze the factors associated with disease severity, unimprovement and mortality.\n\nMethods82 studies were included in the present meta-analysis that all of them have been published before May 1, 2020 and were found by searching through the databases Scopus and MEDLINE. The selected papers were studied and analyzed by employing the version 14 of stata software. It should be noted that, we employed I2 statistics for testing and verifying heterogeneity.\n\nResults82 papers were finally chosen for this meta-analysis, including 74855 infected patients (35673 men, 31140 women). The mean age of the patients was 56.49. The results indicate the prevalence of fever 79.84 (95% CI: 75.22-84.13), cough 59.53 (95% CI: 55.35-63.65), fatigue or myalgia 33.46 (95% CI: 28.68-38.40), dyspnea 31.48 (95% CI: 25.75-37.49) and diarrhea 10.71 (95% CI: 8.20-13.49). The prevalence of the most common comorbidities were hypertension 25.10 (95% CI: 19.91-30.64), diabetes 13.48 (95% CI: 10.61-16.62), cardiovascular diseases 8.94 (95% CI: 6.99-11.10), and chronic kidney disease 3.27 (95% CI: 2.22-4.47).\n\nConclusionThe results of this study are seriously needed to effectively monitor the health of people with comorbidities (hypertension, diabetes, cardiovascular and cerebrovascular disease, coronary heart disease, and chronic kidney disease) to prevent the development of COVID-19 infection.\n\nHighlightsO_LIThe most prevalent risk factors among patients with COVID-19 were hypertension, diabetes, cardiovascular disease, and chronic kidney disease.\nC_LIO_LIThe most common symptoms among individuals who had COVID-19 infection were fever, cough, fatigue or myalgia, dyspnea, and diarrhea.\nC_LIO_LIThe mean age of the patients with COVID-19 infection was 56.49.\nC_LIO_LIIf the patient is an elderly male with underlying diseases, he is more likely to have severe disorders or even face to death.\nC_LI", - "rel_num_authors": 7, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.12.148577", + "rel_abs": "Obesity is one of the biggest public health problems in the world, and its pathophysiological characteristics include chronic inflammation with an increase in various circulating inflammatory markers, such as acute inflammatory cytokines. Complications in the respiratory tract are related to bodily problems, which lead to a restriction of lung function due to reduced volume, inducing an increase in respiratory work. SARS-CoV-2 has a high potential for contamination by respiratory secretions and, therefore, obesity is one of the main risk factors for complications due to the association established between obesity, chronic inflammation and respiratory infection. The objective was to analyze the complex relationships between obesity and COVID-19 in a meta-analysis study using complex network modeling and the theoretical knockouts technique. Here, we identify and justify through a mathematical analysis the relationships between all the immunological agents added to the proposed immunological networks, considered as a simple evident interaction, relationship, influence, response, activation, based on our quantifiers. They performed the knockouts of all 52 vertices in the COVID-19 network and obesity - regardless of the environment, which would result in nonsense - and the COVID-19 infection network without considering obesity. The stationary flow vector (flow profile), for some knockouts of immunological interest in COVID-19 infections, was chosen IFN, IL-6, IL-10, IL-17 and TNF. This initial study pointed out the importance of chronic inflammation in the obese individual as an important factor in potentiating the disease caused by covid-19 and, in particular, the importance on IL-17.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Mobina Fathi", - "author_inst": "Shahid Beheshti University of Medical Sciences" - }, - { - "author_name": "Kimia Vakili", - "author_inst": "Shahid Beheshti University of Medical Sciences" - }, - { - "author_name": "Fatemeh Sayehmiri", - "author_inst": "Shahid Beheshti University of Medical Sciences" + "author_name": "Giovani Marino Favero", + "author_inst": "Universidade Estadual de Ponta Grossa" }, { - "author_name": "Ashraf Mohamadkhani", - "author_inst": "Tehran University of Medical Sciences" + "author_name": "Luis Paulo Gomes Mascarenhas", + "author_inst": "Universidade Estadual do Centro Oeste" }, { - "author_name": "Mohammadreza Hajiesmaeili", - "author_inst": "Shahid Beheshti University of Medical Sciences" + "author_name": "Meirielly Furmann", + "author_inst": "Universidade do Centro Oeste" }, { - "author_name": "Mostafa Rezaei-Tavirani", - "author_inst": "Shahid Beheshti University of Medical Sciences" + "author_name": "Juliana Berton", + "author_inst": "Universidade Estadual de Ponta Grossa" }, { - "author_name": "Owrang Eilami", - "author_inst": "Shiraz University of Medical Science" + "author_name": "Pedro Jeferson Miranda", + "author_inst": "Universidade Estadual de Ponta Grossa" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2020.06.10.20127175", @@ -1360638,43 +1360726,31 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.06.08.141150", - "rel_title": "Modeling the structure of the frameshift stimulatory pseudoknot in SARS-CoV-2 reveals multiple possible conformers", + "rel_doi": "10.1101/2020.06.06.112474", + "rel_title": "Quantitative PCR for cannabis flower containing SARs-CoV-2", "rel_date": "2020-06-11", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.08.141150", - "rel_abs": "The coronavirus causing the COVID-19 pandemic, SARS-CoV-2, uses -1 programmed ribosomal frameshifting (-1 PRF) to control the relative expression of viral proteins. As modulating -1 PRF can inhibit viral replication, the RNA pseudoknot stimulating -1 PRF may be a fruitful target for therapeutics treating COVID-19. We modeled the unusual 3-stem structure of the stimulatory pseudoknot of SARS-CoV-2 computationally, using multiple blind structural prediction tools followed by s-long molecular dynamics simulations. The results were compared for consistency with nuclease-protection assays and single-molecule force spectroscopy measurements of the SARS-CoV-1 pseudoknot, to determine the most likely conformations. We found several possible conformations for the SARS-CoV-2 pseudoknot, all having an extended stem 3 but with different packing of stems 1 and 2. Several conformations featured rarely-seen threading of a single strand through the junction formed between two helices. These structural models may help interpret future experiments and support efforts to discover ligands inhibiting -1 PRF in SARS-CoV-2.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.06.112474", + "rel_abs": "In January of 2020, COVID-19 became a worldwide pandemic. As many industries shutdown to comply with social distancing measures, the cannabis industry was deemed an essential business in most U.S. jurisdictions. Cannabis is manually farmed, trimmed and packaged. Employees and trimmers in cannabis grows have been reported to test qPCR positive for SARs-CoV-2 and as a result cannabis flower can be a potential inhaled SARs-CoV-2 fomite. Many of the comorbidities described in COVID-19 are also qualifying conditions for medical cannabis access. Bat guano has been identified as a rich source for novel coronavirus discovery and it is also a common fertilizer in the cannabis field. To better assess cannabis fomite risk we developed a SARs-CoV-2 quantitative PCR assay optimized to operate with a hemp flower background matrix. This assay was utilized to estimate the stability of gamma irradiated SARs-CoV-2 as a hemp flower fomite.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Sara Ibrahim Omar", - "author_inst": "University of Alberta" - }, - { - "author_name": "Meng Zhao", - "author_inst": "University of Alberta" - }, - { - "author_name": "Rohith Vedhthaanth Sekar", - "author_inst": "University of Alberta" - }, - { - "author_name": "Sahar Arbabi Moghadam", - "author_inst": "University of Alberta" + "author_name": "Kevin McKernan", + "author_inst": "Medicinal Genomics" }, { - "author_name": "Jack A Tuszynski", - "author_inst": "University of Alberta" + "author_name": "Liam T Kane", + "author_inst": "Medicinal Genomics" }, { - "author_name": "Michael T Woodside", - "author_inst": "University of Alberta" + "author_name": "Yvonne Helbert", + "author_inst": "Medicinal Genomics" } ], "version": "1", - "license": "cc_by_nc", - "type": "new results", - "category": "biophysics" + "license": "cc_by", + "type": "confirmatory results", + "category": "genomics" }, { "rel_doi": "10.1101/2020.06.10.144816", @@ -1362332,49 +1362408,209 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.08.20125856", - "rel_title": "Identification of multiple large deletions in ORF7a resulting in in-frame gene fusions in clinical SARS-CoV-2 isolates", + "rel_doi": "10.1101/2020.06.08.20125112", + "rel_title": "A consensus Covid-19 immune signature combines immuno-protection with discrete sepsis-like traits associated with poor prognosis", "rel_date": "2020-06-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.08.20125856", - "rel_abs": "Peculiar among human RNA viruses, coronaviruses have large genomes containing accessory genes that are not required for replication. Numerous mutations within the SARS-CoV-2 genome have been described but few deletions in the accessory genes of SARS-CoV-2 have been reported. Here, we report two large deletions in ORF7a, both of which produce new open reading frames (ORFs) through the fusion of the N-terminus of ORF7a and a downstream ORF.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.08.20125112", + "rel_abs": "Person-to-person transmission of SARS-CoV-2 virus has triggered a global emergency because of its potential to cause life-threatening Covid-19 disease. By comparison to paucisymptomatic virus clearance by most individuals, Covid-19 has been proposed to reflect insufficient and/or pathologically exaggerated immune responses. Here we identify a consensus peripheral blood immune signature across 63 hospital-treated Covid-19 patients who were otherwise highly heterogeneous. The core signature conspicuously blended adaptive B cell responses typical of virus infection or vaccination with discrete traits hitherto associated with sepsis, including monocyte and dendritic cell dampening, and hyperactivation and depletion of discrete T cell subsets. This blending of immuno-protective and immuno-pathogenic potentials was exemplified by near-universal CXCL10/IP10 upregulation, as occurred in SARS1 and MERS. Moreover, specific parameters including CXCL10/IP10 over-expression, T cell proliferation, and basophil and plasmacytoid dendritic cell depletion correlated, often prognostically, with Covid-19 progression, collectively composing a resource to inform SARS-CoV-2 pathobiology and risk-based patient stratification.", + "rel_num_authors": 48, "rel_authors": [ { - "author_name": "Amin Addetia", - "author_inst": "University of Washington" + "author_name": "Adam G. Laing", + "author_inst": "King's College London, London, UK" }, { - "author_name": "Hong Xie", - "author_inst": "University of Washington" + "author_name": "Anna Lorenc", + "author_inst": "Kings College London" }, { - "author_name": "Pavitra Roychoudhury", - "author_inst": "University of Washington" + "author_name": "Irene Del Molino Del Barrio", + "author_inst": "King's College London, London, UK / UCL Cancer Institute, University College London, London, UK" }, { - "author_name": "Lasata Shrestha", - "author_inst": "University of Washington" + "author_name": "Abhishek Das", + "author_inst": "King's College London, London, UK / London School of Hygiene & Tropical Medicine, London, UK" }, { - "author_name": "Michelle Loprieno", - "author_inst": "University of Washington" + "author_name": "Matthew Fish", + "author_inst": "King's College London, London, UK / Guy's and St Thomas' NHS Foundation Trust, London, UK" }, { - "author_name": "Meei-Li Huang", - "author_inst": "University of Washington" + "author_name": "Leticia Monin", + "author_inst": "The Francis Crick Institute" }, { - "author_name": "Keith Jerome", - "author_inst": "University of Washington" + "author_name": "Miguel Munoz-Ruiz", + "author_inst": "The Francis Crick institute" }, { - "author_name": "Alex Greninger", - "author_inst": "University of Washington" + "author_name": "Duncan Mckenzie", + "author_inst": "The Francis Crick Institute" + }, + { + "author_name": "Thomas Hayday", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Isaac Francos Quijorna", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Shraddha Kamdar", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Magdalene Joseph", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Daniel Davies", + "author_inst": "King's College London, London, UK / Royal Free NHS Foundation Trust, London, UK" + }, + { + "author_name": "Richard Davis", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Aislinn Jennings", + "author_inst": "King's College London, London, UK / Guy's and St Thomas' NHS Foundation Trust, London, UK" + }, + { + "author_name": "Iva Zlatareva", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Pierre Vantourout", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Yin Wu", + "author_inst": "King's College London, London, UK / The Francis Crick Institute, London, UK / UCL Cancer Institute, University College London, London, UK" + }, + { + "author_name": "Vasiliki Sofra", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Florencia Cano", + "author_inst": "The Francis Crick Institute, London, UK" + }, + { + "author_name": "Maria Greco", + "author_inst": "The Francis Crick Institute, London, UK." + }, + { + "author_name": "Efstathios Theodoridis", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Joshua Freedman", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Sarah Gee", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Julie Nuo En, Chan", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Sarah Ryan", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Eva Bugallo Blanco", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Part Peterson", + "author_inst": "Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia" + }, + { + "author_name": "Kai Kisand", + "author_inst": "Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia" + }, + { + "author_name": "Liis Haljasmagi", + "author_inst": "Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia" + }, + { + "author_name": "Lauren Martinez", + "author_inst": "Guy's and St Thomas' NHS Foundation Trust, London, UK" + }, + { + "author_name": "Blair Merrick", + "author_inst": "Guy's and St Thomas NHS Foundation Trust, London, UK" + }, + { + "author_name": "Karen Bisnauthsing", + "author_inst": "Guy's and St Thomas NHS Foundation Trust, London, UK" + }, + { + "author_name": "Kate Brooks", + "author_inst": "Guy's and St Thomas' NHS Foundation Trust, London, UK" + }, + { + "author_name": "Mohammad Ibrahim", + "author_inst": "King's College Hospital NHS Foundation Trust, London, UK" + }, + { + "author_name": "Jeremy Mason", + "author_inst": "The European Bioinformatics Institute (EMBL-EBI) Wellcome Genome Campus, Hinxton, UK." + }, + { + "author_name": "Federico Lopez Gomez", + "author_inst": "The European Bioinformatics Institute (EMBL-EBI) Wellcome Genome Campus, Hinxton, UK" + }, + { + "author_name": "Kola Babalola", + "author_inst": "The European Bioinformatics Institute (EMBL-EBI) Wellcome Genome Campus, Hinxton, UK" + }, + { + "author_name": "Sultan Abdul- Jawad", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "John Cason", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Christine Mant", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Katie Doores", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Jeffrey Seow", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Carl Graham", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Francesca di Rosa", + "author_inst": "Institute of Molecular Biology and Pathology, National Research Council of Italy (CNR), Rome, Italy" + }, + { + "author_name": "Jonathan Edgeworth", + "author_inst": "Guy's and St Thomas' NHS Foundation Trust, London, UK" + }, + { + "author_name": "Manu Shankar Hari", + "author_inst": "King's College London, London, UK" + }, + { + "author_name": "Adrian Hayday", + "author_inst": "King's College London, London, UK / The Francis Crick Institute, London, UK" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1364206,18 +1364442,135 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.06.08.139055", - "rel_title": "Rapid whole genome sequence typing reveals multiple waves of SARS-CoV-2 spread", + "rel_doi": "10.1101/2020.06.05.098590", + "rel_title": "Coronavirus testing indicates transmission risk increases along wildlife supply chains for human consumption in Viet Nam, 2013-2014", "rel_date": "2020-06-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.08.139055", - "rel_abs": "As the pandemic SARS-CoV-2 virus has spread globally its genome has diversified to an extent that distinct clones can now be recognized, tracked, and traced. Identifying clonal groups allows for assessment of geographic spread, transmission events, and identification of new or emerging strains that may be more virulent or more transmissible. Here we present a rapid, whole genome, allele-based method (GNUVID) for assigning sequence types to sequenced isolates of SARS-CoV-2 sequences. This sequence typing scheme can be updated with new genomic information extremely rapidly, making our technique continually adaptable as databases grow. We show that our method is consistent with phylogeny and recovers waves of expansion and replacement of sequence types/clonal complexes in different geographical locations.\n\nGNUVID is available as a command line application (https://github.com/ahmedmagds/GNUVID).", - "rel_num_authors": 0, - "rel_authors": null, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.05.098590", + "rel_abs": "Outbreaks of emerging coronaviruses in the past two decades and the current pandemic of a novel coronavirus (SARS-CoV-2) that emerged in China highlight the importance of this viral family as a zoonotic public health threat. To gain a better understanding of coronavirus presence and diversity in wildlife at wildlife-human interfaces in three southern provinces in Viet Nam 2013-2014, we used consensus Polymerase Chain Reactions to detect coronavirus sequences. In comparison to previous studies, we observed high proportions of positive samples among field rats (34.0%, 239/702) destined for human consumption and insectivorous bats in guano farms (74.8%, 234/313) adjacent to human dwellings. Most notably among field rats, the odds of coronavirus RNA detection significantly increased along the supply chain from field rats sold by traders (reference group; 20.7% positivity, 39/188) by a factor of 2.2 for field rats sold in large markets (32.0%, 116/363) and 10.0 for field rats sold and served in restaurants (55.6%, 84/151). Coronaviruses were detected in the majority of wildlife farms (60.7%, 17/28) and in the Malayan porcupines (6.0%, 20/331) and bamboo rats (6.3%, 6/96) that are farmed. We identified six known coronaviruses in bats and rodents, clustered in three Coronaviridae genera, including the Alpha-, Beta-, and Gammacoronaviruses. Our analysis also suggested either mixing of animal excreta in the environment or interspecies transmission of coronaviruses, as both bat and avian coronaviruses were detected in rodent feces in the trade. The mixing of multiple coronaviruses, and their apparent amplification along the wildlife supply chain into restaurants, suggests maximal risk for end consumers and likely underpins the mechanisms of zoonotic spillover to people.", + "rel_num_authors": 29, + "rel_authors": [ + { + "author_name": "Nguyen Quynh Huong", + "author_inst": "Wildlife Conservation Society, Viet Nam Country Program, Ha Noi, Viet Nam" + }, + { + "author_name": "Nguyen Thi Thanh Nga", + "author_inst": "Wildlife Conservation Society, Viet Nam Country Program, Ha Noi, Viet Nam" + }, + { + "author_name": "Nguyen Van Long", + "author_inst": "Department of Animal Health, Ministry of Agricultural and Rural Development of Viet Nam, Ha Noi, Viet Nam" + }, + { + "author_name": "Bach Duc Luu", + "author_inst": "Department of Animal Health, Ministry of Agricultural and Rural Development of Viet Nam, Ha Noi, Viet Nam" + }, + { + "author_name": "Alice Latinne", + "author_inst": "Wildlife Conservation Society, Viet Nam Country Program, Ha Noi, Viet Nam; Wildlife Conservation Society, Health Program, Bronx, New York, United States of Amer" + }, + { + "author_name": "Mathieu Pruvot", + "author_inst": "Wildlife Conservation Society, Health Program, Bronx, New York, United States of America" + }, + { + "author_name": "Nguyen Thanh Phuong", + "author_inst": "Regional Animal Health Office No. 6, Ho Chi Minh City, Viet Nam" + }, + { + "author_name": "Le Tin Vinh Quang", + "author_inst": "Regional Animal Health Office No. 6, Ho Chi Minh City, Viet Nam" + }, + { + "author_name": "Vo Van Hung", + "author_inst": "Regional Animal Health Office No. 6, Ho Chi Minh City, Viet Nam" + }, + { + "author_name": "Nguyen Thi Lan", + "author_inst": "Viet Nam National University of Agriculture, Ha Noi, Viet Nam" + }, + { + "author_name": "Nguyen Thi Hoa", + "author_inst": "Viet Nam National University of Agriculture, Ha Noi, Viet Nam" + }, + { + "author_name": "Phan Quang Minh", + "author_inst": "Department of Animal Health, Ministry of Agricultural and Rural Development of Viet Nam, Ha Noi, Viet Nam" + }, + { + "author_name": "Nguyen Thi Diep", + "author_inst": "Department of Animal Health, Ministry of Agricultural and Rural Development of Viet Nam, Ha Noi, Viet Nam" + }, + { + "author_name": "Nguyen Tung", + "author_inst": "Department of Animal Health, Ministry of Agricultural and Rural Development of Viet Nam, Ha Noi, Viet Nam" + }, + { + "author_name": "Van Dang Ky", + "author_inst": "Department of Animal Health, Ministry of Agricultural and Rural Development of Viet Nam, Ha Noi, Viet Nam; Current address: The Animal Asia Foundation Viet Nam," + }, + { + "author_name": "Scott I. Roberton", + "author_inst": "Wildlife Conservation Society, Viet Nam Country Program, Ha Noi, Viet Nam" + }, + { + "author_name": "Hoang Bich Thuy", + "author_inst": "Wildlife Conservation Society, Viet Nam Country Program, Ha Noi, Viet Nam" + }, + { + "author_name": "Nguyen Van Long", + "author_inst": "Wildlife Conservation Society, Viet Nam Country Program, Ha Noi, Viet Nam" + }, + { + "author_name": "Martin Gilbert", + "author_inst": "Wildlife Conservation Society, Health Program, Bronx, New York, United States of America; Current address: Cornell Wildlife Health Center, College of Veterinary" + }, + { + "author_name": "Leanne Wicker", + "author_inst": "Wildlife Conservation Society, Viet Nam Country Program, Ha Noi, Viet Nam; Current address: Australian Wildlife Health Centre, Healesville Sanctuary, Zoos Victo" + }, + { + "author_name": "Jonna A. K. Mazet", + "author_inst": "One Health Institute, School of Veterinary Medicine, University of California, Davis, California, United States of America" + }, + { + "author_name": "Christine Kreuder Johnson", + "author_inst": "One Health Institute, School of Veterinary Medicine, University of California, Davis, California, United States of America" + }, + { + "author_name": "Tracey Goldstein", + "author_inst": "One Health Institute, School of Veterinary Medicine, University of California, Davis, California, United States of America" + }, + { + "author_name": "Alex Tremeau-Bravard", + "author_inst": "One Health Institute, School of Veterinary Medicine, University of California, Davis, California, United States of America" + }, + { + "author_name": "Victoria Ontiveros", + "author_inst": "One Health Institute, School of Veterinary Medicine, University of California, Davis, California, United States of America" + }, + { + "author_name": "Damien O. Joly", + "author_inst": "Wildlife Conservation Society, Health Program, Bronx, New York, United States of America; Current address: British Columbia Ministry of Environment and Climate " + }, + { + "author_name": "Chris Walzer", + "author_inst": "Wildlife Conservation Society, Health Program, Bronx, New York, United States of America; Research Institute of Wildlife Ecology, University of Veterinary Medic" + }, + { + "author_name": "Amanda E. Fine", + "author_inst": "Wildlife Conservation Society, Viet Nam Country Program, Ha Noi, Viet Nam" + }, + { + "author_name": "Sarah Helen Olson", + "author_inst": "Wildlife Conservation Society, Health Program, Bronx, New York, United States of America" + } + ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "genomics" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.06.08.139477", @@ -1366083,25 +1366436,29 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2020.06.08.20125153", - "rel_title": "Evidence for ethnic inequalities in mortality related to COVID-19 infections: Findings from an ecological analysis of England and Wales", + "rel_doi": "10.1101/2020.06.08.20125393", + "rel_title": "Controlling the Spread of COVID-19: Optimal Control Analysis", "rel_date": "2020-06-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.08.20125153", - "rel_abs": "BackgroundIn the absence of direct data on ethnic inequalities in COVID-19 related mortality in the UK, we examine the relationship between ethnic composition of an area and rate of mortality in the area.\n\nMethodsEcological analysis using COVID-19 related mortality rates occurring by 24th April 2020, and ethnic composition of the population, across local authorities in England and Wales. Account is taken of age, population density, area deprivation and pollution.\n\nResultsFor every 1% rise in proportion of the population who are ethnic minority, COVID-19 related deaths increased by 5{middle dot}10 (3{middle dot}99 to 6{middle dot}21) per million. This rise is present for each ethnic minority category examined. The size of this increase is a little reduced in a fully adjusted model, suggesting that some of the association results from ethnic minority people living in more densely populated, more polluted and more deprived areas.\n\nThis estimate suggests that the average England and Wales COVID-19 related death rate would rise by 25% in a local authority with twice the average number of ethnic minority people.\n\nDiscussionWe find clear evidence that rates of COVID-19 related mortality within a local authority increase as the proportion of the population who are ethnic minority increases. We suggest that this is a consequence of social and economic inequalities, including among key workers, driven by entrenched structural and institutional racism and racial discrimination. We argue that these factors should be central to any investigation of ethnic inequalities in COVID-19 outcomes.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.08.20125393", + "rel_abs": "Coronavirus disease 2019 (COVID-19) is a disease caused by Severe acute respiratory syndrome coronavirus 2 (SARS CoV-2). It was declared on March 11, 2020, by the World Health Organization as pandemic disease. The disease has neither approved medicine nor vaccine and has made government and scholars search for drastic measures in combating the pandemic. Regrettably, the spread of the virus and mortality due to COVID-19 has continued to increase daily. Hence, it is imperative to control the spread of the disease particularly using non-pharmacological strategies such as quarantine, isolation and public health education. This work studied the effect of these different control strategies as time-dependent interventions using mathematical modeling and optimal control approach to ascertain their contributions in the dynamic transmission of COVID-19. The model was proven to have an invariant region and was well-posed. The basic reproduction number was computed with and without interventions and was used to carry out the sensitivity analysis that identified the critical parameters contributing to the spread of COVID-19. The optimal control analysis was carried out using the Pontryagins maximum principle to figure out the optimal strategy necessary to curtail the disease. The findings of the optimal control analysis and numerical simulations revealed that time-dependent interventions reduced the number of exposed and infected individuals compared to time-independent interventions. These interventions were time-bound and best implemented within the first 100 days of the outbreak. Again, the combined implementation of only two of these interventions produced a good result in reducing infection in the population, while the combined implementation of all three interventions performed better, even though zero infection was not achieved in the population. This implied that multiple interventions need to be deployed early in order to the virus to the barest minimum.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "James Nazroo", - "author_inst": "University of Manchester" + "author_name": "Chinwendu Emilian Madubueze", + "author_inst": "University of Agriculture, Makurdi" }, { - "author_name": "Laia Becares", - "author_inst": "University of Sussex" + "author_name": "Dachollom Sambo", + "author_inst": "Akanu Ibiam Federal Polytechnic, Unwana, P.M.B. 1007 Afikpo, Ebonyi State, Nigeria." + }, + { + "author_name": "Isaac O. Onwubuya", + "author_inst": "Airforce Institute of Technology, Kaduna, Nigeria" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1367353,123 +1367710,43 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.06.05.20122622", - "rel_title": "Tocilizumab as a Therapeutic Agent for Critically Ill Patients Infected with SARS-CoV-2", + "rel_doi": "10.1101/2020.06.06.20124024", + "rel_title": "Studying the effect of lockdown using epidemiological modelling of COVID-19 and a quantum computational approach using the Ising spin interaction", "rel_date": "2020-06-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.05.20122622", - "rel_abs": "BackgroundTocilizumab is an IL-6 receptor antagonist with the ability to suppress the cytokine storm in critically ill patients infected with SARS-CoV-2.\n\nMethodsWe evaluated patients treated with tocilizumab for a SARS-CoV-2 infection who were admitted between 3/13/20 and 4/16/20. This was a multi-center study with data collected by chart review both retrospectively and concurrently. Parameters evaluated included age, sex, race, use of mechanical ventilation (MV), usage of steroids and vasopressors, inflammatory markers, and comorbidities. Early dosing was defined as a tocilizumab dose administered prior to or within one (1) day of intubation. Late dosing was defined as a dose administered greater than one (1) day after intubation. In the absence of mechanical ventilation, the timing of the dose was related to the patients date of admission only.\n\nResultsWe evaluated 145 patients. The average age was 58.1 years, 64% were male, 68.3% had comorbidities, and 60% received steroid therapy. Disposition of patients was 48.3% discharged and 29.3% expired, of which 43.9% were African American. Mechanical ventilation was required in 55.9%, of which 34.5% expired. Avoidance of MV (p value = 0.002) and increased survival (p value < 0.001) was statistically associated with early dosing.\n\nConclusionsTocilizumab therapy was effective at decreasing mortality and should be instituted early in the management of critically ill COVID-19 patients.\n\nSummaryUtilizing tocilizumab early in the treatment course of critically ill patients with COVID-19 resulted in significant decreases in mortality and the avoidance of mechanical ventilation.", - "rel_num_authors": 26, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.06.20124024", + "rel_abs": "COVID-19 is a respiratory tract infection that can range from being mild to fatal. In India, the countrywide lockdown has been imposed since 24th march, 2020, and has got multiple extensions with different guidelines for each phase. Among various models of epidemiology, we use the SIR(D) model to analyze the extent to which this multi-phased lockdown has been active in flattening the curve and lower the threat. Analyzing the effect of lockdown on the infection may give us a better insight into the evolution of epidemic while implementing the quarantine procedures as well as improving the healthcare facilities. For accurate modelling, incorporating various parameters along with sophisticated computational facilities, are required. Parallel to SIRD modelling, we tend to compare it with the Ising model and derive a quantum circuit that incorporates the rate of infection and rate of recovery, etc as its parameters. The probabilistic plots obtained from the circuit qualitatively resemble the shape of the curve for the spread of Coronavirus. We also demonstrate how the curve flattens when the lockdown is imposed. This kind of quantum computational approach can be useful in reducing space and time complexities of a huge amount of information related to the epidemic.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Russell Petrak", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Nathan Skorodin", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Nicholas Van Hise", - "author_inst": "Metro Infectious Disease Consultants" + "author_name": "Anshuman Padhi", + "author_inst": "National Institute of Science Education and Research, Bhubaneswar" }, { - "author_name": "Robert Fliegelman", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Jonathan Pinsky", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Vishal Didwania", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Michael Anderson", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Melina Diaz", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Kairav Shah", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Vishnu Chundi", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "David Hines", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Brian Harting", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Kamo Sidwha", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Brian Yu", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Paul Brune", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Anjum Owaisi", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "David Beezhold", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Joseph Kent", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Dana Vais", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Alice Han", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Neethi Gowda", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Nishi Sahgal", - "author_inst": "Metro Infectious Disease Consultants" + "author_name": "Sudev Pradhan", + "author_inst": "Indian Institute of Science Education and Research, Berhampur" }, { - "author_name": "Jan Silverman", - "author_inst": "Metro Infectious Disease Consultants" + "author_name": "Pragna Paramita Sahoo", + "author_inst": "Indian Institute of Science Education and Research, Berhmapur" }, { - "author_name": "Jonathan Stake", - "author_inst": "Metro Infectious Disease Consultants" + "author_name": "Kalyani Suresh", + "author_inst": "University of Mysore, Mysuru" }, { - "author_name": "Jenie Nepomuceno", - "author_inst": "Metro Infectious Disease Consultants" + "author_name": "Bikash Kumar Behera", + "author_inst": "Indian Institute of Science Education and Research, Kolkata" }, { - "author_name": "Renuka Heddurshetti", - "author_inst": "Metro Infectious Disease Consultants" + "author_name": "Prasanta Kumar Panigrahi", + "author_inst": "Indian Institute of Science Education and Research, Kolkata" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.06.06.20124149", @@ -1369279,27 +1369556,23 @@ "category": "nursing" }, { - "rel_doi": "10.1101/2020.06.05.20123356", - "rel_title": "On the Spread of Coronavirus Infection. A Mechanistic Model to Rate Strategies for Disease Management", + "rel_doi": "10.1101/2020.06.05.20123380", + "rel_title": "COVID 19 healthcare facility demand forecasts for rural residents", "rel_date": "2020-06-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.05.20123356", - "rel_abs": "Effective policy making based on ongoing COVID-19 pandemic is an urgent issue. We present a mathematical model describing the viral infection dynamics, which reveals two transmissibility parameters influenced by the management strategies in the area for control of the current pandemic. The parameters readily yield the peak infection rate and means for flattening the curve. Model parameters are shown to be correlated to different management strategies by employing machine learning, enabling comparison of different strategies and suggesting timely alterations. Treatment of population data with the model shows that restricted non-essential business closure, school closing and strictures on mass gathering influence the spread of infection. While a rational strategy for initiation of an economic reboot would call for a wider perspective of the local economics, the model can speculate on its timing based on the status of the infection as reflected by its potential for an unacceptably renewed viral onslaught.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.05.20123380", + "rel_abs": "One of the main challenges in dealing with the current COVID 19 pandemic is how to fulfill the healthcare facility demands especially for the residents living in the rural areas that have restricted healthcare access. Correspondingly, this study aims to record the daily COVID 19 cases and continue with the forecasting of the average daily demand (ADD) of healthcare facilities including beds, ICUs, and ventilators using ARIMA model. The forecasts were made for 3 rural populations located in the southern Amazon. The model shows that the healthcare ADD was different in each population. Likewise, the model forecasts that in a rural population that has the highest daily case with projected average cases equal to 67 cases/day (95%CI: 24, 110), that population has to fulfill healthcare ADD consisting of 57 beds/day (95%CI: 21, 93), 8 ICUs/day (95%CI: 2, 14), and 2 ventilators/day (95%CI: 2, 3). To conclude, the ARIMA model has addressed critical questions about ADD for beds, ICUs, and ventilators for rural residents. This ARIMA model based healthcare plan will hopefully provide versatile tool to improve healthcare resource allocations.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Shiyan Wang", - "author_inst": "Purdue University" - }, - { - "author_name": "Doraiswami Ramkrishna", - "author_inst": "Purdue University" + "author_name": "Andrio Adwibowo", + "author_inst": "University of Indonesia" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "health systems and quality improvement" }, { "rel_doi": "10.1101/2020.06.05.20123117", @@ -1370497,29 +1370770,57 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.05.20123133", - "rel_title": "Pollen Explains Flu-Like and COVID-19 Seasonality", + "rel_doi": "10.1101/2020.06.05.20123372", + "rel_title": "Containment of future waves of COVID-19: simulating the impact of different policies and testing capacities for contact tracing, testing, and isolation", "rel_date": "2020-06-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.05.20123133", - "rel_abs": "Current models for flu-like epidemics insufficiently explain multi-cycle seasonality. Meteorological factors alone, including the associated behavior, do not predict seasonality, given substantial climate differences between countries that are subject to flu-like epidemics or COVID-19. Pollen is documented to be allergenic, it plays a role in immuno-activation and defense against respiratory viruses, and seems to create a bio-aerosol that lowers the reproduction number of flu-like viruses. Therefore, we hypothesize that pollen may explain the seasonality of flu-like epidemics, including COVID-19, in combination with meteorological variables.\n\nWe have tested the Pollen-Flu Seasonality Theory for 2016-2020 flu-like seasons, including COVID-19, in the Netherlands, with its 17.4 million inhabitants. We combined changes in flu-like incidence per 100K/Dutch residents (code: ILI) with pollen concentrations and meteorological data. Finally, a predictive model was tested using pollen and meteorological threshold values, inversely correlated to flu-like incidence.\n\nWe found a highly significant inverse correlation of r(224)= -0.41 (p < 0.001) between pollen and changes in flu-like incidence, corrected for the incubation period. The correlation was stronger after taking into account the incubation time. We found that our predictive model has the highest inverse correlation with changes in flu-like incidence of r(222) = -0.48 (p < 0.001) when average thresholds of 610 total pollen grains/m3, 120 allergenic pollen grains/m3, and a solar radiation of 510 J/cm2 are passed. The passing of at least the pollen thresholds, preludes the beginning and end of flu-like seasons. Solar radiation is a co-inhibitor of flu-like incidence, while temperature makes no difference. However, higher relative humidity increases with flu-like incidence.\n\nWe conclude that pollen is a predictor of the inverse seasonality of flu-like epidemics, including COVID-19, and that solar radiation is a co-inhibitor.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.05.20123372", + "rel_abs": "We used multi-agent simulations to estimate the testing capacity required to find and isolate a number of infections sufficient to break the chain of transmission of SARS-CoV-2. Depending on the mitigation policies in place, a daily capacity between 0.7 to 3.6 tests per thousand was required to contain the disease. However, if contact tracing and testing efficacy dropped below 60% (e.g. due to false negatives or reduced tracing capability), the number of infections kept growing exponentially, irrespective of any testing capacity. Under these conditions, the populations geographical distribution and travel behaviour could inform sampling policies to aid a successful containment.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Martijn J Hoogeveen", - "author_inst": "Open University Netherlands" + "author_name": "Vincenzo G Fiore", + "author_inst": "Icahn School of Medicine at Mount Sinai, Department of Psychiatry" }, { - "author_name": "Eric CM Van Gorp", - "author_inst": "Erasmus Medical Center" + "author_name": "Nicholas DeFelice", + "author_inst": "Icahn School of Medicine at Mount Sinai, Department of Environmental Medicine and Public Health" }, { - "author_name": "Ellen K Hoogeveen", - "author_inst": "Jeroen Bosch Ziekenhuis" + "author_name": "Benjamin S Glicksberg", + "author_inst": "Icahn School of Medicine at Mount Sinai, Department of Genetics and Genomic Sciences" + }, + { + "author_name": "Ofer Perl", + "author_inst": "Icahn School of Medicine at Mount Sinai, Department of Psychiatry" + }, + { + "author_name": "Anastasia Shuster", + "author_inst": "Icahn School of Medicine at Mount Sinai, Department of Psychiatry" + }, + { + "author_name": "Kaustubh Kulkarni", + "author_inst": "Icahn School of Medicine at Mount Sinai, Department of Psychiatry" + }, + { + "author_name": "Madeline O'Brien", + "author_inst": "Icahn School of Medicine at Mount Sinai, Department of Psychiatry" + }, + { + "author_name": "M. Andrea Pisauro", + "author_inst": "Wellcome Centre for Integrative Neuroimaging, University of Oxford, Department of Experimental Psychology" + }, + { + "author_name": "Dongil Chung", + "author_inst": "Ulsan National Institute of Science and Technology, Department of Human Factors Engineering" + }, + { + "author_name": "Xiaosi Gu", + "author_inst": "Icahn School of Medicine at Mount Sinai, Department of Psychiatry" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1372491,57 +1372792,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.04.20109306", - "rel_title": "Host response-based screening to identify undiagnosed cases of COVID-19and expand testing capacity", + "rel_doi": "10.1101/2020.06.03.20121624", + "rel_title": "Association of Bacille Calmette-Guerin (BCG), Adult Pneumococcal and Adult Seasonal Influenza Vaccines with Covid-19 Adjusted Mortality Rates in Level 4 European countries", "rel_date": "2020-06-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.04.20109306", - "rel_abs": "The COVID-19 pandemic has created unprecedented challenges in diagnostic testing. At the beginning of the epidemic, a confluence of factors resulted in delayed deployment of PCR-based diagnostic tests, resulting in lack of testing of individuals with symptoms of the disease. Although these tests are now more widely available, it is estimated that a three- to ten-fold increase in testing capacity will be required to ensure adequate surveillance as communities reopen1. In response to these challenges, we evaluated potential roles of host response-based screening in the diagnosis of COVID-19. Previous work from our group showed that the nasopharyngeal (NP) level of CXCL10, a protein produced as part of the host response to viral infection, is a sensitive predictor of respiratory virus infection across a wide spectrum of viruses2. Here, we show that NP CXCL10 is elevated during SARS-CoV-2 infection and use a CXCL10-based screening strategy to identify four undiagnosed cases of COVID-19 in Connecticut in early March. In a second set of samples tested at the Yale New Haven Hospital, we show that NP CXCL10 had excellent performance as a rule-out test (NPV 0.99, 95% C.I. 0.985-0.997). Our results demonstrate how biomarker-based screening could be used to leverage existing PCR testing capacity to rapidly enable widespread testing for COVID-19.\n\nOne Sentence SummaryWe describe a host-response based screening strategy to identify undiagnosed cases of COVID-19 and to expand capacity for PCR-based testing.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.03.20121624", + "rel_abs": "IntroductionNon-specific effects of vaccines have gained increasing interest during the Covid-19 pandemic. In particular, population use of BCG vaccine has been associated with improved outcomes. This study sought to determine the association of population use of BCG, adult pneumococcal and adult seasonal influenza vaccination with Covid-19 mortality when adjusted for a number of confounding variables.\n\nMethodsUsing publicly available data, mortality adjusted for the timeframe of crisis, population size and population characteristics was calculated. The primary analysis was the relationship between each of the day 15 and day 30 standardised mortality rates and BCG, adult pneumococcal and influenza vaccination scores using unadjusted measures and with adjustment for population structure and case fatality rates. Secondary analyses were measures of case increases and mortality increases from day 15 to day 30 for each of the relative vaccination scores. Finally, we also analysed the peak Z score reflecting increases in total mortality from historical averages reported by EuroMOMO (Euromomo.eu),\n\nResultsFollowing adjustment for the effects of population size, median age, population density, the proportion of population living in an urban setting, life-expectancy, the elderly dependency ratio (or proportion over 65 years), net migration, days from day 1 to lockdown and case-fatality rate, only BCG vaccination score remained significantly associated with Covid-19 mortality at day 30. In the best fit model, BCG vaccination score was associated with a 64% reduction in log(10) mortality per 10 million population (OR 0.362 reduction [95% CI 0.188 to 0.698]), following adjustment for population size, median age, density, urbanization, elderly dependency ratio, days to lockdown, yearly migration and case fatality rate.\n\nConclusionBCG vaccine was associated with reduced mortality rates in level 4 countries while adult pneumococcal and adult seasonal influenza vaccines were not when adjusted for a number of confounding variables. A number of trials are ongoing to determine if BCG is protective against severe Covid-19 infection.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Nagarjuna R. Cheemarla", - "author_inst": "Yale School of Medicine" - }, - { - "author_name": "Anderson F. Brito", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Joseph R. Fauver", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Tara Alpert", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Chantal B.F. Vogels", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Saad B. Omer", - "author_inst": "Yale Institute of Global Health" - }, - { - "author_name": "Albert Ko", - "author_inst": "Yale University School of Public Health" - }, - { - "author_name": "Nathan D. Grubaugh", - "author_inst": "Yale School of Public Health" + "author_name": "Joe Gallagher", + "author_inst": "University College Dublin" }, { - "author_name": "Marie L. Landry", - "author_inst": "Yale School of Medicine" + "author_name": "Chris Watson", + "author_inst": "Queens University Belfast" }, { - "author_name": "Ellen F. Foxman", - "author_inst": "Yale School of Medicine" + "author_name": "Mark Ledwidge", + "author_inst": "University College Dublin" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1373789,99 +1374062,31 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2020.06.04.20121855", - "rel_title": "Diet and physical activity during the COVID-19 lockdown period (March-May 2020): results from the French NutriNet-Sante cohort study", + "rel_doi": "10.1101/2020.06.04.20120725", + "rel_title": "Covid-19 trajectories: Monitoring pandemic in the worldwide context", "rel_date": "2020-06-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.04.20121855", - "rel_abs": "BackgroundSince December 2019, the coronavirus disease (COVID-19) has massively spread, with overwhelming of health care systems and numerous deaths worldwide. To remedy this, several countries, including France, have taken strict lockdown measures, requiring the closure of all but essential places. This unprecedented disruption of daily routines has a strong potential for disrupting nutritional behaviours. Nutrition being one of the main modifiable risk factors for chronic disease risk, this may have further consequences for public health. Our objective was therefore to describe nutritional behaviours during the lockdown period and to put them in light of individual characteristics.\n\nMethods37,252 French adults from the web-based NutriNet-Sante cohort filled lockdown-specific questionnaires in April-May 2020 (nutritional behaviours, body weight, physical activity, 24h-dietary records). Nutritional behaviours were compared before and during lockdown using Student paired t-tests and associated to individual characteristics using multivariable logistic or linear regression models. Clusters of nutritional behaviours were derived from multiple correspondence analysis and ascending hierarchical classification.\n\nResultsDuring the lockdown, trends for unfavourable nutritional behaviours were observed: weight gain (for 35%; +1.8kg on average), decreased physical activity (53%), increased sedentary time (63%), increased snacking, decreased consumption of fresh food products (especially fruit and fish), increased consumption of sweets, biscuits and cakes. Yet, opposite trends were also observed: weight loss (for 23%, -2kg on average), increased home-made cooking (40%), increased physical activity (19%). These behavioural trends related to sociodemographic and economic position, professional situation during the lockdown (teleworking or not), initial weight status, having children at home, anxiety and depressive symptoms, as well as diet quality before the lockdown. Modifications of nutritional practices mainly related to routine change, food supply, emotional reasons but also to voluntary changes to adjust to the current situation.\n\nConclusionThese results suggest that the lockdown led, in a substantial part of the population, to unhealthy nutritional behaviours that, if maintained in the long term, may increase the nutrition-related burden of disease and also impact immunity. Yet, the lockdown situation also created an opportunity for some people to improve their nutritional behaviours, with high stakes to understand the leverages to put these on a long-term footing.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.04.20120725", + "rel_abs": "BackgroundCovid-19 pandemic is developing worldwide with common dynamics but also with partly marked differences between regions and countries. They are not completely understood, but presumably, provide one clue to find ways to mitigate epidemics until exit strategies to its eradication become available.\n\nMethodWe provide a monitoring tool available at www.izbi.de. It enables inspection of the dynamic state of the epidemic in 187 countries using trajectories. They visualize transmission and removal rates of the epidemic and this way bridge epi-curve tracking with modelling approaches.\n\nResultsExamples were provided which characterize state of epidemic in different regions of the world in terms of fast and slow growing and decaying regimes and estimate associated rate factors. Basic spread of the disease associates with transmission between two individuals every two-three days on the average. Non-pharmaceutical interventions decrease this value to up to ten days where complete lock down measures are required to stop the epidemic. Comparison of trajectories revealed marked differences between the countries regarding efficiency of measures taken against the epidemic. Trajectories also reveal marked country-specific dynamics of recovery and death rates.\n\nConclusionsThe results presented refer to the pandemic state in May 2020 and can serve as working instruction for timely monitoring using the interactive monitoring tool as a sort of seismometer for the evaluation of the state of epidemic, e.g., the possible effect of measures taken in both, lock-down and lock-up directions. Comparison of trajectories between countries and regions will support developing hypotheses and models to better understand regional differences of dynamics of Covid-19.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Melanie Deschasaux-Tanguy", - "author_inst": "Sorbonne Paris Nord University, Inserm, Inrae, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of P" - }, - { - "author_name": "Nathalie Druesne-Pecollo", - "author_inst": "Sorbonne Paris Nord University, Inserm, Inrae, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of P" - }, - { - "author_name": "Younes Esseddik", - "author_inst": "Sorbonne Paris Nord University, Inserm, Inrae, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of P" - }, - { - "author_name": "Fabien Szabo de Edelenyi", - "author_inst": "Sorbonne Paris Nord University, Inserm, Inrae, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of P" - }, - { - "author_name": "Benjamin Alles", - "author_inst": "Sorbonne Paris Nord University, Inserm, Inrae, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of P" - }, - { - "author_name": "Valentina A Andreeva", - "author_inst": "Sorbonne Paris Nord University, Inserm, Inrae, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of P" - }, - { - "author_name": "Julia Baudry", - "author_inst": "Sorbonne Paris Nord University, Inserm, Inrae, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of P" - }, - { - "author_name": "Helene Charreire", - "author_inst": "Paris-Est University, LabUrba, UPEC" - }, - { - "author_name": "Valerie Deschamps", - "author_inst": "Nutritional Surveillance and Epidemiology Team (ESEN), French Public Health Agency, Sorbonne Paris Nord University, Epidemiology and Statistics Research Center," - }, - { - "author_name": "Manon Egnell", - "author_inst": "Sorbonne Paris Nord University, Inserm, Inrae, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of P" - }, - { - "author_name": "Leopold K Fezeu", - "author_inst": "Sorbonne Paris Nord University, Inserm, Inrae, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of P" - }, - { - "author_name": "Pilar Galan", - "author_inst": "Sorbonne Paris Nord University, Inserm, Inrae, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of P" - }, - { - "author_name": "Chantal Julia", - "author_inst": "Sorbonne Paris Nord University, Inserm, Inrae, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of P" - }, - { - "author_name": "Emmanuelle Kesse-Guyot", - "author_inst": "Sorbonne Paris Nord University, Inserm, Inrae, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of P" - }, - { - "author_name": "Paule Latino-Martel", - "author_inst": "Sorbonne Paris Nord University, Inserm, Inrae, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of P" - }, - { - "author_name": "Jean-Michel Oppert", - "author_inst": "Department of Nutrition, Institute of Cardiometabolism and Nutrition, Sorbonne University, Pitie-Salpetriere Hospital" - }, - { - "author_name": "Sandrine Peneau", - "author_inst": "Sorbonne Paris Nord University, Inserm, Inrae, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of P" - }, - { - "author_name": "Charlotte Verdot", - "author_inst": "Nutritional Surveillance and Epidemiology Team (ESEN), French Public Health Agency, Sorbonne Paris Nord University, Epidemiology and Statistics Research Center," + "author_name": "Henry Loeffler-Wirth", + "author_inst": "University of Leipzig" }, { - "author_name": "Serge Hercberg", - "author_inst": "Sorbonne Paris Nord University, Inserm, Inrae, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of P" + "author_name": "Maria Schmidt", + "author_inst": "University of Leipzig" }, { - "author_name": "Mathilde Touvier", - "author_inst": "Sorbonne Paris Nord University, Inserm, Inrae, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of P" + "author_name": "Hans Binder", + "author_inst": "University of Leipzig" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "nutrition" + "category": "health informatics" }, { "rel_doi": "10.1101/2020.06.03.20121590", @@ -1375978,43 +1376183,63 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.06.05.136861", - "rel_title": "Insights on cross-species transmission of SARS-CoV-2 from structural modeling", + "rel_doi": "10.1101/2020.06.04.20122192", + "rel_title": "Understanding the impact of the COVID-19 pandemic on well-being and virtual care for people living with dementia and care partners living in the community", "rel_date": "2020-06-05", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.05.136861", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the ongoing global pandemic that has infected more than 14 million people in more than 180 countries worldwide. Like other coronaviruses, SARS-CoV-2 is thought to have been transmitted to humans from wild animals. Given the scale and widespread geographical distribution of the current pandemic, the question emerges whether human-to-animal transmission is possible and if so, which animal species are most at risk. Here, we investigated the structural properties of several ACE2 orthologs bound to the SARS-CoV-2 spike protein. We found that species known not to be susceptible to SARS-CoV-2 infection have non-conservative mutations in several ACE2 amino acid residues that disrupt key polar and charged contacts with the viral spike protein. Our models also predict affinity-enhancing mutations that could be used to design ACE2 variants for therapeutic purposes. Finally, our study provides a blueprint for modeling viral-host protein interactions and highlights several important considerations when designing these computational studies and analyzing their results.", - "rel_num_authors": 6, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.04.20122192", + "rel_abs": "The COVID-19 pandemic has necessitated public health measures that have impacted the provision of care for people living with dementia and their families. Additionally, the isolation that results from social distancing may be harming well-being for families, as formal and informal supports become less accessible. For those with living with dementia and experiencing agitation, social distancing may be even harder to maintain, or social distancing could potentially aggravate dementia-related neuropsychiatric symptoms. To understand the lived experience of social and physical distancing during the COVID-19 pandemic in Canada we remotely interviewed 21 participants who normally attend a dementia specialty clinic in Calgary, Alberta, during a period where essential businesses were closed and healthcare had abruptly transitioned to telemedicine. The impacts of the public health measures in response to the pandemic emerged in three main categories of experience: 1) personal; 2) health services; and 3) health status (of both person living with dementia and care partner). This in-depth understanding of the needs and experiences of the pandemic for people living with dementia suggests that innovative means are urgently needed to facilitate provision of remote medicine and also social interaction and integration.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Jo\u00e3o PGLM Rodrigues", - "author_inst": "Department of Structural Biology - Stanford University School of Medicine" + "author_name": "Pamela Roach", + "author_inst": "University of Calgary" }, { - "author_name": "Susana Barrera-Vilarmau", - "author_inst": "Institute of Advanced Chemistry of Catalonia (IQAC) - CSIC" + "author_name": "Angela Zwiers", + "author_inst": "University of Calgary" }, { - "author_name": "Jo\u00e3o MC Teixeira", - "author_inst": "Hospital for Sick Children, Toronto" + "author_name": "Emily Cox", + "author_inst": "University of Calgary" }, { - "author_name": "Elizabeth Seckel", - "author_inst": "Department of Obstetrics and Gynecology, Stanford University School of Medicine" + "author_name": "Karyn Fischer", + "author_inst": "University of Calgary" }, { - "author_name": "Panagiotis L Kastritis", - "author_inst": "ZIK HALOMEM & Institute of Biochemistry and Biotechnology, Martin Luther University Halle-Wittenberg" + "author_name": "Anna Charlton", + "author_inst": "University of Calgary" }, { - "author_name": "Michael Levitt", - "author_inst": "Department of Structural Biology, Stanford University School of Medicine" + "author_name": "Colin B Josephson", + "author_inst": "University of Calgary" + }, + { + "author_name": "Scott B Patten", + "author_inst": "University of Calgary" + }, + { + "author_name": "Dallas Seitz", + "author_inst": "University of Calgary" + }, + { + "author_name": "Zahinoor Ismail", + "author_inst": "University of Calgary" + }, + { + "author_name": "Eric E Smith", + "author_inst": "University of Calgary" + }, + { + "author_name": "- Prompt Collaborators", + "author_inst": "" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "bioinformatics" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "neurology" }, { "rel_doi": "10.1101/2020.06.04.20122846", @@ -1377296,49 +1377521,53 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.06.02.131144", - "rel_title": "SARS-CoV2 Testing: The Limit of Detection Matters", + "rel_doi": "10.1101/2020.06.04.134379", + "rel_title": "The Zinc Finger Antiviral Protein restricts SARS-CoV-2", "rel_date": "2020-06-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.02.131144", - "rel_abs": "Resolving the COVID-19 pandemic requires diagnostic testing to determine which individuals are infected and which are not. The current gold standard is to perform RT-PCR on nasopharyngeal samples. Best-in-class assays demonstrate a limit of detection (LoD) of ~100 copies of viral RNA per milliliter of transport media. However, LoDs of currently approved assays vary over 10,000-fold. Assays with higher LoDs will miss more infected patients, resulting in more false negatives. However, the false-negative rate for a given LoD remains unknown. Here we address this question using over 27,500 test results for patients from across our healthcare network tested using the Abbott RealTime SARS-CoV-2 EUA. These results suggest that each 10-fold increase in LoD is expected to increase the false negative rate by 13%, missing an additional one in eight infected patients. The highest LoDs on the market will miss a majority of infected patients, with false negative rates as high as 70%. These results suggest that choice of assay has meaningful clinical and epidemiological consequences. The limit of detection matters.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.04.134379", + "rel_abs": "Recent evidence shows that the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is highly sensitive to interferons (IFNs). However, the underlying antiviral effectors remain to be defined. Here, we show that Zinc finger antiviral protein (ZAP) that specifically targets CpG dinucleotides in viral RNA sequences restricts SARS-CoV-2. We demonstrate that ZAP and its cofactors KHNYN and TRIM25 are expressed in human lung cells. Type I, II and III IFNs all strongly inhibited SARS-CoV-2 and further induced ZAP expression. Strikingly, SARS-CoV-2 and its closest relatives from bats show the strongest CpG suppression among all known human and bat coronaviruses, respectively. Nevertheless, knock-down of ZAP significantly increased SARS-CoV-2 production in lung cells, particularly upon treatment with IFN- or IFN-{gamma}. Thus, our results identify ZAP as an effector of the IFN response against SARS-CoV-2, although this pandemic pathogen may be preadapted to the low CpG environment in humans.\n\nHighlightsO_LISARS-CoV-2 and its closest bat relatives show strong CpG suppression\nC_LIO_LIIFN-{beta}, -{gamma} and -{lambda} inhibit SARS-CoV-2 with high efficiency\nC_LIO_LIZAP restricts SARS-CoV-2 and contributes to the antiviral effect of IFNs\nC_LI", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Ramy Arnaout", - "author_inst": "Beth Israel Deaconess Medical Center, Harvard Medical School" + "author_name": "Rayhane Nchioua", + "author_inst": "Ulm University" }, { - "author_name": "Rose Lee", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Janis Mueller", + "author_inst": "Ulm University" }, { - "author_name": "Ghee Rye Lee", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Carina Conzelmann", + "author_inst": "Ulm University" }, { - "author_name": "Cody Callahan", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Ruediger Gross", + "author_inst": "Ulm University" }, { - "author_name": "Christina F Yen", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Steffen Stenger", + "author_inst": "Ulm University Medical Center" }, { - "author_name": "Kenneth P Smith", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Daniel Sauter", + "author_inst": "Ulm University" }, { - "author_name": "Rohit Arora", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Jan Muench", + "author_inst": "Ulm University" }, { - "author_name": "James E Kirby", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Konstantin MJ Sparrer", + "author_inst": "Ulm University" + }, + { + "author_name": "Frank Kirchhoff", + "author_inst": "Ulm University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "microbiology" }, @@ -1378962,59 +1379191,27 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.06.01.20116608", - "rel_title": "Is death from Covid-19 a multistep process?", + "rel_doi": "10.1101/2020.06.01.20114884", + "rel_title": "Concordance of \"rapid\" serological tests and IgG and IgM chemiluminescence for SARS-COV-2", "rel_date": "2020-06-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.01.20116608", - "rel_abs": "Covid-19 death has a different relationship with age than is the case for other severe respiratory pathogens. The Covid-19 death rate increases exponentially with age, and the main risk factors are age itself, as well as having underlying conditions such as hypertension, diabetes, cardiovascular disease, severe chronic respiratory disease and cancer. Furthermore, the almost complete lack of deaths in children suggests that infection alone is not sufficient to cause death; rather, one must have gone through a number of changes, either as a result of undefined aspects of aging, or as a result of chronic disease. These characteristics of Covid-19 death are consistent with the multistep model of disease, a model which has primarily been used for cancer, and more recently for amyotrophic lateral sclerosis (ALS). We applied the multi-step model to data on Covid-19 case fatality rates (CFRs) from China, South Korea, Italy, Spain and Japan. In all countries we found that a plot of ln (CFR) against ln (age) was approximately linear with a slope of about 5. As a comparison, we also conducted similar analyses for selected other respiratory diseases. SARS showed a similar log-log age-pattern to that of Covid-19, albeit with a lower slope, whereas seasonal and pandemic influenza showed quite different age-patterns. Thus, death from Covid-19 and SARS appears to follow a distinct age-pattern, consistent with a multistep model of disease that in the case of Covid-19 is probably defined by comorbidities and age producing immune-related susceptibility. Identification of these steps would be potentially important for prevention and therapy for SARS-COV-2 infection.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.01.20114884", + "rel_abs": "AbstarctO_ST_ABSBackgroundC_ST_ABSThe COVID-19 serological tests for IgG and IgM have been developed with several methodologies: Immunoenzymatic Assay (ELISA), Chemiluminescence, Electro Chemiluminescence, Fluorescent Lateral Flow Immunoassays and Immunochromatography. None of these tests should be used for the diagnosis or population screening of the disease, considering that the antibodies appear only on the 8th - 14th day of the disease onset. The present study evaluates a sample of immunofluorescent and immunochromatographic rapid tests to show their agreement in relation to Chemiluminescence.\n\nMethodsA diagnostic test evaluation assay was performed to establish the performance of five \"rapid\" tests (4 immunochromatographic and 1 immunofluorescent tests) for IgG and IgM serology for SARS-CoV-2 using a panel of 30 serum samples from patients received in the laboratory analysis routine. For the evaluation of clinical performance, the qualitative results of the \"rapid\" tests were compared against those obtained by chemiluminescence, dichotomized as positives ([≥] 10 AU / mL) or negative (<10 UA / mL).\n\nFindingsThe best agreement is seen in the immunofluorescent assay, for the IgG contrast, with a particularly good kappa index (0.85), without positive disagreements and a negative disagreement of about 15%. In the immunochromatographic methods Kappa index was 0.61 at best, with disagreements in negative findings of {approx}35% and in positive cases of up to {approx}70%.\n\nThe IgM concordance behavior, on the other hand, reflects a weak to moderate Kappa concordance value (Kappa 0.2 to 0.6), with negative disagreements reaching up to 55% and positives of up to 84%, without any evaluated test reaching Kappa performance equal to or greater than 0.8.\n\nInterpretationSerological studies should be used in the clinical and epidemiological context and of other diagnostic tests. Given the high demand and supply in the market of \"rapid serological tests\", its evaluation against panels of serologically positive or negative samples established by Chemiluminescence or Electro chemiluminescence is essential to authorize its extensive use in populations\n\nFundingNone", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Neil Pearce", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Giovenale Moirano", - "author_inst": "University of Turin, Italy" - }, - { - "author_name": "Milena Maule", - "author_inst": "University of Turin, Italy" - }, - { - "author_name": "Manolis Kogevinas", - "author_inst": "ISGlobal" - }, - { - "author_name": "Xavier Rodo", - "author_inst": "ISGlobal" - }, - { - "author_name": "Deborah Lawlor", - "author_inst": "University of Bristol" - }, - { - "author_name": "Jan Vandenbroucke", - "author_inst": "Leiden University Medical Center" - }, - { - "author_name": "Christina Vandenbroucke-Grauls", - "author_inst": "Amsterdam UMC" - }, - { - "author_name": "Fernando P Polack", - "author_inst": "Vanderbilt Unversity" + "author_name": "Klever V Saenz-Flor Sr.", + "author_inst": "Universidad Central del Ecuador" }, { - "author_name": "Adnan Custovic", - "author_inst": "Imperial College London" + "author_name": "Lorena M Santafe Sr.", + "author_inst": "Synlab Solutions in Diagnostics Ecuador" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "pathology" }, { "rel_doi": "10.1101/2020.06.01.20119347", @@ -1380120,97 +1380317,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.30.20118067", - "rel_title": "Rethinking antiviral effects for COVID-19 in clinical studies: early initiation is key to successful treatment", + "rel_doi": "10.1101/2020.05.31.20118349", + "rel_title": "Covid-19 and Population Age Structure", "rel_date": "2020-06-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.30.20118067", - "rel_abs": "Development of an effective antiviral drug for COVID-19 is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence for effective drugs from clinical studies is limited. The lack of evidence could be in part due to heterogeneity of virus dynamics among patients and late initiation of treatment. We first quantified the heterogeneity of viral dynamics which could be a confounder in compassionate use programs. Second, we demonstrated that an antiviral drug is unlikely to be effective if initiated after a short period following symptom onset. For accurate evaluation of the efficacy of an antiviral drug for COVID-19, antiviral treatment should be initiated before or soon after symptom onset in randomized clinical trials.\n\nOne Sentence SummaryStudy design to evaluate antiviral effect.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.31.20118349", + "rel_abs": "Epidemiological studies suggest that age distribution of a population has a non-trivial effect on how morbidity rates, mortality rates and case fatality rates (CFR) vary when there is an epidemic or pandemic. We look at the empirical evidence from a large cohort of countries to see the sensitivity of Covid-19 data to their respective median ages. The insights that emerge could be used to control for age structure effects while investigating other factors like cross-protection, comorbidities, etc.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Shoya Iwanami", - "author_inst": "Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan;" - }, - { - "author_name": "Keisuke Ejima", - "author_inst": "Indiana University" - }, - { - "author_name": "Kwang Su Kim", - "author_inst": "Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan;" - }, - { - "author_name": "Koji Noshita", - "author_inst": "Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan" - }, - { - "author_name": "Yasuhisa Fujita", - "author_inst": "Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan" - }, - { - "author_name": "Taiga Miyazaki", - "author_inst": "Department of Infectious Diseases, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan" - }, - { - "author_name": "Shigeru Kohno", - "author_inst": "Nagasaki University, Nagasaki, Japan" - }, - { - "author_name": "Yoshitsugu Miyazaki", - "author_inst": "Department of chemotherapy & mycoses, and Leprosy Research Ctr., National Institute of Infectious Diseases, Tokyo," - }, - { - "author_name": "Shimpei Morimoto", - "author_inst": "Institute of Biomedical Sciences, Nagasaki University, Japan" - }, - { - "author_name": "Shinji Nakaoka", - "author_inst": "Faculty of Advanced Life Science, Hokkaido University, Sapporo, Japan" - }, - { - "author_name": "Yoshiyuki Koizumi", - "author_inst": "National Center for Global Health and Medicine, Tokyo, Japan" - }, - { - "author_name": "Yusuke Asai", - "author_inst": "Disease Control and Prevention Center, National Center for Global Health and Medicine, Tokyo, Japan" - }, - { - "author_name": "Kazuyuki Aihara", - "author_inst": "International Research Center for Neurointelligence, The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Tokyo, Japan" - }, - { - "author_name": "Koichi Watashi", - "author_inst": "Department of Virology II, National Institute of Infectious Diseases, Tokyo, Japan" - }, - { - "author_name": "Robin N Thompson", - "author_inst": "Christ Church, University of Oxford, Oxford OX1 1DP, UK" - }, - { - "author_name": "Kenji Shibuya", - "author_inst": "Institute for Population Health, Kings College London, London" - }, - { - "author_name": "Katsuhito Fujiu", - "author_inst": "The University of Tokyo" - }, - { - "author_name": "Alan S Perelson", - "author_inst": "Los Alamos National Laboratory" - }, - { - "author_name": "Iwami Shingo", - "author_inst": "Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan" + "author_name": "Ajit Haridas", + "author_inst": "individual" }, { - "author_name": "Takaji Wakita", - "author_inst": "National Institute of Infectious Diseases" + "author_name": "Gangan Pratap", + "author_inst": "A P J Abdul Kalam Technological University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1381394,79 +1381519,83 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.06.03.129585", - "rel_title": "Naturally occurring SARS-CoV-2 gene deletions close to the spike S1/S2 cleavage site in the viral quasispecies of COVID19 patients", + "rel_doi": "10.1101/2020.06.03.130591", + "rel_title": "Highly multiplexed oligonucleotide probe-ligation testing enables efficient extraction-free SARS-CoV-2 detection and viral genotyping", "rel_date": "2020-06-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.03.129585", - "rel_abs": "The SARS-CoV-2 spike (S) protein, the viral mediator for binding and entry into the host cell, has sparked great interest as a target for vaccine development and treatments with neutralizing antibodies. Initial data suggest that the virus has low mutation rates, but its large genome could facilitate recombination, insertions, and deletions, as has been described in other coronaviruses. Here, we deep-sequenced the complete SARS-CoV-2 S gene from 18 patients (10 with mild and 8 with severe COVID-19), and found that the virus accumulates deletions upstream and very close to the S1/S2 cleavage site, generating a frameshift with appearance of a stop codon. These deletions were found in a small percentage of the viral quasispecies (2.2%) in samples from all the mild and only half the severe COVID-19 patients. Our results suggest that the virus may generate free S1 protein released to the circulation. We propose that natural selection has favored a \"Dont burn down the house\" strategy, in which free S1 protein may compete with viral particles for the ACE2 receptor, thus reducing the severity of the infection and tissue damage without losing transmission capability.", - "rel_num_authors": 15, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.03.130591", + "rel_abs": "The emergence of SARS-CoV-2 has caused the current COVID-19 pandemic with catastrophic societal impact. Because many individuals shed virus for days before symptom onset, and many show mild or no symptoms, an emergent and unprecedented need exists for development and deployment of sensitive and high throughput molecular diagnostic tests. RNA-mediated oligonucleotide Annealing Selection and Ligation with next generation DNA sequencing (RASL-seq) is a highly multiplexed technology for targeted analysis of polyadenylated mRNA, which incorporates sample barcoding for massively parallel analyses. Here we present a more generalized method, capture RASL-seq (\u201ccRASL-seq\u201d), which enables analysis of any targeted pathogen-(and/or host-) associated RNA molecules. cRASL-seq enables highly sensitive (down to \u223c1-100 pfu/ml or cfu/ml) and highly multiplexed (up to \u223c10,000 target sequences) detection of pathogens. Importantly, cRASL-seq analysis of COVID-19 patient nasopharyngeal (NP) swab specimens does not involve nucleic acid extraction or reverse transcription, steps that have caused testing bottlenecks associated with other assays. Our simplified workflow additionally enables the direct and efficient genotyping of selected, informative SARS-CoV-2 polymorphisms across the entire genome, which can be used for enhanced characterization of transmission chains at population scale and detection of viral clades with higher or lower virulence. Given its extremely low per-sample cost, simple and automatable protocol and analytics, probe panel modularity, and massive scalability, we propose that cRASL-seq testing is a powerful new surveillance technology with the potential to help mitigate the current pandemic and prevent similar public health crises.Competing Interest StatementJ.J.C. and H.B.L. are listed as inventors on a patent describing the cRASL-seq method. H.B.L. has founded a company to license and commercialize oligonucleotide probe ligation related technologies.View Full Text", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Maria Pinana", - "author_inst": "VHIR-HUVH" + "author_name": "Joel J Credle", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Francisco Rodriguez-Frias", - "author_inst": "VHIR-HUVH" + "author_name": "Matthew Robinson", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Mercedes Guerrero", - "author_inst": "VHIR-HUVH" + "author_name": "Jonathan Gunn", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Juliana Esperalba", - "author_inst": "HUVH" + "author_name": "Daniel Monaco", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Ariadna Rando", - "author_inst": "VHIR-HUVH" + "author_name": "Brandon Sie", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Lidia Goterris", - "author_inst": "HUVH" + "author_name": "Alexandra L Tchir", + "author_inst": "Florida International University" }, { - "author_name": "Maria Gema Codina", - "author_inst": "HUVH" + "author_name": "Justin Hardick", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Susanna Quer", - "author_inst": "VHIR" + "author_name": "Xuwen Zheng", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Maria Carmen Martin", - "author_inst": "HUVH" + "author_name": "Kathryn Shaw-Saliba", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Magda Campins", - "author_inst": "HUVH" + "author_name": "Richard Rothman", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Ricard Ferrer", - "author_inst": "HUVH" + "author_name": "Susan Eshleman", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Benito Almirante", - "author_inst": "HUVH" + "author_name": "Andrew Pekosz", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" }, { - "author_name": "Juan Ignacio Esteban", - "author_inst": "VHIR-HUVH" + "author_name": "Kasper Hansen", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Tomas Pumarola", - "author_inst": "HUVH" + "author_name": "Heba Mostafa", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Andres Anton", - "author_inst": "VHIR-HUVH" + "author_name": "Martin Steinegger", + "author_inst": "Seoul National University" + }, + { + "author_name": "Harry Benjamin Larman", + "author_inst": "Johns Hopkins University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "new results", - "category": "microbiology" + "category": "pathology" }, { "rel_doi": "10.1101/2020.06.03.129817", @@ -1382856,25 +1382985,273 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.31.20118521", - "rel_title": "Summer vacation and COVID-19: effects of metropolitan people going to summer provinces", + "rel_doi": "10.1101/2020.05.31.20118554", + "rel_title": "Population-wide evolution of SARS-CoV-2 immunity tracked by a ternary immunoassay", "rel_date": "2020-06-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.31.20118521", - "rel_abs": "Many countries are now investigating what the effects of summer vacation might be on the COVID-19 pandemic. Here one particular such question is addressed: what will happen if large numbers of metropolitan people visit a less populated province during the summer vacation? By means of a simple epidemic model, allowing for both short and long-term visitors to the province, it is studied which features are most influential in determining if such summer movements will result in large number of infections among the province population. The method is applied to the island of Gotland off the South East coast of Sweden. It is shown that the amount of mixing between the metropolitan and province groups and the fraction of metropolitan people being infectious upon arrival are most influential. Consequently, minimizing events gathering both the province and metropolitan groups and/or reducing the number of short-term visitors could substantially decrease spreading, as could measures to lower the fraction initially infectious upon arrival.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.31.20118554", + "rel_abs": "Effective public-health measures and vaccination campaigns against SARS-CoV-2 require granular knowledge of population-level immune responses. We developed a Tripartite Automated Blood Immunoassay (TRABI) to assess the IgG response against the ectodomain and the receptor-binding domain of the spike protein as well as the nucleocapsid protein of SARS-CoV-2. We used TRABI for continuous seromonitoring of hospital patients and healthy blood donors (n=72222) in the canton of Zurich from December 2019 to December 2020 (pre-vaccine period). Seroprevalence peaked in May 2020 and rose again in November 2020 in both cohorts. Validations of results included antibody diffusional sizing and Western Blotting. Using an extended Susceptible-Exposed-Infectious-Removed model, we found that antibodies waned with a half-life of 75 days, whereas the cumulative incidence rose from 2.3% in June 2020 to 12.2% in mid-December 2020 in the population of the canton of Zurich. A follow-up health survey indicated that about 10% of patients infected with wildtype SARS-CoV-2 sustained some symptoms at least twelve months post COVID-19 and up to the timepoint of survey participation. Crucially, we found no evidence for a difference in long-term complications between those whose infection was symptomatic and those with asymptomatic acute infection. The cohort of asymptomatic SARS-CoV-2- infected subjects represents a resource for the study of chronic and possibly unexpected sequelae.", + "rel_num_authors": 64, "rel_authors": [ { - "author_name": "Tom Britton", - "author_inst": "Stockholm University" + "author_name": "Marc Emmenegger", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" }, { - "author_name": "Frank G Ball", - "author_inst": "University of Nottingham" + "author_name": "Elena De Cecco", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "David Lamparter", + "author_inst": "Health2030 Genome Center. 9 Chemin des Mines, 1202 Geneva, Switzerland" + }, + { + "author_name": "Raphael P. B. Jacquat", + "author_inst": "Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom" + }, + { + "author_name": "Julien Riou", + "author_inst": "Institute of Social and Preventive Medicine, University of Bern, 3012 Bern, Switzerland" + }, + { + "author_name": "Dominik Menges", + "author_inst": "Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich" + }, + { + "author_name": "Tala Ballouz", + "author_inst": "Epidemiology, Biostatistics and Prevention Institute" + }, + { + "author_name": "Daniel Ebner", + "author_inst": "Target Discovery Institute, University of Oxford, OX3 7FZ, England" + }, + { + "author_name": "Matthias M Schneider", + "author_inst": "Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom" + }, + { + "author_name": "Itzel Condado Morales", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Berre Dogancay", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Jingjing Guo", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Anne Wiedmer", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Julie Domange", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Marigona Imeri", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Rita Moos", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Chryssa Zografou", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Leyla Batkitar", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Lidia Madrigal", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Dezirae Schneider", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Chiara Trevisan", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Andres Gonzalez-Guerra", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Alessandra Carrella", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Irina L. Dubach", + "author_inst": "Division of Internal Medicine, University Hospital Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Catherine K. Xu", + "author_inst": "Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom" + }, + { + "author_name": "Georg Meisl", + "author_inst": "Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom" + }, + { + "author_name": "Vasilis Kosmoliaptsis", + "author_inst": "Department of Surgery, Addenbrooke's Hospital, University of Cambridge, Hills Road, Cam-bridge CB2 0QQ, United Kingdom" + }, + { + "author_name": "Tomas Malinauskas", + "author_inst": "Division of Structural Biology, The Wellcome Centre for Human Genetics, University of Oxford, Headington, Oxford, OX3 7BN, UK" + }, + { + "author_name": "Nicola Burgess-Brown", + "author_inst": "Structural Genomics Consortium, University of Oxford, Oxford, OX3 7DQ, UK" + }, + { + "author_name": "Ray Owens", + "author_inst": "Division of Structural Biology, The Wellcome Centre for Human Genetics, University of Oxford, Headington, Oxford, OX3 7BN, UK" + }, + { + "author_name": "Stephanie Hatch", + "author_inst": "Target Discovery Institute, University of Oxford, OX3 7FZ, England" + }, + { + "author_name": "Juthathip Mongkolsapaya", + "author_inst": "Nuffield Department of Medicine, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK" + }, + { + "author_name": "Gavin R. Screaton", + "author_inst": "Nuffield Department of Medicine, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK" + }, + { + "author_name": "Katharina Schubert", + "author_inst": "Department of Biology, Institute of Molecular Biology and Biophysics, ETH Zurich, Zurich, Switzerland" + }, + { + "author_name": "John D. Huck", + "author_inst": "Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA" + }, + { + "author_name": "Feimei Liu", + "author_inst": "Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA" + }, + { + "author_name": "Florence Pojer", + "author_inst": "Protein Production and Structure Core Facility, EPFL SV PTECH PTPSP, 1015 Lausanne, Switzerland" + }, + { + "author_name": "Kelvin Lau", + "author_inst": "Protein Production and Structure Core Facility, EPFL SV PTECH PTPSP, 1015 Lausanne, Switzerland" + }, + { + "author_name": "David Hacker", + "author_inst": "Protein Production and Structure Core Facility, EPFL SV PTECH PTPSP, 1015 Lausanne, Switzerland" + }, + { + "author_name": "Elsbeth Probst-Mueller", + "author_inst": "Department of Immunology, University Hospital Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Carlo Cervia", + "author_inst": "Department of Immunology, University Hospital Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Jakob Nilsson", + "author_inst": "Department of Immunology, University Hospital Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Onur Boyman", + "author_inst": "Department of Immunology, University Hospital Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Lanja Saleh", + "author_inst": "Institute of Clinical Chemistry, University Hospital Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Katharina Spanaus", + "author_inst": "Institute of Clinical Chemistry, University Hospital Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Arnold von Eckardstein", + "author_inst": "Institute of Clinical Chemistry, University Hospital Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Dominik J. Schaer", + "author_inst": "Division of Internal Medicine, University Hospital Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Nenad Ban", + "author_inst": "Department of Biology, Institute of Molecular Biology and Biophysics, ETH Zurich, Zurich, Swit-zerland" + }, + { + "author_name": "Ching-Ju Tsai", + "author_inst": "Department of Biology and Chemistry, Laboratory of Biomolecular Research, Paul Scherrer In-stitute, 5303 Villigen-PSI, Switzerland" + }, + { + "author_name": "Jacopo Marino", + "author_inst": "Department of Biology and Chemistry, Laboratory of Biomolecular Research, Paul Scherrer In-stitute, 5303 Villigen-PSI, Switzerland" + }, + { + "author_name": "Gebhard F. X. Schertler", + "author_inst": "Department of Biology and Chemistry, Laboratory of Biomolecular Research, Paul Scherrer In-stitute, 5303 Villigen-PSI, Switzerland" + }, + { + "author_name": "Nadine Ebert", + "author_inst": "Institute of Virology and Immunology IVI, Bern, and Vetsuisse Faculty, University of Bern, 3012 Bern, Switzerland" + }, + { + "author_name": "Volker Thiel", + "author_inst": "Institute of Virology and Immunology IVI, Bern, and Vetsuisse Faculty, University of Bern, 3012 Bern, Switzerland" + }, + { + "author_name": "Jochen Gottschalk", + "author_inst": "Regional Blood Transfusion Service Zurich, Swiss Red Cross, 8952 Schlieren, Switzerland" + }, + { + "author_name": "Beat M. Frey", + "author_inst": "Regional Blood Transfusion Service Zurich, Swiss Red Cross, 8952 Schlieren, Switzerland" + }, + { + "author_name": "Regina Reimann", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Simone Hornemann", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + }, + { + "author_name": "Aaron M. Ring", + "author_inst": "Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA" + }, + { + "author_name": "Tuomas P. J. Knowles", + "author_inst": "Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom" + }, + { + "author_name": "Milo A. Puhan", + "author_inst": "Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich" + }, + { + "author_name": "Christian L Althaus", + "author_inst": "Institute of Social and Preventive Medicine, University of Bern, 3012 Bern, Switzerland" + }, + { + "author_name": "Ioannis Xenarios", + "author_inst": "Health2030 Genome Center. 9 Chemin des Mines, 1202 Geneva, Switzerland" + }, + { + "author_name": "David I. Stuart", + "author_inst": "Division of Structural Biology, The Wellcome Centre for Human Genetics, University of Oxford, Headington, Oxford, OX3 7BN, UK" + }, + { + "author_name": "Adriano Aguzzi", + "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1384294,35 +1384671,47 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.06.02.20113423", - "rel_title": "Predictors to use mobile apps for monitoring COVID-19 symptoms and contact tracing: A survey among Dutch citizens.", + "rel_doi": "10.1101/2020.05.27.20114298", + "rel_title": "Increased expression of ACE2, the SARS-CoV-2 entry receptor, in alveolar and bronchial epithelium of smokers and COPD subjects", "rel_date": "2020-06-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.02.20113423", - "rel_abs": "IntroductioneHealth applications have been recognized as a valuable tool to reduce COVID-19s effective reproduction number. In this paper, we report on an online survey among Dutch citizens with the goal to identify antecedents of acceptance of a mobile application for COVID-19 symptom recognition and monitoring, and a mobile application for contact tracing.\n\nMethodsNext to the demographics, the online survey contained questions focussing on perceived health, fear of COVID-19 and intention to use. We used snowball sampling via posts on social media and personal connections. To identify antecedents of acceptance of the two mobile applications we conducted multiple linear regression analyses.\n\nResultsIn total, 238 Dutch adults completed the survey. Almost 60% of the responders were female and the average age was 45.6 years (SD{+/-}17.4). For the symptom app, the final model included the predictors age, attitude towards technology and fear of COVID-19. The model had an R2 of 0.141. The final model for the tracing app included the same predictors and had an R2 of 0.156. The main reason to use both mobile applications was to control the spread of the COVID-19 virus. Concerns about privacy was mentioned as the main reason not to use the mobile applications.\n\nDiscussionAge, attitude towards technology and fear of COVID-19 are important predictors of the acceptance of COVID-19 mobile applications for symptom recognition and monitoring and for contact tracing. These predictors should be taken into account during the development and implementation of these mobile applications to secure acceptance.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.27.20114298", + "rel_abs": "RationaleSmokers and patients with chronic obstructive pulmonary disease (COPD) are at increased risk for severe Coronavirus Disease 2019 (COVID-19).\n\nObjectivesWe investigated the expression of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entry receptor ACE2 and the protease TMPRSS2 in lung tissue from never smokers and smokers with and without COPD.\n\nMethodsIn a cross-sectional, observational study we measured mRNA expression of ACE2 and TMPRSS2 by RT-PCR in lung tissue samples from 120 well phenotyped subjects. Next, protein levels of ACE2 were visualized by immunohistochemistry on paraffin sections from 87 subjects and quantified in alveolar and bronchial epithelium. Finally, primary human bronchial epithelial cells (HBECs) were cultured at air liquid interface and exposed to air or cigarette smoke.\n\nResultsACE2 mRNA expression was significantly higher in lung tissue from current smokers and subjects with moderate to very severe COPD and correlated with physiological parameters of airway obstruction and emphysema. Pulmonary expression levels of TMPRSS2 were significantly higher in patients with (very) severe COPD and correlated significantly with ACE2 expression. Importantly, protein levels of ACE2 were elevated in both alveolar and bronchial epithelium of current smokers and subjects with moderate to very severe COPD. Finally, TMPRSS2 mRNA expression increased in in vitro cultured HBECs upon acute exposure to cigarette smoke.\n\nConclusionsWe demonstrate increased expression of ACE2 in lungs of smokers and COPD subjects, which might facilitate host cell entry of SARS-CoV-2. These findings help identifying populations at risk for severe COVID-19.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Stephanie Maria Jansen-Kosterink", - "author_inst": "Roessingh Research and Development" + "author_name": "Merel Jacobs", + "author_inst": "Ghent University" + }, + { + "author_name": "Hannelore P Van Eeckhoutte", + "author_inst": "Ghent University" + }, + { + "author_name": "Sara RA Wijnant", + "author_inst": "Ghent University" + }, + { + "author_name": "Wim Janssens", + "author_inst": "University Hospital Leuven" }, { - "author_name": "Marian Hurmuz", - "author_inst": "Roessingh Research and Development" + "author_name": "Guy F Joos", + "author_inst": "Ghent University" }, { - "author_name": "Marjolein den Ouden", - "author_inst": "Saxion University of Applied Sciences" + "author_name": "Guy G Brusselle", + "author_inst": "Ghent University" }, { - "author_name": "Lex van Velsen", - "author_inst": "Roessingh Research and Development" + "author_name": "Ken R Bracke", + "author_inst": "Ghent University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2020.05.29.20114751", @@ -1386492,59 +1386881,47 @@ "category": "oncology" }, { - "rel_doi": "10.1101/2020.05.28.120998", - "rel_title": "Pathogenesis, transmission and response to re-exposure of SARS-CoV-2 in domestic cats", + "rel_doi": "10.1101/2020.05.31.20118687", + "rel_title": "Changes in Reproductive Rate of SARS-CoV-2 Due to Non-pharmaceutical Interventions in 1,417 U.S. Counties", "rel_date": "2020-06-01", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.28.120998", - "rel_abs": "The pandemic caused by SARS-CoV-2 has reached nearly every country in the world with extraordinary person-to-person transmission. The most likely original source of the virus was spillover from an animal reservoir and subsequent adaptation to humans sometime during the winter of 2019 in Wuhan Province, China. Because of its genetic similarity to SARS-CoV-1, it is likely that this novel virus has a similar host range and receptor specificity. Due to concern for human-pet transmission, we investigated the susceptibility of domestic cats and dogs to infection and potential for infected cats to transmit to naive cats. We report that cats are highly susceptible to subclinical infection, with a prolonged period of oral and nasal viral shedding that is not accompanied by clinical signs, and are capable of direct contact transmission to other cats. These studies confirm that cats are susceptible to productive SARS-CoV-2 infection, but are unlikely to develop clinical disease. Further, we document that cats develop a robust neutralizing antibody response that prevented re-infection to a second viral challenge. Conversely, we found that dogs do not shed virus following infection, but do mount an anti-viral neutralizing antibody response. There is currently no evidence that cats or dogs play a significant role in human exposure; however, reverse zoonosis is possible if infected owners expose their domestic pets during acute infection. Resistance to re-exposure holds promise that a vaccine strategy may protect cats, and by extension humans, to disease susceptibility.", - "rel_num_authors": 10, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.31.20118687", + "rel_abs": "In response to the rapid spread of the novel coronavirus, SARS-CoV-2, the U.S. has largely delegated implementation of non-pharmaceutical interventions (NPIs) to local governments on the state and county level. This staggered implementation combined with the heterogeneity of the U.S. complicates quantification the effect of NPIs on the reproductive rate of SARS-CoV-2.\n\nWe describe a data-driven approach to quantify the effect of NPIs that relies on county-level similarities to specialize a Bayesian mechanistic model based on observed fatalities. Using this approach, we estimate change in reproductive rate, Rt, due to implementation of NPIs in 1,417 U.S. counties.\n\nWe estimate that as of May 28th, 2020 1,177 out of the considered 1,417 U.S. counties have reduced the reproductive rate of SARS-CoV-2 to below 1.0. The estimated effect of any individual NPI, however, is different across counties. Stay-at-home orders were estimated as the only effective NPI in metropolitan and urban counties, while advisory NPIs were estimated to be effective in more rural counties. The expected level of infection predicted by the model ranges from 0 to 28.7% and is far from herd immunity even in counties with advanced spread.\n\nOur results suggest that local conditions are pertinent to containment and re-opening decisions.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Angela Bosco-Lauth", - "author_inst": "Colorado State University" - }, - { - "author_name": "Airn E. Hartwig", - "author_inst": "Colorado State University" - }, - { - "author_name": "Stephanie Porter", - "author_inst": "Colorado State University" - }, - { - "author_name": "Paul Gordy", - "author_inst": "Colorado State University" + "author_name": "Jie Ying Wu", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Mary Nehring", - "author_inst": "Colorado State University" + "author_name": "Benjamin D Killeen", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Alex Byas", - "author_inst": "Colorado State University" + "author_name": "Philipp Nikutta", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Sue VandeWoude", - "author_inst": "Colorado State University" + "author_name": "Mareike Thies", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Izabela Ragan", - "author_inst": "Colorado State University" + "author_name": "Anna Zapaishchykova", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Rachel Maison", - "author_inst": "Colorado State University" + "author_name": "Shreya Chakraborty", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Richard Bowen", - "author_inst": "Colorado State University" + "author_name": "Mathias Unberath", + "author_inst": "Johns Hopkins University" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.06.01.20100461", @@ -1387974,18 +1388351,27 @@ "category": "scientific communication and education" }, { - "rel_doi": "10.1101/2020.05.30.125740", - "rel_title": "Synonymous sites in SARS-CoV-2 genes display trends affecting translational efficiency", + "rel_doi": "10.1101/2020.05.31.125302", + "rel_title": "Assignment of coronavirus spike protein site-specific glycosylation using GlycReSoft", "rel_date": "2020-05-31", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.30.125740", - "rel_abs": "A novel coronavirus, SARS-CoV-2, has caused a pandemic of COVID-19. The evolutionary trend of the virus genome may have implications for infection control policy but remains obscure. We introduce an estimation of fold change of translational efficiency based on synonymous variant sites to characterize the adaptation of the virus to hosts. The increased translational efficiency of the M and N genes suggests that the population of SARS-CoV-2 benefits from mutations toward favored codons, while the ORF1ab gene has slightly decreased the translational efficiency. In the coding region of the ORF1ab gene upstream of the -1 frameshift site, the decreasing of the translational efficiency has been weakening parallel to the growth of the epidemic, indicating inhibition of synthesis of RNA-dependent RNA polymerase and promotion of replication of the genome. Such an evolutionary trend suggests that multiple infections increased virulence in the absence of social distancing.", - "rel_num_authors": 0, - "rel_authors": null, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.31.125302", + "rel_abs": "Widely-available LC-MS instruments and methods allow users to acquire glycoproteomics data. Complex glycans, however, add a dimension of complexity to the data analysis workflow. In a sense, complex glycans are post-translationally modified post-translational modifications, reflecting a series of biosynthetic reactions in the secretory pathway that are spatially and temporally regulated. One problem is that complex glycan is micro-heterogeneous, multiplying the complexity of the proteome. Another is that glycopeptide glycans undergo dissociation during tandem MS that must be considered for tandem MS interpretation algorithms and quantitative tools. Fortunately, there are a number of algorithmic tools available for analysis of glycoproteomics LC-MS data. We summarize the principles for glycopeptide data analysis and show use of our GlycReSoft tool to analyze SARS-CoV-2 spike protein site-specific glycosylation.", + "rel_num_authors": 2, + "rel_authors": [ + { + "author_name": "Joshua A. Klein", + "author_inst": "Boston University Medical Campus" + }, + { + "author_name": "Joseph Zaia", + "author_inst": "Boston University Medical Campus" + } + ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "evolutionary biology" + "license": "cc_by_nc", + "type": "confirmatory results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.05.31.116061", @@ -1389503,49 +1389889,109 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.05.28.20116277", - "rel_title": "QMRA of SARS-CoV-2 for workers in wastewater treatment plants", + "rel_doi": "10.1101/2020.05.28.20116178", + "rel_title": "Worsening of pre-existing psychiatric conditions during the COVID-19 pandemic", "rel_date": "2020-05-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.28.20116277", - "rel_abs": "Faecal-oral transmission of SARS-CoV-2 is a hot topic and additional research is needed to elucidate the risks of the novel coronavirus in sanitation systems. This is the first article that investigates the potential health risks of SARS-CoV-2 in sewage to wastewater treatment plants (WWTPs) workers. A quantitative microbial risk assessment (QMRA) is applied for three COVID-19 scenarios (moderate, aggressive and extreme) to study the effect of different stages of the pandemic, in terms of percentage of infected population, on the probability of infection. Results reveal that estimates of viral loads in sewage at the entrance of WWTPs ranged from 1.03x102 to 1.31x104 GC.mL-1 (0.1 to 13.06 PFU.mL-1, respectively) and that estimated risks for the aggressive and extreme scenarios (6.5x10-3 and 3.1x10-2, respectively) were likely to be above a WHO benchmark of tolerable risk used for virus infection of 10-3 and higher than the risk of infection of E. coli, used herein as common pathogen indicator for a relative comparison, thus reinforcing the concern of sewage systems as a transmission pathway of SARS-CoV-2. These findings are helpful as an early-warning tool and in prioritizing upcoming risk management strategies in the sanitation sector during COVID-19 pandemic.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.28.20116178", + "rel_abs": "This study anonymously examined 2,734 psychiatric patients worldwide for worsening of their pre-existing psychiatric condition during the COVID-19 pandemic. Valid responses mainly from 12 featured countries indicated self-reported worsening of psychiatric conditions in 2/3rd of the patients assessed that was validated through their significantly higher scores on scales for general psychological disturbance, post-traumatic stress disorder, and depression. Female gender, feeling no control of the situation and reporting dissatisfaction with the response of the state during the COVID-19 pandemic, and reduced interaction with family and friends increased the worsening of pre-existing psychiatric conditions, whereas optimism, ability to share concerns with family and friends and using social media like usual were associated with less worsening. An independent clinical investigation from the USA confirmed worsening of psychiatric conditions during the COVID-19 pandemic based on identification of new symptoms that necessiated clinical interventions such as dose adjustment or starting new medications in more than half of the patients.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Rafael Newton Zaneti", - "author_inst": "DMAE - Municipal Water and Sewerage Department. Porto Alegre, RS, Brazil" + "author_name": "Susanna Gobbi", + "author_inst": "Zurich Center for Neuroeconomics, University of Zurich, Zurich, Switzerland" }, { - "author_name": "Viviane Girardi", - "author_inst": "University of Feevale" + "author_name": "Martyna Beata Plomecka", + "author_inst": "University of Zurich" }, { - "author_name": "Fernando Rosado Spilki", - "author_inst": "University of Feevale" + "author_name": "Zainab Ashraf", + "author_inst": "Faculty of Arts, University of Waterloo, Canada" + }, + { + "author_name": "Piotr Radzi\u0144ski", + "author_inst": "Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Poland" + }, + { + "author_name": "Rachael Neckels", + "author_inst": "Biomolecular Sciences Graduate Program, Department of Biomolecular Sciences, Boise State University, Boise, Idaho, USA" + }, + { + "author_name": "Samuel Lazzeri", + "author_inst": "Faculty of Science and Engineering, University of Groningen, Groningen, the Netherlands" + }, + { + "author_name": "Alisa Dedi\u0107", + "author_inst": "Faculty of Medicine, University of Tuzla, Bosnia and Herzegovina" + }, + { + "author_name": "Asja Bakalovi\u0107", + "author_inst": "Faculty of Medicine, University of Tuzla, Bosnia and Herzegovina" + }, + { + "author_name": "Lejla Hrusti\u0107", + "author_inst": "Faculty of Medicine, University of Tuzla, Bosnia and Herzegovina" + }, + { + "author_name": "Beata Sk\u00f3rko", + "author_inst": "Faculty of Medicine, Medical University of Warsaw, Warsaw, Poland" + }, + { + "author_name": "Sarvin Es haghi", + "author_inst": "Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran" + }, + { + "author_name": "Kristina Almazidou", + "author_inst": "Faculty of Veterinary Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece" + }, + { + "author_name": "Luis Rodr\u00edguez-Pino", + "author_inst": "Faculty of Medicine, University of Valencia, Spain" + }, + { + "author_name": "A. Beyza Alp", + "author_inst": "Faculty of Medicine, Maltepe University, Turkey" + }, + { + "author_name": "Hafsa Jabeen", + "author_inst": "Medical College, Dow University of Health Sciences, Karachi, Pakistan" + }, + { + "author_name": "Verena Waller", + "author_inst": "Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland" }, { - "author_name": "Kristina Mena", - "author_inst": "University of Texas - Houston School of Public Health. Houston, United States" + "author_name": "Dana Shibli", + "author_inst": "Faculty of Medicine, University of Jordan, Jordan" }, { - "author_name": "Ana Paula Campos Westphalen", - "author_inst": "DMAE - Municipal Water and Sewerage Department. Porto Alegre, RS, Brazil" + "author_name": "Mehdi A Behnam", + "author_inst": "Neuroscience Center Zurich, University of Zurich/ Swiss Federal Institute of Technology (ETH), Zurich, Switzerland" }, { - "author_name": "Evandro Ricardo da Costa Colares", - "author_inst": "DMAE - Municipal Water and Sewerage Department. Porto Alegre, RS, Brazil" + "author_name": "Ahmed Hussain Arshad", + "author_inst": "Baqai Medical University, Karachi, Pakistan" + }, + { + "author_name": "Zofia Bara\u0144czuk - Turska", + "author_inst": "Institute of Mathematics, University of Zurich, Zurich, Switzerland" + }, + { + "author_name": "Zeeshan Haq", + "author_inst": "Texas Behavioral Health, Houston, TX, USA" }, { - "author_name": "Allan Guedes Pozzebon", - "author_inst": "DMAE - Municipal Water and Sewerage Department. Porto Alegre, RS, Brazil" + "author_name": "Salah U Qureshi", + "author_inst": "Texas Behavioral Health, Houston, TX, USA" }, { - "author_name": "Ramiro Goncalves Etchepare", - "author_inst": "UFPR - Federal University of Parana. Curitiba, PR, Brazil" + "author_name": "Ali Jawaid", + "author_inst": "Center of Excellence for Neural Plasticity and Brain Disorders (Braincity), Nencki Institute of Experimental Biology, Warsaw, Poland, Department of Neurology, U" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1391017,59 +1391463,63 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.05.28.20116301", - "rel_title": "Early Impact of COVID-19 on Individuals with Eating Disorders: A survey of ~1000 Individuals in the United States and the Netherlands", + "rel_doi": "10.1101/2020.05.29.20116475", + "rel_title": "Non-pharmaceutical behavioural measures for droplet-borne biological hazards prevention: Health-EDRM for COVID-19 (SARS-CoV-2) pandemic", "rel_date": "2020-05-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.28.20116301", - "rel_abs": "We received rapid ethical permission to evaluate the early impact of COVID-19 on people with eating disorders. Participants in the United States (US, N=511) and the Netherlands (NL, N=510), recruited through ongoing studies and social media, completed an online baseline survey that included both quantitative measures and free-text responses assessing the impact of COVID-19 on situational circumstances, eating disorder symptoms, eating disorder treatment, and general well-being. Results revealed strong and wide-ranging effects on eating disorder concerns and illness behaviors that were consistent with diagnoses. Participants with anorexia nervosa (US 62% of sample; NL 69%) reported increased restriction and fears about being able to find foods consistent with their meal plan. Individuals with bulimia nervosa and binge-eating disorder (US 30% of sample; NL 15%) reported increases in their binge-eating episodes and urges to binge. Respondents noted marked increases in anxiety since 2019 and reported greater concerns about the impact of COVID-19 on their mental health than physical health. Although many participants acknowledged and appreciated the transition to telehealth, limitations of this treatment modality for this population were raised. Individuals with past histories of eating disorders noted concerns about relapse related to COVID-19 circumstances. Encouragingly, respondents also noted positive effects including greater connection with family, more time for self-care, and motivation to recover.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.29.20116475", + "rel_abs": "IntroductionNon-pharmaceutical interventions to facilitate response to the COVID-19 pandemic, a disease caused by novel coronavirus SARS-CoV-2, are urgently needed. Using the WHO health emergency and disaster risk management (health-EDRM) framework, behavioural measures for droplet-borne communicable disease, with their enabling and limiting factors at various implementation levels were evaluated.\n\nSources of dataKeyword search was conducted in PubMed, Google Scholar, Embase, Medline, Science Direct, WHO and CDC online publication database. Using OCEBM as review criteria, 105 English-language articles, with ten bottom-up, non-pharmaceutical prevention measures, published between January 2000 and May 2020 were identified and examined.\n\nAreas of AgreementEvidence-guided behavioural measures against COVID-19 transmission for global at-risk communities are identified.\n\nArea of ConcernStrong evidence-based systematic behavioural studies for COVID-19 prevention are lacking.\n\nGrowing pointsVery limited research publications are available for non-pharmaceutical interventions to facilitate pandemic response.\n\nAreas timely for researchResearch with strong implementation feasibility that targets resource-poor settings with low baseline Health-EDRM capacity is urgently need.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Jet D. Termorshuizen", - "author_inst": "Karolinska Institutet" + "author_name": "Emily Ying Yang Chan", + "author_inst": "Collaborating Centre for Oxford University and CUHK for Disaster and Medical Humanitarian Response (CCOUC), The Chinese University of Hong Kong, Hong Kong, Chin" }, { - "author_name": "Hunna J. Watson", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Tayyab Salim Shahzada", + "author_inst": "JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China" }, { - "author_name": "Laura M. Thornton", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Tiffany Sze Tung Sham", + "author_inst": "JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China" }, { - "author_name": "Stina Borg", - "author_inst": "Karolinska Institutet" + "author_name": "Caroline Dubois", + "author_inst": "GX Foundation, Hong Kong, China" }, { - "author_name": "Rachael E. Flatt", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Zhe Huang", + "author_inst": "Collaborating Centre for Oxford University and CUHK for Disaster and Medical Humanitarian Response (CCOUC), The Chinese University of Hong Kong, Hong Kong, Chin" }, { - "author_name": "Casey M. MacDermod", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Sida Liu", + "author_inst": "Collaborating Centre for Oxford University and CUHK for Disaster and Medical Humanitarian Response (CCOUC), The Chinese University of Hong Kong, Hong Kong, Chin" }, { - "author_name": "Lauren E. Harper", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Janice Ying-en Ho", + "author_inst": "Collaborating Centre for Oxford University and CUHK for Disaster and Medical Humanitarian Response (CCOUC), The Chinese University of Hong Kong, Hong Kong, Chin" }, { - "author_name": "Eric F. van Furth", - "author_inst": "Leiden University Medical Center" + "author_name": "Kevin KC Hung", + "author_inst": "Accident & Emergency Medicine Academic Unit, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China" }, { - "author_name": "Christine M. Peat", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Kin On Kwok", + "author_inst": "The Chinese University of Hong Kong" }, { - "author_name": "Cynthia M. Bulik", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Ryoma Kayano", + "author_inst": "WHO Centre for Health Development, Kobe, Japan" + }, + { + "author_name": "Rajib Shaw", + "author_inst": "Keio University, Japan" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.05.29.20116921", @@ -1392167,81 +1392617,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.25.20113050", - "rel_title": "Cumulative incidence and diagnosis of SARS-CoV-2 infection in New York", + "rel_doi": "10.1101/2020.05.27.20112987", + "rel_title": "Identifying the measurements required to estimate rates of COVID-19 transmission, infection, and detection, using variational data assimilation", "rel_date": "2020-05-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.25.20113050", - "rel_abs": "ImportanceNew York State (NYS) is an epicenter of the United States COVID-19 epidemic. Reliable estimates of cumulative incidence of SARS-CoV-2 infection in the population are critical to tracking the extent of transmission and informing policies, but US data are lacking, in part because societal closure complicates study conduct.\n\nObjectiveTo estimate the cumulative incidence of SARS-CoV-2 infection and percent of infections diagnosed in New York State, overall and by region, age, sex, and race and ethnicity.\n\nDesignStatewide cross-sectional seroprevalence study, conducted April 19-28, 2020.\n\nSettingGrocery stores (n=99) located in 26 counties throughout NYS, which were essential businesses that remained open during a period of societal closure and attract a heterogenous clientele.\n\nParticipantsConvenience sample of patrons [≥]18 years and residing in New York State, recruited consecutively upon entering stores and via an in-store flyer.\n\nExposuresRegion (New York City, Westchester/Rockland, Long Island, Rest of New York State), age, sex, race and ethnicity.\n\nMain OutcomesPrimary outcome: cumulative incidence of SARS-CoV-2 infection, based on dry-blood spot (DBS) SARS-CoV-2 antibody reactivity; secondary outcome: percent of infections diagnosed.\n\nResultsAmong 15,101 adults with suitable DBS specimens, 1,887 (12.5%) were reactive using a validated SARS-CoV-2 IgG microsphere immunoassay (sensitivity 87.9%, specificity 99.75%). Following post-stratification weighting on region, sex, age, and race and ethnicity and adjustment for assay characteristics, estimated cumulative incidence through March 29 was 14.0% (95% CI: 13.3-14.7%), corresponding to 2,139,300 (95% CI: 2,035,800-2,242,800) infection-experienced adults. Cumulative incidence was higher among Hispanic/Latino (29.2%, 95% CI: 27.2-31.2%), non-Hispanic black/African American (20.2% 95% CI, 18.1-22.3%), and non-Hispanic Asian (12.4%, 95% CI: 9.4-15.4%) adults than non-Hispanic white adults (8.1%, 95% CI: 7.4-8.7%, p<.0001). Cumulative incidence was highest in New York City (NYC) 22.7% (95% CI: 21.5%-24.0). Dividing diagnoses reported to NYS by estimated infection-experienced adults, an estimated 8.9% (95% CI: 8.4-9.3%) of infections were diagnosed, with those [≥]55 years most likely to be diagnosed (11.3%, 95% CI: 10.4-12.2%).\n\nConclusions and RelevanceOver 2 million adults were infected through late March 2020, with substantial variations by subpopulations. As this remains below herd immunity thresholds, monitoring, testing, and contact tracing remain essential public health strategies.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.27.20112987", + "rel_abs": "We demonstrate the ability of statistical data assimilation to identify the measurements required for accurate state and parameter estimation in an epidemiological model for the novel coronavirus disease COVID-19. Our context is an effort to inform policy regarding social behavior, to mitigate strain on hospital capacity. The model unknowns are taken to be: the time-varying transmission rate, the fraction of exposed cases that require hospitalization, and the time-varying detection probabilities of new asymptomatic and symptomatic cases. In simulations, we obtain accurate estimates of undetected (that is, unmeasured) infectious populations, by measuring the detected cases together with the recovered and dead - and without assumed knowledge of the detection rates. These state estimates require a measurement of the recovered population, and are tolerant to low errors in that measurement. Further, excellent estimates of all quantities are obtained using a temporal baseline of 112 days, with the exception of the time-varying transmission rate at times prior to the implementation of social distancing. The estimation of this transmission rate is sensitive to contamination in the data, highlighting the need for accurate and uniform methods of reporting. Finally, we employ the procedure using real data from Italy reported by Johns Hopkins. The aim of this paper is not to assign extreme significance to the results of these specific experiments per se. Rather, we intend to exemplify the power of SDA to determine what properties of measurements will yield estimates of unknown model parameters to a desired precision - all set within the complex context of the COVID-19 pandemic.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Eli S Rosenberg", - "author_inst": "University at Albany School of Public Health" - }, - { - "author_name": "James M Tesoriero", - "author_inst": "New York State Department of Health" - }, - { - "author_name": "Elizabeth M Rosenthal", - "author_inst": "University at Albany School of Public Health" - }, - { - "author_name": "Rakkoo Chung", - "author_inst": "New York State Department of Health" - }, - { - "author_name": "Meredith A Barranco", - "author_inst": "University at Albany School of Public Health" - }, - { - "author_name": "Linda M Styer", - "author_inst": "Wadsworth Center, New York State Department of Health" - }, - { - "author_name": "Monica M Parker", - "author_inst": "Wadsworth Center, New York State Department of Health" - }, - { - "author_name": "Shu-Yin John Leung", - "author_inst": "New York State Department of Health" - }, - { - "author_name": "Johanne Morne", - "author_inst": "New York State Department of Health" - }, - { - "author_name": "Danielle Greene", - "author_inst": "New York State Department of Health" - }, - { - "author_name": "David R Holtgrave", - "author_inst": "University at Albany School of Public Health" - }, - { - "author_name": "Dina Hoefer", - "author_inst": "New York State Department of Health" - }, - { - "author_name": "Jessica Kumar", - "author_inst": "New York State Department of Health" - }, - { - "author_name": "Tomoko Udo", - "author_inst": "University at Albany School of Public Health" + "author_name": "Eve Armstrong", + "author_inst": "New York Institute of Technology" }, { - "author_name": "Brad Hutton", - "author_inst": "New York State Department of Health" + "author_name": "Jaline Gerardin", + "author_inst": "Northwestern University" }, { - "author_name": "Howard A Zucker", - "author_inst": "New York State Department of Health" + "author_name": "Manuela Runge", + "author_inst": "Northwestern University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1393505,29 +1393903,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.29.20116749", - "rel_title": "Can medication mitigate the need for a strict lock down?: A mathematical study of control strategies for COVID-19 infection", + "rel_doi": "10.1101/2020.05.29.20117044", + "rel_title": "Predicting Growth of COVID-19 Confirmed Cases in Each U.S. County with a Population of 50,000 or More", "rel_date": "2020-05-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.29.20116749", - "rel_abs": "We formulate a deterministic epidemic model to study the effects of medication on the transmission dynamics of Corona Virus Disease (COVID-19). We are especially interested in how the availability of medication could change the necessary quarantine measures for effective control of the disease. We model the transmission by extending the SEIR model to include asymptomatic, quarantined, isolated and medicated population compartments. We calculate the basic reproduction number R0 and show that for R0 < 1 the disease dies out and for R0 > 1 the disease is endemic. Using sensitivity analysis we establish that R0 is most sensitive to the rates of quarantine and medication. We also study how the effectiveness and the rate of medication along with the quarantine rate affect R0. We devise optimal quarantine, medication and isolation strategies, noting that availability of medication reduces the duration and severity of the lock-down needed for effective disease control. Our study also reinforces the idea that with the availability of medication, while the severity of the lock downs can be eased over time some social distancing protocols need to be observed, at least till a vaccine is found. We also analyze the COVID-109 outbreak data for four different countries, in two of these, India and Pakistan the curve is still rising, and in he other two, Italy and Spain, the epidemic curve is now falling due to effective quarantine measures. We provide estimates of R0 and the proportion of asymptomatic individuals in the population for these countries.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.29.20117044", + "rel_abs": "A simple model of local spread of COVID-19 is needed to assist local governments and health care providers prepare for surges of clinical cases in their communities. National and state based models are inadequate because the virus is introduced and spreads at different rates in local areas. In the U.S. as of July 3, 2020, 73 percent of cases and 84 percent of deaths occurred in the 200 counties with the most cases and deaths. Each county has its own function of cases in time that can be used to predict increases in reported cases two weeks in advance for each of 988 counties in the U.S. with populations of 50,000 or more inhabitants. A logarithmic model based on growth in cases during the past 30 days is substantially predictive of increase in cases during the subsequent 14 days. Predicted increase in cases for the 988 U.S. counties will be published online daily.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Mohsin Ali", - "author_inst": "Lahore University of Management Sciences Lahore" - }, - { - "author_name": "Mudassar Imran", - "author_inst": "Gulf University for Science & Technology, Mishref, Kuwait" - }, - { - "author_name": "Adnan Khan", - "author_inst": "Lahore University of Management Sciences" + "author_name": "Leon S Robertson", + "author_inst": "Yale University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1395031,39 +1395421,51 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.05.27.120121", - "rel_title": "Evidence for anti-viral effects of complete Freunds adjuvant in the mouse model of enterovirus infection", + "rel_doi": "10.1101/2020.05.28.120444", + "rel_title": "Assessment of Inactivation Procedures for SARS-CoV-2", "rel_date": "2020-05-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.27.120121", - "rel_abs": "Group B Coxsackieviruses belonging to the genus, Enterovirus, contain six serotypes that induce various diseases, whose occurrence may involve the mediation of more than one serotype. We recently identified immunogenic epitopes within CVB3 viral protein 1 that induce anti-viral T cell responses in mouse models of CVB infections. In our investigations to determine the protective responses of the viral epitopes, we unexpectedly noted that animals immunized with complete Freunds adjuvant (CFA) alone and later challenged with CVB3 were completely protected against myocarditis. Similarly, the pancreatitis-inducing ability of CVB3 was remarkably reduced to only 10% in the CFA group as opposed to 73.3% in the control group that received no CFA. Additionally, no mortalities were noted in the CFA group, whereas 40% of control animals died during the course of 21 days post-infection with CVB3. Taken together, our data suggest that the adjuvant effects of CFA may be sufficient for protection against CVB infections. These observations may provide new insights into our understanding of the occurrence of viral infections. One example is Coronavirus disease-19 (COVID-19) as individuals suffering from COVID-19 who have been vaccinated with Bacillus Calmette-Guerin appear to have fewer morbidities and mortalities than unvaccinated individuals.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.28.120444", + "rel_abs": "Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of Coronavirus disease 2019 (COVID-19), presents a challenge to laboratorians and healthcare workers around the world. Handling of biological samples from individuals infected with the SARS-CoV-2 virus requires strict biosafety and biosecurity measures. Within the laboratory, non-propagative work with samples containing the virus requires, at minimum, Biosafety Level-2 (BSL-2) techniques and facilities. Therefore, handling of SARS-CoV-2 samples remains a major concern in areas and conditions where biosafety and biosecurity for specimen handling is difficult to maintain, such as in rural laboratories or austere field testing sites. Inactivation through physical or chemical means can reduce the risk of handling live virus and increase testing ability worldwide. Herein we assess several chemical and physical inactivation techniques employed against SARS-CoV-2 isolates from Cambodian COVID-19 patients. This data demonstrates that all chemical (AVL, inactivating sample buffer and formaldehyde) and heat treatment (56{degrees}C and 98{degrees}C) methods tested completely inactivated viral loads of up to 5 log10.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Arunakumar Gangaplara", - "author_inst": "Laboratory of Early Sickle Mortality Prevention, Cellular and Molecular Therapeutics Branch, National Heart, Lung, and Blood Institute, National Institutes of H" + "author_name": "Heidi Auerswald", + "author_inst": "Virology Unit, Institut Pasteur du Cambodge, Institut Pasteur International Network, Phnom Penh, Cambodia" }, { - "author_name": "Chandirasegaran Massilamany", - "author_inst": "CRISPR Therapeutics" + "author_name": "Sokhoun Yann", + "author_inst": "Virology Unit, Institut Pasteur du Cambodge, Institut Pasteur International Network, Phnom Penh, Cambodia" }, { - "author_name": "Ninaad Lasrado", - "author_inst": "University of Nebraska - Lincoln" + "author_name": "Sokha Dul", + "author_inst": "Naval Medical Research Unit TWO, Phnom Penh, Cambodia" }, { - "author_name": "David Steffen", - "author_inst": "University of Nebraska - Lincoln" + "author_name": "Saraden In", + "author_inst": "Virology Unit, Institut Pasteur du Cambodge, Institut Pasteur International Network, Phnom Penh, Cambodia" }, { - "author_name": "Jay Reddy", - "author_inst": "University of Nebraska-Lincoln" + "author_name": "Philippe Dussart", + "author_inst": "Virology Unit, Institut Pasteur du Cambodge, Institut Pasteur International Network, Phnom Penh, Cambodia" + }, + { + "author_name": "Nicholas J Martin", + "author_inst": "Naval Medical Research Unit TWO, Singapore" + }, + { + "author_name": "Erik A Karlsson", + "author_inst": "Virology Unit, Institut Pasteur du Cambodge, Institut Pasteur International Network, Phnom Penh, Cambodia" + }, + { + "author_name": "Jose A Garcia-Rivera", + "author_inst": "Naval Medical Research Unit TWO, Phnom Penh, Cambodia" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.05.24.20101238", @@ -1396549,65 +1396951,41 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.05.26.114033", - "rel_title": "Enantiomers of Chloroquine and Hydroxychloroquine Exhibit Different Activities Against SARS-CoV-2 in vitro, Evidencing S-Hydroxychloroquine as a Potentially Superior Drug for COVID-19", + "rel_doi": "10.1101/2020.05.27.118752", + "rel_title": "SARS-CoV-2 envelope protein topology in eukaryotic membranes", "rel_date": "2020-05-27", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.26.114033", - "rel_abs": "In all of the clinical trials for COVID-19 conducted thus far and among those ongoing involving chloroquine or hydroxychloroquine, the drug substance used has invariably been chloroquine (CQ) diphosphate or hydroxychloroquine (HCQ) sulfate, i.e., the phosphoric or sulfuric acid salt of a racemic mixture of R- and S-enantiomer (50/50), respectively. As a result, the clinical outcome from previous CQ or HCQ trials were, in fact, the collective manifestation of both R and S- enantiomers with inherent different pharmacodynamic and pharmacokinetic properties, and toxicity liabilities. Our data for the first time demonstrated the stereoselective difference of CQ and HCQ against live SARS-CoV-2 virus in a Biosafety Level 3 laboratory. S-chloroquine (S-CQ) and S-hydroxychloroquine (S-HCQ) significantly more active against SARS-CoV-2, as compared to R-CQ and R-HCQ, respectively. In addition, Mpro, as one of the critical enzymes for viral transcription and replication, also exhibited an enantioselective binding affinity toward the S-enantiomers. The most significant finding from this study is the pronounced difference of the two enantiomers of CQ and HCQ observed in hERG inhibition assay. The IC50 value of S-HCQ was higher than 20 M against hERG channel, which was much less active over all tested CQ and HCQ compounds. Moreover, S-HCQ alone did not prolong QT interval in guinea pigs after 3 days and 6 days of administration, indicating a much lower cardiac toxicity potential. With these and previous findings on the enantio-differentiated metabolism, we recommend that future clinical studies should employ S-HCQ, substantially free of the R-enantiomer, to potentially improve the therapeutic index for the treatment of COVID-19 over the racemic CQ and HCQ.", - "rel_num_authors": 12, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.27.118752", + "rel_abs": "Coronavirus E protein is a small membrane protein found in the virus envelope. Different coronavirus E proteins share striking biochemical and functional similarities, but sequence conservation is limited. In this report, we studied the E protein topology from the new SARS-CoV-2 virus both in microsomal membranes and in mammalian cells. Experimental data reveal that E protein is a single-spanning membrane protein with the N-terminus being translocated across the membrane, while the C-terminus is exposed to the cytoplasmic side (Ntlum/Ctcyt). The defined membrane protein topology of SARS-CoV-2 E protein may provide a useful framework to understand its interaction with other viral and host components and establish the basis to tackle the pathogenesis of SARS-CoV-2.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Guanguan Li", - "author_inst": "Southern University of Science and Technology" - }, - { - "author_name": "Jing Sun", - "author_inst": "GIRH" - }, - { - "author_name": "Yi-You Huang", - "author_inst": "Sun Yat-Sen University" - }, - { - "author_name": "Yingjun Li", - "author_inst": "Southern University of Science and Technology" - }, - { - "author_name": "Yongjie Shi", - "author_inst": "Southern University of Science and Technology" - }, - { - "author_name": "Zhe Li", - "author_inst": "Sun Yat-Sen University" - }, - { - "author_name": "Xiang Li", - "author_inst": "Guangdong Province Key Laboratory of Laboratory Animals & Cardiovascular Model Research Center, Guangdong Laboratory Animals Monitoring Institute" + "author_name": "Gerard Duart", + "author_inst": "University of Valencia" }, { - "author_name": "Feng Hua Yang", - "author_inst": "Guangdong Province Key Laboratory of Laboratory Animals & Cardiovascular Model Research Center, Guangdong Laboratory Animals Monitoring Institute" + "author_name": "Maria J. Garcia-Murria", + "author_inst": "University of Valencia" }, { - "author_name": "Jincun Zhao", - "author_inst": "GIRH" + "author_name": "Brayan Grau", + "author_inst": "University of Valencia" }, { - "author_name": "Hai-Bin LUO", - "author_inst": "Sun Yat-Sen University" + "author_name": "Jose M. Acosta-Caceres", + "author_inst": "University of Valencia" }, { - "author_name": "Tony Y. Zhang", - "author_inst": "Tyligand Bioscience (Shanghai) Limited" + "author_name": "Luis Martinez-Gil", + "author_inst": "University of Valencia" }, { - "author_name": "Xumu Zhang", - "author_inst": "Southern University of Science and Technology" + "author_name": "Ismael Mingarro", + "author_inst": "University of Valencia" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "biochemistry" }, @@ -1398091,17 +1398469,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.18.20106146", - "rel_title": "Forecasting COVID-19 cases and deaths in epidemic-mitigating European countries by Richards function-based regression analyses", + "rel_doi": "10.1101/2020.05.19.20106344", + "rel_title": "Ethnic Disparities in Hospitalization for COVID-19: a Community-Based Cohort Study in the UK", "rel_date": "2020-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.18.20106146", - "rel_abs": "The COVID-19 pandemic has hit many countries, and in some European countries it has been mitigated since April. Here we applied Richards function to simulate and forecast the course of COVID-19 epidemics in Italy, Spain, France, Germany, Turkey, Belgium, Ireland, Netherlands, Portugal and Switzerland. Potential total COVID-19 confirmed cases in these countries were estimated to be 240400{+/-}1300, 294100{+/-}4000, 178500{+/-}800, 176900{+/-}700, 155400{+/-}1000, 57900{+/-}400, 24000{+/-}200, 46200{+/-}300, 30000{+/-}300 and 30700{+/-}100 respectively. Most of these countries are predicted to approach ending stage between late May and early June such that daily new cases will become minimal, which may guide societal and economic restorations. In addition, total COVID-19 deaths were estimated to be 33500 {+/-}300, 28200{+/-}200, 27800{+/-}200, 8740{+/-}80, 4500 {+/-}30, 9250{+/-}70, 1530{+/-}20, 6240{+/-}50, 1380{+/-}10 and 1960{+/-}8, respectively. To our best knowledge, this is the first study forecasting the COVID-19 epidemic by applying the Richard function-based regression analysis.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.19.20106344", + "rel_abs": "ImportanceDifferentials in COVID-19 incidence, hospitalization and mortality according to ethnicity are being reported but their origin is uncertain.\n\nObjectiveWe aimed to explain any ethnic differentials in COVID-19 hospitalization based on socioeconomic, lifestyle, mental and physical health factors.\n\nDesignProspective cohort study with national registry linkage to hospitalisation for COVID-19.\n\nSettingCommunity-dwelling.\n\nParticipants340,966 men and women (mean age 56.2 (SD=8.1) years; 54.3% women) residing in England from the UK Biobank study.\n\nExposuresEthnicity classified as White, Black, Asian, and Others.\n\nMain Outcome(s) and Measure(s)Cases of COVID-19 serious enough to warrant a hospital admission in England from 16-March-2020 to 26-April-2020.\n\nResultsThere were 640 COVID-19 cases (571/324,306 White, 31/4,485 Black, 21/5,732 Asian, 17/5,803 Other). Compared to the White study members and after adjusting for age and sex, Black individuals had over a 4-fold increased risk of being hospitalised (odds ratio; 95% confidence interval: =4.32; 3.00-6.23), and there was a doubling of risk in the Asian group (2.12; 1.37, 3.28) and the other non-white group (1.84; 1.13, 2.99). After controlling for 15 confounding factors which included neighbourhood deprivation, education, number in household, smoking, markers of body size, inflammation, and glycated haemoglobin, these effect estimates were attenuated by 33% for Blacks, 52% for Asians and 43% for Other, but remained raised for Blacks (2.66; 1.82, 3.91), Asian (1.43; 0.91, 2.26) and other non-white groups (1.41; 0.87, 2.31).\n\nConclusions and RelevanceOur findings show clear ethnic differences in risk of hospitalization for COVID-19 which do not appear to be fully explained by known explanatory factors. If replicated, our results have implications for health policy, including the targeting of prevention advice and vaccination coverage.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSWhat explains ethnic differences in rates of hospitalisation for COVID-19?\n\nFindingIn a large, community-based cohort, Black and Asian individuals had a markedly higher risk of hospitalisation. After adjustment for socioeconomic, lifestyle, comorbidities, and biomarkers, Black individuals still experienced more than a doubling of risk compared to white individuals though the effect for the Asian group was diminished.\n\nMeaningIn England, the marked ethnic disparities in the risk of hospitalisation for COVID-19, if replicated, has implications for health policy, including the targeting of prevention advice and vaccination coverage.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "XINMIAO FU", - "author_inst": "Fujian Normal University" + "author_name": "Camille Lassale", + "author_inst": "Hospital del Mar Research Institute IMIM" + }, + { + "author_name": "Bamba Gaye", + "author_inst": "Paris Cardiovascular Research Center-INSERM U970" + }, + { + "author_name": "Mark Hamer", + "author_inst": "University College London" + }, + { + "author_name": "Catharine R Gale", + "author_inst": "University of Southampton" + }, + { + "author_name": "G David Batty", + "author_inst": "University College London" } ], "version": "1", @@ -1399749,39 +1400143,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.19.20107094", - "rel_title": "Ethnic and regional variation in hospital mortality from COVID-19 in Brazil", + "rel_doi": "10.1101/2020.05.19.20107227", + "rel_title": "Determinants of cardiac adverse events of chloroquine and hydroxychloroquine in 20 years of drug safety surveillance reports", "rel_date": "2020-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.19.20107094", - "rel_abs": "BackgroundThe COVID-19 pandemic is quickly spreading throughout Brazil, which is rapidly ascending the ranking of countries with the highest number of cases and deaths. A particularly unstable federal regime and fragile socioeconomic situation is likely to have contributed to the impact of the disease. Amid this crisis there is substantial concern in the possible socioeconomic, geopolitical and ethnic inequity of the impact of COVID-19 on the countrys particularly diverse population.\n\nMethodsWe performed a cross-sectional observational study of COVID-19 hospital mortality using observational data from the SIVEP-Gripe dataset. We present descriptive statistics to quantify the COVID-19 pandemic in Brazil. We assess the importance of regional factors such as education, income and health either on a state-by-state basis or by splitting Brazil into a North and a Central-South region. Mixed-effects survival analysis was used to estimate the effects of ethnicity and comorbidity at an individual level in the context of regional variation.\n\nFindingsOur results show that, compared to branco comparators, hospitalised pardo and preto Brazilians have significantly higher risk of mortality, with hazard ratios and 95% CI of 1.47 (1.33-1.58) and 1.32 (1.15-1.52), respectively. In particular, pardo ethnicity was the second most important risk factor (after age). We also found that hospitalised Brazilians in North regions tend to have more comorbidities than in the Central-South, with similar proportions between the various ethnic groups. Finally, we found that states in the North have a higher hazard ratio as compared to the Central-South, and that Rio de Janeiro obtained one of the highest hazard ratios, similar to the ones of the more underdeveloped Pernambuco and Amazonas.\n\nInterpretationOur results can be interpreted according to the interplay of two independent, but correlated, effects: i) mortality by COVID-19 increases going North (vertical effect), ii) mortality increases for the pardo and preto population (horizontal effect). We speculate that the vertical effect is driven by increasing levels of comorbidity in Northern regions where levels of socioeconomic development are lower, whereas the horizontal effect may be related to lower levels of healthcare access or availability (including intensive care) for pardo and preto Brazilians. For most states the vertical and horizontal effects are correlated giving a larger cumulative mortality. However, Rio de Janeiro was found to be an outlier to this trend: It has an ethnicity composition (horizontal effect) similar to the states in the North region, despite high levels of socioeconomic development (vertical effect). Our analysis motivates an urgent effort on the part of Brazilian authorities to consider how the national response to COVID-19 can better protect pardo and preto Brazilians as well as the population of poorer states from their higher death risk from SARS-CoV-2 infection.\n\nFundingNone.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.19.20107227", + "rel_abs": "Chloroquine (CQ) and hydroxychloroquine (HCQ) are on the World Health Organizations List of Essential Medications for treating non-resistant malaria, rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). In addition, both drugs are currently used off-label in hospitals worldwide and in numerous clinical trials for the treatment of SARS-CoV-2 infection. However, CQ and HCQ use has been associated with cardiac side effects, which is of concern due to the higher risk of COVID-19 complications in patients with heart related disorders, and increased mortality associated with COVID-19 cardiac complications. In this study we analyzed over thirteen million adverse event reports form the United States Food and Drug Administration Adverse Event Reporting System to confirm and quantify the association of cardiac side effects of CQ and HCQ. Additionally, we identified several confounding factors, including male sex, NSAID coadministration, advanced age, and prior diagnoses contributing to the risk of drug related cardiotoxicity. These findings may help guide therapeutic decision making and ethical trial design for COVID-19 treatment.", "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Pedro Otavio Baqui", - "author_inst": "Federal University of Espirito Santo" + "author_name": "Isaac V Cohen", + "author_inst": "Clinical Pharmacology and Therapeutics (CPT) Postdoctoral Training Program, University of California San Francisco, San Francisco, California, United States" }, { - "author_name": "Ioana Bica", - "author_inst": "University of Oxford; The Alan Turing Institute" + "author_name": "Tigran Makunts", + "author_inst": "Oak Ridge Institute of Science and Education (ORISE), Clinical Pharmacology and Machine Learning fellowship at the Center for Drug Evaluation and Research, Unit" }, { - "author_name": "Valerio Marra", - "author_inst": "Federal University of Espirito Santo" + "author_name": "Talar Moumedjian", + "author_inst": "Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, United States" }, { - "author_name": "Ari Ercole", - "author_inst": "University of Cambridge" + "author_name": "Masara Issa", + "author_inst": "Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, United States" }, { - "author_name": "Mihaela Van Der Schaar", - "author_inst": "The Alan Turing Institute; University of Cambridge; University of California Los Angeles" + "author_name": "Ruben Abagyan", + "author_inst": "Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, United States" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pharmacology and therapeutics" }, { "rel_doi": "10.1101/2020.05.19.20107532", @@ -1401155,55 +1401549,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.21.20109710", - "rel_title": "Prone Cardiopulmonary Resuscitation: A Rapid Scoping and Expanded Grey Literature Review for the COVID-19 Pandemic", + "rel_doi": "10.1101/2020.05.23.20110452", + "rel_title": "Comprehensive genome analysis of 6,000 USA SARS-CoV-2 isolates reveals haplotype signatures and localized transmission patterns by state and by country", "rel_date": "2020-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.21.20109710", - "rel_abs": "Prone Cardiopulmonary ResuscitationA Rapid Scoping and Expanded Grey Literature Review for the COVID-19 Pandemic\n\nAimTo rapidly identify and summarize the available science on prone resuscitation. To determine the value of undertaking a systematic review on this topic; and to identify knowledge gaps to aid future research, education and guidelines.\n\nMethodsThis review was guided by specific methodological framework and reporting items (PRISMA-ScR). We included studies, cases and grey literature regarding prone position and CPR/cardiac arrest. The databases searched were MEDLINE, Embase, CINAHL, Cochrane CENTRAL, Cochrane Database of Systematic Reviews, Scopus and Google Scholar. Expanded grey literature searching included internet search engine, targeted websites and social media.\n\nResultsOf 453 identified studies, 24 (5%) studies met our inclusion criteria. There were four prone resuscitation-relevant studies examining: blood and tidal volumes generated by prone compressions; prone compression quality metrics on a manikin; and chest computed tomography scans for compression landmarking. Twenty case reports/series described the resuscitation of 25 prone patients. Prone compression quality was assessed by invasive blood pressure monitoring, exhaled carbon dioxide and pulse palpation. Recommended compression location was zero-to-two vertebral segments below the scapulae. Twenty of 25 cases (80%) survived prone resuscitation, although few cases reported long term outcome. Seven cases described full neurological recovery.\n\nConclusionThis scoping review did not identify sufficient evidence to justify a systematic review or modified resuscitation guidelines. It remains reasonable to initiate resuscitation in the prone position if turning the patient supine would lead to delays or risk to providers or patients. Prone resuscitation quality can be judged using end-tidal CO2, and arterial pressure tracing, with patients turned supine if insufficient.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.23.20110452", + "rel_abs": "Genomic analysis of SARS-CoV-2 sequences is crucial in determining the effectiveness of prudent safer at home measures in the United States (US). By haplotype analysis of 6,356 US isolates, we identified a pattern of strongly localized outbreaks at the city-, state-, and country-levels, and temporal transmissions. This points to the effectiveness of existing travel restriction policies and public health measures in controlling the transmission of SARS-CoV-2.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Matthew John Douma", - "author_inst": "University of Alberta" - }, - { - "author_name": "Ella MacKenzie", - "author_inst": "University of Guelph" - }, - { - "author_name": "Tess Loch", - "author_inst": "Cumming School of Medicine, University of Calgary" - }, - { - "author_name": "Maria C Tan", - "author_inst": "John W Scott Health Sciences Library, University of Alberta" - }, - { - "author_name": "Dustin Anderson", - "author_inst": "Department of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta" + "author_name": "Lishuang Shen", + "author_inst": "Children's Hospital Los Angeles" }, { - "author_name": "Christopher Picard", - "author_inst": "University of Alberta Faculty of Nursing & Covenant Health" + "author_name": "Jennifer Dien Bard", + "author_inst": "Children's Hospital Los Angeles" }, { - "author_name": "Lazar Milovanovic", - "author_inst": "Department of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta" + "author_name": "Jaclyn A Biegel", + "author_inst": "Children's Hospital Los Angeles" }, { - "author_name": "Domhnall O'Dochartaigh", - "author_inst": "Edmonton Zone Emergency Departments, Alberta Health Services; Shock Trauma Air Rescue Society, Edmonton, Alberta, Canada." + "author_name": "Alexander R Judkins", + "author_inst": "Children's Hospital Los Angeles" }, { - "author_name": "Peter G Brindley", - "author_inst": "Department of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta" + "author_name": "Xiaowu Gai", + "author_inst": "Children's Hospital Los Angeles" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.05.20.20107755", @@ -1402877,43 +1403255,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.23.20111054", - "rel_title": "Verification of two Alternative Do-it-yourself Equipment Respirators Seal as COVID-19 Protection (VADERS-CoV): a quality assessment pilot study", + "rel_doi": "10.1101/2020.05.24.20111666", + "rel_title": "Evaluation of the disinfecting capacity of ozone in emergency vehicles.", "rel_date": "2020-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.23.20111054", - "rel_abs": "BackgroundDuring the ongoing COVID-19 pandemic, healthcare workers are facing shortage in personal protective equipment, especially adequate respirators. Alternative do-it-yourself respirators (ADR) emerge, without any proof of protection.\n\nObjectiveVerify seal potential of two ADR compared to a common FFP2 respirator.\n\nDesignQuality assessment pilot study.\n\nSettingTertiary Care Hospital.\n\nParticipantsTen anaesthesiology residents.\n\nInterventionsParticipants performed quantitative face-fit tests (QNFT) with three respirators to evaluate seal. A common FFP2 respirator was used as baseline (control group). ADR tested in this study are an Anaesthesia Face Mask (AFM) and a full-face Modified Snorkelling Mask (MSM) with a 3D-printed connector, both in conjunction with a breathing system filter.\n\nMain outcome measuresNon-inferior seal performance of ADR over FFP2, assessed by calculated QNFT based on measured individual fit factors, as defined by the Occupational Safety and Health Administration.\n\nResultsFor each respirator a total of 90 individual fit factor measurements were taken. Within the control group, seal failed in 37 (41%) measurements but only in 10 (11%) within the AFM group and in 6 (7%) within the MSM group (P < 0.001 respectively). However, when calculating the final, mean QNFT results, no statistically significant difference was found between respirators. Successful QNFT were determined for 5 out of 10 participants in the control group, for 8 in the AFM group (P = 0.25) and for 7 in the MSM group (P = 0.69).\n\nConclusionBoth ADR do have the potential to provide non inferior seal compared to a common FFP2 respirator. While AFM respirators are easily assembled, snorkelling masks must undergo significant but feasible modifications. Our results suggest that those ADR masks might be further investigated as they seem to be viable alternatives for situations when certified respirators are not available.\n\nTrial registrationClinicaltrials.gov identifier: NCT04375774", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.24.20111666", + "rel_abs": "ObjectiveAs a consequence of the health crisis arising from the SARS-CoV-2 coronavirus pandemic, ozone treatments are being applied as disinfectant in emergency vehicles, without objective evidence on its efficacy. Here we evaluate the efficacy of ozone treatment over bacterial strains and virus-like particles.\n\nMethodA preparation of a lentiviral vector (lentivector) and dried cultures of two bacterial strains (gram + Staphylococcus aureus and gram - Salmonella enterica ser. Enteritidis) were placed inside an ambulance at two different locations. The interior of the vehicle was subjected to 10 min and 20 min treatments (3 and 6 times the recommended time by the manufacturer). Following the treatments, lentivector preparations were titrated, and viable bacteria (colony forming units, CFUs) counted and compared to pre-treatment titers and infectious CFUs of the same lysates and cultures.\n\nResultsNone of the treatments significantly reduced either lentivector titer or the number of viable bacteria.\n\nConclusionsAt least in the analyzed conditions and for the microorganisms used in this study, it can be concluded that ozone treatment is not advisable for the disinfection of emergency vehicles.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Marco Pettinger", - "author_inst": "Department of Anaesthesiology, Cliniques Universitaires Saint Luc, Brussels" + "author_name": "Jorge Biurrun", + "author_inst": "Subdireccion de Urgencias de Navarra y Direccion Tecnica de la atencion a la Urgencia Vital" + }, + { + "author_name": "Begona Garcia", + "author_inst": "Navarrabiomed" + }, + { + "author_name": "Andrea Perez", + "author_inst": "Navarrabiomed" }, { - "author_name": "Mona Momeni", - "author_inst": "Department of Anaesthesiology, Cliniques Universitaires Saint Luc, Brussels" + "author_name": "Grazyna Kochan", + "author_inst": "Navarrabiomed" }, { - "author_name": "Clemence Michaud", - "author_inst": "Department of Anaesthesiology, Cliniques Universitaires Saint Luc, Brussels" + "author_name": "David Escors", + "author_inst": "Navarrabiomed" }, { - "author_name": "Michel Van Dyck", - "author_inst": "Department of Anaesthesiology, Cliniques Universitaires Saint Luc, Brussels" + "author_name": "Jose Crespo", + "author_inst": "Subdireccion de Urgencias de Navarra y Direccion Tecnica de la atencion a la Urgencia Vital" }, { - "author_name": "David Kahn", - "author_inst": "Department of Anaesthesiology, Cliniques Universitaires Saint Luc, Brussels" + "author_name": "Inigo Lasa", + "author_inst": "Navarrabiomed" }, { - "author_name": "Guillaume Lemaire", - "author_inst": "Department of Anaesthesiology, Cliniques Universitaires Saint Luc, Brussels" + "author_name": "Alfredo Echarri", + "author_inst": "Subdireccion de Urgencias de Navarra y Direccion Tecnica de la atencion a la Urgencia Vital." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "emergency medicine" }, { "rel_doi": "10.1101/2020.05.23.20111310", @@ -1404051,23 +1404437,55 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.21.20109728", - "rel_title": "Would India Really Touch the Peak of SARS COVID 19 Cases or Deaths in Near Future?", + "rel_doi": "10.1101/2020.05.23.20111062", + "rel_title": "Global lessons and Potential strategies in combating COVID-19 pandemic in Ethiopia:Systematic Review", "rel_date": "2020-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.21.20109728", - "rel_abs": "BackgroundThe Government, Health System and even an individual citizen of India is alarmed expecting the height of pandemic of SARS-COVID-19 in near future. Many experts worldwide predict it to happen in India between end of May and end of July.\n\nObjectivesThe aim of this research was to find an answer that whether India would come across the looming conditions of SARS-COVID-19 in coming days given the prevailing circumstances so far.\n\nMethodsThe proposed approach used fundamental concept of Statistics by fixing the standard reference to the number of daily new tests conducted by a country. We thus computed the percentage of daily new cases and daily new deaths, in using such references. The trends were studied using simple line chart. The theory of three sigma was also used to build the upper bound for daily new cases and deaths, specifically for India to see the extreme conditions.\n\nResultsThe analysis was done using data from January to till May 18, 2020 for India, Italy, USA and UK. The trend of India was almost fix between ~2% to ~6% till May 18, 2020. On contrary, Italy, USA and UK were touched the Peak on March 29, 2020 (24.38%), April 26, 2020 (23.51%) and April 24, 2020 (24.91%), respectively and declining since then. Similar trends were also noted in daily new deaths, except Italy.\n\nConclusionsThe proposed new concept for fixing universal reference provides a consistent and coherent results. It is thus clear from observed data so far that India is not going to encounter the frightened conditions or peak, like, Italy, USA, and UK for pandemic SARS-COVID-19, given the existing conditions, excluding the current migration.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.23.20111062", + "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19) is a rapidly emerging disease that has been classified a pandemic by the World Health Organization (WHO). In the absence of treatment for this virus, there is an urgent need to find alternative public health strategies to control the spread. Here, we have conducted an online search for all relevant public health interventions for COVID-19. We then characterize and summarize the global COVID-19 pandemic situation and recommend potential mitigation strategies in the context of Ethiopia.\n\nMethodsInitial search of Pub Med central and Google scholar was undertaken followed by analysis of the text words; COVID-19,SARS-CoV-2, Global lessons and Pandemic; A second search using all identified keywords including COVID-19, Epidemiology, Sociocultural, Ethiopia; thirdly, the reference list of all identified reports and articles were searched. Accordingly, of the 1,402 articles, 39 were included in the analysis for this review.\n\nResultCountries COVID-19 mitigation strategies widely varied. The most common global COVID-19 mitigation strategies include; whole of government approach including individual, community and environmental measures, detecting and isolating cases, contact tracing and quarantine, social and physical distancing measures including for mass gatherings and international travel measures. Models revealed that, social and physical distancing alone could prevent the pandemic from 60-95%, if timely and effectively implemented. Moreover, detecting and isolation of cases were found to be crucial while access to testing was found to the global challenge. Individual measures including proper hand washing were also reported to be effective measures in preventing the pandemic. Asymptomatic cases of COVID-19 ranged from 25% to 80% and as a result, countries are revising the case definition for early detection of mild symptomatic cases of COVID-19 with inclusion of Chills, Muscle pain and new loss of taste or smell in addition to Cough, Shortness of breath, Fever and Sore throat. Global reports also revealed that the incubation period of COVID-19 could go to 24 days. Ethiopia is also unique in the aspects of sociocultural prospects while more than 99.3% of the population has a religion. Moreover, 69% of the population is under the age of 29 years old and the health policy in the country focused on prevention and primary health care. All these could be potential entries and opportunities to combat COVID-19 pandemic in the context of Ethiopia.\n\nConclusionWhile recommendations may change depending on the level of outbreak, we conclude that in Most countries have benefited from early interventions and in setups like Africa including Ethiopia where health system capability is limited, community engagement supported by local evidence with strict implementation of social and physical distancing measures is mandatory. Active involvement of religious Institutions and mobilizing youth could be entry to increase public awareness in mitigating COVID-19. Community level case detection could enhance early identification of cases which could be implemented through the health extension program. Isolation and quarantine beyond 14 days could help identify long term carriers of COVID-19. Validation and use of rapid test kits could be vital to increase access for testing. Revision of case definitions for COVID-19 could be important for early detection and identification of mild symptomatic cases.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Pramod K. Gupta", - "author_inst": "Postgraduate Institute of Medical Education and Research" + "author_name": "Yimam Getaneh", + "author_inst": "Ethiopian Public Health Institute" + }, + { + "author_name": "Ajanaw Yizengaw", + "author_inst": "Ethiopian Public Health Institute" + }, + { + "author_name": "Sisay Adane", + "author_inst": "Ethiopian Public Health Institute" + }, + { + "author_name": "Kidist Zealiyas", + "author_inst": "Ethiopian Public Health Institute" + }, + { + "author_name": "Zelalem Abate", + "author_inst": "Clinton Health Access Initiative" + }, + { + "author_name": "Sileshi Leulseged", + "author_inst": "ICAP-Ethiopia" + }, + { + "author_name": "Hailemichael Desalegn", + "author_inst": "St. Paul's Hospital Millennium Medical Collage" + }, + { + "author_name": "Getnet Yimer", + "author_inst": "Global One Health Initiative,East Africal Regional office" + }, + { + "author_name": "Ebba Abate", + "author_inst": "Ethiopian Public Health Institute" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.05.23.112284", @@ -1405445,63 +1405863,51 @@ "category": "radiology and imaging" }, { - "rel_doi": "10.1101/2020.05.22.20110783", - "rel_title": "A Noncooperative Game Analysis for Controlling COVID-19 Outbreak", + "rel_doi": "10.1101/2020.05.20.20104786", + "rel_title": "COVID-19 knowledge, risk perception and precautionary behaviour among Nigerians: A moderated mediation approach", "rel_date": "2020-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.22.20110783", - "rel_abs": "COVID-19 is a global epidemic. Till now, there is no remedy for this epidemic. However, isolation and social distancing are seemed to be effective to control this pandemic. In this paper, we provide an analytical model on the effectiveness of the sustainable lockdown policy that accommodates both isolation and social distancing features of the individuals. To promote social distancing, we analyze a noncooperative game environment that provides an incentive for maintaining social distancing. Furthermore, the sustainability of the lockdown policy is also interpreted with the help of a game-theoretic incentive model for maintaining social distancing. Finally, an extensive numerical analysis is provided to study the impact of maintaining a social-distancing measure to prevent the Covid-19 outbreak. Numerical results show that the individual incentive increases more than 85% with an increasing percentage of home isolation from 25% to 100% for all considered scenarios. The numerical results also demonstrate that in a particular percentage of home isolation, the individual incentive decreases with an increasing number of individuals.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.20.20104786", + "rel_abs": "IntroductionIndividuals who have knowledge of an infectious disease and also perceive the risks associated with such infectious disease tend to engage more in precautionary behaviour; however, little is known about this association as it relates to the novel Coronavirus (COVID-19). There is possibility of moderated mediation effect in the association between these variables.\n\nObjectivesTo examine whether risk perception determines the association between COVID-19 knowledge and precautionary behaviour among Nigerians, taking into consideration the gender differentials that may exist in the process.\n\nDesignA web-based cross-sectional study.\n\nSettingParticipants were recruited via social media platform, WhatsApp using google form from March 28 to April 4, 2020.\n\nParticipants1500-Nigerian (mean age =27.43, SD=9.75 with 42.7% females and 57.3% males) were recruited from 180 cities in Nigeria using snowball sampling technique. They responded to an online survey form comprising demographic questions and adapted versions of the Ebola knowledge scale, SARS risk perception scale and a precautionary behavior scale.\n\nResultModerated mediation analysis showed that risk perception mediated the association between COVID-19 knowledge and precautionary behavior and this indirect effect was moderated by gender. Having correct knowledge of COVID-19 was linked to higher involvement in precautionary behavior through risk perception for females but not for males. COVID-19 awareness campaigns may target raising more awareness of the risks associated with the infection in order to make individuals engage more in precautionary behaviors.\n\nConclusionAwareness campaigns and psychological intervention strategies may be particularly important at the moment, for males more than females.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Anupam Kumar Bairagi", - "author_inst": "Kyung Hee University, Yongin-si, Gyeonggi-do, Rep. of Korea and Computer Science and Engineering Discipline, Khulna University, Khulna-9208, Bangladesh" - }, - { - "author_name": "Mehedi Masud", - "author_inst": "Department of Computer Science, Taif University, Taif, KSA" - }, - { - "author_name": "Do Hyeon Kim", - "author_inst": "Department of Computer Science and Engineering, Kyung Hee University, Yongin-si, Gyeonggi-do, Rep. of Korea" + "author_name": "Steven Kator Iorfa", + "author_inst": "University of Nigeria Nsukka" }, { - "author_name": "Md. Shirajum Munir", - "author_inst": "Department of Computer Science and Engineering, Kyung Hee University, Yongin-si, Gyeonggi-do, Rep. of Korea" + "author_name": "Iboro F.A. Ottu", + "author_inst": "University of Uyo, Uyo, Nigeria" }, { - "author_name": "Abdullah Al Nahid", - "author_inst": "Computer Science and Engineering Discipline, Khulna University, Khulna-9208, Bangladesh" - }, - { - "author_name": "Sarder Fakhrul Abedin", - "author_inst": "Department of Computer Science and Engineering, Kyung Hee University, Yongin-si, Gyeonggi-do, Rep. of Korea" + "author_name": "Rotimi Oguntayo", + "author_inst": "University of Ilorin" }, { - "author_name": "Kazi Masudul Alam", - "author_inst": "Computer Science and Engineering Discipline, Khulna University, Khulna-9208, Bangladesh" + "author_name": "Olusola Ayandele", + "author_inst": "The Polytechnic Ibadan" }, { - "author_name": "Sujit Biswas", - "author_inst": "Department of Computer Science and Engineering, Faridpur Engineering College, Faridpur, Bangladesh" + "author_name": "Samson O Kolawole", + "author_inst": "Nigeria Police Academy, Wudil, Kano, Nigeria" }, { - "author_name": "Sultan S Alshamrani", - "author_inst": "Department of Information Technology, Taif University, Taif, KSA" + "author_name": "Joshua C. Gandi", + "author_inst": "University of Jos, Jos, Nigeria" }, { - "author_name": "Zhu Han", - "author_inst": "Electrical and Computer Engineering Department, University of Houston, Houston, TX 77004, USA and also Department of Computer Science and Engineering, Kyung Hee" + "author_name": "Abdullahi L. Dangiwa", + "author_inst": "Federal University, Dutse, Nigeria" }, { - "author_name": "Choong Seon Hong", - "author_inst": "Department of Computer Science and Engineering, Kyung Hee University, Yongin-si, Gyeonggi-do, Rep. of Korea" + "author_name": "Peter O. Olapegba", + "author_inst": "University of Ibadan" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.05.24.20104414", @@ -1406651,93 +1407057,45 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.05.20.20107664", - "rel_title": "Management of mild COVID-19: Policy implications of initial experience in India", + "rel_doi": "10.1101/2020.05.19.20107490", + "rel_title": "Diligent medical activities of a publicly designated medical institution for infectious diseases pave the way for overcoming COVID-19: A positive message to people working at the cutting edge", "rel_date": "2020-05-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.20.20107664", - "rel_abs": "ObjectivesOngoing pandemic due to COVID-19 has spread across countries, surprisingly with variable clinical characteristics and outcomes. This study was aimed at describing clinical characteristics and outcomes of admitted patients with mild COVID-19 illness in the initial phase of pandemic in India.\n\nDesignRetrospective (observational) study.\n\nSettingCOVID facilities under AIIMS, New Delhi, where, isolation facilities were designed to manage patients with mild illness and dedicated COVID ICUs was created to cater patients with moderate to severe illness.\n\nParticipantsPatients aged 18 years or more, with confirmed illness were eligible for enrolment. Patients who were either asymptomatic or mildly ill at presentation were included. Patients with moderate to severe illness at admission, or incomplete clinical symptomatology records were excluded.\n\nMethodsData regarding demographic profile, comorbidities, clinical features, hospital course, treatment, details of results of RT-PCR for SARS-CoV-2 done at baseline and at day 14, chest radiographs (wherever available) as well as laboratory parameters was obtained retrospectively from the hospital records.\n\nMain outcome measuresFinal outcome was noted in terms of course of the disease, patients discharged, still admitted (at time of conclusion of study) or death.\n\nResultsOut of 231 cases included, majority were males(78{middle dot}3%) with a mean age of 39{middle dot}8 years. Comorbidities were present in 21{middle dot}2% of patients, diabetes mellitus and hypertension being most common. The most common symptoms were dry cough(81, 35%), fever(64, 27{middle dot}7%), sore throat(36, 15{middle dot}6%), and dyspnoea(24, 10{middle dot}4%); asymptomatic infection was noted in 108(46.8%) patients. Presence of comorbidities was an independent predictor of symptomatic disease (OR- 2{middle dot}66; 95% CI 1{middle dot}08 to 6{middle dot}53, p= 0{middle dot}03). None of the patients progressed to moderate to severe COVID-19. There were no deaths in this cohort.\n\nConclusionsPatients with mild disease at presentation had a stable disease course and therefore such cases can be managed outside hospital setting. A large proportion of patients remained asymptomatic throughout the course of infection and those with comorbidities are more likely to be symptomatic.\n\nTrial registrationNot applicable", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.19.20107490", + "rel_abs": "The analysis of systematically collected data for COVID-19 infectivity and death rates has revealed in many countries around the world a typical oscillatory pattern with a 7-days (circaseptan) period. Additionally, in some countries the 3.5-days (hemicircaseptan) and 14-days periodicities have been also observed. Interestingly, the 7-days infectivity and death rates oscillations are almost in phase, showing local maxima on Thursdays/Fridays and local minima on Sundays/Mondays. These observations are in stark contrast with a known pattern, correlating the death rate with the reduced medical staff in hospitals on the weekends. One possible hypothesis addressing these observations is that they reflect a gradually increasing stress with the progressing week, which can trigger the maximal death rates observed on Thursdays/Fridays. Moreover, assuming the weekends provide the likely time for new infections, the maximum number of new cases might fall again on Thursdays/Fridays. These observations deserve further study to provide better understanding of the COVID-19 dynamics.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Rohit Kumar", - "author_inst": "All India Institute of Medical Sciences" - }, - { - "author_name": "bisakh bhattacharya", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Ved Prakash Meena", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Anivita Aggarwal", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Manasi Tripathi", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Manish Soneja", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Ankit Mittal", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Komal Singh", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Nishkarsh Gupta", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Rakesh Kumar Garg", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Brajesh Ratre", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Balbir Kumar", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Shweta Bhopale", - "author_inst": "All India Institute of Medical Sciences, New Delhi" + "author_name": "Tatsuya Nagano", + "author_inst": "Kobe University Graduate School of Medicine" }, { - "author_name": "Pavan Tiwari", - "author_inst": "All India Institute of Medical Sciences, New Delhi" + "author_name": "Jun Arii", + "author_inst": "Kobe University Graduate School of Medicine" }, { - "author_name": "Ankit Verma", - "author_inst": "All India Institute of Medical Sciences, New Delhi" + "author_name": "Mitsuhiro Nishimura", + "author_inst": "Kobe University Graduate School of Medicine" }, { - "author_name": "Sushma Bhatnagar", - "author_inst": "All India Institute of Medical Sciences, New Delhi" + "author_name": "Naofumi Yoshida", + "author_inst": "Kobe University Graduate School of Medicine" }, { - "author_name": "Anant Mohan", - "author_inst": "All India Institute of Medical Sciences, New Delhi" + "author_name": "Keiji Iida", + "author_inst": "Hyogo Prefectural Kakogawa Medical Center" }, { - "author_name": "Naveet Wig", - "author_inst": "All India Institute of Medical Sciences, New Delhi" + "author_name": "Yoshihiro Nishimura", + "author_inst": "Kobe University Graduate School of Medicine" }, { - "author_name": "Randeep Guleria", - "author_inst": "All India Institute of Medical Sciences, New Delhi" + "author_name": "Yasuko Mori", + "author_inst": "Kobe University Graduate School of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1408281,45 +1408639,117 @@ "category": "radiology and imaging" }, { - "rel_doi": "10.1101/2020.05.22.20109579", - "rel_title": "Association between comorbidities and the risk of death in patients with COVID-19: sex-specific differences", + "rel_doi": "10.1101/2020.05.22.20109850", + "rel_title": "COVID-19 Outcomes in 4712 consecutively confirmed SARS-CoV2 cases in the city of Madrid.", "rel_date": "2020-05-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.22.20109579", - "rel_abs": "BackgroundThe coronavirus disease 2019 (Covid-19) spreads rapidly around the world.\n\nObjectiveTo evaluate the association between comorbidities and the risk of death in patients with COVID-19, and to further explore potential sex-specific differences.\n\nMethodsWe analyzed the data from 18,465 laboratory-confirmed cases that completed an epidemiological investigation in Hubei Province as of February 27, 2020. Information on death was obtained from the Infectious Disease Information System. The Cox proportional hazards model was used to estimate the association between comorbidities and the risk of death in patients with COVID-19.\n\nResultsThe median age for COVID-19 patients was 50.5 years. 8828(47.81%) patients were females. Severe cases accounted for 20.11% of the study population. As of March 7, 2020, a total of 919 cases deceased from COVID-19 for a fatality rate of 4.98%. Hypertension (13.87%), diabetes (5.53%), and cardiovascular and cerebrovascular diseases (CBVDs) (4.45%) were the most prevalent comorbidities, and 27.37% of patients with COVID-19 reported having at least one comorbidity. After adjustment for age, gender, address, and clinical severity, patients with hypertension (HR 1.55, 95%CI 1.35-1.78), diabetes (HR 1.35, 95%CI 1.13-1.62), CBVDs (HR 1.70, 95%CI 1.43-2.02), chronic kidney diseases (HR 2.09, 95%CI 1.47-2.98), and at least two comorbidities (HR 1.84, 95%CI 1.55-2.18) had significant increased risks of death. And the association between diabetes and the risk of death from COVID-19 was prominent in women (HR 1.69, 95%CI 1.27-2.25) than in men (HR 1.16, 95%CI 0.91-1.46) (P for interaction = 0.036).\n\nConclusionAmong laboratory-confirmed cases of COVID-19 in Hubei province, China, patients with hypertension, diabetes, CBVDs, chronic kidney diseases were significantly associated with increased risk of death. The association between diabetes and the risk of death tended to be stronger in women than in men. Clinicians should increase their awareness of the increased risk of death in COVID-19 patients with comorbidities.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.22.20109850", + "rel_abs": "There is limited information describing features and outcomes of patients requiring hospitalization for COVID19 disease and still no treatments have clearly demonstrated efficacy. Demographics and clinical variables on admission, as well as laboratory markers and therapeutic interventions were extracted from electronic Clinical Records (eCR) in 4712 SARS-CoV2 infected patients attending 4 public Hospitals in Madrid. Patients were stratified according to age and stage of severity. Using multivariate logistic regression analysis, cut-off points that best discriminated mortality were obtained for each of the studied variables. Principal components analysis and a neural network (NN) algorithm were applied.\n\nA high mortality incidence associated to age >70, comorbidities (hypertension, neurological disorders and diabetes), altered vitals such as fever, heart rhythm disturbances or elevated systolic blood pressure, and alterations in several laboratory tests. Remarkably, analysis of therapeutic options either taken individually or in combination drew a universal relationship between the use of Cyclosporine A and better outcomes as also a benefit of tocilizumab and/or corticosteroids in critically ill patients.\n\nWe present a large Spanish population-based study addressing factors influencing survival in current SARS CoV2 pandemic, with particular emphasis on the effectivity of treatments. In addition, we have generated an NN capable of identifying severity predictors of SARS CoV2. A rapid extraction and management of data protocol from eCR and artificial intelligence in-house implementations allowed us to perform almost real time monitoring of the outbreak evolution.", + "rel_num_authors": 26, "rel_authors": [ { - "author_name": "Mingyang Wu", - "author_inst": "Huazhong University of Science and Technology" + "author_name": "Sarah Heili-Frades", + "author_inst": "Intermediate Respiratory Care Unit, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud, Madrid, CIBER de enfermedades respir" + }, + { + "author_name": "Pablo Minguez", + "author_inst": "Genetics and Genomics Department, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Center for Biomedical Network Research on Rare Disea" }, { - "author_name": "shuqiong Huang", - "author_inst": "Institute of Preventive Medicine Information, Hubei Provincial Center for Disease Control and Prevention" + "author_name": "Ignacio Mahillo-Fernandez", + "author_inst": "Department of Biostatistics and Epidemiology, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Madrid" }, { - "author_name": "Jun Liu", - "author_inst": "Central office, Qianjiang City Center for Disease Control and Prevention" + "author_name": "Tomas Prieto-Rumeau", + "author_inst": "Statistics Department, National University of Distance Education, UNED, Madrid, Spain" }, { - "author_name": "Yanling Shu", - "author_inst": "Department of Laboratory Medicine, Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science & Technology" + "author_name": "Antonio Herrero Gonzalez", + "author_inst": "Hospital Universitario Fundacion Jimenez Diaz, Data Analytics Director, Department of Big Data analytics, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Mad" }, { - "author_name": "Yinbo Luo", - "author_inst": "Institute for Infectious Disease Control and Prevention, Hubei Provincial Center for Disease Control and Prevention" + "author_name": "Lorena de la Fuente", + "author_inst": "Bioinformatics Unit, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Madrid, Spain" }, { - "author_name": "Lulin Wang", - "author_inst": "Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Maria Jesus Rodriguez Nieto", + "author_inst": "Department Of Interstitial Pathology And Lung Function, Pulmonology Department, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron" }, { - "author_name": "Mingyan Li", - "author_inst": "Institute of Preventive Medicine Information, Hubei Provincial Center for Disease Control and Prevention" + "author_name": "German Peces-Barba Romero", + "author_inst": "Intermediate Respiratory Care Unit, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud, Madrid, CIBER de enfermedades respir" }, { - "author_name": "Youjie Wang", - "author_inst": "Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Mario Peces-Barba", + "author_inst": "ARGOZ Consultants, Av. de Manoteras, 38, 28050 Madrid, Spain" + }, + { + "author_name": "Maria del Pilar Carballosa de Miguel", + "author_inst": "Intermediate Respiratory Care Unit, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud, Madrid, CIBER de enfermedades respir" + }, + { + "author_name": "Itziar Fernandez Ormaechea", + "author_inst": "Intermediate Respiratory Care Unit, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud, Madrid, CIBER de enfermedades respir" + }, + { + "author_name": "Alba Naya Prieto", + "author_inst": "Intermediate Respiratory Care Unit, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud, Madrid, CIBER de enfermedades respir" + }, + { + "author_name": "Farah Ezzine de Blas", + "author_inst": "Intermediate Respiratory Care Unit, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud, Madrid, CIBER de enfermedades respir" + }, + { + "author_name": "Luis Jimenez Hiscock", + "author_inst": "Thoracic Surgery Dept. Sanchinarro University Hospital, HM Hospitals Group, Madrid, Spain" + }, + { + "author_name": "Cesar Perez Calvo", + "author_inst": "Intensive Care Unit, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud, Madrid, CIBER de enfermedades respiratorias (CIBERE" + }, + { + "author_name": "Arnoldo Santos", + "author_inst": "Intensive Care Unit, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud, Madrid, CIBER de enfermedades respiratorias (CIBERE" + }, + { + "author_name": "Luis Enrique Munoz Alameda", + "author_inst": "Head of anesthesiology and resuscitation service. IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud, Avda Reyes Catolicos 2" + }, + { + "author_name": "Fredeswinda Romero Bueno", + "author_inst": "Department of Rheumatology, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud, Avda Reyes Catolicos 2, Madrid, Spain." + }, + { + "author_name": "Miguel Gorgolas Hernandez-Mora", + "author_inst": "Division of Infectious Diseases, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud, Universidad Autonoma de Madrid. Avda Re" + }, + { + "author_name": "Alfonso Cabello Ubeda", + "author_inst": "Division of Infectious Diseases, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud, Avda Reyes Catolicos 2, Madrid, Spain." + }, + { + "author_name": "Beatriz Alvarez Alvarez", + "author_inst": "Division of Infectious Diseases, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud. Avda Reyes Catolicos 2, Madrid, Spain." + }, + { + "author_name": "Elizabet Petkova", + "author_inst": "Division of Infectious Diseases, Fundacion Jimenez Diaz Quiron Salud, Universidad Autonoma de Madrid. Avda Reyes Catolicos 2, Madrid, Spain." + }, + { + "author_name": "Nerea Carrasco", + "author_inst": "Division of Infectious Diseases, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud, Avda Reyes Catolicos 2, Madrid, Spain." + }, + { + "author_name": "Dolores Martin Rios", + "author_inst": "Department of preventive medicine. IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud, Avda Reyes Catolicos 2, Madrid, Spai" + }, + { + "author_name": "Nicolas Gonzalez Mangado", + "author_inst": "Intermediate Respiratory Care Unit, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud, Madrid, CIBER de enfermedades respir" + }, + { + "author_name": "Olga Sanchez Pernaute", + "author_inst": "Department of Rheumatology, IIS-Fundacion Jimenez Diaz-Universidad Autonoma de Madrid (IIS-FJD, UAM), Quiron Salud, Avda Reyes Catolicos 2, Madrid, Spain." } ], "version": "1", @@ -1409731,47 +1410161,27 @@ "category": "radiology and imaging" }, { - "rel_doi": "10.1101/2020.05.22.20110486", - "rel_title": "Outcomes from COVID-19 across the range of frailty: excess mortality in fitter older people", + "rel_doi": "10.1101/2020.05.22.20110585", + "rel_title": "Rate Estimation and Identification of COVID-19 Infections: Towards Rational Policy Making During Early and Late Stages of Epidemics", "rel_date": "2020-05-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.22.20110486", - "rel_abs": "PurposeOur aim was to quantify the mortality from COVID-19 and identify any interactions with frailty and other demographic factors.\n\nMethodsHospitalised patients aged [≥]70 were included, comparing COVID-19 cases with non-COVID-19 controls admitted over the same period. Frailty was prospectively measured and mortality ascertained through linkage with national and local statutory reports.\n\nResultsIn 217 COVID-19 cases and 160 controls, older age and South Asian ethnicity, though not socioeconomic position, were associated with higher mortality. For frailty, differences in effect size were evident between cases (HR 1.02, 95%CI 0.93-1.12) and controls (HR 1.99, 95%CI 1.46-2.72), with an interaction term (HR 0.51, 95%CI 0.37-0.71) in multivariable models.\n\nConclusionsOur findings suggest that (i) frailty is not a good discriminator of prognosis in COVID-19 and (ii) pathways to mortality may differ in fitter compared with frailer older patients.\n\nKey summary pointsO_ST_ABSAimC_ST_ABSTo describe associations between frailty, ethnicity, socioeconomic position and mortality in a cohort of older patients presenting to hospital with COVID-19.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.22.20110585", + "rel_abs": "Pandemics have a profound impact on our world, causing loss of life, affecting our culture and historically shaping our genetics. The response to a pandemic requires both resilience and imagination. It has been clearly documented that obtaining an accurate estimate and trends of the actual infection rate and mortality risk are very important for policy makers and medical professionals. One cannot estimate mortality rates without an accurate assessment of the number of infected individuals in the population. This need is also aligned with identifying the infected individuals so they can be properly treated, monitored and tracked. However, accurate estimation of the infection rate, locally, geographically and nationally is important independently. These infection rate estimates can guide policy makers at both state, national or world level to achieve a better management of risk to society. The decisions facing policy makers are very different during early stages of an emerging epidemic where the infection rate is low, middle stages where the rate is rapidly climbing, and later stages where the epidemic curve has flattened to a low and relatively sustainable rate. In this paper we provide relatively efficient pooling methods to both estimate infection rates and identify infected individuals for populations with low infection rates. These estimates may provide significant cost reductions for testing in rural communities, third world countries and other situations where the cost of testing is expensive or testing is not widely available. As we prepare for the second wave of the pandemic this line of work may provide new solutions for both the biomedical community and policy makers at all levels.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Amy Miles", - "author_inst": "University College Hospitals NHS Foundation Trust" - }, - { - "author_name": "Thomas E Webb", - "author_inst": "University College London Hospitals NHS Foundation Trust" - }, - { - "author_name": "Benjamin Mcloughlin", - "author_inst": "University College London Hospitals NHS Foundation Trust" - }, - { - "author_name": "Imran Mannan", - "author_inst": "University College London Hospital NHS Foundation Trust" - }, - { - "author_name": "Arshad Rather", - "author_inst": "University College London Hospitals NHS Foundation Trust" - }, - { - "author_name": "Paul Knopp", - "author_inst": "University College London Hospitals NHS Foundation Trust" + "author_name": "Richard Beigel", + "author_inst": "Temple University" }, { - "author_name": "Daniel Davis", - "author_inst": "UCL" + "author_name": "Simon Kasif", + "author_inst": "Boston University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "geriatric medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.05.22.20110502", @@ -1411077,55 +1411487,83 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.05.23.112235", - "rel_title": "Targeting the SARS-CoV-2 Main Protease to Repurpose Drugs for COVID-19", + "rel_doi": "10.1101/2020.05.22.111526", + "rel_title": "In silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-19", "rel_date": "2020-05-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.23.112235", - "rel_abs": "Guided by a computational docking analysis, about 30 FDA/EMA-approved small molecule medicines were characterized on their inhibition of the SARS-CoV-2 main protease (MPro). Of these tested small molecule medicines, six displayed an IC50 value in inhibiting MPro below 100 M. Three medicines pimozide, ebastine, and bepridil are basic small molecules. Their uses in COVID-19 patients potentiate dual functions by both raising endosomal pH to slow SARS-CoV-2 entry into the human cell host and inhibiting MPro in infected cells. A live virus-based microneutralization assay showed that bepridil inhibited cytopathogenic effect induced by SARS-CoV-2 in Vero E6 cells completely at and dose-dependently below 5 M and in A549 cells completely at and dose-dependently below 6.25 M. Therefore, the current study urges serious considerations of using bepridil in COVID-19 clinical tests.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.22.111526", + "rel_abs": "Rapid generation of diagnostics is paramount to understand epidemiology and to control the spread of emerging infectious diseases such as COVID-19. Computational methods to predict serodiagnostic epitopes that are specific for the pathogen could help accelerate the development of new diagnostics. A systematic survey of 27 SARS-CoV-2 proteins was conducted to assess whether existing B-cell epitope prediction methods, combined with comprehensive mining of sequence databases and structural data, could predict whether a particular protein would be suitable for serodiagnosis. Nine of the predictions were validated with recombinant SARS-CoV-2 proteins in the ELISA format using plasma and sera from patients with SARS-CoV-2 infection, and a further 11 predictions were compared to the recent literature. Results appeared to be in agreement with 12 of the predictions, in disagreement with 3, while a further 5 were deemed inconclusive. We showed that two of our top five candidates, the N-terminal fragment of the nucleoprotein and the receptor-binding domain of the spike protein, have the highest sensitivity and specificity and signal-to-noise ratio for detecting COVID-19 sera/plasma by ELISA. Mixing the two antigens together for coating ELISA plates led to a sensitivity of 94% (N=80 samples from persons with RT-PCR confirmed SARS-CoV2 infection), and a specificity of 97.2% (N=106 control samples).", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Erol Can Vatansever", - "author_inst": "The Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" + "author_name": "David Kim", + "author_inst": "Department of Biochemistry and Institute for Protein Design (IPD), University of Washington, Seattle, Washington, USA." }, { - "author_name": "Kai S Yang", - "author_inst": "The Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" + "author_name": "Lauren Carter", + "author_inst": "Department of Biochemistry and Institute for Protein Design (IPD), University of Washington, Seattle, Washington, USA." }, { - "author_name": "Kaci C Kratch", - "author_inst": "The Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" + "author_name": "Neil King", + "author_inst": "Department of Biochemistry and Institute for Protein Design (IPD), University of Washington, Seattle, Washington, USA." }, { - "author_name": "Aleksandra Drelich", - "author_inst": "Department of Microbiology and Immunology, University of Texas Medical Branch" + "author_name": "Ivan Anishchenko", + "author_inst": "Department of Biochemistry and Institute for Protein Design (IPD), University of Washington, Seattle, Washington, USA" }, { - "author_name": "Chia-Chuan Cho", - "author_inst": "The Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" + "author_name": "Lynn K Barrett", + "author_inst": "Center for Emerging and Re-emerging Infectious Diseases (CERID), Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, " }, { - "author_name": "Drake M Mellott", - "author_inst": "Department of Biochemistry and Biophysics, Texas A&M University" + "author_name": "Justin K Craig", + "author_inst": "Center for Emerging and Re-emerging Infectious Diseases (CERID), Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, " }, { - "author_name": "Shiqing Xu", - "author_inst": "The Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" + "author_name": "Logan Tillery", + "author_inst": "Center for Emerging and Re-emerging Infectious Diseases (CERID), Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, " }, { - "author_name": "Chien-Te K Tseng", - "author_inst": "Department of Microbiology and Immunology, University of Texas Medical Branch" + "author_name": "Roger Shek", + "author_inst": "Center for Emerging and Re-emerging Infectious Diseases (CERID), Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, " }, { - "author_name": "Wenshe Ray Liu", - "author_inst": "The Texas A&M Drug Discovery Laboratory, Dept of Chemistry; Dept of Biochemistry and Biophysics; Dept of Molecular and Cellular Medicine, College of Medicine, T" + "author_name": "David M Koelle", + "author_inst": "Center for Emerging and Re-emerging Infectious Diseases (CERID), Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, " + }, + { + "author_name": "Anna Wald", + "author_inst": "Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA" + }, + { + "author_name": "Jim Boonyaratanakornkit", + "author_inst": "Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA" + }, + { + "author_name": "Nina Isoherranen", + "author_inst": "Department of Pharmaceutics, University of Washington, Seattle, Washington, USA" + }, + { + "author_name": "Alexander L Greninger", + "author_inst": "Department of Laboratory Medicine, University of Washington, Seattle, Washington, USA" + }, + { + "author_name": "Keith R Jerome", + "author_inst": "Department of Laboratory Medicine, University of Washington, Seattle, Washington, USA" + }, + { + "author_name": "Helen Chu", + "author_inst": "Center for Emerging and Re-emerging Infectious Diseases (CERID), Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, " + }, + { + "author_name": "Wesley C Van Voorhis", + "author_inst": "Center for Emerging and Re-emerging Infectious Diseases (CERID), Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, " } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "new results", - "category": "pharmacology and toxicology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.05.23.107334", @@ -1412651,83 +1413089,51 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.18.20105650", - "rel_title": "Plasma concentration and safety of lopinavir/ritonavir in patients with Covid-19: a retrospective cohort study", + "rel_doi": "10.1101/2020.05.17.20104794", + "rel_title": "Epidemiology of sleep disorders during COVID-19 pandemic: A systematic scoping review protocol", "rel_date": "2020-05-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.18.20105650", - "rel_abs": "BackgroundThere is an urgent need of active treatment for coronavirus disease 2019 (Covid-19). Although efficacy have not been proven, lopinavir/ritonavir 400 mg/100 mg twice daily has been proposed as a treatment of moderate to severe Covid-19. Previously published cohorts showed Covid-19 is associated with major inflammation. To date, no data are available regarding lopinavir/ritonavir plasma concentration and its safety in Covid-19 patients.\n\nMethodsReal-world Covid-19 experience based on a retrospective cohort study.\n\nResultsOn the cohort of 31 patients treated by lopinavir/ritonavir for Covid-19, we observed very high lopinavir plasma concentrations, increased of 4.6-fold (IQR 2.9-6.4), with regards to average plasma concentrations in HIV treatment. All except two patients were above the upper limit of the concentration ranges of HIV treatment. In this cohort, about one over four to five patients prematurely stopped lopinavir/ritonavir therapy due to a moderate adverse drug reaction, mainly hepatic and gastrointestinal disorders.\n\nConclusionPatients with Covid-19 pneumonitis treated with lopinavir/ritonavir have plasma concentrations dramatically higher than expected. Owing to that high plasma concentration may be required for antiviral activity against SARS-CoV-2, it appears that lopinavir dosage should not be reduced in the absence of adverse effect. About 80% of the patients well tolerated lopinavir/ritonavir therapy under these plasma concentrations. However, cautious is necessary as drug repurposing can be associated with a new drug safety profile.\n\nFundingNone", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.17.20104794", + "rel_abs": "BackgroundThe coronavirus disease (COVID-19) is impacting human health globally. In addition to physical health problems, a growing burden of mental health problems has become a global concern amid this pandemic. Sleep disorders are major mental health problems associated with increased psychosocial stressors; however, no research synthesis is available on the epidemiology of sleep disorders. In this systematic scoping review, we aim to assess the current evidence on the epidemiological burden, associated factors, and interventions from the existing literature on sleep disorders.\n\nMethodsWe will search seven major health databases and additional sources to identify, evaluate, and synthesize empirical studies on the prevalence and correlates of sleep disorders and available interventions addressing the same. We will use the Joanna Briggs Institute Methodology for Scoping Review and report the findings using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist.\n\nConclusionThis review will identify the epidemiological burden of and interventions for sleep disorders. The findings of this review will be widely communicated with the research and professional community to facilitate future research and practice.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Laurent Chouchana", - "author_inst": "AP-HP" - }, - { - "author_name": "Sana Boujaafar", - "author_inst": "AP-HP" - }, - { - "author_name": "Ines Gana", - "author_inst": "AP-HP" - }, - { - "author_name": "Laure-Helene Preta", - "author_inst": "AP-HP" - }, - { - "author_name": "Lucile Regard", - "author_inst": "AP-HP" - }, - { - "author_name": "Paul Legendre", - "author_inst": "AP-HP" - }, - { - "author_name": "Celia Azoulay", - "author_inst": "AP-HP" - }, - { - "author_name": "Etienne Canoui", - "author_inst": "AP-HP" - }, - { - "author_name": "Jeremie Zerbit", - "author_inst": "AP-HP" + "author_name": "Samia Tasnim", + "author_inst": "School of Public Health, Texas A&M University, TX 77843, USA." }, { - "author_name": "Nicolas Carlier", - "author_inst": "AP-HP" + "author_name": "Mariya Rahman", + "author_inst": "School of Public Health, Texas A&M University, TX 77843, USA." }, { - "author_name": "Benjamin Terrier", - "author_inst": "AP-HP" + "author_name": "Priyanka Pawar", + "author_inst": "Mamta Foundation, India." }, { - "author_name": "Solen Kerneis", - "author_inst": "AP-HP" + "author_name": "Liye Zou", + "author_inst": "School of Psychology, Shenzhen University, China." }, { - "author_name": "Rui Batista", - "author_inst": "AP-HP" + "author_name": "Abida Sultana", + "author_inst": "Nature Study Society of Bangladesh, Khulna, Bangladesh." }, { - "author_name": "Jean-Marc Treluyer", - "author_inst": "AP-HP" + "author_name": "E. Lisako J. McKyer", + "author_inst": "School of Public Health, Texas A&M University, TX 77843, USA." }, { - "author_name": "Yi Zheng", - "author_inst": "AP-HP" + "author_name": "Ping Ma", + "author_inst": "School of Public Health, Texas A&M University, TX 77843, USA" }, { - "author_name": "Sihem Benaboud", - "author_inst": "AP-HP" + "author_name": "Md Mahbub Hossain", + "author_inst": "School of Public Health, Texas A&M University, College Station, TX 77843, USA" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "pharmacology and therapeutics" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2020.05.18.20105874", @@ -1414257,58 +1414663,38 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.05.21.108563", - "rel_title": "SARS-CoV-2 mutations and where to find them: An in silico perspective of structural changes and antigenicity of the Spike protein", + "rel_doi": "10.1101/2020.05.21.109835", + "rel_title": "Systemic Effects of Missense Mutations on SARS-CoV-2 Spike Glycoprotein Stability and Receptor Binding Affinity", "rel_date": "2020-05-22", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.21.108563", - "rel_abs": "The recent emergence of a novel coronavirus (SARS-CoV-2) is causing a severe global health threat characterized by severe acute respiratory syndrome (Covid-19). At the moment, there is no specific treatment for this disease, and vaccines are still under development. The structural protein Spike is essential for virus infection and has been used as the main target for vaccine and serological diagnosis test development. We analysed 2363 sequences of the Spike protein from SARS-CoV-2 isolates and identified variability in 44 amino acid residues and their worldwide distribution in all continents. We used the three-dimensional structure of the homo-trimer model to predict conformational epitopes of B-cell, and sequence of Spike protein Wuhan-Hu-1 to predict linear epitopes of T-Cytotoxic and T-Helper cells. We identified 45 epitopes with amino acid variations. Finally, we showed the distribution of mutations within the epitopes. Our findings can help researches to identify more efficient strategies for the development of vaccines, therapies, and serological diagnostic tests based on the Spike protein of Sars-Cov-2.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.21.109835", + "rel_abs": "The spike (S) glycoprotein of SARS-CoV-2 is responsible for the binding to the permissive cells. The receptor-binding domain (RBD) of SARS-CoV-2 S protein directly interacts with the human angiotensin-converting enzyme 2 (ACE2) on the host cell membrane. In this study, we used computational saturation mutagenesis approaches, including structure-based energy calculations and sequence-based pathogenicity predictions, to quantify the systemic effects of missense mutations on SARS-CoV-2 S protein structure and function. A total of 18,354 mutations in S protein were analyzed and we discovered that most of these mutations could destabilize the entire S protein and its RBD. Specifically, residues G431 and S514 in SARS-CoV-2 RBD are important for S protein stability. We analyzed 384 experimentally verified S missense variations and revealed that the dominant pandemic form, D614G, can stabilize the entire S protein. Moreover, many mutations in N-linked glycosylation sites can increase the stability of the S protein. In addition, we investigated 3,705 mutations in SARS-CoV-2 RBD and 11,324 mutations in human ACE2 and found that SARS-CoV-2 neighbor residues G496 and F497 and ACE2 residues D355 and Y41 are critical for the RBD-ACE2 interaction. The findings comprehensively provide potential target sites in the development of drugs and vaccines against COVID-19.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Ricardo Lemes Goncalves", - "author_inst": "Universidade Federal de Ouro Preto, Brazil" - }, - { - "author_name": "Tulio Cesar Rodrigues Leite", - "author_inst": "Universidade Federal de Ouro Preto, Brazil" - }, - { - "author_name": "Bruna de Paula Dias", - "author_inst": "Universidade Federal de Ouro Preto, Brazil" - }, - { - "author_name": "Camila Carla da Silva Caetano", - "author_inst": "Universidade Federal de Ouro Preto, Brazil" - }, - { - "author_name": "Ana Clara Gomes de Souza", - "author_inst": "Universidade Federal de Ouro Preto, Brazil" - }, - { - "author_name": "Ubiratan da Silva Batista", - "author_inst": "Universidade Federal de Ouro Preto, Brazil" + "author_name": "Shaolei Teng", + "author_inst": "Howard University" }, { - "author_name": "Camila Cavadas Barbosa", - "author_inst": "Universidade Federal de Ouro Preto, Brazil" + "author_name": "Adebiyi Sobitan", + "author_inst": "Howard University" }, { - "author_name": "Arturo Reyes-Sandoval", - "author_inst": "The Jenner Institute, Nuffield Department of Medicine, University of Oxford, 12 Oxford OX1 2JD, UK" + "author_name": "Raina Rhoades", + "author_inst": "Howard University" }, { - "author_name": "Luiz Felipe Leomil Coelho", - "author_inst": "Universidade Federal de Alfenas, Brazil." + "author_name": "Dongxiao Liu", + "author_inst": "Howard University" }, { - "author_name": "Breno de Mello Silva", - "author_inst": "Universidade Federal de Ouro Preto, Brazil" + "author_name": "Qiyi Tang", + "author_inst": "Howard University" } ], "version": "1", - "license": "cc_by_nd", - "type": "confirmatory results", + "license": "cc_no", + "type": "new results", "category": "bioinformatics" }, { @@ -1415879,123 +1416265,63 @@ "category": "pathology" }, { - "rel_doi": "10.1101/2020.05.18.20103390", - "rel_title": "Interim Analysis of Risk Factors for Severe Outcomes among a Cohort of Hospitalized Adults Identified through the U.S. Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET)", + "rel_doi": "10.1101/2020.05.20.20100362", + "rel_title": "MosMedData: Chest CT Scans with COVID-19 Related Findings", "rel_date": "2020-05-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.18.20103390", - "rel_abs": "BackgroundAs of May 15, 2020, the United States has reported the greatest number of coronavirus disease 2019 (COVID-19) cases and deaths globally.\n\nObjectiveTo describe risk factors for severe outcomes among adults hospitalized with COVID-19.\n\nDesignCohort study of patients identified through the Coronavirus Disease 2019-Associated Hospitalization Surveillance Network.\n\nSetting154 acute care hospitals in 74 counties in 13 states.\n\nPatients2491 patients hospitalized with laboratory-confirmed COVID-19 during March 1-May 2, 2020.\n\nMeasurementsAge, sex, race/ethnicity, and underlying medical conditions.\n\nResultsNinety-two percent of patients had [≥]1 underlying condition; 32% required intensive care unit (ICU) admission; 19% invasive mechanical ventilation; 15% vasopressors; and 17% died during hospitalization. Independent factors associated with ICU admission included ages 50-64, 65-74, 75-84 and [≥]85 years versus 18-39 years (adjusted risk ratio (aRR) 1.53, 1.65, 1.84 and 1.43, respectively); male sex (aRR 1.34); obesity (aRR 1.31); immunosuppression (aRR 1.29); and diabetes (aRR 1.13). Independent factors associated with in-hospital mortality included ages 50-64, 65-74, 75-84 and [≥]85 years versus 18-39 years (aRR 3.11, 5.77, 7.67 and 10.98, respectively); male sex (aRR 1.30); immunosuppression (aRR 1.39); renal disease (aRR 1.33); chronic lung disease (aRR 1.31); cardiovascular disease (aRR 1.28); neurologic disorders (aRR 1.25); and diabetes (aRR 1.19). Race/ethnicity was not associated with either ICU admission or death.\n\nLimitationData were limited to patients who were discharged or died in-hospital and had complete chart abstractions; patients who were still hospitalized or did not have accessible medical records were excluded.\n\nConclusionIn-hospital mortality for COVID-19 increased markedly with increasing age. These data help to characterize persons at highest risk for severe COVID-19-associated outcomes and define target groups for prevention and treatment strategies.\n\nFunding SourceThis work was supported by grant CK17-1701 from the Centers of Disease Control and Prevention through an Emerging Infections Program cooperative agreement and by Cooperative Agreement Number NU38OT000297-02-00 awarded to the Council of State and Territorial Epidemiologists from the Centers for Disease Control and Prevention.", - "rel_num_authors": 26, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.20.20100362", + "rel_abs": "This dataset contains anonymised human lung computed tomography (CT) scans with COVID-19 related findings, as well as without such findings. A small subset of studies has been annotated with binary pixel masks depicting regions of interests (ground-glass opacifications and consolidations). CT scans were obtained between 1st of March, 2020 and 25th of April, 2020, and provided by municipal hospitals in Moscow, Russia. Permanent link:https://mosmed.ai/datasets/covid19_1110. This dataset is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) License.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Lindsay Kim", - "author_inst": "Division of Viral Diseases, Centers for Disease Control and Prevention, Atlanta, GA; US Public Health Service, Rockville, MD" - }, - { - "author_name": "Shikha Garg", - "author_inst": "US Public Health Service, Rockville, MD, Influenza Division" - }, - { - "author_name": "Alissa O'Halloran", - "author_inst": "Influenza Division, Centers for Disease Control and Prevention" - }, - { - "author_name": "Michael Whitaker", - "author_inst": "Division of Viral Diseases, Centers for Disease Control and Prevention" - }, - { - "author_name": "Huong Pham", - "author_inst": "Division of Viral Diseases, Centers for Disease Control and Prevention" - }, - { - "author_name": "Evan J. Anderson", - "author_inst": "Departments of Medicine and Pediatrics, Emory University" - }, - { - "author_name": "Isaac Armistead", - "author_inst": "University of Colorado Anschutz Medical Campus" - }, - { - "author_name": "Nancy M. Bennett", - "author_inst": "University of Rochester School of Medicine and Dentistry" - }, - { - "author_name": "Laurie Billing", - "author_inst": "Ohio Department of Health" - }, - { - "author_name": "Kathryn Como-Sabetti", - "author_inst": "Minnesota Department of Health" - }, - { - "author_name": "Mary Hill", - "author_inst": "Salt Lake County Health Department" - }, - { - "author_name": "Sue Kim", - "author_inst": "Michigan Department of Health and Human Services" - }, - { - "author_name": "Maya L. Monroe", - "author_inst": "Maryland Department of Health" - }, - { - "author_name": "Alison Muse", - "author_inst": "New York State Department of Health" - }, - { - "author_name": "Arthur Reingold", - "author_inst": "University of California Berkeley" - }, - { - "author_name": "William Schaffner", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Sergey Morozov", + "author_inst": "Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow" }, { - "author_name": "Melissa Sutton", - "author_inst": "Oregon Health Authority" + "author_name": "Anna Andreychenko", + "author_inst": "Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow" }, { - "author_name": "H. Keipp Talbot", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Nikolay Pavlov", + "author_inst": "Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow" }, { - "author_name": "Salina M. Torres", - "author_inst": "New Mexico Department of Health" + "author_name": "Anton Vladzymyrskyy", + "author_inst": "Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow" }, { - "author_name": "Kimberly Yousey-Hindes", - "author_inst": "Connecticut Emerging Infections Program, Yale School of Public Health" + "author_name": "Natalya Ledikhova", + "author_inst": "Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow," }, { - "author_name": "Rachel A Holstein", - "author_inst": "Influenza Division, Centers for Disease Control and Prevention" + "author_name": "Victor Gombolevskiy", + "author_inst": "Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow" }, { - "author_name": "Charisse Cummings", - "author_inst": "Influenza Division, Centers for Disease Control and Prevention" + "author_name": "Ivan Blokhin", + "author_inst": "Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow" }, { - "author_name": "Lynette Brammer", - "author_inst": "Influenza Division, Centers for Disease Control and Prevention" + "author_name": "Pavel Gelezhe", + "author_inst": "Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow" }, { - "author_name": "Aron Hall", - "author_inst": "Division of Viral Diseases, Centers for Disease Control and Prevention" + "author_name": "Anna Gonchar", + "author_inst": "Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow" }, { - "author_name": "Alicia Fry", - "author_inst": "Influenza Division, Centers for Disease Control and Prevention" + "author_name": "Valeria Chernina", + "author_inst": "Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow" }, { - "author_name": "Gayle E. Langley", - "author_inst": "Division of Viral Diseases, Centers for Disease Control and Prevention" + "author_name": "Vladimir Babkin", + "author_inst": "Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow H" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "radiology and imaging" }, { "rel_doi": "10.1101/2020.05.17.20104687", @@ -1417333,93 +1417659,17 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.17.20104869", - "rel_title": "Immunogenic profile of SARS-CoV-2 spike in individuals recovered from COVID-19", + "rel_doi": "10.1101/2020.05.17.20104919", + "rel_title": "Modelling to Predict Hospital Bed Requirements for Covid-19 Patients in California", "rel_date": "2020-05-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.17.20104869", - "rel_abs": "The rapid global spread of SARS-CoV-2 and resultant mortality and social disruption have highlighted the need to better understand coronavirus immunity to expedite vaccine development efforts. Multiple candidate vaccines, designed to elicit protective neutralising antibodies targeting the viral spike glycoprotein, are rapidly advancing to clinical trial. However, the immunogenic properties of the spike protein in humans are unresolved. To address this, we undertook an in-depth characterisation of humoral and cellular immunity against SARS-CoV-2 spike in humans following mild to moderate SARS-CoV-2 infection. We find serological antibody responses against spike are routinely elicited by infection and correlate with plasma neutralising activity and capacity to block ACE2/RBD interaction. Expanded populations of spike-specific memory B cells and circulating T follicular helper cells (cTFH) were detected within convalescent donors, while responses to the receptor binding domain (RBD) constitute a minor fraction. Using regression analysis, we find high plasma neutralisation activity was associated with increased spike-specific antibody, but notably also with the relative distribution of spike-specific cTFH subsets. Thus both qualitative and quantitative features of B and T cell immunity to spike constitute informative biomarkers of the protective potential of novel SARS-CoV-2 vaccines.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.17.20104919", + "rel_abs": "A model to predict hospital bed requirements six weeks in advance to treat Covid-19 patients in California is presented. The model also gives prediction for number of cases and deaths during the same period. The model is versatile and can be applied to other countries and regions as well.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Jennifer A Juno", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Hyon-Xhi Tan", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Wen Shi Lee", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Arnold Reynaldi", - "author_inst": "Kirby Institute, UNSW" - }, - { - "author_name": "Hannah G Kelly", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Kathleen Wragg", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Robyn Esterbauer", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Helen E Kent", - "author_inst": "Melbourne Sexual Health Centre" - }, - { - "author_name": "C Jane Batten", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Francesca L Mordant", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Nicholas A Gherardin", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Phillip Pymm", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research" - }, - { - "author_name": "Melanie H Dietrich", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research" - }, - { - "author_name": "Nichollas E Scott", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Wai-Hong Tham", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research" - }, - { - "author_name": "Dale I Godfrey", - "author_inst": "The University of Melbourne" - }, - { - "author_name": "Kanta Subbarao", - "author_inst": "WHO Collaborating Centre for Reference and Research on Influenza" - }, - { - "author_name": "Miles P Davenport", - "author_inst": "The Kirby Institute, UNSW" - }, - { - "author_name": "Stephen J Kent", - "author_inst": "The University of Melbourne" - }, - { - "author_name": "Adam K Wheatley", - "author_inst": "University of Melbourne" + "author_name": "Santanu Basu", + "author_inst": "Sparkle Optics Corporation" } ], "version": "1", @@ -1418983,21 +1419233,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.15.20103259", - "rel_title": "Monitoring the evolution of the COVID-19 pandemic in China, South Korea, Italy and USA through the net relative rate of infection of the total number of confirmed cases", + "rel_doi": "10.1101/2020.05.15.20103655", + "rel_title": "Differential Effects of Intervention Timing on COVID-19 Spread in the United States", "rel_date": "2020-05-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.15.20103259", - "rel_abs": "Managing the COVID-19 pandemic in the middle of the events requires real-time monitoring of its evolution to perform analyses of containment actions and to project near future scenarios. This work proposes a scheme to monitor the temporal evolution of the COVID-19 pandemic using the time series of its total number of confirmed cases in a given region. The monitored parameter is the spread rate obtained from this time series (day-1) expressed in %/day. The schemes capability is verified using the epidemic data from China and South Korea. Its projection capability is shown for Italy and United States with scenarios for the ensuing 30 days from April 2nd, 2020. The spread rate (relative rate of change of the time series) is very sensitive to sudden changes in the epidemic evolution and can be used to monitor in real-time the effectiveness of containment actions. The logarithm of this variable allows identifying clear trends of the evolution of the COVID-10 epidemic in these countries. The spread rate calculated from the number of confirmed cases of infection is interpreted as a probability per unit of time of virus infection and containment actions. Its product with the number of confirmed cases of infections yields the number of new cases per day. The stabilization and control of the epidemic for China and South Korea appear to occur for values of this parameter below 0{middle dot}77 %/day (doubling time of 90 days).", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.15.20103655", + "rel_abs": "Assessing the effects of early non-pharmaceutical interventions1-5 on COVID-19 spread in the United States is crucial for understanding and planning future control measures to combat the ongoing pandemic6-10. Here we use county-level observations of reported infections and deaths11, in conjunction with human mobility data12 and a metapopulation transmission model13,14, to quantify changes of disease transmission rates in US counties from March 15, 2020 to May 3, 2020. We find significant reductions of the basic reproductive numbers in major metropolitan areas in association with social distancing and other control measures. Counterfactual simulations indicate that, had these same control measures been implemented just 1-2 weeks earlier, a substantial number of cases and deaths could have been averted. Specifically, nationwide, 56.5% [95% CI: 48.1%-65.9%] of reported infections and 54.0% [95% CI: 43.6%-63.8%] of reported deaths as of May 3, 2020 could have been avoided if the same control measures had been implemented just one week earlier. We also examine the effects of delays in re-implementing social distancing following a relaxation of control measures. A longer response time results in a stronger rebound of infections and death. Our findings underscore the importance of early intervention and aggressive response in controlling the COVID-19 pandemic.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Joao Manoel Losada Moreira", - "author_inst": "Universidade Federal do ABC" + "author_name": "Sen Pei", + "author_inst": "Columbia University" + }, + { + "author_name": "Sasikiran Kandula", + "author_inst": "Columbia University" + }, + { + "author_name": "Jeffrey Shaman", + "author_inst": "Columbia University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1420253,35 +1420511,51 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2020.05.20.104885", - "rel_title": "RdRp mutations are associated with SARS-CoV-2 genome evolution", + "rel_doi": "10.1101/2020.05.20.107292", + "rel_title": "CD8+ T cell cross-reactivity against SARS-CoV-2 conferred by other coronavirus strains and influenza virus", "rel_date": "2020-05-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.20.104885", - "rel_abs": "COVID-19, caused by the novel SARS-CoV-2 virus, started in China in late 2019, and soon became a global pandemic. With the help of thousands of viral genome sequences that have been accumulating, it has become possible to track the evolution of viral genome over time as it spread across the world. An important question that still needs to be answered is whether any of the common mutations affect the viral properties, and therefore the disease characteristics. Therefore, we sought to understand the effects of mutations in RNA-dependent RNA polymerase (RdRp), particularly the common 14408C>T mutation, on mutation rate and viral spread. By focusing on mutations in the slowly evolving M or E genes, we aimed to minimize the effects of selective pressure. Our results indicate that 14408C>T mutation increases the mutation rate, while the third-most common RdRp mutation, 15324C>T, has the opposite effect. It is possible that 14408C>T mutation may have contributed to the dominance of its co-mutations in Europe and elsewhere.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.20.107292", + "rel_abs": "While individuals infected with coronavirus disease 2019 (COVID-19) manifested a broad range in susceptibility and severity to the disease, the pre-existing immune memory of related pathogens can influence the disease outcome. Here, we investigated the potential extent of T cell cross-reactivity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that can be conferred by other coronaviruses and influenza virus, and generated a map of public and private predicted CD8+ T cell epitopes between coronaviruses. Moreover, to assess the potential risk of self-reactivity and/or diminished T cell response for peptides identical or highly similar to the host, we identified predicted epitopes with high sequence similarity with human proteome. Lastly, we compared predicted epitopes from coronaviruses with epitopes from influenza virus deposited in IEDB to support vaccine development against different virus strains. We believe the comprehensive in silico profile of private and public predicted epitopes across coronaviruses and influenza viruses will facilitate design of vaccines capable of protecting against various viral infections.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Do\u011fa Eskier", - "author_inst": "Izmir Biomedicine and Genome Center (IBG)" + "author_name": "Hashem Koohy", + "author_inst": "The University of Oxford" }, { - "author_name": "G\u00f6khan Karak\u00fclah", - "author_inst": "Izmir Biomedicine and Genome Center (IBG)" + "author_name": "Chloe Hyun-Jung Lee", + "author_inst": "Oxford University" }, { - "author_name": "Asl\u0131 Suner", - "author_inst": "Ege University" + "author_name": "Mariana Pereira Pinho", + "author_inst": "Oxford University" }, { - "author_name": "Yavuz Oktay", - "author_inst": "Izmir Biomedicine and Genome Center(IBG)" + "author_name": "Paul Buckley", + "author_inst": "Oxford University" + }, + { + "author_name": "Isaac B Woodhouse", + "author_inst": "Oxford University" + }, + { + "author_name": "Graham Ogg", + "author_inst": "University of Oxford" + }, + { + "author_name": "Alison Simmons", + "author_inst": "Oxford University" + }, + { + "author_name": "Giorgio Napolitani", + "author_inst": "Oxford University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "genomics" + "category": "immunology" }, { "rel_doi": "10.1101/2020.05.19.105445", @@ -1421679,21 +1421953,45 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.15.20103184", - "rel_title": "Super spreader cohorts and covid-19", + "rel_doi": "10.1101/2020.05.15.20102715", + "rel_title": "COVID-19 in England: spatial patterns and regional outbreaks", "rel_date": "2020-05-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.15.20103184", - "rel_abs": "A simple two-cohort SIR like model can explain the qualitative behaviour of the logarithmic derivative estimations of the covid-19 epidemic evolution as observed in several countries. The model consists of a general population in which the R0 value is slightly below 1, but in which a super-spreading small subgroup with high R0, coupled to the general population, is contaminating a significant fraction of the population. The epidemic starts to slow down when herd immunity is reached in this subgroup. The dynamics of this system is quite robust against non-pharmaceutical measures.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.15.20102715", + "rel_abs": "Aimsto investigate the spatiotemporal distribution of COVID-19 cases in England; to provide spatial quantification of risk at a high resolution; to provide information for prospective antigen and serological testing.\n\nApproachWe fit a spatiotemporal Negative Binomial generalised linear model to Public Health England SARS-CoV-2 testing data at the Lower Tier Local Authority region level. We assume an order-1 autoregressive model for case progression within regions, coupling discrete spatial units via observed commuting data and time-varying measures of traffic flow. We fit the model via maximum likelihood estimation in order to calculate region-specific risk of ongoing transmission, as well as measuring regional uncertainty in incidence.\n\nResultsWe detect marked heterogeneity across England in COVID-19 incidence, not only in raw estimated incidence, but in the characteristics of within-region and between-region dynamics of PHE testing data. There is evidence for a spatially diverse set of regions having a higher daily increase of cases than others, having accounted for current case numbers, population size, and human mobility. Uncertainty in model estimates is generally greater in rural regions.\n\nConclusionsA wide range of spatial heterogeneity in COVID-19 epidemic distribution and infection rate exists in England currently. Future work should incorporate fine-scaled demographic and health covariates, with continued improvement in spatially-detailed case reporting data. The method described here may be used to measure heterogeneity in real-time as behavioural and social interventions are relaxed, serving to identify \"hotspots\" of resurgent cases occurring in diverse areas of the country, and triggering locally-intensive surveillance and interventions as needed.\n\nCaveatsThere is general concern over the ability of PHE testing data to capture the true prevalence of infection within the population, though this approach is designed to provide measures of spatial prevalence based on testing that can be used to guide further future testing effort. Now-casts of epidemic characteristics are presented based on testing data alone (as opposed to \"true\" prevalence in any one area). The model used in this analysis is phenomenological for ease and speed of principled parameter inference; we choose the model which best fits the current spatial case timeseries, without attempting to enforce \"SIR\"-type epidemic dynamics.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Patrick Van Esch", - "author_inst": "Independent" + "author_name": "Claudio Fronterre", + "author_inst": "Lancaster University" + }, + { + "author_name": "Jonathan M Read", + "author_inst": "Lancaster University" + }, + { + "author_name": "Barry Rowlingson", + "author_inst": "Lancaster University" + }, + { + "author_name": "Jessica Bridgen", + "author_inst": "Lancaster University" + }, + { + "author_name": "Simon Alderton", + "author_inst": "Lancaster University" + }, + { + "author_name": "Peter J Diggle", + "author_inst": "Lancaster University" + }, + { + "author_name": "Chris P Jewell", + "author_inst": "Lancaster University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1423085,35 +1423383,127 @@ "category": "health economics" }, { - "rel_doi": "10.1101/2020.05.15.20095927", - "rel_title": "Disparities in COVID-19 Reported Incidence, Knowledge, and Behavior", + "rel_doi": "10.1101/2020.05.14.20100834", + "rel_title": "COVID-19 management in a UK NHS Foundation Trust with a High Consequence Infectious Diseases centre: a detailed descriptive analysis", "rel_date": "2020-05-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.15.20095927", - "rel_abs": "BackgroundData from the COVID-19 pandemic in the United States show large differences in hospitalizations and mortality across race and geography. However, there is limited data on health information, beliefs, and behaviors that might indicate different exposure to risk.\n\nMethodsA sample of 5,198 respondents in the United States (80% population representative, 20% oversample of hotspot areas in New York City, Seattle, New Orleans, and Detroit) was conducted from March 29th to April 13th to measure differences in knowledge, beliefs and behavior regarding COVID-19. Linear regression was used to understand racial, geographic, political, and socioeconomic differences in COVID-19 reported incidence knowledge, and behaviors after adjusting for state-specific and survey date fixed effects.\n\nResultsThe largest differences in COVID-19 knowledge and behaviors are associated with race/ethnicity, gender, and age. African-Americans, men, and people <55 years old are less likely to know how the disease is spread, less likely to know symptoms of COVID-19, wash their hands less frequently, and leave the home more often. Differences by income, political orientation, and living in a hotspot area are much smaller.\n\nConclusionsThere are wide gaps in COVID-19 reported incidence, knowledge regarding disease spread and symptoms, and in social distancing behavior. The findings suggest more effort is needed to increase accurate information and encourage appropriate behaviors among minority communities, men, and younger people.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.14.20100834", + "rel_abs": "BackgroundRecent large national and international cohorts describe the baseline characteristics and outcome of hospitalised patients with COVID-19, however there is little granularity to these reports. We aimed to provide a detailed description of a UK COVID-19 cohort, focusing on clinical decisions and patient journeys.\n\nMethodsWe retrospectively analysed the management and 28-day outcomes of 316 consecutive adult patients with SARS-CoV-2 PCR-confirmed COVID-19 admitted to a large NHS Foundation Trust with a tertiary High Consequence Infectious Diseases centre in the North of England.\n\nFindingsMost patients were elderly (median age 75) with multiple comorbidities. One quarter were admitted from residential or nursing care. Symptoms were consistent with COVID-19, with cough, fever and/or breathlessness in 90.5% of patients. Two thirds of patients had severe disease on admission. Mortality was 81/291 (27.8%). Most deaths were anticipated; decisions to initiate respiratory support were individualised after consideration of patient wishes, premorbid frailty and comorbidities, with specialist palliative care input where appropriate. 22/291 (7.6%) patients were intubated and 11/22 (50%) survived beyond discharge. Multiple logistic regression identified age as the most significant risk factor for death (OR 1.09 [95% CI 1.06 - 1.12] per year increase, p < 0.001).\n\nInterpretationThese findings provide important clinical context to outcome data. Deaths were anticipated, occurring in patients with advance decisions on ceilings of treatment. Age was the most significant risk factor for death, confirming that demographic factors in the population are a major influence on hospital mortality rates.\n\nFundingFunding was not required.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "David Cutler", - "author_inst": "Harvard" + "author_name": "Kenneth F. Baker", + "author_inst": "Translational and Clinical Research Institute, Newcastle University, UK" }, { - "author_name": "Stefanie Stantcheva", - "author_inst": "Harvard" + "author_name": "Aidan T. Hanrath", + "author_inst": "Translational and Clinical Research Institute, Newcastle University, UK" }, { - "author_name": "Marcella Alsan", - "author_inst": "Harvard" + "author_name": "Ina Schim van der Loeff", + "author_inst": "Translational and Clinical Research Institute, Newcastle University, UK" }, { - "author_name": "David Yang", - "author_inst": "Harvard" + "author_name": "Su Ann Tee", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Richard Capstick", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Gabriella Marchitelli", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Ang Li", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Andrew Barr", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Alsafi Eid", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Sajeel Ahmed", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Dalvir Bajwa", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Omer Mohammed", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Neil Alderson", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Clare Lendrem", + "author_inst": "NIHR In Vitro Diagnostics Cooperative, Newcastle University, UK" + }, + { + "author_name": "Dennis Lendrem", + "author_inst": "National Institute of Health Research (NIHR) Biomedical Research Centre, Newcastle University, UK" + }, + { + "author_name": "COVID-19 Control Group", + "author_inst": "" + }, + { + "author_name": "COVID-19 Clinical Group", + "author_inst": "" + }, + { + "author_name": "Lucia Pareja-Cebrian", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Andrew Welch", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Joanne Field", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Brendan A.I. Payne", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Yusri Taha", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "David A. Price", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Christopher Gibbins", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Matthias L. Schmid", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Ewan Hunter", + "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Christopher J.A. Duncan", + "author_inst": "Translational and Clinical Research Institute, Newcastle University, UK" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.05.13.20100495", @@ -1424247,31 +1424637,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.14.20101717", - "rel_title": "How are adversities during COVID-19 affecting mental health? Differential associations for worries and experiences and implications for policy", + "rel_doi": "10.1101/2020.05.14.20101659", + "rel_title": "Medical Doctors Awareness, Perception, and Attitude towards COVID-19 in Bangladesh: A Cross sectional study", "rel_date": "2020-05-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.14.20101717", - "rel_abs": "ImportanceMultiple data sources suggest that COVID-19 is having adverse effects on mental health. But it is vital to understand what is causing this: worries over potential adversities due to the pandemic, or the toll of experiencing adverse events.\n\nObjectiveTo explore the time-varying longitudinal relationship between (i) worries about adversity, and (ii) experience of adversity, and both anxiety and depression and test the moderating role of socio-economic position.\n\nDesignLongitudinal cohort study\n\nSettingCommunity study\n\nParticipantsA well-stratified sample of UK adults recruited into the UCL COVID -19 Social Study (a panel study collecting data weekly during the Covid-19 pandemic) via a combination of convenience and targeted recruitment. The sample was weighted to population proportions of gender, age, ethnicity, education and geographical location.\n\nExposuresWorries or experiences of adversities during the COVID-19 pandemic\n\nOutcomesAnxiety (GAD-7) and depression (PHQ-9)\n\nResultsData were analysed from 41,909 UK adults (weighted data: 51% female, aged 18-99) followed up across 6 weeks (178,430 observations). Using fixed effects regression was used to explore within-person variation over time, cumulative number of worries and experience of adversities were both related to higher levels of anxiety and depression. Number of worries were associated more with anxiety than depression, but number of experiences were equally related to anxiety and depression. Individuals of lower socio-economic position were more negatively affected psychologically by adverse experiences.\n\nConclusions & relevanceMeasures over the first few weeks of lockdown in the UK appear to have been insufficient at reassuring people given we are still seeing clear associations with poor mental health both for cumulative worries and also for a range of specific worries relating to finance, access to essentials, personal safety and COVID-19. Interventions are required that both seek to prevent adverse events (e.g. redundancies) and that reassure individuals and support adaptive coping strategies.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSHow do worries over potential adversities due to the COVID-19 pandemic, or the toll of experiencing adverse events affect mental health?\n\nFindingsCumulative number of worries and experience of adversities were both related to higher levels of anxiety and depression during COVID-19, especially amongst individuals of lower socio-economic position.\n\nMeaningDuring a pandemic, interventions are required that both seek to prevent adverse events (e.g. redundancies) and that reassure individuals and support adaptive coping strategies.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.14.20101659", + "rel_abs": "ObjectiveCOVID-19 has emerged as a pandemic and during the first week of May Bangladesh has reported more than 10,000 cases. A lack of awareness and poor understanding of the disease may result in rapid transmission of the disease in Bangladesh. This study aimed to investigate the awareness, perception, and attitude towards COVID-19 among Bangladeshi medical doctors.\n\nMethodThis cross sectional, web-based study was conducted with the help of an online questionnaire and sent to the doctors which comprised of a series of questions regarding demographics of the participants, symptoms and incubation period of COVID-19, mode of transmission, measures to prevent transmission, availability of training and personal protective equipment in Bangladeshi hospitals, and attitude of doctors towards the treatment of suspected patients with COVID-19.\n\nResultsOf 800 medical doctors, a total 545 completed the survey (response 68.13%). Among the participants, 52.3% were females, 72.8% were below 30 years of age, and majority (52.8%) were working outside the cities in the villages and rural areas. A total of 404 (74.1%) doctors reported the correct incubation period of COVID-19. Majority doctors were aware of the symptoms with mode of transmission of COVID-19, measures to prevent hospital transmission, along with ways of identifying suspected patients with COVID-19. However, more than 90% of the doctors reported of inadequate intensive care unit and ventilator facilities along with extreme scarcity of personal protective equipment in the hospitals. 65.7% doctors prefer avoid working with a COVID-19 patient and more than 50% doctors have expressed that they would send the suspected COVID-19 patients to designated hospitals without providing treatment.\n\nConclusionThe health authorities should take appropriate training measures to increase the awareness of the medical doctors along with providing sufficient amount of personal protective equipment for the medical doctors and supporting staff before deploying them in hospitals.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Liam Wright", - "author_inst": "University College London" + "author_name": "Sadia Biswas Mumu", + "author_inst": "North South University" }, { - "author_name": "Andrew Steptoe", - "author_inst": "University College London" + "author_name": "Most Nasrin Aktar", + "author_inst": "Brac University" }, { - "author_name": "Daisy Fancourt", - "author_inst": "University College London" + "author_name": "Zabun Nahar", + "author_inst": "University of Asia Pacific" + }, + { + "author_name": "Shahana Sharmin", + "author_inst": "Brac University" + }, + { + "author_name": "Md Shaki Mostaid", + "author_inst": "Brac University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.05.14.20101824", @@ -1425797,65 +1426195,141 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.05.18.102087", - "rel_title": "Controlling the SARS-CoV-2 Spike Glycoprotein Conformation", + "rel_doi": "10.1101/2020.05.18.101717", + "rel_title": "Immunologic perturbations in severe COVID-19/SARS-CoV-2 infection", "rel_date": "2020-05-18", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.18.102087", - "rel_abs": "The coronavirus (CoV) viral host cell fusion spike (S) protein is the primary immunogenic target for virus neutralization and the current focus of many vaccine design efforts. The highly flexible S-protein, with its mobile domains, presents a moving target to the immune system. Here, to better understand S-protein mobility, we implemented a structure-based vector analysis of available {beta}-CoV S-protein structures. We found that despite overall similarity in domain organization, different {beta}-CoV strains display distinct S-protein configurations. Based on this analysis, we developed two soluble ectodomain constructs in which the highly immunogenic and mobile receptor binding domain (RBD) is locked in either the all-RBDs down position or is induced to display a previously unobserved in SARS-CoV-2 2-RBDs up configuration. These results demonstrate that the conformation of the S-protein can be controlled via rational design and provide a framework for the development of engineered coronavirus spike proteins for vaccine applications.", - "rel_num_authors": 12, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.18.101717", + "rel_abs": "Although critical illness has been associated with SARS-CoV-2-induced hyperinflammation, the immune correlates of severe COVID-19 remain unclear. Here, we comprehensively analyzed peripheral blood immune perturbations in 42 SARS-CoV-2 infected and recovered individuals. We identified broad changes in neutrophils, NK cells, and monocytes during severe COVID-19, suggesting excessive mobilization of innate lineages. We found marked activation within T and B cells, highly oligoclonal B cell populations, profound plasmablast expansion, and SARS-CoV-2-specific antibodies in many, but not all, severe COVID-19 cases. Despite this heterogeneity, we found selective clustering of severe COVID-19 cases through unbiased analysis of the aggregated immunological phenotypes. Our findings demonstrate broad immune perturbations spanning both innate and adaptive leukocytes that distinguish dysregulated host responses in severe SARS-CoV-2 infection and warrant therapeutic investigation.\n\nOne Sentence SummaryBroad immune perturbations in severe COVID-19", + "rel_num_authors": 31, "rel_authors": [ { - "author_name": "Rory Henderson", - "author_inst": "Duke University" + "author_name": "Leticia Kuri-Cervantes", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Robert J Edwards", - "author_inst": "Duke University" + "author_name": "M. Betina Pampena", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Katayoun Mansouri", - "author_inst": "Duke University" + "author_name": "Wenzhao Meng", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Katarzyna Janowska", - "author_inst": "Duke University" + "author_name": "Aaron M Rosenfeld", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Victoria Stalls", - "author_inst": "Duke University" + "author_name": "Caroline A.G. Ittner", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Sophie Gobeil", - "author_inst": "Duke University" + "author_name": "Ariel R Weisman", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Megan Kopp", - "author_inst": "Duke University" + "author_name": "Roseline Agyekum", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Divij Mathew", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Allen L Hsu", - "author_inst": "NIH/NIEHS" + "author_name": "Amy E Baxter", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Mario J. Borgnia", - "author_inst": "NIH/NIEHS" + "author_name": "Laura Vella", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Robert Parks", - "author_inst": "Duke University" + "author_name": "Olivia Kuthuru", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Barton F Haynes", - "author_inst": "Duke University" + "author_name": "Sokratis Apostolidis", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Priyamvada Acharya", - "author_inst": "Duke University" + "author_name": "Luanne Bershaw", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Jeanette Dougherty", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Allison R. Greenplate", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Ajinkya Pattekar", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Justin Kim", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Nicholas Han", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Sigrid Gouma", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Madison E. Weirick", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Claudia P Arevalo", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Marcus J Bolton", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Eileen C. Goodwin", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Elizabeth M Anderson", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Scott E. Hensley", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Tiffanie K. Jones", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Nilam S. Mangalmurti", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Eline T. Luning Prak", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Nuala J Meyer", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Justin Kim", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Michael R Betts", + "author_inst": "University of Pennsylvania" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "immunology" }, @@ -1427799,79 +1428273,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.12.20094508", - "rel_title": "COVID-19 OUTCOMES IN MS: EARLY EXPERIENCE FROM NYU MULTIPLE SCLEROSIS COMPREHENSIVE CARE CENTER", + "rel_doi": "10.1101/2020.05.14.20102541", + "rel_title": "How well can we forecast the COVID-19 pandemic with curve fitting and recurrent neural networks?", "rel_date": "2020-05-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.12.20094508", - "rel_abs": "ObjectiveReport outcomes on patients with Multiple Sclerosis (MS) and related disorders with COVID-19 illness.\n\nMethodsFrom March 16 to April 30th, 2020, patients with MS or related disorders at NYU Langone MS Comprehensive Care Center (MSCC) were identified with laboratory-confirmed or suspected COVID-19. The diagnosis was established using a standardized questionnaire or by review of in-patient hospital records.\n\nResultsWe identified 76 patients (55 with relapsing MS of which 9 had pediatric-onset;17 with progressive MS; and 4 with related disorders). 37 underwent PCR testing and were confirmed positive. Of the entire group, 64 (84%) patients were on disease-modifying therapy (DMT) including anti-CD20 therapies (n=34, 44.7%) and sphingosine 1-phosphate receptor modulators (n=10, 13.5%). The most common COVID-19 symptoms were fever and cough, but 21.1% of patients had neurologic symptom recrudescence preceding or coinciding with the infection. A total of 18 (23.7%) were hospitalized; 8 (10.5%) had COVID-19 critical illness or related death. Features more common among those hospitalized or with critical illness or death were older age, presence of comorbidities, progressive disease, and a non-ambulatory status. No DMT class was associated with an increased risk of hospitalization or fatal outcome.\n\nConclusionsMost MS patients with COVID-19 do not require hospitalization despite being on DMTs. Factors associated with critical illness were similar to the general at risk patient population. DMT use did not emerge as a predictor of poor COVID-19 outcome in this preliminary sample.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.14.20102541", + "rel_abs": "Predictions of the COVID-19 pandemic in USA are compared using curve fitting and various recurrent neural networks (RNNs) including the standard long short-term memory (LSTM) RNN and 10 types of slim LSTM RNNs. The curve fitting method predicts the pandemic would end in early summer but the exact date and scale vary with the evolving data used for fitting. All LSTM RNNs result in short-term (8 to 10 days) predictions with comparable accuracies (smaller than 10 %) to curve fitting--they do not show advantage over curve fitting.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Erica Parrotta", - "author_inst": "NYU Langone MS Comprehensive Care Center" - }, - { - "author_name": "Ilya Kister", - "author_inst": "NYU Langone MS Comprehensive Care Center" - }, - { - "author_name": "Leigh Charvet", - "author_inst": "NYU Langone MS Comprehensive Care Center" - }, - { - "author_name": "Carrie Sammarco", - "author_inst": "NYU MS Comprehensive Care Center" - }, - { - "author_name": "Valerie Saha", - "author_inst": "NYU Langone MS Comprehensive Care Center" - }, - { - "author_name": "R.E. Charlson", - "author_inst": "NYU Langone MS Comprehensive Care Center" - }, - { - "author_name": "Jonathan Howard", - "author_inst": "NYU Langone MS Comprehensive Care Center" - }, - { - "author_name": "Josef Maxwell Gutman", - "author_inst": "NYU Langone MS Comprehensive Care Center" - }, - { - "author_name": "Malcolm Gottesman", - "author_inst": "NYU Langone MS Comprehensive Care Center" - }, - { - "author_name": "Nada Abou-Fayssal", - "author_inst": "NYU Langone MS Comprehensive Care Center" - }, - { - "author_name": "Robyn Wolintz", - "author_inst": "NYU Langone MS Comprehensive Care Center" - }, - { - "author_name": "Marshall Keilson", - "author_inst": "NYU Langone MS Comprehensive Care Center" - }, - { - "author_name": "Cristina Fernandez-Carbonell", - "author_inst": "Cohen Children Medical Center/Northwell Health" + "author_name": "Zhuowen Zhao", + "author_inst": "Michigan State University" }, { - "author_name": "Lauren B Krupp", - "author_inst": "NYU Langone MS Comprehensive Care Center" + "author_name": "Kieran Nehil-Puleo", + "author_inst": "Michigan State University" }, { - "author_name": "Lana Zhovtis Ryerson", - "author_inst": "NYU Langone MS Comprehensive Care Center" + "author_name": "Yangzhi Zhao", + "author_inst": "Lawrence Berkeley National Laboratory" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "health informatics" }, { "rel_doi": "10.1101/2020.05.14.20096602", @@ -1429057,27 +1429483,59 @@ "category": "obstetrics and gynecology" }, { - "rel_doi": "10.1101/2020.05.12.20098160", - "rel_title": "COVID-19 genomic susceptibility: Definition of ACE2 variants relevant to human infection with SARS-CoV-2 in the context of ACMG/AMP Guidance", + "rel_doi": "10.1101/2020.05.12.20098699", + "rel_title": "Unequal impact of structural health determinants and comorbidity on COVID-19 severity and lethality in older Mexican adults: Looking beyond chronological aging", "rel_date": "2020-05-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.12.20098160", - "rel_abs": "BackgroundMortality remains very high and unpredictable in CoViD-19, with intense public protection strategies tailored to preceived risk. Males are at greater risk of severe CoViD-19 complications. Genomic studies are in process to identify differences in host susceptibility to SARS-CoV-2 infection.\n\nMethodsGenomic structures were examined for the ACE2 gene that encodes angiotensin-converting enzyme 2, the obligate receptor for SARS-CoV-2. Variants in 213,158 exomes/genomes were integrated with ACE2 protein functional domains, and pathogenicity criteria from the American Society of Human Genetics and Genomics/Association for Molecular Pathology.\n\nResults483 variants were identified in the 19 exons of ACE2 on the X chromosome. All variants were rare, including nine loss-of-function (potentially SARS-CoV-2 protective) alleles present only in female heterozygotes. Unopposed variant alleles were more common in males (262/3596 [7.3%] nucleotides) than females (9/3596 [0.25%] nucleotides, p<0.0001). 37 missense variants substituted amino acids in SARS-CoV-2 interacting regions or critical domains for transmembrane ACE2 expression. Four upstream open reading frames with 31 associated variants were identified. Excepting loss-of-function alleles, variants would not meet minimum criteria for classification as Likely Pathogenic/beneficial if differential frequencies emerged in patients with CoViD-19.\n\nConclusionsMales are more exposed to consequences from a single variant ACE2 allele. Common risk/beneficial alleles are unlikely in regions subject to evolutionary constraint. ACE2 upstream open reading frames may have implications for aminoglycoside use in SARS-CoV-2-infected patients. For this SARS-CoV-2-interacting protein with pre-identified functional domains, pre-emptive functional and computational studies are encouraged to accelerate interpretations of genomic variation for personalised and public health use.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.12.20098699", + "rel_abs": "BACKGROUNDCOVID-19 has had a disproportionate impact on older adults. Mexicos population is younger, yet COVID-19s impact on older adults is comparable to countries with older population structures. Here, we aim to identify health and structural determinants that increase susceptibility to COVID-19 in older Mexican adults beyond chronological aging.\n\nMETHODSWe analyzed confirmed COVID-19 cases in older adults using data from the General Directorate of Epidemiology of Mexican Ministry of Health. We modeled risk factors for increased COVID-19 severity and mortality, using mixed models to incorporate multilevel data concerning healthcare access and marginalization. We also evaluated structural factors and comorbidity profiles compared to chronological age for improving COVID-19 mortality risk prediction.\n\nRESULTSWe analyzed 7,029 confirmed SARS-CoV-2 cases in adults aged [≥]60 years. Male sex, smoking, diabetes, and obesity were associated with pneumonia, hospitalization and ICU admission in older adults, CKD and COPD were associated with hospitalization. High social lag indexes and access to private care were predictors of COVID-19 severity and mortality. Age was not a predictor of COVID-19 severity in individuals without comorbidities and structural factors and comorbidities were better predictors of COVID-19 lethality and severity compared to chronological age. COVID-19 baseline lethality hazards were heterogeneously distributed across Mexican municipalities, particularly when comparing urban and rural areas.\n\nCONCLUSIONSStructural factors and comorbidity explain excess risk for COVID-19 severity and mortality over chronological age in older Mexican adults. Clinical decision-making related to COVID-19 should focus away from chronological aging onto more a comprehensive geriatric care approach.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Claire L Shovlin", - "author_inst": "Imperial College London" + "author_name": "Omar Yaxmehen Bello-Chavolla", + "author_inst": "Instituto Nacional de Geriatria" }, { - "author_name": "Marcela P Vizcaychipi", - "author_inst": "Chelsea & Westminster NHS Foundation Trust, London, UK" + "author_name": "Armando Gonz\u00e1lez-D\u00edaz", + "author_inst": "Universidad Nacional Autonoma de Mexico" + }, + { + "author_name": "Neftali E. Antonio-Villa", + "author_inst": "Instituto Nacional de Ciencias Medicasy Nutricion Salvador Zubiran" + }, + { + "author_name": "Carlos A. Ferm\u00edn-Mart\u00ednez", + "author_inst": "Universidad Nacional Autonoma de Mexico" + }, + { + "author_name": "Alejandro M\u00e1rquez-Salinas", + "author_inst": "Universidad Nacional Autonoma de Mexico" + }, + { + "author_name": "Arsenio Vargas-V\u00e1zquez", + "author_inst": "Instituto Nacional de Ciencias Medicasy Nutricion Salvador Zubiran" + }, + { + "author_name": "Jessica Paola Bahena-L\u00f3pez", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" + }, + { + "author_name": "Carmen Garc\u00eda-Pe\u00f1a", + "author_inst": "Instituto Nacional de Geriatria" + }, + { + "author_name": "Carlos A. Aguilar-Salinas", + "author_inst": "Instituto Nacional de Ciencias Medicasy Nutricion Salvador Zubiran" + }, + { + "author_name": "Luis Miguel Guti\u00e9rrez-Robledo", + "author_inst": "Instituto Nacional de Geriatria" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "category": "geriatric medicine" }, { "rel_doi": "10.1101/2020.05.11.20098392", @@ -1430307,31 +1430765,87 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.11.20098541", - "rel_title": "Robot dance: a city-wise automatic control of Covid-19 mitigation levels", + "rel_doi": "10.1101/2020.05.18.102467", + "rel_title": "Structural basis for translational shutdown and immune evasion by the Nsp1 protein of SARS-CoV-2", "rel_date": "2020-05-18", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.11.20098541", - "rel_abs": "We develop an automatic control system to help to design efficient mitigation measures for the Covid-19 epidemic in cities. Taking into account parameters associated to the population of each city and the mobility among them, the optimal control framework suggests the level and duration of protective measures that must be implemented to ensure that the number of infected individuals is within a range that avoids the collapse of the health care system. Compared against other mitigation measures that are implemented simultaneously and in equal strength across cities our method has three major particularities when:\n\nAccounts for city commute and health infrastructure: It takes into account the daily commute among cities to estimate the dynamics of infected people while keeping the number of infected people within a desired level at each city avoiding the collapse of its health care system.\nCity-specific control: It allows for orchestrating the control measures among cities so as to prevent all cities to face the same level control. The model tends to induce alternation between periods of stricter controls and periods of a more normal life in each city and among the cities.\nFlexible scenarios: It is flexible enough to allow for simulating the impact of particular actions. For example, one can simulate the how the control all cities change when the number of care beds increases in specific places.\n\n\nTherefore, our method creates an automatic dance adjusting mitigation levels within cities and alternating among cities as suggested in [9]. This automatic dance may help the city economy and orchestration of resources.\n\nWe provide case studies using the major cities of the state of Sao Paulo given by using estimates on the daily mobility among the cities their health care system capacity. We use official data in our case studies. However, sub-notification of infected people in Brazil is notoriously high. Hence the case study should not be considered as a real world policy suggestion. It high sub-notification is taken into account, the optimal control algorithm will suggest stricter mitigation measures, as also shown in the case studies. Surprisingly, the total duration of the protocol for the state is barely affected by the sub-notification, but the severity of such protocols is strengthened. This stresses a twofold implication, first, the protocol depends on high-quality data and, second, such optimal and orchestrated protocol is robust and can be adjusted to the demand.", - "rel_num_authors": 3, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.18.102467", + "rel_abs": "SARS-CoV-2 is the causative agent of the current COVID-19 pandemic. A major virulence factor of SARS-CoVs is the nonstructural protein 1 (Nsp1) which suppresses host gene expression by ribosome association via an unknown mechanism. Here, we show that Nsp1 from SARS-CoV-2 binds to 40S and 80S ribosomes, resulting in shutdown of capped mRNA translation both in vitro and in cells. Structural analysis by cryo-electron microscopy (cryo-EM) of in vitro reconstituted Nsp1-40S and of native human Nsp1-ribosome complexes revealed that the Nsp1 C-terminus binds to and obstructs the mRNA entry tunnel. Thereby, Nsp1 effectively blocks RIG-I-dependent innate immune responses that would otherwise facilitate clearance of the infection. Thus, the structural characterization of the inhibitory mechanism of Nsp1 may aid structure-based drug design against SARS-CoV-2.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Paulo J. S. Silva", - "author_inst": "University of Campinas" + "author_name": "Matthias Thoms", + "author_inst": "Gene Center, LMU Munich" }, { - "author_name": "Tiago Pereira", - "author_inst": "University of Sao Paulo" + "author_name": "Robert Buschauer", + "author_inst": "Gene Center, LMU Munich" }, { - "author_name": "Luis Gustavo Nonato", - "author_inst": "University of Sao Paulo" + "author_name": "Michael Ameismeier", + "author_inst": "Gene Center, LMU Munich" + }, + { + "author_name": "Lennart Koepke", + "author_inst": "Ulm University Medical Center" + }, + { + "author_name": "Timo Denk", + "author_inst": "Gene Center, LMU Munich" + }, + { + "author_name": "Maximilian Hirschenberger", + "author_inst": "Ulm University Medical Center" + }, + { + "author_name": "Hanna Kratzat", + "author_inst": "Gene Center, LMU Munich" + }, + { + "author_name": "Manuel Hayn", + "author_inst": "Ulm University Medical Center" + }, + { + "author_name": "Timur Mackens-Kiani", + "author_inst": "Gene Center, LMU Munich" + }, + { + "author_name": "Jingdong Cheng", + "author_inst": "Gene Center, LMU Munich" + }, + { + "author_name": "Christina Martina Stuerzel", + "author_inst": "Ulm University Medical Center" + }, + { + "author_name": "Thomas Froehlich", + "author_inst": "LAFUGA, University of Munich" + }, + { + "author_name": "Otto Berninghausen", + "author_inst": "Gene Center, LMU Munich" + }, + { + "author_name": "Thomas Becker", + "author_inst": "Gene Center, LMU Munich" + }, + { + "author_name": "Frank Kirchhoff", + "author_inst": "Ulm University Medical Center" + }, + { + "author_name": "Konstantin Maria Johannes Sparrer", + "author_inst": "Ulm University Medical Center" + }, + { + "author_name": "Roland Beckmann", + "author_inst": "Gene Center, LMU Munich" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "molecular biology" }, { "rel_doi": "10.1101/2020.05.18.099507", @@ -1431585,33 +1432099,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.13.20101121", - "rel_title": "A comparative analysis of statistical methods to estimate the reproduction number in emerging epidemics with implications for the current COVID-19 pandemic", + "rel_doi": "10.1101/2020.05.13.20101030", + "rel_title": "The Influence of Contextual Factors on the Initial Phases of the COVID-19 Outbreak across U.S. Counties", "rel_date": "2020-05-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.13.20101121", - "rel_abs": "As the SARS-CoV-2 pandemic continues its rapid global spread, quantification of local transmission patterns has been, and will continue to be, critical for guiding pandemic response. Understanding the accuracy and limitations of statistical methods to estimate the reproduction number, R0, in the context of emerging epidemics is therefore vital to ensure appropriate interpretation of results and the subsequent implications for control efforts. Using simulated epidemic data we assess the performance of 6 commonly-used statistical methods to estimate R0 as they would be applied in a real-time outbreak analysis scenario - fitting to an increasing number of data points over time and with varying levels of random noise in the data. Method comparison was also conducted on empirical outbreak data, using Zika surveillance data from the 2015-2016 epidemic in Latin America and the Caribbean. We find that all methods considered here frequently over-estimate R0 in the early stages of epidemic growth on simulated data, the magnitude of which decreases when fitted to an increasing number of time points. This trend of decreasing bias over time can easily lead to incorrect conclusions about the course of the epidemic or the need for control efforts. We show that true changes in pathogen transmissibility can be difficult to disentangle from changes in methodological accuracy and precision, particularly for data with significant over-dispersion. As localised epidemics of SARS-CoV-2 take hold around the globe, awareness of this trend will be important for appropriately cautious interpretation of results and subsequent guidance for control efforts.\n\nSignificance StatementIn line with a real-time outbreak analysis we use simulated epidemic data to assess the performance of 6 commonly-used statistical methods to estimate the reproduction number, R0, at different time points during the epidemic growth phase. We find that estimates of R0 are frequently overestimated by these methods in the early stages of epidemic growth, with decreasing bias when fitting to an increasing number of time points. Reductions in R0 estimates obtained at sequential time points during early epidemic growth may reflect increased methodological accuracy rather than reductions in pathogen transmissibility or effectiveness of interventions. As SARS-CoV-2 continues its geographic spread, awareness of this bias will be important for appropriate interpretation of results and subsequent guidance for control efforts.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.13.20101030", + "rel_abs": "ObjectivesTo examine the influence of county- and state-level characteristics on the initial phases of the COVID-19 outbreak across U.S. counties up to April 14, 2020.\n\nMethodsWe used a statistical exponential growth model for the outbreak. Contextual factors at county- and state-level were simultaneously tested with a multilevel linear model. All data was publicly available.\n\nResultsCollectivism was positively associated with the outbreak rate. The racial and ethnic composition of counties contributed to outbreak differences, affecting Black/African and Asian Americans most. Counties with a higher median age had a stronger outbreak, as did counties with more people below the age of 18. Higher income, education, and personal health were generally associated with a lower outbreak. Obesity was negatively related to the outbreak. Smoking was negatively related, but only directionally informative. Air pollution was another significant contributor to the outbreak, but population density did not give statistical significance.\n\nConclusionsBecause of high intrastate and intercounty variation in contextual factors, policy makers need to target pandemic responses to the smallest subdivision possible, so that countermeasures can be implemented effectively.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Megan O'Driscoll", - "author_inst": "Imperial College London" - }, - { - "author_name": "Carole Harry", - "author_inst": "Mines ParisTech" - }, - { - "author_name": "Christl A. Donnelly", - "author_inst": "Imperial College London" - }, - { - "author_name": "Anne Cori", - "author_inst": "Imperial College London" + "author_name": "Wolfgang Messner", + "author_inst": "University of South Carolina" }, { - "author_name": "Ilaria Dorigatti", - "author_inst": "Imperial College London" + "author_name": "Sarah E Payson", + "author_inst": "University of South Carolina" } ], "version": "1", @@ -1432935,97 +1433437,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.12.20099929", - "rel_title": "Tracking the COVID-19 pandemic in Australia using genomics", + "rel_doi": "10.1101/2020.05.13.20100271", + "rel_title": "Identifying baseline clinical features of people with COVID-19", "rel_date": "2020-05-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.12.20099929", - "rel_abs": "BACKGROUNDWhole-genome sequencing of pathogens can improve resolution of outbreak clusters and define possible transmission networks. We applied high-throughput genome sequencing of SARS-CoV-2 to 75% of cases in the State of Victoria (population 6.24 million) in Australia.\n\nMETHODSCases of SARS-CoV-2 infection were detected through active case finding and contact tracing. A dedicated SARS-CoV-2 multidisciplinary genomic response team was formed to enable rapid integration of epidemiological and genomic data. Phylodynamic analysis was performed to assess the putative impact of social restrictions.\n\nRESULTSBetween 25 January and 14 April 2020, 1,333 COVID-19 cases were reported in Victoria, with a peak in late March. After applying internal quality control parameters, 903 samples were included in genomic analyses. Sequenced samples from Australia were representative of the global diversity of SARS-CoV-2, consistent with epidemiological findings of multiple importations and limited onward transmission. In total, 76 distinct genomic clusters were identified; these included large clusters associated with social venues, healthcare facilities and cruise ships. Sequencing of sequential samples from 98 patients revealed minimal intra-patient SARS-CoV-2 genomic diversity. Phylodynamic modelling indicated a significant reduction in the effective viral reproductive number (Re) from 1.63 to 0.48 after the implementation of travel restrictions and population-level physical distancing.\n\nCONCLUSIONSOur data provide a comprehensive framework for the use of SARS-CoV-2 genomics in public health responses. The application of genomics to rapidly identify SARS-CoV-2 transmission chains will become critically important as social restrictions ease globally. Public health responses to emergent cases must be swift, highly focused and effective.", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.13.20100271", + "rel_abs": "ObjectivesTo describe baseline clinical characteristics of adult patients with COVID-19.\n\nMethodsWe conducted a scoping review of the evidence available at LitCovid, until March 23th, 2020, and selected articles that reported the prevalence of socio-demographic characteristics, symptoms and co-morbidities in adults with COVID-19.\n\nResultsIn total, 1 572 publications were published on LitCovid. We have included 56 articles in our analysis, with 89% conducted in China, and 75% contained inpatients. Three studies were conducted in North America and one in Europe. Participants age ranged from 28 to 70 years, with balanced gender distribution. Proportion of asymptomatic cases were from 2 to 79%. The most common reported symptoms were fever [4-99%], cough [4-92%], dyspnoea/shortness of breath [1-90%], fatigue 4-89%], myalgia [3-65%], and pharyngalgia [2-61%], while regarding co-morbidities we found cardiovascular disease [1-40%], hypertension [0-40%] and cerebrovascular disease [1-40%]. Such heterogeneity impairs the conduction of meta-analysis.\n\nConclusionThe infection by COVID-19 seems to affect people in a very diverse manner and with different characteristics. With the available data it is not possible to clearly identify those at higher risk of being infected with this condition. Furthermore, the evidence from countries other than China is, at the day, too scarce.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Torsten Seemann", - "author_inst": "The University of Melbourne at The Doherty Institute" - }, - { - "author_name": "Courtney Lane", - "author_inst": "The University of Melbourne at The Doherty Institute" - }, - { - "author_name": "Norelle Sherry", - "author_inst": "The University of Melbourne at The Doherty Institute" - }, - { - "author_name": "Sebastian Duchene", - "author_inst": "The University of Melbourne at The Doherty Institute" - }, - { - "author_name": "Anders Goncalves da Silva", - "author_inst": "The University of Melbourne at The Doherty Institute" - }, - { - "author_name": "Leon Caly", - "author_inst": "Victorian Infectious Diseases Reference Laboratory at The Doherty Institute" - }, - { - "author_name": "Michelle Sait", - "author_inst": "The University of Melbourne at The Doherty Institute" - }, - { - "author_name": "Susan A Ballard", - "author_inst": "The University of Melbourne at The Doherty Institute" - }, - { - "author_name": "Kristy Horan", - "author_inst": "The University of Melbourne at The Doherty Institute" - }, - { - "author_name": "Mark B Schultz", - "author_inst": "The University of Melbourne at The Doherty Institute" - }, - { - "author_name": "Tuyet Hoang", - "author_inst": "The University of Melbourne at The Doherty Institute" - }, - { - "author_name": "Marion Easton", - "author_inst": "Victorian Department of Health and Human Services, Government of Victoria" - }, - { - "author_name": "Sally Dougall", - "author_inst": "Victorian Department of Health and Human Services, Government of Victoria" - }, - { - "author_name": "Tim Stinear", - "author_inst": "University of Melbourne at The Doherty Institute" - }, - { - "author_name": "Julian Druce", - "author_inst": "Victorian Infectious Diseases Reference Laboratory at The Doherty Institute" - }, - { - "author_name": "mike Catton", - "author_inst": "Victorian Infectious Diseases Reference Laboratory at The Doherty Institute" - }, - { - "author_name": "Brett Sutton", - "author_inst": "Victorian Department of Health and Human Services, Government of Victoria" - }, - { - "author_name": "Annaliese van Diemen", - "author_inst": "Victorian Department of Health and Human Services, Government of Victoria" + "author_name": "Daniela Ferreira-Santos", + "author_inst": "FMUP" }, { - "author_name": "Charles Alpren", - "author_inst": "Victorian Department of Health and Human Services, Government of Victoria" - }, - { - "author_name": "Deborah Williamson", - "author_inst": "The University of Melbourne at The Doherty Institute" + "author_name": "Priscila Maranhao", + "author_inst": "CINTESIS" }, { - "author_name": "Benjamin P Howden", - "author_inst": "University of Melbourne at the Doherty Institute" + "author_name": "Matilde Monteiro-Soares", + "author_inst": "FMUP MEDCIDS & CINTESIS" } ], "version": "1", @@ -1434697,79 +1435127,75 @@ "category": "radiology and imaging" }, { - "rel_doi": "10.1101/2020.05.11.20094854", - "rel_title": "The impact of goggle-associated harms to health and working status of nurses during management of COVID-19", + "rel_doi": "10.1101/2020.05.10.20096958", + "rel_title": "Upregulation of Human Endogenous Retroviruses in Bronchoalveolar Lavage Fluid of COVID-19 Patients", "rel_date": "2020-05-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.11.20094854", - "rel_abs": "BackgroundTo investigate the impact of goggles on their health and clinical practice during management of patients with COVID-19.\n\nMethods231 nurse practitioners were enrolled who worked in isolation region in designated hospitals to admit patients with COVID-19 in China. Demographic data, goggle-associated symptoms and underlying reasons, incidence of medical errors or exposures, the effects of fog in goggles on practice were all collected. Data were stratified and analyzed by age or working experience. Risk factors of goggle-associated medical errors were analyzed by multivariable logistical regression analysis.\n\nFindingsGoggle-associated symptoms and foggy goggles widely presented in nurses. The most common symptoms were headache, skin pressure injury and dizziness. Headache, vomit and nausea were significantly fewer reported in nurses with longer working experience while rash occurred higher in this group. The underlying reasons included tightness of goggles, unsuitable design and uncomfortable materials. The working status of nurses with more working experience was less impacted by goggles. 11.3% nurses occurred medical exposures in clinical practice while 19.5% nurses made medical errors on patients. The risk factors for medical errors were time interval before adapting to goggle-associated discomforts, adjusting goggles and headache.\n\nInterpretationGoggle-associated symptoms and fog can highly impact the working status and contribute to medical errors during management of COVID-19. Increased the experience with working in PPE through adequate training and psychological education may benefit for relieving some symptoms and improving working status. Improvement of goggle design during productive process was strongly suggested to reduce incidence of discomforts and medical errors.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.10.20096958", + "rel_abs": "BackgroundSevere COVID-19 pneumonia has been associated with the development of intense inflammatory responses during the course of infections with SARS-CoV-2. Given that Human Endogenous Retroviruses (HERVs) are known to be activated during and participate in inflammatory processes, we examined whether HERV dysregulation signatures are present in COVID-19 patients.\n\nResultsBy comparing transcriptomes of Peripheral Blood Monocytes (PBMCs) and Bronchoalveolar Lavage Fluid (BALF) from patients and normal controls we have shown that HERVs are intensely dysregulated in BALF, but not in PBMCs. In particular, upregulation in the expression of multiple HERV families was detected in BALF samples of COVID-19 patients, with HERV-W being the most highly upregulated family among the families analysed. In addition, we compared the expression of HERVs in Human Bronchial Epithelial Cells (HBECs) without and after senescence induction in an oncogene-induced senescence model, in order to quantitatively measure changes in the expression of HERVs in bronchial cells during the processes of cellular senescence.\n\nConclusionsThis apparent difference of HERV dysregulation between PBMCs and BALF warrants further studies in involvement of HERVs in inflammatory pathogenetic mechanisms as well as exploration of HERVs as potential biomarkers for disease progression. Furthermore, the increase in the expression of HERVs in senescent HBECs in comparison to non-induced HBECs provides a potential link for increased COVID-19 severity and mortality in aged populations.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Xiao-huan He", - "author_inst": "General Hospital of Western Theater Command" - }, - { - "author_name": "Yan-ru Feng", - "author_inst": "Xi Kang Hospital" + "author_name": "Konstantina Kitsou", + "author_inst": "Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Greece" }, { - "author_name": "Gao-ming Li", - "author_inst": "Army Medical University" + "author_name": "Anastasia Kotanidou", + "author_inst": "1st Department of Critical Care & Pulmonary Services, Medical School, National and Kapodistrian University of Athens, Greece" }, { - "author_name": "Xiao-jiao Pang", - "author_inst": "Air Force Hospital of Western Theater Command" + "author_name": "Dimitrios Paraskevis", + "author_inst": "Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Greece" }, { - "author_name": "Ting Chen", - "author_inst": "General Hospital of Western Theater Command" + "author_name": "Timokratis Karamitros", + "author_inst": "Unit of Bioinformatics and Applied Genomics, Department of Microbiology, Hellenic Pasteur Institute, Athens, Greece" }, { - "author_name": "Ya-li Zhou", - "author_inst": "San Ai Tang Hospital" + "author_name": "Aris Katzourakis", + "author_inst": "Department of Zoology, University of Oxford, United Kingdom" }, { - "author_name": "Hao Zhang", - "author_inst": "Armed Police Force Hospital of Chongqing" + "author_name": "Richard Tedder", + "author_inst": "Imperial College, London, United Kingdom" }, { - "author_name": "Jing Lang", - "author_inst": "General Hospital of Western Theater Command" + "author_name": "Tara Hurst", + "author_inst": "Birmingham City University, Birmingham, United Kingdom" }, { - "author_name": "Li-min Li", - "author_inst": "Characteristic Medical Center of the Chinese people's Armed Police Force" + "author_name": "Spyros Sapounas", + "author_inst": "National Public Health Organization, Athens, Greece" }, { - "author_name": "Li Feng", - "author_inst": "Special Service Sanatorium Center of the Chinese people's Armed Police Force" + "author_name": "Athanassios Kotsinas", + "author_inst": "Department of Histology and Embryology, School of Medicine, National Kapodistrian University of Athens, Greece" }, { - "author_name": "Xin He", - "author_inst": "General Hospital of Western Theater Command" + "author_name": "Vassilis Gorgoulis", + "author_inst": "Department of Histology and Embryology, School of Medicine, National Kapodistrian University of Athens, Greece" }, { - "author_name": "Wei Zheng", - "author_inst": "General Hospital of Western Theater Command" + "author_name": "Vana Spoulou", + "author_inst": "Immunobiology and Vaccine Research Laboratory, First Department of Peadiatrics, Aghia Sophia Childrens Hospital, School of Medicine, National and Kapodistrian U" }, { - "author_name": "Hongming Miao", - "author_inst": "Third Military Medical University (Army Medical University)" + "author_name": "Sotirios Tsiodras", + "author_inst": "4th Department of Internal Medicine, Attikon University Hospital, MedicalSchool, National and Kapodistrian University of Athens, Greece" }, { - "author_name": "Yong-hua Wang", - "author_inst": "General Hospital of Western Theater Command" + "author_name": "Pagona Lagiou", + "author_inst": "Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Greece" }, { - "author_name": "Xia Kang", - "author_inst": "General Hospitalf of Western Theater Command" + "author_name": "Gkikas Magiorkinis", + "author_inst": "Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Greece" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health systems and quality improvement" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.05.11.20095158", @@ -1436190,203 +1436616,35 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2020.05.13.092619", - "rel_title": "Convergent Antibody Responses to SARS-CoV-2 Infection in Convalescent Individuals", + "rel_doi": "10.1101/2020.05.15.097980", + "rel_title": "Structural analysis of the SARS-CoV-2 methyltransferase complex involved in coronaviral RNA cap creation", "rel_date": "2020-05-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.13.092619", - "rel_abs": "During the COVID-19 pandemic, SARS-CoV-2 infected millions of people and claimed hundreds of thousands of lives. Virus entry into cells depends on the receptor binding domain (RBD) of the SARS-CoV-2 spike protein (S). Although there is no vaccine, it is likely that antibodies will be essential for protection. However, little is known about the human antibody response to SARS-CoV-21-5. Here we report on 149 COVID-19 convalescent individuals. Plasmas collected an average of 39 days after the onset of symptoms had variable half-maximal neutralizing titers ranging from undetectable in 33% to below 1:1000 in 79%, while only 1% showed titers >1:5000. Antibody cloning revealed expanded clones of RBD-specific memory B cells expressing closely related antibodies in different individuals. Despite low plasma titers, antibodies to three distinct epitopes on RBD neutralized at half-maximal inhibitory concentrations (IC50s) as low as single digit ng/mL. Thus, most convalescent plasmas obtained from individuals who recover from COVID-19 do not contain high levels of neutralizing activity. Nevertheless, rare but recurring RBD-specific antibodies with potent antiviral activity were found in all individuals tested, suggesting that a vaccine designed to elicit such antibodies could be broadly effective.", - "rel_num_authors": 46, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.15.097980", + "rel_abs": "COVID-19 pandemic is caused by the SARS-CoV-2 virus that has several enzymes that could be targeted by antivirals including a 2-O RNA methyltransferase (MTase) that is involved in the viral RNA cap formation; an essential process for RNA stability. This MTase is composed of two nonstructural proteins, the nsp16 catalytic subunit and the activating nsp10 protein. We have solved the crystal structure of the nsp10-nsp16 complex bound to the pan-MTase inhibitor sinefungin in the active site. Based on the structural data we built a model of the MTase in complex with RNA that illustrates the catalytic reaction. A structural comparison to the Zika MTase revealed low conservation of the catalytic site between these two RNA viruses suggesting preparation of inhibitors targeting both these viruses will be very difficult. Together, our data will provide the information needed for structure-based drug design.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Davide F. Robbiani", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Christian Gaebler", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Frauke Muecksch", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Julio Cetrulo Lorenzi", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Zijun Wang", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Alice Cho", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Marianna Agudelo", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Christopher Barnes", - "author_inst": "Caltech" - }, - { - "author_name": "Shlomo Finkin", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Thomas Hagglof", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Thiago Oliveira", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Charlotte Viant", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Arlene Hurley", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Katrina Millard", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Rhonda Kost", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Melissa Cipolla", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Anna Gazumyan", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Kristie Gordon", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Filippo Bianchini", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Spencer Chen", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Victor Ramos", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Roshni Patel", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Juan Dizon", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Irina Shimeliovich", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Pilar Mendoza", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Harald Hartweger", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Lilian Nogueira", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Maggi Pack", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Jill Horowitz", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Fabian Schmidt", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Yiska Weisblum", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Hans-Heinrich Hoffmann", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Eleftherios Michailidis", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Alison Ashbrook", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Eric F. Waltari", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "John Pak", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Kathryn Huey-Tubman", - "author_inst": "Caltech" - }, - { - "author_name": "Nicholas Koranda", - "author_inst": "Caltech" - }, - { - "author_name": "Pauline Hoffman", - "author_inst": "Caltech" - }, - { - "author_name": "Anthony West", - "author_inst": "Caltech" - }, - { - "author_name": "Charles Rice", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Theodora Hatziioannou", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Pamela Bjorkman", - "author_inst": "Caltech" + "author_name": "Petra Krafcikova", + "author_inst": "IOCB" }, { - "author_name": "Paul Bieniasz", - "author_inst": "Rockefeller University" + "author_name": "Jan Silhan", + "author_inst": "IOCB" }, { - "author_name": "Marina Caskey", - "author_inst": "Rockefeller University" + "author_name": "Radim Nencka", + "author_inst": "Institute of Organic Chemistry and Biochemistry of the CAS" }, { - "author_name": "Michel Nussenzweig", - "author_inst": "Rockefeller University" + "author_name": "Evzen Boura", + "author_inst": "IOCB" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2020.05.14.097204", @@ -1438212,55 +1438470,147 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.05.14.093583", - "rel_title": "Exosomes Facilitate Transmission of SARS-CoV-2 Genome into Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes", + "rel_doi": "10.1101/2020.05.14.096727", + "rel_title": "Characteristic and quantifiable COVID-19-like abnormalities in CT- and PET/CT-imaged lungs of SARS-CoV-2-infected crab-eating macaques (Macaca fascicularis)", "rel_date": "2020-05-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.14.093583", - "rel_abs": "ABSTRACTThe novel coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved into a worldwide pandemic. Early data suggest that the prevalence and severity of COVID-19 appear to be higher among patients with underlying cardiovascular risk factors. Despite the expression of angiotensin-converting enzyme 2 (ACE2), a functional receptor for SARS-CoV-2 infection, in cardiomyocytes, there has been no conclusive evidence of direct viral infection although the presence of inflammation and viral genome within the hearts of COVID-19 patients have been reported. Here we transduced A549 lung epithelial cells with lentivirus overexpressing selected genes of the SARS-CoV-2. We then isolated extracellular vesicles (EVs) from the supernatant of A549 cells and detected the presence of viral RNA within the purified EVs. Importantly, we observed that human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) were able to actively uptake these EVs and viral genes were subsequently detected in the cardiomyocytes. Accordingly, uptake of EVs containing viral genes led to an upregulation of inflammation-related genes in hiPSC-CMs. Thus, our findings indicate that SARS-CoV-2 RNA-containing EVs represent an indirect route of viral RNA entry into cardiomyocytes.Competing Interest StatementThe authors have declared no competing interest.View Full Text", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.14.096727", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is causing an exponentially increasing number of coronavirus disease 19 (COVID-19) cases globally. Prioritization of medical countermeasures for evaluation in randomized clinical trials is critically hindered by the lack of COVID-19 animal models that enable accurate, quantifiable, and reproducible measurement of COVID-19 pulmonary disease free from observer bias. We first used serial computed tomography (CT) to demonstrate that bilateral intrabronchial instillation of SARS-CoV-2 into crab-eating macaques (Macaca fascicularis) results in mild-to-moderate lung abnormalities qualitatively characteristic of subclinical or mild-to-moderate COVID-19 (e.g., ground-glass opacities with or without reticulation, paving, or alveolar consolidation, peri-bronchial thickening, linear opacities) at typical locations (peripheral>central, posterior and dependent, bilateral, multi-lobar). We then used positron emission tomography (PET) analysis to demonstrate increased FDG uptake in the CT-defined lung abnormalities and regional lymph nodes. PET/CT imaging findings appeared in all macaques as early as 2 days post-exposure, variably progressed, and subsequently resolved by 6-12 days post-exposure. Finally, we applied operator-independent, semi-automatic quantification of the volume and radiodensity of CT abnormalities as a possible primary endpoint for immediate and objective efficacy testing of candidate medical countermeasures.", + "rel_num_authors": 32, "rel_authors": [ { - "author_name": "Youjeong Kwon", - "author_inst": "University of Illinois at Chicago" + "author_name": "Courtney L. Finch", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " }, { - "author_name": "Sarath Babu Nukala", - "author_inst": "University of Illinois at Chicago" + "author_name": "Ian Crozier", + "author_inst": "Integrated Research Facility at Fort Detrick, Clinical Monitoring Research Program Directorate, Frederick National Laboratory for Cancer Research supported by t" }, { - "author_name": "Shubhi Srivastava", - "author_inst": "University of Illinois at Chicago" + "author_name": "Ji Hyun Lee", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " }, { - "author_name": "Hiroe Miyamoto", - "author_inst": "University of Illinois at Chicago" + "author_name": "Russ Byrum", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " }, { - "author_name": "Nur Izzah Ismail", - "author_inst": "Chinese University of Hong Kong (CUHK), Hong Kong SAR" + "author_name": "Timothy K. Cooper", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " }, { - "author_name": "Jalees Rehman", - "author_inst": "University of Illinois at Chicago" + "author_name": "Janie Liang", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " }, { - "author_name": "Sang-Bing Ong", - "author_inst": "Chinese University of Hong Kong (CUHK), Hong Kong SAR" + "author_name": "Kaleb Sharer", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " }, { - "author_name": "Won Hee Lee", - "author_inst": "University of Arizona College of Medicine - Phoenix" + "author_name": "Jeffrey Solomon", + "author_inst": "Integrated Research Facility at Fort Detrick, Clinical Monitoring Research Program Directorate, Frederick National Laboratory for Cancer Research supported by t" }, { - "author_name": "Sang-Ging Ong", - "author_inst": "University of Illinois at Chicago" + "author_name": "Philip J. Sayre", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " + }, + { + "author_name": "Gregory Kocher", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " + }, + { + "author_name": "Christopher Bartos", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " + }, + { + "author_name": "Nina M. Aiosa", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " + }, + { + "author_name": "Marcelo Castro", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " + }, + { + "author_name": "Peter A. Larson", + "author_inst": "United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, Frederick, Maryland 21702, USA" + }, + { + "author_name": "Ricky Adams", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " + }, + { + "author_name": "Brett Beitzel", + "author_inst": "United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, Frederick, Maryland 21702, USA" + }, + { + "author_name": "Nicholas Di Paola", + "author_inst": "United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, Frederick, Maryland 21702, USA" + }, + { + "author_name": "Jeffrey R. Kugelman", + "author_inst": "United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, Frederick, Maryland 21702, USA" + }, + { + "author_name": "Jonathan R. Kurtz", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " + }, + { + "author_name": "Tracey Burdette", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " + }, + { + "author_name": "Martha C. Nason", + "author_inst": "Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD 20892, USA" + }, + { + "author_name": "Irwin M. Feuerstein", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " + }, + { + "author_name": "Gustavo Palacios", + "author_inst": "United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, Frederick, Maryland 21702, USA" + }, + { + "author_name": "Marisa C. St. Claire", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " + }, + { + "author_name": "Matthew G. Lackemeyer", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " + }, + { + "author_name": "Reed F. Johnson", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " + }, + { + "author_name": "Katarina M. Braun", + "author_inst": "Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA" + }, + { + "author_name": "Mitchell D. Ramuta", + "author_inst": "Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, WI 53706, USA" + }, + { + "author_name": "Jiro Wada", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " + }, + { + "author_name": "Connie S. Schmaljohn", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " + }, + { + "author_name": "Thomas C. Friedrich", + "author_inst": "Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA; Wisconsin National Primate Research Center, Madison, WI 53706, " + }, + { + "author_name": "Jens H. Kuhn", + "author_inst": "Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD " } ], "version": "1", - "license": "cc_no", + "license": "cc0", "type": "new results", - "category": "cell biology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.05.14.096081", @@ -1439630,29 +1439980,29 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.05.10.20097295", - "rel_title": "COVID-19: Easing the coronavirus lockdowns with caution", + "rel_doi": "10.1101/2020.05.10.20097063", + "rel_title": "Automatic Detection of COVID-19 Infection from Chest X-ray using Deep Learning", "rel_date": "2020-05-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.10.20097295", - "rel_abs": "BackgroundThe spread of the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) has reached a global level, creating a pandemic. The government of various countries, their citizens, politicians, and business owners are worried about the unavoidable economic impacts of this pandemic. Therefore, there is an eagerness for the pandemic peaking.\n\nObjectivesThis study uses an objective approach to emphasize the need to be pragmatic with easing of lockdowns measures worldwide through the forecast of the possible trend of COVID-19. This is necessary to ensure that the enthusiasm about SARS-CoV-2 peaking is properly examined, easing of lockdown is done systematically to avoid second-wave of the pandemic.\n\nMethodsWe used the Facebook prophet on the World Health Organization data for COVID-19 to forecast the spread of SARS-CoV-2 for the 7th April until 3rd May 2020. The forecast model was further used to forecast the trend of the virus for the 8th until 14th May 2020. We presented the forecast of the confirmed and death cases.\n\nResultsOur findings from the forecast showed an increase in the number of new cases for this period. Therefore, the need for easing the lockdown with caution becomes imperative. Our model showed good performance when compared to the official report from the World Health Organization. The average forecasting accuracy of our model was 79.6%.\n\nConclusionAlthough, the global and economic impact of COVID-19 is daunting. However, excessive optimism about easing the lockdown should be appropriately weighed against the risk of underestimating its spread. As seen globally, the risks appeared far from being symmetric. Therefore, the forecasting provided in this study offers an insight into the spread of the virus for effective planning and decision-making in terms of easing the lockdowns in various countries.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.10.20097063", + "rel_abs": "COVID-19 infection has created a panic across the globe in recent times. Early detection of COVID-19 infection can save many lives in the prevailing situation. This virus affects the respiratory system of a person and creates white patchy shadows in the lungs. Deep learning is one of the most effective Artificial Intelligence techniques to analyse chest X-ray images for efficient and reliable COVID-19 screening. In this paper, we have proposed a Deep Convolutional Neural Network method for fast and dependable identification of COVID-19 infection cases from the patient chest X-ray images. To validate the performance of the proposed system, chest X-ray images of more than 150 confirmed COVID-19 patients from the Kaggle data repository are used in the experimentation. The results show that the proposed system identifies the cases with an accuracy of 93%.", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Rasheed Omobolaji Alabi", - "author_inst": "University of Vaasa" + "author_name": "kishore Medhi", + "author_inst": "NEHU" }, { - "author_name": "Akpojoto Siemuri", - "author_inst": "University of Vaasa" + "author_name": "Md. Jamil", + "author_inst": "NEGRIMS" }, { - "author_name": "Mohammed Elmusrati", - "author_inst": "University of Vaasa" + "author_name": "Iftekhar Hussain", + "author_inst": "NEHU" } ], "version": "1", - "license": "cc0_ng", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "health informatics" }, @@ -1441056,25 +1441406,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.08.20096008", - "rel_title": "CoViD-19 Epidemic in India and Projections: Is Relief in Sight?", + "rel_doi": "10.1101/2020.05.08.20095794", + "rel_title": "The Epidemiology of COVID-19 and applying Non Pharmaceutical interventions by using the Susceptible, Infectious Recovered epidemiological Model in Pakistan.", "rel_date": "2020-05-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20096008", - "rel_abs": "BackgroundProjection of cases and deaths in an epidemic such as CoViD-19 is hazardous and the early projections were way-off the actual pattern. However, we now have actual data for more than 50 consecutive days in India that can be effectively used for projection.\n\nMethodsWe closely track the trend and use the same pattern for projection. We call this Empirical Model. We also fit a Theoretical Model based on a Gamma function on the pattern of some of the previous epidemics.\n\nResultsThe Empirical Model predicts the peak around the fourth week of May and the near end of the epidemic by the end of June 2020. The maximum number of active cases is likely to be nearly 75,000 during the second week of June. This would mean a peak demand of nearly 15,000 beds and nearly 4000 ventilators. The case-fatality based on those who have reached an outcome was nearly 10% in the first week of May and is likely to remain at this level for some time. Theoretical Model projected a peak of nearly 2500 new cases per day in the second week of May that seems to have been already breached. This model predicts the near end of the epidemic by the middle of July 2020.\n\nConclusionWith the current trend, the end of the epidemic is in sight with relatively mild consequences in India compared with most other countries.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20095794", + "rel_abs": "IntroductionThe COVID-19 is caused by the virus known as sever acute respiratory syndrome corona virus 2 (SARS-CoV-2) having the common symptoms such as Flue, fever, dry cough and shortness of breath. The first case was reported in WUHAN city china in December 2019 and it spread to the whole world, WHO declared as world pandemic on 11th march 2020.\n\nSIR Epidemiological ModelThe first case in Pakistan was confirmed on 26th Feb 2020 as by the 8th April 2020 the total no of confirmed cases 4187 with 58 deaths and 467 recoveries throughout the country. The upcoming situation of the COVID-19 in Pakistan is forecasted by using SIR epidemiological, which is one of the mathematical derivative models with great accuracy rate prediction used for infectious disease. This model was introduced in the early 20th century.\n\nResultsPakistan is will be having a heavy burden of patients 80000 plus infected patients 45000 recoveries 10000 hospitalized 3000 ICU and 800 plus deaths in the next 20 days. A complete lock down, social distancing and imposing curfew to keep every person at home can save Pakistan from a very huge number 1000000 infected patients with huge number of causalities with next 2 months.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Abhaya Indrayan", - "author_inst": "Max Healthcare" + "author_name": "Abdul Wahid", + "author_inst": "University of Balochistan" }, { - "author_name": "Shubham Shukla", - "author_inst": "Max Healthcare" + "author_name": "Amjad Khan", + "author_inst": "Quaid i Azam University, islamabad" + }, + { + "author_name": "Qaiser Iqbal", + "author_inst": "University of Balochistan, Quetta" + }, + { + "author_name": "Asad Khan", + "author_inst": "Quaid i Azam University" + }, + { + "author_name": "Nazar Mohammad", + "author_inst": "World Health Organization, Quetta" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1442518,159 +1442880,51 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.05.13.093195", - "rel_title": "ChAdOx1 nCoV-19 vaccination prevents SARS-CoV-2 pneumonia in rhesus macaques", + "rel_doi": "10.1101/2020.05.12.090324", + "rel_title": "Infection Groups Differential (IGD) Score Reveals Infection Ability Difference between SARS-CoV-2 and Other Coronaviruses", "rel_date": "2020-05-13", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.13.093195", - "rel_abs": "Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) emerged in December 20191,2 and is responsible for the COVID-19 pandemic3. Vaccines are an essential countermeasure urgently needed to control the pandemic4. Here, we show that the adenovirus-vectored vaccine ChAdOx1 nCoV-19, encoding the spike protein of SARS-CoV-2, is immunogenic in mice, eliciting a robust humoral and cell-mediated response. This response was not Th2 dominated, as demonstrated by IgG subclass and cytokine expression profiling. A single vaccination with ChAdOx1 nCoV-19 induced a humoral and cellular immune response in rhesus macaques. We observed a significantly reduced viral load in bronchoalveolar lavage fluid and respiratory tract tissue of vaccinated animals challenged with SARS-CoV-2 compared with control animals, and no pneumonia was observed in vaccinated rhesus macaques. Importantly, no evidence of immune-enhanced disease following viral challenge in vaccinated animals was observed. ChAdOx1 nCoV-19 is currently under investigation in a phase I clinical trial. Safety, immunogenicity and efficacy against symptomatic PCR-positive COVID-19 disease will now be assessed in randomised controlled human clinical trials.", - "rel_num_authors": 35, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.12.090324", + "rel_abs": "The Corona Virus Disease 2019 (COVID-19) pandemic that began in late December 2019 has resulted in millions of cases diagnosed worldwide. Reports have shown that SARS-CoV-2 shows extremely higher infection rates than other coronaviruses. This study conducted a phylogenetics analysis of 91 representative coronaviruses and found that the functional spike protein of SARS-CoV-2, which interacts with the human receptor ACE2, is actually not undergoing distinct selection pressure compared to other coronaviruses. Furthermore, we define a new measurement, infection group differential (IGD) score, in assessing the infection ability of two human coronavirus groups. There are nine extremely high IGD (ehIGD) sites in the receptor-binding domain (RBD) out of 40 high IGD (hIGD) sites that exhibit a unique infection-related pattern from the haplotype network and docking energy comparison. These 40 hIGD sites are basically conserved among the SARS-CoV-2, i.e. there are only two hIGD sites mutated in four out of 1,058 samples, defined as rare-mutation hIGD (rhIGD) sites. In conclusion, ehIGD and rhIGD sites might be of great significance to the development of vaccines.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Neeltje van Doremalen", - "author_inst": "NIH" - }, - { - "author_name": "Teresa Lambe", - "author_inst": "Oxford" - }, - { - "author_name": "Alex Spencer", - "author_inst": "Oxford" - }, - { - "author_name": "Sandra Belij-Rammerstorfer", - "author_inst": "Oxford" - }, - { - "author_name": "Jyothi Purushotham", - "author_inst": "NIH" - }, - { - "author_name": "Julia Port", - "author_inst": "NIH" - }, - { - "author_name": "Victoria Avanzato", - "author_inst": "NIH" - }, - { - "author_name": "Trenton Bushmaker", - "author_inst": "NIH" - }, - { - "author_name": "Amy Flaxman", - "author_inst": "Oxford" - }, - { - "author_name": "Marta Ulaszewska", - "author_inst": "Oxford" - }, - { - "author_name": "Friederike Feldmann", - "author_inst": "NIH" - }, - { - "author_name": "Elizabeth Allen", - "author_inst": "Oxford" - }, - { - "author_name": "Hannah Sharpe", - "author_inst": "Oxford" - }, - { - "author_name": "Jonathan Schulz", - "author_inst": "NIH" - }, - { - "author_name": "Myndi Holbrook", - "author_inst": "NIH" - }, - { - "author_name": "Atsushi Okumura", - "author_inst": "NIH" - }, - { - "author_name": "Kimberly Meade-White", - "author_inst": "NIH" - }, - { - "author_name": "Lizzette Perez-Perez", - "author_inst": "NIH" - }, - { - "author_name": "Cameron Bissett", - "author_inst": "Oxford" - }, - { - "author_name": "Ciaran Gilbride", - "author_inst": "oxford" - }, - { - "author_name": "Brandi Williamson", - "author_inst": "NIH" - }, - { - "author_name": "Rebecca Rosenke", - "author_inst": "NIH" - }, - { - "author_name": "Dan Long", - "author_inst": "NIH" - }, - { - "author_name": "Alka Ishwarbhai", - "author_inst": "NIH" - }, - { - "author_name": "Reshma Kailath", - "author_inst": "Oxford" - }, - { - "author_name": "Louisa Rose", - "author_inst": "Oxford" - }, - { - "author_name": "Susan Morris", - "author_inst": "Oxford" - }, - { - "author_name": "Claire Powers", - "author_inst": "Oxford" + "author_name": "Ziwei Song", + "author_inst": "State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 210009, China." }, { - "author_name": "Jamie Lovaglio", - "author_inst": "NIH" + "author_name": "Xingchen Zhou", + "author_inst": "School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China." }, { - "author_name": "Patrick Hanley", - "author_inst": "NIH" + "author_name": "Yuanyuan Cai", + "author_inst": "State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 210009, China." }, { - "author_name": "Dana Scott", - "author_inst": "NIH" + "author_name": "Shou Feng", + "author_inst": "School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China." }, { - "author_name": "Greg Saturday", - "author_inst": "NIH" + "author_name": "Tingting Zhang", + "author_inst": "School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China." }, { - "author_name": "Emmie de Wit", - "author_inst": "NIAID, NIH" + "author_name": "Yun Wang", + "author_inst": "School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China." }, { - "author_name": "Sarah C Gilbert", - "author_inst": "University of Oxford" + "author_name": "Maode Lai", + "author_inst": "State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China." }, { - "author_name": "Vincent Munster", - "author_inst": "NIAID" + "author_name": "Jing Li", + "author_inst": "School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China" } ], "version": "1", - "license": "cc0", + "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.05.12.092163", @@ -1443812,163 +1444066,35 @@ "category": "hiv aids" }, { - "rel_doi": "10.1101/2020.05.08.20092866", - "rel_title": "Robust ACE2 protein expression localizes to the motile cilia of the respiratory tract epithelia and is not increased by ACE inhibitors or angiotensin receptor blockers", + "rel_doi": "10.1101/2020.05.08.20095430", + "rel_title": "Total predicted MHC-I epitope load is inversely associated with mortality from SARS-CoV-2", "rel_date": "2020-05-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20092866", - "rel_abs": "We investigated the expression and subcellular localization of the SARS-CoV-2 receptor, angiotensin-converting enzyme 2 (ACE2), within the upper (nasal) and lower (pulmonary) respiratory tracts of healthy human donors. We detected ACE2 protein expression within the cilia organelle of ciliated airway epithelial cells, which likely represents the initial or early subcellular site of SARS-CoV-2 viral entry during respiratory transmission. We further determined whether ACE2 expression in the cilia of upper respiratory cells was influenced by patient demographics, clinical characteristics, co-morbidities, or medication use, and found no evidence that the use of angiotensin-converting enzyme inhibitors (ACEI) or angiotensin II receptor blockers (ARBs) increases ACE2 protein expression.", - "rel_num_authors": 36, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20095430", + "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWPolymorphisms in MHC-I protein sequences across human populations significantly impacts viral peptide binding capacity and thus alters T cell immunity to infection. Consequently, allelic variants of the MHC-I protein have been found to be associated with patient outcome to various viral infections, including SARS-CoV. In the present study, we assess the relationship between observed SARS-CoV-2 population mortality and the predicted viral binding capacities of 52 common MHC-I alleles. Potential SARS-CoV-2 MHC-I peptides were identified using a consensus MHC-I binding and presentation prediction algorithm, called EnsembleMHC. Starting with nearly 3.5 million candidates, we resolved a few hundred highly probable MHC-I peptides. By weighing individual MHC allele-specific SARS-CoV-2 binding capacity with population frequency in 23 countries, we discover a strong inverse correlation between the predicted population SARS-CoV-2 peptide binding capacity and observed mortality rate. Our computations reveal that peptides derived from the structural proteins of the virus produces a stronger association with observed mortality rate, highlighting the importance of S, N, M, E proteins in driving productive immune responses. The correlation between epitope binding capacity and population mortality risk remains robust across a range of socioeconomic and epidemiological factors. A combination of binding capacity, number of deaths due to COPD complications, gender demographics. and the proportions of the population that were over the age of 65 and overweight offered the strongest determinant of at-risk populations. These results bring to light how molecular changes in the MHC-I proteins may affect population-level outcomes of viral infection.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Ivan T Lee", - "author_inst": "Stanford University" - }, - { - "author_name": "Tsuguhisa Nakayama", - "author_inst": "Stanford University" - }, - { - "author_name": "Chien-Ting Wu", - "author_inst": "Stanford University" - }, - { - "author_name": "Yury Goltsev", - "author_inst": "Stanford University" - }, - { - "author_name": "Sizun Jiang", - "author_inst": "Stanford University" - }, - { - "author_name": "Phillip A Gall", - "author_inst": "Stanford University" - }, - { - "author_name": "Chun-Kang Liao", - "author_inst": "National Taiwan University" - }, - { - "author_name": "Liang-Chun Shih", - "author_inst": "China Medical University" - }, - { - "author_name": "Christian M Schurch", - "author_inst": "Stanford University" - }, - { - "author_name": "David R McIlwain", - "author_inst": "Stanford University" - }, - { - "author_name": "Pauline Chu", - "author_inst": "Stanford University" - }, - { - "author_name": "Nicole A Borchard", - "author_inst": "Stanford University" - }, - { - "author_name": "David Zarabanda", - "author_inst": "Stanford University" - }, - { - "author_name": "Sachi S Dholakia", - "author_inst": "Stanford University" - }, - { - "author_name": "Angela Yang", - "author_inst": "Stanford University" - }, - { - "author_name": "Dayoung Kim", - "author_inst": "Stanford University" - }, - { - "author_name": "Tomoharu Kanie", - "author_inst": "Stanford University" - }, - { - "author_name": "Chia-Der Lin", - "author_inst": "China Medical University" - }, - { - "author_name": "Ming-Hsui Tsai", - "author_inst": "China Medical University" - }, - { - "author_name": "Katie M Phillips", - "author_inst": "Stanford University" - }, - { - "author_name": "Raymond Kim", - "author_inst": "Stanford University" - }, - { - "author_name": "Jonathan B Overdevest", - "author_inst": "Columbia University" - }, - { - "author_name": "Matthew A Tyler", - "author_inst": "University of Minnesota" - }, - { - "author_name": "Carol H Yan", - "author_inst": "University of California San Diego School of Medicine" - }, - { - "author_name": "Chih-Feng Lin", - "author_inst": "National Taiwan University" - }, - { - "author_name": "Yi-Tsen Lin", - "author_inst": "National Taiwan University" - }, - { - "author_name": "Da-Tian Bau", - "author_inst": "China Medical University" - }, - { - "author_name": "Gregory J Tsay", - "author_inst": "China Medical University" - }, - { - "author_name": "Zara M Patel", - "author_inst": "Stanford University" - }, - { - "author_name": "Yung-An Tsou", - "author_inst": "China Medical University" - }, - { - "author_name": "Chih-Jaan Tai", - "author_inst": "China Medical University" - }, - { - "author_name": "Te-Huei Yeh", - "author_inst": "National Taiwan University" - }, - { - "author_name": "Peter H Hwang", - "author_inst": "Stanford University" + "author_name": "Eric Wilson", + "author_inst": "Arizona State University" }, { - "author_name": "Garry P Nolan", - "author_inst": "Stanford University" + "author_name": "Gabrielle Hirneise", + "author_inst": "Arizona State University" }, { - "author_name": "Jayakar V Nayak", - "author_inst": "Stanford University" + "author_name": "Abhishek Singharoy", + "author_inst": "Arizona State University" }, { - "author_name": "Peter K Jackson", - "author_inst": "Stanford University" + "author_name": "Karen S Anderson", + "author_inst": "Arizona State University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2020.05.08.20095463", @@ -1445509,49 +1445635,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.08.20093617", - "rel_title": "Use of excess mortality associated with the COVID-19 epidemic as an epidemiological surveillance strategy - preliminary results of the evaluation of six Brazilian capitals", + "rel_doi": "10.1101/2020.05.07.20093807", + "rel_title": "Unreported cases for Age Dependent COVID-19 Outbreak in Japan", "rel_date": "2020-05-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20093617", - "rel_abs": "In early 2020, the World Health Organization (WHO) recognized the pandemic situation of the new coronavirus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2), which causes Coronavirus Disease-2019 (COVID-19). In Brazil by the end of April 2020, another 110 thousand cases and 5,000 deaths had been confirmed. The scarcity of laboratory resources and overload of the care network, added to the broad clinical spectrum of the disease, can make it difficult to capture all mortality from this disease through epidemiological surveillance based on individual notification of cases. The aim of this study was to evaluate the excess of deaths in Brazilian capitals with the highest incidence of COVID-19, as a way of validating the method, we also evaluated a capital with low incidence.\n\nWe assessed weekly mortality from all causes during the year 2020, up to the epidemiological week 17, compared with the previous year. The data were obtained through the National Civil Registry Information Center (CNIRC, acronym in Portuguese). We estimate the expected mortality and the 95% confidence interval by projecting the observed mortality in 2019 for the population of 2020.\n\nIn the five capitals with the highest incidences it was possible to identify excess deaths in the pandemic period, the age group most affected were those over 60 years old, 31% of the excess deaths occurred in the population between 20 and 59 years old. There was a strong correlation (r = 0.94) between the excess of deaths in each city and the number of deaths confirmed by epidemiological surveillance. There was no excess of deaths in the capital with the lowest incidence, nor among the population under 20 years old. We estimate that epidemiological surveillance managed to capture only 52% of all mortality associated with the COVID-19 pandemic in the cities studied.\n\nConsidering the simplicity of the method, its low cost and reliability for assessing the real burden of the disease, we believe that the assessment of excess mortality associated with the COVID-19 pandemic should be widely used as a complementary tool to regular epidemiological surveillance and its use should be encouraged by WHO.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.07.20093807", + "rel_abs": "We investigate the age structured data for the COVID-19 outbreak in Japan. We consider a mathematical model for the epidemic with unreported infectious patient with and without age structure. In particular, we build a new mathematical model and a new computational method to fit the data by using age classes dependent exponential growth at the early stage of the epidemic. This allows to take into account differences in the response of patients to the disease according to their age. This model also allows for a heterogeneous response of the population to the social distancing measures taken by the local government. We fit this model to the observed data and obtain a snapshot of the effective transmissions occurring inside the population at different times, which indicates where and among whom the disease propagates after the start of public mitigation measures.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Andre Ricardo Ribas Freitas", - "author_inst": "Prefeitura Municipal de Campinas" - }, - { - "author_name": "N M Medeiros", - "author_inst": "Secretaria Municipal de Saude de Campinas" - }, - { - "author_name": "Livia Frutuoso", - "author_inst": "Ministerio da Saude" - }, - { - "author_name": "Otto A Beckedorff", - "author_inst": "Faculdade Sao Leopoldo Mandic" - }, - { - "author_name": "Lucas M A Martin", - "author_inst": "Faculdade Sao Leopoldo Mandic" - }, - { - "author_name": "Marcela M M Coelho", - "author_inst": "Universidade Federal de Uberlandia" - }, - { - "author_name": "Giovanna G S Freitas", - "author_inst": "Faculdade de Medicina de Marilia" + "author_name": "quentin griette", + "author_inst": "University of Bordeaux" }, { - "author_name": "Daniele R Q Lemos", - "author_inst": "Centro Universitario Christus" + "author_name": "pierre magal", + "author_inst": "University of Bordeaux" }, { - "author_name": "Luciano P G Cavalcanti", - "author_inst": "Universidade Federal do Ceara" + "author_name": "Ousmane Seydi", + "author_inst": "Ecole polythechinque de Thies" } ], "version": "1", @@ -1447075,165 +1447177,17 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2020.05.06.20092833", - "rel_title": "Studying the pathophysiology of coronavirus disease 2019 - a protocol for the Berlin prospective COVID-19 patient cohort (Pa- COVID-19)", + "rel_doi": "10.1101/2020.05.06.20092718", + "rel_title": "Liver histopathology in COVID 19 infection is suggestive of vascular alteration", "rel_date": "2020-05-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.06.20092833", - "rel_abs": "PurposeSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide causing a global health emergency. Pa-COVID-19 aims to provide comprehensive data on clinical course, pathophysiology, immunology and outcome of COVID-19, in order to identify prognostic biomarkers, clinical scores, and therapeutic targets for improved clinical management and preventive interventions.\n\nMethodsPa-COVID-19 is a prospective observational cohort study of patients with confirmed SARS-CoV-2 infection treated at Charite - Universitatsmedizin Berlin. We collect data on epidemiology, demography, medical history, symptoms, clinical course, pathogen testing and treatment. Systematic, serial blood sampling will allow deep molecular and immunological phenotyping, transcriptomic profiling, and comprehensive biobanking. Longitudinal data and sample collection during hospitalization will be supplemented by long-term follow-up.\n\nResultsOutcome measures include the WHO clinical ordinal scale on day 15 and clinical, functional and health-related quality of life assessments at discharge and during follow-up. We developed a scalable dataset to (i) suit national standards of care (ii) facilitate comprehensive data collection in medical care facilities with varying resources and (iii) allow for rapid implementation of interventional trials based on the standardized study design and data collection. We propose this scalable protocol as blueprint for harmonized data collection and deep phenotyping in COVID-19 in Germany.\n\nConclusionWe established a basic platform for harmonized, scalable data collection, pathophysiological analysis, and deep phenotyping of COVID-19, which enables rapid generation of evidence for improved medical care and identification of candidate therapeutic and preventive strategies. The electronic database accredited for interventional trials allows fast trial implementation for candidate therapeutic agents.", - "rel_num_authors": 38, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.06.20092718", + "rel_abs": "COVID-19 breakout in Italy has caused a huge number of severely ill patients with a serious increase in mortality. Although lungs seem to be the main target of the infection very few information are available about liver involvement in COVID-19 infection, that could possibly evocate a systemic disease targeting a lot of organs. Since now there are no reports of large series of histological evaluation of liver morphology in this setting. Knowledge of histological liver findings connected to clinical data is crucial in management of this disease. Post-mortem wedge liver biopsies from 48 patients died for COVID-19 infection were available from two main hospitals located in northern Italy, Lombardy; all sample were obtained during autopsies. No patient has a significant clinical complain of liver disease or signs of liver failure before and during hospitalization; for each of them laboratory data focused on liver were available. All liver samples showed minimal inflammation features; on the other side, many histological pictures compatible with vascular alterations were observed, characterized by portal vein braches number increase associated with lumen massive dilatation, partial or complete recent luminal thrombosis of portal and sinusoidal vessels, fibrosis of portal tract, focally severely enlarged and fibrotic. Our preliminary results concerning histological liver involvement in COVID-19 infection confirm the clinical impression that liver failure is not a main concern and this organ is not the target of significant inflammatory damage; histopatological findings are highly suggestive for marked alteration of intrahepatic blood vessel network secondary to systemic alterations induced by virus that could target, besides lung parenchyma, cardiovascular system, coagulation cascade or endothelial layer of blood vessels.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Florian Kurth", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite - Universitaetsmedizin Berlin, AND Department of Tropical Medicine, Bernhard Nocht Institute" - }, - { - "author_name": "Maria Roennefarth", - "author_inst": "Clinical Study Center (CSC), Berlin Institute of Health, and Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Charlotte Thibeault", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Victor M. Corman", - "author_inst": "Institute of Virology, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Holger Mueller-Redetzky", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Mirja Mittermaier", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Christoph Ruwwe-Gloesenkamp", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Alexander Krannich", - "author_inst": "Clinical Study Center (CSC), Berlin Institute of Health and Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Sein Schmidt", - "author_inst": "Clinical Study Center (CSC), Berlin Institute of Health and Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Lucie Kretzler", - "author_inst": "Clinical Study Center (CSC), Berlin Institute of Health, and Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Chantip Dang-Heine", - "author_inst": "Clinical Study Center (CSC), Berlin Institute of Health, and Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Matthias Rose", - "author_inst": "Department of Psychosomatic Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Michael Hummel", - "author_inst": "Central Biobank Charite (ZeBanC), Institute of Pathology, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Andreas Hocke", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Ralf H. Huebner", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Marcus A. Mall", - "author_inst": "Department of Pediatric Pulmonology, Immunology and Critical Care Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Jobst Roehmel", - "author_inst": "Department of Pediatric Pulmonology, Immunology and Critical Care Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Ulf Landmesser", - "author_inst": "Department of Cardiology, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Burkert Pieske", - "author_inst": "Medical Department, Division of Cardiology, Campus Virchow-Klinikum, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Samuel Knauss", - "author_inst": "Department of Neurology with Experimental Neurology and Center for Stroke Research Berlin, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Matthias Endres", - "author_inst": "Department of Neurology with Experimental Neurology and Center for Stroke Research Berlin, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Joachim Spranger", - "author_inst": "Department of Endocrinology and Metabolism, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Frank P. Mockenhaupt", - "author_inst": "Institute of Tropical Medicine and International Health Berlin, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Frank Tacke", - "author_inst": "Department of Hepatology and Gastroenterology, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Sascha Treskatsch", - "author_inst": "Department of Anaesthesiology and Intensive Care Medicine, Charite Campus Benjamin Franklin, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Stefan Angermair", - "author_inst": "Department of Anaesthesiology and Intensive Care Medicine, Charite Campus Benjamin Franklin, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Britta Siegmund", - "author_inst": "Medical Department, Division of Gastroenterology, Infectious Diseases, Rheumatology, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Claudia Spies", - "author_inst": "Department of Anesthesiology and Operative Intensive Care Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Steffen Weber-Carstens", - "author_inst": "Department of Anesthesiology and Operative Intensive Care Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Kai-Uwe Eckardt", - "author_inst": "Department of Nephrology and Internal Intensive Care Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Alexander Uhrig", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Thomas Zoller", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Christian Drosten", - "author_inst": "Institute of Virology, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Norbert Suttorp", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Martin Witzenrath", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Stefan Hippenstiel", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Christoph von Kalle", - "author_inst": "Clinical Study Center (CSC), Berlin Institute of Health, and Charite - Universitaetsmedizin Berlin, Germany" - }, - { - "author_name": "Leif Erik Sander", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite - Universitaetsmedizin Berlin, Germany" + "author_name": "aurelio sonzogni", + "author_inst": "Ospedale Papa Giovanni XXIII Bergamo" } ], "version": "1", @@ -1448821,37 +1448775,45 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.05.07.20094607", - "rel_title": "Early Mandated Social Distancing is a Strong Predictor of Reduction in Highest Number of New COVID-19 cases per Day within Various Geographic Regions", + "rel_doi": "10.1101/2020.05.08.20095067", + "rel_title": "A Mathematical Model Approach for Prevention and Intervention Measures of the COVID-19 Pandemic in Uganda", "rel_date": "2020-05-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.07.20094607", - "rel_abs": "Mandated social distancing has been globally applied to limit the spread of corona virus disease 2019 (COVID-19) from highly pathogenic severe acute respiratory syndrome (SARS)-associated coronavirus 2 (SARS-CoV-2). The benefit of this community-based intervention in limiting COVID-19 has not been proven nor quantified. We examined the effect of timing of mandated social distancing on the rate of COVID-19 in 119 geographic regions derived from 41 states within United States and 78 countries. We found that highest number of new COVID-19 cases per day per million persons was significantly associated with total number of COVID-19 cases per million persons on the day before mandated social distancing ({beta}=0.66, p<0.0001). Our findings suggest that the initiation of mandated social distancing for each doubling in number of existing COVID-19 cases would result in eventual peak with 58% higher number of COVID-19 infections per day. Subgroup analysis on those regions where the highest number of new COVID-19 cases per day have peaked increased {beta} to .85 (p<0.0001). We demonstrate that initiating mandated social distancing at a 10 times smaller number of COVID-19 cases will reduce the number of daily new COVID-19 cases at peak by 80% highlighting the importance of this community-based intervention.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20095067", + "rel_abs": "The human-infecting corona virus disease (COVID-19) caused by the novel severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) was declared a global pandemic on March 11th, 2020. Current human deaths due to the infection have raised the threat globally with only 1 African country free of Virus (Lesotho) as of May 6th, 2020. Different countries have adopted different interventions at different stages of the outbreak, with social distancing being the first option while lock down the preferred option for flattening the curve at the peak of the pandemic. Lock down is aimed at adherence to social distancing, preserve the health system and improve survival. We propose a Susceptible-Exposed-Infected-Expected recoveries (SEIR) mathematical model to study the impact of a variety of prevention and control strategies Uganda has applied since the eruption of the pandemic in the country. We analyze the model using available data to find the infection-free, endemic/infection steady states and the basic reproduction number. In addition, a sensitivity analysis done shows that the transmission rate and the rate at which persons acquire the virus, have a positive influence on the basic reproduction number. On other hand the rate of evacuation by rescue ambulance greatly reduces the reproduction number. The results have potential to inform the impact and effect of early strict interventions including lock down in resource limited settings and social distancing.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "M. Fareed K. Suri", - "author_inst": "St Cloud Hospital" + "author_name": "Fulgensia Kamugisha Mbabazi", + "author_inst": "Busitema University, Tororo, Uganda and Uganda Martyrs University, Uganda" }, { - "author_name": "Adnan I Qureshi", - "author_inst": "University of Missouri" + "author_name": "Gavamukulya Yahaya", + "author_inst": "Busitema University" }, { - "author_name": "Haitao Shu", - "author_inst": "University of Minnesota" + "author_name": "Richard Awichi", + "author_inst": "Busitema University" }, { - "author_name": "Habibullah Khan Suri", - "author_inst": "Zeenat Qureshi Stroke Research Center, Columbia MO" + "author_name": "Peter Olupot Olupot", + "author_inst": "Busitema University" }, { - "author_name": "Ayesha Khan Suri", - "author_inst": "Zeenat Qureshi Stroke Research Center, Columbia MO" + "author_name": "Samson Rwahwire", + "author_inst": "Busitema University" + }, + { + "author_name": "Saphina Biira", + "author_inst": "Busitema University" + }, + { + "author_name": "Livingstone Serwadda Luboobi", + "author_inst": "Strathmore University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1450259,37 +1450221,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.06.20093526", - "rel_title": "Mathematical Modeling & the Transmission Dynamics of SARS-CoV-2 in Cali, Colombia: Implications to a 2020 Outbreak & public health preparedness", + "rel_doi": "10.1101/2020.05.06.20093369", + "rel_title": "Bidirectional contact tracing is required for reliable COVID-19 control", "rel_date": "2020-05-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.06.20093526", - "rel_abs": "IntroductionAs SARS-COV-2 and the disease COVID-19 is sweeping through countries after countries around the globe, it is critical to understand potential burden of a future outbreak in cities of Colombia. This pandemic has affected most of the countries in the world because the high global movement of individuals and excessive cost in interventions.\n\nObjectiveUsing demographic data from city of Cali, disease epidemiological information from affected countries and mathematical models, we estimated the rate of initial exponential growth of new cases and the basic reproductive rate for a potential outbreak in city of Cali in Colombia.\n\nMaterials and methodsWe used dynamical models with different modeling assumptions such as use of various types of interventions and/or epidemiological characteristics to compare and contrast the differences between Colombian cities and between Latin American countries.\n\nResultsUnder the assumption of homogeneously mixing population and limited resources, we predicted expected number of infected, hospitalized, in Intensive Care Units (ICU) and deaths during this potential COVID-19 outbreak. Our results suggest that on a given day in Cali there may be up to around 73000 cases who might need hospitalization under no intervention. However, this number drastically reduces if we carry out only-isolation intervention (with 16 days of symptomatic infection; ~13,000 cases) versus both quarantining for 6 days and isolation within 16 days (~3500 cases). The peak in Cali will reach in 2-3 months.\n\nConclusionsThe estimates from these studies provides different scenarios of outbreaks and can help Cali to be better prepared during the ongoing COVID-19 outbreak.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.06.20093369", + "rel_abs": "Contact tracing is critical to controlling COVID-19, but most protocols only \"forward-trace\" to notify people who were recently exposed. Using a stochastic branching-process model, we show that \"bidirectional\" tracing to identify infector individuals and their other infectees robustly improves outbreak control, reducing the effective reproduction number (Reff) by at least [~]0.3 while dramatically increasing resilience to low case ascertainment and test sensitivity. Adding smartphone-based exposure notification can further reduce Reff by 0.25, but only if nearly all smartphones can detect exposure events. Our results suggest that with or without digital approaches, implementing bidirectional tracing will enable health agencies to control COVID-19 more effectively without requiring high-cost interventions.", "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Jorge Humberto Rojas", - "author_inst": "Secretaria de Salud Publica Alcaldia de Santiago de Cali" + "author_name": "William J Bradshaw", + "author_inst": "Max Planck Institute for Biology of Ageing" }, { - "author_name": "Marlio Paredes", - "author_inst": "Universidad del Valle, Cali, Colombia" + "author_name": "Ethan C Alley", + "author_inst": "Massachusetts Institute of Technology" }, { - "author_name": "Malay Banerjee", - "author_inst": "Indian Institute of Technology, Kanpur, India" + "author_name": "Jonathan H Huggins", + "author_inst": "Boston University" }, { - "author_name": "Olcay Akman", - "author_inst": "Illinois State University" + "author_name": "Alun L Lloyd", + "author_inst": "North Carolina State University" }, { - "author_name": "Anuj Mubayi", - "author_inst": "Arizona State University" + "author_name": "Kevin M Esvelt", + "author_inst": "Massachusetts Institute of Technology" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1451949,105 +1451911,49 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.05.05.20092023", - "rel_title": "Mental Health Impact of COVID-19: A global study of risk and resilience factors", + "rel_doi": "10.1101/2020.05.05.20092106", + "rel_title": "Impact of small-area lockdowns for the control of the COVID-19 pandemic", "rel_date": "2020-05-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20092023", - "rel_abs": "This study anonymously screened 13,332 individuals worldwide for psychological symptoms related to Corona virus disease 2019 (COVID-19) pandemic from March 29th to April 14th, 2020. A total of n=12,817 responses were considered valid with responses from 12 featured countries and five WHO regions. Female gender, pre-existing psychiatric condition, and prior exposure to trauma were identified as notable risk factors, whereas optimism, ability to share concerns with family and friends like usual, positive prediction about COVID-19, and daily exercise predicted fewer psychological symptoms. These results could aid in dynamic optimization of mental health services during and following COVID-19 pandemic.", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20092106", + "rel_abs": "BackgroundCountries confronting the COVID-19 pandemic are implementing different social distancing strategies. We evaluated the impact of small-area lockdowns in Chile, aimed to reduce viral transmission while minimizing the population disrupted. The effectiveness of this intervention on the outbreak control is unknown.\n\nMethodsA natural experiment assessing the impact of small-area lockdowns between February 15th and April 25th, 2020. We used mobility data and official governmental reports to compare regions with small-area lockdowns versus regions without. The primary outcome was the mean difference in the effective reproductive number (Re) of COVID-19. Secondary outcomes were changes in mobility indicators. We used quasi-experimental methods for the analysis and examined the impact of other concurrent public health interventions to disentangle their effects.\n\nResultsSmall-area lockdown produced a sizable reduction in human mobility, equivalent to an 11.4% reduction (95%CI -14.4% to -8.38%) in public transport and similar effects in other mobility indicators. Ten days after implementation, the small-area lockdown produced a reduction of the effective reproductive number (Re) of 0.86 (95%CI -1.70 to -0.02). School and university closures, implemented earlier, led to a 40% reduction in urban mobility. Closure of educational institutions resulted in an even greater Re reduction compared with small-area lockdowns.\n\nConclusionsSmall-area lockdowns produced a reduction in mobility and viral transmission, but the effects were smaller than the early closures of schools and universities. Small-area lockdowns may have a relevant supporting role in reducing SARS-CoV-2 transmission and could be useful for countries considering scaling-down stricter social distancing interventions.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Martyna Beata Plomecka", - "author_inst": "Methods of Plasticity Research, Department of Psychology, University of Zurich, Zurich, Switzerland" - }, - { - "author_name": "Susanna Gobbi", - "author_inst": "Zurich Center for Neuroeconomics, University of Zurich, Zurich, Switzerland" - }, - { - "author_name": "Rachael Neckels", - "author_inst": "Biomolecular Sciences Graduate Program, Department of Biomolecular Sciences, Boise State University, Boise, Idaho, USA" - }, - { - "author_name": "Piotr Radzi\u0144ski", - "author_inst": "Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Poland" - }, - { - "author_name": "Beata Sk\u00f3rko", - "author_inst": "Faculty of Medicine, Medical University of Warsaw, Warsaw, Poland" - }, - { - "author_name": "Samuel Lazerri", - "author_inst": "Faculty of Science and Engineering, University of Groningen, Groningen, the Netherlands" - }, - { - "author_name": "Kristina Almazidou", - "author_inst": "Faculty of Veterinary Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece" - }, - { - "author_name": "Alisa Dedi\u0107", - "author_inst": "Faculty of Medicine, University of Tuzla, Bosnia and Herzegovina" - }, - { - "author_name": "Asja Bakalovi\u0107", - "author_inst": "Faculty of Medicine, University of Tuzla, Bosnia and Herzegovina" - }, - { - "author_name": "Lejla Hrusti\u0107", - "author_inst": "Faculty of Medicine, University of Tuzla, Bosnia and Herzegovina" - }, - { - "author_name": "Zainab Ashraf", - "author_inst": "Faculty of Arts, University of Waterloo, Canada" - }, - { - "author_name": "Sarvin Es haghi", - "author_inst": "Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran" - }, - { - "author_name": "Luis Rodr\u00edguez-Pino", - "author_inst": "Faculty of Medicine, University of Valencia, Spain" - }, - { - "author_name": "Verena Waller", - "author_inst": "Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland" - }, - { - "author_name": "Hafsa Jabeen", - "author_inst": "Medical College, Dow University of Health Sciences, Karachi, Pakistan" + "author_name": "Crist\u00f3bal Cuadrado", + "author_inst": "Universidad de Chile" }, { - "author_name": "A. Beyza Alp", - "author_inst": "Faculty of Medicine, Maltepe University, Turkey" + "author_name": "Mar\u00eda Jos\u00e9 Monsalves", + "author_inst": "Universidad San Sebastian" }, { - "author_name": "Mehdi A. Behnam", - "author_inst": "Neuroscience Center Zurich, University of Zurich/ Swiss Federal Institute of Technology (ETH), Zurich, Switzerland" + "author_name": "Jean Gajardo", + "author_inst": "Universidad de Chile" }, { - "author_name": "Dana Shibli", - "author_inst": "Faculty of Medicine, University of Jordan, Jordan" + "author_name": "Mar\u00eda Paz Bertoglia", + "author_inst": "Universidad de Chile" }, { - "author_name": "Zofia Bara\u0144czuk Turska", - "author_inst": "Methods of Plasticity Research, Department of Psychology, University of Zurich, Zurich, Switzerland" + "author_name": "Manuel Najera", + "author_inst": "Universidad del Desarrollo" }, { - "author_name": "Zeeshan Haq", - "author_inst": "Texas Behavioral Health, Houston, TX, USA" + "author_name": "Tania Alfaro", + "author_inst": "Universidad de Chile" }, { - "author_name": "Salah U Qureshi", - "author_inst": "Texas Behavioral Health, Houston, TX, USA" + "author_name": "Mauricio Canals", + "author_inst": "Universidad de Chile" }, { - "author_name": "Adriana M. Strutt", - "author_inst": "Department of Neurology, Baylor College of Medicine, Houston, TX, USA" + "author_name": "Jay Kaufmann", + "author_inst": "McGill University" }, { - "author_name": "Ali Jawaid", - "author_inst": "Brain Research Institute, University of Zurich, Switzerland, Center of Excellence in Neural Plasticity and Brain Disorders (Braincity), Nencki Institute of Expe" + "author_name": "Sebasti\u00e1n Pe\u00f1a", + "author_inst": "Finnish Institute for Health and Welfare, Helsinki, Finland" } ], "version": "1", @@ -1453499,35 +1453405,55 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.05.05.20050419", - "rel_title": "COVID-19 Induced Anxiety and Protective Behaviors During COVID-19 Outbreak: Scale Development and Validation", + "rel_doi": "10.1101/2020.05.06.20068882", + "rel_title": "Myocardial characteristics as the prognosis for COVID-19 patients", "rel_date": "2020-05-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20050419", - "rel_abs": "BackgroundThe outbreak of communicable diseases increases community anxiety levels; however, it demands protective behavioral changes with adjacent awareness of the emerging epidemic. This work aims to develop valid instruments to evaluate COVID-19 induced anxiety, protective behaviors, and knowledge towards COVID-19, and to explore the relationship between the three constructs.\n\nMethodsA total sample of 215 university students were recruited to participate in an online self-administered questionnaire. The e-survey consisted of three instruments: COVID-19 Induced Anxiety Scale (CIAS) with 10 items, Protective Behaviors towards COVID-19 Scale (PBCS) with 14 items, and COVID-19 Related Knowledge Scale (CRKS) with 12 items.\n\nResultsItem-total analysis and CFA models indicated that CIAS items no. 1, 2, 5, and 8 should be removed to achieve adequate internal consistency (Cronbachs alpha=0.78) and structural validity. The protective behaviors towards COVID-19 can be estimated from 3 dimensions: Routine Protective Behaviors (RPB), Post-exposure Protective Behaviors (PPB), and Post-exposure Risky Behaviors (PRB). Meanwhile, PBCS showed good internal consistency (Cronbachs alpha=0.85). Although the sample was unbalanced on gender, gender explained 5% of the variance in protective behaviors with females being more inclined to engage in protective behaviors. Structural Equation Model (SEM) implied that an individuals COVID-19 related knowledge was associated with the three dimensions of protective behaviors (RPB, PPB and PRB) positively. However, the level of COVID-19 induced anxiety was linked to RPB and PPB positively but negatively to PRB.\n\nConclusionThe 6-item version of CIAS and the 14-item version of PBCS are promising tools for measuring COVID-19 induced anxiety and protective behaviors and can be adopted for future use during early phases of communicable diseases outbreaks. Knowledge is a key indicator for protective behavior; therefore, awareness strategies need to suppress infodemic impact. Severe stress must be monitored during early phases of outbreaks as it significantly increases the probability of risk behavior engagement.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.06.20068882", + "rel_abs": "BackgroundAmid the crisis of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), front-line clinicians in collaboration with backstage medical researchers analyzed clinical characteristics of COVID-19 patients and reported the prognosis using myocardial data records upon hospitalization.\n\nMethodsWe reported 135 cases of laboratory-confirmed COVID-19 patients admitted in The First Peoples Hospital of Jiangxia District in Wuhan, China. Demographic data, medical history, and laboratory parameters were taken from inpatient records and compared between patients at the Intensive Care Unit (ICU) and non-ICU isolation wards for prognosis on disease severity. In particular, survivors and non-survivors upon ICU admission were compared for prognosis on disease mortality.\n\nResultsFor COVID-19 patients, blood test results showed more significantly deranged values in the ICU group than those in non-ICU. Among those parameters for ICU patients, myocardial variables including troponin T, creatine kinase isoenzymes, myoglobin, were found significantly higher in non-survivors than in survivors.\n\nConclusionsUpon hospitalization abnormal myocardial metabolism in COVID-19 patients could be prognostic indicators of a worsened outcome for disease severity and mortality.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Abanoub Riad", - "author_inst": "Masaryk University" + "author_name": "Jianguo Zhang", + "author_inst": "School of Medicine, Jiangsu University, and The Affiliated Hospital of Jiangsu University" }, { - "author_name": "Yi Huang", - "author_inst": "Masaryk University" + "author_name": "Daoyin Ding", + "author_inst": "The First People's Hospital of Jiangxia District, Wuhan" }, { - "author_name": "Liping Zheng", - "author_inst": "East China Normal University" + "author_name": "Can Cao", + "author_inst": "The First People's Hospital of Jiangxia District, Wuhan" }, { - "author_name": "Steriani Elavsky", - "author_inst": "Masaryk University" + "author_name": "Jinhui Zhang", + "author_inst": "The Affiliated Hospital of Jiangsu University" + }, + { + "author_name": "Xing Huang", + "author_inst": "Zhongnan Hospital of Wuhan University" + }, + { + "author_name": "Peiwen Fu", + "author_inst": "School of Medicine, Jiangsu University" + }, + { + "author_name": "Guoxin Liang", + "author_inst": "The First Affiliated Hospital, China Medical University" + }, + { + "author_name": "Wenrong Xu", + "author_inst": "School of Medicine, Jiangsu University" + }, + { + "author_name": "Zhimin Tao", + "author_inst": "School of Medicine, Jiangsu University" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.05.05.20091637", @@ -1454981,27 +1454907,271 @@ "category": "radiology and imaging" }, { - "rel_doi": "10.1101/2020.05.04.20090845", - "rel_title": "Asthma and COVID-19 in Children - A Systematic Review and Call for Data", + "rel_doi": "10.1101/2020.05.04.20090944", + "rel_title": "Acute Kidney Injury in Hospitalized Patients with COVID-19", "rel_date": "2020-05-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.04.20090845", - "rel_abs": "RationaleWhether asthma constitutes a risk factor for COVID-19 is unclear.\n\nMethodsWe performed a systematic literature search in three stages: First, we reviewed PubMed, EMBASE and CINAHL for systematic reviews of SARS-CoC-2 and COVID-19 in pediatric populations, and reviewed their primary articles; next, we searched PubMed for studies on COVID-19 or SARS-CoV-2 and asthma/wheeze, and evaluated whether the resulting studies included pediatric populations; lastly, we repeated the second search in BioRxiv.org and MedRxiv.org to find pre-prints that may have information on pediatric asthma.\n\nResultsIn the first search, eight systematic reviews were found, of which five were done in pediatric population; after reviewing 67 primary studies we found no data on pediatric asthma as a comorbidity for COVID-19. In the second search, we found 25 results in PubMed, of which five reported asthma in adults, but none included data on children. In the third search, 14 pre-prints in MedRxiv were identified with data on asthma, but again none with pediatric data. We found only one report by the U.S. CDC stating that 40/345 (~11.5%) children with data on chronic conditions had \"chronic lung diseases including asthma\".\n\nConclusionThere is scarcely any data on whether childhood asthma (or other pediatric respiratory diseases) constitute risk factors for SARS-CoV-2 infection or COVID-19 severity. Studies are needed that go beyond counting the number of cases in the pediatric age range.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.04.20090944", + "rel_abs": "ImportancePreliminary reports indicate that acute kidney injury (AKI) is common in coronavirus disease (COVID)-19 patients and is associated with worse outcomes. AKI in hospitalized COVID-19 patients in the United States is not well-described.\n\nObjectiveTo provide information about frequency, outcomes and recovery associated with AKI and dialysis in hospitalized COVID-19 patients.\n\nDesignObservational, retrospective study.\n\nSettingAdmitted to hospital between February 27 and April 15, 2020.\n\nParticipantsPatients aged [≥]18 years with laboratory confirmed COVID-19\n\nExposuresAKI (peak serum creatinine increase of 0.3 mg/dL or 50% above baseline).\n\nMain Outcomes and MeasuresFrequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aOR) with mortality. We also trained and tested a machine learning model for predicting dialysis requirement with independent validation.\n\nResultsA total of 3,235 hospitalized patients were diagnosed with COVID-19. AKI occurred in 1406 (46%) patients overall and 280 (20%) with AKI required renal replacement therapy. The incidence of AKI (admission plus new cases) in patients admitted to the intensive care unit was 68% (553 of 815). In the entire cohort, the proportion with stages 1, 2, and 3 AKI were 35%, 20%, 45%, respectively. In those needing intensive care, the respective proportions were 20%, 17%, 63%, and 34% received acute renal replacement therapy. Independent predictors of severe AKI were chronic kidney disease, systolic blood pressure, and potassium at baseline. In-hospital mortality in patients with AKI was 41% overall and 52% in intensive care. The aOR for mortality associated with AKI was 9.6 (95% CI 7.4-12.3) overall and 20.9 (95% CI 11.7-37.3) in patients receiving intensive care. 56% of patients with AKI who were discharged alive recovered kidney function back to baseline. The area under the curve (AUC) for the machine learned predictive model using baseline features for dialysis requirement was 0.79 in a validation test.\n\nConclusions and RelevanceAKI is common in patients hospitalized with COVID-19, associated with worse mortality, and the majority of patients that survive do not recover kidney function. A machine-learned model using admission features had good performance for dialysis prediction and could be used for resource allocation.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat is incidence and outcomes of acute kidney injury (AKI) in patients hospitalized with COVID-19?\n\nFindingsIn this observational study of 3,235 hospitalized patients with COVID-19 in New York City, AKI occurred in 46% of patients and 20% of those patients required dialysis. AKI was associated with increased mortality. 44% of patients discharged alive had residual acute kidney disease. A machine learned predictive model using baseline features for dialysis requirement had an AUC Of 0.79.\n\nMeaningAKI was common in patients with COVID-19, associated with increased mortality, and nearly half of patients had acute kidney disease on discharge.", + "rel_num_authors": 63, "rel_authors": [ { - "author_name": "Jose A Castro-Rodriguez", - "author_inst": "Pontificia Universidad Catolica de Chile" + "author_name": "Lili Chan", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" }, { - "author_name": "Erick Forno", - "author_inst": "University of Pittsburgh School of Medicine" + "author_name": "Kumardeep Chaudhary", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Aparna Saha", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Kinsuk Chauhan", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Akhil Vaid", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Mukta Baweja", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Kirk Campbell", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Nicholas Chun", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Miriam Chung", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Priya Deshpande", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Samira S Farouk", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Lewis Kaufman", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Tonia Kim", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Holly Koncicki", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Vijay Lapsia", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Staci Leisman", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Emily Lu", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Kristin Meliambro", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Madhav C Menon", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Joshua L Rein", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Shuchita Sharma", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Joji Tokita", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Jaime Uribarri", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Joseph A Vassalotti", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Jonathan Winston", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Kusum S Mathews", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Shan Zhao", + "author_inst": "The Hasso Plattner Institute for Digital Health at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Ishan Paranjpe", + "author_inst": "The Hasso Plattner Institute for Digital Health at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Sulaiman Somani", + "author_inst": "The Hasso Plattner Institute for Digital Health at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Felix Richter", + "author_inst": "The Hasso Plattner Institute for Digital Health at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Ron Do", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Riccardo Miotto", + "author_inst": "The Hasso Plattner Institute for Digital Health at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Anuradha Lala", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Arash Kia", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Prem Timsina", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Li Li", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Matteo Danieletto", + "author_inst": "The Hasso Plattner Institute for Digital Health at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Eddye Golden", + "author_inst": "The Hasso Plattner Institute for Digital Health at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Patricia Glowe", + "author_inst": "The Hasso Plattner Institute for Digital Health at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Micol Zweig", + "author_inst": "The Hasso Plattner Institute for Digital Health at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Manbir Singh", + "author_inst": "The Hasso Plattner Institute for Digital Health at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Robert Freeman", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Rong Chen", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Eric Nestler", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Jagat Narula", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Allan C Just", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Carol Horowitz", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Judith Aberg", + "author_inst": "judith.aberg@mssm.edu" + }, + { + "author_name": "Ruth J.F. Loos", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Judy Cho", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Zahi Fayad", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Carlos Cordon-Cardo", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Eric Schadt", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Matthew A Levin", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "David L Reich", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Valentin Fuster", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Barbara Murphy", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "John Cijiang He", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Alexander W Charney", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Erwin P Bottinger", + "author_inst": "Digital Health Center, Hasso Plattner Institute, University of Potsdam, Professor-Dr.-Helmert-Strasse 2-3, Potsdam, Germany" + }, + { + "author_name": "Benjamin S Glicksberg", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Steven G Coca", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" + }, + { + "author_name": "Girish N Nadkarni", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "nephrology" }, { "rel_doi": "10.1101/2020.05.04.20090316", @@ -1456751,109 +1456921,65 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.05.08.083964", - "rel_title": "A potent neutralizing human antibody reveals the N-terminal domain of the Spike protein of SARS-CoV-2 as a site of vulnerability", + "rel_doi": "10.1101/2020.05.08.083618", + "rel_title": "Multiple expression assessments of ACE2 and TMPRSS2 SARS-CoV-2 entry molecules in the urinary tract and their associations with clinical manifestations of COVID-19", "rel_date": "2020-05-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.08.083964", - "rel_abs": "The pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents a global public health threat. Most research on therapeutics against SARS-CoV-2 focused on the receptor binding domain (RBD) of the Spike (S) protein, whereas the vulnerable epitopes and functional mechanism of non-RBD regions are poorly understood. Here we isolated and characterized monoclonal antibodies (mAbs) derived from convalescent COVID-19 patients. An mAb targeting the N-terminal domain (NTD) of the SARS-CoV-2 S protein, named 4A8, exhibits high neutralization potency against both authentic and pseudotyped SARS-CoV-2, although it does not block the interaction between angiotensin-converting enzyme 2 (ACE2) receptor and S protein. The cryo-EM structure of the SARS-CoV-2 S protein in complex with 4A8 has been determined to an overall resolution of 3.1 Angstrom and local resolution of 3.4 Angstrom for the 4A8-NTD interface, revealing detailed interactions between the NTD and 4A8. Our functional and structural characterizations discover a new vulnerable epitope of the S protein and identify promising neutralizing mAbs as potential clinical therapy for COVID-19.", - "rel_num_authors": 24, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.08.083618", + "rel_abs": "BackgroundSince December 2019, the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first spread quickly in Wuhan, China, then globally. From previously published evidence, ACE2 and TMPRSS2, are both pivotal entry molecules that enable cellular infection by SARS-CoV-2. Meanwhile, increased expression of pro-inflammatory cytokines, or a \"cytokine storm,\" is associated with multiple organ dysfunction syndrome that is often observed in critically ill patients.\n\nMethodsWe investigated the expression pattern of ACE2 and TMPRSS2 in major organs in the human body, especially under specific disease conditions. Multiple sequence alignment of ACE2 in different species was used to explain animal susceptibility. Moreover, the cell-specific expression patterns of ACE2 and cytokine receptors in the urinary tract were assessed using single-cell RNA sequencing (scRNA-seq). Additional biological relevance was determined through Gene Set Enrichment Analysis (GSEA) using an ACE2 specific signature.\n\nResultsOur results revealed that ACE2 and TMPRSS2 were highly expressed in genitourinary organs. ACE2 was highly and significantly expressed in the kidney among individuals with chronic kidney diseases or diabetic nephropathy. In single cells, ACE2 was primarily enriched in gametocytes in the testis, and renal proximal tubules. The receptors for pro-inflammatory cytokines, especially IL6ST, were remarkably concentrated in endothelial cells, macrophages, and spermatogonial stem cells in the testis, and renal endothelial cells, which suggested the occurrence of alternative damaging mechanisms via autoimmune attacks.\n\nConclusionsThis study provided new insights into the pathogenicity mechanisms of SARS-CoV-2 that underlie the clinical manifestations observed in the human testis and kidney. These observations might substantially facilitate the development of effective treatments for this rapidly spreading disease.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Xiangyang Chi", - "author_inst": "Beijing Institute of Biotechnology" - }, - { - "author_name": "Renhong Yan", - "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, Institute of Biology, Westlake Institute for Advanced Study, School of Life Sciences, Westlake Univer" - }, - { - "author_name": "Jun Zhang", - "author_inst": "Beijing Institute of Biotechnology" - }, - { - "author_name": "Guanying Zhang", - "author_inst": "Beijing Institute of Biotechnology" - }, - { - "author_name": "Yuanyuan Zhang", - "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, Institute of Biology, Westlake Institute for Advanced Study, School of Life Sciences, Westlake Univer" - }, - { - "author_name": "Meng Hao", - "author_inst": "Beijing Institute of Biotechnology" - }, - { - "author_name": "Zhe Zhang", - "author_inst": "Beijing Institute of Biotechnology" - }, - { - "author_name": "Pengfei Fan", - "author_inst": "Beijing Institute of Biotechnology" - }, - { - "author_name": "Yunzhu Dong", - "author_inst": "Beijing Institute of Biotechnology" - }, - { - "author_name": "Yilong Yang", - "author_inst": "Beijing Institute of Biotechnology" - }, - { - "author_name": "Zhengshan Chen", - "author_inst": "Beijing Institute of Biotechnology" - }, - { - "author_name": "Yingying Guo", - "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, Institute of Biology, Westlake Institute for Advanced Study, School of Life Sciences, Westlake Univer" + "author_name": "Xiaohan Ren", + "author_inst": "The State Key Lab of Reproductive; Department of Urology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China." }, { - "author_name": "Jinlong Zhang", - "author_inst": "Beijing Institute of Biotechnology" + "author_name": "Xiyi Wei", + "author_inst": "The State Key Lab of Reproductive; Department of Urology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China." }, { - "author_name": "Yaning Li", - "author_inst": "Beijing Institute of Biotechnology" + "author_name": "Guangyao Li", + "author_inst": "The State Key Lab of Reproductive; Department of Urology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China." }, { - "author_name": "Xiaohong Song", - "author_inst": "Beijing Institute of Biotechnology" + "author_name": "Shancheng Ren", + "author_inst": "Changhai Hospital" }, { - "author_name": "Yi Chen", - "author_inst": "Beijing Institute of Biotechnology" + "author_name": "Xinglin Chen", + "author_inst": "The State Key Lab of Reproductive; Department of Urology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China." }, { - "author_name": "Lu Xia", - "author_inst": "Beijing Advanced Innovation Center for Structural Biology, Tsinghua-Peking Joint Center for Life Sciences, School of Life Sciences, Tsinghua University" + "author_name": "Tongtong Zhang", + "author_inst": "The State Key Lab of Reproductive; Department of Urology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China." }, { - "author_name": "Ling Fu", - "author_inst": "Beijing Institute of Biotechnology" + "author_name": "Xu Zhang", + "author_inst": "The State Key Lab of Reproductive; Department of Urology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China." }, { - "author_name": "Lihua Hou", - "author_inst": "Beijing Institute of Biotechnology" + "author_name": "Zhongwen Lu", + "author_inst": "The State Key Lab of Reproductive; Department of Urology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China." }, { - "author_name": "Junjie Xu", - "author_inst": "Beijing Institute of Biotechnology" + "author_name": "Zebing You", + "author_inst": "The State Key Lab of Reproductive; Department of Urology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China." }, { - "author_name": "Changming Yu", - "author_inst": "Beijing Institute of Biotechnology" + "author_name": "Shanqiang Wang", + "author_inst": "The State Key Lab of Reproductive; Department of Urology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China." }, { - "author_name": "Jianmin Li", - "author_inst": "Beijing Institute of Biotechnology" + "author_name": "Chao Qin", + "author_inst": "The State Key Lab of Reproductive; Department of Urology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China." }, { - "author_name": "Qiang Zhou", - "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, Institute of Biology, Westlake Institute for Advanced Study, School of Life Sciences, Westlake Univer" + "author_name": "Ninghong Song", + "author_inst": "The State Key Lab of Reproductive; Department of Urology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China." }, { - "author_name": "Wei Chen", - "author_inst": "Beijing Institute of Biotechnology" + "author_name": "Zengjun Wang", + "author_inst": "The State Key Lab of Reproductive; Department of Urology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China." } ], "version": "1", @@ -1458313,43 +1458439,43 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.05.05.20083436", - "rel_title": "Extending A Chronological and Geographical Analysis of Personal Reports of COVID-19 on Twitter to England, UK", + "rel_doi": "10.1101/2020.05.04.20090399", + "rel_title": "Estimation of the Potential Impact of COVID-19 Responses on the HIV Epidemic: Analysis using the Goals Model", "rel_date": "2020-05-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20083436", - "rel_abs": "The rapidly evolving COVID-19 pandemic presents challenges for actively monitoring its transmission. In this study, we extend a social media mining approach used in the US to automatically identify personal reports of COVID-19 on Twitter in England, UK. The findings indicate that natural language processing and machine learning framework could help provide an early indication of the chronological and geographical distribution of COVID-19 in England.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.04.20090399", + "rel_abs": "We applied a simulation model of HIV to analyze the effects of 3 and 6-month disruptions in health services as a result of COVID-19. We found that disruptions to primary prevention programs (male circumcision, behavior change programs, condom distribution) would have small but transitory effects on new infections that might be more than offset by reductions in commercial and multi-partner sex due to lock downs. However, if COVID-19 leads to disruptions in ART services the impacts on mortality could be severe, doubling or tripling the estimated number of HIV deaths in 2020.", "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Su Golder", - "author_inst": "University of York" + "author_name": "John Stover", + "author_inst": "Avenir Health" }, { - "author_name": "Ari Klein", - "author_inst": "University of Pennsylvania" + "author_name": "Newton Chagoma", + "author_inst": "National AIDS Commission, Malawi" }, { - "author_name": "Arjun Magge", - "author_inst": "University of Pennsylvannia" + "author_name": "Issac Taramusi", + "author_inst": "National AIDS Council, Zimbabwe" }, { - "author_name": "Karen O'Connor", - "author_inst": "University of Pennsylvannia" + "author_name": "Yu Teng", + "author_inst": "Avenir Health" }, { - "author_name": "Haitao Cai", - "author_inst": "University of Pennsylvannia" + "author_name": "Robert Glaubius", + "author_inst": "Avenir Health" }, { - "author_name": "Davy Weissenbacher", - "author_inst": "University of Pennsylvannia" + "author_name": "Severin Guy Mahiane", + "author_inst": "Avenir Health" } ], "version": "1", "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "hiv aids" }, { "rel_doi": "10.1101/2020.05.04.20090076", @@ -1460119,31 +1460245,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.05.20092593", - "rel_title": "Epidemiological Transition of Covid-19 in India from Higher to Lower HDI States and Territories: Implications for Prevention and Control", + "rel_doi": "10.1101/2020.05.03.20089318", + "rel_title": "Reduced mortality and shorten ICU stay in SARS-COV-2 pneumonia: a low PEEP strategy", "rel_date": "2020-05-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20092593", - "rel_abs": "Background & ObjectiveSocial determinants of evolving covid-19 pandemic have not been well studied. To determine trends in transition of this epidemic in India we performed a study in states at various levels of human development index (HDI).\n\nMethodsWe used publicly available data sources to track progress of covid-19 epidemic in India in different states and territories where it was reported in significant numbers. The states (n=20) were classified into tertiles of HDI and weekly trends in cases and deaths plotted from 15 March to 2 May 2020. To assess association of HDI with state-level covid-19 burden we performed Pearsons correlation. Logarithmic trends were evaluated for calculation of projections. A microlevel study was performed in select urban agglomerations for identification of socioeconomic status (SES) differentials.\n\nResultsThere is wide regional variation in covid-19 cases and deaths in India from mid-March to early-May 2020. High absolute numbers have been reported from states of Maharashtra, Gujarat, Delhi, Madhya Pradesh, Rajasthan and Tamilnadu. Growth rate in cases and deaths is slow in high HDI states while it has increased rapidly in middle and lower HDI states. In mid-March 2020 there was a strong positive correlation of state-level HDI with weekly covid-19 cases (r= 0.37, 0.40) as well as deaths (r= 0.31, 0.42). This declined by early-May for cases (r= 0.04, 0.06) as well as deaths (r= - 0.005, 0.001) with significant negative logarithmic trend (cases R squared= 0.92; deaths R squared= 0. 84). These trends indicate increasing cases and deaths in low HDI states. Projection reveals that this trend is likely to continue to early-June 2020. Microlevel evaluation shows that urban agglomerations are major focus of the disease in India and it has transited from middle SES to low SES locations.\n\nConclusionThere is wide variability in burden of covid-19 in India. Slow growth and flattening of curve is observed in high-HDI states while disease is increasing in mid and lower HDI states. Projections reveal that lower HDI states would achieve parity with high HDI states by early-June 2020. Covid-19 is mostly present in urban agglomerations where it has transited from upper-middle to low SES locations. Public health strategies focusing on urban low SES locations and low HDI states are crucial to decrease covid-19 burden in India.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.03.20089318", + "rel_abs": "BackgroundIntensive Care Unit (ICU) management of COVID-19 patients with severe hypoxemia is associated with high mortality. We implemented a care map, as a standardized multidisciplinary approach to improve patients monitoring using: uniform patient selection for ICU admission, a low-PEEP strategy and a pharmacologic strategic thromboembolism management.\n\nMethodsA standardized protocol for managing COVID-19 patients and ICU admissions was implemented through accurate Early Warning Score (EWS) monitoring and thromboembolism prophylaxis at hospital admission. Dyspnea, mental confusion or SpO2 less than 85% were criteria for ICU admission. Ventilation approach employed low PEEP values (about 10 cmH2O in presence of lung compliance > 40 mL/cmH2O) and FiO2 as needed. In presence of lower lung compliance (< 40 mL/cmH2O) PEEP value was increased to about 14 cmH2O.\n\nFindingsFrom March 16th to April 12nd 2020, 41 COVID-19 patients were admitted to our ICU from a total of 310 patients. 83% (34) of them needed mechanical ventilation. The ventilation approach chosen employed low PEEP value based on BMI (PEEP 11{+/-} 3.8 (10-12) cmH2O if BMI < 30 Kg/m2; PEEP 15{+/-} 3.26 (12-18) cmH2O if BMI >30 Kg/m2). To date, ten patients (24%) died, four (9.7%) received mechanical ventilation, two were transferred to another hospital and 25 (60.9%) were discharged from ICU after a median of nine days.\n\nInterpretationA multimodal approach for COVID-19 patients is mandatory. The knowledge of this multi-organ disease is growing rapidly, requiring improvements in the standard of care. Our approach implements an accurate pre-ICU monitoring and strict selection for ICU admission, and allows to reduce mechanical ventilation, ICU stay and mortality.\n\nFundingNo funding has been required.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Rajeev Gupta", - "author_inst": "Eternal Heart Care Centre & Research Institute" + "author_name": "Samuele Ceruti", + "author_inst": "Clinica Luganese Moncucco" }, { - "author_name": "Rajinder K Dhamija", - "author_inst": "Lady Hardinge Medical College and SSK Hospital, New Delhi, India" + "author_name": "Marco Roncador", + "author_inst": "University Hospital Zurich" }, { - "author_name": "Kiran Gaur", - "author_inst": "SKN Agricultural College, SKN Agricultural University, Jobner, Jaipur, India" + "author_name": "Olivier Gie", + "author_inst": "Clinica Luganese Moncucco" + }, + { + "author_name": "Giovanni Bona", + "author_inst": "Clinica Luganese Moncucco" + }, + { + "author_name": "Martina Iattoni", + "author_inst": "Clinica Luganese Moncucco" + }, + { + "author_name": "Maira Biggiogero", + "author_inst": "Clinica Luganese Moncucco" + }, + { + "author_name": "Pier Andrea Maida", + "author_inst": "Clinica Luganese Moncucco" + }, + { + "author_name": "COVID-19 Clinical Management Team", + "author_inst": "" + }, + { + "author_name": "Christian Garzoni", + "author_inst": "Clinica Luganese Moncucco" + }, + { + "author_name": "Romano Mauri", + "author_inst": "Clinica Luganese Moncucco" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.05.06.20092858", @@ -1461516,59 +1461670,79 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.05.06.081968", - "rel_title": "Suramin inhibits SARS-CoV-2 infection in cell culture by interfering with early steps of the replication cycle", + "rel_doi": "10.1101/2020.05.06.079830", + "rel_title": "Development of a COVID-19 vaccine based on the receptor binding domain displayed on virus-like particles", "rel_date": "2020-05-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.06.081968", - "rel_abs": "The SARS-CoV-2 pandemic that originated from Wuhan, China, in December 2019 has impacted public health, society and economy and the daily lives of billions of people in an unprecedented manner. There are currently no specific registered antiviral drugs to treat or prevent SARS-CoV-2 infections. Therefore, drug repurposing would be the fastest route to provide at least a temporary solution while better, more specific drugs are being developed. Here we demonstrate that the antiparasitic drug suramin inhibits SARS-CoV-2 replication, protecting Vero E6 cells with an EC50 of [~]20 {micro}M, which is well below the maximum attainable level in human serum. Suramin also decreased the viral load by 2-3 logs when Vero E6 cells or cells of a human lung epithelial cell line (Calu-3) were treated. Time of addition and plaque reduction assays showed that suramin acts on early steps of the replication cycle, possibly preventing entry of the virus. In a primary human airway epithelial cell culture model, suramin also inhibited the progression of infection. The results of our preclinical study warrant further investigation and suggest it is worth evaluating whether suramin provides any benefit for COVID-19 patients, which obviously requires well-designed, properly controlled randomized clinical trials.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.06.079830", + "rel_abs": "The ongoing coronavirus COVID-19 pandemic is caused by a new coronavirus (SARS-CoV-2) with its origin in the city of Wuhan in China. From there it has been rapidly spreading to many cities inside and outside China. Nowadays more than 33 millions with deaths surpassing 1 million have been recorded worldwide thus representing a major health issue. Rapid development of a protective vaccine against COVID-19 is therefore of paramount importance. Here we demonstrated that recombinantly expressed receptor binding domain (RBD) of the spike protein homologous to SARS binds to ACE2, the viral receptor. Higly repetitive display of RBD on immunologically optimized virus-like particles derived from cucumber mosaic virus (CuMVTT) resulted in a vaccine candidate that induced high levels of specific antibodies in mice which were able to block binding of spike protein to ACE2 and potently neutralized COVID-19 virus in vitro.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Clarisse Salgado-Benvindo", - "author_inst": "Leiden University Medical Center" + "author_name": "Lisha Zha", + "author_inst": "International Immunology Centre, Anhui Agricultural University, Hefei, China" }, { - "author_name": "Melissa Thaler", - "author_inst": "Leiden University Medical Center" + "author_name": "Hongxin Zhao", + "author_inst": "High Magnetic Field Laboratory, CAS, 350 Shushan Hu Road, Hefei, Anhui, China" }, { - "author_name": "Ali Tas", - "author_inst": "Leiden University Medical Center" + "author_name": "Mona O Mohsen", + "author_inst": "Department of Rheumatology, Immunology and Allergology, University Hospital Bern, Bern, Switzerland; Department of BioMedical Research, University of Bern, Bern" }, { - "author_name": "Natacha S. Ogando", - "author_inst": "Leiden University Medical Center" + "author_name": "Liang Hong", + "author_inst": "International Immunology Centre, Anhui Agricultural University, Hefei, China" }, { - "author_name": "Peter J Bredenbeek", - "author_inst": "Leiden University Medical Center" + "author_name": "Yuhang Zhou", + "author_inst": "Shandong H&Z lifescience Gmbh, Yantai, China" }, { - "author_name": "Dennis Ninaber", - "author_inst": "Leiden University Medical Center" + "author_name": "Zehua Li", + "author_inst": "International Immunology centre, Anhui agricultural University" }, { - "author_name": "Ying Wang", - "author_inst": "Leiden University Medical Center" + "author_name": "Hongquan Chen", + "author_inst": "International Immunology Centre, Anhui Agricultural University, Hefei, China" }, { - "author_name": "Pieter Hiemstra", - "author_inst": "Leiden University Medical Center" + "author_name": "Xuelan Liu", + "author_inst": "International Immunology Centre, Anhui Agricultural University, Hefei, China; Department of Rheumatology, Immunology and Allergology, University Hospital Bern, " }, { - "author_name": "Eric J. Snijder", - "author_inst": "Leiden University Medical Center" + "author_name": "Xinyue Chang", + "author_inst": "Department of Rheumatology, Immunology and Allergology, University Hospital Bern, Bern, Switzerland; Department of BioMedical Research, University of Bern, Bern" }, { - "author_name": "Martijn J. van Hemert", - "author_inst": "Leiden University Medical Center" + "author_name": "Jie Zhang", + "author_inst": "Beijing key laboratory of monoclonal antibody research and development, Beijing, China" + }, + { + "author_name": "Dong Li", + "author_inst": "Beijing key laboratory of monoclonal antibody research and development, Beijing, China" + }, + { + "author_name": "Ke Wu", + "author_inst": "Institute of Risk Analysis, Prediction and Management, Academy of Interdisciplinary and Advanced Studies, Southern University of Science and Technology, Shenzhe" + }, + { + "author_name": "Monique Vogel", + "author_inst": "Department of Rheumatology, Immunology and Allergology, University Hospital Bern, Bern, Switzerland; Department of BioMedical Research, University of Bern, Bern" + }, + { + "author_name": "Martin F Bachmann", + "author_inst": "International Immunology Centre, Anhui Agricultural University, Hefei, China; Department of Rheumatology, Immunology and Allergology, University Hospital Bern, " + }, + { + "author_name": "Junfeng Wang", + "author_inst": "High Magnetic Field Laboratory, CAS, 350 Shushan Hu Road, Hefei, Anhui, China" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "immunology" }, { "rel_doi": "10.1101/2020.05.06.074039", @@ -1462878,39 +1463052,71 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.01.20088211", - "rel_title": "Automatic Detection of COVID-19 Using X-ray Images with Deep Convolutional Neural Networks and Machine Learning", + "rel_doi": "10.1101/2020.05.05.079608", + "rel_title": "Inhibition of the replication of SARS-CoV-2 in human cells by the FDA-approved drug chlorpromazine", "rel_date": "2020-05-06", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20088211", - "rel_abs": "The COVID-19 pandemic continues to have a devastating effect on the health and well-being of the global population. A vital step in the combat towards COVID-19 is a successful screening of contaminated patients, with one of the key screening approaches being radiological imaging using chest radiography. This study aimed to automatically detect COVID- 19 pneumonia patients using digital chest x- ray images while maximizing the accuracy in detection using deep convolutional neural networks (DCNN). The dataset consists of 864 COVID- 19, 1345 viral pneumonia and 1341 normal chest x- ray images. In this study, DCNN based model Inception V3 with transfer learning have been proposed for the detection of coronavirus pneumonia infected patients using chest X-ray radiographs and gives a classification accuracy of more than 98% (training accuracy of 97% and validation accuracy of 93%). The results demonstrate that transfer learning proved to be effective, showed robust performance and easily deployable approach for COVID-19 detection.", - "rel_num_authors": 5, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.05.079608", + "rel_abs": "Urgent action is needed to fight the ongoing COVID-19 pandemic by reducing the number of infected people along with the infection contagiousness and severity. Chlorpromazine (CPZ), the prototype of typical antipsychotics from the phenothiazine group, is known to inhibit clathrin-mediated endocytosis and acts as an antiviral, in particular against SARS-CoV-1 and MERS-CoV. In this study, we describe the in vitro testing of CPZ against a SARS-CoV-2 isolate in monkey and human cells. We evidenced an antiviral activity against SARS-CoV-2 with an IC50 of [~]10M. Because of its high biodistribution in lung, saliva and brain, such IC50 measured in vitro may translate to CPZ dosage used in clinical routine. This extrapolation is in line with our observations of a higher prevalence of symptomatic and severe forms of COVID-19 infections among health care professionals compared to patients in psychiatric wards. These preclinical findings support the repurposing of CPZ, a largely used drug with mild side effects, in COVID-19 treatment.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Sohaib Asif", - "author_inst": "Xi'an Jiaotong University" + "author_name": "Marion Plaze", + "author_inst": "GHU PARIS Psychiatrie & Neurosciences" }, { - "author_name": "Yi Wenhui", - "author_inst": "Xi'an Jiaotong University" + "author_name": "David Attali", + "author_inst": "GHU PARIS Psychiatrie & Neurosciences" }, { - "author_name": "Hou Jin", - "author_inst": "Xi'an Jiaotong University" + "author_name": "Matthieu Prot", + "author_inst": "Institut Pasteur" }, { - "author_name": "Yi Tao", - "author_inst": "Xi'an Jiaotong University" + "author_name": "Anne-Cecile Petit", + "author_inst": "Institut Pasteur" }, { - "author_name": "Si Jinhai", - "author_inst": "Xi'an Jiaotong University" + "author_name": "Michael Blatzer", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Fabien Vinckier", + "author_inst": "GHU PARIS Psychiatrie & Neurosciences" + }, + { + "author_name": "Laurine Levillayer", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Florent Perin-Dureau", + "author_inst": "Fondation Rotschild" + }, + { + "author_name": "Arnaud Cachia", + "author_inst": "Universite de Paris" + }, + { + "author_name": "Gerard Friedlander", + "author_inst": "Universite de Paris" + }, + { + "author_name": "Fabrice Chretien", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Etienne Simon-Loriere", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Raphael Gaillard", + "author_inst": "GHU PARIS Psychiatrie & Neurosciences" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "radiology and imaging" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2020.05.06.080119", @@ -1464352,203 +1464558,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.02.20082461", - "rel_title": "Clinical features, diagnostics, and outcomes of patients presenting with acute respiratory illness: a comparison of patients with and without COVID-19", + "rel_doi": "10.1101/2020.05.02.20078642", + "rel_title": "Impact of ethnicity on outcome of severe COVID-19 infection. Data from an ethnically diverse UK tertiary centre", "rel_date": "2020-05-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.02.20082461", - "rel_abs": "BackgroundEmerging data on the clinical presentation, diagnostics, and outcomes of patients with COVID-19 have largely been presented as case series. Few studies have compared these clinical features and outcomes of COVID-19 to other acute respiratory illnesses.\n\nMethodsWe examined all patients presenting to an emergency department in San Francisco, California between February 3 and March 31, 2020 with an acute respiratory illness who were tested for SARS-CoV-2. We determined COVID-19 status by PCR and metagenomic next generation sequencing (mNGS). We compared demographics, comorbidities, symptoms, vital signs, and laboratory results including viral diagnostics using PCR and mNGS. Among those hospitalized, we determined differences in treatment (antibiotics, antivirals, respiratory support) and outcomes (ICU admission, ICU interventions, acute respiratory distress syndrome, cardiac injury).\n\nFindingsIn a cohort of 316 patients, 33 (10%) tested positive for SARS-CoV-2; 31 patients, all without COVID-19, tested positive for another respiratory virus (16%). Among patients with additional viral testing, no co-infections with SARS-CoV-2 were identified by PCR or mNGS. Patients with COVID-19 reported longer symptoms duration (median 7 vs. 3 days) and were more likely to report fever (82% vs. 44%) fatigue (85% vs. 50%) and myalgias (61% vs 27%); p<0.001 for all comparisons. Lymphopenia (55% vs 34%, p=0.018) and bilateral opacities on initial chest radiograph (55% vs. 24%, p=0.001) were more common in patients with COVID-19. Patients with COVID-19 were more often hospitalized (79% vs. 56%, p=0.014). Of 186 hospitalized patients, patients with COVID-19 had longer hospitalizations (median 10.7d vs. 4.7d, p<0.001) and were more likely to develop ARDS (23% vs. 3%, p<0.001). Most comorbidities, home medications, signs and symptoms, vital signs, laboratory results, treatment, and outcomes did not differ by COVID-19 status.\n\nInterpretationWhile we found differences in clinical features of COVID-19 compared to other acute respiratory illnesses, there was significant overlap in presentation and comorbidities. Patients with COVID-19 were more likely to be admitted to the hospital, have longer hospitalizations and develop ARDS, and were unlikely to have co-existent viral infections. These findings enhance understanding of the clinical characteristics of COVID-19 in comparison to other acute respiratory illnesses.", - "rel_num_authors": 46, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.02.20078642", + "rel_abs": "During the current COVID-19 pandemic, it has been suggested that BAME background patients may be disproportionately affected compared to White but few detailed data are available. We took advantage of near real-time hospital data access and analysis pipelines to look at the impact of ethnicity in 1200 consecutive patients admitted between 1st March 2020 and 12th May 2020 to Kings College Hospital NHS Trust in London (UK).\n\nOur key findings are firstly that BAME patients are significantly younger and have different co-morbidity profiles than White individuals. Secondly, there is no significant independent effect of ethnicity on severe outcomes (death or ITU admission) within 14-days of symptom onset, after adjustment for age, sex and comorbidities.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Sachin J Shah", - "author_inst": "UCSF" - }, - { - "author_name": "Peter N Barish", - "author_inst": "UCSF" - }, - { - "author_name": "Priya A Prasad", - "author_inst": "UCSF" - }, - { - "author_name": "Amy L Kistler", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Norma Neff", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Jack Kamm", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Lucy M Li", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Charles Y Chiu", - "author_inst": "UCSF" - }, - { - "author_name": "Jennifer M Babick", - "author_inst": "UCSF" - }, - { - "author_name": "Margaret C Fang", - "author_inst": "UCSF" - }, - { - "author_name": "Yumiko Abe-Jones", - "author_inst": "UCSF" - }, - { - "author_name": "Narges Alipanah", - "author_inst": "UCSF" - }, - { - "author_name": "Francisco N Alvarez", - "author_inst": "UCSF" - }, - { - "author_name": "Olga B Botvinnik", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Jennifer M Davis", - "author_inst": "UCSF" - }, - { - "author_name": "Gloria D Castenada", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "CLIAHub Consortium", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Rand M Dadasovich", - "author_inst": "UCSF" - }, - { - "author_name": "Xianding Deng", - "author_inst": "UCSF" - }, - { - "author_name": "Joseph L DeRisi", - "author_inst": "UCSF" - }, - { - "author_name": "Angela M Detweiler", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Scot Federman", - "author_inst": "UCSF" - }, - { - "author_name": "John R Haliburton", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Samantha L Hao", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Andrew D Kerkhoff", - "author_inst": "UCSF" - }, - { - "author_name": "Renuka Kumar", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Katherine Malcolm", - "author_inst": "UCSF" - }, - { - "author_name": "Sabrina A Mann", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Sandra P Martinez", - "author_inst": "UCSF" - }, - { - "author_name": "Rupa Marya", - "author_inst": "UCSF" - }, - { - "author_name": "Eran Mick", - "author_inst": "UCSF" - }, - { - "author_name": "Lusajo L Mwakibete", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Nader Najafi", - "author_inst": "UCSF" - }, - { - "author_name": "Michael J Peluso", - "author_inst": "UCSF" - }, - { - "author_name": "Maira S Phelps", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Angela O Pisco", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Kalani Ratnasiri", - "author_inst": "Stanford" - }, - { - "author_name": "Luis A Rubio", - "author_inst": "UCSF" - }, - { - "author_name": "Anna B Sellas", - "author_inst": "Chan Zuckerberg Biohub" - }, - { - "author_name": "Kyla D Sherwood", - "author_inst": "UCSF" - }, - { - "author_name": "Jonathan Sheu", - "author_inst": "Chan Zuckerberg Initiative" - }, - { - "author_name": "Natasha Spottiswoode", - "author_inst": "UCSF" + "author_name": "James T Teo", + "author_inst": "Kings College Hospital NHS Foundation Trust" }, { - "author_name": "Michelle Tan", - "author_inst": "Chan Zuckerberg Biohub" + "author_name": "Daniel Bean", + "author_inst": "King's College London" }, { - "author_name": "Guixa Yu", - "author_inst": "UCSF" + "author_name": "Rebecca Bendayan", + "author_inst": "King's College London" }, { - "author_name": "Kirsten N Kangelaris", - "author_inst": "UCSF" + "author_name": "Richard Dobson", + "author_inst": "Kings College London" }, { - "author_name": "Charles Langelier", - "author_inst": "University of California San Francisco" + "author_name": "Ajay Shah", + "author_inst": "King's College London" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.05.01.20086801", @@ -1465782,21 +1465824,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.01.20087569", - "rel_title": "Buying time: an ecological survival analysis of COVID-19 spread based on the gravity model", + "rel_doi": "10.1101/2020.05.01.20087791", + "rel_title": "Did elderly people living in small towns or rural areas suffer heavier disease burden during the COVID-19 epidemic?", "rel_date": "2020-05-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20087569", - "rel_abs": "COVID-19 has spread in a matter of months to most countries in the world. Various social and economic factors determine the time in which a pandemic reaches a country. This time is essential, because it allows countries to prepare their response. This study considered a gravity model that expressed time to first case as a function of multiple socio-economic factors. First, Kaplan-Meier analysis was performed for each variable in the model by dividing countries into two groups according to the median of the respective variable. In order to measure the effect of these variables, parameters of the gravity model were estimated using accelerated failure time (AFT) survival analysis. In the Kaplan-Meier analysis the differences between high and low value groups were significant for every variable except population. The AFT analysis determined that increased personal freedom had the largest effect on lowering the survival time, controlling for detection capacity. Higher GDP per capita and a larger population also reduced survival time, while a greater distance from the outbreak source increased it. Understanding the influence of factors affecting time to index case can help us understand disease spread in the early stages of a pandemic.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20087791", + "rel_abs": "ObjectivesHealth inequalities were often exacerbated during the emerging epidemic. This study examined urban and non-urban inequalities in health services among COVID-19 patients aged 65 or above in US Florida from March 2 to May 27, 2020.\n\nMethodsA retrospective time series analysis was conducted using individual patient records. Multivariable Poisson and logistic models were used to calculate adjusted incidence of COVID-19 and the associated rates of emergency department (ED) visits, hospitalizations and deaths.\n\nResultsAs of May 27, 2020, there were 13,659 elderly COVID-19 patients (people aged 65 or above) in Florida and 14.9% of them died. Elderly people living in small metropolitan areas might be less likely to be confirmed with COVID-19 infection than those living in large metropolitan areas. The ED visit and hospitalization rates decreased significantly across metropolitan statuses for both men and women. Those patients living in small metropolitan or rural areas were less likely to be hospitalized than those living in large metropolitan areas (35% and 34% versus 41%). Elderly women aged 75 or above living in rural areas had 113% higher adjusted incidence of COVID-19 than those living in large metropolitan areas, and the rates of hospitalizations were lower compared with those counterparts living in large metropolitan areas (29% versus 46%; OR: 0.37 [0.25-0.54]; p <0.001).\n\nConclusionsFor elderly people living in US Florida, those who living in small metropolitan or rural areas were less likely to receive adequate health care than those who living in large or medium metropolitan areas during the COVID-19 pandemic.", "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Alon Vigdorovits", - "author_inst": "Carol Davila University of Medicine and Pharmacy" + "author_name": "Xinhua Yu", + "author_inst": "University of Memphis" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1467312,25 +1467354,41 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.29.20085126", - "rel_title": "Suppress, and not just flatten:Strategies for Rapid Suppression of COVID19 transmission in Small World Communities", + "rel_doi": "10.1101/2020.04.29.20084707", + "rel_title": "Epidemic Models for Personalised COVID-19 Isolation and Exit Policies Using Clinical Risk Predictions", "rel_date": "2020-05-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.29.20085126", - "rel_abs": "Many countries have introduced Lockdowns to contain the COVID19 epidemic. Lockdowns, though an effective policy for containment, imposes a heavy cost on the economy as it enforces extreme social distancing measures on the whole population. The objective of this note is to study alternatives to Lockdown which are either more targeted or allows partial opening of the economy. Cities are often spatially organized into wards. We introduce Multi-lattice small world (MLSW) network as a model of a city where each ward is represented by a 2D lattice and each vertex in the latex represents an agent endowed with SEIR dynamics. Through simulation studies on MLSW we examine a variety of candidate suppression policies and find that restricting Lockdowns to infected wards can indeed out-perform global Lockdowns in both reducing the attack rate and also shortening the duration of the epidemic. Even policies such as partial opening of the economy, such as Two Day Work Week, can be competitive if augmented with extensive Contact Tracing.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.29.20084707", + "rel_abs": "The widespread lockdowns imposed in many countries at the beginning of the COVID-19 pandemic elevated the importance of research on pandemic management when medical solutions such as vaccines are unavailable. We present a framework that combines a standard epidemiological SEIR (susceptible-exposed-infected-removed) model with an equally standard machine learning classification model for clinical severity risk, defined as an individuals risk needing intensive care unit (ICU) treatment if infected. Using COVID-19-related data and estimates for France as of spring 2020, we then simulate isolation and exit policies. Our simulations show that policies considering clinical risk predictions could relax isolation restrictions for millions of the lowest-risk population months earlier while consistently abiding by ICU capacity restrictions. Exit policies without risk predictions, meanwhile, would considerably exceed ICU capacity or require the isolation of a substantial portion of population for over a year in order to not overwhelm the medical system. Sensitivity analyses further decompose the impact of various elements of our models on the observed effects.\n\nOur work indicates that predictive modelling based on machine learning and artificial intelligence could bring significant value to managing pandemics. Such a strategy, however, requires governments to develop policies and invest in infrastructure to operationalize personalized isolation and exit policies based on risk predictions at scale. This includes health data policies to train predictive models and apply them to all residents, as well as policies for targeted resource allocation to maintain strict isolation for high-risk individuals.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Chiranjib Bhattacharyya", - "author_inst": "Indian Institute of Science" + "author_name": "Theodoros Evgeniou", + "author_inst": "INSEAD" }, { - "author_name": "V. Vinay", - "author_inst": "Chennai Mathematical Institute" + "author_name": "Mathilde Fekom", + "author_inst": "Universite Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli" + }, + { + "author_name": "Anton Ovchinnikov", + "author_inst": "Smith School of Business, Queen's University" + }, + { + "author_name": "Raphael Porcher", + "author_inst": "Universite de Paris CRESS, INSERM, INRA" + }, + { + "author_name": "Camille Pouchol", + "author_inst": "Universite de Paris" + }, + { + "author_name": "Nicolas Vayatis", + "author_inst": "Universite Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1468742,87 +1468800,99 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.05.01.20086207", - "rel_title": "TRACKING AND PREDICTING COVID-19 RADIOLOGICAL TRAJECTORY USING DEEP LEARNING ON CHEST X-RAYS: INITIAL ACCURACY TESTING", + "rel_doi": "10.1101/2020.04.30.20086090", + "rel_title": "Incidence of COVID-19 in a cohort of adult and paediatric patients with rheumatic diseases treated with targeted biologic and synthetic disease-modifying anti-rheumatic drugs", "rel_date": "2020-05-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20086207", - "rel_abs": "BackgroundDecision scores and ethically mindful algorithms are being established to adjudicate mechanical ventilation in the context of potential resources shortage due to the current onslaught of COVID-19 cases. There is a need for a reproducible and objective method to provide quantitative information for those scores.\n\nPurposeTowards this goal, we present a retrospective study testing the ability of a deep learning algorithm at extracting features from chest x-rays (CXR) to track and predict radiological evolution.\n\nMaterials and MethodsWe trained a repurposed deep learning algorithm on the CheXnet open dataset (224,316 chest X-ray images of 65,240 unique patients) to extract features that mapped to radiological labels. We collected CXRs of COVID-19-positive patients from two open-source datasets (last accessed on April 9, 2020)(Italian Society for Medical and Interventional Radiology and MILA). Data collected form 60 pairs of sequential CXRs from 40 COVID patients (mean age {+/-} standard deviation: 56 {+/-} 13 years; 23 men, 10 women, seven not reported) and were categorized in three categories: \"Worse\", \"Stable\", or \"Improved\" on the basis of radiological evolution ascertained from images and reports. Receiver operating characteristic analyses, Mann-Whitney tests were performed.\n\nResultsOn patients from the CheXnet dataset, the area under ROC curves ranged from 0.71 to 0.93 for seven imaging features and one diagnosis. Deep learning features between \"Worse\" and \"Improved\" outcome categories were significantly different for three radiological signs and one diagnostic (\"Consolidation\", \"Lung Lesion\", \"Pleural effusion\" and \"Pneumonia\"; all P < 0.05). Features from the first CXR of each pair could correctly predict the outcome category between \"Worse\" and \"Improved\" cases with 82.7% accuracy.\n\nConclusionCXR deep learning features show promise for classifying the disease trajectory. Once validated in studies incorporating clinical data and with larger sample sizes, this information may be considered to inform triage decisions.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.30.20086090", + "rel_abs": "OBJECTIVESTo investigate the incidence of COVID-19 in a cohort of adult and paediatric patients with rheumatic diseases receiving targeted biologic and synthetic disease modifying anti-rheumatic drugs (tDMARDs) and to explore the possible effect of these treatments in the clinical expression of COVID-19.\n\nMETHODSA cross-sectional study comprising of a telephone survey and electronic health records review was performed including all adult and paediatric patients with rheumatic diseases treated with tDMARDs in a large rheumatology tertiary centre in Barcelona, Spain. Demographics, disease activity, COVID-19 related symptoms and contact history data were obtained from the start of the 2020 pandemic. Cumulative incidence of confirmed cases (SARS-CoV-2 positive PCR test) was compared to the population estimates for the same city districts from a governmental COVID-19 health database. Suspected cases were defined following WHO criteria and compared to those without compatible symptoms.\n\nRESULTS959 patients with rheumatic diseases treated with tDMARDs were included. We identified 11 confirmed SARS-CoV-2 positive cases in the adult cohort and no confirmed positive cases in the paediatric cohort. All patients had a successful recovery and only one patient required admission in the intensive care unit. When using the same classification criteria (only COVID-19 positive cases with pneumonia), COVID-19 incidence rates of the rheumatic patient cohort were very similar to that of the general population [(0.48% (95% CI 0.09 to 8.65%)] and [0.58% (95% CI 5.62 to 5.99%)], respectively. We found significant differences in tDMARDs proportions between the suspected and non-suspected cases (p=0.002).\n\nCONCLUSIONAdult and paediatric patients with rheumatic diseases on tDMARDs do not seem to present a higher risk of COVID-19 or a more severe disease outcome when compared to general population. Our exploratory analysis suggests that the proportion of COVID-19 suspected cases differs between tDMARDs.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Simon Duchesne", - "author_inst": "Universite Laval" + "author_name": "Xabier Michelena", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" }, { - "author_name": "Daniel Gourdeau", - "author_inst": "Universite Laval" + "author_name": "Helena Borrell", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" }, { - "author_name": "Patrick Archambault", - "author_inst": "Universite Laval" + "author_name": "Mireia Lopez-Corbeto", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" }, { - "author_name": "Carl Chartrand-Lefebvre", - "author_inst": "Universite de Montreal" + "author_name": "Maria Lopez-Lasanta", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" }, { - "author_name": "Louis Dieumegarde", - "author_inst": "CERVO Brain Research Center" + "author_name": "Estefania Moreno", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" }, { - "author_name": "Reza Forghani", - "author_inst": "McGill University" + "author_name": "Maria Pascual-Pastor", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" }, { - "author_name": "Christian Gagne", - "author_inst": "Universite Laval" + "author_name": "Alba Erra", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" }, { - "author_name": "Alexandre Hains", - "author_inst": "Universite Laval" + "author_name": "Mayte Serrat", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" }, { - "author_name": "David Hornstein", - "author_inst": "McGill University" + "author_name": "Esther Espartal", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" }, { - "author_name": "Huy Le", - "author_inst": "McGill University" + "author_name": "Susana Anton", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" }, { - "author_name": "Simon Lemieux", - "author_inst": "Universite Laval" + "author_name": "Gustavo A Anez", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" }, { - "author_name": "Marie-Helene Levesque", - "author_inst": "Universite Laval" + "author_name": "Raquel Caparros-Ruiz", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" }, { - "author_name": "Diego Martin", - "author_inst": "McGill University" + "author_name": "Andrea Pluma", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" }, { - "author_name": "Lorne Rosenbloom", - "author_inst": "McGill University" + "author_name": "Ernesto Trallero-Araguas", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" }, { - "author_name": "An Tang", - "author_inst": "Universite de Montreal" + "author_name": "Mireia Barcelo-Bru", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" }, { - "author_name": "Fabrizio Vecchio", - "author_inst": "IRCCS San Raffaele Pisana" + "author_name": "Miriam Almirall", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" }, { - "author_name": "Nathalie Duchesne", - "author_inst": "Universite Laval" + "author_name": "Juan Jose De Agustin", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" + }, + { + "author_name": "Jordi Llados", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" + }, + { + "author_name": "Antonio Julia", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" + }, + { + "author_name": "Sara Marsal", + "author_inst": "Rheumatology Research Group, Vall Hebron Research Institute, Vall Hebron University Hospital" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "radiology and imaging" + "category": "rheumatology" }, { "rel_doi": "10.1101/2020.04.30.20086462", @@ -1470024,37 +1470094,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.28.20082750", - "rel_title": "Transmission dynamics of coronavirus disease 2019 outside of Daegu-Gyeongsangbuk provincial region in South Korea", + "rel_doi": "10.1101/2020.04.30.20080978", + "rel_title": "Continued and Serious Lockdown Could Minimize Many Newly Transmitted Cases of COVID-19 in the U.S.: Wavelets, Deterministic Models, and Data", "rel_date": "2020-05-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20082750", - "rel_abs": "We analyzed transmission of coronavirus disease 2019 in South Korea. We estimated that non-pharamaceutical measures reduced the immediate transmissibility by maximum of 34% for coronavirus disease 2019. Continuous efforts are needed for monitoring the transmissibility to optimize epidemic control.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.30.20080978", + "rel_abs": "All the newly reported COVID-19 cases of April in the U.S. have not acquired the virus in the same month. We estimate that there was an average of 29,000/day COVID-19 cases in the U.S. transmitted from infected to susceptible during April 1-24, 2020 after adjusting for under-reported and under-diagnosed. We have provided model-base d predictions of COVID-19 for the low and high range of transmission rates and with varying degrees of preventive measures including the lockdowns. We predict that even if 10% of the susceptible and 20 % of the infected who were not identified as of April 23, 2020, do not adhere to proper care or do not obey lockdown, then by the end of May and by end of June 50,000 and 55,000 new cases will emerge, respectively. These values for the months of May and June with worse adherence rates of 50% by susceptible and infected (but not identified) will be 251,000 and 511,000, respectively. Continued and serious lockdown measures could bring this average daily new cases to a further low at 4,300/day to 8,000/day in May.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Sukhyun Ryu", - "author_inst": "Konyang University College of Medicine, Daejeon, Republic of Korea" - }, - { - "author_name": "Sheikh Ali", - "author_inst": "The University of Hong Kong, Hong Kong Special Administrative Region, China" - }, - { - "author_name": "Cheolsun Jang", - "author_inst": "Konyang University College of Medicine, Daejeon, Republic of Korea" - }, - { - "author_name": "Baekjin Kim", - "author_inst": "Konyang University College of Medicine, Daejeon, Republic of Korea" + "author_name": "Arni S.R. Srinivasa Rao", + "author_inst": "Medical College of Gerogia, Augusta University, Augusta, Georgia, U.S.A" }, { - "author_name": "Benjamin J Cowling", - "author_inst": "The University of Hong Kong" + "author_name": "Steven G Krantz", + "author_inst": "Washington University in St. Louis" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1471690,37 +1471748,17 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.28.20084004", - "rel_title": "Warmer weather and global trends in the coronavirus COVID-19", + "rel_doi": "10.1101/2020.05.01.20075754", + "rel_title": "RSI model: COVID-19 in Germany Alternating quarantine episodes and normal episodes", "rel_date": "2020-05-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20084004", - "rel_abs": "Predicting COVID-19 epidemic development in the upcoming warm season has attracted much attention in the hope of providing helps to fight the epidemic. It requires weather (environmental) factors to be included in prediction models, but there are few models to achieve it successfully. In this study, we proposed a new concept of environmental infection rate (RE), based on floating time of respiratory droplets in the air and inactivation rate of virus to solve the problem. More than half of the particles in the droplets can float in the atmosphere for 1-2 hours. The prediction results showed that high RE values (>3.5) are scattered around 30{degrees}N in winter (Dec.-Feb.). As the weather warms, its distribution area expands and extends to higher latitudes of northern hemisphere, reaching its maximum in April, and then shrinking northward. These indicated that the spread of COVID-19 in most parts of the northern hemisphere is expected to decline after Apr., but the risks in high latitudes will remain high in May. In the south of southern hemisphere, the RE values tend to subside from Apr. to July. The high modeled RE values up to July, however, suggested that warmer weather will not stop COVID-19 from spreading. Public health intervention is needed to overcome the outbreak.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20075754", + "rel_abs": "This paper was developed in the Civil Systems Engineering Department at the Technical University of Berlin. The background is the spread of COVID-19 pandemic in Germany. Our current situation is a threat from the COVID-19 virus without vaccine and medication. Germany has increased its intensive capacities, intensified research in its analyzes and research projects and is currently testing the influence of various measures on the rate of expansion.\n\nThe goal now is to find a strategy that slows the spread so that medical capacities are not overloaded. The approach is to alternate between quarantine and normal episodes and the result is an oscillation in the number of cases between two limits.\n\nThe mathematical model is an SRI model that can be used to calculate the development of the case numbers. All uncertain parameters are varied at significant intervals. Influence parameters and control parameters were defined. By adjusting the length of the episode to match the speed of spread of the virus, the gap can be bridged until a vaccine has been developed or sufficient immunity is available in the population. By observing the capacity limits in connection with the number of cases, the need for a new quarantine episode and the possibility of initiating a normal episode can be predetermined. This does not exceed the capacity limit.\n\nIn quarantine, contagion within households is limited by the size of the household; only system-critical professions continue to work in public. All others must remain in the homeschooling / home office. In the normal episode, everyone can work, go to school, have social contacts. A solution could be found in all parameter combinations. The ratio of the normal episode duration / quarantine episode lies between 0.3 and 0.95 in the examination area.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Hong Li", - "author_inst": "Shanghai Jiao Tong University" - }, - { - "author_name": "Hongwei Xiao", - "author_inst": "East China University of Technology" - }, - { - "author_name": "Renguo Zhu", - "author_inst": "East China University of Technology" - }, - { - "author_name": "Chengxing Sun", - "author_inst": "Shanghai Jiao Tong University" - }, - { - "author_name": "Cheng Liu", - "author_inst": "East China University of Technology" - }, - { - "author_name": "Huayun Xiao", - "author_inst": "Shanghai Jiao Tong University" + "author_name": "Carolin Knoch", + "author_inst": "TU Berlin" } ], "version": "1", @@ -1473468,71 +1473506,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.29.20075747", - "rel_title": "Development and validation of direct RT-LAMP for SARS-CoV-2", + "rel_doi": "10.1101/2020.04.28.20074302", + "rel_title": "Structure of anxiety associated with the COVID-19 pandemic in the Russian-speaking sample: results from on-line survey", "rel_date": "2020-05-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.29.20075747", - "rel_abs": "We have developed a reverse-transcriptase loop mediated amplification (RT-LAMP) method targeting genes encoding the Spike (S) protein and RNA-dependent RNA polymerase (RdRP) of SARS-CoV-2. The LAMP assay achieves comparable limit of detection as commonly used RT-PCR protocols based on artificial targets, recombinant Sindbis virus, and clinical samples. Clinical validation of single-target (S gene) LAMP (N=120) showed a positive percent agreement (PPA) of 41/42 (97.62%) and negative percent agreement (NPA) of 77/78 (98.72%) compared to reference RT-PCR. Dual-target RT-LAMP (S and RdRP gene) achieved a PPA of 44/48 (91.97%) and NPA 72/72 (100%) when including discrepant samples. The assay can be performed without a formal extraction procedure, with lyophilized reagents which do need cold chain, and is amenable to point-of-care application with visual detection.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20074302", + "rel_abs": "The COVID-19 pandemic imposed not only serious threats to the physical health of the population, but also provoked a wide range of psychological problems.\n\nObjectiveTo identify the most vulnerable populations during the epidemic period (including individuals with affective disorders) who are most in need of psychological and / or psychiatric help.\n\nMaterial and methodsOn-line survey of 1957 Russian-speaking respondents over 18 years old from March 30 to April 5, 2020. The level of anxiety distress was verified with the psychological stress scale (PSM-25). Stigmatization of individuals experiencing respiratory symptoms was assessed with modified devaluation / discrimination questionnaire (PDD; Cronbachs = 0.707).\n\nResults99.8% of respondents had variable concerns associated with COVID-19. Their mean scores of psychological stress were increased to moderate levels (104.9 {+/-} 34.4 points), and the stigmatization scores exceeded the value of the whole sample median (19.5 {+/-} 3.4; Me = 19). 35% of respondents had concerns about COVID-19 associated with anxiety distress (Cohens d = 0.16-0.39): these were \"risk of isolation\" and \"possible lack of medication for daily use\". The most prone to concerns were respondents groups with affective disorders, young people ([≤]20 years old), unemployed, single, those without higher education and women.\n\nConclusionsLarge sub-cohorts of the Russian-speaking sample need correction of anxiety distress associated with the COVID-19 pandemic. The implementation of such measures should be targeted and oriented in terms of coverage and content to identified vulnerable social groups.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Abu Naser Mohon", - "author_inst": "University of Calgary" - }, - { - "author_name": "Jana Hundt", - "author_inst": "University of Calgary" - }, - { - "author_name": "Guido van Marle", - "author_inst": "University of Calgary" - }, - { - "author_name": "Kanti Pabbaraju", - "author_inst": "Alberta Public Health Laboratory" - }, - { - "author_name": "Byron Berenger", - "author_inst": "Alberta Public Health Laboratory" - }, - { - "author_name": "Thomas Griener", - "author_inst": "Alberta Precision Laboratories" - }, - { - "author_name": "Luiz Lisboa", - "author_inst": "Alberta Precision Laboratories" + "author_name": "Mikhail Yu. Sorokin", + "author_inst": "V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology" }, { - "author_name": "Deirdre Church", - "author_inst": "Alberta Precision Laboratories" + "author_name": "Evgeny D. Kasyanov", + "author_inst": "V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology" }, { - "author_name": "Markus Czub", - "author_inst": "University of Calgary" + "author_name": "Grigory V. Rukavishnikov", + "author_inst": "V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology" }, { - "author_name": "Alexander Greninger", - "author_inst": "University of Washington" + "author_name": "Olga V. Makarevich", + "author_inst": "V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology" }, { - "author_name": "Keith Jerome", - "author_inst": "Universityof Washington" + "author_name": "Nikolay G. Neznanov", + "author_inst": "V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology; I.P. Pavlov First Saint-Petersburg State Medical University" }, { - "author_name": "Cody Doolan", - "author_inst": "Illucidx Inc." + "author_name": "Nataliya B. Lutova", + "author_inst": "V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology" }, { - "author_name": "Dylan R Pillai", - "author_inst": "University of Calgary" + "author_name": "Galina E. Mazo", + "author_inst": "V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2020.05.03.073080", @@ -1475050,79 +1475064,199 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.04.28.20082222", - "rel_title": "Risk prediction for poor outcome and death in hospital in-patients with COVID-19: derivation in Wuhan, China and external validation in London, UK", + "rel_doi": "10.1101/2020.04.28.20083246", + "rel_title": "Systematic investigations of COVID-19 in 283 cancer patients", "rel_date": "2020-05-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20082222", - "rel_abs": "BackgroundAccurate risk prediction of clinical outcome would usefully inform clinical decisions and intervention targeting in COVID-19. The aim of this study was to derive and validate risk prediction models for poor outcome and death in adult inpatients with COVID-19.\n\nMethodsModel derivation using data from Wuhan, China used logistic regression with death and poor outcome (death or severe disease) as outcomes. Predictors were demographic, comorbidity, symptom and laboratory test variables. The best performing models were externally validated in data from London, UK.\n\nFindings4.3% of the derivation cohort (n=775) died and 9.7% had a poor outcome, compared to 34.1% and 42.9% of the validation cohort (n=226). In derivation, prediction models based on age, sex, neutrophil count, lymphocyte count, platelet count, C-reactive protein and creatinine had excellent discrimination (death c-index=0.91, poor outcome c-index=0.88), with good-to-excellent calibration. Using two cut-offs to define low, high and very-high risk groups, derivation patients were stratified in groups with observed death rates of 0.34%, 15.0% and 28.3% and poor outcome rates 0.63%, 8.9% and 58.5%. External validation discrimination was good (c-index death=0.74, poor outcome=0.72) as was calibration. However, observed rates of death were 16.5%, 42.9% and 58.4% and poor outcome 26.3%, 28.4% and 64.8% in predicted low, high and very-high risk groups.\n\nInterpretationOur prediction model using demography and routinely-available laboratory tests performed very well in internal validation in the lower-risk derivation population, but less well in the much higher-risk external validation population. Further external validation is needed. Collaboration to create larger derivation datasets, and to rapidly externally validate all proposed prediction models in a range of populations is needed, before routine implementation of any risk prediction tool in clinical care.\n\nFundingMRC, Wellcome Trust, HDR-UK, LifeArc, participating hospitals, NNSFC, National Key R&D Program, Pudong Health and Family Planning Commission\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSSeveral prognostic models for predicting mortality risk, progression to severe disease, or length of hospital stay in COVID-19 have been published.1 Commonly reported predictors of severe prognosis in patients with COVID-19 include age, sex, computed tomography scan features, C-reactive protein (CRP), lactic dehydrogenase, and lymphocyte count. Symptoms (notably dyspnoea) and comorbidities (e.g. chronic lung disease, cardiovascular disease and hypertension) are also reported to have associations with poor prognosis.2 However, most studies have not described the study population or intended use of prediction models, and external validation is rare and to date done using datasets originating from different Wuhan hospitals.3 Given different patterns of testing and organisation of healthcare pathways, external validation in datasets from other countries is required.\n\nAdded value of this studyThis study used data from Wuhan, China to derive and internally validate multivariable models to predict poor outcome and death in COVID-19 patients after hospital admission, with external validation using data from Kings College Hospital, London, UK. Mortality and poor outcome occurred in 4.3% and 9.7% of patients in Wuhan, compared to 34.1% and 42.9% of patients in London. Models based on age, sex and simple routinely available laboratory tests (lymphocyte count, neutrophil count, platelet count, CRP and creatinine) had good discrimination and calibration in internal validation, but performed only moderately well in external validation. Models based on age, sex, symptoms and comorbidity were adequate in internal validation for poor outcome (ICU admission or death) but had poor performance for death alone.\n\nImplications of all the available evidenceThis study and others find that relatively simple risk prediction models using demographic, clinical and laboratory data perform well in internal validation but at best moderately in external validation, either because derivation and external validation populations are small (Xie et al3) and/or because they vary greatly in casemix and severity (our study). There are three decision points where risk prediction may be most useful: (1) deciding who to test; (2) deciding which patients in the community are at high-risk of poor outcomes; and (3) identifying patients at high-risk at the point of hospital admission. Larger studies focusing on particular decision points, with rapid external validation in multiple datasets are needed. A key gap is risk prediction tools for use in community triage (decisions to admit, or to keep at home with varying intensities of follow-up including telemonitoring) or in low income settings where laboratory tests may not be routinely available at the point of decision-making. This requires systematic data collection in community and low-income settings to derive and evaluate appropriate models.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20083246", + "rel_abs": "AbstractsO_ST_ABSBackgroundC_ST_ABSCancer patients are considered to be highly susceptible to viral infections, however, the comprehensive features of COVID-19 in these patients remained largely unknown. The present study aimed to assess the clinical characteristics and outcomes of COVID-19 in a large cohort of cancer patients.\n\nDesign, Setting, and ParticipantsData of consecutive cancer patients admitted to 33 designated hospitals for COVID-19 in Hubei province, China from December 17, 2019 to March 18, 2020 were retrospectively collected. The follow-up cutoff date was April 02, 2020. The clinical course and survival status of the cancer patients with COVID-19 were measured, and the potential risk factors of severe events and death were assessed through univariable and multivariable analyses.\n\nResultsA total of 283 laboratory confirmed COVID-19 patients (50% male; median age, 63.0 years [IQR, 55.0 to 70.0]) with more than 20 cancer types were included. The overall mortality rate was 18% (50/283), and the median hospitalization stay for the survivors was 26 days. Amongst all, 76 (27%) were former cancer patients with curative resections for over five years without recurrence. The current cancer patients exhibited worse outcomes versus former cancer patients (overall survival, HR=2.45, 95%CI 1.10 to 5.44, log-rank p=0.02; mortality rate, 21% vs 9%). Of the 207 current cancer patients, 95 (46%) have received recent anti-tumor treatment, and the highest mortality rate was observed in the patients receiving recent chemotherapy (33%), followed by surgery (26%), other anti-tumor treatments (19%), and no anti-tumor treatment (15%). In addition, a higher mortality rate was observed in patients with lymphohematopoietic malignancies (LHM) (53%, 9/17), and all seven LHM patients with recent chemotherapy died. Multivariable analysis indicated that LHM (p=0.001) was one of the independent factors associating with critical illness or death.\n\nConclusionsThis is the first systematic study comprehensively depicting COVID-19 in a large cancer cohort. Patients with tumors, especially LHM, may have poorer prognosis of COVID-19. Additional cares are warranted and non-emergency anti-tumor treatment should be cautiously used for these patients under the pandemic.", + "rel_num_authors": 45, "rel_authors": [ { - "author_name": "Huayu Zhang", - "author_inst": "Centre for Medical Informatics, Usher Institute, University of Edinburgh, Scotland, United Kingdom" + "author_name": "Jie Wang", + "author_inst": "State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/" }, { - "author_name": "Ting Shi", - "author_inst": "Centre for Global Health, Usher Institute, University of Edinburgh, Scotland, United Kingdom" + "author_name": "Qibin Song", + "author_inst": "Cancer Center, Renmin Hospital of Wuhan University" }, { - "author_name": "Xiaodong Wu", - "author_inst": "Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China" + "author_name": "Yuan Chen", + "author_inst": "Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Xin Zhang", - "author_inst": "Department of Pulmonary and Critical Care Medicine, Peoples Liberation Army Joint Logistic Support Force 920th Hospital, Yunnan, China" + "author_name": "Zhijie Wang", + "author_inst": "State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital" }, { - "author_name": "Kun Wang", - "author_inst": "Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China" + "author_name": "Qian Chu", + "author_inst": "Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Daniel Bean", - "author_inst": "Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, England, United Kingdom" + "author_name": "Hongyun Gong", + "author_inst": "Cancer Center, Renmin Hospital of Wuhan University" }, { - "author_name": "Richard Dobson", - "author_inst": "Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, England, United Kingdom" + "author_name": "Shangli Cai", + "author_inst": "Burning Rock Biotech" }, { - "author_name": "James T Teo", - "author_inst": "Department of Stroke and Neurology, Kings College Hospital NHS Foundation Trust, London, England, United Kingdom" + "author_name": "Xiaorong Dong", + "author_inst": "Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Jiaxing Sun", - "author_inst": "Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China" + "author_name": "Bin Xu", + "author_inst": "Cancer Center, Renmin Hospital of Wuhan University" }, { - "author_name": "Pei Zhao", - "author_inst": "Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China" + "author_name": "Weidong Hu", + "author_inst": "Department of thoracic Surgery, Zhongnan Hospital of Wuhan University" }, { - "author_name": "Chenghong Li", - "author_inst": "Department of Pulmonary and Critical Care Medicine, Wuhan Sixth Hospital, Jianghan University, Wuhan, China" + "author_name": "Qun Wang", + "author_inst": "Department of Oncology, The Fifth Hospital of Wuhan" }, { - "author_name": "Kevin Dhaliwal", - "author_inst": "Centre for Inflammation Research, Queens Medical Research Institute, University of Edinburgh, Scotland, United Kingdom" + "author_name": "Linjun Li", + "author_inst": "Department of Oncology, Hubei Provincial Hospital of Integrated Chinese and Western Medicine" }, { - "author_name": "Honghan Wu", - "author_inst": "Centre for Medical Informatics, Usher Institute, University of Edinburgh, Scotland, United Kingdom" + "author_name": "Jiyuan Yang", + "author_inst": "Department of Oncology, First Affiliated Hospital of Yangtze University" }, { - "author_name": "Qiang Li", - "author_inst": "Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China" + "author_name": "Zhibin Xie", + "author_inst": "Department of respiratory and criticaI care medicine, Xiaogan Hospital Affiliated to Wuhan University of science and technology" }, { - "author_name": "Bruce Guthrie", - "author_inst": "Centre for Population Health Sciences, Usher Institute, University of Edinburgh, Scotland, United Kingdom" + "author_name": "Zhiguo Luo", + "author_inst": "Department of oncology, Taihe Hospital, Hubei University of Medicine" + }, + { + "author_name": "Jing Liu", + "author_inst": "Department of oncology, Huanggang central hospital" + }, + { + "author_name": "Xiuli Luo", + "author_inst": "Department of Oncology, HuBei provincial hospital of TCM" + }, + { + "author_name": "Jie Ren", + "author_inst": "Department of Medical Oncology, General Hospital of The Yangtze River Shipping" + }, + { + "author_name": "Zhiguo Rao", + "author_inst": "Department of Oncology, General Hospital of Central Theater Command, People's Liberation Army" + }, + { + "author_name": "Xinhua Xu", + "author_inst": "Department of Oncology, Yichang Central People's Hospital" + }, + { + "author_name": "Dongfeng Pan", + "author_inst": "Department of Oncology, Suizhou Hospital, HuBei University of Medicine" + }, + { + "author_name": "Zuowei Hu", + "author_inst": "Department of Oncology, Wuhan No.1 Hospital" + }, + { + "author_name": "Gang Feng", + "author_inst": "Department of Oncology, Wuhan Fourth Hospital (Puai Hospital), Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Chiding Hu", + "author_inst": "Department of Oncology, Affiliated Hospital of Jianghan University" + }, + { + "author_name": "Liqiong Luo", + "author_inst": "Department of Oncology, Tianyou Hospital Affiliated to Wuhan University of Science and Technology" + }, + { + "author_name": "Hongda Lu", + "author_inst": "Department of Oncology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Ruizhi Ran", + "author_inst": "Department of Oncology, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture" + }, + { + "author_name": "Jun Jin", + "author_inst": "Department of Oncology, Ezhou Central Hospital" + }, + { + "author_name": "Yanhua Xu", + "author_inst": "Department of Oncology, Jingzhou Central Hospital" + }, + { + "author_name": "Yong Yang", + "author_inst": "Department of oncology, The Second Hospital of WISCO (Wuhan Iron and Steel Corporation)" + }, + { + "author_name": "Zhihong Zhang", + "author_inst": "Department of Oncology, Gong'an County People's Hospital" + }, + { + "author_name": "Li Kuang", + "author_inst": "Department of Oncology, Affliated Dongfeng Hospital, Hubei University of Medicine" + }, + { + "author_name": "Runkun Wang", + "author_inst": "Department of oncology, The first people's hospital of Guangshui" + }, + { + "author_name": "Youhong Dong", + "author_inst": "Department of oncology, Xiangyang No.1 People's Hospital, Hubei Univeristy of Medicine" + }, + { + "author_name": "Jianhai Sun", + "author_inst": "Department of Oncology, Hubei No.3 People's Hospital" + }, + { + "author_name": "Wenbing Hu", + "author_inst": "Department of Oncology, Huangshi Central Hospital of EDong Healthcare" + }, + { + "author_name": "Tienan Yi", + "author_inst": "Department of Oncology, Xiangyang Central Hospital, Hubei University of Medicine" + }, + { + "author_name": "Hanlin Wu", + "author_inst": "Department of Oncology, The First People's Hospital of Jingmen" + }, + { + "author_name": "Mingyu Liu", + "author_inst": "The No. 9 hospital of Wuhan" + }, + { + "author_name": "Jiachen Xu", + "author_inst": "State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital" + }, + { + "author_name": "Jianchun Duan", + "author_inst": "State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital" + }, + { + "author_name": "Zhengyi Zhao", + "author_inst": "The Medical Department, 3D Medicines, Inc." + }, + { + "author_name": "Guoqiang Wang", + "author_inst": "Burning Rock Biotech" + }, + { + "author_name": "Yu Xu", + "author_inst": "The Medical Department, 3D Medicines, Inc." + }, + { + "author_name": "Jie He", + "author_inst": "State Key Laboratory of Molecular Oncology, Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital," } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "oncology" }, { "rel_doi": "10.1101/2020.04.27.20081794", @@ -1476960,43 +1477094,31 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2020.04.28.20082370", - "rel_title": "Ecologic correlation between underlying population level morbidities and COVID-19 case fatality rate among countries infected with SARS-CoV-2", + "rel_doi": "10.1101/2020.04.27.20081885", + "rel_title": "Control with uncertain data of socially structured compartmental epidemic models", "rel_date": "2020-05-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20082370", - "rel_abs": "BackgroundThe ongoing Coronavirus disease 2019 (COVID-19) pandemic is unprecedented in scope. High income countries (HIC) seemingly account for the majority of the mortalities considering that these countries have screened more persons. Low middle income countries (LMIC) countries may experience far worse mortalities considering the existence of a weaker health care system and the several underlying population level morbidities. As a result, it becomes imperative to understand the ecological correlation between critical underlying population level morbidities and COVID-19 case fatality rates (CFR).\n\nMethodThis is an ecological study using data on COVID-19 cases, prevalence of COPD, prevalence of tobacco use, adult HIV prevalence, quality of air and life expectancy. We plotted a histogram, performed the Shapiro-Wilk normality test and used spearman correlation to assess the degree of correlation between COVID-19 case fatality rate (CFR) and other covariates mentioned above.\n\nResultAs at the 31st of March 2020, there were a total of 846,281 cases of COVID-19 from 204 countries and a global case fatality rate of 5% (range 0% to 29%). Angola and Sudan both had the highest CFR of 29%, while Italy had the highest number of deaths (i.e. 12,428) as at 31st of March 2020. Adult HIV prevalence has a significant but weak negative correlation with CFR (correlation coefficient = - 0.24, p value =0.01) while all the other variables have positive correlation with CFR due to COVID-19 though not statistically significant. Of the 204 countries analyzed, only 11 countries (i.e. 5%) had complete datasets across all 5 population level morbidities (i.e. prevalence of COPD, prevalence of tobacco use, life expectancy, quality of air, and adult HIV prevalence variables). Correlations of CFR from these 11 countries were similar to that from the 204 countries except for the correlation with quality of air and prevalence of tobacco use. Conclusion: While we interpret our data with caution given the fact that this is an ecological study, our findings suggest that population level factors such as prevalence of COPD, prevalence of tobacco use, life expectancy and quality of air are positively correlated with CFR from COVID-19 but, adult HIV prevalence has a weak and negative correlation with COVID-19 CFR and would require extensive research.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20081885", + "rel_abs": "The adoption of containment measures to reduce the amplitude of the epidemic peak is a key aspect in tackling the rapid spread of an epidemic. Classical compartmental models must be modified and studied to correctly describe the effects of forced external actions to reduce the impact of the disease. In addition, data are often incomplete and heterogeneous, so a high degree of uncertainty must naturally be incorporated into the models. In this work we address both these aspects, through an optimal control formulation of the epidemiological model in presence of uncertain data. After the introduction of the optimal control problem, we formulate an instantaneous approximation of the control that allows us to derive new feedback controlled compartmental models capable of describing the epidemic peak reduction. The need for long-term interventions shows that alternative actions based on the social structure of the system can be as effective as the more expensive global strategy. The importance of the timing and intensity of interventions is particularly relevant in the case of uncertain parameters on the actual number of infected people. Simulations related to data from the recent COVID-19 outbreak in Italy are presented and discussed.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "EVAEZI OKPOKORO", - "author_inst": "Institute of Human Virology Nigeria" - }, - { - "author_name": "VICTORIA IGBINOMWANHIA", - "author_inst": "International Research Center of Excellence, Institute of Human Virology Nigeria" - }, - { - "author_name": "ELIMA JEDY-AGBA", - "author_inst": "International Research Center of Excellence, Institue of Human virology Nigeria" - }, - { - "author_name": "GBENGA KAYODE", - "author_inst": "International Research Center of Excellence, Institute of Human Virology Nigeria" + "author_name": "Giacomo Albi", + "author_inst": "University of Verona" }, { - "author_name": "EZENWA ONYEMATA", - "author_inst": "International Research Center of Excellence, Institute of Human Virology Nigeria" + "author_name": "Lorenzo Pareschi", + "author_inst": "University of Ferrara" }, { - "author_name": "ALASH'LE ABIMIKU", - "author_inst": "International Research Center of Excellence, Institute of Human Virology Nigeria" + "author_name": "Mattia Zanella", + "author_inst": "University of Pavia" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.27.20081893", @@ -1478510,67 +1478632,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.30.20085670", - "rel_title": "Beyond the Spike: identification of viral targets of the antibody response to SARS-CoV-2 in COVID-19 patients", + "rel_doi": "10.1101/2020.04.28.20083451", + "rel_title": "Identification of Three Endotypes in Pediatric Acute Respiratory Distress Syndrome by Nasal Transcriptomic Profiling", "rel_date": "2020-05-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.30.20085670", - "rel_abs": "BackgroundThe SARS-CoV-2 virus emerged in December 2019 and caused a pandemic associated with a spectrum of COVID-19 disease ranging from asymptomatic to lethal infection. Serology testing is important for diagnosis of infection, determining infection attack rates and immunity in the population. It also informs vaccine development. Although several serology tests are in use, improving their specificity and sensitivity for early diagnosis on the one hand and for detecting past infection for population-based studies, are priorities.\n\nMethodsWe evaluated the anti-SARS-CoV-2 antibody profiles to 15 SARS-CoV-2 antigens by cloning and expressing 15 open reading frames (ORFs) in mammalian cells and screened antibody responses to them in COVID-19 patients using the Luciferase Immunoprecipitation System (LIPS).\n\nResultsThe LIPS technique allowed us to detect antibody responses in COVID-19 patients to 11 of the 15 SARS-CoV-2 antigens tested, identifying novel immunogenic targets. This technique shows that antigens ORF3b and ORF8 allow detection of antibody early in infection in a specific manner and reveals the immuno-dominance of the N antigen in COVID-19 patients.\n\nConclusionOur report provides an unbiased characterization of antibody responses to a range of SARS-CoV-2 antigens. The combination of 3 SARS-CoV-2 antibody LIPS assays, i.e. N, ORF3b, and ORF8, is sufficient to identify all COVID-19 patients of our cohort even at early time-points of illness, whilst Spike alone fails to do so. Furthermore, our study highlights the importance of investigating new immunogens NSP1, ORF3b, ORF7a and ORF8 which may mediate immune functions other than neutralization which may be beneficial or harmful to the patient.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20083451", + "rel_abs": "1Acute respiratory distress syndrome (ARDS) and pediatric ARDS (PARDS) can be triggered by multiple pulmonary and non-pulmonary insults and are the source of substantial morbidity and mortality. The nasal and lower conducting airways have similar cell composition and nasal transcriptomes identify disease state and sub-classes in lung cancer, COPD, and asthma. We conducted an observational, prospective trial to determine whether this technique could identify PARDS endotypes in 26 control and 25 PARDS subjects <18 admitted to the pediatric ICU. RNA from inferior turbinate brushing was collected on days 1, 3, 7, and 14. Standard RNA-processing yielded 29% usable specimens by mRNA-Seq, and a low-input protocol increased yield to 95% usable specimens. 64 low-input specimens from 10 control and 15 PARDS subjects were used for model development. Control and some PARDS subjects clustered together in Group A while some day 1, 3, and 7 specimens clustered into Groups B and C with specimens from these subjects moving to Group A with PARDS resolution. In multivariate analysis, the only clinical variables associated with specimen Group B or C assignment was severity of lung injury or viral PARDS trigger. Compared to Group A, Group B had upregulation of innate immune processes and Group C had upregulation of ciliary and microtuble processes. Analysis of the 15 standard processing specimens identified the same grouping. Mortality trended higher in group B (25%) and C subjects (28.6%) compared to A (5%, p=0.1). Comparison of groups with 16 PARDS-associated serum biomarkers identified correlation of Endotype B with Tumor Necrosis Factor-, but not other inflammatory cytokines and Endotype C with Surfactant Protein D. We identified three nasal transcriptomic PARDS endotypes. A is similar to control. B is marked by an innate immune signature only weakly reflected in the serum. C may be associated with loss of epithelial barrier integrity. Nasal transcriptomics may be useful for prognostic and predictive enrichment in future PARDS trials. ClinicalTrials.gov Identifier NCT03539783", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Asmaa Hachim", - "author_inst": "The University of Hong Kong" + "author_name": "James \"Garrett\" Williams", + "author_inst": "Cincinnati Children's Hospital Medical Center Division of Critical Care Medicine" }, { - "author_name": "Niloufar Kavian", - "author_inst": "The University of Hong Kong" - }, - { - "author_name": "Carolyn A Cohen", - "author_inst": "The University of Hong Kong" + "author_name": "Rashika Joshi", + "author_inst": "Cincinnati Children's Hospital Medical Center Division of Critical Care Medicine" }, { - "author_name": "Alex WH Chin", - "author_inst": "The University of Hong Kong" + "author_name": "Rhonda Jones", + "author_inst": "Cincinnati Children's Hospital Medical Center Division of Critical Care Medicine" }, { - "author_name": "Daniel KW Chu", - "author_inst": "The University of Hong Kong" + "author_name": "Aditi Paranjpe", + "author_inst": "Cincinnati Children's Hospital Medical Center" }, { - "author_name": "Chris Ka Pun Mok", - "author_inst": "The University of Hong Kong" + "author_name": "Mario Pujato", + "author_inst": "Cincinnati Children's Hospital Medical Center" }, { - "author_name": "Owen TY Tsang", - "author_inst": "Princess Margaret Hospital, Hospital Authority of Hong Kong" + "author_name": "Krishna Roskin", + "author_inst": "Cincinnati Children's Hospital Medical Center" }, { - "author_name": "Yiu Cheong Yeung", - "author_inst": "Princess Margaret Hospital, Hospital Authority of Hong Kong" + "author_name": "Toni Yunger", + "author_inst": "Cincinnati Children's Hospital Medical Center Division of Critical Care Medicine" }, { - "author_name": "Ranawaka APM Perera", - "author_inst": "The University of Hong Kong" + "author_name": "Erin Stoneman", + "author_inst": "Cincinnati Children's Hospital Medical Center Division of Critical Care Medicine" }, { - "author_name": "Leo LM Poon", - "author_inst": "The University of Hong Kong" + "author_name": "Patrick Lahni", + "author_inst": "Cincinnati Children's Hospital Medical Center" }, { - "author_name": "Malik JS Peiris", - "author_inst": "University of Hong Kong" + "author_name": "Hector R Wong", + "author_inst": "Cincinnati Children's Hospital Medical Center" }, { - "author_name": "Sophie A Valkenburg", - "author_inst": "The University of Hong Kong" + "author_name": "Brian Michael Varisco", + "author_inst": "Cincinnati Children's Hospital Medical Center" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.04.28.20083089", @@ -1480200,25 +1480318,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.26.20080820", - "rel_title": "Knowledge, attitudes, and practices (KAP) towards COVID-19: A quick online cross-sectional survey among Tanzanian residents.", + "rel_doi": "10.1101/2020.04.27.20080432", + "rel_title": "High rate of increased level of plasma Angiotensin II and its gender difference in COVID-19: an analysis of 55 hospitalized patients with COVID-19 in a single hospital, WuHan, China", "rel_date": "2020-05-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.26.20080820", - "rel_abs": "BackgroundThe Corona Virus Disease -19 (COVID-19) pandemic is a global health emergency that requires the adoption of unprecedented measures to control its rapid spread. Tanzanians adherence to control measures is affected by their knowledge, attitudes, and practices (KAP) towards the disease. This study was carried out to investigate knowledge, attitudes and practices towards COVID-19 among residents in Tanzania during the April - May 2020 period of the epidemic.\n\nMethodsThis cross-sectional study analyzes responses of self-selected Tanzanians who responded to an invitation to complete an online questionnaire. Survey Monkey tool was used to develop the questionnaire used for data collection. The survey assessed demographic characteristics of participants as well as their knowledge, attitudes, and practices toward COVID-19. A Chi-square analysis was used to compare proportions. Analysis of variance (ANOVA) was used to determine differences among age groups, whereas results were considered significant if the p-value was <0.05\n\nResultsFour hundred residents completed the survey. The mean age of study participants was 32 years, and the majority was female (n= 216,54.0%). There were no significant differences in demographic variables). Participants with a bachelors degree or above (n= 241, 60.3%) had higher scores. Overall, 84.4% (n=338) of participants had good knowledge, which was significantly associated with education level (p=0.001). Nearly all participants (n=384, 96.0%) had confidence that COVID-19 will be eliminated. The majority of respondents (n=308, 77.0%) did not go to a crowded place in recent days. Multiple linear regression analysis showed that males, age-group 16-29 years, and education of secondary or lower (OR = 1.2, CI = 1.3-1.5) were significantly associated with lower knowledge score.\n\nConclusionsOur findings revealed good knowledge, optimistic attitudes, and appropriate practices towards preventing COVID-19 infection. Suggesting that community-based health education programs about COVID-19 is helpful and necessary to control the disease.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20080432", + "rel_abs": "Background2019 Novel coronavirus disease (COVID-19) is turning into a pandemic globally lately. Angiotensin-converting enzyme 2 (ACE2) is identified as an important functional receptor for SARS-Cov-2. ACE2 and ACE are homologues with inverse functions in the renin-angiotensin system. ACE converts angiotensin I into a vital vasoactive peptide called angiotensin II(AngII), whereas ACE2 hydrolyzes AngII into a series of vasodilators. There were few reports illustrated the expression of AngII in COVID-19. This study aimed to demonstrate the expression of angiotensin II in COVID-19 and how it correlated to the disease.\n\nMethodsWe enrolled 55 patients with COVID-19 admitted to renmin Hospital of Wuhan University from January 21st to February 21st, 2020. Demographic data were collected upon admission. COVID-19 nuclear acid, plasma AngII, Renin and aldosterone in the lying position without sodium restriction, and other laboratory indicators were together measured by the laboratory department of our hospital.\n\nFindingsOf the 55 patients with COVID-19, 34(61.8%) had an increased level of AngII. The severity of COVID-19 and male is positively related with the level of AngII. The level of blood lymphocyte, PCT, ALT, and AST were remarkably severe with those of normal level of AngII (P < 0.05). CD4/CD8 cells ratio was significantly higher whereas CD3+CD8+ cells amount, CD3+CD8+ cells proportion, CD56+CD16+CD3- cells amount and CD19+CD3- cells amount were considerably lower than those of normal level of AngII (P < 0.05). Abnormal rates of blood lymphocyte and PCT were significantly higher in Patients with elevated AngII level. The results of binary logistic regression analysis showed that the severity of COVID-19 (OR=4.123) and CD4/CD8 ratio(OR=4.050) were the co-directional impact factor while female(OR=0.146) was inverse impact factor of elevated AngII level.\n\nInterpretationHigh rate of increased level of AngII was detected in COVID-19 patients. Patients with elevated AngII level were more likely to be critically ill with COVID-19. Considering the gender differences in ACE2 expression and no gender differences in angiotensin expression, the gender differences in AngII level might indicate less loss of ACE2 in female patients. Elevated AngII level was correlated with CD4/CD8 ratio, suggesting it might involve in immune disorder.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "sima rugarabamu", - "author_inst": "MUHAS" + "author_name": "Na Liu", + "author_inst": "Renmin Hospital of Wuhan University" }, { - "author_name": "Aisha Byanaku", - "author_inst": "AMREF TANZANIA" + "author_name": "Yan Hong", + "author_inst": "Pediatric Emergency Department,Guangzhou Women and Children's Medical Center,Guangzhou Medical University" }, { - "author_name": "Mariam Ibrahim", - "author_inst": "TIRDO-Tanzania" + "author_name": "Ren-Gui Chen", + "author_inst": "Department of Nephrology, renmin Hospital of Wuhan University" + }, + { + "author_name": "Heng-Mei Zhu", + "author_inst": "the First Affiliated Hospital of Nanchang University" } ], "version": "1", @@ -1481418,21 +1481540,61 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2020.04.26.20081083", - "rel_title": "Impact of mitigating interventions and temperature on the instantaneous reproduction number in the COVID-19 epidemic among 30 US metropolitan areas", + "rel_doi": "10.1101/2020.04.26.20081208", + "rel_title": "COVID-19 mathematical model reopening scenarios for Sao Paulo - Brazil", "rel_date": "2020-05-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.26.20081083", - "rel_abs": "BackgroundAfter more than four months into the coronavirus disease (COVID-19) epidemic, over 347,500 people had died worldwide. The current study aims to evaluate how mitigating interventions affected the epidemic process in the 30 largest metropolitan areas in the US and whether temperature played a role in the epidemic process.\n\nMethodsPublicly available data for the time series of COVID-19 cases and deaths and weather were analyzed at the metropolitan level. The time-varying reproductive numbers (Rt) based on retrospective moving average were used to explore the trends. Student t tests were used to compare temperature and peak Rt cross-sectionally.\n\nResultsWe found that virus transmissibility, measured by instantaneous reproduction number (Rt), had declined since the end of March for all areas and almost all of them reached a Rt of 1 or below after April 15, 2020. However, the Rts remained around 1 for most areas since then and some small and short rebounds were presented in some areas, suggesting a persistent epidemic in those areas. The timing of the main decline was concurrent with the implementation of mitigating interventions. Cities with warm temperature also tended to have a lower peak Rt than that of cities with cold temperature. However, large geographic variations existed.\n\nConclusionsAggressive interventions might have mitigated the current epidemic of COVID-19, while temperature might have some weak effects on the virus transmission. We may need to prepare for a possible return of the coronavirus outbreak.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.26.20081208", + "rel_abs": "An epidemiological compartmental model was used to simulate social distancing strategies to contain the COVID-19 pandemic and prevent a second wave in Sao Paulo, Brazil. Optimization using genetic algorithm was used to determine the optimal solutions. Our results suggest the best-case strategy for Sao Paulo is to maintain or increase the current magnitude of social distancing for at least 60 more days and increase the current levels of personal protection behaviors by a minimum of 10% (e.g., wearing facemasks, proper hand hygiene and avoid agglomeration). Followed by a long-term oscillatory level of social distancing with a stepping-down approach every 80 days over a period of two years with continued protective behavior.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Xinhua Yu", - "author_inst": "University of Memphis" + "author_name": "Osmar Pinto Neto", + "author_inst": "Anhembi Morumbi University" + }, + { + "author_name": "Josa Clark Reis", + "author_inst": "Embraer - SJC" + }, + { + "author_name": "Ana Carolina Brisola Brizzi", + "author_inst": "Anhembi Morumbi University" + }, + { + "author_name": "Gustavo Jose Zambrano", + "author_inst": "Arena235 Research Lab" + }, + { + "author_name": "Joabe Marcos de Souza", + "author_inst": "Universidade de Sao Paulo" + }, + { + "author_name": "Wellington Pedroso E. Amorim", + "author_inst": "Anhembi Morumbi University" + }, + { + "author_name": "Rodrigo Cunha de Mello Pedreiro", + "author_inst": "Estacio de Sa University" + }, + { + "author_name": "Bruno de Matos Brizzi", + "author_inst": "Arena235 Research Lab" + }, + { + "author_name": "Ellysson Oliveira Abinader", + "author_inst": "Instituto Abinader" + }, + { + "author_name": "Deanna M. Kennedy", + "author_inst": "Texas A&M University" + }, + { + "author_name": "Renato A Zangaro", + "author_inst": "Anhembi Morumbi University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1482916,33 +1483078,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.24.20078709", - "rel_title": "Extensive testing may reduce COVID-19 mortality: a lesson from northern Italy", + "rel_doi": "10.1101/2020.04.27.20077180", + "rel_title": "COVID-19-induced acute respiratory failure: an exacerbation of organ-specific autoimmunity?", "rel_date": "2020-05-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20078709", - "rel_abs": "We examined data on the progression of COVID-19 epidemics in four regions in northern Italy. Lombardy, Emilia-Romagna, and Piedmont had an extremely steeper increase in mortality with increasing number of tests performed than Veneto, which applied a policy of broader swab testing. This suggests that the strategy adopted in Veneto, similar to that in South Korea, is effective in containing COVID-19 epidemics and should be applied in other regions of Italy and countries in Europe.\n\nOn February 20, 2020, a first autochthonous case of COVID-19 respiratory disease was observed in Lombardy, Italy (1), soon followed by a second patient in Veneto, which borders Lombardy. Since then, the outbreak has rapidly expanded, mostly in regions in northern Italy (2).\n\nInitially, epidemiological surveillance and strategies for swab testing were under control of regional healthcare authorities. On February 25, the Italian Ministry of Health issued more stringent testing policies for application of swabs to identify COVID-19 cases, prioritizing patients with respiratory symptoms and possible COVID-19 contacts who required hospitalization. Most regions promptly complied with these recommendations, whereas Veneto maintained its policy, implemented after the occurrence of the first cases, of extensive testing and isolation of positive cases (3). Surprisingly, the debate stemming from these different regional policies valued international more than Italian evidences (4). We aimed at assessing, using data from the first month of the Italian experience, how different policies for swab testing may impact on the initial progression of COVID-19 epidemics.\n\nData were obtained from the reports of the Italian Department of Civil Protection, issued since February 24, which include daily number of swabs performed and deaths from COVID-19 in each region (5). We compared Lombardy, Emilia-Romagna, and Piedmont, three regions in northern Italy that closely followed the recommendations for restrictive COVID-19 testing, and Veneto, which applied a policy of broader testing (3).\n\nConflict of interestNone declared.\n\nFunding statementNo funding.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20077180", + "rel_abs": "BackgroundUnderstanding the pathophysiology of respiratory failure (ARDS) in coronavirus disease 2019 (COVID-19) patients is of utmost importance for the development of therapeutic strategies and identification of risk factors. Since we observed clinical and histopathological similarities between COVID-19 and lung manifestations of connective tissue disease (CTD-ILD) in our clinical practice, aim of the present study is to analyze a possible role of autoimmunity in SARS-CoV-2-associated respiratory failure.\n\nMethodsIn this prospective, single-center trial, we enrolled 22 consecutive patients with RT-PCR-confirmed SARS-CoV-2 infection hospitalized in March and April, 2020. We performed high-resolution computed tomography (HR-CT) and full laboratory testing including autoantibody (AAB) screening (anti-ANA, SS-B/La, Scl-70, Jo-1, CENP-B, PM-Scl). Transbronchial biopsies as well as post mortem tissue samples were obtained from 3 and 2 cases, respectively, and subsequent histopathologic analysis with special emphasis on characterization of interstitial lung disease was performed.\n\nResultsTwelve of 22 patients (54.5%) were male and median age was 69.0 (range: 28-88). 11 (50.0%) patients had to be undergo intensive care unit (ICU) treatment. Intubation with ventilation was required in 10/22 cases (46%). Median follow-up was 26 days. Clinical and serological parameters were comparable to previous reports. Radiological and histopathological findings were highly heterogeneous including patterns reminiscent of CTD-ILD. AAB titers [≥]1:100 were detected in 10/11 (91.9%) COVID-19 patients who required ICU treatment, but in 4/11 (36.4%) patients with mild clinical course (p=0.024). Patients with AABs tended to require invasive ventilation and showed significantly more severe complications (64.3% vs. 12.5%, p=0.031). Overall COVID-19-related mortality was 18.2% among hospitalized patients at our institution.\n\nConclusionOur findings point out serological, radiological and histomorphological similarities between COVID-19-associated ARDS and acute exacerbation of CTD-ILD. While the exact mechanism is still unknown, we postulate that SARS-CoV-2 infection might trigger or simulate a form of organ-specific autoimmunity in predisposed patients. The detection of autoantibodies might identify patients who profit from immunosuppressive therapy to prevent the development of respiratory failure.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Mauro Di Bari", - "author_inst": "University of Florence" + "author_name": "Daniel Gagiannis", + "author_inst": "Department of Pulmonology, Bundeswehrkrankenhaus Ulm" }, { - "author_name": "Daniela Balzi", - "author_inst": "Azienda USL Toscana Centro" + "author_name": "Julie Steinestel", + "author_inst": "Clinic of Urology, University Hospital Augsburg" }, { - "author_name": "Giulia Carreras", - "author_inst": "University of Florence" + "author_name": "Carsten Hackenbroch", + "author_inst": "Department of Radiology, Bundeswehrkrankenhaus Ulm" }, { - "author_name": "Graziano Onder", - "author_inst": "Istituto Superiore di Sanit\u00e1" + "author_name": "Michael Hannemann", + "author_inst": "Department of Laboratory Medicine, Bundeswehrkrankenhaus Ulm" + }, + { + "author_name": "Vincent G Umathum", + "author_inst": "Institute of Pathology and Molecular Pathology, Bundeswehrkrankenhaus Ulm" + }, + { + "author_name": "Niklas Gebauer", + "author_inst": "Department of Hematology and Oncology, University Hospital Schleswig-Holstein Campus Luebeck" + }, + { + "author_name": "Marcel Stahl", + "author_inst": "Department of Pulmonology, Bundeswehrkrankenhaus Ulm" + }, + { + "author_name": "Hanno M Witte", + "author_inst": "Department of Hematology and Oncology, Bundeswehrkrankenhaus Ulm" + }, + { + "author_name": "Konrad Steinestel", + "author_inst": "Bundeswehrkrankenhaus Ulm" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1484110,39 +1484292,35 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.04.29.069591", - "rel_title": "A Rapid COVID-19 RT-PCR Detection Assay for Low Resource Settings", + "rel_doi": "10.1101/2020.04.29.068999", + "rel_title": "Estimating seroprevalence with imperfect serological tests: a cutoff-free approach", "rel_date": "2020-04-30", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.29.069591", - "rel_abs": "Quantitative reverse transcription polymerase chain reaction (RT-qPCR) assay is the gold standard recommended to test for acute SARS-CoV-2 infection. It has been used by the Centers for Disease Control and Prevention (CDC) and several other companies in their Emergency Use Authorization (EUA) assays. RT-qPCR requires expensive equipment such as RNA isolation instruments and real-time PCR thermal cyclers, which are not available in many low resource settings and developing countries. As a pandemic, COVID-19 has quickly spread to the rest of the world. Many underdeveloped and developing counties do not have the means for fast and accurate COVID-19 detection to control this outbreak. Using COVID-19 positive clinical specimens, we demonstrated that RT-PCR assays can be performed in as little as 12 minutes using untreated samples, heat-inactivated samples, or extracted RNA templates. Rapid RT-PCR was achieved using thin-walled PCR tubes and a setup including sous vide immersion heaters/circulators. Our data suggest that rapid RT-PCR can be implemented for sensitive and specific molecular diagnosis of COVID-19 in situations where sophisticated laboratory instruments are not available.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.29.068999", + "rel_abs": "Large-scale serological testing in the population is essential to determine the true extent of the current SARS-CoV-2 pandemic. Serological tests measure antibody responses against pathogens and use predefined cutoff levels that dichotomize the quantitative test measures into sero-positives and negatives and use this as a proxy for past infection. With the imperfect assays that are currently available to test for past SARS-CoV-2 infection, the fraction of seropositive individuals in serosurveys is a biased estimator of the cumulative incidence and is usually corrected to account for the sensitivity and specificity. Here we use an inference method -- referred to as mixture-model approach -- for the estimation of the cumulative incidence that does not require to define cutoffs by integrating the quantitative test measures directly into the statistical inference procedure. We confirm that the mixture model outperforms the methods based on cutoffs, leading to less bias and error in estimates of the cumulative incidence. We illustrate how the mixture model can be used to optimize the design of serosurveys with imperfect serological tests. We also provide guidance on the number of control and case sera that are required to quantify the tests ambiguity sufficiently to enable the reliable estimation of the cumulative incidence. Lastly, we show how this approach can be used to estimate the cumulative incidence of classes of infections with an unknown distribution of quantitative test measures. This is a very promising application of the mixture-model approach that could identify the elusive fraction of asymptomatic SARS-CoV-2 infections. An R-package implementing the inference methods used in this paper is provided. Our study advocates using serological tests without cutoffs, especially if they are used to determine parameters characterizing populations rather than individuals. This approach circumvents some of the shortcomings of cutoff-based methods at exactly the low cumulative incidence levels and test accuracies that we are currently facing in SARS-CoV-2 serosurveys.\n\nAuthor SummaryAs other pathogens, SARS-CoV-2 elicits antibody responses in infected people that can be detected in their blood serum as early as a week after the infection until long after recovery. The presence of SARS-CoV-2 specific antibodies can therefore be used as a marker of past infection, and the prevalence of seropositive people, i.e. people with specific antibodies, is a key measure to determine the extent of the SARS-CoV-2 pandemic. The serological tests, however, are usually not perfect, yielding false positive and false negative results. Here we exploit an approach that refrains from classifying people as seropositive or negative, but rather compares the antibody level of an individual to that of confirmed cases and controls. This approach leads to more reliable estimates of cumulative incidence, especially for the low prevalence and low test accuracies that we face during the current SARS-CoV-2 pandemic. We also show how this approach can be extended to infer the presence of specific types of cases that have not been used for validating the test, such as people that underwent a mild or asymptomatic infection.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Arunkumar Arumugam", - "author_inst": "AI Biosciences, Inc." - }, - { - "author_name": "Matthew L Faron", - "author_inst": "The Medical College of Wisconsin" + "author_name": "Judith A Bouman", + "author_inst": "ETH Zurich" }, { - "author_name": "Peter Yu", - "author_inst": "AI Biosciences, Inc." + "author_name": "Julien Riou", + "author_inst": "University of Bern" }, { - "author_name": "Cole Markham", - "author_inst": "AI Biosciences, Inc." + "author_name": "Sebastian Bonhoeffer", + "author_inst": "ETH Zurich" }, { - "author_name": "Season S Wong", - "author_inst": "AI Biosciences, Inc." + "author_name": "Roland R Regoes", + "author_inst": "ETH Zurich" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "new results", - "category": "molecular biology" + "category": "immunology" }, { "rel_doi": "10.1101/2020.04.29.069054", @@ -1485484,47 +1485662,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.24.20078303", - "rel_title": "Concentration-dependent mortality of chloroquine in overdose", + "rel_doi": "10.1101/2020.04.27.065383", + "rel_title": "In silico analysis of RT-qPCR designs recommended by WHO for detection of SARS-CoV-2 and a commercial kit validated following UNE/EN ISO 17025:2005 and two reference laboratories", "rel_date": "2020-04-29", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20078303", - "rel_abs": "Hydroxychloroquine and chloroquine are used extensively in malaria and rheumatological conditions, and now in COVID-19 prevention and treatment. Although generally safe they are potentially lethal in overdose. In-vitro data suggest that high concentrations and thus high doses are needed for COVID-19 infections, but as yet there is no convincing evidence they are clinically effective. Bayesian regression models were fitted to survival outcomes and electrocardiograph QRS durations from 302 prospectively studied French patients who had taken intentional chloroquine overdoses, of whom 33 died (11%), and 16 healthy volunteers who took 620 mg base chloroquine single doses. Whole blood concentrations of 13.5 mol/L (95% credible interval 10.1-17.7) were associated with 1% mortality. Prolongation of ventricular depolarisation is concentration-dependent with a QRS duration >150 msec independently highly predictive of mortality. Pharmacokinetic modelling combined with these lethality data predicts that the majority of chloroquine regimens trialled in COVID-19 should not cause serious cardiovascular toxicity.", - "rel_num_authors": 7, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.27.065383", + "rel_abs": "BackgroundThe Corona Virus Disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has become a serious infectious disease affecting human health worldwide and rapidly declared a pandemic by WHO. Early, several RT-qPCR were designed by using only the first SARS-CoV-2 genome sequence.\n\nObjectivesA few days later, when additional SARS-CoV-2 genome were retrieved, the kit GPS CoVID-19 dtec-RT-qPCR Test was designed to provide a highly specific detection method and commercially available worldwide. The kit was validated following criteria recommended by the UNE/EN ISO 17025:2005 and ISO/IEC 15189:2012.\n\nMethodsThe present study approached the in silico specificity of the GPS CoVID-19 dtec-RT-qPCR Test and RT-qPCR designs currently published. The empirical validation parameters specificity (inclusivity/exclusivity), quantitative phase analysis (10-106 copies), reliability (repeatability/reproducibility) and sensitivity (detection/quantification limits) were evaluated for a minimum of 10-15 assays. Diagnostic validation was achieved by two independent reference laboratories, the Instituto de Salud Carlos III (ISCIII), (Madrid, Spain) and the Public Health England (PHE; Colindale, London, UK).\n\nResultsThe GPS RT-qPCR primers and probe showed the highest number of mismatches with the closet related non-SARS-CoV-2 coronavirus, including some indels. The kits passed all parameters of validation with strict acceptance criteria. Results from reference laboratories 100% correlated with these obtained by suing reference methods and received an evaluation with 100% of diagnostic sensitivity and specificity.\n\nConclusionsThe GPS CoVID-19 dtec-RT-qPCR Test, available with full analytical and diagnostic validation, represents a case of efficient transfer of technology being successfully used since the pandemic was declared. The analysis suggested the GPS CoVID-19 dtec-RT-qPCR Test is the more exclusive by far.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "James A Watson", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit" - }, - { - "author_name": "Joel Tarning", - "author_inst": "Mahidol Oxford Research Unit" + "author_name": "Antonio J Martinez-Murcia", + "author_inst": "Universidad Miguel Hern\u00e1ndez" }, { - "author_name": "Richard M Hoglund", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit" + "author_name": "Gema Bru", + "author_inst": "Genetic Analysis Strategies S.L." }, { - "author_name": "Frederic J Baud", - "author_inst": "Assistance Publique - Hopitaux de Paris" + "author_name": "Aaron Navarro", + "author_inst": "Universidad Miguel Hern\u00e1ndez" }, { - "author_name": "Bruno Megarbane", - "author_inst": "Universite de Paris" + "author_name": "Patricia Ros-T\u00e1rraga", + "author_inst": "Genetic Analysis Strategies S.L." }, { - "author_name": "Jean-Luc Clemessy", - "author_inst": "Clinique du Sport" + "author_name": "Adri\u00e1n Garc\u00eda-Sirera", + "author_inst": "Genetic Analysis Strategies S.L." }, { - "author_name": "Nicholas J White", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit" + "author_name": "Laura P\u00e9rez", + "author_inst": "genetic PCR solutions" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "pharmacology and therapeutics" + "license": "cc_no", + "type": "new results", + "category": "genetics" }, { "rel_doi": "10.1101/2020.04.24.20078824", @@ -1486754,125 +1486928,113 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.27.20082347", - "rel_title": "The natural history and transmission potential of asymptomatic SARS-CoV-2 infection", + "rel_doi": "10.1101/2020.04.26.20080408", + "rel_title": "A gene locus that controls expression of ACE2 in virus infection", "rel_date": "2020-04-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20082347", - "rel_abs": "BackgroundLittle is known about the natural history of asymptomatic SARS-CoV-2 infection or its contribution to infection transmission.\n\nMethodsWe conducted a prospective study at a quarantine centre for COVID-19 in Ho Chi Minh City, Vietnam. We enrolled quarantined people with RT-PCR-confirmed SARS-CoV-2 infection, collecting clinical data, travel and contact history, and saliva at enrolment and daily nasopharyngeal throat swabs (NTS) for RT-PCR testing. We compared the natural history and transmission potential of asymptomatic and symptomatic individuals.\n\nResultsBetween March 10th and April 4th, 2020, 14,000 quarantined people were tested for SARS-CoV-2; 49 were positive. Of these, 30 participated in the study: 13(43%) never had symptoms and 17(57%) were symptomatic. 17(57%) participants acquired their infection outside Vietnam. Compared with symptomatic individuals, asymptomatic people were less likely to have detectable SARS-CoV-2 in NTS samples collected at enrolment (8/13 (62%) vs. 17/17 (100%) P=0.02). SARS-CoV-2 RNA was detected in 20/27 (74%) available saliva; 7/11 (64%) in the asymptomatic and 13/16 (81%) in the symptomatic group (P=0.56). Analysis of the probability of RT-PCR positivity showed asymptomatic participants had faster viral clearance than symptomatic participants (P<0.001 for difference over first 19 days). This difference was most pronounced during the first week of follow-up. Two of the asymptomatic individuals appeared to transmit the infection to up to four contacts.\n\nConclusionsAsymptomatic SARS-CoV-2 infection is common and can be detected by analysis of saliva or NTS. NTS viral loads fall faster in asymptomatic individuals, but they appear able to transmit the virus to others.", - "rel_num_authors": 27, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.26.20080408", + "rel_abs": "The SARS-CoV-2 pandemic has resulted in widespread morbidity and mortality globally. ACE2 is a receptor for SARS-CoV-2 and differences in expression may affect susceptibility to COVID-19. Using HCV-infected liver tissue from 195 individuals, we discovered that among genes negatively correlated with ACE2, interferon signalling pathways were highly enriched and observed down-regulation of ACE2 after interferon-alpha treatment. Negative correlation was also found in the gastrointestinal tract and in lung tissue from a murine model of SARS-CoV-1 infection suggesting conserved regulation of ACE2 across tissue and species. Performing a genome-wide eQTL analysis, we discovered that polymorphisms in the interferon lambda (IFNL) region are associated with ACE2 expression. Increased ACE2 expression in the liver was also associated with age and presence of cirrhosis. Polymorphisms in the IFNL region may impact not only antiviral responses but also ACE2 with potential consequences for clinical outcomes in distinct ethnic groups and with implications for therapeutic interventions.", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Nguyen Van Vinh Chau", - "author_inst": "Hospital for Tropical Diseases" - }, - { - "author_name": "Vo Thanh Lam", - "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam" - }, - { - "author_name": "Nguyen Thanh Dung", - "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam" - }, - { - "author_name": "Lam Minh Yen", - "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam" + "author_name": "M. Azim Ansari", + "author_inst": "University of Oxford" }, { - "author_name": "Ngo Ngoc Quang Minh", - "author_inst": "Children's Hospital 1, Ho Chi Minh City, Vietnam" + "author_name": "Emanuele Marchi", + "author_inst": "Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford, Oxford OX1 3SY, UK" }, { - "author_name": "Le Manh Hung", - "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam" + "author_name": "Narayan Ramamurthy", + "author_inst": "Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford, Oxford OX1 3SY, UK" }, { - "author_name": "Nghiem My Ngoc", - "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam" + "author_name": "Dominik Aschenbrenner", + "author_inst": "Translational Gastroenterology Unit, Nuffield Department of Medicine, University of Oxford, Oxford OX3 9DU, UK" }, { - "author_name": "Nguyen Tri Dung", - "author_inst": "Center for Disease Control and Prevention, Ho Chi Minh City, Vietnam" + "author_name": "Carl-Philipp Hackstein", + "author_inst": "Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford, Oxford OX1 3SY, UK" }, { - "author_name": "Dinh Nguyen Huy Man", - "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam" + "author_name": "- STOP-HCV consortium", + "author_inst": "-" }, { - "author_name": "Lam Anh Nguyet", - "author_inst": "OUCRU" + "author_name": "- ISARIC-4C Investigators", + "author_inst": "-" }, { - "author_name": "Le Thanh Hoang Nhat", - "author_inst": "OUCRU" + "author_name": "Shang-Kuan Lin", + "author_inst": "Wellcome Centre for Human Genetics, Roosevelt Dr, Headington, Oxford OX3 7BN" }, { - "author_name": "Le Nguyen Truc Nhu", - "author_inst": "OUCRU" + "author_name": "Rory Bowden", + "author_inst": "Wellcome Centre for Human Genetics, Roosevelt Dr, Headington, Oxford OX3 7BN" }, { - "author_name": "Nguyen Thi Han Ny", - "author_inst": "OUCRU" + "author_name": "Eshita Sharma", + "author_inst": "Wellcome Centre for Human Genetics, Roosevelt Dr, Headington, Oxford OX3 7BN" }, { - "author_name": "Nguyen Thi Thu Hong", - "author_inst": "OUCRU" + "author_name": "Vincent Pedergnana", + "author_inst": "French National Centre for Scientific Research (CNRS), Laboratory MIVEGEC (CNRS, IRD, UM), Montpellier, France" }, { - "author_name": "Evelyne Kestelyn", - "author_inst": "OUCRU" + "author_name": "Suresh Venkateswaran", + "author_inst": "Department of Pediatrics, Emory University School of Medicine and Children health care of Atlanta, Atlanta, USA" }, { - "author_name": "Nguyen Thi Phuong Dung", - "author_inst": "OUCRU" + "author_name": "Subra Kugathasan", + "author_inst": "Department of Pediatrics, Emory University School of Medicine and Children health care of Atlanta, Atlanta, USA" }, { - "author_name": "Nguyen Thanh Phong", - "author_inst": "Hospital for Tropical Diseases" + "author_name": "Angela Mo", + "author_inst": "Center for Integrative Genomics, Georgia Institute of Technology, Atlanta, USA" }, { - "author_name": "Tran Chan Xuan", - "author_inst": "Cu Chi Hospital, Ho Chi Minh City, Vietnam" + "author_name": "Greg Gibson", + "author_inst": "Center for Integrative Genomics, Georgia Institute of Technology, Atlanta, USA" }, { - "author_name": "Tran Tinh Hien", - "author_inst": "OUCRU" + "author_name": "John McLauchlan", + "author_inst": "MRC-University of Glasgow Centre for Virus Research, Sir Michael Stoker Building, University of Glasgow, Glasgow, G61 1qh," }, { - "author_name": "Tran Nguyen Hoang Tu", - "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam" + "author_name": "Eleanor Barnes", + "author_inst": "Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford, Oxford OX1 3SY, UK" }, { - "author_name": "Ronald B. Geskus", - "author_inst": "OUCRU" + "author_name": "John Kenneth Baillie", + "author_inst": "Genetics and Genomics, Roslin Institute, University of Edinburgh, Edinburgh EH25 9RG, UK." }, { - "author_name": "Tran Tan Thanh", - "author_inst": "OUCRU" + "author_name": "Sarah Teichmann", + "author_inst": "Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton Cambridge, CB10 1SA UK" }, { - "author_name": "Nguyen Thanh Truong", - "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam" + "author_name": "Alex Mentzer", + "author_inst": "Wellcome Centre for Human Genetics, Roosevelt Dr, Headington, Oxford OX3 7BN" }, { - "author_name": "Nguyen Tan Binh", - "author_inst": "Department of Health, Ho Chi Minh City, Vietnam" + "author_name": "John Todd", + "author_inst": "Wellcome Centre for Human Genetics, Roosevelt Dr, Headington, Oxford OX3 7BN" }, { - "author_name": "Tang Chi Thuong", - "author_inst": "Department of Health, Ho Chi Minh City, Vietnam" + "author_name": "Julian Knight", + "author_inst": "Wellcome Centre for Human Genetics, Roosevelt Dr, Headington, Oxford OX3 7BN" }, { - "author_name": "Guy Thwaites", - "author_inst": "OUCRU" + "author_name": "Holm Uhlig", + "author_inst": "Translational Gastroenterology Unit, Nuffield Department of Medicine, University of Oxford, Oxford OX3 9DU, UK" }, { - "author_name": "Le Van Tan", - "author_inst": "OUCRU" + "author_name": "Paul Klenerman", + "author_inst": "Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford, Oxford OX1 3SY, UK" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1488296,45 +1488458,65 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.24.20077388", - "rel_title": "Hypertension and Renin-Angiotensin-Aldosterone System Inhibitors in Patients with Covid-19", + "rel_doi": "10.1101/2020.04.23.20077644", + "rel_title": "Epidemiological and clinical characteristics of discharged patients infected with SARS-CoV-2 on the Qinghai plateau", "rel_date": "2020-04-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20077388", - "rel_abs": "IntroductionCOVID-19 disproportionately affects those with comorbidities and the elderly. Hypertension is the most common pre-existing condition amongst COVID-19 patients. Upregulation of the renin-angiotensin-aldosterone system (RAAS) is common in hypertensive patients and may promote inflammation and ensuing cytokine storm in COVID-19. It is unknown whether RAAS inhibition with ACE1 inhibitors or angiotensin-receptor blockers (ARB) can be harmful or beneficial.\n\nMethodsWithin Hackensack Meridian Health network, the largest healthcare provider in New Jersey, we performed a retrospective, multicenter, convenience sampling study of hospitalized COVID-19 patients. Demographics, clinical characteristics, treatments, and outcomes were manually abstracted. Fishers exact tests, and logistic regression were performed.\n\nResultsAmong 3017 hospitalized COVID-19 patients, 1584 (52.5%) carried a diagnosis of hypertension. In the discharged or deceased cohort, the overall mortality was significantly increased at 35% vs 13% among COVID-19 patients with hypertension. However, when adjusted for age, the effect of hypertension on mortality was greatly diminished, with a reduction in odds-ratio by over half; and completely disappeared when adjusted for other major covariates. The mortality rates were lower for hypertensive patients prescribed ACE1 (27%, p=0.001) or ARBs (33%, p=0.12) compared to other anti-hypertensive agents (39%) in the unadjusted analyses. RAAS inhibitor therapy appeared protective compared to other anti-hypertensive agents (p=0.001).\n\nConclusionsWhile our results are limited by the retrospective nature of our study and by potential confounders, our data argue against a harmful effect of RAAS inhibition and support the HFSA/AHA/ACC joint statement recommending continuing ACE1 and ARB therapy in hypertensive COVID-19 patients.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.23.20077644", + "rel_abs": "Since the outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in Wuhan, a series of confirmed cases of COVID-19 were found on the Qinghai-Tibet plateau. We aimed to describe the epidemiological, clinical characteristics, and outcomes of all confirmed cases in Qinghai, a province at high altitude. With efficient measures to stop the spread of coronavirus, no new cases were found in Qinghai Province for 60 consecutive days between Feb 6 and April 6, 2020. Of all 18 patients with confirmed SARS-CoV-2 infection, 15 patients comprising 4 transmission clusters were identified. Three patients were infected by direct contact without travel history to Wuhan. Seven patients were asymptomatic on admission. Of 18 patients, 10 patients showed bilateral pneumonia and 2 patients showed no abnormalities. Three patients with comorbidities such as hypertension, liver diseases or diabetes developed severe illness. High C-reactive protein levels and elevations of both ALT and AST were observed in 3 severely ill patients on admission. All 18 patients were eventually discharged, including the 3 severe patients who recovered after treatment with non-invasive mechanical ventilation, convalescent plasma and other therapies. Our findings confirmed human-to-human transmission of SARS-CoV-2 in clusters. The strategies of early diagnosis, early isolation, and early treatment are important to prevent the spread of COVID-19 and improve the cure rate. Patients with comorbidities are more likely to develop severe illness and could benefit from convalescent plasma transfusion.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Andrew Ip", - "author_inst": "Division of Outcomes and Value Research, John Theurer Cancer Center at Hackensack University Medical Center" + "author_name": "AIqi Xi", + "author_inst": "The Fourth People Hospital of Qinghai Province" }, { - "author_name": "Kaushal Parikh", - "author_inst": "Hackensack University Medical Center" + "author_name": "Zhuo Ma", + "author_inst": "The Fourth People Hospital of Qinghai Province" }, { - "author_name": "Joseph E Parrillo", - "author_inst": "Hackensack University Medical Center" + "author_name": "Jingtao Dai", + "author_inst": "The Fourth People Hospital of Qinghai Province" }, { - "author_name": "Shivam Mathura", - "author_inst": "COTA" + "author_name": "Yuehe Ding", + "author_inst": "The Fourth People Hospital of Qinghai Province" }, { - "author_name": "Eric Hansen", - "author_inst": "COTA" + "author_name": "Xiuzhen Ma", + "author_inst": "The Fourth People Hospital of Qinghai Province" }, { - "author_name": "Ihor S Sawczuk", - "author_inst": "Hackensack Meridian Health" + "author_name": "Xiaoli Ma", + "author_inst": "The Fourth People Hospital of Qinghai Province" }, { - "author_name": "Stuart L Goldberg", - "author_inst": "Division of Outcomes and Value Research, John Theurer Cancer Center at Hackensack University Medical Center" + "author_name": "Xiaoyi Wang", + "author_inst": "The Fourth People Hospital of Qinghai Province" + }, + { + "author_name": "Lianmeng Shi", + "author_inst": "The Third People Hospital of Xining" + }, + { + "author_name": "Huanying Bai", + "author_inst": "The Third People Hospital of Xining" + }, + { + "author_name": "Hongying Zheng", + "author_inst": "The Third People Hospital of Xining" + }, + { + "author_name": "Eric Nuermberger", + "author_inst": "Johns Hopkins University School of Medicine" + }, + { + "author_name": "Jian Xu", + "author_inst": "Beijing Chest Hospital, Capital Medical University; The Fourth People Hospital of Qinghai Province" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1489698,29 +1489880,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.24.20078022", - "rel_title": "Investigating duration and intensity of Covid-19 social-distancing strategies", + "rel_doi": "10.1101/2020.04.24.20077958", + "rel_title": "A model for 2019-nCoV infection with treatment", "rel_date": "2020-04-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20078022", - "rel_abs": "The exponential character of the recent Covid-19 outbreak requires a change in strategy from containment to mitigation. Meanwhile, most countries apply social distancing with the objective to keep the number of critical cases below the capabilities of the health care system. Due to the novelty and rapid spread of the virus, an a priori assessment of this strategy was not possible. In this study, we present a model-based systems analysis to assess the effectiveness of social distancing measures in terms of intensity and duration of application. Results show a super-linear scaling between intensity (percent contact reduction) and required duration of application to have an added value (lower fatality rate). This holds true for an effective reproduction of R > 1 and is reverted for R < 1. If R is not reduced below 1, secondary effects of required long-term isolation are likely to unravel the added value of disease mitigation. If an extinction is not feasible, we recommend moderate social-distancing that is well balanced against capability limits of national health-care systems.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20077958", + "rel_abs": "The current emergence of coronavirus (SARS-CoV-2) puts the world in threat. The structural research on the receptor recognition by SARS-CoV-2 has identified the key interactions between SARS-CoV-2 spike protein and its host (epithelial cell) receptor, also known as angiotensin-converting enzyme 2 (ACE2). It controls both the crossspecies and human-to-human transmissions of SARS-CoV-2. In view of this, we propose and analyze a mathematical model for investigating the effect of CTL responses over the viral mutation to control the viral infection when a postinfection immunostimulant drug (pidotimod) is administered at regular intervals. Dynamics of the system with and without impulses have been analyzed using the basic reproduction number. This study shows that the proper dosing interval and drug dose both are important to eradicate the viral infection.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Christian Neuwirth", - "author_inst": "Interfaculty Department of Geoinformatics - Z_GIS, University of Salzburg" + "author_name": "Amar Nath Chatterjee", + "author_inst": "K.L.S. COLLEGE NAWADA" }, { - "author_name": "Christoph Gruber", - "author_inst": "Center for Computational Material Science, Institute of Applied Physics, Vienna University of Technology" - }, - { - "author_name": "Thomas Murphy", - "author_inst": "Interfaculty Department of Geoinformatics - Z_GIS, University of Salzburg" + "author_name": "Fahad Al Basir", + "author_inst": "Asansol Girls' College" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1491492,55 +1491670,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.04.23.20076935", - "rel_title": "Association of Digestive Symptoms and Hospitalization in Patients with SARS-CoV-2 Infection", + "rel_doi": "10.1101/2020.04.23.20076943", + "rel_title": "Variation in COVID-19 Outbreaks at U.S. State and County Levels", "rel_date": "2020-04-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.23.20076935", - "rel_abs": "BackgroundHigh rates of concurrent gastrointestinal manifestations have been noted in patients with COVID-19, however the association between these digestive manifestations and need for hospitalization has not been established.\n\nMethodsFollowing expedited approval from our Institutional Review Board, we analyzed retrospectively collected data from consecutive patients with confirmed COVID-19 based on a positive polymerase chain reaction testing at our institution from March 03, 2020 to April 7, 2020. Baseline demographic, clinical, laboratory and patient-reported symptom data were collected at presentation in the emergency room. Multivariable logistic regression analyses were performed to evaluate the association between hospitalization and presence of gastrointestinal symptoms.\n\nResultsDuring this study period, we identified 207 consecutive patients with confirmed COVID-19. 34.5% noted concurrent gastrointestinal symptoms; of which 90% of gastrointestinal symptoms were mild. In a multivariate regression model controlled for demographics and disease severity, an increased risk for hospitalization was noted in patients with any gastrointestinal symptom (adjusted OR 4.84 95% CI: 1.68-13.94]. Diarrhea was associated with a seven-fold higher likelihood for hospitalization (adjusted OR=7.58, 95% CI: 2.49-20.02, P <0.001) and nausea or vomiting had a four times higher odds. (adjusted OR 4.39, 95% CI: 1.61-11.4, P = 0.005).\n\nConclusionWe demonstrate that a significant portion of COVID19 patients have concurrent mild gastrointestinal symptoms and that the presence of these digestive symptoms is associated with a need for hospitalization. With the current focus on streamlining triaging efforts, first responders and frontline providers should consider assessing for digestive symptoms in their initial clinical evaluation and decision-making.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.23.20076943", + "rel_abs": "BackgroundThe COVID-19 pandemic poses an unprecedented threat to the health and economic prosperity of the worlds population. Yet, some countries or regions within a country appear to be affected in different ways.\n\nObjectivesThis research aims to understand whether the outbreak varies significantly between U.S. states and counties.\n\nMethodsA statistical model is estimated using publicly available outbreak data in the U.S., and regional differences are statistically analyzed.\n\nResultsThere is significant variance in outbreak data between U.S. states and counties. At the state level, the outbreak rate follows a normal distribution with an average relative growth rate of 0.197 (doubling time 3.518 days). But there is a low degree of reliability between state-wide and county-specific data reported (ICC = 0.169, p < 0.001), with a bias of 0.070 (standard deviation 0.062) as shown with a Bland-Altman plot.\n\nConclusionsThe results emphasize the need for policy makers to look at the pandemic from the smallest population subdivision possible, so that countermeasures can be implemented, and critical resources provided effectively. Further research is needed to understand the reasons for these regional differences.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "George Cholankeril", - "author_inst": "Stanford University School of Medicine" - }, - { - "author_name": "Alexander Podboy", - "author_inst": "Stanford University" - }, - { - "author_name": "Vickie Aivaliotas", - "author_inst": "Stanford University" - }, - { - "author_name": "Edward A Pham", - "author_inst": "Stanford University" - }, - { - "author_name": "Branden Tarlow", - "author_inst": "Stanford University" - }, - { - "author_name": "Sean Spencer", - "author_inst": "Stanford University" - }, - { - "author_name": "Donghee Kim", - "author_inst": "Stanford University" - }, - { - "author_name": "Ann Hsing", - "author_inst": "Stanford University" + "author_name": "Wolfgang Messner", + "author_inst": "University of South Carolina" }, { - "author_name": "Aijaz Ahmed", - "author_inst": "Stanford University" + "author_name": "Sarah E Payson", + "author_inst": "University of South Carolina" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.28.066761", @@ -1492994,29 +1493144,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.22.20076281", - "rel_title": "Nowcasting and Forecasting the Spread of COVID-19 in Iran", + "rel_doi": "10.1101/2020.04.23.20075796", + "rel_title": "COVID-19 serial interval estimates based on confirmed cases in public reports from 86 Chinese cities", "rel_date": "2020-04-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.22.20076281", - "rel_abs": "IntroductionAs of early December 2019, COVID-19, a disease induced by SARS-COV-2, has started spreading, originated in Wuhan, China, and now on, have infected more than 2 million individuals throughout the world.\n\nPurposeThis study aimed to nowcast the COVID-19 outbreak throughout Iran and to forecast the trends of the disease spreading in the upcoming month.\n\nMethodsThe cumulative incidence and fatality data were extracted from official reports of the National Ministry of Health and Medical Educations of Iran. To formulate the outbreak dynamics, six phenomenological models, as well as a modified mechanistic Susciptible-Exposed-Infectious-Recovered (SEIR) model, were implemented. The models were calibrated with the integrated data, and trends of the epidemic in Iran was then forecasted for the next month.\n\nResultsThe final outbreak size calculated by the best fitted phenomenological models was estimated to be in the range of 68,486 to 118,923 cases; however, the calibrated SEIR model estimated that the outbreak would rage again, starting from April 26. Moreover, projected by the mechanistic model, approximately half of the infections have undergone undetected.\n\nConclusionAlthough the advanced phenomenological models perfectly fitted the data, they are incapable of applying behavioral aspects of the outbreak and hence, are not reliable enough for authorities decision adoptions. In contrast, the mechanistic SEIR model alarms that the COVID-19 outbreak in Iran may peak for the second time, consequent to lifting the control measures. This implies that the government may implement a more granular decision making to control the outbreak.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.23.20075796", + "rel_abs": "As a novel coronavirus (COVID-19) continues to spread widely and claim lives worldwide, its transmission characteristics remain uncertain. Here, we present and analyze the serial intervals-the time period between the onset of symptoms in an index (infector) case and the onset of symptoms in a secondary (infectee) case-of 339 confirmed cases of COVID-19 identified from 264 cities in mainland China prior to February 19, 2020. Here, we provide the complete dataset in both English and Chinese to support further COVID-19 research and modeling efforts.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Hamidreza Masjedi", - "author_inst": "Shahid Sadoughi University of Medical Sciences and Health Services" + "author_name": "Zhanwei Du", + "author_inst": "University of Texas at Austin" }, { - "author_name": "Jomar Fajardo Rabajante", - "author_inst": "University of the Philippines Los Banos" + "author_name": "xiaoke Xu", + "author_inst": "Dalian Minzu university" + }, + { + "author_name": "Ye Wu", + "author_inst": "Beijing Normal University" }, { - "author_name": "Fatemeh Bahranizadd", - "author_inst": "Shahid Sadoughi University of Medical Sciences and Health Services" + "author_name": "Lin Wang", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Benjamin J Cowling", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Mohammad Hosein Zare", - "author_inst": "Shahid Sadoughi University of Medical Sciences and Health Services" + "author_name": "Lauren Ancel Meyers", + "author_inst": "The University of Texas at Austin" } ], "version": "1", @@ -1493980,31 +1494138,59 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2020.04.23.057307", - "rel_title": "Open Access and Altmetrics in the pandemic age: Forescast analysis on COVID-19 related literature", + "rel_doi": "10.1101/2020.04.26.061705", + "rel_title": "Structural Basis of RNA Cap Modification by SARS-CoV-2 Coronavirus", "rel_date": "2020-04-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.23.057307", - "rel_abs": "We present an analysis on the uptake of open access on COVID-19 related literature as well as the social media attention they gather when compared with non OA papers. We use a dataset of publications curated by Dimensions and analyze articles and preprints. Our sample includes 11,686 publications of which 67.5% are openly accessible. OA publications tend to receive the largest share of social media attention as measured by the Altmetric Attention Score. 37.6% of OA publications are bronze, which means toll journals are providing free access. MedRxiv contributes to 36.3% of documents in repositories but papers in BiorXiv exhibit on average higher AAS. We predict the growth of COVID-19 literature in the following 30 days estimating ARIMA models for the overall publications set, OA vs. non OA and by location of the document (repository vs. journal). We estimate that COVID-19 publications will double in the next 20 days, but non OA publications will grow at a higher rate than OA publications. We conclude by discussing the implications of such findings on the dissemination and communication of research findings to mitigate the coronavirus outbreak.Competing Interest StatementThe authors have declared no competing interest.View Full Text", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.26.061705", + "rel_abs": "The novel severe acute respiratory syndrome coronoavirus-2 (SARS-CoV-2), the causative agent of COVID-19 illness, has caused over 2 million infections worldwide in four months. In SARS coronaviruses, the non-structural protein 16 (nsp16) methylates the 5-end of virally encoded mRNAs to mimic cellular mRNAs, thus protecting the virus from host innate immune restriction. We report here the high-resolution structure of a ternary complex of full-length nsp16 and nsp10 of SARS-CoV-2 in the presence of cognate RNA substrate and a methyl donor, S-adenosyl methionine. The nsp16/nsp10 heterodimer was captured in the act of 2-O methylation of the ribose sugar of the first nucleotide of SARS-CoV-2 mRNA. We reveal large conformational changes associated with substrate binding as the enzyme transitions from a binary to a ternary state. This structure provides new mechanistic insights into the 2-O methylation of the viral mRNA cap. We also discovered a distantly located ligand-binding site unique to SARS-CoV-2 that may serve as an alternative target site for antiviral development.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Daniel Torres-Salinas", - "author_inst": "Universidad de Granada" + "author_name": "Thiruselvam Viswanathan", + "author_inst": "University of Texas Health San Antonio, TX, USA" }, { - "author_name": "Nicolas Robinson-Garcia", - "author_inst": "University of Delft" + "author_name": "Shailee Arya", + "author_inst": "University of Texas Health San Antonio, TX, USA" }, { - "author_name": "Pedro A Castillo-Valdivieso", - "author_inst": "Universidad de Granada" + "author_name": "Siu-Hong Chan", + "author_inst": "New England Biolabs, MA, USA" + }, + { + "author_name": "Shan Qi", + "author_inst": "University of Texas Health San Antonio, TX, USA" + }, + { + "author_name": "Nan Dai", + "author_inst": "New England Biolabs, MA, USA" + }, + { + "author_name": "Robert A Hromas", + "author_inst": "University of Texas Health San Antonio, TX, USA" + }, + { + "author_name": "Jun-Gyu Park", + "author_inst": "Texas Biomedical Research Institute, San Antonio, TX, USA" + }, + { + "author_name": "Fatai Oladunni", + "author_inst": "Texas Biomedical Research Institute, San Antonio, TX, USA" + }, + { + "author_name": "Luis Martinez-Sobrido", + "author_inst": "Texas Biomedical Research Institute, San Antonio, TX, USA" + }, + { + "author_name": "Yogesh K Gupta", + "author_inst": "University of Texas Health San Antonio, TX, USA" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "scientific communication and education" + "category": "biophysics" }, { "rel_doi": "10.1101/2020.04.26.062406", @@ -1495398,293 +1495584,53 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.04.22.20074336", - "rel_title": "An international characterisation of patients hospitalised with COVID-19 and a comparison with those previously hospitalised with influenza", + "rel_doi": "10.1101/2020.04.21.20074633", + "rel_title": "The role of comorbidities and clinical predictors of severe disease in COVID-19: a systematic review and meta-analysis", "rel_date": "2020-04-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.22.20074336", - "rel_abs": "BackgroundIn this study we phenotyped individuals hospitalised with coronavirus disease 2019 (COVID-19) in depth, summarising entire medical histories, including medications, as captured in routinely collected data drawn from databases across three continents. We then compared individuals hospitalised with COVID-19 to those previously hospitalised with influenza.\n\nMethodsWe report demographics, previously recorded conditions and medication use of patients hospitalised with COVID-19 in the US (Columbia University Irving Medical Center [CUIMC], Premier Healthcare Database [PHD], UCHealth System Health Data Compass Database [UC HDC], and the Department of Veterans Affairs [VA OMOP]), in South Korea (Health Insurance Review & Assessment [HIRA]), and Spain (The Information System for Research in Primary Care [SIDIAP] and HM Hospitales [HM]). These patients were then compared with patients hospitalised with influenza in 2014-19.\n\nResults34,128 (US: 8,362, South Korea: 7,341, Spain: 18,425) individuals hospitalised with COVID-19 were included. Between 4,811 (HM) and 11,643 (CUIMC) unique aggregate characteristics were extracted per patient, with all summarised in an accompanying interactive website (http://evidence.ohdsi.org/Covid19CharacterizationHospitalization/). Patients were majority male in the US (CUIMC: 52%, PHD: 52%, UC HDC: 54%, VA OMOP: 94%,) and Spain (SIDIAP: 54%, HM: 60%), but were predominantly female in South Korea (HIRA: 60%). Age profiles varied across data sources. Prevalence of asthma ranged from 4% to 15%, diabetes from 13% to 43%, and hypertensive disorder from 24% to 70% across data sources. Between 14% and 33% were taking drugs acting on the renin-angiotensin system in the 30 days prior to hospitalisation. Compared to 81,596 individuals hospitalised with influenza in 2014-19, patients admitted with COVID-19 were more typically male, younger, and healthier, with fewer comorbidities and lower medication use.\n\nConclusionsWe provide a detailed characterisation of patients hospitalised with COVID-19. Protecting groups known to be vulnerable to influenza is a useful starting point to minimize the number of hospital admissions needed for COVID-19. However, such strategies will also likely need to be broadened so as to reflect the particular characteristics of individuals hospitalised with COVID-19.", - "rel_num_authors": 69, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.21.20074633", + "rel_abs": "BackgroundCOVID_19 is unpredictable due to non-specific symptoms and clinical course diversity in different individuals. We analyzed studies regarding the factors associated with severe status of the disease to identify unique findings in severely affected patients.\n\nMethodsWe systematically searched the electronic databases, including PubMed, Scopus, EMBASE, Web of Science, and Google Scholar from inception to 12th of March 2020. Cochranes Q and I-square statistics were used to assess the existence of heterogeneity between the included studies. We used the random-effects model to pool the odds ratios (ORs) at 95% confidence intervals (CIs).\n\nResultsSeventeen articles out of 3009 citations were included. These contained 3189 patients, of whom 732 were severely affected (severe group) and 3189 were in non-severe group. Using the random-effects model, our meta-analyses showed that the odds of comorbidities, including COPD, DM, HTN, CVD, CKD, and symptoms, including dyspnea, dizziness, anorexia, and cough, were significantly higher among the severe group compared with the non-severe group. There were no significant changes in odds of CVA, liver disease, immunodeficiency/immunosuppression, fever, fatigue, myalgia, headache, diarrhea, sore throat, nasal congestion, sputum, nausea, vomiting, chest pain between the two groups.\n\nConclusionsEarly recognition and intervention can be critical in management, and might stop progression to severe disease. Predictive symptoms and comorbidities can be used as a predictor in patients who are at risk of severe disease.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Edward Burn", - "author_inst": "University of Oxford" - }, - { - "author_name": "Seng Chan You", - "author_inst": "Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea" - }, - { - "author_name": "Anthony Sena", - "author_inst": "Janssen Research & Development, Titusville, NJ, USA" - }, - { - "author_name": "Kristin Kostka", - "author_inst": "Real World Solution, IQVIA, Cambridge, MA, USA" - }, - { - "author_name": "Hamed Abedtash", - "author_inst": "Eli Lilly and Company, Indianapolis, IN, USA" - }, - { - "author_name": "Maria Tereza F. Abrahao", - "author_inst": "Faculty of Medicine, University of Sao Paulo, Sao Paulo, Brazil" - }, - { - "author_name": "Amanda Alberga", - "author_inst": "Observational Health Data Sciences and Informatics Network, Alberta, Canada" - }, - { - "author_name": "Heba Alghoul", - "author_inst": "Faculty of Medicine, Islamic University of Gaza, Palestine" - }, - { - "author_name": "Osaid Alser", - "author_inst": "Massachusetts General Hospital, Harvard Medical School, Boston, USA" - }, - { - "author_name": "Thamir M Alshammari", - "author_inst": "Medication Safety Research Chair, King Saud University, Riyadh, Saudi Arabia" - }, - { - "author_name": "Maria Aragon", - "author_inst": "Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain" - }, - { - "author_name": "Carlos Areia", - "author_inst": "Nuffield Department of Clinical Neurosciences, University of Oxford, UK" - }, - { - "author_name": "Juan M Banda", - "author_inst": "Department of Computer Science, Georgia State Univeristy, Atlanta" - }, - { - "author_name": "Jaehyeong Cho", - "author_inst": "Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Republic of Korea" - }, - { - "author_name": "Aedin C Culhane", - "author_inst": "Department of Data Sciences, Dana-Farber Cancer Institute, Department of Biostatistics, Harvard TH Chan School of Public Health, Boston" - }, - { - "author_name": "Alexander Davydov", - "author_inst": "Medical Ontology Solutions, Odysseus Data Services Inc., Cambridge, MA, USA" - }, - { - "author_name": "Frank J DeFalco", - "author_inst": "Janssen Research and Development, Titusville, NJ, USA" - }, - { - "author_name": "Talita Duarte-Salles", - "author_inst": "Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol)" - }, - { - "author_name": "Scott L DuVall", - "author_inst": "Department of Veterans Affairs" - }, - { - "author_name": "Thomas Falconer", - "author_inst": "Department of Biomedical Informatics, Columbia University, New York, NY" - }, - { - "author_name": "Sergio Fernandez-Bertolin", - "author_inst": "Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain," - }, - { - "author_name": "Weihua Gao", - "author_inst": "Health Economics and Outcomes Research, AbbVie, North Chicago, US" - }, - { - "author_name": "Asieh Golozar", - "author_inst": "Pharmacoepidemiology, Regeneron, NY" - }, - { - "author_name": "Jill Hardin", - "author_inst": "Janssen Research & Development, Titusville, NJ, USA" - }, - { - "author_name": "George Hripcsak", - "author_inst": "Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA" - }, - { - "author_name": "Vojtech Huser", - "author_inst": "National Library of Medicine, National Institutes of Health, MD, USA" - }, - { - "author_name": "Hokyun Jeon", - "author_inst": "Department of Biomedical Informatics, Ajou University School of Medicine" - }, - { - "author_name": "Yonghua Jing", - "author_inst": "Health Economics and Outcomes Research, AbbVie, North Chicago, US," - }, - { - "author_name": "Chi Young Jung", - "author_inst": "Daegu Catholic University Medical Center" - }, - { - "author_name": "Benjamin Skov Kaas-Hansen", - "author_inst": "Clinical Pharmacology Unit, Zealand University Hospital, Denmark" - }, - { - "author_name": "Denys Kaduk", - "author_inst": "Odysseus Data Services, Inc., MA, Cambridge" - }, - { - "author_name": "Seamus Kent", - "author_inst": "National Institute for Health and Care Excellence, UK" - }, - { - "author_name": "Yeesuk Kim", - "author_inst": "Department of Orthopaedic Surgery, College of Medicine, Hanyang University, Seoul, Korea" - }, - { - "author_name": "Spyros Kolovos", - "author_inst": "Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford" - }, - { - "author_name": "Jennifer Lane", - "author_inst": "Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford" - }, - { - "author_name": "Hyejin Lee", - "author_inst": "Bigdata Department, Health Insurance Review & Assessment Service" - }, - { - "author_name": "Kristine E. Lynch", - "author_inst": "Department of Veterans Affairs" - }, - { - "author_name": "Rupa Makadia", - "author_inst": "Janssen Research & Development, Titusville, NJ, USA" - }, - { - "author_name": "Michael E. Matheny", - "author_inst": "Department of Veterans Affairs" - }, - { - "author_name": "Paras Mehta", - "author_inst": "College of Medicine, University of Arizona" - }, - { - "author_name": "Daniel R. Morales", - "author_inst": "Division of Population Health and Genomics, University of Dundee" - }, - { - "author_name": "Karthik Natarajan", - "author_inst": "Department of Biomedical Informatics, Columbia University, New York, NY" - }, - { - "author_name": "Fredrik Nyberg", - "author_inst": "School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden" - }, - { - "author_name": "Anna Ostropolets", - "author_inst": "Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA" - }, - { - "author_name": "Rae Woong Park", - "author_inst": "Ajou University" - }, - { - "author_name": "Jimyung Park", - "author_inst": "Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea" - }, - { - "author_name": "Jose D. Posada", - "author_inst": "Department of Medicine, School of Medicine, Stanford University" - }, - { - "author_name": "Albert Prats-Uribe", - "author_inst": "Centre for Statistics in Medicine. Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK" - }, - { - "author_name": "Gowtham A. Rao", - "author_inst": "Janssen Research & Development, Titusville, NJ, USA" - }, - { - "author_name": "Christian Reich", - "author_inst": "Real World Solution, IQVIA, Cambridge, MA, USA" - }, - { - "author_name": "Yeunsook Rho", - "author_inst": "Bigdata Department, Health Insurance Review & Assessment Service" - }, - { - "author_name": "Peter Rijnbeek", - "author_inst": "Erasmus MC, Rotterdam, Netherlands" - }, - { - "author_name": "Lisa M. Schilling", - "author_inst": "Data Science to Patient Value Program, Department of Medicine, University of Colorado Anschutz Medical Campus" - }, - { - "author_name": "Martijn Schuemie", - "author_inst": "Janssen Research & Development, Titusville, NJ, USA" - }, - { - "author_name": "Nigam H. Shah", - "author_inst": "Department of Medicine, School of Medicine, Stanford University" - }, - { - "author_name": "Azza Shoaibi", - "author_inst": "Janssen Research & Development, Titusville, NJ, USA" - }, - { - "author_name": "Seokyoung Song", - "author_inst": "Department of Anesthesiology and Pain Medicine, Catholic University of Daegu, School of medicine" - }, - { - "author_name": "Matthew Spotnitz", - "author_inst": "Department of Biomedical Informatics, Columbia University Irving Medical Center, New York" - }, - { - "author_name": "Marc A. Suchard", - "author_inst": "Department of Biostatistics, University of California, Los Angeles" - }, - { - "author_name": "Joel Swerdel", - "author_inst": "Janssen Research & Development, Titusville, NJ, USA" - }, - { - "author_name": "David Vizcaya", - "author_inst": "Bayer pharmaceuticals, Barcelona, Spain" + "author_name": "Reza Tabrizi", + "author_inst": "Health Policy Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Salvatore Volpe", - "author_inst": "Department of Biomedical Informatics, Columbia University, New York, NY" + "author_name": "Kamran B Lankarani", + "author_inst": "Health Policy Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Haini Wen", - "author_inst": "Shuguang Hospital affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China" + "author_name": "Peyman Nowrouzi-sohrabi", + "author_inst": "Department of Biochemistry, Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Andrew E Williams", - "author_inst": "Tufts Institute for Clinical Research and Health Policy Studies" + "author_name": "Mojtaba Shabani-Borujeni", + "author_inst": "Department of Clinical Pharmacy, Faculty of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Belay B Yimer", - "author_inst": "Centre for Epidemiology Versus Arthritis, Manchester Academic Health Science Centre, The University of Manchester, Manchester" + "author_name": "Shahla Rezaei", + "author_inst": "School of Nutrition and Food Sciences, Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Lin Zhang", - "author_inst": "School of Public Health, Peking Union Medical College, Chinese Academy of Medical Sciences" + "author_name": "Mahnaz Hosseini-bensenjan", + "author_inst": "Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Oleg Zhuk", - "author_inst": "Medical Ontology Solutions, Odysseus Data Services Inc., Cambridge, MA, USA" + "author_name": "Sina vakili", + "author_inst": "Department of Biochemistry, Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Daniel Prieto-Alhambra", - "author_inst": "Centre for Statistics in Medicine, NDORMS, University of Oxford" + "author_name": "Seyed Taghi Heydari", + "author_inst": "Health Policy Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Patrick Ryan", - "author_inst": "Janssen Research & Development, Titusville, NJ, USA" + "author_name": "Mohammad Ali Ashraf", + "author_inst": "Shiraz University of Medical Sciences" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1497036,79 +1496982,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.24.060418", - "rel_title": "Treating Influenza and SARS-CoV-2 via mRNA-encoded Cas13a", + "rel_doi": "10.1101/2020.04.20.20067538", + "rel_title": "Modest effects of contact reduction measures on the reproduction number of SARS-CoV-2 in the most affected European countries and the US", "rel_date": "2020-04-24", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.24.060418", - "rel_abs": "Here, Cas13a has been used to target and mitigate influenza virus A (IAV) and SARS-CoV-2 using a synthetic mRNA-based platform. CRISPR RNAs (crRNA) against PB1 and highly conserved regions of PB2 were screened in conjunction with mRNA-encoded Cas13a. Screens were designed such that only guides that decreased influenza RNA levels in a Cas13-mediated fashion, were valid. Cas13a mRNA and validated guides, delivered post-infection, simulating treatment, were tested in combination and across multiplicities of infection. Their function was also characterized over time. Similar screens were performed for guides against SARS-CoV-2, yielding multiple guides that significantly impacted cytopathic effect. Last, the approach was utilized in vivo, demonstrating the ability to degrade influenza RNA in a mouse model of infection, using polymer-formulated, nebulizer-based mRNA delivery. Our findings demonstrate the applicability of Cas13a in mitigating respiratory infections both in vitro and in a mouse model, paving the way for future therapeutic use.", - "rel_num_authors": 15, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.20.20067538", + "rel_abs": "Population density, behaviour and cultural habits strongly influence the spread of pathogens. Consequently, key epidemiological parameters may vary from country to country. Many estimates of SARS-CoV-2 and COVID-19 strongly depend on testing frequency and case definitions. The fatal cases due to SARS-CoV2 could be a more reliable parameter, since missing of deaths is less likely. We analysed the dynamics of new infection and death cases to estimate the daily reproduction numbers (Rt) and the effectiveness of control measures in the most affected European Countries and the US. In summary, calculating Rt based on the daily number of deaths as well as of new infections may lead to more reliable estimates than those based on infection cases alone, as death based Rt are expected to be less susceptible to testing bias or limited capacities.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Emmeline L Blanchard", - "author_inst": "Georgia Institute of Technology and Emory University" - }, - { - "author_name": "Daryll Vanover", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "Swapnil Subhash Bawage", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "Pooja Munnilal Tiwari", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "Laura Rotolo", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "Jared Beyersdorf", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "Hannah E. Peck", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "Nicholas C Bruno", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "Robert Hincapie", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "M. G. Finn", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "Frank Michel", - "author_inst": "University of Georgia" - }, - { - "author_name": "Eric R. Lafontaine", - "author_inst": "University of Georgia" - }, - { - "author_name": "Robert J Hogan", - "author_inst": "University of Georgia" + "author_name": "Armin Ensser", + "author_inst": "Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander Universitaet Erlangen-Nuernberg (FAU)" }, { - "author_name": "Chiara Zurla", - "author_inst": "Georgia Institute of Technology" + "author_name": "Pia \u00dcberla", + "author_inst": "Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander Universitaet Erlangen-Nuernberg (FAU)" }, { - "author_name": "Philip J Santangelo", - "author_inst": "Georgia Institute of Technology" + "author_name": "Klaus \u00dcberla", + "author_inst": "Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander Universitaet Erlangen-Nuernberg (FAU)" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "bioengineering" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.04.24.059576", @@ -1498986,59 +1498884,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.20.20072322", - "rel_title": "COVID-19 pandemic: examining the faces of spatial differences in the morbidity and mortality in sub-Saharan Africa, Europe and USA.", + "rel_doi": "10.1101/2020.04.21.20074724", + "rel_title": "Clinical Characteristics and Risk factors for developed COVID-19 patients transferring to designated hospital from Jianghan Fangcang shelter Hospital: a retrospective, observational study", "rel_date": "2020-04-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.20.20072322", - "rel_abs": "BackgroundCOVID-19, the disease associated with the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is currently a global pandemic with several thousands of confirmed cases of infection and death. However, the death rate across affected countries shows variation deserving of critical evaluation.\n\nMethodsIn this study, we evaluated differentials in COVID-19 confirmed cases of infection and associated deaths of selected countries in Sub-Sahara Africa (Nigeria and Ghana), South Africa, Europe (Italy, Spain, Sweden and UK) and USA. Data acquired for various standard databases on mutational shift of the SARS-CoV-2 virus based on geographical location, BCG vaccination policy, malaria endemicity, climatic conditions (temperature), differential healthcare approaches were evaluated over a period of 45 days from the date of reporting the index case.\n\nResultsThe number of confirmed cases of infection and associated deaths in Sub-Sahara Africa were found to be very low compared to the very high values in Europe and USA over the same period. Recovery rate from COVID-19 is not correlated with the mutational attributes of the virus with the sequenced strain from Nigeria having no significant difference (p>0.05) from other geographical regions. Significantly higher (p<0.05) infection rate and mortality from COVID-19 were observed in countries (Europe and USA) without a current universal BCG vaccination policy compared to those with one (Sub-Sahara African countries). Countries with high malaria burden had significantly lower (p<0.05) cases of COVID-19 than those with low malaria burden. A strong negative correlation (-0.595) between mean annual temperature and COVID-19 infection and death was observed with 14.8% variances between temperature and COVID-19 occurrence among the countries. A clear distinction was observed in the COVID-19 disease management between the developed countries (Europe and USA) and Sub-Sahara Africa.\n\nConclusionsThe study established that the wide variation in the outcome of the COVID-19 disease burden in the selected countries are attributable largely to climatic condition (temperature) and differential healthcare approaches to management of the disease. We recommend consideration and mainstreaming of these findings for urgent intervention and management of COVID-19 across these continents.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.21.20074724", + "rel_abs": "BackgroundThe outbreak of coronavirus disease 2019 (COVID-19) has become a world-wide emergency. Fangcang shelter hospitals have been applied in COVID-19 to ease ongoing shortage of medical resources in Wuhan since February 2020.\n\nMethodThis study enrolled all cases (no=1848) with mild or moderate type of COVID-19 in Fangcang shelter hospital of Jianghan in Wuhan from Feb 5th to Mar 9th, 2020. Diagnosis of COVID-19 was based on the National health commission of China. Epidemiological history, comorbidity, vital signs, symptoms and signs were recorded in detail. Laboratory tests included biochemical indicators and nucleic acid tests by throat swabs have been performed as well.\n\nFindingA total of 1327 patients reached the criteria of isolation release. Meanwhile, 521 patients have been transferred to the designated hospitals for further treatment, including severe type, fever more than 3 days, and severe comorbidity. The case-severity rate (rate of mild or moderate type transforming to severe type) was 3.0% in the shelter hospital. The patients from mild or moderate type to severe type showed the following clinical characteristics: the median incubation (onset to shelter) period was 10 days; they were all symptomatic at admission; fever, cough, and fatigue were the most common symptoms; hypertension, diabetes and coronary heart diseases were common co-morbidities; most of the patients had elevated levels of CRP at ill onset with 33.3% over 10 mg per L; bilateral distribution and ground-glass opacity were the most common manifestations in chest CT.\n\nInterpretationThe potential risk factors of fever, fatigue, high level of C-reactive protein were the risk factors to identify the progression of COVID-19 patients with mild or moderate type. Fangcang shelter hospitals have substantially reduced the time from the onset of severe symptoms transfer to a designated hospital. Early application of the Fangcang shelter hospital may contribute to decrease the ratio of mild transforming to severe patients.\n\nFundingNo specific grant from any funding was applied to this research.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed from Nov 1, 2019, to Apr 8, 2020, for studies published in any language using the terms \"COVID-19\", \"coronavirus disease 2019\", \"novel coronavirus\", \"cabin hospital\", \"shelter hospital\". Five studies have been found about coronavirus disease 2019 (COVID-19) in shelter hospital or cabin hospital. Fangcang shelter hospital of Jianghan received the largest number of patients among Fangcang shelter hospitals in Wuhan. These studies were related to development of Fangcang shelter hospitals, explaining three key characteristics (rapid construction, massive scale, and low cost) and five essential functions (isolation, triage, basic medical care, frequent monitoring and rapid referral, and essential living and social engagement). To our knowledge, there are no studies to comprehensively investigate a cohort of mild COVID-19 patients transfer to designated hospital from shelter hospital and their distinctive clinical features. Since Fangcang shelter hospital is a novel public health strategy, we aimed to investigate the clinical characteristics and risk factors for developed COVID-19 patients transfer to the designated hospital in Jianghan Fangcang shelter Hospital.\n\nAdded value of this studyFrom Feb 5th to Mar 9th, a total of 1848 cases of mild or moderate type of COVID-19 were enrolled in Fangcang shelter hospital of Jianghan (Wuhan, China). Of these cases, 521 patients were transferred to designated hospitals. Rate of mild or moderate type transforming to severe type was 3.0 % (56/1848) in the Fangcang shelter hospital. The median incubation (onset to shelter) period was 10 days (IQR 8.0-16.0). Patients with fever on cabin admission, high level C-reactive protein were also associated with mild-to-severe. Early application of the shelter hospital may contribute to alleviate the shortage of medical resources and decrease the ratio of severe patients. Furthermore, Fangcang shelter hospitals are likely to have substantially reduced the time from the onset of severe symptoms to admission to a designated hospital. The clinical characteristics of patients transferred to the designated hospital were important for the revision of admission criteria of COVID patients in Fangcang shelter hospitals. Dynamic observation the risk factors of mild to severe patients is contribute to great value for early prognosis and treatment.\n\nImplications of all the available evidenceKeep vigilance of those mild patients whose had a fever over 38.0{degrees}C, cough and fatigue when they isolated at home. Fangcang shelter hospital could provide the rational strategy for isolation and triage of infected patients and decrease the family or community transmission cases.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Adebayo A Otitoloju", - "author_inst": "Department of Zoology, Ecotoxicology and Conservation Unit, Faculty of Science, University of Lagos, Lagos, Nigeria" + "author_name": "Yunfei Liao", + "author_inst": "Union Hospital,Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Ifeoma P Okafor", - "author_inst": "Community Health & Primary Care, College of Medicine, University of Lagos, Lagos, Nigeria" + "author_name": "Yong Feng", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Mayowa Fasona", - "author_inst": "Department of Geography, Faculty of Social Sciences, University of Lagos, Lagos, Nigeria" + "author_name": "Bo Wang", + "author_inst": "Wuhan No.1 Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Kafilat Adebola Bawa-Allah", - "author_inst": "Department of Zoology, Ecotoxicology & Conservation Unit, Faculty of Science, University of Lagos, Lagos, Nigeria" + "author_name": "Hanyu Wang", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Chukwuemeka Isanbor", - "author_inst": "Department of Chemistry, Faculty of Science, University of Lagos, Akoka, Lagos, Nigeria" + "author_name": "Jinsha Huang", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Chukwudozie Solomon Onyeka", - "author_inst": "Department of Cell Biology and Genetics, Faculty of Science, University of Lagos, Akoka, Lagos, Nigeria" + "author_name": "Yaxin Wu", + "author_inst": "First Clinical College, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Olawale S Folarin", - "author_inst": "Department of Zoology, Ecotoxicology & Conservation Unit, Faculty of Science, University of Lagos, Lagos, Nigeria" + "author_name": "Ziling Wu", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Taiwo O Adubi", - "author_inst": "Department of Zoology, Parasitology Unit, Faculty of Science, University of Lagos, Akoka, Lagos, Nigeria" + "author_name": "Xiao Chen", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Temitope O Sogbanmu", - "author_inst": "Department of Zoology, Ecotoxicology & Conservation Unit, Faculty of Science, University of Lagos, Lagos, Nigeria" + "author_name": "Chao Yang", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Anthony E Ogbeibu", - "author_inst": "Department of Animal and Environmental Biology, Faculty of Life Sciences, University of Benin, Benin City, Edo State, Nigeria" + "author_name": "Xinqiao Fu", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Hui Sun", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.04.20.20072157", @@ -1500296,49 +1500198,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.21.20074211", - "rel_title": "An Adaptive, Interacting, Cluster-Based Model Accurately Predicts the Transmission Dynamics of COVID-19", + "rel_doi": "10.1101/2020.04.20.20072629", + "rel_title": "Estimating the undetected infections in the Covid-19 outbreak by harnessing capture-recapture methods", "rel_date": "2020-04-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.21.20074211", - "rel_abs": "The SARS-CoV-2 driven disease, COVID-19, is presently a pandemic with increasing human and monetary costs. COVID-19 has put an unexpected and inordinate degree of pressure on healthcare systems of strong and fragile countries alike. In order to launch both containment and mitigation measures, each country requires accurate estimates of COVID-19 incidence as such preparedness allows agencies to plan efficient resource allocation and design control strategies. Here, we have developed a new adaptive, interacting, and cluster-based mathematical model to predict the granular trajectory COVID-19. We have analyzed incidence data from three currently afflicted countries of Italy, the United States of America, and India, and show that our approach predicts state-wise COVID-19 spread for each country with high accuracy. We show that R0 as the basic reproduction number exhibits significant spatial and temporal variation in these countries. However, by including a new function for temporal variation of R0 in an adaptive fashion, the predictive model provides highly reliable estimates of asymptomatic and undetected COVID-19 patients, both of which are key players in COVID-19 transmission. Our dynamic modeling approach can be applied widely and will provide a new fillip to infectious disease management strategies worldwide.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.20.20072629", + "rel_abs": "A major open question, affecting the policy makers decisions, is the estimation of the true size of COVID-19 infections. Most of them are undetected, because of a large number of asymptomatic cases. We provide an efficient, easy to compute and robust lower bound estimator for the number of undetected cases. A \"modified\" version of the Chao estimator is proposed, based on the cumulative time-series distribution of cases and deaths. Heterogeneity has been accounted for by assuming a geometrical distribution underlying the data generation process. An (approximated) analytical variance formula has been properly derived to compute reliable confidence intervals at 95%. An application to Austrian situation is provided and results from other European Countries are mentioned in the discussion.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "R. Ravinder", - "author_inst": "Indian Institute of Technology Delhi" - }, - { - "author_name": "Sourabh Singh", - "author_inst": "Indian Institute of Technology Delhi" - }, - { - "author_name": "Suresh Bishnoi", - "author_inst": "Indian Institute of Technology Delhi" - }, - { - "author_name": "Amreen Jan", - "author_inst": "Indian Institute of Technology Delhi" - }, - { - "author_name": "Abhinav Sinha", - "author_inst": "ICMR-National Institute of Malaria Research" + "author_name": "Dankmar Boehning", + "author_inst": "University of Southampton" }, { - "author_name": "Amit Sharma", - "author_inst": "ICMR-National Institute of Malaria Research" + "author_name": "Irene Rocchetti", + "author_inst": "Consiglio Superiore della Magistratura, Italy" }, { - "author_name": "Hariprasad Kodamana", - "author_inst": "Indian Institute of Technology Delhi" + "author_name": "Antonello Maruotti", + "author_inst": "Dipartimento di Giurisprudenza, Economia, Politica e Lingue Moderne Libera Universita Ss Maria Assunta" }, { - "author_name": "N. M. Anoop Krishnan", - "author_inst": "Indian Institute of Technology Delhi" + "author_name": "Heinz Holling", + "author_inst": "Department of Methods and Statistics, Faculty of Psychology and Sports University of Muenster. Germany" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1501734,115 +1501620,95 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.04.21.052209", - "rel_title": "Recombinant SARS-CoV-2 spike S1-Fc fusion protein induced high levels of neutralizing responses in nonhuman primates", + "rel_doi": "10.1101/2020.04.22.056218", + "rel_title": "Coronavirus surveillance of wildlife in the Lao People's Democratic Republic detects viral RNA in rodents", "rel_date": "2020-04-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.21.052209", - "rel_abs": "The COVID-19 outbreak has become a global pandemic responsible for over 2,000,000 confirmed cases and over 126,000 deaths worldwide. In this study, we examined the immunogenicity of CHO-expressed recombinant SARS-CoV-2 S1-Fc fusion protein in mice, rabbits, and monkeys as a potential candidate for a COVID-19 vaccine. We demonstrate that the S1-Fc fusion protein is extremely immunogenic, as evidenced by strong antibody titers observed by day 7. Strong virus neutralizing activity was observed on day 14 in rabbits immunized with the S1-Fc fusion protein using a pseudovirus neutralization assay. Most importantly, in less than 20 days and three injections of the S1-Fc fusion protein, two monkeys developed higher virus neutralizing titers than a recovered COVID-19 patient in a live SARS-CoV-2 infection assay. Our data strongly suggests that the CHO-expressed SARS-CoV-2 S1-Fc recombinant protein could be a strong candidate for vaccine development against COVID-19.\n\nHighlightsO_LICHO-expressed S1-Fc protein is very immunogenic in various animals and can rapidly induce strong antibody production\nC_LIO_LIS1-Fc protein solicits strong neutralizing activities against live virus\nC_LIO_LIStable CHO cell line expressing 50 mg/L of S1-Fc and a 3,000 L Bioreactor can produce 3 million doses of human COVID-19 vaccine every 10 days, making it an accessible and affordable option for worldwide vaccination\nC_LI", - "rel_num_authors": 24, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.22.056218", + "rel_abs": "Coronaviruses can become zoonotic as in the case of COVID-19, and hunting, sale, and consumption of wild animals in Southeast Asia facilitates an increased risk for such incidents. We sampled and tested rodents (851) and other mammals, and found Betacoronavirus RNA in 12 rodents. The sequences belong to two separate genetic clusters, and relate closely to known rodent coronaviruses detected in the region, and distantly to human coronaviruses OC43 and HKU1. Considering close human-wildlife contact with many species in and beyond the region, a better understanding of virus diversity is urgently needed for the mitigation of future risks.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Wenlin Ren", - "author_inst": "AbMax Biotechnology Co., LTD" - }, - { - "author_name": "Hunter Sun", - "author_inst": "AnyGo Technology Co., LTD" - }, - { - "author_name": "George Fu Gao", - "author_inst": "Institute of Microbiology Chinese Academy of Sciences" - }, - { - "author_name": "Jianxin Chen", - "author_inst": "ZhenGe Biotechnology Co., LTD" - }, - { - "author_name": "Sean Sun", - "author_inst": "AnyGo Technology Co., LTD" + "author_name": "David J McIver", + "author_inst": "Metabiota Inc" }, { - "author_name": "Rongqing Zhao", - "author_inst": "AnyGo Technology Co., LTD" + "author_name": "Soubanh Silithammavong", + "author_inst": "Wildlife Conservation Society" }, { - "author_name": "Guang Gao", - "author_inst": "AnyGo Technology Co., LTD" + "author_name": "Watthana Theppangna", + "author_inst": "National Animal Health Laboratory" }, { - "author_name": "Yalin Hu", - "author_inst": "Sinovac Biotech Ltd." - }, - { - "author_name": "Gan Zhao", - "author_inst": "Advaccine (Suzhou) Biopharmaceuticals, Co., LTD" + "author_name": "Amethyst Gillis", + "author_inst": "Metabiota Inc" }, { - "author_name": "Yuxin Chen", - "author_inst": "Medical School of Nanjing University" + "author_name": "Bounlom Douangngeun", + "author_inst": "National Animal Health Laboratory" }, { - "author_name": "Xia Jin", - "author_inst": "Shanghai Public Health Clinical Center, Fudan University" + "author_name": "Kongsy Khammavong", + "author_inst": "Wildlife Conservation Society" }, { - "author_name": "Feng Fang", - "author_inst": "AbMax Biotechnology Co., LTD" + "author_name": "Sinpakone Singhalath", + "author_inst": "Wildlife Conservation Society" }, { - "author_name": "Jinggong Chen", - "author_inst": "ZhenGe Biotechnology Co., LTD" + "author_name": "Veasna Duong", + "author_inst": "Institut Pasteur du Cambodge" }, { - "author_name": "Qi Wang", - "author_inst": "AbMax Biotechnology Co., LTD" + "author_name": "Philippe Buchy", + "author_inst": "Institut Pasteur du Cambodge" }, { - "author_name": "Sitao Gong", - "author_inst": "AbMax Biotechnology Co., LTD" + "author_name": "Sarah H Olson", + "author_inst": "Wildlife Conservation Society" }, { - "author_name": "Wen Gao", - "author_inst": "ZhenGe Biotechnology Co., LTD" + "author_name": "Lucy Keatts", + "author_inst": "Wildlife Conservation Society" }, { - "author_name": "Yufei Sun", - "author_inst": "AnyGo Technology Co., LTD" + "author_name": "Amanda E Fine", + "author_inst": "Wildlife Conservation Society" }, { - "author_name": "Junchi Su", - "author_inst": "AnyGo Technology Co., LTD" + "author_name": "Zoe Greatorex", + "author_inst": "Wildlife Conservation Society" }, { - "author_name": "Ailiang He", - "author_inst": "ZhenGe Biotechnology Co., LTD" + "author_name": "Martin Gilbert", + "author_inst": "Wildlife Conservation Society" }, { - "author_name": "Xin Cheng", - "author_inst": "Advaccine (Suzhou) Biopharmaceuticals, Co., LTD" + "author_name": "Matthew LeBreton", + "author_inst": "Mosaic" }, { - "author_name": "Min Li", - "author_inst": "Shanghai Public Health Clinical Center, Fudan University" + "author_name": "Karen Saylors", + "author_inst": "Labyrinth Global Health, Inc." }, { - "author_name": "Chenxi Xia", - "author_inst": "AbMax Biotechnology Co., LTD" + "author_name": "Damien O Joly", + "author_inst": "British Columbia Ministry of Environment and Climate Change Strategy" }, { - "author_name": "Maohua Li", - "author_inst": "AbMax Biotechnology Co., LTD" + "author_name": "Edward M Rubin", + "author_inst": "Metabiota Inc." }, { - "author_name": "Le Sun", - "author_inst": "AbMax Biotechnology Co., LTD" + "author_name": "Christian E Lange", + "author_inst": "Metabiota" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.04.23.057810", @@ -1503452,141 +1503318,193 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.19.20067660", - "rel_title": "Augmented Curation of Unstructured Clinical Notes from a Massive EHR System Reveals Specific Phenotypic Signature of Impending COVID-19 Diagnosis", + "rel_doi": "10.1101/2020.04.19.20062117", + "rel_title": "Clinical Characteristics of Hospitalized Covid-19 Patients in New York City", "rel_date": "2020-04-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.19.20067660", - "rel_abs": "Understanding temporal dynamics of COVID-19 patient symptoms could provide fine-grained resolution to guide clinical decision-making. Here, we use deep neural networks over an institution-wide platform for the augmented curation of clinical notes from 77,167 patients subjected to COVID-19 PCR testing. By contrasting Electronic Health Record (EHR)-derived symptoms of COVID-19-positive (COVIDpos; n=2,317) versus COVID-19-negative (COVIDneg; n=74,850) patients for the week preceding the PCR testing date, we identify anosmia/dysgeusia (27.1-fold), fever/chills (2.6-fold), respiratory difficulty (2.2-fold), cough (2.2-fold), myalgia/arthralgia (2-fold), and diarrhea (1.4-fold) as significantly amplified in COVIDpos over COVIDneg patients. The combination of cough and fever/chills has 4.2-fold amplification in COVIDpos patients during the week prior to PCR testing, and along with anosmia/dysgeusia, constitutes the earliest EHR-derived signature of COVID-19. This study introduces an Augmented Intelligence platform for the real-time synthesis of institutional biomedical knowledge. The platform holds tremendous potential for scaling up curation throughput, thus enabling EHR-powered early disease diagnosis.", - "rel_num_authors": 31, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.19.20062117", + "rel_abs": "BackgroundThe coronavirus 2019 (Covid-19) pandemic is a global public health crisis, with over 1.6 million cases and 95,000 deaths worldwide. Data are needed regarding the clinical course of hospitalized patients, particularly in the United States.\n\nMethodsDemographic, clinical, and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed Covid-19 between February 27 and April 2, 2020 were identified through institutional electronic health records. We conducted a descriptive study of patients who had in-hospital mortality or were discharged alive.\n\nResultsA total of 2,199 patients with Covid-19 were hospitalized during the study period. As of April 2nd, 1,121 (51%) patients remained hospitalized, and 1,078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 ug/ml, C-reactive protein was 162 mg/L, and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 ug/ml, C-reactive protein was 79 mg/L, and procalcitonin was 0.09 ng/mL.\n\nConclusionsThis is the largest and most diverse case series of hospitalized patients with Covid-19 in the United States to date. Requirement of intensive care and mortality were high. Patients who died typically had pre-existing conditions and severe perturbations in inflammatory markers.", + "rel_num_authors": 44, "rel_authors": [ { - "author_name": "Tyler Wagner", - "author_inst": "nference" + "author_name": "Ishan Paranjpe", + "author_inst": "Ican School of Medicine at Mount Sinai" }, { - "author_name": "FNU Shweta", - "author_inst": "Mayo Clinic" + "author_name": "Adam Russak", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Karthik Murugadoss", - "author_inst": "nference" + "author_name": "Jessica K De Freitas", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Samir Awasthi", - "author_inst": "nference" + "author_name": "Anuradha Lala", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "AJ Venkatakrishnan", - "author_inst": "nference" + "author_name": "Riccardo Miotto", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Sairam Bade", - "author_inst": "nference Labs" + "author_name": "Akhil Vaid", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Arjun Puranik", - "author_inst": "nference" + "author_name": "Kipp W Johnson", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Martin Kang", - "author_inst": "nference" + "author_name": "Matteo Danieletto", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Brian W Pickering", - "author_inst": "Mayo Clinic" + "author_name": "Eddye Golden", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "John C O'Horo", - "author_inst": "Mayo Clinic" + "author_name": "Dara Meyer", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Philippe R Bauer", - "author_inst": "Mayo Clinic" + "author_name": "Manbir Singh", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Raymund R Razonable", - "author_inst": "Mayo Clinic" + "author_name": "Sulaiman Somani", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Paschalis Vergidis", - "author_inst": "Mayo Clinic" + "author_name": "Sayan Manna", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Zelalem Temesgen", - "author_inst": "Mayo Clinic" + "author_name": "Udit Nangia", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Stacey Rizza", - "author_inst": "Mayo Clinic" + "author_name": "Arjun Kapoor", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Maryam Mahmood", - "author_inst": "Mayo Clinic" + "author_name": "Ross O'Hagan", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Walter R Wilson", - "author_inst": "Mayo Clinic" + "author_name": "Paul F O'Reilly", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Douglas Challener", - "author_inst": "Mayo Clinic" + "author_name": "Laura M Huckins", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Praveen Anand", - "author_inst": "nference" + "author_name": "Patricia Glowe", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Matt Liebers", - "author_inst": "nference" + "author_name": "Arash Kia", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Zainab Doctor", - "author_inst": "nference" + "author_name": "Prem Timsina", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Eli Silvert", - "author_inst": "nference" + "author_name": "Robert M Freeman", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Hugo Solomon", - "author_inst": "nference" + "author_name": "Matthew A Levin", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Akash Anand", - "author_inst": "nference Labs" + "author_name": "Jeffrey Jhang", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Rakesh Barve", - "author_inst": "nference Labs" + "author_name": "Adolfo Firpo", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Gregory J Gores", - "author_inst": "Mayo Clinic" + "author_name": "Patricia Kovatch", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Amy W Williams", - "author_inst": "Mayo Clinic" + "author_name": "Joseph Finkelstein", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "William G Morice", - "author_inst": "Mayo Clinic Laboratories" + "author_name": "Judith A Aberg", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "John Halamka", - "author_inst": "Mayo Clinic" + "author_name": "Emilia Bagiella", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Andrew D Badley", - "author_inst": "Mayo Clinic" + "author_name": "Carol R Horowitz", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Venky Soundararajan", - "author_inst": "nference" + "author_name": "Barbara Murphy", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Zahi A Fayad", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Jagat Narula", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Eric J Nestler", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Valentin Fuster", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Carlos Cordon-Cardo", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Dennis S Charney", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "David L Reich", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Allan C Just", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Erwin P Bottinger", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Alexander W Charney", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Benjamin S Glicksberg", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Girish Nadkarni", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "- Mount Sinai Covid Informatics Center (MSCIC)", + "author_inst": "" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1505322,31 +1505240,47 @@ "category": "pharmacology and therapeutics" }, { - "rel_doi": "10.1101/2020.04.16.20068205", - "rel_title": "Hydroxychloroquine for the management of COVID-19: Hope or Hype? A Systematic review of the current evidence", + "rel_doi": "10.1101/2020.04.16.20067801", + "rel_title": "Mental health outcomes among front and second line health workers associated with the COVID-19 pandemic in Italy.", "rel_date": "2020-04-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.16.20068205", - "rel_abs": "ImportanceThe COVID-19 Pandemic has literally left the world breathless in the chase for pharmacotherapy. With vaccine and novel drug development in early clinical trials, repurposing of existing drugs takes the center stage.\n\nObjectiveA potential drug discussed in global scientific community is hydroxychloroquine. We intend to systematically explore, analyze, rate the existing evidence of hydroxychloroquine in the light of published, unpublished and clinical trial data.\n\nEvidence reviewPubMed Ovid MEDLINE, EMBASE, Google scholar databases, pre-proof article repositories, clinical trial registries were comprehensively searched with focused question of use of hydroxychloroquine in COVID-19 patients. The literature was systematically explored as per PRISMA guidelines.\n\nFindingsTotal 156 articles were available as of 7th May 2020; of which 11 articles of relevance were analyzed. Three in-vitro studies were reviewed. Two open label non-randomized trials, two open label randomized control trials, one large observational study, one follow-up study and two retrospective cohort studies were systematically analyzed and rated by oxford CEBM and GRADE framework for quality and strength of evidence. Also 27 clinical trials registered in three clinical trial registries were analyzed and summarized. Hydroxychloroquine seems to be efficient in inhibiting SARS-CoV-2 in in-vitro cell lines. However, there is lack of strong evidence from human studies. It was found that overall quality of available evidence ranges from very low to low.\n\nConclusions and relevanceThe in-vitro cell culture based data of viral inhibition does not suffice for the use of hydroxychloroquine in the patients with COVID-19. Current literature shows inadequate, low level evidence in human studies. Scarcity of safety and efficacy data warrants medical communities, health care agencies and governments across the world against the widespread use of hydroxychloroquine in COVID-19 prophylaxis and treatment, until robust evidence becomes available.\n\nKEY POINTSO_ST_ABSQuestionC_ST_ABSWhat is the current evidence for use of Hydroxychloroquine in pharmacotherapy of COVID-19?\n\nFindingsWe electronically explored various databases and clinical trial registries and identified 11 publications and 27 clinical trials with active recruitment. The in-vitro study data demonstrates the viral inhibition by hydroxychloroquine. The clinical studies are weakly designed and conducted with insufficient reporting and significant limitations. Well designed robust clinical trials are being conducted all over the world and results of few such robust studies are expected shortly.\n\nMeaningCurrent evidence stands inadequate to support the use of hydroxychloroquine in pharmacotherapy of COVID-19.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.16.20067801", + "rel_abs": "In this study, we report on mental health outcomes among health workers (HWs) involved with the COVID-19 pandemic in Italy.\n\nData on mental health on 1379 HWs were collected between March 27th and March 31th 2020 using an on-line questionnaire spread throughout social networks, using a snowball technique along with sponsored social network advertisement. Key mental health outcomes were Post-Traumatic Stress Disorder symptoms (PTSD), severe depression, anxiety, insomnia and perceived stress.\n\nPTSD symptoms, severe depression, anxiety and insomnia, and high perceived stress were endorsed respectively by 681 (49.38%), 341 (24.73%), 273 (19.80%), 114 (8.27%) and 302 (21.90%) respondents. Regression analysis show that younger age, female gender, being a front-line HWs, having a colleague deceased, hospitalised or in quarantine were associated with poor mental health outcomes.\n\nThis is the first report on mental health outcomes and associated risk factors among HWs associated with the COVID-19 pandemic in Italy, confirming a substantial proportion of health workers involved with the COVID-19 pandemic having mental health issues, in particular young women, first-line HWs.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Umesh Devappa Suranagi", - "author_inst": "Lady Hardinge Medical College" + "author_name": "Rodolfo Rossi", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Harmeet Singh Rehan", - "author_inst": "Lady Hardinge Medical College" + "author_name": "Valentina Socci", + "author_inst": "University of L'Aquila" }, { - "author_name": "Nitesh Goyal", - "author_inst": "Lady Hardinge Medical College" + "author_name": "Francesca Pacitti", + "author_inst": "University of L'Aquila" + }, + { + "author_name": "Giorgio Di Lorenzo", + "author_inst": "University of Rome Tor Vergata" + }, + { + "author_name": "Antinisca Di Marco", + "author_inst": "University of L'Aquila" + }, + { + "author_name": "Alberto Siracusano", + "author_inst": "University of Rome Tor Vergata" + }, + { + "author_name": "Alessandro Rossi", + "author_inst": "University of L'Aquila" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pharmacology and therapeutics" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2020.04.17.20068601", @@ -1506620,29 +1506554,93 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.04.17.20069393", - "rel_title": "Why does COVID-19 case fatality rate vary among countries?", + "rel_doi": "10.1101/2020.04.16.20068528", + "rel_title": "Cholesterol Metabolism--Impact for SARS-CoV-2 Infection Prognosis, Entry, and Antiviral Therapies", "rel_date": "2020-04-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.17.20069393", - "rel_abs": "BackgroundWhile the epidemic of SARS-CoV-2 is spreading worldwide, there is much concern over the mortality rate that the infection induces. Available data suggest that COVID-19 case fatality rate varies temporally (as the epidemic progresses) and spatially (among countries). Here, we attempted to identify key factors possibly explaining the variability in case fatality rate across countries.\n\nMethodsWe used data on the temporal trajectory of case fatality rate provided by the European Center for Disease Prevention and Control, and country-specific data on different metrics describing the incidence of known comorbidity factors associated with an increased risk of COVID-19 mortality at the individual level (Institute for Health Metrics and Evaluation). We also compiled data on demography, economy and political regimes for each country.\n\nFindingsWe first showed that temporal trajectories of case fatality rate greatly vary among countries. We found no evidence for association between comorbidities and case fatality rate at the country level. Case fatality rate was negatively associated with number of hospital beds x1,000 inhabitants. We also report evidence suggesting an association between case fatality rate and the political regime, with democracies suffering from the highest mortality burden, compared to autocratic regimes. However, most of the among-country variance in case fatality rate remained unexplained.\n\nInterpretationOverall, these results emphasize the role of socio-economic and political factors as possible drivers of COVID-19 case fatality rate at the country level.\n\nFundingNone.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.16.20068528", + "rel_abs": "In this study, we specifically addressed the connection between the SARS-CoV-2 virus with host cholesterol metabolism. Plasma lipid profile was measured in 861 COVID-19 patients classified as mild (n=215), moderate (n=364), severe (n=217) or critical (n=65) and 1108 age- and sex-matched healthy individuals. We showed that the levels of both TG and HDL-C were significantly lower in patients with severe disease than in patients with moderate or mild disease. After successful treatment, cholesterol metabolism was reestablished in patients with SARS-CoV-2 infection. The serum concentrations of TC and HDL-C can be used as indicators of disease severity and prognosis in COVID-19 patients.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Gabriele Sorci", - "author_inst": "CNRS" + "author_name": "Yumeng Peng", + "author_inst": "Beijing Institute of Biotechnology, Beijing, 100850, China" }, { - "author_name": "Bruno Faivre", - "author_inst": "University of Burgondy" + "author_name": "Luming Wan", + "author_inst": "Beijing Institute of Biotechnology, Beijing, 100850, China" }, { - "author_name": "Serge Morand", - "author_inst": "CNRS" + "author_name": "Chen Fan", + "author_inst": "Department of Laboratory Medicine, the 960th Hospital of PLA, Jinan, 250031, China" + }, + { + "author_name": "Pingping Zhang", + "author_inst": "Clinical Laboratory Center, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China" + }, + { + "author_name": "Xiaolin Wang", + "author_inst": "Beijing Institute of Biotechnology, Beijing, 100850, China" + }, + { + "author_name": "Jin Sun", + "author_inst": "Beijing Institute of Biotechnology, Beijing, 100850, China" + }, + { + "author_name": "Yanhong Zhang", + "author_inst": "Beijing Institute of Biotechnology, Beijing, 100850, China" + }, + { + "author_name": "Qiulin Yan", + "author_inst": "Beijing Institute of Biotechnology, Beijing, 100850, China" + }, + { + "author_name": "Jing Gong", + "author_inst": "Beijing Institute of Biotechnology, Beijing, 100850, China" + }, + { + "author_name": "Huan Yang", + "author_inst": "Beijing Institute of Biotechnology, Beijing, 100850, China" + }, + { + "author_name": "Xiaopan Yang", + "author_inst": "Beijing Institute of Biotechnology, Beijing, 100850, China" + }, + { + "author_name": "Huilong Li", + "author_inst": "Beijing Institute of Biotechnology, Beijing, 100850, China" + }, + { + "author_name": "Yufei Wang", + "author_inst": "Department of Clinical Laboratory, the Third Medical Centre, Chinese PLA General Hospital, Beijing, P.R. China" + }, + { + "author_name": "Yulong Zong", + "author_inst": "Department of Laboratory Medicine, Taian City Central Hospital, Taian, 271000, China" + }, + { + "author_name": "Feng Yin", + "author_inst": "Department of Laboratory Medicine, Taian City Central Hospital Branch, Taian, 271000, China" + }, + { + "author_name": "Xiaoli Yang", + "author_inst": "Department of Clinical Laboratory, the Third Medical Centre, Chinese PLA General Hospital, 100850, China" + }, + { + "author_name": "Hui Zhong", + "author_inst": "Beijing Institute of Biotechnology, Beijing, China" + }, + { + "author_name": "Yuan Cao", + "author_inst": "Department of Laboratory Medicine, the 960th Hospital of PLA, Jinan, 250031, China" + }, + { + "author_name": "Congwen Wei", + "author_inst": "Beijing Institute of Biotechnology, Beijing, 100850, China" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1507950,37 +1507948,133 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.04.19.20071456", - "rel_title": "The Novel Coronavirus Disease (COVID-19): A PRISMA Systematic Review and Meta-analysis of Clinical and Paraclinical characteristics", + "rel_doi": "10.1101/2020.04.19.20071563", + "rel_title": "COVID-19 experience: first Italian survey on healthcare staff members from a Mother-Child Research hospital using combined molecular and rapid immunoassays test", "rel_date": "2020-04-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.19.20071456", - "rel_abs": "An outbreak of pneumonia, caused by a novel coronavirus (COVID-19) was Identified in China in Dec 2019. This virus expanded worldwide, causing global concern. Clinical, laboratory and imaging features of this infection are characterized in some observational studies. We undertook a systematic review and meta-analysis to assess the frequency of clinical, laboratory, and CT features in COVID-19 patients.\n\nWe did a systematic review and meta-analysis using three databases to identify clinical, laboratory, and CT features of rRT-PCR confirmed cases of COVID-19. Data for 3420 patients from 30 observational studies were included.\n\nOverall, the results showed that fever (84.2%, 95%CI 82.6-85.7), cough (62%, 95%CI 60-64), and fatigue (39.4%, 95%CI 37.2-41.6%) were the most prevalent symptoms in COVID-19 patients. Increased CRP level, decreased lymphocyte count, and increased D-dimer level were the most common laboratory findings. Among COVID-19 patients, 92% had a positive CT finding, most prevalently GGO (60%, 95%CI 58-62) and peripheral distribution (64%, 95%CI 60-69).\n\nThese results demonstrate the clinical, paraclinical, and imaging features of COIVD-19.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.19.20071563", + "rel_abs": "The fast spread of the novel coronavirus (SARS-CoV-2) has become a global threat hitting the worldwide fragile health care system. In Italy, there is a continued COVID-19 growth of cases and deaths that requires control measures for the correct management of the epidemiological emergency. To contribute to increasing the overall knowledge of COVID-19, systematic tests in the general population are required.\n\nHere, we describe the first Italian survey performed in 727 employees belonging to a Mother-Child Research hospital tested for both viral (nasopharyngeal and oropharyngeal swabs) and antibody presence. Individuals were divided into three risk categories (high, medium and low) according to their job activity. Only one subject was positive at the swab test while 17.2% of the cohort was positive for the presence of antibodies. Results highlighted that the presence of Positive antibodies is significantly associated with high and medium risk exposure occupation (p-value=0.026) as well as cold and conjunctivitis symptoms (p-value=0.016 and 0.042 respectively). Moreover, among healthcare professionals, the category of medical doctors showed a significant association with the presence of antibodies against SARS-CoV-2 (p-value=0.0127). Finally, we detected a rapid decrease in antibody intensity between two assessments performed within a very short period (p-value=0.009). Overall, the present study increases our knowledge of the epidemiological data of COVID-19 infection in Italy, suggesting a high prevalence of immune individuals (i.e. at least among at-risk categories) and the efficacy of the combined diagnostic protocol to monitor the possible outbreak.", + "rel_num_authors": 29, "rel_authors": [ { - "author_name": "Hamidreza Hasani", - "author_inst": "Iran University of Medical Sciences" + "author_name": "Manola Comar", + "author_inst": "1Department of Medicine, Surgery and Health Sciences, University of Trieste; 2Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" }, { - "author_name": "Shayan Mardi", - "author_inst": "Alborz University of Medical Sciences" + "author_name": "Marco Brumat", + "author_inst": "1Department of Medicine, Surgery and Health Sciences, University of Trieste 2Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" }, { - "author_name": "Sareh Shakerian", - "author_inst": "Shahid Beheshti University of Medical Sciences and Health Services" + "author_name": "Maria Pina Concas", + "author_inst": "1Department of Medicine, Surgery and Health Sciences, University of Trieste 2Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" }, { - "author_name": "Nooshin Taherzadeh-Ghahfarokhi", - "author_inst": "Alborz University of Medical Sciences" + "author_name": "Giorgia Argentini", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Annamonica Bianco", + "author_inst": "1Department of Medicine, Surgery and Health Sciences, University of Trieste 2Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Livia Bicego", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Roberta Bottega", + "author_inst": "1Department of Medicine, Surgery and Health Sciences, University of Trieste 2Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Petra Carli", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Andrea Cassone", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Eulalia Catamo", + "author_inst": "1Department of Medicine, Surgery and Health Sciences, University of Trieste 2Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Massimiliano Cocca", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Massimo Del Pin", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Mariateresa Di Stazio", + "author_inst": "1Department of Medicine, Surgery and Health Sciences, University of Trieste 2Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Agnese Feresin", + "author_inst": "1Department of Medicine, Surgery and Health Sciences, University of Trieste 2Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Martina La Bianca", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Sara Morassut", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Anna Morgan", + "author_inst": "1Department of Medicine, Surgery and Health Sciences, University of Trieste 2Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Giulia Pelliccione", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Vincenzo Petix", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" }, { - "author_name": "Parham Mardi", - "author_inst": "Alborz University of medical sciences" + "author_name": "Giulia Ragusa", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Antonietta Robino", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Stefano Russian", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Beatrice Spedicati", + "author_inst": "1Department of Medicine, Surgery and Health Sciences, University of Trieste 2Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Sarah Suergiu", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Marianela Urriza", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Fulvia Vascotto", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Paola Toscani", + "author_inst": "Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Giorgia Girotto", + "author_inst": "1Department of Medicine, Surgery and Health Sciences, University of Trieste 2Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" + }, + { + "author_name": "Paolo Gasparini", + "author_inst": "1Department of Medicine, Surgery and Health Sciences, University of Trieste 2Institute for Maternal and Child Health IRCCS, Burlo Garofolo, Trieste, Italy" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1509252,27 +1509346,63 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.04.16.20063990", - "rel_title": "Diagnosis and Prediction Model for COVID19 Patients Response to Treatment based on Convolutional Neural Networks and Whale Optimization Algorithm Using CT Images", + "rel_doi": "10.1101/2020.04.16.20058560", + "rel_title": "Epidemiological and Genomic Analysis of SARS-CoV-2 in Ten Patients from a Mid-sized City outside of Hubei, China", "rel_date": "2020-04-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.16.20063990", - "rel_abs": "The outbreak of coronavirus diseases (COVID-19) has rabidly spread all over the world. The World Health Organization (WHO) has announced that coronavirus COVID-19 is an international pandemic. The Real-Time Reverse transcription-polymerase Chain Reaction (RT-PCR) has a low positive and sensitivity rate in the early stage of COVID-19. As a result, the Computed Tomography (CT) imaging is used for diagnosing. COVID-19 has different key signs on a CT scan differ from other viral pneumonia. These signs include ground-glass opacities, consolidations, and crazy paving. In this paper, an Artificial Intelli-gence-inspired Model for COVID-19 Diagnosis and Prediction for Patient Response to Treatment (AIMDP) is proposed. AIMDP model has two main functions reflected in two proposed modules, namely, the Diagnosis Module (DM) and Prediction Module (PM). The Diagnosis Module (DM) is proposed for early and accurately detecting the patients with COVID-19 and distinguish it from other viral pneumonias using COVID-19 signs obtained from CT scans. The DM model, uses Convolutional Neural Networks (CNNs) as a Deep learning technique for segmentation, can process hundreds of CT images in seconds to speed up diagnosis of COVID-19 and contribute in its containment. In addition, some countries havent the ability to provide all patients with the treatment and intensive care services, so it will be mandatory to give treatment to only responding patients. In this context, the Prediction Module (PM) is proposed for predicting the ability of the patient to respond to treatment based on different factors e.g. age, infection stage, respiratory failure, multi-organ failure and the treatment regimens. PM implement the Whale Optimization Algorithm for selecting the most relevant patients features. The experimental results show promising performance for the proposed diagnosing and prediction modules, using a dataset with hundreds of real data and CT images.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.16.20058560", + "rel_abs": "A novel coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing COVID-19 pandemic. In this study, we performed a comprehensive epidemiological and genomic analysis of SARS-CoV-2 genomes from ten patients in Shaoxing, a mid-sized city outside of the epicenter Hubei province, China, during the early stage of the outbreak (late January to early February, 2020). We obtained viral genomes with > 99% coverage and a mean depth of 296X demonstrating that viral genomic analysis is feasible via metagenomics sequencing directly on nasopharyngeal samples with SARS-CoV-2 Real-time PCR Ct values less than 28. We found that a cluster of 4 patients with travel history to Hubei shared the exact same virus with patients from Wuhan, Taiwan, Belgium and Australia, highlighting how quickly this virus spread to the globe. The virus from another cluster of two family members living together without travel history but with a sick contact of a confirmed case from another city outside of Hubei accumulated significantly more mutations (9 SNPs vs average 4 SNPs), suggesting a complex and dynamic nature of this outbreak. We also found 70% patients in this study had the S genotype, consistent with an early study showing a higher prevalence of genotype out of Hubei than that inside Hubei. We calculated an average mutation rate of 1.37x10-3 nucleotide substitution per site per year, which is similar to that of other coronaviruses. Our findings add to the growing knowledge of the epidemiological and genomic characteristics of SARS-CoV-2 that are important for guiding outbreak containment and vaccine development. The moderate mutation rate of this virus also lends hope that development of an effective, long-lasting vaccine may be possible.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Sally M. ELGhamrawy", - "author_inst": "MISR Higher Institute for Engineering and Technology, Computer Engineering Depart-ment" + "author_name": "Jinkun Chen", + "author_inst": "Shaoxing Center for Disease Control and Prevention" }, { - "author_name": "Abou Ellah Hassanien", - "author_inst": "Faculty of Computers and Artificial Intelligence, Cairo University, Egypt" + "author_name": "Evann Hilt", + "author_inst": "UCLA Health System" + }, + { + "author_name": "Huan Wu", + "author_inst": "IngeniGen XunMinKang Biotechnology Inc., Shaoxing, Zhejiang, China" + }, + { + "author_name": "ZhuoJing Jiang", + "author_inst": "Shaoxing Center for Disease Control and Prevention" + }, + { + "author_name": "QinChao Zhang", + "author_inst": "Shaoxing Center for Disease Control and Prevention" + }, + { + "author_name": "JiLing Wang", + "author_inst": "Shaoxing Center for Disease Control and Prevention" + }, + { + "author_name": "Yifang Wang", + "author_inst": "IngeniGen XunMinKang Biotechnology Inc., Shaoxing, Zhejiang, China" + }, + { + "author_name": "Fan Li", + "author_inst": "Three Coin Analytics, Inc. Pleasanton, CA, USA" + }, + { + "author_name": "Ziqin Li", + "author_inst": "Zhejiang-Californina International Nanosystems Institute, Zhejiang University, Hangzhou, Zhejiang, China" + }, + { + "author_name": "JiaLiang Tang", + "author_inst": "Shaoxing Center for Disease Control and Prevention" + }, + { + "author_name": "Shangxin Yang", + "author_inst": "UCLA Health System" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.04.17.20064691", @@ -1511458,75 +1511588,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.04.20.050039", - "rel_title": "Phylodynamics of SARS-CoV-2 transmission in Spain", + "rel_doi": "10.1101/2020.04.20.051557", + "rel_title": "Design an efficient multi-epitope peptide vaccine candidate against SARS-CoV-2: An in silico analysis", "rel_date": "2020-04-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.20.050039", - "rel_abs": "ObjectivesSARS-CoV-2 whole-genome analysis has identified three large clades spreading worldwide, designated G, V and S. This study aims to analyze the diffusion of SARS-CoV-2 in Spain/Europe.\n\nMethodsMaximum likelihood phylogenetic and Bayesian phylodynamic analyses have been performed to estimate the most probable temporal and geographic origin of different phylogenetic clusters and the diffusion pathways of SARS-CoV-2.\n\nResultsPhylogenetic analyses of the first 28 SARS-CoV-2 whole genome sequences obtained from patients in Spain revealed that most of them are distributed in G and S clades (13 sequences in each) with the remaining two sequences branching in the V clade. Eleven of the Spanish viruses of the S clade and six of the G clade grouped in two different monophyletic clusters (S-Spain and G-Spain, respectively), with the S-Spain cluster also comprising 8 sequences from 6 other countries from Europe and the Americas. The most recent common ancestor (MRCA) of the SARS-CoV-2 pandemic was estimated in the city of Wuhan, China, around November 24, 2019, with a 95% highest posterior density (HPD) interval from October 30-December 17, 2019. The origin of S-Spain and G-Spain clusters were estimated in Spain around February 14 and 18, 2020, respectively, with a possible ancestry of S-Spain in Shanghai.\n\nConclusionsMultiple SARS-CoV-2 introductions have been detected in Spain and at least two resulted in the emergence of locally transmitted clusters, with further dissemination of one of them to at least 6 other countries. These results highlight the extraordinary potential of SARS-CoV-2 for rapid and widespread geographic dissemination.", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.20.051557", + "rel_abs": "BackgroundTo date, no specific vaccine or drug has been proven to be effective for SARS-CoV-2 infection. Therefore, we implemented immunoinformatics approach to design an efficient multi-epitopes vaccine against SARS-CoV-2.\n\nResultsThe designed vaccine construct has several immunodominant epitopes from structural proteins of Spike, Nucleocapsid, Membrane and Envelope. These peptides promote cellular and humoral immunity and Interferon gamma responses. In addition, these epitopes have antigenicity ability and no allergenicity probability. To enhance the vaccine immunogenicity, we used three potent adjuvants; Flagellin, a driven peptide from high mobility group box 1 as HP-91 and human beta defensin 3 protein. The physicochemical and immunological properties of the vaccine structure were evaluated. Tertiary structure of the vaccine protein was predicted and refined by I-Tasser and galaxi refine and validated using Rampage and ERRAT. Results of Ellipro showed 242 residues from vaccine might be conformational B cell epitopes. Docking of vaccine with Toll-Like Receptors 3, 5 and 8 proved an appropriate interaction between the vaccine and receptor proteins. In silico cloning demonstrated that the vaccine can be efficiently expressed in Escherichia coli.\n\nConclusionsThe designed multi epitope vaccine is potentially antigenic in nature and has the ability to induce humoral and cellular immune responses against SARS-CoV-2. This vaccine can interact appropriately with the TLR3, 5, and 8. Also, this vaccine has high quality structure and suitable characteristics such as high stability and potential for expression in Escherichia coli.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Francisco D\u00edez Fuertes", - "author_inst": "Centro Nacional de Microbiolog\u00eda - Instituto de Salud Carlos III / IDIBAPS - Hospital Cl\u00ednic de Barcelona" - }, - { - "author_name": "Mar\u00eda Iglesias Caballero", - "author_inst": "Centro Nacional de Microbiolog\u00eda - Instituto de Salud Carlos III" - }, - { - "author_name": "Sara Monz\u00f3n", - "author_inst": "Unidad de Bioinform\u00e1tica - Instituto de Salud Carlos III" - }, - { - "author_name": "Pilar Jim\u00e9nez", - "author_inst": "Unidad de Gen\u00f3mica - Instituto de Salud Carlos III" - }, - { - "author_name": "Sarai Varona", - "author_inst": "Unidad de Bioinform\u00e1tica - Instituto de Salud Carlos III" - }, - { - "author_name": "Isabel Cuesta", - "author_inst": "Unidad de Bioinform\u00e1tica - Instituto de Salud Carlos III" - }, - { - "author_name": "\u00c1ngel Zaballos", - "author_inst": "Unidad de Gen\u00f3mica - Instituto de Salud Carlos III" - }, - { - "author_name": "Michael M. Thomson", - "author_inst": "Centro Nacional de Microbiolog\u00eda - Instituto de Salud Carlos III" - }, - { - "author_name": "Mercedes Jim\u00e9nez", - "author_inst": "Unidad de Gen\u00f3mica - Instituto de Salud CarlosIII" - }, - { - "author_name": "Javier Garc\u00eda P\u00e9rez", - "author_inst": "Centro Nacional de Microbiolog\u00eda - Instituto de Salud Carlos III" - }, - { - "author_name": "Francisco Pozo", - "author_inst": "Centro Nacional de Microbiolog\u00eda - Instituto de Salud Carlos III" + "author_name": "Zahra Yazdani", + "author_inst": "Department of Immunology, Molecular and Cell Biology Research Center, School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran" }, { - "author_name": "Mayte P\u00e9rez Olmeda", - "author_inst": "Centro Nacional de Microbiolog\u00eda - Instituto de Salud Carlos III" + "author_name": "Alireza Rafiei", + "author_inst": "Department of Immunology, Molecular and Cell Biology Research Center, School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran" }, { - "author_name": "Jos\u00e9 Alcam\u00ed", - "author_inst": "Centro Nacional de Microbiolog\u00eda - Instituto de Salud Carlos III / Hospital Cl\u00ednic de Barcelona" + "author_name": "Mohammadreza Yazdani", + "author_inst": "Department of Chemistry, Isfahan University of Technology, Isfahan, 84156-83111, Iran" }, { - "author_name": "Inmaculada Casas", - "author_inst": "Centro Nacional de Microbiolog\u00eda - Instituto de Salud Carlos III" + "author_name": "Reza Valadan", + "author_inst": "Department of Immunology, Molecular and Cell Biology Research Center, School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "immunology" }, { "rel_doi": "10.1101/2020.04.20.051219", @@ -1513108,51 +1513198,43 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.04.17.046086", - "rel_title": "A dynamic nomenclature proposal for SARS-CoV-2 to assist genomic epidemiology", + "rel_doi": "10.1101/2020.04.17.047324", + "rel_title": "Exploring Conformational Transition of 2019 Novel Coronavirus Spike Glycoprotein Between Its Closed and Open States Using Molecular Dynamics Simulations", "rel_date": "2020-04-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.17.046086", - "rel_abs": "The ongoing pandemic spread of a novel human coronavirus, SARS-COV-2, associated with severe pneumonia disease (COVID-19), has resulted in the generation of thousands of virus genome sequences. The rate of genome generation is unprecedented, yet there is currently no coherent nor accepted scheme for naming the expanding phylogenetic diversity of SARS-CoV-2. We present a rational and dynamic virus nomenclature that uses a phylogenetic framework to identify those lineages that contribute most to active spread. Our system is made tractable by constraining the number and depth of hierarchical lineage labels and by flagging and declassifying virus lineages that become unobserved and hence are likely inactive. By focusing on active virus lineages and those spreading to new locations this nomenclature will assist in tracking and understanding the patterns and determinants of the global spread of SARS-CoV-2.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.17.047324", + "rel_abs": "Since its first recorded appearance in December 2019, a novel coronavirus (SARS-CoV-2) causing the disease COVID-19 has resulted in more than 2,000,000 infections and 128,000 deaths. Currently there is no proven treatment for COVID-19 and there is an urgent need for the development of vaccines and therapeutics. Coronavirus spike glycoproteins play a critical role in coronavirus entry into the host cells, as they provide host cell recognition and membrane fusion between virus and host cell. Thus, they emerged as popular and promising drug targets. Crystal structures of spike protein in its closed and open states were resolved very recently in March 2020. These structures comprise 77% of the sequence and provide almost the complete protein structure. Based on down and up positions of receptor binding domain (RBD), spike protein can be in a receptor inaccessible closed or receptor accessible open state, respectively. Starting from closed and open state crystal structures, and also 16 intermediate conformations, an extensive set of all-atom molecular dynamics (MD) simulations in the presence of explicit water and ions were performed. Simulations show that in its down position, RBD has significantly lower mobility compared to its up position; probably caused by the 6 interdomain salt bridges of RBD in down position compared to 3 in up position. Free energy landscapes based on MD simulations revealed a semi-open state located between closed and open states. Minimum energy pathway between down and up positions comprised a gradual salt bridge switching mechanism. Furthermore, although significantly lower than open state, ACE2 binding surface of RBD contained a partial solvent accessibility in its closed state.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Andrew Rambaut", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Edward C Holmes", - "author_inst": "University of Sydney" - }, - { - "author_name": "Verity Hill", - "author_inst": "University of Edinburgh" + "author_name": "Mert Gur", + "author_inst": "Istanbul Technical University" }, { - "author_name": "Aine OToole", - "author_inst": "University of Edinburgh" + "author_name": "Elhan Taka", + "author_inst": "Istanbul Technical University" }, { - "author_name": "John McCrone", - "author_inst": "University of Edinburgh" + "author_name": "Sema Zeynep Yilmaz", + "author_inst": "Istanbul Technical University" }, { - "author_name": "Chris Ruis", - "author_inst": "University of Cambridge" + "author_name": "Ceren Kilinc", + "author_inst": "Istanbul Technical University" }, { - "author_name": "Louis du Plessis", - "author_inst": "University of Oxford" + "author_name": "Umut Aktas", + "author_inst": "Istanbul Technical University" }, { - "author_name": "Oliver Pybus", - "author_inst": "University of Oxford" + "author_name": "Mert Golcuk", + "author_inst": "Istanbul Technical University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "biophysics" }, { "rel_doi": "10.1101/2020.04.17.046375", @@ -1515070,167 +1515152,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.17.20053157", - "rel_title": "Suppression of COVID-19 outbreak in the municipality of Vo, Italy", + "rel_doi": "10.1101/2020.04.14.20063420", + "rel_title": "Modeling COVID-19 latent prevalence to assess a public health intervention at a state and regional scale", "rel_date": "2020-04-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.17.20053157", - "rel_abs": "On the 21st of February 2020 a resident of the municipality of Vo, a small town near Padua, died of pneumonia due to SARS-CoV-2 infection1. This was the first COVID-19 death detected in Italy since the emergence of SARS-CoV-2 in the Chinese city of Wuhan, Hubei province2. In response, the regional authorities imposed the lockdown of the whole municipality for 14 days3. We collected information on the demography, clinical presentation, hospitalization, contact network and presence of SARS-CoV-2 infection in nasopharyngeal swabs for 85.9% and 71.5% of the population of Vo at two consecutive time points. On the first survey, which was conducted around the time the town lockdown started, we found a prevalence of infection of 2.6% (95% confidence interval (CI) 2.1-3.3%). On the second survey, which was conducted at the end of the lockdown, we found a prevalence of 1.2% (95% CI 0.8-1.8%). Notably, 43.2% (95% CI 32.2-54.7%) of the confirmed SARS-CoV-2 infections detected across the two surveys were asymptomatic. The mean serial interval was 6.9 days (95% CI 2.6-13.4). We found no statistically significant difference in the viral load (as measured by genome equivalents inferred from cycle threshold data) of symptomatic versus asymptomatic infections (p-values 0.6 and 0.2 for E and RdRp genes, respectively, Exact Wilcoxon-Mann-Whitney test). Contact tracing of the newly infected cases and transmission chain reconstruction revealed that most new infections in the second survey were infected in the community before the lockdown or from asymptomatic infections living in the same household. This study sheds new light on the frequency of asymptomatic SARS-CoV-2 infection and their infectivity (as measured by the viral load) and provides new insights into its transmission dynamics, the duration of viral load detectability and the efficacy of the implemented control measures.", - "rel_num_authors": 37, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.14.20063420", + "rel_abs": "BackgroundEmergence of COVID-19 caught the world off-guard and unprepared, initiating a global pandemic. In the absence of evidence, individual communities had to take timely action to reduce the rate of disease spread and avoid overburdening their healthcare systems. Although a few predictive models have been published to guide these decisions, most have not taken into account spatial differences and have included assumptions that do not match the local realities. Access to reliable information that is adapted to local context is critical for policymakers to make informed decisions during a rapidly evolving pandemic.\n\nObjectiveThe goal of this study was to develop an adapted susceptible-infected-removed (SIR) model to predict the trajectory of the COVID-19 pandemic in North Carolina (NC) and the Charlotte metropolitan region and to incorporate the effect of a public health intervention to reduce disease spread, while accounting for unique regional features and imperfect detection.\n\nMethodsUsing the software package R, three SIR models were fit to infection prevalence data from the state and the greater Charlotte region and then rigorously compared. One of these models (SIR-Int) accounted for a stay-at-home intervention and imperfect detection of COVID-19 cases. We computed longitudinal total estimates of the susceptible, infected, and removed compartments of both populations, along with other pandemic characteristics (e.g., basic reproduction number).\n\nResultsPrior to March 26, disease spread was rapid at the pandemic onset with the Charlotte region doubling time of 2.56 days (95% CI: (2.11, 3.25)) and in NC 2.94 days (95% CI: (2.33, 4.00)). Subsequently, disease spread significantly slowed with doubling times increased in the Charlotte region to 4.70 days (95% CI: (3.77, 6.22)) and in NC to 4.01 days (95% CI: (3.43, 4.83)). Reflecting spatial differences, this deceleration favored the greater Charlotte region compared to NC as a whole. A comparison of the efficacy of intervention, defined as 1 - the hazard ratio of infection, gave 0.25 for NC and 0.43 for the Charlotte region. Also, early in the pandemic, the initial basic SIR model had good fit to the data; however, as the pandemic and local conditions evolved, the SIR-Int model emerged as the model with better fit.\n\nConclusionsUsing local data and continuous attention to model adaptation, our findings have enabled policymakers, public health officials and health systems to proactively plan capacity and evaluate the impact of a public health intervention. Our SIR-Int model for estimated latent prevalence was reasonably flexible, highly accurate, and demonstrated the efficacy of a stay-at-home order at both the state and regional level. Our results highlight the importance of incorporating local context into pandemic forecast modeling, as well as the need to remain vigilant and informed by the data as we enter into a critical period of the outbreak.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Enrico Lavezzo", - "author_inst": "University of Padua" - }, - { - "author_name": "Elisa Franchin", - "author_inst": "University of Padua" - }, - { - "author_name": "Constanze Ciavarella", - "author_inst": "Imperial College London" - }, - { - "author_name": "Gina Cuomo-Dannenburg", - "author_inst": "Imperial College London" - }, - { - "author_name": "Luisa Barzon", - "author_inst": "University of Padua" - }, - { - "author_name": "Claudia Del Vecchio", - "author_inst": "University of Padua" - }, - { - "author_name": "Lucia Rossi", - "author_inst": "Azienda Ospedaliera Padova" - }, - { - "author_name": "Riccardo Manganelli", - "author_inst": "University of Padua" - }, - { - "author_name": "Arianna Loregian", - "author_inst": "University of Padua" - }, - { - "author_name": "Nicol\u00f2 Navarin", - "author_inst": "University of Padua" - }, - { - "author_name": "Davide Abate", - "author_inst": "University of Padua" - }, - { - "author_name": "Manuela Sciro", - "author_inst": "Azienda Ospedaliera Padova" - }, - { - "author_name": "Stefano Merigliano", - "author_inst": "University of Padua" - }, - { - "author_name": "Ettore Decanale", - "author_inst": "Azienda Ospedaliera Padova" - }, - { - "author_name": "Maria Cristina Vanuzzo", - "author_inst": "Azienda Ospedaliera Padova" - }, - { - "author_name": "Francesca Saluzzo", - "author_inst": "University of Padua" - }, - { - "author_name": "Francesco Onelia", - "author_inst": "University of Padua" - }, - { - "author_name": "Monia Pacenti", - "author_inst": "Azienda Ospedaliera Padova" - }, - { - "author_name": "Saverio Parisi", - "author_inst": "University of Padua" - }, - { - "author_name": "Giovanni Carretta", - "author_inst": "Azienda Ospedaliera Padova" - }, - { - "author_name": "Daniele Donato", - "author_inst": "Azienda Ospedaliera Padova" - }, - { - "author_name": "Luciano Flor", - "author_inst": "Azienda Ospedaliera Padova" - }, - { - "author_name": "Silvia Cocchio", - "author_inst": "University of Padua" - }, - { - "author_name": "Giulia Masi", - "author_inst": "University of Padua" - }, - { - "author_name": "Alessandro Sperduti", - "author_inst": "University of Padua" - }, - { - "author_name": "Lorenzo Cattarino", - "author_inst": "Imperial College London" - }, - { - "author_name": "Renato Salvador", - "author_inst": "University of Padua" - }, - { - "author_name": "Katy A.M. Gaythorpe", - "author_inst": "Imperial College London" - }, - { - "author_name": "- Imperial College London COVID-19 Response Team", - "author_inst": "-" - }, - { - "author_name": "Alessandra R Brazzale", - "author_inst": "University of Padua" + "author_name": "Philip J. Turk", + "author_inst": "Atrium Health" }, { - "author_name": "Stefano Toppo", - "author_inst": "University of Padua" + "author_name": "Shih-Hsiung Chou", + "author_inst": "Atrium Health" }, { - "author_name": "Marta Trevisan", - "author_inst": "University of Padua" + "author_name": "Marc A. Kowalkowski", + "author_inst": "Atrium Health" }, { - "author_name": "Vincenzo Baldo", - "author_inst": "University of Padua" + "author_name": "Pooja P. Palmer", + "author_inst": "Atrium Health" }, { - "author_name": "Christl A. Donnelly", - "author_inst": "Imperial College London; University of Oxford" + "author_name": "Jennifer S. Priem", + "author_inst": "Atrium Health" }, { - "author_name": "Neil M. Ferguson", - "author_inst": "Imperial College London" + "author_name": "Melanie D. Spencer", + "author_inst": "Atrium Health" }, { - "author_name": "Ilaria Dorigatti", - "author_inst": "Imperial College London" + "author_name": "Yhenneko J. Taylor", + "author_inst": "Atrium Health" }, { - "author_name": "Andrea Crisanti", - "author_inst": "University of Padua; Imperial College London" + "author_name": "Andrew D. McWilliams", + "author_inst": "Atrium Health" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.04.14.20065466", @@ -1516424,147 +1516390,51 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.16.045617", - "rel_title": "Single-cell analysis of human lung epithelia reveals concomitant expression of the SARS-CoV-2 receptor ACE2 with multiple virus receptors and scavengers in alveolar type II cells", + "rel_doi": "10.1101/2020.04.13.20063792", + "rel_title": "Multi-chain Fudan-CCDC model for COVID-19 -- a revisit to Singapore's case", "rel_date": "2020-04-17", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.16.045617", - "rel_abs": "The novel coronavirus SARS-CoV-2 was identified as the causative agent of the ongoing pandemic COVID 19. COVID-19-associated deaths are mainly attributed to severe pneumonia and respiratory failure. Recent work demonstrated that SARS-CoV-2 binds to angiotensin converting enzyme 2 (ACE2) in the lung. To better understand ACE2 abundance and expression patterns in the lung we interrogated our in-house single-cell RNA-sequencing dataset containing 70,085 EPCAM+ lung epithelial cells from paired normal and lung adenocarcinoma tissues. Transcriptomic analysis revealed a diverse repertoire of airway lineages that included alveolar type I and II, bronchioalveolar, club/secretory, quiescent and proliferating basal, ciliated and malignant cells as well as rare populations such as ionocytes. While the fraction of lung epithelial cells expressing ACE2 was low (1.7% overall), alveolar type II (AT2, 2.2% ACE2+) cells exhibited highest levels of ACE2 expression among all cell subsets. Further analysis of the AT2 compartment (n = 27,235 cells) revealed a number of genes co-expressed with ACE2 that are important for lung pathobiology including those associated with chronic obstructive pulmonary disease (COPD; HHIP), pneumonia and infection (FGG and C4BPA) as well as malarial/bacterial (CD36) and viral (DMBT1) scavenging which, for the most part, were increased in smoker versus light or non-smoker cells. Notably, DMBT1 was highly expressed in AT2 cells relative to other lung epithelial subsets and its expression positively correlated with ACE2. We describe a population of ACE2-positive AT2 cells that co-express pathogen (including viral) receptors (e.g. DMBT1) with crucial roles in host defense thus comprising plausible phenotypic targets for treatment of COVID-19.", - "rel_num_authors": 32, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.13.20063792", + "rel_abs": "BackgroundCOVID-19 has been impacting on the whole world critically and constantly since late December 2019. Rapidly increasing infections has raised intense world-wide attention. How to model the evolution of COVID-19 effectively and efficiently is of great significance for prevention and control.\n\nMethodsWe propose the multi-chain Fudan-CCDC model based on the original single-chain model in [8] to describe the evolution of COVID-19 in Singapore. Multi-chains can be considered as the superposition of several single chains with different characteristics. We identify parameters of models by minimizing the penalty function.\n\nResultsThe numerical simulation results exhibit the multichain model performs well on data fitting. Though unsteady the increments are, they could still fall within the range of {+/-}25% fluctuation from simulation results. It is predicted by multi-chain models that Singapore are experiencing a nonnegligible risk of explosive outbreak, thus stronger measures are urgently needed to contain the epidemic.\n\nConclusionThe multi-chain Fudan-CCDC model provides an effective way to early detect the appearance of imported infectors and super spreaders and forecast a second outbreak. It can also explain the data in those countries where the single-chain model shows deviation from the data.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Guangchun Han", - "author_inst": "Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Ansam Sinjab", - "author_inst": "Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Warapen Treekitkarnmongkol", - "author_inst": "Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Patrick Brennan", - "author_inst": "Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Kieko Hara", - "author_inst": "Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Kyle Chang", - "author_inst": "Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Elena Bogatenkova", - "author_inst": "Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Beatriz Sanchez-Espiridion", - "author_inst": "Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Carmen Behrens", - "author_inst": "Department of Thoracic, Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Boning Gao", - "author_inst": "Hamon Center for Therapeutic Oncology Research, University of Texas Southwestern, Dallas, TX, USA" - }, - { - "author_name": "Luc Girard", - "author_inst": "Hamon Center for Therapeutic Oncology Research, University of Texas Southwestern, Dallas, TX, USA" - }, - { - "author_name": "Jianjun Zhang", - "author_inst": "Department of Thoracic, Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Boris Sepesi", - "author_inst": "Department of Cardiovascular and Thoracic Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Tina Cascone", - "author_inst": "Department of Thoracic, Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Lauren Byers", - "author_inst": "Department of Thoracic, Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Don L. Gibbons", - "author_inst": "Department of Thoracic, Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Jichao Chen", - "author_inst": "Department of Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Seyed Javad Moghaddam", - "author_inst": "Department of Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Edwin J. Ostrin", - "author_inst": "Department of General Internal Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Junya Fujimoto", - "author_inst": "Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "Jerry Shay", - "author_inst": "Department of Cell Biology, University of Texas Southwestern, Dallas, TX, USA" - }, - { - "author_name": "John V. Heymach", - "author_inst": "Department of Thoracic, Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" - }, - { - "author_name": "John D. Minna", - "author_inst": "Hamon Center for Therapeutic Oncology Research, University of Texas Southwestern, Dallas, TX, USA" - }, - { - "author_name": "Steven Dubinett", - "author_inst": "Department of Medicine, The University of California Los Angeles, Los Angeles, CA, USA" - }, - { - "author_name": "Paul A. Scheet", - "author_inst": "Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" + "author_name": "Hanshuang Pan", + "author_inst": "Fudan University" }, { - "author_name": "Ignacio I. Wistuba", - "author_inst": "Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" + "author_name": "Nian Shao", + "author_inst": "Fudan University" }, { - "author_name": "Edward Hill", - "author_inst": "Lung Cancer Initiative at Johnson and Johnson, Lansdale, PA, USA" + "author_name": "Yue Yan", + "author_inst": "Shanghai University of Finance and Economics" }, { - "author_name": "Shannon Telesco", - "author_inst": "Lung Cancer Initiative at Johnson and Johnson, Lansdale, PA, USA" + "author_name": "Xinyue Luo", + "author_inst": "Shanghai University of Finance and Economics" }, { - "author_name": "Christopher Stevenson", - "author_inst": "Lung Cancer Initiative at Johnson and Johnson, Lansdale, PA, USA" + "author_name": "Shufen Wang", + "author_inst": "Fudan University" }, { - "author_name": "Avrum E. Spira", - "author_inst": "Lung Cancer Initiative at Johnson and Johnson, Lansdale, PA, USA and Section of Computational Biomedicine, Boston University, Boston, MA, USA" + "author_name": "Ling Ye", + "author_inst": "Daishan County Center for Disease Control and Prevention" }, { - "author_name": "Linghua Wang", - "author_inst": "Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" + "author_name": "Jin Cheng", + "author_inst": "Fudan University" }, { - "author_name": "Humam Kadara", - "author_inst": "Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA" + "author_name": "Wenbin Chen", + "author_inst": "Fudan University" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "genomics" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.16.044503", @@ -1518214,41 +1518084,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.15.20067199", - "rel_title": "Optimizing RT-PCR detection of SARS-CoV-2 for developing countries using pool testing", + "rel_doi": "10.1101/2020.04.15.20066050", + "rel_title": "Basic estimation-prediction techniques for Covid-19, and a prediction for Stockholm", "rel_date": "2020-04-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.15.20067199", - "rel_abs": "The global shortage of reagents and kits for nucleic acid extraction and molecular detection of SARS-CoV-2, requires new cost-effective strategies for the diagnosis of suspected COVID-19 cases, especially in countries that need to increase detection capacity. Pooled nucleic acid testing has been extensively used as a cost-effective strategy for HIV, HepB, HepC and influenza. Also, protocols dispensing of RNA extraction appears as an attractive option for detection of SARS-CoV-2. In this study, pooling nasopharyngeal samples with both automated and manual extraction proved reliable, and thus a potential efficient alternative for the diagnosis of suspected COVID-19 in developing countries.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.15.20066050", + "rel_abs": "Predicting future infections for covid-19 is essential in planning healthcare system as well as deciding on relaxed or strengthened preventive measures. Here a quick and simple estimation-prediction method for an urban area is presented, a method which only uses the observed initial doubling time and R0, and prediction is performed without or with preventive measures put in place. The method is applied to the urban area of Stockholm, and predictions indicate that the peak of infections happened in mid-April and infections start settling towards end of May.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Mauricio J Farfan", - "author_inst": "Universidad de Chile-Hospital Dr. Luis Calvo Mackenna" - }, - { - "author_name": "Juan P Torres", - "author_inst": "Universidad de Chile" - }, - { - "author_name": "Miguel ORyan", - "author_inst": "Universidad de Chile" - }, - { - "author_name": "Mauricio Olivares", - "author_inst": "Universidad de Chile" - }, - { - "author_name": "Pablo Gallardo", - "author_inst": "Universidad de Chile" - }, - { - "author_name": "Carolina Salas", - "author_inst": "Hospital Dr. Luis Calvo Mackenna" + "author_name": "Tom Britton", + "author_inst": "Stockholm University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1519324,49 +1519174,41 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.13.20060228", - "rel_title": "Basic reproduction number of 2019 Novel Coronavirus Disease in Major Endemic Areas of China: A latent profile analysis", + "rel_doi": "10.1101/2020.04.13.20059253", + "rel_title": "Age could be driving variable SARS-CoV-2 epidemic trajectories worldwide", "rel_date": "2020-04-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.13.20060228", - "rel_abs": "ObjectiveThe aim of the study is to analyze the latent class of basic reproduction number (R0) trend of 2019 novel coronavirus disease (COVID-19) in major endemic areas of China.\n\nMethodsThe provinces that reported more than 500 cases of COVID-19 till February 18, 2020 were selected as the major endemic area. The Verhulst model was used to fit the growth rate of cumulative confirmed cases. The R0 of COVID-19 was calculated using the parameters of severe acute respiratory syndrome (SARS) and COVID-19, respectively. The latent class of R0 was analyzed using a latent profile analysis model.\n\nResultsThe median R0 calculated from SARS and COVID-19 parameters were 1.84 - 3.18 and 1.74 - 2.91, respectively. The R0 calculated from the SARS parameters was greater than that of calculated from the COVID-19 parameters (Z = -4.782 - -4.623, P < 0.01). Both R0 can be divided into three latent classes. The initial value of R0 in class 1 (Shandong Province, Sichuan Province and Chongqing Municipality) was relatively low and decreases slowly. The initial value of R0 in class 2 (Anhui Province, Hunan Province, Jiangxi Province, Henan Province, Zhejiang Province, Guangdong Province and Jiangsu Province) was relatively high and decreases rapidly. Moreover, the initial value of R0 of class 3 (Hubei Province) was between that of class 1 and class 2, but the higher level of R0 lasts longer and decreases slowly.\n\nConclusionThe results indicated that overall trend of R0 has been falling with the strengthening of Chinas comprehensive prevention and control measures for COVID-19, however, presents regional differences.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.13.20059253", + "rel_abs": "BackgroundCurrent geographic spread of documented severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections shows heterogeneity. This study explores the role of age in potentially driving differentials in infection spread, epidemic potential, and rates of disease severity and mortality across countries.\n\nMethodsAn age-stratified deterministic mathematical model that describes SARS-CoV-2 transmission dynamics was applied to 159 countries and territories with a population [≥]1 million.\n\nResultsAssuming worst-case scenario for the pandemic, the results indicate that there could be stark regional differences in epidemic trajectories driven by differences in the distribution of the population by age. In the African Region (median age: 18.9 years), the median R0 was 1.05 versus 2.05 in the European Region (median age: 41.7 years), and the median (per 100 persons) for the infections rate was 22.5 (versus 69.0), for severe and/or critical disease cases rate was 3.3 (versus 13.0), and for death rate was 0.5 (versus 3.9).\n\nConclusionsAge could be a driver of variable SARS-CoV-2 epidemic trajectories worldwide. Countries with sizable adult and/or elderly populations and smaller children populations may experience large and rapid epidemics in absence of interventions. Meanwhile, countries with predominantly younger age cohorts may experience smaller and slower epidemics. These predictions, however, should not lead to complacency, as the pandemic could still have a heavy toll nearly everywhere.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Honglv Xu", - "author_inst": "School of Public Health, Anhui Medical University" - }, - { - "author_name": "Min Yuan", - "author_inst": "School of Health Service Management, Anhui Medical University" - }, - { - "author_name": "Liya Ma", - "author_inst": "School of Public Health, Anhui Medical University" + "author_name": "Houssein H. Ayoub", + "author_inst": "Department of Mathematics, Statistics, and Physics, Qatar University, Doha, Qatar" }, { - "author_name": "Meng Liu", - "author_inst": "School of Public Health, Anhui Medical University" + "author_name": "Hiam Chemaitelly", + "author_inst": "Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar" }, { - "author_name": "Yi Zhang", - "author_inst": "School of Public Health, Anhui Medical University" + "author_name": "Shaheen Seedat", + "author_inst": "Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar" }, { - "author_name": "Wenwen Liu", - "author_inst": "School of Public Health, Anhui Medical University" + "author_name": "Ghina R. Mumtaz", + "author_inst": "Department of Epidemiology and Population Health, American University of Beirut, Beirut, Lebanon" }, { - "author_name": "Hong Gan", - "author_inst": "School of Public Health, Anhui Medical University" + "author_name": "Monia Makhoul", + "author_inst": "Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar" }, { - "author_name": "Fangbiao Tao", - "author_inst": "School of Public Health, Anhui Medical University" + "author_name": "Laith J Abu-Raddad", + "author_inst": "Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1520606,21 +1520448,29 @@ "category": "anesthesia" }, { - "rel_doi": "10.1101/2020.04.13.20064014", - "rel_title": "Quantifying interpersonal contact in the United States during the spread of COVID-19: first results from the Berkeley Interpersonal Contact Study", + "rel_doi": "10.1101/2020.04.13.20063768", + "rel_title": "Sequential data assimilation of the stochastic SEIR epidemic model for regional COVID-19 dynamics", "rel_date": "2020-04-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.13.20064014", - "rel_abs": "SARS-CoV-2 is transmitted primarily through close, person-to-person interactions. In the absence of a vaccine, interventions focused on physical distancing have been widely used to reduce community transmission. These physical distancing policies can only control the spread of SARS-CoV-2 if they are able to reduce the amount of close interpersonal contact in a population. To quantify the impact of these policies over the first months of the COVID-19 pandemic in the United States, we conducted three waves of contact surveys between March 22 and June 23, 2020. We find that rates of interpersonal contact have been dramatically reduced at all ages in the US, with an 82% (95% CI:80% - 83%) reduction in the average number of daily contacts observed during the first wave compared to pre-pandemic levels. We find that this decline reduced the reproduction number, R0, to below one in March and early April (0.66, 95% CI:0.35 - 0.88). However, with easing of physical distancing measures, we find increases in interpersonal contact rates over the subsequent two waves, pushing R0 above 1. We also find significant differences in numbers of reported contacts by age, gender, race and ethnicity. Certain demographic groups, including people under 45, males, and Black and Hispanic respondents, have significantly higher contact rates than the rest of the population. Tracking changes in interpersonal contact patterns can provide rapid assessments of the impact of physical distancing policies over the course of the pandemic and help identify at-risk populations.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.13.20063768", + "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWNewly emerging pandemics like COVID-19 call for predictive models to implement precisely tuned responses to limit their deep impact on society. Standard epidemic models provide a theoretically well-founded dynamical description of disease incidence. For COVID-19 with infectiousness peaking before and at symptom onset, the SEIR model explains the hidden build-up of exposed individuals which creates challenges for containment strategies. However, spatial heterogeneity raises questions about the adequacy of modeling epidemic outbreaks on the level of a whole country. Here, we show that by applying sequential data assimilation to the stochastic SEIR epidemic model, we can capture the dynamic behavior of outbreaks on a regional level. Regional modeling, with relatively low numbers of infected and demographic noise, accounts for both spatial heterogeneity and stochasticity. Based on adapted models, short-term predictions can be achieved. Thus, with the help of these sequential data assimilation methods, more realistic epidemic models are within reach.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Dennis Feehan", - "author_inst": "University of California, Berkeley" + "author_name": "Ralf Engbert", + "author_inst": "University of Potsdam, Germany" }, { - "author_name": "Ayesha Mahmud", - "author_inst": "University of California, Berkeley" + "author_name": "Maximilian M. Rabe", + "author_inst": "University of Potsdam, Germany" + }, + { + "author_name": "Reinhold Kliegl", + "author_inst": "University of Potsdam, Germany" + }, + { + "author_name": "Sebastian Reich", + "author_inst": "University of Potsdam, Germany" } ], "version": "1", @@ -1521608,29 +1521458,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.11.20061481", - "rel_title": "AN EPIDEMIOLOGICAL MODEL TO AID DECISION-MAKING FOR COVID-19 CONTROL IN SRI LANKA", + "rel_doi": "10.1101/2020.04.12.20063008", + "rel_title": "Prediction of the time evolution of the COVID-19 disease in Guadeloupe with a stochastic evolutionary model", "rel_date": "2020-04-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.11.20061481", - "rel_abs": "BackgroundSri Lanka diagnosed its first local case of COVID-19 on 11 March 2020. The government acted swiftly to contain transmission, with extensive public health measures. At the end of 30 days, Sri Lanka had 197 cases, 54 recovered and 7 deaths; a staged relaxing of the lockdown is now underway. This paper proposes a theoretical basis for estimating the limits within which transmission should be constrained in order to ensure that the case load remains within the capacity of the health system.\n\nMethodsWe used Susceptible, Infected, Recovered model to estimate the ICU bed requirement at different levels of R0 values after lockout. We developed a web application that enables visualization of cases and ICU bed requirements with time, with adjustable parameters that include: population exposed; proportion asymptomatic; number of active and recovered cases; infectious period; R0 or doubling time; proportion critically ill; available ICU beds and duration of ICU stay.\n\nResultsThe three-day moving average of the caseload suggested two waves of transmission from Day 0 to 17 (R0=3.32, 95% CI 1.85 - 5.41) and from Day 18 - 30 (R=1.25, 95%CI: 0.93 - 1.63). We estimate that if there are 156 active cases with 91 recovered at the time of lockout, and R increases to 1.5 (doubling time 19 days), under the standard parameters for Sri Lanka, the ICU bed capacity of 300 is likely to be saturated by about 100 days, signalled by 18 new infections (95% CI 15 - 22) on Day 14 after lockout.\n\nConclusionOur model suggests that to ensure that the case load remains within the available capacity of the health system after lockout, transmission should not exceed R=1.5. This model and the web-based application may be useful in other low- and middle-income countries which have similar constraints on health resources.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.12.20063008", + "rel_abs": "Predictions on the time-evolution of the number of severe and critical cases of COVID-19 patients in Guadeloupe are presented. A stochastic model is purposely developed to explicitly account for the entire population ([~=]400000 inhabitants) of Guadeloupe. The available data for Guadeloupe are analysed and combined with general characteristics of the COVID-19 to constrain the parameters of the model. The time-evolution of the number of cases follows the well-known exponential-like model observed at the very beginning of a pandemic outbreak. The exponential growth of the number of infected individuals is controlled by the so-called basic reproductive number, R0, defined as the likely number of additional cases generated by a single infectious case during its infectious period TI. Because of the rather long duration of infectious period ([~=]14 days) a high rate of contamination is sustained during several weeks after the beginning of the containment period. This may constitute a source of discouragement for people restrained to respect strict containment rules. It is then unlikely that, during the containment period, R0 falls to zero. Fortunately, our models shows that the containment effects are not much sensitive to the exact value of R0 provided we have R0 < 0.6. For such conditions, we show that the number of severe and critical cases is highly tempered about 4 to 6 weeks after the beginning of the containment. Also, the maximum number of critical cases (i.e. the cases that may exceed the hospitals intensive care capacity) remains near 30 when R0 < 0.6. For a larger R0 = 0.8 a slower decrease of the number of critical cases occurs, leading to a larger number of deceased patients. This last example illustrates the great importance to maintain an as low as possible R0 during and after the containment period. The rather long delay between the beginning of the containment and the appearance of the slowing-down of the rate of contamination puts a particular strength on the communication and sanitary education of people. To be mostly efficient, this communication must be done by a locally recognised medical staff. We believe that this point is a crucial matter of success. Appendix Posterior model assessment with data acquired after April 11, 2020 added in a second version of the paper compares the model predictions with the data acquired from April 12 to May 25 2020, after the construction of the model discussed in the present study. The remarkable agreement between the model predictions and the data may be explained by the good quality of first-hand data used to constrain the model, the ability of the stochastic approach to integrate new information and stability of the sanitary situation due to the respect of the recommendations emitted by medical and administrative authorities by the guadeloupean population.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Dileepa S Ediriweera", - "author_inst": "Faculty of Medicine, University of Kelaniya, Sri Lanka" + "author_name": "MERIEM ALLALI", + "author_inst": "CHU POINTE A PITRE, URGENCES SAMU SMUR" }, { - "author_name": "Nilanthi R de Silva", - "author_inst": "Faculty of Medicine, University of Kelaniya, Sri Lanka" + "author_name": "PATRICK PORTECOP", + "author_inst": "CHU POINTE A PITRE, HEAD OF SAMU SMUR UNIT" }, { - "author_name": "Neelika G Malavige", - "author_inst": "Faculty of Medical Sciences, University of Sri Jayewardenepura, Sri Lanka" + "author_name": "MICHEL CARLES", + "author_inst": "CHU POINTE A PITRE, HEAD OF CRITICAL CARE DEPARTMENT" }, { - "author_name": "H Janaka de Silva", - "author_inst": "Faculty of Medicine, University of Kelaniya, Sri Lanka" + "author_name": "DOMINIQUE GIBERT", + "author_inst": "LYON 1 UNIVERSITY OBSERVATORY" } ], "version": "1", @@ -1522881,21 +1522731,45 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.04.10.20060863", - "rel_title": "Time-Varying COVID-19 Reproduction Number in the United States", + "rel_doi": "10.1101/2020.04.12.20062604", + "rel_title": "Clinical characteristics of 34 COVID-19 patients admitted to ICU in Hangzhou, China", "rel_date": "2020-04-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.10.20060863", - "rel_abs": "The basic reproduction number is the average number of people to whom an infected person transmits the infection when virtually all individuals in a population are susceptible. We sought to calculate the current reproduction number for COVID-19 for each state in the United States. For the entire United States, the time-varying reproduction number declined from 4.02 to 1.51 between March 17 and April 1, 2020. We also found that the time-varying reproduction number for COVID-19 has declined in most states over the same two week period which suggests that social isolation measures may be having a beneficial effect.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.12.20062604", + "rel_abs": "IntroductionThe purpose of the study was to summarize the clinical and laboratory characteristics of the coronavirus disease 2019 patients admitted to intensive care unit.\n\nMethodsWe tracked the data until March 5, 2020. The cases in our cohort were divided into cases only received noninvasive ventilation (NIV) and cases required invasive mechanical ventilation (IMV). The characteristics between the two groups were compared.\n\nResults34 cases were included in the study. The complications rate (including, acute liver injury, acute cardiac injury and acute kidney injury) were higher in IMV cases. Lymphocytopenia and neutrophilia occurred in most cases in both groups on the admission day, however, lymphocyte levels dropped progressively and more severe lymphopenia occurred in IMV group. Increased amounts of plasma IL-6 and IL-10 were found in both groups on the admission day, the progressive decrease of which occurred in NIV cases rather than IMV cases, and the levels were higher in IMV cases during hospitalization.\n\nConclusionsLymphocytopenia, neutrophilia, and increase of IL-6 and IL-10 occurred in SARS-CoV-2 infected patients in ICU, however, the dynamics of those were significantly different in IMV cases and NIV cases during hospitalization.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Douglas Gunzler", - "author_inst": "Case Western Reserve University" + "author_name": "Yi Zheng", + "author_inst": "The First Affiliated Hospital, College of Medicine, Zhejiang University" }, { - "author_name": "Ashwini R Sehgal", - "author_inst": "Case Western Reserve University" + "author_name": "Lijun Sun", + "author_inst": "The First Affiliated Hospital, College of Medicine, Zhejiang University" + }, + { + "author_name": "Mi Xu", + "author_inst": "The First Affiliated Hospital, College of Medicine, Zhejiang University" + }, + { + "author_name": "Jian Pan", + "author_inst": "The First Affiliated Hospital, College of Medicine, Zhejiang University" + }, + { + "author_name": "Yuntao Zhang", + "author_inst": "The First Affiliated Hospital, College of Medicine, Zhejiang University" + }, + { + "author_name": "Xueling Fang", + "author_inst": "The First Affiliated Hospital, College of Medicine, Zhejiang University" + }, + { + "author_name": "Qiang Fang", + "author_inst": "The First Affiliated Hospital, College of Medicine, Zhejiang University" + }, + { + "author_name": "Hongliu Cai", + "author_inst": "The First Affiliated Hospital, College of Medicine, Zhejiang University" } ], "version": "1", @@ -1524383,51 +1524257,79 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.04.14.042010", - "rel_title": "Humanized Single Domain Antibodies Neutralize SARS-CoV-2 by Targeting Spike Receptor Binding Domain", + "rel_doi": "10.1101/2020.04.14.040204", + "rel_title": "Relevance of enriched expression of SARS-CoV-2 binding receptor ACE2 in gastrointestinal tissue with pathogenesis of digestive symptoms, diabetes-associated mortality, and disease recurrence in COVID-19 patients", "rel_date": "2020-04-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.14.042010", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread across more than 200 countries and regions, leading to an unprecedented medical burden and live lost. SARS-CoV-2 specific antivirals or prophylactic vaccines are not available. Neutralizing antibodies provide efficient blockade for viral infection and are a promising category of biological therapies. Using SARS-CoV-2 spike RBD as a bait, we have discovered a panel of humanized single domain antibodies (sdAbs). These sdAbs revealed binding kinetics with the equilibrium dissociation constant (KD) of 0.7~33 nM. The monomeric sdAbs showed half maximal inhibitory concentration (IC50) of 0.003~0.3 g/mL in pseudotyped particle neutralization assay, and 0.23~0.50 g/mL in authentic SARS-CoV-2 neutralization assay. Competitive ligand-binding data suggested that the sdAbs either completely blocked or significantly inhibited the association between SARS-CoV-2 RBD and viral entry receptor ACE2. Finally, we showed that fusion of the human IgG1 Fc to sdAbs improved their neutralization activity by tens of times. These results reveal the novel SARS-CoV-2 RBD targeting sdAbs and pave a road for antibody drug development.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.14.040204", + "rel_abs": "IntroductionCOVID-19 is caused by a new strain of coronavirus called SARS-coronavirus-2 (SARS-CoV-2), which is a positive sense single strand RNA virus. In humans, it binds to angiotensin converting enzyme 2 (ACE2) with the help a structural protein on its surface called the S-spike. Further, cleavage of the viral spike protein (S) by the proteases like transmembrane serine protease 2 (TMPRSS2) or Cathepsin L (CTSL) is essential to effectuate host cell membrane fusion and virus infectivity. COVID-19 poses intriguing issues with imperative relevance to clinicians. The pathogenesis of GI symptoms, diabetes-associated mortality, and disease recurrence in COVID-19 are of particular relevance because they cannot be sufficiently explained from the existing knowledge of the viral diseases. Tissue specific variations of SARS-CoV-2 cell entry related receptors expression in healthy individuals can help in understanding the pathophysiological basis the aforementioned collection of symptoms.\n\nMaterials and MethodsThe data were downloaded from the Human Protein Atlas available at (https://www.proteinatlas.org/humanproteome/sars-cov-2) and the tissue specific expressions (both mRNA and protein) of ACE2 and TMPRSS2 as yielded from the studies with RNA sequencing and immunohistochemistry (IHC) were analyzed as a function of the various components of the digestive tract. A digestive system specific functional enrichment map of ACE2 gene was created using g:profiler (https://biit.cs.ut.ee/gprofiler/gost) utility and the data were visualized using Cytoscape software, version 3.7.2 (https://cytoscape.org/).\n\nResultsThe correlated expression (transcriptomic and proteomic) of ACE2 (to which SARS-CoV-2 binds through the S-spike) was found to be enriched in the lower gastrointestinal tract (GIT) (highest in small intestine, followed by colon and rectum), and was undetectable in the upper GIT components: mouth cavity (tongue, oral mucosa, and salivary glands), esophagus, and stomach. High expression of ACE2 was noted in the glandular cells as well as in the enterocytes in the lining epithelium (including brush border epithelium). Among other digestive system organs, Gall bladder (GB) showed high expression of ACE2 in glandular cells, while any protein expression was undetectable in liver and pancreas. TMPRSS2 was found enhanced in GIT and exocrine glands of pancreas, and co-localized with ACE2 in enterocytes.\n\nConclusionsBased on the findings of this study and supportive evidence from the literature we propose that a SARS-CoV-2 binding with ACE2 mediates dysregulation of the sodium dependent nutrient transporters and hence may be a plausible basis for the digestive symptoms in COVID-19 patients. ACE2 mediated dysregulation of sodium dependent glucose transporter (SGLT1 or SLC5A1) in the intestinal epithelium also links it to the pathogenesis of diabetes mellitus which can be a possible reason for the associated mortality in COVID-19 patients with diabetes. High expression of ACE2 in mucosal cells of the intestine and GB make these organs potential sites for the virus entry and replication. Continued replication of the virus at these ACE2 enriched sites may be a basis for the disease recurrence reported in some, thought to be cured, patients.\n\nGraphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Xiaojing Chi", - "author_inst": "NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing" + "author_name": "- Etiologically Elusive Disorders Research Network (EEDRN)", + "author_inst": "-" }, { - "author_name": "Xiuying Liu", - "author_inst": "NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing" + "author_name": "Ashutosh Kumar", + "author_inst": "Department of Anatomy, All India Institute of Medical Sciences (AIIMS), Patna, India" }, { - "author_name": "Conghui Wang", - "author_inst": "NHC Key Laboratory of Systems Biology of Pathogens and Christophe Merieux Laboratory, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Pek" + "author_name": "Muneeb A. Faiq", + "author_inst": "New York University (NYU) Langone Health Center, NYU Robert I Grossman School of Medicine, New York, New York, USA" }, { - "author_name": "Xinhui Zhang", - "author_inst": "NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing" + "author_name": "Vikas Pareek", + "author_inst": "National Brain Research center" }, { - "author_name": "Lili Ren", - "author_inst": "NHC Key Laboratory of Systems Biology of Pathogens and Christophe Merieux Laboratory, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Pek" + "author_name": "Khursheed Raza", + "author_inst": "Department of Anatomy, All India Institute of Medical Sciences, Deoghar, India" }, { - "author_name": "Qi Jin", - "author_inst": "NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing" + "author_name": "Ravi K. Narayan", + "author_inst": "Department of Anatomy, All India Institute of Medical Sciences (AIIMS), Patna, India" }, { - "author_name": "Jianwei Wang", - "author_inst": "NHC Key Laboratory of Systems Biology of Pathogens and Christophe Merieux Laboratory, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Pek" + "author_name": "Pranav Prasoon", + "author_inst": "Pittsburgh Center for Pain Research, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA" }, { - "author_name": "Wei Yang", - "author_inst": "NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing" + "author_name": "Pavan Kumar", + "author_inst": "Department of Pediatrics, Medical University of South Carolina, Charleston, USA" + }, + { + "author_name": "Maheswari Kulandhasamy", + "author_inst": "Department of Biochemistry, Maulana Azad Medical College (MAMC), New Delhi, India" + }, + { + "author_name": "Chiman Kumari", + "author_inst": "Department of Anatomy, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India" + }, + { + "author_name": "Kamla Kant", + "author_inst": "Department of Microbiology, All India Institute of Medical Sciences (AIIMS), Bhatinda, India" + }, + { + "author_name": "Himanshu N. Singh", + "author_inst": "TAGC-INSERM, U1090, Aix Marseille University, Marseille, France" + }, + { + "author_name": "Rizwana Qadri", + "author_inst": "Neuro-oncology Laboratory, Rockefeller University, New York, New York, USA" + }, + { + "author_name": "Sada N. Pandey", + "author_inst": "Department of Zoology, Banaras Hindu University (BHU), Varanasi, India" + }, + { + "author_name": "Santosh Kumar", + "author_inst": "Department of Anesthesiology and Critical Care Medicine, School of Medicine, Johns Hopkins University, Baltimore, USA" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "pathology" }, { "rel_doi": "10.1101/2020.04.14.041962", @@ -1525449,133 +1525351,25 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.04.10.20060699", - "rel_title": "No evidence of clinical efficacy of hydroxychloroquine in patients hospitalized for COVID-19 infection with oxygen requirement: results of a study using routinely collected data to emulate a target trial", + "rel_doi": "10.1101/2020.04.10.20061325", + "rel_title": "Potency and timing of antiviral therapy as determinants of duration of SARS CoV-2 shedding and intensity of inflammatory response", "rel_date": "2020-04-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.10.20060699", - "rel_abs": "BackgroundTreatments are urgently needed to prevent respiratory failure and deaths from coronavirus disease 2019 (COVID-19). Hydroxychloroquine (HCQ) has received worldwide attention because of positive results from small studies.\n\nMethodsWe used data collected from routine care of all adults in 4 French hospitals with documented SARS-CoV-2 pneumonia and requiring oxygen [≥] 2 L/min to emulate a target trial aimed at assessing the effectiveness of HCQ at 600 mg/day. The composite primary endpoint was transfer to intensive care unit (ICU) within 7 days from inclusion and/or death from any cause. Analyses were adjusted for confounding factors by inverse probability of treatment weighting.\n\nResultsThis study included 181 patients with SARS-CoV-2 pneumonia; 84 received HCQ within 48 hours of admission (HCQ group) and 97 did not (no-HCQ group). Initial severity was well balanced between the groups. In the weighted analysis, 20.2% patients in the HCQ group were transferred to the ICU or died within 7 days vs 22.1% in the no-HCQ group (16 vs 21 events, relative risk [RR] 0.91, 95% CI 0.47-1.80). In the HCQ group, 2.8% of the patients died within 7 days vs 4.6% in the no-HCQ group (3 vs 4 events, RR 0.61, 95% CI 0.13-2.89), and 27.4% and 24.1%, respectively, developed acute respiratory distress syndrome within 7 days (24 vs 23 events, RR 1.14, 95% CI 0.65-2.00). Eight patients receiving HCQ (9.5%) experienced electrocardiogram modifications requiring HCQ discontinuation.\n\nInterpretationThese results do not support the use of HCQ in patients hospitalised for documented SARS-CoV-2-positive hypoxic pneumonia.", - "rel_num_authors": 30, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.10.20061325", + "rel_abs": "Treatments are desperately needed to lower the hospitalization and case fatality rates of SARS CoV-2 infection. In order to meaningfully impact the COVID-19 pandemic, promising antiviral therapies must be identified within the next several months. However, the number of clinical trials that can be performed in this timeframe is limited. We therefore developed a mathematical model which allows projection of all possible therapeutic approaches. Our model recapitulates off-treatment viral dynamics and predicts a three-phase immune response. Addition of treatment with remdesivir, hydroxychloroquine, neutralizing antibodies or cellular immunotherapy demonstrates that if in vivo drug potency is high, then rapid elimination of virus is possible. Potent therapies dosed soon after peak viral load when infected people typically develop symptoms, are predicted to decrease shedding duration and intensity of the effector immune response, but to have little effect on viral area under the curve, which is driven by high levels of early SARS CoV-2 replication. Potent therapy dosed prior to peak viral load, when infection is usually pre-symptomatic, is predicted to be the only option to lower viral area under the curve. We also identify that clinically meaningful drug resistance is less likely to emerge with a highly potent agent that is dosed after peak viral load. Our results support an early test and treat approach for COVID-19, but also demonstrate the need to identify early viral shedding kinetic features that are the most predictive surrogates of clinical severity and transmission risk.\n\nOne Sentence SummaryWe developed a mathematical model to predict the outcomes of different possible COVID-19 treatments.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Matthieu Mahevas", - "author_inst": "APHP" - }, - { - "author_name": "Viet-Thi Tran", - "author_inst": "APHP" - }, - { - "author_name": "Mathilde Roumier", - "author_inst": "Foch Hospital" - }, - { - "author_name": "Amelie Chabrol", - "author_inst": "Centre Hospitalier Sud Francilien" - }, - { - "author_name": "Romain Paule", - "author_inst": "Foch Hospital" - }, - { - "author_name": "Constance Guillaud", - "author_inst": "APHP" - }, - { - "author_name": "Sebastien Gallien", - "author_inst": "APHP" - }, - { - "author_name": "Raphael Lepeule", - "author_inst": "APHP" - }, - { - "author_name": "Tali-Anne Szwebel", - "author_inst": "APHP" - }, - { - "author_name": "Xavier Lescure", - "author_inst": "APHP" - }, - { - "author_name": "Frederic Schlemmer", - "author_inst": "APHP" - }, - { - "author_name": "Marie Matignon", - "author_inst": "APHP" - }, - { - "author_name": "Mehdi Khellaf", - "author_inst": "APHP" - }, - { - "author_name": "Etienne Crickx", - "author_inst": "APHP" - }, - { - "author_name": "Benjamin Terrier", - "author_inst": "APHP" - }, - { - "author_name": "Caroline Morbieu", - "author_inst": "APHP" - }, - { - "author_name": "Paul Legendre", - "author_inst": "APHP" - }, - { - "author_name": "Julien Dang", - "author_inst": "INSERM" - }, - { - "author_name": "Yoland Schoindre", - "author_inst": "Foch Hospital" - }, - { - "author_name": "Jean-Michel Pawlotski", - "author_inst": "APHP" - }, - { - "author_name": "Marc Michel", - "author_inst": "APHP" - }, - { - "author_name": "Elodie Perrodeau", - "author_inst": "APHP" - }, - { - "author_name": "Nicolas Carlier", - "author_inst": "APHP" - }, - { - "author_name": "Nicolas Roche", - "author_inst": "APHP" - }, - { - "author_name": "Victoire De Lastours", - "author_inst": "APHP" - }, - { - "author_name": "Luc Mouthon", - "author_inst": "APHP" - }, - { - "author_name": "Etienne Audureau", - "author_inst": "APHP" - }, - { - "author_name": "Philippe Ravaud", - "author_inst": "APHP" + "author_name": "Ashish Goyal", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "Bertrand Godeau", - "author_inst": "APHP" + "author_name": "E. Fabian Cardozo-Ojeda", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "Nathalie Costedoat", - "author_inst": "APHP" + "author_name": "Joshua T Schiffer", + "author_inst": "Fred Hutchinson Cancer Research Center" } ], "version": "1", @@ -1526951,27 +1526745,55 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.04.10.20060459", - "rel_title": "Global COVID-19 transmission rate is influenced by precipitation seasonality and the speed of climate temperature warming", + "rel_doi": "10.1101/2020.04.12.038554", + "rel_title": "The origin and underlying driving forces of the SARS-CoV-2 outbreak", "rel_date": "2020-04-14", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.10.20060459", - "rel_abs": "The novel coronavirus disease 2019 (COVID-19) became a rapidly spreading worldwide epidemic; thus, it is a global priority to reduce the speed of the epidemic spreading. Several studies predicted that high temperature and humidity could reduce COVID-19 transmission. However, exceptions exist to this observation, further thorough examinations are thus needed for their confirmation. In this study, therefore, we used a global dataset of COVID-19 cases and global climate databases and comprehensively investigated how climate parameters could contribute to the growth rate of COVID-19 cases while statistically controlling for potential confounding effects using spatial analysis. We also confirmed that the growth rate decreased with the temperature; however, the growth rate was affected by precipitation seasonality and warming velocity rather than temperature. In particular, a lower growth rate was observed for a higher precipitation seasonality and lower warming velocity. These effects were independent of population density, human life quality, and travel restrictions. The results indicate that the temperature effect is less important compared to these intrinsic climate characteristics, which might thus be useful for explaining the exceptions. However, the contributions of the climate parameters to the growth rate were moderate; rather, the contribution of travel restrictions in each country was more significant. Although our findings are preliminary owing to data-analysis limitations, they may be helpful when predicting COVID-19 transmission.", - "rel_num_authors": 2, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.12.038554", + "rel_abs": "The spread of SARS-CoV-2 since December 2019 has become a pandemic and impacted many aspects of human society. Here, we analyzed genetic variation of SARS-CoV-2 and its related coronavirus and found the evidence of intergenomic recombination. After correction for mutational bias, analysis of 137 SARS-CoV-2 genomes as of 2/23/2020 revealed the excess of low frequency mutations on both synonymous and nonsynonymous sites which is consistent with recent origin of the virus. In contrast to adaptive evolution previously reported for SARS-CoV in its brief epidemic in 2003, our analysis of SARS-CoV-2 genomes shows signs of relaxation of selection. The sequence similarity of the spike receptor binding domain between SARS-CoV-2 and a sequence from pangolin is probably due to an ancient intergenomic introgression. Therefore, SARS-CoV-2 might have cryptically circulated within humans for years before being recently noticed. Data from the early outbreak and hospital archives are needed to trace its evolutionary path and reveal critical steps required for effective spreading. Two mutations, 84S in orf8 protein and 251V in orf3 protein, occurred coincidentally with human intervention. The 84S first appeared on 1/5/2020 and reached a plateau around 1/23/2020, the lockdown of Wuhan. 251V emerged on 1/21/2020 and rapidly increased its frequency. Thus, the roles of these mutations on infectivity need to be elucidated. Genetic diversity of SARS-CoV-2 collected from China was two time higher than those derived from the rest of the world. In addition, in network analysis, haplotypes collected from Wuhan city were at interior and have more mutational connections, both of which are consistent with the observation that the outbreak of cov-19 was originated from China.\n\nSUMMARYIn contrast to adaptive evolution previously reported for SARS-CoV in its brief epidemic, our analysis of SARS-CoV-2 genomes shows signs of relaxation of selection. The sequence similarity of the spike receptor binding domain between SARS-CoV-2 and a sequence from pangolin is probably due to an ancient intergenomic introgression. Therefore, SARS-CoV-2 might have cryptically circulated within humans for years before being recently noticed. Data from the early outbreak and hospital archives are needed to trace its evolutionary path and reveal critical steps required for effective spreading. Two mutations, 84S in orf8 protein and 251V in orf3 protein, occurred coincidentally with human intervention. The 84S first appeared on 1/5/2020 and reached a plateau around 1/23/2020, the lockdown of Wuhan. 251V emerged on 1/21/2020 and rapidly increased its frequency. Thus, the roles of these mutations on infectivity need to be elucidated.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Katsumi Chiyomaru", - "author_inst": "Kyushu Institute of Technology" + "author_name": "Shu-Miaw Chaw", + "author_inst": "Biodiversity Research Center, Academia Sinica" + }, + { + "author_name": "Jui-Hung Tai", + "author_inst": "Biodiversity Research Center, Academia Sinica" }, { - "author_name": "Kazuhiro Takemoto", - "author_inst": "Kyushu Institute of Technology" + "author_name": "Shi-Lun Chen", + "author_inst": "Department of Life Science, National Taiwan Normal University" + }, + { + "author_name": "Chia-Hung Hsieh", + "author_inst": "Department of Forestry and Nature Conservation, Chinese Culture University" + }, + { + "author_name": "Sui-Yuan Chang", + "author_inst": "Department of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University" + }, + { + "author_name": "Shiou-Hwei Yeh", + "author_inst": "Department of Microbiology, College of Medicine, National Taiwan University" + }, + { + "author_name": "Wei-Shiung Yang", + "author_inst": "Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University" + }, + { + "author_name": "Pei-Jer Chen", + "author_inst": "Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University" + }, + { + "author_name": "Hurng-Yi Wang", + "author_inst": "Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "type": "new results", + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2020.04.11.20061432", @@ -1528417,27 +1528239,27 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.04.13.038752", - "rel_title": "Bioinformatic characterization of angiotensin-converting enzyme 2, the entry receptor for SARS-CoV-2", - "rel_date": "2020-04-13", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.13.038752", - "rel_abs": "The World Health Organization declared the COVID-19 epidemic a public health emergency of international concern on March 11th, 2020, and the pandemic is rapidly spreading worldwide. COVID-19 is caused by a novel coronavirus SARS-CoV-2, which enters human target cells via angiotensin converting enzyme 2 (ACE2). We used a number of bioinformatics tools to computationally characterize ACE2 by determining its cell-specific expression in trachea, lung, and small intestine, derive its putative functions, and predict transcriptional regulation. The small intestine expressed higher levels of ACE2 than any other organ. The large intestine, kidney and testis showed moderate signals, whereas the signal was weak in the lung. Single cell RNA-Seq data from trachea indicated positive signals along the respiratory tract in key protective cell types including club, goblet, proliferating, and ciliary epithelial cells; while in lung the ratio of ACE2-expressing cells was low in all cell types (<2.6%), but was highest in vascular endothelial and goblet cells. Gene ontology analysis suggested that, besides its classical role in renin-angiotensin system, ACE2 may be functionally associated with angiogenesis/blood vessel morphogenesis. Using a novel tool for the prediction of transcription factor binding sites we identified several putative binding sites within two tissue-specific promoters of the ACE2 gene. Our results also confirmed that age and gender play no significant role in the regulation of ACE2 mRNA expression in the lung.\n\nIMPORTANCEVaccines and new medicines are urgently needed to prevent spread of COVID-19 pandemic, reduce the symptoms, shorten the duration of disease, prevent virus spread in the body, and most importantly to save lives. One of the key drug targets could be angiotensin-converting enzyme 2 (ACE2), which is a crucial receptor for the corona virus (SARS-CoV-2). It is known that SARS coronavirus infections lead to worse outcome in the elderly and in males. Therefore, one aim of the present study was to investigate whether age or sex could contribute to the regulation of ACE2 expression. We also decided to explore the transcriptional regulation of ACE2 gene expression. Since data on ACE2 distribution is still conflicting, we aimed to get a more comprehensive view of the cell types expressing the receptor of SARS-CoV-2. Finally, we studied the coexpression of ACE2 with other genes and explored its putative functions using gene ontology enrichment analysis.", + "rel_doi": "10.1101/2020.04.11.20061424", + "rel_title": "Blueprint for a Pop-up SARS-CoV-2 Testing Lab", + "rel_date": "2020-04-12", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.11.20061424", + "rel_abs": "The appearance and spread of the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) led to the official declaration of a global pandemic, with states in the US implementing shelter-in-place orders at an unprecedented scale. SARS-CoV-2 has a robust person-to-person transmission rate and an asymptomatic period of two weeks or more, leading to widespread infection that has overwhelmed healthcare infrastructures around the globe. Effective public health measures require extensive, accurate, and rapid testing to determine infection rates. Here we describe the strategy we used to establish a CLIA-licensed clinical laboratory to perform a validated Laboratory-Developed Test (LDT) for SARS-CoV-2 in Berkeley, California and the surrounding Bay Area community. Our procedures for implementing the technical, regulatory, and data management workstreams necessary for clinical sample processing provide a roadmap to aid others in setting up similar testing centers.\n\nNote on Nomenclaturein accordance with established virology and infectious disease nomenclature, throughout this document we use \"SARS-CoV-2\" to refer to the viral agent causing infection and \"COVID-19\" to refer to the human infectious disease caused by that viral agent.", "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Harlan Barker", - "author_inst": "Faculty of Medicine and Health Technology, Tampere University and Fimlab Ltd, Tampere University Hospital, Finland" + "author_name": "- Innovative Genomics Institute SARS-CoV-2 Testing Consortium", + "author_inst": "" }, { - "author_name": "Seppo Parkkila", - "author_inst": "Faculty of Medicine and Health Technology, Tampere University and Fimlab Ltd, Tampere University Hospital, Finland" + "author_name": "Jennifer A. Doudna", + "author_inst": "University of California Berkeley" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "bioinformatics" + "license": "cc_by_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2020.04.10.036533", @@ -1529743,51 +1529565,79 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.08.20056630", - "rel_title": "A first study on the impact of current and future control measures on the spread of COVID-19 in Germany", + "rel_doi": "10.1101/2020.04.09.20056374", + "rel_title": "Mental health status of the general population, healthcare professionals, and university students during 2019 coronavirus disease outbreak in Jordan: a cross-sectional study", "rel_date": "2020-04-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.08.20056630", - "rel_abs": "The novel coronavirus (SARS-CoV-2), identified in China at the end of December 2019 and causing the disease COVID-19, has meanwhile led to outbreaks all over the globe, with about 571,700 confirmed cases and about 26,500 deaths as of March 28th, 2020. We present here the preliminary results of a mathematical study directed at informing on the possible application or lifting of control measures in Germany. The developed mathematical models allow to study the spread of COVID-19 among the population in Germany and to asses the impact of non-pharmaceutical interventions.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20056374", + "rel_abs": "BackgroundThe emergence of COVID-19 global pandemic coupled with high transmission rate and mortality has created an unprecedented state of emergency worldwide. This global situation may have a negative impact on the psychological well-being of individuals which in turn impacts individuals performance.\n\nMethodsA cross-sectional study using an online survey was conducted in Jordan between 22nd and 28th of March 2020 to explore the mental health status (depression and anxiety) of the general population, healthcare professionals, and university students during the COVID-19 outbreak. The Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) were used to assess depression and anxiety among the study participants. Logistic regression analysis was used to identify predictors of depression and anxiety.\n\nResultsThe prevalence of depression and anxiety among the entire study participants was 23.8% and 13.1%, respectively. Anxiety was most prevalent across university students 21.5%, followed by healthcare professionals 11.3%, and general population 8.8%. Females among healthcare professionals and university students, divorced healthcare professionals, pulmonologists, and university students with history of chronic disease were at higher risk of developing depression. Females, divorced participants among the general population, and university students with history of chronic disease and those with high income ([≥]1500 JD) were at higher risk of developing anxiety.\n\nConclusionsDuring outbreaks, individuals are put under extreme stressful condition resulting in higher risk of developing anxiety and depression particularly for students and healthcare professionals. Policymakers and mental healthcare providers are advised to provide further mental support to these vulnerable groups during this pandemic.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Maria Vittoria Barbarossa", - "author_inst": "Frankfurt Institute of Advanced Studies" + "author_name": "Abdallah Y Naser", + "author_inst": "Isra University" }, { - "author_name": "Jan Fuhrmann", - "author_inst": "Juelich Supercomputing Center" + "author_name": "Eman Zmaily Dahmash", + "author_inst": "Isra University" }, { - "author_name": "Julian Heidecke", - "author_inst": "Heidelberg University" + "author_name": "Rabaa Al-Rousan", + "author_inst": "Isra University" + }, + { + "author_name": "Hassan Alwafi", + "author_inst": "Umm Alqura University" }, { - "author_name": "Hridya Vinod Varma", - "author_inst": "Interdisciplinary Center for Scientific Computing, Heidelberg, Germany" + "author_name": "Hamzeh Mohammad Alrawashdeh", + "author_inst": "Ibn AL Haytham Hospital" }, { - "author_name": "Noemi Castelletti", - "author_inst": "Institute of Radiation Medicine, Helmholtz Zentrum Muenchen, Neuherberg, Germany" + "author_name": "Imene Ghoul", + "author_inst": "Ibn AL Haytham Hospital" }, { - "author_name": "Jan H Meinke", - "author_inst": "Juelich Supercomputing Centre, Forschungszentrum Juelich" + "author_name": "Anwar Abidine", + "author_inst": "King Abdulaziz Hospital" }, { - "author_name": "Stefan Krieg", - "author_inst": "Juelich Supercomputing Centre, Forschungszentrum Juelich" + "author_name": "Mohammed A. Bokhary", + "author_inst": "King Abdulaziz Hospital" }, { - "author_name": "Thomas Lippert", - "author_inst": "Juelich Supercomputing Centre, Forschungszentrum Juelich" + "author_name": "H. T. AL-Hadithi", + "author_inst": "Isra University" + }, + { + "author_name": "Dalia Ali", + "author_inst": "Isra University" + }, + { + "author_name": "Rasha Abuthawabeh", + "author_inst": "Isra University" + }, + { + "author_name": "Ghada Mohammad Abdelwahab", + "author_inst": "Isra University" + }, + { + "author_name": "Yosra J Alhartani", + "author_inst": "Isra University" + }, + { + "author_name": "Haneen Al Muhaisen", + "author_inst": "Isra University" + }, + { + "author_name": "Ayah Dagash", + "author_inst": "Isra University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2020.04.08.20054023", @@ -1530993,67 +1530843,27 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.05.20054544", - "rel_title": "Nitric oxide gas inhalation to prevent COVID-2019 in healthcare providers", + "rel_doi": "10.1101/2020.04.09.20058933", + "rel_title": "Fear of exponential growth in Covid19 data of India andfuture sketching", "rel_date": "2020-04-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.05.20054544", - "rel_abs": "IntroductionIn human hosts, SARS-CoV-2 causes a respiratory syndrome (named COVID-19) which can range from a mild involvement of the upper airways to a severe pneumonia with acute respiratory syndrome that requires mechanical ventilation in an intensive care unit (ICU). Hospital-associated transmission is an important route of spreading for the SARS-CoV-2 virus and healthcare providers are at the highest risk. As of February 2020, 1716, Chinese healthcare workers had confirmed SARS-CoV-2 infections and at least 6 died. Unfortunately, there is currently no vaccine or pharmacological prophylaxis to decrease the risk of healthcare providers contracting the infection.\n\nMethods and analysisWe will randomize 470 healthcare providers scheduled to work with COVID 19 patients to receive nitric oxide gas administration (NO group, n=235) or no gas administration (control group, n=235). The primary endpoint of this study is the incidence of subjects with COVID-19 disease at 14 days from enrollment. Secondary endpoints are the proportion of healthcare providers who present a positive real time RT-PCR test for SARS-CoV- 2 14 days after enrollment, the proportion of healthcare providers requiring quarantine, and the total number of quarantine days in the two groups.\n\nEthics and disseminationThe trial protocol is under the approval of The Partners Human Research Committee of Massachusetts General Hospital (Boston, USA) and recruitment is expected to start in April 2020. The results of this study will be published in scientific journals and presented at scientific meetings.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20058933", + "rel_abs": "We have attempted to interpret existing n-cov positive data in India with respect to other countries - Italy, USA, China and South Korea. We have mainly zoomed in the exponential growth in a particular zone of time axis, which is well followed in the data profile of India and Italy but not in others. A deviation from exponential growth to Sigmoid function is analyzed in the data profile of China and South Korea. Projecting that pattern to time dependent data of total number and new cases in India, we have drawn three possible Sigmoid functions, which saturate to cases 104, 105, 106. Ongoing data has doubtful signal of those possibilities and future hope is probably in extension of lock-down and additional imposition of interventions.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Stefano Gianni", - "author_inst": "Department of Anesthesia,Critical Care and Pain Medicine, Massachussets General Hospital, Boston, Massachussets, USA." + "author_name": "Supriya Mondal Jr.", + "author_inst": "Adarsh Nursing Institute" }, { - "author_name": "Bijan Safaee Fakhr", - "author_inst": "Department of Anesthesia,Critical Care and Pain Medicine, Massachussets General Hospital, Boston, Massachussets, USA." - }, - { - "author_name": "Caio Cesar Araujo Morais", - "author_inst": "Department of Anesthesia,Critical Care and Pain Medicine, Massachussets General Hospital, Boston, Massachussets, USA." - }, - { - "author_name": "Raffaele Di Fenza", - "author_inst": "Department of Anesthesia,Critical Care and Pain Medicine, Massachussets General Hospital, Boston, Massachussets, USA." - }, - { - "author_name": "Grant Larson", - "author_inst": "Department of Anesthesia, Critical Care and Pain Medicine, Massachussets General Hospital, Boston, Massachussets, USA" - }, - { - "author_name": "Riccardo Pinciroli", - "author_inst": "Department of Anesthesia,Critical Care and Pain Medicine, Massachussets General Hospital, Boston, Massachussets, USA." - }, - { - "author_name": "Timothy Houle", - "author_inst": "Department of Anesthesia,Critical Care and Pain Medicine, Massachussets General Hospital, Boston, Massachussets, USA." - }, - { - "author_name": "Ariel Louise Mueller", - "author_inst": "Department of Anesthesia, Critical Care and Pain Medicine, Massachussets General Hospital, Boston, Massachussets, USA" - }, - { - "author_name": "Andrea Bellavia", - "author_inst": "Department of Enviromental Health, Harvard T.H. Chan School of Public Health, Boston, Massachussets, USA" - }, - { - "author_name": "Robert Kacmarek", - "author_inst": "Department of Anesthesia,Critical Care and Pain Medicine, Massachussets General Hospital, Boston, Massachussets, USA." - }, - { - "author_name": "Ryan Carroll", - "author_inst": "Department of Pediatrics, Massachussets General Hospital, Boston, Massachussets, USA" - }, - { - "author_name": "Lorenzo Berra", - "author_inst": "Department of Anesthesia,Critical Care and Pain Medicine, Massachussets General Hospital, Boston, Massachussets, USA." + "author_name": "Sabyasachi Ghosh", + "author_inst": "IIT Bhilai" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.08.20057851", @@ -1532234,31 +1532044,39 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2020.04.08.20058347", - "rel_title": "A Comprehensive Analysis of COVID-19 Outbreak situation in India", + "rel_doi": "10.1101/2020.04.08.20058297", + "rel_title": "Work-related Covid-19 transmission", "rel_date": "2020-04-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.08.20058347", - "rel_abs": "The outbreak of COVID-19 in different parts of the world is a major concern for all the administrative units of respective countries. India is also facing this very tough task for controlling the virus outbreak and has managed its growth rate through some strict measures. This study presents the current situation of coronavirus spread in India along with the impact of various measures taken for it. With the help of data sources (till 7th-8th April 2020) from various state units of India and Ministry of Health and Family Welfare, Government of India, this study presents various trends and patterns. This study answers six different research questions in a comprehensive manner. It has been reported that growth rate of infected cases has been controlled with the help of National Lockdown, however some uncontrolled mass level events had a negative impact on the infected cases. With the help of exponential and polynomial regression modelling, the predictions of up to 75000 cases have been done by the end of April 2020. It has also been seen that there are some prominent clusters and patient nodes in the network of patients which are the major influencers for COVID-19 spread. Also, death rate case predictions have been done through two-class classification models with an accuracy of 60%. At the end, strategies for continuation for lockdown has been discussed and presented. It appears that only essential services should be open for the citizens of India and the national lockdown should be carried on for next 2-4 weeks. This study will be useful for the Government of India and various states of India, Administrative Units of India, Frontline health workforce of India, researchers and scientists. This study will also be favorable for the administrative units of other countries to consider various aspects related to the control of COVID-19 outspread in their respective regions.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.08.20058297", + "rel_abs": "ImportanceOur study helps fill the knowledge gap related to work-related transmission in the emerging coronaviral pandemic.\n\nObjectiveTo demonstrate high-risk occupations for early coronavirus disease 2019 (Covid-19) local transmission.\n\nMethodsIn this observational study, we extracted confirmed Covid-19 cases from governmental investigation reports in Hong Kong, Japan, Singapore, Taiwan, Thailand, and Vietnam. We followed each country/area for 40 days after its first locally transmitted case, and excluded all imported cases. We defined a possible work-related case as a worker with evidence of close contact with another confirmed case due to work, or an unknown contact history but likely to be infected in the working environment (e.g. an airport taxi driver). We calculated the case number for each occupation, and illustrated the temporal distribution of all possible work-related cases and healthcare worker (HCW) cases. The temporal distribution was further defined as early outbreak (the earliest 10 days of the following period) and late outbreak (11th to 40th days of the following period).\n\nResultsWe identified 103 possible work-related cases (14.9%) among a total of 690 local transmissions. The five occupation groups with the most cases were healthcare workers (HCWs) (22%), drivers and transport workers (18%), services and sales workers (18%), cleaning and domestic workers (9%) and public safety workers (7%). Possible work-related transmission played a substantial role in early outbreak (47.7% of early cases).\n\nOccupations at risk varied from early outbreak (predominantly services and sales workers, drivers, construction laborers, and religious professionals) to late outbreak (predominantly HCWs, drivers, cleaning and domestic workers, police officers, and religious professionals).\n\nConclusionsWork-related transmission is considerable in early Covid-19 outbreaks, and the elevated risk of infection was not limited to HCW. Implementing preventive/surveillance strategies for high-risk working populations is warranted.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Rajan Gupta", - "author_inst": "University of Delhi" + "author_name": "Fan-Yun Lan", + "author_inst": "Department of Environmental Health, Harvard University T.H. Chan School of Public Health, Boston, MA, USA" }, { - "author_name": "Saibal Kumar Pal", - "author_inst": "DRDO, Delhi" + "author_name": "Chih-Fu Wei", + "author_inst": "Department of Environmental Health, Harvard University T.H. Chan School of Public Health, Boston, MA, USA" }, { - "author_name": "Gaurav Pandey", - "author_inst": "TheNorthCap University" + "author_name": "Yu-Tien Hsu", + "author_inst": "Department of Social and Behavioral Science, Harvard University T.H. Chan School of Public Health, Boston, MA, USA" + }, + { + "author_name": "David C Christiani", + "author_inst": "Department of Environmental Health, Harvard University T.H. Chan School of Public Health, Boston, MA, USA" + }, + { + "author_name": "Stefanos N Kales", + "author_inst": "Department of Environmental Health, Harvard University T.H. Chan School of Public Health, Boston, MA, USA" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2020.04.08.20057679", @@ -1533376,71 +1533194,31 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.04.07.20056887", - "rel_title": "A secure and rapid query-software for COVID-19 test results that can easily be integrated into the clinical workflow to avoid communication overload", + "rel_doi": "10.1101/2020.04.06.20055384", + "rel_title": "Noisy Pooled PCR for Virus Testing", "rel_date": "2020-04-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.07.20056887", - "rel_abs": "Overcoming the COVID-19 crisis requires new ideas and strategies. Rapid testing of a large number of subjects is essential to monitor, and delay, the spread of SARS-CoV-2 to mitigate the consequences of the pandemic. People not knowing that they are infected may not stay in quarantine and, thus, are a risk for infecting others. Unfortunately, the massive number of COVID-19 tests performed is challenging for both laboratories and the units that take the throat swab and have to communicate test results. Here, we present a secure tracking system (CTest) to report COVID-19 test results online as soon as they become available. The system can be integrated into the clinical workflow with very modest effort and avoids excessive load to telephone hotlines. With this open-source and browser-based online tracking system, we aim to minimize the time required to inform the tested person but also the test units, e.g. hospitals or the public healthcare system. Instead of personal calls, CTest updates the status of the test automatically when the test results are available. Test reports are published on a secured web-page enabling regular status checks also by patients not using smartphones with dedicated mobile apps which has some importance as smartphone usage diminishes with age.\n\nThe source code, as well as further information to integrate CTest into the IT environment of other clinics or test-centres, are freely available from https://github.com/sysbio-bioinf/CTest under the Eclipse Public License v2.0 (EPL2).", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.06.20055384", + "rel_abs": "Fast testing can help mitigate the coronavirus disease 2019 (COVID-19) pandemic. Despite their accuracy for single sample analysis, infectious diseases diagnostic tools, like RT-PCR, require substantial resources to test large populations. We develop a scalable approach for determining the viral status of pooled patient samples. Our approach converts group testing to a linear inverse problem, where false positives and negatives are interpreted as generated by a noisy communication channel, and a message passing algorithm estimates the illness status of patients. Numerical results reveal that our approach estimates patient illness using fewer pooled measurements than existing noisy group testing algorithms. Our approach can easily be extended to various applications, including where false negatives must be minimized. Finally, in a Utopian world we would have collaborated with RT-PCR experts; it is difficult to form such connections during a pandemic. We welcome new collaborators to reach out and help improve this work!", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Gunnar Voelkel", - "author_inst": "Ulm University" - }, - { - "author_name": "Axel Fuerstberger", - "author_inst": "Ulm University" - }, - { - "author_name": "Julian D. Schwab", - "author_inst": "Ulm University" - }, - { - "author_name": "Silke D. Kuehlwein", - "author_inst": "Ulm University" - }, - { - "author_name": "Thomas Gscheidmeier", - "author_inst": "University Hospital Ulm" - }, - { - "author_name": "Johann M. Kraus", - "author_inst": "Ulm University" - }, - { - "author_name": "Alexander Gross", - "author_inst": "Ulm University" - }, - { - "author_name": "Florian Kohlmayer", - "author_inst": "TU Munich" - }, - { - "author_name": "Peter Kuhn", - "author_inst": "University Hospital Ulm" - }, - { - "author_name": "Klaus A. Kuhn", - "author_inst": "TU Munich" - }, - { - "author_name": "Oliver Kohlbacher", - "author_inst": "University Hospital Tuebingen" + "author_name": "Junan Zhu", + "author_inst": "Harvest Fund Management" }, { - "author_name": "Thomas Seufferlein", - "author_inst": "University Hospital Ulm" + "author_name": "Kristina Rivera", + "author_inst": "North Carolina State University" }, { - "author_name": "Hans A. Kestler", - "author_inst": "Ulm University" + "author_name": "Dror Baron", + "author_inst": "North Carolina State University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.04.09.20056291", @@ -1534698,33 +1534476,41 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.08.20057893", - "rel_title": "Hydroxychloroquine (HCQ): an observational cohort study in primary and secondary prevention of pneumonia in an at-risk population", + "rel_doi": "10.1101/2020.04.09.20049924", + "rel_title": "Temporal Association Between Particulate Matter Pollution and Case Fatality Rate of COVID-19 in Wuhan, China", "rel_date": "2020-04-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.08.20057893", - "rel_abs": "BackgroundRecent studies suggest that hydroxychloroquine (HCQ) could be effective against COVID-19. It is reasonable to expect that if HCQ can prevent or reduce the adverse effects of influenza, it may also reduce the effects of COVID-19 in humans. The objective of this study was to test whether HCQ can prevent or reduce the risk and severity of influenza.\n\nMethodsThis is an observational cohort study using medico-administrative data from Quebec. Patients included had at least one emergency department (ED) visit in 2012 or 2013, with a prior diagnosis of chronic conditions, and were admissible to the public drug insurance plan. Two sub-cohorts were considered depending on reasons for ED visit: other than influenza or pneumonia (primary prevention) and influenza or pneumonia (secondary prevention).\n\nResultsIn the primary prevention analysis (n=417,353), patients taking HCQ (n=3,659) had an increased risk of hospitalization for pneumonia in the following year compared to those who did not (5.2% vs. 2.9%; adjusted OR=1.25, p=0.0079). In the secondary prevention analysis (n=27,152), patients taking HCQ (n=392), compared to those who did not had a modest and non-significant increased risk of hospitalization for pneumonia after 30 days (25.8% vs. 22.6%; adjusted OR=1.14, p=0.3177).\n\nInterpretationBased on the assumption that HCQ has similar effects on the COVID-19 as those observed on influenza, we can infer that it will not have positive effects on COVID-19. We should therefore act cautiously before initiating prospective interventional studies on the use of HCQ to reduce adverse effects of COVID-19.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20049924", + "rel_abs": "The Coronavirus (COVID-19) epidemic, which was first reported in December 2019 in Wuhan, China, has caused 3,314 death as of March 31, 2020 in China. This study aimed to investigate the temporal association between case fatality rate (CFR) of COVID-19 and particulate matter (PM) in Wuhan. We conducted a time series analysis to explore the temporal day-by-day associations. We found COVID-19 held higher case fatality rate with increasing concentrations of PM2.5 and PM10 in temporal scale, which may affect the process of patients developed from mild to severe and finally influence the prognosis of COVID-19 patients.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Alain Vanasse", - "author_inst": "Department of family medicine and emergency medicine, Universite de Sherbrooke" + "author_name": "Ye Yao", + "author_inst": "Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China" + }, + { + "author_name": "Jinhua Pan", + "author_inst": "Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China" + }, + { + "author_name": "Zhixi Liu", + "author_inst": "Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China" }, { - "author_name": "Josiane Courteau", - "author_inst": "PRIMUS Research Group, Centre de recherche du Centre hospitalier universitaire de Sherbrooke (CRCHUS)" + "author_name": "Xia Meng", + "author_inst": "Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China" }, { - "author_name": "Yohann Chiu", - "author_inst": "Department of family medicine and emergency medicine, Universite de Sherbrooke" + "author_name": "Weidong Wang", + "author_inst": "Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China" }, { - "author_name": "Andre Cantin", - "author_inst": "Respiratory service, Medicine Department, Universite de Sherbrooke" + "author_name": "Haidong Kan", + "author_inst": "Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China" }, { - "author_name": "Richard Leduc", - "author_inst": "Department of pharmacology-physiology, Universite de Sherbrooke" + "author_name": "Weibing Wang", + "author_inst": "Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China" } ], "version": "1", @@ -1536300,47 +1536086,55 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.04.05.20054403", - "rel_title": "Projected early spread of COVID-19 in Africa", + "rel_doi": "10.1101/2020.04.07.029447", + "rel_title": "Role of RNA Guanine Quadruplexes in Favoring the Dimerization of SARS Unique Domain in Coronaviruses", "rel_date": "2020-04-10", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.05.20054403", - "rel_abs": "For African countries currently reporting COVID-19 cases, we estimate when they will report more than 1 000 and 10 000 cases. Assuming current trends, more than 80% are likely to exceed 1 000 cases by the end of April 2020, with most exceeding 10 000 a few weeks later.", - "rel_num_authors": 7, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.07.029447", + "rel_abs": "Coronaviruses may produce severe acute respiratory syndrome (SARS). As a matter of fact, a new SARS-type virus, SARS-CoV-2, is responsible of a global pandemic in 2020 with unprecedented sanitary and economic consequences for most countries. In the present contribution we study, by all-atom equilibrium and enhanced sampling molecular dynamics simulations, the interaction between the SARS Unique Domain and RNA guanine quadruplexes, a process involved in eluding the defensive response of the host thus favoring viral infection of human cells. Our results evidence two stable binding modes involving an interaction site spanning either the protein dimer interface or only one monomer. The free energy profile unequivocally points to the dimer mode as the thermodynamically favored one. The effect of these binding modes in stabilizing the protein dimer was also assessed, being related to its biological role in assisting SARS viruses to bypass the host protective response. This work also constitutes a first step of the possible rational design of efficient therapeutic agents aiming at perturbing the interaction between SARS Unique Domain and guanine quadruplexes, hence enhancing the host defenses against the virus.\n\nTOC GRAPHICS\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC=\"FIGDIR/small/029447v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (99K):\norg.highwire.dtl.DTLVardef@1497e69org.highwire.dtl.DTLVardef@a4c44org.highwire.dtl.DTLVardef@1511b7org.highwire.dtl.DTLVardef@13e12c1_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Carl Andrew Pearson", - "author_inst": "London School of Hygiene & Tropical Medicine" + "author_name": "Cecilia Hognon", + "author_inst": "Universite de Lorraine" }, { - "author_name": "Cari Van Schalkwyk", - "author_inst": "South African DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis, Stellenbosch University" + "author_name": "Tom Miclot", + "author_inst": "Universita di Palermo" }, { - "author_name": "Anna M Foss", - "author_inst": "London School of Hygiene & Tropical Medicine" + "author_name": "Cristina Garcia Iriepa", + "author_inst": "Universitad de Alcala" }, { - "author_name": "Kathleen M O'Reilly", - "author_inst": "London School of Hygiene & Tropical Medicine" + "author_name": "Antonio France-Monerris", + "author_inst": "Universite de Lorraine" }, { - "author_name": "- CMMID COVID-19 working group", - "author_inst": "-" + "author_name": "Stephanie Grandemange", + "author_inst": "Universite de Lorraine" }, { - "author_name": "- SACEMA 10 Modelling and Analysis Response Team", - "author_inst": "-" + "author_name": "Alessio Terenzi", + "author_inst": "Universita di Palermo" }, { - "author_name": "Juliet R C Pulliam", - "author_inst": "South African DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis, Stellenbosch University" + "author_name": "Marco Marazzi", + "author_inst": "Universidad de Alacala" + }, + { + "author_name": "Giampaolo Barone", + "author_inst": "Universita di Palermo" + }, + { + "author_name": "Antonio Monari", + "author_inst": "Universite de Lorraine" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "type": "new results", + "category": "biophysics" }, { "rel_doi": "10.1101/2020.04.07.023903", @@ -1537953,57 +1537747,45 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.04.06.20052522", - "rel_title": "Co-detection of respiratory pathogens in patients hospitalized with Coronavirus viral disease-2019 pneumonia", + "rel_doi": "10.1101/2020.04.03.20052373", + "rel_title": "Social distancing to slow the U.S. COVID-19 epidemic: an interrupted time-series analysis", "rel_date": "2020-04-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.06.20052522", - "rel_abs": "There is scarce information on the frequency of co-detection of respiratory pathogens (RP) in patients with Covid-19. Documentation of coinfections in Covid-19 pneumonia patients may be relevant for appropriate clinical and therapeutic management of patients. Between March 4th and March 28th, 2020, a total of 183 adult patients testing positive by SARS CoV-2 RT-PCR on respiratory specimens were hospitalized with interstitial pneumonia at our center, of whom 103 were tested for other RP by a multiplexed PCR assay. Three patients had a positive result for either one (n=2; Coronavirus HKU1 or Mycoplasma pneumoniae) or two targets (n=1; Influenza virus A (H3) and Respiratory syncytial virus B). Twenty-three patients testing negative by SARS CoV-2 RT-PCR and presentig with clinical, laboratory findings and imaging compatibe with Covid-19 pneumonia underwent RP screening. Of these, 6 (26%) had a positive result for a single RP. Our data indicate that despite the apparent rarity of coinfections in patients with Covid-19 pneumonia, routine testing for RP should be advised, since agents for which specific therapy can be prescribed may be detected.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.03.20052373", + "rel_abs": "BackgroundSocial distancing measures to address the U.S. coronavirus disease 2019 (COVID-19) epidemic may have notable health and social impacts.\n\nMethods and FindingsWe conducted a longitudinal pretest-posttest comparison group study to estimate the change in COVID-19 case growth before versus after implementation of statewide social distancing measures in the U.S. The primary exposure was time before (14 days prior to, and up to 3 days after) versus after (beginning 4 days after, and up to 21 days after) implementation of the first statewide social distancing measures. Statewide restrictions on internal movement were examined as a secondary exposure. The primary outcome was the COVID-19 case growth rate. The secondary outcome was the COVID-19-attributed mortality growth rate. All states initiated social distancing measures between March 10-25, 2020. The mean daily COVID-19 case growth rate decreased beginning four days after implementation of the first statewide social distancing measures, by 0.9% per day (95% confidence interval [CI], -1.3% to -0.4%; P<0.001). We did not estimate a statistically significant difference in the mean daily case growth rate before versus after implementation of statewide restrictions on internal movement (0.1% per day; 95% CI, -0.04% to 0.3%, P=0.14), but there is significant difficulty in disentangling the unique associations with statewide restrictions on internal movement from the unique associations with the first social distancing measures. Beginning seven days after social distancing, the COVID-19-attributed mortality growth rate decreased by 1.7% per day (95% CI, -3.0% to -0.7%; P<0.001). Our analysis is susceptible to potential bias resulting from the aggregate nature of the ecological data, potential confounding by contemporaneous changes (e.g., increases in testing), and potential underestimation of social distancing due to spillovers across neighboring states.\n\nConclusionsStatewide social distancing measures were associated with a decrease in the COVID-19 epidemic case growth rate that was statistically significant and a decrease in the COVID-19-attributed mortality growth rate that was not statistically significant.\n\nAuthor SummaryO_ST_ABSWhy was the study doneC_ST_ABSThere are few empirical data about the population health benefits of imposing statewide social distancing measures to reduce transmission of severe acute respiratory syndrome coronavirus 2, which causes coronavirus disease 2019 (COVID-19).\n\nWhat did the researchers findWe compared data from each state before vs. after implementation of statewide social distancing measures to estimate changes in mean COVID-19 daily case growth rates. Growth rates declined by approximately 1% per day beginning four days (approximately one incubation period) after statewide social distancing measures were implemented. Stated differently, our model implies that social distancing reduced the total number of COVID-19 cases by approximately 1,600 reported cases at 7 days after implementation, by approximately reported 55,000 cases at 14 days after implementation, and by approximately reported 600,000 cases at 21 days after implementation.\n\nWhat do these findings meanStatewide social distancing measures were associated with a reduction in the growth rate of COVID-19 cases in the U.S. However, our analysis is susceptible to potential bias resulting from the aggregate nature of the data, potential confounding by other changes that occurred during the study period (e.g., increases in testing), and potential underestimation of social distancing due to spillovers across neighboring states.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Maria Luisa Blasco", - "author_inst": "Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." - }, - { - "author_name": "Javier Buesa", - "author_inst": "Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." - }, - { - "author_name": "Javier Colomina", - "author_inst": "Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." - }, - { - "author_name": "Maria Jose Forner", - "author_inst": "Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." + "author_name": "Mark J Siedner", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Maria Jose Galindo", - "author_inst": "Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." + "author_name": "Guy Harling", + "author_inst": "Africa Health Research Institute" }, { - "author_name": "Jorge Navarro", - "author_inst": "Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." + "author_name": "Zahra Reynolds", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Jose Noceda", - "author_inst": "Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." + "author_name": "Rebecca F Gilbert", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Josep Redon", - "author_inst": "Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." + "author_name": "Sebastian Haneuse", + "author_inst": "Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States" }, { - "author_name": "Jaime Signes-Costa", - "author_inst": "Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." + "author_name": "Atheendar Venkataramani", + "author_inst": "University of Pennsylvania" }, { - "author_name": "David Navarro", - "author_inst": "Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." + "author_name": "Alexander C Tsai", + "author_inst": "Massachusetts General Hospital" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1539319,47 +1539101,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.04.20053546", - "rel_title": "Community responses during early phase of the COVID-19 epidemic: a cross-sectional study", + "rel_doi": "10.1101/2020.04.03.20052571", + "rel_title": "The distress of Iranian adults during the Covid-19 pandemic - More distressed than the Chinese and with different predictors", "rel_date": "2020-04-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.04.20053546", - "rel_abs": "Community responses are important for outbreak management during the early phase when preventive interventions are the major options. Therefore, this study aims to examine the behavioral responses of the community during the early phase of the COVID-19 epidemic in the Razavi Khorasan Province of Iran. A cross-sectional online survey was proceeded after confirmed COVID-19 in Iran. The population of the study was 500 residents of Razavi Khorasan areas were randomly surveyed. The research tool was demographic and risk perception questionnaire and Anxiety was assessed using the 7-item GAD Scale. The data analyzed using the SPSS statistical version (V.20). The means of age participants was 31.9{+/-}11.9. The mean GAD-7 scores were 6.4{+/-}5.2 and 92.4% had moderate or severe anxiety (GAD-7 score [≥]10). Many respondents reported their health status were very good or good (62.2 %; 311/500). About a quarter of them had respiratory symptoms in the past 14 days and experienced 20% of them travelled outside the Razavi Khorasan Province in the previous. Risk perception toward COVID-19 in the community of the Razavi Khorasan Province was moderate. Most participants are alert to disease progression. This study suggested timely behavioral assessment of the community is beneficial and effective to inform next intervention, and risk communication strategies in epidemic disease.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.03.20052571", + "rel_abs": "Early papers on the mental health of the public during the Covid-19 pandemic surveyed participants from China. Outside of China, Iran has emerged as one of the most affected countries with a high death count and rate. The paper presents the first empirical evidence from Iranian adults during the Covid-19 pandemic on their level of distress and its predictors. On March 25-28, 2020, a dire time for Covid-19 in Iran, we surveyed 1058 adults from all 30 provinces in Iran using the Covid-19 Peritraumatic Distress Index (CPDI). The distress level of Iranian adults (mean: 34.54; s.d.: 14.92) was significantly higher (mean difference: 10.9; t=22.7; p<0.0001; 95% CI: 10.0 to 11.8) than that of Chinese adults (mean: 23.65; s.d.: 5.45) as reported in a prior study with the same measure of Covid-19 Peritraumatic Distress Index (CPDI). We also found the predictors of distress in Iran vary from those in China. Our findings that the predictors of distress in Iran vary from those in China suggest the need to study the predictors of mental health in individual countries during the Covid-19 pandemic to effectively identify and screen for those more susceptible to mental health issues.\n\nFundingNone", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "fatemeh pourhaji Sr.", - "author_inst": "Torbat Heydariyeh University of Medical Sciences" - }, - { - "author_name": "mohammad hossien delshad Jr.", - "author_inst": "Torbat Heydariyeh University" - }, - { - "author_name": "Fahimeh Pourhaji Sr.", - "author_inst": "Mashhad University of Medical Sciences, Mashhad, Iran." + "author_name": "Asghar Afshar Jahanshahi", + "author_inst": "Pontificia Universidad Catolica del Peru" }, { - "author_name": "Saeed Reza Ghanbarizadeh Jr.", - "author_inst": "Torbat Heydariyeh University of Medical Sciences" + "author_name": "Maryam Mokhtari Dinani", + "author_inst": "Alzahra University" }, { - "author_name": "Hassan Azhdari Zarmehri", - "author_inst": "Torbat Heydariyeh University of Medical Sciences" + "author_name": "Abbas Nazarian Madavani", + "author_inst": "Shahid Rajaee University" }, { - "author_name": "Edris Bazrafshan", - "author_inst": "Torbat Heydariyeh University of Medical Sciences" + "author_name": "Jizhen Li", + "author_inst": "Tsinghua University" }, { - "author_name": "Mahdi Gholian-Aval Jr.", - "author_inst": "Mashhad University of Medical Sciences" + "author_name": "Stephen X Zhang", + "author_inst": "University of Adelaide" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2020.04.04.20052696", @@ -1540481,37 +1540255,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.05.20054163", - "rel_title": "Mandated Bacillus Calmette-Guerin (BCG) vaccination predicts flattened curves for the spread of COVID-19", + "rel_doi": "10.1101/2020.04.05.20054775", + "rel_title": "Increased Detection coupled with Social Distancing and Health Capacity Planning Reduce the Burden of COVID-19 Cases and Fatalities: A Proof of Concept Study using a Stochastic Computational Simulation Model", "rel_date": "2020-04-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.05.20054163", - "rel_abs": "BCG vaccination may reduce the risk of a range of infectious diseases, and, if so, could serve as a protective factor against COVID-19. Here, we compared countries that mandated BCG vaccination at least until 2000 with to countries that did not (140 countries in total). To minimize any systematic effects of reporting biases, we analyzed the rate of the day-by-day increase in both confirmed cases and deaths in the first 30-day period of country-wise outbreaks. The 30-day window was adjusted to begin at the country-wise onset of the pandemic. Linear mixed models revealed a significant effect of mandated BCG policies on the growth rate of both cases and deaths after controlling for median age, gross domestic product per capita, population density, population size, net migration rate, and various cultural dimensions (e.g., individualism and the tightness vs. looseness of social norms). Our analysis suggests that mandated BCG vaccination can be effective in the fight against COVID-19.\n\nTeaserNational policies for universal BCG vaccination are associated with flattened growth of country-wise COVID-19 cases and deaths.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.05.20054775", + "rel_abs": "ObjectiveIn absence of any vaccine, the Corona Virus Disease 2019 (COVID-19) pandemic is being contained through a non-pharmaceutical measure termed Social Distancing (SD). However, whether SD alone is enough to flatten the epidemic curve is debatable. Using a Stochastic Computational Simulation Model, we investigated the impact of increasing SD, hospital beds and COVID-19 detection rates in preventing COVID-19 cases and fatalities.\n\nResearch Design and MethodsThe Stochastic Simulation Model was built using the EpiModel package in R. As a proof of concept study, we ran the simulation on Kasaragod, the most affected district in Kerala. We added 3 compartments to the SEIR model to obtain a SEIQHRF (Susceptible-Exposed-Infectious-Quarantined-Hospitalised-Recovered-Fatal) model.\n\nResultsImplementing SD only delayed the appearance of peak prevalence of COVID-19 cases. Doubling of hospital beds couldnt reduce the fatal cases probably due to its overwhelming number compared to the hospital beds. Increasing detection rates could significantly flatten the curve and reduce the peak prevalence of cases (increasing detection rate by 5 times could reduce case number to half).\n\nConclusionsAn effective strategy to contain the epidemic spread of COVID-19 in India is to increase detection rates in combination with SD measures and increase in hospital beds.\n\nHIGHLIGHTSO_LIIncreased Detection of COVID-19 cases must accompany Social Distancing and Health Capacity Planning to reduce the burden of cases and fatalities.\nC_LIO_LIInterruptive Social Distancing is an effective alternative to continuous Social Distancing.\nC_LIO_LIGiven the overwhelming burden of COVID-19 fatalities, there is immediate need of co-ordination with the Private Healthcare Sector.\nC_LIO_LICOVID-19 cases will be peaking after May, 2020 giving us time for Healthcare Capacity Building in the government and private sector both.\nC_LI", "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Martha K Berg", - "author_inst": "University of Michigan" + "author_name": "Pramit Ghosh", + "author_inst": "Purulia Government Medical College, Purulia, West Bengal, India" }, { - "author_name": "Qinggang Yu", - "author_inst": "University of Michigan" + "author_name": "Salah Basheer", + "author_inst": "Institute of Mental Health and Neurosciences, Kozhikode, Kerala, India" }, { - "author_name": "Cristina E Salvador", - "author_inst": "University of Michigan" + "author_name": "Sandip Paul", + "author_inst": "CSIR-Indian Institute of Chemical Biology" }, { - "author_name": "Irene Melani", - "author_inst": "University of Michigan" + "author_name": "Partha Chakrabarti", + "author_inst": "CSIR-Indian Institute of Chemical Biology" }, { - "author_name": "Shinobu Kitayama", - "author_inst": "University of Michigan" + "author_name": "Jit Sarkar", + "author_inst": "CSIR-Indian Institute of Chemical Biology" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1541815,67 +1541589,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.03.20052183", - "rel_title": "Clinical meanings of rapid serological assay in patients tested for SARS-Co2 RT-PCR", + "rel_doi": "10.1101/2020.04.03.20052217", + "rel_title": "Pressure-Regulated Ventilator Splitting (PReVentS): A COVID-19 Response Paradigm from Yale University", "rel_date": "2020-04-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.03.20052183", - "rel_abs": "BackgroundRT-PCR test for identification of viral nucleic acid is the current standard diagnostic method for the diagnosis of COVID-19 disease but technical reasons limit the utilization of this assay onlarge scalescreenings.\n\nMethodWe verified in a consecutive series of 191 symptomatic patients the clinical information that new rapid serological colorimetric test qualitatively analyzing IgM/IgG expression can provide with respect to standard assay and with respect to clinical outcome of patients.\n\nResultsRapid serological test showed a sensitivity of 30% and a specificity of 89% with respect to the standard assay but, interestingly, these performances improve after 8 days of symptoms appearance. After 10 days of symptoms the predictive value of rapid serological test is higher than that of standardassay. When the behaviour of the two immunoglobulins was evaluated with respect to time length of symptoms appaerance, no significant difference in immunoglobulins behaviour was shown.\n\nConclusionsThe rapid serological test analyzed in the present study is candidate to provide information on immunoreaction of the subject to COVID-19 exposure.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.03.20052217", + "rel_abs": "In the current COVID-19 crisis, the US and many countries in the world are suffering acute shortages of modern ventilators to care for desperately ill patients. Since modern ICU ventilators are powerful devices that can deliver very high gas flow rates and pressures, multiple physicians have attempted to ventilate more than one patient on a single ventilator - so-called \"vent splitting\". Early applications of this approach have utilized simple concatenations of ventilator tubing and T-pieces, to provide flow to more than one patient. Additional approaches using custom flow splitters - sometimes made using 3D printing technologies - have also advanced into the clinic with FDA approval. However, heretofore there has been less progress made on controlling individual ventilatory pressures for patients with severe lung disease. Given the inherent variability and instability of lung compliance amongst patients with COVID-19, there remains an important need to provide a means of extending ventilator usefulness to more than one patient, but in a way that provides more tailored pressures that can be titrated over time. In this descriptive report, we provide the basis for a ventilator circuit that can support two patients with individualized peak inspiratory and end-expiratory pressures. The circuit is comprised of exclusively \"off the shelf\" materials and is inexpensive to produce. The circuit can be used with typical ICU ventilators, and with anesthesia ventilators used in operating rooms. Inspiratory and end-expiratory pressures for each patient can be titrated over time, without changes for one patient affecting the ventilation parameters of the other patient. Using in-line spirometry, individual tidal volumes can be measured for each patient. This Pressure-Regulated Ventilator Splitting (PReVentS) Yale University protocol operates under a pressure-control ventilatory mode, and may function optimally when patients are not triggering breaths from the ventilator.\n\nThis method has been tested thus far only in the laboratory with mock lungs, and has not yet been deployed in animals or in patients. However, given the novelty and potential utility of this approach, we deemed it appropriate to provide this information to the broader critical care community at the present time. In coming days and weeks, we will continue to characterize and refine this approach, using large animal models and proof-of-principle human studies.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Angelo Virgilio Paradiso", - "author_inst": "IRCCS Istituto Tumori Giovanni Paolo II" - }, - { - "author_name": "Simona De Summa", - "author_inst": "IRCCS-Istituto Tumori \"Giovanni Paolo II\"" - }, - { - "author_name": "Daniela Loconsole", - "author_inst": "University of Bari" - }, - { - "author_name": "Vito Procacci", - "author_inst": "University of Bari" + "author_name": "Micha Sam Brickman Raredon", + "author_inst": "Yale University" }, { - "author_name": "Anna Sallustio", - "author_inst": "University of Bari" + "author_name": "Clark Fisher", + "author_inst": "Yale University" }, { - "author_name": "Francesca Centrone", - "author_inst": "University of Bari" + "author_name": "Paul Heerdt", + "author_inst": "Yale University" }, { - "author_name": "Nicola Silvestris", - "author_inst": "University of Bari" + "author_name": "Ranjit Deshpande", + "author_inst": "Yale University" }, { - "author_name": "Vito Cafagna", - "author_inst": "IRCCS Istituto Tumori Giovanni Paolo II" + "author_name": "Steven Nivison", + "author_inst": "Yale-New Haven Hospital" }, { - "author_name": "Giuseppe De Palma", - "author_inst": "IRCCS Istituto Tumori Giovanni Paolo II" + "author_name": "Elaine Fajardo", + "author_inst": "Yale University" }, { - "author_name": "Antonio Tufaro", - "author_inst": "IRCCS Istituto Tumori Giovanni Paolo II" + "author_name": "Shamsuddin Akhtar", + "author_inst": "Yale University" }, { - "author_name": "Vito Garrisi", - "author_inst": "IRCCS Istituto Tumori Giovanni Paolo II" + "author_name": "Thomas Raredon", + "author_inst": "HB/TR Collaborative Inc." }, { - "author_name": "Maria Chironna", - "author_inst": "University of Bari" + "author_name": "Laura E. Niklason", + "author_inst": "Yale University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.03.31.20048652", @@ -1543201,47 +1542963,27 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2020.03.31.20049197", - "rel_title": "Aerosol-spread during chest compressions in a cadaver model", + "rel_doi": "10.1101/2020.04.03.20049734", + "rel_title": "Monitoring Italian COVID-19 spread by an adaptive SEIRD model", "rel_date": "2020-04-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.31.20049197", - "rel_abs": "ObjectiveTo evaluate aerosol-spread in cardiopulmonary resuscitation (CPR) using different methods of airway management. Knowledge about aerosol-spread is vital during the SARS-CoV-2-Pandemic.\n\nMethodsTo evaluate feasibility we nebulized ultraviolet sensitive detergents into the artificial airway of a resuscitation dummy and performed CPR. The spread of the visualized aerosol was documented by a camera. In a second approach we applied nebulized detergents into human cadavers by an endotracheal tube and detected aerosol-spread during chest compressions the same way. We did recordings with undergoing compression-only-CPR, with a surgical mask and with an inserted laryngeal tube with and without a connected airway filter.\n\nResultsMost aerosol-spread at the direction of the provider was visualized during compression-only-CPR. The use of a surgical mask deflected the spread. Inserting a laryngeal tube connected to an airway filter lead to a remarkable reduction of aerosol-spread.\n\nConclusionThe early insertion of a laryngeal tube connected to an airway filter before starting chest compression may be good for two things - the treatment of hypoxemia as the likeliest cause of cardiac arrest and for staff protection during CPR.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.03.20049734", + "rel_abs": "Due to the recent diffusion of COVID-19 outbreak, the scientific community is making efforts in analysing models for understanding the present situation and predicting future scenarios. In this paper, we propose a Susceptible-Infected-Exposed-Recovered-Dead (SEIRD) differential model [Weitz J. S. and Dushoff J., Scientific reports, 2015] for the analysis and forecast of the COVID-19 spread in Italian regions, using the data from the Italian Protezione Civile from February 24th 2020. In this study, we investigate an adaptation of SEIRD that takes into account the actual policies of the Italian government, consisting of modelling the infection rate as a time-dependent function (SEIRD(rm)). Preliminary results on Lombardia and Emilia-Romagna regions confirm that SEIRD(rm) fits the data more accurately than the original SEIRD model with constant rate infection parameter. Moreover, the increased flexibility in the choice of the infection rate function makes it possible to better control the predictions due to the lockdown policy.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Matthias Ott", - "author_inst": "Klinikum Stuttgart, Department of interdisciplinary emergency and intensive care medicine" - }, - { - "author_name": "Alfio Milazzo", - "author_inst": "Institute of Neuroanatomy & Developmental Biology INDB, Eberhard Karls University Tuebingen" - }, - { - "author_name": "Stefan Liebau", - "author_inst": "Institute of Neuroanatomy & Developmental Biology INDB, Eberhard Karls University Tuebingen" - }, - { - "author_name": "Christina Jaki", - "author_inst": "Klinikum Stuttgart, Simulation Center STUPS" - }, - { - "author_name": "Tobias Schilling", - "author_inst": "Klinikum Stuttgart, Department of interdisciplinary emergency and intensive care medicine" - }, - { - "author_name": "Alexander Krohn", - "author_inst": "Klinikum Stuttgart, Department of interdisciplinary emergency and intensive care medicine" + "author_name": "Elena Loli Piccolomiini", + "author_inst": "University of Bologna" }, { - "author_name": "Johannes Heymer", - "author_inst": "Klinikum Stuttgart, Department of interdisciplinary emergency and intensive care medicine" + "author_name": "Fabiana Zama", + "author_inst": "University of Bologna" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "emergency medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.03.31.20049387", @@ -1544291,47 +1544033,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.02.20051029", - "rel_title": "Therapeutic Management of COVID-19 Patients: A systematic review", + "rel_doi": "10.1101/2020.04.02.20050898", + "rel_title": "COVID-19 scenario modelling for the mitigation of capacity-dependent deaths in intensive care: computer simulation study", "rel_date": "2020-04-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.02.20051029", - "rel_abs": "BackgroundSARS-CoV-2 is the cause of the COVID-19 that has been declared a global pandemic by the WHO in 2020. The COVID-19 treatment guidelines vary in each country, and yet there is no approved therapeutic for COVID-19.\n\nAims of the studythis review aimed to report any evidence of therapeutics used for the management of COVID-19 patients in clinical practice since the emergence of the virus.\n\nMethodsA systematic review protocol was developed based on PRISMA Statement. Articles for review were selected from electronic databases (Embase, Medline and Google Scholar). Readily accessible peer-reviewed full articles in English published from December 1 st, 2019 to March 26 th, 2020 were included. The search terms included combinations of: COVID, SARS-COV-2, glucocorticoids, convalescent plasma, antiviral, antibacterial. There were no restrictions on the type of study design eligible for inclusion.\n\nResultsAs of March 26, 2020, of the initial manuscripts identified (n=449) articles. Forty-one studies were included, of which clinical trials (n=3), (case reports n=7), case series (n=10), retrospective (n=11) and prospective (n=10) observational studies. Thirty-six studies were conducted in China (88%).\n\nThe most common mentioned and reported medicine in this systematic review was corticosteroids (n=25), followed by Lopinavir (n=21) and oseltamivir (n=16).\n\nConclusionsThis is the first systematic review up to date related to the therapeutics used in COVID-19 patients. Only forty-one research articles on COVID-19 and therapeutics were found eligible to be included, most conducted in China, corticosteroid therapy was found to be the most used medicine in these studies.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.02.20050898", + "rel_abs": "BackgroundManaging healthcare demand and capacity is especially difficult in the context of the COVID-19 pandemic, where limited intensive care resources can be overwhelmed by a large number of cases requiring admission in a short space of time. If patients are unable to access this specialist resource, then death is a likely outcome. The aim of this study is to estimate the extent to which such capacity-dependent deaths can be mitigated through demand-side initiatives involving non-pharmaceutical interventions and supply-side measures to increase surge capacity or reduce length of stay.\n\nMethodsA stochastic discrete event simulation model is developed to represent the key dynamics of the intensive care admissions process for COVID-19 patients. Model inputs are aligned to levers available to planners with key outputs including duration of time at maximum capacity (to inform workforce requirements), peak daily deaths (for mortuary planning), and total deaths (as an ultimate marker of intervention efficacy). The model - freely available - is applied to the COVID-19 response at a large hospital in England for which the effect of a number of possible interventions are simulated.\n\nResultsCapacity-dependent deaths are closely associated with both the nature and effectiveness of non-pharmaceutical interventions and availability of intensive care beds. For the hospital considered, results suggest that capacity-dependent deaths can be reduced five-fold through a combination of isolation policies, a doubling of bed capacity, and 25% reduced length of stay.\n\nConclusionsWithout treatment or vaccination there is little that can be done to reduce deaths occurring when patients have otherwise been treated in the most appropriate hospital setting. Healthcare planners should therefore focus on minimising the capacity-dependent deaths that are within their influence.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Mansour Tobaiqy", - "author_inst": "BSc, MSc Clin. Pharmacol, PhD, PgCert, Assistant Professor, Department of Pharmacology, College of Medicine, University of Jeddah, Jeddah, Kingdom of Saudi Ar" - }, - { - "author_name": "Mohammed Qashqary", - "author_inst": "Assistant Professor, MD, Department of Family Medicine, College of Medicine, University of Jeddah, Jeddah, Saudi Arabia" - }, - { - "author_name": "Shrooq Al-Dahery", - "author_inst": "Assistant Professor, Department of Applied Radiologic Technology, College of Applied Medical Sciences, University of Jeddah, Jeddah, Saudi Arabia" + "author_name": "Richard M Wood", + "author_inst": "UK National Health Service and University of Bath" }, { - "author_name": "Alaa Mujallad", - "author_inst": "Assistant Professor, Department of Nursing, College of Applied Medical Sciences, University of Jeddah, Jeddah, Saudi Arabia" + "author_name": "Christopher J McWilliams", + "author_inst": "University of Bristol" }, { - "author_name": "Almonther Abdullah Hershan", - "author_inst": "Assistant Professor, MD, Department of Medical Microbiology and Parasitology, College of Medicine, University of Jeddah, Jeddah, Saudi Arabia" + "author_name": "Matthew J Thomas", + "author_inst": "University of Bristol" }, { - "author_name": "Mohammad Azhar Kamal", - "author_inst": "Assistant Professor, 1-Department of Biochemistry College of Science University of Jeddah, Jeddah, Saudi Arabia 2-Centre for Science and Medical Research (UJC-" + "author_name": "Christopher P Bourdeaux", + "author_inst": "University of Bristol" }, { - "author_name": "Nawal Helmi", - "author_inst": "Assistant Professor, 1- Department of Medical Laboratory Technology, College of Applied Medical Sciences, University of Jeddah 2- Department of Biochemistry, C" + "author_name": "Christos Vasilakis", + "author_inst": "University of Bath" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.04.02.20050773", @@ -1545557,53 +1545291,33 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.04.03.024257", - "rel_title": "SARS-CoV-2 and SARS-CoV differ in their cell tropism and drug sensitivity profiles", + "rel_doi": "10.1101/2020.04.02.022764", + "rel_title": "Potent Antiviral Activities of Type I Interferons to SARS-CoV-2 Infection", "rel_date": "2020-04-05", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.03.024257", - "rel_abs": "SARS-CoV-2 is a novel coronavirus currently causing a pandemic. We show that the majority of amino acid positions, which differ between SARS-CoV-2 and the closely related SARS-CoV, are differentially conserved suggesting differences in biological behaviour. In agreement, novel cell culture models revealed differences between the tropism of SARS-CoV-2 and SARS-CoV. Moreover, cellular ACE2 (SARS-CoV-2 receptor) and TMPRSS2 (enables virus entry via S protein cleavage) levels did not reliably indicate cell susceptibility to SARS-CoV-2. SARS-CoV-2 and SARS-CoV further differed in their drug sensitivity profiles. Thus, only drug testing using SARS-CoV-2 reliably identifies therapy candidates. Therapeutic concentrations of the approved protease inhibitor aprotinin displayed anti-SARS-CoV-2 activity. The efficacy of aprotinin and of remdesivir (currently under clinical investigation against SARS-CoV-2) were further enhanced by therapeutic concentrations of the proton pump inhibitor omeprazole (aprotinin 2.7-fold, remdesivir 10-fold). Hence, our study has also identified anti-SARS-CoV-2 therapy candidates that can be readily tested in patients.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.02.022764", + "rel_abs": "The historical outbreak of COVID-19 disease not only constitutes a global public health crisis, but also has a devastating social and economic impact. The disease is caused by a newly identified coronavirus, Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). There is an urgent need to identify antivirals to curtail the COVID-19 pandemic. Herein, we report the remarkable sensitivity of SARS-CoV-2 to recombinant human interferons and {beta} (IFN/{beta}). Treatment with IFN- or IFN-{beta} at a concentration of 50 international units (IU) per milliliter drastically reduce viral titers by 3.4 log or 4.5 log, respectively in Vero cells. The EC50 of IFN- and IFN-{beta} treatment is 1.35 IU/ml and 0.76 IU/ml, respectively, in Vero cells. These results suggested that SARS-CoV-2 is more sensitive to many other human pathogenic viruses, including the SARS-CoV. Overall, our results demonstrate the potent efficacy of human Type I IFN in suppressing SARS-CoV-2 replication, a finding which could inform future treatment options for COVID-19.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Denisa Bojkova", - "author_inst": "Goethe-University" - }, - { - "author_name": "Jake E McGreig", - "author_inst": "University of Kent" - }, - { - "author_name": "Katie-May McLaughlin", - "author_inst": "University of Kent" - }, - { - "author_name": "Stuart G Masterson", - "author_inst": "University of Kent" - }, - { - "author_name": "Marek Widera", - "author_inst": "Goethe-University" - }, - { - "author_name": "Verena Kraehling", - "author_inst": "University of Marburg" + "author_name": "Emily K. Mantlo", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Sandra Ciesek", - "author_inst": "Goethe-University" + "author_name": "Natalya Bukreyeva", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Mark N Wass", - "author_inst": "University of Kent" + "author_name": "Junki Maruyama", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Martin Michaelis", - "author_inst": "University of Kent" + "author_name": "Slobodan Paessler", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Jindrich N Cinatl Jr.", - "author_inst": "Klinikum der Goethe-Universitaet" + "author_name": "Cheng Huang", + "author_inst": "University of Texas Medical Branch" } ], "version": "1", @@ -1547039,53 +1546753,37 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.03.31.20048777", - "rel_title": "Reply to Gautret et al. 2020: A Bayesian reanalysis of the effects of hydroxychloroquine and azithromycin on viral carriage in patients with COVID-19", + "rel_doi": "10.1101/2020.03.31.20048876", + "rel_title": "Japanese citizens' behavioral changes and preparedness against COVID-19: How effective is Japan's approach of self-restraint?", "rel_date": "2020-04-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.31.20048777", - "rel_abs": "Gautret and colleagues reported results of a non-randomised open-label case series which examined the effects of hydroxychloroquine and azithromycin on viral load in the upper respiratory tract of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patients. The authors report that hydroxychloroquine (HCQ) had significant virus reducing effects, and that dual treatment of both HCQ and azithromycin further enhanced virus reduction. These data have triggered speculation whether these drugs should be considered as candidates for the treatment of severe COVID-19. However, questions have been raised regarding the studys data integrity, statistical analyses, and experimental design. We therefore reanalysed the original data to interrogate the main claims of the paper. Here we apply Bayesian statistics to assess the robustness of the original papers claims by testing four variants of the data: 1) The original data; 2) Data including patients who deteriorated; 3) Data including patients who deteriorated with exclusion of untested patients in the comparison group; 4) Data that includes patients who deteriorated with the assumption that untested patients were negative. To ask if HCQ monotherapy is effective, we performed an A/B test for a model which assumes a positive effect, compared to a model of no effect. We find that the statistical evidence is highly sensitive to these data variants. Statistical evidence for the positive effect model ranged from strong for the original data (BF+0 [~]11), to moderate when including patients who deteriorated (BF+0 [~]4.35), to anecdotal when excluding untested patients (BF+0 [~]2), and to anecdotal negative evidence if untested patients were assumed positive (BF+0 [~]0.6). To assess whether HCQ is more effective when combined with AZ, we performed the same tests, and found only anecdotal evidence for the positive effect model for the original data (BF+0 [~]2.8), and moderate evidence for all other variants of the data (BF+0 [~]5.6). Our analyses only explore the effects of different assumptions about excluded and untested patients. These assumptions are not adequately reported, nor are they justified in the original paper, and we find that varying them causes substantive changes to the evidential support for the main claims of the original paper. This statistical uncertainty is exacerbated by the fact that the treatments were not randomised, and subject to several confounding variables including the patients consent to treatment, different care centres, and clinical decision-making. Furthermore, while the viral load measurements were noisy, showing multiple reversals between test outcomes, there is greater certainty around other clinical outcomes such as the 4 patients who seriously deteriorated. The fact that all of these belonged to the HCQ group should be assigned greater weight when evaluating the potential clinical efficacy of HCQ. Randomised controlled trials are currently underway, and will be critical in resolving this uncertainty as to whether HCQ and AZ are effective as a treatment for COVID-19.\n\nWarningThere have been reports of people self-administering chloroquine phosphate (intended for treatment of disease in aquarium fish), which has led to at least one death and one serious illness. We state that under no circumstances should people self-administer hydroxychloroquine, chloroquine phosphate, azithromycin, or anything similar-sounding, or indeed any other drug, unless approved by a medical doctor. The FDA has issued a specific warning: https://www.fda.gov/animal-veterinary/product-safety-information/fda-letter-stakeholders-do-not-use-chloroquine-phosphate-intended-fish-treatment-covid-19-humans", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.31.20048876", + "rel_abs": "The Japanese government instituted countermeasures against COVID-19, a pneumonia caused by the new coronavirus, in January 2020. Seeking \"peoples behavioral changes,\" in which the government called on the public to take precautionary measures or exercise self-restraint, was one of the important strategies. The purpose of this study is to investigate how and from when Japanese citizens have changed their precautionary behavior under these circumstances, where the government has only requested their cooperation. This study uses micro data from a cross-sectional survey conducted on an online platform of an online research company, based on quota sampling that is representative of the Japanese population. By the end of March 2020, we had recruited a total of 11,342 respondents, aged from 20 to 64 years. About 85% reported practising the social distancing recommended by the government. More females than males and more older than younger participants are supportive of practicing social distancing. Frequent handwashing is conducted by 86 percent of all, 92 percent of female and 87.9 percent of over-40 participants. The most important event influencing these precautionary actions was the infection aboard the Diamond Princess cruise ship, which occurred in early February 2020 (23%). Information from the central and local governments, received by 60% of the participants, was deemed trustworthy by 50%. However, the results also showed that about 20% of the participants were reluctant to implement proper prevention measures. The statistical analysis indicated that the typical characteristics of those people were male, younger (under 30 years old), unmarried, from lower-income households, with a drinking or smoking habit and a higher extraversion score. To prevent the spread of infection in Japan, it is imperative to address these individuals and encourage their behavioral changes using various means to reach and influence them.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Oliver J Hulme", - "author_inst": "Danish Research Centre for Magnetic Resonance" - }, - { - "author_name": "Eric-Jan Wagenmakers", - "author_inst": "University of Amsterdam" - }, - { - "author_name": "Per Damkier", - "author_inst": "Odense University Hospital" - }, - { - "author_name": "Christopher Fugl Madelung", - "author_inst": "Danish Research Centre for Magnetic Resonance" - }, - { - "author_name": "Hartwig Roman Siebner", - "author_inst": "Danish Research Centre for Magnetic Resonance" + "author_name": "Kaori Muto", + "author_inst": "The Institute of Medical Science, The University of Tokyo" }, { - "author_name": "Jannik Helweg-Larsen", - "author_inst": "Copenhagen University Hospital Rigshospitalet" + "author_name": "Isamu Yamamoto", + "author_inst": "Faculty of Business and Commerce, Keio University" }, { - "author_name": "Quentin Gronau", - "author_inst": "University of Amsterdam" + "author_name": "Miwako Nagasu", + "author_inst": "Faculty of Economics, Keio University" }, { - "author_name": "Thomas Lars Benfield", - "author_inst": "Amager Hvidovre Hospital" + "author_name": "Mikihito Tanaka", + "author_inst": "Faculty of Political Science and Economics, Waseda University" }, { - "author_name": "Kristoffer H Madsen", - "author_inst": "Danish Research Centre for Magnetic Resonance" + "author_name": "Koji Wada", + "author_inst": "Graduate School of Medicine and Public Health International University of Health and Welfare" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1548157,23 +1547855,35 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.03.31.20048967", - "rel_title": "Knowledge and behaviors toward COVID-19 among U.S. residents during the early days of the pandemic", + "rel_doi": "10.1101/2020.03.30.20047878", + "rel_title": "ACE2 and TMPRSS2 variants and expression as candidates to sex and country differences in COVID-19 severity in Italy", "rel_date": "2020-04-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.31.20048967", - "rel_abs": "ObjectiveTo test the hypothesis that knowledge of COVID-19 influences participation in different behaviors including self-reports of purchasing more goods than usual, attending large gatherings, and using medical masks.\n\nMethodsCross-sectional online survey of 1,034 U.S. residents age 18+ conducted on March 17, 2020.\n\nResultsFor every point increase in knowledge, the odds of participation in purchasing more goods (OR=0.88, 95% CI:0.81-0.95), attending large gatherings (OR=0.87, 95%CI: 0.81-0.93), and using medical masks (OR=0.56, 95% CI:0.50-0.62) decreased by 12%, 13%, and 44%, respectively. Gen X and Millennial participants had 56% to 76% higher odds, respectively, of increased purchasing behavior, compared to Baby Boomers. Results suggest politicization of response recommendations. Democrats had 30% lower odds of attending large gatherings (OR=0.70, 95% CI:0.50-0.97), and 48% lower odds of using medical masks (OR=0.52, 95% CI:0.34-0.78), compared to Republicans.\n\nConclusionsThis survey is one of the first attempts to study determinants of knowledge and behaviors in response to the COVID-19 pandemic in the U.S. A national, coordinated effort at pandemic response may ensure better compliance with behavioral recommendations to address this public health emergency.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.30.20047878", + "rel_abs": "BackgroundAs the outbreak of coronavirus disease 2019 (COVID-19) progresses, prognostic markers for early identification of high-risk individuals are an urgent medical need. Italy has the highest rate of SARS-CoV-2 infection, the highest number of deaths, and the highest mortality rate among large countries. Worldwide, a more severe course of COVID-19 is associated with older age, comorbidities, and male sex. Hence, we searched for possible genetic components of the peculiar severity of COVID-19 among Italians, by looking at expression levels and variants in ACE2 and TMPRSS2 genes, which are crucial for viral infection.\n\nMethodsExome and SNP array data from a large Italian cohort representative of the countrys population were used to compare the burden of rare variants and the frequency of polymorphisms with European and East Asian populations. Moreover, we looked into gene expression databases to check for sex-unbalanced expression.\n\nResultsWhile we found no significant evidence that ACE2 is associated with disease severity/sex bias in the Italian population, TMPRSS2 levels and genetic variants proved to be possible candidate disease modulators, contributing to the observed epidemiological data among Italian patients.\n\nConclusionsOur analysis suggests a role for TMPRSS2 variants and expression levels in modulating COVID-19 severity, a hypothesis that fosters a rapid experimental validation on large cohorts of patients with different clinical manifestations.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "John M. Clements", - "author_inst": "Michigan State University" + "author_name": "Rosanna Asselta", + "author_inst": "Humanitas University" + }, + { + "author_name": "Elvezia Maria Paraboschi", + "author_inst": "Humanitas University" + }, + { + "author_name": "Alberto Mantovani", + "author_inst": "Humanitas University" + }, + { + "author_name": "Stefano Duga", + "author_inst": "Humanitas University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2020.03.31.20048439", @@ -1549471,25 +1549181,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.03.30.20047993", - "rel_title": "Assessing the interactions between COVID-19 and influenza in the United States", + "rel_doi": "10.1101/2020.03.30.20047597", + "rel_title": "How will this continue? Modelling interactions between the COVID-19 pandemic and policy responses", "rel_date": "2020-04-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.30.20047993", - "rel_abs": "As healthcare capacities in the US and Europe reach their limits due to a surge in the COVID-19 pandemic, both regions enter the 2020-2021 influenza season. Southern hemisphere countries that had suppressed influenza seasons provide a hopeful example, but the lack of reduction in influenza in the 2019-2020 influenza season and heterogeneity in nonpharmaceutical and pharmaceutical interventions show that we cannot assume the same effect will occur globally. The US and Europe must promote the implementation and continuation of these measures in order to prevent additional burden to healthcare systems due to influenza.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.30.20047597", + "rel_abs": "Much of the uncertainty about the progression of the COVID-19 pandemic stems from questions about when and how non-pharmaceutical interventions (NPI) by governments, in particular social distancing measures, are implemented, to what extent the population complies with these measures, and how compliance changes through time. Further uncertainty comes from a lack of knowledge of the potential effects of removing interventions once the epidemic is declining. By combining an epidemiological model of COVID-19 for the United Kingdom with simple sub-models for these societal processes, this study aims to shed light on the conceivable trajectories that the pandemic might follow over the next 1.5 years. We show strong improvements in outcomes if governments review NPI more frequently whereas, in comparison, the stability of compliance has surprisingly small effects on cumulative mortality. Assuming that mortality does considerably increase once a countrys hospital capacity is breached, we show that the inherent randomness of societal processes can lead to a wide range of possible outcomes, both in terms of disease dynamics and mortality, even when the principles according to which policy and population operate are identical.. Our model is easily modified to take other aspects of the socio-pandemic interaction into account.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Casey M Zipfel", - "author_inst": "Georgetown University" + "author_name": "Axel G Rossberg", + "author_inst": "School of Biological and Chemical Sciences, Queen Mary University of London" }, { - "author_name": "Vittoria Colizza", - "author_inst": "INSERM" - }, - { - "author_name": "Shweta Bansal", - "author_inst": "Georgetown University" + "author_name": "Robert J. Knell", + "author_inst": "School of Biological and Chemical Sciences, Queen Mary University of London" } ], "version": "1", @@ -1550513,49 +1550219,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.03.30.20046227", - "rel_title": "Forecasting the dynamics of COVID-19 Pandemic in Top 15 countries in April 2020 through ARIMA Model with Machine Learning Approach", + "rel_doi": "10.1101/2020.03.29.20046532", + "rel_title": "Prediction of Peak and Termination of Novel Coronavirus Covid-19 Epidemic in Iran", "rel_date": "2020-03-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.30.20046227", - "rel_abs": "We here predicted some trajectories of COVID-19 in the coming days (until April 30, 2020) using the most advanced Auto-Regressive Integrated Moving Average Model (ARIMA). Our analysis predicted very frightening outcomes, which defines to worsen the conditions in Iran, entire Europe, especially Italy, Spain, and France. While South Korea, after the initial blast, has come to stability, the same goes for the COVID-19 origin country China with more positive recovery cases and confirm to remain stable. The United States of America (USA) will come as a surprise and going to become the epicenter for new cases during the mid-April 2020. Based on our predictions, public health officials should tailor aggressive interventions to grasp the power exponential growth, and rapid infection control measures at hospital levels are urgently needed to curtail the COVID-19 pandemic.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.29.20046532", + "rel_abs": "The growth and development of Covid-19 transmission have significantly cut the attention of many societies, particularly Iran that has been struggling with this contagious, infectious disease since late February 2020. In the present study, the known SIR model was used for the dynamics of an epidemic to provide a suitable assessment of the COVID-19 virus epidemic in Iran. The epidemic curve and SIR model parameters were obtained with the use of Iran statistical data. The recovered people were considered alongside the official number of confirmed victims as the reliable long-time statistical data of Iran. The results offered many important predictions of the COVID-19 virus epidemic such as realistic number of victims, infection rate, peak time, and other characteristics.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Pavan Kumar", - "author_inst": "Department of Horticulture and Forestry, Rani Lakshmi Bai Central Agricultural University, Jhansi-284003, India" - }, - { - "author_name": "Himangshu Kalita", - "author_inst": "Haryana Space Applications Centre (HARSAC), Department of Science & Technology, CCS HAU Campus, HISAR 125004, India" - }, - { - "author_name": "Shashikanta Patairiya", - "author_inst": "Anchor Systems Corp. Reston, VA 20194, USA" - }, - { - "author_name": "Yagya Datt Sharma", - "author_inst": "Hughes SystiqueCorporation, Germantown (MD), 20876 USA" + "author_name": "AmirPouyan Zahiri", + "author_inst": "Ferdowsi University of Mashhad" }, { - "author_name": "Chintan Nanda", - "author_inst": "Indian Institute of Remote Sensing, ISRO, Dehradune, India" + "author_name": "Sepehr RafieeNasab", + "author_inst": "Ferdowsi University of Mashhad" }, { - "author_name": "Meenu Rani", - "author_inst": "Department of Geography, Kumaun University, Nainital, Uttarakhand, India" - }, - { - "author_name": "Jamal Rahmani", - "author_inst": "Department of Community Nutrition, National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, Iran" - }, - { - "author_name": "Akshaya Srikanth Bhagavathula", - "author_inst": "Institute of Public Health, College of Medicine and Health Sciences, United Arab Emirates University,Al Ain, UAE" + "author_name": "Ehsan Roohi", + "author_inst": "Xi'an Jiaotong University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1551942,101 +1551628,97 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.26.20044222", - "rel_title": "Clinical characteristics of the recovered COVID-19 patients with re-detectable positive RNA test", + "rel_doi": "10.1101/2020.03.25.20043166", + "rel_title": "Risk assessment of progression to severe conditions for patients with COVID-19 pneumonia: a single-center retrospective study", "rel_date": "2020-03-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.26.20044222", - "rel_abs": "BackgroundIt has been reported that several cases recovered from COVID-19 tested positive for SARS-CoV-2 after discharge (re-detectable positive, RP), however the clinical characteristics, significance and potential cause of RP patients remained elusive.\n\nMethodsA total of 262 COVID-19 patients were discharged from January 23 to February 25, 2020, and were enrolled for analysis of their clinical parameters. The RP and non-RP (NRP) patients were grouped according to the disease severity during their hospitalization period. The clinical characterization at re-admission to the hospital was analyzed. SARS-CoV-2 RNA and plasma antibody levels were detected using high-sensitive detection methods.\n\nFindingsUp to March 10, 2020, all of patients were followed up for at least 14 days, and 38/262 of RP patients (14.5%) were present. The RP patients were characterized by being less than 14-years old and having mild and moderate conditions as compared to NRP patients, while no severe patients became RP. Retrospectively, the RP patients displayed fewer symptoms, more sustained remission of CT imaging and earlier RNA negative-conversion but similar plasma antibody levels during their hospitalization period as compared to those NRP patients. When re-admitted to the hospital, these RP patients showed no obvious clinical symptoms or disease progression indicated by normal or improving CT imaging and inflammatory cytokine levels. All 21 close contacts of RP patients were tested negative for SARS-CoV-2 RNA, and no suspicious clinical symptoms were reported. However, 18/24 of RNA-negative samples detected by the commercial kit were tested to be positive for virus RNA using a hyper-sensitive method, suggesting the carrier status of virus possibly existed in patients recovered from COVID-19.\n\nInterpretationOur results showed that young and mild COVID-19 patients seem to be RP patients after discharge, who show no obviously clinical symptoms and disease progression upon re-admission. More sensitive RNA detection methods are required to monitor these patients during follow-up. Our findings provide empirical information and evidence for the effective management of COVID-19 patients during their convalescent phase.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.25.20043166", + "rel_abs": "BackgroundManagement of high mortality risk due to significant progression requires prior assessment of time-to-progression. However, few related methods are available for COVID-19 pneumonia.\n\nMethodsWe retrospectively enrolled 338 adult patients admitted to one hospital between Jan 11, 2020 to Feb 29, 2020. The final follow-up date was March 8, 2020. We compared characteristics between patients with severe and non-severe outcome, and used multivariate survival analyses to assess the risk of progression to severe conditions.\n\nResultsA total of 76 (31.9%) patients progressed to severe conditions and 3 (0.9%) died. The mean time from hospital admission to severity onset is 3.7 days. Age, body mass index (BMI), fever symptom on admission, co-existing hypertension or diabetes are associated with severe progression. Compared to non-severe group, the severe group already demonstrated, at an early stage, abnormalities in biomarkers indicating organ function, inflammatory responses, blood oxygen and coagulation function. The cohort is characterized with increasing cumulative incidences of severe progression up to 10 days after admission. Competing risks survival model incorporating CT imaging and baseline information showed an improved performance for predicting severity onset (mean time-dependent AUC = 0.880).\n\nConclusionsMultiple predisposition factors can be utilized to assess the risk of progression to severe conditions at an early stage. Multivariate survival models can reasonably analyze the progression risk based on early-stage CT images that would otherwise be misjudged by artificial analysis.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Jianghong An", - "author_inst": "Department of Oncology and Hematology, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" - }, - { - "author_name": "Xuejiao Liao", - "author_inst": "Institute of Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" + "author_name": "Lijiao Zeng", + "author_inst": "Shenzhen Third People's Hospital" }, { - "author_name": "Tongyang Xiao", - "author_inst": "Institute of Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" + "author_name": "Jialu Li", + "author_inst": "HuaJia Biomedical Intelligence" }, { - "author_name": "Shen Qian", - "author_inst": "Institute of Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" + "author_name": "Mingfeng Liao", + "author_inst": "Shenzhen Third People's Hospital" }, { - "author_name": "Jing Yuan", - "author_inst": "Department of Infectious Diseases, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" + "author_name": "Rui Hua", + "author_inst": "HuaJia Biomedical Intelligence" }, { - "author_name": "Haocheng Ye", - "author_inst": "Institute of Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" + "author_name": "Pilai Huang", + "author_inst": "Shenzhen Third People's Hospital" }, { - "author_name": "Furong Qi", - "author_inst": "Institute of Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" + "author_name": "Mingxia Zhang", + "author_inst": "Shenzhen Third People's Hospital" }, { - "author_name": "Chengguang Shen", - "author_inst": "Institute of Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" + "author_name": "Youlong Zhang", + "author_inst": "HuaJia Biomedical Intelligence" }, { - "author_name": "Yang Liu", - "author_inst": "Institute of Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" + "author_name": "Qinlang Shi", + "author_inst": "Shenzhen Third People's Hospital" }, { - "author_name": "Lifei Wang", - "author_inst": "Department of Radiology, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" + "author_name": "Zhaohua Xia", + "author_inst": "Shenzhen Third People's Hospital" }, { - "author_name": "Xiaoya Cheng", - "author_inst": "Department of Oncology and Hematology, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" + "author_name": "Xinzhong Ning", + "author_inst": "Shenzhen Third People's Hospital" }, { - "author_name": "Na Li", - "author_inst": "Institute of Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" + "author_name": "Dandan Liu", + "author_inst": "Shenzhen Third People's Hospital" }, { - "author_name": "Qingxian Cai", - "author_inst": "Department of Hepatology, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" + "author_name": "Jiu Mo", + "author_inst": "HuaJia Biomedical Intelligence" }, { - "author_name": "Fang Wang", - "author_inst": "Department of Hepatology, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" + "author_name": "Ziyuan Zhou", + "author_inst": "Shenzhen Third People's Hospital" }, { - "author_name": "Jun Chen", - "author_inst": "Department of Hepatology, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" + "author_name": "Zigang Li", + "author_inst": "Shenzhen Bay Laboratory" }, { - "author_name": "Yingxia Liu", - "author_inst": "Department of Infectious Diseases, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" + "author_name": "Yu Fu", + "author_inst": "Shenzhen Third People's Hospital" }, { - "author_name": "Yunfang Wang", - "author_inst": "Translational Research Center, Beijing Tsinghua Changgung Hospital, Tsinghua University, Beijing 102218, Beijing , China" + "author_name": "Yuhui Liao", + "author_inst": "Southern Medical University" }, { - "author_name": "Feng Zhang", - "author_inst": "Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA" + "author_name": "Jing Yuan", + "author_inst": "Shenzhen Third People's Hospital" }, { - "author_name": "Yang Fu", - "author_inst": "School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong, 518055, China" + "author_name": "Lifei Wang", + "author_inst": "Shenzhen Third People's Hospital" }, { - "author_name": "Xiaohua Tan", - "author_inst": "Department of Oncology and Hematology, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China" + "author_name": "Qing He", + "author_inst": "Shenzhen Third People's Hospital" }, { "author_name": "Lei Liu", - "author_inst": "The Second Affiliated Hospital, School of Medicine,Southern University of Science and Technology, Shenzhen 518112, Guangdong Province, China.Institute of Hepato" + "author_inst": "Shenzhen Third People's Hospital" }, { - "author_name": "Zheng Zhang", - "author_inst": "Institute of Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third Peoples Hospital, Shenzhen 518112, Guangdong Province, China.T" + "author_name": "Kun Qiao", + "author_inst": "Shenzhen Third People's Hospital" } ], "version": "1", @@ -1553356,29 +1553038,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.03.29.20046730", - "rel_title": "Scaling analysis of COVID-19 spreading based on Belgian hospitalization data", + "rel_doi": "10.1101/2020.03.29.20046870", + "rel_title": "COVID-19 Modelling: the Effects of Social Distancing", "rel_date": "2020-03-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.29.20046730", - "rel_abs": "We analyze the temporal evolution of accumulated hospitalization cases due to COVID-19 in Belgium. The increase of hospitalization cases is consistent with an initial exponential phase, and a subsequent power law growth. For the latter, we estimate a power law exponent of {approx} 2.2, which is consistent with growth kinetics of COVID-19 in China and indicative of the underlying small world network structure of the epidemic. Finally, we fit an SIR-X model to the experimental data and estimate the effect of containment policies in comparison to their effect in China. This model suggests that the base reproduction rate has been significantly reduced, but that the number of susceptible individuals that is isolated from infection is very small. Based on the SIR-X model fit, we analyze the COVID-19 mortality and the number of patients requiring ICU treatment over time.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.29.20046870", + "rel_abs": "The purpose of this article is to reach all those who find it difficult to become well informed about the repercussions of a lockdown strategy to tackle the COVID-19 pandemic and to spark discussion and thought. Here we use simple stochastic simulations to evaluate different approaches taken to tackle the crisis, along with the efficiency they will hold and the number of casualties they may incur. It is clear that the less strict the social distancing the more time it will take for life to return to normal, and the more lives will be at risk. This is shown through simulations formed by an open sourced code, which allows evaluation of the outcomes from different intervention scenarios or conditions.", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Bart Smeets", - "author_inst": "KU Leuven" + "author_name": "Oliva Bendtsen Cano", + "author_inst": "Stephen Perse Foundation" }, { - "author_name": "Rodrigo Watte", - "author_inst": "Indigo" + "author_name": "Sabrina Cano Morales", + "author_inst": "Cambridge University" }, { - "author_name": "Herman Ramon", - "author_inst": "KU Leuven" + "author_name": "Claus Bendtsen", + "author_inst": "N/A" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1554778,39 +1554460,23 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2020.03.29.20045880", - "rel_title": "Presence of SARS-Coronavirus-2 in sewage", + "rel_doi": "10.1101/2020.03.26.20044552", + "rel_title": "Inclusive Costs of NPI Measures for COVID-19 Pandemic: Three Approaches", "rel_date": "2020-03-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.29.20045880", - "rel_abs": "In the current COVID-19 pandemic, a significant proportion of cases shed SARS-Coronavirus-2 (SARS-CoV-2) with their faeces. To determine if SARS-CoV-2 is present in sewage during the emergence of COVID-19 in the Netherlands, sewage samples of 7 cities and the airport were tested using RT-PCR against three fragments of the nucleocapsid protein gene (N1-3) and one fragment of the envelope protein gene (E). No SARS-CoV-2 was detected in samples of February 6, three weeks before the first case was reported in the Netherlands on February 27. On March 5, the N1 fragment was detected in sewage of five sites. On March 15/16, the N1 fragment was detected in sewage of six sites, and the N3 and E fragment were detected at 5 and 4 sites respectively. This is the first report of detection of SARS-CoV-2 in sewage. The detection of the virus in sewage, even when the COVID-19 prevalence is low, indicates that sewage surveillance could be a sensitive tool to monitor the circulation of the virus in the population.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.26.20044552", + "rel_abs": "The paper evaluates total inclusive costs of three public health approaches to address the COVID-19 epidemic in the US based on epidemiological projections in Ferguson et al (2020). We calculate and add costs of lost productivity and costs of mortality measured through the value of statistical life. We find that the aggressive approach which involves strict suppression measures and a drastic reduction of economic activity for three months with extensive testing and case tracking afterwards results in the lowest total costs for the society. The approach of doing no non-pharmaceutical measures results in the lowest total costs if the infection fatality rate falls below 0.15%.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Gertjan Medema", - "author_inst": "KWR Water Research Institute" - }, - { - "author_name": "Leo Heijnen", - "author_inst": "KWR Water Research Institute" - }, - { - "author_name": "Goffe Elsinga", - "author_inst": "KWR Water Research Institute" - }, - { - "author_name": "Ronald Italiaander", - "author_inst": "KWR Water Research Institute" - }, - { - "author_name": "Anke Brouwer", - "author_inst": "KWR Water Research Institute" + "author_name": "Alexander Ugarov", + "author_inst": "University of Oklahoma" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "health economics" }, { "rel_doi": "10.1101/2020.03.26.20044388", @@ -1556108,21 +1555774,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.03.26.20044628", - "rel_title": "First month of the epidemic caused by COVID-19 in Italy: current status and real-time outbreak development forecast", + "rel_doi": "10.1101/2020.03.28.20046177", + "rel_title": "A data-driven tool for tracking and predicting the course of COVID-19 epidemic as it evolves", "rel_date": "2020-03-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.26.20044628", - "rel_abs": "BackgroundThe first outbreaks of COVID-19 in Italy occurred during the second half of February 2020 in some areas in the North of the country. Due to the high contagiousness of the infection, further spread by asymptomatic people, Italy has become in a few weeks the country with the greatest number of infected people after China. The large number of severe cases among infected people in Italy led to the hospitalization of thousands of patients, with a heavy burden on the National Health Service.\n\nMethodsWe analyzed data provided daily by Italian Authorities for the period from 24 February 2020 to 26 March 2020. Considering such information, we developed a forecast model in real-time, based on the cumulative logistic distribution. We then produced an estimate of the overall number of potentially infected individuals and epidemic duration at a national and Regional level, for the most affected Regions.\n\nResultsWe reported the daily distribution of performed swabs and confirmed cases, and the cumulative distribution of confirmed cases, of patients quarantined at home (42%), hospitalized in non-intensive care (31%), recovered or discharged (13%), deceased (10%), and hospitalized in intensive care (4%). The forecast model estimated a number of infected persons for Italy of 115,000 about, and a duration of the epidemic not less than 2 months.\n\nConclusionsOnce month after the first outbreaks there seems to be the first signs of a decrease in the number of infections, showing that we could be now facing the descending phase of the epidemic. The forecast obtained thanks to our model could be used by decision-makers to implement coordinative and collaborative efforts in order to control the epidemic.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.28.20046177", + "rel_abs": "New COVID-19 epicenters have sprung up in Europe and US as the epidemic in China wanes. Many mechanistic models past predictions for China were widely off the mark (1, 2), and still vary widely for the new epicenters, due to uncertain disease characteristics. The epidemic ended in Wuhan, and later in South Korea, with less than 1% of their population infected, much less than that required to achieve \"herd immunity\". Now as most countries pursue the goal of \"suppressed equilibrium\", the traditional concept of \"herd immunity\" in epidemiology needs to be re-examined. Traditional model predictions of large potential impacts serve their purpose in prompting policy decisions on contact suppression and lockdown to combat the spread, and are useful for evaluating various scenarios. After imposition of these measures it is important to turn to statistical models that incorporate real-time information that reflects ongoing policy implementation and degrees of compliance to more realistically track and project the epidemics course. Here we apply such a tool, supported by theory and validated by past data as accurate, to US and Europe. Most countries started with a Reproduction Number of 4 and declined to around 1 at a rate highly dependent on contact-reduction measures.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Rosario Megna", - "author_inst": "National Council of Research" + "author_name": "Norden E Huang", + "author_inst": "First Institute of Oceanography" + }, + { + "author_name": "Fangli Qiao", + "author_inst": "First Institute of Oceanography" + }, + { + "author_name": "Qian Wang", + "author_inst": "Shanghai Jiao Tong University" + }, + { + "author_name": "Ka-Kit Tung", + "author_inst": "University of Washington" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1557314,127 +1556992,55 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2020.03.25.996348", - "rel_title": "Structure-Based Design, Synthesis and Biological Evaluation of Peptidomimetic Aldehydes as a Novel Series of Antiviral Drug Candidates Targeting the SARS-CoV-2 Main Protease", + "rel_doi": "10.1101/2020.03.26.010694", + "rel_title": "The Nucleocapsid Protein of SARS-CoV-2 Abolished Pluripotency in Human Induced Pluripotent Stem Cells", "rel_date": "2020-03-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.25.996348", - "rel_abs": "SARS-CoV-2 is the etiological agent responsible for the COVID-19 outbreak in Wuhan. Specific antiviral drug are urgently needed to treat COVID-19 infections. The main protease (Mpro) of SARS-CoV-2 is a key CoV enzyme that plays a pivotal role in mediating viral replication and transcription, which makes it an attractive drug target. In an effort to rapidly discover lead compounds targeting Mpro, two compounds (11a and 11b) were designed and synthesized, both of which exhibited excellent inhibitory activity with an IC50 value of 0.05 M and 0.04 M respectively. Significantly, both compounds exhibited potent anti-SARS-CoV-2 infection activity in a cell-based assay with an EC50 value of 0.42 M and 0.33 M, respectively. The X-ray crystal structures of SARS-CoV-2 Mpro in complex with 11a and 11b were determined at 1.5 [A] resolution, respectively. The crystal structures showed that 11a and 11b are covalent inhibitors, the aldehyde groups of which are bound covalently to Cys145 of Mpro. Both compounds showed good PK properties in vivo, and 11a also exhibited low toxicity which is promising drug leads with clinical potential that merits further studies.", - "rel_num_authors": 27, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.26.010694", + "rel_abs": "The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is raging across the world, leading to a global mortality rate of 3.4% (estimated by World Health Organization in March 2020). As a potential vaccine and therapeutic target, the nucleocapsid protein of SARS-CoV-2 (nCoVN) functions in packaging the viral genome and viral self-assembly. To investigate the biological effects of nCoVN to human stem cells, genetically engineered human induced pluripotent stem cells (iPSC) expressing nCoVN (iPSC-nCoVN) were generated by lentiviral expression systems, in which the expression of nCoVN could be induced by the doxycycline. The proliferation rate of iPSC-nCoVN was decreased. Unexpectedly, the morphology of iPSC started to change after nCoVN expression for 7 days. The pluripotency marker TRA-1-81 were not detectable in iPSC-nCoVN after a four-day induction. Meanwhile, iPSC-nCoVN lost the ability for differentiation into cardiomyocytes with a routine differentiation protocol. The RNA-seq data of iPSC-nCoVN (induction for 30 days) and immunofluorescence assays illustrated that iPSC-nCoVN were turning to fibroblast-like cells. Our data suggested that nCoVN disrupted the pluripotent properties of iPSC and turned them into other types of cells, which provided a new insight to the pathogenic mechanism of SARS-CoV-2.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Wenhao Dai", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" - }, - { - "author_name": "Bing Zhang", - "author_inst": "ShanghaiTech University" - }, - { - "author_name": "Xia-Ming Jiang", - "author_inst": "Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" - }, - { - "author_name": "Haixia Su", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" - }, - { - "author_name": "Jian Li", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" - }, - { - "author_name": "Yao Zhao", - "author_inst": "ShanghaiTech University" - }, - { - "author_name": "Xiong Xie", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" - }, - { - "author_name": "Zhenming Jin", - "author_inst": "ShanghaiTech University" - }, - { - "author_name": "Jingjing Peng", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" - }, - { - "author_name": "Fengjiang Liu", - "author_inst": "ShanghaiTech University" - }, - { - "author_name": "Chunpu Li", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" - }, - { - "author_name": "You Li", - "author_inst": "National Chengdu Center for Safety Evaluation of Drugs" - }, - { - "author_name": "Fang Bai", - "author_inst": "ShanghaiTech University" - }, - { - "author_name": "Haofeng Wang", - "author_inst": "ShanghaiTech University" - }, - { - "author_name": "Xi Cheng", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" - }, - { - "author_name": "Xiaobo Cen", - "author_inst": "National Chengdu Center for Safety Evaluation of Drugs" - }, - { - "author_name": "Shulei Hu", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" + "author_name": "Zebin Lin", + "author_inst": "School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, China" }, { - "author_name": "Xiuna Yang", - "author_inst": "ShanghaiTech University" + "author_name": "Zhiming Wu", + "author_inst": "Department of Urology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicin" }, { - "author_name": "Jiang Wang", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" + "author_name": "Jinlian Mai", + "author_inst": "Guangdong Beating Origin Regenerative Medicine Co. Ltd., Foshan, China" }, { - "author_name": "Xiang Liu", - "author_inst": "Nankai University" + "author_name": "Lishi Zhou", + "author_inst": "Guangdong Beating Origin Regenerative Medicine Co. Ltd., Foshan, China" }, { - "author_name": "Gengfu Xiao", - "author_inst": "Chinese Academy of Sciences" + "author_name": "Yu Qian", + "author_inst": "School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, China" }, { - "author_name": "Hualiang Jiang", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" + "author_name": "Tian Cai", + "author_inst": "Nanhai District Peoples Hospital of Foshan, Foshan, China" }, { - "author_name": "Zihe Rao", - "author_inst": "Tsinghua University" + "author_name": "Zhenhua Chen", + "author_inst": "Nanhai District Peoples Hospital of Foshan, Foshan, China" }, { - "author_name": "Leike Zhang", - "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences" - }, - { - "author_name": "Yechun Xu", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" - }, - { - "author_name": "Haitao Yang", - "author_inst": "ShanghaiTech University" + "author_name": "Ping Wang", + "author_inst": "School of Medical Imaging, Tianjin Medical University, Tianjin, China" }, { - "author_name": "Hong Liu", - "author_inst": "Shanghai Institute of Material Medica" + "author_name": "Bin Lin", + "author_inst": "Guangdong Beating Origin Regenerative Medicine Co. Ltd., Foshan, Guangdong 528231, China" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "new results", - "category": "biochemistry" + "category": "cell biology" }, { "rel_doi": "10.1101/2020.03.26.009605", @@ -1558732,119 +1558338,115 @@ "category": "pharmacology and therapeutics" }, { - "rel_doi": "10.1101/2020.03.25.20043489", - "rel_title": "UV Sterilization of Personal Protective Equipment with Idle Laboratory Biosafety Cabinets During the Covid-19 Pandemic", + "rel_doi": "10.1101/2020.03.23.20041707", + "rel_title": "Serology characteristics of SARS-CoV-2 infection since the exposure and post symptoms onset", "rel_date": "2020-03-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.25.20043489", - "rel_abs": "DISCLAIMERThis article does not represent the official recommendation of the Cleveland Clinic or Case Western Reserve University School of Medicine, nor has it yet been peer reviewed. We are releasing it early, pre-peer review, to allow for quick dissemination/vetting by the scientific/clinical community given the necessity for rapid conservation of personal protective equipment (PPE) during this dire global situation. We welcome feedback from the community.\n\nPersonal protective equipment (PPE), including face shields, surgical masks, and N95 respirators, is crucially important to the safety of both patients and medical personnel, particularly in the event of an infectious pandemic. As the incidence of Coronavirus Disease (COVID-19) increases exponentially in the United States and worldwide, healthcare provider demand for these necessities is currently outpacing supply. As such, strategies to extend the lifespan of the supply of medical equipment as safely as possible are critically important. In the midst of the current pandemic, there has been a concerted effort to identify viable ways to conserve PPE, including decontamination after use. Some hospitals have already begun using UV-C light to decontaminate N95 respirators and other PPE, but many lack the space or equipment to implement existing protocols. In this study, we outline a procedure by which PPE may be decontaminated using ultraviolet (UV) radiation in biosafety cabinets (BSCs), a common element of many academic, public health, and hospital laboratories, and discuss the dose ranges needed for effective decontamination of critical PPE. We further discuss obstacles to this approach including the possibility that the UV radiation levels vary within BSCs. Effective decontamination of N95 respirator masks or surgical masks requires UV-C doses of greater than 1 Jcm-2, which would take a minimum of 4.3 hours per side when placing the N95 at the bottom of the BSCs tested in this study. Elevating the N95 mask by 48 cm (so that it lies 19 cm from the top of the BSC) would enable the delivery of germicidal doses of UV-C in 62 minutes per side. Effective decontamination of face shields likely requires a much lower UV-C dose, and may be achieved by placing the face shields at the bottom of the BSC for 20 minutes per side. Our results are intended to provide support to healthcare organizations looking for alternative methods to extend their reserves of PPE. We recognize that institutions will require robust quality control processes to guarantee the efficacy of any implemented decontamination protocol. We also recognize that in certain situations such institutional resources may not be available; while we subscribe to the general principle that some degree of decontamination is preferable to re-use without decontamination, we would strongly advise that in such cases at least some degree of on-site verification of UV dose delivery be performed.", - "rel_num_authors": 25, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.23.20041707", + "rel_abs": "BackgroundTimely diagnosis of SARS-CoV-2 infection is the prerequisite for treatment and preventive quarantine. The serology characteristics and complement diagnosis value of antibody test to RNA test needs to be demonstrated.\n\nMethodA patient cohort study was conducted at the first affiliated hospital of Zhejiang University, China. Serial plasma of COVID-19 patients and were collected and total antibody (Ab), IgM and IgG antibody against SARS-CoV-2 were detected. The antibody dynamics during the infection were described.\n\nResultsThe seroconversion rate for Ab, IgM and IgG in COVID-19 patients was 98.8% (79/80), 93.8% (75/80) and 93.8% (75/80), respectively. The first detectible serology marker is total antibody and followed by IgM and IgG, with a median seroconversion time of 15, 18 and 20 day post exposure (d.p.e) or 9, 10 and 12 days post onset, separately. The antibody levels increased rapidly since 6 d.p.o and accompanied with the decline of viral load. For patients in the early stage of illness (0-7d.p.o),Ab showed the highest sensitivity (64.1%) compared to the IgM and IgG (33.3% for both, p<0.001). The sensitivities of Ab, IgM and IgG detection increased to 100%, 96.7% and 93.3% two weeks later, respectively.\n\nConclusionsTypical acute antibody response is induced during the SARS-CoV-2 infection. The serology testing provides important complementation to RNA test for pathogenic specific diagnosis and helpful information to evaluate the adapted immunity status of patient. It should be strongly recommended to apply well-validated antibody tests in the clinical management and public health practice to improve the control of COVID-19 infection.\n\nTake-Home MessageAntibody responses are induced after SARS-CoV-2 infection and complement diagnosis value of antibody test to RNA test was observed. Antibody tests are critical tools in clinical management and control of SARS-CoV-2 infection and COVID-19.", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Davis T Weaver", - "author_inst": "Cleveland Clinic Lerner Research Institute" - }, - { - "author_name": "Benjamin D. McElvany", - "author_inst": "University of Vermont Medical Center" + "author_name": "Bin Lou", + "author_inst": "Zhejaing University" }, { - "author_name": "Vishhvaan Gopalakrishnan", - "author_inst": "Cleveland Clinic Lerner Research Institute" + "author_name": "Tigndong Li", + "author_inst": "Xiamen University" }, { - "author_name": "Kyle J Card", - "author_inst": "Michigan State University" + "author_name": "Shufa Zheng", + "author_inst": "Zhejiang University" }, { - "author_name": "Dena Crozier", - "author_inst": "Cleveland Clinic Lerner Research Institute" + "author_name": "Yingying Su", + "author_inst": "Xiamen University" }, { - "author_name": "Andrew Dhawan", - "author_inst": "Cleveland Clinic Lerner Research Institute" + "author_name": "Zhiyong Li", + "author_inst": "Xiamen University" }, { - "author_name": "Mina Dinh", - "author_inst": "Cleveland Clinic Lerner Research Institute" + "author_name": "Wei Liu", + "author_inst": "Xiamen University" }, { - "author_name": "Emily Dolson", - "author_inst": "Cleveland Clinic Lerner Research Institute" + "author_name": "Fei Yu", + "author_inst": "Zhejiang University" }, { - "author_name": "Nathan Farrokhian", - "author_inst": "Cleveland Clinic Lerner Research Institute" + "author_name": "Shengxiang Ge", + "author_inst": "Xiamen University" }, { - "author_name": "Masahiro Hitomi", - "author_inst": "Cleveland Clinic Lerner Research Institute" + "author_name": "Qianda Zou", + "author_inst": "Zhejiang University" }, { - "author_name": "Emily Ho", - "author_inst": "Cleveland Clinic Lerner Research Institute" + "author_name": "Quan Yuan", + "author_inst": "Xiamen University" }, { - "author_name": "Tanush Jagdish", - "author_inst": "Harvard University" + "author_name": "Sha Lin", + "author_inst": "Zhejiang University" }, { - "author_name": "Eshan S King", - "author_inst": "Cleveland Clinic Lerner Research Institute" + "author_name": "Congming Hong", + "author_inst": "Xiamen University" }, { - "author_name": "Nikhil Krishnan", - "author_inst": "Cleveland Clinic Lerner Research Institute" + "author_name": "Xiangyang Yao", + "author_inst": "Xiamen University" }, { - "author_name": "Gleb Kuzmin", - "author_inst": "Cleveland Clinic Lerner Research Institute" + "author_name": "Xuejie Zhang", + "author_inst": "Xiamen University" }, { - "author_name": "Ju Li", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Dinghui Wu", + "author_inst": "Xiamen University" }, { - "author_name": "Jeff Maltas", - "author_inst": "University of Michigan" + "author_name": "Guoliang Zhou", + "author_inst": "Xiamen University" }, { - "author_name": "Jinhan Mo", - "author_inst": "Tsinghua University" + "author_name": "Wangheng Hou", + "author_inst": "Xiamen University" }, { - "author_name": "Julia Pelesko", - "author_inst": "Cleveland Clinic Lerner Research Institute" + "author_name": "Tingting Li", + "author_inst": "Xiamen University" }, { - "author_name": "Jessica A Scarborough", - "author_inst": "Cleveland Clinic Lerner Research Institute" + "author_name": "Yali Zhang", + "author_inst": "Xiamen University" }, { - "author_name": "Enze Tian", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Shiyin Zhang", + "author_inst": "Xiamen University" }, { - "author_name": "Geoff Sedor", - "author_inst": "Cleveland Clinic Lerner Research Institute" + "author_name": "Jian Fan", + "author_inst": "Zhejiang University" }, { - "author_name": "Gary C. An", - "author_inst": "University of Vermont Medical Center" + "author_name": "Jun Zhang", + "author_inst": "Xiamen University" }, { - "author_name": "Sean A. Diehl", - "author_inst": "University of Vermont" + "author_name": "Ningshao Xia", + "author_inst": "Xiamen University" }, { - "author_name": "Jacob G Scott", - "author_inst": "Cleveland Clinic Lerner Research Institute" + "author_name": "Yu Chen", + "author_inst": "Zhejiang University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.03.24.20042234", @@ -1560226,47 +1559828,51 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.03.24.20043018", - "rel_title": "Age-dependent effects in the transmission and control of COVID-19 epidemics", + "rel_doi": "10.1101/2020.03.24.20042119", + "rel_title": "A New Predictor of Disease Severity in Patients with COVID-19 in Wuhan, China", "rel_date": "2020-03-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.24.20043018", - "rel_abs": "The COVID-19 pandemic has shown a markedly low proportion of cases among children. Age disparities in observed cases could be explained by children having lower susceptibility to infection, lower propensity to show clinical symptoms, or both. We evaluate these possibilities by fitting an age-structured mathematical model to epidemic data from six countries. We estimate that clinical symptoms occur in 25% (95% CrI: 19-32%) of infections in 10-19-year-olds, rising to 76% (68-82%) in over-70s, and that susceptibility to infection in under-20s is approximately half that of older adults. Accordingly, we find that interventions aimed at children may have a relatively small impact on total cases, particularly if the transmissibility of subclinical infections is low. The age-specific clinical fraction and susceptibility we have estimated has implications for the expected global burden of COVID-19 because of demographic differences across settings: in younger populations, the expected clinical attack rate would be lower, although it is likely that comorbidities in low-income countries will affect disease severity. Without effective control measures, regions with older populations may see disproportionally more clinical cases, particularly in the later stages of the pandemic.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.24.20042119", + "rel_abs": "BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) broke out in Wuhan, Hubei, China. This study sought to elucidate a novel predictor of disease severity in patients with coronavirus disease-19 (COVID-19) cased by SARS-CoV-2.\n\nMethodsPatients enrolled in this study were all hospitalized with COVID-19 in the Central Hospital of Wuhan, China. Clinical features, chronic comorbidities, demographic data, and laboratory and radiological data were reviewed. The outcomes of patients with severe pneumonia and those with non-severe pneumonia were compared using the Statistical Package for the Social Sciences (IBM Corp., Armonk, NY, USA) to explore clinical characteristics and risk factors. The receiver operating characteristic curve was used to screen optimal predictors from the risk factors and the predictive power was verified by internal validation.\n\nResultsA total of 377 patients diagnosed with COVID-19 were enrolled in this study, including 117 with severe pneumonia and 260 with non-severe pneumonia. The independent risk factors for severe pneumonia were age [odds ratio (OR): 1.059, 95% confidence interval (CI): 1.036-1.082; p < 0.001], N/L (OR: 1.322, 95% CI: 1.180-1.481; p < 0.001), CRP (OR: 1.231, 95% CI: 1.129-1.341; p = 0.002), and D-dimer (OR: 1.059, 95% CI: 1.013-1.107; p = 0.011). We identified a product of N/L*CRP*D-dimer as having an important predictive value for the severity of COVID-19. The cutoff value was 5.32. The negative predictive value of less than 5.32 for the N/L*CRP*D-dimer was 93.75%, while the positive predictive value was 46.03% in the test sets. The sensitivity and specificity were 89.47% and 67.42%. In the training sets, the negative and positive predictive values were 93.80% and 41.32%, respectively, with a specificity of 70.76% and a sensitivity of 89.87%.\n\nConclusionsA product of N/L*CRP*D-dimer may be an important predictor of disease severity in patients with COVID-19.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Nicholas G Davies", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Ying Zhou", + "author_inst": "The Central Hospital of Wuhan" }, { - "author_name": "Petra Klepac", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Zhen Yang", + "author_inst": "The Central Hospital of Wuhan" }, { - "author_name": "Yang Liu", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Yanan Guo", + "author_inst": "The Central Hospital of Wuhan" }, { - "author_name": "Kiesha Prem", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Shuang Geng", + "author_inst": "The Central Hospital of Wuhan" }, { - "author_name": "Mark Jit", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Shan Gao", + "author_inst": "The Central Hospital of Wuhan" }, { - "author_name": "CMMID COVID-19 working group", - "author_inst": "" + "author_name": "Shenglan Ye", + "author_inst": "The Central Hospital of Wuhan" }, { - "author_name": "Rosalind M Eggo", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Yi Hu", + "author_inst": "The Central Hospital of Wuhan" + }, + { + "author_name": "Yafei Wang", + "author_inst": "The Central Hospital of Wuhan" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2020.03.23.20041889", @@ -1561840,37 +1561446,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.24.20042556", - "rel_title": "Home collection of nasal swabs for detection of influenza in the Household Influenza Vaccine Evaluation Study", + "rel_doi": "10.1101/2020.03.24.20038828", + "rel_title": "Symptomatology during seasonal coronavirus infections in children is associated with viral and bacterial co-detection", "rel_date": "2020-03-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.24.20042556", - "rel_abs": "BackgroundCommunity based studies of influenza and other respiratory viruses (e.g. SARS-COV-2) require laboratory confirmation of infection. During the current COVID-19 pandemic, social distancing guidelines require alternative data collection in order protect both research staff and participants.\n\nHome-collected respiratory specimens are less resource intensive, can be collected earlier after symptom onset, and provide a low-contact means of data collection. A prospective, multi-year, community-based cohort study is an ideal setting to examine the utility of home-collected specimens for identification of influenza.\n\nMethodsWe describe the feasibility and reliability of home-collected specimens for the detection of influenza. We collected data and specimens between October 2014 and June 2017 from the Household Influenza Vaccine Evaluation (HIVE) Study. Cohort participants were asked to collect a nasal swab at home upon onset of acute respiratory illness. Research staff also collected nose and throat swab specimens in the study clinic within 7 days of onset. We estimated agreement using Cohens kappa and calculated sensitivity and specificity of home-collected compared to staff-collected specimens.\n\nResultsWe tested 336 paired staff- and home-collected respiratory specimens for influenza by RT-PCR; 150 staff-collected specimens were positive for influenza A/H3N2, 23 for influenza A/H1N1, 14 for influenza B/Victoria, and 31 for influenza B/Yamagata. We found moderate agreement between collection methods for influenza A/H3N2 (0.70) and B/Yamagata (0.69) and high agreement for influenza A/H1N1 (0.87) and B/Victoria (0.86). Sensitivity ranged from 78-86% for all influenza types and subtypes. Specificity was high for influenza A/H1N1 and both influenza B lineages with a range from 96-100%, and slightly lower for A/H3N2 infections (88%).\n\nConclusionsCollection of nasal swab specimens at home is both feasible and reliable for identification of influenza virus infections.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.24.20038828", + "rel_abs": "Lower respiratory tract symptoms during seasonal coronavirus infections in children are associated with RSV co-detection and increased levels of Haemophilus and Fusobacterium species.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Ryan E Malosh", - "author_inst": "University of Michigan School of Public Health" - }, - { - "author_name": "Joshua G Petrie", - "author_inst": "University of Michigan School of Public Health" + "author_name": "Emma M. de Koff", + "author_inst": "Spaarne Gasthuis, Hoofddorp and Haarlem, The Netherlands" }, { - "author_name": "Amy P Callear", - "author_inst": "University of Michigan School of Public Health" + "author_name": "Marlies A. van Houten", + "author_inst": "Spaarne Gasthuis, Hoofddorp and Haarlem, The Netherlands" }, { - "author_name": "Arnold S Monto", - "author_inst": "University of Michigan School of Public Health" + "author_name": "Elisabeth A.M. Sanders", + "author_inst": "National Institute for Public Health and the Environment, Bilthoven, The Netherlands and University Medical Centre Utrecht, Utrecht, The Netherlands" }, { - "author_name": "Emily Toth Martin", - "author_inst": "University of Michigan School of Public Health" + "author_name": "Debby Bogaert", + "author_inst": "Queen's Medical Research Institute, Edinburgh, UK and University Medical Centre Utrecht, Utrecht,The Netherlands" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1563490,87 +1563092,23 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.21.20040121", - "rel_title": "Myocardial injury is associated with in-hospital mortality of confirmed or suspected COVID-19 in Wuhan, China: A single center retrospective cohort study", + "rel_doi": "10.1101/2020.03.21.20039867", + "rel_title": "A New, Simple Projection Model for COVID-19 Pandemic", "rel_date": "2020-03-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.21.20040121", - "rel_abs": "BackgroundSince December 2019, a cluster of coronavirus disease 2019 (COVID-19) occurred in Wuhan, Hubei Province, China and spread rapidly from China to other countries. In-hospital mortality are high in severe cases and cardiac injury characterized by elevated cardiac troponin are common among them. The mechanism of cardiac injury and the relationship between cardiac injury and in-hospital mortality remained unclear. Studies focused on cardiac injury in COVID-19 patients are scarce.\n\nObjectivesTo investigate the association between cardiac injury and in-hospital mortality of patients with confirmed or suspected COVID-19.\n\nMethodsDemographic, clinical, treatment, and laboratory data of consecutive confirmed or suspected COVID-19 patients admitted in Wuhan No.1 Hospital from 25th December, 2019 to 15th February, 2020 were extracted from electronic medical records and were retrospectively reviewed and analyzed. Univariate and multivariate Cox regression analysis were used to explore the risk factors associated with in-hospital death.\n\nResultsA total of 110 patients with confirmed (n=80) or suspected (n=30) COVID-19 were screened and 48 patients (female 31.3%, mean age 70.58{+/-}13.38 year old) among them with high-sensitivity cardiac troponin I (hs-cTnI) test within 48 hours after admission were included, of whom 17 (17/48, 35.4%) died in hospital while 31 (31/48, 64.6%) were discharged or transferred to other hospital. High-sensitivity cardiac troponin I was elevated in 13 (13/48, 27.1%) patents. Multivariate Cox regression analysis showed pulse oximetry of oxygen saturation (SpO2) on admission (HR 0.704, 95% CI 0.546-0.909, per 1% decrease, p=0.007), elevated hs-cTnI (HR 10.902, 95% 1.279-92.927, p=0.029) and elevated d-dimer (HR 1.103, 95%CI 1.034-1.176, per 1mg/L increase, p=0.003) on admission were independently associated with in-hospital mortality.\n\nConclusionsCardiac injury defined by hs-cTnI elevation and elevated d-dimer on admission were risk factors for in-hospital death, while higher SpO2 could be seen as a protective factor, which could help clinicians to identify patients with adverse outcome at the early stage of COVID-19.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.21.20039867", + "rel_abs": "BackgroundWith the worldwide outbreak of COVID-19, an accurate model to predict how the coronavirus pandemic will evolve in individual countries becomes important and urgent. Our goal is to provide a prediction model to help policy makers in different countries address the epidemic outbreak and adjust the control policies to contain the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) more effectively.\n\nMethodsUnlike the classic public health and virus propagation models, this new projection model takes both government intervention and public response into account to generate reliable projections of the outbreak 10 days to 2 weeks in advance. This method is an observation based projection similar than the classic Moores Law in miroelectronics. The Moores law is not based on any physics law and yet has anticipated the development of microelectronics for decades. This work is an empirical relation to decribe the evolution of epidemic to pandemic situations in different countries. The country was selected as an observation unit because the regulation and political decision is an national decision for numerous measures such as the implementation of social distancing, the quarantine of suspected cases, and the closing of borders to achieve territorial containment.\n\nFindingsThis model has been successfully applied to predict the evolution of pendemic situation in China. Then the model was also validated by the South Korean data. With a reduction of cases calculated as reduction coefficient of the increase rate of daily cases Rc = 2% per day, we observed a very efficient policy with a strict systematic control in both China and South Korea. For the moment, the Canada, USA, Australia may have difficulties to limit the fast evolution of the epidemic. With a Rc<0.5%, its particularly important for the USA to consider escalating the control measures because the affected cases can reach more than one million very soon.\n\nInterpertationDue to the difference of national disciplines and historical culture, the national policy may be implemented and observed with different efficiency. The starting point where the government decided to apply total containment can also play a key role for the evolution of the pendemic situation. The model will allow each national government of the nations still affected by the pandemic to project the situation for the coming 10 to 14 days. Its very important for the deployment of national and international efforts to stop the pandemic situation.\n\nFundingNational Key R&D Program of China (Ministry of Science & Technology (MOST, China))", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Fan Zhang", - "author_inst": "Department of Cardiology, Wuhan No.1 Hospital" - }, - { - "author_name": "Deyan Yang", - "author_inst": "Department of Cardiology, Peking Union Medical College Hospital, Chinese Academy Medical Sciences & Peking Union Medical college, Beijing, China" - }, - { - "author_name": "Jing Li", - "author_inst": "Department of Cardiology, Wuhan No.1 Hospital" - }, - { - "author_name": "Peng Gao", - "author_inst": "Department of Cardiology, Peking Union Medical College Hospital, Chinese Academy Medical Sciences & Peking Union Medical college, Beijing, China" - }, - { - "author_name": "Taibo Chen", - "author_inst": "Department of Cardiology, Peking Union Medical College Hospital, Chinese Academy Medical Sciences & Peking Union Medical college, Beijing, China" - }, - { - "author_name": "Zhongwei Cheng", - "author_inst": "Department of Cardiology, Peking Union Medical College Hospital, Chinese Academy Medical Sciences & Peking Union Medical college, Beijing, China" - }, - { - "author_name": "Kangan Cheng", - "author_inst": "Department of Cardiology, Peking Union Medical College Hospital, Chinese Academy Medical Sciences & Peking Union Medical college, Beijing, China" - }, - { - "author_name": "Quan Fang", - "author_inst": "Department of Cardiology, Peking Union Medical College Hospital, Chinese Academy Medical Sciences & Peking Union Medical college, Beijing, China" - }, - { - "author_name": "Wan Pan", - "author_inst": "Department of Cardiology, Wuhan No.1 Hospital" - }, - { - "author_name": "Chunfeng Yi", - "author_inst": "Department of Cardiology, Wuhan No.1 Hospital" - }, - { - "author_name": "Hongru Fan", - "author_inst": "Department of Cardiology, Wuhan No.1 Hospital" - }, - { - "author_name": "Yonghong Wu", - "author_inst": "Department of Cardiology, Wuhan No.1 Hospital" - }, - { - "author_name": "Liwei Li", - "author_inst": "Department of Cardiology, Wuhan No.1 Hospital" - }, - { - "author_name": "Yong Fang", - "author_inst": "Department of Cardiology, Wuhan No.1 Hospital" - }, - { - "author_name": "Juan Liu", - "author_inst": "Department of Cardiology, Wuhan No.1 Hospital" - }, - { - "author_name": "Guowei Tian", - "author_inst": "Department of Cardiology, Wuhan No.1 Hospital" - }, - { - "author_name": "Liqun He", - "author_inst": "Department of Cardiology, Wuhan No.1 Hospital" + "author_name": "Jian Lu", + "author_inst": "City University of Hong Kong" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "cardiovascular medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.03.21.20040139", @@ -1565216,29 +1564754,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.03.19.20037192", - "rel_title": "Trend analysis of the COVID-19 pandemic in China and the rest of the world", + "rel_doi": "10.1101/2020.03.20.20039594", + "rel_title": "Covid-19 health care demand and mortality in Sweden in response to non-pharmaceutical (NPIs) mitigation and suppression scenarios", "rel_date": "2020-03-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.19.20037192", - "rel_abs": "The recent epidemic of Coronavirus (COVID-19) that started in China has already been \"exported\" to more than 140 countries in all the continents, evolving in most of them by local spreading. In this contribution we analyze the trends of the cases reported in all the Chinese provinces, as well as in some countries that, until March 15th, 2020, have more than 500 cases reported. Notably and differently from other epidemics, the provinces did not show an exponential phase. The data available at the Johns Hopkins University site [1] seem to fit well an algebraic sub-exponential growing behavior as was pointed out recently [2]. All the provinces show a clear and consistent pattern of slowing down with growing exponent going nearly zero, so it can be said that the epidemic was contained in China. On the other side, the more recent spread in countries like, Italy, Iran, and Spain show a clear exponential growth, as well as other European countries. Even more recently, US --which was one of the first countries to have an individual infected outside China (Jan 21st, 2020)-- seems to follow the same path. We calculate the exponential growth of the most affected countries, showing the evolution along time after the first local case. We identify clearly different patterns in the analyzed data and we give interpretations and possible explanations for them. The analysis and conclusions of our study can help countries that, after importing some cases, are not yet in the local spreading phase, or have just started.\n\nHIGHLIGHTSO_LIAll the provinces of China show very similar epidemic behaviour.\nC_LIO_LIEarly stages of spreading can be explained in terms of SIR standard model, considering that reported cases accounts for the removed individuals, with algebraic growing (sub-exponential) in most locations.\nC_LIO_LIWorldwide, we observe two classes of epidemic growth: sub-exponential during almost all stages (China and Japan) and exponential on the rest of the countries, following the early stage.\nC_LIO_LIThe exponential growth rates ranges from 0.016day-1 (South Korea) to 0.725day-1 (Brunei) which means 1.6% to 107% of new cases per day, for the different countries but China.\nC_LI", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.20.20039594", + "rel_abs": "BackgroundWhile the COVID-19 outbreak in China now appears surpressed, Europe and the US have become the epicenters, both reporting many more deaths than China. Responding to the pandemic, Sweden has taken a different approach aiming to mitigate, not suppressing community transmission, by using physical distancing without lock-downs. Here we contrast consequences of different responses to COVID-19 within Sweden, the resulting demand for care, intensive care, the death tolls, and the associated direct healthcare related costs.\n\nMethodsWe use an age stratified health-care demand extended SEIR compartmental model calibrated to the municipality level for all municipalities in Sweden, and a radiation model describing inter-municipality mobility.\n\nResultsOur model fit well with the observed deaths in Sweden up to 20th of April, 2020. The intensive care unit (ICU) demand is estimated to reach almost 10,000 patients per day by early May in an unmitigated scenario, far above the pre-pandemic ICU capacity of 526 beds. In contrast, a scenario with moderate physical distancing and shielding of elderly in combination with more effective isolation of infectious individuals would reduce numbers to below 500 per day. This would substantially flatten the curve, extend the epidemic period, but a risk resurgence is expected if measures are relaxed. The different scenarios show quite different death tolls up to the 1th of September, ranging from 5,000 to 41,000 deaths, exluding deaths potentially caused by ICU shortage. Further, analyses of the total all-cause mortality in Stockholm indicate that a confirmed COVID-19 death is associated with a additional 0.40 (95% Cl: 0.24, 0.57) all-cause death.\n\nConclusionThe results of this study highlight the impact of different combinations of non-pharmaceutical interventions, especially moderate physical distancing and shielding of elderly in combination with more effective isolation of infectious individuals, on reducing deaths and lower healthcare costs. In less effective mitigation scenarios, the demand on ICU beds would rapidly exceed capacity, showing the tight interconnection between the healthcare demand and physical distancing in the society. These findings have relevance for Swedish policy and response to the COVID-19 pandemic and illustrate the importance of maintaining the level of physical distancing for a longer period to suppress or mitigate the impacts from the pandemic.\n\nKey messagesO_LIWe find physical distancing and isolation of infectious individuals without lockdown is effective in mitigating much of the negative direct health impact from the COVID-19 pandemic in Sweden, but has a higher death toll compared to other Scandinavian countries who did implement a lockdown\nC_LIO_LIBetween the start of the Swedish model of physical distancing and shiedling the elderly in March to late April, it appears Sweden has managed to ensure that ICU demands do not exceed ICU capacities and that deaths are substantially reduced compared to a counterfactual scenario.\nC_LIO_LIIn the counterfactual scenario (eg no public health interventions), the intensive care unit demand is estimated to be almost 20 times higher than the intensive care capacity in Sweden and the number of deaths would be between 40,000 to 60,000\nC_LIO_LIUnder current mitigation strategies, the death toll, health care need, and its associated cost are, however, still substantial, and it is likely to continue to rise unless the virus is suppressed, or eliminated. In the stronger mitigation and suppression scenarios, including the scenario fitting best to data from Sweden by late April 2020, there is an obvious risk of resurgence of the epidemic unless physical distancing, shielding of the elderly, and home isolation are effectively sustained.\nC_LIO_LIAdditional analyses indicate all-cause non COVID-19 excess mortality rises with 0.4 deaths per every reported COVID-19 death in the Stockholm area.\nC_LI", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Albertine Weber", - "author_inst": "Instituto de Fisica, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil" - }, - { - "author_name": "Flavio Iannelli", - "author_inst": "URPP Social Networks, University of Zurich, Andreasstrasse 15, CH-8050 Zurich, Switzerland" - }, - { - "author_name": "Sebastian Goncalves", - "author_inst": "Instituto de Fisica, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil" + "author_name": "Joacim Rocklov", + "author_inst": "Umea University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1566566,85 +1566096,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.19.20034124", - "rel_title": "COVID-19 Myocarditis and Severity Factors\uff1a An Adult Cohort Study", + "rel_doi": "10.1101/2020.03.20.20039776", + "rel_title": "Modelling the Potential Health Impact of the COVID-19 Pandemic on a Hypothetical European Country", "rel_date": "2020-03-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.19.20034124", - "rel_abs": "BackgroundNotwithstanding the clinical hallmarks of COVID-19 patients were reported, several critical issues still remain mysterious, i.e., prognostic factors for COVID-19 including extrinsic factors as viral load of SARS-CoV-2 and intrinsic factors as individuals health conditions; myocarditis incidence rate and hallmarks.\n\nMethodsDemographic, epidemiologic, radiologic and laboratory data were collected by medical record reviews of adult hospitalized patients diagnosed as COVID-19. Cycle threshold (Ct) value data of real-time PCR (RT-PCR) were collected. The time duration was from 21 January to 2 March, 2020. Pulmonary inflammation index (PII) values were used for chest CT findings. Multivariate logistic regression analysis was used to identify independent severity risk factors.\n\nRESULTSIn total, 84 hospitalized adult patients diagnosed as COVID-19 were included, including 20 severe and 64 nonsevere cases. The viral load of the severe group was significantly higher than that of the non-severe group, regardless of the Ct values for N or ORF1ab gene of virus (all p<0.05).Typical CT abnormalities was more likely existing in the severe group than in the nonsevere group in patchy shadows or ground glass opacities, consolidation, and interlobular septal thickening (all p<0.05). In addition, the PII values in the severe group was significantly higher than that in the nonsevere group (52.5 [42.5-62.5] vs 20 [5.0-31.6]; p<0.001). Amongst 84 patients, 13 patients (15.48%) were noted with abnormal electrocardiograms (ECGs) and serum myocardial enzyme levels; whereas 4 (4.8%) were clinically diagnosed as SARS-CoV-2 myocarditis. Multivariable logistic regress analysis distinguished three key independent risk factors for the severity of COVID-19, including age [OR 2.350; 95% CI (1.206 to 4.580); p=0.012], Ct value [OR 0.158; 95% CI (0.025 to 0.987); p=0.048] and PII [OR 1.912; 95% CI (1.187 to 3.079); p=0.008].\n\nInterpretationThree key-independent risk factors of COVID-19 were identified, including age, PII, and Ct value. The Ct value is closely correlated with the severity of COVID-19, and may act as a predictor of clinical severity of COVID-19 in the early stage. SARS-CoV-2 myocarditis should be highlighted despite a relatively low incidence rate (4.8%). The oxygen pressure and blood oxygen saturation should not be neglected as closely linked with the altitude of epidemic regions.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched Pubmed on March 15, 2020 using the terms (\"COVID-19\" OR \"novel coronavirus\" OR \"2019 novel coronavirus\" OR \"2019-nCoV\" OR \"pneumonia\" OR \"coronavirus\"), AND \"Myocarditis\" OR \"Cycle threshold (Ct)\" OR \"Altitude\". We found that one article analyzed the risk factors affecting the prognosis of adult patients with COVID-19 in terms of survivorship, without considering Ct values as extrinsic factors. Moreover, there are no reported studies on viral myocarditis caused by COVID-19 and the relationship between the altitude and COVID-19.\n\nAdded value of this studyWe retrospectively analyzed the clinical data, Ct values, laboratory indicators and imaging findings of 84 adult patients with confirmed COVID-19. Three key-independent risk factors of COVID-19 were identified in our study, including age [OR 2.350; 95% CI (1.206 to 4.580); p=0.012], Ct value [OR 0.158; 95% CI (0.025 to 0.987); p=0.048] and PII [OR 1.912; 95% CI (1.187 to 3.079); p=0.008]. Amongst 84 patients, 13 patients (15.48%) were noted with abnormal electrocardiograms (ECGs) and serum myocardial enzyme levels; whereas 4 (4.8%) were clinically diagnosed as SARS-CoV-2 myocarditis. Moreover, altitude should be considered for COVID-19 severity classification, given that oxygen partial pressure and blood oxygen saturation of regional patients vary with altitudes.\n\nImplications of all the available evidenceThree key-independent risk factors of COVID-19 were identified, including age, PII, and Ct value. The Ct value is closely correlated with the severity of COVID-19, and may act as a predictor of clinical severity of COVID-19 in the early stage. SARS-CoV-2 myocarditis should be highlighted despite a relatively low incidence rate (4.8%). The oxygen pressure and blood oxygen saturation should not be neglected as closely linked with the altitude of epidemic regions.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.20.20039776", + "rel_abs": "A SEIR simulation model for the COVID-19 pandemic was developed (http://covidsim.eu) and applied to a hypothetical European country of 10 million population. Our results show which interventions potentially push the epidemic peak into the subsequent year (when vaccinations may be available) or which fail. Different levels of control (via contact reduction) resulted in 22% to 63% of the population sick, 0.2% to 0.6% hospitalised, and 0.07% to 0.28% dead (n=6,450 to 28,228).", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Kun-Long Ma", - "author_inst": "Yongchuan Hospital of Chongqing Medical University" - }, - { - "author_name": "Zhi-Heng Liu", - "author_inst": "Xi'an Air Force 986 Hospital, Air Force Medical University" - }, - { - "author_name": "Chun-feng Cao", - "author_inst": "Yongchuan Hospital of Chongqing Medical University" - }, - { - "author_name": "Ming-Ke Liu", - "author_inst": "Yongchuan Hospital of Chongqing Medical University" - }, - { - "author_name": "Juan Liao", - "author_inst": "Yongchuan Hospital of Chongqing Medical University" - }, - { - "author_name": "Jing-Bo Zou", - "author_inst": "Yongchuan Center for Disease and Prevention" - }, - { - "author_name": "Ling-Xi Kong", - "author_inst": "Yongchuan Hospital of Chongqing Medical University" - }, - { - "author_name": "Ke-Qiang Wan", - "author_inst": "Yongchuan Hospital of Chongqing Medical University" - }, - { - "author_name": "Jun Zhang", - "author_inst": "Baoji Central Hospital" - }, - { - "author_name": "Qun-Bo Wang", - "author_inst": "Yongchuan Hospital of Chongqing Medical University" - }, - { - "author_name": "Wen-Guang Tian", - "author_inst": "Yongchuan Hospital of Chongqing Medical University" - }, - { - "author_name": "Guang-Mei Qin", - "author_inst": "Yongchuan Hospital of Chongqing Medical University" - }, - { - "author_name": "Lei Zhang", - "author_inst": "Chinese Academy of Medical Sciences & Peking Union Medical College" + "author_name": "Nick Wilson", + "author_inst": "University of Otago, Wellington" }, { - "author_name": "Fun-Jun Luan", - "author_inst": "Yongchuan Hospital of Chongqing Medical University" + "author_name": "Lucy Telfar Barnard", + "author_inst": "University of Otago Wellington" }, { - "author_name": "Shi-Ling Li", - "author_inst": "Yongchuan Hospital of Chongqing Medical University" + "author_name": "Amanda Kvalsig", + "author_inst": "University of Otago Wellington" }, { - "author_name": "Liang-Bo Hu", - "author_inst": "Yongchuan Hospital of Chongqing Medical University" + "author_name": "Ayesha Verrall", + "author_inst": "University of Otago Wellington" }, { - "author_name": "Qian-Lu Li", - "author_inst": "Yongchuan Hospital of Chongqing Medical University" + "author_name": "Michael G Baker", + "author_inst": "University of Otago Wellington" }, { - "author_name": "Hai-Qiang Wang", - "author_inst": "Shaanxi University of Chinese Medicine" + "author_name": "Markus Schwehm", + "author_inst": "Explosys" } ], "version": "1", @@ -1568548,55 +1568030,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.17.20036681", - "rel_title": "Change in outbreak epicenter and its impact on the importation risks of COVID-19 progression: a modelling study", + "rel_doi": "10.1101/2020.03.18.20037101", + "rel_title": "Epidemiology of seasonal coronaviruses: Establishing the context for COVID-19 emergence", "rel_date": "2020-03-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.17.20036681", - "rel_abs": "The outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) that originated in the city of Wuhan, China has now spread to every inhabitable continent, but now theattention has shifted from China to other epicenters, especially Italy. This study explored the influence of spatial proximities and travel patterns from Italy on the further spread of SARS-CoV-2 around the globe. We showed that as the epicenter changes, the dynamics of SARS-CoV-2 spread change to reflect spatial proximities.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.18.20037101", + "rel_abs": "Public health preparedness for coronavirus disease 2019 (COVID-19) is challenging in the absence of setting-specific epidemiological data. Here we describe the epidemiology of seasonal human coronaviruses (sCoVs) and other cocirculating viruses in the West of Scotland, UK. We analyzed routine diagnostic data for >70,000 episodes of respiratory illness tested molecularly for multiple respiratory viruses between 2005 and 2017. Statistical associations with patient age and sex differed between CoV-229E, CoV-OC43 and CoV-NL63. Furthermore, the timing and magnitude of sCoV outbreaks did not occur concurrently and coinfections were not reported. With respect to other cocirculating respiratory viruses, we found evidence of positive, rather than negative, interactions with sCoVs. These findings highlight the importance of considering cocirculating viruses in the differential diagnosis of COVID-19. Further work is needed to establish the occurrence/degree of cross-protective immunity conferred across sCoVs and with COVID-19, as well as the role of viral coinfection in COVID-19 disease severity.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Oyelola Adegboye", - "author_inst": "James Cook University" - }, - { - "author_name": "Adeshina Adekunle", - "author_inst": "James Cook University" - }, - { - "author_name": "Anton Pak", - "author_inst": "James Cook University" + "author_name": "Sema Nickbakhsh", + "author_inst": "MRC-University of Glasgow Centre for Virus Research" }, { - "author_name": "Ezra Gayawan", - "author_inst": "Federal University of Technology" + "author_name": "Antonia Ho", + "author_inst": "MRC-University of Glasgow Centre for Virus Research" }, { - "author_name": "Denis Leung", - "author_inst": "Singapore Management University" + "author_name": "Diogo F.P. Marques", + "author_inst": "Health Protection Scotland, NHS National Services Scotland" }, { - "author_name": "Diana Rojas", - "author_inst": "James Cook University" - }, - { - "author_name": "Faiz Elfaki", - "author_inst": "Qatar University" + "author_name": "Jim McMenamin", + "author_inst": "Health Protection Scotland, NHS National Services Scotland" }, { - "author_name": "Emma McBryde", - "author_inst": "James Cook University" + "author_name": "Rory R. Gunson", + "author_inst": "West of Scotland Specialist Virology Centre, NHS Greater Glasgow and Clyde" }, { - "author_name": "Damon Eisen", - "author_inst": "James Cook University" + "author_name": "Pablo Murcia", + "author_inst": "MRC-University of Glasgow Centre for Virus Research" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.03.16.20036939", @@ -1569826,41 +1569296,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.18.20038190", - "rel_title": "A brief review of antiviral drugs evaluated in registered clinical trials for COVID-19", + "rel_doi": "10.1101/2020.03.18.20037952", + "rel_title": "Estimating Preventable COVID19 Infections Related to Elective Outpatient Surgery in Washington State: A Quantitative Model", "rel_date": "2020-03-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.18.20038190", - "rel_abs": "BackgroundAlthough a number of antiviral agents have been evaluated for coronaviruses there are no approved drugs available. To provide an overview of the landscape of therapeutic research for COVID-19, we conducted a review of registered clinical trials.\n\nMethodsA review of currently registered clinical trials was performed on registries, including the Chinese (chictr.org.cn) and US (clinicaltrials.gov) databases to identify relevant studies up to March, 7th 2020. The search was conducted using the search terms \"2019-nCoV\", \"COVID-19\", \"SARS-CoV-2\", \"Hcov-19\", \"new coronavirus\", \"novel coronavirus\". We included interventional clinical trials focusing on patients with COVID-19 and assessing antiviral drugs or agents.\n\nFindingsOut of the 353 studies identified, 115 clinical trials were selected for data extraction. Phase IV trials were the most commonly reported study type (n=27, 23%). However, 62 trials (54%) did not describe the phase of the study. Eighty percent (n=92) of the trials were randomized with parallel assignment and the median number of planned inclusions was 63 (IQR, 36-120). Open-label studies were the most frequent (46%) followed by double-blind (13%) and single blind studies (10%). The most frequently assessed therapies were: stem cells therapy (n=23 trials), lopinavir/ritonavir (n=15), chloroquine (n=11), umifenovir (n=9), hydroxychloroquine (n=7), plasma treatment (n=7), favipiravir (n=7), methylprednisolone (n=5), and remdesivir (n=5). Remdesivir was tested in 5 trials with a median of 400 (IQR, 394-453) planned inclusions per trial, while stem cells therapy was tested in 23 trials, but had a median of 40 (IQR, 23-60) planned inclusions per trial. Lopinavir/ritonavir was associated with the highest total number of planned inclusions (2606) followed by remdesivir (2155). Only 52% of the clinical trials reported the treatment dose (n=60) and only 34% (n=39) the duration. The primary outcome was clinical in 76 studies (66%), virological in 27 (23%); radiological in 9 (8%) or immunological in three studies (3%).\n\nInterpretationNumerous clinical trials have been registered since the beginning of the COVID-19 outbreak, however, a number of information regarding drugs or trial design were lacking.\n\nFundingNone", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.18.20037952", + "rel_abs": "BackgroundAs the number of suspected and confirmed COVID-19 cases in the US continues to rise, the US surgeon general, Centers for Disease Control and Prevention, and several specialty societies have issued recommendations to consider canceling elective surgeries. However, these recommendations have also faced controversy and opposition.\n\nMethodsUsing previously published information and publicly available data on COVID-19 infections, we calculated a transmission rate and generated a mathematical model to predict a lower bound for the number of healthcare-acquired COVID-19 infections that could be prevented by canceling or postponing elective outpatient surgeries in Washington state.\n\nResultsOur model predicts that over the course of 30 days, at least 75.9 preventable patient infections and at least 69.3 preventable healthcare worker (HCW) infections would occur in WA state alone if elective outpatient procedures were to continue as usual.\n\nConclusionCanceling elective outpatient surgeries during the COVID-19 pandemic could prevent a large number of patient and healthcare worker infections.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Drifa Belhadi", - "author_inst": "Universite de Paris, IAME, INSERM" - }, - { - "author_name": "Nathan Peiffer-Smadja", - "author_inst": "Universite de Paris, IAME, INSERM" - }, - { - "author_name": "Fran\u00e7ois-Xavier Lescure", - "author_inst": "Universite de Paris, IAME, INSERM" - }, - { - "author_name": "Yazdan Yazdanpanah", - "author_inst": "Universite de Paris, IAME, INSERM" - }, - { - "author_name": "France Mentr\u00e9", - "author_inst": "Universite de Paris, IAME, INSERM" + "author_name": "Yuemei Zhang", + "author_inst": "University of Washington" }, { - "author_name": "C\u00e9dric Laou\u00e9nan", - "author_inst": "Universite de Paris, IAME, INSERM" + "author_name": "Sheng-Ru Cheng", + "author_inst": "University of Illinois at Urbana-Champaign" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1571408,139 +1570862,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.17.20037713", - "rel_title": "A serological assay to detect SARS-CoV-2 seroconversion in humans", + "rel_doi": "10.1101/2020.03.15.20036673", + "rel_title": "Stability of SARS-CoV-2 in different environmental conditions", "rel_date": "2020-03-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.17.20037713", - "rel_abs": "SARS-Cov-2 (severe acute respiratory disease coronavirus 2), which causes Coronavirus Disease 2019 (COVID19) was first detected in China in late 2019 and has since then caused a global pandemic. While molecular assays to directly detect the viral genetic material are available for the diagnosis of acute infection, we currently lack serological assays suitable to specifically detect SARS-CoV-2 antibodies. Here we describe serological enzyme-linked immunosorbent assays (ELISA) that we developed using recombinant antigens derived from the spike protein of SARS-CoV-2. Using negative control samples representing pre-COVID 19 background immunity in the general adult population as well as samples from COVID19 patients, we demonstrate that these assays are sensitive and specific, allowing for screening and identification of COVID19 seroconverters using human plasma/serum as early as two days post COVID19 symptoms onset. Importantly, these assays do not require handling of infectious virus, can be adjusted to detect different antibody types and are amendable to scaling. Such serological assays are of critical importance to determine seroprevalence in a given population, define previous exposure and identify highly reactive human donors for the generation of convalescent serum as therapeutic. Sensitive and specific identification of coronavirus SARS-Cov-2 antibody titers may, in the future, also support screening of health care workers to identify those who are already immune and can be deployed to care for infected patients minimizing the risk of viral spread to colleagues and other patients.", - "rel_num_authors": 30, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.15.20036673", + "rel_abs": "Stability of SARS-CoV-2 in different environmental conditions.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Fatima Amanat", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Daniel Stadlbauer", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Shirin Strohmeier", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Thi Nguyen", - "author_inst": "Department of Microbiology & Immunology, University of Melbourne, The Peter Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia" - }, - { - "author_name": "Veronika Chromikova", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Meagan McMahon", - "author_inst": "Mount Sinai" - }, - { - "author_name": "Kaijun Jiang", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Guha Asthagiri-Arunkumar", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Denise Jurczyszak", - "author_inst": "Mount Sinai" - }, - { - "author_name": "Jose Polanco", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Maria Bermudez-Gonzalez", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Giulio Kleiner", - "author_inst": "Mount Sinai" - }, - { - "author_name": "Teresa Aydillo", - "author_inst": "Mount Sinai" - }, - { - "author_name": "Lisa Miorin", - "author_inst": "Mount Sinai" - }, - { - "author_name": "Daniel Fierer", - "author_inst": "daniel.fierer@mssm.edu" - }, - { - "author_name": "Luz Amarilis Lugo", - "author_inst": "Mount Sinai" - }, - { - "author_name": "Erna Milunka Kojic", - "author_inst": "Mount Sinai" - }, - { - "author_name": "Jonathan Stoever", - "author_inst": "Mount Sinai" - }, - { - "author_name": "Sean T.H. Liu", - "author_inst": "Mount Sinai" - }, - { - "author_name": "Charlotte Cunningham-Rundles", - "author_inst": "Mount Sinai" - }, - { - "author_name": "Philip L. Felgner", - "author_inst": "UC Irvine" - }, - { - "author_name": "Daniel Caplivski", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Adolfo Garcia-Sastre", - "author_inst": "Mount Sinai" + "author_name": "Alex Chin", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Allen Cheng", - "author_inst": "Monash University" + "author_name": "Julie Chu", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Katherine Kedzierska", - "author_inst": "University of Melbourne" + "author_name": "Mahen Perera", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Olli Vapalahti", - "author_inst": "University of Helsinki" + "author_name": "Kenrie Hui", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Jussi Hepojoki", - "author_inst": "University of Helsinki / Medicum" + "author_name": "Hui-Ling Yen", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Viviana Simon", - "author_inst": "Icahn School of Medicine" + "author_name": "Michael Chan", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Florian Krammer", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Malik Peiris", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Thomas Moran", - "author_inst": "Mount Sinai" + "author_name": "Leo Poon", + "author_inst": "The University of Hong Kong" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.03.15.20036368", @@ -1572922,71 +1572288,155 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2020.03.13.20035428", - "rel_title": "Serological immunochromatographic approach in diagnosis with SARS-CoV-2 infected COVID-19 patients", + "rel_doi": "10.1101/2020.03.16.993584", + "rel_title": "Multiple approaches for massively parallel sequencing of HCoV-19 genomes directly from clinical samples", "rel_date": "2020-03-17", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.13.20035428", - "rel_abs": "An outbreak of new coronavirus SARS-CoV-2 was occurred in Wuhan, China and rapidly spread to other cities and nations. The standard diagnostic approach that widely adopted in the clinic is nuclear acid detection by real-time RT-PCR. However, the false-negative rate of the technique is unneglectable and serological methods are urgently warranted. Here, we presented the colloidal gold-based immunochromatographic (ICG) strip targeting viral IgM or IgG antibody and compared it with real-time RT-PCR. The sensitivity of ICG assay with IgM and IgG combinatorial detection in nuclear acid confirmed cases were 11.1%, 92.9% and 96.8% at the early stage (1-7 days after onset), intermediate stage (8-14 days after onset), and late stage (more than 15 days), respectively. The ICG detection capacity in nuclear acid-negative suspected cases was 43.6%. In addition, the consistencies of whole blood samples with plasma were 100% and 97.1% in IgM and IgG strips, respectively. In conclusion, serological ICG strip assay in detecting SARS-CoV-2 infection is both sensitive and consistent, which is considered as an excellent supplementary approach in clinical application.", - "rel_num_authors": 13, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.16.993584", + "rel_abs": "COVID-19 has caused a major epidemic worldwide, however, much is yet to be known about the epidemiology and evolution of the virus. One reason is that the challenges underneath sequencing HCoV-19 directly from clinical samples have not been completely tackled. Here we illustrate the application of amplicon and hybrid capture (capture)-based sequencing, as well as ultra-high-throughput metatranscriptomic (meta) sequencing in retrieving complete genomes, inter-individual and intra-individual variations of HCoV-19 from clinical samples covering a range of sample types and viral load. We also examine and compare the bias, sensitivity, accuracy, and other characteristics of these approaches in a comprehensive manner. This is, to date, the first work systematically implements amplicon and capture approaches in sequencing HCoV-19, as well as the first comparative study across methods. Our work offers practical solutions for genome sequencing and analyses of HCoV-19 and other emerging viruses.", + "rel_num_authors": 34, "rel_authors": [ { - "author_name": "Yunbao Pan", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Minfeng Xiao", + "author_inst": "BGI-Shenzhen" }, { - "author_name": "Xinran Li", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Xiaoqing Liu", + "author_inst": "State Key Laboratory of Respiratory Disease (Guangzhou Medical University), National Clinical Research Center for Respiratory Disease, First Affiliated Hospital" }, { - "author_name": "Gui Yang", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Jingkai Ji", + "author_inst": "University of Chinese Academy of Sciences" }, { - "author_name": "Junli Fan", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Min Li", + "author_inst": "University of Chinese Academy of Sciences" }, { - "author_name": "Yueting Tang", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Jiandong Li", + "author_inst": "University of Chinese Academy of Sciences" }, { - "author_name": "Jin Zhao", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Lin Yang", + "author_inst": "MGI, BGI-Shenzhen" }, { - "author_name": "Xinghua Long", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Wanying Sun", + "author_inst": "University of Chinese Academy of Sciences" }, { - "author_name": "Shuang Guo", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Peidi Ren", + "author_inst": "BGI-Shenzhen" }, { - "author_name": "Ziwu Zhao", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Guifang Yang", + "author_inst": "MGI, BGI-Shenzhen" }, { - "author_name": "Yinjuan Liu", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Jincun Zhao", + "author_inst": "State Key Laboratory of Respiratory Disease (Guangzhou Medical University), National Clinical Research Center for Respiratory Disease, First Affiliated Hospital" }, { - "author_name": "Hanning Hu", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Tianzhu Liang", + "author_inst": "BGI-Shenzhen" }, { - "author_name": "Han Xue", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Huahui Ren", + "author_inst": "BGI-Shenzhen" }, { - "author_name": "Yirong Li", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Tian Chen", + "author_inst": "MGI, BGI-Shenzhen" + }, + { + "author_name": "Huanzi Zhong", + "author_inst": "BGI-Shenzhen" + }, + { + "author_name": "Wenchen Song", + "author_inst": "BGI-Shenzhen" + }, + { + "author_name": "Yanqun Wang", + "author_inst": "State Key Laboratory of Respiratory Disease (Guangzhou Medical University), National Clinical Research Center for Respiratory Disease, First Affiliated Hospital" + }, + { + "author_name": "Ziqing Deng", + "author_inst": "BGI-Shenzhen" + }, + { + "author_name": "Yanping Zhao", + "author_inst": "BGI-Shenzhen" + }, + { + "author_name": "Zhihua Ou", + "author_inst": "BGI-Shenzhen" + }, + { + "author_name": "Daxi Wang", + "author_inst": "BGI-Shenzhen" + }, + { + "author_name": "Jielun Cai", + "author_inst": "BGI-Shenzhen" + }, + { + "author_name": "Xinyi Cheng", + "author_inst": "BGI-Shenzhen" + }, + { + "author_name": "Taiqing Feng", + "author_inst": "MGI, BGI-Shenzhen" + }, + { + "author_name": "Honglong Wu", + "author_inst": "BGI PathoGenesis Pharmaceutical Technology, Shenzhen" + }, + { + "author_name": "Yanping Gong", + "author_inst": "BGI PathoGenesis Pharmaceutical Technology, Shenzhen" + }, + { + "author_name": "Huanming Yang", + "author_inst": "BGI-Shenzhen" + }, + { + "author_name": "Jian Wang", + "author_inst": "BGI-Shenzhen" + }, + { + "author_name": "Xun Xu", + "author_inst": "BGI-Shenzhen" + }, + { + "author_name": "Shida Zhu", + "author_inst": "BGI-Shenzhen" + }, + { + "author_name": "Fang Chen", + "author_inst": "MGI, BGI-Shenzhen" + }, + { + "author_name": "Yanyan Zhang", + "author_inst": "MGI, BGI-Shenzhen" + }, + { + "author_name": "Weijun Chen", + "author_inst": "BGI PathoGenesis Pharmaceutical Technology, Shenzhen" + }, + { + "author_name": "Yimin Li", + "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease" + }, + { + "author_name": "Junhua Li", + "author_inst": "BGI-Shenzhen" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "genomics" }, { "rel_doi": "10.1101/2020.03.15.20035204", @@ -1574372,41 +1573822,73 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.12.20034736", - "rel_title": "Immunopathological characteristics of coronavirus disease 2019 cases in Guangzhou, China", + "rel_doi": "10.1101/2020.03.11.20034546", + "rel_title": "Environmental contamination of the SARS-CoV-2 in healthcare premises: An urgent call for protection for healthcare workers", "rel_date": "2020-03-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.12.20034736", - "rel_abs": "Coronavirus disease 2019 (COVID-19) is a respiratory disorder caused by the highly contagious SARS-CoV-2. The immunopathological characteristics of COVID-19 patients, either systemic or local, have not been thoroughly studied. In the present study, we analyzed both the changes in the cellularity of various immune cell types as well as cytokines important for immune reactions and inflammation. Our data indicate that patients with severe COVID-19 exhibited an overall decline of lymphocytes including CD4+ and CD8+ T cells, B cells, and NK cells. The number of immunosuppressive regulatory T cells was moderately increased in patients with mild COVID-19. IL-2, IL-6, and IL-10 were remarkably up-regulated in patients with severe COVID-19. The levels of IL-2 and IL-6 relative to the length of hospital stay underwent a similar \"rise-decline\"pattern, probably reflecting the therapeutic effect. In conclusion, our study shows that the comprehensive decrease of lymphocytes, and the elevation of IL-2 and IL-6 are reliable indicators of severe COVID-19.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.11.20034546", + "rel_abs": "ImportanceA large number of healthcare workers (HCWs) were infected by SARS-CoV-2 during the ongoing outbreak of COVID-19 in Wuhan, China. Hospitals are significant epicenters for the human-to-human transmission of the SARS-CoV-2 for HCWs, patients, and visitors. No data has been reported on the details of hospital environmental contamination status in the epicenter of Wuhan.\n\nObjectiveTo investigate the extent to which SARS-CoV-2 contaminates healthcare settings, including to identify function zones of the hospital with the highest contamination levels and to identify the most contaminated objects, and personal protection equipment (PPE) in Wuhan, China.\n\nDesignA field investigation was conducted to collect the surface swabs in various environments in the hospital and a laboratory experiment was conducted to examine the presence of the SARS-CoV-2 RNA.\n\nSettingSix hundred twenty-six surface samples were collected within the Zhongnan Medical Center in Wuhan, China in the mist of the COVID-19 outbreak between February 7 - February 27, 2020.\n\nParticipantsDacron swabs were aseptically collected from the surfaces of 13 hospital function zones, five major objects, and three major personal protection equipment (PPE). The SARS-CoV-2 RNAs were detected by reverse transcription-PCR (RT-PCR).\n\nMain Outcomes and MeasuresSARS-CoV-2 RNAs\n\nResultsThe most contaminated zones were the intensive care unit specialized for taking care of novel coronavirus pneumonia (NCP) (31.9%), Obstetric Isolation Ward specialized for pregnant women with NCP (28.1%), and Isolation Ward for NCP (19.6%). We classified the 13 zones into four contamination levels. The most contaminated objects are self-service printers (20.0%), desktop/keyboard (16.8%), and doorknob (16.0%). Both hand sanitizer dispensers (20.3%) and gloves (15.4%) were most contaminated PPE.\n\nConclusions and RelevanceMany surfaces were contaminated with SARS-CoV-2 across the hospital in various patient care areas, commonly used objects, medical equipment, and PPE. The 13 hospital function zones were classified into four contamination levels. These findings emphasize the urgent need to ensure adequate environmental cleaning, strengthen infection prevention training, and improve infection prevention precautions among HCWs during the outbreak of COVID-19. The findings may have important implications for modifying and developing urgently needed policy to better protect healthcare workers during this ongoing pandemic of SARS-CoV-2.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat was the hospital setting contamination status, the most contaminated objects and PPE of SARS-CoV-2 during the outbreak of COVID-19 in Wuhan, China?\n\nFindingsThe most contaminated zones were the intensive care unit for novel coronavirus pneumonia (NCP) (31.9%), Obstetric Isolation Ward specialized for pregnant women with NCP (28.1%), and Isolation Ward for NCP (19.6%). The most contaminated objects and PPE are self-service printers (20.0%), hand sanitizer dispensers (20.3%), and gloves (15.4%).\n\nMeaningThe findings may have important implications for modifying and developing urgently needed policy to better protect healthcare workers during this ongoing pandemic of SARS-CoV-2.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Yaling Shi", - "author_inst": "Clinical Laboratory of Guangzhou Eighth People's Hospital" + "author_name": "Guangming Ye", + "author_inst": "Zhongnan Hospital of Wuhan University" }, { - "author_name": "Mingkai Tan", - "author_inst": "Clinical Laboratory of Guangzhou Eighth People's Hospital" + "author_name": "Hualiang Lin", + "author_inst": "Sun Yat-sen University" }, { - "author_name": "Xing Chen", - "author_inst": "Clinical Laboratory of Guangzhou Eighth People's Hospital" + "author_name": "Liangjun Chen", + "author_inst": "Zhongnan Hospital of Wuhan University" }, { - "author_name": "Yanxia Liu", - "author_inst": "Clinical Laboratory of Guangzhou Eighth People's Hospital" + "author_name": "Shichan Wang", + "author_inst": "Zhongnan Hospital of Wuhan University" }, { - "author_name": "Jide Huang", - "author_inst": "Clinical Laboratory of Guangzhou Eighth People's Hospital" + "author_name": "Zhikun Zeng", + "author_inst": "Zhongnan Hospital of Wuhan University" }, { - "author_name": "Jingyi Ou", - "author_inst": "Clinical Laboratory of Guangzhou Eighth People's Hospital" + "author_name": "Wei Wang", + "author_inst": "Zhongnan Hospital of Wuhan University" }, { - "author_name": "Xilong Deng", - "author_inst": "ICU of Guangzhou Eighth People's Hospital" + "author_name": "Shiyu Zhang", + "author_inst": "Sun Yat-sen University" + }, + { + "author_name": "Terri Rebmann", + "author_inst": "Saint Louis University" + }, + { + "author_name": "Yirong Li", + "author_inst": "Zhongnan Hospital of Wuhan University" + }, + { + "author_name": "Zhenyu Pan", + "author_inst": "Zhongnan Hospital of Wuhan University" + }, + { + "author_name": "Zhonghua Yang", + "author_inst": "Zhongnan Hospital of Wuhan University" + }, + { + "author_name": "Ying Wang", + "author_inst": "Zhongnan Hospital of wuhan university" + }, + { + "author_name": "Fubing Wang", + "author_inst": "Zhongnan Hospital of Wuhan University" + }, + { + "author_name": "Zhengmin Qian", + "author_inst": "Saint Louis University" + }, + { + "author_name": "Xinghuan Wang", + "author_inst": "Zhongnan Hospital of Wuhan University, Leishengshan Hospital" } ], "version": "1", @@ -1576207,39 +1575689,79 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.03.10.20033670", - "rel_title": "The Prediction for Development of COVID-19 in Global Major Epidemic Areas Through Empirical Trends in China by Utilizing State Transition Matrix Model", + "rel_doi": "10.1101/2020.03.09.20033118", + "rel_title": "Epidemiological, Clinical Characteristics and Outcome of Medical Staff Infected with COVID-19 in Wuhan, China: A Retrospective Case Series Analysis", "rel_date": "2020-03-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.10.20033670", - "rel_abs": "BackgroundSince pneumonia caused by coronavirus disease 2019 (COVID-19) broke out in Wuhan, Hubei province, China, tremendous infected cases has risen all over the world attributed to high transmissibility. We managed to mathematically forecast the inflection point (IFP) of new cases in South Korea, Italy, and Iran, utilizing the transcendental model from Hubei and non-Hubei in China.\n\nMethodsWe extracted data from reports released by the National Health Commission of the Peoples Republic of China (Dec 31, 2019 to Mar 5, 2020) and the World Health Organization (Jan 20, 2020 to Mar 5, 2020) as the training set to deduce the arrival of the IFP of new cases in Hubei and non-Hubei on subsequent days and the data from Mar 6 to Mar 9 as validation set. New close contacts, newly confirmed cases, cumulative confirmed cases, non-severe cases, severe cases, critical cases, cured cases, and death data were collected and analyzed. Using this state transition matrix model, the horizon of the IFP of time (the rate of new increment reaches zero) could be predicted in South Korean, Italy, and Iran. Also, through this model, the global trend of the epidemic will be decoded to allocate international medical resources better and instruct the strategy for quarantine.\n\nResultsthe optimistic scenario (non-Hubei model, daily increment rate of -3.87%), the relative pessimistic scenario (Hubei model, daily increment rate of -2.20%), and the relatively pessimistic scenario (adjustment, daily increment rate of -1.50%) were inferred and modeling from data in China. Matching and fitting with these scenarios, the IFP of time in South Korea would be Mar 6-Mar 12, Italy Mar 10-Mar 24, and Iran is Mar 10-Mar 24. The numbers of cumulative confirmed patients will reach approximately 20k in South Korea, 209k in Italy, and 226k in Iran under fitting scenarios, respectively. There should be room for improvement if these metrics continue to improve. In that case, the IFP will arrive earlier than our estimation. However, with the adoption of different diagnosis criteria, the variation of new cases could impose various influences in the predictive model. If that happens, the IFP of increment will be higher than predicted above.\n\nConclusionWe can affirm that the end of the burst of the epidemic is still inapproachable, and the number of confirmed cases is still escalating. With the augment of data, the world epidemic trend could be further predicted, and it is imperative to consummate the assignment of global medical resources to manipulate the development of COVID-19.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.09.20033118", + "rel_abs": "BackgroundsSince December 2019, a novel coronavirus epidemic has emerged in Wuhan city, China and then rapidly spread to other areas. As of 20 Feb 2020, a total of 2,055 medical staff confirmed with coronavirus disease 2019 (COVID-19) caused by SARS-Cov-2 in China had been reported. We sought to explore the epidemiological, clinical characteristics and prognosis of novel coronavirus-infected medical staff.\n\nMethodsIn this retrospective study, 64 confirmed cases of novel coronavirus-infected medical staff admitted to Union Hospital, Wuhan between 16 Jan, 2020 to 15 Feb, 2020 were included. Two groups concerned were extracted from the subjects based on duration of symptoms: group 1 ([≤]10 days) and group 2 (>10 days). Epidemiological and clinical data were analyzed and compared across groups. The Kaplan-Meier plot was used to inspect the change in hospital discharge rate. The Cox regression model was utilized to identify factors associated with hospital discharge.\n\nFindingsThe median age of medical staff included was 35 years old. 64% were female and 67% were nurses. None had an exposure to Huanan seafood wholesale market or wildlife. A small proportion of the cohort had contact with specimens (5%) as well as patients in fever clinics (8%) and isolation wards (5%). Fever (67%) was the most common symptom, followed by cough (47%) and fatigue (34%). The median time interval between symptoms onset and admission was 8.5 days. On admission, 80% of medical staff showed abnormal IL-6 levels and 34% had lymphocytopenia. Chest CT mainly manifested as bilateral (61%), septal/subpleural (80%) and ground-glass (52%) opacities. During the study period, no patients was transferred to intensive care unit or died, and 34 (53%) had been discharged. Higher body mass index (BMI) ([≥] 24 kg/m2) (HR 0.14; 95% CI 0.03-0.73), fever (HR 0.24; 95% CI 0.09-0.60) and higher levels of IL-6 on admission (HR 0.31; 95% CI 0.11-0.87) were unfavorable factors for discharge.\n\nInterpretationIn this study, medical staff infected with COVID-19 have relatively milder symptoms and favorable clinical course, which may be partly due to their medical expertise, younger age and less underlying diseases. Smaller BMI, absence of fever symptoms and normal IL-6 levels on admission are favorable for discharge for medical staff. Further studies should be devoted to identifying the exact patterns of SARS-CoV-2 infection among medical staff.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Zhong Zheng", - "author_inst": "Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China." + "author_name": "Jie Liu", + "author_inst": "Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Ke Wu", - "author_inst": "Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China;Department of Evidence-based medicine, Shan" + "author_name": "Liu Ouyang", + "author_inst": "Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Zhixian Yao", - "author_inst": "Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China." + "author_name": "Pi Guo", + "author_inst": "Department of Preventive Medicine, Shantou University Medical College" }, { - "author_name": "Junhua Zheng", - "author_inst": "Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China; Department of Evidence-based medicine, Sha" + "author_name": "Hai sheng Wu", + "author_inst": "Department of Preventive Medicine, Shantou University Medical College" }, { - "author_name": "Jian Chen", - "author_inst": "CreditWise Technology Company Limited, Chengdu, China; Caixin Insight Group, Beijing, China; MSCI, Shanghai, China." + "author_name": "Peng Fu", + "author_inst": "Department of Thyroid and Breast Surgery, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Yu liang Chen", + "author_inst": "Department of Preventive Medicine, Shantou University Medical College" + }, + { + "author_name": "Dan Yang", + "author_inst": "Department of Respiratory and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Xiao yu Han", + "author_inst": "Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Yu kun Cao", + "author_inst": "Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Osamah Alwalid", + "author_inst": "Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Juan Tao", + "author_inst": "Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Shu yi Peng", + "author_inst": "Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "He shui Shi", + "author_inst": "Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Fan Yang", + "author_inst": "Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Chuan sheng Zheng", + "author_inst": "Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.03.09.20033126", @@ -1577773,731 +1577295,18 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.03.09.20032896", - "rel_title": "First 12 patients with coronavirus disease 2019 (COVID-19) in the United States", + "rel_doi": "10.1101/2020.03.09.20033068", + "rel_title": "Retrospective Analysis of Clinical Features in 101 Death Cases with COVID-19", "rel_date": "2020-03-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.09.20032896", - "rel_abs": "IntroductionMore than 93,000 cases of coronavirus disease (COVID-19) have been reported worldwide. We describe the epidemiology, clinical course, and virologic characteristics of the first 12 U.S. patients with COVID-19.\n\nMethodsWe collected demographic, exposure, and clinical information from 12 patients confirmed by CDC during January 20-February 5, 2020 to have COVID-19. Respiratory, stool, serum, and urine specimens were submitted for SARS-CoV-2 rRT-PCR testing, virus culture, and whole genome sequencing.\n\nResultsAmong the 12 patients, median age was 53 years (range: 21-68); 8 were male, 10 had traveled to China, and two were contacts of patients in this series. Commonly reported signs and symptoms at illness onset were fever (n=7) and cough (n=8). Seven patients were hospitalized with radiographic evidence of pneumonia and demonstrated clinical or laboratory signs of worsening during the second week of illness. Three were treated with the investigational antiviral remdesivir. All patients had SARS-CoV-2 RNA detected in respiratory specimens, typically for 2-3 weeks after illness onset, with lowest rRT-PCR Ct values often detected in the first week. SARS-CoV-2 RNA was detected after reported symptom resolution in seven patients. SARS-CoV-2 was cultured from respiratory specimens, and SARS-CoV-2 RNA was detected in stool from 7/10 patients.\n\nConclusionsIn 12 patients with mild to moderately severe illness, SARS-CoV-2 RNA and viable virus were detected early, and prolonged RNA detection suggests the window for diagnosis is long. Hospitalized patients showed signs of worsening in the second week after illness onset.", - "rel_num_authors": 178, - "rel_authors": [ - { - "author_name": "Stephanie A. Kujawski", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Karen K Wong", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Jennifer P. Collins", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Lauren Epstein", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Marie E. Killerby", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Claire M. Midgley", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Glen R. Abedi", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "N. Seema Ahmed", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Olivia Almendares", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Francisco N. Alvarez", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Kayla N. Anderson", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Sharon Balter", - "author_inst": "Los Angeles County Department of Public Health" - }, - { - "author_name": "Vaughn Barry", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Karri Bartlett", - "author_inst": "Public Health Madison Dane County" - }, - { - "author_name": "Karlyn Beer", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Michael A. Ben-Aderet", - "author_inst": "Cedars-Sinai Health System" - }, - { - "author_name": "Isaac Benowitz", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Holly Biggs", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Alison M. Binder", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Stephanie R. Black", - "author_inst": "Chicago Department of Public Health" - }, - { - "author_name": "Brandon Bonin", - "author_inst": "Santa Clara County, Public Health Department" - }, - { - "author_name": "Catherine M. Brown", - "author_inst": "Massachusetts Department of Public Health" - }, - { - "author_name": "Hollianne Bruce", - "author_inst": "Snohomish Health District" - }, - { - "author_name": "Jonathan Bryant-Genevier", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Alicia Budd", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Diane Buell", - "author_inst": "Hoag Memorial Hospital Presbyterian" - }, - { - "author_name": "Rachel Bystritsky", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Jordan Cates", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "E. Matt Charles", - "author_inst": "Illinois Department of Public Health" - }, - { - "author_name": "Kevin Chatham-Stephens", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Nora Chea", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Howard Chiou", - "author_inst": "Los Angeles County Department of Public Health" - }, - { - "author_name": "Demian Christiansen", - "author_inst": "Cook County Department of Public Health" - }, - { - "author_name": "Victoria Chu", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Sara Cody", - "author_inst": "Santa Clara County, Public Health Department" - }, - { - "author_name": "Max Cohen", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Erin Conners", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Aaron Curns", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Vishal Dasari", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Patrick Dawson", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Traci DeSalvo", - "author_inst": "Wisconsin Department of Health Services" - }, - { - "author_name": "George Diaz", - "author_inst": "Providence Regional Medical Center Everett" - }, - { - "author_name": "Matthew Donahue", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Suzanne Donovan", - "author_inst": "Olive View-UCLA Medical Center" - }, - { - "author_name": "Lindsey M. Duca", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Keith Erickson", - "author_inst": "Providence Regional Medical Center Everett" - }, - { - "author_name": "Mathew D. Esona", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Suzanne Evans", - "author_inst": "Hoag Memorial Hospital Presbyterian" - }, - { - "author_name": "Jeremy Falk", - "author_inst": "Cedars-Sinai Health System" - }, - { - "author_name": "Leora R. Feldstein", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Martin Fenstersheib", - "author_inst": "San Benito County Public Health Services" - }, - { - "author_name": "Marc Fischer", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Rebecca Fisher", - "author_inst": "Los Angeles County Department of Public Health" - }, - { - "author_name": "Chelsea Foo", - "author_inst": "Los Angeles County Department of Public Health" - }, - { - "author_name": "Marielle J. Fricchione", - "author_inst": "Chicago Department of Public Health" - }, - { - "author_name": "Oren Friedman", - "author_inst": "Cedars-Sinai Health System" - }, - { - "author_name": "Alicia M. Fry", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Romeo R. Galang", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Melissa M. Garcia", - "author_inst": "Hoag Memorial Hospital Presbyterian" - }, - { - "author_name": "Susa I. Gerber", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Graham Gerrard", - "author_inst": "Hoag Memorial Hospital Presbyterian" - }, - { - "author_name": "Isaac Ghinai", - "author_inst": "Illinois Department of Public Health" - }, - { - "author_name": "Prabhu Gounder", - "author_inst": "Los Angeles County Department of Public Health" - }, - { - "author_name": "Jonathan Grein", - "author_inst": "Cedars-Sinai Health System" - }, - { - "author_name": "Cheri Grigg", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Jeffrey D. Gunzenhauser", - "author_inst": "Los Angeles County Department of Public Health" - }, - { - "author_name": "Gary I. Gutkin", - "author_inst": "Cedars-Sinai Health System" - }, - { - "author_name": "Meredith Haddix", - "author_inst": "Los Angeles County Department of Public Health" - }, - { - "author_name": "Aron J. Hall", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "George Han", - "author_inst": "Santa Clara County, Public Health Department" - }, - { - "author_name": "Jennifer Harcourt", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Kathleen Harriman", - "author_inst": "California Department of Public Health" - }, - { - "author_name": "Thomas Haupt", - "author_inst": "Wisconsin Department of Health Services" - }, - { - "author_name": "Amber Haynes", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Michelle Holshue", - "author_inst": "Washington State Department of Health" - }, - { - "author_name": "Cora Hoover", - "author_inst": "California Department of Public Health" - }, - { - "author_name": "Jennifer C. Hunter", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Max W. Jacobs", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Claire Jarashow", - "author_inst": "Los Angeles County Department of Public Health" - }, - { - "author_name": "Michael A. Jhung", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Kiran Joshi", - "author_inst": "Cook County Department of Public Health" - }, - { - "author_name": "Talar Kamali", - "author_inst": "Los Angeles County Department of Public Health" - }, - { - "author_name": "Shifaq Kamili", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Lindsay Kim", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Moon Kim", - "author_inst": "Los Angeles County Department of Public Health" - }, - { - "author_name": "Jan King", - "author_inst": "Los Angeles County Department of Public Health" - }, - { - "author_name": "Hannah L. Kirking", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Amanda Kita-Yarbro", - "author_inst": "Public Health Madison Dane County" - }, - { - "author_name": "Rachel Klos", - "author_inst": "Wisconsin Department of Health Services" - }, - { - "author_name": "Miwako Kobayashi", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Anna Kocharian", - "author_inst": "Wisconsin Department of Health Services" - }, - { - "author_name": "Kenneth K. Komatsu", - "author_inst": "Arizona Department of Health Services" - }, - { - "author_name": "Ram Koppaka", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Jennifer E. Layden", - "author_inst": "Chicago Department of Public Health" - }, - { - "author_name": "Yan Li", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Scott Lindquist", - "author_inst": "Washington State Department of Health" - }, - { - "author_name": "Stephen Lindstrom", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Ruth Link-Gelles", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Joana Lively", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Michelle Livingston", - "author_inst": "Hoag Memorial Hospital Presbyterian" - }, - { - "author_name": "Kelly Lo", - "author_inst": "Cedars-Sinai Health System" - }, - { - "author_name": "Jennifer Lo", - "author_inst": "Massachusetts Department of Public Health" - }, - { - "author_name": "Xiaoyan Lu", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Brian Lynch", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Larry Madoff", - "author_inst": "Massachusetts Department of Public Health" - }, - { - "author_name": "Lakshmi Malapati", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Gregory Marks", - "author_inst": "Cedars-Sinai Health System" - }, - { - "author_name": "Mariel Marlow", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Glenn E. Mathisen", - "author_inst": "Olive View-UCLA Medical Center" - }, - { - "author_name": "Nancy McClung", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Olivia McGovern", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Tristan D. McPherson", - "author_inst": "Chicago Department of Public Health" - }, - { - "author_name": "Mitali Mehta", - "author_inst": "Cedars-Sinai Health System" - }, - { - "author_name": "Audrey Meier", - "author_inst": "Providence Regional Medical Center Everett" - }, - { - "author_name": "Lynn Mello", - "author_inst": "San Benito County Public Health Services" - }, - { - "author_name": "Sung-sil Moon", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Margie Morgan", - "author_inst": "Cedars-Sinai Health System" - }, - { - "author_name": "Ruth N. Moro", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Janna' Murray", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Rekha Murthy", - "author_inst": "Cedars-Sinai Health System" - }, - { - "author_name": "Shannon Novosad", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Sara E. Oliver", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Jennifer O'Shea", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Massimo Pacilli", - "author_inst": "Chicago Department of Public Health" - }, - { - "author_name": "Clinton R. Paden", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Mark A. Pallansch", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Manisha Patel", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Sajan Patel", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Isabel Pedraza", - "author_inst": "Cedars-Sinai Health System" - }, - { - "author_name": "Satish K. Pillai", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Talia Pindyck", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Ian Pray", - "author_inst": "Wisconsin Department of Health Services" - }, - { - "author_name": "Krista Queen", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Nichole Quick", - "author_inst": "Los Angeles County Department of Public Health" - }, - { - "author_name": "Heather Reese", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Brian Rha", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Heather Rhodes", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Susan Robinson", - "author_inst": "Arizona Department of Health Services" - }, - { - "author_name": "Philip Robinson", - "author_inst": "Hoag Memorial Hospital Presbyterian" - }, - { - "author_name": "Melissa Rolfes", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Janell Routh", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Rachel Rubin", - "author_inst": "Cook County Department of Public Health" - }, - { - "author_name": "Sarah L. Rudman", - "author_inst": "Santa Clara County, Public Health Department" - }, - { - "author_name": "Senthilkumar K. Sakthivel", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Sarah Scott", - "author_inst": "Maricopa County Department of Public Health" - }, - { - "author_name": "Christopher Shepherd", - "author_inst": "Cedars-Sinai Health System" - }, - { - "author_name": "Varun Shetty", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Ethan A. Smith", - "author_inst": "Cedars-Sinai Health System" - }, - { - "author_name": "Shanon Smith", - "author_inst": "Santa Clara County, Public Health Department" - }, - { - "author_name": "Bryan Stierman", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "William Stoecker", - "author_inst": "Metro Infectious Disease Consultants" - }, - { - "author_name": "Rebecca Sunenshine", - "author_inst": "Maricopa County Department of Public Health" - }, - { - "author_name": "Regina Sy-Santos", - "author_inst": "Hoag Memorial Hospital Presbyterian" - }, - { - "author_name": "Azaibi Tamin", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Ying Tao", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Dawn Terashita", - "author_inst": "Los Angeles County Department of Public Health" - }, - { - "author_name": "Natalie J. Thornburg", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Suxiang Tong", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Elizabeth Traub", - "author_inst": "Los Angeles County Department of Public Health" - }, - { - "author_name": "Ahmet Tural", - "author_inst": "Providence Regional Medical Center Everett" - }, - { - "author_name": "Anna Uehara", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Timothy M. Uyeki", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Grace Vahey", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Jennifer R. Verani", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Elsa Villarino", - "author_inst": "Santa Clara County , Public Health Department" - }, - { - "author_name": "Megan Wallace", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Lijuan Wang", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "John T. Watson", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Matthew Westercamp", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Brett Whitaker", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Sarah Wilkerson", - "author_inst": "Providence Regional Medical Center Everett" - }, - { - "author_name": "Rebecca C. Woodruff", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Jonathan M. Wortham", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Tiffany Wu", - "author_inst": "Cedars-Sinai Health System" - }, - { - "author_name": "Amy Xie", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Anna Yousaf", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Matthew Zahn", - "author_inst": "Orange County Health Care Agency" - }, - { - "author_name": "Jing Zhang", - "author_inst": "Centers for Disease Control and Prevention" - } - ], + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.09.20033068", + "rel_abs": "BackgroundThe illness progress of partial patient of COVID-19 is rapid and the mortality rate is high.we aim to describe the clinical features in death cases with COVID-19.\n\nMethodsIn this single center, observational study, We recruited all Death Cases with COVID-19 from Dec 30, 2019 to Feb 16, 2020 in Intensive care unit of Wuhan Jinyintan Hospital.Demographics, basic diseases, X-ray/CT results, possible therapy strategies and test results when their entrance into admission, ICU and 48 h before death were collected and analyzed.\n\nResultsThis study involved 101 COVID-19 dead cases in Intensive care unit of Wuhan Jinyintan Hospital.47 patients went directly to the ICU because of critical condition, and 54 patients were transferred to ICU with aggravated condition.57 (56.44%) were laboratory confirmed by RT-PCR, and 44 (43.6%) were consistent with clinical diagnostic criteria.The cases included 64 males and 37 females with average age of 65.46 years (SD 9.74). The blood type distribution was significantly different, with type A 44.44%, type B 29.29%, type AB 8.08% and type O 18.19%.The clinical manifestations of new coronavirus pneumonia are non-specific,the common symptom was fever (91 [90.10%] of 101 patients),Cough (69[68.32%]) and dyspnea (75[74.26%]). Neutrophils, PCT, CRP,IL-6,D-dimer gradually increased as time went on.Myocardial enzymes were abnormal in most patients at admission,with the progress of the disease, myocardial damage indicators were significantly increased.61(60.40%) used antiviral drugs,59(58.42%) used glucocorticoids, 63.37% used intravenous immunoglobulins, and 44.55% used thymosin preparations. All patients received antibiotic treatment, 63(62.38%) used restricted antibiotics, 23(22.78%) used antifungal drugs.84(83.17%) used non-invasive ventilator or high-flow oxygen therapy equipment, and 76.24% used invasive mechanical ventilation. 7 patients were treated with ECMO and 8 patients were treated with CRRT.The median time from ARDS to invasive mechanical ventilation was 3.00 days(IQR 0.00-6.00). The duration of invasive mechanical ventilation was 5 days (IQR2.00-8.00).\n\nConclusionsCritical COVID-19 can cause fatal respiratory distress syndrome and multiple organ failure with high mortality rate. Heart may be the earliest damaged organ except the lungs. Secondary infection in the later period is worthy of attention.", + "rel_num_authors": 0, + "rel_authors": null, "version": "1", - "license": "cc0", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.03.08.980383", @@ -1579855,37 +1578664,137 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2020.03.06.20032144", - "rel_title": "CORONAVIRUS IN PREGNANCY AND DELIVERY: RAPID REVIEW AND EXPERT CONSENSUS", + "rel_doi": "10.1101/2020.03.05.20032011", + "rel_title": "Amplicon based MinION sequencing of SARS-CoV-2 and metagenomic characterisation of nasopharyngeal swabs from patients with COVID-19", "rel_date": "2020-03-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.06.20032144", - "rel_abs": "BACKGROUNDPerson to person spread of COIVD-19 in the UK has now been confirmed. There are limited case series reporting the impact on women affected by coronaviruses (CoV) during pregnancy. In women affected by SARS and MERS, the case fatality rate appeared higher in women affected in pregnancy compared with non-pregnant women. We conducted a rapid, review to guide management of women affected by COVID -19 during pregnancy and developed interim practice guidance with the RCOG and RCPCH to inform maternity and neonatal service planning\n\nMETHODSSearches were conducted in PubMed and MedRxiv to identify primary case reports, case series, observational studies or randomised-controlled trial describing women affected by coronavirus in pregnancy and on neonates. Data was extracted from relevant papers and the review was drafted with representatives of the RCPCH and RCOG who also provided expert consensus on areas where data were lacking\n\nRESULTSFrom 9964 results on PubMed and 600 on MedRxiv, 18 relevant studies (case reports and case series) were identified. There was inconsistent reporting of maternal, perinatal and neonatal outcomes across case reports and series concerning COVID-19, SARS, MERS and other coronaviruses. From reports of 19 women to date affected by COVID-19 in pregnancy, delivering 20 babies, 3 (16%) were asymptomatic, 1 (5%) was admitted to ICU and no maternal deaths have been reported. Deliveries were 17 by caesarean section, 2 by vaginal delivery, 8 (42%) delivered pre-term. There was one neonatal death, in 15 babies who were tested there was no evidence of vertical transmission.\n\nCONCLUSIONSMorbidity and mortality from COVID-19 appears less marked than for SARS and MERS, acknowledging the limited number of cases reported to date. Pre-term delivery affected 42% of women hospitalised with COVID-19, which may put considerable pressure on neonatal services if the UK reasonable worse-case scenario of 80% of the population affected is realised. There has been no evidence of vertical transmission to date. The RCOG and RCPCH have provided interim guidance to help maternity and neonatal services plan their response to COVID-19.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.05.20032011", + "rel_abs": "COVID-19 is a complex disease phenotype where the underlying microbiome could influence morbidity and mortality. Amplicon and metagenomic MinION based sequencing was used to rapidly (within 8 hours) identify SARS-CoV-2 and assess the microbiome in nasopharyngeal swabs obtained from patients with COVID-19 by the ISARIC 4C consortium.", + "rel_num_authors": 30, "rel_authors": [ { - "author_name": "Edward Mullins", - "author_inst": "Imperial College" + "author_name": "Shona C Moore", + "author_inst": "University of Liverpool" }, { - "author_name": "David Evans", - "author_inst": "RCPCH" + "author_name": "Rebekah Penrice-Randal", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Muhannad Alruwaili", + "author_inst": "University of Liverpool" }, { - "author_name": "Russell Viner", - "author_inst": "RCPCH" + "author_name": "Xiaofeng Dong", + "author_inst": "University of Liverpool" }, { - "author_name": "Patrick O'Brien", - "author_inst": "RCOG" + "author_name": "Steven T Pullan", + "author_inst": "Public Health England" }, { - "author_name": "Eddie Morris", - "author_inst": "RCOG" + "author_name": "Daniel Carter", + "author_inst": "Public Health England" + }, + { + "author_name": "Kevin Bewley", + "author_inst": "Public Health England" + }, + { + "author_name": "Qin Zhao", + "author_inst": "Northwest A&F University" + }, + { + "author_name": "Yani Sun", + "author_inst": "Northwest A&F University" + }, + { + "author_name": "Catherine Hartley", + "author_inst": "University of Liverpool" + }, + { + "author_name": "En-min Zhou", + "author_inst": "Northwest A&F University" + }, + { + "author_name": "Tom Solomon", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Michael B. J. Beadsworth", + "author_inst": "Liverpool University Hospitals NHS Foundation Trust" + }, + { + "author_name": "James Cruise", + "author_inst": "Liverpool University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Debby Bogaert", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Derrick W T Crook", + "author_inst": "NIHR Oxford Biomedical Research Centre" + }, + { + "author_name": "David A Matthews", + "author_inst": "University of Bristol" + }, + { + "author_name": "Andrew D. Davidson", + "author_inst": "University of Bristol" + }, + { + "author_name": "Zana Mahmood", + "author_inst": "Directorate of Veterinary in Sulaimany" + }, + { + "author_name": "Waleed Aljabr", + "author_inst": "King Fahad Medical City" + }, + { + "author_name": "Julian Druce", + "author_inst": "The Peter Doherty Institute for Infection and Immunity" + }, + { + "author_name": "Richard T Vipond", + "author_inst": "Public Health England" + }, + { + "author_name": "Lisa Ng", + "author_inst": "A*STAR" + }, + { + "author_name": "Laurent Renia", + "author_inst": "A*STAR" + }, + { + "author_name": "Peter Openshaw", + "author_inst": "Imperial College London" + }, + { + "author_name": "J Kenneth Baillie", + "author_inst": "Roslin Institute, University of Edinburgh" + }, + { + "author_name": "Miles W Carroll", + "author_inst": "Public Health England" + }, + { + "author_name": "Calum Semple", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Lance Turtle", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Julian Alexander Hiscox", + "author_inst": "University of Liverpool" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1581420,67 +1580329,47 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.03.04.976662", - "rel_title": "Genome-wide data inferring the evolution and population demography of the novel pneumonia coronavirus (SARS-CoV-2)", - "rel_date": "2020-03-07", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.04.976662", - "rel_abs": "As the highly risk and infectious diseases, the outbreak of coronavirus disease 2019 (COVID-19) poses unprecedent challenges to global health. Up to March 3, 2020, SARS-CoV-2 has infected more than 89,000 people in China and other 66 countries across six continents. In this study, we used 10 new sequenced genomes of SARS-CoV-2 and combined 136 genomes from GISAID database to investigate the genetic variation and population demography through different analysis approaches (e.g. Network, EBSP, Mismatch, and neutrality tests). The results showed that 80 haplotypes had 183 substitution sites, including 27 parsimony-informative and 156 singletons. Sliding window analyses of genetic diversity suggested a certain mutations abundance in the genomes of SARS-CoV-2, which may be explaining the existing widespread. Phylogenetic analysis showed that, compared with the coronavirus carried by pangolins (Pangolin-CoV), the virus carried by bats (bat-RaTG13-CoV) has a closer relationship with SARS-CoV-2. The network results showed that SARS-CoV-2 had diverse haplotypes around the world by February 11. Additionally, 16 genomes, collected from Huanan seafood market assigned to 10 haplotypes, indicated a circulating infection within the market in a short term. The EBSP results showed that the first estimated expansion date of SARS-CoV-2 began from 7 December 2019.", - "rel_num_authors": 12, + "rel_doi": "10.1101/2020.03.02.20030320", + "rel_title": "Preliminary estimation of the novel coronavirus disease (COVID-19) cases in Iran: a modelling analysis based on overseas cases and air travel data", + "rel_date": "2020-03-06", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.02.20030320", + "rel_abs": "As of 1 March 2020, Iran has reported 987 COVID-19 cases and including 54 associated deaths. At least six neighboring countries (Bahrain, Iraq, Kuwait, Oman, Afghanistan and Pakistan) have reported imported COVID-19 cases from Iran. We used air travel data and the cases from Iran to other Middle East countries and estimated 16533 (95% CI: 5925, 35538) COVID-19 cases in Iran by 25 February, before UAE and other Gulf Cooperation Council countries suspended inbound and outbound flights from Iran.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Bing Fang", - "author_inst": "Influenza Reference Laboratory, Institute of Health Inspection and Testing, Hubei Provincial Center for Disease Control and Prevention" - }, - { - "author_name": "Linlin Liu", - "author_inst": "Influenza Reference Laboratory, Institute of Health Inspection and Testing, Hubei Provincial Center for Disease Control and Prevention" - }, - { - "author_name": "Xiao Yu", - "author_inst": "Influenza Reference Laboratory, Institute of Health Inspection and Testing, Hubei Provincial Center for Disease Control and Prevention" - }, - { - "author_name": "Xiang Li", - "author_inst": "Influenza Reference Laboratory, Institute of Health Inspection and Testing, Hubei Provincial Center for Disease Control and Prevention" - }, - { - "author_name": "Guojun Ye", - "author_inst": "Influenza Reference Laboratory, Institute of Health Inspection and Testing, Hubei Provincial Center for Disease Control and Prevention" - }, - { - "author_name": "Juan Xu", - "author_inst": "Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Wuhan University of Science and Technology" + "author_name": "Zian Zhuang", + "author_inst": "Hong Kong Polytechnic University" }, { - "author_name": "Ling Zhang", - "author_inst": "Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Wuhan University of Science and Technology" + "author_name": "Shi Zhao", + "author_inst": "Chinese University of Hong Kong" }, { - "author_name": "Faxian Zhan", - "author_inst": "Influenza Reference Laboratory, Institute of Health Inspection and Testing, Hubei Provincial Center for Disease Control and Prevention" + "author_name": "Qianying Lin", + "author_inst": "University of Michigan" }, { - "author_name": "Guiming Liu", - "author_inst": "Beijing Agro-Biotechnology Research Center, Beijing Academy of Agriculture and Forestry Sciences" + "author_name": "Peihua Cao", + "author_inst": "Southern Medical University" }, { - "author_name": "Tao Pan", - "author_inst": "Anhui Province Key Laboratory for Conservation and Exploitation of Biological Resource, College of Life Sciences, Anhui Normal University" + "author_name": "Yijun Lou", + "author_inst": "Hong Kong Polytechnic University" }, { - "author_name": "Yilin Shu", - "author_inst": "Anhui Province Key Laboratory for Conservation and Exploitation of Biological Resource, College of Life Sciences, Anhui Normal University" + "author_name": "Lin Yang", + "author_inst": "The Hong Kong Polytechnic University" }, { - "author_name": "Yongzhong Jiang", - "author_inst": "Influenza Reference Laboratory, Institute of Health Inspection and Testing, Hubei Provincial Center for Disease Control and Prevention" + "author_name": "Daihai He", + "author_inst": "Hong Kong Polytechnic University" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "evolutionary biology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.03.02.20030148", @@ -1583070,49 +1581959,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.03.02.20029868", - "rel_title": "Close contacts and household transmission of SARS-CoV-2 in China: a content analysis based on local Heath Commissions' public disclosures.", + "rel_doi": "10.1101/2020.03.04.20031187", + "rel_title": "The impact of social distancing and epicenter lockdown on the COVID-19 epidemic in mainland China: A data-driven SEIQR model study", "rel_date": "2020-03-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.02.20029868", - "rel_abs": "ImportanceSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in the city of Wuhan, China, in December 2019 and then spread globally. Limited information is available for characterizing epidemiological features and transmission patterns in the regions outside of Hubei Province. Detailed data on transmission at the individual level could be an asset to understand the transmission mechanisms and respective patterns in different settings.\n\nObjectiveTo reconstruct infection events and transmission clusters of SARS-CoV-2 for estimating epidemiological characteristics at household and non-household settings, including super-spreading events, serial intervals, age- and gender-stratified risks of infection in China outside of Hubei Province.\n\nDesign, Setting, and Participants9,120 confirmed cases reported online by 264 Chinese urban Health Commissions in 27 provinces from January 20 to February 19, 2020. A line-list database is established with detailed information on demographic, social and epidemiological characteristics. The infection events are categorized into the household and non-household settings.\n\nExposuresConfirmed cases of SARS-CoV-2 infections.\n\nMain Outcomes and MeasuresInformation about demographic characteristics, social relationships, travel history, timelines of potential exposure, symptom onset, confirmation, and hospitalization were extracted from online public reports. 1,407 infection events formed 643 transmission clusters were reconstructed.\n\nResultsIn total 34 primary cases were identified as super spreaders, and 5 household super-spreading events were observed. The mean serial interval is estimated to be 4.95 days (standard deviation: 5.24 days) and 5.19 days (standard deviation: 5.28 days) for households and non-household transmissions, respectively. The risk of being infected outside of households is higher for age groups between 18 and 64 years, whereas the hazard of being infected within households is higher for age groups of young (<18) and elderly (>65) people.\n\nConclusions and RelevanceThe identification of super-spreading events, short serial intervals, and a higher risk of being infected outside of households for male people of age between 18 and 64 indicate a significant barrier to the case identification and management, which calls for intensive non-pharmaceutical interventions (e.g. cancellation of public gathering, limited access of public services) as the potential mitigation strategies.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat epidemiological characteristics and risk factors are associated with household and non-household transmissions of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China outside of Hubei Province?\n\nFindingsIn this epidemiological study analyzing 1,407 SARS-CoV-2 infection events reported between 20 January 2020 and 19 February 2020, 643 transmission clusters were reconstructed to demonstrate the non-negligible frequency of super-spreading events, short duration of serial intervals, and a higher risk of being infected outside of household for male people of age between 18 and 64 years.\n\nMeaningThese findings provide epidemiological features and risk estimates for both household and non-household transmissions of SARS-CoV-2 in China outside of Hubei Province.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.04.20031187", + "rel_abs": "The outbreak of coronavirus disease 2019 (COVID-19) which originated in Wuhan, China, constitutes a public health emergency of international concern with a very high risk of spread and impact at the global level. We developed data-driven susceptible-exposed-infectious-quarantine-recovered (SEIQR) models to simulate the epidemic with the interventions of social distancing and epicenter lockdown. Population migration data combined with officially reported data were used to estimate model parameters, and then calculated the daily exported infected individuals by estimating the daily infected ratio and daily susceptible population size. As of Jan 01, 2020, the estimated initial number of latently infected individuals was 380.1 (95%-CI: 379.8[~]381.0). With 30 days of substantial social distancing, the reproductive number in Wuhan and Hubei was reduced from 2.2 (95%-CI: 1.4[~]3.9) to 1.58 (95%-CI: 1.34[~]2.07), and in other provinces from 2.56 (95%-CI: 2.43[~]2.63) to 1.65 (95%-CI: 1.56[~]1.76). We found that earlier intervention of social distancing could significantly limit the epidemic in mainland China. The number of infections could be reduced up to 98.9%, and the number of deaths could be reduced by up to 99.3% as of Feb 23, 2020. However, earlier epicenter lockdown would partially neutralize this favorable effect. Because it would cause in situ deteriorating, which overwhelms the improvement out of the epicenter. To minimize the epidemic size and death, stepwise implementation of social distancing in the epicenter city first, then in the province, and later the whole nation without the epicenter lockdown would be practical and cost-effective.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "xiaoke Xu", - "author_inst": "Dalian Minzu university" - }, - { - "author_name": "Xiaofan Liu", - "author_inst": "City University of Hong Kong" - }, - { - "author_name": "Lin Wang", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Sheikh Taslim ALI", - "author_inst": "The University of Hong Kong" - }, - { - "author_name": "Zhanwei Du", - "author_inst": "University of Texas at Austin" + "author_name": "Yuzhen Zhang", + "author_inst": "The First Affiliated Hospital of Soochow University" }, { - "author_name": "Paolo Bosetti", - "author_inst": "Institut Pasteur" + "author_name": "Bin Jiang", + "author_inst": "The First Affiliated Hospital of Soochow University" }, { - "author_name": "Benjamin J Cowling", - "author_inst": "The University of Hong Kong" + "author_name": "Jiamin Yuan", + "author_inst": "The First Affiliated Hospital of Soochow University" }, { - "author_name": "Ye Wu", - "author_inst": "Beijing Normal University" + "author_name": "Yanyun Tao", + "author_inst": "Soochow University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1584759,47 +1583632,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.02.968388", - "rel_title": "Crystal structure of Nsp15 endoribonuclease NendoU from SARS-CoV-2", + "rel_doi": "10.1101/2020.02.28.20028514", + "rel_title": "The level of plasma C-reactive protein is closely related to the liver injury in patients with COVID-19", "rel_date": "2020-03-03", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.02.968388", - "rel_abs": "Severe Acute Respiratory Syndrome Coronavirus 2 is rapidly spreading around the world. There is no existing vaccine or proven drug to prevent infections and stop virus proliferation. Although this virus is similar to human and animal SARS- and MERS-CoVs the detailed information about SARS-CoV-2 proteins structures and functions is urgently needed to rapidly develop effective vaccines, antibodies and antivirals. We applied high-throughput protein production and structure determination pipeline at the Center for Structural Genomics of Infectious Diseases to produce SARS-CoV-2 proteins and structures. Here we report the high-resolution crystal structure of endoribonuclease Nsp15/NendoU from SARS-CoV-2 - a virus causing current world-wide epidemics. We compare this structure with previously reported models of Nsp15 from SARS and MERS coronaviruses.", - "rel_num_authors": 7, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.28.20028514", + "rel_abs": "AimsCorona virus disease 2019 (COVID-19) has rapidly become the most severe public health issue all over the world. Despite respiratory symptoms, hepatic injury has also been observed in clinical settings. This study aimed to investigate the risk factors involved with hepatic injury in the patients with COVID-19.\n\nMethodsA total of 85 hospitalized patients who were diagnosed with COVID-19 in Beijing Youan Hospital were retrospectively analyzed. According to liver function, they were divided into ALT normal group (n=52) and ALT elevation group (n=33). Clinical features and laboratory data were compared between the two groups. The independent risk factors for liver injury were analyzed.\n\nResultsThere were 33 patients with hepatic injury in our study, accounting for 38.8% (33/85). The patients in ALT elevation group were older than those in ALT normal group. The levels of lactic acid, CRP, myoglobin, and neutrophils were significantly higher in ALT elevation group. The lymphocytes and albumin were significantly lower in ALT elevation group. The proportion of severe and critical patients in ALT elevation group was significantly higher. Multivariate logistic regression analysis showed CRP [≥]20 mg/L and lymphocyte count< 1.1x10^9/L were independently related to hepatic injury.\n\nConclusionsLymphopenia and CRP may serve as the risk factors related to hepatic injury in patients with COVID-19, which might be related to inflammatory cytokine storm in liver injury. Early detection and timely treatment of hepatic injury in patients with COVID-19 are necessary.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Youngchang Kim", - "author_inst": "University of Chicago/Argonne National Laboratory" + "author_name": "Lu Li", + "author_inst": "Difficult & Complicated Liver Diseases and Artificial Liver Center, Beijing Youan Hospital, Capital Medical University" }, { - "author_name": "Robert Jedrzejczak", - "author_inst": "University of Chicago/Argonne National Laboratory" + "author_name": "Shuang Li", + "author_inst": "Difficult & Complicated Liver Diseases and Artificial Liver Center, Beijing Youan Hospital, Capital Medical University" }, { - "author_name": "Natalia I. Maltseva", - "author_inst": "University of Chicago/Argonne National Laboratory" + "author_name": "Manman Xu", + "author_inst": "Difficult & Complicated Liver Diseases and Artificial Liver Center, Beijing Youan Hospital, Capital Medical University" }, { - "author_name": "Michael Endres", - "author_inst": "Argonne National Laboratory" + "author_name": "Pengfei Yu", + "author_inst": "Beijing Municipal Key Laboratory of Liver Failure and Artificial Liver Treatment Research, Beijing, China, 100069" }, { - "author_name": "Adam Godzik", - "author_inst": "University of California Riverside" + "author_name": "Sujun Zheng", + "author_inst": "Difficult & Complicated Liver Diseases and Artificial Liver Center, Beijing Youan Hospital, Capital Medical University" }, { - "author_name": "Karolina Michalska", - "author_inst": "University of Chicago/Argonne National Laboratory" + "author_name": "Zhongping Duan", + "author_inst": "Difficult & Complicated Liver Diseases and Artificial Liver Center, Beijing Youan Hospital, Capital Medical University" }, { - "author_name": "Andrzej Joachimiak", - "author_inst": "University of Chicago/Argonne National Laboratory" + "author_name": "Jing Liu", + "author_inst": "Hemodialysis Room, Urinary Center, Beijing Youan Hospital, Capital Medical University, Beijing, China,100069" + }, + { + "author_name": "Yu Chen", + "author_inst": "Difficult & Complicated Liver Diseases and Artificial Liver Center, Beijing Youan Hospital, Capital Medical University" + }, + { + "author_name": "Junfeng Li", + "author_inst": "Institute of Infectious Diseases, Department of Infectious Diseases, The First Hospital of Lanzhou University" } ], "version": "1", - "license": "cc_by_nd", - "type": "new results", - "category": "molecular biology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.03.02.973255", @@ -1586601,67 +1585482,75 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.02.29.971093", - "rel_title": "The 2019 coronavirus (SARS-CoV-2) surface protein (Spike) S1 Receptor Binding Domain undergoes conformational change upon heparin binding.", + "rel_doi": "10.1101/2020.03.02.20030130", + "rel_title": "Rapid Detection of SARS-CoV-2 Using Reverse transcription RT-LAMP method", "rel_date": "2020-03-02", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.29.971093", - "rel_abs": "Many pathogens take advantage of the dependence of the host on the interaction of hundreds of extracellular proteins with the glycosaminoglycans heparan sulphate to regulate homeostasis and use heparan sulphate as a means to adhere and gain access to cells. Moreover, mucosal epithelia such as that of the respiratory tract are protected by a layer of mucin polysaccharides, which are usually sulphated. Consequently, the polydisperse, natural products of heparan sulphate and the allied polysaccharide, heparin have been found to be involved and prevent infection by a range of viruses including S-associated coronavirus strain HSR1. Here we use surface plasmon resonance and circular dichroism to measure the interaction between the SARS-CoV-2 Spike S1 protein receptor binding domain (SARS-CoV-2 S1 RBD) and heparin. The data demonstrate an interaction between the recombinant surface receptor binding domain and the polysaccharide. This has implications for the rapid development of a first-line therapeutic by repurposing heparin and for next-generation, tailor-made, GAG-based antivirals.", - "rel_num_authors": 12, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.02.20030130", + "rel_abs": "Corona Virus Disease 2019 (COVID-19) is a recently emerged life-threatening disease caused by SARS-CoV-2. Real-time fluorescent PCR (RT-PCR) is the clinical standard for SARS-CoV-2 nucleic acid detection. To detect SARS-CoV-2 early and control the disease spreading on time, a faster and more convenient method for SARS-CoV-2 nucleic acid detecting, RT-LAMP method (reverse transcription loop-mediated isothermal amplification) was developed. RNA reverse transcription and nucleic acid amplification were performed in one step at 63 {degrees}C isothermal conditions, and the results can be obtained within 30 minutes. ORF1ab gene, E gene and N gene were detected at the same time. ORF1ab gene was very specific and N gene was very sensitivity, so they can guarantee both sensitivity and specificity for SARS-CoV-2. The sensitivity of RT-LAMP assay is similar to RT-PCR, and specificity was 99% as detecting 208 clinical specimens. The RT-LAMP assay reported here has the advantages of rapid amplification, simple operation, and easy detection, which is useful for the rapid and reliable clinical diagnosis of SARS-CoV-2.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Courtney J Mycroft-West", - "author_inst": "Keele University" + "author_name": "Weihua Yang", + "author_inst": "Jinan central hospital affiliated to shandong first medical university" }, { - "author_name": "Dunhao Su", - "author_inst": "University of Liverpool" + "author_name": "Xiaofei Dang", + "author_inst": "Jinan central hospital affiliated to shandong first medical university," }, { - "author_name": "Stefano Elli", - "author_inst": "Istituto di Ricerche Chimiche e Biochimiche G. Ronzoni" + "author_name": "Qingxi Wang", + "author_inst": "Jinan central hospital affiliated to shandong first medical university" }, { - "author_name": "Yong Li", - "author_inst": "University of Liverpool" + "author_name": "Mingjie Xu", + "author_inst": "Jinan central hospital affiliated to shandong first medical university" }, { - "author_name": "Scott E Guimond", - "author_inst": "Keele University" + "author_name": "Qianqian Zhao", + "author_inst": "Jinan central hospital affiliated to shandong first medical university" }, { - "author_name": "Gavin J Miller", - "author_inst": "Keele University" + "author_name": "Yunying Zhou", + "author_inst": "Jinan central hospital affiliated to shandong first medical university" }, { - "author_name": "Jeremy E Turnbull", - "author_inst": "University of Liverpool" + "author_name": "Huailong Zhao", + "author_inst": "Jinan center for disease control and prevention" }, { - "author_name": "Edwin A Yates", - "author_inst": "University of Liverpool" + "author_name": "Li Wang", + "author_inst": "Infectious disease hospital of Jinan" }, { - "author_name": "Marco Guerrini", - "author_inst": "Istituto di Ricerche Chimiche e Biochimiche G. Ronzoni" + "author_name": "Yihui Xu", + "author_inst": "Department of clinical laboratory, Jinan central hospital affiliated to shandong first medical university" }, { - "author_name": "David G Fernig", - "author_inst": "University of Liverpool" + "author_name": "Jun Wang", + "author_inst": "Department of clinical laboratory, Jinan central hospital affiliated to shandong first medical university" }, { - "author_name": "Marcelo Andrade de Lima", - "author_inst": "Keele University" + "author_name": "Shuyi Han", + "author_inst": "Department of clinical laboratory, Jinan central hospital affiliated to shandong first medical university" }, { - "author_name": "Mark A Skidmore", - "author_inst": "Keele University" + "author_name": "Min Wang", + "author_inst": "Department of clinical laboratory, Jinan central hospital affiliated to shandong first medical university" + }, + { + "author_name": "Fengyan Pei", + "author_inst": "Department of clinical laboratory, Jinan central hospital affiliated to shandong first medical university" + }, + { + "author_name": "Yunshan Wang", + "author_inst": "Department of clinical laboratory, Jinan central hospital affiliated to shandong first medical university.Department of clinical laboratory, Jinan central hos" } ], "version": "1", "license": "cc_no", - "type": "new results", - "category": "biochemistry" + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.03.02.20030080", @@ -1588050,73 +1586939,205 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.02.25.20027763", - "rel_title": "Prevalence and clinical features of 2019 novel coronavirus disease (COVID-19) in the Fever Clinic of a teaching hospital in Beijing: a single-center, retrospective study", + "rel_doi": "10.1101/2020.02.25.20027664", + "rel_title": "Comorbidity and its impact on 1,590 patients with COVID-19 in China: A Nationwide Analysis", "rel_date": "2020-02-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.25.20027763", - "rel_abs": "BackgroundWith the spread of COVID-19 from Wuhan, Hubei Province to other areas of the country, medical staff in Fever Clinics faced the challenge of identifying suspected cases among febrile patients with acute respiratory infections. We aimed to describe the prevalence and clinical features of COVID-19 as compared to pneumonias of other etiologies in a Fever Clinic in Beijing.\n\nMethodsIn this single-center, retrospective study, 342 cases of pneumonia were diagnosed in Fever Clinic in Peking University Third Hospital between January 21 to February 15, 2020. From these patients, 88 were reviewed by panel discussion as possible or probable cases of COVID-19, and received 2019-nCoV detection by RT-PCR. COVID-19 was confirmed by positive 2019-nCoV in 19 cases, and by epidemiological, clinical and CT features in 2 cases (the COVID-19 Group, n=21), while the remaining 67 cases served as the non-COVID-19 group. Demographic and epidemiological data, symptoms, laboratory and lung CT findings were collected, and compared between the two groups.\n\nFindingsThe prevalence of COVID-19 in all pneumonia patients during the study period was 6.14% (21/342). Compared with the non-COVID-19 group, more patients with COVID-19 had an identified epidemiological history (90.5% versus 32.8%, P<0.001). The COVID-19 group had lower WBC [5.19x109/L ({+/-}1.47) versus 7.21x109/L ({+/-}2.94), P<0.001] and neutrophil counts [3.39x109/L ({+/-}1.48) versus 5.38x109/L ({+/-}2.85), P<0.001] in peripheral blood. However, the count of lymphocytes was not different. On lung CT scans, involvement of 4 or more lobes was more common in the COVID-19 group (45% versus 16.4%, P=0.008).\n\nInterpretationIn the period of COVID-19 epidemic outside Hubei Province, the prevalence of COVID-19 in patients with pneumonia visiting our Fever Clinic in Beijing was 6.14%. Epidemiological evidence was important for prompt case finding, and lower blood WBC and neutrophil counts may be useful for differentiation from pneumonia of other etiologies.\n\nFundingNone.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.25.20027664", + "rel_abs": "ObjectiveTo evaluate the spectrum of comorbidities and its impact on the clinical outcome in patients with coronavirus disease 2019 (COVID-19).\n\nDesignRetrospective case studies\n\nSetting575 hospitals in 31 province/autonomous regions/provincial municipalities across China\n\nParticipants1,590 laboratory-confirmed hospitalized patients. Data were collected from November 21st, 2019 to January 31st, 2020.\n\nMain outcomes and measuresEpidemiological and clinical variables (in particular, comorbidities) were extracted from medical charts. The disease severity was categorized based on the American Thoracic Society guidelines for community-acquired pneumonia. The primary endpoint was the composite endpoints, which consisted of the admission to intensive care unit (ICU), or invasive ventilation, or death. The risk of reaching to the composite endpoints was compared among patients with COVID-19 according to the presence and number of comorbidities.\n\nResultsOf the 1,590 cases, the mean age was 48.9 years. 686 patients (42.7%) were females. 647 (40.7%) patients were managed inside Hubei province, and 1,334 (83.9%) patients had a contact history of Wuhan city. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached to the composite endpoints. 399 (25.1%) reported having at least one comorbidity. 269 (16.9%), 59 (3.7%), 30 (1.9%), 130 (8.2%), 28 (1.8%), 24 (1.5%), 21 (1.3%), 18 (1.1%) and 3 (0.2%) patients reported having hypertension, cardiovascular diseases, cerebrovascular diseases, diabetes, hepatitis B infections, chronic obstructive pulmonary disease, chronic kidney diseases, malignancy and immunodeficiency, respectively. 130 (8.2%) patients reported having two or more comorbidities. Patients with two or more comorbidities had significantly escalated risks of reaching to the composite endpoint compared with those who had a single comorbidity, and even more so as compared with those without (all P<0.05). After adjusting for age and smoking status, patients with COPD (HR 2.681, 95%CI 1.424-5.048), diabetes (HR 1.59, 95%CI 1.03-2.45), hypertension (HR 1.58, 95%CI 1.07-2.32) and malignancy (HR 3.50, 95%CI 1.60-7.64) were more likely to reach to the composite endpoints than those without. As compared with patients without comorbidity, the HR (95%CI) was 1.79 (95%CI 1.16-2.77) among patients with at least one comorbidity and 2.59 (95%CI 1.61-4.17) among patients with two or more comorbidities.\n\nConclusionComorbidities are present in around one fourth of patients with COVID-19 in China, and predispose to poorer clinical outcomes.\n\nHighlightsO_ST_ABSWhat is already known on this topicC_ST_ABS- Since November 2019, the rapid outbreak of coronavirus disease 2019 (COVID-19) has recently become a public health emergency of international concern. There have been 79,331 laboratory-confirmed cases and 2,595 deaths globally as of February 25th, 2020\n- Previous studies have demonstrated the association between comorbidities and other severe acute respiratory diseases including SARS and MERS.\n- No study with a nationwide representative cohort has demonstrated the spectrum of comorbidities and the impact of comorbidities on the clinical outcomes in patients with COVID-19.\n\n\nWhat this study adds- In this nationwide study with 1,590 patients with COVID-19, comorbidities were identified in 399 patients. Comorbidities of COVID-19 mainly included hypertension, cardiovascular diseases, cerebrovascular diseases, diabetes, hepatitis B infections, chronic obstructive pulmonary disease, chronic kidney diseases, malignancy and immunodeficiency.\n- The presence of as well as the number of comorbidities predicted the poor clinical outcomes (admission to intensive care unit, invasive ventilation, or death) of COVID-19.\n- Comorbidities should be taken into account when estimating the clinical outcomes of patients with COVID-19 on hospital admission.", + "rel_num_authors": 47, "rel_authors": [ { - "author_name": "Ying Liang", - "author_inst": "Peking University Third Hospital" + "author_name": "Wei-jie Guan", + "author_inst": "Guangzhou Institute of Respiratory Health" }, { - "author_name": "Jingjin Liang", - "author_inst": "Peking University Third Hospital" + "author_name": "Wen-hua Liang", + "author_inst": "Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the " }, { - "author_name": "Qingtao Zhou", - "author_inst": "Peking University Third Hospital" + "author_name": "Yi Zhao", + "author_inst": "Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the " }, { - "author_name": "Xiaoguang Li", - "author_inst": "Peking University Third Hospital" + "author_name": "Heng-rui Liang", + "author_inst": "Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the " }, { - "author_name": "Fei Lin", - "author_inst": "Peking University Third Hospital" + "author_name": "Zi-sheng Chen", + "author_inst": "Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the " }, { - "author_name": "Zhonghua Deng", - "author_inst": "Peking University Third Hospital" + "author_name": "Yi-min Li", + "author_inst": "Department of Pulmonary and Critical Care Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseas" }, { - "author_name": "Biying Zhang", - "author_inst": "Peking University Third Hospital" + "author_name": "Xiao-qing Liu", + "author_inst": "Department of Pulmonary and Critical Care Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseas" }, { - "author_name": "Lu Li", - "author_inst": "Peking University Third Hospital" + "author_name": "Ru-chong Chen", + "author_inst": "State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical Univ" }, { - "author_name": "Xiaohua Wang", - "author_inst": "Peking University Third Hospital" + "author_name": "Chun-li Tang", + "author_inst": "State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical Univ" }, { - "author_name": "Hong Zhu", - "author_inst": "Peking University Third Hospital" + "author_name": "Tao Wang", + "author_inst": "State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical Univ" }, { - "author_name": "Qingbian Ma", - "author_inst": "Peking University Third Hospital" + "author_name": "Chun-quan Ou", + "author_inst": "State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public " }, { - "author_name": "Xiaomei Tong", - "author_inst": "Peking University Third Hospital" + "author_name": "Li Li", + "author_inst": "State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public " }, { - "author_name": "Jie Xu", - "author_inst": "Peking University Third Hospital" + "author_name": "Ping-yan Chen", + "author_inst": "State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public " }, { - "author_name": "Yongchang Sun", - "author_inst": "Peking University Third Hospital" + "author_name": "Ling Sang", + "author_inst": "Department of Pulmonary and Critical Care Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseas" + }, + { + "author_name": "Wei Wang", + "author_inst": "Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the " + }, + { + "author_name": "Jian-fu Li", + "author_inst": "Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the " + }, + { + "author_name": "Cai-chen Li", + "author_inst": "Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the " + }, + { + "author_name": "Li-min Ou", + "author_inst": "Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the " + }, + { + "author_name": "Bo Cheng", + "author_inst": "Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the " + }, + { + "author_name": "Shan Xiong", + "author_inst": "Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the " + }, + { + "author_name": "Zheng-yi Ni", + "author_inst": "Wuhan Jin-yintan Hospital" + }, + { + "author_name": "Yu Hu", + "author_inst": "Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Jie Xiang", + "author_inst": "Wuhan Jin-yin-tan Hospital" + }, + { + "author_name": "Lei Liu", + "author_inst": "Shenzhen Third People's Hospital; The Second Affiliated Hospital of Southern University of Science and Technology, National Clinical Research Center for Infecti" + }, + { + "author_name": "Hong Shan", + "author_inst": "The fifth Affiliated Hospital of Sun Yat-sen University" + }, + { + "author_name": "Chun-liang Lei", + "author_inst": "Guangzhou Eighth People's Hospital, Guangzhou Medical University" + }, + { + "author_name": "Yi-xiang Peng", + "author_inst": "The Central Hospital of Wuhan" + }, + { + "author_name": "Li Wei", + "author_inst": "Wuhan No.1 Hospital, Wuhan Hospital of Traditional Chinese and Western Medicine" + }, + { + "author_name": "Yong Liu", + "author_inst": "Chengdu Public Health Clinical Medical Center" + }, + { + "author_name": "Ya-hua Hu", + "author_inst": "Huangshi Central Hospital of Edong Healthcare Group, Affiliated Hospital of Hubei Polytechnic University" + }, + { + "author_name": "Peng Peng", + "author_inst": "Wuhan Pulmonary Hospital" + }, + { + "author_name": "Jian-ming Wang", + "author_inst": "Tianyou Hospital Affiliated to Wuhan University of Science and Technology" + }, + { + "author_name": "Ji-yang Liu", + "author_inst": "The First Hospital of Changsha" + }, + { + "author_name": "Zhong Chen", + "author_inst": "the Third People's Hospital of Hainan Province" + }, + { + "author_name": "Gang Li", + "author_inst": "Huanggang Central Hospital" + }, + { + "author_name": "Zhi-jian Zheng", + "author_inst": "Wenling First People's Hospital" + }, + { + "author_name": "Shao-qin Qiu", + "author_inst": "The Third People's Hospital of Yichang" + }, + { + "author_name": "Jie Luo", + "author_inst": "Affiliated Taihe Hospital of Hubei University of Medicine" + }, + { + "author_name": "Chang-jiang Ye", + "author_inst": "Xiantao First People's Hospital" + }, + { + "author_name": "Shao-yong Zhu", + "author_inst": "The People's Hospital of Huangpi District" + }, + { + "author_name": "Lin-ling Cheng", + "author_inst": "State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical Univ" + }, + { + "author_name": "Feng Ye", + "author_inst": "State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical Univ" + }, + { + "author_name": "Shi-yue Li", + "author_inst": "State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical Univ" + }, + { + "author_name": "Jin-ping Zheng", + "author_inst": "State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical Univ" + }, + { + "author_name": "Nuo-fu Zhang", + "author_inst": "State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical Univ" + }, + { + "author_name": "Nan-shan Zhong", + "author_inst": "State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical Univ" + }, + { + "author_name": "Jian-xing He", + "author_inst": "Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the " } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "respiratory medicine" }, @@ -1589632,69 +1588653,65 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.02.25.20024711", - "rel_title": "Can routine laboratory tests discriminate 2019 novel coronavirus infected pneumonia from other community-acquired pneumonia?", + "rel_doi": "10.1101/2020.02.22.20025791", + "rel_title": "Temperature significant change COVID-19 Transmission in 429 cities", "rel_date": "2020-02-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.25.20024711", - "rel_abs": "BackgroundThe clinical presentation of 2019 Novel Coronavirus (2019-nCov) infected pneumonia (NCIP) resembles that of other etiologies of community-acquired pneumonia (CAP). We aimed to identify clinical laboratory features to distinguish NCIP from CAP.\n\nMethodsWe compared the ability of the hematological and biochemical features of 84 patients with NCIP at hospital admission and 316 patients with CAP. Parameters independently predictive of NCIP were calculated by multivariate logistic regression. The receiver operating characteristic (ROC) curves were generated and the area under the ROC curve (AUC) was measured to evaluate the discriminative ability.\n\nResultsMost hematological and biochemical indexes of patients with NCIP were significantly different from patients with CAP. Nine laboratory parameters were identified to be highly predictive of a diagnosis of NCIP by multivariate analysis. The AUCs demonstrated good discriminatory ability for red cell distribution width (RDW) with an AUC of 0.88 and Hemoglobin (HGB) with an AUC of 0.82. Red blood cell (RBC), albumin (ALB), eosinophil (EO), hematocrit (HCT), alkaline phosphatase (ALP), and white blood cell (WBC) had fair discriminatory ability. Combinations of any two parameters performed better than did the RDW alone.\n\nConclusionsRoutine laboratory examinations may be helpful for the diagnosis of NCIP. Application of laboratory tests may help to optimize the use of isolation rooms for patients when they present with unexplained febrile respiratory illnesses.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.22.20025791", + "rel_abs": "BackgroundThere is no evidence supporting that temperature changes COVID-19 transmission.\n\nMethodsWe collected the cumulative number of confirmed cases of all cities and regions affected by COVID-19 in the world from January 20 to February 4, 2020, and calculated the daily means of the average, minimum and maximum temperatures in January. Then, restricted cubic spline function and generalized linear mixture model were used to analyze the relationships.\n\nResultsThere were in total 24,139 confirmed cases in China and 26 overseas countries. In total, 16,480 cases (68.01%) were from Hubei Province. The lgN rose as the average temperature went up to a peak of 8.72{degrees}C and then slowly declined. The apexes of the minimum temperature and the maximum temperature were 6.70{degrees}C and 12.42{degrees}C respectively. The curves shared similar shapes. Under the circumstance of lower temperature, every 1{degrees}C increase in average, minimum and maximum temperatures led to an increase of the cumulative number of cases by 0.83, 0.82 and 0.83 respectively. In the single-factor model of the higher-temperature group, every 1{degrees}C increase in the minimum temperature led to a decrease of the cumulative number of cases by 0.86.\n\nConclusionThe study found that, to certain extent, temperature could significant change COVID-19 transmission, and there might be a best temperature for the viral transmission, which may partly explain why it first broke out in Wuhan. It is suggested that countries and regions with a lower temperature in the world adopt the strictest control measures to prevent future reversal.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Yunbao Pan", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Mao Wang", + "author_inst": "Sun Yat-sen University" }, { - "author_name": "Guangming Ye", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Aili Jiang", + "author_inst": "Deparment of Occupatinal and Environmetal Health, School of Public Health, Sun Yat-sen University" }, { - "author_name": "Xiantao Zeng", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Lijuan Gong", + "author_inst": "Deparment of Occupatinal and Environmetal Health, School of Public Health, Sun Yat-sen University" }, { - "author_name": "Guohong Liu", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Lina Luo", + "author_inst": "Department of health and nurse, Nanfang College of Sun Yat-sen University" }, { - "author_name": "Xiaojiao Zeng", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Wenbin Guo", + "author_inst": "Department of health and nurse, Nanfang College of Sun Yat-sen University" }, { - "author_name": "Xianghu Jiang", - "author_inst": "Zhongnan Hospital of Wuhan University" - }, - { - "author_name": "Jin Zhao", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Chuyi Li", + "author_inst": "Department of health and nurse, Nanfang College of Sun Yat-sen University" }, { - "author_name": "Liangjun Chen", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Jing Zheng", + "author_inst": "Department of health and nurse, Nanfang College of Sun Yat-sen University" }, { - "author_name": "Shuang Guo", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Chaoyong Li", + "author_inst": "Department of health and nurse, Nanfang College of Sun Yat-sen University" }, { - "author_name": "Qiaoling Deng", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Bixing Yang", + "author_inst": "Department of health and nurse, Nanfang College of Sun Yat-sen University" }, { - "author_name": "Xiaoyue Hong", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Jietong Zeng", + "author_inst": "Department of health and nurse, Nanfang College of Sun Yat-sen University" }, { - "author_name": "Ying Yang", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Youping Chen", + "author_inst": "Department of health and nurse, Nanfang College of Sun Yat-sen University" }, { - "author_name": "Yirong Li", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Ke Zheng", + "author_inst": "Department of health and nurse, Nanfang College of Sun Yat-sen University" }, { - "author_name": "Xinghuan Wang", - "author_inst": "Zhongnan Hospital of Wuhan University" + "author_name": "Hongyan Li", + "author_inst": "Department of health and nurse, Nanfang College of Sun Yat-sen University" } ], "version": "1", @@ -1591374,101 +1590391,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.02.20.20025510", - "rel_title": "ACP risk grade: a simple mortality index for patients with confirmed or suspected severe acute respiratory syndrome coronavirus 2 disease (COVID-19) during the early stage of outbreak in Wuhan, China", + "rel_doi": "10.1101/2020.02.19.20025163", + "rel_title": "Estimating the risk of 2019 Novel Coronavirus death during the course of the outbreak in China, 2020", "rel_date": "2020-02-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.20.20025510", - "rel_abs": "BackgroundSince the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19) outbreaks in Wuhan, China, healthcare systems capacities in highly endemic areas have been overwhelmed. Approaches to efficient management are urgently needed and key to a quicker control of the outbreaks and casualties. We aimed to characterize the clinical features of hospitalized patients with confirmed or suspected COVID-19, and develop a mortality risk index for COVID-19 patients.\n\nMethodsIn this retrospective one-centre cohort study, we included all the confirmed or suspected COVID-19 patients hospitalized in a COVID-19-designated hospital from January 21 to February 5, 2020. Demographic, clinical, laboratory, radiological and clinical outcome data were collected from the hospital information system, nursing records and laboratory reports.\n\nResultsOf 577 patients with at least one post-admission evaluation, the median age was 55 years (interquartile range [IQR], 39 - 66); 254 (44.0%) were men; 22.8% (100/438) were severe pneumonia on admission, and 37.7% (75/199) patients were SARS-CoV-2 positive. The clinical, laboratory and radiological data were comparable between positive and negative SARS-CoV-2 patients. During a median follow-up of 8.4 days (IQR, 5.8 - 12.0), 39 patients died with a 12-day cumulative mortality of 8.7% (95% CI, 5.9% to 11.5%). A simple mortality risk index (called ACP index), composed of Age and C-reactive Protein, was developed. By applying the ACP index, patients were categorized into three grades. The 12-day cumulative mortality in grade three (age [≥] 60 years and CRP [≥] 34 mg/L) was 33.2% (95% CI, 19.8% to 44.3%), which was significantly higher than those of grade two (age [≥] 60 years and CRP < 34 mg/L; age < 60 years and CRP [≥] 34 mg/L; 5.6% [95% CI, 0 to 11.3%]) and grade one (age < 60 years and CRP < 34 mg/L, 0%) (P <0.001), respectively.\n\nConclusionThe ACP index can predict COVID-19 related short-term mortality, which may be a useful and convenient tool for quickly establishing a COVID-19 hierarchical management system that can greatly reduce the medical burden and therefore mortality in highly endemic areas.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.19.20025163", + "rel_abs": "Since the first case of Novel Coronavirus (2019-nCov) was identified in December 2019 in Wuhan City, China, the number of cases continues to grow across China and multiple cases have been exported to other countries. The cumulative number of reported deaths is at 637 as of February 7, 2020. Here we statistically estimated the time-delay adjusted death risk for Wuhan as well as for China excluding Wuhan to interpret the current severity of the epidemic in China. We found that the latest estimates of the death risk in Wuhan could be as high as 20% in the epicenter of the epidemic whereas we estimate it [~]1% in the relatively mildly-affected areas. Because the elevated death risk estimates are likely associated with a breakdown of the medical/health system, enhanced public health interventions including social distancing and movement restrictions should be effectively implemented to bring the epidemic under control.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Jiatao Lu", - "author_inst": "Wuhan Hankou Hospital, Wuhan, China" - }, - { - "author_name": "Shufang Hu", - "author_inst": "Department of Endocrinology, Wuhan Hankou Hospital, Wuhan, China" - }, - { - "author_name": "Rong Fan", - "author_inst": "Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China" - }, - { - "author_name": "Zhihong Liu", - "author_inst": "Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China" - }, - { - "author_name": "Xueru Yin", - "author_inst": "Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China" - }, - { - "author_name": "Qiongya Wang", - "author_inst": "Wuhan Hankou Hospital, Wuhan, China" - }, - { - "author_name": "Qingquan Lv", - "author_inst": "Department of Medical Affairs, Wuhan Hankou Hospital, Wuhan, China" - }, - { - "author_name": "Zhifang Cai", - "author_inst": "Department of Respiratory Diseases, Wuhan Hankou Hospital, Wuhan, China" - }, - { - "author_name": "Haijun Li", - "author_inst": "Department of Radiology, Wuhan Hankou Hospital, Wuhan, China" - }, - { - "author_name": "Yuhai Hu", - "author_inst": "Department of Laboratory Medicine, Wuhan Hankou Hospital, Wuhan, China" - }, - { - "author_name": "Ying Han", - "author_inst": "Department of Nursing, Wuhan Hankou Hospital, Wuhan, China" - }, - { - "author_name": "Hongping Hu", - "author_inst": "Department of Emergency, Wuhan Hankou Hospital, Wuhan, China" - }, - { - "author_name": "Wenyong Gao", - "author_inst": "Department of Neurology, Wuhan Hankou Hospital, Wuhan, China" - }, - { - "author_name": "Shibo Feng", - "author_inst": "Department of Orthopaedics, Wuhan Hankou Hospital, Wuhan, China" - }, - { - "author_name": "Qiongfang Liu", - "author_inst": "Department of Nosocomial Infection Administration, Wuhan Hankou Hospital, Wuhan, China" - }, - { - "author_name": "Hui Li", - "author_inst": "Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China" - }, - { - "author_name": "Jian Sun", - "author_inst": "Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China" - }, - { - "author_name": "Jie Peng", - "author_inst": "Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China" - }, - { - "author_name": "Xuefeng Yi", - "author_inst": "Health Commission of Guangdong Province, Guangzhou, China" - }, - { - "author_name": "Zixiao Zhou", - "author_inst": "Health Commission of Guangdong Province, Guangzhou, China" - }, - { - "author_name": "Yabing Guo", - "author_inst": "Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China" + "author_name": "Kenji Mizumoto", + "author_inst": "Kyoto University" }, { - "author_name": "Jinlin Hou", - "author_inst": "Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China" + "author_name": "Gerardo Chowell", + "author_inst": "Georgia State University School of Public Health" } ], "version": "1", @@ -1592971,29 +1591908,57 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.02.19.955484", - "rel_title": "Potential T-cell and B-cell Epitopes of 2019-nCoV", + "rel_doi": "10.1101/2020.02.20.957472", + "rel_title": "Vulnerabilities in coronavirus glycan shields despite extensive glycosylation", "rel_date": "2020-02-21", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.19.955484", - "rel_abs": "As of early March, 2019-nCoV has infected more than one hundred thousand people and claimed thousands of lives. 2019-nCoV is a novel form of coronavirus that causes COVID-19 and has high similarity with SARS-CoV. No approved vaccine yet exists for any form of coronavirus. Here we use computational tools from structural biology and machine learning to identify 2019-nCoV T-cell and B-cell epitopes based on viral protein antigen presentation and antibody binding properties. These epitopes can be used to develop more effective vaccines and identify neutralizing antibodies. We identified 405 viral peptides with good antigen presentation scores for both human MHC-I and MHC-II alleles, and two potential neutralizing B-cell epitopes near the 2019-nCoV spike protein receptor binding domain (440-460 and 494-506). Analyzing mutation profiles of 68 viral genomes from four continents, we identified 96 coding-change mutations. These mutations are more likely to occur in regions with good MHC-I presentation scores (p=0.02). No mutations are present near the spike protein receptor binding domain. Based on these findings, the spike protein is likely immunogenic and a potential vaccine candidate. We validated our computational pipeline with SARS-CoV experimental data.\n\nSignificance StatementThe novel coronavirus 2019-nCoV has affected more than 100 countries and continues to spread. There is an immediate need for effective vaccines that contain antigens which trigger responses from human T-cells and B-cells (known as epitopes). Here we identify potential T-cell epitopes through an analysis of human antigen presentation, as well as B-cell epitopes through an analysis of protein structure. We identify a list of top candidates, including an epitope located on 2019-nCoV spike protein that potentially triggers both T-cell and B-cell responses. Analyzing 68 samples, we observe that viral mutations are more likely to happen in regions with strong antigen presentation, a potential form of immune evasion. Our computational pipeline is validated with experimental data from SARS-CoV.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.20.957472", + "rel_abs": "Severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) coronaviruses (CoVs) are zoonotic pathogens with high fatality rates and pandemic potential. Vaccine development has focussed on the principal target of the neutralizing humoral immune response, the spike (S) glycoprotein, which mediates receptor recognition and membrane fusion. Coronavirus S proteins are extensively glycosylated viral fusion proteins, encoding around 69-87 N-linked glycosylation sites per trimeric spike. Using a multifaceted structural approach, we reveal a specific area of high glycan density on MERS S that results in the formation of under-processed oligomannose-type glycan clusters, which was absent on SARS and HKU1 CoVs. We provide a comparison of the global glycan density of coronavirus spikes with other viral proteins including HIV-1 envelope, Lassa virus glycoprotein complex, and influenza hemagglutinin, where glycosylation plays a known role in shielding immunogenic epitopes. Consistent with the ability of the antibody-mediated immune response to effectively target and neutralize coronaviruses, we demonstrate that the glycans of coronavirus spikes are not able to form an efficacious high-density global shield to thwart the humoral immune response. Overall, our data reveal how differential organisation of viral glycosylation across class I viral fusion proteins influence not only individual glycan compositions but also the immunological pressure across the viral protein surface.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Ethan Fast", - "author_inst": "NASH" + "author_name": "Yasunori Watanabe", + "author_inst": "University of Oxford" }, { - "author_name": "Russ B Altman", - "author_inst": "Stanford University" + "author_name": "Zachary T. Berndsen", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Binbin Chen", - "author_inst": "Stanford Medicine" + "author_name": "Jayna Raghwani", + "author_inst": "University of Oxford" + }, + { + "author_name": "Gemma E. Seabright", + "author_inst": "University of Oxford" + }, + { + "author_name": "Joel D. Allen", + "author_inst": "University of Southampton" + }, + { + "author_name": "Jason S McLellan", + "author_inst": "The University of Texas at Austin" + }, + { + "author_name": "Ian A. Wilson", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Thomas A. Bowden", + "author_inst": "University of Oxford" + }, + { + "author_name": "Andrew B. Ward", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Max Crispin", + "author_inst": "University of Southampton" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "new results", "category": "microbiology" }, @@ -1594493,21 +1593458,53 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.02.16.20023820", - "rel_title": "Fractal kinetics of COVID-19 pandemic", + "rel_doi": "10.1101/2020.02.18.20024513", + "rel_title": "Estimating the cure rate and case fatality rate of the ongoing epidemic COVID-19", "rel_date": "2020-02-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.16.20023820", - "rel_abs": "We give an update to the original paper posted on 2/17/20 - now (as of 3/1/20) the China deaths are rapidly decreasing, and we find an exponential decline to the power law similar to the that predicted by the network model of Vazquez [2006]. At the same time, we see non-China deaths increasing rapidly, and similar to the early behavior of the China statistics. Thus, we see three stages of the spread of the disease in terms of number of deaths: exponential growth, power-law behavior, and then exponential decline in the daily rate.\n\n(Original abstract) The novel coronavirus (COVID-19) continues to grow rapidly in China and is spreading in other parts of the world. The classic epidemiological approach in studying this growth is to quantify a reproduction number and infection time, and this is the approach followed by many studies on the epidemiology of this disease. However, this assumption leads to exponential growth, and while the growth rate is high, it is not following exponential behavior. One approach that is being used is to simply keep adjusting the reproduction number to match the dynamics. Other approaches use rate equations such as the SEIR and logistical models. Here we show that the current growth closely follows power-law kinetics, indicative of an underlying fractal or small-world network of connections between susceptible and infected individuals. Positive deviations from this growth law might indicate either a failure of the current containment efforts while negative deviations might indicate the beginnings of the end of the pandemic. We cannot predict the ultimate extent of the pandemic but can get an estimate of the growth of the disease.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.18.20024513", + "rel_abs": "The epidemic caused by the novel coronavirus COVID-19 in Wuhan at the end of 2019 has become an urgent public event of worldwide concern. However, due to the changing data of the epidemic, there is no scientific estimate of the cure rate and case fatality rate of the epidemic. This study proposes a method to estimate the cure rate and case fatality rate of COVID-19. The ratio of cumulative discharges on a given day to the sum of cumulative discharges on a given day and cumulative deaths before j days is used to estimate the cure rate. Moreover, the case fatality ratio can also be estimated. After simulation calculations, j is statistically appropriate when it is 8-10, and it is also clinically appropriate. When j is 9, based on the available data, it is inferred that the cure rate of this epidemic is about 93% and the case fatality rate is about 7%. This method of estimating the cure rate can be used to evaluate the effectiveness of treatment in different medical schemes and different regions, and has great value and significance for decision-making in the epidemic.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Anna L. Ziff", - "author_inst": "Duke University" + "author_name": "Ying Diao", + "author_inst": "Wuhan University; Chongqing University of Arts and Sciences" }, { - "author_name": "Robert M. Ziff", - "author_inst": "University of Michigan" + "author_name": "Xiaoyun Liu", + "author_inst": "Wuhan Windoor Information Technology Co. Ltd." + }, + { + "author_name": "Tao Wang", + "author_inst": "Wuhan University" + }, + { + "author_name": "Xiaofei Zeng", + "author_inst": "Southern University of Science and Technology" + }, + { + "author_name": "Chen Dong", + "author_inst": "Henan University of Technology" + }, + { + "author_name": "Changlong Zhou", + "author_inst": "Yongchuan Hospital of Chongqing Medical University" + }, + { + "author_name": "Yuanming Zhang", + "author_inst": "Huazhong Agricultural University" + }, + { + "author_name": "Xuan She", + "author_inst": "Wuhan University" + }, + { + "author_name": "Dingfu Liu", + "author_inst": "Hubei Academy of Agricultural Sciences" + }, + { + "author_name": "Zhongli Hu", + "author_inst": "Wuhan University" } ], "version": "1", @@ -1595851,57 +1594848,41 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.02.14.20023028", - "rel_title": "A deep learning algorithm using CT images to screen for Corona Virus Disease (COVID-19)", + "rel_doi": "10.1101/2020.02.13.20022830", + "rel_title": "A simple laboratory parameter facilitates early identification of COVID-19 patients", "rel_date": "2020-02-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.14.20023028", - "rel_abs": "BackgroundThe outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) has caused more than 2.5 million cases of Corona Virus Disease (COVID-19) in the world so far, with that number continuing to grow. To control the spread of the disease, screening large numbers of suspected cases for appropriate quarantine and treatment is a priority. Pathogenic laboratory testing is the gold standard but is time-consuming with significant false negative results. Therefore, alternative diagnostic methods are urgently needed to combat the disease. Based on COVID-19 radiographical changes in CT images, we hypothesized that Artificial Intelligences deep learning methods might be able to extract COVID-19s specific graphical features and provide a clinical diagnosis ahead of the pathogenic test, thus saving critical time for disease control.\n\nMethods and FindingsWe collected 1,065 CT images of pathogen-confirmed COVID-19 cases (325 images) along with those previously diagnosed with typical viral pneumonia (740 images). We modified the Inception transfer-learning model to establish the algorithm, followed by internal and external validation. The internal validation achieved a total accuracy of 89.5% with specificity of 0.88 and sensitivity of 0.87. The external testing dataset showed a total accuracy of 79.3% with specificity of 0.83 and sensitivity of 0.67. In addition, in 54 COVID-19 images that first two nucleic acid test results were negative, 46 were predicted as COVID-19 positive by the algorithm, with the accuracy of 85.2%.\n\nConclusionThese results demonstrate the proof-of-principle for using artificial intelligence to extract radiological features for timely and accurate COVID-19 diagnosis.\n\nAuthor summaryTo control the spread of the COVID-19, screening large numbers of suspected cases for appropriate quarantine and treatment measures is a priority. Pathogenic laboratory testing is the gold standard but is time-consuming with significant false negative results. Therefore, alternative diagnostic methods are urgently needed to combat the disease. We hypothesized that Artificial Intelligences deep learning methods might be able to extract COVID-19s specific graphical features and provide a clinical diagnosis ahead of the pathogenic test, thus saving critical time. We collected 1,065 CT images of pathogen-confirmed COVID-19 cases along with those previously diagnosed with typical viral pneumonia. We modified the Inception transfer-learning model to establish the algorithm. The internal validation achieved a total accuracy of 89.5% with specificity of 0.88 and sensitivity of 0.87. The external testing dataset showed a total accuracy of 79.3% with specificity of 0.83 and sensitivity of 0.67. In addition, in 54 COVID-19 images that first two nucleic acid test results were negative, 46 were predicted as COVID-19 positive by the algorithm, with the accuracy of 85.2%. Our study represents the first study to apply artificial intelligence to CT images for effectively screening for COVID-19.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.13.20022830", + "rel_abs": "The total number of COVID-19 patients since the outbreak of this infection in Wuhan, China has reached 40000 and are still growing. To facilitate triage or identification of the large number of COVID-19 patients from other patients with similar symptoms in designated fever clinics, we set to identify a practical marker that could be conveniently utilized by first-line health-care workers in clinics. To do so, we performed a case-control study by analyzing clinical and laboratory findings between PCR-confirmed SARS-CoV-2 positive patients (n=52) and SARS-CoV-2 negative patients (n=53). The patients in two cohorts all had similar symptoms, mainly fever and respiratory symptoms. The rates of patients with leukocyte counts (normal or decreased number) or lymphopenia (two parameters suggested by current National and WHO COVID-19 guidelines) had no differences between these two cohorts, while the rate of eosinopenia (decreased number of eosinophils) in SARS-CoV-2 positive patients (79%) was much higher than that in SARS-CoV-2 negative patients (36%). When the symptoms were combined with eosinopenia, this combination led to a diagnosis sensitivity and specificity of 79% and 64%, respectively, much higher than 48% and 53% when symptoms were combined with leukocyte counts (normal or decreased number) and/ or lymphopenia. Thus, our analysis reveals that eosinopenia may be a potentially more reliable laboratory predictor for SARS-CoV-2 infection than leukocyte counts and lymphopenia recommended by the current guidelines.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Shuai Wang", - "author_inst": "Tianjin Medical University Cancer Institute and Hospital" - }, - { - "author_name": "Bo Kang", - "author_inst": "Tianjin University, National Supercomputing Center of Tianjin" - }, - { - "author_name": "Jinlu Ma", - "author_inst": "First Affiliated Hospital, Xian Jiaotong University" - }, - { - "author_name": "Xianjun Zeng", - "author_inst": "Nanchang University First Hospital" - }, - { - "author_name": "Mingming Xiao", - "author_inst": "Tianjin Medical University Cancer Institute and Hospital" + "author_name": "Qilin Li", + "author_inst": "Wuhan Union Hospital" }, { - "author_name": "Jia Guo", - "author_inst": "National Supercomputing Center of Tianjin" + "author_name": "Xiuli Ding", + "author_inst": "Wuan Union Hospital" }, { - "author_name": "Mengjiao Cai", - "author_inst": "First Affiliated Hospital, Xian Jiaotong University" + "author_name": "Geqing Xia", + "author_inst": "Wuhan Union Hospital" }, { - "author_name": "Jingyi Yang", - "author_inst": "First Affiliated Hospital, Xian Jiaotong University" + "author_name": "Zhi Geng", + "author_inst": "Wuhan Union Hospital" }, { - "author_name": "Yaodong Li", - "author_inst": "No.8 Hospital, Xian Medical College" + "author_name": "Fenghua Chen", + "author_inst": "Wuhan Union Hospital" }, { - "author_name": "Xiangfei Meng", - "author_inst": "National Supercomputing Center of Tianjin" + "author_name": "Lin Wang", + "author_inst": "Wuhan Union Hospital" }, { - "author_name": "Bo Xu", - "author_inst": "Tianjin Medical University Cancer Institute and Hospital" + "author_name": "Zheng Wang", + "author_inst": "Wuhan Union Hospital" } ], "version": "1", @@ -1597165,27 +1596146,107 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.02.10.20021519", - "rel_title": "Simulating the infected population and spread trend of 2019-nCov under different policy by EIR model", + "rel_doi": "10.1101/2020.02.10.20021584", + "rel_title": "Neutrophil-to-Lymphocyte Ratio Predicts Severe Illness Patients with 2019 Novel Coronavirus in the Early Stage", "rel_date": "2020-02-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.10.20021519", - "rel_abs": "BackgroundChinese government has taken strong measures in response to the epidemic of new coronavirus (2019-nCoV) from Jan.23, 2020. The number of confirmed infected individuals are still increasing rapidly. Estimating the accurate infected population and the future trend of epidemic spreading under control measures is significant and urgent. There have been reports external icon of spread from an infected patient with no symptoms to a close contact, which means the incubation individuals may has the possibility of infectiousness. However, the traditional transmission model, Susceptible-Exposed-Infectious-Recovered (SEIR) model, assumes that the exposed individual is being infected but without infectiousness. Thus, the estimating infected populations based on SEIR model from the existing literatures seems too far more than the official reported data.\n\nMethodsHere, we inferred that the epidemic could be spread by exposed (incubation) individuals. Then, we provide a new Exposed-identified-Recovered (EIR) model, and simulated the epidemic spreading processes from free propagation phase to extremely control phase. Then, we estimate of the size of the epidemic and forecast the future development of the epidemics under strong prevention interventions. According to the spread characters of 2019-nCov, we construct a novel EIR compartment system dynamics model. This model integrates two phases of the epidemic spreading: before intervention and after intervention. We assume that 2019-nCov is firstly spread without intervention then the government started to take strong quarantine measures. Use the latest reported data from National Health Commission of the Peoples Republic of China, we estimate the basic parameters of the model and the basic reproduction number of 2019-nCov. Then, based on this model, we simulate the future spread of the epidemics. Both the infected population and the spreading trend of 2019-nCov under different prevention policy scenarios are estimated. The epidemic spreading trends under different quarantine rate and action starting date of prevention policy are simulated and compared.\n\nFindingsIn our baseline scenario, the government has taken strict prevention actions, and the estimate numbers fit the official numbers very well. Simulation results tells that, if the prevention measures are relaxed or the action starting date of prevention measures is later than Jan. 23, 2020, the peak of identified individuals would be greatly increased, and the elimination date also would be delayed. We estimate the reproductive number for 2019-nCoV was 2.7. And simulation of the baseline scenario tells that, the peak infected individuals will be 49093 at Feb.16, 2020 and the epidemic spreading will be eliminated at the end of March 2020. The simulation results also tell that the quarantine rate and the starting date of intervention action policy have great effect on the epidemic spreading. Specifically, if the quarantine rate is reduced from 100% to less than 63%, which is the threshold of the quarantine rate to control the epidemic spreading, the epidemic spreading would never be eliminated out. And, if the starting date of intervention is delayed for 1 day than the date Jan. 23, the peak infected population will increase about 6351 individuals. If the delayed period is 3 days or 7 days, the increasing number would be 21621 or 65929 individuals, thus the peak infected number would up to 70714 and 115022 individuals.\n\nInterpretationGiven that 2019-nCoV could be controlled under the strong prevention measures of what China has taken and it will take about three months. The confirmed infected individuals will still keep quick increasing for a generation period (27 days, equal to the sum of exposed period and identified period) after the start time point of control. The strong prevention measures should be insisted until the epidemics is wiped out. Other domestic places and overseas have confirmed infected individuals should take strong interventions immediately. Generally, earlier strong prevention measures could efficiently mitigate the outbreaks in other cities all over the world has confirmed individuals of epidemic of 2019-nCoV.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.10.20021584", + "rel_abs": "BackgroundSevere ill patients with 2019 novel coronavirus (2019-nCoV) infection progressed rapidly to acute respiratory failure. We aimed to select the most useful prognostic factor for severe illness incidence.\n\nMethodsThe study prospectively included 61 patients with 2019-nCoV infection treated at Beijing Ditan Hospital from January 13, 2020 to January 31, 2020. Prognostic factor of severe illness was selected by the LASSO COX regression analyses, to predict the severe illness probability of 2019-CoV pneumonia. The predictive accuracy was evaluated by concordance index, calibration curve, decision curve and clinical impact curve.\n\nResultsThe neutrophil-to-lymphocyte ratio (NLR) was identified as the independent risk factor for severe illness in patients with 2019-nCoV infection. The NLR had a c-index of 0.807 (95% confidence interval, 0.676-0.38), the calibration curves fitted well, and the decision curve and clinical impact curve showed that the NLR had superior standardized net benefit. In addition, the incidence of severe illness was 9.1% in age [≥] 50 and NLR < 3.13 patients, and half of patients with age [≥] 50 and NLR [≥] 3.13 would develop severe illness. Based on the risk stratification of NLR with age, the study developed a 2019-nCoV pneumonia management process.\n\nConclusionsThe NLR was the early identification of risk factors for 2019-nCoV severe illness. Patients with age [≥] 50 and NLR [≥] 3.13 facilitated severe illness, and they should rapidly access to intensive care unit if necessary.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Hao Xiong", - "author_inst": "Hainan University" + "author_name": "Jingyuan Liu", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" }, { - "author_name": "Huili Yan", - "author_inst": "Hainan University" + "author_name": "Yao Liu", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Pan Xiang", + "author_inst": "Department, Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Lin Pu", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Haofeng Xiong", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Chuansheng Li", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Ming Zhang", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Jianbo Tan", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Yanli Xu", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Rui Song", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Meihua Song", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Lin Wang", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Wei Zhang", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Bing Han", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Li Yang", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Xiaojing Wang", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Guiqin Zhou", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Ting Zhang", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Ben Li", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Yanbin Wang", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Zhihai Chen", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" + }, + { + "author_name": "Xianbo Wang", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.02.10.20021725", @@ -1598639,87 +1597700,75 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.02.08.926006", - "rel_title": "The transmembrane serine protease inhibitors are potential antiviral drugs for 2019-nCoV targeting the insertion sequence-induced viral infectivity enhancement", - "rel_date": "2020-02-11", + "rel_doi": "10.1101/2020.02.10.936898", + "rel_title": "Alpha-ketoamides as broad-spectrum inhibitors of coronavirus and enterovirus replication", + "rel_date": "2020-02-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.08.926006", - "rel_abs": "At the end of 2019, the SARS-CoV-2 induces an ongoing outbreak of pneumonia in China1, even more spread than SARS-CoV infection2. The entry of SARS-CoV into host cells mainly depends on the cell receptor (ACE2) recognition and spike protein cleavage-induced cell membrane fusion3,4. The spike protein of SARS-CoV-2 also binds to ACE2 with a similar affinity, whereas its spike protein cleavage remains unclear5,6. Here we show that an insertion sequence in the spike protein of SARS-CoV-2 enhances the cleavage efficiency, and besides pulmonary alveoli, intestinal and esophagus epithelium were also the target tissues of SARS-CoV-2. Compared with SARS-CoV, we found a SPRR insertion in the S1/S2 protease cleavage sites of SARS-CoV-2 spike protein increasing the cleavage efficiency by the protein sequence aligment and furin score calculation. Additionally, the insertion sequence facilitates the formation of an extended loop which was more suitable for protease recognition by the homology modeling and molicular docking. Furthermore, the single-cell transcriptomes identified that ACE2 and TMPRSSs are highly coexpressed in AT2 cells of lung, along with esophageal upper epithelial cells and absorptive enterocytes. Our results provide the bioinformatics evidence for the increased spike protein cleavage of SARS-CoV-2 and indicate its potential target cells.", - "rel_num_authors": 17, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.10.936898", + "rel_abs": "The main protease of coronaviruses and the 3C protease of enteroviruses share a similar active-site architecture and a unique requirement for glutamine in the P1 position of the substrate. Because of their unique specificity and essential role in viral polyprotein processing, these proteases are suitable targets for the development of antiviral drugs. In order to obtain near-equipotent, broad-spectrum antivirals against alphacoronaviruses, betacoronaviruses, and enteroviruses, we pursued structure-based design of peptidomimetic -ketoamides as inhibitors of main and 3C proteases. Six crystal structures of protease:inhibitor complexes were determined as part of this study. Compounds synthesized were tested against the recombinant proteases as well as in viral replicons and virus-infected cell cultures; most of them were not cell-toxic. Optimization of the P2 substituent of the -ketoamides proved crucial for achieving near-equipotency against the three virus genera. The best near-equipotent inhibitors, 11u (P2 = cyclopentylmethyl) and 11r (P2 = cyclohexylmethyl), display low-micromolar EC50 values against enteroviruses, alphacoronaviruses, and betacoronaviruses in cell cultures. In Huh7 cells, 11r exhibits three-digit picomolar activity against Middle East Respiratory Syndrome coronavirus.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Tong Meng", - "author_inst": "Tongji Hospital, Tongji University School of Medicine, Tongji University" - }, - { - "author_name": "Hao Cao", - "author_inst": "School of Life Science and Biopharmaceutics, Shenyang Pharmaceutical University" - }, - { - "author_name": "Hao Zhang", - "author_inst": "Department of Orthopaedic Oncology, Changzheng Hospital, Second Military Medical University" - }, - { - "author_name": "Zijian Kang", - "author_inst": "Department of Rheumatology and Immunology, Changzheng Hospital, Second Military Medical University" + "author_name": "Linlin Zhang", + "author_inst": "Institute of Biochemistry, Center for Structural and Cell Biology in Medicine, University of Luebeck, 23562 Luebeck, Germany." }, { - "author_name": "Da Xu", - "author_inst": "Depanrtment of Urology, The Third Affiliated Hospital of Second Military Medical University" + "author_name": "Daizong Lin", + "author_inst": "Institute of Biochemistry, Center for Structural and Cell Biology in Medicine, University of Luebeck, 23562 Luebeck, Germany." }, { - "author_name": "Haiyi Gong", - "author_inst": "Department of Orthopaedic Oncology, Changzheng Hospital, Second Military Medical University" + "author_name": "Yuri Kusov", + "author_inst": "Institute of Biochemistry, Center for Structural and Cell Biology in Medicine, University of Luebeck, 23562 Luebeck, Germany." }, { - "author_name": "Jing Wang", - "author_inst": "Department of Neurosurgery, Changhai hospital, Second Military Medical University" + "author_name": "Yong Nian", + "author_inst": "Shanghai Institute of Materia Medica, 201203 Shanghai, China" }, { - "author_name": "Zifu Li", - "author_inst": "Department of Neurosurgery, Changhai hospital, Second Military Medical University" + "author_name": "Qingjun Ma", + "author_inst": "Institute of Biochemistry, Center for Structural and Cell Biology in Medicine, University of Luebeck, 23562 Luebeck, Germany." }, { - "author_name": "Xingang Cui", - "author_inst": "Depanrtment of Urology, The Third Affiliated Hospital of Second Military Medical University" + "author_name": "Jiang Wang", + "author_inst": "Shanghai Institute of Materia Medica, 201203 Shanghai, China" }, { - "author_name": "Huji Xu", - "author_inst": "Department of Rheumatology and Immunology, Changzheng Hospital, Second Military Medical University" + "author_name": "Albrecht von Brunn", + "author_inst": "Max von Pettenkofer Institute, Ludwig-Maximilians-University Munich, 80336 Munich, Germany" }, { - "author_name": "Haifeng Wei", - "author_inst": "Department of Orthopaedic Oncology, Changzheng Hospital, Second Military Medical University" + "author_name": "Pieter Leyssen", + "author_inst": "Rega Institute for Medical Research, University of Leuven, 3000 Leuven, Belgium" }, { - "author_name": "Xiuwu Pan", - "author_inst": "Depanrtment of Urology, The Third Affiliated Hospital of Second Military Medical University" + "author_name": "Kristina Lanko", + "author_inst": "Rega Institute for Medical Research, University of Leuven, 3000 Leuven, Belgium" }, { - "author_name": "Rongrong Zhu", - "author_inst": "Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Orthopaedic Department of Tongji Hospital, School of Life Scien" + "author_name": "Johan Neyts", + "author_inst": "Rega Institute for Medical Research, University of Leuven, 3000 Leuven, Belgium" }, { - "author_name": "Jianru Xiao", - "author_inst": "Department of Orthopaedic Oncology, Changzheng Hospital, Second Military Medical University" + "author_name": "Adriaan de Wilde", + "author_inst": "Leiden University Medical Center, 2333 ZA Leiden, The Netherlands" }, { - "author_name": "Wang Zhou", - "author_inst": "Peking-Tsinghua Center for Life Sciences, TsinghuaUniversity" + "author_name": "Eric J. Snijder", + "author_inst": "Leiden University Medical Center, 2333 ZA Leiden, The Netherlands" }, { - "author_name": "Liming Cheng", - "author_inst": "Division of Spine, Department of Orthopedics, Tongji Hospital affiliated to Tongji University School of Medicine" + "author_name": "Hong Liu", + "author_inst": "Shanghai Institute of Materia Medica, 201203 Shanghai, China" }, { - "author_name": "Jianmin Liu", - "author_inst": "Department of Neurosurgery, Changhai hospital, Second Military Medical University" + "author_name": "Rolf Hilgenfeld", + "author_inst": "Institute of Biochemistry, Center for Structural and Cell Biology in Medicine, University of Luebeck, 23562 Luebeck, Germany" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2020.02.07.20021071", @@ -1600141,27 +1599190,35 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2020.02.01.930537", - "rel_title": "Fast assessment of human receptor-binding capability of 2019 novel coronavirus (2019-nCoV)", - "rel_date": "2020-02-03", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.01.930537", - "rel_abs": "The outbreaks of 2002/2003 SARS, 2012/2015 MERS and 2019/2020 Wuhan respiratory syndrome clearly indicate that genome evolution of an animal coronavirus (CoV) may enable it to acquire human transmission ability, and thereby to cause serious threats to global public health. It is widely accepted that CoV human transmission is driven by the interactions of its spike protein (S-protein) with human receptor on host cell surface; so, quantitative evaluation of these interactions may be used to assess the human transmission capability of CoVs. However, quantitative methods directly using viral genome data are still lacking. Here, we perform large-scale protein-protein docking to quantify the interactions of 2019-nCoV S-protein receptor-binding domain (S-RBD) with human receptor ACE2, based on experimental SARS-CoV S-RBD-ACE2 complex structure. By sampling a large number of thermodynamically probable binding conformations with Monte Carlo algorithm, this approach successfully identified the experimental complex structure as the lowest-energy receptor-binding conformations, and hence established an experiment-based strength reference for evaluating the receptor-binding affinity of 2019-nCoV via comparison with SARS-CoV. Our results show that this binding affinity is about 73% of that of SARS-CoV, supporting that 2019-nCoV may cause human transmission similar to that of SARS-CoV. Thus, this study presents a method for rapidly assessing the human transmission capability of a newly emerged CoV and its mutant strains, and demonstrates that post-genome analysis of protein-protein interactions may provide early scientific guidance for viral prevention and control.", - "rel_num_authors": 2, + "rel_doi": "10.1101/2020.01.31.20019265", + "rel_title": "Effectiveness of airport screening at detecting travellers infected with 2019-nCoV", + "rel_date": "2020-02-02", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.01.31.20019265", + "rel_abs": "As the number of novel coronavirus cases grows both inside and outside of China, public health authorities require evidence on the effectiveness of control measures such as thermal screening of arrivals at airports. We evaluated the effectiveness of exit and entry screening for 2019-nCoV infection. In our baseline scenario, we estimated that 46.5% (95%CI: 35.9 to 57.7) of infected travellers would not be detected, depending on the incubation period, sensitivity of exit and entry screening, and the proportion of cases which are asymptomatic. Airport screening is unlikely to detect a sufficient proportion of 2019-nCoV infected travellers to avoid entry of infected travellers. We developed an online tool so that results can be updated as new information becomes available.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Qiang Huang", - "author_inst": "Fudan University" + "author_name": "Billy Quilty", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Andreas Herrmann", - "author_inst": "Humboldt-Universitaet zu Berlin," + "author_name": "Sam Clifford", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Stefan Flasche", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Rosalind M Eggo", + "author_inst": "London School of Hygiene and Tropical Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "genomics" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.01.31.20019901", @@ -1601350,39 +1600407,43 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.01.26.920249", - "rel_title": "Full-genome evolutionary analysis of the novel corona virus (2019-nCoV) rejects the hypothesis of emergence as a result of a recent recombination event", - "rel_date": "2020-01-27", + "rel_doi": "10.1101/2020.01.26.919985", + "rel_title": "Single-cell RNA expression profiling of ACE2, the putative receptor of Wuhan 2019-nCov", + "rel_date": "2020-01-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.01.26.920249", - "rel_abs": "BackgroundA novel coronavirus (2019-nCoV) associated with human to human transmission and severe human infection has been recently reported from the city of Wuhan in China. Our objectives were to characterize the genetic relationships of the 2019-nCoV and to search for putative recombination within the subgenus of sarbecovirus.\n\nMethodsPutative recombination was investigated by RDP4 and Simplot v3.5.1 and discordant phylogenetic clustering in individual genomic fragments was confirmed by phylogenetic analysis using maximum likelihood and Bayesian methods.\n\nResultsOur analysis suggests that the 2019-nCoV although closely related to BatCoV RaTG13 sequence throughout the genome (sequence similarity 96.3%), shows discordant clustering with the Bat-SARS-like coronavirus sequences. Specifically, in the 5-part spanning the first 11,498 nucleotides and the last 3-part spanning 24,341-30,696 positions, 2019-nCoV and RaTG13 formed a single cluster with Bat-SARS-like coronavirus sequences, whereas in the middle region spanning the 3-end of ORF1a, the ORF1b and almost half of the spike regions, 2019-nCoV and RaTG13 grouped in a separate distant lineage within the sarbecovirus branch.\n\nConclusionsThe levels of genetic similarity between the 2019-nCoV and RaTG13 suggest that the latter does not provide the exact variant that caused the outbreak in humans, but the hypothesis that 2019-nCoV has originated from bats is very likely. We show evidence that the novel coronavirus (2019-nCov) is not-mosaic consisting in almost half of its genome of a distinct lineage within the betacoronavirus. These genomic features and their potential association with virus characteristics and virulence in humans need further attention.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.01.26.919985", + "rel_abs": "A novel coronavirus SARS-CoV-2 was identified in Wuhan, Hubei Province, China in December of 2019. According to WHO report, this new coronavirus has resulted in 76,392 confirmed infections and 2,348 deaths in China by 22 February, 2020, with additional patients being identified in a rapidly growing number internationally. SARS-CoV-2 was reported to share the same receptor, Angiotensin-converting enzyme 2 (ACE2), with SARS-CoV. Here based on the public database and the state-of-the-art single-cell RNA-Seq technique, we analyzed the ACE2 RNA expression profile in the normal human lungs. The result indicates that the ACE2 virus receptor expression is concentrated in a small population of type II alveolar cells (AT2). Surprisingly, we found that this population of ACE2-expressing AT2 also highly expressed many other genes that positively regulating viral entry, reproduction and transmission. This study provides a biological background for the epidemic investigation of the COVID-19, and could be informative for future anti-ACE2 therapeutic strategy development.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Dimitrios Paraskevis", - "author_inst": "Department of Hygiene Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece" + "author_name": "Yu Zhao", + "author_inst": "Tongji University" }, { - "author_name": "Evangelia Georgia Kostaki", - "author_inst": "Department of Hygiene Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece" + "author_name": "Zixian Zhao", + "author_inst": "Tongji University" }, { - "author_name": "Gkikas Magiorkinis", - "author_inst": "Department of Hygiene Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece" + "author_name": "Yujia Wang", + "author_inst": "Tongji University" }, { - "author_name": "Georgios Panayiotakopoulos", - "author_inst": "National Public Health Organization (NPHO), Athens, Greece" + "author_name": "Yueqing Zhou", + "author_inst": "Tongji University" }, { - "author_name": "Sotirios Tsiodras", - "author_inst": "Medical School, National and Kapodistrian University of Athens, Athens, Greece" + "author_name": "Yu Ma", + "author_inst": "Regend Therapeutics" + }, + { + "author_name": "Wei Zuo", + "author_inst": "Tongji University" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.01.25.919787",